利用无线数据遥测技术对高架起重机关键系统进行远程监控

K. Singh, K. Chatterjee, Vikas Khemani
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引用次数: 2

摘要

近年来,工业4.0和工业物联网为各行各业的可靠性工作提供了强大的支持工具。这些努力的一个重要方面是从工厂设施的各个部分获取相关数据,将其实时传输到远程中央服务器,对这些数据进行上下文分析,并使其无处不在,随时可供授权用户使用,以便分散和有效地制定纠正行动的决策。虽然有许多方法可以通过有线传感器和设备实现数据传输,但在移动设备(如高架起重机)中实现具有挑战性。测量和传输装置通常安装在难以接近的位置,传感器布线容易受到移动构件的影响,暴露在高温和腐蚀性环境中。这使得整体可靠性难以保证。出于同样的原因,在移动资产中使用有线通信将获取的数据传输到远程服务器也是不切实际的。在本文中,我们提出了两种用于移动资产(如高架起重机)数据遥测的无线配置,用于关键系统的远程监控和智能预测诊断。在所提出的实现中,我们从安装在此类移动资产上的无线传感器获取数据,并将该数据无线传输到远程云服务器进行分析,并使分析的数据随时可供授权用户普遍使用。第一种配置使用现有的无线因特网网络将数据传输到服务器,第二种配置使用4G LTE蜂窝网络。使用车间模拟和测试设置,我们演示了这些配置的成功实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Remote Monitoring of Critical Systems in Overhead Cranes Using Wireless Data Telemetry
In recent years, Industry 4.0 and Industrial Internet of Things have provided a strong enabling toolset to the reliability efforts of various industries. An important aspect in these efforts is the acquisition of relevant data from various parts of a plant facility, transmitting it to a remotely-located central server in real time, contextually analyzing this data, and making it ubiquitous and readily available to authorized users for decentralized and efficient decision making for corrective action. While there are numerous ways to achieve data transmission via wired sensors and devices, the implementation is challenging in mobile assets, such as overhead cranes. Measurement and transmission devices are often installed in locations difficult to approach, and the sensor wiring is susceptible to moving members and exposure to hot and corrosive environment. This makes it difficult to ensure overall Reliability. For the same reasons, transmission of acquired data to the remote server is also impractical using wired communication in mobile assets. In this paper, we present two wireless configurations for data telemetry in mobile assets, such as overhead cranes, for the purpose of Remote Monitoring and Intelligent Predictive Diagnostics of critical systems. In the presented implementations, we acquire data from wireless sensors, meant to be installed on such mobile assets, and transmit this data wirelessly to a remotely-located cloud server for analysis, and for making the analyzed data readily and universally available to authorized users. The first configuration uses an existing wireless internet network for data transmission to the server, and the second uses a 4G LTE cellular network. Using a workshop simulation and test setup, we demonstrate the successful implementation of these configurations.
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