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Federal State Autonomous
educational institution
higher professional education
"SIBERIAN FEDERAL UNIVERSITY"
Department of Transport
Course work
In the discipline "Fundamentals of the theory of reliability and diagnostics"
Completed by a student, groups FT 10-06 V.V. Korolenko
Checked by V.V. Kovalenko
Received by Doctor of Technical Sciences, prof. N.F. Bulgakov
Krasnoyarsk 2012
INTRODUCTION
1 Analysis of research works on reliability and diagnostics
2 Assessment of vehicle reliability indicators
2.2 Point estimation
2.3 Interval assessment
2.5 Testing the null hypothesis
4 Second variation row
5 Assessment of indicators of the recovery process
CONCLUSION
LIST OF SOURCES USED
INTRODUCTION
reliability trouble-free operation recovery
The theory and practice of reliability studies the processes of failure and how to deal with them in the component parts of objects of any complexity - from large complexes to elementary details.
Reliability - the property of an object to keep in time within the established limits the value of all parameters characterizing the ability to perform the required functions in the specified modes and conditions of use, maintenance, repairs, storage and transportation.
Reliability is a complex property, which, depending on the purpose of the object and the conditions of its use, consists of combinations of properties: reliability, durability, maintainability and preservation.
There is an extensive system of state standards "Reliability in technology" described by GOST 27.001 - 81.
The main ones are:
GOST 27.002 - 83. Reliability in technology. Terms and Definitions.
GOST 27.003 - 83. Selection and standardization of reliability indicators. Basic provisions.
GOST 27.103 - 83. Criteria for failures and limiting states. Basic provisions.
GOST 27.301-83. Predicting the reliability of products during design. General requirements.
GOST 27.410 - 83. Methods and plans for statistical control of reliability indicators on an alternative basis.
1 Analysis of research papers
The article tells about the outstanding engineer and entrepreneur A.E. Struve, who was the founder of the famous Kolomna Machine-Building Plant (now OJSC “Kolomna Plant). He was engaged in the construction of 400 railway platforms for the Moscow-Kursk railway. Under his leadership, the largest railway bridge in Europe across the Dnieper was built. Along with the freight yards, platforms and bridge structures, the Struve plant mastered the production of steam locomotives and passenger cars of all classes, service cars and tanks.
The article describes the activities of E.A. and M.E. Cherepanovs, who built the first steam locomotive in Russia. The steam locomotive, using a steam engine as a power plant, has long been the dominant type of locomotive and played a huge role in the development of railway communication.
The article describes the activities of V. Kh. Balashenko, the famous creator of track technology, honored inventor, three times "Honorary Railwayman", laureate of the USSR State Prize. He has designed a snow-removing machine. At the same time, he manufactured a mobile conveyor for loading open wagons and a press for stamping anti-theft protectors from old-year rails. Developed 103 track lining machines, which replaced over 20 thousand track fitters.
The article tells about S.M. Serdinov, who was engaged in the feasibility study and preparation of the first projects of electrified sections, developed samples of electric rolling stock and equipment for power supply devices, and subsequently put into operation the first electrified sections and their subsequent operation. Later S.M. Serdinov supported proposals to increase the energy efficiency of the 25 kV alternating current system, developed and implemented a 2x25 kV system, first on the Vyazma - Orsha section, and then on a number of other roads (more than 3 thousand km).
The article tells about B.S. Jacobi, who was one of the first in the world, used the electric motor he created for transport purposes - the movement of a boat (bot) with passengers along the Neva. He created a model of an electric motor consisting of eight electromagnets arranged in pairs on a movable and stationary wooden drum. For the first time, I used a commutator with rotating metal discs and copper levers in my electric motor, which, when sliding along the discs, provided current collection
The article describes the work of I.P. Prokofiev, who developed a number of original projects, including the arched floors of railway workshops at Perovo and Murom stations (the first three-span frame structures in Russia), the overlap of the landing stage (a canopy in the area of arrival and departure of trains) of the Kazan station in Moscow. He also developed a project for a railway bridge across the river. Kazanka and a number of standard designs of retaining walls of variable height.
The article describes the activities of V.G. Inozemtsev, Honored Scientist of the Russian Federation, inventor of brake technology, which is used to this day. Created at VNIIZhT a unique laboratory base for studying the brakes of trains of large mass and length.
The article tells about F.P. Kochnev, doctor of technical sciences, professor. He developed the scientific principles of the organization of passenger traffic, concerning the choice of the rational speed of movement of passenger trains and their weight. The solution of the problem of the rational organization of passenger traffic, the development of a system of technical and economic calculations for passenger traffic were of great importance.
The article tells about I. L. Perist, who established the technology of driving heavy freight trains, and improved the work of the passenger infrastructure and the formation of the largest networks of marshalling complexes. He was the main initiator of the unprecedented reconstruction of Moscow railway stations.
The article describes P. P. Melnikov, an outstanding Russian engineer, scientist and organizer in the field of transport, building the first long-distance railroad in Russia. The construction took almost 8 years.
The article describes the activities of I. I. Rerberg. He is a Russian engineer, architect, author of projects for the Kievsky railway station, he organized the protection of the line from snow drifts with the help of afforestation. On his initiative, the first in Russia impregnation plant was opened. He created mechanical workshops, which began the production of the first domestic cars. He worked to improve the working and living conditions of railway workers.
The article tells about the Russian engineer and scientist in the field of structural mechanics and bridge building N. A. Belyumbsky, who developed more than 100 projects of large bridges. The total length of bridges built according to his designs exceeds 17 km. These include bridges across the Volga, Dnieper, Ob, Kama, Oka, Neva, Irtysh, Belaya, Ufa, Volkhov, Neman, Selena, Ingulets, Chu sova yu, Berezina, etc.
The article describes the activities of S.P.Syromyatnikov, a Soviet scientist in the field of steam locomotive construction and heat engineering, who developed the design, modernization and thermal calculation of steam locomotives. The founder of the scientific design of steam locomotives; developed the theory and calculation of thermal processes, and also created the theory of the combustion process of steam locomotive boilers.
The article describes the work of V.N. Obraztsov, who proposed ways to solve problems associated with the design of railway stations and junctions, organized the planning of sorting work on the railway network, as well as issues of interaction between railway services and various types of transport among themselves. He is the founder of the science of designing stations and junctions of a railway junction.
