CN107831422B - GIS equipment partial discharge diagnosis method and system - Google Patents
GIS equipment partial discharge diagnosis method and system Download PDFInfo
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- CN107831422B CN107831422B CN201711065111.0A CN201711065111A CN107831422B CN 107831422 B CN107831422 B CN 107831422B CN 201711065111 A CN201711065111 A CN 201711065111A CN 107831422 B CN107831422 B CN 107831422B
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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
- G01R31/1227—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 of components, parts or materials
- G01R31/1254—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 of components, parts or materials of gas-insulated power appliances or vacuum gaps
Abstract
The embodiment of the invention discloses a GIS equipment partial discharge diagnosis method and a GIS equipment partial discharge diagnosis system. The method judges whether the monitoring data of each ultrahigh frequency sensor at the same interval are from the same signal source by carrying out similarity analysis on the monitoring data of each ultrahigh frequency sensor at the same interval, avoids that each ultrahigh frequency sensor makes wrong judgments on the severity and fault types of the partial discharge due to the interference of a plurality of signal sources, judges whether the ultrahigh frequency sensor is an internal fault of GIS equipment, and avoids false alarm due to external fault; the method has the advantages that the occurrence position of the partial discharge is accurately positioned according to the ultrahigh frequency signal amplitude, the equipment structure information and the same operation data of the interval to be detected in the monitoring data, and the discharge severity is analyzed by integrating the discharge amplitude variation trend, the positioning information, the operation data and the discharge type, so that the analysis result is more accurate, timely and effective early warning is realized, important reference is provided for workers, and the technical problems that the traditional partial discharge monitoring system has incomplete reference factors, cannot effectively diagnose the partial discharge fault of the GIS equipment and cannot perform early warning timely are solved.
Description
Technical Field
The invention relates to the field of power equipment detection, in particular to a GIS equipment partial discharge diagnosis method and system.
Background
GIS equipment has higher fail safe nature, is non-maintaining equipment. However, some insulation defects may be generated during the manufacturing, installation, operation and maintenance of the GIS equipment, resulting in insulation failure. Through GIS partial discharge on-line measuring can help the staff in time to discover the insulation defect of GIS equipment, avoids the emergence of accident, ensures the safe operation of GIS equipment.
Based on the on-line monitoring of partial discharge, a more reasonable operation scheme and a maintenance strategy can be formulated on the basis of fully mastering the actual condition of the equipment, the potential of the equipment is fully excavated under the condition of optimal system safety, the service life and the service life of the equipment are prolonged, and the total life cycle cost of the equipment is reduced.
At present, in a traditional GIS ultrahigh frequency partial discharge online monitoring system, the local discharge fault type is diagnosed with an expert diagnosis database only through information of each sensor, correlation factors such as signal similarity among the sensors and discharge amplitude trend change conditions of the sensors are not comprehensively considered, and in the operation process, the traditional partial discharge monitoring system gradually exposes the defects of inaccurate fault type diagnosis, false alarm, missed alarm and the like, the monitoring effectiveness of the partial discharge monitoring system is seriously influenced, the insulation defect of GIS equipment cannot be timely warned, and the safe and stable operation of the GIS equipment is guaranteed. Therefore, the traditional partial discharge monitoring system has incomplete reference factors, and cannot effectively diagnose the partial discharge fault of the GIS equipment and timely early warn.
Disclosure of Invention
The invention provides a GIS equipment partial discharge diagnosis method and a GIS equipment partial discharge diagnosis system, which solve the technical problems that the traditional partial discharge monitoring system has incomplete reference factors and cannot effectively diagnose partial discharge faults of GIS equipment and early warn in time.
