Abstract Moving towards industrial internet of things (IIoT) concept is one of the hot issues of the management, control, and maintenance of railway transportation. The wayside hotbox systems are useful for monitoring of overheated axle bearings in the harsh dust environment. In the paper, the fuzzy-based fault detection algorithm (FDA) of the spatially distributed hotbox monitoring system (SDHMS) and its IIoT concept are presented. SDHMS consists of three stand-alone wayside hotbox monitoring systems that are installed in three distant locations: two thermal power plants and a coal mine. The system plays an important role in keeping railway safety, preventive maintenance and accident avoidance. Therefore, the IIoT concept is needed for increasing the reliability of coal transportation and the energy efficiency of electricity production. The main advantage of the presented concept is the application of the FDA at the edge and fog levels as well as the application of a complex fuzzy model for decision making at the cloud level. Edge computing involves signal processing in hotbox systems with the aim of the fault detection and quality assessment of the measured signals. Fog computing involves data processing with the aim of detecting an overheated bearing (temperature, position, axle number and train side), and alarming. Cloud computing is in charge of assessing the bearing condition and the need for replacement and maintenance planning. The proposed algorithm and fuzzy model were validated in real conditions of exploitation, successfully.

中文翻译：

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工业物联网环境下具有模糊和故障检测算法的路边热箱系统

摘要 向工业物联网（IIoT）概念迈进是铁路运输管理、控制和维护的热点问题之一。路边热箱系统可用于在恶劣的灰尘环境中监测过热的轴轴承。在本文中，提出了空间分布式热箱监控系统 (SDHMS) 的基于模糊的故障检测算法 (FDA) 及其 IIoT 概念。SDHMS 由三个独立的路边热箱监控系统组成，这些系统安装在三个遥远的位置：两个热电厂和一个煤矿。该系统在保持铁路安全、预防性维护和避免事故方面发挥着重要作用。因此，需要 IIoT 概念来提高煤炭运输的可靠性和电力生产的能源效率。所提出概念的主要优点是 FDA 在边缘和雾级别的应用，以及在云级别决策制定的复杂模糊模型的应用。边缘计算涉及热箱系统中的信号处理，目的是对测量信号进行故障检测和质量评估。雾计算涉及数据处理，目的是检测过热的轴承（温度、位置、轴号和列车侧）并发出警报。云计算负责评估轴承状况以及更换和维护计划的需求。所提出的算法和模糊模型在实际开发条件下得到了成功验证。