The article describes the activities of P.P. Roterte, the head of the metro construction, who organized the construction of the first stage of the Moscow metro. The following sections were approved for the first stage of construction: Sokolniki - Okhotny Ryad, Okhotny Ryad - Krymskaya Ploshchad and Okhotny Ryad - Smolenskaya Ploshchad. They provided for the construction of 13 stations and 17 ground lobbies.
2 Assessment of reliability indicators of railway facilities
78 35 39 46 58 114 137 145 119 64 106 77 108 112 159 160 161 101 166 179 189 93 199 200 81 215 78 80 91 98 216 224
2.1 Estimation of mean time between failures
As a result of statistical processing of the variational series, sample characteristics are obtained, which are necessary for further calculations.
2.2 Point estimation
A point estimate of the mean time to failure of an ATS element between replacements is the sample mean, thousand km:
where Li is the i-th member of the variation series, thousand km;
N - Sample size.
The number of members of the variation series is N = 32.
Lav = 1/32 3928 = 122.75
Dispersion (unbiased) of the point estimate of mean time to failure, (thousand km) 2:
D (L) = 1/31 (577288 - 482162) = 3068.5745
Mean square deviation, thousand km,
S (L) = = 55.39471
Coefficient of variation of a point estimate of the mean time to failure
The Weibull - Gnedenko form parameter in is determined according to Table 11, depending on the obtained coefficient of variation V.
If it is difficult to determine the shape in by the coefficient of variation, then we calculate the shape in according to the following algorithm:
1. We divide the obtained coefficient of variation into the sum of two numbers, and one of them determines the value of the form in from the table
V = 0.4512 = 0.44 + 0.0112
2. We find from table 11 the value of the form in for the coefficient of variation, decomposed in the sum and the next value of the form in
for V1 = 0.44 B1 = 2.4234
for V2 = 0.46 V2 = 2.3061
3. Find the difference? V and? In for the values we found
V = 0.46 - 0.44 = 0.02
B = 2.4234 - 2.3061 = 0.1173
4. Composing the proportion
5. Find the value of the form in for the coefficient of variation V = 0.45128
in = in (0.44) - in = 2, 4234 - 0, 06568 = 2, 35772
Let us determine q at b = 0.90, for which we calculate the significance level e and select the value (64) from Table 12:
Quantile of distribution:
Required accuracy of MTBF estimation:
e = (1-0.9) / 2 = 0.05
The calculated value of the marginal relative error:
q = ((2 * 32 / 46.595) ^ (1 / 2.3577)) - 1 = 0.1441
2.3 Interval assessment
With probability b, it can be argued that the mean time to failure of the L-13U pantograph is in the interval, which is the interval estimate.
The lower and upper boundaries of this interval are as follows:
Lsrn = 122.75 * (1-0.1441) = 105.0617
Lav = 122.75 * (1 + 0.1441) = 140.4382
As a result, we obtain point and interval estimates of the mean time to failure of the L-13U pantograph - one of the quantitative safety indicators. For non-renewable elements, it is at the same time an indicator of durability - an average resource.
2.4 Estimation of the scale parameter of the Weibull - Gnedenko law
The point estimate of the scale parameter a of the Weibull - Gnedenko law, we calculate by the formula, thousand km:
where Г (1 + 1 / в) is the gamma function for the argument x = 1 + 1 / в, which is taken from Table 12 depending on the coefficient of variation V. To find the gamma function Г (1 + 1 / в), we use by the same algorithm, similarly to the estimation of the shape parameter in the Weibull - Gnedenko law.
G (1 = 1 / c) = 0.8862
We obtain, respectively, the lower bound of the scale parameter
Upper bound
2.5 Testing the null hypothesis
We check the correspondence of the Weibull-Gnedenko law to the experimental distribution using X2, the Pearson's goodness-of-fit criterion. There is no reason to reject the null hypothesis if the condition
X2calculation< Х2табл(,к), (2.9)
where is the value of the criterion calculated from experimental data;
The critical point (tabular value) of the criterion at the level of significance and the number of degrees of freedom (see Table 12 Appendix 1).
The significance level is usually taken equal to one of the values of the series: 0.1, 0.05, 0.025, 0.02, 0.01.
Number of degrees of freedom
k = S - 1 - r, (2.10)
where S is the number of partial sampling intervals;
r is the number of parameters of the assumed distribution.
With the two-parameter Weibull - Gnedenko law, k = S-3.
The null hypothesis is tested using the following algorithm:
S = 1 + 3.32 * lnN (2.11)
Divide the range of the variation series into S intervals, i.e. the difference between the largest and smallest numbers. The boundaries of the intervals are found by the formula
where j - 1,2,…., S.
Determine empirical frequencies, i.e. nj - the number of members of the variation series that fell into the j -th interval. When a zero interval occurs (nj = 0), this interval is divided into two parts and added to the neighboring ones with a recalculation of their boundaries and the total number of intervals.
where j = 1,2,…, S.
The failure distribution function included in formula (14) is determined by the formula (for the Weibull-Gnedenko law).
3) Determine the calculated value of the criterion
Hrasch2 = (2.15)
We will consider the assessment of the X2 criterion using the previously given example of a variation series.
1) Number of intervals S = 1 + 3.332 * ln316. The number of degrees of freedom k = 6 - 3 = 3. The level of significance is assumed to be 0.1. The tabular value of the X2tabl criterion (0.1; 3) = 6.251 (see Table 12). The range of the variation series 224-35 = 189 thousand km is divided into 6 intervals: 189/6 = 31.5 thousand km. It should be noted that the first interval starts at zero, and the last one ends at infinity.
Table 1 - Calculation of empirical frequencies
2) We calculate the theoretical frequencies by the formula (2.13) and determine the calculated value of the criterion X2calculated by the formula (2.15). For clarity, the calculation is summarized in Table 2.
Table 2 - Calculation of X2 - Pearson's goodness-of-fit test
3) As a result, we get that the calculated value of the criterion:
X2calculated = 33.968 - 32 = 1.968
X2calculated = 1.968 X2tabl = 6.251
The null hypothesis is accepted.
3 Assessment of quantitative characteristics of reliability and durability
3.1 Evaluation of the probability of failure-free operation
We calculate the quantitative characteristics of reliability using the example of the brake system. The probability of failure-free operation of the L-13U pantograph is estimated according to the Weibull-Gnedenko law, using the formula:
P (L) = exp [- (L / a)]. (3.1)
The interval estimate is determined by substituting the values of a and a in the formula (3.1), respectively, instead of a.
