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Process parameters analysis and prediction during laser deposition manufacturing based on melt pool monitoring
Author:
Affiliation:

1.Key Laboratory of Fundamental Science for National Defense of Aeronautical Digital Manufacturing Process,Shenyang Aerospace University;2.China

Clc Number:

TG146.2+3

Fund Project:

The National Key R&D Program of China (2016YFB1100504); NSFC (51505301, 51375316); Shenyang additive manufacturing engineering research center program (F16-078-8-00)

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    Abstract:

    During laser deposition manufacturing (LDM) process, melt pool width which is greatly influenced by process parameters is essential for the forming tracks geometry. In this paper, the melt pool geometry evolution was monitored by a CCD camera, and a method of applying Kalman filtering for the melt pool width detection during LDM process was presented to obtain accurate value. Orthogonal experimental design and multiple regression analysis were used to establish an empirical model describing the correlation between the melt pool width and three main process parameters (laser power, scanning speed, and powder feeding rate). And the developed model was verified experimentally. Finally, Particle swarm optimization (PSO) was implemented for prediction of process parameters during the buildup of a thin wall. The results indicate that process parameters analysis and prediction for LDM process could make it possible to acquire an efficient process for the forming tracks geometry control.

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[Qin Lanyun, Xu Lili, Yang Guang, Shang Chun, Wang Wei. Process parameters analysis and prediction during laser deposition manufacturing based on melt pool monitoring[J]. Rare Metal Materials and Engineering,2019,48(2):419~425.]
DOI:10.12442/j. issn.1002-185X.20170663

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History
  • Received:July 27,2017
  • Revised:August 23,2017
  • Adopted:September 12,2017
  • Online: March 15,2019
  • Published: