基于智能控制的机械设备金属结构故障诊断研究  

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

作　　者：杨岱桦 雷菊阳[1] 姚辉 Yang Daihua;Lei Juyang;Yao Hui(School of Mechanical and Automotive Engineering,Shanghai University of Engineering Science,Shanghai 201620,China)

机构地区：[1]上海工程技术大学机械与汽车工程学院

出　　处：《农业装备与车辆工程》2020年第2期123-126,共4页Agricultural Equipment & Vehicle Engineering

摘　　要：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。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.

关 键 词：智能控制 ANSYS有限元分析 模糊推理 故障诊断 

分 类 号：TH165.3[机械工程—机械制造及自动化] S22[农业科学—农业机械化工程]