基于故障树的汽车起重机液压故障诊断专家系统

根据汽车起重机液压系统故障诊断的特点,建立了汽车起重机液压故障诊断专家系统。该系统提出将故障树和模糊神经网络相融合,并以汽车起重机常见故障为例建立了相应的故障树模型,完成了基于专家规则表示与模糊表示下知识数据库的构建与推理机的实现。解决了传统专家系统知识获取困难的问题;运用模糊神经网络的自学机制,保证知识库的完整性和正确性;实现了对汽车起重机液压系统的故障诊断内容的不断的更新和扩充,并及时将已发生及预测到的的故障写入数据库中,提高了查找故障的准确率及效率,有利于预防和控制汽车起重机液压系统的故障。

An Expert System for Diagnosing Hydraulic Fault of Automobile Crane Using Fault Tree

According to the characteristics of hydraulic fault diagnosed of an automobile crane,its hydraulic fault diagnosis expert system crane was developed.This expert system combines a fault tree with a fuzzy neural network.The construction of knowledge base and the realization of reasoning engine with expert rule representation and fuzzy representation were completed by taking the example of a common fault of the automobile crane.The fault tree model was accordingly established.The difficulty for the expert system to acquire knowledge was solved;self-learning mechanism of the fuzzy neural network was utilized to ensure the completeness and correctness of the knowledge base.The constant update and expansion of the content of the hydraulic fault diagnosis was achieved and the fault,if it happened,was promptly written in a database which improves the fault-searching accuracy and efficiency,thus preventing the fault of the hydraulic system of the automobile crane.