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. Δ T corr )] 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.

中文翻译：

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使用自适应神经模糊推理系统缓解电子元件和设备中的热点

电气系统中的热点管理不善通常会导致非常严重的后果；四肢是火灾爆发，可能导致生命和/或财产损失。因此，有效管理或处理电气热点的必要性怎么强调都不为过。本文提出了一种通过控制电气元件/设备内的温度、湿度和灰尘密度来阻止工业电气热点破坏性活动发生的模型。为此，采用热成像摄像机来检测电气系统内热点的各种位置和大小。基于全球认可的防止热致电气系统故障的工业标准，每个电气元件和设备[其热偏移超出测量负载值下的允许温升（即ΔT corr ）] 均通过采用推荐措施进行识别和处理。此外，还设计了模糊逻辑控制（FLC）系统。这进一步发展为自适应神经模糊推理系统 (ANFIS)，用于控制空气处理单元 (AHU) 的运行和吸气速度。因此，这种布置导致工业空间中的电气部件/设备内的热量减少和除尘，从而防止热点发生的破坏性影响。然而，为了这个方案的图形表示，MATLAB 环境是为在电气系统内的不同位置生成最佳温度而创建的。从这一发展来看，该框架在消除电气系统中热点的灾难性影响方面具有非常高的潜力。