基于卡尔曼滤波的X射线测厚仪噪声处理方法

X-ray thickness gauge noise processing method based on Kalman filtering

X射线测厚仪在实际应用中受环境噪声、探测器噪声以及信号放大电路噪声等多重影响,导致初始电压存在较大波动问题。提出了一种基于卡尔曼滤波算法的X射线测厚仪噪声处理方法,采用网格搜索方法确定卡尔曼滤波的最优超参数。实验结果表明,相比传统的均值滤波和中值滤波,卡尔曼滤波算法能有效地去除测量信号中的噪声,显著地降低了测量误差,最大测量误差为0.08%。此方法对于X射线测厚仪的数据处理、提升测量精度以及实际生产中的应用具有重要意义。

In practical applications,X-ray thickness gauges are affected by environmental noise,detector noise,and signal amplification circuit noise,etc.,resulting in large fluctuations in the initial voltage.a noise processing method is proposed for X-ray thickness gauges based on the Kalman filter algorithm,using a grid search method to determine the optimal hyperparameters of the Kalman filter.Experimental results showed that compared with traditional mean filtering and median filtering,the Kalman filter algorithm could effectively remove noise in the measurement signal and significantly reduce the measurement error.The maximum measurement error is 0.08%.This method is of great significance for data processing of X-ray thickness gauges,improving measurement accuracy,and application in actual production.