• Smart Structures and Systems
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• 제6권5_6호
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• pp.661-673
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• 2010

This paper presents recent developments in an extremely compact, wireless impedance sensor node (the WID3, $\underline{W}$ireless $\underline{I}$mpedance $\underline{D}$evice) for use in high-frequency impedance-based structural health monitoring (SHM), sensor diagnostics and validation, and low-frequency (< ~1 kHz) vibration data acquisition. The WID3 is equipped with an impedance chip that can resolve measurements up to 100 kHz, a frequency range ideal for many SHM applications. An integrated set of multiplexers allows the end user to monitor seven piezoelectric sensors from a single sensor node. The WID3 combines on-board processing using a microcontroller, data storage using flash memory, wireless communications capabilities, and a series of internal and external triggering options into a single package to realize a truly comprehensive, self-contained wireless active-sensor node for SHM applications. Furthermore, we recently extended the capability of this device by implementing low-frequency analog-to-digital and digital-to-analog converters so that the same device can measure structural vibration data. The compact sensor node collects relatively low-frequency acceleration measurements to estimate natural frequencies and operational deflection shapes, as well as relatively high-frequency impedance measurements to detect structural damage. Experimental results with application to SHM, sensor diagnostics and low-frequency vibration data acquisition are presented.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2013년도 추계학술대회 논문집
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• pp.799-804
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• 2013

The sensor/actuator active sensor diagnostics procedure, where the sensors/actuators are confirmed to be functioning properly during operation, is a critical component to successfully complete the structural health monitoring (SHM) process with large numbers of active sensors typically installed in a structure. The basis of this process is to track the changes in the capacitive value of piezoelectric materials, which shows up in measured admittance. Due to the temperature dependent nature of piezoelectric materials, we investigated the effects of temperature variations on sensor diagnostic process. The effect of temperature variations found to be remarkable, modifying the measured capacitive values significantly. In addition we analyzed the effect of bonding agents between a PZT patch and a host structure. This paper summarizes considerations needed to develop such sensor diagnostic processes, experimental procedures and results, and additional issues that can be used as guidelines for future investigations.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2003년도 하계학술대회 논문집 Vol.4 No.1
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• pp.96-99
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• 2003

In this paper, ageing diagnostics in the large capacity oil transformer are investigated. Following items are investigated for the ageing diagnostic in transformer oils (leakage current of sensor, power consumption and temperature of transformer oil). All temperature data are gathered from daily report in the substation. The power consumption of transformer are gathered output report of APIS(Airport Power Information System). Especially, data of sensor leakage current are accumulated from the online diagnostic system for transformer oil. The temperature of transformer oils major change factor was ambient temperature and capacity of power load. The leakage current are change by oil temperature. The leakage current ware not more than 2 [nA] in summer,

• Smart Structures and Systems
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• 제7권3호
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• pp.229-240
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• 2011

Recent developments in Smart Structures with very large scale embedded sensors and actuators have introduced new challenges in terms of data processing and sensor fusion. These smart structures are dynamically classified as a large-scale system with thousands of sensors and actuators that form the musculoskeletal of the structure, analogous to human body. In order to develop structural health monitoring and diagnostics with data provided by thousands of sensors, new sensor informatics has to be developed. The focus of our on-going research is to develop techniques and algorithms that would utilize this musculoskeletal system effectively; thus creating the intelligence for such a large-scale autonomous structure. To achieve this level of intelligence, three major research tasks are being conducted: development of a Bio-Inspired data analysis and information extraction from thousands of sensors; development of an analytical technique for Optimal Sensory System using Structural Observability; and creation of a bio-inspired decision-making and control system. This paper is focused on the results of our effort on the first task, namely development of a Neuro-Morphic Engineering approach, using a neuro-symbolic data manipulation, inspired by the understanding of human information processing architecture, for sensor fusion and structural diagnostics.

• 센서학회지
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• 제22권3호
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• pp.191-196
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• 2013

A particulate matter sensor fabricated by MEMS process is proposed. It is developed to accommodate Euro6 on-board diagnostics regulation for diesel automobile. In the regulation, emission of diesel particulate matter is restricted to 9 mg/km. Particulate matter sensor is designed to use induced charges by charged particulate matter. To increase sensitivity of the sensor, groove is formed on sensor surface because wider surface area generates more induced charges. Sensitivity of the sensor is measured 10.6 mV/(mg/km) and the sensor shows good linearity up to 15.7 mg/km. Also its minimum detectable range is about 0.25 mg/km. It is suitable to detect failure of a diesel particulate filter which should filter particulate matter more than 9 mg/km. For removing accumulated particulate matter on the sensor which can disturb normal operation, platinum heater is designed on the backside of the sensor. The developed sensor can sense very low amount of particulate matter from exhaust gas in real-time with good linearity.

