Introduction to literature basic processing vibration signal of bearing fault detection

Introduction to literature basic processing vibration signal of bearing fault detection - 2018 10 - Article source: 18 IEEETransactions on Education ( 体积:46岁的问题:1、2003年2月) English title: bearing fault detection of the basic vibration signal processing project background: the university of Alabama engineering college teachers to develop the application of spectral analysis of multidisciplinary curriculum, in order to complete the course the students must be able to use and understand the dual-channel spectrum analyzer, which means that students must have a basic understanding of the analysis of time domain and frequency domain. Paper to solve the problem and significance: this paper mainly puts forward the lab of rolling bearing fault detection module, this paper introduces the basic working characteristic of rolling bearing background, and the calculated failure frequency characteristics of the formula is given. Papers focus: first, basic introduction to A. A major part of the rolling bearings rolling bearing including inner ring and outer ring, rolling elements and cage ( Some bearings include additional components, such as used for guide ring of spherical roller bearing and seal) , is often used in applications with high bearing capacity. B。 Bearing wear failure mechanism for mechanical damage, crack, damage, lubricants and corrosion defect reason is likely to cause bearing failure. C。 Characteristics of the failure frequency vision defects resulting from the failure mechanism of ball bearing outer ring, whenever one of the ball rolled defects, will produce a high level of short time ( Impact) Force, leading to bearing vibration, ultimate bearing with inherent frequency 'ringing' response, rapid response due to the damping attenuation ( As shown in the figure below) 。 Every time one of the small ball rolled defects occur incentive and response, so the fundamental frequency response waveform is element rolling on the defect rate. This is when the bearing fault detection basic frequency of interest. Second, the basic bearing fault detection technology in the bearing measuring the vibration of the main affected by highly unbalanced and without taking part, including the random vibration associated with friction and other sources. The main story is divided into five parts: a piece of synthetic signal, the application of traditional spectral analysis, modulation and Hilbert transform, the envelope analysis, and the time domain statistical - Kurtosis. In one of the synthesized signal the signal component ( Square wave approximation, random noise and ringing pulse sequence) And the sum of the composite signal waveform graph as follows: under the plan shows the use of synthetic waveform and component of the spectrum to explain when applied to the bearing fault detection is simple the limitations of spectrum analysis ( Square wave approximation of spectral, random noise and ringing pulse sequence, and compound waveform in figure 5) : envelope analysis usually use amplitude modulation settlement were explained. Amplitude modulation (am) is defined as a high frequency carrier signal with low frequency modulation signal multiplied, and the amplitude of the first step is to correct the signal demodulation, can be done by using the Hilbert transform. Besides kurtosis coefficient used for bearing fault detection measure. Conclusion: the guidance of the rolling bearing fault detection module is developed for the application of spectral analysis of the existing curriculum, at the same time can also be used as a separate tutorial, or into the machine state monitoring in the course. Reviewed in this paper the basic operation of rolling bearing and idealized bearing fault vibration characteristics, synthetic signal is generated by the MATLAB illustrates the spectrum analysis of the disadvantages of the conventional. The basis of error analysis was carried out on the tolerance analysis and effectiveness were studied. Finally, the paper puts forward a set of graphics drivers to illustrate bearing fault detection technology.