Inverter fed induction machine condition monitoring using the bispectrum

Abstract

This paper proposes the use of the unnormalised bispectrum as a signal processing tool for the diagnosis of inverter-fed induction machine fault conditions. Increasingly, induction machines are supplied from nonsinusoidal, variable speed sources which increases the complexity and magnitude of the machine cage vibration. In addition, contamination of the vibration signal from both known and unknown sources makes accurate fault detection more difficult. This paper addresses both issues, experimental results are presented and it is shown that the unnormalised bispectrum improves on the diagnostic capability of more conventional second order statistical measures.