CN114460520A - Method and system for diagnosing equipment state of capacitive voltage transformer - Google Patents
Method and system for diagnosing equipment state of capacitive voltage transformer Download PDFInfo
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- 238000012544 monitoring process Methods 0.000 claims abstract description 80
- 230000002159 abnormal effect Effects 0.000 claims abstract description 53
- 239000003990 capacitor Substances 0.000 claims abstract description 46
- 238000001514 detection method Methods 0.000 claims abstract description 33
- 238000003745 diagnosis Methods 0.000 claims description 24
- 230000005856 abnormality Effects 0.000 claims description 15
- 238000007405 data analysis Methods 0.000 claims description 6
- 238000011156 evaluation Methods 0.000 claims description 6
- 238000002405 diagnostic procedure Methods 0.000 claims 2
- 238000012423 maintenance Methods 0.000 abstract description 11
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- 238000009413 insulation Methods 0.000 description 2
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- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical group [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R35/00—Testing or calibrating of apparatus covered by the other groups of this subclass
- G01R35/02—Testing or calibrating of apparatus covered by the other groups of this subclass of auxiliary devices, e.g. of instrument transformers according to prescribed transformation ratio, phase angle, or wattage rating
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Abstract
The invention discloses a method and a system for diagnosing the state of a capacitor voltage transformer device, which are characterized in that monitoring indexes of different detection points of the capacitor voltage transformer device are collected, whether monitoring data are abnormal or not is judged through an abnormal model, then the state of the capacitor voltage transformer device is further diagnosed through a fault model and a parameter model when the monitoring data are abnormal, a large amount of comparison operation in the use of the fault model is saved, the fault is analyzed and judged through the monitoring indexes, the fault reason is accurately found out, the real-time monitoring of the capacitor voltage transformer and the healthy running state are realized, and maintenance personnel can more accurately obtain detailed information of fault types, grades and the like and make corresponding emergency maintenance measures.
Description
Technical Field
The invention relates to equipment state diagnosis, in particular to a method and a system for diagnosing the equipment state of a capacitor voltage transformer.
Background
The voltage transformer is one of indispensable main devices for normal operation, monitoring, metering, protection, control and the like of a power grid. The voltage transformers mainly used in the power grid are divided into a capacitor voltage transformer and an electromagnetic voltage transformer, along with the increase of power transmission distance and voltage of the power grid, the required electromagnetic voltage transformer is larger and larger in size, higher in cost and not suitable for high-voltage long-distance power transmission grid, the capacitor voltage transformer has the advantages of being simple in structure, economical and safe, small in maintenance workload, high in insulation reliability and the like, the capacitor voltage transformer is widely applied to the power system, the measurement result of the capacitor voltage transformer is an important basis for normal work of secondary metering, relay protection, monitoring equipment and the like, and the capacitor voltage transformer is vital to safe and stable operation of the power grid.
On the other hand, due to the strictly sealed manufacturing process of the capacitor voltage transformer and the complex operating environment, in the actual operating process, the capacitor breakdown, oil leakage, abnormal sound and other operating faults often occur, and once the capacitor voltage transformer fails and operates in an abnormal state, the safe operation of the power system is seriously affected.
Therefore, the capacitor voltage transformer needs to be monitored in real time, the healthy running state of the capacitor voltage transformer equipment is evaluated in real time, when the capacitor voltage transformer breaks down, the fault can be immediately checked, the fault reason can be accurately found out, the fault is alarmed, and maintenance personnel can obtain and master the information and the fault reason of the capacitor voltage transformer which breaks down more quickly.
Disclosure of Invention
The invention provides a method and a system for diagnosing the equipment state of a capacitor voltage transformer, which are used for solving the technical problem of how to monitor the capacitor voltage transformer in real time and evaluate the healthy running state in real time.
