CN110058103A - Intelligent transformer fault diagnosis system based on Vxworks platform - Google Patents
Intelligent transformer fault diagnosis system based on Vxworks platform Download PDFInfo
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- CN110058103A CN110058103A CN201910432952.3A CN201910432952A CN110058103A CN 110058103 A CN110058103 A CN 110058103A CN 201910432952 A CN201910432952 A CN 201910432952A CN 110058103 A CN110058103 A CN 110058103A
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- G—PHYSICS
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- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
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- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
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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
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Abstract
The present invention relates to a kind of intelligent transformer fault diagnosis systems based on Vxworks platform, it is characterized by: installing corresponding sensor on different monitoring positions according to the type of transformer, complete the multi pass acquisition to each characteristic quantity of transformer, using the least square method supporting vector machine of ant group optimization, three ratios, optimum binary tree, the resultant fault diagnostic method that reasoning by cases scheduling algorithm combines, improve the accuracy of fault diagnosis, status assessment is carried out using support vector machines clustering algorithm, optimize analytic hierarchy process (AHP) and carries out risk analysis, finally according to fault diagnosis, status assessment, risk analysis result is as input feature vector amount, generate the maintenance decision of optimization, to realize to transformer from fault diagnosis, status assessment, integration of the risk analysis to diagnostic analysis processes such as maintenance decisions, improve the management water to transformer Gentle benefit.The present invention can monitor more transformers simultaneously, support a variety of communication protocols, meet the needs of to Condition Maintenance Method of Transformer.
Description
Technical field
The present invention relates to the technical fields of transformer, are especially related to the online prison of transformer to power grid, substation, booster stations
Survey and fault diagnosis system.
Background technique
Transformer is the core equipment in electric system, but with the increase of electrical network capacity and the transformer station high-voltage side bus time limit, fortune
H in row bad environments, oil2, hydro carbons, CO, CO2, micro-water content rise etc. factors so that the original mechanical performance of transformer itself and
Insulation performance is gradually lost, so that failure rate is at ascendant trend.
Transformer online monitoring device (IED) at present only has data acquisition, transmission, alarm, real-time display and three ratios
Traditional diagnostic methods such as value, David's triangle do not have the diagnostic analysis streams such as status assessment, risk analysis and maintenance suggestion
Journey, diagnostic analysis process are typically all to run on background server, while multi-source heterogeneous data are not merged and being built
The diagnostic characteristic amount of vertical various dimensions, to be greatly reduced the validity of fault diagnosis result, method for diagnosing faults is more single
One, very big inconvenience is brought to operation maintenance personnel；General one change of only monitoring of a current transformer online monitoring device (IED) simultaneously
Depressor, an IED difficult to realize are monitored while being monitored more transformers.Since the operation conditions of transformer is directly related to electric power
The safety and stablization of system, to influence the production and life of people indirectly.Therefore the reliability of transformer station high-voltage side bus how is ensured
With prolong the service life, to improving the utilization rate of transformer, reduce maintenance cost to the overall operation efficiency, quality and peace of enterprise
Full production important in inhibiting.
Summary of the invention
The present invention be directed to not have fault diagnosis, status assessment, risk in current transformer online monitoring device (IED)
Analysis and the integrated diagnostic analysis process of maintenance decision, using function, method for diagnosing faults it is relatively easy, not to multi-source
Isomeric data is merged and is established the problem of various dimensions fault diagnosis characteristic quantity, does not also have a transformer online monitoring
Device (IED) monitors phenomena such as more transformers, proposes a kind of intelligent transformer fault diagnosis system based on Vxworks platform
System.
It is carried out by characteristic quantities such as micro- water oil temperatures in iron core grounding electric current to transformer, oil dissolved gas content, oil real-time
Monitoring acquires the data such as basic data, preventive trial offline, excellent using ant colony by establishing Fault Diagnosis Model for Power Transformer
The comprehensive event that the least square method supporting vector machine of change, three ratios, reasoning by cases and optimal binary decision tree scheduling algorithm combine
Hinder diagnostic method, support vector machines clustering algorithm carries out status assessment, optimization analytic hierarchy process (AHP) carries out risk analysis, last basis
Fault diagnosis, status assessment, risk analysis result are as input feature vector amount, finally according to fault diagnosis, status assessment, risk point
Analyse result as input feature vector amount, generate the maintenance decision of optimization, thus realization to transformer from fault diagnosis, status assessment,
Risk analysis is to the integrated analysis process of maintenance decision.Data are uploaded to using IEC61850 communication protocol by Ethernet
Remote server, user can also be remotely accessed in client by browser, mobile phone A pp or mobile device.
