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传统的齿轮故障诊断及状态评估建立在对典型故障机理的研究和特征提取的基础上,往往忽视温度、湿度、PH值等环境因素对齿轮可靠运行带来的影响。同时,即便在考虑环境因素的一些健康状态评估方法中,也存在处理定性语言描述的环境因素时受到很大主观因素干扰的问题,影响了评估的准确性。针对以上问题,引入云模型,对定性的环境因素语言描述进行定量不确定性转换,建立了基于云模型的齿轮健康状态评估模型,使其更符合实际情况,通过案例验证了该方法的实用效果。
Based on the research on the typical fault mechanism and the feature extraction, traditional gear fault diagnosis and condition assessment often ignore the influence of environmental factors such as temperature, humidity and PH on the reliable operation of the gear. At the same time, even in some health assessment methods that consider the environmental factors, there are some problems that are disturbed by the subjective factors when dealing with the environmental factors described in the qualitative language, which affects the accuracy of the assessment. In view of the above problems, a cloud model is introduced to quantitatively convert the qualitative description of environmental factors to uncertainty. A gear health assessment model based on cloud model is established to make it more realistic. The practical results of the method are validated by the case studies .