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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.

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.

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.

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

The purpose of this paper is to predict and control the composition during laser additive manufacturing, since composition control is important for parts manufactured by laser additive manufacturing. Aluminum and steel functionally graded material (FGM) were manufactured by laser metal deposition, and the composition was analyzed by means of spectral analysis simultaneously.

The laser metal deposition process was carried out on a 5 mm thick 316L plate. Spectral line intensity ratio and plasma temperature were chosen as two main spectroscopic diagnosis parameters to predict the compositional variation. Single-trace single-layer experiments and single-trace multi-layer experiments were done, respectively, to test the feasibility of the spectral diagnosis method.

Experiment results showed that with the composition of metal powder changing from steel to aluminum, the spectral intensity ratio of the characteristic spectral line is proportional to the elemental content in the plasma. When the composition of deposition layers changed, the characteristic spectrum line intensity ratio changed obviously. And the linear chemical composition analysis results confirmed the gradient composition variation of the additive manufacturing parts. The results verified the feasibility of composition analysis based on spectral information in the laser additive manufacturing process.

The composition content of aluminum and steel FGM was diagnosed by spectral information during laser metal deposition, and the relationship between spectral intensity and composition was established.