The present invention realizes the intelligent Fault Diagnose Systems based on Vxworks transformer used by the above technical requirements, packet
Include data acquisition module, on-line monitoring module, fault diagnosis module, state estimation module, risk analysis module, maintenance suggestion mould
Block, defect knowledge base module, communication module, control module and WebServer service module.
The data acquisition module includes A/D capture card, current sensor, micro- water sensor, oil temperature temperature sensor.
Wherein A/D capture card is placed on device interior circuit board, current sensor is placed on iron core grounding line, micro- water sensor is placed
In oil return line, oil temperature temperature sensor is placed on the several designated positions of body.
The control module includes Power PC Processor chip, Vxworks image file, flash memory, can interface
Circuit, A/D capture card, Wireless/wired transmission circuit, SD storage card, power circuit all concentrate on one piece of circuit board, with small
The IED device of type maintenance easy to install is presented；The can interface circuit, Wireless/wired transmission circuit are, it can be achieved that IED device passes through
Wired between communication protocol and different sensors, wireless, far and near distance carries out transmission data.
Basic data data are classified as transformer fault diagnosis input feature vector value for the first time, followed by the fault diagnosis module
Transformer Faults Analysis process carries out integrated diagnosing and analyzing to transformer, and the basic data data include: manufacture and factory's examination
Test, transport, installing and equipment safety operation record etc. data.
The integrated diagnosing and analyzing is calculated using least square method supporting vector machine, three ratios and reasoning by cases of ant group optimization etc.
The resultant fault diagnostic mode that method combines, to obtaining different diagnostic results using different diagnostic methods, further according to setting in advance
It sets specific weight values and screening is optimized using optimal binary decision tree, to improve the validity of diagnosis, the fault diagnosis
It as a result include the probability occurred, abort situation, fault type.The defect knowledge base module include fault diagnosis data model,
Status assessment rule and risk probability values, are pre-entered into database.
The state estimation module uses support vector machines clustering algorithm, over time, to different types of
Characteristic value assigns Dynamic Weights, and to improve the validity of status assessment conclusion, status assessment includes operating status assessment score, stops
Electricity condition assessment point, status assessment total score and state grade, different types of characteristic value are respectively real-time oil chromatography prison
Measured data, preventive trial data, electrical test data and basic data.
The risk analysis module assigns probability values using physical fault defect as risk source, to each risk source,
Be entered into database in advance, then using optimization level parser, by screening, obtain risk severity it is maximum first three
Group risk analysis is as a result, risk analysis result includes every group of abort situation, severity, risk priority and risk class.
The maintenance suggestion module, as input feature vector value, is finally obtained using the result after comprehensive diagnosis module diagnosis
Maintenance decision after to optimization: sequence, repair time, the efficiency-cost ratio, maintenance mode at position are overhauled.
The implementation method of intelligent transformer fault diagnosis system based on Vxworks platform, comprising the following steps:
Step 1. is to features such as micro-water content, oil temperatures in the iron core grounding electric current of transformer, Oil Dissolved Gases Concentration, oil
Amount is acquired and is monitored in real time, pre-enters preventive trial data, electrical test data and basic data to database；
Step 2. is using least square method supporting vector machine, three ratios and the reasoning by cases scheduling algorithm of ant group optimization to characteristic quantity
Carry out fault diagnosis；
Step 3. is for difference diagnostic result obtained in the step 2, further according to prior setting specific weight values using most
Excellent binary decision tree optimizes screening, finally obtains effective fault diagnosis conclusion；
Step 4. carries out status assessment using support vector machines clustering algorithm to various features value；
Step 5. carries out risk analysis using optimization analytic hierarchy process (AHP) to various features value；
Step 6. is made for obtaining fault diagnosis conclusion, condition evaluation results and risk analysis result in the step 3-5
For input feature vector amount, with reliability is preferential and the minimum optimization aim of efficiency-cost ratio, the maintenance decision of optimization is ultimately produced；
Step 7. user carries out the real time execution shape of long-range monitoring transformer in client by browser or cell phone application
State, fault diagnosis result, condition evaluation results, risk analysis result and maintenance decision.