The invention provides a GIS equipment partial discharge diagnosis method, which comprises the following steps:
s1: acquiring sensor monitoring data of at least two ultrahigh frequency sensors at the same interval to be detected in a transformer substation, segmenting and integrating the sensor monitoring data, operating data of the same interval to be detected and environmental data of the same interval to be detected, performing cluster analysis on the segmented and integrated sensor monitoring data through a similarity analysis algorithm, judging whether the sensor monitoring data are from the same signal source and whether the signal source is in the GIS equipment, and if the sensor monitoring data are from the same signal source and the signal source is in the GIS equipment, executing step S2;
s2: determining the area range of the signal source according to the ultrahigh frequency signal amplitude in the sensor monitoring data and the position of the corresponding ultrahigh frequency sensor, further determining the position of the signal source according to the equipment structure information in the production information of the GIS equipment, the same operation data of the interval to be detected and the area range of the signal source, and acquiring the positioning information of the signal source;
s3: the method comprises the steps of carrying out signal analysis on sensor monitoring data, obtaining the discharge amplitude variation trend and the discharge type of the sensor monitoring data, calculating according to positioning information, the discharge amplitude variation trend of the sensor monitoring data, the discharge type of the sensor monitoring data and a first weight coefficient corresponding to the same operation data of an interval to be detected, and determining the discharge severity degree according to the calculation result.
Preferably, step S3 is followed by: step S4;
s4: and calculating the failure probability of the GIS equipment according to the discharge type of the sensor monitoring data, the discharge amplitude variation trend of the sensor monitoring data and a second weight coefficient corresponding to the historical defect failure case in the production information.
Preferably, step S2 specifically includes:
s201: carrying out mirror image modeling and longitudinal comparison according to the ultrahigh frequency signal amplitude in the sensor monitoring data and the position of the corresponding ultrahigh frequency sensor to determine the region range of the signal source;
s202: and further determining the position of the signal source according to the equipment structure information in the production information of the GIS equipment, the same operation data of the interval to be detected and the area range where the signal source is located, and acquiring the positioning information of the signal source.
Preferably, step S1 is preceded by: step S0;
s0: and acquiring production information and operation data of the GIS equipment and sensor monitoring data of all ultrahigh frequency sensors in the transformer substation, and establishing a GIS database.
Preferably, step S0 specifically includes:
s001: acquiring production information and operation data of GIS equipment and sensor monitoring data of all ultrahigh frequency sensors in a transformer substation;
s002: modeling is carried out according to different characteristics of production information and operation data of GIS equipment and sensor monitoring data of all ultrahigh frequency sensors in a transformer substation through a processing mode of filtering and/or conversion and/or combination and/or cutting;
s003: and establishing a GIS database, and importing the processed production information and operation data of the GIS equipment and models of sensor monitoring data of all ultrahigh frequency sensors in the transformer substation into the database for storage.
The invention provides a GIS equipment partial discharge diagnosis system, comprising:
the signal distinguishing module is used for acquiring sensor monitoring data of at least two ultrahigh frequency sensors in the same interval to be detected in the transformer substation, segmenting and integrating the sensor monitoring data, operating data of the same interval to be detected and environment data of the same interval to be detected, performing cluster analysis on the segmented and integrated sensor monitoring data through a similarity analysis algorithm, judging whether the sensor monitoring data come from the same signal source and whether the signal source is in the GIS equipment, and triggering the signal positioning module if the sensor monitoring data come from the same signal source and the signal source is in the GIS equipment;
the signal positioning module is used for determining the area range where the signal source is located according to the ultrahigh frequency signal amplitude in the sensor monitoring data and the position where the corresponding ultrahigh frequency sensor is located, further determining the position of the signal source according to the equipment structure information in the production information of the GIS equipment, the same operation data of the interval to be detected and the area range where the signal source is located, and acquiring the positioning information of the signal source;
and the analysis and judgment module is used for carrying out signal analysis on the sensor monitoring data, acquiring the discharge amplitude variation trend and the discharge type of the sensor monitoring data, calculating according to the positioning information, the discharge amplitude variation trend of the sensor monitoring data, the discharge type of the sensor monitoring data and a first weight coefficient corresponding to the same operation data of the interval to be detected, and determining the discharge severity degree according to the calculation result.
Preferably, the method further comprises the following steps: a failure probability module;
and the fault probability module is used for calculating the fault probability of the GIS equipment according to the discharge type of the sensor monitoring data, the discharge amplitude variation trend of the sensor monitoring data and a second weight coefficient corresponding to the historical defect fault case in the production information.
Preferably, the signal positioning module specifically includes:
the primary positioning sub-module is used for carrying out mirror image modeling and longitudinal comparison according to the ultrahigh frequency signal amplitude in the sensor monitoring data and the position of the corresponding ultrahigh frequency sensor to determine the area range of the signal source;
and the accurate positioning submodule is used for further determining the position of the signal source according to the equipment structure information in the production information of the GIS equipment, the same operation data of the interval to be detected and the area range where the signal source is located, and acquiring the positioning information of the signal source.
