Empirical modeling for real-time weld process control and generator monitoring
- American Welding Inst., Knoxville, TN (United States)
Artificial Neural System (ANS), also known as neural network, is an attempt to develop computer systems that emulate the neural reasoning behavior of biological neural systems (e.g., the human brain). As such, they are loosely based on biological neural networks. The ANS consists of a series of nodes (neurons) and weighted connections (axons) that, when presented with a specific input pattern, can associate specific output patterns. It is essentially a highly complex, non-linear, mathematical relationship or transform. These constructs have two significant properties that have proven useful to the authors in signal processing and process modeling: noise tolerance and complex pattern recognition. Specifically, the authors have developed a new network learning algorithm that has resulted in the successful application of ANS to high speed signal processing and to developing models of highly complex processes. Two of the applications, the Weld Bead Geometry Control System, and Welding Penetration Monitoring System are discussed in the body of this paper. Additionally, the authors have developed a signal analysis technique for a gear monitoring system. Such a system would be particularly useful in the engine health monitoring of field welding power systems.
- OSTI ID:
- 72654
- Journal Information:
- Bulletin - Welding Research Council, Journal Issue: 397; Other Information: PBD: Dec 1994
- Country of Publication:
- United States
- Language:
- English
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