• Transactions of the Korean Society of Mechanical Engineers
• /
• v.18 no.8
• /
• pp.1939-1951
• /
• 1994

This study introduces a new tool breakage detecting technology comprised of an unsupervised neural network combined with adaptive time series autoregressive(AR) model where parameters are estimated recursively at each sampling instant using a parameter adaptation algorithm based on an RLS(Recursive Least Square). Experiment indicates that AR parameters are good features for tool breakage, therefore it can be detected by tracking the evolution of the AR parameters during milling process. an ART 2(Adaptive Resonance Theory 2) neural network is used for clustering of tool states using these parameters and the network is capable of self organizing without supervised learning. This system operates successfully under the wide range of cutting conditions without a priori knowledge of the process, with fast monitoring time.

• Journal of the Korean Society for Precision Engineering
• /
• v.21 no.12
• /
• pp.84-91
• /
• 2004

A CCD camera with a laser stripe was applied to realize the automatic weld seam tracking in GMAW. It takes relatively long time to process image on-line control using the basic Hough transformation, but it has a tendency of robustness over the noises such as spatter and arc tight. For this reason, it was complemented with adaptive Hough transformation to have an on-line processing ability for scanning specific weld points. The adaptive Hough transformation was used to extract laser stripes and to obtain specific weld points. The 3-dimensional information obtained from the vision system made it possible to generate the weld torch path and to obtain the information such as width and depth of weld line. In this study, a neural network based on the generalized delta rule algorithm was adapted for the process control of GMA, such as welding speed, arc voltage and wire feeding speed.

• Journal of Korean Society for Quality Management
• /
• v.26 no.4
• /
• pp.143-150
• /
• 1998

We propose an adaptive monitoring a, pp.oach for serially correlated data. This algorithm uses the adaptive linear prediction lattice filter (ALPLF) which makes it compute process parameters in real time and recursively update their estimates. It involves computation of the forward and backward prediction errors. CUSUM control charts are a, pp.ied to prediction errors simulaneously in both directions as an omnibus method for detecting changes in process parameters. Results of computer simulations demonstrate that the proposed adaptive monitoring a, pp.oach has great potentials for real-time industrial a, pp.ications, which vary frequently in their control environment.

• Journal of Korean Society for Quality Management
• /
• v.24 no.1
• /
• pp.73-86
• /
• 1996

Adaptive EWMA(Exponentially Weighted Moving Average)-x control chart using the Kalman gain recursive average is designed. The designed control chart is effective to on-line process monitoring as continuous flow processes. Performance evaluation between the designed control chart and traditional one is implemented. For this, ARL(Average Run Length) is adopted as a criterion. Results show that the designed adaptive EWMA-x control chart has shorter ARL than EWMA-x control chart when process mean is shifted. This model can be extended to process prevention control. The methodology proposed in this research is turned out to show the high performance than that of the given methodologies.

• Proceedings of the Korea Society for Simulation Conference
• /
• 2002.05a
• /
• pp.169-173
• /
• 2002

반도체 공정은 복잡하고 다양한 물리, 화학작용을 수반하며, 폭넓은 데이터 발생 및 관리에도 불구하고 공정진행시 내부 특성의 복잡함 때문에 효율적인 모델링이 어려웠다. 또한 원하는 출력을 얻기 위한 제어입력의 선정도 용이하지 않으므로 현재의 최적공정운영은 전문가의 경험에 의존하여 많은 시행 착오를 거쳐 수행되고 있다. 본 논문에서는 반도체 공정의 최적운영을 위해 다음 세 단계로 나누어 연구를 수행하였다. 첫째, 반도체 공정을 설비를 기반으로 컬러드 페트리 넷을 이용하여 모델링하고 둘째, Run-to-Run control에 기반한 최적공정운영 관리모델을 실험하고 셋째, 지식기반 데이터베이스를 기반으로 하는 지능적인 적응형 공정관리모델(Adaptive Process Control model)의 프레임 웍을 제안한다.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.506-509
• /
• 2005

An adaptive ${\alpha}-{\beta}$ tracker is proposed for tracking maneuvering targets with a track-while-scan radar system. The tracker gain is updated on-line corresponding to the adjusted process noise variance which is obtained via time averaging of the process over a sliding window. The adjusted process noise variance is used to compute the maneuverability index for the tracker gain based on the steady-state Kalman filter equation for each epoch. It is shown via simulation that the proposed approach provides robust and accurate position estimates during the target maneuver while the performance of the conventional ${\alpha}-{\beta}$ tracker is shown much degraded.

• Journal of Drive and Control
• /
• v.9 no.3
• /
• pp.1-7
• /
• 2012

This paper deals with the issue of model reference adaptive control strategy to control the injection molding machine. Prior to controller design, a pair of transfer functions are derived for the injection and dwelling process based on mathematical models of components. As external disturbances to examine the robustness of the proposed controller, nozzle clogging and contraction of molded objects are considered and realized by proportional valve. The overall simulation system, consisting of hydraulic components, controller and sensors, is implemented using the components of commercial software SimulationX. The simulation results confirm the proposed scheme's efficiency and robustness.

• Journal of Satellite, Information and Communications
• /
• v.6 no.1
• /
• pp.12-18
• /
• 2011

Signal fading due to rain is one of the most significant factors degrading link quality in satellite communication systems. Adaptive transmission is considered to be the most efficient means to countermeasure the rain attenuation. In order to develop and design a good adaptive transmission system, we need a dynamic rain attenuation model which can synthesize time series of rain attenuation. In this paper, we present a modeling technique for dynamic rain attenuation using a Markov process. We derive statistical fading properties of the rain attenuation data measured in second time interval and define four states in the Markov process. We synthesize the rain attenuation data using the 4-state Markov process, and compare statistical properties of the simulated data to those of the measured data.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.720-723
• /
• 2005

Ship motion is a complex controlled process with several hydrodynamic parameters that vary in wide ranges with respect to ship load condition, speed and surrounding conditions (such as wind, current, tide, etc.). Therefore, to effectively control ships in a designed track is always an important task for ship masters. This paper presents an effective adaptive autopilot ships that ensure the optimal accuracy, economy and stability characteristics. The PID control methodology is modified and parameters of a PID controller is designed to satisfy conditions for an optimal objective function that comprised by heading error, resistance and drift during changing course, and loss of surge velocity or fuel consumption. Designing of the controller for course changing process is based on the Model Reference Adaptive System (MRAS) control theory, while as designing of the automatic course keeping process is based on the Self Tuning Regulator (STR) control theory. Simulation (using MATLAB software) in various disturbance conditions shows that in comparison with conventional PID autopilots, the designed autopilot has several notable advantages: higher course turning speed, lower swing of ship bow even in strong waves and winds, high accuracy of course keeping, shorter time of rudder actions smaller times of changing rudder direction.

• Journal of Sensor Science and Technology
• /
• v.6 no.2
• /
• pp.123-130
• /
• 1997

In this paper, we present an original stereo vision system which comprises two process: 1. An image segmentation algorithm based on new concept called declivity and using automatic thresholds. 2. A new stereo matching algorithm based on an optimal path search. This path is obtained by dynamic programming method which uses the threshold values calculated during the segmentation process. At present, a complete depth map of indoor scene only needs about 3 s on a Sun workstation IPX, and this time will be reduced to a few tenth of second on a specialised architecture based on several DSPs which is currently under consideration.