On-Line Fan Monitoring System Based on Improved Intelligent Regression Algorithm

Abstract:

The running state of the fan has significant influence on the safety and economy of the power plant unit, so it is necessary to monitor the fan performance and running state in real time. According to the basic theory of the fan, there is a stable, good nonlinear mapping relation between the inlet pressure difference and flow, which can be utilized to monitor the flow of the fan. Thus, the fan differential pressure - flow curve model is established by the optimized BP neural network and the modified Support Vector Machine (SVM). The fitting error shows that the improved SVM model is better. Finally, the on-line fan monitoring system software is established by using Visual Basic (VB) language and Matlab programming based on the improved SVM fan differential pressure - flow curve model, which can accurately monitor the fan operation.

• Periodical: Applied Mechanics and Materials (Volumes 291-294)
• Pages: 1874-1879
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.291-294.1874
• Online since: February 2013
• Authors: Xiao Gang Xu, Song Ling Wang, Jin Lian Liu, Fei Li, Hui Jie Wang
• Keywords: Fan Performance, Neural Network (NN), Online Monitoring, Optimization, Support Vector Machine (SVM)

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