Fault diagnosis method for switching current circuit based on improved FastICA
A technology of switching current and circuit faults, which is applied in the field of fault diagnosis of switching current circuits, can solve the problems of long time consumption and heavy algorithm workload, achieve fast convergence speed, good separation effect, and improve the efficiency of fault diagnosis
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[0067] Basic Principles of Independent Component Analysis
[0068] ICA is a signal processing method developed from blind signal separation in recent years. It can be regarded as an extension of PCA. It transforms data into mutually independent directions. Independent. For a set of n-dimensional observation data, ICA decomposes n-dimensional random signals into a set of linear combinations of statistically independent random variables by looking for directions that can make the data independent of each other in the feature space. Compared with the disadvantage that PCA can only use the second-order statistics of data, ICA uses high-order statistical information, which is more conducive to the decomposition of observed signals.
[0069] Let a group of observation signals X={x 1 ,x 2 ,L,x m} is the source signal S={s 1 ,s 2 ,L,s n}, assuming that the i-th observation signal is linearly mixed with n independent components S:
[0070] x 1 =a i1 the s 1 +a i2 the s 2 +...
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