Programmable Logic Controller Research Articles

AUTOMATED EFFLUENT TREATMENT SYSTEM

This paper introduces the Programmable Logic Controller (PLC) Based Automated Effluent Treatment System as an innovative solution for efficiently managing industrial effluents. The system employs sophisticated technology, including PLCs and various sensors, to automate and optimize the treatment process. Specifically designed for industries like electroplating, where water contamination is prevalent, the system effectively monitors and controls water levels, temperature, gas presence, and pH levels to ensure the safe disposal of effluent. Through a detailed exploration of its components and functionalities, this paper demonstrates how the PLC-based system enhances efficiency, reliability, and environmental sustainability in industrial wastewater treatment. Key Words: Programmable Logic Controller, Automation, Effluent treatment plant, Environment safety, Sewage, Chemicals.

An Overview of the Security of Programmable Logic Controllers in Industrial Control Systems

An Overview of the Security of Programmable Logic Controllers in Industrial Control Systems

Exploration of Practical Teaching Mode of Electrical Control and Programmable Logic Controller Application Based on Project Teaching Method

In today’s prosperous industrial era, training electrical control personnel to meet the needs of the industry remains one of the important tasks of colleges and universities. How to effectively cultivate electrical control personnel has become an unavoidable issue for industry and colleges and universities. Aiming at the problems existing in the current teaching mode of electrical control and programmable logic controller (PLC) application, this paper proposes a new teaching mode based on the project teaching method. The methodology aims to increase student engagement, deepen understanding of theoretical knowledge, and reinforce the development of practical skills. Through the implementation of the project teaching method, it is expected to effectively cultivate electrical control talents to meet the needs of the industrial control industry and inject new vigor into the development of modern industry.

Precision Regulation and Forecasting of Greenhouse Tomato Growth Conditions Using an Improved GA-BP Model

Tomatoes are annual herbaceous plants of the family Solanaceae. They have very stringent requirements for their growing environment and climate conditions. To precisely control the greenhouse environment for tomato growth, this project designed and implemented a monitoring system utilizing programmable logic controllers and a data acquisition system for monitoring. Sensors are installed at key locations in the greenhouse, such as near the ground, in the plant canopy, and under the roof, to monitor environmental parameters such as temperature, humidity, light intensity, and carbon dioxide concentration in real time. A three-layer feedforward GA-BP neural network model was established using soil temperature, soil humidity, air humidity, and illumination as predictive parameters. This technology predicts optimal environmental parameters and performs real-time monitoring and intelligent control, overcoming the traditional BP neural network’s drawbacks of slow convergence, susceptibility to disturbance, and poor generalization ability, with the current model’s average prediction error being less than 5%. It provides a theoretical basis and decision support for precision control and related environmental forecasting in agricultural projects. Based on the growth characteristics, physiological and morphological features of tomatoes, and the comprehensive impact of planting conditions, the technology enhances tomato yield and quality while reducing production costs and labor inputs. It mainly includes the establishment of tomato growth models, measurement and control of environmental parameters, and the design and optimization of intelligent decision control systems. Research outcomes in this field are significant for improving agricultural production efficiency, ensuring food security, and promoting sustainable agricultural development.

An Automatized Rebalancing System to Address Faradaic Imbalance and Prolong Cycle Life in Alkaline Ferrocyanide – Anthraquinone Redox Flow Batteries

An Automatized Rebalancing System to Address Faradaic Imbalance and Prolong Cycle Life in Alkaline Ferrocyanide – Anthraquinone Redox Flow Batteries

