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A method of diagnosing leakage of boiler steam and water pipes based on genetic neural network

机译:基于遗传神经网络的锅炉汽水管道泄漏诊断方法

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It is of great significance to study the method of diagnosing leakage of boiler steam and water pipe so as to improve safety and economy of the power plant. According to the characteristics of the power plant boiler, the model of diagnosing fault is established with the method of BP neural network optimized with genetic algorithm. On this basis, simulation experiments were carried out to diagnosing fault. Diagnosis results show that the optimized model can diagnose fault accurately and timely.
机译:研究诊断锅炉蒸汽,水管泄漏的方法,对于提高电厂的安全性和经济性具有重要意义。根据发电厂锅炉的特点,采用遗传算法优化的BP神经网络方法建立故障诊断模型。在此基础上,进行了故障诊断的仿真实验。诊断结果表明,优化后的模型可以准确,及时地诊断故障。

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