Heating Control Research Articles

Fault Diagnosis of Wire Disconnection in Heater Control System Using One-Dimensional Convolutional Neural Network

Heaters are critical components in various heating control systems, and their faults are often a primary cause of system failure, drawing significant attention from engineers and researchers. Early and accurate fault diagnosis is crucial to prevent cascading failures. Many diagnostic methods target faults under generally stable and simple operating conditions, such as constant load or steady-state temperature. However, real-world scenarios are often complex and variable, involving dynamic loads, nonlinear temperature rises, and other challenges, which limit diagnostic accuracy. To address this issue, this paper proposes an intelligent fault diagnosis model based on a one-dimensional convolutional neural network (CNN), using the heater’s current and voltage as the input to the neural network. The effectiveness and accuracy of the proposed model were validated through experimental data under two different conditions, achieving an average accuracy rate of 98%. The disconnection faults were generated during actual operation and occurred in the early stages, differing significantly from artificially simulated faults, thereby increasing the difficulty of accurate diagnosis. Analysis and comparison of the experimental results demonstrate the feasibility of the intelligent diagnostic model and its high diagnostic accuracy.

Design of a Water Heater Heating System Based on Industrial Control Configuration Software WinCC

The report presents the design and implementation of a water heater control system utilizing SIMATIC WinCC configuration software. The research highlights the transition from traditional manual control methods to automated systems, demonstrating significant improvements in efficiency, user convenience, and energy conservation. By leveraging the advanced capabilities of WinCC, the system effectively monitors and controls water levels and temperatures, integrating real-time data processing with a user-friendly interface. The project showcases enhanced operational efficiency, safety, and environmental sustainability, emphasizing the critical role of technological advancements in industrial automation.

Reduction of Heating Energy Demand by Combining Infrared Heaters and Infrared Reflective Walls

We study the potential of infrared (IR) heaters in combination with IR reflective walls to reduce heating energy demand in buildings. Using IR heaters increases radiant temperature. Combined with IR reflective walls, less radiant heat is absorbed by the surrounding walls, and more is reflected to and absorbed by the occupants. This allows for lower air temperatures while maintaining constant thermal comfort. Lower air temperatures result in heating energy savings. In simulations, we examine the impact of four parameters on the thermal comfort indicator Predicted Mean Vote (PMV): wall temperature, inlet air temperature, IR heater power, and IR emissivity of the walls. To reduce the number of data points needed, we use a Central Composite Design for the layout of the simulation plan. The results show that the PMV can be changed from 0.15 to 1.16 only by lowering the emissivity of the surrounding walls from 0.9 to 0.1. At high IR heater power and at low wall temperature the impact of the emissivity on the PMV becomes larger. From the simulation data, we derive a response surface function to determine the required IR heating power for any given room conditions, which could be used for automated IR heater control.

Model Validation and Real-Time Process Control of a Continuous Flow Ohmic Heater

Ohmic heating is a highly efficient method for rapid fluid heating, with applications in fields such as food processing, pharmaceuticals, and chemical engineering. Prior to its industrial application, thorough analysis and modeling are crucial to ensure safe and efficient operations. Therefore, this research focuses on the development and validation of a transfer function-based model for a continuous flow ohmic heater (CFOH). Validation metrics include root mean square error (RMSE) and mean absolute percentage error (MAPE). The developed model achieves an RMSE of ±1.48 and a MAPE of ±2.58% compared to experimental results, demonstrating its accuracy. Furthermore, the research presents the implementation of robust real-time applications of advanced process controllers, including PID, MPC, and AMPC. These controllers were first simulated using the developed model and subsequently deployed in the pilot plant ohmic heater system to achieve precise temperature control and optimised input voltage. The reliability of this procedure was affirmed through a comparison between simulated results and empirical data obtained from the CFOH pilot plant. The study concludes by suggesting potential applications in fault diagnosis, educational training, system identification, and controller design.

RANCANG BANGUN MODUL TRAINER KIT SISTEM KENDALI BERBASIS DIGITAL

A control system is defined as a combination of several components that aim to produce a system response in accordance with the desired process variables. Therefore, control systems are now widely used in various fields such as industry, automotive, public facilities, and household appliances. Especially in the industrial field, control systems play a role in improving production quality and reducing production costs. To create qualified human resources who have a good understanding in this field, universities have an important role in realizing this. One of them is Udayana University through the Electrical Engineering Study Program in the Independent Learning Curriculum in the Control System + Lab Course. This study aims to design a Digital-Based Control System + Lab Trainer Kit Module using Arduio Uno to support the process of implementing practicum in the laboratory. In the trainer kit module, there will be three systems designed, which are DC motor direction and speed control system using L298N motor driver, water heater control system using DS18B20 temperature sensor, and also water level control system using HC-SR04 ultrasonic sensor.

