An automated dynamic-balancing-inspection scheme for wheel machining

Hao Tieng, Yu Yong Li, Kuang Ping Tseng, Haw Ching Yang, Fan Tien Cheng

Research output: Contribution to journalArticle

Abstract

Wheel balance plays an important role in vehicle safety. The existing inspection method for wheel balance mainly relies on the off-machine measurement technique, which is time-and manpower-consuming as the worldwide requirement of the automated production system gradually increases. However, the multi-unbalance causes are difficult to identify due to complex machine structures; and the low signal-noise-ratio between wheel and machine vibration makes traditional handcrafted features difficult to detect wheel unbalance. To overcome these two challenges, this paper proposes a Dynamic-Balancing-Inspection (DBI) scheme which integrates steps of data collection, data preprocessing, and ensemble average of Convolution Neural Network (CNN) based models with well-Tailored filters and activation functions, to automatically uncover critical information from frequency data and provide the on-machine and real-Time total inspection for the wheel balance. The application of the wheel balance from a practical CNC-machine is adopted to illustrate the performance of the DBI approach.

Original languageEnglish
Article number8978473
Pages (from-to)2224-2231
Number of pages8
JournalIEEE Robotics and Automation Letters
Volume5
Issue number2
DOIs
Publication statusPublished - 2020 Apr

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Biomedical Engineering
  • Human-Computer Interaction
  • Mechanical Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Control and Optimization
  • Artificial Intelligence

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