Hugo O. Garces

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We present a study for optimization of a combustion process based on optical measurements. First, we adapt a data-driven Hammerstein model on optical and key variables in a laboratory scale boiler. We then discuss the concepts of combustion diagnosis, optimization based on flame spectrum analysis and the inclusion of optical variables in the control system.(More)
In this work, the theoretical fundamentals and the experimental results of combustion control for a ladle furnace preheating process are presented, featured by a high fuel consumption and their subsequent high operational temperatures. The ladle furnace preheating process maximize the ladle's inner refractory temperature, via combustion. The highlights of(More)
This work presents a non-parametric method based on a principal component analysis (PCA) and a parametric one based on artificial neural networks (ANN) to remove continuous baseline features from spectra. The non-parametric method estimates the baseline based on a set of sampled basis vectors obtained from PCA applied over a previously composed continuous(More)
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