Preferably, the method further comprises the following steps: a data acquisition module;
and the data acquisition module is used for acquiring the production information and the operation data of the GIS equipment and the sensor monitoring data of all the ultrahigh frequency sensors in the transformer substation and establishing a GIS database.
Preferably, the data acquisition module specifically includes:
the system comprises an original acquisition submodule and a monitoring submodule, wherein the original acquisition submodule is used for acquiring production information and operation data of GIS equipment and sensor monitoring data of all ultrahigh frequency sensors in a transformer substation;
the processing modeling submodule is used for modeling respectively through a processing mode of filtering and/or conversion and/or combination and/or cutting according to different characteristics of production information and operation data of GIS equipment and sensor monitoring data of all ultrahigh frequency sensors in the transformer substation;
and the data import submodule is used for establishing a GIS database and importing the processed production information and operation data of the GIS equipment and models of sensor monitoring data of all ultrahigh frequency sensors in the transformer substation into the database for storage.
According to the technical scheme, the invention has the following advantages:
the invention provides a GIS equipment partial discharge diagnosis method, which comprises the following steps: s1: acquiring sensor monitoring data of at least two ultrahigh frequency sensors at the same interval to be detected in a transformer substation, segmenting and integrating the sensor monitoring data, operating data of the same interval to be detected and environmental data of the same interval to be detected, performing cluster analysis on the segmented and integrated sensor monitoring data through a similarity analysis algorithm, judging whether the sensor monitoring data are from the same signal source and whether the signal source is in the GIS equipment, and if the sensor monitoring data are from the same signal source and the signal source is in the GIS equipment, executing step S2; s2: determining the area range of the signal source according to the ultrahigh frequency signal amplitude in the sensor monitoring data and the position of the corresponding ultrahigh frequency sensor, further determining the position of the signal source according to the equipment structure information in the production information of the GIS equipment, the same operation data of the interval to be detected and the area range of the signal source, and acquiring the positioning information of the signal source; s3: the method comprises the steps of carrying out signal analysis on sensor monitoring data, obtaining the discharge amplitude variation trend and the discharge type of the sensor monitoring data, calculating according to positioning information, the discharge amplitude variation trend of the sensor monitoring data, the discharge type of the sensor monitoring data and a first weight coefficient corresponding to the same operation data of an interval to be detected, and determining the discharge severity degree according to the calculation result.
The method judges whether the monitoring data of each ultrahigh frequency sensor at the same interval are from the same signal source by carrying out similarity analysis on the monitoring data of each ultrahigh frequency sensor at the same interval, avoids that each ultrahigh frequency sensor makes wrong judgments on the severity and fault types of the partial discharge due to the interference of a plurality of signal sources, judges whether the ultrahigh frequency sensor is an internal fault of GIS equipment, and avoids false alarm due to external fault; the method has the advantages that the occurrence position of the partial discharge is accurately positioned according to the ultrahigh frequency signal amplitude, the equipment structure information and the same operation data of the interval to be detected in the monitoring data, and the discharge severity is analyzed by integrating the discharge amplitude variation trend, the positioning information, the operation data and the discharge type, so that the analysis result is more accurate, timely and effective early warning is realized, important reference is provided for workers, and the technical problems that the traditional partial discharge monitoring system has incomplete reference factors, cannot effectively diagnose the partial discharge fault of the GIS equipment and cannot perform early warning timely are solved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without inventive exercise.
Fig. 1 is a schematic flowchart of an embodiment of a partial discharge diagnosis method for a GIS device according to an embodiment of the present invention;
fig. 2 is a schematic flowchart of a partial discharge diagnostic method for a GIS device according to another embodiment of the present invention;
fig. 3 is a schematic connection relationship diagram of an embodiment of a partial discharge diagnosis system for GIS equipment according to an embodiment of the present invention;
fig. 4 is a schematic connection relationship diagram of another embodiment of a GIS device partial discharge diagnosis system according to an embodiment of the present invention.
Detailed Description
The embodiment of the invention provides a GIS device partial discharge diagnosis method and a GIS device partial discharge diagnosis system, and solves the technical problems that a traditional partial discharge monitoring system has incomplete reference factors and cannot effectively diagnose GIS device partial discharge faults and early warn in time.
