An Intelligent Metrology Architecture with AVM for Metal Additive Manufacturing

Haw Ching Yang, Muhammad Adnan, Chih Hung Huang, Fan Tien Cheng, Yu Lung Lo, Chih Hua Hsu

研究成果: Article同行評審

8 引文 斯高帕斯(Scopus)

摘要

The capability of measuring melt pool variation is the key evaluating metal additive manufacturing quality. To measure the variation, a metrology architecture with in situ melt pool measurement and an estimation module is required. However, it is a challenge to effectively extract significant features from the huge data collected by the in situ metrology for quality estimation requirement. The purpose of this letter is to propose an intelligent metrology architecture with an in situ metrology (ISM) module and an enhanced automatic virtual metrology (AVM) system. The ISM module can extract the melt pool features with a coaxial camera and a pyrometer. On the other hand, the AVM system is improved with a feature selection method to solve the issue of limited samples in the component modeling quality. The examples with different metals are adopted to illustrate how the system works for estimating surface roughness and density of components, and, in the future, the system can even serve as the feedback signal for adaptive control of the process parameters by layering in an additive manufacturing system.

原文English
文章編號8733865
頁(從 - 到)2886-2893
頁數8
期刊IEEE Robotics and Automation Letters
4
發行號3
DOIs
出版狀態Published - 2019 七月

All Science Journal Classification (ASJC) codes

  • 控制與系統工程
  • 生物醫學工程
  • 人機介面
  • 機械工業
  • 電腦視覺和模式識別
  • 電腦科學應用
  • 控制和優化
  • 人工智慧

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