• 센서학회지
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• 제21권3호
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• pp.198-203
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• 2012

In this paper, the driving information system of the bicycle has been studied by using the 3-axis acceleration sensor. The sensor module composed of 3-axis acceleration sensor and MCU(Microcontroller Unit) was mounted onto the handle of bicycle and the experiments were conducted on the flatland, uphill and downhill of bicycle road. Three axis acceleration values were converted to the pitch and roll angles, then four major compensation methods have been applied to achieve meaningful data for driving information system. The experimental results of pitch angles showed 2.46, -1.26, 7.79 degrees in case of flatland, uphill, downhill, respectively. When the steering handle turned to the left direction, roll angles showed -29.35, -41.67, -36.98 degrees at each road condition. With the right-turn, roll angles presented 20.05, 33.75, 24.44 degrees in case of flatland, uphill, and downhill, respectively. The pitch angle has been increased more than 40 degrees at stop mode. By using the change of pitch and roll angles, we could obtain the driving information system of bicycle successfully.

• 대한기계학회논문집A
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• 제39권2호
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• pp.179-185
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• 2015

가속도계의 신호는 운동체의 가속도와 다르며, 운동체의 자세가 변화하는 경우 가속도계 단독으로 센서가속도를 계측할 수 없다. 본 논문에서는 3 축 가속도계와 3 축 자이로스코프로 구성된 6 축관성센서 신호를 바탕으로 운동체의 자세가 지속적으로 변화하는 가운데 가속도를 정확히 추정할 수 있는 칼만필터를 제안한다. 제안하는 알고리즘은 센서의 자세뿐 아니라 센서가속도가 상태벡터의 일부로 설정되어 있는 새로운 구조의 칼만필터로써, 센서 가속도를 명시적으로 정확히 구할 수 있다. 제안된 필터는 다양한 조건하에서 광학모션캡쳐시스템을 이용하여 그 정확성이 검증되었는데, 최신 Xsens MTw 센서와 동등수준의 성능이었다. 제안된 알고리즘은 6 축 관성센서를 바탕으로 운동체의 가속도 추정이 필요한 다양한 모션센서 응용분야에 적용될 수 있다.

• 통합자연과학논문집
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• 제10권4호
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• pp.232-239
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• 2017

The researcher set up multiple sensor units on the road slope such as national highway and highway where there is a possibility of loss, and using the acceleration sensor built into the sensor unit the researcher will sense whether the inclination of the road slope occur in real time, and Based on the sensed data, the researcher tries to implement a system that detects collapse of road slope and dangerous situation. In the experiment of measuring the error between the actual measurement time and the judgment time of the monitoring system when judging the warning of the sensor and falling rock detection by using the acceleration sensor, the error between measurement time and the judgment time at the sensor warning was 0.34 seconds on average, and an error between measurement time and judgment time at falling rock detection was 0.21 seconds on average. The error is relatively small, the accuracy is high, and thus the change of the slope can be clearly judged.

• International Journal of Ocean System Engineering
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• 제1권3호
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• pp.165-170
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• 2011

In this paper, for the accurate estimation of the position and orientation of the UUV (unmanned underwater vehicle), an AHRS (Attitude Heading Reference System) was developed using the IMU (inertial measurement unit) sensor which provides information on acceleration and orientation in the object coordinate and the initial alignment algorithm and the E-KF (extended Kalman Filter). The initial position and orientation of the UUV are estimated using the initial alignment algorithm with 3-axis acceleration and geomagnetic information of the IMU sensor. The position and orientation of the UUV are estimated using the AHRS composed of 3-axis acceleration, velocity, and geomagnetic information and the E-KF. For the performance test of the orientation estimation of the AHRS, a testbed using IMU sensor(ADIS16405) and DSP28335 coded with an E-KF algorithm was developed and its performance was verified through tests.

• Asian-Australasian Journal of Animal Sciences
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• 제29권1호
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• pp.149-156
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• 2016

In this experiment, we proposed and implemented a disease forecasting system using a received signal strength indication ZigBee-based wireless network with a 3-axis acceleration sensor to detect illness at an early stage by monitoring movement of experimentally infected weaned piglets. Twenty seven piglets were divided into control, Salmonella enteritidis (SE) infection, and Escherichia coli (EC) infection group, and their movements were monitored for five days using wireless sensor nodes on their backs. Data generated showed the 3-axis movement of piglets (X-axis: left and right direction, Y-axis: anteroposterior direction, and Z-axis: up and down direction) at five different time periods. Piglets in both infected groups had lower weight gain and feed intake, as well as higher feed conversion ratios than the control group (p<0.05). Infection with SE and EC resulted in reduced body temperature of the piglets at day 2, 4, and 5 (p<0.05). The early morning X-axis movement did not differ between groups; however, the Y-axis movement was higher in the EC group (day 1 and 2), and the Z-axis movement was higher in the EC (day 1) and SE group (day 4) during different experimental periods (p<0.05). The morning X and Y-axis movement did not differ between treatment groups. However, the Z-axis movement was higher in both infected groups at day 1 and lower at day 4 compared to the control (p<0.05). The midday X-axis movement was significantly lower in both infected groups (day 4 and 5) compared to the control (p<0.05), whereas the Y-axis movement did not differ. The Z-axis movement was highest in the SE group at day 1 and 2 and lower at day 4 and 5 (p<0.05). Evening X-axis movement was highest in the control group throughout the experimental period. During day 1 and 2, the Z-axis movement was higher in both of the infected groups; whereas it was lower in the SE group during day 3 and 4 (p<0.05). During day 1 and 2, the night X-axis movement was lower and the Z-axis movement was higher in the infected piglets (p<0.05). Overall, the movement of infected piglets was altered, and the acceleration sensor could be successfully employed for monitoring pig activity.

