Estimation of gear tooth transverse crack size from vibration by fusing selected gear condition indices

Gears are common power transmission elements and are frequently responsible for transmission failures. Since a tooth crack is not directly measurable while a gear is in operation, one has to develop an indirect method to estimate its size from some measurables. This study developed such a method to estimate the size of a tooth transverse crack for a spur gear in operation. Using gear vibrations measured from an actual gear accelerated test, this study examined existing gear condition indices to identify those correlated well to crack size and established their utility for crack size estimation through index fusion using a neural network. When tested with vibrations measured from another accelerated test, the method had an averaged estimation error of about 5%.