CN106093613A - Pump-storage generator equipment dependability analysis platform and method thereof - Google Patents
Pump-storage generator equipment dependability analysis platform and method thereof Download PDFInfo
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- CN106093613A CN106093613A CN201610357596.XA CN201610357596A CN106093613A CN 106093613 A CN106093613 A CN 106093613A CN 201610357596 A CN201610357596 A CN 201610357596A CN 106093613 A CN106093613 A CN 106093613A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/003—Environmental or reliability tests
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- G—PHYSICS
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Abstract
The present invention relates to pump-storage generator equipment dependability analysis platform, including reliability testing platform and Comprehensive Analysis of Reliability platform；Described reliability testing platform includes multiple component test device and the total interface of system being connected with described multiple component test device, and described reliability testing platform can test every fundamental performance parameter of component；Comprehensive Analysis of Reliability platform includes reliability distribution function, parameter estimation algorithm, the fault sample data of component to be measured are obtained by described reliability testing platform test, determine the reliability distribution function that component to be measured is met, import component fault statistics data to be measured, draw Reliable Mathematics model and the distribution curve of component to be measured through parameter estimation algorithm.Analysis platform is powerful, friendly interface, easy and simple to handle, it is easy to promote the use of in technical staff.
Description
Technical field
The present invention relates to equipment dependability and evaluate field, particularly relate to a kind of pump-storage generator equipment dependability analysis and put down
Platform and method thereof.
Background technology
Along with the automatization level of social production, economic activity improves constantly, the mankind are to Operation of Electric Systems reliability
Require the highest, and the basis of whole electric power business activities safe and stable operation is that " safety can for Electric Power Generating Equipment
By running ".It is the most complicated that current power produces equipment, and more and more expensive, power management techniques personnel are to equipment dependability
Require and wish the highest.And at present Electric Power Generating Equipment reliability can be tested, analyzes and assessed in industry
Comprehensive platform the rarest, the research to the Method and kit for of equipment dependability test analysis lacks the most very much.
Specific to Pumped Storage Plant, carry the vital task of peak load regulation network, frequency modulation, phase modulation, it is ensured that it is safe and reliable
Run self-evident to the effect of grid stability.Owing to pump-storage generator operating mode is many, start and stop frequency, major-minor device action frequency
Numerous, running status often changes, and therefore the life cycle of equipment components is shorter compared to conventional power plant, reliable to equipment
Property test, analyze and seem even more important with the necessity assessed.
For a long time, the technical staff of each power generation unit biography to Pumped Storage Plant part of appliance reliability assessment
System method is by making regular check on, and during by making regular check on, the state of equipment judges the reliability of equipment a period of time in future.
Pumped Storage Plant part of appliance convectional reliability appraisal procedure is existed by the technical staff of each power generation unit
Following subject matter:
1, there is randomness in Probability meaning in checking regularly at of part of appliance, owing to part of appliance is frequent movement
Wearing detail, even if this passed examination, can not prove that future is the most qualified.
2, insecure part of appliance typically can pass through twice test, but cannot stand the inspection of tens of up to a hundred times,
And manually to carry out the task that hundreds and thousands of tests have been practically impossible to.
3, traditional method seldom has and combines Reliable Mathematics theory and carry out the assessment of part of appliance state.
4, have been used up the most artificial mode relay is verified.In the face of comprising the electrical control of a large amount of relay
The regular inspection work of system, the intensity of technical staff's not only duplication of labour compared with big, verification efficiency is low, easily cause fatigue, and sentence
Whether disconnected verification data meet technology requirement, are mainly determined by verification personnel, subjective, are unfavorable for the mark of equipment
Standardization is safeguarded.
5, verification Work tool is the most backward, needs artificial shorting stub by outside AC DC electric source current during due to verification
It is overlapped on the coil-end of relay, therefore there is technical staff and the potential safety hazard of Danger Electric shock risk occurs during verifying.
6, tradition verification mode also can only measure the part electrical quantity of relay, such as coil resistance, normally opened contact resistance,
Normally-closed contact resistance.And cannot measure for important relay parameters such as pick-up voltage, release voltage, movement times.
7, verification data the most effectively preserve and sort out.During all previous big light maintenance, the regular inspection data one of relay
As only isolated be saved in papery regular inspection file, do not set up independent data base, by effective for the regular inspection data of relay
Sort out and preserve.So will be unfavorable for from relay regular inspection historical data finding objective law, it is judged that relevant secondary device
Health status and potential risk, work for the repair based on condition of component of unit equipment and decision support be provided, thus avoid power system control
System and protection equipment are in operation because the various exceptions that cause of the problem of relay and fault.
