Open AccessSteam Turbine Performance Evaluation Based on Principal Component Analysis and Information Entropy
Author(s) -
Chunmei Lu,
Taiyan Zhang,
Xiaofeng Liu,
Yongling Yao,
Chen Hua-gui
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/571/1/012119
Subject(s) - principal component analysis , power station , entropy (arrow of time) , fuzzy logic , steam turbine , data mining , computer science , turbine , benchmark (surveying) , thermal power station , reliability engineering , artificial intelligence , engineering , mechanical engineering , thermodynamics , physics , geodesy , geography , electrical engineering , waste management
Information entropy and fuzzy analytical theory were combined and applied on the state assessment of power plant steam turbine unit. This method can be combined with the measured data of power plant, and made a comprehensive evaluation of the different working conditions. Fuzzy analysis of the original matrix can be a evaluation matrix, and the information entropy was introduced to solve the problem of calculating the weight of multi attribute factor set. Once the attribute weight is determined, the comprehensive evaluation value corresponding to the different working conditions can be defined and calculated. The results obtained by this method were compared with those obtained by the principal component analysis method. And the results obtained by information entropy method were objective and unique. The superiority of the method was verified. Under all conditions, the comprehensive evaluation value can be used as one index of the thermal archives as a benchmark for fault diagnosis, which provided a new idea and evaluation method for steam turbine fault diagnosis, and had a strong basic research and practical application value.