In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the embodiments described below are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, an embodiment of the present invention provides an embodiment of a method for diagnosing partial discharge of a GIS device, including:
step 101: acquiring sensor monitoring data of at least two ultrahigh frequency sensors at the same interval to be detected in a transformer substation, segmenting and integrating the sensor monitoring data, operating data of the same interval to be detected and environmental data of the same interval to be detected, performing cluster analysis on the segmented and integrated sensor monitoring data through a similarity analysis algorithm, judging whether the sensor monitoring data come from the same signal source and whether the signal source is in the GIS equipment, and if the sensor monitoring data come from the same signal source and the signal source is in the GIS equipment, executing step 102;
it should be noted that, in the design and construction of the transformer substation, the transformer substation is formed by respectively combining parts such as an incoming line, a main transformer high voltage, a main transformer low voltage, a main transformer, a low voltage outgoing line and the like, and each part is called an interval;
for example, the incoming line interval is formed by combining a line side grounding switch, a line side disconnecting link, a switch side grounding switch, a bus side disconnecting link and a bus grounding switch from a cable head at the end of a line, and all electrical equipment form the incoming line interval;
by carrying out similarity calculation on sensor monitoring data of the same ultrahigh frequency sensor to be detected at intervals, whether signals monitored by each sensor are from the same signal source can be distinguished, and misjudgment on the local amplification severity and fault type caused by interference of a plurality of signal sources of each ultrahigh frequency sensor is avoided;
meanwhile, whether the internal fault of the GIS equipment exists or not is judged, and false alarm caused by external fault is avoided.
Step 102: determining the area range of the signal source according to the ultrahigh frequency signal amplitude in the sensor monitoring data and the position of the corresponding ultrahigh frequency sensor, further determining the position of the signal source according to the equipment structure information in the production information of the GIS equipment, the same operation data of the interval to be detected and the area range of the signal source, and acquiring the positioning information of the signal source;
the partial discharge is an electrical breakdown of a partial region in the electrical insulation, accompanied by neutralization of positive and negative charges, thereby generating electromagnetic transients and electromagnetic waves in a wide frequency band;
the electric breakdown process of different types of partial discharge is different, and pulse currents with different amplitudes and steepnesses are generated, so that electromagnetic transient states and electromagnetic waves with different frequency components are generated. The spatial positioning of a partial discharge source can be realized by adopting ultrahigh frequency measurement, the attenuation is faster in the transmission process of ultrahigh frequency signals, and the amplitude of the detected discharge signal is obviously reduced along with the increase of the distance from the discharge source, so that the approximate positioning of discharge can be carried out by comparing the amplitudes of the ultrahigh frequency signals;
the ultrahigh frequency electromagnetic pulse of the partial discharge has a rising edge of ns time magnitude, a plurality of ultrahigh frequency sensors are adopted for simultaneous measurement, the pulse time difference of ns magnitude accuracy can be obtained, and the discharge source can be accurately positioned based on the time difference measurement;
meanwhile, the position of the partial discharge in the GIS equipment can be accurately positioned by combining the ultrahigh frequency signal amplitude, the equipment structure information and the same operation data of the interval to be detected in the monitoring data.
Step 103: the method comprises the steps of carrying out signal analysis on sensor monitoring data, obtaining the discharge amplitude variation trend and the discharge type of the sensor monitoring data, calculating according to positioning information, the discharge amplitude variation trend of the sensor monitoring data, the discharge type of the sensor monitoring data and a first weight coefficient corresponding to the same operation data of an interval to be detected, and determining the discharge severity degree according to the calculation result.
It should be noted that, the conventional partial discharge monitoring system only refers to the monitoring data of the ultrahigh frequency sensor, which easily causes the problems of inaccurate fault type diagnosis, false alarm, missed alarm, and the like, and seriously affects the monitoring effectiveness of the online monitoring system for the GIS partial discharge, and cannot timely warn the insulation defect of the GIS equipment and ensure the safe and stable operation of the GIS equipment;
according to the invention, the occurrence position of partial discharge, the variation trend of the discharge amplitude, the discharge type and the operation data are comprehensively considered, and a plurality of data sources are fused to judge the discharge severity, so that the problems of inaccurate fault type diagnosis, false alarm, missing alarm and the like are avoided, the effectiveness of GIS partial discharge monitoring is improved, the insulation defect of GIS equipment is timely warned in advance, and the safe and stable operation of the GIS equipment is ensured;
the technical problems that the reference factors of a traditional partial discharge monitoring system are not comprehensive, partial discharge faults of GIS equipment cannot be effectively diagnosed, and early warning cannot be timely achieved are solved.
