• 대한전자공학회논문지SP
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• 제45권2호
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• pp.90-94
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• 2008

적응 필터의 입력 신호의 상관도 (correlation)가 클 경우 LMS 알고리즘의 수렴 속도는 상당히 느려지게 된다. 본 논문에서는 입력 신호의 상관도가 높은 상황에서 수렴 속도를 향상시킬 수 있는 적응 필터링 알고리즘을 제안한다. 입력 신호에 대하여 직교성을 가지도록 변환을 인위적으로 가하여 LMS 알고리즘의 한계를 극복한다. 제안한 알고리즘의 성능 향상은 시스템식별 모델을 통하여 그 수렴 속도의 개선을 확인하며 또한 시변 환경 하에서 적응 필터의 시변 추적 능력을 통해 보여 진다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2015년도 제46회 하계학술대회
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• pp.1427-1428
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• 2015

MEMS(Micro Electro-mechanical System) are getting attention as promising industry in the 21st century. Car air bags, acceleration sensors, and medical, information appliances are being actively applied in MEMS. This paper suggest the electrical electrodes of brain signal applied MEMS model and the prototype design for EEG signal amplification circuit. Also, we suggest an independent BCI(Brain Computer Interface) system with brain electrical signal of electrode models and wireless communication platform.

• 한국기계가공학회지
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• 제3권3호
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• pp.11-16
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• 2004

In this study, the characteristics of signals such as acoustic emission, vibration amplitude and noise level which are derived from the abnormal condition of compressor are investigated. The normal condition, vane stick sound and roller defect condition are chosen to analyze the signal in each cases. From the feature extraction of each signals, the dominant parameters of each signals which can identify the abnormal condition are suggested.

• 대한산업공학회지
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• 제26권4호
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• pp.315-324
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• 2000

This paper presents an efficient dynamic programming(DP) method, so called EDPAS (Efficient Dynamic Programming Algorithm for Signal), for optimally controlling traffic signal in real-time mode at a single intersection. The objective of EDPAS is to minimize total vehicle delay. It applies reaching method to solve forward DP functional equation, which does not need any priori knowledge on the states of DP network. Two acceleration techniques within reaching method are the main feature of EDPAS. They are devised to eliminate inferior DP states by comparing between states and maintaining incumbent value, resulting in a great amount of computational efficiency. An example is shown to verify the advantage of EDPAS.

• 반도체디스플레이기술학회지
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• 제18권2호
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• pp.87-91
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• 2019

In this paper, we have development of horizontal attitude monitoring system for agricultural robots. A two-axis gyro sensor and a two-axis accelerometer sensor are used to measure the horizontal attitude angle. The roll angle and pitch angle were measured through the fusion of the gyro sensor signal and the acceleration sensor signal for the horizontal attitude monitoring of the robot. This attitude monitoring system includes GPS and Bluetooth communication module for remote monitoring. The roll angle and pitch angle can be measured by the error of less than 1 degree and the linearity and the reproducibility of the output signal are excellent.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.2187-2191
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• 2003

In this paper, a x/y-axis accelerometer is fabricated, using the SBM process on a <111> SOI wafer. This fabrication method solves the problem of the footing phenomenon in the conventional SOI process for improved manufacturability and performance. The roughened lower parts as well as the loose silicon fragments due to the footing phenomenon are removed by the alkaline lateral etching step of the SBM process. The fabricated accelerometer has a demodulated signal-to-noise ratio of 92 dB, when 40Hz, 5 g input acceleration is applied. The noise equivalent input acceleration resolution and bandwidth are $125.59\;{\mu}g$ and over 100 Hz, respectively. The acceleration random walk is $12.5\;{\mu}g/\sqrt{Hz}$. The output linearity is measured to be 1.2 % FSO(Full Scale Output) at 40 Hz, and the input range is over ${\pm}\;10g$.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제15권3호
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• pp.216-220
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• 2009

