Jo Feb 7, 2025
PID control is a very effective control method for industry and more than 95% of controllers for process control are of PID type. It is well-known that the performance of a PID controller depends on the tuning of its parameters. For this reason, a lot of tuning methods have been proposed.
Among them, predictive functional control (PFC) has appeared as a better choice to solve different problems. If the control objective is to improve the behavior of low-order processes, PFC is a good choice because of the simplicity of both algorithm calculation and tuning and its easy implementation and capability of constraints handling. In addition, PFC has many advantages over PID control. First, it can control time delay processes and constrain both the manipulated and controlled variables. Second, the tuning parameters have physical meaning, which is helpful for applying algorithms to practice. Therefore, if PID control and PFC are combined, better control performance can be achieved. In many papers, various design methods of PID controllers based on predictive functional control optimization are proposed. But these papers are focused on SISO systems and they do not cover MIMO systems.
Based on the principle of decoupling control, Kang Chung Hyok, a researcher at the Faculty of Metal Engineering, has proposed a new design method of PID controllers by PFC optimization for MIMO systems with time delay.
First, after decoupling, he divided the complex MIMO systems with time delay into independent subsystems. Then, he designed a PID controller based on PFC optimization after simplifying the subsystems into FOPDT models. The proposed controller not only inherits the advantages of PFC, but also has the same structure as a PID controller.
The simulation results show that the proposed controller has more improved control performance and better robustness than traditional PID controllers under the conditions of time delay and model/plant mismatches, and that the actuator’s life can be lengthened as the manipulated variable has no oscillating characteristics. In summary, the proposed controller can meet the requirements of complex industrial processes.
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Jo Feb 6, 2025
Today, the energy demand of mankind is growing with each passing day, and the need for construction and operational stability of all power plants including thermal power plants is increasing. Therefore, many non-destructive testing (NDT) methods have been developed and used in safety analysis of power plants worldwide. X-ray inspection, ultrasonic inspection and magnetic particle inspection are typical ones. But these methods do not provide a guarantee for the safety of structures since they are not suitable for regular full-scale inspection of various structures in the industrial sector due to their high cost of inspection, artificial magnetization process of objects to be tested, complex operating conditions and high time consumption.
Recently, metal magnetic memory (MMM) method is widely used in the world for its cost-effectiveness, easy operation, time saving and high sensitivity. In particular, MMM method has two advantages. First, fatigue failure occurring in stress concentration zones (SCZ) can be diagnosed and prevented. Second, the inspection device is effective for regular whole inspection of different structures like power plants for its simplicity and high inspection speed.
Based on the metal magnetic memory test principle and the data on the sensor type, Ryu Yong Chol, a researcher at the General Assay Office, has selected sensor material for weak magnetostatic field measurement and made an SCZ inspector.
First, he determined the optimum excitation method for highest sensitivity, the influences of various factors on the characteristics of the sensor and the method of measuring the leakage magnetic field. Then, he conducted a tensile test and inspection on different specimens to verify its reliability.
The results show that MMM device enables fast inspection of ferromagnetic structures and diagnostics and prevention of fatigue failure in SCZ, which is impossible with other non-destructive testing methods.
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Jo Feb 4, 2025
Nowadays NdFeB magnets are widely used in many applications such as electric two-wheelers, air conditioners, hybrid and electric cars, MRI scanners, wind generators, HDD, acoustic transducers, magnetic separators, etc. Thus, the global demand for NdFeB magnets is expected to continuously increase in the near future.
However, the supply of rare earth elements including neodymium, praseodymium and dysprosium for NdFeB magnets does not meet this growing demand, so rare earth elements are regarded as critical elements. Despite their criticality, less than 1% of rare earths are being recycled from end-of-life rare earth permanent magnets. Moreover, during the manufacturing process of NdFeB magnets, approximately 20~30% of rare earth alloy are lost and stockpiled as industrial waste. Therefore, development of an efficient recycling process for separation and recovery of rare earths from end-of-life products and magnet waste is an important issue.
Rare earth double sulfate precipitation is a traditional method for separation of rare earths from non-rare earths, which has advantages such as simple operation, low reagent cost, easy filtration of rare earth precipitates, high recovery of rare earths, etc. However, recovery of rare earths from NdFeB magnet waste by the rare earth double sulfate precipitation has not been reported.
Kim Sok Chol, a section head at the Faculty of Chemical Engineering, has succeeded in applying the rare earth double sulfate precipitation to the separation and recovery of rare earths from the solution obtained by leaching NdFeB magnet waste with sulfuric acid on a laboratory scale. He has also conducted a pilot plant test in order to investigate and optimize the various steps of the whole process for its application on an industrial scale.
The process includes leaching of NdFeB magnet waste by sulfuric acid, precipitation of rare earths in the form of double sulfate by sodium chloride, and conversion of rare earth double sulfates into hydroxides.
The yields of neodymium and dysprosium in the whole process were 92.3% and 90.8%, respectively. In the final rare earth hydroxides, the total rare earth oxides (TREO) content was 79.8%, where the contents of neodymium and dysprosium were 94.2% and 5.8%, respectively.
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Jo Feb 3, 2025
Selection of the optimal plan for maintaining the roadway affected by mining operations, when mining coal seams in weak rock formations with complex conditions of occurrence, has been studied a lot over the past decades, which has brought about many successes.
The optimal design of roadway maintenance plan requires a precise understanding of the mechanical properties of the surrounding rock mass, the interaction between the rock mass and the installed support system, and the stress distribution induced around the mining face and around the tunnel. Hence, researchers have been trying to solve the roadway maintenance problem by empirical methods such as mechanical, statistical and visual methods and numerical simulation analysis.
