CN110032821A - A kind of intelligent electric actuating mechanism failure analysis method - Google Patents
A kind of intelligent electric actuating mechanism failure analysis method Download PDFInfo
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- CN110032821A CN110032821A CN201910319017.6A CN201910319017A CN110032821A CN 110032821 A CN110032821 A CN 110032821A CN 201910319017 A CN201910319017 A CN 201910319017A CN 110032821 A CN110032821 A CN 110032821A
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Abstract
A kind of intelligent electric actuating mechanism failure analysis method.It is related to automation field, especially a kind of intelligent electric actuating mechanism failure analysis method.A kind of method of intelligent electric actuating mechanism failure analysis is provided, to being analyzed before electric operator failure cause, electric operator failpoint is judged, improves the design and processes of electric operator, reduce the generation of failure.By to intelligent electric actuating mechanism function division, count the work tentative idea and danger crash rate of component, then in order to which the crash rate to each component carries out Comprehensive Comparison, data normalization processing is carried out to crash rate, in addition, increasing live use experience data, failure statistics database can be enriched, it is bonded this method more practical, on the one hand which can provide the foundation of reference to the reduction of failure risk, in addition the positioning to failure of removal point provides prediction technique.
Description
Technical field
The present invention relates to automation field, especially a kind of intelligent electric actuating mechanism failure analysis method.
Background technique
Intelligent electric actuating mechanism is auxiliary products needed for valve realizes industrial automation, and intelligent electric executes machine
Structure increases the intelligent control unit of control motor operation, intelligent control unit packet on the basis of traditional electric operator
Containing Important Components such as capacitor, resistance, transistor, gate circuit, chips, and these components may cause electronic once failing
The forfeiture of actuating mechanism function, or even valve pipe is caused to damage, it causes huge human and economic losses.
Summary of the invention
The present invention is in view of the above problems, provide a kind of method of intelligent electric actuating mechanism failure analysis, to electronic
Analyzed before executing agency's failure cause, judge electric operator failpoint, improve electric operator design and
Technique reduces the generation of failure.
The technical scheme is that being analyzed according to the following steps:
Step 1), statistical work crash rate λp；
λp=λbπQπEπTπS, λbFor the basic failure rate for not considering other factors, πQFor quality coefficient, πEEnvironmental coefficient, πT
Temperature coefficient, πSStress coefficient；The component inventory of all components of intelligent electric actuating mechanism is counted, it is every to what is be applied to
A component carries out work tentative idea λpStatistics；
Step 2) divides invalidation functions block；
Intelligent electric actuating mechanism can provide specific dead code when failing, and can divide electronic hold according to dead code
Whether safety-related row body function block defines the function according to the effect of electric operator functional block, if safety-related,
By the height of component failure rate in analytic function block, i.e., predictable failure of removal point；
The electric operator functional block is that electric operator is the hardware circuit integrated package for realizing a certain function, institute
Stating electric operator functional block includes power module circuitry, phase sequence and phase shortage decision circuitry, remote switching operations circuit, on the spot
Operation circuit, analog quantity operation circuit, master chip circuit, sensor Acquisition Circuit, signal feedback circuit, EEPROM storage circuit
With interface display circuit；
Step 3) counts dangerous failure probability λd；
Each component has its failure mode, and different failure modes can generate safety in the application of specific circuit
Failure and dangerous failure, analyze the failure mode of component in electric operator functional block, calculate dangerous failure probability λd, λd
=k λp, k is dangerous invalid coefficient, is determined according to the failure mode of component；
Step 4), data normalization processing；
Data normalization processing is carried out to work tentative idea, Closer to 1, cause electronic execution
A possibility that failure mechanisms, is bigger, and to dangerous crash rate, Closer to 1, which causes electricity
A possibility that dynamic executing agency's danger failure, is bigger；
For the work tentative idea after normalized,For the dangerous crash rate after normalized,It is all
The minimum value of work tentative idea in component,For the maximum value of work tentative idea in all components,For all members
The minimum value of dangerous crash rate in device,For the maximum value of crash rate dangerous in all components；
The reduction of step 5) failure risk；
In order to reduce the crash rate of intelligent electric actuating mechanism, segment processing is carried out to the crash rate after normalization, such as
FruitIt is considered as change design, replaces the component；IfThe component is paid close attention to,The probability for illustrating that failing occurs in the component is low；λdBecause of its intrinsic failure mode, value depends on λp, can make
For assistant analysis object；
Step 6), abundant failure statistics database:
After crash rate counts, with the batch application of product, fail data is imported in database, is failed each time
Generation, find corresponding failure component, its crash rate handled, λ 'p≤λp+ μ, μ are that failure increases coefficient, can be with
It is determined according to statistical sample；
Step 7) finishes.
