CN117406047A - Partial discharge state on-line monitoring system of power equipment - Google Patents
Partial discharge state on-line monitoring system of power equipment Download PDFInfo
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 213
- 238000004451 qualitative analysis Methods 0.000 claims abstract description 16
- 238000004445 quantitative analysis Methods 0.000 claims abstract description 16
- 238000007405 data analysis Methods 0.000 claims abstract description 11
- 238000004458 analytical method Methods 0.000 claims description 161
- 238000012423 maintenance Methods 0.000 claims description 25
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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
- G01R31/12—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing
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- G—PHYSICS
- G01—MEASURING; TESTING
- 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
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
Abstract
The invention discloses an online monitoring system for partial discharge state of power equipment, which comprises: the data acquisition module acquires power data and environment data of a plurality of monitoring areas in the power equipment; the data analysis module is used for carrying out qualitative and quantitative analysis on the power equipment based on the power data and the environment data of the plurality of monitoring areas to obtain qualitative power data and quantitative power data; the on-line monitoring platform performs threshold comparison based on the qualitative data and the quantitative data of the electric power, and performs preliminary monitoring judgment on the operation of the electric power equipment; and through quantitative and qualitative analysis, the faults existing in the power equipment can be accurately monitored and analyzed.
Description
Technical Field
The invention relates to the technical field of power equipment, in particular to an online monitoring system for a partial discharge state of power equipment.
Background
Chinese patent CN110647093B discloses an intelligent monitoring system and a monitoring method for an electric power system based on big data analysis, where a partial discharge sensor collects partial discharge data of an electric power device, a temperature sensor collects temperature data of the electric power device, a data analysis module performs historical data longitudinal analysis on the partial discharge data and the temperature data, related device data transverse analysis, and multidimensional data transverse analysis, and a data display and early warning module displays an analysis result of the data analysis module and performs early warning according to the analysis result of the data analysis module;
in the prior art, an intelligent monitoring system of the power system longitudinally analyzes historical data, transversely analyzes associated equipment data and transversely analyzes multidimensional data; however, in the online monitoring process, qualitative and quantitative analysis and monitoring can not be effectively performed on the fault area in the power equipment according to the power data and the environment data, so that the problem of difficulty in rapidly solving the fault area when the power equipment breaks down is solved.
Disclosure of Invention
The invention aims to provide an on-line monitoring system for the partial discharge state of power equipment, which solves the following technical problems: the fault area in the power equipment cannot be qualitatively and quantitatively analyzed and monitored according to the power data and the environment data, so that the problem that the fault area is difficult to rapidly solve when the power equipment breaks down is solved.
The aim of the invention can be achieved by the following technical scheme:
an on-line monitoring system for partial discharge state of an electrical device, comprising:
the data acquisition module acquires power data and environment data of a plurality of monitoring areas in the power equipment; the power data comprise local discharge average values of each monitoring area; the environmental data comprises a temperature average value of each monitoring area and a noise average value of each monitoring area;
the data analysis module is used for carrying out qualitative and quantitative analysis on the power equipment based on the power data and the environment data of the plurality of monitoring areas to obtain qualitative power data and quantitative power data;
the qualitative analysis is carried out according to the environmental data of the plurality of monitoring areas to obtain electric qualitative data; the qualitative electric power data comprise analysis period temperature fluctuation values and analysis period noise fluctuation values; the quantitative analysis is carried out according to the electric power data of the monitoring areas to obtain electric power quantitative data; the quantitative power data comprise analysis period partial discharge fluctuation values;
the on-line monitoring platform is used for respectively adding and summing the analysis period temperature fluctuation values and the analysis period noise fluctuation values of all the monitoring areas to obtain an analysis period temperature fluctuation total value and an analysis period noise fluctuation total value of the power equipment, comparing the analysis period temperature fluctuation total value and the analysis period noise fluctuation total value of the power equipment with a corresponding analysis period temperature fluctuation total threshold value and analysis period noise fluctuation total threshold value, if both the analysis period temperature fluctuation total value and the analysis period noise fluctuation total value are smaller than the corresponding analysis period temperature fluctuation total threshold value and the analysis period noise fluctuation total threshold value, indicating that the working state of the power equipment is normal, generating a power equipment normal signal, and if one of the analysis period temperature fluctuation total value and the analysis period noise fluctuation total value is larger than the analysis period temperature fluctuation total threshold value, indicating that the state of the power equipment is abnormal, and generating a power equipment abnormal signal;
and based on the abnormal signals of the power equipment, adding and summing the analysis period partial discharge fluctuation values of all the monitoring areas to obtain an analysis period partial discharge fluctuation total value of the power equipment, and carrying out difference value calculation on the obtained analysis period partial discharge fluctuation total value and the analysis period partial discharge fluctuation total threshold value to obtain the abnormal value of the power equipment.
