CN116359652A - State monitoring system for power equipment - Google Patents
State monitoring system for power equipment Download PDFInfo
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- CN116359652A CN116359652A CN202310393404.0A CN202310393404A CN116359652A CN 116359652 A CN116359652 A CN 116359652A CN 202310393404 A CN202310393404 A CN 202310393404A CN 116359652 A CN116359652 A CN 116359652A
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 169
- 230000002159 abnormal effect Effects 0.000 claims abstract description 33
- 238000007689 inspection Methods 0.000 claims abstract description 12
- 238000000034 method Methods 0.000 claims description 14
- 238000010586 diagram Methods 0.000 claims description 12
- 239000013598 vector Substances 0.000 claims description 10
- 238000004364 calculation method Methods 0.000 claims description 9
- 238000005457 optimization Methods 0.000 claims description 9
- 238000012216 screening Methods 0.000 claims description 6
- 230000005540 biological transmission Effects 0.000 abstract description 10
- 238000012549 training Methods 0.000 description 12
- 238000006243 chemical reaction Methods 0.000 description 5
- 230000005856 abnormality Effects 0.000 description 3
- 238000010248 power generation Methods 0.000 description 3
- 238000011835 investigation Methods 0.000 description 2
- 238000013528 artificial neural network Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000003111 delayed effect Effects 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000012806 monitoring device Methods 0.000 description 1
- 230000001502 supplementing effect Effects 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/243—Classification techniques relating to the number of classes
- G06F18/2433—Single-class perspective, e.g. one-against-all classification; Novelty detection; Outlier detection
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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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- 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
- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/088—Aspects of digital computing
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00002—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by monitoring
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
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- General Engineering & Computer Science (AREA)
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- Life Sciences & Earth Sciences (AREA)
- Power Engineering (AREA)
- Mathematical Physics (AREA)
- Remote Monitoring And Control Of Power-Distribution Networks (AREA)
Abstract
The invention discloses a state monitoring system for power equipment, which belongs to the technical field of power equipment monitoring and comprises an analysis module and a monitoring module; the analysis module is used for analyzing an outdoor power line network, distributing corresponding monitoring points and monitoring equipment corresponding to the monitoring points, and acquiring real-time data through the distributed monitoring equipment to obtain monitoring data corresponding to the monitoring points; the monitoring module is used for analyzing the monitoring data of each monitoring point, identifying abnormal data in the monitoring data, analyzing a corresponding abnormal value set, evaluating problem values corresponding to each line based on the obtained abnormal value set, and carrying out inspection according to the obtained problem values of each line; through mutually supporting between analysis module and the monitoring module, realize the real-time supervision to transmission line, utilize various monitoring parameters to carry out the state monitoring, solve the current mode that adopts artifical inspection to carry out inspection monitoring's problem, improve monitoring efficiency and timeliness.
Description
Technical Field
The invention belongs to the technical field of power equipment monitoring, and particularly relates to a state monitoring system for power equipment.
Background
The power equipment mainly comprises two major types of power generation equipment and power supply equipment, wherein the power generation equipment mainly comprises a power station boiler, a steam turbine, a gas turbine, a water turbine, a generator, a transformer and the like, and the power supply equipment mainly comprises power transmission lines, transformers, contactors and the like with various voltage levels; the state monitoring of the power generation equipment is provided with a relatively perfect monitoring system, and various state monitoring systems are also more applied; however, the monitoring of power supply equipment is rare, especially the state monitoring of a power transmission line and the like, and the state monitoring of the current power transmission line is extremely delayed due to the outdoor complex characteristics of the power transmission line, so that the state monitoring system for the power equipment is provided for realizing the real-time monitoring of the state of the power transmission line.
Disclosure of Invention
In order to solve the problems of the above solutions, the present invention provides a condition monitoring system for an electrical device.
The aim of the invention can be achieved by the following technical scheme:
a condition monitoring system for an electrical device, comprising an analysis module and a monitoring module;
the analysis module is used for analyzing an outdoor power line network, distributing corresponding monitoring points and monitoring equipment corresponding to the monitoring points, and acquiring real-time data through the distributed monitoring equipment to obtain monitoring data corresponding to the monitoring points.