A novel approach detection for IIoT attacks via artificial intelligence

AbstractThe Industrial Internet of Things (IIoT) is a paradigm that enables the integration of cyber-physical systems in critical infrastructures, such as power grids, water distribution networks, and transportation systems. IIoT devices, such as sensors, actuators, and controllers, can provide various benefits, such as performance optimization, efficiency improvement, and remote management. However, these devices also pose new security risks and challenges, as they can be targeted by malicious actors to disrupt the normal operation of the infrastructures they are connected to or to cause physical damage or harm. Therefore, it is essential to develop effective and intelligent solutions to detect and prevent attacks on IIoT devices and to ensure the security and resilience of critical infrastructures. In this paper, we present a comprehensive analysis of the types and impacts of attacks on IIoT devices based on a literature review and a data analysis of real-world incidents. We classify the attacks into four categories: denial-of-service, data manipulation, device hijacking, and physical tampering. We also discuss the potential consequences of these attacks on the safety, reliability, and availability of critical infrastructures. We then propose an expert system that can detect and prevent attacks on IIoT devices using artificial intelligence techniques, such as rule-based reasoning, anomaly detection, and reinforcement learning. We describe the architecture and implementation of our system, which consists of three main components: a data collector, a data analyzer, and a data actuator. We also present a table that summarizes the main features and capabilities of our system compared to existing solutions. We evaluate the performance and effectiveness of our system on a testbed consisting of programmable logic controllers (PLCs) and IIoT protocols, such as Modbus and MQTT. We simulate various attacks on IIoT devices and measure the accuracy, latency, and overhead of our system. Our results show that our system can successfully detect and mitigate different types of attacks on IIoT devices with high accuracy and low latency and overhead. We also demonstrate that our system can enhance the security and resilience of critical infrastructures by preventing or minimizing the impacts of attacks on IIoT devices.

Fruit Sorting by Pizzo-electric Sensor and PLC Controlling

Abstract: The fruit sorting process traditionally relies on visual inspection, primarily considering size as a key quality parameter. However, industries engaged in large-scale fruit trading have turned to image processing technology for sorting, despite its high cost and impracticality for small traders. This paper proposes an alternative sorting system that offers an economical solution suitable for automated fruit sorting at various scales. Aim: The aim of this study is to develop an economical automated fruit sorting system capable of classifying fruits based on their weight, thereby eliminating the need for manual labor and improving sorting accuracy and efficiency. Place and Duration of Study: Department of Electrical Engineering Finolex Academy of Management and Technology, Ratnagiri, Maharashtra, between July 2023 to April 2024. Study Design: This study employs a practical approach to design an automated fruit sorting system that utilizes Programmable Logic Controller (PLC) technology in conjunction with load cells. The system is designed to classify fruits based on their weight as they move along a conveyor belt, thereby automating the sorting process. Methodology: The proposed sorting system integrates PLC technology and load cells to accurately measure and classify fruits based on their weight. By eliminating the need for manual intervention, the system enhances sorting efficiency and accuracy. The system is designed to be cost-effective and suitable for implementation by small traders and farmers. Results: The developed sorting system demonstrates precise, reliable, and consistent sorting outcomes based on fruit weight. By automating the sorting process, the system achieves improved efficiency and productivity compared to traditional manual sorting methods. Moreover, the cost-effectiveness of the system makes it accessible to small traders and farmers seeking to enhance their sorting practices. Conclusion: The proposed sorting system offers an economical and efficient solution for automated fruit sorting, particularly for small traders and farmers. By leveraging PLC technology and load cells, the system provides reliable alternative to costly image processing-based methods. The automation of the sorting process eliminates the risk of errors and inconsistencies associated with manual sorting, while ensuring accurate and quantitative classification based on fruit weight. This sorting system presents a practical approach to improving fruit trading operations, enhancing efficiency, and productivity.

Development of undulator motion control system with redundant protections

The undulator is a key luminous component of the Shanghai high repetition rate x-ray free electron laser and extreme light facility, and the motion control system is an important part of the undulator. The main task of the motion control system is to complete the high precision adjustment of the gap and taper between the upper magnetic pole girder and lower magnetic pole girder, so as to adjust the wavelength of the radiation light. According to the development requirements of the motion control system for the U26 undulator, which is a conventional permanent magnet, this paper proposes a new motion control system with double position feedback closed-loop control, including programmable logic controller (PLC) closed-loop control based on position feedback by a linear absolute encoder (LAE) and driver closed-loop control based on position feedback by a rotary absolute encoder (RAE) of a servo motor. Multiple motion tests of the U26 undulator have shown that the repeatability accuracy of the gap is ±50 nm and the gap drive can reach 0.1 µm step size, the error of which is about ±20 nm according to the feedback of the LAE. The conclusion can be drawn that the motion step size and repeatability accuracy of the motion control system for the U26 undulator are improved by one order of magnitude on the basis of meeting all technical requirements. At the same time, motor torque protection, motor temperature protection, and redundant position protection with RAE can further improve the reliability and safety of the motion control system for the U26 undulator.

