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新型管芯式散热器既有良好的散热性和抗振性,又维修方便,在工作条件恶劣的矿用汽车上应用优势明显。通过分析影响散热器传热性能的主要因素,利用改进BP神经网络方法建立新型矿用管芯式散热器传热性能预测模型,并利用建立的阻力性能计算模型编制预测阻力性能的程序,对具有2、3、4排管芯式散热器的热工性能作出预测,同时,搭建风筒试验台架对管芯式散热器进行热工性能试验。通过比较预测结果和试验结果发现,两者相对误差在±5%左右,可用于工程设计。
The new tube radiator has both good heat dissipation and vibration resistance, and easy maintenance, mining conditions in the poor mining applications obvious advantages. By analyzing the main factors that affect the heat transfer performance of the radiator, a new BP neural network method is used to establish the heat transfer performance prediction model of the new mine tube radiator, and the program of predicting the resistance performance is established by using the established resistance performance calculation model. 2,3,4 rows of radiator core thermal performance prediction, at the same time, build a hairdryer test bench thermal performance of the die-sink radiator. By comparing the prediction results with the experimental results, it is found that the relative error between the two is about ± 5%, which can be used in engineering design.