Design energy flexibility within a comfort and climate box – An experimental evaluation of the internal heat pump control effects

Heat pumps are key in decarbonising the heating and cooling sector, while also supporting further integration of renewable energy resources when flexible heat pump operation is allowed. Within this context, smartly combining a heat pump, thermal energy storage and control system into a single product was introduced by the International Energy Agency and was named as a Comfort and Climate Box. Regarding heat pumps, manufacturers mainly include internal control constraints on the compressor ramping rate, cycling times, pump control etc. to ensure a safe and reliable operation. While these rules can generally not be bypassed, current literature mainly neglects or simplifies these control constraints, while the potential effects on the energy flexibility provision remains unknown. This leads to two main uncertainties. One the one hand on how flexible heat pumps really are when having to communicate from an overarching control system to the actual heat pump system, taking into account all the different internal heat pump control strategies. On the other hand, uncertainties also arise on which control aspects are of crucial importance to incorporate, even within a simplified heat pump model. Hence, this paper aims to experimentally investigate the effects of the on-board heat pump control in a Comfort and Climate Box system, while providing energy flexibility services, both for space heating and domestic hot water services. Comparison of experimental results retrieved from a hardware-in-the-loop set-up to results obtained from a simplified heat pump simulation tool for design energy flexibility evaluation showed deviations up to 17.73 % on the flexibility efficiency, 125.95 % on the charging time and 32.90 % on the discharging time. These results prove the requirement of incorporating the internal heat pump control for energy flexibility analysis, even within the design stage. Investigated aspects included the compressor ramping rate, back-up heater control, pump control, temperature measurement location in a thermal energy storage and the hydraulic integration of a thermal energy storage. Results show that especially the compressor ramping rate and mutual influence between the compressor speed, pump speed and back-up heater power cannot be neglected and should be incorporated in any heat pump model for energy flexibility analysis.

Fuzzy Logic Temperature Control on Blood Warmer Equipped with Patient Temperature and Blood Temperature

Body temperature in humans varies greatly depending on the location where the reading is taken. Normal core body temperature in humans is maintained by the hypothalamus and usually ranges from 36.5°C to 37.5°C. One of the causes of the failure of Too high or too low of a temperature during the blood transfusion procedure may cause blood to freeze or get damaged, both of which can be fatal to humans, therefore the purpose of this tool is to lower blood temperature admission to the patient can be achieved so that there is no temperature drop or temperature drop and so that the blood is not too hot because it can cause damage to red blood cells. This study uses the DS18B20 Sensor to control the heater with PID and Fuzzy controls, the MLX90614 Sensor to adjust the temperature according to the patient's body temperature and the Optocoupler Sensor as an indicator when fluids run out. Previous studies have not used the MLX90614 sensor to detect patient body temperature, have not used TFT Nextion and have not used Fuzzy controls. This Fuzzy control is used as a heater control which then the results are displayed on the Nextion TFT. The results of this study obtained the highest error value of 0.09 with an average error value of 0.04 and obtained the highest overshoot value of 0.8. From the results of the above study it can be concluded that by using the Fuzzy control the response time is slower with a larger overshoot. In the creation of this tool, the benefits that can be derived for the community are facilitating the monitoring of patient temperature and blood temperature during blood transfusions using the Blood Warmer device. The device is also equipped with sensors to detect patient and blood temperatures, and it comes with a Nextion TFT display. Therefore, this device is crucial in assisting the community in performing Blood Transfusions.

Controller Performance of Air Blowing Heater Applicable on Forming Process of UHMW Sheet Material

This paper presents the performance of an airblowing heater controller used with UHMW sheet material. Temperature control is implemented within the range of 80°C to 110°C to achieve the re-crystallization temperature of the UHMW sheet material. A PID controller was applied, and its performance was analyzed by varying the temperature set point (SET VALUE), the fan’s flow capacity, and the use of dual heaters to heat both surfaces of the UHMW sheet simultaneously. This paper also examines the effects of auto-tuning and selftuning PID methods on control performance. The test results indicate that balancing the fan’s flow capacity and the heat generation of the heater unit is the dominant factor in PID controller performance. In addition, with the use of double heaters, the material’s energy accumulation becomes the main factor, causing a slower PID controller response in reaching the target temperature. Implementing self-tuning PID constants yielded better controller performance compared to the auto-tuning method.

