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A Wireless Ultrasonic Guided Wave Structural Health Monitoring System for Aircraft Wing Inspection

AIP Conference Proceedings 2007年第1期894卷 1548-1555页

作者： X. Zhao T. Qian Z. Popovic R. Zane G. Mei C. Walsh T. Paing C. Kwan 1Intelligent Automation Inc. 15400 Calhoun Drive Rockville MD 20855 2Department of Electrical and Computer Engineering University of Colorado at Boulder Boulder Colorado 80309

A wireless, in‐situ ultrasonic guided wave structural health monitoring (SHM) system was developed and tested for aircraft wing inspection. It applies small, low cost and light weight piezoelectric (PZT) disc transducer network bonded to the surface of a structure, and an embedded miniature diagnosis device that can generate 350 kHz, 70 V peak‐to‐peak tone‐burst signal; collect, amplify and digitize multiple channel ultrasonic signals; and process the data on‐board and transfer them wirelessly to a ground station. The whole system could be powered by an X‐band microwave rectenna that converts illuminating microwave energy into DC. The data collected with this device are almost identical with those collected through a direct‐wire connection.

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Measurement of Local Strain Distribution of Austenitic Stainless Steels by Using Magnetic Sensors

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AIP Conference Proceedings 2006年第1期820卷 1261-1268页

作者： Y. Tsuchida M. Oka T. Yakushiji M. Enokizono 1Department of Electrical and Electronic Engineering Oita University 700 Dannoharu Oita 870‐1192 Japan 2Department of Computer and Control Engineering Oita National College of Technology 1666 Maki Oita 870‐0152 JAPAN

Austenitic stainless steel is classified as a nonmagnetic material. However application of stress transforms the plastic part of it into a martensitic crystal structure and it takes on magnetization. Strain evaluation can be performed by measuring the leakage magnetic flux from the remanent magnetization after applying stress to austenitic stainless steels. This paper presents the measurement to make clear the distributions of the leakage magnetic flux after applying strain into austenitic stainless steels by magnetic sensors.

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Water shock Hugoniot measurement up to less than 1 GPa

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AIP Conference Proceedings 2000年第1期505卷 65-68页

作者： Kunihito Nagayama Yasuhito Mori Katsuya Shimada Motonao Nakahara 1Department of Aeronautics and Astronautics Graduate School of Engineering Kyushu University Hakozaki Fukuoka 812-8581 Japan 2Department of Computer and Communication Engineering Faculty of Engineering Fukuoka Institute of Technology Fukuoka 811-0295 Japan

Shock Hugoniot compression curve for water has been measured up to less than 1 GPa. Plane and steady shock wave is produced in water by the flat plate impact of a projectile accelerated up to 500m/s by a compressed gas gun. To measure shock Hugoniot in this pressure range in higher precision, a new experimental procedure was proposed, which is based on the very large pressure dependence of the refractive index of water upon compression. By using this method, shock compression curve was determined. It was confirmed that within the pressure range covered in this experiment, shock-particle velocity Hugoniot can be described by a linear relation with a large slope. Shock temperature was calculated by using the obtained Hugoniot data combined with the values of thermodynamical variables.

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Measuring the Functioning Human Brain

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Statistics and Its Application 1000年第1期12卷 283-309页

作者： Martin A. Lindquist Bonnie B. Smith Arunkumar Kannan Angela Zhao Brian Caffo 1Department of Biostatistics Johns Hopkins University Baltimore Maryland USA email: mlindqui@jhsph.edu 2Department of Electrical and Computer Engineering Johns Hopkins University Baltimore Maryland USA

The emergence of functional magnetic resonance imaging (fMRI) marked a significant technological breakthrough in the real-time measurement of the functioning human brain in vivo. In part because of their 4D nature (three spatial dimensions and time), fMRI data have inspired a great deal of statistical development in the past couple of decades to address their unique spatiotemporal properties. This article provides an overview of the current landscape in functional brain measurement, with a particular focus on fMRI, highlighting key developments in the past decade. Furthermore, it looks ahead to the future, discussing unresolved research questions in the community and outlining potential research topics for the future.

