Programmable Logic Controller Research Articles

Real-time anomaly detection in electric motor operation noise

Anomaly detection plays a very important role in many fields to identify abnormalities occurring in the system earlier. This study proposes a new abnormality detection solution for 3-phase electric motors based on their working noise. Normal and abnormal operating noise data sets for an electric motor were acquired in the laboratory. These datasets are converted into the corresponding two-dimensional gray spectrogram image sets. The normal set is used to train the autoencoder (AE) model to find the abnormality evaluation threshold. This threshold is validated again with anomalous data sets. The trained AE is then quantized to be installed on a system consisting of two duo-core microcontroller units (MCUs) for real-time testing. Free real-time operating system (FreeRTOS), a real-time operating system, is used to schedule tasks on the system. Experimental results show that the designed anomaly detector can accurately detect over 99% of abnormal events. The system can communicate with a supervisory control and data acquisition (SCADA) application running on the S7-1200 programmable logic controller (PLC) platform using the Modbus transmission control protocol (TCP) protocol. The SCADA application can continuously record evaluated results from the system and adjust abnormal thresholds for the system directly on the human-machine interface (HMI) screen.

Design and verification of monitoring system of DC microgrid based on Ethernet communication

AbstractReal‐time acquisition of microgrid (MG) operation data and remote control play a crucial role in the safe and stable operation of MG. A design scheme of monitoring system is proposed for the wind/photovoltaic/energy storage islanded direct current MG. The core controllers used in direct current MG system are programmable logic controller and digital signal processor. The monitoring system mainly adopts Ethernet communication, together with serial port communication mode Recommend Standard 232 (RS232) and Recommended Standard 485 (RS485) communication modes. A heterogeneous networking is built with controllers and data display instruments. Different monitoring interfaces are designed, the important information can be real‐time detected, collected and displayed. The multi‐energy and multi‐load dispatching operation control are realized according to scheduling operation plan. The parameters of the inverter can be adjusted, and the output voltage waveform and sinusoidal pulse width modulation waveform of the inverter can be measured. The communication of the proposed monitoring system is reliable, flexible and expandable, and easy to realize remote operation control. Moreover, the detection and control functions can be extended further. Through experiments, the effective control and monitoring of the designed monitoring system is verified, and the intelligent management is realized.

PLC/HMI Based Portable Workbench for PLC and Digital Logic Learning and Application Development

A Programmable logic controller (PLC) uses the digital logic circuits and their operating concepts in its hardware structure and its programming instructions and algorithms. Therefore, the deep understanding of these two items is staple for the development of control applications using the PLC. This target is only possible through the practical sensing of the various components or instructions of these two items and their applications. In this work, a user-friendly and re-configurable ladder, digital logic learning and application development design and testing platform has been designed and implemented using a Programmable Logic Controller (PLC), Human Machine Interface panel (HMI), four magnetic contactors, one Single-phase power line controller and one Variable Frequency Drive (VFD) unit. The PLC role is to implement the ladder and digital logic functions. The HMI role is to establish the virtual circuit wiring and also to drive and monitor the developed application in real time mode of application. The magnetic contactors are to play the role of industrial field actuators or to link the developed application control circuit to another field actuator like three phase induction motor. The Single -phase power line controller is to support an application like that of the soft starter. The VFD is to support induction motor driven applications like that of cut-to-length process in which steel coils are uncoiled and passed through cutting blade to be cut into required lengths. The proposed platform has been tested through the development of 14 application examples. The test results proved the validity of the proposed platform.

