A feedforward controller for tuning laser cladding melt pool geometry in real time

Moralejo, S.; Penaranda, X.; Nieto, S.; Barrios, Asier; Arrizubieta, I.; Tabernero, I.; Figueras, J.

doi:10.1007/s00170-016-9138-7

Cited by 38 publications

(10 citation statements)

References 11 publications

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“…In LDED, high-speed cameras and three-dimensional (3-D) scanners are used to monitor geometry signatures. Charge-coupled device (CCD) cameras 7,8 and complementary metal oxide semiconductor (CMOS) cameras 9,10 are two commonly used image acquisition devices. According to experimental requirements and the actual situation on site, the position of the camera can be divided into coaxial 9,11 and off-axis.…”

Section: Devices and Basic Principlesmentioning

confidence: 99%

“…A filter must be used to eliminate the interference of energy beam radiation and powder and obtain the best image of the molten pool. 7,9,10 Other related devices will also be described below.…”

Section: Devices and Basic Principlesmentioning

confidence: 99%

“…In several studies of direct control, only one input and one output were selected to reduce the complexity of the controller. Moralejo et al 10 adjusted the laser power to control the final width based on the pool width monitored by CMOS cameras. Recently, the trend of direct control is from a single input, single output to multiple inputs, multiple outputs.…”

Section: Direct Control and Indirect Controlmentioning

confidence: 99%

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Review on adaptive control of laser-directed energy deposition

et al. 2020

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Laser directed energy deposition (LDED) is one of the most important parts of metal additive manufacturing, which can provide fast building speed, allows for large building volumes, and is suitable for part repair. LDED can manufacture components layer by layer through processes of rapid heating, melting, solidification, and cooling with the laser beam as a heat source. However, deposition quality and repeatability of components produced by LDED are poor because of the complex thermal cycle and processing environment, hindering the spread of this technique. Adaptive control technology (ACT) is consistently considered an effective and potential way to solve the problem. Many studies have focused on LDED and established the relations of process parameters, process signatures, and product qualities, which promote the rapid development of ACT, with the development of monitoring devices and data processing technology. We review and discuss the problems existing in the ACT of LDED.

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Section: Devices and Basic Principlesmentioning

confidence: 99%

Section: Devices and Basic Principlesmentioning

confidence: 99%

Section: Direct Control and Indirect Controlmentioning

confidence: 99%

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Review on adaptive control of laser-directed energy deposition

et al. 2020

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“…CMOS visible and NIR cameras were traditionally used for melt pool size control. The control of melt pool width in a cladding process using visible and NIR CMOS cameras is presented in [7] and [8]. To do so, a fixed threshold is used to binarize images and the dimensions of the resulting ellipse corresponding to the cladding area are measured.…”

Section: Previous Workmentioning

confidence: 99%

Online Calculation of Melt Pool Cooling Rate with Automatic Background Correction

Lois

Molanes

Gonzalez-Val

et al. 2019

IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society

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This paper presents a generic method to process mid-wave infrared (MWIR) images in laserbased manufacturing processes. The background noise of the camera is used as a source of information for correcting different problems that affect MWIR cameras. The mean of the noise distribution is used to correct the background drift due to sensor heat-up, whereas the standard deviation is used to generate dynamic thresholds for subsequent algorithms. The proposed method is portable, robust, and independent of the background, scale, and optical and electronic aberrations of the camera. The method is validated in the calculation of melt pool cooling rate. Performance is tested in a real scenario using a Field Programmable System-on-Chip platform. Results show that the system is capable of sending to a remote computer MWIR images at 1,435 frames per second and cooling rate information at a rate of 10,680 samples per second.

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“…The laser power, scan speed, and shape and temperature of melt pools the common measurement items for monitoring and controlling in the AM process. Because the MPI shapes are parts of the significant features used to judge the stability and quality of the AM process, the camera-based in-situ systems are developed to monitor the melt pool and regulate the laser power online and in real time for the stability of the manufacturing process once the system detects some abnormal behaviors [6]. Hence, the chamber image and MPI will be captured by the overview CCD and coaxial CCD, respectively, and the fog or smoke generated during melting would be carried from the chamber by the Nitrogen airflow [7] [8].…”

Section: Introductionmentioning

confidence: 99%

MPI-Based System 2 for Determining LPBF Process Control Thresholds and Parameters

Adnan

Yang

Kuo

et al. 2021

IEEE Robot. Autom. Lett.

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Determining thresholds of the primary control loops (System 1) of an additive manufacturing (AM) process is challenging when realizing System 1 with its fast and intuitive capability for adapting to different metal powers, machine configurations, and process parameters. Based on the convolution neural network and long short-term memory models, this paper presents a secondary tuning loop (System 2) to classify the types of melt-pool images (MPIs) from a coaxial camera online, suggest polishing parameters, and determine the control thresholds of System 1 offline. Case studies indicate that the thresholds and parameters of System 1 including smoke discharging, powder coating, and laser polishing of control loops of a laser powder bed fusion (LPBF) machine can be more deliberatively and logically decided by the proposed MPI-based System 2.

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A feedforward controller for tuning laser cladding melt pool geometry in real time

Cited by 38 publications

References 11 publications

Review on adaptive control of laser-directed energy deposition

Review on adaptive control of laser-directed energy deposition

Online Calculation of Melt Pool Cooling Rate with Automatic Background Correction

MPI-Based System 2 for Determining LPBF Process Control Thresholds and Parameters

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