As a further aspect of the present invention, the plurality of monitoring areas are configured to divide the spatial perspective view of the monitored power equipment into a plurality of areas in the voltage transmission direction based on the acquired spatial perspective view of the monitored power equipment.
As a further scheme of the invention, the acquisition mode of the analysis period temperature fluctuation value is as follows:
presetting analysis periods, acquiring temperature average values of two adjacent monitoring periods in each monitoring region, subtracting absolute values from the temperature average values of the two monitoring periods to obtain temperature fluctuation values of the monitoring periods, and adding and summing all the temperature fluctuation values of the monitoring periods in the analysis periods to obtain the temperature fluctuation value of the analysis period of each monitoring region.
As a further scheme of the invention, the acquisition mode of analyzing the periodic noise fluctuation value is as follows:
presetting analysis periods, acquiring noise average values of two adjacent monitoring periods in each monitoring region, subtracting absolute values from the noise average values of the two monitoring periods to obtain monitoring period noise fluctuation values, and adding and summing all monitoring period noise fluctuation values in the analysis periods to obtain analysis period noise fluctuation values of each monitoring region.
As a further scheme of the invention, the acquisition mode of the analysis period partial discharge fluctuation value is as follows:
presetting analysis periods, obtaining local discharge average values of two adjacent monitoring periods in each monitoring region, subtracting absolute values from the local discharge average values of the two monitoring periods to obtain local discharge fluctuation values of the monitoring periods, and adding and summing the local discharge values of all the monitoring periods in the analysis periods to obtain the local discharge fluctuation values of the analysis periods of each monitoring region.
As a further scheme of the invention, the system also comprises a fault positioning module for performing double positioning on the monitoring area of the power equipment;
wherein, the double positioning is: positioning the fault level of the monitoring area and positioning the fault area of the monitoring area;
the fault level is a fault level for determining the fault of the current monitoring area, wherein the fault level comprises a first-level fault, a second-level fault and a third-level fault, the dangerous condition of the first-level fault is smaller than that of the second-level fault, and the dangerous condition of the second-level fault is smaller than that of the third-level fault;
the fault area is used for determining the position of a fault point in the current monitoring area corresponding to the space perspective view of the monitored power equipment, and comprises a spherical area taking the fault point as a sphere center and taking a preset specific distance as a radius.
As a further scheme of the invention, the analysis period temperature fluctuation value, the analysis period noise fluctuation value and the analysis period partial discharge fluctuation value are respectively divided with the corresponding analysis period temperature fluctuation threshold value, the analysis period noise fluctuation threshold value and the analysis period partial discharge fluctuation threshold value to obtain a temperature-time wave ratio, a noise-time wave ratio and a partial discharge wave ratio, and then the temperature-time wave ratio, the noise-time wave ratio and the partial discharge wave ratio are summed up to obtain an online wave ratio; and comparing the online wave ratio with a preset proportion interval corresponding to the fault level to obtain the fault level of the current power equipment.
As a further scheme of the invention, determining a position with the largest analysis period temperature fluctuation value and a position with the largest analysis period noise fluctuation value in a monitoring area, respectively corresponding the positions to a space perspective view of the monitored power equipment, and marking the positions as a first fault point and a second fault point in the space perspective view of the monitored power equipment; taking the midpoint of the connection line of the first fault point and the second fault point, namely positioning the first fault point and the second fault point as fault points; and positioning the area with the preset specific distance as the radius as a fault area.
As a further aspect of the present invention, the preset specific distance is: the specific distance corresponding to the first-level wave ratio section is L1, the specific distance corresponding to the second-level wave ratio section is L2, and the specific distance corresponding to the third-level wave ratio section is L3.
The invention further provides a maintenance judging module, which is used for acquiring maintenance obstacle information of a fault area based on the fault area in the space perspective view of the monitored power equipment;
the maintenance obstacle information comprises the space volume of a fault area, the nearest channel between the fault area and the equipment cabinet door, and the model of the nearest channel containing the power element.
The invention has the beneficial effects that:
according to the invention, the data acquisition module is used for acquiring the electric power data and the environmental data of a plurality of monitoring areas in the electric power equipment, the data analysis module is used for carrying out qualitative and quantitative analysis on the electric power equipment to obtain electric power qualitative data and electric power quantitative data, the on-line monitoring platform is used for carrying out threshold comparison and carrying out preliminary monitoring judgment on the operation of the electric power equipment; the method has the advantages of realizing the online real-time monitoring, analysis and judgment of the power equipment by taking time as a reference axis from environmental factors and power factors, and realizing the online real-time monitoring, the rapid accuracy and the online real-time monitoring of the power equipment; the faults existing in the power equipment can be accurately monitored and analyzed through quantitative and qualitative analysis;
the qualitative positioning of the fault level and the quantitative positioning of the fault area are carried out on the monitoring area of the power equipment based on qualitative and quantitative analysis in the online monitoring system through the fault positioning module, so that a maintainer can quickly know the position and the level of the fault of the power equipment, and a corresponding maintenance scheme is designed, so that the maintenance efficiency of the power equipment is improved;
the invention designs the proper maintenance scheme by the maintenance judging module, and enables maintenance personnel to accurately solve the fault of the power equipment based on the maintenance scheme.
