A novel baseline-free approach for acousto-ultrasonic crack monitoring of rotating axles

Axles are widely used mechanical components in rotating machines. In many applications, axles are exposed to varying environmental and operational conditions, including for example, temperature, load and rotational speed. To apply acousto-ultrasonics–based structural health monitoring for axles, it is in some cases not economically feasible to collect data and to construct a baseline model for each combination of all possible environmental and operational conditions. In consideration of such a practical limit, a novel baseline-free method, called Dynamic Reference Method, is proposed in this article for the detection of transverse cracks in axles. Piezoelectric wafer active sensors are applied for exciting and sensing ultrasonic waves. In case a transverse crack is present in an axle, it is noticed that the crack will sequentially open and close within one revolution of the axle when it is mechanically loaded in the radial direction. Such an opening and closing phenomenon of the transverse crack will influence the propagation of the ultrasonic waves. During the short time of data acquisition, the environmental and operational conditions remain nearly constant and the changes in the propagation of the ultrasonic waves may indicate the appearance of a transverse crack on the axle, and a baseline model for the environmental and operational conditions is not needed. To validate the proposed baseline-free method, an axle is put on a rotating bending test rig to first initiate a fatigue crack on the surface of the axle and second to observe its growth. During the test, the ultrasonic waves are measured by piezoelectric wafer active sensor in situ and are analysed online using the proposed baseline-free method. According to the test results, not only can the crack be effectively detected, but also the progressive changes of the crack size can be differentiated. Such results demonstrate the potential of the proposed baseline-free method in condition-based maintenance and predictive maintenance for critical axle components.