气体往复式压缩机组的数字孪生:概念、结构和试点实施

Q4 Engineering
А. Prokhorenko, S. Kravchenko, E. Solodkii
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引用次数: 0

摘要

信息和操作技术的结合导致了一种新的生产方式,一场新的技术革命,被称为工业4.0。数字孪生在这项技术中起着核心作用。Digital Twin是一种预测性维护工具,可以根据设备的运行模式、环境影响和不同程度的磨损,模拟设备故障的各种选项。提出了创建真实物理研究对象的数字双胞胎的概念-带有气体活塞压缩机的AJAX DPS-180内燃机,旨在从气井中抽出气体。其工作特点是在野外长期自主运行,服务人员地处偏远,环境影响直接,保证了工作的可靠性和稳定性。因此,监测发动机的参数并对其故障进行后续预测尤为重要。在该设备运营商Armco-Engineering的合作和支持下,为AJAX DPS-180创建数字孪生的工作正在进行。显示了创建给定对象的数字孪生过程的六个阶段:收集和初步处理有关真实对象的技术状态的数据;早期发现故障,预测故障时间;服务计划;优化服务的资金和时间资源。为实物配备各种传感器,可以持续收集其技术状态数据,工业物联网技术,如大数据和预测统计模型,可以高精度地预测故障次数。提出了为物体配备数据采集设备的开发和实现方案,并给出了该数据在物联网中的流图。数据采集系统的基础是一个微控制器,一套曲轴转速传感器和热电偶,一个多路复用器和转换热电偶热电势的16位模数转换器。目前,已经实施了测量速度、冷却剂和废气温度的通道。建议使用ThingSpeak服务器作为远程资源,作为该数据的云聚合器和载体。将MATLAB数学包集成到资源中,用作数据分析器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
DIGITAL TWIN OF GAS RECIPROCATING COMPRESSOR UNIT: CONCEPT, ARCHITECTURE & PILOT IMPLEMENTATION
Combination of information and operational technologies has led to a new way of production, to a new technological revolution, known as Industry 4.0. The Digital Twin plays a central role in this technology. The Digital Twin is a predictive maintenance tool, and allows you to simulate various options for device failures taking into account their operation modes, environmental influences and various degrees of wear. The concept of creating a digital twin of a real physical object of research is proposed - an AJAX DPS-180 internal combustion engine with a gas piston compressor, which is designed to pump gas from gas wells. A feature of its work is autonomous long-term operation in the field with the remoteness of the service personnel, direct environmental impact and ensuring the reliability and stability of work. Therefore, monitoring the parameters of the engine with the subsequent prediction of its failures is especially important. The work on creating a digital twin for AJAX DPS-180 is being carried out in cooperation and with the support of Armco-Engineering, the operator of this equipment. Six stages of the process of creating a digital twin of a given object are shown: collection and preliminary processing of data on the technical state of a real object; early detection of malfunctions, predicting the time of failure; service planning; optimization of financial and time resources for service. Equipping a real object with various sensors made it possible to continuously collect data on its technical condition, and technologies of the industrial Internet of things, such as Big Data and the predictive statistical model, predict failure times with high accuracy. The developed and implemented schemes for equipping an object with data collection equipment and a diagram of the flow of this data in the Internet of Things are presented. The basis of the data collection system is a microcontroller, a set of a crankshaft speed sensor and thermocouples, a multiplexer and 16-bit analog-to-digital converters that convert thermo-EMF of thermocouples. At the moment, channels for measuring the speed, coolant and exhaust gas temperatures have been implemented. It is proposed to use the ThingSpeak server as a remote resource as a cloud aggregator and carrier of this data. The MATLAB mathematical package integrated into the resource is used as a data analyzer.
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