Design of Heater Control Equipment in Interface Mill Product Part Separator Process

The interface mill product's indication of the supporting components reveals a surplus of flaws, leading to the waste of plastic and iron materials. Black spots and holes are the two main forms of defect criterion finds, and both require correct handling to prevent long-term material and financial consequences. The equipment in this study is being designed with the intention of separating the supporting components of the plastic material from the iron substance so that both materials can be recycled. The strategy used to accomplish the goals of this study is the creation of a heater control system. The findings indicated that for the separation process for iron material portions to be carried out optimally, the temperature needed to melt plastic material was between 177 and 276 oC. Conclusion: This tool's design makes it easier for workers to separate parts with a 93% efficiency, lowering material prices by about Rp. 39,280,000 and handling time with tools by 164,976 seconds. Additionally, the iron material that is separated may be recycled.

Control Software Design for a Multisensing Multicellular Microscale Gas Chromatography System.

Microscale gas chromatography (μGC) systems are miniaturized instruments that typically incorporate one or several microfabricated fluidic elements; such systems are generally well suited for the automated sampling and analysis of gas-phase chemicals. Advanced μGC systems may incorporate more than 15 elements and operate these elements in different coordinated sequences to execute complex operations. In particular, the control software must manage the sampling and analysis operations of the μGC system in a time-sensitive manner; while operating multiple control loops, it must also manage error conditions, data acquisition, and user interactions when necessary. To address these challenges, this work describes the investigation of multithreaded control software and its evaluation with a representative μGC system. The μGC system is based on a progressive cellular architecture that uses multiple μGC cells to efficiently broaden the range of chemical analytes, with each cell incorporating multiple detectors. Implemented in Python language version 3.7.3 and executed by an embedded single-board computer, the control software enables the concurrent control of heaters, pumps, and valves while also gathering data from thermistors, pressure sensors, capacitive detectors, and photoionization detectors. A graphical user interface (UI) that operates on a laptop provides visualization of control parameters in real time. In experimental evaluations, the control software provided successful operation and readout for all the components, including eight sets of thermistors and heaters that form temperature feedback loops, two sets of pressure sensors and tunable gas pumps that form pressure head feedback loops, six capacitive detectors, three photoionization detectors, six valves, and an additional fixed-flow gas pump. A typical run analyzing 18 chemicals is presented. Although the operating system does not guarantee real-time operation, the relative standard deviations of the control loop timings were <0.5%. The control software successfully supported >1000 μGC runs that analyzed various chemical mixtures.

Comparison of optimizers for model predictive thermal control of buildings

Considering recent developments in the energy sector, further reduction of electricity cost and flattening of the electric power demand curve are needed. We have focused on an autonomous electric heater control system that can easily be implemented in existing buildings without strict comfort requirements. Examples are winter heating of warehouses and vacation homes, and heat drying of buildings under construction. We have set up a system that typically reduces electricity cost by about 40% on the basis of automatic weather and real time pricing forecasts. The system uses the building as an energy reservoir over periods with high electricity cost. Using a model predictive control system, we compare use of a genetic algorithm, a particle swarm optimization, and a neural network for heater control, all working in a closed loop to reduce the influence of modeling errors. We have simulated the performance of the systems using realistic data and found that all three optimizers give about the same performance, varying only a few percent in efficiency. However, the computational and memory requirements of the neural network are much lower than for the other optimizers, so it is preferable for use with inexpensive microcontrollers. We carried out a full-scale experiment at a residential house and found agreement with simulation results.

APPLICATION OF CARBON-CARBON COMPOSITE MATERIALS FOR THE MANUFACTURE OF HIGH-TEMPERATURE HEATERS OF HEAT EXCHANGERS WITH AUTOMATIC TEMPERATURE CONTROL