Further, the process of setting the monitoring point includes:
obtaining a circuit diagram, analyzing each corresponding point to be selected in the circuit diagram, determining a plurality of point to be selected combinations based on the point to be selected and the circuit diagram, screening the point to be selected combinations, determining a target combination, and setting monitoring points according to the positions of the point to be selected in the target combination.
Further, the sum of the monitoring ranges corresponding to the points to be selected in the point to be selected combination can cover all areas needing line monitoring in the line graph.
Further, the process of screening the candidate point combination comprises the following steps:
acquiring a monitoring energy efficiency value and monitoring cost corresponding to a point to be selected, and establishing a priority value formula;
inputting the obtained monitoring energy efficiency value and monitoring cost corresponding to each monitoring point into the priority value formula for calculation to obtain a priority value corresponding to each point combination to be selected;
and marking the point combination to be selected with the largest priority value as a target combination.
Further, the priority value formula is:
wherein:
b1 and b2 are proportionality coefficients, and the value range is 0< b1 less than or equal to 1,0< b2 less than or equal to 1;
YM is a priority value;
i represents a point to be selected, i=1, 2, … …, n being a positive integer;
JCi is a monitoring energy efficiency value corresponding to each point to be selected;
CHi is the monitoring cost corresponding to each point to be selected;
c is the cost conversion factor.
The monitoring module is used for analyzing the monitoring data of each monitoring point, identifying abnormal data in the monitoring data, analyzing a corresponding abnormal value set, evaluating problem values corresponding to each line based on the obtained abnormal value set, and carrying out inspection according to the obtained problem values of each line.
Further, determining the set of outliers includes:
real-time digitizing the collected monitoring data to form feature vectors; and establishing a monitoring analysis model, and analyzing the obtained feature vector through the established monitoring analysis model to obtain an abnormal value set.
Further, the calculation process of the problem value includes:
and carrying out distribution analysis on each line by using the abnormal value set to obtain a distribution value and an optimization coefficient corresponding to each line, and inputting the obtained distribution value and optimization coefficient into a problem value formula for calculation to obtain a corresponding problem value.
Further, the problem value calculation formula is:
wherein: WT is the problem value;
PFj is an assigned value;
vj is an optimization coefficient;
j=1, 2, … …, m being a positive integer.
Compared with the prior art, the invention has the beneficial effects that:
through the mutual coordination between the analysis module and the monitoring module, the real-time monitoring of the power transmission line is realized, various monitoring parameters are utilized for carrying out state monitoring, the problem of carrying out inspection monitoring in the manual inspection mode at present is solved, the monitoring efficiency and timeliness are improved, the problem of the line with the problem is found early, and the problem can be found without waiting for the circuit to be broken completely; the intelligent monitoring of the power transmission line is realized.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings can be obtained according to these drawings without inventive effort to a person skilled in the art.
Fig. 1 is a functional block diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in fig. 1, a condition monitoring system for an electrical device includes an analysis module and a monitoring module;
the analysis module is used for analyzing the outdoor power line network, distributing corresponding monitoring equipment and acquiring corresponding monitoring data, and solving the problem that the outdoor line data acquisition is difficult at present; the characteristics of the line transmission are utilized to carry out the layout of monitoring equipment, and monitoring parameters such as voltage, current, loss and the like are utilized to monitor the line transmission; because the faults of the line can be reflected on the monitoring parameters, the monitoring data collected during the faults are different from the monitoring parameters collected during the normal conditions; through the way that expert group discusses, set up the monitoring parameter that corresponds needs to gather based on the problem that the circuit probably has, and then set up each monitoring parameter and can select various monitoring equipment, the selection of specific monitoring equipment is based on the monitoring point that selects, because the actual monitoring condition of different monitoring points probably has the difference, if a certain monitoring point already has the gathering function of certain monitoring parameter, then the monitoring equipment that corresponds just need not add, or certain monitoring point certain monitoring equipment can not be used, need apply other types of monitoring equipment, need carry out specific analysis according to actual conditions, but based on current general knowledge, can be directed against its corresponding additional equipment of each monitoring point analysis.
