• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.6
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• pp.182-193
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• 2000

Several metrics have been used in crash discrimination algorithms in order to have timely air bag deployment during all frontal crash modes. However, it is still challengine to have timely air bag deployment especially during the oblique, the pole and the underride crash mode. Therefore, in this paper a new crash discrimination algorithm was proposed, using the absolute value of the deceleration change multiplied by the velocity change as a metric, and processing the metric as a function of the velocity change. The new algorithm was applied for all frontal crash modes of a minivan and a sports utility vehicle, and it resulted in timely air bag deployment for all frontal crash modes including the oblique, the pole and the underride crash mode. Moreover, it was proposed that an accelerometer be installed at each side of the rails, rockers or pillars to assess the crash severity of each side and to deploy the frontal air bags at different time especially during an asymmetric crash such as an oblique and an offset crash. As an example, the deceleration pulses measured at the left and right B-pillar·rocker locations were processed through the new algorithm, and faster time-to-fires were obtained for the air bag at the struck side for the air bag at the other side.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.7
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• pp.489-495
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• 2020

An accelerometer-based system was designed and constructed for drag measurement in a shock tunnel. Drag coefficient of a conical model was measured under a Mach 6 flow condition. A simple and intuitive calibration method was presented to compensate for the friction force of the drag measurement system, and the results of the measurement were compared with computational fluid dynamics in which the simple conical model was analyzed. The influence of drag measurement interference by supports of various shapes was identified and the design was presented to minimize. The drag coefficient measurement using the modified support showed that the error of the drag coefficient by the support was decreased.

• Journal of KIISE
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• v.41 no.9
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• pp.633-641
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• 2014

This paper proposes algorithms to detect jump motion and automatically take a picture when the jump reaches its top. Based on the algorithms, we build jump-shot system by using accelerometer-equipped smart phones. Since the jump motion may vary depending on one's physical condition, gender, and age, it is critical to figure out common features which are independent from such differences. Also it is obvious that the detection algorithm needs to work in real-time because of the short duration of the jump. We propose two different algorithms considering these requirements and develop the system as a smart phone application. Through a series of experiments, we show that the system is able to successfully detect the jump motion and take a picture when it reaches the top.

• Journal of Biomedical Engineering Research
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• v.27 no.6
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• pp.301-309
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• 2006

The main purpose of this study is to derive a regression equation that predicts the individual differences in activity energy expenditure (AEE) using accelerometer during different types of activity. Two subject groups were recruited separately in time: One is a homogeneous group of 94 healthy young adults with age ranged from $20\sim35$ yrs. The other subject group has a broad spectrum of physical characteristics in terms of age and fat ratio. 226 adolescents and adults of age ranged from $12\sim57$ yrs and fat ratio from $4.1\sim39.7%$ were in the second group. The wireless 3-axis accelerometers were developed and carefully fixed at the waist belt level. Simultaneously the total calorie expenditure was measured by gas analyzer. Each subject performed walking and running at speeds of 1.5, 3.0, 4.5, 6.0, 6.5, 7.5, and 8.5 km/hr. A generalized sensor-independent regression equation for AEE was derived. The regression equation was developed fur walking and running. The regression coefficients were predicted as functions of physical factors-age, gender, height, and weight with multivariable regression analysis. The generalized calorie estimation equation predicts AEE with correlation coefficient of 0.96 and the average accuracy of the accumulated calorie was $89.6{\pm}7.9%$.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.8
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• pp.872-878
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• 2008

Many industrial operations require continuous or nearly-continuous operation of machines, interruption of which can result in significant cost loss. The condition monitoring of these machines has received considerable attentions in recent years. Rapid developments in semiconductor, computing, and communication with a remote site have led to a new generation of sensor called "smart" sensors which are capable of wireless communication with a remote site. The purpose of this research is to develop a new type of smart sensor for on-line condition monitoring. This system is addressed to detect conditions that may lead to equipment failure when it is running. Moreover it will reduce condition monitoring expense using low cost MEMS accelerometer. This system is capable for signal preprocessing task and analog to digital converter which is controlled by CPU. This sensor communicates with a remote site PC using TCP/IP protocols. The developed sensor executes performance tests for data acquisition accuracy estimations.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.445-450
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• 2004