&#x0D; The article justifies the use of high-temperature heaters made of carbon-carbon composite material (CCCM) for the thermal unit of a silicon single crystal growth chamber. The conducted analysis confirms that the electrical properties of composite materials, specifically their specific resistance, allow for the creation of heating elements for high-temperature vacuum furnaces or furnaces operating in inert atmospheres at temperatures up to 2200°C.&#x0D; The use of heaters made from carbon-carbon composite material eliminates the main drawback of graphite heaters - uncontrolled energy dissipation during resistive heating due to the presence of transient electrical resistance at the junctions of graphite plates, and ensures a more uniform temperature field throughout the chamber volume. The capabilities in terms of the maximum permissible temperature of such a CCCM heater exceed the working temperature by more than two times, which also positively affects the service life.&#x0D; The modes of thermal processes occurring during crystal growth are determined by the technological process depending on the composition of the raw material and require high uniformity of heating in the working zone, high precision, and stability of the heater's temperature control. For precise temperature regulation, it is proposed to additionally measure the integral temperature in the chamber indirectly, which is based on measuring the electrical current passing through the heater, which is in thermodynamic equilibrium with the object. Thus, the heater is considered as a system susceptible to various thermal influences that determine the heat transfer process and the temperature change within the chamber and in the zone of the thermal unit's bricks.&#x0D; An improved structural diagram of a step-type extremal control system is proposed for automatic temperature control of a high-temperature heater using modern power electronics, sensors, microprocessors. To ensure speed and accuracy in temperature control, the pulse-phase control method implemented with modern specialized thermoregulator with PID-regulation was applied.&#x0D; Experimental tests conducted on the «Redmet-30» installation under factory conditions confirm the energy efficiency of using high-temperature heaters made of CCCM.

Code generation for embedded predictive control of gas water heaters

Conventional control strategies usually employed in tankless gas water heaters present difficulty in controlling the hot water temperature when subjected to sudden changes in water flow rate. Inadequate control leads to temperature overshoots and undershoots with long settling times that severely affect the user comfort, increasing water and energy wastage and associated gas emissions. A strategy based on model predictive control is presented to reduce the impact of changes in hot water demand. A semi-empirical model, parameterized with experimental data and compatible with real-time simulation, is used for the heat cell. A tailored state observer is proposed, considering time-varying delays characterizing this thermal process. An automatic code generation software tool was developed for the embedded implementation of gas water heater predictive controllers. Numerical simulations and hardware-in-the-loop experiments were established to evaluate conventional and predictive control strategies. It was demonstrated that embedded model predictive control could be successfully implemented on computationally limited microcontrollers, even for thermal systems with extensive varying time delays. Predictive control has shown significant performance improvements, with decreased temperature fluctuations, a gain in comfort index from 36% to 75% and a reduction of up to 32 s in the settling time.

Embedded Model Predictive Control of Tankless Gas Water Heaters to Enhance Users’ Comfort

Water heating is a significant part of households’ energy consumption, and tankless gas water heaters (TGWHs) are commonly used. One of the limitations of these devices is the difficulty of keeping hot water temperature setpoints when changes in water flow occur. As these changes are usually unexpected, the controllers typically used in these devices cannot anticipate them, strongly affecting the users’ comfort. Moreover, considerable water and energy waste are associated with the long-time response to cold starts. This work proposes the development of a model predictive control (MPC) to be deployed in low-cost hardware, such that the users’ thermal comfort and water savings can be improved. Matlab/Simulink were used to develop, validate and automatically generate C code for implementing the controller in microcontroller-based systems. Hardware-in-the-loop simulations were performed to evaluate the performance of the MPC algorithm in 8-bit and 32-bit microcontrollers. A 6.8% higher comfort index was obtained using the implementation on the 32-bit microcontroller compared to the current deployments; concerning the 8-bit microcontroller, a 4.2% higher comfort index was achieved. These applications in low-cost hardware highlight that users’ thermal comfort can be successfully enhanced while ensuring operation safety. Additionally, the environmental impact can be significantly reduced by decreasing water and energy consumption in cold starts of TGWHs.

Realizing tight-binding Hamiltonians using site-controlled coupled cavity arrays

Analog quantum simulators rely on programmable and scalable quantum devices to emulate Hamiltonians describing various physical phenomenon. Photonic coupled cavity arrays are a promising alternative platform for realizing such simulators, due to their potential for scalability, small size, and high-temperature operability. However, programmability and nonlinearity in photonic cavities remain outstanding challenges. Here, using a silicon photonic coupled cavity array made up of 8 high quality factor (Q up to, sim 7.1times {10}^{4}) resonators and equipped with specially designed thermo-optic island heaters for independent control of cavities, we demonstrate a programmable photonic cavity array in the telecom regime, implementing tight-binding Hamiltonians with access to the full eigenenergy spectrum. We report a sim 50% reduction in the thermal crosstalk between neighboring sites of the cavity array compared to traditional heaters, and then present a control scheme to program the cavity array to a given tight-binding Hamiltonian. The ability to independently program high-Q photonic cavities, along with the compatibility of silicon photonics to high volume manufacturing opens new opportunities for scalable quantum simulation using telecom regime infrared photons.

