Equipment fault diagnosis method based on improved negative selection algorithm of particle swarm algorithm
A particle swarm algorithm and negative selection technology, applied in the field of electrical equipment fault diagnosis, can solve problems such as equipment loss, achieve the effects of reducing operating costs, reducing time complexity, and expanding coverage
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[0041]An equipment fault diagnosis method based on the negative selection algorithm improved by the particle swarm optimization algorithm, which specifically solves the defect of insufficient abnormal samples through the negative selection algorithm. The self-set P1 of hash value strings composed of , c strings and the string to be detected D1 are constructed through the relationship between the standard deviation of the m-point data and the standard deviation of all data to construct the self-set of hash value strings P2 and the strings to be detected. String D2, detectors A and B are generated by particle swarm optimization algorithm, and the distances between D1 and detector A substrings and the distances between D2 and detector B each substring are calculated by Hamming distance; Improvement, that is, the optimal value is obtained in each round of iteration of the particle swarm optimization algorithm constructed by generating different substrings, so as to solve the proble...
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