The above is an embodiment of a partial discharge diagnostic method for a GIS device provided by the present invention, and the following is another embodiment of a partial discharge diagnostic method for a GIS device provided by the present invention.
Referring to fig. 2, another embodiment of a partial discharge diagnosis method for a GIS device according to the present invention includes:
step 201: acquiring production information and operation data of GIS equipment and sensor monitoring data of all ultrahigh frequency sensors in a transformer substation;
the production information includes manufacturing parameters of the GIS equipment, equipment structure information, historical defect fault cases of the GIS equipment of the corresponding manufacturer, and the like;
the operation data are various electrical data and non-electrical data monitored in the working operation of the GIS equipment.
Step 202: modeling is carried out according to different characteristics of production information and operation data of GIS equipment and sensor monitoring data of all ultrahigh frequency sensors in a transformer substation through a processing mode of filtering and/or conversion and/or combination and/or cutting;
it should be noted that if the data of various data sources are not processed and modeled respectively, the subsequent calling is more complicated, and after the data of various data sources are processed and modeled respectively, the data can be directly called in the subsequent flow by calling the data model;
for example: and filtering the data with larger deviation, converting various data into values under the unified standard for comparison, and cutting and recombining the data.
Step 203: establishing a GIS database, and importing the processed production information and operation data of the GIS equipment and models of sensor monitoring data of all ultrahigh frequency sensors in the transformer substation into the database for storage;
it should be noted that the database can be used for uniformly managing the data of a plurality of data sources;
the database can provide a dragging type and interactive intuitive mode for data operation.
Step 204: acquiring sensor monitoring data of at least two ultrahigh frequency sensors at the same interval to be detected in a transformer substation, segmenting and integrating the sensor monitoring data, operating data of the same interval to be detected and environmental data of the same interval to be detected, performing cluster analysis on the segmented and integrated sensor monitoring data through a similarity analysis algorithm, judging whether the sensor monitoring data are from the same signal source and whether the signal source is in the GIS equipment, and if the sensor monitoring data are from the same signal source and the signal source is in the GIS equipment, executing step 205;
it should be noted that, if the signal source is not inside the GIS device, it may also be determined whether the signal source is generated by partial discharge of other devices, and the approximate direction of the signal source is estimated and the worker is prompted.
Step 205: carrying out mirror image modeling and longitudinal comparison according to the ultrahigh frequency signal amplitude in the sensor monitoring data and the position of the corresponding ultrahigh frequency sensor to determine the region range of the signal source;
step 206: further determining the position of the signal source according to equipment structure information in the production information of the GIS equipment, the same operation data of the interval to be detected and the area range where the signal source is located, and acquiring the positioning information of the signal source;
step 207: performing signal analysis on the sensor monitoring data, acquiring the discharge amplitude variation trend and the discharge type of the sensor monitoring data, calculating according to the positioning information, the discharge amplitude variation trend of the sensor monitoring data, the discharge type of the sensor monitoring data and a first weight coefficient corresponding to the same operation data of an interval to be detected, and determining the discharge severity degree according to the calculation result;
it should be noted that, in this embodiment, a reference standard and a first weight coefficient are preset for the positioning information, the discharge amplitude variation trend of the sensor monitoring data, the discharge type of the sensor monitoring data, and the operation data of the same interval to be detected, and the positioning information, the discharge amplitude variation trend of the sensor monitoring data, the discharge type of the sensor monitoring data, and the operation data of the same interval to be detected may respectively obtain corresponding first weight coefficients according to the reference standard, perform calculation according to the corresponding first weight coefficients, and determine the discharge severity according to the calculation result.
Step 208: and calculating the failure probability of the GIS equipment according to the discharge type of the sensor monitoring data, the discharge amplitude variation trend of the sensor monitoring data and a second weight coefficient corresponding to the historical defect failure case in the production information.
