Some standard content:
National Metrology Technical Specification of the People's Republic of China JJF1024-2006
Reliability Analysis for Measuring InstrumentsIssued on September 6, 2006
Implementation on March 6, 2007
Issued by the General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China JJF1024—2006
Reliability Analysis for
Measuring Instruments
JJF1024—2006
Replaces JJF1024—1991
This specification was approved by the General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China on September 6, 2006, and came into effect on March 6, 2007.
Responsible unit: National Legal Metrology Management Metrology Technical Committee Drafting unit: Ministry of Information Industry Electronic Fifth Research Institute Jiangxi Metrology and Testing Research Institute
China Metrology Science Research Institute
This specification is interpreted by the National Legal Metrology Management Metrology Technical Committee Drafting persons of this specification:
Xie Shaofeng
Yu Huixia
Chen Dazhou
Zhang Zengzhao
Gu Wengang
Shi Changyan
JJF1024—2006
(Ministry of Information Industry Electronic Fifth Research Institute)
(Jiangxi Metrology and Testing Research Institute)
(China Metrology Science Research Institute)
(Ministry of Information Industry Electronic Fifth Institute) (Fifth Electronic Research Institute of the Ministry of Information Industry) (National Legal Metrology Management Metrology Technical Committee) 1
References
4 Reliability analysis procedures and methods
Analysis and determination of reliability indicators·
4.2 Establishment of reliability model.
Allocation of reliability indicators·
4.4 Reliability prediction
Failure mode and effect analysis·
Barrier tree analysis
Tolerance and drift analysis
5 Reliability evaluation·
5.1 Life test
5.2 Environmental test
5.3 Maintenance period analysis
6 Timing of application of reliability work items,
JJF 1024—2006
Appendix A Reliability life evaluation test for measuring instruments Appendix B Type evaluation reliability test for fully electronic electric energy meters Appendix Reference standards
(14)
1 Scope
JJF10242006
Reliability analysis of measuring instruments
This specification specifies the basic principles, requirements and methods for reliability analysis of measuring instruments, and provides guidance for reliability description, modeling, prediction, indicator allocation and indicator series division, failure mode and effect analysis, fault tree analysis, test verification, and fault judgment of measuring instruments. Applicable to measuring instruments in the design, development, testing, production, acceptance, use of reference documents
GB/T2423 series standards
Electrical and electronic
Reliability,
GB/T3187-
GB/T508041985
(Exponential distribution)
GB/T508076/-1996
GB/T 5080
Time verification test plan
GB/T7289-1987
Basic environment test procedures for products
Maintainability terms
Equipment reliability test Multi-estimation and interval estimation methods for reliability determination test Equipment reliability test
Effective test of constant failure rate assumption
Equipment reliability test Failure rate and mean failure-free maintainability and effectiveness design report writing guide Reliability,
GB/T7826
GB/T782931987
GJB/Z89
GJB/Z108
GJB/Z299B
System reliability
Analysis technology
Fault tree analysis procedure
Circuit tolerance analysis guide
Effect mode and effect extension
MEA) procedure
Handbook of reliability prediction of electronic equipment in non-operating state
Reliability prediction handbook of electronic equipment
2002General specification for type evaluation and type approval of measuring instruments JJF1015-
JB/T6214-
Guidelines for reliability verification and test (exponential distribution) of public instruments
-2002 Reliability requirements and assessment methods of electric energy meters JB/T50070-2
When using this specification, attention should be paid to the use of the current valid versions of the above-mentioned references METROLOG
|3 Terminology
3.1 Reliability reliability [performance] The ability of a measuring instrument to complete the specified functions under specified conditions and within a specified time. Note: The specified time is in a broad sense and can be hours, years, mileage, number of times, etc. depending on the measuring instrument. 3.2 Basic reliability basicreliability The duration or probability of a measuring instrument being fault-free under specified conditions. 3.3 Mission reliability missionreliability The ability of a measuring instrument to complete specified functions within a specified mission profile. Note: Mission profile refers to the time sequence description of events and environments experienced by a measuring instrument within the time it takes to complete a specified mission. 1
3.4 Reliability reliability
JJF 1024—2006
The probability that a measuring instrument can complete a specified function under specified conditions and within a specified time is generally recorded as r. It is a function of time, so it is also recorded as R (t), which is called the reliability function. R(t) = p(0 > )
Where is the specified time, when r=0, R(0)=1 When t=0o, R(αo)=0. 3.5 Failure fault
The measuring instrument loses its specified function, which is manifested by its uncertainty exceeding the allowable value or malfunction (for repairable measuring instruments, it is also called a fault).