Integrated Simulation Research of Multi-natural Energy-driven Unmanned Surface Vehicle

In response to the limitations of existing unmanned surface vehicles in complex marine environments, where they often fail to meet the requirements for extended endurance, broad operational range, offshore missions, and prolonged operational durations, an autonomous Unmanned Surface Vehicle (NUSV) has been designed and developed. The NUSV is propelled by wind, solar, and wave energy sources. Concerning wind energy, a micro wind energy storage mechanism based on a spiral spring has been designed to enable power generation in low-wind conditions. A wave energy transmission device, complete with a dynamic model, has been devised for wave energy. This device converts torque generated from wave action in different directions into a unified torque, providing continuous power to drive the generator. Solar energy is harnessed using Maximum Power Point Tracking (MPPT) algorithms to ensure optimal operation of the solar panels. The electrical energy generated from these three natural sources is stored using Pulse Width Modulation (PWM) and DC-DC Boost converters. A programmable logic controller manages and allocates this stored electrical energy for the NUSV’s equipment, including underwater propulsion systems, surface cameras, laser radar, GPS, and other electronic devices. This integration of wind, solar, and wave energy sources enables the NUSV to meet power demands, allowing for long-duration operations at sea, extended offshore missions, wide operational ranges, and prolonged mission durations.

Thermo-mechanical behaviours investigation of Nano-Sized Al2O3, TiO2, and Graphene Nanoplatelet Reinforced Epoxy Composites

Composite materials find extensive applications in various industries, thanks to their remarkable properties. These sectors include energy, maritime, motor sports, aviation, space and defense. The materials commonly used in these sectors are fiber reinforced plastic (FRP) composite materials. Epoxy materials are commonly used as matrix in the production of FRP materials. This study delves into the enhancement of epoxy-based nanocomposites by using graphene nanoplatelets (GNP-5nm), TiO2 (13nm), and Al2O3 (8nm) nanoparticles. These nanoparticles were added at varying mass ratios into a commercial epoxy to investigate their effects on some chemical, thermal and mechanical properties. Meticulous mixing methodologies were used to reduce clumping effects and ensure even distribution during the process. The curing process was carried out in a PLC (Programmable Logic Controller) controlled hot air oven under isothermal conditions under the influence of 100 °C for 30 minutes. Tensile strength, elongation at break, toughness, resilience modulus, elasticity modulus, hardness, FTIR analysis and thermal conductivity properties were characterized to assess the nanoparticle influence on the epoxy matrix. The results showed that there were remarkable improvements in mechanical properties with nanoparticle reinforcement. Especially, 1.25% Al2O3 inclusion exhibited a substantial increase of 140.32% in tensile strength and a 7% rise in shore D hardness compared to pure epoxy. This enhancement was attributed to enhanced O-H bonding between 'O' atoms in Al2O3 nanoparticles and epoxy polymer chains, enhancing matrix-filler interactions. Additionally, the effect of 1.0% TiO2 led to plasticity, displaying a 32% rise in elongation at break, signifying improved deformation energy absorption compared to neat epoxy. In thermal conductivity measurements, the highest thermal conductivity was observed in the sample with 1.25% GNP added and it increased by 123.5% compared to neat epoxy. In TiO2 and Al2O3 added samples, an increase of 69% and 47%, respectively, was observed at 1.25% additive rates compared to neat epoxy. According to the results, thanks to the nanoparticle reinforcement added into the epoxy matrix, composite structures can be given new and superior properties specific to the applications.