It should be noted that the occurrence of partial discharge of the GIS device does not mean that a fault has occurred certainly, so that the probability of the occurrence of the fault of the GI device can be further calculated by using the second weight coefficient in combination with data such as a historical defect fault case after the severity of discharge is determined, thereby providing an important reference basis for a worker to make a maintenance plan;
the traditional partial discharge monitoring system only refers to the monitoring data of an ultrahigh frequency sensor, so that the problems of inaccurate fault type diagnosis, false alarm, missing alarm and the like are easily caused, the monitoring effectiveness of the GIS partial discharge online monitoring system is seriously influenced, and the insulation defect of GIS equipment cannot be early warned in time and the safe and stable operation of the GIS equipment cannot be guaranteed;
the invention comprehensively considers the occurrence position of partial discharge, the variation trend of the discharge amplitude, the discharge type and the operation data, integrates the field operation condition, and fuses and judges the discharge severity degree by various data sources, thereby avoiding the problems of inaccurate fault type diagnosis, false alarm, missing alarm and the like, improving the effectiveness of GIS partial discharge monitoring, timely early warning the insulation defect of GIS equipment and ensuring the safe and stable operation of the GIS equipment;
the invention is particularly suitable for the identification of the discharge signal and the interference signal, the judgment of the discharge severity and the GIS equipment fault prediction, has good application effect on the judgment of the discontinuous signal when the on-site interference signal is larger, integrates multidimensional data such as monitoring, operation and production and the like, and has obvious advantages on the identification of the interference signal and the judgment of the discharge severity;
the technical problems that the reference factors of a traditional partial discharge monitoring system are not comprehensive, partial discharge faults of GIS equipment cannot be effectively diagnosed, and early warning cannot be timely achieved are solved.
The above is another embodiment of the partial discharge diagnosis method for the GIS device provided by the present invention, and the following is an embodiment of a partial discharge diagnosis system for the GIS device provided by the present invention.
Referring to fig. 3, an embodiment of a partial discharge diagnostic system for a GIS device according to the present invention includes:
the signal distinguishing module 301 is configured to acquire sensor monitoring data of at least two ultrahigh-frequency sensors in the same interval to be detected in the substation, divide and integrate the sensor monitoring data, the operating data of the same interval to be detected and the environmental data of the same interval to be detected, perform cluster analysis on the divided and integrated sensor monitoring data through a similarity analysis algorithm, determine whether the sensor monitoring data are from the same signal source and whether the signal source is inside the GIS device, and trigger the signal positioning module 302 if the sensor monitoring data are from the same signal source and the signal source is inside the GIS device;
the signal positioning module 302 is configured to determine an area range where the signal source is located according to the ultrahigh frequency signal amplitude in the sensor monitoring data and the location where the corresponding ultrahigh frequency sensor is located, further determine the location of the signal source according to the equipment structure information in the production information of the GIS equipment, the same operation data of the interval to be detected, and the area range where the signal source is located, and acquire positioning information of the signal source;
the analyzing and judging module 303 is configured to perform signal analysis on the sensor monitoring data, obtain a discharge amplitude variation trend and a discharge type of the sensor monitoring data, perform calculation according to the positioning information, the discharge amplitude variation trend of the sensor monitoring data, the discharge type of the sensor monitoring data, and a first weight coefficient corresponding to the same operation data of the interval to be detected, and determine the discharge severity according to a calculation result.
The above is an embodiment of a GIS device partial discharge diagnostic system provided by the present invention, and the following is another embodiment of a GIS device partial discharge diagnostic system provided by the present invention.
