上海交通大学学报(自然版) ›› 2015, Vol. 49 ›› Issue (06): 830-836.
李元1,吴杰1,王国柱2
收稿日期:
2014-12-02
出版日期:
2015-06-29
发布日期:
2015-06-29
基金资助:
国家自然科学基金重点项目(61034006),国家自然科学基金项目(61174119,60774070)
LI Yuan1,WU Jie1,WANG Guozhu2
Received:
2014-12-02
Online:
2015-06-29
Published:
2015-06-29
摘要:
摘要: 针对贡献图分析方法在故障分离方面存在拖尾效应以及不能准确定位故障变量的问题,提出一种将k近邻(kNearest Neighbor, kNN)补值与传统贡献图相结合的故障定位方法.首先利用主成分分析建模并求取综合控制指标;然后将kNN方法与综合控制指标相结合初步提取故障变量;最终用贡献图从初步提取的故障变量中确定故障根源,该方法有效地避免了正常变量的贡献值对最终诊断结果的影响.本文运用数值算例和TE过程进行仿真,并将该方法与基于重构的贡献方法比较,验证了算法的准确性和有效性.
中图分类号:
李元1,吴杰1,王国柱2. k近邻补值方法在工业过程故障诊断中的应用[J]. 上海交通大学学报(自然版), 2015, 49(06): 830-836.
LI Yuan1,WU Jie1,WANG Guozhu2. k-Nearest Neighbor Imputation Method and Its Application in Fault Diagnosis of Industrial Process[J]. Journal of Shanghai Jiaotong University, 2015, 49(06): 830-836.
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