The present invention that realizes according to the above technical scheme the beneficial effect is that:
The present invention is based on the intelligent transformer fault diagnosis systems of Vxworks platform, not only using Vxworks operating system
Realize the access to a variety of monitoring feature amounts, and be easy to software upgrading and Function Extension that there is stronger flexibility, intelligence
Property, reliability, and the features such as device shape is small, is easily installed, and has a wide range of application, at low cost, it is right to preferably resolve IED itself
Diagnosis Method of Transformer Faults and the problem relatively simple using function.
The present invention is determined using least square method supporting vector machine, three ratios, reasoning by cases and the optimal y-bend of ant group optimization
The resultant fault diagnostic mode that plan tree scheduling algorithm combines, greatly improves the accuracy of fault diagnosis result.
The present invention carries out status assessment using support vector machines clustering algorithm, optimization analytic hierarchy process (AHP) carries out risk analysis,
Finally finally commented according to fault diagnosis, state according to fault diagnosis, status assessment, risk analysis result as input feature vector amount
Estimate, risk analysis result is as input feature vector amount, generates the maintenance decision of optimization, realize to transformer from fault diagnosis, shape
State assessment, risk analysis to the integrated analysis process of maintenance decision.
The present invention provides embedded Web Server service function, realizes operation maintenance personnel and utilizes remote server, mobile phone
The diversity and convenience that APP or mobile device can access IED, meet long-range management requirement and meet to transformer shape
State maintenance requirement, has broad popularization and application prospect.
Detailed description of the invention
Fig. 1 is that the present invention is based on the structural schematic diagrams of the intelligent Fault Diagnose Systems of Vxworks platform.
Fig. 2 is Transformer Faults Analysis flow chart of the invention.
Specific embodiment
To make the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawing, to the present invention make into
The detailed description of one step, specific embodiment described herein are used only for explaining the embodiment of the present invention, and the limit of non-present invention
It is fixed.It is further to note that only illustrate in order to be beneficial to describe, in attached drawing to the relevant part of the embodiment of the present invention and
Not all structure.
As shown in Figure 1, the intelligent transformer fault diagnosis system based on Vxworks platform, including data acquisition module,
Line monitoring modular, fault diagnosis module, state estimation module, risk analysis module, maintenance suggestion module, defect knowledge base mould
Block, communication module, control module and WebServer service module.
The data acquisition module includes A/D capture card, current sensor, micro- water sensor, oil temperature temperature sensor,
Middle A/D capture card is placed on device interior circuit board, current sensor is placed on iron core grounding line, micro- water sensor is placed on
In oil return line, oil temperature temperature sensor is placed on the several positions of body.
The output end of each sensor is connected by RS485 or serial ports, for the processing and transmission to acquisition characteristics value.Oil
Middle dissolved gas is acquired by A/D capture card, Vxworks image file is first produced, then in advance by various transformers
Essential information, fault diagnosis model, status assessment rule and risk probability values etc., are pre-entered into database, SD
The characteristic value and diagnostic result of the transformer of card memory storage acquisition.
As shown in Fig. 2, Transformer Faults Analysis flow chart of the invention, adopt in real time or offline to various features value
Collection, various oil dissolved gas, steel core current, Wei Shui, temperature when can check transformer station high-voltage side bus by Web browser and
Warning information.Historical data, spectrogram waveform diagram, cube graph, TD figure, diagnostic result and the maintenance that may browse through transformer are determined
Plan etc..
Further, fault diagnosis is carried out to various features value, using the least square method supporting vector machine of ant group optimization, three
Ratio, optimal binary decision tree and reasoning by cases scheduling algorithm carry out fault diagnosis to characteristic quantity respectively.
Further, for above-mentioned acquired different diagnostic result, further according in advance to the specific weight values of different settings
Screening is optimized to diagnostic result using optimal Binary decision tree algorithm, finally obtains effective fault diagnosis conclusion.
Further, variety classes characteristic value is calculated in advance to the Dynamic Weights of different settings using support vector clustering
Method carries out status assessment, and status assessment includes: electrification assessment score, the assessment score that has a power failure, assessment total score, state grade, shape
State ranking score are as follows: excellent, good qualified, attention, five grades.
By using optimization analytic hierarchy process (AHP) to transformer risk analysis, comprising: trouble location, risk priority index, wind
Dangerous probability, risk probability are divided into: extremely low risk, low-risk, risk, high risk.
