• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.2
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• pp.310-316
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• 2003

One of the significant subject in the automatic arc welding is to establish control system of the welding parameters for controlling bead geometry as a criterion to evaluate the quality of arc welding. This paper proposes an inference algorithm for bead geometry in CMA Welding using Neuro-Fuzzy algorithm. The characteristic welding parameters are measured by the circuit composed of hall sensor, voltage divider tachometer, etc. and then the bead geometry of each weld pool is calculated and detected by an image processing with CCD camera and a measuring with microscope. The relationships between the characteristic welding parameters and the bead geometry have been arranged empirically. From the result of experiments, membership functions and fuzzy rules are tuned and determined by the learning of neural network, and then the relationship between actual bead geometry and inferred bead geometry are concluded by fuzzy logic controller. In the applied inference system of bead geometry using Neuro-Fuzzy algorithm, the inference error percent is within -5%∼+4% in case of bead width, -10%∼+10% in bead height, -5%∼+6% in bead area, -10%∼+10% in penetration. Use of the Neuro-Fuzzy algorithm allows the CMA Welding system to evaluate the quality in bead geometry in real time as the welding parameters change.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.3
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• pp.230-237
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• 2004

Lane Sensing techniques based on vision sensors are regarded promising because they require little infrastructure on the highway except clear lane markers. However, they require more intelligent processing algorithms in vehicles to generate the previewed roadway from the vision images. In this paper, a lane sensing algorithm using vision sensors is developed to improve the sensing robustness. The parallel stereo-camera is utilized to regenerate the 3-dimensional road geometry. The lane geometry models are derived such that their parameters represent the road curvature, lateral offset and heading angle, respectively. The parameters of the lane geometry models are estimated by the Kalman filter and utilized to reconstruct the lane geometry in the global coordinate. The inverse perspective mapping from the image plane to the global coordinate considers roll and pitch motions of a vehicle so that the mapping error is minimized during acceleration, braking or steering. The proposed sensing system has been built and implemented on a 1/10-scale model car.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1494-1499
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• 2003

Kinematic calibration is a process whereby the actual values of geometric parameters are estimated so as to minimize the error in absolute positioning. Measuring all components of Cartesian posture, particularly the orientation, can be difficult. With partial pose measurements, all parameters may not be identifiable. This paper proposes a new device that can be used to identify all kinematic parameters with partial pose measurements. Study is performed for a six degree-of-freedom fully parallel Hexa Slide manipulator. The device, however, is general and can be used for other parallel manipulators. The proposed device consists of a link with U joints on both sides and is equipped with a rotary sensor and a biaxial inclinometer. When attached between the base and the mobile platform, the device restricts the end-effector's motion to five degree-of-freedom and can measure position of the end-effector and one of its rotations. Numerical analyses of the identification Jacobian reveal that all parameters are identifiable. Computer simulations show that the identification is robust for the errors in the initial guess and the measurement noise.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.303-306
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• 2003

In radar tracking, since the sensor measures range, azimuth and elevation angle of a target, the measurement equation is nonlinear and the extended Kalman filter (EKF) is applied to nonlinear estimation. The conventional EKF has been widely used as a nonlinear filter for radar tracking, but the considerably large measurement error due to the linearization of nonlinear function in highly nonlinear situations may deteriorate the performance of the EKF To solve this problem, a fuzzy-model-based Kalman filter (FMBKF) is proposed for radar tracking. The FMBKF uses a local model approximation based on a TS fuzzy model instead of a Jacobian matrix to linearize nonlinear measurement equation. The hybrid GA and RLS method is used to identify the premise and the consequent parameters and the rule numbers of this TS fuzzy model. In two-dimensional radar tracking problem, the proposed method is compared with the conventional EKF.

• Journal of the Korea Convergence Society
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• v.6 no.5
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• pp.233-240
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• 2015

In this paper, we present an algorithm that estimates the speed of a moving object only using its sound information. In general, the speed gun projects the incident light onto a moving object and measures the frequency variation of the scattered light. Then the speed is measured by this frequency difference. In our study, instead of light information, we measure the speed by sound frequency difference when the object is coming and moving away. In our experiments on the speed measurement, on average the error of 6.08% was obtained. Utilizing this algorithm for smart device, we can measure the speed of a moving object without sensor that measures the frequency of the light.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.4
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• pp.89-97
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• 2014

