Accession Number:

AD1090879

Title:

Intelligent Welding: Real Time Monitoring, Diagnosis, Decision and Control Using Multi-Sensor and Machine Learning

Descriptive Note:

Technical Report,05 Dec 2016,31 Dec 2018

Corporate Author:

University of Illinois at Chicago Chicago United States

Personal Author(s):

Report Date:

2018-12-31

Pagination or Media Count:

55.0

Abstract:

In this project, the industry problem of real-time weld quality assurance is studied. An automated weld quality assurance can increase the efficiency and the productivity of weld manufacturing. In order to ensure an adequate weld quality, the selection of proper evaluation approaches is critical. Currently, inspections are usually conducted either destructively or in the post-weld stage. Thus, if defects are found in welded product, few of them can be remedied. This may result in the disposal of expensive material, thus decreasing overall productivity. Therefore, an efficient nondestructive weld quality monitoring method is critically needed.

Subject Categories:

  • Fabrication Metallurgy

Distribution Statement:

APPROVED FOR PUBLIC RELEASE