【摘要】 基于起升机构液压系统故障诊断的特点,提出基于故障树的模糊神经网络作为汽车起重机起升机构液压系统故障诊断的方法。该方法利用故障树知识,提取汽车起重机起升机构液压系统故障诊断的输入变量和输出变量,引入模糊逻辑的概念,运用模糊隶属度函数来描述这些的程度,利用共轭梯度优化算法对神经网络进行训练,并通过实例分析,验证了汽车起重机起升机构液压系统模糊神经网络故障诊断的有效性。更多还原

【Abstract】 Based on the characteristics of the hoisting mechanism hydraulic system fault diagnosis, fuzzy neural network fault diagnosis based on fault tree as a method for variable amplitude hydraulic system is proposed in this paper. The method uses fault tree knowledge, extracts fault diagnosis input and output variables of truck crane hoisting mechanism hydraulic system, and introduces the concept of fuzzy logic, fuzzy membership functions to describe the extent to which these failures. Besides, it uses fuzzy membership functions to describe the extent of these failures,and uses Conjugate Gradient algorithm to train the neural network system. The effectiveness of truck crane hoisting mechanism hydraulic system fuzzy neural network fault diagnosis is analyzed and verified through case.更多还原