• 한국분무공학회지
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• 제18권3호
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• pp.132-139
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• 2013

Smoke emissions from light duty diesel vehicles were measured using light extinction method with the free acceleration test mode. The smoke emissions for each measurement cycle of the free acceleration method showed large variations according to driver's pedal pushing pattern. The smoke values for each measurement cycle initially increased and reach a peak value. Integration of the smoke emissions with time for each measurement cycle was performed to get a representative smoke value which was obtained by averaging the integrated results. Two kinds of integration time range were used. One is range over the whole measurement cycle of the free acceleration method. The other is only the acceleration range in the measurement cycle. Overall, variation of the representative smoke values obtained by the integration method was reduced comparing to the traditional representative smoke value which was obtained from a peak smoke value over the measurement cycle. Ten vehicles of the same model with 2.5 liter diesel engines, and seven vehicles of the same model with 2.7 liter diesel engines, were tested using the free acceleration test method.

• 전기학회논문지
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• 제60권12호
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• pp.2346-2351
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• 2011

This paper presents the intelligent external noise analysis method for nonlinear maneuvering target. After recognizing maneuvering pattern of the target by the proposed method, we track the state of the target. The external noise can be divided into mere noise and acceleration using only the measurement. divided noise passes through the filtering step and acceleration is punched into dynamic model to compensate expected states. The acceleration is the most deterministic factor to the maneuvering. By dividing, approximating, and compensating the acceleration, we can reduce the tracking error effectively. We use the fuzzy c-means (FCM) clustering as the method to divide external noise. FCM can separate the acceleration from the noise without criteria. It makes the criteria with the data made by measurement at every sampling time. So it can show the adaptive tracking result. The proposed method proceeds the tracking target simultaneously with the learning process. Thus it can apply to the online system. The proposed method shows the remarkable tracking result on the linear and nonlinear maneuvering. Finally, some examples are provided to show the feasibility of the proposed algorithm.

• 한국음향학회:학술대회논문집
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• 한국음향학회 1994년도 FIFTH WESTERN PACIFIC REGIONAL ACOUSTICS CONFERENCE SEOUL KOREA
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• pp.796-801
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• 1994

Measuring noise, sound quality or acoustical comfort presents a difficult task for the acoustic engineer. Sound and noise are ultimately jugded by human beings acting as analysers. Regulations for determining noise levels are based on A-weighted SPL measurement performed with only one microphone. This method of measurement is usually specified when determining whether the ear can be physically damaged. Such a simple measurement procedure is not able to determine annoyance of sound events or sound quality in general. For some years investigations with binaural measurement analysis technique have shown new possibilities for the objective determination of sound quality. By using Artificial Head technology /1/, /2/ in conjunction with psychoacoustic evaluation algorithms - and taking into account binaural signal processing of human hearing, considerable progress regarding the analysis of sounds has been made. Because sound events often arise in a complex way, direct conclusions about components subjectively judged to be annoying with regard to their causes and transmission paths, can be drawn in a limited way only. A new procedure, complementing binaural measurement technology combined with mulit-channel measuements of acceleration sensor signals has been developed. This involves correlating signals influencing sound quality, analyzed by means of human hearing, with signals form different acceleration sensors fixed at different positions of the sound source. Now it is possible to recognize the source and the transmission way of those signals which have an influence on the annoyance of sound.

• Smart Structures and Systems
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• 제15권2호
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• pp.489-503
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• 2015

Response estimation at unmeasured locations using the limited number of measurements is an attractive topic in the field of structural health monitoring (SHM). Because of increasing complexity and size of civil engineering structures, measuring all structural responses from the entire body is intractable for the SHM purpose; the response estimation can be an effective and practical alternative. This paper investigates a response estimation technique based on the Kalman state estimator to combine multi-sensor data under non-zero mean input excitations. The Kalman state estimator, constructed based on the finite element (FE) model of a structure, can efficiently fuse different types of data of acceleration, strain, and tilt responses, minimizing the intrinsic measurement noise. This study focuses on the effects of (a) FE model error and (b) combinations of multi-sensor data on the estimation accuracy in the case of non-zero mean input excitations. The FE model error is purposefully introduced for more realistic performance evaluation of the response estimation using the Kalman state estimator. In addition, four types of measurement combinations are explored in the response estimation: strain only, acceleration only, acceleration and strain, and acceleration and tilt. The performance of the response estimation approach is verified by numerical and experimental tests on a simply-supported beam, showing that it can successfully estimate strain responses at unmeasured locations with the highest performance in the combination of acceleration and tilt.

• Smart Structures and Systems
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• 제6권9호
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• pp.1025-1039
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• 2010

Measuring displacement response for civil structures is very important for assessing their performance, safety and integrity. Recently, video-based techniques that utilize low-cost high-resolution digital cameras have been developed for such an application. These techniques however have relatively low sampling frequency and the results are usually contaminated with noises. In this study, an integrated visual-inertial measurement method that combines a monocular videogrammetric displacement measurement technique and a collocated accelerometer is proposed for displacement and velocity measurement of civil engineering structures. The monocular videogrammetric technique extracts three-dimensional translation and rotation of a planar target from an image sequence recorded by one camera. The obtained displacement is then fused with acceleration measured from a collocated accelerometer using a multi-rate Kalman filter with smoothing technique. This data fusion not only can improve the accuracy and the frequency bandwidth of displacement measurement but also provide estimate for velocity. The proposed measurement technique is illustrated by a shake table test and a pedestrian bridge test. Results show that the fusion of displacement and acceleration can mitigate their respective limitations and produce more accurate displacement and velocity responses with a broader frequency bandwidth.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2010년도 춘계학술대회 논문집
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• pp.989-995
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• 2010

