A Novel Method of Gearbox Health Vibration Monitoring Using Empirical Mode Decomposition

Nowadays, many industrial types of machinery rely on different types of gears to transmit rotational torque. Gearbox faults are one of the major reasons for breakdown of industrial machinery. Therefore, gearbox diagnosing is one of the most important topics in machine condition monitoring. A number of signal processing techniques are described for the vibrodiagnostics of gearboxes, but there are also different limitations for vibration based gear diagnostic methods. For some specific requirements (e.g. time-triggered signal acquisition), not all of described techniques can be always applied in industrial reality. This paper introduces a novel, easy to use method of gearbox health vibromonitoring based on Empirical Mode Decomposition (EMD) and a time-domain analysis of vibration signal parts. Six sets of data collected from gearboxes are used to validate the proposed method. The experimental results demonstrate that the gear tooth defect can be detected and evaluated at an early stage of development when both Empirical Mode Decomposition and statistical analysis technique are used.