Nonlinear Identification of Laser Welding Process

Abstract

It has been well recognized that the weld pool geometry plays a critical role in the welding process. In this study, a diode laser welding control system is established. The authors performed a series of open-loop experiments to investigate the interaction and the correlation among of the laser energy, the welding speed, and the weld pool geometry. A digital camera with a high speed shutter is equipped to take pictures of the weld pool in real time. Custom computer vision software and image processing programs are applied to acquire the surface width of the weld pool. Based on the experimental study, the authors propose an applicable method to identify a SISO nonlinear continuous model for the established diode laser welding process. The identified nonlinear model takes the reciprocal of the welding speed as the input and the surface width of the weld pool as the output. To validate the model, the authors conduct further experiments including step and PRTS (Pseudo-random Ternary Signal) responses. In addition, the authors simulate the nonlinear model with same inputs and check the data agreements between the simulated results and the experimental data. The validation results confirm the applicability of the proposed nonlinear identification method and show that the model can successfully predict the surface width of weld pool for later use.

An intelligent approach for optimal regulation of blood glucose level

“…The Hammerstein model has been considered by researchers for identifying nonlinear systems [14] [15]. This model is composed of a nonlinear static part which is in series with a linear dynamic part.…”

Crosscorrelation functions based nonlinear identification of diode laser welding process

“…Recently, based on nonlinear Least Square and optimization approaches, a nonlinear identification method has been presented for a diode laser welding process in [7], where a single-input single-output (SISO) nonlinear continuous model is obtained for the process.…”

Laser Welding: Techniques of Real Time Sensing and Control Development

“…Some focused on the emission signals such as acoustic, infrared, ultraviolet, plasma, and so on (Shao 2005, Ostendorf 2003, Ono 1992, Li 2002, Steen 1986, Gu 1996. Others aimed to the weld pool images acquired with CCD cameras (Beersiek 2001, Zhang 1996, Na 2009, Beersiek 1999. …”

“…In 0, a camera system was developed to measure the surface geometric size of the weld pool. In (Na 2009, Zhang 1996,Beersiek 2000, a system for process monitoring of laser beam welding based on a CMOS-camera was presented. The system observed the welding process online and coaxial to the laser beam.…”

“…Others aimed to the weld pool images acquired with CCD cameras (Beersiek 2001, Zhang 1996, Na 2009, Beersiek 1999). Though it is promising, its application might be compromised by the complexity and noises in the laser welding.…”