The monitoring point setting process is as follows:
obtaining a circuit diagram, wherein the circuit diagram is the existing distributed data of each circuit in a region needing to be monitored; establishing a corresponding point location analysis model based on a CNN network or a DNN network, establishing a corresponding training set based on the distribution condition of each existing line by a manual mode for training, analyzing which positions meet the monitoring requirements of each monitoring parameter based on the existing line distribution data, taking the positions as a point to be selected and the monitoring energy efficiency value corresponding to the point to be selected, setting the monitoring energy efficiency value based on the range corresponding to the point to be selected and the optimal monitoring range, wherein the different point locations have different corresponding line lengths, numbers and the like, the monitoring ranges are different, the monitoring range is too large and too small, the monitoring energy efficiency value has the maximum value, the monitoring energy efficiency value is smaller as the difference between the monitoring energy efficiency value and the optimal monitoring range is larger, and the optimal monitoring range is set by an expert group; analyzing through the point location analysis model after the training is successful, and outputting settable points to be selected corresponding to the circuit diagram and monitoring energy efficiency values corresponding to the points to be selected; because neural networks are prior art in the art, the specific setup and sequence process is not described in detail in this disclosure.
According to the actual conditions of each point to be selected, analyzing monitoring equipment which is required to be additionally arranged in order to realize monitoring of each monitoring parameter, evaluating the monitoring cost which should be input by the point to be selected according to the additionally arranged monitoring equipment, and setting a cost conversion coefficient for carrying out common calculation with the monitoring energy efficiency value after unit conversion; the method comprises the steps of obtaining a plurality of point combination to be selected by utilizing the monitoring range of each point to be selected, the monitoring range corresponding to a circuit diagram and the existing point distribution common knowledge, and carrying out the combination of each point to be selected by utilizing the prior art in order to realize the monitoring of the monitoring range, so that each combination can realize the comprehensive monitoring of the range to be monitored.
Identifying points to be selected in each combination, and marking the points as i, wherein i=1, 2, … …, n and n are positive integers; the obtained monitoring energy efficiency value, the monitoring cost and the cost conversion coefficient are respectively marked as JCI, CHi and c; according to the formula of priority value
Calculating corresponding priority values YM, wherein b1 and b2 are proportionality coefficients, and the value range is 0<b1≤1，0<b2 is less than or equal to 1, selecting the point combination to be selected with the largest priority value as a target combination, and determining the corresponding monitoring points and the arrangement of each monitoring device according to the target combination.
And acquiring data corresponding to each monitoring parameter through the set monitoring equipment to obtain monitoring data corresponding to each monitoring point.
In other embodiments, the screening of the candidate point combinations may also be performed using other existing techniques to determine the target combinations.
The monitoring module is used for analyzing the monitoring data of each monitoring point, judging whether the monitoring data corresponding to each monitoring point is abnormal, further analyzing the abnormal data, analyzing the lines possibly having problems in the lines corresponding to the monitoring points, and further performing targeted inspection, such as inspection by using unmanned aerial vehicles, manual inspection and other inspection modes, or supplementing by combining the line image data which can be acquired; the specific inspection mode is selected according to the actual situation.
Thus, the process of how to determine whether each monitored data is abnormal includes:
converting all the collected monitoring data into real-time numerical values, namely converting non-numerical parameters into numerical values, presetting corresponding conversion modes by using various existing numerical conversion modes in a manual mode, further converting all the monitoring data, and finishing the data corresponding to all the monitoring parameters into feature vectors after converting the numerical values; simulating a feature vector corresponding to each monitoring point in normal operation and a feature vector when an exceeding problem occurs, establishing a corresponding training set in a manual mode, wherein the training set comprises the feature vector, monitoring point information, whether the feature vector is abnormal or not and an abnormal value corresponding to an abnormal parameter, wherein the abnormal value is the abnormal value corresponding to the abnormal value analyzed by combining the numerical value abnormality of the monitoring parameter with the numerical value of other monitoring parameters, a certain numerical value abnormality can be reflected or influenced on other parameters, and the abnormal value is comprehensively set; establishing a corresponding monitoring analysis model based on a CNN network or a DNN network, training through the established training set, analyzing the feature vector in real time through the successfully trained monitoring analysis model, and outputting a corresponding monitoring analysis result, wherein the monitoring analysis result comprises a normal operation value set and an abnormal operation value set; the abnormal value set is a set of abnormal values corresponding to each parameter with parameter abnormality, and indicates the parameter corresponding to each abnormal value.
