DOI: 10.3390/app132312931 ISSN: 2076-3417

An Intelligent Detection System for Surface Shape Error of Shaft Workpieces Based on Multi-Sensor Combination

Xiaoyan Guan, Ying Tang, Baojiang Dong, Guochao Li, Yanling Fu, Chongshun Tian
  • Fluid Flow and Transfer Processes
  • Computer Science Applications
  • Process Chemistry and Technology
  • General Engineering
  • Instrumentation
  • General Materials Science

As the main components of mechanical products and important transmission components of mechanical motion, shaft workpieces (SW) need to undergo high-speed motion while also withstanding high torque motion, which has high processing requirements. At the same time, the processing quality of the workpieces determines the success of the entire processing process, and the quality-inspection methods and the accuracy of the technology directly affect the evaluation of the product. This paper designs an intelligent detection system for the surface shape error (SSE) of SW that combines multiple sensors. Based on the principle of sensor use and specific experimental status, the overall scheme of the detection system is designed, followed by research on the spatial positioning algorithm and surface measurement algorithm of the workpiece to be tested. We then compensate and correct the errors with the algorithm. The effectiveness of the system is verified by measuring the surface size of the workpiece. Finally, the radial circular runout error is taken as an example to verify the detection system. The results show that the measurement error is less than 5%, and the accuracy of the system is high.