摘要
高压电动机是造纸厂的重要设备,在高压电动机故障诊断过程中,受到复杂环境的影响,信号含噪声比例较高,一般的故障诊断方法抗干扰能力比较差。针对这一情况,提出基于小波变换的造纸厂高压电动机故障诊断方法。依据高压电动机状态数据采集参数,选择合适的小波函数和分解尺度,使用数据采集卡采集高压电动机信号数据,利用小波变换中的滤波技术处理原始信号,消除噪声,从原始信号数据中提取出故障特征,经过分解、重构处理后,计算出原始信号的能量,依据能量变化诊断出电动机故障。实验结果表明:提出的基于小波变换的电动机故障诊断方法信噪比低,故障诊断准确,该方法的抗干扰能力得到了明显提升。
High-voltage motors are important equipment in paper mills.During the process of diagnosing faults in high-voltage motors,they are affected by a complex environment with a high proportion of signal noise.General fault diagnosis methods have poor anti-interference abilities.In view of this situation,a fault diagnosis method for high voltage motors in paper mills based on wavelet transform is proposed.Based on the state data acquisition parameters of the high-voltage motor,an appropriate wavelet function and decomposition scale are selected.The data acquisition card is used to collect the signal data from the high-voltage motor.The original signal is processed using wavelet transform filtering technology to eliminate noise and extract fault characteristics from the original signal data.After decomposition and reconstruction processing,the energy of the original signal is calculated to diagnose motor faults based on energy changes.Experimental results show that the proposed motor fault diagnosis method based on wavelet transform has a low signal-to-noise ratio,accurate fault diagnosis,and significantly improved anti-interference ability.
作者
魏晓艳
张瑜
袁观娜
WEI Xiaoyan;ZHANG Yu;YUAN Guanna(Engineering College,Xi'an Siyuan University,Xi'an 710038,China)
出处
《造纸科学与技术》
2023年第4期35-38,45,共5页
Paper Science & Technology
基金
陕西省教育厅专项科研计划项目(19JK0692)。
关键词
小波变换
造纸厂
高压电动机
故障诊断
特征提取
噪声处理
wavelet transform
paper mill
high-voltage motor
fault diagnosis
feature extraction
noise processing
