Development of monitoring and fault diagnosing system for ship power plant

A digital monitoring and fault diagnosing system for ship power plant based on fuzzy neural network and dempster shafer(D S) evidence theory is developed. The system includes data acquisition part, software control part and analysis part, which can monitor the main propulsion device, diesel generator and auxiliaries. The main propulsion device can be real time dynamicly monitored by acquiring cylinder pressure and instantaneous angular speed. Using thermodynamic parameters and instantaneous angular speed, two sub fuzzy neural networks are parallel constructed. The fault of main propulsion device is judged by data fusing algorithm of D S evidence theory, and finally the result of fault diagnosis can be obtained. Test shows that the system’s real time performance and measurement accuracy can meet requirements, and the fusion method of fuzzy neural network according to D S evidence theory has relatively high reliability.