Unified Analysis of Diagnosis Methods for Process Monitoring

Several diagnosis methods have been proposed for statistical process monitoring. They have been developed from different backgrounds and considerations. In this paper, five existing diagnosis methods are analyzed and compared. It is shown that these methods can be unified into three more general methods, making the original diagnosis methods special cases of the general methods. An analysis of the diagnosability of the general methods shows that some diagnosis methods guarantee correct diagnosis for simple sensor faults with large magnitudes, while others do not. For the case of sensor faults with modest fault magnitudes, a Monte Carlo simulation is used to compare the performance of the diagnosis methods. © 2009 IFAC.