UTILIZAÇÃO DE MAPAS CONCEITUAIS PARA VERIFICAÇÃO DE APRENDIZAGEM SIGNIFICATIVA EM ATIVIDADES INTERDISCIPLINARES NO TÉCNICO INTEGRADO EM AUTOMAÇÃO INDUSTRIAL

This article presents the results of an investigation into the use of concept maps to assess meaningful learning in interdisciplinary activities with students from a Technical Course in Industrial Automation integrated into High School at a Federal Institute campus in the interior of Rio de Janeiro state. Based on David Ausubel's Theory of Meaningful Learning and using Joseph Novak's Concept Maps, this work adopted a qualitative approach with a pedagogical intervention through an Interdisciplinary Didactic Sequence. Concepts from Physics, Programmable Logic Controllers, Instrumentation, Process Control, and Pneumatic Commands were integrated, using the Flipped Classroom and practical activities on a Didactic Bench. The analysis of the concept maps, created by students before and after the intervention, revealed a significant increase of 32.56% in the quality of cross-links, indicating deep integrative reconciliations and improved assimilation of interdisciplinary concepts.

Development and Design of an Online Quality Inspection System for Electric Car Seats.

As the market share of electric vehicles continues to rise, consumer demands for comfort within the vehicle interior have also increased. The noise generated by electric seats during operation has become one of the primary sources of in-cabin noise. However, the offline detection methods for electric seat noise severely limit production capacity. To address this issue, this paper presents an online quality inspection system for automotive electric seats, developed using LabVIEW. This system is capable of simultaneously detecting both the noise and electrical functions of electric seats, thereby resolving problems associated with multiple detection processes and low integration levels that affect production efficiency on the assembly line. The system employs NI boards (9250 + 9182) to collect noise data, while communication between LabVIEW and the Programmable Logic Controller (PLC) allows for programmed control of the seat motor to gather motor current. Additionally, a supervisory computer was developed to process the collected data, which includes generating frequency and time-domain graphs, conducting data analysis and evaluation, and performing database queries. By being co-located with the production line, the system features a highly integrated hardware and software design that facilitates the online synchronous detection of noise performance and electrical functions in automotive electric seats, effectively streamlining the detection process and enhancing overall integration. Practical verification results indicate that the system improves the production line cycle time by 34.84%, enabling rapid and accurate identification of non-conforming items in the seat motor, with a detection time of less than 86 s, thereby meeting the quality inspection needs for automotive electric seats.

The Application of PLC in Industry Fields

This article explores the widespread application and importance of the Programmable Logic Controller (PLC) in industry. PLC, as an industrial controller designed specifically for industrial environments, occupies an important position in the field of industrial automation control due to its advantages of being less susceptible to interference, high reliability, easy programming, fast installation, and small size. With the rapid development of PLC technology, great progress has been made in the development of technology, hardware, and software, resulting in increasingly powerful functionalities and significantly enhanced system development and compatibility. This paper mainly analyzes the design ideas and applications of PLC in life and industry in detail, aiming to research PLC and find more scenes in industry fields in which PLC can participate. PLC has a wide range of applications and significant importance in industry. The continuous progress and innovation of its technology will bring more opportunities and challenges to the field of industrial automation control. In the future, with the deepening development of advanced manufacturing models such as Industry 4.0 and intelligent manufacturing, PLC technology is expected to play a greater role in more fields and promote industrial automation to a higher level.

Control and monitor bottle filling, capping and labelling machine using a programmable logic controller and human machine interface

Bottle filling, closing, and labellingmachine control and monitoring tool using Programmable Logic Controller (PLC) and Human-Machine Interface (HMI). This tool is designed to optimize the production process in the bottled beverage industry,with dimensions of 200 cm × 70 cm × 100 cm. The conveyor transports bottles through the filling, capping, and labeling units. In each unit, sensors are installed to detect the presence of bottles. Bottle liquid volume is determined through time settings inputted through the HMI,and the filling is performed by a water pump. After filling, bottles are capped and tightened mechanically using an air impact system. Labeling is handled by two DC motors which unroll the label and rotate the bottle, ensuringthe label adheres evenlyto all sides of the bottle. The number of bottles produced is calculated using a capacitive proximity sensor and displayed on the HMI. Testing results show that the system effectivelycontrols and monitors the bottle filling, capping, and labeling process viaPLC and HMI. Based on the test results on the bottle filling unit, the system can fill water into the bottle with a maximum percentage error of 0.5% on a 1000 ml volume bottle. In the capping unit, the success rate achieved is 70%, while the success rate in the bottle labeling unit is 80%.

