Mitigation of hotspots in electrical components and equipment using an adaptive neuro-fuzzy inference system
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ORIGINAL PAPER
Mitigation of hotspots in electrical components and equipment using an adaptive neuro‑fuzzy inference system Peter O. Oluseyi1 · Jamiu A. Adeagbo1 · Demilade D. Dinakin1 · Tolu O. Akinbulire1 Received: 29 November 2019 / Accepted: 26 May 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract The poor management of hotspots in electrical systems often leads to very devastating consequences; an extremity is fire outbreak which could result in loss of lives and/or properties. Hence, the necessity to effectively manage or handle electrical hotspots cannot be overstated. This paper proposes a model for arresting the occurrence of the destructive activities of electrical hotspots in industries by controlling the temperature, humidity and dust density within electrical components/ equipment. To this end, a thermal imaging camera is employed for the detection of various locations and magnitudes of hotspots within electrical systems. Based on the globally approved industrial standards for the prevention of thermally induced electrical systems failure, each of the electrical components and equipment [whose thermal excursion is beyond the allowable temperature rise under measured load values (i.e. ΔTcorr)] is identified and treated by adopting the recommended actions. Additionally, a fuzzy logic control (FLC) system is designed. This is further developed into an adaptive neuro-fuzzy inference system (ANFIS) for the control of the operation of the air handling unit (AHU) and the aspirator suction speed. This arrangement, thus, leads to heat reduction and dust elimination within the electrical components/equipment in industrial space, thus preventing the destructive effects of the occurrence of hotspots. However, for the sake of graphical representations of this scheme, the MATLAB environment is created for the generation of the optimum temperatures at various locations within the electrical systems. From this development, it is established that the framework has very high potential to eliminate the catastrophic effects of hotspots in electrical systems. Keywords Air handling unit · Electrical components and equipment · Hotspot mitigation · Infrared thermography · Neurofuzzy Abbreviations ACO Ant colony optimization AHU Air handling unit ANFIS Adaptive neuro-fuzzy inference system CA Cultural algorithm COG Center of gravity COMP Component CS Cuckoo search * Peter O. Oluseyi [email protected] Jamiu A. Adeagbo [email protected] Demilade D. Dinakin [email protected] Tolu O. Akinbulire [email protected] 1
Department of Electrical and Electronics Engineering, University of Lagos, Lagos, Nigeria
EQPT Equipment FCS Fuzzy control system FIS Fuzzy inference system FLC Fuzzy logic control GA Genetic algorithm IR Infrared IRT Infrared thermography MATLAB Matrix laboratory MIMO Multiple input multiple output MF Membership function PSO Particle swamp optimization RMSE Root-mean-square error List of symbols Tcomp Continuously permissible temperature of compon
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