A Mobile Agent Platform for Remote Measurements

Industrial applications require suitable monitoring systems able to identify any decrement in the production efficiency involving economical losses. The information coming from a general purpose monitoring system can be usefully exploited to implement a sensorless instrument monitoring an AC motor drive and a diagnostic tool providing useful risk coefficients. The method is based on a complex digital processing of the line signals acquired by means of a Virtual Instrument. In this paper a Genetic Algorithm implemented in a Mathcad environment performs the evaluation of the risk indexes from the processed line signals. The combination of Genetic Algorithms and Neural Network is also investigated as a promising possibility for the development of a reliable diagnostic tool. The risk coefficients derived from this approach are evaluated, discussed and compared to other indexes – in particular Fuzzy Indexes introduced by the authors in previous papers.