Table 3 - Point estimate of the probability of failure-free operation of the brake system before the first failure
|
L, thousand km |
||||
Figure 1 - Graph of the probability of failure-free operation of the pantograph L-13U
3.2 Estimation of gamma percent MTBF
According to GOST 27.002 - 83 gamma-percent operating time to failure Lj, thousand km, is the operating time during which a failure of an ATS element does not occur with probability j. For non-recoverable elements, it is at the same time an indicator of durability - a gamma - percentage resource (operating time during which an ATS element will not reach the limit state with a given probability j). For the Weibull - Gnedenko law, its point estimate, thousand km,
Lj = a * (- ln (j / 100)) 1 / b. (3.2)
We take the probability j to be equal to 90%, respectively. Then we get:
3.3 Assessment of failure rate
Failure rate (L), thousand km-1, is the conditional density of the probability of failure of the pantograph L-13U, determined for the considered moment of time, provided that no failure has occurred before this moment.
For the Weibull - Gnedenko law, its point estimate, refusal, thousand km,
(L) = in / av * (L) in-1. (3.3)
b = 2.3577; a = 138.1853
The interval estimate is determined by substituting into formula (3.3) instead of a the values of an and a.
Table 4 - Point estimate of the failure rate of the pantograph L-13U
|
L, thousand km |
||||
Figure 2 - Graph of the failure rate of the pantograph L-13U
3.4 Estimation of the density distribution of failures
The failure distribution density f (L), thousand km-1, is the probability density that the operating time of the L-13U pantograph to failure will be less than L. For the Weibull - Gnedenko law:
f (L) = b / a * (L / a) b-1 * (3.4)
f (10) = 2.357 / 138.185 * (10 / 138.185) 2.3577-1 * 0.00048
Table 5 - Density of distribution of operating time to failure of pantograph L-13U
Figure 3 - Graph of the density distribution of failures of the pantograph L-13U
4 To simplify the problem, we calculate the second variational series using a computer program.
Variational range:
54 67 119 14 31 41 68 90 94 112 80 130 146 71 45 148 88 99 113
As a result of the calculation, we obtain the following tables and graphs.
Table 6 - initial data for estimating the mean time to failure
Table 7 - Calculation of X2 - Pearson's goodness-of-fit test
X2calculated = 1.6105 X2tabl = 11.345
The null hypothesis is accepted.
Table 8 - Point estimate of the probability of failure-free operation of the pantograph L-13U
|
L, thousand km |
||||
Figure 4 - Graph of the probability of failure-free operation of the pantograph L-13U
Table 9 - Point estimate of the failure rate of the pantograph L-13U
|
L, thousand km |
||||
Figure 5 - Graph of the intensity of the first failures of the pantograph L-13U
Table 10 - Density of distribution of operating time to failure of pantograph L-13U
Figure 5 - Graph of the density distribution of failures of the pantograph L-12U
Table 11 - The results of calculating the main parameters of the 1st, 2nd variation series
|
Index |
First row |
Second row |
|
5 Assessment of indicators of the recovery process (graphic-analytical method)
Let's calculate an estimate of the average operating time before the first, second recovery:
Let's calculate the estimate of the standard deviation before the first, second recovery:
Let's calculate the distribution composition function before the first, second, third recovery, and enter the calculated data into the table.
The calculation of the functions of the distribution composition of the operating time before replacing the elements of the L-13U pantograph will be performed according to the formula:
where lcp is the mean time between failures;
Up - distribution quantile;
K - standard deviation
Table 12 - Calculation of the composition function of the distribution of operating time before replacements
|
l№ср ± Uр? у№к |
lІср ± Uр? уІк |
|||
Let's make a graphical construction of the distribution composition functions. Let's calculate the values of the leading function and the parameter of the failure flow at the intervals chosen by us. Let's enter the calculated data into tables and make a graphical construction (see Figure 6).
The calculation is carried out by the graphic-analytical method, the indicators are taken from the resulting graph and entered into the table.
Table 13 - Leading function definitions
The failure flow parameter is determined by the formula:
substitute values for
Let's calculate the parameter of the flow of failures for other values of the mileage, and enter the result into the table.
Table 13 - Determination of the parameter of the recovery flow
Figure 6 - Graphic-analytical method for calculating the characteristics of the recovery process,? (L) and u (L) of the L-13U pantograph
CONCLUSION
In the course of the course work, the theoretical knowledge in the discipline "Fundamentals of the theory of reliability and diagnostics", "Fundamentals of the operability of technical systems" was consolidated. For the first sample, the following were made: an estimate of the average technical resource before the replacement of vehicle elements (point estimate); calculation of the confidence interval for the average technical resource of the vehicle; estimation of the scale parameter of the Weibull-Gnedenko law; evaluation of the parameters of the null hypothesis, evaluation of the characteristics of probability theory: probability density and failure distribution functions f (L), F (L); estimation of the probability of failure-free operation; determination of the need for spare parts; assessment of gamma - percentage time to failure; failure rate assessment; assessment of indicators of the recovery process (by graphic-analytical method); calculation of the leading recovery function; calculation of the parameter of the recovery flow; graphic-analytical method for calculating the leading function and the parameter of the restoration flow. The second variational series was calculated in a computer program developed especially for students “Model of statistical evaluation of the characteristics of reliability and efficiency of technology”.
The reliability assessment system allows not only to constantly monitor the technical condition of the rolling stock, but also to manage their performance. Operational planning of production, quality management of maintenance and repair of railway vehicles is facilitated.
LIST OF USED SOURCES
1 Bulgakov N.F., Burkhiev Ts. Ts. Quality management of vehicle prevention. Modeling and optimization: Textbook. allowance. Krasnoyarsk: IPC KSTU, 2004.184 p.
2 GOST 27.002-89 Reliability in technology. Basic concepts. Terms and Definitions.
3 Kasatkin G.S. Journal"Railway transport" No. 10, 2010.
4 Kasatkin GS Journal "Railway transport" No. 4, 2010.
5 Sadchikov P.I., Zaitseva T.N. Journal "Railway Transport" No. 12, 2009.
6 Prilepko A. I. Journal "Railway transport" No. 5, 2009.
7 Shilkin P.M. Journal "Railway Transport" No. 4, 2009.
8 Kasatkin G.S. Journal "Railway Transport" No. 12, 2008.
9 Balabanov V.I. Journal "Railway Transport" No. 3, 2008.
10 Anisimov P.S. Journal "Railway Transport" No. 6, 2006.
11 Levin B.A. Railway transport "No. 3, 2006.
12 X Abstract. The builder of the first railway in Russia. http://xreferat.ru.
13 GZD News. Bronze bust of Ivan Rerberg. http://gzd.rzd.ru.
14 Websib. Nikolay Apollonovich Belelyubsky. http://www.websib.ru.
15 Syromyatnikov S. P. Bibliography of scientists of the USSR. "Izvestia of the Academy of Sciences of the USSR. Department of technical sciences", 1951, No. 5.64s.