3.6 Life span Tlife
The continuous use period of the measuring instrument. The life span of the measuring instrument is a random variable. 3.7 Mean time between failures (MTBF) For repairable measuring instruments, the mean time between failures refers to the average time between two failures. Sometimes it is also called the mean time between failures.
3.8 Mean time to failure (MTTF) For non-repairable measuring instruments, the mean time to failure refers to the average time from the start of operation to the time before failure. Sometimes it is also called the mean failure time.
3.9 Mean life span 8mean ife
In reliability analysis and reliability testing, 6 is often used to represent the average life span. At this time, it can represent MTBF or MTTF depending on the characteristics of the measuring instrument.
3.10 Failure distribution function F(t) The function of the probability of failure of a measuring instrument under specified conditions that varies with time is denoted as F(). F(t) = p(8 ≤t)
Wherein, t is the specified time. When t=0, F(0)-0; when t=, F(oo)=1. 3.11 Instantaneous failure rate function F(t) failure rate function The probability of failure of a measuring instrument in a unit time after a time when the measuring instrument has not failed and has not failed yet. It is referred to as failure rate.
F(t + At) - F(t) - dF(t)
(t) = jim
dtR(t)
R(t)At
Note: When the life distribution law of the measuring instrument obeys the exponential distribution, it can be obtained that: F(t) = 1 -e-
f(t) = Ae-
R(t) = er
A() = ^(constant)
Wherein, f (1) is the failure distribution density. 4 Reliability analysis procedures and methods
4.1 Analysis and determination of reliability indicators
The reliability indicators of measuring instruments are usually specified as MTBF (or MTTF) and R(t). In the measuring instrument scheme 2
JJF 1024—2006
4.2.4.3 When modeling, the reliability block diagram and the working principle diagram should be correctly distinguished. The former represents the logical relationship of faults between the components of the instrument, and the latter represents the physical relationship between the units. 4.3 Allocation of reliability indicators
The allocation of reliability indicators refers to the decomposition of reliability indicators or indicators that are expected to be achieved, and the scientific and reasonable allocation to the specified instrument units. The allocation of reliability indicators should be based on the reliability block diagram, that is, each box should have a corresponding reliability indicator, so that the reliability indicator of the instrument can be guaranteed. 4.3.1 Proportional allocation method
If one of the following conditions is met, the proportional allocation method can be used to allocate reliability indicators: 1. The structure of the measuring instrument is relatively simple and mature, and the reliability of each functional block has been predicted, or there is empirical data in this regard;
There are similar instruments that have been used for a long time, with a certain historical field failure rate record, or there are examples in this regard;
The main part of the equipment is composed of purchased parts, and these purchased parts have relatively complete reliability data. When the system reliability index of the original instrument is known and the failure rate of each subsystem is known, the allocation formula is: Anew = A,new × K
wherein, Anew is the failure rate assigned to the ith new subsystem; Anew is the failure rate of the specified new system; K, is the ratio of the failure rate of the ith subsystem in the original system to the failure rate of the original system. (6)
For example: A measuring instrument is designed to be miniaturized based on the original instrument. The reliability index of the original instrument is known to be MTBF=40h, and the reliability index of the new measuring instrument is required to be MTBF=100h. Obviously, A;original=40h
= 25 × 10-3/h
A:x = 100h = 1 × 10-2/h
The failure rate indexes of the 6 subsystems of the original instrument are shown in Table 1. Taking subsystem 1 as an example, K,=
Then the failure rate assigned to subsystem 1
2×10-3
25×10-
入1新= 入新·K, = 8× 10-*/hThe reliability index MTBF assigned to subsystem 1=-h=1250h
8× 10-
Similarly, the reliability indexes of other subsystems can be obtained, see Table 1 for details. Table 1 Reliability index allocation table of a profit measuring instrument Subsystem number
Original failure rate/(10-3/h)
Newly allocated failure rate/(10-/h)Newly allocated MTBE0.8
Subsystem number
Original failure rate/(10-/h)
4.3.2 Comprehensive factor evaluation method
JJF 1024—2006
Table 1 (wisp)
Newly allocated failure rate/(10->/h)Newly allocated MTBF3.2
The comprehensive factor evaluation method can be used to allocate reliability indexes when any of the following conditions are met: when there are multiple instruments forming a system and reliability indexes are allocated to the system; when the technology is relatively complex, the working conditions are relatively harsh or new technologies are adopted; when there are no similar instruments.