Using a Yolov8-Based Object Detection Model for an Automatic Garbage Sorting System

This study presents the development of an automatic garbage sorting system based on computer vision techniques and the You Only Look Once version 8 (YOLOv8) algorithm. RGB images of garbage, including cans and plastic bottles, were collected by a camera. The YOLOv8 model, trained on a dataset of both RGB images of cans and plastic bottles, acts as the core for detection and classification. During real-time sorting, the classification results and picking points from the YOLOv8 model are used by a gantry robot. The gantry robot is developed and controlled by a Programmable Logic Controller (PLC) to place each type of garbage into its respective categories. A conveyor tracking algorithm was implemented to pick up garbage moving on the conveyor. The system's performance is evaluated using 20 garbage samples for the can and the plastic bottle category. The accuracy, precision, recall, and F1 score were 92.5%, 90.5%, 95%, and 92.7%, respectively. The system proposed in this study can be modified to sort other garbage types.

Development of the intelligent traffic light system based on image processing and fuzzy control techniques

In Viet Nam's current traffic conditions, congestion and jams—especially at intersections during peak hours—present major challenges. Traditional traffic light systems, which rely on fixed timing principles, often fail to manage traffic flow efficiently, particularly when vehicle density varies significantly across different directions. This research aims to develop an intelligent traffic light system where the signal timings automatically adjust based on the vehicle density at intersections. The study uses an object recognition algorithm to identify, classify, and count vehicles. The data was then fed into a fuzzy logic model to calculate the optimal signal timings. Experimental results demonstrate an accuracy of approximately 88% in vehicle detection. The fuzzy logic model and the programmable logic controller were able to effectively compute reasonable signal timings based on real-time vehicle density. Future developments include expanding the system's functionalities, creating a user-friendly interface, and developing a management application for mobile devices.

Full-scale wind turbine performance assessment using the turbine performance integral (TPI) method: a study of aerodynamic degradation and operational influences

Abstract. This study investigates how blade aerodynamic modifications, including leading edge roughness (LER), influence wind turbine performance over their operational lifespan. It introduces a methodology developed to examine the intricate relationship between blade erosion, blade enhancements, operations and maintenance (O&M) events, control programmable logic controller (PLC) parameter updates, and their cumulative impact on turbine efficiency. Analysing data from 12 multi-megawatt offshore turbines over a 12-year period, the investigation hinges on the integration of supervisory control and data acquisition (SCADA) data, O&M records, and air density corrections. A key contribution is the development of the turbine performance integral (TPI) method, which, for the investigated turbines, leverages generator speed and power output data to track performance trajectories. Seasonal trend decomposition using locally estimated scatterplot smoothing (STL) further isolates long-term trends and seasonal variations in performance. Despite data availability and quality limitations, the study reveals significant findings concerning the impact of manufacturer software updates on turbine control strategies, resulting in improved performance; the variable effects of blade repairs and enhancements; and the complex interaction between O&M events and performance. This work applies a methodical approach and statistical rigour, offering a path forward for effectively monitoring wind turbine efficiency and advancing renewable energy.

Hyper CLS-Data-Based Robotic Interface and Its Application to Intelligent Peg-in-Hole Task Robot Incorporating a CNN Model for Defect Detection

