基于分形维数的表面粗糙度实时监测

Real-time Monitoring of Surface Roughness Based on Fractal Dimension

零件的表面粗糙度是影响零件加工质量的因素之一,目前企业通常采用抽检形式结合轮廓仪等设备对零件进行表面粗糙度测量。此类离线检测方法在大部分企业的质量管理模式中较常见,但存在漏洞,由于是抽样检测,因此可能存在部分有质量缺陷的零件未被检测到,导致废品率的产生,增加了成本。基于分形维数理论,研究了一种在零件加工时对表面粗糙度进行实时监测的方法,通过某企业加工中心采集数据,验证了其可行性。

The surface roughness of parts is one of the factors affecting the processing quality of parts.At present,enterprises usually use the form of sampling inspection,combined with profilometer and other equipment,to measure the surface roughness.This kind of offline detection method is common in the quality management mode of most enterprises at present,but it also has loopholes.Due to sampling detection,some parts with quality defects may not be detected,resulting in rejection rate and increased cost.Based on the fractal dimension theory,a method for real-time monitoring of surface roughness during machining of parts is studied,and its feasibility is verified by collecting data from a machining center of an enterprise.