Manual Control Research Articles

Analysis of security parameters specific to coal mines

Coal continues to remain a basic energy source for industry, but the impact on the environment and underground security resulting from its extraction and use must be given ever-increasing attention. Ecological impact analysis is currently the most powerful tool for preventing pollution and environmental degradation, respectively for underground security, in any project related to coal mining. The current trend of restricting mining activity in more productive perimeters, but far from the main connections with the surface, implies a substantial increase in the demand for ventilation systems due to underground pollutants and implicitly the continuously increasing risk factors. The particularly complex conditions and with major implications in the security levels of mining operations require the objectification of control by monitoring security parameters, through systems, installations, devices and modern automatic programs in parallel with the manual control system with modern portable devices. The paper analyzes the possibility of monitoring security parameters related to the environment, mine fires and degassing installations specific to mining operations in the Valea Jiului coal basin, in order to remove several risk factors that endanger underground mining. The main safety parameters analyzed refer to the underground environment, endogenous fires and degassing of coal seams. The parameters that are followed in order to assess the efficiency of the degassing networks are: the depression in the degassing network, the methane concentration of the captured gas and the methane flow from the network.

Design of Home Automation System with Emergency Control

In today's society, there is a growing demand for smart home solutions that not only enhance convenience but also make a significant impact on affordability and widespread adoption. This paper describes the proposed design of a Node MCU-based Home Automation system with an integrated Wi-Fi module that enables internet-based remote control of home devices. The design utilizes a basic code template to connect with the Tasmota Web interface to configure the ESP module. The system is integrated with Alexa, offering various integration options such as routines, schedules and alarms. Furthermore, it adds a manual control feature for situations where there is no internet connection and an additional level of safety through emergency controls in the event of electronic failure. A comparison of energy usage with and without the use of the proposed system is also reported. A noticeable decrease in daily electricity consumption is observed on using the designed automation system. To ensure cost-effectiveness, locally available components are utilized in the design. Consequently, it ensures that enhanced comfort, convenience, and control over one's living environment are available to a wider audience.

РАЗРАБОТКА ПРОГРАММНОГО ОБЕСПЕЧЕНИЯ ДЛЯ СИСТЕМ АВТОМАТИЗИРОВАННОГО УПРАВЛЕНИЯ ТЕХНОЛОГИЧЕСКИМ ПРОЦЕССОМ МЕХАНООБРАБОТКИ

The automation of production processes is the main direction in which manufacturing is currently being taken around the world. Currently, production automation is one of the ways to increase the efficiency of an enterprise. The main direction of automation of machining production is based on the widespread introduction of computer numerical control (CNC) systems. In a situation of limited opportunities to purchase new equipment with numerical control, the task of import substitution is set. One of the directions in solving this issue is expanding the functionality of existing CNC equipment at the enterprise by developing new control programs for them. This paper presents the results obtained for the milling section of numerically controlled machines of the HAAS model of the Super Mini Mill series of the industrial enterprise Avia LLC. The fundamental feature of a CNC machine is that it works according to a control program (CP), on which the cycle of operation of the equipment for processing a specific part is recorded. A preliminary analysis of the technical documentation of these machines showed that a number of important operations are missing from the control program, as a result of which some of them are performed manually by operators. The authors have developed new software, taking into account the identified shortcomings, using additional operations that expand the functionality of the considered equipment and eliminate manual control by machine operators. The software in automatic mode provides: setting a correction for the tool radius, which allows you to make the part contour programmed in the NC program independent of the diameter of the tool used; control of turning on/off the cutting fluid (coolant); the function of turning on the optional stop of the machine, in which the next operation starts automatically; recording the time of operations at each section of product processing. The program allows you to automatically control the trajectory of movement of the machine's executive bodies, and automates the process at the stage of setting up the tool for the product processing technology. Thus, automation of a number of operations on a CNC machine is aimed at increasing productivity, quality and accuracy of processing, reducing processing time and reducing the risk of producing defective parts. Author's certificates for state registration of the computer program were received.

