热力发电2018，Vol.47Issue(3)：32-37,6.DOI:10.19666/j.rlfd.201706059
基于模糊分析与信息熵的大型机组故障诊断基准值研究
Research on fault diagnosis benchmark of large scale unit based on fuzzy analysis and information entropy
摘要
Abstract
Under all conditions,the comprehensive evaluation value can be used as the benchmark for fault diagnosis of thermal archives.In this study the information entropy and fuzzy theory are fused together and then introduced to the state assessment of power plant steam turbine unit under different conditions.Fuzzy analysis of the original matrix for thermal parameters can be used to obtain an evaluation matrix.And the information entropy is used to calculate the multi-attribute factors and their weights.Finally,the corresponding comprehensive evaluation values under different working conditions can be calculated.The results show that,compared with the comprehensive evaluation values obtained by the principal component analysis method,the attribute weight calculation of evaluation matrix is accurate and objective,and the results obtained by the information entropy method are objective and unique.关键词
信息熵/模糊分析/主成分分析/热力参数/综合评价/故障诊断/汽轮机Key words
information entropy/fuzzy analysis/principal component analysis/thermal parameters/comprehensive evaluation/fault diagnosis/steam turbine分类
能源科技引用本文复制引用
王惠杰,张家宁,王雷雨,赵立坤..基于模糊分析与信息熵的大型机组故障诊断基准值研究[J].热力发电,2018,47(3):32-37,6.基金项目
中央高校基本科研业务费专项资金资助(916021209)Foundametal Research Funds for the Central Universities (916021209) （916021209）