In such a case it is necessary to consider that developing corresponding test platform is carried out the visual plant parts of Pumped Storage Plant
Reliability testing, analyze and assess.
Summary of the invention
In view of this, it is necessary to at least one above-mentioned problem, a kind of pump-storage generator equipment is on the one hand provided
Fail-safe analysis platform, including reliability testing platform and Comprehensive Analysis of Reliability platform；
(1) the reliability testing platform described in includes multiple component test device and fills with the test of described multiple component
Putting the total interface of system of connection, described reliability testing platform can test every fundamental performance parameter of component；Described
Reliability testing platform receives demand order and orders reading as requested through the described total interface of system, the total interface of described system
Take the test data in the described test device of correspondence and preserve, then being transmitted data to by the total interface of system described reliable
The comprehensive analysis platform of property；
(2) the Comprehensive Analysis of Reliability platform described in includes reliability distribution function, parameter estimation algorithm, by described
Reliability testing platform test obtains the fault sample data of component to be measured, determines that the reliability that component to be measured is met is divided
Cloth function, imports component fault statistics data to be measured, draws the Reliable Mathematics of component to be measured through parameter estimation algorithm
Model and distribution curve.
Wherein, described Comprehensive Analysis of Reliability platform also includes specialist system, and inputting the expectation to component to be measured can
After degree, specialist system calculates the time that under this reliability, component to be measured can work continuously automatically, and provides maintenance strategy
And change suggestion.
Wherein, described component test device includes relay test-device, spring fatigue test device, electronics unit device
Part ageing tester, can test every electric parameter of each component, palikinesia test, testing fatigue.
Wherein, described fault sample data can be obtained by test data, and test data is to be put down by reliability testing
Platform carries out life test or repeats fatigability test and obtain component to be measured.Can also be obtained by field data, described
Field data be component to be measured fault statistics data of user record in actual moving process.
Wherein, described reliability distribution function includes exponential type distribution, normal distribution, logarithm normal distribution, Wei Bu
You are distributed (two-parameter, three parameters).Described parameter estimation algorithm includes least-squares estimation (LSE), Maximum-likelihood estimation
(MLE), Best Linear Unbiased Estimate (BLUE), Simple correlation (GLUE), interval estimation.
Another aspect of the present invention provides a kind of pump-storage generator equipment dependability to analyze method, comprises the following steps:
(1) every fundamental performance parameter of component to be measured is tested；
(2) the fault sample data of component to be measured are obtained by the fatigability test of many groups or palikinesia test；
(3) reliability distribution function that component to be measured is met is determined；
(4) fault statistics data of component to be measured is read in；
(5) parameter estimation algorithm is utilized to calculate reliability distribution function character parameter undetermined；
(6) Reliable Mathematics model and the distribution curve of component to be measured are obtained.
Wherein, it is also possible to include expert system analysis, after input is to the expectation reliability of component to be measured, specialist system is certainly
The time that under the described reliability of dynamic calculating, component to be measured can work continuously, and provide maintenance strategy and change suggestion.
Beneficial effects of the present invention:
1, initiative of the present invention designs a set of pump-storage generator equipment dependability comprehensive test analysis platform, including can
By property test platform and Comprehensive Analysis of Reliability platform, possess component parameter performance test and equipment dependability analysis and evaluation
Deng several functions, the most responsible reliability testing platform and Comprehensive Analysis of Reliability platform two parts are with the use of testing portion of unit
The Reliable Mathematics model of part and distribution curve, can independently make again the every fundamental performance parameter for testing component to be measured.
2, pump-storage generator equipment dependability comprehensive test analysis platform is that the intelligent test integrating soft and hardware divides
Analysis system, it is powerful, possesses the several functions such as component parameter performance test and equipment dependability analysis and evaluation.It is applicable to
The multiple application such as equipment regular inspection, equipment state evaluation, analysis equipment life, equipment dependability assessment in power industry production process
Demand.
3, reliability testing platform can be used to test every fundamental performance parameter of component, with relay contact analog control system therein
As a example by device, both can carry out relay palikinesia test test the life-span, again can to every characterisitic parameter of electromagnetic relay,
Facts have proved this equipment safety, easy-to-use, efficient, general, have very broad application prospects.
4, Comprehensive Analysis of Reliability platform carries Various Components library model and parameter estimation algorithm, can be applicable to major part electricity
Power produces fail-safe analysis and the assessment of equipment, the most complicated in Electric Power Generating Equipment, and more and more expensive, equipment dependability is wanted
Seeking the highest society, its application prospect is quite varied.