Attributes and Effect of Implementation of Warehouse Management System (WMS) for Company Sustainability

This research discusses the effect of implementing a Warehouse Management System (WMS) on company continuity by coordinating and integrating other systems that will directly control the important attributes of a physical warehouse as a facility for warehouse operational activities. The aim of this research is to answer specific questions regarding the important attributes of a warehouse with optimal WMS implementation, which will have a significant impact on the company. This research was conducted using the Systematic Literature Review (SLR) method with references from various literature sources discussing WMS research results in the last 10 years. The results of this research state that optimal implementation of WMS in a company's warehouse will have a significant effect on the smooth running of warehouse operations, which will increase customer relationships and customer satisfaction. This happens because there are minimal errors and obstacles that will occur during the process of controlling and managing goods as a whole in the warehouse until they are sent to consumers. Optimal implementation of WMS is a more effective and efficient solution than manual warehouse management and control in the current era of technology.

Rancang Bangun Prototipe Home Automation Menggunakan Teknologi Internet Of Things

Internet of Things (IoT) technology is often used to monitor and control electronic equipment remotely using the internet. The implementation of Internet of Things technology can be applied to home automation. The implementation of IoT in a home automation system (home automation) can be used to control home lights, home temperature, and electronic plates in the home, and it can even be used to determine the whereabouts of home occupants. In this research, we will create a home automation prototype with the Internet of Things concept, which can be built using the NodeMCU module integrated with a web application. The data communication system in home automation will communicate with the MQTT server and can send data (publish) and receive data (subscribe). The home automation system can carry out manual or scheduled monitoring and control. It can provide notifications whenever a change in the condition or status of the device is being monitored or controlled. Changes in conditions can also occur through sensor readings connected to the NodeMCU module.

Diagnostics and predictive maintenance of industrial electric motors

Automatic continuous or periodic control is the most promising method of diagnosing electric motors in productionnowadays. Itis aimed at predicting breakdowns and the remaining useful lifetimeof motors. However, research in this arearemains purely theoretical and eitherfocuses on very narrow problemsor providestoo superficial overview.Consequently,manual control devices orpartially automated devices are mainlyusedin practice[1]. In view of this, there is great interest in the development of a software method for predictive maintenance of electric motors. In this research recurrent neural networks with long short-term memory layers (LSTM-layers)are investigated due to their abilityto effectively model sequential data and learn complex dependencies [2].

Revolutionizing Accessibility: Smart Wheelchair Robot and Mobile Application for Mobility, Assistance, and Home Management

This research aims to advance accessibility and inclusivity for individuals with disabilities. We focus on specific daily challenges facing people with disabilities in communication, mobility, and daily task management and introduce AssistEase, a groundbreaking smart wheelchair solution designed to empower people with disabilities by improving mobility, communication capabilities, and daily task management. AssistEase will contribute to the disabled community around the world by allowing them to manage daily tasks and communicate more easily while ensuring mobility. AssistEase offers control options such as handsfree voice control, traditional manual control, smartphone-based Bluetooth control, or innovative gesture control, designed to cater to different user preferences and needs. This uses technologies such as speech recognition, computer vision, and haptic [92] feedback to help users navigate safely while avoiding obstacles. It integrates technologies like Flutter, TensorFlow, YOLOV8, Global Positioning System (GPS), Bluetooth, and Apple Home Kit, along with hardware components including Arduino and Raspberry PI. Preliminary trials have shown improvements in mobility, communication, and daily tasks for users in need. It achieves 95% precision in guiding wheelchair users while maintaining about 90% accuracy for the robotic arm and 89% for health monitoring and location tracking. Also, it provides a user-friendly app with 90% control accuracy. The communication device has 92% accuracy in facilitating user communication, while hand gesture control achieves 90% accuracy. To advance AssistEase smart wheelchair technology, further research, and development are required to enhance its adaptability for specific disabilities. AssistEase reflects a commitment to creating a more inclusive and thriving society, focusing on innovation and inclusion for individuals of all abilities.

