联合收割机滚动轴承故障诊断系统研究OA
Research on Fault Diagnosis System of Combine Rolling Bearing
首先,介绍了联合收割机滚动轴承振动机理和故障特征,并研究了基于声场空间分布特征的故障诊断流程;然后,对联合收割机滚动轴承的声音信号采集及特征提取进行了深入研究;最后,利用神经网络算法的模式识别对联合收割机滚动轴承的故障进行诊断.验证结果表明:系统对联合收割机滚动轴承故障的综合诊断率为 91.67%,系统具有可行性.
It firstly introduces the vibration mechanism and fault characteristics of the combine rolling bearing,then studies the fault diagnosis process based on the spatial distribution characteristics of the sound field,and then conducts in-depth research on the sound signal acquisition and feature extraction of the combine rolling bearing,and finally uses the pattern recognition of neural network algorithm to diagnose the fault of the combine rolling bearing.The verification re-sults show that the comprehensive diagnostic rate of the system for the faults of the combine rolling bearing is 91.67%,which proves the feasibility of the system.
杨旭;唐靖哲
河南工业职业技术学院, 河南 南阳 473000
农业工程
联合收割机滚动轴承故障诊断声场空间分布特征神经网络
combine harvesterrolling bearingfault diagnosisspatial distribution characteristics of sound fieldneural network
《农机化研究》 2024 (006)
185-189,194 / 6
教育部科技发展中心第三批"云数融合科教创新"基金项目(2018A10004)
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