Algorithms on determining the correlation laws between ultrasonic images and quality of spot welds.

Conventional quality control devices for spot welding cannot perform on-line inspection and provide feedback to the welding control system. In this way, the traditional quality control systems are similar to statistical welding parameters monitoring systems. It is imperative to combine the idea of on-line quality inspection with closed-loop feedback control in a robust control system. However, there is no single acoustic method to date capable of manipulating real-time control and on-line quality inspection, concurrently, since specific procedures (e.g. scanning time and adjustment time) need to be adopted by traditional acoustic microscopes to retrieve proper information, and these procedures tend to disable the real-time and on-line capability of acoustic microscopy. With recent hardware improvements, the novel portable acoustic device is able to reduce the scanning time to real-time fashion without losing any significant data. On the other hand, the adjustment time of the portable acoustic device can be reduced noticeably by employing intelligent control software instead of human operators. This new hardware-software configuration will be an ideal approach to the on-line, real-time nondestructive inspection of spot welds. The primary goal of this research is to develop an intelligent system to accomplish the on-line, real-time nondestructive inspection for spot welds. The following objectives were fulfilled to reach the final goal. (1) Classification of the acoustic images of spot welds. (2) Quantification of acoustic information as parameters. (3) The study of the influence of each parameter on the strength of spot welds. (4) Identification of important and significant parameters. (5) Integration of these parameters into the knowledge base of the software. The system developed can be an on-line advisor that is capable of providing critical information about the quality of spot welds during the process. Furthermore, this system is able to render warning signals to the process control unit to prevent further mistakes.Dept. of Industrial and Manufacturing Systems Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis1999 .L33. Source: Dissertation Abstracts International, Volume: 66-02, Section: B, page: 1132. Advisers: Roman Maev; Michael Wang. Thesis (Ph.D.)--University of Windsor (Canada), 1999