Power equipment temperature rise detection and early warning method based on RST-PNN-GA
A technology of RST-PNN-GA and power equipment, applied in the field of temperature rise detection and early warning of power equipment based on the RST-PNN-GA neural network algorithm, can solve problems such as false positives and fault deterioration, achieve accurate judgment and early warning, and improve Diagnosis rate and the effect of improving the diagnosis rate
Pending Publication Date: 2021-09-07
国网甘肃省电力公司兰州供电公司
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But when the monitored value is greater than the set value, some faults have deteriorated
However, if the threshold is set too low, it will often produce false positives.
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Embodiment 1
[0078] Please refer to the attached Figure 1-2 As shown, a RST-PNN-GA-based power equipment temperature rise detection and early warning method includes the following steps:
[0079] (1) Build an online monitoring system for temperature rise of power equipment, and then use the online monitoring system for temperature rise of power equipment to monitor the temperature of power equipment in real time, obtain the temperature data of power equipment, and use the temperature data of power equipment obtained through real-time monitoring as input variables;
[0080] (2) Based on the RST-PNN-GA neural network algorithm, a power equipment temperature rise detection and early warning model is constructed, and part of the power equipment temperature data obtained through step (1) is input into the constructed power equipment temperature rise detection and early warning model for training;
[0081] (3) Input part of the electric equipment temperature data obtained through step (1) into ...
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The invention provides a power equipment temperature rise detection and early warning method based on RST-PNN-GA, and relates to the technical field of power equipment detection. According to the method, a probabilistic neural network is adopted to analyze temperature rise characteristic signals, a rough set is utilized to simplify collected characteristic samples, a genetic algorithm is utilized to carry out error back propagation calculation, the power equipment temperature rise detection early warning method based on an RST-PNN-GA neural network algorithm is established, the defects of traditional artificial neural network detection are overcome, and the temperature rise change of the power equipment can be predicted more accurately and effectively, so that efficient maintenance can be realized. The power equipment temperature rise on-line monitoring system is constructed to monitor the temperature data of the power equipment in real time, and the data are input into a power equipment temperature rise detection and early warning model to be analyzed, so that a temperature rise early warning signal can be obtained.
Description
technical field [0001] The invention relates to the technical field of power equipment detection, in particular to a temperature rise detection and early warning method for power equipment based on the RST-PNN-GA neural network algorithm. Background technique [0002] Combined with the actual situation of my country's power grid distribution, the connection parts between the contacts in the power equipment will generate heat due to the aging of materials or the increase of contact resistance during long-term operation. Since most of these heating parts are inside the power equipment, the current monitoring The means cannot effectively realize online monitoring. At the same time, the complexity of the power distribution network makes the measurement points widely distributed, and there is high voltage around them, which is not convenient for manual measurement, and various faults often occur in the operation of electrical equipment. According to the statistics of relevant dep...
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IPC IPC(8): G01D21/02G08C17/02G06N3/04G06N3/08
CPCG01D21/02G06N3/08G08C17/02G06N3/047
Inventor 胡潇文郭海龙任伟张斌陈敏李亚东冉利利陶冶郑立柯成军王生鹏靳夏常雪
Owner 国网甘肃省电力公司兰州供电公司