This paper describes an optimal design system for multi-disciplinary structural design. An automatic finite element (FE) mesh generation technique, which is based on the fuzzy knowledge processing and computational geometry technique, is incorporated into the system, together with a commercial FE analysis code and a commercial solid modelers. An optimum design solution or satisfactory solutions are then automatically searched using the genetic algorithms modified for real search space, together with the automated FE analysis system. With an aid of genetic algorithms, the present design system allows us to effectively obtain a multi-dimensional solutions. The developed system is successfully applied to the shape design of a micro accelerometer based on a tunnel current concept.

• Smart Structures and Systems
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• v.31 no.3
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• pp.301-309
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• 2023

Tilt is a key indicator of structural safety. Real-time monitoring of tilt responses helps to evaluate structural condition, enable cost-effective maintenance, and enhance lifetime resilience. This paper presents a prototype wireless sensing system for structural tilt measurement. Long range (LoRa) technology is adopted by the sensing system to offer long-range wireless communication with low power consumption. The sensor integrates a gyroscope and an accelerometer as the sensing module. Although tilt can be estimated from the gyroscope or the accelerometer measurements, these estimates suffer from either drift issue or high noise. To address this challenging issue and obtain more reliable tilt results, two sensor fusion algorithms, the complementary filter and the Kalman filter, are investigated to fully exploit the advantages of both gyroscope and accelerometer measurements. Numerical simulation is carried out to validate and compare the sensor fusion algorithms. Laboratory experiment is conducted on a simply supported beam under moving vehicle load to further investigate the performance of the proposed wireless tilt sensing system.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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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 ${\pm}\;10g$.

• Journal of Multimedia Information System
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• v.2 no.2
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• pp.233-240
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• 2015

Mobile devices are becoming increasingly sophisticated and the latest generation of smartphones now incorporates many diverse and powerful sensors. These sensors include acceleration sensor, magnetic field sensor, light sensor, proximity sensor, gyroscope sensor, pressure sensor, rotation vector sensor, gravity sensor and orientation sensor. The availability of these sensors in mass-marketed communication devices creates exciting new opportunities for data mining and data mining applications. In this paper, we describe and evaluate a system that uses phone-based accelerometers to perform activity recognition, a task which involves identifying the physical activity that a user is performing. To implement our system, we collected labeled accelerometer data from 10 users as they performed daily activities such as "phone detached", "idle", "walking", "running", and "jumping", and then aggregated this time series data into examples that summarize the user activity 5-minute intervals. We then used the resulting training data to induce a predictive model for activity recognition. This work is significant because the activity recognition model permits us to gain useful knowledge about the habits of millions of users-just by having them carry cell phones in their pockets.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.6
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• pp.851-858
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• 2012

In this paper, we design a seismic data acquisition system(SDAS) and implement it. This system is essential for development of a noble local earthquake disaster preventing system in population center. In the system, we choose a proper MEMS-type triaxial accelerometer as a sensor, and FPGA and ARM processor are used for implementing the system. In the SDAS, each module is realized by Verilog HDL and C Language. We carry out the ModelSim simulation to verify the performances of important modules. The simulation results show that the FPGA-based data acquisition module can guarantee an accurate time-synchronization for the measured data from each axis sensor. Moreover, the FPGA-ARM based embedded technology in system hardware design can reduce the system cost by the integration of data logger, communication sever, and facility control system. To evaluate the data acquisition performance of the SDAS, we perform experiments for real seismic signals with the exciter. Performances comparison between the acquired data of the SDAS and the reference sensor shows that the data acquisition performance of the SDAS is valid.