Referring to fig. 4, another embodiment of a partial discharge diagnostic system for a GIS device according to the present invention includes:
the signal distinguishing module 401 is configured to acquire sensor monitoring data of at least two ultrahigh-frequency sensors in a same interval to be detected in a transformer substation, divide and integrate the sensor monitoring data, operating data of the same interval to be detected and environmental data of the same interval to be detected, perform cluster analysis on the divided and integrated sensor monitoring data through a similarity analysis algorithm, determine whether the sensor monitoring data are from the same signal source and whether the signal source is inside the GIS device, and trigger the signal positioning module 402 if the sensor monitoring data are from the same signal source and the signal source is inside the GIS device;
the signal positioning module 402 is configured to determine an area range where the signal source is located according to the ultrahigh frequency signal amplitude in the sensor monitoring data and the location of the corresponding ultrahigh frequency sensor, further determine the location of the signal source according to the equipment structure information in the production information of the GIS equipment, the same operation data of the interval to be detected, and the area range where the signal source is located, and acquire positioning information of the signal source;
the analyzing and judging module 403 is configured to perform signal analysis on the sensor monitoring data, obtain a discharge amplitude variation trend and a discharge type of the sensor monitoring data, perform calculation according to the positioning information, the discharge amplitude variation trend of the sensor monitoring data, the discharge type of the sensor monitoring data, and a first weight coefficient corresponding to the same operation data of the interval to be detected, and determine a discharge severity according to a calculation result.
Further, still include: a failure probability module 404;
and the failure probability module 404 is configured to calculate a failure probability of the GIS device according to the discharge type of the sensor monitoring data, the discharge amplitude variation trend of the sensor monitoring data, and a second weight coefficient corresponding to the historical defect failure case in the production information.
Further, the signal positioning module 402 specifically includes:
the preliminary positioning sub-module 4021 is used for performing mirror modeling and longitudinal comparison according to the ultrahigh frequency signal amplitude in the sensor monitoring data and the position of the corresponding ultrahigh frequency sensor to determine the area range of the signal source;
the accurate positioning sub-module 4022 is configured to further determine the position of the signal source according to the device structure information in the production information of the GIS device, the same operation data of the interval to be detected, and the region range where the signal source is located, and acquire the positioning information of the signal source.
Further, still include: a data acquisition module 400;
and the data acquisition module 400 is used for acquiring production information and operation data of the GIS equipment and sensor monitoring data of all ultrahigh frequency sensors in the transformer substation, and establishing a GIS database.
Further, the data obtaining module 400 specifically includes:
the original acquisition submodule 4001 is used for acquiring production information and operation data of the GIS equipment and sensor monitoring data of all ultrahigh frequency sensors in the transformer substation;
the processing modeling submodule 4002 is used for modeling respectively through a processing mode of filtering and/or conversion and/or combination and/or cutting according to different characteristics of production information and operation data of GIS equipment and sensor monitoring data of all ultrahigh frequency sensors in the transformer substation;
and the data import sub-module 4003 is used for establishing a GIS database, and importing the processed production information and operation data of the GIS equipment and models of sensor monitoring data of all ultrahigh frequency sensors in the transformer substation into the database for storage.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the system and the module described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system and method may be implemented in other ways. For example, the above-described system embodiments are merely illustrative, and for example, the division of the modules is merely a logical division, and in actual implementation, there may be other divisions, for example, multiple modules or components may be combined or integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, systems or modules, and may be in an electrical, mechanical or other form.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical modules, may be located in one place, or may be distributed on a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
In addition, functional modules in the embodiments of the present invention may be integrated into one processing module, or each of the modules may exist alone physically, or two or more modules are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode.
The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (8)
1. A GIS device partial discharge diagnosis method is characterized by comprising the following steps:
s1: acquiring sensor monitoring data of at least two ultrahigh frequency sensors at the same interval to be detected in a transformer substation, segmenting and integrating the sensor monitoring data, operating data of the same interval to be detected and environmental data of the same interval to be detected, performing cluster analysis on the segmented and integrated sensor monitoring data through a similarity analysis algorithm, judging whether the sensor monitoring data are from the same signal source and whether the signal source is in the GIS equipment, and if the sensor monitoring data are from the same signal source and the signal source is in the GIS equipment, executing step S2;
s2: carrying out mirror image modeling and longitudinal comparison according to the ultrahigh frequency signal amplitude in the sensor monitoring data and the position of the corresponding ultrahigh frequency sensor to determine the area range of the signal source, further determining the position of the signal source according to the equipment structure information in the production information of the GIS equipment, the same operation data of the interval to be detected and the area range of the signal source, and acquiring the positioning information of the signal source;
s3: and performing signal analysis on the sensor monitoring data to obtain the discharge amplitude variation trend and the discharge type of the sensor monitoring data, calculating according to the weight coefficients respectively corresponding to the positioning information, the discharge amplitude variation trend of the sensor monitoring data, the discharge type of the sensor monitoring data and the same operation data of the interval to be detected, and determining the discharge severity degree according to the calculation result.
