Application of the wavelets multiresolution analysis and the high-frequency resonance technique for gears and bearings faults diagnosis

Defects diagnosis and condition surveillance of production and manufacturing rotating machinery in a plant is very important for guaranteeing production efficiency and plant safety. Condition surveillance for gear and bearing defects diagnosis for all rotating machines is a serious job because they cause accidents and consequently great production losses. For gear and bearing faults, and early detection especially in the gearboxes, researchers in the conditional maintenance and vibratory analysis used different methods and techniques in signal processing, among those and in full rise, demodulation by wavelets multiresolution analysis (WMRA) and high-frequency resonance technique (HFRT), based on the Hilbert transform, which allows filtering and the demodulation at the same time. In this paper, we propose to make a precise diagnosis for gears and bearings combined faults detection and identification in a laboratory test rig which simulate a rotating machine like in the manufacturing processes using WMRA and HFRT techniques. First of all, we applied WMRA method on simulated signals of gear or bearing defects or the combination of them, then we applied it on real signals measured on a test rig of the LMS laboratory in the University of Guelma.