Mapping and correction of the CMM workspace error with the use of an electronic gyroscope and neural networks—practical application

Abstract

The article presents the application of neural networks in determining and correction of the deformation of a coordinate measuring machine (CMM) workspace. The information about the CMM errors is acquired using an ADXRS401 electronic gyroscope. A test device (PS-20 module) was built and integrated with a commercial measurement system based on the SP25M passive scanning probe and with a PH10M module (Renishaw). The proposed solution was tested on a Kemco 600 CMM and on a DEA Global Clima CMM. In the former case, correction of the CMM errors was performed using the source code of WinIOS software owned by The Institute of Advanced Manufacturing Technology, Cracow, Poland and in the latter on an external PC. Optimum parameters of full and simplified mapping of a given layer of the CMM workspace were determined for practical applications. The proposed method can be employed for the interim check (ISO 10360-2 procedure) or to detect local CMM deformations, occurring when the CMM works at high scanning speeds (>20 mm/s).