16 Wikipedia. Free encyclopedia. V.N. Obraztsov. http://ru.wikipedia.org.
17 Kasatkin G.S. Kasatkin "Railway Transport" No. 5 2010.
18 GZD News. An outstanding figure in the railway industry. http://www.rzdtv.ru.
19 Methodical manual "Fundamentals of the theory of reliability and diagnostics." 2012
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The fundamentals of the theory of reliability and diagnostics are stated in relation to the most capacious component of the system man - car - road - environment. The basic information about the quality and reliability of the car as a technical system is presented. Basic terms and definitions are given, indicators of reliability of complex and dismembered systems and methods of their calculation are given. Attention is paid to the physical foundations of vehicle reliability, methods of processing information about reliability and methods of testing for reliability. The place and role of diagnostics in the system of maintenance and repair of cars in modern conditions are shown.
For university students.
The concepts of "quality" and "reliability" of machines.
The life of modern society is unthinkable without the use of machines of a wide variety in design and purpose, which transform energy, materials, information, change people's lives and the environment.
Despite the huge variety of all machines, in the process of their development, uniform criteria are used to assess the degree of their perfection.
In the conditions of market relations, the creation of most new machines requires compliance with the most important condition of competitiveness, namely, giving them new functions and high technical and economic indicators of their use.
For effective use of machines, it is necessary that they have high quality and reliability indicators.
The international standard ISO 8402 - 86 (ISO - International Organization Standartization) gives the following definition: "Quality is a set of properties and characteristics of a product or service that give them the ability to satisfy conditioned or implied needs."
TABLE OF CONTENTS
Foreword
Introduction
Chapter 1. Reliability is the most important property of product quality
1.1. The quality of products and services is the most important indicator of the successful operation of transport and road enterprises
1.2. The concepts of "quality" and "reliability" of machines
1.3. Reliability and Human Issues
Chapter 2. Basic concepts, terms and definitions adopted in the field of reliability
2.1. Objects considered in the field of reliability
2.1.1. General concepts
2.1.2. Classification of technical systems
2.2. The main states of the object (technical system)
2.3. The transition of an object to various states. Types and characteristics of failures of technical systems
2.4. Basic concepts, terms and definitions in the field of reliability
2.5. Reliability indicators
2.6. Reliability criteria for non-recoverable systems
2.7. Reliability criteria for recoverable systems
2.8. Durability indicators
2.9. Persistence indicators
2.10. Repairability indicators
2.11. Comprehensive reliability indicators
Chapter 3. Collection, analysis and processing of operational data on product reliability
3.1. Goals and objectives of collecting information and assessing the reliability of machines
3.2. Principles of collection and systematization of operational information on product reliability
3.3. Construction of empirical distribution and statistical estimation of its parameters
3.4. The distribution laws of the operating time to failure, most often used in the theory of reliability
3.5. Laplace transform
3.6. Confidence interval and confidence level
Chapter 4. Reliability of Complex Systems
4.1. Complex system and its characteristics
4.2. Reliability of Dismembered Systems
Chapter 5. Mathematical models of the reliability of the functioning of technical elements and systems
5.1. General reliability model of a technical element
5.2. General system reliability model in terms of integral equations
5.2.1. Basic notation and assumptions
5.2.2. State Matrix
5.2.3. Transition Matrix
5.3. Reliability Models for Non-Recoverable Systems
Chapter 6. The life cycle of a technical system and the role of scientific and technical preparation of production to ensure the requirements of its quality
6.1. The structure of the life cycle of a technical system
6.2. Comprehensive product quality assurance system
6.3. Quality assessment and reliability management
6.3.1. International quality standards ISO 9000-2000 series
6.3.2. Quality control and its methods
6.3.3. Quality control methods, analysis of defects and their causes
6.4. Technical and economic management of product reliability
6.5. Seven simple statistical methods for assessing quality used in ISO 9000 standards
6.5.1. Classification of statistical quality control methods
6.5.2. Data layering
6.5.3. Graphical presentation of data
6.5.4. Pareto chart
6.5.5. Causal diagram
6.5.6. Scatter plot
6.5.7. Checklist
6.5.8. Control card
Chapter 7. The physical essence of the processes of changing the reliability of structural elements of cars during their operation
7.1. Reasons for loss of performance and types of damage to machine elements
7.2. Physicochemical processes of destruction of materials
7.2.1. Classification of physical and chemical processes
7.2.2. Processes of mechanical destruction of solids
7.2.3. Aging of materials
7.3. Failures in terms of strength
7.4. Tribological failures
7.5. Types of wear of car parts
7.6. Corrosion parameters failures
7.7. Wear chart and methods for measuring wear of car parts
7.8. Methods for determining the wear of machine parts
7.8.1. Periodic wear measurement
7.8.2. Continuous wear measurement
7.9. Influence of permanent deformations and aging of materials on wear of parts
7.10. Assessment of the reliability of elements and technical systems of vehicles during their design
7.11. The most common ways and methods of ensuring and predicting reliability used in the creation of machines
Chapter 8. System of maintenance and repair of machines
8.1. Maintenance and repair systems of machines, their essence, content and principles of construction
8.2. Requirements for the system of maintenance and repair, and methods for determining the frequency of their implementation
8.3. Operation of the machine in extreme situations
Chapter 9. Diagnostics as a method of monitoring and ensuring the reliability of the vehicle during operation
9.1. General information about diagnostics
9.2. Basic concepts and terminology of technical diagnostics
9.3. Diagnostic value
9.4. Diagnostic parameters, determination of limiting and permissible values of technical condition parameters
9.5. Principles of car diagnostics
9.6. Organization of car diagnostics in the maintenance and repair system
9.7. Types of car diagnostics
9.8. Diagnostics of car units during repair
9.9. Diagnostics of the state of the cylinder-piston group
9.10. The concept of diagnosing technology in modern conditions
9.11. Technical diagnostics is an important element of technological certification of services of service enterprises
9.12. Management of reliability, technical condition of machines based on the results of diagnostics
9.13. Diagnostics and vehicle safety
9.14. Brake system diagnostics
9.15. Headlight diagnostics
9.16. Suspension and steering diagnostics
Conclusion
Bibliography.