• 센서학회지
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• 제23권5호
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• pp.291-294
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• 2014

In this study, a chemiresistive sensor based on one-dimensional $WO_3$ nanostructures is presented for application in non-invasive medical diagnostics. $WO_3$ nanostructures were used as an active gas sensing layer and were deposited onto a $SiO_2/Si$substrate using Pt interdigitated electrodes (IDEs). The IDE spacing was $5{\mu}m$ and deposition was performed using RF sputter with glancing angle deposition mode. Pt IDEs fabricated by photolithography and dry etching. In comparison with thin film sensor, sensing performance of nanostructure sensor showed an enhanced response of more than 20 times when exposed to 50 ppm acetone at $400^{\circ}C$. Such a remarkable faster response can pave the way for a new generation of exhaled breath analyzers based on chemiresistive sensors which are less expensive, more reliable, and less complicated to be manufactured. Moreover, presented sensor technology has the potential of being used as a personalized medical diagnostics tool in the near future.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 춘계학술대회 논문집
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• pp.1463-1467
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• 2005

This paper proposes an analytical redundancy technique for fault diagnostics of the sensor in steer-by-wire system. We use incorporating vehicle dynamics modeling into the design of a diagnostic system for steer-by-wire system. The use of a model of vehicle dynamics improves the speed and accuracy of the diagnoses. The proposed fault diagnostics algorithm is based on parity-space methods to generate residuals. To reduce the effects of modeling uncertainty and dynamic transients, the residuals are subject to filtering. We construct diagnostic system consisting residual threshold for detection and isolator with using the directional residual vector.

• Composites Research
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• 제28권4호
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• pp.148-154
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• 2015

구조건전성 모니터링은 구조물에 발생된 손상을 조기에 감지 및 적절한 유지보수를 통해 재정적 혹은 인명 피해를 방지하기 위해 실시된다. 대부분의 능동센싱 기반 구조건전성 모니터링에서는 많은 수의 압전체(piezoelectric transducer) 센서와 구동기(actuator)를 필요로 한다. 구조건전성 모니터링 시 사용된 압전센서에 결합이 존재하는 경우, 구조물의 상태진단에 문제가 발생할 수 있다. 본 연구에서는 신뢰성 있는 구조건전성 모니터링 결과를 위해 임피던스 기반 센서 자가 진단법을 사용하여 다수 센서의 결함을 탐지하였다. 또한 사용된 접착제와 센서의 정보가 충분치 못한 경우, 사용된 센서로부터 측정된 데이터만을 토대로 센서결함 진단을 위한 알고리즘을 소개하였다. 알고리즘이 적용 가능한 온도 범위를 실험적으로 분석함으로써 개발된 기법이 실제 환경에서 응용이 가능함을 확인하였다.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2005년도 제24회 춘계학술대회논문집
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• pp.248-251
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• 2005

본 연구에서는 가스 터빈 엔진의 결함에 의해 나타나는 엔진의 성능 저하를 진단하는 기법을 연구하였다. 대상 엔진을 모델화하기 위해 상용 프로그램 GSP를 이용하여 저하된 성능 진단을 위한 변수들을 추출하였으며 이를 바탕으로 Health Monitoring을 위한 Virtual Sensor Model을 구축하였다. 단일 결함과 복합 결함을 예측하기 위한 방법으로 Multiple Linear Regression기법과 가중치를 이용한 기법을 도입하여 엔진 구성품의 결함 위치 및 결함 정도를 예측하였다.

• 한국자동차공학회논문집
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• 제13권6호
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• pp.99-104
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• 2005

The CARB in USA has demanded OBD functions that detect any deterioration of performance of OTS as well as a simple defect of OTS which can affect emission to meet the reinforced emission regulation. In this paper, OTS plausibility monitoring functions to meet the demand from CARB are discussed. The output from OTS is used for the diagnostics of the torque converter clutch stuck and the gear ratio synchronous error. It is possible to diagnose the abnormality of OTS function by considering the oil temperature characteristics which changes according to the driving status of vehicles. In result, the OBD regulations of the CARB can be satisfied obligating car manufacturer to detect any problems in OTS functions which can affect emissions.