CN-121978285-A - Multi-source data-based thermal degradation monitoring and early warning method and system for insulating material of electrical equipment

CN121978285ACN 121978285 ACN121978285 ACN 121978285ACN-121978285-A

Abstract

The invention relates to the technical field of thermal degradation monitoring, in particular to a method and a system for monitoring and early warning thermal degradation of an insulating material of electrical equipment based on multi-source data, the method mainly comprises the steps of outputting a first monitoring node with a current risk through a thermal degradation early warning model based on current target data, obtaining a target loop with abnormal current based on residual electric quantity detection, obtaining a second monitoring node on the target loop, and judging whether all target gas types of the target monitoring nodes belong to standard gas types. By the method, the possible volatilized gas of the current monitoring node is analyzed, the possibility of false alarm of the current detection point is reduced, all current monitoring nodes are evaluated based on the obtained sequencing result and the early warning value, and a processing sequence for reference of staff is obtained, so that the situation that the current monitoring node is not preferentially processed to the emergency monitoring node to cause serious accidents is avoided as far as possible.

Inventors

CHU XIAOCHEN
LIAO LIJUAN
HU JIAJIA
LIN XIAOFU
HE CHUAN
QI SHAN
MA LING
WU JUN
HUANG LEI
TIAN QIGUI
SHI WEIHONG
HU TAOTAO
HE XIANGYU
ZHAO JIANXIN
YANG FAN
DENG CHANGSHENG
CAI SHIPING
WANG DERONG
LU LIN
HUANG XIAOYUAN
LIU DENG
LI MING

Assignees

国网四川省电力公司资阳供电公司

Dates

Publication Date: 20260505
Application Date: 20260407

Claims (10)