关键词： fMRI functional magnetic resonance imaging brain connectivity prediction resting-state fMRI statistics

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Enhancing accuracy of data acquired by a laser vibrometer in a field setting

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AIP Conference Proceedings 2002年第1期615卷 2013-2019页

作者： E. S. Sazonov P. Klinkhachorn H. V. S. GangaRao U. B. Halabe 1Lane Department of Computer Science and Electrical Engineering West Virginia University Morgantown West Virginia 26506 2Department of Civil and Environmental Engineering Constructed Facilities Center West Virginia University Morgantown West Virginia 26506

The Laser Doppler Vibrometers (LDVs) have gained increased popularity among researchers and practitioners. However, LDVs suffer from their dependency on the optical properties of the surface and sensitivity to external interference that may be easily controlled in the laboratory environment. Applying an LDV to large structures in field setting poses new challenges. This paper considers the problems that were encountered during the design of an automated damage detection system for the Armored Vehicle Launched Bridge and solutions that were applied to enhance the accuracy of the acquired data.

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Evaluation of Fiber Optic Strain Measurement System for Monitoring FRP Bridge Decks

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AIP Conference Proceedings 2005年第1期760卷 1485-1492页

作者： P. Klinkhachorn G. M. Lonkar Udaya B. Halabe H. V. S. GangaRao 1Lane Department of Computer Science and Electrical Engineering West Virginia University Morgantown WV 26505‐6109 2Department of Civil and Environmental Engineering Constructed Facilities Center West Virginia University Morgantown WV 26505‐6103

The use of Fiber Optic sensors for structural monitoring applications has attained popularity among researchers and practitioners recently due to their immense advantages. This paper discusses a continuous structural monitoring technique using surface mounted and embedded fiber optic strain sensors to measure the strain in FRP bridge decks. An Extrinsic Fabry‐Perot Interferometric (EFPI) strain sensor was selected for evaluation as it offers a good compromise between accuracy and cost considerations. This EFPI strain sensor, along with a conventional strain gauge, was surface mounted on a FRP bridge decks. The decks were then subjected to an accelerated aging test in an environmental chamber and the performance of both the strain sensors was recorded for a performance comparison. The results from the seven months of accelerated aging that is equivalent to 10 years of actual life show that the strain gauge sensor and the EFPI Fiber Optic sensor are still in working condition. The EFPI fiber optic sensor detects minute and sudden changes in strain more effectively than the strain gauge sensor. Placement in the environmental chamber did not affect the EFPI sensor’s performance and is an indication of its applicability to field structural monitoring for lengthy periods of time. The second part is a preliminary work where a fiber optic sensor was embedded inside a FRP plate during the pultrusion process. This shows the feasibility of manufacturing FRP bridge decks with embedded fiber optic sensors.

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An automated damage detection system for armored vehicle launched bridge

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AIP Conference Proceedings 2002年第1期615卷 1326-1333页

This paper presents an overview of an automated damage detection system for the Armored Vehicle Launched Bridge (AVLB). The system utilizes a non-contact laser vibrometer mounted on a computer-controlled robotic gantry as the measurement sensor. Acquired data is automatically processed to obtain strain energy mode shapes, which are used as the damage indicator. The analysis of the strain energy mode shapes is performed by a fuzzy expert system. This system was successfully tested on a full-scale AVLB with different damage scenarios.