The present invention is by the way that intelligent electric actuating mechanism function division, the work tentative idea and danger for counting component are lost
Efficiency carries out data normalization processing to crash rate then in order to which the crash rate to each component carries out Comprehensive Comparison,
According to treated data, the measure that available failure risk reduces, in addition, increasing live use experience data, Ke Yifeng
Rich failure statistics database is bonded this method more practical, on the one hand which can provide ginseng to the reduction of failure risk
The foundation examined, in addition the positioning to failure of removal point provides prediction technique.
Detailed description of the invention
Fig. 1 is intelligent electric actuating mechanism failure analysis flow chart
Fig. 2 is intelligent electric actuating mechanism function division figure
Specific embodiment
The present invention is as shown in Figs. 1-2, is analyzed according to the following steps:
Step 1), statistical work crash rate λp
The component inventory for counting all components of intelligent electric actuating mechanism, works to the component being applied to
Crash rate λpStatistics, the calculating of each component work tentative idea can provide by manufacturer or be obtained according to national standard calculating
Obtain λp=λbπQπEπTπS；
The component inventory should include the component of had an impact electric operator function；
The work tentative idea is a general crash rate, obtains every a collection of intelligent electric actuating mechanism if necessary
Crash rate, it should increase electric operator failure statistics sample；
λbFor the basic failure rate for not considering other factors, πQFor quality coefficient, πEEnvironmental coefficient, πTTemperature coefficient, πSIt answers
Force coefficient；
Step 2) divides invalidation functions block:
Intelligent electric actuating mechanism failure can provide specific dead code, divide electronic execution machine according to dead code
Whether safety-related structure functional block defines the function according to the effect of functional block, if safety-related, by analytic function block
Failure of removal point can be predicted in the height of component failure rate；
As shown in Figure 2, it is the hardware circuit for realizing a certain function that the electronic execution functional block, which is electric operator,
Integrated package includes power module circuitry, phase sequence and phase shortage decision circuitry, remote switching operations circuit, local operation circuit, simulation
Measure operation circuit, master chip circuit, sensor Acquisition Circuit, signal feedback circuit, EEPROM storage circuit and interface display electricity
Road；
Step 3) counts dangerous failure probability λd:
Each component has its failure mode, and different failure modes can generate safety in the application of specific circuit
Failure and danger are failed, and the failure mode of component carries out in analytic function block, calculate dangerous failure probability λd, λd=k λp；
Failure mode is consequence caused by component failure, and safe consequence is Safe Failure, and dangerous consequence is danger
Failure；
K is dangerous invalid coefficient, is determined according to the failure mode of component；
Step 4), data normalization processing:
In order to eliminate the dimension impact between data, need to carry out data normalization processing, each data are in same quantity
Grade is carrying out Comprehensive Comparison, is carrying out data normalization processing to work tentative idea first, More
Close to 1, a possibility that causing electric operator to fail, is bigger, and to dangerous crash rate, More connect
Nearly 1, the component cause electric operator danger fail a possibility that it is bigger；
For the work tentative idea after normalized,For the dangerous crash rate after normalized,It is all
The minimum value of work tentative idea in component,For the maximum value of work tentative idea in all components,For all members
The minimum value of dangerous crash rate in device,For the maximum value of crash rate dangerous in all components；
The reduction of step 5) failure risk:
In order to reduce the crash rate of intelligent electric actuating mechanism, segment processing is carried out to the crash rate after normalization, such as
FruitIt is considered as change design, replaces the component；IfThe component is paid close attention to,The probability for illustrating that failing occurs in the component is low；λdBecause of its intrinsic failure mode, value depends on λp, can make
For assistant analysis object；
Step 6), abundant failure statistics database:
After crash rate counts, with the batch application of product, fail data is imported in database, is failed each time
Generation, find corresponding failure component, its crash rate handled, λ 'p≤λp+μ；
The μ is that failure increases coefficient, can be determined according to statistical sample；
Step 7) finishes.
The beneficial effects of the present invention are: firstly, passing through the division of electric operator functional block, error code can be passed through
Fault point is quickly found, conducive to the analysis of failure, secondly, the work tentative idea and dangerous crash rate to component are calculated
Analysis, a possibility that can predicting which component failure, are larger, are that the crash rate of intelligent electric actuating mechanism reduces again
A set of theoretical foundation is provided, finally, joined scene using data, this method is allowed more to be bonded actual use operating condition.
Intelligent electric actuating mechanism failure analysis method in the present invention executes primarily to solving intelligent electric
Mechanism is in various environment, failure analysis difficulty and quick the problem of searching fault point, work tentative idea and dangerous crash rate
Calculating, the sample etc. of the statistics of failure mode, operating condition application is of great significance to the realization of this method.
