• Transactions on Control, Automation and Systems Engineering
• /
• v.2 no.1
• /
• pp.40-46
• /
• 2000

In this paper, a transient identification based on a Hidden Markov Model (HMM) has been suggested and evaluated experimentally for the classification of transients in the dynamic process. The transient can be identified by its unique time dependent patterns related to the principal variables. The HMM, a double stochastic process, can be applied to transient identification which is a spatial and temporal classification problem under a statistical pattern recognition framework. The HMM is created for each transient from a set of training data by the maximum-likelihood estimation method. The transient identification is determined by calculating which model has the highest probability for the given test data. Several experimental tests have been performed with normalization methods, clustering algorithms, and a number of states in HMM. Several experimental tests have been performed including superimposing random noise, adding systematic error, and untrained transients. The proposed real-time transient identification system has many advantages, however, there are still a lot of problems that should be solved to apply to a real dynamic process. Further efforts are being made to improve the system performance and robustness to demonstrate reliability and accuracy to the required level.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.1953-1957
• /
• 2004

The machine vision has been applied to a number of industrial applications for quality control and automations to improve the manufacturing processes. In this paper, the automation system using the machine vision is developed, which is applicable to the marking process in a steel production process line. The working environment is very harsh to workers so that the automatic system in the steel industry is required increasingly. The developed automatic marking system consists of several mechanical and electrical elements such as the laser position detecting sensor system for a structured laser beam which is projected to the billet in order to detect the geometry of the billet. An image processing algorithm has been developed to percept the two center positions of a camera and a billet, respectively, and to align two centers. A series of experiments has been conducted to investigate the performance of the proposed algorithm. The results show that two centers of the camera and the billet could be detected very well and differences between two center positions could be also decreased via the proposed tracking algorithm.

• Transactions on Control, Automation and Systems Engineering
• /
• v.4 no.2
• /
• pp.109-113
• /
• 2002

Van de Vusse reactor is known as a highly nonlinear chemical process and has been considered by a number of researchers as a benchmark problem for nonlinear chemical process. Various identification methods for nonlinear system are also verified by applying these methods to Van de Vusse reactor. From the point of view of identification, only the Volterra kernel of second order has been obtained until now. In this paper, the authors show that Volterra kernels of nonlinear Van de Vusse reactor of up to 3rd order are obtained by use of M-sequence correlation method. A pseudo-random M-sequence is applied to Van de Vusse reactor as an input and its output is measured. Taking the crosscorrelation function between the input and the output, we obtain up to 3rd order Volterra kernels, which is the highest order Volterra kernel obtained until now for Van de Vusse reactor. Computer simulations show that when Van de Vusse chemical process is identified by use of up to 3rd order Volterra kernels, a good agreement is observed between the calculated output and the actual output.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.310-313
• /
• 1996

In this paper, a neural control algorithm is proposed on the automation of adjustment process. The adjustment processes in camcoder production line are modelled, and the processes are adjusted automatically by means of off-line supervisory trained multi-layer neural network. We have made many experiments on the several adjustment processes by using the control algorithm. There are many unexpected troubles to achieve the desirable adjust time in the practical application. To overcome those, some auxiliary algorithms are demanded. As a result, our proposed algorithm has some advantages - simple architecture, easy extraction of the training data without expertises, adaptability to the varying systems, and wide application for the other resemble processes.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.179.3-179
• /
• 2001

This paper describes the dual system technology of PC based control system at steel plant. Because PC is developed to be used in wide area such as Office Automation, Personal, It is cheaper and more portable than the present process control system, but is less stable and less reliable. In this research, We gathered the fault example of a general process control system and steel process control system, analyzed the cause of fault and decided the target fault that took over in our proposed system. The proposed PC based system is the dual system that has a shared RAID system connected by SCSI bus between two systems. In order to assist system reliability, we proposed watchdog manager to monitor ...