I. Foundations of the theory of reliability and diagnostics.
1. Maintenance systems for vehicles. The essence of the planned preventive system is that preventive actions are performed compulsorily without agreeing on the actual need, and malfunctions and failures are eliminated when they occur. In the case of PPR, runs are planned from the 1st impact to another of the same type.
The PPR system has the following types of preventive effects: EO: washing (cosmetic and in-depth), refueling Zh., Polishing, installing studs, sanitizing vans and saloons of the ambulance car. TO-1: it is normalized strictly after 4-5 thousand km of run, including work: fasteners - periodic tightening of threaded connections; lubricating, including oil change in the crankcase; simple low-volume adjustments (fan belt tension). TO-2: incl. all work related to TO-1 + required adjustment work. CO: 2 times a year. It is planned to replace seasonal oils, tires, batteries, gaps in the candles. The work is determined by the "Regulations on TO and TR".
Pros: 1) It is necessary for low education; 2) You can predetermine the scope of work, distribute them by days of the week. Cons: 1) recommendations are developed based on average observation results; 2) the system requires to perform work sometimes without their need.
2. Calculation of the reliability of the vehicle with sequential and parallel connection of elements. A complex system is understood as an object that performs specified functions, which can be divided into elements, each of which also performs certain functions and interacts with other elements. Elements can have a variety of output parameters, which, from the point of view of reliability, can be divided into three groups (types): XI - parameters, the change of which with going beyond the established levels of indicators leads to the loss of the operability of the element and the system; X2 - parameters involved in the formation of the output parameters of the entire system, by which it is difficult to judge the failure of an element; HZ - parameters affecting the performance of other elements are similar to changes in the external operating conditions of the system. For greater clarity of the possible types of output parameters, a system of two elements (for example, an engine) can be represented by the structural diagram B shown in Fig. 18 diagram for the power supply system XI - this is the throughput of the fuel jet (if the jet is clogged and the fuel does not flow, then the power system fails and the engine fails), X2 - this is the wear of the fuel jet (the fuel economy of the vehicle deteriorates), HZ - a rich mixture will overheat the engine and make the cooling system difficult to operate. In turn, the poor performance of the cooling system leads to overheating of the engine and the formation of steam locks in the power system - this is HZ for element # 2, poor thermostat performance delays engine warm-up, which leads to a decrease in the fuel economy of the car - this is X2, a broken belt leads to a failure of the cooling system and a failure of the car - this XI for element # 2. In real complex systems, elements can have either all three types of output parameters or less (one or two). This largely depends on the degree of dismemberment of the system into elements. In this example, the power system and the cooling system are themselves complex systems. A car is a very complex system that can be broken down into a large number of elements. When analyzing the reliability of such a complex system, it is useful to divide its elements into groups; 1.Elements, the failure of which practically does not affect the vehicle's performance (damage to the upholstery, wing corrosion). Failure of such elements is usually considered in isolation from the system. 2.Elements, the performance of which practically does not change during the considered period of time or operating time (for a car sent for harvesting, it makes no sense to take into account the change in the state of the gearbox housing). 3. Elements, the restoration of efficiency of which does not require a significant investment of time and, practically, does not reduce the performance indicators of the vehicle (fan belt tension). 4. Elements, the failures of which lead to the failure of the car and regulate its reliability. Due to the fact that the functioning of the car is associated with the performance of various tasks in unequal operating conditions, the allocation of elements into these groups can be problematic (failure of a wiper in dry good weather does not lead to a failure of the car, and in rain and slush it leads to failure). Depending on the nature of the impact on the reliability of a complex system, its elements can be considered connected in series or in parallel (by analogy with the inclusion of light bulbs in a garland). In this case, the real structural diagram of the system should be represented by the structural diagram of reliability. Let's give an example of a structural diagram of a bearing assembly consisting of the following elements; 1 - shaft, 2 - bearing, 3 - bearing housing, 4 - bearing cap screws (4 pcs.), 5 bearing cap. If the failure of an element leads to a failure of the system, then we can assume that the element is connected in series. If, in the event of an element failure, the system continues to function, then the element is connected in parallel. In accordance with this, the structural diagram of the bearing unit will have the first element, however, with an increase in operating time to a value of 2, the probability of failure of the second element may increase significantly. The third element, at the considered operating time values, remains practically trouble-free. Thus, in order to improve the reliability of a system consisting of series connected elements, the reliability of the "weakest" elements should be increased first of all. It is impractical to increase the average resource of all system elements equally.
3. Basic concepts, definitions, properties and indicators of reliability. During the operation of a car, its quality usually deteriorates due to changes in indicators. Reliability is a property of quality because it only manifests itself for a long time. Reliability is expressed by four parameters: a) reliability - the property of an object to continuously maintain an operable state for some time, the indicators are the mean time between failures; b) durability - the property of an object to maintain performance up to the limiting state with the necessary breaks for maintenance, the indicators are the average service life, the average resource; c) maintainability - a property of an object, which consists in its adaptability to the detection, elimination of failures and malfunctions, indicators are the frequency of maintenance, specific labor intensity, the number of tools used; d) preservation - the property of an object to maintain the established quality indicators during storage, transportation, indicators are the average and gamma percentage shelf life. The main terms and concepts are: a) failure - a change in one or more indicators of the given parameters of an object, leading it to an inoperative state; b) malfunction - a state when the object does not meet at least one of the requirements of the normative and technical documentation; c) failure - self-correcting failure. According to the origin or reasons of occurrence, failures and malfunctions are divided into three types: a) structural, production, and operational.
4. Processes of changes in the properties of structural materials that affect the reliability of the car. A wide variety of materials are used in the construction of a car: various metals, plastics, rubber, fabrics, glass. As the vehicle is used, the properties of structural materials also change in a very diverse way. Let's consider the most essential processes: Temperature softening- typical for metals and other materials. With an increase in temperature for different metals, their strength characteristics (yield stress) more or less decrease. For example, if the engine overheats, the pistons can break off the bridges between the piston rings. Fatigue- softening of metals under cyclic loads, leading to the destruction of parts under stresses. The sources of cyclic loads can be the conditions of the natural functioning of the part (for example, when the gear is working, the tooth perceives the load, then "rests", again perceives the load, etc.), vibration loads, etc. Intergranular corrosion - it is the process of oxygen diffusion (seepage) into the metal crystal lattice. This process reduces the fatigue strength of the parts. Flooding - This is the process of diffusion of hydrogen into the crystal lattice of metals, leading to an increase in fragility and a decrease in the fatigue strength of a part. Hydration can occur when the mode of galvanic coatings of parts is violated. Intercrystalline adsorption (Rebinder effect) This is the process of softening of parts due to the wedging action of molecules falling into cracks or notches.
