基于智能控制的机械设备金属结构故障诊断研究

针对传统故障诊断方法不具备自动学习功能,在复杂系统中难以对被检测对象建立精确的数学模型,提出基于智能控制的故障诊断方法。通过对农机金属结构进行参数化建模并完成可靠性分析,将智能诊断中模糊推理算法应用在故障识别中,可自动高效地提取出反映设备运行状态的有效故障特征并实时监测,得出诊断结果。在满足结构系统可靠性要求的同时,该方法不仅缩短了平均诊断时间,将机械设备的失效控制在可以接受的层面,而且提高了诊断效率和故障识别精度。

Research on Metal Structure Fault Diagnosis of Lifting Equipment Based on Intelligent Control

Aiming at the traditional fault diagnosis method with no automatic learning function,which is difficult to establish accurate mathematical model for the detected object in the complex system,a fault diagnosis method based on intelligent control is proposed.Through parameterized modeling of agricultural machinery metal structure and reliability analysis,fuzzy reasoning algorithm in intelligent diagnosis is applied in fault identification,which can automatically and efficiently extract the effective fault characteristics reflecting the running state of equipment and real-time monitoring,and obtain the diagnosis results.This method not only shortens the average diagnosis time and controls the failure of mechanical equipment in an acceptable level,but also improves the diagnosis efficiency and fault identification accuracy.