• Transactions on Control, Automation and Systems Engineering
• /
• v.1 no.1
• /
• pp.75-86
• /
• 1999

An air-data estimator for generic air-breathing hypersonic vehicles (AHSVs) is developed and demonstrated with an example vehicle configuration. The AHSV air-data estimation strategy emphasized improvement of the angle of attack estimate accuracy to a degree necessitated by the stringent operational requirements of the air-breathing propulsion. the resulting estimation problem involves highly nonlinear diffusion process (propagation); consequently, significant distortion of a posteriori conditional density is suspected. A simulation based statistical analysis tool is developed to characterize the nonlinear diffusion process. The statistical analysis results indicate that the diffusion process preserves the symmetry and unimodality of initial probability density shape state variables, and provide the basis for applicability of an Extended Kalman Filter (EKF). An EKF is designed for the AHSV air-data system and the air data estimation capabilities are demonstrated.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10a
• /
• pp.1144-1148
• /
• 1991

The problems occurred when developing a automatic wheel deburring system are to make effective flexibility in model change and the irregularity of the position/shape of the burr, to select optimal robotic manufacturing process and to develope optimal end effector. The locations where burr exists are on flange, rim and spoke. Here will be discussed the optimal solution for the removal of rim burr by using robot. The research can be summarized as the automatic robot path generation by recognizing rim contour and automatic deburring process technique. Various rim contour data is generated automatically when the sensor which is fixed to robot is moving with the parallel motion to the wheel center axis and this generated data is transferred to the data storage system and converted to the robot path data. The robotic tool system which is suitable to the rim deburring process is developed by integrating tool, compliance function and sensor. And factory automation system controlled by robot controller and PC is developed. This system shows good productivity and flexibility.

• Journal of Institute of Control, Robotics and Systems
• /
• v.21 no.5
• /
• pp.427-433
• /
• 2015

Hot forging industry workers are prone to encounter several health risks due to lack of automation and poor working environment conditions. These workers particularly suffer from muscle fatigue owing to the constant handling of heavy products during the forging process. Thus we developed an assistant robot for workers who carry out hot forging tasks. The purpose of a robot is to compensate gravity-loads for heavy products. To verify the functionality of a robot, we performed a muscle fatigue analysis using Electromyography (EMG) signals. Four muscles of the upper extremity were chosen to measure muscle activity. And experiment conditions were setup to imitate the hot forging process. Post experimental analysis of the captured muscle activity revealed a reduction in the median frequency of the EMG signals, which means clear fatigue reduction due to a robot's assistance. The developed assist robot with compact and economical components can be efficiently utilized at forging work sites to create better working conditions for operators.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10b
• /
• pp.1639-1645
• /
• 1991

Because of the important role LD converters play in the production of high quality steel, various dynamic models have been attempted in the past by many researchers not only to understand the complex chemical reactions that take place in the converter process but also to assist the converter operation itself using computers. And yet no single dynamic model was found to be completely satisfactory because of the complexity involved with the process. The process indeed involves dynamic energy and mass balances at high temperatures accompanied by complex chemical reactions and transport phenomena in the molten state. In the present study, a mathematical model describing the dynamic behavior of LD converter process has been developed. The dynamic model describes the time behavior of the temperature and the concentrations of chemical species in the hot metal bath and slag. The analysis was greatly facilitated by dividing the entire process into three zones according to the physical boundaries and reaction mechanisms. These three zones were hot metal (zone 1), slag (zone 2) and emulsion (zone 3) zones. The removal rate of Si, C, Mn and P and the rate of Fe oxidation in the hot metal bath, and the change of composition in the slag were obtained as functions of time, operating conditions and kinetic parameters. The temperature behavior in the metal bath and the slag was also obtained by considering the heat transfer between the mixing and the slag zones and the heat generated from chemical reactions involving oxygen blowing. To identify the unknown parameters in the equations and simulate the dynamic model, Hooke and Jeeves parttern search and Runge-Kutta integration algorithm were used. By testing and fitting the model with the data obtained from the operation of POSCO #2 steelmaking plant, the dynamic model was able to predict the characteristics of the main components in the LD converter. It was possible to predict the optimum CO gas recovery by computer simulation

• Journal of Digital Convergence
• /
• v.19 no.7
• /
• pp.129-138
• /
• 2021

Many organizations are applying robotic process automation (RPA) to automate repetitive and rule based tasks to enhance the accuracy and efficiency of works. Some members are willing to join the projects hoping to eliminate annoying and meaningless tasks, but others are resisting this innovation fearing that they may lose their jobs. In this study, both positive and negative antecedents are posited to influence the performance in adopting RPA. The effects of relative advantage, compatibility, change management effect, innovation resistance and satisfaction, conclusively to performance improvement were examined via a survey of 109 employees involved in the 11 RPA projects in a manufacturing company, and the structural equation model analysis. The research considering the consumer characteristics of the innovation resistance model can be followed for the development of individualized change management strategy.