본 연구에서는 손에 들고 있는 컨트롤러를 이용하여 사용자의 동작을 인식하는 방법을 제안한다. 컨트롤러에는 3축 가속도 센서가 부착되어 있어 사용자의 움직임에 따라 가속도 신호를 생성 이를 블루투스 통신을 이용하여 컴퓨터로 전달한 후 분석하여 사용자의 동작을 인식한다. 입력된 가속도 신호로부터 중력 가속도를 제거한 후 동작구간을 추출하여 이를 동작 모델에 적용 가장 높은 우도(likelihood)를 갖는 동작으로 인식한다. 각 동작 모델은 HMM을 이용하여 학습되며 성능 향상을 위한 가중치 보정과정과 인식 속도향상을 위한 방법을 포함한다. 제안된 방법을 3가지의 동작 집합에 적용하여 실용화가 가능한 정도의 높은 인식 결과를 얻었다.

• Smart Structures and Systems
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• 제17권6호
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• pp.903-915
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• 2016

The classical Kalman filter (KF) provides a practical and efficient state estimation approach for structural identification and vibration control. However, the classical KF approach is applicable only when external inputs are assumed known. Over the years, some approaches based on Kalman filter with unknown inputs (KF-UI) have been presented. However, these approaches based solely on acceleration measurements are inherently unstable which leads poor tracking and so-called drifts in the estimated unknown inputs and structural displacement in the presence of measurement noises. Either on-line regularization schemes or post signal processing is required to treat the drifts in the identification results, which prohibits the real-time identification of joint structural state and unknown inputs. In this paper, it is aimed to extend the classical KF approach to circumvent the above limitation for real time joint estimation of structural states and the unknown inputs. Based on the scheme of the classical KF, analytical recursive solutions of an improved Kalman filter with unknown excitations (KF-UI) are derived and presented. Moreover, data fusion of partially measured displacement and acceleration responses is used to prevent in real time the so-called drifts in the estimated structural state vector and unknown external inputs. The effectiveness and performance of the proposed approach are demonstrated by some numerical examples.

• 한국기계가공학회지
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• 제19권11호
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• pp.49-57
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• 2020

The forced vibration characteristics for two impulse forces with time lag was discussed in the vehicle dull progress model. Detailed numerical analyses of the time domain were performed systematically. By the two exciting impulse forces, the responses of displacement, the velocity, and the acceleration were investigated in detail for the vehicle's vibration. Notably, the forced vibration responses in the time domain can be used to identify and monitor several vehicle vibration models. In order to define the responses of displacement, the velocity, and the acceleration, we applied a numerical technique (i.e., the Runge-Kutta-Gill method[1,2]). These variables were subsequently used to analyze the vehicle's vibration according to the time lapse and while it passed over a bump stock; moreover, the characteristics of the variables were analyzed in detail according to their force conditions. Finally, the intrinsic characteristics of the forced vibration were discussed in the context of the automobile model. Overall, our results indicate that the tested method can be successfully applied under different damped conditions.

• 자동차안전학회지
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• 제13권1호
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• pp.14-25
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• 2021

This paper presents a RLS based adaptive sliding mode observer (A-SMO) for unknown fault reconstruction in longitudinal autonomous driving. Securing the functional safety of autonomous vehicles from unexpected faults of sensors is essential for avoidance of fatal accidents. Because the magnitude and type of the faults cannot be known exactly, the RLS based A-SMO for unknown acceleration fault reconstruction has been designed with relationship function in this study. It is assumed that longitudinal acceleration of preceding vehicle can be obtained by using the V2V (Vehicle to Vehicle) communication. The kinematic model that represents relative relation between subject and preceding vehicles has been used for fault reconstruction. In order to reconstruct fault signal in acceleration, the magnitude of the injection term has been adjusted by adaptation rule designed based on MIT rule. The proposed A-SMO in this study was developed in Matlab/Simulink environment. Performance evaluation has been conducted using the commercial software (CarMaker) with car-following scenario and evaluation results show that maximum reconstruction error ratios exist within range of ±10%.