In order to solve the technical problems, the technical scheme provided by the invention is as follows: a method for diagnosing the state of a capacitor voltage transformer device comprises the following steps:
collecting monitoring indexes of different detection points of the capacitive voltage transformer equipment;
setting an abnormal threshold value of the monitoring index through the abnormal model, and comparing each monitoring index with the abnormal threshold value for judging whether to carry out fault diagnosis or not;
through the fault model, the fault model is provided with various fault types, and index combinations and index ranges corresponding to the fault types, and the monitoring indexes are compared with all indexes in the fault model for fault diagnosis;
and setting a normal index and a fault index range for the monitoring index by the parameter model through the parameter model, and comparing the monitoring index with each index in the parameter model for fault degree evaluation.
Preferably, the abnormality threshold includes an upper abnormality limit and a lower abnormality limit, and the fault diagnosis is performed when each monitoring index exceeds the upper abnormality limit or the lower abnormality limit.
Preferably, a fault level is set for each fault type, a corresponding level index range is set for each fault level, and each monitored fault data is compared with the level index range to judge the level of the fault.
Preferably, detection indexes of different detection points of the capacitor voltage transformer device are collected through different intelligent sensors.
Preferably, the detection indexes include a plurality of detection indexes such as a capacitance value, an internal temperature, humidity of an operating environment, and vibration intensity.
The embodiment of the invention also provides a system for diagnosing the state of the capacitive voltage transformer equipment, which comprises the following components:
the data acquisition module is used for collecting monitoring indexes of different detection points of the capacitive voltage transformer equipment;
a data analysis module, the data analysis module comprising:
the abnormal model is used for setting an abnormal threshold value of the monitoring index, comparing each monitoring index with the abnormal threshold value and judging whether to carry out fault diagnosis or not;
the fault model is provided with various fault types, index combinations and index ranges corresponding to the fault types, and the monitoring indexes are compared with the indexes in the fault model for fault diagnosis;
and the parameter model sets normal indexes and fault index ranges for the monitoring indexes, and compares the monitoring indexes with all indexes in the parameter model for fault degree evaluation.
Preferably, the abnormality threshold includes an upper abnormality limit and a lower abnormality limit, and the fault diagnosis is performed when each monitoring index exceeds the upper abnormality limit or the lower abnormality limit.
Preferably, the parameter model sets a fault level for each fault type, sets a corresponding level index range for each fault level, compares each monitored fault data with the level index range, and judges the level of the fault.
Preferably, the data acquisition module collects detection indexes of different detection points of the capacitor voltage transformer device through different intelligent sensors.
Preferably, the detection indexes include a plurality of detection indexes of capacitance value, internal temperature, humidity of operating environment and vibration intensity.
The invention has the following beneficial effects:
the invention provides a method and a system for diagnosing the state of a capacitor voltage transformer device, which are characterized in that monitoring indexes of different detection points of the capacitor voltage transformer device are collected, whether monitoring data are abnormal or not is judged through an abnormal model, and then the state of the capacitor voltage transformer device is further diagnosed through a fault model and a parameter model when the monitoring data are abnormal, so that a large amount of comparison operation in the use of the fault model is saved, the fault is analyzed and judged through the monitoring indexes, the fault reason is accurately found out, the real-time monitoring of the capacitor voltage transformer and the healthy running state are realized, and a maintenance worker can more accurately obtain detailed information of fault types, grades and the like and make corresponding emergency maintenance measures.
In addition to the objects, features and advantages described above, other objects, features and advantages of the present invention are also provided. The present invention will be described in further detail below with reference to the accompanying drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
FIG. 1 is a schematic diagram of a method for diagnosing the condition of a capacitive voltage transformer apparatus in accordance with a preferred embodiment of the present invention;
Detailed Description
The embodiments of the invention will be described in detail below with reference to the drawings, but the invention can be implemented in many different ways as defined and covered by the claims.
