Abstract
Building management systems are costly for small- to medium-sized buildings. A massive volume of data is collected on different building contexts by the Internet of Things (IoT), which is then further monitored. This intelligence is integrated into building management systems (BMSs) for energy consumption management in a cost-effective manner. Electric fire safety is paramount in buildings, especially in hospitals. Facility managers focus on fire protection strategies and identify where system upgrades are needed to maintain existing technologies. Furthermore, BMSs in hospitals should minimize patient disruption and be immune to nuisance alarms. This paper proposes an intelligent detection technology for electric fires based on multi-information fusion for green buildings. The system model was established by using fuzzy logic reasoning. The extracted multi-information fusion was used to detect the arc fault, which often causes electrical fires in the low-voltage distribution system of green buildings. The reliability of the established multi-information fusion model was verified by simulation. Using fuzzy logic reasoning and the membership function in fuzzy set theory to solve the uncertain relationship between faults and symptoms is a widely applied method. In order to realize the early prediction and precise diagnosis of faults, a fuzzy reasoning system was applied to analyze the arcs causing electrical fires in the lines. In order to accurately identify the fault arcs that easily cause electrical fires in low-voltage distribution systems for building management, this paper introduces in detail a fault identification method based on multi-information fusion, which can consolidate the complementary advantages of different types of judgment. The results demonstrate that the multi-information fusion method reduces the deficiency of a single criterion in fault arc detection and prevents electrical fires in green buildings more comprehensively and accurately. For the real-time dataset, the data results are presented, showing disagreements among the testing methods.
Highlights
Licensee MDPI, Basel, Switzerland.The safe use of electricity has become one of the eternal themes of China’s power industry development
Multi-information fusion technology is a functional simulation of the complex treatment of the human brain
In view of the causes of the frequent occurrence of electrical fires and the investigation and study of the existing protective devices against electric fires in the market, it is concluded that the effective protection measures for preventing electrical fires in low-voltdistribution systems in buildings are based on the original fuse, overload, under-voltage age distribution systems in buildings are based on the original fuse, overload, under-voltprotection, and residual current protection devices
Summary
The safe use of electricity has become one of the eternal themes of China’s power industry development. How to effectively detect the cause of an electrical fire and reduce the incidence of electrical fire accidents that cause loss of life and property has become the focus of research on electricity safety in today’s society. Multi-information fusion technology is a functional simulation of the complex treatment of the human brain.
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