基于小波分析的水轮机故障诊断研究
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摘要
随着传感技术、信号处理技术、计算机网络技术、模糊数学以及神经网络的迅速发展，世界各国对设备状态监测、故障诊断的研究和实践水平不断提高，逐步形成完整的理论和实践体系，检修体制逐步由计划检修向状态检修发展。为实现状态检修，应大力发展和引进故障诊断技术。对于水轮发电机而言，故障诊断将成为今后确定水电机组是否检修的依据，因此，尽快实施水电机组故障诊断是发展的方向。
状态非平稳信号是故障诊断的重要依据，在状态监测中是远未成熟的关键问题。状态非平稳信号可以表征某些故障的存在，表征它的特征量也会发生变化，因此只要故障源存在，这种故障的信息就会通过信号特征信息表现出来。本文结合理论和实际应用详细论述了非平稳状态信号特征信息抽取和故障信号分离。
小波包分析能有效地提取水轮机振动信号中的有用成分，作为故障诊断的依据。本文用小波包分析对水轮机故障诊断进行了研究。
故障信号特征信息的抽取，也称为故障信号分离，涉及到如何用尽可能少的数据表征最大的信息的问题。这是信号处理、模式识别领域的关键问题。信号在小波域的表征是稀疏的，因此小波变换具有降维特性。本文从空间变换和信息熵的角度，在小波域内消除冗余信息，去相关，提取非平稳信号的特征信息；进而达到故障信号分离的目的。针对状态监测非平稳信号特征信息抽取。
本文从实际和理论做了以下研究，主要内容：
1．在windows2000系统中，采用borland c++ bulider开发工作站的诊断系统，实现了对中间层数据库服务器的通信以及控制和设置。
2．针对故障信息的提取，论述Fourier分析、短时傅立叶变换(STFT)的假设前提，从理论上分析Fourier变换的不足和局限性。依据小波变换多分辨率分析(MRA)能够自适应性描述状态非平稳信号局部时频信息，易于故障信息的抽取。
3．详细介绍小波理论，连续小波，小波包变换及性质。详细阐述小波基的数学特性，分析了它们对实际应用的影响和作用。针对不同的分析信号、信号不同的时频结构、不同的分析目的，论述了选取小波基函数和小波变换的基本原则。
4．论述了故障信号分离即故障信号重建，是从测量空间到信号特征空间特征信息的抽取过程，故障诊断最终决策判断的过程实际上也是降低“不确定性”的过程。
5．针对高频振动信号，本文实现了一种基于信号能量在小波包空间的分布特性，消除信号白噪声和有色噪声，利用频带分割技术，提取信号特征信息的方法。计算各子空间的能量，抽取低维特征矢量，给出小波包网络的频带分析和故障诊断
武汉大学硕士学位论文
方法。以水轮机机架的振动信号为例，验证了这种抽取特征信息的方法，在强噪
声背景下高频信号故障识别中的有效性，这种方法简化了决策网络，减少了诊断
误差。
With the high-speed development of sensor, signal processing, network, fuzzy math & nerve network technology, and the improved level of research & practice on device state monitoring and faults diagnosis of every country in the world, the traditional plan periodic examine and repair mode are gradually changing into state repair mode. In order to realize state repair, should fetch in and develop faults diagnosis technology. As to hydraulic generator, faults diagnosis is the basis of examine and repair, so it is necessary to put it in practice.
It is the unsteady signal component analyzing that FDI (Fault Detection and Isolation) mainly according to which is the important subject of modern Data Signal Processing. Moreover, this is the sixty-four-dollar question in Condition Monitoring field without good solution. The fault is described by unsteady signal, the signal's feature vectors change correspondingly. So if there is fault, the feature information emerges out form signals. The paper dissertate unsteady signal feature extraction and fault signal isolation in detail combining theory and application.
Wavelet package analysis can pick up the useful information of the Hydraulic Generators, which is regarded as evidence to diagnosis fault. The paper studies wavelet package analysis and the NN used on fault diagnosis of Hydraulic Generators.
The fault character information extracting, comes down to the question how represent maximal information with minimal datum as possible as we can. This is the sixty-four-dollar question of signal processing and pattern identification. Signal is represented sparsely in wavelet domain, namely wavelet transform has the property of dimension reduction. This paper eliminates signal redundant information, de-correlates signal correlated information in wavelet domain and extracts unsteady signal character information in wavelet space, namely "entropy compression"; this paper separates mixture observation signals, namely de-correlates signal correlated information successfully.
