表面粗糙度非接触测量中的高斯滤波算法及其LabVIEW软件设计

Gaussian Filtering Algorithm and LabVIEW Software Design for Non-Contact Measurement of Surface Roughness

探究高斯滤波方法在表面粗糙度非接触测量中的适应性问题。以基于光谱共焦位移传感器采集的表面粗糙度样块的表面形貌数据为实例,引入高斯滤波算法,计算出滤波中心线,分离出粗糙度信号。在LabVIEW平台中,进行高斯滤波算法的程序设计,计算出粗糙度值,与现行接触校准的结果进行对比。实验结果表明,非接触数据处理后的R_(a)值的MPE为±5%,高斯滤波方法适用于非接触测量的数据处理。用LabVIEW进行算法的模块化设计容易实现,且易与其他模块集成,便于维护,有一定的推广价值。

This study investigates the adaptability of the Gaussian filtering method in non-contact measurement of surface roughness.Using surface profile data obtained from a spectral confocal displacement sensor as an example,the Gaussian filtering algorithm is introduced to compute the filtering centerline and separate the roughness signal.A program for the Gaussian filtering algorithm is designed on the LabVIEW platform,calculating the roughness values and comparing them with the results of current contact calibration.Experimental results indicate that the Maximum Permissible Error(MPE)of the Ra value after non-contact data processing is±5%,demonstrating that the Gaussian filtering method is suitable for data processing in non-contact measurements.The modular design of the algorithm in LabVIEW is easy to implement,integrates well with other modules,is easy to maintain,and holds significant potential for wider application.