A gis state recognition method based on vibration signal principal component analysis

Abstract

The invention discloses a GIS state recognition method based on principal component analysis of vibration signals, extracting 14 feature quantities of GIS vibration signals under normal and different fault states to form a 14-dimensional composite feature vector; The vector is compressed and dimensionally reduced into the principal component feature vector; then the corresponding decision function between the vibration signal principal component feature vector and the GIS state is obtained through the two-stage training of the deep belief network, and the principal component feature vector of the GIS vibration signal to be recognized is used. Carry out classification, and determine the GIS status according to the classification. Using principal component analysis to optimize the composite eigenvector not only retains the original information of the composite eigenvector, but also reduces the dimension of the eigenvector, improves the efficiency of the classifier, and effectively improves the accuracy and speed of GIS state recognition.

Description

technical field [0001] The invention relates to the technical field of gas-insulated metal-enclosed switchgear (GIS) state recognition technology, in particular to a GIS state recognition method based on a vibration signal principal component analysis method. Background technique [0002] Gas Insulated Switchgear (GIS) came out in the 1960s and developed rapidly because of its small footprint, high reliability, strong safety, short installation period, and small maintenance workload. , has been widely used in substations of all levels around the world. However, due to its complex and fully enclosed structure, once GIS fails, it will have a wide range of effects and it is difficult to accurately locate and quickly repair it. [0003] Therefore, in order to ensure the safe and stable operation of the power grid, the reliability of GIS is particularly important, so it has become a top priority to effectively identify the fault state of GIS. At present, the methods for monitor...

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Problems solved by technology

[0004] However, the existing GIS state recognition based on vibration signals often performs GIS state recognition for a single feature quantity of vibration signals, but the mechanical state of GIS does not have a one-to-one correspondence with the feature quantity, and different mechanical states may cause the same feature. Quantity changes, so the GIS state identification based on a single feature quantity often leads to misjudgment

In order to improve the detection accuracy, it is necessary to collect a variety of feature quantities to form a composite feature vector, combined with the information complementary relationship between different feature quantities, to make a more reliable judgment on the GIS status, but the increase of feature quantities will increase the workload of the computer. Reduce calculation speed and accuracy

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