• 한국철도학회:학술대회논문집
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• 한국철도학회 2002년도 추계학술대회 논문집(II)
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• pp.1053-1058
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• 2002

Calibration of the health monitoring system is considered in this study. For this, brief introduction on the realtime monitoring system, installed in some of the Korea Highspeed Railway bridges, is made and specifications of the calibrators are outlined. Calibration method is next explained for each sensor and detailed procedures are illustrated. Calibration results will be published elsewhere and modification of the gauge factors will also be investigated in detail.

• Safety and Health at Work
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• 제10권4호
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• pp.452-460
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• 2019

Background: Monitoring and control of PM_2.5 are being recognized as key to address health issues attributed to PM_2.5. Availability of low-cost PM_2.5 sensors made it possible to introduce a number of portable PM_2.5 monitors based on light scattering to the consumer market at an affordable price. Accuracy of light scatteringe-based PM_2.5 monitors significantly depends on the method of calibration. Static calibration curve is used as the most popular calibration method for low-cost PM_2.5 sensors particularly because of ease of application. Drawback in this approach is, however, the lack of accuracy. Methods: This study discussed the calibration of a low-cost PM_2.5-monitoring device (PMD) to improve the accuracy and reliability for practical use. The proposed method is based on construction of the PM_2.5 sensor network using Message Queuing Telemetry Transport (MQTT) protocol and web query of reference measurement data available at government-authorized PM monitoring station (GAMS) in the republic of Korea. Four machine learning (ML) algorithms such as support vector machine, k-nearest neighbors, random forest, and extreme gradient boosting were used as regression models to calibrate the PMD measurements of PM_2.5. Performance of each ML algorithm was evaluated using stratified K-fold cross-validation, and a linear regression model was used as a reference. Results: Based on the performance of ML algorithms used, regression of the output of the PMD to PM_2.5 concentrations data available from the GAMS through web query was effective. The extreme gradient boosting algorithm showed the best performance with a mean coefficient of determination (R²) of 0.78 and standard error of 5.0 ㎍/㎥, corresponding to 8% increase in R² and 12% decrease in root mean square error in comparison with the linear regression model. Minimum 100 hours of calibration period was found required to calibrate the PMD to its full capacity. Calibration method proposed poses a limitation on the location of the PMD being in the vicinity of the GAMS. As the number of the PMD participating in the sensor network increases, however, calibrated PMDs can be used as reference devices to nearby PMDs that require calibration, forming a calibration chain through MQTT protocol. Conclusions: Calibration of a low-cost PMD, which is based on construction of PM_2.5 sensor network using MQTT protocol and web query of reference measurement data available at a GAMS, significantly improves the accuracy and reliability of a PMD, thereby making practical use of the low-cost PMD possible.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2012년도 춘계학술대회 논문집
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• pp.667-668
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• 2012

• Smart Structures and Systems
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• 제15권6호
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• pp.1543-1567
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• 2015

In this study, a wireless crack sensor is developed for monitoring cracks propagating in two dimensions. This sensor is developed by incorporating a laser-based optical navigation sensor board (ADNS-9500) into a smart wireless platform (Imote2). To measure crack propagation, the Imote2 sends a signal to the ADNS-9500 to collect a sequence of images reflected from the concrete surface. These acquired images can be processed in the ADNS-9500 directly (the navigation mode) or sent to Imote2 for processing (the frame capture mode). The computed crack displacement can then be transmitted wirelessly to a base station. The design and the construction of this sensor are reported herein followed by some calibration tests on one prototype sensor. Test results show that the sensor can provide sub-millimeter accuracy under sinusoidal and step movement. Also, the two modes of operation offer complementary performance as the navigation mode is more accurate in tracking large amplitude and fast crack movement while the frame capture mode is more accurate for small and slow crack movement. These results illustrate the feasibility of developing such a crack sensor as well as point out directions of further research before its actual implementation.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2010년도 추계 학술발표회
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• pp.587-597
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• 2010

Analysis of the behavior of a laterally loaded pile is important in the design of critical civil structures. Recently, the electric strain gauge has been widely used to measure the strains along the pile. The electric strain gauge, due to lack of durability, is inappropriate in the use of long-term measurements. Herein, the feasibility of implementing the FBG sensor was investigated using a cantilever-type calibrator in laboratory. A special calibrating tool called "cantilever-calibrator" was used to calibrate the FBG sensors. The calibrator consists of a special calibration beam, a holding-clamp at one end of the beam, and a micrometer on the other end. Three FBG sensors were installed on the calibration beam. The strains measured by FBG sensors were compared with those calculated theoretically using cantilever beam theory. The calibration factor of FBG sensors were suggested to compensate the difference between measured and calculate strains.

• International Journal of Aeronautical and Space Sciences
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• 제10권2호
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• pp.43-51
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• 2009

In the flight of air vehicles, accurate air data information is required to control them effectively. Especially, helicopters are often put in drastic motion involved with high angle of attacks in order to perform difficult missions. Among various sensors, the multi function probe (MFP) has been used in the present study mainly owing to its advantages in structural simplicity and capability of providing various information such as static and total pressure, speed, and pitch and yaw angles. In this study, a five-hole multi-function probe (FHMFP) is developed and its calibration is conducted using multiple regressions. In this work a calibration study on the FHMFP, an air data sensor for helicopters, is reported. It is shown that the pitch and yaw angles' accuracy of calibration is ${\pm}0.91^{\circ}$ at a cone angle of $0^{\circ}{\sim}30^{\circ}$ and ${\pm}2.0^{\circ}$ at $30^{\circ}{\sim}43^{\circ}$, respectively, which is summarized in table 3.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.814-822
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• 2022