Further, above-mentioned variety classes feature, comprising: oil dissolved gas (H2, C2h4, C2H2, C2H4, C2H6,
CO, CO2, total hydrocarbon etc.), preventive trial data, electrical test data and basic data wait, it is over time, right
Variety classes characteristic value uses Dynamic Weights in fault diagnosis, to improve the accuracy of fault diagnosis.
Further, risk analysis is carried out using optimization analytic hierarchy process (AHP) to various features value, by screening, obtains risk
The maximum first three groups risk analysis of severity is as a result, risk analysis result includes every group of abort situation, severity, risk
Priority, risk probability and risk class, risk probability are divided into: extremely low risk, low-risk, risk, high risk.
Further, using fault diagnosis result obtained above, status assessment and risk analysis as input feature vector value, with
Reliability is preferential and the minimum optimization aim of efficiency-cost ratio, ultimately produces the maintenance decision of optimization.
Further, to above-mentioned fault diagnosis result, status assessment, risk analysis and maintenance decision add their confirmation whether into
Row storage, preferably to make fault diagnosis model, status assessment rule have adaptive and self-teaching ability, Yi Jijian
Found reliable defect knowledge data base.
When breaking down for transformer, the alarm setting of Web page will provide alarm prompt, and operation maintenance personnel is combinable
Diagnosis report and maintenance decision take corresponding measure to failure in time.
According to practical engineering application, by Ethernet/local area network, using IEC61850/I2 communication protocol characteristic value or
Diagnostic result is uploaded to remote server.
Embodiments described above is only used for being illustrated the technical solution that the present invention describes, and limits it not as only
One embodiment.For it will be appreciated by those skilled in the art that simultaneously still can be to the specific embodiment party of invention
Formula improves or equivalent replacement, these modifications or equivalent replacement also should be regarded as in scope of the presently claimed invention.
Claims (9)
1. the intelligent Fault Diagnose Systems of the transformer based on Vxworks platform, it is characterised in that: including data acquisition module,
Control module, fault diagnosis module, state estimation module, risk analysis module, maintenance suggestion module, defect knowledge base module,
Monitor module, communication module and WebServer service module on-line；
The data acquisition module includes A/D capture card, current sensor, micro- water sensor, oil temperature temperature sensor, wherein A/
D capture card is placed on device interior circuit board, current sensor is placed on iron core grounding line, micro- water sensor is placed on oil and returns
Lu Zhong, oil temperature temperature sensor are placed on the several designated positions of body；
The control module includes Power PC Processor chip, Vxworks image file, flash memory, can interface electricity
Road, A/D capture card, Wireless/wired transmission circuit, SD storage card, power circuit all concentrate on one piece of circuit board, with small-sized
The IED device of maintenance easy to install is presented；The can interface circuit, Wireless/wired transmission circuit, it can be achieved that IED device pass through it is logical
Wired, wireless, far and near distance carries out transmission data between letter specification and different sensors；
Basic data data are classified as transformer fault diagnosis input feature vector value for the first time, follow transformation by the fault diagnosis module
Device accident analysis process carries out integrated diagnosing and analyzing to transformer；
The state estimation module uses support vector machines clustering algorithm, over time, to different types of feature
Value assigns Dynamic Weights, and to improve the validity of status assessment conclusion, status assessment includes operating status assessment score, power failure shape
State assessment point, status assessment total score and state grade；
The risk analysis module assigns probability values using physical fault defect as risk source, to each risk source, in advance
It is entered into database, the maximum first three groups wind of risk severity is then obtained by screening using optimization level parser
Danger analysis result.
2. the intelligent transformer fault diagnosis system according to claim 1 based on Vxworks platform, it is characterised in that:
The basic data data include: the data such as manufacture and shop test, transport, installation and equipment safety operation record.
3. the intelligent transformer fault diagnosis system according to claim 1 based on Vxworks platform, it is characterised in that:
The integrated diagnosing and analyzing is combined using least square method supporting vector machine, three ratios and the reasoning by cases scheduling algorithm of ant group optimization
Resultant fault diagnostic mode, it is special further according to prior setting to obtaining different fault diagnosis results using different diagnostic methods
Determine weight and screening is optimized using optimal binary decision tree, to improve the validity of diagnosis.