Drawings
The invention is further described below with reference to the accompanying drawings.
Fig. 1 is a system block diagram of an online monitoring system for a partial discharge state of an electrical device according to a first embodiment of the present invention;
fig. 2 is a system block diagram of an online monitoring system for a partial discharge state of an electrical device according to a first alternative embodiment provided by a second embodiment of the present invention;
fig. 3 is a system block diagram of an online monitoring system for a partial discharge state of an electrical device according to a second alternative embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but 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.
Example 1
Fig. 1 is a system block diagram of an online monitoring system for a partial discharge state of an electrical device according to a first embodiment of the present invention, where the embodiment is applicable to an application scenario of real-time online monitoring of an electrical device such as a power transformation cabinet, a power distribution cabinet, and a switch cabinet in a working state;
as shown in fig. 1, the power equipment status online monitoring system includes:
the data acquisition module acquires power data and environment data of a plurality of monitoring areas in the power equipment;
the method comprises the steps that a plurality of monitoring areas are used for dividing a space perspective view of monitored power equipment into a plurality of areas according to a voltage conveying direction based on the acquired space perspective view of the monitored power equipment;
the power data comprise local discharge average values of each monitoring area, and the power data are distributed with local discharge sensors in the corresponding monitoring areas; partial discharge local values are obtained by carrying out mean value calculation on the partial discharge values obtained in the monitoring period according to a preset monitoring period;
the environmental data comprises a temperature average value of each monitoring area and a noise average value of each monitoring area; the environmental data is provided with a temperature sensor and a noise sensor by arranging the temperature sensor and the noise sensor in the corresponding monitoring areas; the temperature average value is obtained by carrying out average value calculation on the temperature value acquired in the monitoring period according to a preset monitoring period; the noise average value is obtained by carrying out average value calculation on the noise value acquired in the monitoring period according to the preset monitoring period;
in some embodiments, based on the obtained spatial perspective view of the monitored power equipment, dividing the spatial perspective view of the monitored power equipment into a plurality of areas in the voltage conveying direction, obtaining a partial discharge real-time value of each area by using a partial discharge sensor according to a preset monitoring period, carrying out mean value calculation to obtain a partial discharge mean value, obtaining a temperature real-time value of each area by using a temperature sensor, carrying out mean value calculation to obtain a temperature mean value, obtaining a noise real-time value of each area by using a noise sensor, and carrying out mean value calculation to obtain a noise mean value;
the data analysis module is used for carrying out qualitative and quantitative analysis on the power equipment based on the power data and the environment data of the plurality of monitoring areas to obtain qualitative power data and quantitative power data;
the qualitative analysis is carried out according to the environmental data of the plurality of monitoring areas to obtain electric qualitative data; the qualitative electric power data comprise analysis period temperature fluctuation values and analysis period noise fluctuation values;
the quantitative analysis is carried out according to the electric power data of the monitoring areas to obtain electric power quantitative data; the quantitative power data comprise analysis period partial discharge fluctuation values;
specifically, the analysis period temperature fluctuation value is obtained by the following steps:
presetting analysis periods, acquiring temperature average values of two adjacent monitoring periods in each monitoring region, subtracting absolute values from the temperature average values of the two monitoring periods to obtain temperature fluctuation values of the monitoring periods, and adding and summing all the temperature fluctuation values of the monitoring periods in the analysis periods to obtain the temperature fluctuation value of the analysis period of each monitoring region;
the acquisition mode of analyzing the periodic noise fluctuation value is as follows:
presetting analysis periods, acquiring noise average values of two adjacent monitoring periods in each monitoring region, subtracting absolute values from the noise average values of the two monitoring periods to obtain monitoring period noise fluctuation values, and adding and summing all monitoring period noise fluctuation values in the analysis periods to obtain analysis period noise fluctuation values of each monitoring region;
the acquisition mode of the analysis period partial discharge fluctuation value is as follows:
presetting analysis periods, obtaining local discharge average values of two adjacent monitoring periods in each monitoring region, subtracting absolute values from the local discharge average values of the two monitoring periods to obtain local discharge fluctuation values of the monitoring periods, and adding and summing the local discharge values of all the monitoring periods in the analysis periods to obtain the local discharge fluctuation values of the analysis periods of each monitoring region;
the method is characterized in that the preset analysis period consists of a plurality of monitoring periods;
