Roller kiln energy consumption anomaly detection method based on self-adaptive principal component analysis
A principal component analysis and anomaly detection technology, applied in the field of detection, can solve the problems of low detection efficiency and abnormal energy consumption of roller kiln, and achieve the effect of reducing false alarm rate, saving calculation time, and optimizing algorithm process.
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[0059] As shown in the figure, an embodiment of an abnormal detection method for energy consumption of a roller kiln based on adaptive principal component analysis of the present invention, the specific steps are as follows:
[0060] (1) First collect the sample L, and calculate the covariance matrix S after standardizing the collected samples;
[0061] (2) Decompose the eigenvalues of S, use the CPV method to calculate the number of principal components k, and intercept the eigenvectors and eigenvalues to obtain the load matrix P and eigenvalue matrix Λ;
[0062] (3) Calculate the initial control limit and
[0063] (4) Continue to collect new samples of sample L after a certain period of time, and perform standardization; and perform abnormal judgment on the new samples, if abnormal, output abnormal information to end, if normal, put the sample into the system to be updated and perform step (5) );
[0064] (5) Loop (1)(2)(3(4) until the number of samples to be updat...
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