Various types of numerical control (NC) machine tools can be standardly operated and controlled based on NC data that can be easily generated using widespread CAD/CAM systems. On the other hand, the operation environments of industrial robots still depend on conventional teaching and playback systems provided by the makers, so it seems that they have not been standardized and unified like NC machine tools yet. Additionally, robotic functional extensions, e.g., the easy implementation of a machine learning model, such as a convolutional neural network (CNN), a visual feedback controller, cooperative control for multiple robots, and so on, has not been sufficiently realized yet. In this paper, a hyper cutter location source (HCLS)-data-based robotic interface is proposed to cope with the issues. Due to the HCLS-data-based robot interface, the robotic control sequence can be visually and unifiedly described as NC codes. In addition, a VGG19-based CNN model for defect detection, whose classification accuracy is over 99% and average time for forward calculation is 70 ms, can be systematically incorporated into a robotic control application that handles multiple robots. The effectiveness and validity of the proposed system are demonstrated through a cooperative pick and place task using three small-sized industrial robot MG400s and a peg-in-hole task while checking undesirable defects in workpieces with a CNN model without using any programmable logic controller (PLC). The specifications of the PC used for the experiments are CPU: Intel(R) Core(TM) i9-10850K CPU 3.60 GHz, GPU: NVIDIA GeForce RTX 3090, Main memory: 64 GB.

A geometric model with stochastic error for abnormal motion detection of portal crane bucket grab

Abnormal swing angle detection of bucket grabs is crucial for efficient harbor operations. In this study, we develop a practically convenient swing angle detection method for crane operation, requiring only a single standard surveillance camera at the fly-jib head, without the need for sophisticated sensors or markers on the payload. Specifically, our algorithm takes the video images from the camera as input. Next, a fine-tuned ‘the fifth version of the You Only Look Once algorithm’ (YOLOv5) model is used to automatically detect the position of the bucket grab on the image plane. Subsequently, a novel geometric model is constructed, which takes the pixel position of the bucket grab, the steel rope length provided by the Programmable Logic Controller (PLC) system, and the optical lens information of the camera into consideration. The key parameters of this geometric model are statistically estimated by a novel iterative algorithm. Once the key parameters are estimated, the algorithm can automatically detect swing angles from video streams. Being analytically simple, the computation of our algorithm is fast, as it takes about 0.01 s to process one single image generated by the surveillance camera. Therefore, we are able to obtain an accurate and fast estimation of the swing angle of an operating crane in real-time applications. Simulation studies are conducted to validate the model and algorithm. Real video examples from Qingdao Seaport under various weather conditions are analyzed to demonstrate its practical performance.

DEVELOPMENT AND EVALUATION OF A MULTI-CHAMBER ENVIRONMENTAL CONTROL SYSTEM

Growth chambers are control devices used in plant research. However, their high costs limit their application to a single environment, which compromises their efficiency for the generation of experimental data. The objective of this research was to design, construct, and assess the performance of a multi-chamber environmental control system capable of regulating both air temperature (AT) and relative humidity (RH). The evaluation was carried out using Syngonium podophyllum Schott plants. Three constant target temperature values (18, 23, and 40 °C) were established, together with a target RH value of 60 %. AT and RH data were recorded every 4 min for three days. The system was built with 15 growth chambers and the following devices: output (AT, RH, and lighting control), input (sensors), and central control managed by two Arduino® Mega 2560 based microcontrollers, plus a programmable logic controller. Programming was done in open-source languages such as Arduino® and Python®. Results indicate that the absolute error (AE) and standard deviation (SD) in AT were higher when the target temperature was lower (AE = 0.59 °C and SD = 0.93 °C) compared to the other higher target temperatures (AE = 0.31 °C and SD = 0.43 °C at 23 °C, and AE = 0.25 °C and SD = 0.51 °C at 40 °C). On the other hand, the AE in RH increased as temperature increased, going from AE = 3.75 % and SD = 5.12 % at 18 °C, to AE = 9.23 % and SD = 10.77 % at 40 °C. The use of open-source technologies allowed the construction of a multi-chamber environmental control system capable of replicating controlled environments.