As the digital control technologies in automotive industry have advanced, electronic control units(ECUs) play a key-role to improve system performance. Transmission control unit(TCU) is a shifting controller for automatic transmission of which major functions are to determine the shift and manage the shifting process considering the various sensor signal on transmission and driver's commands. As with any ECU in vehicle, TCU performs complex algorithms such as shift control, diagnostic and failsafe functions. However, firmware design analysis is hardly possible by the reverse engineering due to code protection. Transmission simulator is a hardware-in-the-loop simulator which enables TCU to work in normal mode by simulating the electrical signal of TCU interface. In this research, diagnosis and failsafe algorithm implemented on commercialized TCU is analyzed by using the transmission simulator that is developed for wheel loader construction vehicle. This paper gives various experimental results on the proportional solenoid current trajectories for different operating modes, error detection criterion and limphome mode gears for all the possible cases of clutch malfunction. The derived results for conventional TCU can be applied to the development of inherent TCU algorithms and the transmission simulator can also be utilized for the test of TCU to be developed.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.10
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• pp.968-974
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• 2006

We are moving into the era of ubiquitous computing. Ubiquitous Sensor Network (USN) is a base of such computing paradigm, where recognizing the identification and the position of objects is important. For the object identification, RFID tags are commonly used. For the object positioning, use of sensors such as laser and ultrasonic scanners is popular. Recently, there have been a few attempts to apply RFID technology in robot localization by replacing the sensors with RFID readers to achieve simpler and unified USN settings. However, RFID does not provide enough sensing accuracy for some USN applications such as robot navigation, mainly because of its inaccuracy in distance measurements. In this paper, we describe our approach on achieving accurate navigation using RFID. We solely rely on RFID mechanism for the localization by providing coordinate information through RFID tag installed floors. With the accurate positional information stored in the RFID tag, we complement coordinate errors accumulated during the wheel based robot navigation. We especially focus on how to distribute RFID tags (tag pattern) and how many to place (tag granularity) on the RFID tag-floor. To determine efficient tag granularities and tag patterns, we developed a simulation program. We define the error in navigation and use it to compare the effectiveness of the navigation. We analyze the simulation results to determine the efficient granularities and tag arrangement patterns that can improve the effectiveness of RFID navigation in general.

• Korean Journal of Remote Sensing
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• v.28 no.6
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• pp.611-622
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• 2012

This study proposed two multisensor fusion methods for segment-based image classification utilizing a region-growing segmentation. The proposed algorithms employ a Gaussian-PDF measure and an evidential measure respectively. In remote sensing application, segment-based approaches are used to extract more explicit information on spatial structure compared to pixel-based methods. Data from a single sensor may be insufficient to provide accurate description of a ground scene in image classification. Due to the redundant and complementary nature of multisensor data, a combination of information from multiple sensors can make reduce classification error rate. The Gaussian-PDF method defines a regional measure as the PDF average of pixels belonging to the region, and assigns a region into a class associated with the maximum of regional measure. The evidential fusion method uses two measures of plausibility and belief, which are derived from a mass function of the Beta distribution for the basic probability assignment of every hypothesis about region classes. The proposed methods were applied to the SPOT XS and ENVISAT data, which were acquired over Iksan area of of Korean peninsula. The experiment results showed that the segment-based method of evidential measure is greatly effective on improving the classification via multisensor fusion.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.3
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• pp.288-293
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• 2009

This study presents the active noise control of duct noise. The duct was excited by a steady-state harmonic and white noise force and the control was performed by one control speaker attached to surface of the duct. An adaptive controller based on filtered x LMS(FXLMS) algorithm was used and controller was defined by minimizing the square of the response of the error microphone. The assemble controller, which is called a hybrid ANC(active noise control) system, was combined with feedforward and feedback controller. The feedforward ANC attenuates primary noise that is correlated with the reference signal, while the feedback ANC cancels the narrowband components of the primary noise that are not observed by the reference sensor. Furthermore, in many ANC applications, the periodic components of noise are the most intense and the feedback ANC system has the effect of reducing the spectral peaks of the primary noise, thus easing the burden of the feedforward ANC filter.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.9
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• pp.66-73
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• 2002

Since cross-feed directional cutting force which is normal to machined surface directly influences the machined surface of the workpiece and total force loaded in cutter, it is necessary to estimate this force to control the roughness of the machined surface and total force in cutter. However, there have been difficulties in using the current existing in a stationary motor for cutting state prediction because of some unpredictable behavior of the current. Empirical approach was conducted to resolve the problem. As a result, we showed that the current and its unpredictable behavior are related to the infinitesimal rotation of the motor. Subsequently, the relationship between the current and the cutting force was identified with the error less than 50%. And, the estimation results of the two machine tools with different characteristics were compared to each other to confirm the validity of the presented estimation method and the characteristics of current of the stationary feed motor.