Sparse Random Projections of Camera Images for Monitoring of a Combustion Process in a Gas Burner
Résumé
In this paper we present a fast and easy method of quality monitoring for processes observed by cameras. A process of combustion in an industrial gas burner is used as an example. It is shown that we can observe only a small randomly chosen part of subsequent camera images. We propose a few, working in parallel manner, quality control charts. These Shewart type charts operate on squared norms of sparse partial image projections. Each chart is used for monitoring only a part of the whole camera image. The charts provide a partial decision about the state of the monitored system. A final decision is the logical product of these partial decisions. A simulation study based on 144 images of a working gas burner is presented.
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