Vector Spectrum Of The Full Information On Energy Research

With the maximization, complication, automation, high-speed and heavy-load orientation of the modern rotating machinery, the technologies in terms of condition monitoring and fault diagnosis are playing an increasingly important role in the fundamental areas of national industry.The information of the rotor is usually collected by the sensors vertically installed on the section. However, as for the traditional condition monitoring and fault diagnosis of rotating machinery only base on the single-source vibration signal and disserve the organic relations among each channel,thus it leads to the incomplete and unreliable information.It is diffcult for the single-source signal to reflect the work condition of the equipment,and as a result, it is easy to lose or get mistaken conclusions.The full information technologies have successfully made the diagnosis results come true. They have greatly improved the condition monitoring and fault diagnosis of rotation machinery. Practices show it is of great superiority.On the basis of the fundamental theories about data fusion and dynamics of rotor, the basic theory of full vector spectrum, and its numerical method, spectrum illustration, physical meaning and application in fault diagnosis are well introduced. Full vector spectrum analysis technology is featured by being comprehensive, direct and easy to be exploited. It can reflect the real work condition of the rotor.Based on the full vector spectrum theory of fusion signals together with traditional signal power spectrum analysis theory, the definition, quality and implement method of full vector power spectrum of multi-sensor fusion signal as well as its estimation method are discussed in details. Studies show that full vector power spectrum possesses explicit physical meaning, improves the defects of the traditional single-source signal power spectrum technology which used to show incomplete and one-sided information, thus providing the only evidence for fault diagnosis.In order to improve the resolution of the full vector spectrum, it is to integrate the zoom spectrum theory of complex modulation and full vector spectrum theory.After several steps like complex modulation frequency-shifting,low-pass filtering,sub-sampling and FFT,the vector spectrum of the multi-sensor fusion signal has been partially zoomed.Full vector zoom spectrum is characterized by showing comprehensive information and high resolution. Its computation load is far less than the common full vector spectrum with the same resolution. It is able to fully reflect the partial fine features of frequency domain of fusion vector signal, and improve the efficiency and accuracy of fault diagnosis and effectively save the cost of the hardware.It can be applied in fault diagnosis of rotation machinery and effectively analyze multi-resource vector signal with intensive frequency.With the basis theories in terms of full information technology, wavelet analysis and information entropy, the signals in two vertical channels can be decomposed into two different frequency bands by wavelet. Then full vector wavelet energy entropy can be reached by calculating all decomposition coefficients, thus quantizing the disorder degree of energy distribution of fusion signal. Full information wavelet energy entropy can fully show the complexity of energy distribution of the fusion vibration signal and be sensitive to the changes of energy distribution, thus successfully predicting the fault and its development trend. It can be used as a standard for judging equipment operation and be used in condition monitoring of rotation machinery.After careful theory discussion and programming test under the matlab enviroment, the new method above is proved to be effective and practical. At the same time, it shows that the full vector spectrum analysis method can truly reflect the whole features of machinery vibration and greatly improve the objectivity and accuracy of diagnosis. It is of a new technology with high research value, engineering application and broad development prospect.