Application of ultrasonic vibrations in welding and metal processing: A status review

A method and apparatus for welding include initiating a pulse welding process includes initiating a welding arc by providing CC type welding power, maintaining the arc by providing CV type power. Then, pulse type welding power is provided. The method and system can be used to start short circuit, or other welding processes by providing short circuit power, or welding power of a given mode, instead of providing pulse power. Also, in one alternative, a method and system of initiating a pulse, short circuit, or given welding process includes initiating a welding arc by providing CC type welding power at least until a pseudo-equilibrium for the arc is established. Then, providing welding power in a pulse, short circuit, or the given mode.

Method and apparatus for welding

Artificial neural network modeling of weld joint strength prediction of a pulsed metal inert gas welding process using arc signals

This paper addresses the problems involved in the automatic monitoring of the weld quality produced by robotized short-arc welding. A simple statistical change detection algorithm for the weld quality, the repeated Sequential Probability Ratio Test (SPRT), was used. The algorithm may similarly be viewed as a cumulative sum (CUSUM) type test, and is well-suited to detecting sudden minor changes in the monitored test statistic. The test statistic is based on the variance of the weld voltage, wherein it will be shown that the variance decreases when the welding process is not operating under optimal conditions. The performance of the algorithm is assessed through the use of experimental data. The results obtained from the algorithm show that it is possible to detect changes in weld quality automatically and on-line.

On-line quality monitoring in short-circuit gas metal arc welding

Industrial robots play an important role in industry, due to their flexibility. Many applications (almost all that require human intervention) may be performed with advantages by robots. Nevertheless, set‐up operations, necessary when changing production models, are still tricky and time‐consuming. It is common to have detailed data of working pieces in computer aided design (CAD) files, resulting from product design and project. This information is not used satisfactorily, or even not used at all, for robot programming. In this paper, we propose a solution capable of extracting robot motion information from the CAD data.

CAD interface for automatic robot welding programming

This paper addresses the problem of automatic monitoring the weld quality produced by robotised short arc welding. A simple statistical change detection algorithm for the weld quality, recursive sequential probability ratio test (SPRT), is used. The algorithm may equivalently be viewed as a cumulative sum (CUSUM) type test. The test statistics is based upon the variance of the amplitude of the weld voltage. It is shown that the variance of the weld voltage amplitude decreases when the welding process is not operating under optimal condition. The performance of the algorithm is evaluated using experimental data. The results obtained from the algorithm indicate that it is possible to detect changes in the weld quality automatically and on-line.

I. Claesson

Papers

On-line quality monitoring in short-circuit gas metal arc welding

Quality monitoring in robotised welding using sequential probability ratio test