Study of diagnosis system framework using remote knowledge service

It is quite difficult to acquire criterion knowledge for the condition monitoring and fault diagnosis in machinery. The traditional approach depends on constant summary of experiences from the experts. However, the acquired knowledge is probably inaccurate and inefficient. With the benefit of network, the different companies and users that have the same equipments can be organized to form an integrated information source in order to share the original data and diagnosis knowledge. Thus, the more accurate diagnosis knowledge may be acquired using knowledge mining and information fusion so that the precision of status identification can be improved. Furthermore, the diagnostic services based on remote knowledge service can be provided via network. The framework of remote knowledge service system based on web service technology is proposed in this study. Combined with the ferrography analysis method, the application of knowledge service for remote wear debris analysis has been studied and demonstrated in this study.