Since the gear undergoes a continuous change process from normal to broken teeth during the experiment, it also covers the whole process from crack initiation and development to broken teeth. Therefore, the gear state in the short time before the broken teeth belongs to the crack state. The vibration signal of the gearbox is picked up by the acceleration sensor and installed near the output shaft on the outer surface of the box. The sampling frequency of the signal is skHz, which is the time domain waveform and spectrum of the acceleration signal of the normal, crack and broken teeth of the gear.
Cyclic domain scanning for cyclic spectrum, modulation source search process gear fault diagnosis example Gear crack is the most difficult fault in gear fault identification. When the gear has local defects, it mainly produces amplitude modulation phenomenon, and the gear tooth stiffness occurs when the gear teeth are cracked. There will be changes, so both amplitude modulation and frequency modulation exist, but the signal impact energy is weak. The method based on continuous wavelet variation has no impact component cycle when the waveform of the gear normal, crack and broken teeth of Fig. 5 is not close. This is because after the two symmetrical teeth are broken, the impact frequency during the meshing process is twice the frequency of the output shaft, that is, 4.2 Hz. Normal and crack, only the difference between the two can not be found in the time domain signal, and their spectrum is not much different.
When a crack occurs in the root, due to the decrease in rigidity, an impact occurs every time the tooth is engaged, and the signal should contain such a periodic impact component, and the 4.2 Hz impact component generated by the crack has been detected.
According to the demodulation principle, the low frequency band of the amplitude modulation signal loop field only appears 1 times and 2 times the frequency of the modulation source, and the frequency modulation will appear in the 1x, 2nd frequency and above components of the modulation source. Using information on the cyclical changes in cyclic statistics, this information is important for mechanical monitoring and fault diagnosis.
Research shows that the demodulation method based on cyclic statistic is applied to machines with complex vibration signals, such as gears, which can effectively extract fault characteristics and their modulation types. The demodulation method of the second-order cyclic statistic effectively separates the modulation source of the modulated signal from the carrier, indicating that the information has redundancy, and the redundancy makes the result of the fault diagnosis more reliable. For gear cracks, which are difficult to diagnose, the cyclic statistical method can not only detect the impact fault characteristics, but also detect the frequency modulation information caused by the stiffness variation, which is beyond the method of the stationarity hypothesis.
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