基于经验小波变换的智能上肢力量训练器故障监测方法  

Fault monitoring method of intelligent upper limb strength training device based on empirical wavelet transform

作　　者：戴丽[1] 韩春华 孙耀华[1] DAI Li;HAN Chunhua;SUN Yaohua(Shanxi University of Finance and Economics,Taiyuan 030006,China;Shijiazhuang Tiedao University SiFang College,Shijiazhuang 050081,China)

机构地区：[1]山西财经大学,太原030006 [2]石家庄铁道大学四方学院,石家庄050081

出　　处：《自动化与仪器仪表》2020年第5期130-133,共4页Automation & Instrumentation

基　　金：河北省高等教育学会2015年度高等教育科学研究课题:普通高校开展马拉松运动的现状调查及对策研究(No.GJXHZ2015-42)。

摘　　要：为了提高智能上肢力量训练器故障的监测精度,确保训练器故障的监测能力,提出了基于经验小波变换的智能上肢力量训练器故障监测方法。采用经验小波变换将添加后的输出信号映射,得到智能上肢力量训练器故障监测的传递函数,基于智能上肢力量训练器故障参数的提取公式,完成智能上肢力量训练器故障参数的提取;将智能上肢力量训练器故障样本划分成两类,确定故障样本划分条件,得到智能上肢力量训练器故障监测模型表达式,完成智能上肢力量训练器故障监测模型的构建;最后通过智能上肢力量训练器故障监测流程,实现了基于经验小波变换的智能上肢力量训练器故障监测。对比实验结果证明,基于经验小波变换的故障监测方法与基于音频识别的故障监测方法相比,智能上肢力量训练器故障的监测能力提高了82.86%。In order to improve the monitoring accuracy of the failure of the intelligent upper limb strength training device,ensuring the monitoring ability of trainer failure.Based on the empirical wavelet transform,a fault monitoring method of intelligent upper limb strength training device is proposed.The empirical wavelet transform is used to map the added output signal to obtain the transfer function of fault monitoring of the intelligent upper limb strength trainer.Based on the extraction formula of fault parameters of the intelligent upper limb strength trainer,the fault parameters of the intelligent upper limb strength trainer are extracted,the fault samples of the intelligent upper limb strength trainer are divided into two categories,the fault sample classification conditions are determined,the fault detection model expression of the intelligent upper limb strength trainer is obtained,and the fault monitoring model of the intelligent upper limb strength trainer is constructed.Finally,through the fault monitoring process of intelligent upper limb strength training device,fault monitoring of intelligent upper limb strength training device based on empirical wavelet transform is realized.The results of comparative experiments prove that,compared with the audio recognition based fault monitoring method,the empirical wavelet transform based fault monitoring method,the monitoring ability of intelligent upper limb strength training device is improved by 82.86%.

关 键 词：经验小波变换 上肢力量 训练器 故障监测 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]