in some embodiments, based on local discharge average values, temperature average values and noise average values of a plurality of monitoring areas of a data acquisition module, firstly acquiring the temperature average value/noise average value of two adjacent monitoring periods in each monitoring area, subtracting absolute values from the temperature average value/noise average values of the two monitoring periods to obtain monitoring period temperature/noise fluctuation values, and adding and summing all monitoring period temperature/noise fluctuation values in an analysis period to obtain analysis period temperature fluctuation values/analysis period noise fluctuation values of each monitoring area; obtaining local discharge average values of two adjacent monitoring periods in each monitoring region, subtracting absolute values from the local discharge average values of the monitoring period nodes to obtain local discharge fluctuation values of the monitoring periods, and adding and summing all the local discharge values of the monitoring periods in the analysis period to obtain the local discharge fluctuation values of the analysis periods of each monitoring region;
in other embodiments, the quantitative power data may be acquired first and then the qualitative power data may be acquired; or simultaneously acquiring the quantitative data and qualitative data of the electric power;
the on-line monitoring platform is used for carrying out threshold comparison based on the qualitative data and the quantitative data of the electric power and carrying out preliminary monitoring judgment on the operation of the electric power equipment;
the threshold values comprise an electric qualitative data threshold value and an electric quantitative data threshold value, wherein the electric qualitative data threshold value comprises an analysis period temperature fluctuation total threshold value and an analysis period noise fluctuation total threshold value, and the electric quantitative data threshold value comprises an analysis period partial discharge fluctuation total threshold value; the power qualitative data threshold and the power quantitative data threshold are obtained by storing historical power qualitative data and power quantitative data through a data storage module and dividing according to the relation between the historical power qualitative data and the power quantitative data and the power equipment faults;
comparing the power qualitative data with a power qualitative data threshold value, and then comparing the power quantitative data with a power quantitative data threshold value;
the preliminary monitoring judgment is explained as follows: performing first monitoring judgment processing on the power equipment through the electric power qualitative data and the electric power quantitative data;
in some embodiments, the analysis period temperature fluctuation values and the analysis period noise fluctuation values of all the monitoring areas are added and summed respectively to obtain an analysis period temperature fluctuation total value and an analysis period noise fluctuation total value of the power equipment, the analysis period temperature fluctuation total value and the analysis period noise fluctuation total value of the power equipment are compared with a corresponding analysis period temperature fluctuation total threshold value and analysis period noise fluctuation total threshold value, if the analysis period temperature fluctuation total value and the analysis period noise fluctuation total value are smaller than the corresponding analysis period temperature fluctuation total threshold value and the analysis period noise fluctuation total threshold value, the power equipment working state is normal, a power equipment normal signal is generated, and if one of the analysis period temperature fluctuation total value and the analysis period noise fluctuation total value is larger than the corresponding analysis period temperature fluctuation total threshold value, the power equipment state abnormality is represented, and a power equipment abnormality signal is generated;
based on the abnormal signals of the power equipment, adding and summing the analysis period partial discharge fluctuation values of all the monitoring areas to obtain an analysis period partial discharge fluctuation total value of the power equipment, and performing difference value calculation on the obtained analysis period partial discharge fluctuation total value and an analysis period partial discharge fluctuation total threshold value to obtain the abnormal value of the power equipment;
according to the technical scheme, the data acquisition module is used for acquiring the electric power data and the environment data of a plurality of monitoring areas in the electric power equipment, the data analysis module is used for carrying out qualitative and quantitative analysis on the electric power equipment to obtain electric power qualitative data and electric power quantitative data, the on-line monitoring platform is used for carrying out threshold comparison and carrying out preliminary monitoring judgment on the operation of the electric power equipment; the method has the advantages of realizing the online real-time monitoring, analysis and judgment of the power equipment by taking time as a reference axis from environmental factors and power factors, and realizing the online real-time monitoring, the rapid accuracy and the online real-time monitoring of the power equipment; the faults existing in the power equipment can be accurately monitored and analyzed through quantitative and qualitative analysis;
the online monitoring platform in the embodiment of the invention performs summation calculation through the qualitative data and the quantitative data of the electric power in each monitoring area, compares the summation calculation with the corresponding threshold value to reflect the integral performance of the electric power equipment, can qualitatively reflect the fault condition of the electric power equipment through the abnormal signal of the electric power equipment, and quantitatively reflects the fault condition of the electric power equipment through the abnormal value of the electric power equipment.
