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

Author:

Xu Xiao Gang1,Wang Song Ling1,Liu Jin Lian1,Li Fei1,Wang Hui Jie1

Affiliation:

1. North China Electric Power University

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.

Publisher

Trans Tech Publications, Ltd.

Reference8 articles.

1. Junhu Hou, Songling Wang and Liansuo An: Proceedings of the CSEE. Vol. 23 (2003) No. 10, p.209 (In Chinese).

2. C Cortes, V. N Vapnik: Machine learning. Vol. 20 (1995), p.273.

3. P Wawrzynski, B Papis: Neurocomputing. Vol. 74 (2011), p.2893.

4. Wei Wua, Jian Wang, Mingsong Cheng and Zhengxue Li: Neural Networks. Vol. 24 (2011), p.91.

5. Zhonghe Han, Tiejun Wu: Compressor Blower & Fan Technology. Vol. 1 (2008), p.46 (In Chinese).

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3