The process of analyzing the anomaly data includes:
determining a corresponding abnormal value set, distributing each abnormal value in the abnormal value set to each line, and obtaining a problem value of each line after integration, specifically presetting a distribution proportion of each abnormal value relative to each line in a manual mode, distributing according to the corresponding distribution proportion, setting a corresponding optimization coefficient according to the corresponding distribution, optimizing the distributed value, specifically setting a corresponding training set in the manual mode, establishing a corresponding distribution analysis model based on a CNN (computer numerical network) or DNN (digital network), training the training set through the established training set, analyzing the abnormal value set through the distribution analysis model after training success to obtain a distribution value corresponding to each line and a corresponding optimization coefficient, and marking the obtained distribution value and the obtained optimization coefficient as PFj and vj respectively, wherein j=1, 2, … …, m and m are positive integers, and j represents the distribution of the corresponding abnormal value; according to the problem value formula
Calculating a corresponding problem value WT; and sorting the calculated problem values according to the order from large to small, performing corresponding investigation according to the sorting, and also setting a threshold value X1 for screening to perform important investigation on the lines corresponding to the problem values which are not lower than the threshold value X1.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas which are obtained by acquiring a large amount of data and performing software simulation to obtain the closest actual situation, and preset parameters and preset thresholds in the formulas are set by a person skilled in the art according to the actual situation or are obtained by simulating a large amount of data.
The above embodiments are only for illustrating the technical method of the present invention and not for limiting the same, and it should be understood by those skilled in the art that the technical method of the present invention may be modified or substituted without departing from the spirit and scope of the technical method of the present invention.
Claims (8)
1. A condition monitoring system for an electrical device, comprising an analysis module and a monitoring module;
the analysis module is used for analyzing an outdoor power line network, distributing corresponding monitoring points and monitoring equipment corresponding to the monitoring points, and acquiring real-time data through the distributed monitoring equipment to obtain monitoring data corresponding to the monitoring points;
the monitoring module is used for analyzing the monitoring data of each monitoring point, identifying abnormal data in the monitoring data, analyzing a corresponding abnormal value set, evaluating problem values corresponding to each line based on the obtained abnormal value set, and carrying out inspection according to the obtained problem values of each line.
2. A condition monitoring system for an electrical device according to claim 1, wherein the process of performing the monitoring point setting comprises:
obtaining a circuit diagram, analyzing each corresponding point to be selected in the circuit diagram, determining a plurality of point to be selected combinations based on the point to be selected and the circuit diagram, screening the point to be selected combinations, determining a target combination, and setting monitoring points according to the positions of the point to be selected in the target combination.
3. The condition monitoring system for electrical equipment according to claim 2, wherein the sum of the monitoring ranges corresponding to the candidate points in the candidate point combination can cover all areas in the circuit diagram where circuit monitoring is required.
4. The condition monitoring system for electrical equipment of claim 2, wherein the process of screening the candidate point combinations comprises:
acquiring a monitoring energy efficiency value and monitoring cost corresponding to a point to be selected, and establishing a priority value formula;
inputting the obtained monitoring energy efficiency value and monitoring cost corresponding to each monitoring point into the priority value formula for calculation to obtain a priority value corresponding to each point combination to be selected;
and marking the point combination to be selected with the largest priority value as a target combination.
