Mark Gartner

A model for estimating penetration depth of laser welding processes

Penetration depth is one of the most important factors critical to the quality of a laser weld. However, no on-line, non-destructive method exists by which to inspect this quantity. Indirect, model-based estimation schemes are feasible solutions for monitoring laser welding processes. In this paper, a model for estimating penetration depth based on a 2D heat conduction model and a conical keyhole assumption is developed. This model relates the penetration depth to the incident power and the Peclet number, which is a function of the welding speed, the keyhole radius and thermal diffusivity. The Peclet number is determined by measuring the weld width on the top surface. The model is validated by a number of laser welds made to join a low-carbon steel hub and plate assembly using a 5 kW laser with different combinations of power and speed. The results show that the proposed model is consistent with the experimental data and is computationally efficient. Therefore, this model is suitable as a basis for model-based, on-line depth estimation schemes.

Sensor systems for real-time monitoring of laser weld quality

On-line process monitoring is beneficial for maintaining high quality products at high production rates and low cost. Off-line traditional testing of welds can be costly in terms of time, material, and productivity. Real-time nondestructive testing, however, can be just as accurate as off-line testing; yet faster, cheaper, and increase productivity, when perfected for high volume repetitive applications. In the field of real-time monitoring, various sensors have shown promise in detecting weld states. These include acoustic emission, audible sound, infrared detectors, ultraviolet detectors, electromagnetic acoustic transducers, and polyvinylidene fluoride. Nevertheless, previous work indicates that no single sensor can reliably detect the full spectrum of weld states. As a result, sensor fusion has been investigated for integrating the advantages of individual sensors. This article presents a survey of technical information that is currently available in the literature, commercial systems, and patents, fo...

Monitoring of laser weld penetration using sensor fusion

Depth of penetration is a critical parameter in laser welding. In many applications, full penetration is desired, but difficult to detect in real time. A sensor fusion system using infrared, ultraviolet, audible sound, and acoustic emission has been implemented for real time monitoring of CO2 laser lap welds in both laboratory and industrial production settings. Signals from the welds were analyzed by: (1) singular value decomposition with data fusion, (2) class mean scatter with decision fusion, (3) class mean scatter with feature fusion, and (4) singular value decomposition with decision fusion using minimum distance and quadratic classification. A classification rate of 100% was obtained for detection of full penetration for both laboratory and production settings.

Laser weld penetration estimation using temperature measurements

Penetration depth is an important factor critical to the quality of a laser weld. This paper examines the feasibility of using temperature measurements on the bottom surface of the work-piece to estimate weld penetration. A three-dimensional analytical model relating penetration depth, weld bead width and welding speed to temperature distribution at the bottom surface of the workpiece is developed. Temperatures on the bottom surface of the workpiece are measured using infrared thermocouples located behind the laser beam. Experimental results from bead-on-plate welds on low carbon steel plates of varying thickness at different levels of laser power and speeds validate the model and show that the temperature on the bottom surface is a sensitive indicator of penetration depth. The proposed model is computationally efficient and is suitable for on-line process monitoring application.

Predictive cathode maintenance of an industrial laser using statistical process control charting

The performance of a dc-excited transverse-flow CO2 laser welder can be adversely affected by many factors such as electrode arcing, optical contamination, poor maintenance, etc. Many of these factors which occur in production environments are unpredictable, and therefore, difficult to simulate in the laboratory or the laser manufacturer’s facilities. In this article the feasibility of using statistical control charts for laser condition monitoring was demonstrated. In particular, its application for predictive maintenance for the cathode and for verification of the effectiveness of cathode cleaning were investigated. The same approach is readily applicable to other laser components. With more experimental data, optimal control limits can be defined to dictate the maintenance schedule. Future work will include the development of an on-line user-friendly monitoring system that can be used to indicate the condition of the laser and warn the user should any abnormalities be observed. The proposed monitoring ...

A power distribution model of industrial CO2 lasers for system diagnosis

Industrial lasers are high power pieces of equipment that occasionally function under undesirable operating conditions. For example, the performance of a transverse‐flow d.c.‐excited gas laser can be adversely affected by many factors such as electrode arcing, poor lens and mirror cleanliness, focusing problems, improper gas mixture composition, poor gas quality, poor beam stability, poor beam path cleanliness, operator error, poor maintenance, poor chiller water temperature and flow rate stability, and improper laser beam ramp‐in/ramp‐out rates. Many of these factors which occur in the production environment are unpredictable and therefore difficult to simulate in the laboratory or the laser manufacturers facilities. In this paper, a power distribution model of a transverse flow d.c.‐excited CO2 laser is developed and validated to link the input discharge power to the output laser beam power, as well as the heat losses. This model establishes a foundation for monitoring the laser performance by measurin...

Time-frequency analysis of laser weld signature

Reliable monitoring methods are essential for maintaining a high level of quality control in laser welding. In industrial processes, monitoring systems allow for quick decisions on the quality of the weld, allowing for high productions rates and reducing overall cost due to scrap. A monitoring system using infrared, ultraviolet, audible sound, and acoustic emission was implemented for monitoring CO2 laser welds in real-time. The signals were analyzed using time-frequency analysis techniques. The time-frequency distribution using the Choi-Williams kernel was calculated, and the resulting distributions were analyzed using the Renyi information distribution. Results for porosity monitoring showed that an acoustic emission sensor held the most promise with 100% classification in two weld studies. These encouraging results led to a second study for monitoring of weld penetration and in the second case, infrared, ultraviolet, and audible sound showed the most promise with 100% classification for both laboratory and industrial data.

A Dynamic Model for Condition Monitoring of a High-Power CO2 Industrial Laser

Industrial laser systems handle high power consumptions and may function under undesirable operating conditions if the systems are not properly maintained. It is sometimes difficult to diagnose why a laser is not functioning properly because the optical output is the result of complex interactions among many parameters such as the total gas pressure, effectiveness of the laser cooling system, operating environment, and gradual deterioration of laser components. In this paper, a dynamic power distribution model is developed to characterize the power distribution of a high-power transverse-flow DC-excited CO 2 laser to account for dynamic effects such as continuously ramping up and down the laser output power and the cyclic nature of the chiller. The model contains the essential dynamic features of a CO 2 laser system and yields solutions sufficiently accurate for practical diagnostic purposes.

Real-time monitoring of laser weld penetration using sensor fusion

Depth of penetration is a critical parameter in laser welding. In many applications, full penetration is desired, but difficult to detect in real-time. A sensor fusion system using infrared, ultraviolet, audible sound, and acoustic emission has been implemented for real time monitoring of CO2 laser lap welds in both laboratory and industrial production settings. Signals from the welds were analyzed by: (1) singular value decomposition with data fusion, (2) class mean scatter with decision fusion, (3) class mean scatter with feature fusion, (4) singular value decomposition with decision fusion. Classification results for detection of full penetration and inadequate penetration were 100% for laboratory results and 68% – 100% in a production setting.Depth of penetration is a critical parameter in laser welding. In many applications, full penetration is desired, but difficult to detect in real-time. A sensor fusion system using infrared, ultraviolet, audible sound, and acoustic emission has been implemented for real time monitoring of CO2 laser lap welds in both laboratory and industrial production settings. Signals from the welds were analyzed by: (1) singular value decomposition with data fusion, (2) class mean scatter with decision fusion, (3) class mean scatter with feature fusion, (4) singular value decomposition with decision fusion. Classification results for detection of full penetration and inadequate penetration were 100% for laboratory results and 68% – 100% in a production setting.