• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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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.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.3
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• pp.89-95
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• 2002

This paper describes a new identification method for friction in motion control systems, in which the friction model is not necessarily linear in parameters. The proposed method works well with any measurement data of velocity and input control force, as long as the initial and final velocities are identical. Most importantly, the proposed method does not require the information of acceleration for its implementation, in contrast with the previously known methods. This is due to the orthogonality property between acceleration and a function of velocity. In particular, if the parametric model is linear in parameters, its friction parameters can be identified in closed form without resorting to numerical search methods. To illuminate further the generality and practicality of the proposed friction identification method, we show good performance of the proposed method through some simulation results.

• Smart Structures and Systems
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• v.14 no.6
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• pp.1055-1079
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• 2014

Substructure shake table testing is a class of real-time hybrid simulation (RTHS). It combines shake table tests of substructures with real-time computational simulation of the remaining part of the structure to assess dynamic response of the entire structure. Unlike in the conventional hybrid simulation, substructure shake table testing imposes acceleration compatibilities at substructure boundaries. However, acceleration tracking of shake tables is extremely challenging, and it is not possible to produce perfect acceleration tracking without time delay. If responses of the experimental substructure have high correlation with ground accelerations, response errors are inevitably induced by the erroneous input acceleration. Feeding the erroneous responses into the RTHS procedure will deteriorate the simulation results. This study presents a set of techniques to enable reliable substructure shake table testing. The developed techniques include compensation techniques for errors induced by imperfect input acceleration of shake tables, model-based actuator delay compensation with state observer, and force correction to eliminate process and measurement noises. These techniques are experimentally investigated through RTHS using a uni-axial shake table and three-story steel frame structure at the Johns Hopkins University. The simulation results showed that substructure shake table testing with the developed compensation techniques provides an accurate and reliable means to simulate the dynamic responses of the entire structure under earthquake excitations.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.1
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• pp.73-81
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• 2011

The performance of emission factor has been validated by comparison with on-road test data. Emission factor, which is a function of vehicle speed, has been acquired based on chassis dynamometer test with NIER driving pattern. Portable Emission Measurement System, PEMS has measured on-road emission. Test vehicle was operated on defined test routes under different driving conditions, and made ten trips along its route. Emission factors properly simulate on-road test result, although there is some drawback to consider variety of driving condition on real world. Vehicle specific power and acceleration have been used to explain the distributed on-road result within same vehicle speed range. The trend in carbon dioxide and nitrogen oxide emission with respect to specific power and acceleration is clear. It has been found that specific power is a good explanatory variable for microscopic analysis for modal test result. Acceleration is good for microscopic as well as macroscopic analysis.

• Smart Structures and Systems
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• v.15 no.2
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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.

• Proceedings of the KSR Conference
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• 2011.05a
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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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.12
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• pp.2285-2290
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• 2017

Automation systems are evolving in many areas of industry in recent years. At the same time, the necessity of the height inspection of the object by the 3D measurement is gradually increasing. Among the various 3D measurement methods, this paper discusses phase measuring profilometry(PMP). The PMP is a method of obtaining the height of an object using the phase value of the fringe pattern. Since the PMP is an algorithm requiring a large amount of computation, a method for efficiently solving the problem is needed. In this paper, we propose to use CUDA from NVIDIA to solve this problem. We also propose using pinned memory and streams provided by CUDA. This can greatly improve the measurement speed while maintaining accuracy. Finally, we demonstrate the performance of the proposed method through experiments.

• Journal of the Society of Naval Architects of Korea
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• v.57 no.3
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• pp.175-181
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• 2020

For the success of a structural integrity management, it is essential to acquire structural response data at some critical locations with limited number of sensors. In this study, the structural response of numerical model was estimated by data fusion approach based on the Kalman filter known as stochastic recursive filter. Firstly, transient direct analysis was conducted to calculate the acceleration and strain of the numerical standing beam model, then the noise signals were mixed to generate the numerical measurement signals. The acceleration measurement signal was provided to the Kalman filter as an information on the external load, and the displacement measurement, which was transformed from the strain measurement by using strain-displacement conversion relationship, was provided into the Kalman filter as an observation information. Finally, the Kalman filter estimated the displacement by combining both displacements calculated from each numerically measured signal, then the estimated results were compared with the results of the transient direct analysis.

• Structural Engineering and Mechanics
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• v.10 no.6
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• pp.545-559
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• 2000

A Wind and Structural Health Monitoring System (WASHMS) has been installed in the Tsing Ma suspension Bridge in Hong Kong with one of the objectives being the verification of analytical processes used in wind-resistant design. On 2 August 1997, Typhoon Victor just crossed over the Bridge and the WASHMS timely recorded both wind and structural response. The measurement data are analysed in this paper to obtain the mean wind speed, mean wind direction, mean wind inclination, turbulence intensity, integral scale, gust factor, wind spectrum, and the acceleration response and natural frequency of the Bridge. It is found that some features of wind structure and bridge response are difficult to be considered in the currently used analytical process for predicting buffeting response of long suspension bridges, for the Bridge is surrounded by a complex topography and the wind direction of Typhoon Victor changes during its crossing. It seems to be necessary to improve the prediction model so that a reasonable comparison can be performed between the measurement and prediction for long suspension bridges in typhoon prone regions.

• Journal of Internet Computing and Services
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• v.18 no.3
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• pp.11-17
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• 2017

To the elderly, sudden falls are one of the most frightening accidents. If an accident occurs, a prompt action has to be taken to deal with the situation. Recently, there have been a number of attempts to detect sudden falls using acceleration sensors embedded in the mobile devices, such as smart phones and wrist-bands. However, using the sensor readings only, the detection rate of the falls is around 65%. Ordinary daily activities such as running or jumping could not be well distinguished from the falls. In this paper, we describe our attempts on improving the fall-detection rate. We implemented a wrist-band fall detection module, using a three-axis acceleration sensor. With the pattern matching on the fall signal-strength frequency spectrum, in addition to the conventional signal strength measurement, we could improve the detection rate by 9% point. Furthermore, by applying two wrist-bands in the experiment, we could further improve the detection rate to 82%.