Changes in the properties of non-metallic materials are very diverse and should be considered separately in each case.
5. Processing the results of truncated tests of the durability of parts and assemblies. The emergence of this technique is due to the elongation of the moments of observation of failures and the desire to get a result as soon as possible. When processing truncated tests, a failure probability curve is first built and numerical characteristics (average resource or gamma percentage resource) are found from it. Without a significant decrease in the accuracy of determining the average resource, the tests of the durability of cars can be stopped (truncated) after the failure of 60 ... .70 of the number of tested cars. By arranging the test results х1 х2, х1 ... х in the order of increasing resources, it is possible to calculate the failure probabilities corresponding to the obtained values of the random variables, dividing the ordinal number of the random variable by the number of tested cars. ... By plotting probability points and drawing a curve through them, you can obtain a probability distribution law. With a small number of test cars n = 1, the curve shifts significantly and in order to avoid an incorrect result, you should use the formula:. The second technique that increases the accuracy of test results is the use of special probabilistic paper, when the curve of the probability distribution law is plotted on a graph with nonlinear scales.The order of constructing nonlinear scales is determined by the form of the probability distribution law for the normal law, the ordinate scale is linear, and the abscissa (probabilities) scale is nonlinear. ... This scale can be built on a special table, or by evenly postponing the values of the quantiles with an indication of the probability corresponding to the value of the quantile, or directly by graphing. By plotting the values against the corresponding values on a probability paper and drawing a straight line through the obtained points, we obtain the desired probability distribution. The numerical characteristics of the resulting distribution of random variables are determined by the position of the distribution line relative to the coordinate axes on the graph, For example, for the normal law when testing the durability, the average resource corresponds to a probability of 0.5.
6. Determination of indicators of durability according to tests truncated on the left. Tests truncated on the left - the moment of failure is observed, and the moment when the unit under test starts operation is unknown. Observing a large group of cars of different ages of the same model on a relatively short period of time or operating time, you can get information about the durability of their units or parts. This period of time should be long enough to have failures, but the likelihood of successive two or more failures on one vehicle should be extremely small. Since 6 ... 8 points are sufficient to construct the distribution law, the value of the segment T can be chosen approximately equal to 0.25 of the estimated average service life of the part.
The observation results are entered in the table: Dividing the possible service life into intervals, we will have a histogram (Fig.), Characterizing the probabilities of observing failures P;, in intervals T ,. If the probability distribution is close to the normal law, then with a long service life, the failure probabilities decrease, since the bulk of the parts have already failed earlier. In practice, old cars have parts failure more often than new ones. This is due to the fact that among the failed parts there are not only the first (installed at the factory) parts, but also those installed during the repair. Thus, to construct the law of probability distribution, it is necessary to exclude failures of parts installed during repairs from the observed number of failures or to correct the observed (experimental) probabilities. To derive a formula that allows you to adjust the experimental probabilities, consider the graph of possible outcomes of events for objects with different operating time or service life. On the graph, the state of failure is shown with a cross, and the operable state is shown with a circle, the probability of failure in the first interval - for the second - ... The probability of failure of a part in the first period will coincide with the experimental probability, which is determined by the results of observing a group of new cars, 
... Instead of a failed part, another part will be installed during vehicle repair, which may also fail in the second period. The probability of two failures in a row will be expressed by the product of the failure probabilities and will be equal. In the second period, a failure of the part installed at the factory, the service life of which we are looking for, may be observed. That. the experimental failure probability of a part in the age group of a / m will be equal to P2 ° = P, 2 + P2. Whence P2 = P2 ° - P, 2. Similarly, for the third period, you can write 
... Transforming we get the expression:. Comparing the obtained expressions, we see a general trend, which is written as follows: 
The advantage of this method for assessing the durability of parts is that, having come to an ATP with a large fleet of cars of different ages, an engineer, after a year of work, is able to determine the average service life of all parts. Knowing the average annual vehicle mileage based on the average service life, it is easy to determine the average resource, which allows you to assess the reliability of vehicles and plan the consumption of spare parts.
7. Determination of the rate of spare parts, which guarantees a given probability of no downtime of vehicles due to lack of parts. The calculation makes it possible to determine such norms of the stock of parts that, with any predetermined probability, guarantee the absence of downtime of the car due to the lack of parts during the planned period. The calculation method is acceptable for any number of cars, if the resource of parts is described by an exponential law (failures are of a sudden nature), and can also be extended to large groups of cars, dissimilar in operating time and service life, when the resource is described by any law of probability distribution. In the first and second cases, when the failures of the standardized parts occur on different cars and are not related to each other, the number of failures over the planned period of time is described by Poisson's law 
a - average consumption of spare parts for the planned period. With a stock of On parts, the probability that a random number of failures will be less than this stock is expressed by the sum of probabilities a = P (k = 0) + P (k = 1) + P (k = 2) + ... + P (k = Na Using Poisson's law, we can write 
for the convenience of the calculation, we will rewrite the formula by transferring the constant factor to the left side of the equality. 
Knowing the average consumption of spare parts and setting the required probability of no downtime due to a lack of spare parts, the left side of the equality is calculated, and then they begin to count the sum of the right side by sequential enumeration of the number k until the value of the sum reaches the value of the left side of the equality. That number k at which equality will be achieved will be the required norm of spare parts Na. On the basis of the considered formulas, tables of relative norms of spare parts were compiled, providing a given probability of no downtime due to lack of parts. Analyzing the tabular values, one can notice a very important pattern: the greater the average consumption of spare parts, the closer the value of ρ is to unity, that is, with large average costs, a slight excess of average stocks guarantees a high probability of no downtime due to lack of spare parts. Thus, warehouses should not be located at the entrance to production, but at the exit of production. To guarantee the absence of downtime, ATP with a small fleet of vehicles must have a stock of bearings several times higher than their average consumption, and it is not necessary to have excess stocks in the warehouse of the bearing plant; with a slight increase in consumption, the requests of all consumers will be satisfied with a very high guarantee.
8. Determination of the frequency of maintenance of parallel connected systems, smoothly changing their characteristics. Consider changing the engine oil. As the engine runs, the lubricating properties of the
the oil sump gradually deteriorates, which leads to an increase in the intensity of wear of parts
engine. Let us express the amount of wear by the formula I = a-xb, where x is the oil production, a and b are
empirical coefficients. If you change the oil through Xto kilometers, then with each change
the nature of the increase in wear will be repeated. According to the technical and economic method for determining the frequency of maintenance, the target function of unit costs.
