This study deals with the analysis and implementation of compensation algorithms applied to a shunt active power filter, which uses three single-phase full-bridge converters sharing the same dc-bus voltage. The shunt filter is applied to three-phase four-wire systems, performing harmonic current suppression, reactive power compensation and power factor improvement. In addition, load unbalances compensation is also carried out. Two different control strategies are presented. In the first strategy, which is called independent current control, the currents of the three-phase power source are independently compensated performing harmonic suppression and load reactive power compensation, that is, the three-phase four-wire system is treated as three independent single-phase systems. In the second strategy, in addition to harmonic suppression and load reactive power compensation, the shunt filter also performs load unbalance compensation, resulting in sinusoidal and balanced source currents. The compensating algorithms are evaluated by means of several experimental test conditions, in order to validate the theoretical development and analyse the performance of the shunt filter.

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A comprehensive study of intelligent tools used to classify broken rotor bars in induction motors, which operate with three different types of frequency inverters, is presented. The diagnosis of defective rotor bars is a critical issue for the predictive maintenance of induction motors. A proper classification of these defects in their early stages of evolution is necessary for preventing major machine failures and production downtime. The proposed approach is performed by analysing the amplitude of the stator current signal in the time domain, using a dynamic acquisition rate based on machine frequency supply. To assess classification accuracy under the various severity levels of the faults, the performance of four different learning machine techniques is investigated: (i) fuzzy ARTMAP network; (ii) support vector machine (sequential minimal optimisation); (iii) k-nearest neighbour; and (iv) multilayer perceptron network. Results obtained from 1274 experimental tests are presented in order to validate the study, which considers a wide range of load conditions and operating frequencies. Experimental results presented in this study validate the robustness and efficacy of the proposed approach.