5, the built-in specialist system of platform, it is possible to according to user's request, automatically assess the optimum useful life of component to be measured,
And provide maintenance suggestion, it is the supervisory engineering staff good assistants that formulate equipment maintenance and management strategy.
6, pump-storage generator equipment dependability comprehensive test analysis platform feature is powerful, and friendly interface is easy and simple to handle, easily
In promoting the use of in technical staff.
Accompanying drawing explanation
Fig. 1 pump-storage generator equipment dependability analysis platform overall structure schematic diagram
Fig. 2 reliability testing platform topology structure chart
Fig. 3 Comprehensive Analysis of Reliability platform process figure
Detailed description of the invention
The present invention is described in detail below in conjunction with the accompanying drawings.
Fig. 1 is the pump-storage generator equipment dependability analysis platform 100 based on fault statistics data according to the present invention
Structural representation, platform use Distributed Design, including 2 parts: reliability testing platform 101 and Comprehensive Analysis of Reliability
Platform 102；Owing to using Distributed Design scheme, greatly reduce the coupling between platform two parts, improve two parts
Independence, both can be with the use of by property test platform 101 and Comprehensive Analysis of Reliability platform 102, can be independently operated, again because of
The motility that this pump-storage generator equipment dependability analysis platform 100 uses is the strongest.
It is made up of the multiple total interface of test Apparatus and system 215 by property test platform 101, as in figure 2 it is shown, test device bag
Include relay test-device 211, spring fatigue test device 212, electronic component ageing tester 213 and other test device
214。
One of effect by property test platform 101 is the every fundamental performance parameter that can be used to test component, with wherein
Relay test-device 211 as a example by.Both can carry out relay palikinesia test and test the life-span, again can be to electromagnetic relay
Every characterisitic parameter (coil resistance, contact resistance, adhesive/release voltage, adhesive/release time, adhesive rebound, be released back into
Jump) automatically detect, and reach at a relatively high measuring accuracy.
Another effect by property test platform 101 is to be measured with the use of testing with Comprehensive Analysis of Reliability platform 102
The Reliable Mathematics model of component and distribution curve.Under this purposes, it is used for component to be measured is carried out by property test platform 101
Palikinesia is tested, until the stopping the most up to standard of component performance.The fault of component to be measured is obtained by many group fatigability tests
Sample data.
Comprehensive Analysis of Reliability platform 102 is the core of pump-storage generator equipment dependability analysis platform, obtains to be measured
After equipment component fault sample data, can easily this component be carried out by this Comprehensive Analysis of Reliability platform 102
Quickly accurate reliability prediction, and provide the maintenance suggestion of this component.
As it is shown in figure 1, pump-storage generator equipment dependability analysis platform based on fault statistics data includes reliability
Test platform 101 and Comprehensive Analysis of Reliability platform 102, the data transmission between them is two-way real-time.Reliability Synthesis
Analysis platform 102 sends demand data order by the total interface of system 215 and puts down to reliability testing platform 101, reliability testing
The test data of oneself are sent back to Comprehensive Analysis of Reliability platform 102 after receiving demand order by platform 101.
Specifically, such as Fig. 2, the demand order that reliability testing platform 101 receives first passes around the total interface of built-in system
215, total interface reads the test data in internal corresponding test device (such as relay test-device 211) as requested and protects
Leave, then by the total interface of system 215, data are sent.
Comprehensive Analysis of Reliability platform 102, according to the kind of component to be measured, determines that its reliability met is distributed letter
Number type.By importing component fault statistics data to be measured, estimate that parser draws to be measured through built-in many kinds of parameters
The Reliable Mathematics model of equipment and distribution curve.After user's input is to the expectation reliability of equipment, just can automatically calculate this can
By the time that can work continuously of the lower equipment of degree, and provide maintenance strategy and change suggestion, specifically including following steps:
321, obtain test data or field data；The basis of pump-storage generator equipment dependability analysis and assessment is
Fault sample data, the accuracy of fault sample data directly affects the accuracy of fail-safe analysis, therefore fault sample number
According to source particularly significant.The fault sample data of this analysis platform are mainly obtained by test data or field data.Examination
Test data by reliability testing platform, component to be measured to be carried out life test or repetition fatigability test and obtain；On-the-spot
Data are component to be measured fault statistics data of user record in actual moving process.User can be very by this platform
Easily fault sample data are read in platform, provide data basis for carrying out equipment dependability analysis and evaluation.
322, device type selects, and determines the reliability distribution function that component to be measured is met；Difference in power equipment
The component of kind, its reliability distribution function met is not quite similar.Such as relay, catalyst, motor etc.