The comprehensive factor evaluation method takes into account the complexity, importance, environmental conditions, maintainability, technical maturity, reliability improvement potential and other factors of each functional block. Each factor is given a quantitative evaluation coefficient K, and the ith evaluation coefficient of the ith unit is recorded as K. For the model of exponential distribution series structure, the allocation formula is MTBF:
Where: MTBF--the average failure interval time of the ith subsystem: MTBF the average failure interval time of the whole machine (or system); K,--the i-th allocation factor of the j-th subsystem. (7)
Example: The reliability index of a measuring instrument is: MTBF = 40h. It is known that the measuring instrument consists of 6 subsystems. The weighted factor of each item of the first subsystem is 1. The values of other subsystems compared with it are shown in Table 2. According to the reliability index distribution, according to formula (7), the reliability index distribution of the measuring instrument is as follows: Subsystem 1: MTBF = 11.44-1×40==458 (h) Subsystem 2: MTBF = 11.44-1.12×40~408 (h) Subsystem 3: MTBF = 11.44-4.80×4095 (h) Subsystem 4 MTBF = 11.44-3.60 × 40 = 127 (h) Subsystem 5: MTBF = 11.44-0.16× 40~2860 (h) Subsystem 6: MTBF = 11.44-0.75×40^=610 (h) Table 2 Reliability index allocation table of a measuring instrument Item
Complexity factor
Important factor
Subsystem 1
Subsystem 2
Subsystem 3
Subsystem 4
Subsystem 5
Subsystem 6
Environmental factor
Standardized factor
Maintenance factor
Component quality factor
4.4 Reliability prediction
Subsystem!
JJF 1024-2006
Table 2 (continued)
Subsystem 2
Subsystem 3
Subsystem 4
Subsystem 5
Subsystem 6
Reliability prediction refers to the method of predicting the future reliability performance of the measuring instrument based on its parts, performance, working environment and their relationship. It is the key to transform the reliability of the measuring instrument from qualitative consideration to quantitative analysis. 4.4.1 Reliability prediction method
Different methods can be used for reliability prediction at different stages. 4.4.1.1 Similarity method
The similarity method is applicable to the overall demonstration stage of the initial conception and planning of the measuring instrument, and can usually only make a rough estimate. Among them, the accuracy of the prediction of the similar equipment method depends on the credibility of the reliability data of the existing equipment and the similarity between the existing equipment and the new equipment.
4.4.1.2 Component Counting Method
The component counting method is applicable to the early stage of the development phase, when preliminary design has been carried out and functional principle block diagrams and circuit sketches have been formed. The number of each component has been basically determined, but stress data is still missing. This method is used to determine whether the design scheme meets the reliability index, optimize and carry out reliability allocation. 4.4.1.3 Component Stress Analysis Method
The component stress analysis method is applicable to the middle and late stages of the development phase, that is, during the prototype development period after comprehensive circuit testing. At this time, detailed circuit diagrams, component lists and stress data on each component are available. Through stress analysis, the weak links in the reliability of the prototype are discovered and corresponding measures are taken to improve the design. 4.4.2 Reliability Prediction Process
The general process of reliability prediction of measuring instruments is shown in Table 3: Table 3 Reliability Prediction Process of Measuring Instruments
Process No.
