Application of kernel principal component and Pearson correlation coefficient in prediction of mine pressure failure

Aiming at the problem of mine fault prediction, a fault prediction model based on KPCA and Pearson correlation coefficient is proposed. The model obtains the abnormal sampling data by the kernel principal component method, extracts the abnormal sampling data and draws the contribution plots, then the Pearson correlation coefficient is compared with the existing fault contribution plots. Finally, according to the correlation of Pearson correlation coefficient to predict the failure will occur. Failures can be predicted through this model timely. This model have a certain degree of practicality and effectiveness.