5. The condition monitoring system for electrical equipment of claim 4, wherein the priority value formula is:
wherein: b1 and b2 are proportionality coefficients, and the value range is 0< b1 less than or equal to 1,0< b2 less than or equal to 1; YM is a priority value; i represents a point to be selected, i=1, 2, … …, n being a positive integer; JCi is a monitoring energy efficiency value corresponding to each point to be selected; CHi is the monitoring cost corresponding to each point to be selected; c is the cost conversion factor.
6. The condition monitoring system for an electrical device of claim 1, wherein determining the set of outliers comprises:
real-time digitizing the collected monitoring data to form feature vectors; and establishing a monitoring analysis model, and analyzing the obtained feature vector through the established monitoring analysis model to obtain an abnormal value set.
7. The condition monitoring system for electrical equipment of claim 6, wherein the calculation of the problem value comprises:
and carrying out distribution analysis on each line by using the abnormal value set to obtain a distribution value and an optimization coefficient corresponding to each line, and inputting the obtained distribution value and optimization coefficient into a problem value formula for calculation to obtain a corresponding problem value.
8. The condition monitoring system for electrical equipment of claim 7, wherein the problem value calculation formula is:
wherein: WT is the problem value; PFj is an assigned value; vj is an optimization coefficient; j=1, 2, … …, m being a positive integer.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN202310393404.0A CN116359652A (en) | 2023-04-13 | 2023-04-13 | State monitoring system for power equipment |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202310393404.0A CN116359652A (en) | 2023-04-13 | 2023-04-13 | State monitoring system for power equipment |
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| CN116359652A true CN116359652A (en) | 2023-06-30 |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116742484A (en) * | 2023-08-15 | 2023-09-12 | 希格玛电气(珠海)有限公司 | Circuit connection control system of solid insulation cabinet |
| CN116826976A (en) * | 2023-08-11 | 2023-09-29 | 国网安徽省电力有限公司铜陵供电公司 | Distribution network operation automatic supervision control system |
| CN116955455A (en) * | 2023-07-21 | 2023-10-27 | 上海策溯科技有限公司 | Processing method and platform suitable for radiation monitoring system |
| CN117010867A (en) * | 2023-10-07 | 2023-11-07 | 南通庄吉华威电子有限公司 | Packaging equipment monitoring system based on data analysis |
| CN118337534A (en) * | 2024-06-13 | 2024-07-12 | 山东网驰信息技术有限公司 | Data monitoring system for determining abnormal flow |
-
2023
- 2023-04-13 CN CN202310393404.0A patent/CN116359652A/en not_active Withdrawn
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116955455A (en) * | 2023-07-21 | 2023-10-27 | 上海策溯科技有限公司 | Processing method and platform suitable for radiation monitoring system |
| CN116955455B (en) * | 2023-07-21 | 2024-01-16 | 上海策溯科技有限公司 | Processing method and platform suitable for radiation monitoring system |
| CN116826976A (en) * | 2023-08-11 | 2023-09-29 | 国网安徽省电力有限公司铜陵供电公司 | Distribution network operation automatic supervision control system |
| CN116826976B (en) * | 2023-08-11 | 2024-01-26 | 国网安徽省电力有限公司铜陵供电公司 | Distribution network operation automatic supervision control system |
| CN116742484A (en) * | 2023-08-15 | 2023-09-12 | 希格玛电气(珠海)有限公司 | Circuit connection control system of solid insulation cabinet |
| CN117010867A (en) * | 2023-10-07 | 2023-11-07 | 南通庄吉华威电子有限公司 | Packaging equipment monitoring system based on data analysis |
| CN117010867B (en) * | 2023-10-07 | 2023-12-22 | 南通庄吉华威电子有限公司 | Packaging equipment monitoring system based on data analysis |
| CN118337534A (en) * | 2024-06-13 | 2024-07-12 | 山东网驰信息技术有限公司 | Data monitoring system for determining abnormal flow |
| CN118337534B (en) * | 2024-06-13 | 2024-08-27 | 山东网驰信息技术有限公司 | Data monitoring system for determining abnormal flow |
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Application publication date: 20230630 |