Robust Information Indices for Diagnosing Mechanical Drives Under Non-stationary Operating Conditions

Reliable fault diagnosis of mechanical drives can become nontrivial task in case of restricted instrumentation and variable operating conditions. Under such circumstances changes in the calculated features can not be unambiguously associated with change in system condition. In this paper we propose a feature appropriate for diagnosing faults in mechanical drives that is robust to fluctuations in operating conditions. Therefore, its time evolution seems to be correlated only with the machine condition. Instead of relying on spectral properties of the vibration signal, we rather observe changes in the statistical patterns of the derived distribution functions. The effectiveness of the algorithm was evaluated on three datasets comprising both gear and bearing faults under constant and variable load.