Definition Measuring Instruments
Measuring Instrument Components
Measuring Instrument Scheme Demonstration Phase
Specify its working mode, characteristics, performance requirements
Generally divided into functional blocks
Measuring Instrument Design Phase
Specify its Working mode, characteristics, performance requirements, more specific indicators, more sufficient reasons
Understand the structure, divide the determined functional blocks
Process number
Reliability frame
Environmental information
Stress information
Probability distribution
Failure rate
Establish reliability model
Reliability prediction
Write reliability prediction report
4.4.3 Reliability prediction requirements
JJF 1024--2006
Table 3 ()
Measuring instrument scheme demonstration stage
Simple Shenlian system
Specify the environmental information that affects the components
Not conduct
Exponential distribution
Use the reliability item calculation manual or
similar instrument field failure rate to obtain
Establish a basic reliability model
Use similar equipment method, similar
circuit method, etc.
According to GB/7289-1987 Regulations
Implementation
Measuring instrument design stage
Simplify the parallel system
Further specify the environmental information that affects the components
Measurement instruments are subjected to harsh conditions when working, electrical stress, thermal stress and the distribution of the working mode index
Use reliability prediction or similar instrument field failure rate to obtain
Establish a basic reliability model. If necessary, a mission reliability model can also be established
Use the component counting method and component stress separation method
According to GB/T7289-1987 regulations
4.4.3.1 Reliability prediction shall be carried out in accordance with the provisions of GJB/Z299B-1998 and GJB/Z 108A1998. 4.4.3.2 Reliability prediction shall be carried out in parallel with the distribution and development of measuring instruments. After the development contract of ordinary measuring instruments is signed, reliability distribution is generally not carried out; however, reliability prediction shall still be carried out in succession as the development work progresses. 4.4.3.3 For non-electronic equipment, the similarity method can be used for reliability prediction. Example: The reliability of a newly developed measuring instrument is predicted by the "component counting method": a) Establish a reliability model and divide it into three parts according to the characteristics and structure of the measuring instrument, namely, the power supply part, the measuring part, and the display part, as shown in Figure 4.
Power supply part
Figure 4 Reliability model of a measuring instrument
Display part
b) List the types and quantities of components, quality grades and application environment categories of the above parts. c) From Section 5.2 of GJB299B-1998, find out the general failure rate of various components in this environmental category and the general quality factor Q
d) Fill the data obtained in steps (b) and (c) into the standardized prediction tables 4, 5, and 6. e) Calculate the general failure rate of each part according to the formula
of GJB299B-1998.
f) Calculate the failure rate according to the reliability model
SN; .(AGTQ)
Enter, = Enter the electric game + Enter the bottle + Human strain = (3.9316 + 3.6996 + 0.73536) ×10-*/h = 8.367 × 10-6/h8
JJF1024-2006
Therefore, the failure rate of the measuring instrument is 8.367×10-/h, and the expected MTBF value is 1.195×10°h. Table 4 Reliability prediction table of a power module of a measuring instrument Component types and parameters
CMOS digital circuit, 10 gates
Power transformer
Semiconductor regulator
Metal film resistor
Aluminum electrolytic capacitor
Mica capacitor
Circular connector
No wrap soldering iron solder joint
Metalized hole
Double-sided printed circuit board,
Quantity N
/(10-6/h)
(10-6/h）
EONIESI
Imported from source
Component types
CMOS mathematics
Developed parameters
Circular connector
No wrap soldering
Double-sided printed circuit board,
Metalized holes
Reliability prediction table of a measuring instrument measurement module quantity
(10-6/h）
os004s
Reliability prediction table of a measuring instrument display module Table 6
Component types and parameters
CMOS digital circuit, 10 gates
2-digit digital tube
Circular connector
No wrap soldering iron solder joint
Double-sided printed circuit board, 40 metalized holes
Input display
METROLOG
(10-6/h）
SN, (XeQ)
入GTo
(10-6/h）
N(AGTQ)
（10-*/h）
N·(AGQ)
（（10-5/h）
N·（入G元）
(10-6/h)
4.5 Failure mode and effects analysis
JJF 1024—2006
Failure mode and effects analysis (FMEA) refers to the analysis of the potential failure modes of each component of the measuring instrument and its impact on the instrument function, and the possible preventive measures to improve the instrument design. If the criticality of the failure mode is further analyzed according to the probability of occurrence, it is a fault model, effects and criticality analysis (FMEA). analysis, referred to as FMECA). 4.5,1 General steps of FMEA
a) Draw the functional logic block diagram of the measuring instrument to explain the functional dependence relationship between the various units or functional modules that constitute the instrument;
b) Understand the failure mode of the components or functional modules: c) According to the severity of the failure mode on the instrument, classify the severity level; d) Use the network diagram analysis method to determine the severity of the failure mode: c) Propose preventive measures.
