Development of an embedded piezoelectric transducer for bearing fault detection

The trend toward intelligent monitoring and industry 4.0 has attracted more attention to the performance of intelligent bearings with integrated sensors. Compared with the standard technique of mounting a sensor on the housing of machines, embedding the sensor inside the bearing housing can benefit several aspects. The short transmission path between the fault and sensor provides more efficient condition monitoring and fault detection, especially in a noisy setting or at low rotational speeds where fault symptoms have low energy. Therefore, this paper presents the design and implementation of an embedded piezoelectric transducer for fault detection in a cylindrical roller bearing. Experimental tests and simulations using ANSYS are employed to investigate the transducer performance in three different tests. The first test analyzes experimental voltage signals and a simulated transducer for a faulty outer ring and roller. Experimental tests and simulations have demonstrated that the proposed transducer can successfully detect the local fault in the bearing through obvious fault symptoms in the voltage signal. The piezoelectric transducer and accelerometer signals are analyzed in the second test by artificially exciting the bearing apparatus structure and creating noise using an air motor. In the noisy condition, the piezoelectric transducer performed better in time and frequency domain analysis than the reference accelerometer. Contrary to the accelerometer, the signal statistical indicators of the transducer remained constant during the impact, and the air motor frequency did not mask the fault symptoms. In the third test, a preliminary analysis of the transducer's durability was performed, and according to the results, the transducer was not significantly stressed under high radial loads from the shaft, which is promising for real applications.