Example 1:
referring to fig. 1, a method for diagnosing the state of a capacitive voltage transformer device includes:
s1, collecting monitoring indexes of different detection points of the capacitive voltage transformer equipment;
s2, setting an abnormal threshold value of the monitoring index through an abnormal model, comparing each monitoring index with the abnormal threshold value, and judging whether to carry out fault diagnosis;
s3, comparing the monitoring index with each index in the fault model through a fault model which is provided with various fault types and index combinations and index ranges corresponding to the fault types for fault diagnosis to obtain the fault types;
s4, setting normal indexes and fault index ranges for the monitoring indexes through a parameter model, and comparing the monitoring indexes with all indexes in the parameter model for fault degree evaluation.
During implementation, the fault type and the index combination and the index range corresponding to the fault type can be set through historical experience, network data, parameter setting of the capacitive voltage transformer and other data.
In this embodiment, the abnormal threshold includes an abnormal upper limit and an abnormal lower limit, and when each monitoring index exceeds the abnormal upper limit or the abnormal lower limit, fault diagnosis is performed.
It should be noted that, if the monitoring indexes are directly compared with the indexes in the fault model after the monitoring indexes are collected, a large number of comparison operations are performed for the index combinations and index ranges corresponding to the fault types, whether each index is abnormal or not is judged through the abnormal model, and the fault model is used for fault diagnosis when the indexes are abnormal, so as to obtain the fault types.
During implementation, monitoring indexes of the capacitor voltage transformer equipment are collected in real time, the monitoring indexes are used for conducting state diagnosis on the capacitor voltage transformer equipment, after fault types are judged through the fault models, fault diagnosis is conducted through the fault models through multiple groups of historical monitoring indexes, a group of historical monitoring indexes which can judge the fault types of the capacitor voltage transformer firstly in terms of time can be obtained, and therefore the time of fault occurrence is obtained. And obtaining the fault grade corresponding to each group of data by using the monitoring data from a group of historical monitoring indexes which can firstly judge the fault type of the capacitor voltage transformer to the current moment, thereby obtaining the change trend of the fault grade from the fault occurrence moment to the current moment and judging the acceleration of the fault grade.
It should be noted that the capacitor voltage transformers are often found in the power grid, so that a situation that a plurality of capacitor voltage transformers have a fault at the same time may exist, and the emergency degree of the plurality of capacitor voltage transformers needing to be maintained can be judged by integrating the fault type, the fault level and the acceleration of the fault level.
In an optional scheme of this embodiment, a normal index range of the capacitor voltage transformer may be referred to when the abnormal upper limit and the abnormal lower limit are set, but in actual implementation, an index combination and an index range corresponding to a fault type set in the fault model may not intersect with the normal index range of the capacitor voltage transformer, for example, in the normal index range, the internal temperature of the capacitor voltage transformer is less than or equal to 75 ℃ and belongs to the normal index range, and when the internal temperature of the capacitor voltage transformer is set in the fault model to be greater than 80 ℃, it is determined that insulation between iron core pieces is damaged, so that when the abnormal upper limit and the abnormal lower limit are set, the index combination and the index range corresponding to the fault type set in the fault model may also be referred to.
In this embodiment, a fault level is set for each fault type, a corresponding level index range is set for each fault level, and each monitored fault data is compared with the level index range to determine the level of the fault.
In this embodiment, detection indexes of different detection points of the capacitor voltage transformer device are collected by different intelligent sensors.
The intelligent sensor comprises a capacitance value monitoring module, an internal temperature monitoring module, an operating environment humidity monitoring module, a vibration intensity monitoring module, an insulating oil level monitoring module, an insulating oil temperature monitoring module, a capacitive divider voltage monitoring module, an intermediate transformer voltage monitoring module, a secondary side voltage monitoring module and an internal current data monitoring module.
In this embodiment, the detection indicators include a plurality of detection indicators of a capacitance value, an internal temperature, a humidity of an operating environment, and a vibration intensity.
