Development and Application of IoT Monitoring Systems for Typical Large Amusement Facilities

娱乐 系统工程 风险分析(工程) 膨胀的 工程类 鉴定(生物学) 计算机科学 计算机安全 物联网 建筑工程 植物 医学 生物 复合材料 材料科学 心理治疗师 抗压强度 心理学
作者
Zhao Zhao,Weike Song,Huajie Wang,Yifeng Sun,Haifeng Luo
出处
期刊:Sensors [MDPI AG]
卷期号:24 (14): 4433-4433 被引量:1
标识
DOI:10.3390/s24144433
摘要

The advent of internet of things (IoT) technology has ushered in a new dawn for the digital realm, offering innovative avenues for real-time surveillance and assessment of the operational conditions of intricate mechanical systems. Nowadays, mechanical system monitoring technologies are extensively utilized in various sectors, such as rotating and reciprocating machinery, expansive bridges, and intricate aircraft. Nevertheless, in comparison to standard mechanical frameworks, large amusement facilities, which constitute the primary manned electromechanical installations in amusement parks and scenic locales, showcase a myriad of structural designs and multiple failure patterns. The predominant method for fault diagnosis still relies on offline manual evaluations and intermittent testing of vital elements. This practice heavily depends on the inspectors’ expertise and proficiency for effective detection. Moreover, periodic inspections cannot provide immediate feedback on the safety status of crucial components, they lack preemptive warnings for potential malfunctions, and fail to elevate safety measures during equipment operation. Hence, developing an equipment monitoring system grounded in IoT technology and sensor networks is paramount, especially considering the structural nuances and risk profiles of large amusement facilities. This study aims to develop customized operational status monitoring sensors and an IoT platform for large roller coasters, encompassing the design and fabrication of sensors and IoT platforms and data acquisition and processing. The ultimate objective is to enable timely warnings when monitoring signals deviate from normal ranges or violate relevant standards, thereby facilitating the prompt identification of potential safety hazards and equipment faults.

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