... Let us determine the engine resource unknown to us from the following considerations. If during the time before the oil change the engine wears out by the value AI = a * Xhmo then the wear limit according to the technical conditions 1pr will be reached during the operating time 
Substituting the resource value into the objective function, we get a formula with one unknown unknown - the maintenance frequency: 
We take the derivative of this formula with respect to Chi and equate it to zero. 
From here we express the optimal oil change intervals: 
The resulting formula can be simplified by introducing the value of the minimum resource of the engine running without oil change. From the condition 
express: 
9. Determination of the periodicity of maintenance of parallel connected systems that discretely change their characteristics. As an example of the system under consideration, a full-flow filter for oil purification can be taken, which fails when the filter element is mechanically destroyed or clogged when oil begins to pass through the pressure reducing valve uncleaned. Let us consider the nature of the increase in the wear of engine parts as the operating time (Fig.) With a failed filter, the wear rate is high and the maximum wear of the engine (curve 1) can be achieved during operating time, if the filter is guaranteed to work, then the wear rate is low (curve 2) and the engine will be able to work ... Filters are often made non-separable and are routinely replaced at intervals during which the filter may fail. For a particular engine, the increase in wear will be expressed by broken line 1, and its resource will be a random value. Let us find the optimal frequency of filter replacement using the objective function of total unit costs: 
. 
Obviously, if, then if (filters are not replaced), then. In addition to the periodicity of maintenance, the reliability of the filter itself over the period, which can be represented by the reliability curve, will also affect the engine resource. As the vehicle operates, the probability of filter failure-free operation will vary from 1 to, the average filter failure-free operation can be determined from the equal area under the failure-free curve by integrating 
... Knowing the reliability of the filter, it is possible to find the average engine resource as the mathematical expectation of two values and. Substituting the value of the resource into the target cost function, we get. The optimal frequency of maintenance can be determined by the minimum cost from the condition Since the analytical solution is difficult to perform, you can use a numerical solution, finding the average reliability of the filter by the area under the curve on a given segment, you can find such a value that will give the minimum total costs.
10. Determination of the frequency of maintenance of sequentially connected systems.
The systems connected in series include the units and systems of the car, the failure of which leads to the loss of the car's performance without serious damage to other systems - these are devices for the power supply system, ignition, start-up, etc.
Maintenance and repair of sequentially connected systems on demand leads to high costs, including possible fines for flight disruptions, the need to tow the car to the garage, etc. Regulated maintenance of these systems in the conditions of an ATC or service station requires costs. Let us determine the optimal maintenance frequency of sequentially connected systems using
the law of probability distribution of its operating time between failures. At the specified frequency, the probability of system failure in road conditions 
, the probability that the failure will be prevented during routine maintenance, 
... Failure can be observed in the interval, on average, failure will occur during operating time, which can be found by the formula: 
... Thus, part of the car will fail and be serviced, on average, during operating time, and part - during operating time. It is possible to find the average operating time, at which the systems connected in series will be serviced, as the mathematical expectation:. Similarly, you can find the average cost of maintaining the system:, where is the coefficient that takes into account the maintenance at the next maintenance of the system, which failed earlier and was serviced as needed. If all systems are serviced in a planned manner, then if only those systems that have not previously failed and were not serviced as required were serviced in a planned manner, then. Knowing the average maintenance costs and the average operating time at which maintenance is carried out, it is possible to write down the unit total costs, that is, the objective function for determining the maintenance frequency,.
The frequency of maintenance, at which the unit costs are minimal, is optimal. Let's carry out a qualitative analysis of unit costs: with probability,, for, i.e. the system will not be serviced in a planned manner,,,. The optimal maintenance frequency can be found by a numerical solution, having the values of maintenance costs in a planned manner and the average cost of eliminating system failures, as well as the curve of the distribution of the probability of system failure. The nature of the change in unit costs is shown in the figure.
11. The essence of the method of diagnosing a complex of diagnostic parameters. Technical diagnostics is a branch of knowledge that studies the signs of vehicle malfunctions, methods, means and algorithms for determining its technical condition without disassembly, as well as the technology and organization of the use of diagnostic systems in the process of technical operation. Diagnostics is the process of determining the technical state of an object without disassembling it, by external signs by changing the values that characterize its state and comparing them with the standards. Diagnosis is carried out according to the algorithm (set of sequential actions) established by the technical documentation. The complex, including the object, tools and algorithms, form a diagnostic system. Diagnostic systems are divided into functional, when the objects are diagnosed during operation, and test systems, when, when the diagnostic parameters are changed, the operation of the object is artificially reproduced. There are universal systems designed for several different diagnostic processes, and special systems that provide only one diagnostic process. The purpose of the diagnosis is to identify malfunctions of the facility, to determine the need for repair or maintenance, to assess the quality of the work performed, or to confirm the suitability of the diagnosed mechanism for operation before the next service. 
It is required to make a diagnosis based on a set of signs: 
; 
; 
;
- probability of diagnostic parameters - diagnosis
II... Licensing and certification in road transport.
1. Activities licensed in the field of road transport, the procedure for obtaining a license. In accordance with the law, the provision provides for the licensing of passenger transportation by road vehicles equipped for the carriage of more than eight people. Licensing of passenger transportation by road is carried out by the Ministry of Transport of the Russian Federation, which entrusted these responsibilities to RTI. The Ministry of Transport of the Russian Federation in the field of motor transport is entrusted with the authority to license only three types of activities: the carriage of passengers by buses, the carriage of passengers by cars and the carriage of goods. An appropriate license is provided for the licensed type of activity. Licensing requirements and conditions for the carriage of passengers and goods by road are: a) compliance with the requirements established by federal laws; b) the conformity of the vehicles declared for the transportation; c) compliance of an individual entrepreneur and employees with qualification requirements; d) the presence in the staff of a legal entity of officials responsible for ensuring road safety. License - a document representing a permit to carry out a specific type of activity subject to mandatory compliance with licensing requirements. To obtain a license, the license applicant submits the following documents to the licensing authority: 1) Application indicating the legal entity, legal form, address, for individual entrepreneurs: full name, passport data, indication of the type of activity; 2) A copy of the constituent document or a copy of the IP registration certificate; 3) A copy of the certificate of registration with the tax office; 4) Copy of qualification documents; 5) A copy of the documents of the road safety specialist; 6) Information about vehicles; 7) Receipt of payment for licensing. The decision to issue a license must be issued within 30 days. The license is valid for no more than 5 years.
