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A Performance Evaluation Method of Coal-Fired Boiler Based on Neural Network

机译:基于神经网络的燃煤锅炉性能评价方法

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摘要

According to the evaluation and control of energy-saving and emission reduction performance of coal-fired boilers, the performance indexes of boiler combustion and emissions were studied, and a performance evaluation and control method based on neural network was proposed. Firstly, the influencing factors of boiler combustion emission are analyzed. A boiler combustion emission evaluation model based on AdaBoost-BP algorithm is designed. The model is trained and tested by coal-fired power plant data and national emission standards, and the principal component analysis method is adopted. The core parameters are adjusted to get the best control solution. Finally, experiments show that the model and method have better advantages in comparison with similar methods.
机译:根据燃煤锅炉节能减排性能的评价和控制,研究了锅炉燃烧和排放的性能指标,提出了一种基于神经网络的性能评估和控制方法。首先,分析了锅炉燃烧排放的影响因素。设计了一种基于Adaboost-BP算法的锅炉燃烧发射评估模型。该模型经过培训并通过燃煤发电站数据和国家排放标准进行培训,并采用了主要成分分析方法。调整核心参数以获得最佳控制解决方案。最后,实验表明,与类似方法相比,该模型和方法具有更好的优势。

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