Diagnostic system of the facility for studying superconducting quadrupoles

For the HED@FAIR project, NRC “Kurchatov Institute” — IHEP creates four quadrupole magnets with a unique combination of a large internal diameter of the superconducting winding and a high magnetic field gradient in the magnet aperture. To evaluate these superconducting magnets in different operation modes (cooling, maintaining operating parameters, heating, and transitioning magnet to the normal state), a cryogenic facility equipped with a diagnostic system was created. The main measured parameters of the unit were temperature, pressure, and vacuum in the equipment and pipelines, levels of liquid helium and liquid nitrogen, level of the gas holder, and helium flow rate. The control devices were represented by valves with electric and valves. For processing incoming signals from sensors and generation of control actions, the equipment of the domestic company OVEN was used, particularly analog input modules MV110, discrete output modules MU110, and interface converters alternating current four and direct current power supplies. The critical part of the diagnostics system, namely, the control of cryogenic valves, was provided through analog output modules NI 9219 and input modules NI 9212 (feedback) of the CompactRIO chassis. The program part of the installation for the study of superconducting quadruples is a mnemonic diagram with interactive graphic elements, physically located on the computer (operator console), and available in the read mode via the remote desktop protocol to users outside the installation. The mnemonic scheme allows the manual control of the plant’s valves and the automatic regulation of some indicators, depending on the settings assigned by the operator. The dynamics of the processes can be monitored with graphs on the right side of the interface. These graphs are displayed on a separate display at the operator’s console, whereas they are displayed on a unified screen for remote users.

Pengaruh herbisida bentazon 400 g/l + mcpa 60 g/l terhadap gulma, pertumbuhan dan hasil tanaman padi (Oryza sativa L.)

Weeds are one of the obstacles in rice cultivation because they can reduce rice yields both in quality and quantity. Weeds compete in terms of necessities of life such as water, nutrients and sunlight. This study aims to determine the effect of betazon 400 g/l + MCPA 60 g/l in controlling weeds and the growth of paddy rice. The research was conducted in Palasah Village, Kertajati District, Majalengka Regency, West Java. The experiment used a one-factor Randomized Block Design (RBD) with seven treatments and four replications. The experiment consisted of five treatments of bentazone 400 g/l + MCPA 60 g/l at a dose of 1.5 L/ha, 2.0 L/ha, 2.5 L/ha, 3.0 L/ha, 3.5 L/ha, the comparison is in the form of manual control and without weed control. The data obtained if there is a significant difference will be further tested using the testDuncan Multiple Range Test (DMRT) at the level of 5%. The results showed that the application of the herbicide Bentazone 400 g/l + MCPA 60 g/l at a dose of 1.5 L/ha was able to suppress the growth of broadleaf weeds (Lindernia crustarcea, Spenoclia zeylanica and Marsilea crenata), sedge weeds (Cypress iria and Fimbristylis miliacea) and does not cause symptoms of toxicity (phytotoxicity) to rice plants which so that they do not interfere with their growth.

Изменение бюджетных параметров в условиях турбулентности

Declining budget revenues, the coronavirus pandemic, economic sanctions imposed by unfriendly states, and other similar factors that have a significant impact on the budget and budget system require prompt management decisions. The fiscal policy of all budget levels is currently being implemented in conditions of turbulence, faced with the need to respond to the challenges of the new reality. The research hypothesis was that there are many facts and phenomena that reflect the presence of non-systemic external influence on the approval and execution of the budget. These include budget imbalance, deviation of its execution from the approved one, adjustments to the approved volumes of budget revenues and expenditures, asynchrony of its execution in during the financial year, etc. Using data collected from federal laws on the federal budget since 1999, as well as data from the Russian Treasury, we show that the above phenomena are generally characteristic of the budget policy of the Russian Federation, and elements of manual control only increase during crisis periods. At the same time, the lower levels of the budget system have fewer opportunities to respond to the challenges of turbulent time than the higher ones.