Meet Weibull distribution, the distribution of the index of coincidence such as switch, chopper, and the mechanical parts such as spring, gear meets normal distribution.
The reliability distribution function of the present invention includes the reliable of the components such as relay, catalyst, spring, electronic component
Property function, user only need to choose correspondence test component, just can automatically generate the mathematical model of these parts.When component to be measured
When not having the device needed for user in storehouse, user by newly-increased device, and can also specify reliability distribution for newly-increased device
Mathematical model, including exponential type distribution, normal distribution, logarithm normal distribution, Weibull distribution (two-parameter, three parameters) etc..
Example: as a example by the Weibull distribution meeting relay reliability mathematical model, its failure distribution function F (t) is:
Failure density function f (t) is:
Reliability Function R (t) is:
Q-percentile life trFor:
tr=η (-lnR)1/β (4)
Failure rate estimation λ (t) is:
In formula: η represents scale parameter；β represents form parameter, refers to failure mode.
323, parameter estimation algorithm selects, after component reliability model to be measured determines, by reading in fault data sample,
Use the form parameter undetermined in series of parameters algorithm for estimating computational mathematics model, so that it is determined that meet the true of component to be measured
Real reliability distribution function.Parameter estimation algorithm includes: least-squares estimation (LSE), Maximum-likelihood estimation (MLE), optimal line
Property unbiased esti-mator (BLUE), Simple correlation (GLUE), interval estimation etc., user only need to choose the parameter estimation of correspondence
Algorithm, will use this algorithm to calculate form parameter undetermined automatically.
Example: calculating process is described as a example by the least-squares estimation carrying Weibull distribution.
By the deformation of formula (3) left and right, taking twice logarithm continuously can obtain:
Ln [-lnR (t) [=β lnt-β ln η (6)
Order:
X=lnt, y=ln [-lnR (t)]
A=β, B=-β ln η
Then formula (6) can turn to:
Y=AX+B (7)
For equation of linear regression (7), the least square solution of regression coefficient A and B is as follows:
In formula:
When using method of least square to carry out parameter estimation, in order to obtain optimal regression straight line, it is important to raising experience is divided
The precision of cloth function, traditional experience branch function computational methods are to be obtained by approximation Median rank formula formula (9).
In formula: i is the serial number of faulty equipment；N is the total capacity of sample.
Mean rank order computing formula such as (10)～(13).
Ak=Ak-1+ΔAk (11)
R(tk)=1-F (tk) (13)
In formula: Ak is the mean rank order of fault sample；K is the serial number of fault sample；Ak-1 is previous fault sample
Mean rank order；△ Ak is mean rank order increment；I is that all samples is by the order arrangement number of action frequency before fault；Tk is i-th
Action frequency before the fault of individual sample.In the case of known to fault data sample, available formula (10)～(13) calculate one group
Dependability of experience index, then utilizes least square fitting regression straight line, determine Weibull distribution model scale parameter η and
Form parameter β.
324, parametric solution；
325, distribution curve is mapped；Obtain the distribution curve figure of component to be measured；
326, mathematical model result shows, it is thus achieved that Reliable Mathematics models show.
327, it is desirable to value input, after trying to achieve component reliable life function to be measured, user can input component expectation
Reliability；
328, plant maintenance is advised, can automatically calculate its service life and suggestion maintenance period according to built-in specialist system,
The operation maintenance strategy formulating equipment for power station technology personnel provides reference.
Pump-storage generator equipment dependability analysis platform is simple to operate, can one key test component to be measured every spy
Property parameter；Comprehensive Analysis of Reliability platform interface is friendly, it is only necessary to shirtsleeve operation, analysis result just can be the most directly perceived
Output.
Embodiment described above only have expressed the several embodiments of the present invention, and it describes more concrete and detailed, but also
Therefore the restriction to the scope of the claims of the present invention can not be interpreted as.It should be pointed out that, for those of ordinary skill in the art
For, without departing from the inventive concept of the premise, it is also possible to make some deformation and improvement, these broadly fall into the guarantor of the present invention
Protect scope.Therefore, the protection domain of patent of the present invention should be as the criterion with claims.
Claims (10)
1. a pump-storage generator equipment dependability analysis platform, it is characterised in that include reliability testing platform and reliable
The comprehensive analysis platform of property；
(1) the reliability testing platform described in includes multiple component test device and connects with described multiple component test device
The total interface of system connect, described reliability testing platform can test every fundamental performance parameter of component；Described is reliable
Property test platform receive demand order through the described total interface of system, the total interface of described system orders reading right as requested
Test data in the described test device answered also preserve, then transmit data to described reliability by the total interface of system and combine
Close analysis platform；
(2) the Comprehensive Analysis of Reliability platform described in includes reliability distribution function, parameter estimation algorithm, by described reliable
Property test platform test obtain the fault sample data of component to be measured, determine the reliability distribution letter that component to be measured met
Number, imports component fault statistics data to be measured, draws the Reliable Mathematics model of component to be measured through parameter estimation algorithm
And distribution curve.