4.5.2 Through FMEA, it should be
- Identify the unacceptable or very serious failures caused by the analyzed unit, determine the failure mode that may have a fatal impact on the expected or required operation, and list the subordinate failures caused by it;- Determine the components, parts and complete parts that need to be selected;- Ensure that the failure modes caused by various detection methods can be identified;- Select the key points of prevention or correct maintenance, and formulate a fault repair guide. 4.5.3FMEA should be carried out from the scheme demonstration stage, and it must be continuously modified, supplemented and improved as the design work gradually deepens. The specific methods and procedures of FMEA can be found in GB/T7826-1987. 4.6 Fault Tree Analysis
Fault tree analysis (FTA for short) is a method of starting from the fault phenomenon being studied, finding out the root cause of its occurrence, and studying system failures from effect to cause or from top to bottom. It takes the undesirable fault state (top event) of the system as the analysis standard, finds out all possible direct causes (intermediate events) that cause this fault, and then traces and finds out all possible causes that cause each intermediate event, step by step, until the basic cause (bottom event) is found.
4.6.1 General steps of fault tree analysis
a) Construct a fault tree;
b) Simplify the fault tree;
c) Qualitative analysis, that is, find the minimum cut set, make qualitative comparison, and determine the direction of improvement: d) Quantitative calculation, that is, calculate the probability of each event according to the minimum cut set, bottom event probability and mathematical model; perform importance analysis to determine the priority of corrective measures; e) Propose improvement measures.
Figure 5 shows the fault tree analysis diagram of the overheating of the motor of the channel electric energy meter. 4.6.2FTA should be combined with FMEA, that is, through FMEA, the key failure modes that affect safety and task completion are found, and the fault tree is established based on this; at the same time, multi-factor analysis is carried out to find the combination of various failure modes to provide a basis for improving the design. The fault tree should be established by the designer on the basis of FMEA and by relevant technical personnel.195×10°h. Table 4 Reliability prediction table of a power module of a measuring instrument Component types and parameters
CMOS digital circuit, 10 gates
Power transformer
Semiconductor regulator
Metal film resistor
Aluminum electrolytic capacitor
Mica capacitor
Circular connector
No wrap soldering iron solder joint
Metalized hole
Double-sided printed circuit board,
Quantity N
/(10-6/h)
(10-6/h）
EONIESI
Imported from source
Component types
CMOS mathematics
Development parameters
Circular connector
No wrap soldering
Double-sided printed circuit board,
Metalized holes
Reliability prediction table of a measuring instrument measurement module quantity
(10-6/h）
os004s
Reliability prediction table of a measuring instrument display module Table 6
Component types and parameters
CMOS digital circuit, 10 gates
2-digit digital tube
Circular connector
No wrap soldering iron solder joint
Double-sided printed circuit board, 40 metalized holes
Input display
METROLOG
(10-6/h）
SN, (XeQ)
入GTo
(10-6/h）
N(AGTQ)
（10-*/h）
N·(AGQ)
（（10-5/h）
N·（入G元）
(10-6/h)
4.5 Failure mode and effects analysis
JJF 1024—2006
Failure mode and effects analysis (FMEA) refers to the analysis of the potential failure modes of each component of the measuring instrument and its impact on the instrument function, and the possible preventive measures to improve the instrument design. If the criticality of the failure mode is further analyzed according to the probability of occurrence, it is a fault model, effects and criticality analysis (FMEA). analysis, referred to as FMECA). 4.5,1 General steps of FMEA
a) Draw the functional logic block diagram of the measuring instrument to explain the functional dependence relationship between the various units or functional modules that constitute the instrument;
b) Understand the failure mode of the components or functional modules: c) According to the severity of the failure mode on the instrument, classify the severity level; d) Use the network diagram analysis method to determine the severity of the failure mode: c) Propose preventive measures.