The main content as following:
1. The paper use BCB to realize the communication between the workstation and the blind SQL Server in windows 2000.
2.This paper discusses hypothesizes of Fourier Transform (Short Time Fourier Transform). Basing on theory, this paper explains the shortcoming of Fourier
0
Transform. With the information carrier of wavelet atom for unsteady signal, the Multi-Resolution Analysis of Wavelet Transformation describes unsteady signal time-frequency information adaptively which is apt to feature extraction.
3. The Wavelet theory, Wavelet Frame Theory, Continuous Wavelet Transform (CWT), Discrete Wavelet Transform, Wavelet Packet Transform and Wavelet Packet Network are discussed in detail. The paper dissertate the mathematic property of wavelet basis function and their influence to application. The paper gives some principals for selecting wavelet basis and wavelet transform scheme for different signal, different signal, different signal time-frequency structure and different analysis aim.
4. when the fault signal is separated, namely, fault signal re-construction is procession of fault character information extraction from measure space. The system uncertainty decreases in the Fault Detection and Isolation processes.
5.As for high oscillation vibration signal, this paper discusses in detail the property of wavelet packet energy distribution, white-noise and color-noise elimination, low-dimension feature information vectors extraction and the fault diagnosis system realization with wavelet packet analysis and signal energy frequency band analysis. An example of high frequency signal of hydro-generator is given. A perfect method is designed that improves the capability of FDI of WNN, extracts the character low dimension vectors of fault information and takes the vectors as the input data of WNN, so as to simplify the structure and improve the convergence speed of the WNN and reduce diagnosis errors.
状态非平稳信号是故障诊断的重要依据，在状态监测中是远未成熟的关键问题。状态非平稳信号可以表征某些故障的存在，表征它的特征量也会发生变化，因此只要故障源存在，这种故障的信息就会通过信号特征信息表现出来。本文结合理论和实际应用详细论述了非平稳状态信号特征信息抽取和故障信号分离。
小波包分析能有效地提取水轮机振动信号中的有用成分，作为故障诊断的依据。本文用小波包分析对水轮机故障诊断进行了研究。
故障信号特征信息的抽取，也称为故障信号分离，涉及到如何用尽可能少的数据表征最大的信息的问题。这是信号处理、模式识别领域的关键问题。信号在小波域的表征是稀疏的，因此小波变换具有降维特性。本文从空间变换和信息熵的角度，在小波域内消除冗余信息，去相关，提取非平稳信号的特征信息；进而达到故障信号分离的目的。针对状态监测非平稳信号特征信息抽取。
本文从实际和理论做了以下研究，主要内容：
1．在windows2000系统中，采用borland c++ bulider开发工作站的诊断系统，实现了对中间层数据库服务器的通信以及控制和设置。
2．针对故障信息的提取，论述Fourier分析、短时傅立叶变换(STFT)的假设前提，从理论上分析Fourier变换的不足和局限性。依据小波变换多分辨率分析(MRA)能够自适应性描述状态非平稳信号局部时频信息，易于故障信息的抽取。
3．详细介绍小波理论，连续小波，小波包变换及性质。详细阐述小波基的数学特性，分析了它们对实际应用的影响和作用。针对不同的分析信号、信号不同的时频结构、不同的分析目的，论述了选取小波基函数和小波变换的基本原则。
4．论述了故障信号分离即故障信号重建，是从测量空间到信号特征空间特征信息的抽取过程，故障诊断最终决策判断的过程实际上也是降低“不确定性”的过程。
5．针对高频振动信号，本文实现了一种基于信号能量在小波包空间的分布特性，消除信号白噪声和有色噪声，利用频带分割技术，提取信号特征信息的方法。计算各子空间的能量，抽取低维特征矢量，给出小波包网络的频带分析和故障诊断
武汉大学硕士学位论文
方法。以水轮机机架的振动信号为例，验证了这种抽取特征信息的方法，在强噪
声背景下高频信号故障识别中的有效性，这种方法简化了决策网络，减少了诊断
误差。
With the high-speed development of sensor, signal processing, network, fuzzy math & nerve network technology, and the improved level of research & practice on device state monitoring and faults diagnosis of every country in the world, the traditional plan periodic examine and repair mode are gradually changing into state repair mode. In order to realize state repair, should fetch in and develop faults diagnosis technology. As to hydraulic generator, faults diagnosis is the basis of examine and repair, so it is necessary to put it in practice.