• 한국멀티미디어학회논문지
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• 제25권2호
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• pp.297-310
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• 2022

Road facilities such as CCTV poles have potential risk of collision accidents with a car. A collision detection algorithm installed in the facility allows the collision accident to be known remotely. Most collision detection algorithms are operated by simply focusing on whether a collision have occurred, because these methods are used to measure only acceleration data from a 3-axis sensor to detect collision. However, it is difficult to detect other detailed information such as malfunction of the sensor, collision direction and collision strength, because it is not known without witness the accident. Therefore, we proposed enhanced detection algorithm to get the collision direction, and the collision strength from the tilt of the facility after accident using a 9-axis sensor in this paper. In order to confirm the performance of the algorithm, an accuracy evaluation experiment was conducted according to the data measurement cycle and the invocation cycle to an detection algorithm. As a result, the proposed enhanced algorithm confirmed 100% accuracy for 50 weak collisions and 50 strong collisions at the 9-axis data measurement cycle of 10ms and the invocation cycle of 1,000ms. In conclusion, the algorithm proposed is expected to provide more reliable and detailed information than existing algorithm.

• 한국구조물진단유지관리공학회 논문집
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• 제18권1호
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• pp.160-165
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• 2014

본 연구에서는 MEMS 기반 3축 가속도 센서 모듈을 제작하여 성능 시험을 수행하였고, 지진 모니터링 시스템을 구성하였다. 3축 가속도 센서 모듈의 성능 향상을 위하여 데이터 수집장치를 24bit ADC (Analog to Digital Converter)가 내장된 NI-9239를 사용하였고, 잡음을 줄이기 위해 100Hz LPF (Low Pass Filter)를 통과시킨 데이터를 사용하였다. 또한 지진 모니터링 소프트웨어를 개발하여 구조물에 유의한 진동을 감지하는데 초점을 맞추었다. 진동을 감지하기 위한 방법으로 각 축의 가속도 크기 뿐만 아니라 3축 가속도의 벡터 합을 구하여 이 벡터 합이 미리 설정한 값을 초과할 때의 수치를 별도로 표시하고 이를 파일로 저장하는 알고리즘을 사용하였다.

• International Journal of Internet, Broadcasting and Communication
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• 제11권4호
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• pp.71-75
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• 2019

Sleep apnea is a disease that causes various complications, and the polysomnography is expensive and difficult to measure. The purpose of this study is to develop an unrestricted wearable monitoring system so that patients can be examined in a familiar environment. We used a method to detect sleep apnea events and to determine sleep satisfaction by non-constrained method using SpO2 measurement sensor and 3-axis acceleration sensor. Heart rate and SpO2 were measured at the finger using max30100. After acquiring the SpO2 data of the user in real time, the apnea measurement algorithm was used to transmit the number of apnea events of the user to the mobile phone using Bluetooth (HC-06) on the wrist. Using the three-axis acceleration sensor (mpu6050) attached to the upper body, the number of times of tossing and turning during sleep was measured. Based on this data, this algorithm evaluates the patient's tossing and turning during sleep and transmits the data to the mobile phone via Bluetooth. The power source used 9 volts battery to operate Arduino UNO and sensors for portability and stability, and the data received from each sensor can be used to check the various degree between sleep apnea and sleep tossing and turning on the mobile phone. Through thisstudy, we have developed a wearable sleep apnea measurement system that can be easily used at home for the problem of low sleep efficiency of sleep apnea patients.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2018년도 춘계학술대회
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• pp.431-432
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• 2018

인간은 행동을 인식하는데 가속도 센서를 많이 사용해왔다. 관성력, 전기변형, 자이로의 응용 원리를 이용한 이 센서는 3차원 축에 인가되는 힘을 통해 간접적으로 움직임을 측정한다. 여기에는 같은 방법이라도 소지하는 센서의 위치에 따라서 다른 결과가 나올 수 있다. 대중적으로 많이 쓰이는 스마트폰에도 탑재되어 있는 이 센서는 오늘날 현대인들이 자주 사용하는 형태인 손에 들고 있거나 주머니에 넣은 상태에서 가속도 센서의 값을 측정했을 때 어떻게 다른지 비교하였다.

• 전기학회논문지
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• 제59권1호
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• pp.220-224
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• 2010

In this study, we designed a device for consecutively observing position, utilizing 3-axises acceleration sensor. This method offer to check his or her wrong position and developed could to help derived a position appliance. And, we developed a Cobb's angle value in three dimensional using 3-axises acceleration sensor. A proposed device with integrated accelerometers, which can detect postural changes in terms of curvature variation of the spine in the sagittal and coronal planes, has been developed with intention to facilitate posture training. The proposed device was evaluated with 3 normal subjects daily activities. We evaluated the performance of our designed device as calculating the correlation coefficients and mean errors between the angle measured by an electro-goniometer and that estimated by a gravity accelerometer and verified the accuracy and sensitivity. The results showed that the angle obtained from the proposed device revealed a linear characteristic at the range of $\pm60^{\circ}$(correlation coefficient 0.99, error range $\pm2^{\circ}$). We demonstrated that our device could detect the changes of the motion in upper trunk accurately. Also, our device showed good potential for treatment of the patients with scoliosis and prevention of the unbalance position during a daily life.