Research on the fuzzy and dynamic monitoring of the diesel engine operating conditions

Abstract

In this paper the fuzzy and dynamic monitoring of mechanical equipment is studied using fuzzy techniques. Generally there are two types of condition monitoring: one is that the standard syndrome can be established in advance and, therefore, the fault samples can be identified by this; the other is that the standard syndrome is difficult to establish in advance, and information only about the operation condition of the mechanical equipment is needed. For the former the measure of fuzzy nearness can be used without using a series of weights for the characteristic parameters; for the latter the fuzzy cluster can be used without the standard syndrome. The vibration signal samples obtained from the 190A diesel engine block are identified and classified by the fuzzy measures. The results show that the fuzzy nearness and fuzzy cluster are practical and work well.