2. The partial discharge diagnosis method for the GIS device according to claim 1, wherein the step S3 is followed by further comprising: step S4;
s4: and calculating the fault probability of the GIS equipment according to the discharge type of the sensor monitoring data, the discharge amplitude variation trend of the sensor monitoring data and the weight coefficient corresponding to the historical defect fault case in the production information.
3. The partial discharge diagnosis method for the GIS device according to claim 1, wherein step S1 is preceded by: step S0;
s0: and acquiring production information and operation data of the GIS equipment and sensor monitoring data of all ultrahigh frequency sensors in the transformer substation, and establishing a GIS database.
4. The GIS device partial discharge diagnosis method according to claim 3, wherein step S0 specifically includes:
s001: acquiring production information and operation data of GIS equipment and sensor monitoring data of all ultrahigh frequency sensors in a transformer substation;
s002: modeling is carried out according to different characteristics of production information and operation data of GIS equipment and sensor monitoring data of all ultrahigh frequency sensors in a transformer substation through a processing mode of filtering and/or conversion and/or combination and/or cutting;
s003: and establishing a GIS database, and importing the processed production information and operation data of the GIS equipment and models of sensor monitoring data of all ultrahigh frequency sensors in the transformer substation into the database for storage.
5. A partial discharge diagnostic system for a GIS device, comprising:
the signal distinguishing module is used for acquiring sensor monitoring data of at least two ultrahigh frequency sensors in the same interval to be detected in the transformer substation, segmenting and integrating the sensor monitoring data, operating data of the same interval to be detected and environment data of the same interval to be detected, performing cluster analysis on the segmented and integrated sensor monitoring data through a similarity analysis algorithm, judging whether the sensor monitoring data come from the same signal source and whether the signal source is in the GIS equipment, and triggering the signal positioning module if the sensor monitoring data come from the same signal source and the signal source is in the GIS equipment;
the signal positioning module comprises a primary positioning submodule and an accurate positioning submodule, wherein the primary positioning submodule is used for carrying out mirror image modeling and longitudinal comparison according to the ultrahigh frequency signal amplitude in the sensor monitoring data and the position of the corresponding ultrahigh frequency sensor to determine the area range of the signal source, and the accurate positioning submodule further determines the position of the signal source according to the equipment structure information in the production information of the GIS equipment, the same operation data of the interval to be detected and the area range of the signal source to acquire the positioning information of the signal source;
and the analysis and judgment module is used for carrying out signal analysis on the sensor monitoring data, acquiring the discharge amplitude variation trend and the discharge type of the sensor monitoring data, calculating according to the weight coefficients respectively corresponding to the positioning information, the discharge amplitude variation trend of the sensor monitoring data, the discharge type of the sensor monitoring data and the same operation data of the interval to be detected, and determining the discharge severity degree according to the calculation result.
6. The GIS device partial discharge diagnostic system of claim 5, further comprising: a failure probability module;
and the fault probability module is used for calculating the fault probability of the GIS equipment according to the discharge type of the sensor monitoring data, the discharge amplitude variation trend of the sensor monitoring data and the weight coefficient corresponding to the historical defect fault case in the production information.
7. The GIS device partial discharge diagnostic system of claim 5, further comprising: a data acquisition module;
and the data acquisition module is used for acquiring the production information and the operation data of the GIS equipment and the sensor monitoring data of all the ultrahigh frequency sensors in the transformer substation and establishing a GIS database.
8. The partial discharge diagnostic system of the GIS device according to claim 7, wherein the data acquisition module specifically includes:
the system comprises an original acquisition submodule and a monitoring submodule, wherein the original acquisition submodule is used for acquiring production information and operation data of GIS equipment and sensor monitoring data of all ultrahigh frequency sensors in a transformer substation;
the processing modeling submodule is used for modeling respectively through a processing mode of filtering and/or conversion and/or combination and/or cutting according to different characteristics of production information and operation data of GIS equipment and sensor monitoring data of all ultrahigh frequency sensors in the transformer substation;
and the data import submodule is used for establishing a GIS database and importing the processed production information and operation data of the GIS equipment and models of sensor monitoring data of all ultrahigh frequency sensors in the transformer substation into the database for storage.
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