This paper is focused on a simplified measurement of rail irregularity by some axle-box accelerometers for high-speed rail condition monitoring with in-service high-speed trains. Generally, the rail condition monitoring has been done by a special railway inspection vehicle with a 10m versine method. But, the monitoring method needs some expensive measurement system, and have been performed only at night due to its speed limit. In this research, a simplified measurement of rail irregularity using axle-box accelerometers is proposed to monitor the rail condition with in-service high-speed trains. The acceleration is measured by using two accelerometers on a axle-box, and stored in an on-board data acquisition system. The displacement is estimated from the acceleration data by a combination of Kalman filter and the frequency selective filter. The estimated results are compared with the measurement from a laser rail inspection system which is near the axle-box. From the comparison, the proposed method shows promise as a tool for the simplified measurement of rail irregularity at high-speed.

• Smart Structures and Systems
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• 제18권3호
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• pp.375-387
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• 2016

The classical Kalman filter (KF) can provide effective state estimation for structural identification and vibration control, but it is applicable only when external inputs are measured. So far, some studies of Kalman filter with unknown inputs (KF-UI) have been proposed. However, previous KF-UI approaches based solely on acceleration measurements are inherently unstable which leads to poor tracking and fictitious drifts in the identified structural displacements and unknown inputs in the presence of measurement noises. Moreover, it is necessary to have the measurements of acceleration responses at the locations where unknown inputs applied, i.e., with collocated acceleration measurements in these approaches. In this paper, it aims to extend the classical KF approach to circumvent the above limitations for general real time estimation of structural state and unknown inputs without using collocated acceleration measurements. Based on the scheme of the classical KF, an improved Kalman filter with unknown excitations (KF-UI) and without collocated acceleration measurements is derived. Then, data fusion of acceleration and displacement or strain measurements is used to prevent the drifts in the identified structural state and unknown inputs in real time. Such algorithm is not available in the literature. Some numerical examples are used to demonstrate the effectiveness of the proposed approach.

• 한국자동차공학회논문집
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• 제13권4호
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• pp.58-65
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• 2005

A method measuring angular speed and estimating angular acceleration of an automotive wind shield wiper pivot with limited resources has been proposed. Limited resources refer to the fact that processes cannot be operated in real-time with a regular notebook running a Microsoft Windows. Also, they refer to the fact that data acquisition cards have only two general purpose counters as many generic cards do. An optical incremental encoder has been employed for measuring angular motion. To measure the angular speed of the pivot, periods for the encoder's output pulses have been measured as the speed is related to the reciprocal of the period. Since only information acquired from one counter channel is the magnitude of the angular speed, sign correction is necessary. Also the information for the exact time when a pivot passes left and right dead points is also missing and the situation is inherent to the hardware setup. To find out the zero-crossing time of the angular speed, a linear interpolation technique has been employed. Lastly, to overcome the imperfection of the mechanical encoders, the angular speed has been curve fitted to a spline. Angular acceleration can be obtained by a differentiation of the angular speed.

• 한국ITS학회 논문지
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• 제23권1호
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• pp.82-96
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• 2024

교통류에서는 거시적인 지표로 속도, 교통량, 밀도가 중요한 파라미터로 활용되고 있으며, 미시적인 지표로는 가속도와 차두거리가 중요한 파라미터로 활용되고 있다. 속도와 교통량은 현재 설치된 교통정보 수집장치로 수집이 가능하지만 가속도와 차두거리는 안전과 자율주행분야 등에 필요성이 있지만 현재 교통정보 수집장치로는 수집이 불가능한 실정이다. 객체인식 기법인 YOLO는 정확도와 실시간성이 우수하여 교통분야를 포함하여 다양한 분야에서 활용되고 있다. 본 연구에서는 YOLO를 활용하여 가속도와 차두거리를 측정하기 위해 측정 간격을 조밀하게 설정하여 간격별 차량의 속도 변화와 차량 간 통행시간 차이를 통해 가속도와 차두거리를 측정하는 모델을 개발하였다. 지점별 교통특성에 따라 가속도와 차두거리의 범위가 다름을 확인하였고, 측정률 확보를 위한 기준거리와 화면각도에 따른 비교분석을 수행하다. 측정간격은 20m, 각도는 직각에 가까울수록 측정률이 높아짐을 분석하였다. 이를 통해 교차로별 안전도 분석과 국내 차량행태모델 분석에 기여할 수 있을 것이다.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2011년도 춘계학술대회 논문집
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• pp.427-434
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• 2011

This paper is focused on application of recursive least squares method to estimate rail irregularities from the acceleration measurement on an axle-box or a bogie for the rail condition monitoring with in-service high-speed trains. Generally, the rail condition was monitored by a special railway inspection vehicle but the monitoring method needs an expensive measurement system. A monitoring method using accelerometers on an axle-box or a bogie was already proposed in the previous study, and the displacement was successfully estimated from the acceleration data by using Kalman and frequency selective band-pass filters. However, it was found that the displacement included not only the rail irregularities but also phase delay of the applied filters, and effect of suspension of the bogie and conicity of the wheel. To identify the rail irregularities from the estimated displacement, a compensation filter method is proposed. The compensation filters are derived by using recursive least squares method with the estimated displacement as input and the measured rail irregularity as output. The estimated rail irregularities are compared with the true rail irregularity data from the rail inspection system. From the comparison, the proposed method is a useful tool for the measurement of lateral and vertical rail irregularity.