2. Technical regulations and other documents used for certification. Technical regulations - a document that is adopted by an international treaty of the Russian Federation, ratified in the manner prescribed by the legislation of the Russian Federation or federal law and establishes requirements for the application and execution of the objects of technical regulation (products, production processes, operation, storage, transportation). purposes: a) to protect the life or health of citizens; b) property of individuals or legal entities, state or municipal property; c) protection of the environment, life or health of animals and plants; d) prevention of actions misleading purchasers (consumers of services). The adoption of technical regulations for other purposes is not allowed. Unlike mandatory technical regulations, a standard as a basis for certification is a normative document developed on the basis of consensus, approved by a recognized body, aimed at achieving an optimal degree of harmonization in a particular area. A standard is a document in which, for the purpose of voluntary repeated use, the characteristics of products, rules for implementation and characteristics of the processes of production, operation, storage, transportation, and sale are established.
3. Basic concepts of certification, its forms and participants. Certification translated from Latin means “done right”. Certification is a procedure by which a third party certifies in writing that a properly identified product, process, or service meets specified requirements. The certification system consists of: a central body; rules and procedure for certification; regulations; inspection control procedure. The objectives of certification are: a) certification of the conformity of products, production processes, operation, storage of transportation to standards and terms of contracts; b) assistance to purchasers in the choice of products, works and services; c) increasing the competitiveness of products, works, services in the Russian and international markets; d) creating conditions to ensure the free movement of goods across the territory of the Russian Federation. Certification can be mandatory or voluntary, which is directly related to the presence or absence of adopted technical regulations. To carry out certification, systems are created, including: 1) a central body that manages the entire system; 2) certification bodies; 3) rules and regulations of certification; 4) regulatory documentation. The system is usually organized on a sectoral basis. Certification body - an individual or legal entity accredited in accordance with the established procedure. The functions of the certification body: a) carry out confirmation of conformity; b) issues a certificate; c) represents the right to use a mark of circulation on the market (if mandatory) or conformity (if voluntary); d) suspend or terminate the issued certificate. To register a voluntary certification system, you need: a) a certificate of state registration of a legal entity or individual entrepreneur; b) the image of the conformity mark; c) receipt of payment for registration (registration takes place within 5 days). The law provides for 2 types of mandatory certification: 1) declaration of conformity; 2) certification of conformity. Declaration of conformity is carried out: a) adoption of a declaration of conformity based on their own evidence; b) acceptance of a declaration of conformity based on their own evidence and evidence obtained with the participation of a certification body or an accredited testing laboratory.
1.1. Fundamentals of the theory of reliability
a) Reliability and solution of problems of accelerating scientific and technological progress.
As the technology becomes more complex, the scope of its use expands, the level of automation increases, loads and speeds increase, the role of reliability issues increases. Their solution is one of the main sources of increasing the efficiency of technology, saving material, labor and energy costs.
Example 1. The cost of a 10% increase in the resource of automobile tires is 0.2% of their cost. Increasing the reliability of tires leads to a corresponding decrease in the need for them. As a result, the cost of producing tires that provide a solution to a specific transport problem is 0.898 of their initial cost.
In connection with the complication of technology, the price of malfunctions arising during its operation has significantly increased.
Example 2. Excavator E-652 replaces the work of 150 excavators. One hour of its downtime leads to significant material losses.
Insufficient, high level of reliability is one of the main reasons for unreasonably high costs for maintenance, equipment repair and production of spare parts.
Example 3. To maintain tractors in working order, twice as much money is spent on repair and maintenance during the service life as on the purchase of a new one.
b) Basic concepts of reliability.
Reliability is a property of the system keep in time within the established limits, the values of all parameters characterizing the ability to perform the required functions in the specified modes of use, maintenance, repair, storage and transportation.
Reliability is a complex, complex, but nevertheless clearly (at the level of GOST) regulated property of the system.
Let us consider sequentially, in accordance with the cause-and-effect relationship, the basic concepts used to describe reliability.
Reliability as a complex property of a system is determined by a combination of four whiter than simpler properties, namely: reliability, durability, maintainability and preservation. Moreover, depending on the design and functioning of the system, this or that property (or properties) may not be included in the reliability. For example, if a rolling bearing cannot be repaired, then maintainability is not included in the reliability property. The classification of reliability properties is shown in Fig. 1.1.
Reliability is a property of the system continuously maintain a healthy state when operating for some(given) time or some(given) operating time.
Durability - the property of the system to function up to the ultimate condition under the established procedure for maintenance and repair.
Maintainability is a system property that in fitness for warning and detection pre-failure conditions, failures and damages, maintenance and restoration of an operable state through maintenance and repair.
Persistence - the property of the system to retain the values of indicators of reliability, durability and maintainability during and after storage and (or) transportation.
When determining the properties of reliability, concepts were used that define various states of the system. Their classification is shown in Fig. 1.2.
Serviceable - the state of the system in which it currently corresponds to all requirements established as in relation main parameters characterizing the functioning of the system, and in relation to secondary parameters, characterizing ease of use, appearance, etc.
Defective - the state of the system in which it is at a given time of the requirements established as in relation major and minor parameters.
Serviceable - the state of the system, in which it at a given time corresponds to all requirements established in relation main parameters.
Inoperative - the state of the system in which it is at a given time does not match at least one of the requirements established for main parameters.
Limit - the state of the system in which it temporarily or finally cannot be operated. The limiting state criteria for different systems are different and are established in the normative and technical design or operational documentation.
It follows from the above definitions that a faulty system can be operable (for example, a car with a damaged body paint), and an inoperative system is also faulty.
The transition of the system from one state to another occurs as a result of an event. The classification of events is shown in Fig. 1.3., And the graph explaining it in Fig. 1.4.
Damage is an event as a result of which the system ceases to meet the requirements for secondary parameters.
Failure is an event as a result of which the system ceases to meet the requirements for the main poi of the main and secondary parameters, i.e. complete or partial loss of working capacity.
Failure - self-healing failure.
Exhaustion of a resource is an event as a result of which the system goes to the limit state. Of the listed events, the most important is failure, which is classified as:
A. By importance (critical, essential, insignificant).
B. By the nature of the occurrence (sudden, gradual).
B. By the nature of detectability (explicit, hidden).
D. By reason of occurrence (constructive, production, operational, degradation).