The most direct reflection of gear defect is the change in the amplitude and phase modulations of vibration. The slice spectral correlation density (SSCD) method presented in this paper can be used to extract modulation information from the gear vibration signal; amplitude and phase modulation information can be extracted either individually or in combination. This method can detect slight defects with comparatively evident phase modulation as well as serious defects with strong amplitude modulation. Experimental vibration signals presenting gear defects of different levels of severity verify to its character identification capability and indicate that the SSCD is an effective method, especially to detect defects at an early stage of development.
Minor and random slip between rolling elements and races in rolling element bearings makes vibration signals have periodically time-varying ensemble statistics, which is known as cyclostationarity. Two second-order cyclostationary methods, the spectral correlation density (SCD) and the degree of cyclostationarity (DCS), are talked about in this paper based on a statistical model of rolling element bearings. The SCD provides redundant information in bi-frequency plane and cyclic frequency domain embodies the majority of it, which is a series of non-zero discrete cyclic frequencies completely reflecting the fault characters of rolling element bearings. The DCS has virtues of less computation and clearer representation, at the same time keeps the same characters with SCD in cyclic frequency domain. And the DCS is also proved to be resistant to the additive and multiplicative stationary noise. Simulation and experiential results from three rolling element bearing faults: outer race defect, inner race defect and rolling element defect, indicate practicability of the DCS analysis in rolling element bearing condition monitoring and fault diagnosis.
The demodulation analysis has been extensively used for gear diagnosis. However these techniques mainly deal with the amplitude-modulated signal instead of the frequency-modulated signal. Due to the symmetrical phase relationship of the sidebands, the amplitude-demodulated methods are not suitable for the frequency-modulated signal. This paper introduces the theory of cyclostationary processes as a powerful frequency-demodulation tool for the diagnosis of gears. The Cyclic Autocorrelation Function (CAF) is an important second-order cyclic statistics and acts as an efficient parameter to the frequency-demodulated analysis. In this paper, the CAF of frequency-modulated signal is deduced carefully. Through the discussion of frequency feature of the CAF slice at different cyclic frequency, two useful conclusions have been arrived about the frequency-demodulation. Firstly, the CAF slice at even multiples of the modulator-frequency can demodulate the frequency-modulated signal directly. Secondly, the amplitude-demodulated methods are suitable for the CAF slice of frequency-modulated signal at some special cyclic frequencies, which are equal to odd multiples of the modulator-frequency or close to the double carrier-frequency. These features of the CAF slice mentioned above overcome the invalidation of amplitude-demodulated methods for the frequency-modulated signal and increase it’s application range in engineering. Application in simulated and experimental data from a gear rig verifies the effectiveness of the frequency-demodulated method based on cyclostationarity.
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