Slagging diagnosis of boiler based on wavelet packet analysis and support vector machine

doi:10.3785/j.issn.1008-973X.2016.08.011

JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE)

Energy engineering

Slagging diagnosis of boiler based on wavelet packet analysis and support vector machine

ZHONG Wei, PENG Liang, ZHOU Yong gang, XU Jian, CONG Fei yun

1.Institute of Thermal Science and Power System, Zhejiang University, Hangzhou 310027, China|

2. Institute of Thermal Power Engineering, Zhejiang University, Hangzhou, 310027, China|

3. Institute of Mechanical Design, Zhejiang University, Hangzhou, 310027, China|

4. Changzhou Engipower Technology Ltd. Co. Changzhou, 213022

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Abstract

A slagging fault diagnosis method based on support vector machine (SVM) and wavelet packet analysis of superheater tube panel vibration signal outside of the boiler was proposed in view of the slagging problem on heating surface during the running of a pulverized coal boiler in power station. The vibration signals of tube panel were collected according to the structural features of the boiler, which were analyzed with wavelet packet method. A slagging fault diagnosis model was established based on support vector machine using wavelet packet energy and time domain indexes of the tube panel vibration signals as feature vector. Results show that the model can identify different fault categories correctly with the tube panel signals measured in laboratory.

Published: 01 August 2016

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Cite this article:

ZHONG Wei, PENG Liang, ZHOU Yong gang, XU Jian, CONG Fei yun. Slagging diagnosis of boiler based on wavelet packet analysis and support vector machine. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2016, 50(8): 1499-1506.

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http://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2016.08.011 OR http://www.zjujournals.com/eng/Y2016/V50/I8/1499

基于小波包分析和支持向量机的锅炉结渣诊断

针对燃煤锅炉运行中管屏受热面的结渣问题,提出基于对炉外测量的管屏振动信号小波包分析和支持向量机的结渣故障诊断方法.根据锅炉过热器管屏的结构特征,采集过热器管屏炉外管段的振动信号进行小波包对信号分析,利用管屏振动信号的时域指标和小波包分解后的相对小波包能量作为特征向量,建立基于支持向量机的结渣故障诊断模型.结果表明,实验平台上该模型能够对过热器管屏不同结渣故障实现有效的诊断.

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