Modern Digital and Analog Communication Systems 3e Osece
Modern Digital and Analog Communication Systems 3e Osece
Self-Organizing Maps
Design and Evaluation of a Reconfigurable Digital Architecture for Self-Organizing Maps
MICRONEURO '99 Proceedings of the 7th International Conference on Microelectronics for Neural, Fuzzy and Bio-Inspired Systems
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This paper presents a proactive maintenance scheme for the detection and diagnosis of faults in electrical valves. In our case study, these actuators are used for controlling the flow in an oil distribution network. An embedded system implements selforganizing maps for the detection and classification of faults that lead to deviations either on torque, or on the valve opening position. For fault detection, the map is trained using a mathematical model devised for the electrical valve. For fault classification, training is performed by fault injection based on parameter deviations over this same mathematical model. In both cases, the maps store the energies of the torque and the opening position that are computed using the wavelet packet transform. Once the maps are trained, the embedded system is ready for online monitoring the actuator. During the on-line testing phase, the embedded system computes the best matching between an acquired input vector (current torque and position energies) and the synaptic weight vector of the trained map. This matching is quantified by computing the Euclidean distance between these vectors and guide the fault detection and classification steps. The complete scheme was prototyped using FPGAs. The results obtained for area, performance and memory requirements point out to a low cost, promising solution for embedding maintenance in electrical actuators.