1. The method for monitoring and early warning the thermal degradation of the insulating material of the electrical equipment based on the multi-source data is characterized by comprising the following steps of: Acquiring gas detection data of different current monitoring nodes, establishing a thermal degradation early warning model, and outputting a first monitoring node with current risk through the thermal degradation early warning model based on current target data; The method comprises the steps of obtaining standard gas types generated after thermal degradation of insulating materials in each monitoring node, establishing a table according to the standard gas types of different monitoring nodes, and adding an index value to each monitoring node; detecting the electric quantity of each loop, obtaining a target loop with abnormal current based on the electric quantity detection, and obtaining a second monitoring node on the target loop; Judging whether the first monitoring node and the second monitoring node have repeated monitoring nodes, if not, storing the first monitoring node as a target monitoring node, if so, storing the repeated monitoring node as the target monitoring node, and if not, storing the first monitoring node as a common monitoring node; Acquiring an early warning value of a target monitoring node and a detected target gas type, indexing in a table based on the index value of the monitoring node, acquiring a standard gas type of the target monitoring node, judging whether the target gas type of the target monitoring node is all of the standard gas type, if so, storing the early warning value of the current target monitoring node, and if not, correcting the early warning value of the current target monitoring node; And sequencing the early warning values of the current target monitoring nodes to obtain a first result, sequencing the early warning values of the common monitoring nodes after the last early warning value of the first result, and outputting a final sequenced result.
2. The method for monitoring and early warning thermal degradation of an insulating material of an electrical device based on multi-source data according to claim 1, further comprising: preprocessing the gas detection data, the preprocessing comprising: grouping gas detection data by the type of gas, and sequencing time sequence in each group of data according to the time obtained by each data; detecting abnormal values and missing values in each group of data, supplementing the abnormal values after eliminating the abnormal values, and outputting and processing gas detection data after supplementing the missing values.
3. The method for monitoring and early warning thermal degradation of an insulating material of an electrical device based on multi-source data according to claim 2, wherein detecting abnormal values in each group of data and supplementing the abnormal values after eliminating the abnormal values comprises: Acquiring the absolute value of the difference value of the adjacent first data with the front time sequence and the second data with the rear time sequence, setting a difference value threshold value, judging whether the current absolute value of the difference value is larger than the difference value threshold value, if the current absolute value of the difference value is smaller than or equal to the difference value threshold value, not processing, and if the current absolute value of the difference value is larger than the difference value threshold value, continuing to acquire third data positioned behind the second data; When the difference between the first data and the second data is negative, if the third data is larger than or equal to the second data, the second data is taken as a normal value, if the third data is smaller than the second data, the absolute value of the difference between the second data and the third data is obtained, if the absolute value of the difference between the second data and the third data is larger than or equal to a difference threshold, the second data is taken as an abnormal value, and if the absolute value of the difference between the second data and the third data is smaller than the difference threshold, the second data is taken as a normal value; And when the difference value between the first data and the second data is positive, if the third data is smaller than the second data, the second data is taken as a normal value, if the third data is larger than or equal to the second data, the absolute value of the difference value between the second data and the third data is obtained, if the absolute value of the difference value between the second data and the third data is larger than or equal to a difference threshold, the second data is taken as an abnormal value, and if the difference value is smaller than the difference threshold, the second data is taken as the normal value.
4. The method for monitoring and early warning thermal degradation of insulation materials of electrical equipment based on multi-source data according to claim 3, wherein the supplementing the abnormal value after eliminating or supplementing the missing value comprises the following steps: acquiring a missing record point of a removed abnormal value or a missing value in current data, acquiring data on two adjacent sides of the missing record point, and writing the average value of the data on two adjacent sides into the missing data point by taking the average value of the data on two adjacent sides as a filling value; when the data on one side or two sides adjacent to the data are also empty recording points, acquiring the data of the next target recording point with the data, judging the number of the recording points separated from the empty recording points by the target recording points, setting a selection threshold value, taking the data on the other side as a filling value if the number of the recording points on one side is larger than the selection threshold value, and taking the average value of the current data set as a supplementary value if the numbers of the recording points on two sides are larger than the selection threshold value.
5. The method for monitoring and early warning thermal degradation of insulation materials of electrical equipment based on multi-source data according to claim 4, wherein the establishing a thermal degradation early warning model comprises: In the formula, Is the early warning value of the ith monitoring node, The current monitoring node exceeds the alarm threshold value The concentration of the seed gas is determined, Is the first An alarm threshold value for the concentration of the seed gas, For the current monitoring of the temperature of the node, For the lowest combustion temperature of several cables in the current detection point, For the average current flowing through all the cables in the current monitoring node, The average current flowing through the cable in all detection points, For the current monitoring node to exceed the alarm threshold of the gas species, 、 And To calculate the coefficients, the sum is 1.
6. The method for monitoring and early warning thermal degradation of insulation materials of electrical equipment based on multi-source data according to claim 5, wherein outputting the first monitoring node currently at risk through the thermal degradation early warning model based on the current target data comprises: setting a judgment threshold value, and when the early warning value is larger than the judgment threshold value, storing a monitoring node corresponding to the current early warning value as a first monitoring node; the judging threshold value is as follows: In the formula, To determine the threshold.
7. The method for monitoring and early warning thermal degradation of insulation material of electrical equipment based on multi-source data according to claim 6, wherein the correcting the early warning value of the current target monitoring node comprises: Establishing a correction model, the correction model comprising: In the formula, In order to correct the early warning value after the correction, Is the number of target gas types that are not located within the standard gas types.
8. The method for monitoring and early warning thermal degradation of insulation materials of electrical equipment based on multi-source data according to claim 7, further comprising the steps of encrypting and sending the final sequenced result: Dividing data into two data packets, constructing an elliptic curve, and selecting points on the curve 、 As a generator and find a point Sum point Is the midpoint of (2) ; Selecting a private key based on a point And Respectively generating two public keys; Encoding plaintext into , Is a point on the curve based on two public keys and a midpoint Generate the first ciphertext and take the midpoint As a second ciphertext; Based on the first ciphertext and the second ciphertext, respectively sending the first ciphertext and the second ciphertext to a receiving end, and decrypting by the receiving end to obtain 。
9. The method for monitoring and early warning thermal degradation of insulation material of electrical equipment based on multi-source data according to claim 8, wherein the method is based on two public keys and a midpoint Generating the first ciphertext includes: the second ciphertext includes: the receiving end decrypts to obtain Comprising the following steps: By passing through The plaintext can be obtained For plaintext Decoding to obtain a final ordered result; In the formula, As a first portion of the first ciphertext, For the second portion of the first ciphertext, As the second ciphertext is provided in the form of a second ciphertext, Is a private key.
10. A multi-source data-based thermal degradation monitoring and early warning system for an insulating material of an electrical device, which is characterized by being used for executing the multi-source data-based thermal degradation monitoring and early warning method for the insulating material of the electrical device according to any one of claims 1 to 9, comprising: The data detection module is configured to acquire gas detection data of different current monitoring nodes, establish a thermal degradation early warning model, output a first monitoring node with a current risk through the thermal degradation early warning model based on the current target data, acquire standard gas types generated after thermal degradation of insulating materials in each monitoring node, establish a table according to the standard gas types of the different monitoring nodes, and add an index value to each monitoring node; The correction module is used for judging whether the first monitoring node and the second monitoring node have repeated monitoring nodes, if not, storing the first monitoring node as a target monitoring node, if yes, storing the repeated monitoring node as a target monitoring node, and not repeatedly as a common monitoring node, acquiring an early warning value of the target monitoring node and the detected target gas type, indexing in a table based on the index value of the monitoring node, acquiring the standard gas type of the target monitoring node, judging whether the target gas type of the target monitoring node is all of the standard gas type, if yes, storing the early warning value of the current target monitoring node, if no, correcting the early warning value of the current target monitoring node, sorting the early warning value of the current target monitoring node to obtain a first result, sorting the early warning value of the common monitoring node after the last early warning value of the first result, and outputting a final sorted result.

