Application of image registration methods in monitoring the progression of surface fatigue failures in geared transmission systems

Surface fatigue failure occurs in geared transmission systems due to factors such as high contact stress, and monitoring its progression is vital if the eventual failure of the tooth flank is to be prevented. Techniques involving the analysis of vibration, acoustic emission and oil debris have been used to successfully monitor the progression of the different phases of gear surface fatigue failure. However, during monitoring a suitable assessment method is required to correlate the characteristics of the signal with the condition of the gear surface. The most commonly used such methods are gear flank profile scanning, replica sample analysis and conventional image analysis, with each technique having both advantages and disadvantages. Responding to the demand for effective assessment methods, this study experimentally evaluates the development of micro-pitting in gears using a new image registration technique in an online health monitoring system. Given a set of captured images of gear surface degradation with different exposure times and geometric deformations, an image registration approach is proposed to cope with inter-image illumination changes of arbitrary shape. Then correlation between the resulting aligned images is compared to a reference one before testing obtained. The results validate the system's capabilities to detect early gear defects and reliably identify the gradual development of micro-pitting in gears, so that it could be used in predictive health monitoring (PHM) systems.