摘要
液压油的性能是由众多指标共同决定,其质量优劣直接影响设备的稳定运行与否。笔者选取黏度变化率、酸值等5个参数作为评价油液性能的重要指标,并采用模糊推理和神经网络评价这2种方法对油液的综合性能进行评价,并将这2种评价方法得到的结果与实际情况对比,分析各种方法存在的缺点及原因。并以模糊推理法为理论基础,对神经网络评价法提出相应的改进措施,不断修正其评价结果,使之与实际情况相符,确立一个准确、有效的评价方案。
The performance of the hydraulic oil is determined by many indicators, it directly affects the stable operation of the equipment. In the paper, five parameters such as viscosity and acid value etc. as the important indices of appraising the oil performance, and fuzzy reasoning method and neural network appraisement method were applied to appraise the comprehensive performance of the oil. And then, the appraisement results separately obtained by the two methods were contrasted with actual status, and the shortcomings of the two methods and their causes were analyzed. In addition, the fuzzy reasoning method was taken as the theoretical basis, and improvement of the neural network appraisement method was proposed, so as to continually correct the appraisement results to make it accord with actual status. Thus, an accurate and effective appraisement scheme was identified.
出处
《矿山机械》
2016年第2期82-85,共4页
Mining & Processing Equipment
关键词
液压油
性能评价
模糊推理
神经网络
hydraulic oil
performance appraisement
fuzzy reasoning
neural network