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Full information on energy research based on full vector spectrum

Author: XieKai
Tutor: HanJie
School: Zhengzhou University
Course: Mechanical and Electronic Engineering
Keywords: Data Fusion Fault Diagnosis Vector spectrum Refined analysis Wavelet Energy Entropy
CLC: TH165.3
Type: Master's thesis
Year: 2008
Downloads: 22
Quote: 3
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Abstract

With modern rotating mechanical equipment to large-scale, complex, automated, high-speed, overloading the direction, condition monitoring and fault diagnosis technology plays an increasingly important role in the fundamental areas of the national economy. The rotor vibration information is usually collected by the installation of the sensors of the cross-section perpendicular to each other, but the tradition of rotating machinery condition monitoring and fault diagnosis using only a single source of vibration signal as a basis for discrimination equipment operating status separates the organic link between each channel signal, resulting in incomplete and unreliable information. Single source signal from the magnitude and structure is difficult to reflect the actual condition of the equipment running, using the traditional method of analysis can easily lead to the Missing and misjudgment. Full IT without omission detection of rotating machinery vibration information, greatly improving the status of rotating machinery condition monitoring and fault diagnosis of incomplete information basis, proved to have great superiority. In this paper, data-level fusion of multi-sensor signal and rotor dynamics basic theory, introduced based on the theoretical basis of the information fusion vector spectrum technology, numerical methods, map expression, physical meaning and its application in fault diagnosis work. Full vector spectrum analysis technique is comprehensive, intuitive, easy to expand the features reflect true motion characteristics of the rotor. Vector spectrum analysis based on the fusion signal, combined with the traditional theory of signal power spectrum analysis, multi-sensor fusion the full vector signal power spectrum definition, nature, pathways and spectral estimation method. The study showed that the full vector power spectrum has a clear physical meaning, to improve the traditional single-channel signal power spectrum information is incomplete, reflects a one-sided problem of defects, a variety of spectral estimation technique, simple and easy to calculate and provide a reliable basis for fault diagnosis work . In order to improve the resolution of the full vector spectrum analysis, the the complex modulation spectrum refine principle with full vector spectrum theory combining multi-sensor fusion signal through multiplexing modulation frequency shift - low-pass filter - Select pumping - Fast Fourier Transform step , to achieve a local refinement of the the fusion vector signal spectrum. Full vector spectrum refine both comprehensive and high-resolution features, computing the amount is far less than the ordinary vector spectrum with the same resolution, can reflect the the local fine features of the frequency-domain fusion vector signal, help to improve the fault diagnosis work The efficiency and accuracy, and saving on hardware costs. The method can be applied to the rotating machinery fault diagnosis of the spectrum intensive multi-source fusion vector signal effective analysis. Combination of IT, wavelet analysis and information entropy theory, the use of wavelet transform two vertical channel signals were decomposed to different frequency bands, comprehensive all decomposition coefficients calculated the full vector wavelet energy entropy fusion signal energy distribution disorder extent quantization. Vector wavelet energy entropy can reflect the complexity of the integration of the vibration signal energy distribution, and are more sensitive to changes in the distribution of energy, able to detect the abnormal signal failure caused, and the use of its forecast the development trend of the fault, and thus as a measure of device work status indicators applied to the field of condition monitoring of rotating machinery. On the basis of the theoretical discussion, programming in Matlab environment verify that this new method is effective and practical. Vector spectrum analysis also proved to be able to truly reflect all the characteristics of the mechanical vibration, greatly improve the objectivity and accuracy of the diagnosis, is the value of a high value of theoretical research and engineering applications, broad prospects for development of the technology.

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CLC: > Industrial Technology > Machinery and Instrument Industry > Machinery Manufacturing Technology > Flexible manufacturing systems and flexible manufacturing cell > Fault diagnosis and maintenance
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