PLC BASED RAILWAY ACCIDENT AVOIDANCE SYSTEM

The paper presents a comprehensive framework for enhancing railroad security by integrating technologies such as signalling arrangements, train closure security systems, automatic railroad gate control, intrusion detection, obstacle detection, tunnel control, and automatic blockade systems. These systems utilize sensors and advanced controls to detect and mitigate potential threats, enhancing security measures and reducing the risk of accidents. Programmable Logic Controllers (PLCs) in railroad systems manage several security protocols, including emergency brake, over-speed control, train door control, and fire detection. They also ensure passenger and train safety by monitoring temperature, pressure, and voltage parameters. In the event of any anomalies, the PLC triggers an alert and takes necessary actions to prevent accidents. Key Words: : Automatic Barricade System, Automatic Railway Gate Controlling, Crack Detection System, Obstacle Detection, PLC, Signalling Deployment System, Tunnel Power Saving System.

Automated Storage and Retrieval System for Warehouse

Manual picking and retrieval of items from storage locations can be time-consuming, leading to delays in order fulfillment. This can negatively impact customer satisfaction and the overall responsiveness of the supply chain. In addition, manual data entry and tracking systems are prone to human errors, resulting in discrepancies between recorded and actual inventory levels. This can lead to stockouts, overstocking, and difficulties in maintaining accurate inventory records. Therefore, a fully automated storage and retrieval system is proposed to tackle this problem. The overall system consists of infrared sensor as presence of item stored, LEDs indicator, warehouse model with compartments and stepper motors act as actuator to pick and place the item. This project aims to automate the storage and retrieval system with the assist of monitoring system for accurate tracking of inventory and space savings. The use of Programmable Logic Controller (PLC) in this project is a good representation of integrated automation technology in automated storage system design. Furthermore, monitoring system connected to a web-based system will be used to remotely monitor and operate the facility. Implementing an Automated Storage and Retrieval System (ASRS) in the warehouse can address these challenges by automating the storage, retrieval, and tracking of inventory.

Application of Photovoltaic Panels as Producers of Electrical Energy With IoT Technology Based on Programmable Logic Controller

The process of converting solar cell electrical energy is a form of utilizing environmentally friendly alternative energy sources (renewable energy). The conversion system is in the form of PV panels that are installed in a location exposed to sunlight and unobstructed. Monitoring is carried out when the sun shines from morning to evening. The location of the panel is in the vehicle parking lot of the engineering faculty, while monitoring is carried out in the Control Laboratory of the Tanjungpura University Engineering Faculty, which is 300 meters away. Factors that determine the quality of PV panels are the system and dimensions. This shows that fluctuations in current (I), voltage (V) and power (P) need to be controlled so that load distribution and reserves can prevent reduced energy generation. Observation and control using Long Range Area (LoRa) radio transmission media connections, Internet of Things (IoT) and Programmable Logical Control (PLC) in real-time. Observation and test results show that energy generation has experienced an increase in temperature which has an impact on reducing power. Meanwhile, the effect of the distance between the installed panels produces an average delay of 7 milliseconds (midday conditions). Meanwhile, the Signal to Noise Ratio (SNR) value for data transmission is 30 dBm at the device frequency of 868.125 MHz. Baud rate 2400-9600 bps with a speed of 0.3 bps – 62.5 Kbps. The application of this system is a research novelty because it can determine and control the generation of electrical energy at minimum, maximum and optimum conditions with a certain distance between the observer and the installed panel.

Synthesis of resilient fallback control system under cyber-attacks via supervisory control

Industrial control systems (ICS) require system design and operation under cyber-attacks. This study aims to design a fallback control system that can switch from normal control to fallback control and verify its superiority. The target system is a factory automation (FA) system consisting of a normal programmable logic controller (PLC) and a fallback PLC. In this system, we design a fallback logic that takes over control in the case of cyber-attacks. The design of this logic requires a system model that manages smooth state transitions between normal control and fallback control in an integrated manner under cyber-attacks. In response, we model a control program in the framework of discrete event systems (DESs) and apply supervisory control to derive a supervisor model that can manage the system in an integrated manner. To ensure the controllability of the FA system during cyber-attacks, we design a control specification that includes a detection function to enable rapid switching of the control state. As a result, we generate the fallback logic from the supervisor model with guaranteed controllability under cyber-attacks and implement it in a fallback PLC to verify the effectiveness of the proposed logic.

