机械外文翻译---机械状态监测和故障诊断的最新进展(编辑修改稿)

机械外文翻译---机械状态监测和故障诊断的最新进展(编辑修改稿)内容摘要：

ration signal analysis and fault feature extraction. However, classical spectrum analysis also has obvious disadvantages. Fourier transform reflects the overall statistical properties of a signal, and is suitable for stationary signal analysis. In reality, the signals measured from mechanical equipment are everchanging, nonstationary, nonGaussian distribution and nonlinear random. Especially when the equipment breaks down, this situation appears to be more prominent. For nonstationary signal, some timefrequency details 外文翻译原文及译文 8 can not be reflected in the spectrum and its frequency resolution is limited using Fourier transform. New methods need to be proposed for those nonlinearity and nonstationary signals. The strong demand from the engineering practice also contributes to the rapid development of signal analysis. New analytical methods for nonstationary signal and nonlinear signal are emerging constantly, which are soon applied in the field of machinery fault diagnosis. New methods of signal analysis are main including timefrequency analysis, wavelet analysis, HilbertHuang transform, independent ponent analysis, advanced statistical analysis, nonlinear signal analysis and so on. The advantages and disadvantages of these approaches are discussed below. 山东交通学院毕业设计 9 4. Research on Fault Reasoning At present, many methods are adopted in the process of diagnostic reasoning. According to the subject systems which they belong to, the fault diagnosis can be divided into three categories: (1) the fault diagnosis based on control model。 (2) the fault diagnosis based on pattern recognition。 (3) the fault diagnosis based on artificial intelligence. Among them, the fault diagnosis based on control model needs to establish model through theoretic or experimental methods. The changes of system parameters or system status could directly reflect the changes of equipments physical process, and hence it is able to provide basis for fault diagnosis. This technology refers to model establishment, parameters estimation, status estimation, application of observers, etc. Since it requires accurately system model, this method is not economically feasible for the plicated devices in the practice. Pattern recognition conducts cluster description for a series of process or events. It is mainly divided into statistical method and language structure method. The fault diagnosis of equipments could be recognized as the pattern recognition process, that is to say, it recognizes the fault based on the extraction of fault characteristics. There are many mon recognition methods, including bayes category, distance function category, fuzzy diagnosis, fault tree analysis, grey theory diagnosis and so on. Recent years, some new technologies have been also applied in the field of the fault diagnosis of rotary machines, such as the bination of fuzzy set and neural work, the dynamic pattern recognition based on hidden markov model, etc. 外文翻译原文及译文 10 5. Research and Development of Fault Diagnosis Devices Fault diagnosis technology ultimately es down to the actual devices, and at present research and development of fault diagnosis devices is in the following two directions: (1) Portable vibration monitoring and diagnosis (including data collector system), and (2) Online condition monitoring and fault diagnosis system. Portable instrument is mainly adopted singlechip microputers to plete data acquisition, which has certain ability for signal analysis and fault diagnosis. Online monitoring and diagnosis system is usually equipped with sensors, data acquisition, alarm and interlock protection, condition monitoring subsystem, etc. And it is also fitted with rich signal analysis and diagnosis software. These software include America BENTLY Corporation 3300, 3500 and DM2020 systems, America Westinghouse Company PDS system, the 5911 system developed by ENTECK and IRD Company, Japan Mitsubishi MHM system, the Danish Bamp。 K Company Bamp。 K 3450 COMPASS system, etc. China has also successively developed large online monitoring and fault diagnosis system, which has been put into use on steam turbine and other important equipments. Based on the realization of condition monitoring of equipments, work diagnostics center can monitor and diagnose the operation of equipments at any time through the work to achieve the long distance information transmission. The remote monitor。