卡尔曼滤波在车辆振动信号处理的应用研究

通过测量车辆在沥青路面上行驶的振动数据,从而实现沥青路面平整度的预测。而在实际测量过程中,振动信号受到外界环境的影响,掺杂了大量的散粒噪声、热噪声、高斯噪声,严重影响了路面平整度的计算与评价。实验采用最小二乘法进行趋势项消除,通过功率谱分析不同滤波方法的处理结果,确定出卡尔曼滤波技术对沥青路面振动信号的降噪效果。结果表明:卡尔曼滤波降噪技术在振动信号处理中不仅能消除外部干扰噪声,还能较大程度地保持原有信号的特征和强度。验证了卡尔曼滤波降噪技术的可行性与可靠性。

By measuring the vibration data of the vehicle driving on the asphalt pavement,the smoothness of the asphalt pavement is predicted.In the actual measurement process,the vibration signal is affected by the external environment,mixed with a large amount of shot noise,thermal noise,and Gaussian noise,which seriously affects the calculation and evaluation of road smoothness.The experiment uses the least square method to eliminate the trend term,and analyzes the processing results of different filtering methods through the power spectrum to determine the noise reduction effect of the Kalman filtering technology on the vibration signal of the asphalt pavement.The results show that Kalman filter noise reduction technology can not only eliminate external interference noise in vibration signal processing,but also maintain the original signal characteristics and strength to a large extent.The feasibility and reliability of the Kalman filter noise reduction technology are verified.