4.5.2 Through FMEA, it should be
- Identify the unacceptable or very serious failures caused by the analyzed unit, determine the failure mode that may have a fatal impact on the expected or required operation, and list the subordinate failures caused by it;- Determine the components, parts and complete parts that need to be selected;- Ensure that the failure modes caused by various detection methods can be identified;- Select the key points of prevention or correct maintenance, and formulate a fault repair guide. 4.5.3FMEA should be carried out from the scheme demonstration stage, and it must be continuously modified, supplemented and improved as the design work gradually deepens. The specific methods and procedures of FMEA can be found in GB/T7826-1987. 4.6 Fault Tree Analysis
Fault tree analysis (FTA for short) is a method of starting from the fault phenomenon being studied, finding out the root cause of its occurrence, and studying system failures from effect to cause or from top to bottom. It takes the undesirable fault state (top event) of the system as the analysis standard, finds out all possible direct causes (intermediate events) that cause this fault, and then traces and finds out all possible causes that cause each intermediate event, step by step, until the basic cause (bottom event) is found.
4.6.1 General steps of fault tree analysis
a) Construct a fault tree;
b) Simplify the fault tree;
c) Qualitative analysis, that is, find the minimum cut set, make qualitative comparison, and determine the direction of improvement: d) Quantitative calculation, that is, calculate the probability of each event according to the minimum cut set, bottom event probability and mathematical model; perform importance analysis to determine the priority of corrective measures; e) Propose improvement measures.
Figure 5 shows the fault tree analysis diagram of the overheating of the motor of the channel electric energy meter. 4.6.2FTA should be combined with FMEA, that is, through FMEA, the key failure modes that affect safety and task completion are found, and the fault tree is established based on this; at the same time, multi-factor analysis is carried out to find the combination of various failure modes to provide a basis for improving the design. The fault tree should be established by the designer on the basis of FMEA and by relevant technical personnel.195×10°h. Table 4 Reliability prediction table of a power module of a measuring instrument Component types and parameters
CMOS digital circuit, 10 gates
Power transformer
Semiconductor regulator
Metal film resistor
Aluminum electrolytic capacitor
Mica capacitor
Circular connector
No wrap soldering iron solder joint
Metalized hole
Double-sided printed circuit board,
Quantity N
/(10-6/h)
(10-6/h）
EONIESI
Imported from source
Component types
CMOS mathematics
Development parameters
Circular connector
No wrap soldering
Double-sided printed circuit board,
Metalized holes
Reliability prediction table of a measuring instrument measurement module quantity
(10-6/h）
os004s
Reliability prediction table of a measuring instrument display module Table 6
Component types and parameters
CMOS digital circuit, 10 gates
2-digit digital tube
Circular connector
No wrap soldering iron solder jointwwW.bzxz.Net
Double-sided printed circuit board, 40 metalized holes
Input display
METROLOG
(10-6/h）
SN, (XeQ)
入GTo
(10-6/h）
N(AGTQ)
（10-*/h）
N·(AGQ)
（（10-5/h）
N·（入G元）
(10-6/h)
4.5 Failure mode and effects analysis
JJF 1024—2006
Failure mode and effects analysis (FMEA) refers to the analysis of the potential failure modes of each component of the measuring instrument and its impact on the instrument function, and the possible preventive measures to improve the instrument design. If the criticality of the failure mode is further analyzed according to the probability of occurrence, it is a fault model, effects and criticality analysis (FMEA). analysis, referred to as FMECA). 4.5,1 General steps of FMEA
a) Draw the functional logic block diagram of the measuring instrument to explain the functional dependence relationship between the various units or functional modules that constitute the instrument;
b) Understand the failure mode of the components or functional modules: c) According to the severity of the failure mode on the instrument, classify the severity level; d) Use the network diagram analysis method to determine the severity of the failure mode: c) Propose preventive measures.
