Multivariate process monitoring based on the distribution test of the data

In most industry processes, there is no prior knowledge of the data distribution. If the process monitoring method is chosen without considering its constraints, it will get wrong conclusions and increase the rate of high leaking and false alarm. To solve the problem, a method of multivariate process monitoring and fault diagnosis based on distribution test of the data is proposed. First, the improved F-straight method is used to test the distribution of the process data. According to the test result, appropriate modeling method is chosen automatically to monitor the process and conduct fault diagnosis, which solves the constraints of PCA, ICA in application. Feasibility, efficiency and accuracy of the method are evaluated by the case study.