摘要
异常运行状态数据获取困难是制约机械状态评估的主要因素。针对此问题,将模糊数学原理与基于免疫机理的否定选择算法应用于机械状态评估中,该算法在对机械正常运行数据学习的基础上就可对机械进行状态评估。通过对齿轮运行状态的检测结果表明,该方法对在异常数据缺乏的情况下的机械状态评估问题是可行有效的,为机械的状态评估提供了有效途径。
Shortage of abnormal condition samples is the main reasons that restricting the mechanical condition assessment.In order to solve this problem, the fuzzy mathematics principle and negative selection algorithm based on immune mechanism were used in the mechanical condition assessment, with this method, the mechanical condition assessment can be carried out on the basis of the data to the normal operation of mechanical learning .The detection results of the gear running show that the method is feasible and effective in the abnormal data under the condition of lack of mechanical state evaluation problem, and provides an effective way for machinery condition assessment.
出处
《机械研究与应用》
2014年第1期44-46,50,共4页
Mechanical Research & Application
关键词
机械状态评估
免疫机理
否定选择
machine condition assessment
immune mechanism
negative selection
