| Detection of faults in gears and rolling element bearings has been paid much attention and deserves further investigation because of the diversity of the types and work conditions of these mechanical parts. Vibration analysis is widely used in the condition monitoring and fault detection of the gears and rolling element bearings. Many researches on this topic have been made[20-60], but much still remains to be done. For example, one of the problems is to suppress noise in the vibration signals measured on a gearbox or on a bearing pedestal. It is particularly important in demodulating the vibration signals. It is well known that the modulation of vibration signals is a decisive signature of the present of a local fault in either gears or bearings. The demodulation of these signals will more clearly reveal the signatures. However the result of demodulation is often masked by noise containing in the measured signals. Vibration signal processing techniques are sought in this dissertation. So the test rigs of the gear and the rolling element bearing are built. And different types of the faults are simulated individually in the gear and the rolling element bearing.In this paper, several conventional methods for processing the vibration signals are verified for detecting faults in gears and ball bearings with two test rigs designed especially for this investigation. The results of the experiment show that the peak value, RMS, standard deviation, crest factor, kurtosis value and impulse value of the vibration signals can distinguish between the normal and abnormal conditions of the ball bearing when the level of noise is low. However, why and how the faults happen in the machines can not be revealed. Then the resonance demodulation technique is used in analyzing the vibration signal of the gear and ball bearing. To some extent the results depend on the selected frequency band. In order to effectively extract the defect signature of the vibration signal, two new methods, single gear tooth analysis (period segmentation technique) and time-delayed correlation demodulation, are established and experimentally tested.The main idea of the single gear tooth analysis, is that the vibration signals collected with high sampling rate are divided into a number of segments with a same time interval. The number of the signal segments is equal to that of gear teeth. The analysis of individual segment reveals more sensitively the changes of the vibration signals in both time and frequency domain caused by gear faults. In addition, the location of failed tooth can be indicated in terms of the position of the segment that deviates from normal segments. An experimental investigation verified the advantages of the single gear tooth analysis. It is a good method for more sensitive detection of the incipient faults and locating the faults in the gear.The time-delayed correlation demodulation is established in order to suppress the noise and demodulating the signal. The auto-correlation functions of vibration signals measured on bearing cases are first computed, which will reduce the noise greatly, but not change the modulation signature of the signals. Then the auto-correlation functions are delayed for some time lags in order to decrease the affection of noise before demodulated by Hilbert Transform. The effectiveness of this method is confirmed by simulated data and experimental data. Moreover, thefaults on the outer ring, inner ring and rolling element can be recognized by the time-delayed correlation demodulation.Moreover, the time-frequency analysis methods, Wigner-Ville distribution and wavelet transform, are studied in this paper. Some faults in the gear and ball bearing can be detected by these two methods, however, the computing time is some long. So they can not be used in on-line fault detection and condition monitoring. And the explanation of the time-frequency analysis is not easily accepted by the engineers.The experimental factors, such as rotational speed and measured position and fault distribution a...
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