Time series data cleaning method based on correlation analysis and principal component analysis
A principal component analysis, time series technology, applied in neural learning methods, character and pattern recognition, instruments, etc., can solve problems such as efficiency limitations, affecting accuracy, and being less sensitive to faults
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[0045] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.
[0046] Such as figure 1 As shown, a time series data cleaning method based on correlation analysis and principal component analysis includes the following steps:
[0047] Step S1: Use the Pearson coefficient analysis method (PCC) to find out other power data that has a hidden relationship with the transformer fault, and add new basis for fault diagnosis.
[0048] The present invention analyzes other electrical data at this stage using Pearson analysis (PCC). Pearson analysis method (PCC) is a measurement method widely used in pattern recognition, statistical analysis and image processing. The Pearson coefficient is a parameter indicating the degree of linear correlation between two data sets, and its value range is [-1, 1], 1 represents a complete positive correlation, -1 represents a complete negative correlation, and 0 represents no relationship, as...
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