基于引力搜索BP神经网络的柴油机故障诊断  

Fault Diagnosis of Diesel Engine Using BP Neural Network Based on Gravitational Search Algorithm

作　　者：陈晗[1] 李垣江[1,2] 王建华[1] 

机构地区：[1]江苏科技大学电子信息学院,江苏镇江212003 [2]南京理工大学电子工程与光电技术学院,南京210094

出　　处：《船舶工程》2015年第10期49-53,共5页Ship Engineering

摘　　要：为了提高柴油机故障诊断的精度,将引力搜索算法用于BP神经网络初始权值及阈值优化,提出了一种基于引力搜索算法和BP神经网络相结合的智能故障诊断方法,并将其运用于柴油机磨损故障的振动诊断。结果表明,该方法与BP神经网络相比,对柴油机的磨合、磨损、极限等故障诊断准确,精度提高明显,验证了该方法的有效性。In order to improve the precision of the fault diagnosis of diesel engine, the gravitational search algorithm is used to optimize the initial weights and threshold of BP neural network in the article. Moreover, an intelligent fault diagnosis method based on the combination of gravitational search algorithm and BP neural network is proposed. The method is applied to the vibration diagnosis of diesel engine wear fault. With the example of diesel engine, the results show that the proposed method has higher accuracy than BP neural network. Besides, it is effective in classification and diagnosis of the faults of diesel engine.

关 键 词：柴油机 引力搜索算法 BP神经网络 故障诊断 

分 类 号：TK428[动力工程及工程热物理—动力机械及工程] U664.121[交通运输工程—船舶及航道工程]