Example two
Optionally, fig. 2 is a system block diagram of an online monitoring system for a partial discharge state of an electrical device according to a first alternative embodiment provided in a second embodiment of the present invention;
as shown in fig. 2, the system further comprises a fault positioning module for performing double positioning on the monitoring area of the power equipment;
the specific explanation is as follows: the fault locating module is used for analyzing and judging each monitoring area of the power equipment one by one based on the condition of the overall abnormal condition of the power equipment obtained by the first embodiment, and particularly the fault caused by which monitoring area is generated;
wherein, the double positioning can be: positioning the fault level of the monitoring area and positioning the fault area of the monitoring area;
the fault level is a fault level for determining the fault of the current monitoring area, wherein the fault level comprises a first-level fault, a second-level fault and a third-level fault, the dangerous condition of the first-level fault is smaller than that of the second-level fault, and the dangerous condition of the second-level fault is smaller than that of the third-level fault;
the fault area is used for determining the position of a fault point in the current monitoring area corresponding to a space perspective view of the monitored power equipment, and comprises a spherical area taking the fault point as a sphere center and taking a preset specific distance as a radius;
in some embodiments, the fault positioning module obtains an analysis period temperature fluctuation value, an analysis period noise fluctuation value and an analysis period partial discharge fluctuation value of each monitoring area in the power equipment, divides the analysis period temperature fluctuation value, the analysis period noise fluctuation value and the analysis period partial discharge fluctuation value of each monitoring area with a corresponding analysis period temperature fluctuation threshold, an analysis period noise fluctuation threshold and an analysis period partial discharge fluctuation threshold respectively to obtain a temperature-time wave ratio, a noise-time wave ratio and a partial discharge wave ratio, and then adds and sums the temperature-time wave ratio, the noise-time wave ratio and the partial discharge wave ratio to obtain an online wave ratio; judging the fault grade of the monitoring area according to the preset proportion interval range if the online wave ratio is in the preset proportion interval corresponding to the fault level, marking the monitoring area as a fault monitoring area, indicating that the monitoring area has no fault if the online wave ratio is not in the preset proportion interval corresponding to the fault level, marking the monitoring area as a non-fault monitoring area (judging whether the monitoring area has a fault or not through the online wave ratio of each monitoring area and the corresponding preset proportion interval, analyzing to obtain the monitoring area with the fault and the area without the fault monitoring, and further judging the fault grade in the monitoring area with the fault; wherein, the preset proportion interval is: the first-level wave ratio interval corresponding to the first-level fault is (B0, B1), the second-level wave ratio interval corresponding to the second-level fault is (B1, B2), and the third-level wave ratio interval corresponding to the third-level fault is (B2, B3);
determining a position where an analysis period temperature fluctuation value is maximum and a position where an analysis period noise fluctuation value is maximum in a fault monitoring area (wherein the determination of the position where the analysis period temperature fluctuation value is maximum and the determination of the position where the analysis period noise fluctuation value is maximum in the monitoring area are that the analysis period temperature fluctuation value and the analysis period noise fluctuation value of all fault monitoring areas in the power equipment are obtained, extracting the fault monitoring area corresponding to the analysis period temperature fluctuation value and the analysis period noise fluctuation value with the maximum value in the analysis period, marking the fault monitoring area with the maximum analysis period temperature fluctuation value and the fault monitoring area with the maximum analysis period noise fluctuation value as the fault monitoring area with the maximum analysis period temperature fluctuation value and the central point position of the fault monitoring area with the maximum analysis period noise fluctuation value as the position where the analysis period temperature fluctuation value is maximum in the fault monitoring area, and the analysis period noise fluctuation value is maximum, and respectively corresponding the positions to a space perspective view of the monitored power equipment, and marking the positions as a first fault point and a second fault point in the space view of the monitored power equipment; taking the midpoint of the connection line of the first fault point and the second fault point, namely positioning the first fault point and the second fault point as fault points; a region with a preset specific distance as a radius is positioned as a fault region; wherein, preset specific distance is: the specific distance corresponding to the primary wave ratio interval is L1, the specific distance corresponding to the secondary wave ratio interval is L2, and the specific distance corresponding to the tertiary wave ratio interval is L3;
illustratively, L1 may take the value 80mm, L2 may take the value 140mm, L3 may take the value 180mm;
specifically, the maximum analysis period temperature fluctuation value comprises an analysis period temperature fluctuation maximum value and the maximum occurrence number of the analysis period temperature fluctuation maximum value;
the maximum analysis period noise fluctuation value comprises the maximum analysis period noise fluctuation value and the maximum analysis period noise fluctuation value occurrence frequency;
in other embodiments, the obtained fault level and fault area are sent to the online monitoring platform and displayed by a display module of the online monitoring platform, so that the technical staff can observe the fault level and fault area conveniently;
according to the technical scheme provided by the embodiment of the invention, the fault locating module is used for qualitatively locating the fault level and quantitatively locating the fault area in the monitoring area of the power equipment based on qualitative and quantitative analysis in the online monitoring system, so that a maintainer can know the position and the level of the fault of the power equipment quickly, and a corresponding maintenance scheme is designed, so that the maintenance efficiency of the power equipment is improved.