Converting a DJI Tello Quadcopter into a Face-follower Machine Using the Haar Cascade with PID Controller

Drones have been frequently used for photography in recent years at significantly cheaper rates. However, the most modern drones are exceedingly error-prone and require precise manual control to take high-quality photos or films. We suggest using the AI method of Haar cascades with a PID controller to give drones vision, enabling them to do autonomous tracking and detection. This project aims to improve photography fields. The proposed system tries to detect the face and track the person's movements. This system will help photographers and journalists upgrade their work, even if it is used in surveillance and the military. The algorithm's results show that the DJI Tello tiny drone's camera is capable of detecting and tracking faces. The micro drone was picked since it is lightweight and compact, making its use safe and enabling testing to take place inside. Additionally, the DJI Tello may be easily programmed using Python. The position of the drone is contrasted with the set point in the center of the image to identify errors, allowing control signals for calculating forward/backwards, right/left, and yaw movements. The proposed system results show that the drone can detect and track the face very well, and the PID values are stable.

Prediction of Duration of Dry Bamboo Leaf Counting Using Fuzzy Logic

Dry bamboo leaves are selected as a planting medium for ornamental plants to enhance nutrient content and improve soil drainage. Before being processed into fertilizer, dry bamboo leaves need to be shredded first. The leaf counting process for planting ornamental plants in villages still relies on manual methods such as using knives and scissors, which can be time-consuming and less effective. In response to this issue, a device for shredding dry bamboo leaves has been developed to improve efficiency and facilitate the leaf counting process. The innovation created is a household-scale dry bamboo leaf shredder that is more affordable and easy to mobilize due to its compact dimensions and lighter weight. The device is also easy to operate, as the shredding occurs when it is closed, and the process stops when it is opened, ensuring safe use for various users. The manual control of bamboo leaf weight and counting duration results in inconsistent shredding outcomes. Therefore, development has been carried out on the dry bamboo leaf shredder with artificial intelligence capabilities, specifically using fuzzy logic to automate the counting duration based on the size and weight of the bamboo leaves being inputted.

Driver behavior while using Level 2 vehicle automation: a hybrid naturalistic study

Vehicle automation is becoming more prevalent. Understanding how drivers use this technology and its safety implications is crucial. In a 6–8 week naturalistic study, we leveraged a hybrid naturalistic driving research design to evaluate driver behavior with Level 2 vehicle automation, incorporating unique naturalistic and experimental control conditions. Our investigation covered four main areas: automation usage, system warnings, driving demand, and driver arousal, as well as secondary task engagement. While on the interstate, drivers were advised to engage Level 2 automation whenever they deemed it safe, and they complied by using it over 70% of the time. Interestingly, the frequency of system warnings increased with prolonged use, suggesting an evolving relationship between drivers and the automation features. Our data also revealed that drivers were discerning in their use of automation, opting for manual control under high driving demand conditions. Contrary to common safety concerns, our data indicated no significant rise in driver fatigue or fidgeting when using automation, compared to a control condition. Additionally, observed patterns of engagement in secondary tasks like radio listening and text messaging challenge existing assumptions about automation leading to dangerous driver distraction. Overall, our findings provide new insights into the conditions under which drivers opt to use automation and reveal a nuanced behavioral profile that emerges when automation is in use.

Automatic Crop Protection from Rain Fall Using IOT and IBM Cloud

With the ongoing fourth revolution, technology has been growing rapidly day by day. One of the most significant and efficient uses of this has been evident in the farming sector. From a basic water sprinkler system to the requirement of Fertilizer for specific crops, the likes of Artificial intelligence and the Internet of things have brought in great changes. One of the issues which need to be addressed is the protection of crops from heavy rainfall which causes significant damage to the crop production and soil yield, also causing huge mental distress to a farmer. We in our proposed model have given a solution to this problem by giving automated as well as manual control. The motivation behind our paper is to keep the crops protected from these heavy precipitations and preserve the same rainwater for future purposes when water is scarce. We use a sensor with a NodeMCU module to ensure the covering of the estimated field and LCD display to show status of Field. This project addresses the critical issue of protecting crops from heavy rainfall through the integration of Internet of Things (IoT) technology and the IBM Cloud platform. By deploying a network of sensors capable of measuring rainfall intensity, soil moisture, temperature, and humidity, real-time data is collected and transmitted to the IBM Cloud for analysis. These measures may include adjusting protective structures, or activating drainage systems. The project aims to improve crop yield and reduce losses caused by adverse weather conditions, making agriculture more sustainable and efficient. The combination of IoT and IBM Cloud empowers farmers with real-time monitoring and control, enhancing their ability to protect valuable crops. This project not only demonstrates the practical application of advanced technologies in agriculture but also provides a foundation for future research and development in this field.