4. the intelligent transformer fault diagnosis system according to claim 3 based on Vxworks platform, it is characterised in that:
The fault diagnosis result includes the probability occurred, abort situation, fault type.
5. the intelligent transformer fault diagnosis system according to claim 1 based on Vxworks platform, it is characterised in that:
The defect knowledge base module include fault diagnosis data model, status assessment rule and risk probability values, in advance it is defeated
Enter into database.
6. the intelligent transformer fault diagnosis system according to claim 1 based on Vxworks platform, it is characterised in that:
Different types of characteristic value be respectively real-time oil chromatography monitoring data, preventive trial data, electrical test data and
Basic data.
7. the intelligent transformer fault diagnosis system according to claim 1 based on Vxworks platform, it is characterised in that:
The risk analysis result includes every group of abort situation, severity, risk priority and risk class.
8. the intelligent transformer fault diagnosis system according to claim 1 based on Vxworks platform, it is characterised in that institute
Maintenance suggestion module is stated using the result after comprehensive diagnosis module diagnosis as input feature vector value, is examined after finally obtaining optimization
It repairs decision: overhauling sequence, repair time, the efficiency-cost ratio, maintenance mode at position.
9. a kind of intelligent transformer method for diagnosing faults based on Vxworks platform is constructed as described in one of claim 1 to 8
The intelligent transformer fault diagnosis system based on Vxworks platform, which comprises the following steps:
Step 1, the iron core grounding electric current to transformer, Oil Dissolved Gases Concentration, in oil the characteristic quantities such as micro-water content, oil temperature into
Row acquisition in real time and monitoring, pre-enter preventive trial data, electrical test data and basic data to database；
Step 2 carries out characteristic quantity using the least square method supporting vector machine, three ratios and reasoning by cases scheduling algorithm of ant group optimization
Fault diagnosis；
Step 3, for difference diagnostic result obtained in the step 2, use optimal two further according to prior setting specific weight values
Fork decision tree optimizes screening, finally obtains effective fault diagnosis conclusion；
Step 4 carries out status assessment using support vector machines clustering algorithm to various features value；
Step 5 carries out risk analysis using optimization analytic hierarchy process (AHP) to various features value；
Step 6, for obtaining fault diagnosis conclusion, condition evaluation results and risk analysis result in the step 3-5 as defeated
Enter characteristic quantity, with reliability is preferential and the minimum optimization aim of efficiency-cost ratio, ultimately produces the maintenance decision of optimization；
Step 7, user carry out real-time running state, the event of long-range monitoring transformer in client by browser or cell phone application
Hinder diagnostic result, condition evaluation results, risk analysis result and maintenance decision.
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| CN110609198A (en) * | 2019-09-11 | 2019-12-24 | 广东电网有限责任公司 | Operation and maintenance monitoring method for cable line and related equipment |
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| CN111175651A (en) * | 2020-01-10 | 2020-05-19 | 河北大学 | Big data-based wind turbine generator fault early warning and diagnosis system |
| CN111487562A (en) * | 2020-04-15 | 2020-08-04 | 国网江苏省电力有限公司 | Early warning and decision-making assisting method for power transformer state |
| CN113379313A (en) * | 2021-07-02 | 2021-09-10 | 贵州电网有限责任公司 | Intelligent preventive test operation management and control system |
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| CN117993894A (en) * | 2024-04-03 | 2024-05-07 | 四川航天职业技术学院(四川航天高级技工学校) | Rail transit operation and maintenance state data processing method and system based on artificial intelligence |
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| CN113379313B (en) * | 2021-07-02 | 2023-06-20 | 贵州电网有限责任公司 | Intelligent preventive test operation management and control system |
| CN116245357A (en) * | 2023-01-31 | 2023-06-09 | 南京工大金泓能源科技有限公司 | Fault diagnosis method and system for intelligent energy-saving cabinet |
| CN116245357B (en) * | 2023-01-31 | 2023-09-22 | 南京工大金泓能源科技有限公司 | Fault diagnosis method and system for intelligent energy-saving cabinet |
| CN117993894A (en) * | 2024-04-03 | 2024-05-07 | 四川航天职业技术学院(四川航天高级技工学校) | Rail transit operation and maintenance state data processing method and system based on artificial intelligence |
| CN118228089A (en) * | 2024-05-23 | 2024-06-21 | 国网安徽省电力有限公司经济技术研究院 | Improved fault diagnosis method for dissolved gas in transformer oil |
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