4.5.2 Through FMEA, it should be
- Identify the unacceptable or very serious failures caused by the analyzed unit, determine the failure mode that may have a fatal impact on the expected or required operation, and list the subordinate failures caused by it;- Determine the components, parts and complete parts that need to be selected;- Ensure that the failure modes caused by various detection methods can be identified;- Select the key points of prevention or correct maintenance, and formulate a fault repair guide. 4.5.3FMEA should be carried out from the scheme demonstration stage, and it must be continuously modified, supplemented and improved as the design work gradually deepens. The specific methods and procedures of FMEA can be found in GB/T7826-1987. 4.6 Fault Tree Analysis
Fault tree analysis (FTA for short) is a method of starting from the fault phenomenon being studied, finding out the root cause of its occurrence, and studying system failures from effect to cause or from top to bottom. It takes the undesirable fault state (top event) of the system as the analysis standard, finds out all possible direct causes (intermediate events) that cause this fault, and then traces and finds out all possible causes that cause each intermediate event, step by step, until the basic cause (bottom event) is found.
4.6.1 General steps of fault tree analysis
a) Construct a fault tree;
b) Simplify the fault tree;
c) Qualitative analysis, that is, find the minimum cut set, make qualitative comparison, and determine the direction of improvement: d) Quantitative calculation, that is, calculate the probability of each event according to the minimum cut set, bottom event probability and mathematical model; perform importance analysis to determine the priority of corrective measures; e) Propose improvement measures.
Figure 5 shows the fault tree analysis diagram of the overheating of the motor of the channel electric energy meter. 4.6.2FTA should be combined with FMEA, that is, through FMEA, the key failure modes that affect safety and task completion are found, and the fault tree is established based on this; at the same time, multi-factor analysis is carried out to find the combination of various failure modes to provide a basis for improving the design. The fault tree should be established by the designer on the basis of FMEA and by relevant technical personnel.1 General steps of fault tree analysis
a) Construct fault tree;
b) Simplify fault tree;
c) Qualitative analysis, that is, find the minimum cut set, make qualitative comparison, and determine the direction of improvement: d) Quantitative calculation, that is, calculate the probability of each event according to the minimum cut set, the probability of the bottom event and the mathematical model; perform importance analysis to determine the priority of corrective measures; e) Propose improvement measures.
Figure 5 shows the fault tree analysis diagram of the overheating of the channel electric energy meter motor. 4.6.2FTA should be combined with FMEA, that is, find out the key failure modes that affect safety and task completion through FMEA, and establish a fault tree based on this as the top event; at the same time, conduct multi-factor analysis to find out the combination of various failure modes and provide a basis for improving the design. The fault tree should be established by the designer on the basis of FMEA and by relevant technical personnel.1 General steps of fault tree analysis
a) Construct fault tree;
b) Simplify fault tree;
c) Qualitative analysis, that is, find the minimum cut set, make qualitative comparison, and determine the direction of improvement: d) Quantitative calculation, that is, calculate the probability of each event according to the minimum cut set, the probability of the bottom event and the mathematical model; perform importance analysis to determine the priority of corrective measures; e) Propose improvement measures.
Figure 5 shows the fault tree analysis diagram of the overheating of the electric energy meter motor. 4.6.2FTA should be combined with FMEA, that is, find out the key failure modes that affect safety and task completion through FMEA, and establish a fault tree based on this as the top event; at the same time, conduct multi-factor analysis to find out the combination of various failure modes and provide a basis for improving the design. The fault tree should be established by the designer on the basis of FMEA and by relevant technical personnel.
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