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IoT is the network of physical devices embedded with electronics, software, sensors, actuators and network connectivity which can identify, collect and exchange the data. With the emergence of the internet and the computational era, a smart monitoring and reliable controlling system over the entire pipeline sensor parameters are highly desirable that can be achieved by introducing the Internet of Things (IoT) technology. Remote monitoring and controlling of the sub-station equipment are an important issue for the transportation management department which is normally done manually or using an expensive PLC and SCADA system. Hence in recent scenarios, the need for an advanced controller is increased to determine the optimal system performances.
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The main motivation for advanced control systems is safety since the loops having adequate performance are only 68% which are in manual mode. This is attained by continually measuring operating parameters such as temperature, pressure, level, flow, and concentration, and creating decisions to open or close a valve, slow down or speed up a pump, or increase or decrease heat so that selected process measurements are sustained at the set range values. Through the use of the Proportional-Integral-Derivative (PID) controller, automated control systems facilitate complex transportation processes to be functioning safely and cost-effectively. In recent years, communication occurs wirelessly to the remote information analytics center to examine and interpret the process behavior and provide the appropriate decision in case of risk circumstances.
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Also, the performance analyses are validated experimentally using unsupervised K-means clustering to identify abnormality caused by blockage and crack in the pipeline on the cloud-stored data. For experimental real-time validation of the proposed work, a lab-scale DCS (Distributed Control System) based fluid transportation system is undertaken where flow and pressure prevail to be the most influencing parameters during risk occurrences in the pipelines. When the local intelligence fails to react proactively during risk occurrences, immediately its performance is deactivated by the webserver through the NB (Narrow Band)-IoT module. In the proposed methodology, SCADA with the LQR-PID controller serves as Local Intelligence. To enhance the supervision performances, the SCADA (Supervisory Control and Data Acquisition) platform is incorporated with IoT by utilizing the NB-IOT module holding a high-level engineering interface. Minidown#mail.It is important to concentrate on monitoring and control of the pipeline transportation system before the failure resulting in fatal accidents. IronCAD Design Collaboration Suite 2012 HF1 14.0īentley Structural Dashboard V8i 08.11.09.08īentley Structural Modeler V8i 08.11.07.94 Integrated Production Modelling Tookit v8.0 273 Intusoft Magnetics Designer v4.1.0 Build 350 Intergraph Intools Engineering Suite v5.2
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