Quality-related Fault Monitoring and Fault Variable Tracing Based on Bacth Process

As the multi-way kernel entropy partial least squares(MKEPLS) method does not make full use of the higher-order statistics of the process data,which will lose the important information in the feature extraction,and result in degraded fault identification performance.To solve this problem,a novel method based on higher order statistics and multi-way kernel entropy partial least squares(HOSMKEPLS) is proposed,in which the raw data space is projected into statistics space by calculating the higher order statistics of the data set,establishing the monitoring MKEPLS model,then adopting the contribution figure method on the trace of the fault variables.Finallay,the method is applied to an industrial penicillin fermentation process,and compared with the MKEPLS model.Resultsshow that the method has a better monitoring performance and can detect and identify the fault.