Example III
Optionally, fig. 3 is a system block diagram of an online monitoring system for a partial discharge state of an electrical device according to a second alternative embodiment provided in a third embodiment of the present invention;
as shown in fig. 3, the system further comprises a maintenance judging module, wherein maintenance obstacle information of a fault area is obtained based on the fault area in the space perspective view of the monitored power equipment;
the maintenance obstacle information comprises the space volume of a fault area, the nearest channel between the fault area and the equipment cabinet door, and the model of the electric power element contained in the nearest channel;
in some embodiments, when the maintenance judging module obtains the fault area of the fault positioning module, according to the space perspective view of the monitored power equipment, the space volume of the fault area in the area where the fault area is located is obtained, the nearest channel (namely the shortest distance between the fault area and the equipment cabinet door) between the fault area and the equipment cabinet door is obtained, and the model of the power element is contained in the nearest channel;
firstly, marking the nearest channel as a route to be maintained according to the nearest channel between the fault area and a cabinet door of the equipment, thereby determining the route to be maintained of the fault area, determining the type of the electric power element required to be disassembled on the route to be maintained according to the type of the electric power element contained on the nearest channel, and finally determining a maintenance tool with the required size matched with the required size to be maintained according to the space volume of the fault area;
in other embodiments, the obtained space volume of the fault area, the nearest channel between the fault area and the equipment cabinet door, and the model of the electric power element contained in the nearest channel are sent to the online monitoring platform and displayed by the display module of the online monitoring platform, so that the technical staff can observe the space volume conveniently;
according to the technical scheme provided by the embodiment of the invention, the maintenance judgment module plans an appropriate maintenance scheme, so that maintenance personnel can accurately solve the fault of the power equipment based on the maintenance scheme.
The working principle of the invention is as follows: the data acquisition module acquires power data and environment data of a plurality of monitoring areas in the power equipment;
the data analysis module is used for carrying out qualitative and quantitative analysis on the power equipment based on the power data and the environment data of the plurality of monitoring areas to obtain qualitative power data and quantitative power data;
the on-line monitoring platform is used for carrying out threshold comparison based on the qualitative data and the quantitative data of the electric power and carrying out preliminary monitoring judgment on the operation of the electric power equipment;
the fault positioning module is used for performing double positioning on the monitoring area of the power equipment based on the monitoring area unqualified signal;
and the maintenance judging module is used for acquiring maintenance obstacle information of the fault area based on the fault area in the space perspective view of the monitored power equipment.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas with a large amount of data collected for software simulation to obtain the latest real situation, and preset parameters in the formulas are set by those skilled in the art according to the actual situation.
The foregoing describes one embodiment of the present invention in detail, but the description is only a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. All equivalent changes and modifications within the scope of the present invention are intended to be covered by the present invention.
Claims (10)
1. An on-line monitoring system for a partial discharge state of an electrical device, comprising:
the data acquisition module acquires power data and environment data of a plurality of monitoring areas in the power equipment; the power data comprise local discharge average values of each monitoring area; the environmental data comprises a temperature average value of each monitoring area and a noise average value of each monitoring area;
the data analysis module is used for carrying out qualitative and quantitative analysis on the power equipment based on the power data and the environment data of the plurality of monitoring areas to obtain qualitative power data and quantitative power data;
the qualitative analysis is carried out according to the environmental data of the plurality of monitoring areas to obtain electric qualitative data; the qualitative electric power data comprise analysis period temperature fluctuation values and analysis period noise fluctuation values; the quantitative analysis is carried out according to the electric power data of the monitoring areas to obtain electric power quantitative data; the quantitative power data comprise analysis period partial discharge fluctuation values;
the on-line monitoring platform is used for respectively adding and summing the analysis period temperature fluctuation values and the analysis period noise fluctuation values of all the monitoring areas to obtain an analysis period temperature fluctuation total value and an analysis period noise fluctuation total value of the power equipment, comparing the analysis period temperature fluctuation total value and the analysis period noise fluctuation total value of the power equipment with a corresponding analysis period temperature fluctuation total threshold value and analysis period noise fluctuation total threshold value, if both the analysis period temperature fluctuation total value and the analysis period noise fluctuation total value are smaller than the corresponding analysis period temperature fluctuation total threshold value and the analysis period noise fluctuation total threshold value, indicating that the working state of the power equipment is normal, generating a power equipment normal signal, and if one of the analysis period temperature fluctuation total value and the analysis period noise fluctuation total value is larger than the analysis period temperature fluctuation total threshold value, indicating that the state of the power equipment is abnormal, and generating a power equipment abnormal signal;
and based on the abnormal signals of the power equipment, adding and summing the analysis period partial discharge fluctuation values of all the monitoring areas to obtain an analysis period partial discharge fluctuation total value of the power equipment, and carrying out difference value calculation on the obtained analysis period partial discharge fluctuation total value and the analysis period partial discharge fluctuation total threshold value to obtain the abnormal value of the power equipment.
2. The system for on-line monitoring of partial discharge state of electrical equipment according to claim 1, wherein the plurality of monitoring areas are based on obtaining a spatial perspective view of the electrical equipment to be monitored, and the spatial perspective view of the electrical equipment to be monitored is divided into a plurality of areas in a voltage transmission direction.
3. The system for on-line monitoring of partial discharge state of electrical equipment according to claim 1, wherein the analysis period temperature fluctuation value is obtained by:
presetting analysis periods, acquiring temperature average values of two adjacent monitoring periods in each monitoring region, subtracting absolute values from the temperature average values of the two monitoring periods to obtain temperature fluctuation values of the monitoring periods, and adding and summing all the temperature fluctuation values of the monitoring periods in the analysis periods to obtain the temperature fluctuation value of the analysis period of each monitoring region.