Otomatisasi Penyemprotan Polyester Menggunakan Kawasaki Cobot dengan Human Machine Interface (HMI) Berbasis Web

Brago Luchttechniek BV is a company specializing in the production of PIR (Polyisocyanurate) air ducts, facing challenges in maintaining accuracy and consistency in the polyester insulation spraying process on its products using Kawasaki collaborative robots (cobot) for automation. To address these challenges, this study designed a web-based Human Machine Interface (HMI) to automate the polyester insulation spraying process on PIR air ducts using the Kawasaki Cobot. A web-based HMI was chosen for its ease of development, flexibility, and integration capabilities with modern technology. This HMI uses the TCP/IP protocol to send real-time command signals to automation devices such as the Kawasaki Cobot and devices connected to the Programmable Logic Controller (PLC). Testing results demonstrated an improvement in the spraying process efficiency, reducing the time from 15–18 minutes conventionally to 5–7 minutes with the web-based HMI automation. Additionally, the web-based HMI successfully communicated with other devices connected to the robot, such as the conveyor belt and rotating table, via TCP/IP protocols, with each device having its own ID and IP address to facilitate linear message delivery, prevent collisions, and minimize errors. After eight successful automation tests on four different products, the system operated smoothly and systematically through the available HMI controls. The system was also evaluated by four respondents, with an overall score of 4.33 out of 5, indicating a high level of satisfaction.

Integrating reinforcement learning and supervisory control theory for optimal directed control of discrete-event systems

Directed control is crucial for implementing controllers on programmable logic controllers. A directed controller is one that actively selects at most one controllable event (control command) to execute at any instant. This study investigates the numerical optimization problem of directed control for discrete-event systems, such as traffic systems and robotic systems. By integrating supervisory control theory and reinforcement learning, an algorithmic procedure is designed to synthesize an optimal directed controller, which minimizes the total cost associated with event execution while ensuring the safety and liveness of the controlled system. Two improved Q-learning algorithms incorporating dynamic parameter adaptation strategies are developed to enhance the global search ability of basic Q-learning. To demonstrate applicability and effectiveness, we apply the proposed method to control a guideway system and a multi-train traffic system, respectively. The experimental results indicate the superiority of the proposed method over the comparison methods.

Cybersecurity in Prognostics and Health Management

PHM continues to show its value by improving operational efficiencies, increasing safety, reducing downtime, and decreasing cost of operations. PHM technologies are therefore not only being deployed as retrofit solutions but are being integrated into new systems as standard practice. Deployment covers areas such as medical equipment, nuclear power plants, aeronautics applications, oil and gas, mining, and many others. As the impact of PHM increases, it is imperative to also consider the potential vulnerabilities that are being exposed. Hackers have famously used Supervisory Control and Data Acquisition (SCADA) and Programmable Logic Controller (PLC) systems to sabotage industrial facilities. As such, it is important to understand the exposure to malfeasance to ensure that PHM does not end up being the enabling mechanism for unauthorized access to the system it is meant to keep in running order. It is also important to understand the measures that need to be taken to avoid or respond to an attack. These range from extensive penetration testing to conducting extensive counter-social engineering training, setting up a PHM-specific CERT plan and team in place. This paper discusses various threats that are emerging and that may have to be considered when designing a PHM solution. Additionally, the NIST cybersecurity framework is discussed in the context of PHM. Finally, this paper looks at the diagnostic capabilities of PHM systems to detect cyber security attacks and to contain these threats.

PLC Honeypots: Enhancing Interaction-Level Assessment

The motivation for this work arose when noticing that definitions of honeypots’ interaction level are mainly based on the information technology environment and do not reflect operational technology even if several honeypot projects approach this field. Within operational technology, programmable logic controllers (PLCs) have a main role, resulting in several honeypot researchers choosing to mimic this device at a certain interaction level. However, searching for an interaction level definition that approaches PLCs results in few studies. In this context, this work aims to explore how to adapt the information technology definition of the interaction level in order to encompass PLCs and their specific features. The method chosen to obtain inputs was a literature review where, in attempting to keep the connection with information technology, the features were based in terms of honey system, honey service, and honey token. The findings of this review provide a means to translate these terms when developing a PLC honeypot for a desired interaction level, resulting in a metrics proposal for low and high interaction. Summarizing the proposed metrics, the system of a PLC can be considered as the vendor specific firmware, its unique device banner, and a realistic network topology. For services, a PLC honeypot reflects the tasks performed by the real device, thus resulting in industrial communication protocols, network management protocols, appropriate response times, code-related interactions, dynamic input and output data processing, physical process simulation, and web interface. Lastly, a PLC honey token can be approached with the PLC program file, MIB file, and software license, among other elements. Based on these metrics, researchers can better evaluate how to design a programmable logic controller honeypot or select tools that match their target interaction level.

