The Fault Diagnosis Algorithm of PLS-LSSVM Process Based on Base Vector Space

The method of least squares support vector machine has been improved based on base vector space theory, which solved the problem of weak handling ability of nonlinear, sparsity and variable multiple correlation in the fault diagnosis process for LSSVM. This article proposed a double sections fault diagnosis algorithm combined PLS with LSSVMBVS, it first builds regression analysis model, then puts the detected fault data in the trained LSSVMBVS classifier, diagnosing troubles. It verified the algorithm has better prediction accuracy and generalization performance by the TE platform.