Work

Study on identifying GMAW process deviations by means of optical and electrical process data using ANN

Year: 2020

Type: conference-paper

Source: 2022 IEEE 18th International Conference on Automation Science and Engineering (CASE)

DOI: 10.1109/case48305.2020.9216744

Authors: U. Reisgen, S. Mann, L. Oster, G. Gott, R. Sharma, D. Uhrlandt

Institutions: RWTH Aachen University, Leibniz Institute for Plasma Science and Technology

Language: English

Topic: Welding Techniques and Residual Stresses

Subfield: Mechanical Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: closed

OpenAlex ID: W3092400219

FWCI: 1.848

Cites: 13

Cited by: 4

Related to: 10