Abstract
In order to realize real-time measurement and identification of moisture as received basis in coal-fired power plants, a soft-sensing model is built in this chapter. By introducing mechanism of energy conversation inside the pulverizing system, the model can rationally discriminate between the high calorific value coal (HCV coal) and low calorific value coal (LCV coal) through one distributed computing software. For verification, mass data from field are adopted to show the accuracy and reliability of the model in practical application with coal fluctuation. Identification results show that the model can calculate multiple mills’ moisture and summarize to the weighted results through weighting coal feed quantity, and this method can be utilized to meet the need of power plant depending on proximate analysis. The soft-sensing model based on mechanism analysis can effectively measure the moisture of firing coal and thus the problem of safe operation of boiler will be solved.
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Huang, X., Tang, H., Chi, D. (2014). Moisture Real-Time Identification for Utility Boiler Based on Mechanism Analysis. In: Xing, S., Chen, S., Wei, Z., Xia, J. (eds) Unifying Electrical Engineering and Electronics Engineering. Lecture Notes in Electrical Engineering, vol 238. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-4981-2_7
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DOI: https://doi.org/10.1007/978-1-4614-4981-2_7
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