Application of an Automated System for Converting Waste Cooking Oil into Aromatherapy Candles

This research focuses on the development of an automated system for the production of aromatherapy candles using waste cooking oil. The study addresses the challenges faced in small-scale production, including limited capacity, manual processes, and inconsistent product quality. To overcome these challenges, an automated machine is proposed to improve efficiency and productivity. The homogenization process and heating time were identified as critical areas for improvement. A sequential control system was successfully implemented, enabling the conversion of waste cooking oil into aromatherapy candles with a production capacity of 10.5 liters per unit run. The motor control system utilized On-Off control with modified power input to minimize vibration issues, operating the motor at 50-60 RPM. The temperature heater control system employed a PID control method, specifically the Ziegler-Nichols type 2 method, with Kp and Ki values of 247.5 and 1.104, respectively. The chosen PID parameters demonstrated satisfactory performance, including a rise time of 22.95 minutes, maximum overshoot of 2.85%, and a dead time of 510 seconds. The implemented system was controlled using an Arduino controller, ensuring a fast response and stable operation.

On-Chip Heater Design and Control Methodology for Reliability Testing Applications Requiring Over 300°C Local Temperatures

This paper presents the design details and control methodologies for on-chip heaters that can provide fast and accurate local temperature control for reliability testing applications. The on-chip heater uses the Joule heating effect of a metal or poly line to heat the surrounding devices-under-test (DUT) to a target temperature as high as 300∘C. Many generations of on-chip heaters, including different heater positions, heater areas, and heater layers, have been demonstrated in technology nodes from 350nm to 16nm. To accurately operate the heater and extend the heater’s operation lifetime for long-term reliability testing, we have also developed control methodologies for precise and reliable heater control.

Optimized Placement of Frost-Measuring Sensors in Heat Exchangers via Image Processing of Frost Formation Pattern.

Heat exchangers (HXs) play a critical role in maintaining human thermal comfort and ensuring product safety and quality in various industries. However, the formation of frost on HX surfaces during cooling operations can significantly impact their performance and energy efficiency. Traditional defrosting methods primarily rely on time-based control of heaters or HX operation, overlooking the actual frost formation pattern across the surface. This pattern is influenced by ambient air conditions (humidity and temperature) and surface temperature variations. To address this issue, frost formation sensors can be strategically placed within the HX. However, the non-uniform frost pattern poses challenges in sensor placement. This study proposes an optimized sensor placement approach using computer vision and image processing techniques to analyze the frost formation pattern. Through creating a frost formation map and evaluating various sensor locations, frost detection can be optimized to control defrosting operations with higher accuracy, thereby enhancing the thermal performance and energy efficiency of HXs. The results demonstrate the effectiveness of the proposed method in accurately detecting and monitoring frost formation, providing valuable insights for sensor placement optimization. This approach presents significant potential in enhancing the overall performance and sustainability of the operation of HXs.

Digital Twins of Induction Heating Processes in the Metallurgical Industry

Digitalization of induction heating systems in metallurgy passes the way from digital simulation of electromagnetic fields to the construction of digital twins. The main stages in the evolution of digital simulation, including computational experiments and the development of digital twins of induction heating systems, are considered. The main features in the development of digital twins have been identified. Efficient methods for computing electromagnetic fields in induction heating devices and principles for constructing multiphysical models, including the most important electrothermal models, have been developed. A package of dedicated computer programs for simulating not only induction heating devices, but also technologies involving the use of induction heating has been developed. A close relationship between optimal design and control of induction heaters is shown. Examples of building digital twins of various systems with the use of induction heating are given.

Demand–Response Control of Electric Storage Water Heaters Based on Dynamic Electricity Pricing and Comfort Optimization

Electric Storage Water Heaters (ESWH) are a widespread solution to supply domestic hot water (DHW) to dwellings and other applications. The working principle of these units makes them a great resource for peak shaving, which is particularly important due to the level of penetration renewable energies are achieving and their intermittent nature. Renewable energy deployment in the electricity market translates into large electricity price fluctuations throughout the day for individual users. The purpose of this study was to find a demand–response strategy for the activation of the heating element based on a multiobjective minimization of electricity cost and user discomfort, assuming a known DHW consumption profile. An experimentally validated numerical model was used to perform an evaluation of the potential savings with the demand–response optimized strategy compared to a thermostat-based approach. Results showed that cost savings of approximately 12% can be achieved on a yearly basis, while even improving user thermal comfort. Moreover, increasing the ESWH volume would allow (i) more aggressive demand–response strategies in terms of cost savings, and (ii) higher level of uncertainty in the DHW consumption profile, without detriment to discomfort.