Description

Multi-source data-based thermal degradation monitoring and early warning method and system for insulating material of electrical equipment Technical Field The invention relates to the technical field of thermal degradation monitoring, in particular to a thermal degradation monitoring and early warning method and system for an insulating material of electrical equipment based on multi-source data. Background With the promotion of special works such as construction of centralized control stations and digital transformation, power transformation operation and maintenance personnel are continuously reduced, power cables, signal cables and the like in cable channels of the transformer substation are relatively concentrated, and fire hazards such as cable short circuits, overload, aging, poor contact and the like cannot be timely found. In addition, the residual current abnormality also becomes a great threat to the power supply safety. Therefore, the residual current monitoring technology is integrated into the existing system, and the aim of building a dual intelligent early warning system for overheat hidden danger and electrical insulation faults is achieved, so that intelligent upgrading of the safety early warning of the transformer substation is achieved. In the prior art, referring to CN118707240A, an ad hoc network covered type cable thermal degradation monitoring method and system are disclosed, cable thermal degradation gas data are collected and sent to a server side for storage, a gas monitoring model is established at an edge end to analyze the gas data, the signs of the cable thermal degradation are identified in real time and early warning is carried out, the data at the edge end are summarized at the server side, the long-term trend of the gas data is analyzed, and the gas monitoring model is optimized, so that the cable thermal degradation long-term monitoring and early warning are realized. According to the method, the cable area is covered by the edge end ad hoc network for sampling detection, so that the gas data is analyzed in real time, the degradation signs are rapidly identified, early warning signals are timely sent out, and the degradation problem of the cable is solved. However, in the detection process, whether detected gas occurs after the current monitoring node is thermally degraded is not considered, so that final misjudgment is caused, the processing of other monitoring nodes is affected, the current prior art only analyzes and alarms, and a reference processing sequence result is not given, so that the processing of the more urgent monitoring nodes is delayed. Disclosure of Invention The invention aims to provide a multi-source data-based thermal degradation monitoring and early warning method and system for an insulating material of electrical equipment, which are used for solving the problems in the prior art. The invention is realized by the following technical scheme: in a first aspect, the invention provides a thermal degradation monitoring and early warning method for an insulating material of an electrical device based on multi-source data, which comprises the following steps: Acquiring gas detection data of different current monitoring nodes, establishing a thermal degradation early warning model, and outputting a first monitoring node with current risk through the thermal degradation early warning model based on current target data; The method comprises the steps of obtaining standard gas types generated after thermal degradation of insulating materials in each monitoring node, establishing a table according to the standard gas types of different monitoring nodes, and adding an index value to each monitoring node; detecting the electric quantity of each loop, obtaining a target loop with abnormal current based on the electric quantity detection, and obtaining a second monitoring node on the target loop; Judging whether the first monitoring node and the second monitoring node have repeated monitoring nodes, if not, storing the first monitoring node as a target monitoring node, if so, storing the repeated monitoring node as the target monitoring node, and if not, storing the first monitoring node as a common monitoring node; Acquiring an early warning value of a target monitoring node and a detected target gas type, indexing in a table based on the index value of the monitoring node, acquiring a standard gas type of the target monitoring node, judging whether the target gas type of the target monitoring node is all of the standard gas type, if so, storing the early warning value of the current target monitoring node, and if not, correcting the early warning value of the current target monitoring node; And sequencing the early warning values of the current target monitoring nodes to obtain a first result, sequencing the early warning values of the common monitoring nodes after the last early warning value of the first result, and outputting a final sequenced result. Prefer