A Power Quality Disturbance Identification Method Using Time-Domain Compression and Multi-resolution Fast S-Transform Feature Extraction
A power quality disturbance, multi-resolution technology, applied in character and pattern recognition, data processing applications, special data processing applications, etc., can solve the problems of increasing network structure complexity, large data storage space, and high space complexity, achieving The effect of reducing space storage requirements and storage costs, storage space reduction, and time-domain dimension reduction
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[0069] The present invention uses a power quality disturbance identification method based on time-domain compression and fast S-transform feature extraction to perform feature extraction and identification of disturbance signals, and its specific implementation includes the following steps:
[0070] 1) Use Matlab simulation to generate 12 types of power quality disturbance signals;
[0071] 2) Process the perturbation signal using multi-resolution fast S-transform;
[0072] 3) Determine the type of feature extracted;
[0073] 4) Construct intermediate vectors and intermediate matrices based on time-domain compressed fast S-transform;
[0074] 5) further extract features to the intermediate matrix, and construct feature vectors;
[0075] 6) Construct an extreme learning machine classifier based on particle swarm optimization to classify disturbance signals.
[0076] The present invention will be further described below in conjunction with the accompanying drawings and specific...
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