Abstract: Methods and apparatus for identifying in real time an operating condition of an in-service electrical device which draws a power load by monitoring spectral content of the power signature and associating spectral components with device operating conditions. In the preferred embodiment, motor (12) power line current signature is sampled by data conditioning sampler (18). Preprocessor (30) spectrally separates the current signature into plural frequency domain components having respective frequency and magnitude values. Spectral characteristic component selector filter (40) selects for analysis at least one specific spectral component by referencing a base of stored knowledge of operational characteristics of the motor. A neural network (50) associates without supervision the selected detected spectral component with an operating condition of the motor (12). The base of stored knowledge is updated with new operating condition associations which have been made during real-time monitoring.