The deployment of sensors for Structural Health Monitoring requires a complicated network arrangement, ground truthing, and calibration for validating sensor performance periodically. Any conventional sensor on a structural element is also subjected to static and dynamic vertical loadings in conjunction with other environmental factors, such as brightness, noise, temperature, and humidity. A structural model with strain gauges was built and tested to get realistic sensory information. This paper investigates different deep learning architectures and algorithms, including unsupervised, autoencoder, and supervised methods, to benchmark blind drift calibration methods using deep learning. It involves a fully connected neural network (FCNN), a long short-term memory (LSTM), and a gated recurrent unit (GRU) to address the blind drift calibration problem (i.e., performing calibrations of installed sensors when ground truth is not available). The results show that the supervised methods perform much better than unsupervised methods, such as an autoencoder, when ground truths are available. Furthermore, taking advantage of time-series information, the GRU model generates the most precise predictions to remove the drift overall.

• 방송공학회논문지
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• 제24권4호
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• pp.580-591
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• 2019

본 논문의 목적은 자율주행을 위하여 카메라와 라이다를 이용하여 객체를 검출하고 각 센서에서 검출된 객체를 late fusion 방식으로 융합을 하여 성능을 향상하는 것을 목적으로 한다. 카메라를 이용한 객체 검출은 one-stage 검출인 YOLOv3을, 검출된 객체의 거리 추정은 perspective matrix를, 라이다의 객체 검출은 K-means 군집화 기반 객체 검출을 각각 이용하였다. 카메라와 라이다 calibration은 PnP-RANSAC을 이용하여 회전, 변환 행렬을 구하였다. 센서 융합은 라이다에서 검출된 객체를 이미지 평면에 옮겨 Intersection over union(IoU)을 계산하고, 카메라에서 검출된 객체를 월드 좌표에 옮겨 거리, 각도를 계산하여 IoU, 거리 그리고 각도 세 가지 속성을 로지스틱 회귀를 이용하여 융합을 하였다. 융합을 통하여 각 센서에서 검출되지 않은 객체를 보완해주어 성능이 약 5% 증가하였다.

• 생물환경조절학회지
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• 제31권4호
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• pp.401-408
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• 2022

최근 원예작물의 지속가능한 생산을 위한 작물 생육환경 센싱 기반 복합환경제어시스템 연구와 산업적 이용이 부각되면서, 노지재배에 적용하기 적합한 토양센서 활용 방안 연구가 활발히 이루어지고 있다. 본 연구는 산업 및 연구 현장에서 많이 사용되고 있는 TEROS 12 FDR 센서(frequency domain reflectometry sensor)를 노지 과수원의 토양에 알맞게 활용하기 위하여 국내 세 지역 과수원 토양의 토성별 FDR 센서 활용 방법을 제시하고자 수행하였다. 실제 과수가 재배되고 있는 각 과수원에서 토양을 채취하여, 토성 및 토양수분보유곡선을 조사하였으며, 토양별 TEROS 12 센서 Raw 값과 이에 대응하는 용적수분함량 값을 선형 회귀 분석, 3차 회귀 분석을 통해 보정식을 얻은 뒤 제조사에서 제공하는 광질 토양 보정식과 비교 분석하였다. 채취한 세 과수원의 토양은 모두 토성이 달랐으며, 토성에 따라 각 보수력에 따른 용적수분함량 수치에 차이가 있었다. 또한, TEROS 12 센서 보정식에서는 모든 토양에서 3차 회귀 분석 보정식이 결정계수 0.95 이상으로 가장 높게 나타났으며, RMSE도 가장 낮게 나타났다. 제조사에서 제공하는 보정식을 사용하여 TEROS 12 센서의 용적수분함량을 보정할 경우 토양에 따라 실제 수치에 비해 최대 0.09-0.17m³·m^-3가량 낮게 나타나, FDR 센서 사용시 적용 토양에 알맞은 보정이 반드시 선행되어야 함을 확인하였다. 또한 토성에 따라 토양의 보수력 구간에 따른 용적수분함량 범위의 차이가 있었으며, 토양 용적수분함량의 수치 해석에 보수력 정보가 수반되어야 할 것으로 나타났다. 또한, 사질이 많은 토양에서는 관수 개시점 측정을 위해 FDR 센서를 활용하는 데 있어 용적수분함량 측정 범위가 상대적으로 좁아 정밀도가 떨어질 것으로 판단되었다. 결론적으로 토양에서 FDR 센서를 통해 토양수분의 변화를 알맞게 해석하고 노지에서 알맞은 관수 시점을 선정하기 위해서는, 적용 토양의 수분보유특성을 파악하고 FDR 센서 보정을 선행하여 올바른 토양 수분 정보 제공이 필요할 것이다.

• Journal of Electrical Engineering and Technology
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• 제10권4호
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• pp.1830-1835
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• 2015

In this paper, we propose an algorithm for the automatic registration of two rigid parts using multiple 3D sensor systems on a robot. Four sets of structured laser stripe system consisted of a camera and a visible laser stripe is used for the acquisition of 3D information. Detailed procedures including extrinsic calibration among four 3D sensor systems and hand/eye calibration of 3D sensing system on robot arm are presented. We find a best pose using search-based pose estimation algorithm where cost function is proposed by reflecting geometric constraints between sensor systems and target objects. A pose with minimum gap and height difference is found by greedy search. Experimental result using demo system shows the robustness and feasibility of the proposed algorithm.