4. The system for on-line monitoring of partial discharge state of electrical equipment according to claim 1, wherein the analysis of periodic noise fluctuation value is obtained by:
presetting analysis periods, acquiring noise average values of two adjacent monitoring periods in each monitoring region, subtracting absolute values from the noise average values of the two monitoring periods to obtain monitoring period noise fluctuation values, and adding and summing all monitoring period noise fluctuation values in the analysis periods to obtain analysis period noise fluctuation values of each monitoring region.
5. The system for on-line monitoring of partial discharge state of electrical equipment according to claim 1, wherein the analysis period partial discharge fluctuation value is obtained by:
presetting analysis periods, obtaining local discharge average values of two adjacent monitoring periods in each monitoring region, subtracting absolute values from the local discharge average values of the two monitoring periods to obtain local discharge fluctuation values of the monitoring periods, and adding and summing the local discharge values of all the monitoring periods in the analysis periods to obtain the local discharge fluctuation values of the analysis periods of each monitoring region.
6. The system for on-line monitoring of the partial discharge state of an electrical device according to claim 1, further comprising a fault locating module for double locating a monitored area of the electrical device;
wherein, the double positioning is: positioning the fault level of the monitoring area and positioning the fault area of the monitoring area;
the fault level is a fault level for determining the fault of the current monitoring area, wherein the fault level comprises a first-level fault, a second-level fault and a third-level fault, the dangerous condition of the first-level fault is smaller than that of the second-level fault, and the dangerous condition of the second-level fault is smaller than that of the third-level fault;
the fault area is used for determining the position of a fault point in the current monitoring area corresponding to the space perspective view of the monitored power equipment, and comprises a spherical area taking the fault point as a sphere center and taking a preset specific distance as a radius.
7. The system for on-line monitoring of partial discharge state of electrical equipment according to claim 6, wherein the analysis period temperature fluctuation value, the analysis period noise fluctuation value, and the analysis period partial discharge fluctuation value are divided by the corresponding analysis period temperature fluctuation threshold, analysis period noise fluctuation threshold, and analysis period partial discharge fluctuation threshold to obtain a temperature-time wave ratio, a noise-time wave ratio, and a partial discharge-time wave ratio, and the temperature-time wave ratio, the noise-time wave ratio, and the partial discharge-time wave ratio are summed together to obtain an on-line wave ratio; and comparing the online wave ratio with a preset proportion interval corresponding to the fault level to obtain the fault level of the current power equipment.
8. The system for on-line monitoring of a partial discharge state of an electric power apparatus according to claim 7, wherein a position where a maximum analysis period temperature fluctuation value occurs and a position where a maximum analysis period noise fluctuation value occurs in the monitored area are determined, and the positions are respectively mapped to a spatial perspective view of the monitored electric power apparatus, and the positions are marked as a first fault point and a second fault point in the spatial perspective view of the monitored electric power apparatus; taking the midpoint of the connection line of the first fault point and the second fault point, namely positioning the first fault point and the second fault point as fault points; and positioning the area with the preset specific distance as the radius as a fault area.
9. The system for on-line monitoring of partial discharge state of electrical equipment according to claim 8, wherein the preset specific distance is: the specific distance corresponding to the first-level wave ratio section is L1, the specific distance corresponding to the second-level wave ratio section is L2, and the specific distance corresponding to the third-level wave ratio section is L3.
