摘要
压缩机是工业领域的一类重要生产设备,运行过程中存在诸多的不稳定因素,如转子系统振动、轴承结合不良、元件滑落等。以压缩机中的转子振动故障为研究对象,用数据挖掘中的可辨识矩阵方法进行属性约简,用C4.5方法进行分类,得到故障诊断规则,通过诊断规则可以预测压缩机故障的发生。
Compressor is a kind of important production equipment in the industrial field,there are many unstable factors in the operation process,such as rotor system vibration,poor bearing combination,components slide and so on.In this paper,the rotor vibration fault in the compressor is taken as the research object,the identification matrix method in data mining is used for attribute reduction,and the C4.5 method is used for classification,and the fault diagnosis rules are obtained.The occurrence of compressor faults can be predicted by the diagnosis rules.
作者
侯国安
田舟祺
Hou Guo'an;Tian Zhouqi(Yinchuan Energy College,Yinchuan Ningxia 750015)
出处
《山西化工》
2022年第2期212-215,共4页
Shanxi Chemical Industry
基金
宁夏回族自治区自然科学基金《具有抗微生物活性的3′-prenylisoflavone异黄酮类化合物的首次全合成及抗菌活性研究》(2020A0363)
银川能源学院校级重点科研项目(2019-KY-Z-01)。
