基于大数据分析的轴承退卸工装智能化研究

Intelligent Research on Bearing Removal Tooling Based on Big Data Analysis

为了提升轴承退卸工装工艺可靠性,设计大数据分析的轴承退卸工装智能化分析方法。采集轴承运行信号,采用多层小波分解对轴承运行信号进行处理,从处理后轴承运行信号中提取轴承故障特征,然后采用支持向量机根据轴承故障特征进行故障诊断,最后利用轴承故障诊断结果保障轴承退卸工装顺利进行。实验结果表明,该方法的诊断轴承故障精度高,数据传输速率快,可以满足轴承退卸工装智能化管理要求。

In order to improve the reliability of bearing disassembly tooling technology,an intelligent analysis method of bearing disassem-bly tooling based on big data analysis is designed.It collects the bearing operation signal,processes the bearing operation signal by multi-layer wavelet decomposition,extracts the bearing fault characteristics from the processed bearing operation signal,then uses support vector machine to diagnose the fault according to the bearing fault characteristics,and finally uses the bearing fault diagnosis results to ensure the smooth progress of bearing unloading tooling.The experimental results show that this method has high accuracy and fast data transmission rate,and can meet the requirements of intelligent management of bearing return tooling.