Fault diagnosis method based on multi-feature information weighted fusion under spectral clustering analysis
A technology of weighted fusion and fault diagnosis, which is applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as failure to consider reliability, synthetic results cannot reflect objective facts, etc., and achieve the effect of simplifying the diffusion distance
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[0077] Such as figure 1 As shown, the present invention relates to a fault diagnosis method based on weighted fusion of multi-feature information under spectral clustering analysis, comprising the following steps:
[0078] S1: Judging the faulty equipment of each power plant, if two faulty equipment are concentrated, put them in the same partition, otherwise, use the spectral clustering method to divide the faulty equipment and obtain multiple sub-regions; the specific content includes :
[0079] 11) Divide multiple faulty devices into the same sample set.
[0080] Assuming that there are n faulty devices, the sample set that needs to be divided is:
[0081] X={X 1 ,X 2 ,...,X i ,...,X n}∈R m×n
[0082] In the formula, R m×n is the set of real numbers, m is the number of matrix rows, X i For the i-th faulty device, pass the data X of the group i (t) The parameter set formed by sampling, X i The expression is:
[0083] x i ={x i (1),x i (2),...,x i (t),,...,x ...
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