Empirical methods, where the complex mechanical interaction between rock mass and roof support is represented by simple equations, are supported by a large database, but they generally neglect the stress distribution generated by mining, the geological relationships of roof support management systems, and the interaction between the support system and the rock mass. On the other hand, numerical simulation analysis, which is dependent on the subjective experience of humans, cannot reflect well the nonlinear relationship between the factors affecting the stability of workings, and thus, it is not reliable for stability determination.
To solve this problem, researchers have used GA and ANN or their combination to establish nonlinear relationships, predict the displacement of the roadway influenced by the roadway depth, principal stress, drilling method, and rock load, and determine the displacement of the rock mass around roadway and the geological parameters for mining. This intelligent analysis method is very effective for its objectivity when evaluating the stability of roadways in a region of relatively regular coal seams. However, when the coal seams are in an irregular state and the roadway is strongly affected by mining operation, the nonlinear relationships between the factors should be taken into account for stability determination.
Pak Tae Song, a section head at the Faculty of Mining Engineering, has found the optimal maintenance scheme of roadways strongly affected by mining operation for nonlinear problems by combining ANN with high adaptive capacity and GA with strong adaptive optimization ability.
He applied a two-stage ANN-GA. First, he obtained the installation space and failure rate of the support from the combination of ANN and GA in the second stage. Then, he found the optimal roadway maintenance scheme from the combination of ANN and GA in the first stage.
After that, he compared the selected scheme with field observations. The results show that the scheme is effective in optimizing the maintenance system of workings, which is affected by the nonlinear relationship among mining geological parameters.
The ANN-GA method can be effectively applied to the study of the geo-mechanical behavior of rock mass affected by the uncertainty relations of qualitative and quantitative factors caused by mining operations.
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Jo Jan 31, 2025
Image super-resolution (SR) is the process of artificially producing a high-resolution (HR) image from one or several low-resolution (LR) images. Image super-resolution techniques are based on interpolation, reconstruction and learning.
In recent times, learning-based super-resolution algorithms are widely used. In learning-based super-resolution algorithms, HR image is obtained from a single LR image using training database. In these algorithms, the priori information is derived from the training database.
Ro Mi Ha, a lecturer at the Faculty of Information Science and Technology, has proposed a learning-based image super-resolution for a single LR image using discrete wavelet transform (DWT) and Gaussian mixture model (GMM).
In this method, if a low resolution (LR) input image and a database consisting of low and high resolution images are given, a high-resolution image for the input image is obtained by learning of the high-frequency details from the database. Then, high-frequency details of an HR image are described as wavelet coefficients at finer scale using DWT. The conversion function for obtaining the finer wavelet coefficients of an HR image from the coarse wavelet coefficients of an LR image is set as a weighted linear transformation using GMM.
She has demonstrated the effectiveness of the proposed method by conducting some experiments on gray images.
The proposed method can be used in applications such as remote surveillance where the memory, the transmission bandwidth and the camera performance are the main constraints.
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Jo Jan 30, 2025
The electrode support arm is the key component of an electric furnace, which supports the electrode, conducts electrical energy from the transformer through the electrode to the furnace, and produces a strong arc current within the furnace material to raise the temperature of the weld pool. The electrode support arm is usually mounted on the brace, and its front end holds the electrode by the gripper to keep it in position at the electrode center circle during the lift process.
During the operation, a high-temperature arc with a large power output is formed between the extremes of electrodes and the weld pool, which can cause intense electromagnetic oscillation of the electrode support arm. Therefore, the electrode support arm should have great strength and low resistance value. In modern electric furnaces, the secondary bus on the furnace body is retrofitted from the former copper tube bus to the copper-steel conductive electrode arm and aluminum conductive arm. To manufacture the copper-steel conductive electrode arm of a 5-ton ultrahigh power (UHP) electric furnace, a copper plate is welded around the steel structure and a cooling water pipe with a rectangular cross-section is formed on its bottom surface to cool the heat generated when the high current flows through the copper plate.
So far, many studies have been published on the cooling systems in the furnace body and furnace ceiling, but no mention has been made on the cooling in the electrode support arm section. The reason lies in the fact that Joule heat generated in the conductive arm is too small and only recently has the bimetallic conductive arm been widely used. However, during the reducing operation of the electric furnace, the temperature of the furnace should be raised to the maximum, so the operation is carried out without ventilation. Therefore, the convective heat transfer by this flue gas must be considered because the gas ambient temperature around the electrode support arm increases to about 700K.
Ri Sim Hyok, a researcher at the Faculty of Metal Engineering, has analyzed the temperature distribution of the copper-steel conductive electrode arm of UHP electric furnace, determined the geometry of the cooling water pipeline to minimize the cooling water consumption, while keeping the temperature of the conductive copper plate within the acceptable range (50℃), and determined the consumption amount of cooling water.
He analyzed the current flow in the bimetallic conductive arm using Maxwell software and found that the current flows only into the copper plate. Then, he simulated the temperature distribution of the bimetallic conductive arm during the reducing stroke with ANSYS FLUENT. After that, he simulated the temperature changes of the conductive copper plate and the cooling water, and verified the results with the experimental data obtained in situ.
The results show that the cooling water flow rate of 1 to 1.5kg/s and the 6-stroke pipeline guarantee the minimum consumption of cooling water while keeping the temperature of the copper plate bus of the copper-steel conductive electrode arm within the acceptable range.
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