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Method for predicting rise of temperature of fitting based on fuzzy system

WANG Gang;TAN Shengwu;LIN Shengjun;CHANG Linjing;LI Junhui;Pinggao Group Co.,Ltd.;  
To elevate the veracity of predicting the rise of temperature of connection fitting,an improved particle swarm optimization algorithm was constituted by incorporating recursive least square algorithm into basic particle swarm optimization algorithm.Training data and testing data were obtained from experiment.Fuzzy system is adjusted through training data,and training algorithms are basic particle swarm optimization algorithm,recursive least square algorithm and the improved particle swarm optimization algorithm respectively.The convergence effect of the improved particle swarm optimization algorithm is better than that of the other two algorithms.Through training data,the model of the rise of temperature of connection fitting in value hall is found by regression analysis.All models are tested by testing data,the prediction effect of the fuzzy system trained by the improved particle swarm optimization algorithm is the best of all models.The prediction results show that if training data is enough,the fuzzy system trained by the improved particle swarm optimization algorithm is reliable to predict the rise of temperature of connection fitting.
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