关键词: 灰色模糊, 熵权法, 综合性能评价, 飞灰含碳量, 信息熵

Abstract: Aiming at the problems that the comprehensive performance evaluation of combustion detection instruments of thermal power units was difficult to achieve due to the complex structure, numerous indexes and difficult to quantify, a comprehensive performance evaluation method was proposed based on information entropy-grey fuzzy fusion model, and an information entropy-grey fuzzy evaluation model was established. The proposed method was compared and verified by 3 detection methods of the engineering examples of carbon content in fly ash of generator sets. The fuzzy mathematics was used to quantify the 3 types of language scales, such as instrument performance, applicable performance and risk performance, and the model inputs were established by normalizing 11 indexes from the optimal membership degree. The coupling correlation degree between the inputs was comprehensively considered by the grey correlation coefficient matrix, and the entropy weight method was used to replace the traditional expert method, eliminating the subjective influences of the weighting processes. The comparison results show that the secondary index weights of 3 schemes account for 14.63%, 58.51% and 26.86% of the total respectively under the eliminating human interference environments. The membership degrees of the optimal result 1 are as 0.4265, 0.6642 and 0.9673 respectively. Compared with the single factor analysis method, the model has consistency in the evaluation results, and shows better comprehensive evaluation efficiency in multi data analysis and eliminating human interference.

Key words: grey fuzzy, entropy weight method, comprehensive performance evaluation, carbon content in fly ash, information entropy