The existing marine diesel engine fault diagnosis methods mainly have the problems of model complexity, large amount of calculation, and unable to carry out real-time fault diagnosis of diesel engine. In this paper, a...The existing marine diesel engine fault diagnosis methods mainly have the problems of model complexity, large amount of calculation, and unable to carry out real-time fault diagnosis of diesel engine. In this paper, a simple and practical approach to detect faults of marine diesel engine is studied. According to a set of sensing data, the fitting equation of each parameter changing with the running state of diesel engine was fitted statistically. Then, the threshold range of each parameter changing with the running state of diesel engine was fitted. During fault diagnosis, the real-time parameters of the sensor in the current running state were calculated according to the real-time running data. If the parameters exceed the threshold range, it is abnormal operation. Because the sensor signal corresponds to the operation status of each specific component, the abnormal evaluation directly indicates the specific fault. Experimental results show that the method has a good practical effect.展开更多
Condition-based maintenance based on fault prediction has been widely concerned by the industry. Most of the contributions on fault prediction are based on various sensor data and mathematical models of the equipment....Condition-based maintenance based on fault prediction has been widely concerned by the industry. Most of the contributions on fault prediction are based on various sensor data and mathematical models of the equipment. The complexity of the model and data signal is the key factor affecting the practicability of the model. In addition, even for the same type and batch of equipment, the manufacturing process, operation environment and other factors also affect the model parameters. In this paper, a series event model is conducted to predict the fault of marine diesel engines. Numerical example illustrates that the proposed event model is feasible.展开更多
文摘The existing marine diesel engine fault diagnosis methods mainly have the problems of model complexity, large amount of calculation, and unable to carry out real-time fault diagnosis of diesel engine. In this paper, a simple and practical approach to detect faults of marine diesel engine is studied. According to a set of sensing data, the fitting equation of each parameter changing with the running state of diesel engine was fitted statistically. Then, the threshold range of each parameter changing with the running state of diesel engine was fitted. During fault diagnosis, the real-time parameters of the sensor in the current running state were calculated according to the real-time running data. If the parameters exceed the threshold range, it is abnormal operation. Because the sensor signal corresponds to the operation status of each specific component, the abnormal evaluation directly indicates the specific fault. Experimental results show that the method has a good practical effect.
文摘Condition-based maintenance based on fault prediction has been widely concerned by the industry. Most of the contributions on fault prediction are based on various sensor data and mathematical models of the equipment. The complexity of the model and data signal is the key factor affecting the practicability of the model. In addition, even for the same type and batch of equipment, the manufacturing process, operation environment and other factors also affect the model parameters. In this paper, a series event model is conducted to predict the fault of marine diesel engines. Numerical example illustrates that the proposed event model is feasible.