Finally, counting library, the available operational failure for intelligent electric actuating mechanism by abundant failure analysis
Rate, it might even be possible to be directed to varying environment, provide different staqtistical data bases, be intelligent electric actuating mechanism failure analysis,
Fault diagnosis and location provides solid foundation.
Claims (1)
1. a kind of intelligent electric actuating mechanism failure analysis method, which is characterized in that analyzed according to the following steps:
Step 1), statistical work crash rate λp；
λp=λbπQπEπTπS, λbFor the basic failure rate for not considering other factors, πQFor quality coefficient, πEEnvironmental coefficient, πTTemperature
Coefficient, πSStress coefficient；The component inventory for counting all components of intelligent electric actuating mechanism, to each member being applied to
Device carries out work tentative idea λpStatistics；
Step 2) divides invalidation functions block；
Intelligent electric actuating mechanism can provide specific dead code when failing, and can divide electronic execution machine according to dead code
Whether safety-related structure functional block defines the function according to the effect of electric operator functional block, if safety-related, passes through
The height of component failure rate in analytic function block, i.e., predictable failure of removal point；
The electric operator functional block is that electric operator is the hardware circuit integrated package for realizing a certain function, the electricity
Dynamic actuating mechanism function block includes power module circuitry, phase sequence and phase shortage decision circuitry, remote switching operations circuit, local operation
Circuit, analog quantity operation circuit, master chip circuit, sensor Acquisition Circuit, signal feedback circuit, EEPROM storage circuit and boundary
Face display circuit；
Step 3) counts dangerous failure probability λd；
Each component has its failure mode, and different failure modes can generate Safe Failure in the application of specific circuit
It fails with danger, analyzes the failure mode of component in electric operator functional block, calculate dangerous failure probability λd, λd=k
λp, k is dangerous invalid coefficient, is determined according to the failure mode of component；
Step 4), data normalization processing；
Data normalization processing is carried out to work tentative idea, Closer to 1, electric operator is caused to lose
A possibility that effect, is bigger, and to dangerous crash rate, Closer to 1, which causes electronic execution
A possibility that mechanism danger is failed is bigger；
For the work tentative idea after normalized,For the dangerous crash rate after normalized,For all first devices
The minimum value of work tentative idea in part,For the maximum value of work tentative idea in all components,For in all components
The minimum value of dangerous crash rate,For the maximum value of crash rate dangerous in all components；
The reduction of step 5) failure risk；
In order to reduce the crash rate of intelligent electric actuating mechanism, segment processing is carried out to the crash rate after normalization, ifIt is considered as change design, replaces the component；IfThe component is paid close attention to,The probability for illustrating that failing occurs in the component is low；λdBecause of its intrinsic failure mode, value depends on λp, can make
For assistant analysis object；
Step 6), abundant failure statistics database:
After crash rate counts, with the batch application of product, fail data is imported in database, the hair to fail each time
It is raw, corresponding failure component is found, its crash rate is handled, λ 'p≤λp+ μ, μ are that failure increases coefficient, can basis
Statistical sample determines；
Step 7) finishes.
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| CN201910319017.6A CN110032821B (en) | 2019-04-19 | 2019-04-19 | Failure analysis method for intelligent electric actuator |
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| CN201910319017.6A CN110032821B (en) | 2019-04-19 | 2019-04-19 | Failure analysis method for intelligent electric actuator |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117031956A (en) * | 2023-08-23 | 2023-11-10 | 无锡纬途流体科技有限公司 | Control method and system of intelligent embedded electric actuator |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101414165A (en) * | 2008-11-18 | 2009-04-22 | 浙江大学 | Method for designing recycle hydrogen heating furnace gas pressure safe instrument system |
| WO2010017745A1 (en) * | 2008-08-14 | 2010-02-18 | 中兴通讯股份有限公司 | Reliability predicting method of communication device |
| CN106355298A (en) * | 2016-10-13 | 2017-01-25 | 哈尔滨电工仪表研究所 | Intelligent watt-hour meter reliability prediction cloud service platform |
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2010017745A1 (en) * | 2008-08-14 | 2010-02-18 | 中兴通讯股份有限公司 | Reliability predicting method of communication device |
| CN101414165A (en) * | 2008-11-18 | 2009-04-22 | 浙江大学 | Method for designing recycle hydrogen heating furnace gas pressure safe instrument system |
| CN106355298A (en) * | 2016-10-13 | 2017-01-25 | 哈尔滨电工仪表研究所 | Intelligent watt-hour meter reliability prediction cloud service platform |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117031956A (en) * | 2023-08-23 | 2023-11-10 | 无锡纬途流体科技有限公司 | Control method and system of intelligent embedded electric actuator |
| CN117031956B (en) * | 2023-08-23 | 2024-03-19 | 无锡纬途流体科技有限公司 | Control method and system of intelligent embedded electric actuator |
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