Remote Process Monitoring Research Articles

Microcontrollers programming for control and automation in undergraduate biotechnology engineering education

This paper presents the utilization of the ESP32 microcontroller as a teaching tool for signal acquisition, processing, and control theory in biotechnological engineering. The ESP32 microcontroller, equipped with Bluetooth and WiFi capabilities, offers an affordable and versatile solution for educational purposes. By leveraging the Arduino© software, students can easily learn microcontroller programming and utilize various peripherals such as sensors and actuators. Several practical exercises related to process control have been conducted using this microcontroller. Additionally, remote process monitoring and control are enabled through integration with a database. Furthermore, concepts of artificial intelligence are explored using the Edge Impulse platform to obtain an artificial neural network that can be downloaded onto the ESP32. Positive feedback from students highlights the effectiveness and engagement of utilizing these microcontrollers, and the integration of internet connectivity enhances the overall learning experience.

Hybrid modelling for remote process monitoring and optimisation

Process simulation is used to develop a digital twin representation of chemical processes typically for process optimization or what-if scenarios. However, it is known to be computationally expensive and there is an increasing need for process remote monitoring and optimization. This is where machine learning models shine, where they can run up to several orders of magnitude faster than their equivalent first principle process simulation models. Most of the previous work in this area tend to demonstrate the ability of machine learning models to accurately capture complex, non-linear relationships between process parameters in various chemical processes. Two important aspects are rarely discussed, namely the construction of machine learning models using operating data and the deployment of these models. In this paper, we address these two aspects and review the different information silos in industrial settings that need to be considered when working with hybrid models (combining process simulation and machine learning). This is illustrated by a case study for an operating natural gas dehydration unit, covering data management, process simulation, machine learning and visualization. We demonstrate how the hybrid models can be constructed and packaged as an online monitoring and a prediction dashboard. Several unique challenges are also highlighted including the reliability of field data and operational deviations due to operability and controllability - all of which need to be understood in order to successfully translate operating systems to process simulation and machine learning models that are reliable and accurate. While the exact implementation may vary from project to project, the current work serves as an example and highlights the important considerations to make when working with such systems.

Expanded Wireless Networking Options Benefit Water Treatment Plants

Advances in radio frequency technology can boost productivity, increase efficiency, and save money for water and wastewater utilities. Wi‐Fi, Bluetooth, and cellular have great potential for remote process monitoring and control.

Process Monitoring System Based on Anomaly Detection Statistics Algorithm

In order to find more efficient and handle the internal network threat with the LAN network threat warning and real-time processing, remote process monitoring and management of computer systems is used in this paper. By getting the system process handle on the local computer, realizes the acquisition of the threat source information of the system. By customization of the application layer protocol AMCP, realizes the efficient information transmission between server and client. In order to enhance the reliability of the system security threat model, the System security threat information is analysised with the anomaly detection algorithm based on statistics. Analysis of the test data shows that: through getting the system process handle on the local computer, the system treating information can be obtained. Through the security threat model based the anomaly detection algorithm based on statistics, network threat is dealed efficiently and real time.

Remote milling tool-wear monitoring and direct wear features extraction by image processing

The extraction of accurate and correct feature parameters, which describe the useful cutting life of a milling cutter, is important for remote process monitoring. The main parameters extracted and analysed are the highest and the average flank length of the wear land depth as well as the area within the wear land. The problems with the internet speed and bandwidth are overcome by only uploading specific wear-land features the resulting file size is adequate for internet monitoring. This paper outlines a methodology for automatically extracting useful direct tool-wear parameters remotely via the internet for tool wear decision-making.

Tablet Press Automation: A Modular Approach to Fully Integrated Production

Fully automated tablet production is an exciting and emerging trend in the pharmaceutical industry. Improved tablet quality, manufacturing efficiency, and process validation are major reasons for the increasing emphasis on automated technology. This paper outlines the vast options and possibilities associated with tablet press automation and presents a specific modular approach in which the extent and time flame for the automation transition is dictated by the tablet manufacturer. This modular approach uses the tablet press control system as the central building block on which a variety of control modules are constructed to facilitate automated material flow, data collection, and remote process monitoring. The emphasis is placed on design flexibility due to the fact that each company will construct a unique definition of automation, which may be subject to change as various phases of automation are implemented and evaluated.

Development of an Effluent Treatment Feedforward Control System

This paper describes the implementation of a novel feedforward control strategy in a Programmable Logic Controller (PLC) to neutralise acidic wastewater with a 50% sodium hydroxide solution. This control strategy was developed because the common 3 term PID controller is unsuitable for this application. The control algorithm overcomes problems associated with measurement deadtime and logarithmic pH scale. In addition, suitable hardware for caustic flow monitoring and remote process monitoring and control are addressed. The described system has been running successfully since the beginning of June, 1994.

Networks of low-Earth orbit store-and-forward satellites

A slotted multiaccess protocol is proposed for networks of low-Earth orbit store-and-forward communications satellites. Networks of this type would provide communication between low cost geographically distributed Earth stations, and would be particularly attractive in areas where conventional terrestrial communications systems were not available. Applications of this type include data acquisition and remote process monitoring. The proposed protocol incorporates time division multiplexing (TDM) on the downlink, slotted Aloha with collision resolution on the uplink, and an automatic repeat request (ARQ) algorithm. Since the network connectivity is intermittent, analysis of networks of this type is difficult. Nevertheless, relationships among the performance parameters for a general network are deduced, and performance of three particular network configurations is studied via simulation.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Radio-controlled apparatus for automatic analytical measurements

An apparatus is described for remote control of chemical operations and for remote monitoring of processes, by means of a radio-receiver tuned to the initial frequency of an oscillator that transduces some physical parameter of the system monitored. The receiver operates a relay (with feed-back to the system) when the emitted frequency changes as a result of a change in the system examined.