Study On The Radiative Properties Of Particulate Media In Coal-firing Boiler And Combustion Optimizing Technique

As the world economic growing, energy and environment problems have been more serious than ever especially for our developing countries. As the primary coal-firing power plant boiler model, 300MWe corner-firing tangential boilers have been the mainly fossil fuel consumer and air contaminations producer. The stability, efficiency and safety operation of the boiler combustion process is all-important for our country's continual economic development. During the last several years many optical measurement and analysis techniques have been introduced for non-invade boiler internal combustion process diagnostic, such as boiler-section-temperature distribution reconstruction based on flame images. And also some artificial intelligence techniques have been used for combustion optimizing such as neural networks and etc. The object of this paper is to establish an expert system for boiler combustion operation optimizing based on the radiative property of the boiler inside particulate media integrated with boiler operation parameters such as boiler load, drum pressure and also.The radiative property of the solid particles inside the boiler were calculated and discussed based on Rayleigh and Mie scattering theories. The affection of the complex refractive index for different radius distribution particle clouds was analysis. The band model and line-by-line model have been used to calculated the absorption coefficient of molecular gases, and also the temperature and pressures band widen effect were discussed. Based on the discussed results, multi-wavelength extinction method integrated with modified evolution program was provided for particles radius distribution sizing. And a diode tunable laser detector was used to measure the gas concentration by gas molecular spectrum-line broaden mechanism.In this paper , the backward Monte Carlo method was improved to analysis the radiative intensity received by the detector located at the boiler water cooler walls based on the output of the CFD simulationThe BP neural network's fast mapping techniques and interpolated filtered back projection algorithm were introduced for on-line section temperature-distribution diagnostic.In this paper an expert system was provided for combustion optimizing and diagnostic based on boiler flame image information integrated with boiler operation parameters through object oriented method and self-organization neural networks. The implementation of the expert system on 300MWe boiler was discussed.The last part of this paper discussed boiler fuel control optimizing strategy based on the radiative intensity detected by photon-electronic sensor. And some in situ experiments were done to evaluate the feasibility of the optimizing strategy.