METHOD OF PROTOTYPING CONTROL UNITS BASED ON THE OPENPLC APPLICATION

The problem of designing control devices based on programmable logic controllers (PLCs) is their high cost and, as a rule, unavailability at the initial design stage. The purpose of the research is to reduce the time and cost of designing the system by creating prototypes of control units with the software implementation of control algorithms in the languages of the MEK 61131-3 standard and the execution of programs in the Arduino board. The research method consists in the decomposition of project models of operating and control automata of the control device and their implementation in the software environment of the OpenPLC application in the form of program organization components (POU) in Ladder Diagram, Function Block Diagram, Sequential Function Chart and Structured Text languages. The result of the study is a method of creating typical POU operating and control automata of the control system, which are executed in the Arduino board. An example of the application of the proposed methodology for the design of a prototype of the facility's temperature control system is given. The developed prototype was tested using a logical PLC and a physical prototype, which confirmed their functional compliance with the original and a reduction in the cost of the equipment by at least an order of magnitude.

PLC Based Transformer Protection from Over Voltage and Under Voltage

A PLC (Programmable Logic Controller) based transformer protection system is an electronic system designed to protect industrial transformers from various electrical faults and abnormalities. The system utilizes sensors to detect electrical parameters such as voltage, current, and temperature and uses a PLC to process the data and control the transformer's operation. The protection system can be programmed to detect faults such as overload, overvoltage, undervoltage, phase loss, phase reversal, and over-temperature conditions. Once a fault is detected, the PLC will automatically shut down the transformer to prevent further damage. The system provides reliable and accurate protection to the transformer, reducing the risk of costly downtime and repairs. Transformer protection from over and under voltages is a critical aspect of any transformer control system. Overvoltage can damage the transformer's insulation, bearings, and winding, while undervoltage can cause the transformer to stall or overheat. To protect the transformer from these conditions, various protection devices can be employed, including overload relays, circuit breakers, and voltage monitors. To protect against overvoltage, a voltage monitor can be installed, which will detect any voltage spikes or surges and trigger an alarm or shut down the transformer if the voltage exceeds a predetermined threshold. Similarly, an undervoltage relay can be used to protect the transformer from low voltage conditions. The undervoltage relay will monitor the voltage levels and shut down the transformer if the voltage drops below a certain level.. Key Words:-PLC (Programmable Logic Controller), SMPS, Voltage Controlled Relay, LED indicators, Transformer and Dimmer.

Programmable logic controlled lithium-ion battery management system using passive balancing method

Advancements in electric vehicle technologies and the widespread adoption of electric vehicles have brought energy storage systems to the forefront. However, efficient and secure utilization of energy storage systems requires Battery Management Systems (BMS).BMSs are typically designed with power electronics, electronic cards, integrated circuits, and auxiliary hardware components. Nevertheless, BMSs designed with such microcontrollers can only control a limited number of battery cells and constrained current values. Furthermore, employing a separate controller for each battery pack exacerbates these issues.In this study, a Programmable Logic Controller (PLC) - based BMS proposal for lithium-ion batteries has been presented, aiming to address the challenges in existing BMSs. The developed system is a passive balancing BMS comprised of controller PLC modules and auxiliary hardware. The Ladder Diagram (LD) programming language was employed for programming the PLC.In the conducted research, the voltage levels of the cells comprising the battery pack were monitored, and a passive balancing method was employed to equalize the cell voltages. Passive balancing has been applied to cells with voltage values of 2.70 V, 2.40 V, and 2.80 V using the minimum reference voltage cell balancing method to equalize the voltage levels. The output voltage has been balanced according to the maximum reference charge voltage set at 6 V through the maximum reference charge voltage balancing method. Additionally, a cooling circuit was integrated into the system to safeguard the Battery Management System (BMS) against thermal hazards. The developed PLC controller and algorithm can effectively control multiple battery packs with a single controller and operate at higher current values. This advantage allows the PLC-controlled BMS to have a broader control capacity. The presented test results indicate the successful performance of the PLC-based BMS.

