Detection and quantification of the gear tooth damage from the vibration and acoustic signatures

The application of the joint time-frequency Wigner-Ville Distribution for the gear diagnostics is presented in this study. A new gear fault detection parameter called NP4 is derived from the Wigner-Ville Distribution. The utility of the gear fault detection parameter has been demonstrated using numerous gear vibration experiments and simulations.; An analytical procedure to simulate the vibration of a gear with a single damaged gear tooth has been developed. The utility of this analytical procedure relies on the relationship between the wear or damage of a gear tooth and the change in gearmesh stiffness. An analysis demonstrates that the perturbation of the gearmesh stiffness function from the nominal profile over a given tooth pass can be used to quantify the level of damage in the tooth. The gear vibration signatures for progressively increasing gear tooth damage are analyzed in a joint time-frequency domain. A correlation between the level of the gear tooth damage and the value of the gear fault detection parameter NP4 is demonstrated.; The fact that the Wigner-Ville Distribution can represent the energy of a gear vibration signal was used for the gear damage quantification. An image processing algorithm has been developed to analyze the Wigner-Ville image. The developed image processing algorithm extracts from the Wigner-Ville Distribution image the components with a large energy content in the joint time-frequency domain. The extracted Wigner-Ville image components are analyzed individually. A set of features such as eccentricity, orientation, and energy content is calculated for each Wigner-Ville image component. It is shown that the values of the Wigner-Ville image component features can indicate and quantify the gear tooth damage.; The same signal analysis and image processing techniques are also applied to gearbox acoustic signals. The acoustic signals are obtained using acoustic intensity measurements and filtered using a novel technique that eliminates background noise. The developed technique to filter the background noise is based on the property of the sound acoustic intensity to measure the direction of the net flow of acoustic energy at a given position. The technique has been demonstrated on the experimental data obtained from a gear test rig. The application of this technique significantly reduces the complexity of the gear diagnostics from the acoustic signal.; The developed methods and algorithms are integrated into a general health monitoring procedure for a gear transmission. Thus, a unified Wigner-Ville Distribution based approach is presented for a gear damage detection and quantification.