According to the scheme, the abnormal model, the fault model and the parameter model are compared in sequence, then the obtained result can be transmitted to maintenance personnel or uploaded to the cloud platform for the maintenance personnel to give an alarm through a communication means, the cloud platform can also provide a basis for realizing the function of providing a report form for monitoring the data change curve, and the communication means is mobile communication, the Internet of things, a wireless network, optical fiber communication and the like.
During implementation, the monitoring indexes can be uploaded to the cloud platform, and fault diagnosis is performed on the monitoring indexes by using the computing capacity of the cloud platform, the abnormal model, the fault model and the parameter model.
During implementation, fault grades are divided for different fault types, the status indicator lamp is connected with the capacitor voltage transformer, and when the capacitor voltage transformer has a fault, the status indicator lamp is turned on to warn maintenance personnel or workers.
Example 2:
a capacitive voltage transformer device condition diagnostic system comprising:
the data acquisition module is used for collecting monitoring indexes of different detection points of the capacitive voltage transformer equipment;
a data analysis module, the data analysis module comprising:
the abnormal model is used for setting an abnormal threshold value of the monitoring index, comparing each monitoring index with the abnormal threshold value and judging whether to carry out fault diagnosis or not;
the fault model is provided with various fault types, index combinations and index ranges corresponding to the fault types, and the monitoring indexes are compared with the indexes in the fault model for fault diagnosis;
and the parameter model is used for setting normal indexes and fault index ranges for the monitoring indexes, and comparing the monitoring indexes with all indexes in the parameter model for fault degree evaluation.
In this embodiment, the abnormal threshold includes an abnormal upper limit and an abnormal lower limit, and when each monitoring index exceeds the abnormal upper limit or the abnormal lower limit, fault diagnosis is performed.
In this embodiment, the parameter model sets a fault level for each fault type, sets a corresponding level index range for each fault level, compares each monitored fault data with the level index range, and determines the level of the fault.
In this embodiment, the data acquisition module collects detection indexes of different detection points of the capacitor voltage transformer device through different intelligent sensors.
In this embodiment, the detection indexes include a plurality of detection indexes such as a capacitance value, an internal temperature, humidity of an operating environment, and vibration intensity.
In implementation, the system for diagnosing the state of the capacitive voltage transformer device in this scheme further includes another memory, a processor, and a computer program stored in the memory and capable of running on the processor, so that the method in embodiment 1 can be implemented, and the same beneficial effects can be achieved, which is not described herein again.
In summary, the method and the system for diagnosing the state of the capacitive voltage transformer equipment collect monitoring indexes of different detection points of the capacitive voltage transformer equipment, judge whether monitoring data are abnormal or not through an abnormal model, and further diagnose the state of the capacitive voltage transformer equipment through a fault model and a parameter model when the monitoring data are abnormal, so that a large amount of comparison operation during the use of the fault model is saved, the fault type is analyzed and judged through the monitoring indexes, the fault reason is accurately found out, the real-time monitoring of the capacitive voltage transformer and the healthy running state are realized, and maintenance personnel can more accurately obtain detailed information of the fault type, the grade and the like and make corresponding emergency maintenance measures.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method for diagnosing the state of a capacitor voltage transformer device is characterized by comprising the following steps:
collecting monitoring indexes of different detection points of the capacitive voltage transformer equipment;
setting an abnormal threshold value of the monitoring index through an abnormal model, and comparing each monitoring index with the abnormal threshold value for judging whether to carry out fault diagnosis or not;
comparing the monitoring index with each index in the fault model through the fault model, wherein the fault model is provided with various fault types, and index combinations and index ranges corresponding to the fault types for fault diagnosis;
and setting a normal index and a fault index range for the monitoring index by the parameter model through the parameter model, and comparing the monitoring index with each index in the parameter model for fault degree evaluation.