CONTROL SYSTEM OF CATENARY CONTINOUS VULCANIZATION LINE FOR RUBBER CABLES

The paper presents the control system of a continuous vulcanization line for the production of cables and conductors with rubber insulation, where the vulcanization process takes place in water and steam (vapour) atmosphere. The control, monitoring and recording of relevant parameters of the whole technological process was carried out with help of PLC (Programmable Logic Controller) and HMI (Human Machine Interface) and KepwareEx server. The control system is used to generate control signals for the regulation of speed, tension force, extruder temperature, water level and steam pressure in the vulcanization tube according to the technological parameters of the line. The monitoring system enables visualization of all technological units of the line via the HMI screens. The parts and entirety of the line are represented by conveniently drawn symbols that change colour depending on the current state and display the variables relevant to the operation of this object. Through the use of the KepwareEx server and database, the values of the variables important for the operation of the plant are recorded in real time. The developed supervisory and control system allows easy operation and monitoring of all important parameters of the plant.

Carryover slag weight prediction under converter tapping process by applying attention-shifting infrared thermal mapping technique

The prediction model of actual slag weight under converter tapping process was constructed by applying attention-shifting infrared thermal mapping technique. Firstly, the linkage between programmable logic controller signal of the converter mechanical structure and the infrared thermal mapping detector image was realized to ensure the real-time monitoring of the whole tapping process. Images should be preprocessed to ensure a good distinction between the flowing liquid and background at the tapping beginning, furthermore to separated slag from liquid steel at the following process. Moreover, the use of attention-shifting block belonging to the infrared thermal detector was effect to obtain more accurate image distinction between the liquid steel and slag. Hence the gray degree threshold value was adjusted to 220–225 in the early stage, and the value was needed to be lowered to 170–176 in the end. After using the model, the slag weight was less than < 8.0kg/t when only slag-stopping awl was adopted in tapping process. The average weight of slag in converter was 7.3kg/t by using slag-stopping awl and sliding plate slag-blocking.

Sistem Otomatisasi Pemberian Pakan secara Terjadwal untuk Pembibitan Ikan Lele di Fardu Farm Pekanbaru menggunakan PLC dan IoT

<p><strong>With the increasing global population growth, the demand for fishery products, including catfish, continues to rise. Catfish seed production plays a crucial role in the fisheries production chain, as this stage ensures the availability of high-quality fish seeds. However, fish farmers still face challenges in increasing aquaculture production, especially regarding inefficient manual feeding practices. This research aims to develop an automated catfish feeding system on a schedule at Fardu Farm using a combination of Programmable Logic Controller (PLC) and Internet of Things (IoT) technologies. In this study, the researchers design and implement an automation system that enables scheduled feeding in catfish seedlings. The use of Outseal PLC connected to IoT allows for precise and efficient feeding control. This research conducts testing to verify the system's performance, including measuring the weight of the feed dispensed and testing feeding over specific time periods. The results of the study indicate that this automation system successfully provides timely feeding according to the established schedule. Additionally, manual control using the Blynk platform also yields good responsiveness. Thus, the developed system can enhance efficiency in feeding catfish seedlings at Fardu Farm.</strong></p><p><strong><em>Keywords</em></strong> - <em>Automation, Feeding, Catfish Breeding, PLC, IoT.</em></p>