10. The system for on-line monitoring of a partial discharge state of an electrical apparatus according to claim 9, further comprising a maintenance judging module that acquires maintenance obstacle information of a fault area based on the fault area in a spatial perspective view of the electrical apparatus to be monitored;
the maintenance obstacle information comprises the space volume of a fault area, the nearest channel between the fault area and the equipment cabinet door, and the model of the nearest channel containing the power element.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117723917A (en) * | 2024-02-07 | 2024-03-19 | 国网山西省电力公司太原供电公司 | Monitoring application method based on optical fiber extrinsic Fabry-Perot type ultrasonic sensor |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20070078195A (en) * | 2006-01-26 | 2007-07-31 | 삼현컴텍(주) | System and method for detecting a partial discharge of a powercable |
| CN111624445A (en) * | 2020-04-29 | 2020-09-04 | 珠海一多监测科技有限公司 | Partial discharge detection method and system based on infrared temperature measurement sensor |
| CN112116211A (en) * | 2020-08-25 | 2020-12-22 | 国网福建省电力有限公司检修分公司 | Method for judging working state of valve module through surface temperature and ultrasonic data |
| CN113255166A (en) * | 2021-06-28 | 2021-08-13 | 中国南方电网有限责任公司超高压输电公司检修试验中心 | Submarine cable fault detection method using temperature prediction |
| CN113253059A (en) * | 2021-06-24 | 2021-08-13 | 中国南方电网有限责任公司超高压输电公司检修试验中心 | Submarine cable fault detection method using temperature break variable |
| CN114200272A (en) * | 2022-02-17 | 2022-03-18 | 山东汇能电气有限公司 | Switch cabinet health state operation feedback system based on partial discharge detection |
| CN114252749A (en) * | 2022-02-28 | 2022-03-29 | 国网湖北省电力有限公司检修公司 | Transformer partial discharge detection method and device based on multiple sensors |
| US20220246378A1 (en) * | 2021-02-01 | 2022-08-04 | General Electric Technology Gmbh | Enhanced switchgear monitoring and diagnostics in a protection relay |
| CN114994471A (en) * | 2022-05-19 | 2022-09-02 | 国家电网有限公司 | Heat accumulator insulation performance detection and protection device and method |
| CN218213274U (en) * | 2022-10-10 | 2023-01-03 | 阿特美斯智能电气有限公司 | Monitoring devices is put in cubical switchboard office |
| CN116026403A (en) * | 2022-11-09 | 2023-04-28 | 国能四川西部能源股份有限公司 | Switch cabinet fault early warning method and device, medium and electronic equipment |
| CN116298737A (en) * | 2023-05-24 | 2023-06-23 | 广东电网有限责任公司佛山供电局 | Switch cabinet discharge monitoring system, method and equipment |
| CN116819247A (en) * | 2023-06-19 | 2023-09-29 | 国网山东省电力公司电力科学研究院 | Device and method for detecting partial discharge position of converter transformer winding |
-
2023
- 2023-12-14 CN CN202311720771.3A patent/CN117406047B/en active Active
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20070078195A (en) * | 2006-01-26 | 2007-07-31 | 삼현컴텍(주) | System and method for detecting a partial discharge of a powercable |
| CN111624445A (en) * | 2020-04-29 | 2020-09-04 | 珠海一多监测科技有限公司 | Partial discharge detection method and system based on infrared temperature measurement sensor |
| CN112116211A (en) * | 2020-08-25 | 2020-12-22 | 国网福建省电力有限公司检修分公司 | Method for judging working state of valve module through surface temperature and ultrasonic data |
| US20220246378A1 (en) * | 2021-02-01 | 2022-08-04 | General Electric Technology Gmbh | Enhanced switchgear monitoring and diagnostics in a protection relay |
| CN113253059A (en) * | 2021-06-24 | 2021-08-13 | 中国南方电网有限责任公司超高压输电公司检修试验中心 | Submarine cable fault detection method using temperature break variable |
| CN113255166A (en) * | 2021-06-28 | 2021-08-13 | 中国南方电网有限责任公司超高压输电公司检修试验中心 | Submarine cable fault detection method using temperature prediction |
| CN114200272A (en) * | 2022-02-17 | 2022-03-18 | 山东汇能电气有限公司 | Switch cabinet health state operation feedback system based on partial discharge detection |
| CN114252749A (en) * | 2022-02-28 | 2022-03-29 | 国网湖北省电力有限公司检修公司 | Transformer partial discharge detection method and device based on multiple sensors |
| CN114994471A (en) * | 2022-05-19 | 2022-09-02 | 国家电网有限公司 | Heat accumulator insulation performance detection and protection device and method |
| CN218213274U (en) * | 2022-10-10 | 2023-01-03 | 阿特美斯智能电气有限公司 | Monitoring devices is put in cubical switchboard office |
| CN116026403A (en) * | 2022-11-09 | 2023-04-28 | 国能四川西部能源股份有限公司 | Switch cabinet fault early warning method and device, medium and electronic equipment |
| CN116298737A (en) * | 2023-05-24 | 2023-06-23 | 广东电网有限责任公司佛山供电局 | Switch cabinet discharge monitoring system, method and equipment |
| CN116819247A (en) * | 2023-06-19 | 2023-09-29 | 国网山东省电力公司电力科学研究院 | Device and method for detecting partial discharge position of converter transformer winding |
Non-Patent Citations (2)
| Title |
|---|
| Q.KHAN ET AL.: "Partial discharge detection and diagnosis in gas insulated switchgea: State of art", 《IEEE ELECTRICAL INSULATION MAGAZINE》, 31 August 2019 (2019-08-31), pages 16 - 33 * |
| 任庆庆: "开关柜温度和局部放电综合监测系统设计", 《中国优秀硕士学位论文全文数据库 工程科技II辑》, 15 April 2021 (2021-04-15), pages 042 - 496 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117723917A (en) * | 2024-02-07 | 2024-03-19 | 国网山西省电力公司太原供电公司 | Monitoring application method based on optical fiber extrinsic Fabry-Perot type ultrasonic sensor |
| CN117723917B (en) * | 2024-02-07 | 2024-05-03 | 国网山西省电力公司太原供电公司 | Monitoring application method based on optical fiber extrinsic Fabry-Perot type ultrasonic sensor |
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