摘要
为了提高工业机器人薄壁角接触球轴承的故障信号诊断效率,设计了一种混沌优化萤火虫参数(CFA)故障信号诊断方法,建立了其相应的控制流程。以工业机器人轴承测试故障平台为依托,开展振动信号处理分析。研究结果表明:模态分量信号已经实现了合成信号准确分离,达到了理想分离性能,有助于从信号包络谱内提取获得故障信号频率。混沌优化萤火虫方法得到的故障诊断准确率明显增加,接近99%左右。相比较其他方法,混沌优化萤火虫方法准确率是最优的,表现出来很高的准确性。该研究可以拓展到其他的机械传动领域,具有很好的应用价值。
In order to improve the fault signal diagnosis efficiency of industrial robot bearings,a chaotic optimization Firefly parameter(CFA)fault signal diagnosis method was designed and its corresponding control flow was established.Based on the fault test platform of industrial robot bearing,the vibration signal processing analysis is carried out.The results show that the modal component signals have achieved accurate separation of synthetic signals and achieved ideal separation performance,which is helpful to extract the fault signal frequency from the signal envelope spectrum.The accuracy of fault diagnosis obtained by chaotic firefly method is increased significantly,which is close to 99%.Compared with other methods,chaos optimization firefly method has the best accuracy,showing high accuracy.
作者
冀永曼
Ji Yongman(College of Intelligent Manufacturing,Xinxiang Vocational and Technical College,Xinxiang Henan 453000,China)
出处
《现代工业经济和信息化》
2024年第6期267-269,共3页
Modern Industrial Economy and Informationization
关键词
工业机器人
轴承振动信号
故障诊断
萤火虫算法
industrial robot
bearing vibration signal
fault diagnosis
firefly algorithm
