基于卡尔曼滤波的油液金属磨屑检测系统

Oil metal abrasive swarf detection system based on Kalman filtering

面对油液中金属磨屑的检测需求,针对传统油液金属磨屑检测系统的检测精度易受噪声影响的问题,文章设计了基于卡尔曼滤波的油液金属磨屑检测好的,系统。首先,根据电磁感应原理设计磁激励传感器并建立电压扰动模型;然后,根据金属磨屑电压信号的特点设计卡尔曼滤波器;接着,通过数据拟合验证电压扰动模型并计算过程噪声协方差;再利用小波分析得到测量噪声协方差;最后根据所得到的参数对金属磨屑电压扰动数据进行卡尔曼滤波得到最终结果。试验结果表明,经过卡尔曼滤波之后,300um金属磨屑的电压扰动信号误差减小了2%,400um金属磨屑的电压扰动信号误差降低了2.5%,500um金属磨屑的电压扰动信号误差降低了3%,证明了卡尔曼滤波用于该系统是可行的。

Faced with the detection needs of metal abrasive chips in oil,aiming at the problem that the detection accuracy of traditional oil metal abrasive swarf detection systems is easily affected by noise,an oil metal abrasive swarf detection system based on Kalman filtering is designed.Firstly;the magnetic excitation sensor is designed according to the principle of electromagnetic induction and the voltage disturbance model is established.Secondly,the Kalman filter is designed according to the characteristics of the metal abrasive chip voltage signal.Thirdly,the voltage disturbance model is verified by data fitting and the process noise covariance is calculated.Then the measured noise covariance is obtained by wavelet analysis.Finally according to the obtained parameters,the metal grinding chip voltage disturbance data is Kalman filtered to obtain the final result.The test results show that after Kalman filtering,the voltage disturbance signal error of 300um metal grinding chips is reduced by 2%,1he voltage disturbance signal error of400um metal grinding chips is reduced by 2.5%,and the voltage disturbance signal error of500um metal grinding chips is reduced by 3%,which proves that Kalman filter is feasible for this system.