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

Area of Science:

• Metrology
• Machine Vision
• Manufacturing Engineering

Background:

• Periodic health checks are crucial for evaluating machine performance and ensuring value-added manufacturing.
• Existing devices for contouring error detection face limitations in dimension, range, and speed.
• Accurate measurement of machine error motions is essential for quality control.

Purpose of the Study:

• To propose a cost-effective, knowledge-driven approach for detecting error motions of arbitrary paths using a single camera.
• To overcome the measurement limitations (dimension, range, speed) of existing contouring error detection devices.
• To improve the accuracy, efficiency, and capability of vision-based measurement for machine performance evaluation.

Main Methods:

• A novel camera calibration method considering depth-of-field distortion for accurate distortion behavior description.
• Design of high-efficient encoding markers on a cooperative target to characterize machine motion information.
• A decoding method based on finding the optimal start bit for automatic marker identification and location.
• Three-dimensional (3D) evaluation of large-scale contouring error using the PNP algorithm and a priori geometrical knowledge.

Main Results:

• The proposed method enables 3D evaluation of large-scale contouring errors under relatively high feed rate conditions.
• Experimental results validate the measurement accuracy and advantages of the proposed vision measurement method.
• The system successfully detected and verified errors for both planar and spatial trajectories.

Conclusions:

• The developed knowledge-driven, single-camera approach provides an accurate and efficient solution for measuring machine contouring errors.
• This method enhances machine performance evaluation and supports value-added manufacturing by overcoming existing technological barriers.
• The validated experimental results demonstrate the practical applicability and benefits of the proposed vision measurement system.