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International Conference on Instrumentation, Measurement, Circuits and Systems (ICIMCS 2011)

Chen Ming
Chen Ming
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Carbon content in ash is one of the important factors to reflect thermal efficiency in the boiler and evaluate superiority and inferiority of the burning, but it is difficult to measure online, can get assay value by chemistry analysis offline at present. In this paper, establish the related main variates through the mechanism analysis, use multivariale linear regression method to build soft-sensing model, and give real- time monitoring reference predictive values of the carbon content in ash, and make rolling verification and correction according to the chemical test measured values. Through the practical operation in a 15t/h steam boiler, it verifies the good positive correlation between the model outputs and measured values, reflects the actual availability of this method of model building, and put some reference and guidance for the actual operation.

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