It is the unsteady signal component analyzing that FDI (Fault Detection and Isolation) mainly according to which is the important subject of modern Data Signal Processing. Moreover, this is the sixty-four-dollar question in Condition Monitoring field without good solution. The fault is described by unsteady signal, the signal's feature vectors change correspondingly. So if there is fault, the feature information emerges out form signals. The paper dissertate unsteady signal feature extraction and fault signal isolation in detail combining theory and application.
Wavelet package analysis can pick up the useful information of the Hydraulic Generators, which is regarded as evidence to diagnosis fault. The paper studies wavelet package analysis and the NN used on fault diagnosis of Hydraulic Generators.
The fault character information extracting, comes down to the question how represent maximal information with minimal datum as possible as we can. This is the sixty-four-dollar question of signal processing and pattern identification. Signal is represented sparsely in wavelet domain, namely wavelet transform has the property of dimension reduction. This paper eliminates signal redundant information, de-correlates signal correlated information in wavelet domain and extracts unsteady signal character information in wavelet space, namely "entropy compression"; this paper separates mixture observation signals, namely de-correlates signal correlated information successfully.
The main content as following:
1. The paper use BCB to realize the communication between the workstation and the blind SQL Server in windows 2000.
2.This paper discusses hypothesizes of Fourier Transform (Short Time Fourier Transform). Basing on theory, this paper explains the shortcoming of Fourier
0
Transform. With the information carrier of wavelet atom for unsteady signal, the Multi-Resolution Analysis of Wavelet Transformation describes unsteady signal time-frequency information adaptively which is apt to feature extraction.
3. The Wavelet theory, Wavelet Frame Theory, Continuous Wavelet Transform (CWT), Discrete Wavelet Transform, Wavelet Packet Transform and Wavelet Packet Network are discussed in detail. The paper dissertate the mathematic property of wavelet basis function and their influence to application. The paper gives some principals for selecting wavelet basis and wavelet transform scheme for different signal, different signal, different signal time-frequency structure and different analysis aim.
4. when the fault signal is separated, namely, fault signal re-construction is procession of fault character information extraction from measure space. The system uncertainty decreases in the Fault Detection and Isolation processes.
5.As for high oscillation vibration signal, this paper discusses in detail the property of wavelet packet energy distribution, white-noise and color-noise elimination, low-dimension feature information vectors extraction and the fault diagnosis system realization with wavelet packet analysis and signal energy frequency band analysis. An example of high frequency signal of hydro-generator is given. A perfect method is designed that improves the capability of FDI of WNN, extracts the character low dimension vectors of fault information and takes the vectors as the input data of WNN, so as to simplify the structure and improve the convergence speed of the WNN and reduce diagnosis errors.
引文
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(2)．潘建忠．水轮发电机组的状态检修与定期检修．广东水利水电．2001，(3)：27～31．
(3)．黄中华．水轮发电机组检修的必然趋势—状态检修．西北电力技术．1999，(2)：30～33．
(4)．黄文虎，夏松波，刘瑞岩．设备故障诊断原理技术及应用．1996．8．第1版．北京：科学出版社．
(5)．郑杰．水电机组的状态监测及状态检修．水利科技．2001，(3)：61～62．
(6)．刘万景．水电厂机组的状态监测．水力发电．1999，(9)：55～57．
(7)．杨晓萍，解建宝．水轮发电机组的状态监测和故障智能诊断系统的研究．西北水电．1998，(1)：22～24．
(8)．吴世林，梅宏，高峰．水轮发电机组状态监测及故障诊断系统的硬件系统设计．云南水力发电．2002，(2)：53～55．
(9)．刘光临，蒋劲，符向前．水轮发电机组状态监测与诊断系统研究．华中电力．2001，14(4)：16～19．
(10)．曹洪恩．水轮发电机组状态监测与诊断技术．水电厂自动化．1995，(10)：42～45．
(11)．吕杜鹃，程远楚．基于现场总线的发电机状态监测仪．工业仪表与自动化装置．2002，(1)：57～59．
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