Quality detection of laser additive manufacturing process based on coaxial vision monitoring

Abstract

Purpose

This paper aims to explore the influences of different process parameters, including laser power, scanning speed, defocusing distance and scanning mode, on the shape features of molten pool and, based on the obtained relationship, realize the diagnosis of forming defects during the process.

Design/methodology/approach

Molten pool was captured on-line based on a coaxial CCD camera mounted on the welding head, then image processing algorithms were developed to obtain melt pool features that could reflect the forming status, and it suggested that the molten pool area was the most sensitive characteristic. The influence of the processing parameters such as laser power, traverse speed, powder feed rate, defocusing distance and the melt pool area was studied, and then the melt pool area was used as the characteristic to detect the forming defects during the cladding and additive manufacturing process.

Findings

The influences of different process parameters on molten pool area were explored. Based on the relationship, different types of defects were accurately detected through analyzing the relationship between the molten pool area and time.

Originality/value

The findings would be helpful for the quality control of laser additive manufacturing.

Citation

Chen, B., Yao, Y., Huang, Y., Wang, W., Tan, C. and Feng, J. (2019), "Quality detection of laser additive manufacturing process based on coaxial vision monitoring", Sensor Review, Vol. 39 No. 4, pp. 512-521. https://doi.org/10.1108/SR-03-2018-0068