Fail-safe analysis platform the most according to claim 1, it is characterised in that described Comprehensive Analysis of Reliability platform is also
Including specialist system, after input is to the expectation reliability of component to be measured, specialist system calculates unit to be measured under this reliability automatically
The time that parts can work continuously, and provide maintenance strategy and change suggestion.
Fail-safe analysis platform the most according to claim 1, it is characterised in that described component test device includes continuing
Electric test device, spring fatigue test device, electronic devices and components ageing tester, can test every electricity of each component
Gas parameter, palikinesia test, testing fatigue.
Fail-safe analysis platform the most according to claim 1, it is characterised in that described fault sample data are by test
Data obtain, test data be by reliability testing platform, component to be measured carried out life test or repeat fatigability test and
Obtain.
Fail-safe analysis platform the most according to claim 1, it is characterised in that described fault sample data can also be led to
Crossing field data to obtain, described field data is component to be measured fault statistics number of user record in actual moving process
According to.
Fail-safe analysis platform the most according to claim 1, it is characterised in that described reliability distribution function includes referring to
Number type distribution, normal distribution, logarithm normal distribution, Weibull distribution.
Fail-safe analysis platform the most according to claim 6, it is characterised in that described Weibull distribution includes Radix Triplostegiae Grandiflorae
Number, three parameters.
Fail-safe analysis platform the most according to claim 1, it is characterised in that described parameter estimation algorithm includes minimum
Two take advantage of estimation (LSE), Maximum-likelihood estimation (MLE), Best Linear Unbiased Estimate (BLUE), Simple correlation
(GLUE), interval estimation.
9. a pump-storage generator equipment dependability analyzes method, it is characterised in that comprise the following steps:
(1) every fundamental performance parameter of component to be measured is tested；
(2) the fault sample data of component to be measured are obtained by the fatigability test of many groups or palikinesia test；
(3) reliability distribution function that component to be measured is met is determined；
(4) fault statistics data of component to be measured is read in；
(5) parameter estimation algorithm is utilized to calculate reliability distribution function character parameter undetermined；
(6) Reliable Mathematics model and the distribution curve of component to be measured are obtained.
Analysis method for reliability the most according to claim 9, it is characterised in that also include expert system analysis, it is right to input
After the expectation reliability of component to be measured, specialist system calculates what component to be measured under described reliability can work continuously automatically
Time, and provide maintenance strategy and change suggestion.
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| CN107733366A (en) * | 2017-11-08 | 2018-02-23 | 河海大学常州校区 | Photovoltaic module Failure Assessment and its Forecasting Methodology based on accelerated test case |
| CN108828648A (en) * | 2018-06-21 | 2018-11-16 | 山东新华医疗器械股份有限公司 | A kind of reliability test device and method of electron linear accelerator target assembly |
| CN109299846A (en) * | 2018-07-20 | 2019-02-01 | 岭东核电有限公司 | A kind of nuclear power plant equipment analysis method for reliability, system and terminal device |
| CN115795999A (en) * | 2022-10-26 | 2023-03-14 | 国网新源控股有限公司 | Performance abnormity early warning method for long-term service pumped storage unit |
| CN117634932A (en) * | 2024-01-25 | 2024-03-01 | 深圳市微克科技股份有限公司 | Management system of platform for production test of intelligent watch |
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| CN107733366A (en) * | 2017-11-08 | 2018-02-23 | 河海大学常州校区 | Photovoltaic module Failure Assessment and its Forecasting Methodology based on accelerated test case |
| CN108828648A (en) * | 2018-06-21 | 2018-11-16 | 山东新华医疗器械股份有限公司 | A kind of reliability test device and method of electron linear accelerator target assembly |
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| CN115795999B (en) * | 2022-10-26 | 2023-08-01 | 国网新源控股有限公司 | Early warning method for abnormal performance of long-term service pumped storage unit |
| CN117634932A (en) * | 2024-01-25 | 2024-03-01 | 深圳市微克科技股份有限公司 | Management system of platform for production test of intelligent watch |
| CN117634932B (en) * | 2024-01-25 | 2024-04-30 | 深圳市微克科技股份有限公司 | Management system of platform for production test of intelligent watch |
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Application publication date: 20161109 |