This paper describes a novel method of detecting and unambiguously diagnosing the type and magnitude of three induction machine fault conditions from the single sensor measurement of the radial electromagnetic machine vibration. The detection mechanism is based on the hypothesis that the induction machine can be considered as a simple system, and that the action of the fault conditions are to alter the output of the system in a characteristic and predictable fashion. Further, the change in output and fault condition can be correlated allowing explicit fault identification. Using this technique, there is no requirement for a priori data describing machine fault conditions, the method is equally applicable to both sinusoidally and inverter-fed induction machines and is generally invariant of both the induction machine load and speed. The detection mechanisms are rigorously examined theoretically and experimentally, and it is shown that a robust and reliable induction machine condition-monitoring system has been produced. Further, this technique is developed into a software-based automated commercially applicable system.