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Vision is one of the most powerful forms of non-contact sensory feedback for monitoring and control of manufacturing processes such as welding. Machine vision applications in welding have included the off-line determination of the locations of the workpieces to be welded (typically referred to as part-finding); the in-process correction of robot paths to compensate for fixturing inaccuracies, part tolerances, or weld distortions during welding (seam-tracking); the real-time sensing of weld joint and pool shape and geometry for welding process control; the automated inspection of the weld joint and bead surface shape [1,2]. However, welding poses particularly challenging problems to conventional optical sensing techniques. One of the major problems is the presence of the welding arc which is not limited to a single spectral region and thus cannot be easily filtered out optically. A novel vision sensing technique has been developed and is used to overcome the extreme variation in scene brightness created by the welding arc. The system incorporates intense pulsed laser illumination and synchronized shuttered image sensing to overpower the arc light and electronically produce a video image virtually free of arc glare. In this paper, we present an effort for the development of integrated monitoring and analysis techniques which combine the above mentioned laser video sensing techniques with extensive vision processing schemes and simultaneous monitoring and analysis of the arc signals and other process parameters. The comprehensive vision processing techniques are used for image enhancement, detection of important features, and calculation of relevant dimensional measurements. This information allows more effective monitoring by a human operator and better record keeping. It also provides reliable sensory feedback for realtime process control in robotic applications. This research effort is mainly sponsored by a Department of Energy (DoE) Small Business Innovation Research program for the development of novel integrated vision monitoring and analysis systems to be used in the fabrication, maintenance, and repair of nuclear reactor components. The developed techniques are also applicable to other critical robotic welding applications in the defense, aerospace, and other industries. The vision sensing techniques discussed in this paper have also been used in other applications where high luminosity of a combustion flame, an explosive event, or some form of plasma is present.
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