A Knowledge-Driven Approach for 3D High Temporal-Spatial Measurement of an Arbitrary Contouring Error of CNC Machine Tools Using Monocular Vision.

Xiao Li,Wei Liu,Yi Pan,Jianwei Ma,Fuji Wang

doi:10.3390/s19030744

Abstract

Periodic health checks of contouring errors under unloaded conditions are critical for machine performance evaluation and value-added manufacturing. Aiming at breaking the dimension, range and speed measurement limitations of the existing devices, a cost-effective knowledge-driven approach for detecting error motions of arbitrary paths using a single camera is proposed. In combination with the PNP algorithm, the three-dimensional (3D) evaluation of large-scale contouring error in relatively high feed rate conditions can be deduced from a priori geometrical knowledge. The innovations of this paper focus on improving the accuracy, efficiency and ability of the vision measurement. Firstly, a camera calibration method considering distortion partition of the depth-of-field (DOF) is presented to give an accurate description of the distortion behavior in the entire photography domain. Then, to maximize the utilization of the decimal involved in the feature encoding, new high-efficient encoding markers are designed on a cooperative target to characterize motion information of the machine. Accordingly, in the image processing, markers are automatically identified and located by the proposed decoding method based on finding the optimal start bit. Finally, with the selected imaging parameters and the precalibrated position of each marker, the 3D measurement of large-scale contouring error under relatively high dynamic conditions can be realized by comparing the curve that is measured by PNP algorithm with the nominal one. Both detection and verification experiments are conducted for two types of paths (i.e., planar and spatial trajectory), and experimental results validate the measurement accuracy and advantages of the proposed method.

Highlights

As high-end equipment places ever-increasing demands on the accuracy of parts, the manufacturing quality of components is directly related to the performance of the machines utilized on the production line
The results indicate that the maximum high and accuracy of theare proposed average differences
A 3D high temporal-spatial measurement method and system based on a single camera are proposed, this knowledge-driven approach realizes the 3D detection of contouring errors camera are proposed, this knowledge-driven approach realizes the 3D detection of contouring errors of arbitrary paths, especially that of interpolated spatial contours

Summary

Introduction

As high-end equipment places ever-increasing demands on the accuracy of parts, the manufacturing quality of components is directly related to the performance (i.e., static and dynamic performance) of the machines utilized on the production line. To meet these requirements, measurement is inseparable from any basic or complex CNC machine tool machining process. The conventional post-inspection method is too late for the needs of value-added manufacturing, which drives us to evaluate machine performance before machining to determine or improve the processing capacity. The periodic health check of contouring performance in unloaded conditions is critical for maintaining and improving parts’ accuracy [1]. ISO 230 [2] (parts 1–11) specifies the test code for vertical-spindled

Methods

Results

Conclusion