2. The apparatus state diagnosis method according to claim 1, wherein the abnormal threshold includes an upper abnormal limit and a lower abnormal limit, and the fault diagnosis is performed when each monitoring index exceeds the upper abnormal limit or the lower abnormal limit.
3. The apparatus state diagnostic method according to claim 1, wherein a fault level is set for each fault type, a corresponding level index range is set for each fault level, and each monitored fault data is compared with the level index range to determine the level of the fault.
4. The method for diagnosing the state of the capacitor voltage transformer equipment as recited in claim 1, wherein detection indexes of different detection points of the capacitor voltage transformer equipment are collected by different intelligent sensors.
5. The apparatus state diagnostic method according to claim 1, wherein the detection indicators include a plurality of detection indicators such as a capacitance value, an internal temperature, a humidity and a vibration intensity of an operating environment.
6. A capacitive voltage transformer device condition diagnostic system, comprising:
the data acquisition module is used for collecting monitoring indexes of different detection points of the capacitive voltage transformer equipment;
a data analysis module, the data analysis module comprising:
the abnormal model is used for setting an abnormal threshold value of the monitoring index, comparing each monitoring index with the abnormal threshold value and judging whether to carry out fault diagnosis or not;
the fault model is provided with various fault types, index combinations and index ranges corresponding to the fault types, and the monitoring indexes are compared with the indexes in the fault model for fault diagnosis;
and the parameter model is used for setting normal indexes and fault index ranges for the monitoring indexes, and comparing the monitoring indexes with all indexes in the parameter model for fault degree evaluation.
7. The system according to claim 6, wherein the abnormality threshold includes an upper abnormality limit and a lower abnormality limit, and the fault diagnosis is performed when each monitoring index exceeds the upper abnormality limit or the lower abnormality limit.
8. The system according to claim 6, wherein the parametric model sets a fault level for each fault type, each fault level sets a corresponding level index range, and each monitored fault data is compared with the level index range to determine the level of the fault.
9. The system for diagnosing the state of the capacitor voltage transformer equipment as claimed in claim 6, wherein the data acquisition module collects detection indexes of different detection points of the capacitor voltage transformer equipment through different intelligent sensors.
10. The system according to claim 6, wherein the detection indicators comprise a plurality of detection indicators of capacitance, internal temperature, humidity of operating environment and vibration intensity.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202111582915.4A CN114460520A (en) | 2021-12-22 | 2021-12-22 | Method and system for diagnosing equipment state of capacitive voltage transformer |
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| CN202111582915.4A CN114460520A (en) | 2021-12-22 | 2021-12-22 | Method and system for diagnosing equipment state of capacitive voltage transformer |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117472629A (en) * | 2023-11-02 | 2024-01-30 | 兰州航空职业技术学院 | Multi-fault diagnosis method and system for electronic information system |
| CN117849691A (en) * | 2024-03-08 | 2024-04-09 | 国网江西省电力有限公司电力科学研究院 | Multi-dimensional collaborative operation monitoring and early warning system and method for capacitive voltage transformer |
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2021
- 2021-12-22 CN CN202111582915.4A patent/CN114460520A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117472629A (en) * | 2023-11-02 | 2024-01-30 | 兰州航空职业技术学院 | Multi-fault diagnosis method and system for electronic information system |
| CN117472629B (en) * | 2023-11-02 | 2024-05-28 | 兰州航空职业技术学院 | Multi-fault diagnosis method and system for electronic information system |
| CN117849691A (en) * | 2024-03-08 | 2024-04-09 | 国网江西省电力有限公司电力科学研究院 | Multi-dimensional collaborative operation monitoring and early warning system and method for capacitive voltage transformer |
| CN117849691B (en) * | 2024-03-08 | 2024-05-14 | 国网江西省电力有限公司电力科学研究院 | Multi-dimensional collaborative operation monitoring and early warning system and method for capacitive voltage transformer |
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