Assessment of the influence of interfering factors on the measurement of the depth of surface cracks of rails during manual eddy current control

Experimental studies have been carried out on the effect on the amplitude and phase of the signal of the eddy current converter of the angle of inclination, the curvature of the surface, the gap between the converter and the controlled surface of the rolling rail.

Effect of Some Chemical Herbicides on the Weeds Accompanying the Field's Peanut Crop

A field experiment was conducted during the spring season of 2021 in a selected field of preparative Ibn Al-Bitar occupational/ Al-Hussainiya region in Holy Karbala. The experiment involved cultivating peanut plants (Arachis hypogaea L.), specifically a local variety, in soil characterized by a clay loam texture. The experiment aimed to determine the most effective chemical herbicides for controlling weed growth in conjunction with the Peanut crop. The experiment utilized a randomized complete block design (RCBD) with three replications. The study encompassed six conditions: weedy and weed-free, which were under manual control for the entire duration of the growing season. Furthermore, there were treatments that involved the administration of chemical herbicides before planting, specifically Trifluralin and Pendimethalin, which were applied ten days before the planting phase. Additionally, post-planting herbicides, namely Oxyfluorfen and Clethodim, were sprayed during the vegetative growth phase of the plant as well as at the initiation of the flowering stage. The herbicides were administered according to the prescribed dosages. The findings demonstrated significant differences in the management procedure utilizing chemical herbicides throughout a 30-day period of applying said herbicides. This discrepancy became apparent when evaluating the two herbicides, specifically Oxyfluorfen and Pendimethalin, which produced the lowest quantity of broad-leaf weeds, with a recorded density of 4.6 and 7.6 plants m-2, respectively. Additionally, the results demonstrated that notable disparities were observed after 60 days from the application of herbicides. Specifically, the herbicides Pendimethalin and Oxyfluorfen exhibited the lowest density of broad-leaf weeds, with a count of 4.6 and 6.0 m-2 plants, respectively. Moreover, the impact of herbicides on narrow-leaf weed was examined at 30 and 60 days post-spraying. There was no significant difference in the means of the herbicides, and the herbicides Oxyfluorfen and Pendimethalin yielded the least density of broad leaf weeds after 90 days of herbicide application, with quantities of 6.0 and 6.3 plant m-2, respectively. Similarly, concerning narrow-leaf weed density on the same date, the herbicides Trifluralin, Clethodim,, and Ox-yfluorfen exhibited superiority in achieving the lowest density of narrow-leaf weeds, with quantities of 5.0, 5.3, and 5.6 plant m-2, respectively. Furthermore, no statistically significant difference was observed among these herbicides. The findings demonstrate the superiority of the herbicides Oxyfluorfen and Pendimethalin in achieving the highest percentage of control for broad-leaf weeds after 30, 60, and 90 days of herbicide application. Regarding the specific dates for the narrow-leaf weeds, the herbicides Oxyfluorfen, Clethodim, and Trifluralin exhibited superiority in providing optimal control. In contrast to alternative treatments involving herbicides, the herbicide Oxyfluorfen showcased the most diminished mean mass and the utmost level of hindrance on both extensive and limited-leafed weeds. Keywords: Herbicides; Oxyfluorfen; Pendimethalin; Clethodim; Trifluralin; Weeds; Narrow leaf; Broad leaf.