Continuous and low-carbon production of biomass flash graphene

Flash Joule heating (FJH) is an emerging and profitable technology for converting inexhaustible biomass into flash graphene (FG). However, it is challenging to produce biomass FG continuously due to the lack of an integrated device. Furthermore, the high-carbon footprint induced by both excessive energy allocation for massive pyrolytic volatiles release and carbon black utilization in alternating current-FJH (AC-FJH) reaction exacerbates this challenge. Here, we create an integrated automatic system with energy requirement-oriented allocation to achieve continuous biomass FG production with a much lower carbon footprint. The programmable logic controller flexibly coordinated the FJH modular components to realize the turnover of biomass FG production. Furthermore, we propose pyrolysis-FJH nexus to achieve biomass FG production. Initially, we utilize pyrolysis to release biomass pyrolytic volatiles, and subsequently carry out the FJH reaction to focus on optimizing the FG structure. Importantly, biochar with appropriate resistance is self-sufficient to initiate the FJH reaction. Accordingly, the medium-temperature biochar-based FG production without carbon black utilization exhibited low carbon emission (1.9 g CO2-eq g−1 graphene), equivalent to a reduction of up to ~86.1% compared to biomass-based FG production. Undoubtedly, this integrated automatic system assisted by pyrolysis-FJH nexus can facilitate biomass FG into a broad spectrum of applications.

Domain‐specific translation tool from structured text to C source code with code readability enhancement in programmable logic controllers

AbstractThe Industrial Internet has emerged as a key technology in the field of industrial automation, revolutionizing traditional manufacturing processes and enabling advanced control systems by integrating machines, sensors, and software systems through network connectivity, allowing for real‐time data exchange, analysis, and decision‐making in industrial environments. Programmable Logic Controllers (PLCs) play a critical role in industrial automation systems, which are specialized digital computers designed to control various manufacturing processes and machinery. As a promising language, Structured Text (ST) is of paramount importance for industrial Internet, and it is essential to translate ST into C, which is widely used in various industries for implementing control systems. However, due to differences in syntax, data types, and programming paradigms between the two languages, the translation process is facing several challenges. In this paper, we present a domain‐specific translation tool that automates the process of converting ST code to C code. This tool incorporates advanced AI techniques, particularly leveraging the capabilities of NL‐PL LLMs, to facilitate accurate and efficient translation while generating comprehensive documentation to assist developers. Finally, the evaluation and case studies conducted validate the effectiveness of the tool, demonstrating its practical applicability and benefits in real‐world industrial settings.

A cloud-based infrastructure to deploy supervisory forecast models for predictive coagulant dosing control

Abstract Advanced optimal dosing control based on multiple online sensor data is operational in several treatment facilities in Norway. The benefits of the dosing control system in maintaining stable phosphate/solids removal and saving coagulant usage are documented in the literature. The dosing algorithm is currently implemented in a programmable logic controller (PLC) connected to the treatment plant's Supervisory Control and Data Acquisition System (SCADA) system. The PLC receives online sensor data from the plant's SCADA, calculates the optimal dosing values, and transmits optimal dosage values back to the SCADA system. The dosing algorithm is frequently updated to keep in sync with the process and equipment upgrades of the treatment plant and advances in control algorithm schemes. The upgrades include new regulatory feedback loops structural changes to the dose equation, and the addition of conditional setpoints. Each maintenance and upgrade routine entails operational downtime where the dosing algorithm is set to a sub-optimal flow-proportional dose. This paper presents a non-intrusive Internet of Things (IoT) infrastructure to implement a predictive/forecast component to an existing dosing control algorithm. The benefits of the new cloud-based system in improving nutrient removal, increasing operational flexibility, and reducing maintenance downtime are presented in this work.