Abstract
Gearboxes play an important role in industries that use rotating machinery since they have high efficiency and compact structure. Their components such as gears, shafts, and bearings are fundamental in the transmission of mechanical power. However, the industry should stop its operation for maintenance and repair if machines fail unexpectedly. To prevent this, Structural Health Monitoring (SHM) can be a powerful tool for damage detection and prediction, whose correct implementation may avoid faults. In this way, a back-to-back test rig was used as a reference to investigate healthy and damaged cases in terms of eigenfrequencies. Two approaches were developed to investigate the system’s vibrational behavior and operating conditions. Approach 1 (AP1) uses a combination of the Lumped Parameter Method (LPM) and Finite Element Method (FEM). Here, the stiffnesses of the gear train components were estimated by static FEM simulations and used in the LPM. Approach 2 (AP2) consists of the application of the dynamic FEM simulations. For the healthy systems, the eigenfrequencies of AP1 and AP2 were considered in line with the experimental data acquired from the test rig. Moreover, the effects of tooth root crack on the eigenfrequencies, for both approaches, were analyzed and compared with each other. Their results were considered adequate.