Constrained model predictive control of an industrial high-rate thickener

High-rate thickeners are used in the mining industry to improve water recovery from slurries and increase their solids ratio. High-rate thickeners operate under strict constraints and several disturbances. To control this process, a constrained model predictive control (MPC) is developed in this paper. For process identification, a historical data-driven methodology is used and a vector autoregressive with exogenous variables (VARX) model structure is considered. The model takes underflow slurry density as both a state variable and the process output, along with turbidity, bed level, rake torque, and cone pressure as additional state variables. It takes feed slurry and flocculant flow rates as manipulated inputs and considers inlet slurry density, slurry circulation flow rate, and underflow slurry flow rate as disturbances. The VARX model structural parameters (orders and delays) and coefficients are estimated using a bilevel optimization method. From the model obtained, a discrete state-space representation is derived. This latter is augmented to obtain a standard formulation without delays. The MPC is then formulated considering the process constraints. To evaluate the control performance, simulations are conducted and a baseline comparison is established using proportional integral (PI) control. Simulation results demonstrate that the proposed control method outperforms the baseline method by providing reduced settling times (−32%), minimized peak errors (−20%), and constraints handling ability. Accordingly, the proposed MPC is implemented in an industrial environment and compared to existing manual control based on an object linking and embedding (OLE) for process control (OPC) architecture. Finally, the industrial results show that the proposed control method effectively stabilizes the underflow slurry density and handles process constraints, resulting in a minimized average error (−90%) and a reduced standard deviation (−50%) compared to existing manual control.

Research on the Application of Mechanical Automation Technology in the Field of Food Packaging

In recent years, the application of mechanical automation technology in the field of food packaging has greatly improved production efficiency and saved a lot of material and human resources in the production process. In mechanical automation, mechanical equipment runs the whole process automatically according to the specified program without manual control. Through the use of mechanical automation, it can realize automatic control and operation through mechanical means, promoting the development of the food packaging field, so that the backward production conditions have been improved. However, even so, there are still many aspects of mechanical automation worthy of attention, to make it better to promote the development of the field of food packaging, and improve production efficiency and quality, but also need to solve the existing problems.

A DRONE SYSTEM FOR AUTONOMOUS MAPPING FLIGHTS INSIDE A FOREST – A FEASIBILITY STUDY AND FIRST RESULTS

Abstract. In recent years, drones have gained wide popularity in forest research and operational applications. Over the forest canopy, where Global Navigation Satellite Systems (GNSS) are available, the flights are already highly automated. However, under the canopy of dense forests, the flights still need active manual control by a human pilot due to missing GNSS signal and obstacles. The objective of this study was to design and implement a prototype of a drone autonomously flying inside a forest for future boreal forest research purposes by utilizing open-source algorithms. Based on a literature survey, EGO-Planner-v2 with VINS-Fusion localization and stereo-depth camera-based mapping was chosen as the base of the implemented prototype. The algorithms were first tested in a simulator and later a custom drone hardware was built to evaluate the performance and suitability in real boreal forest environments. The evaluation criteria for the performance were the success of the mission, the reliability of the obstacle avoidance, and the accuracy of the localization. Based on the results, the performance of the prototype was promising, but in dense forests, the sensing of small needleless branches and leafless understory vegetation needs to be improved to increase reliability. In a dense spruce forest, nine of 19 test flights were successful, when approximate flight distances varied between 35 m and 80 m. In the longest of those test flights, the error of the VINS-Fusion estimate of the trajectory length was approximately 1 m.

PENJADWALAN DAN PEMBERIAN PAKAN IKAN OTOMATIS BERBASIS INTERNET OF THING MENGGUNAKAN NODEMCU ESP8266 DAN APLIKASI BLYNK STUDI KASUS : TOKO FISH FRIENDLY

The utilization of the Internet of Things (IOT) in everyday life has penetrated into various fields, including in the field of animal husbandry. In this study, the authors raised a problem found in the Fish Friendly fish shop as a research site. The main problem found in this study is that farmers have difficulty in feeding which is carried out regularly and on a schedule. Sometimes in certain conditions, farmers cannot feed fish according to their schedule, this can cause a decrease in the quality of fish health so that it has a negative impact on the selling price of fish. This factor can be very important considering that fish feed must be maintained in quality and quantity. Based on the existing problems, a solution was created to design and make a tool by utilizing an automation system using IoT (Internet of things). To get the complete data needed, the author uses interview and field observation methods, besides that this research uses NodeMCU ESP8266 microcontroller devices and Servo Motors to design automatic feeders, as well as the use of the Blynk application as a remote control via a smartphone. The result of this study is that the tool made can provide feed to fish according to a predetermined schedule so that feeding can work periodically and effectively. In addition, remote control carried out through the blynk application runs smoothly, so the tool can work without manual control anymore.