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Automatic Detection of Subsurface Defects Using Infrared Thermography

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AIP Conference Proceedings 2005年第1期760卷 1469-1476页

作者： G. M. Lonkar P. Klinkhachorn Udaya B. Halabe H. V. S. GangaRao 1Lane Department of Computer Science and Electrical Engineering West Virginia University Morgantown WV 26505‐6109 2Department of Civil and Environmental Engineering Constructed Facilities Center West Virginia University Morgantown WV 26505‐6103

The popularity of FRP bridge decks has increased in recent times because of their high strength to weight ratio, fatigue resistance etc. Defects due to degradation of the bridge deck malign their properties and adversely affect the structural integrity. These defects need to be detected and continuously monitored using field techniques such as infrared thermography. The process of manually analyzing the infrared images is tedious and ambiguous. Instead, using software algorithms on the infrared images of FRP decks can increase the defect detection speed and accuracy. This paper proposes a software automated defect detection technique to detect subsurface anomalies in fiber reinforced polymer (FRP) bridge decks. Thermal images of the FRP decks were captured using a radiometric infrared camera. Software algorithms using morphological image processing and fuzzy clustering techniques were developed to analyze the images for detecting the defects automatically. They were tested on infrared images of FRP bridge decks prepared in the laboratory. In the tests conducted, simulated subsurface defects of varying size, thickness and wearing surfaces were fabricated in the laboratory. The tests include a performance analysis of detecting delaminations and debonds, and the effect of distance on the detecting ability of the algorithm. The algorithms were also tested with FRP deck specimens under solar radiation, to test the response under a passive heat source. The study showed that Infrared Thermography can be effectively used to detect subsurface defects and the process can be automated with substantial accuracy.

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Real Time Detection of Defects in GFRP Bridge Decks Using Infrared Thermography

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AIP Conference Proceedings 2006年第1期820卷 1640-1647页

作者： P. Klinkhachorn G. M. Lonkar Udaya B. Halabe Hota V. S. GangaRao 1Lane Department of Computer Science and Electrical Engineering West Virginia University Morgantown WV 26505‐6109 2Department of Civil and Environmental Engineering Constructed Facilities Center West Virginia University Morgantown WV 26505‐6103

This work is aimed at building a real time system to detect subsurface defects in GFRP bridge decks using infrared thermography. The issues addressed are: (a) development of a real time defect detection system, and (b) image mosaicking to build a composite image map. In the tests conducted, a turn key system was built in Matlab environment using the FLIR SDK to acquire image from the ThermaCAM S60 infrared camera. The images were then analyzed by defect detection algorithms. Efforts were made to minimize the time to detect defects in a captured image. In the second phase, image mosaicking was used to build a “composite image” that combines all the infrared images to form a single image. The location of defects in the “composite image” leads to a system that will be able to point out defects in the bridge as a whole. The study creates a base that can be used for real time defect detection in GFRP bridge decks.

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Unmanned Ground Vehicle for Autonomous Non‐Destructive Testing of FRP Bridge Decks

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AIP Conference Proceedings 2007年第1期894卷 1723-1730页

作者： P. Klinkhachorn A. Scott Mercer Udaya B. Halabe Hota V. S. GangaRao 1Lane Department of Computer Science and Electrical Engineering West Virginia University Morgantown WV 26505‐6109 2Department of Civil and Environmental Engineering Constructed Facilities Center West Virginia University Morgantown WV 26505‐6103

Current non‐destructive techniques for defect analysis of FRP bridge decks have a narrow scope. These techniques are very good at detecting certain types of defects but are not robust enough to detect all defects by themselves. For example, infrared thermography (IRT) can detect air filled defects and Ground Penetrating Radar (GPR) is good at detecting water filled ones. These technologies can be combined to create a more robust defect detection scheme. To accomplish this, an Unmanned Ground Vehicle (UGV) has been designed that incorporates both IR and GPR analysis to create a comprehensive defect map of a bridge deck. The UGV autonomously surveys the deck surface and acquires data. The UGV has two 1.5 GHz ground coupled GPR antennas that are mounted on the front of the UGV to collect GPR data. It also incorporates an active heating source and a radiometric IR camera to capture IR images of the deck, even in less than ideal weather scenarios such as cold cloudy days. The UGV is designed so that it can collect data in an assembly line fashion. It moves in 1 foot increments. When moving, it collects GPR data from the two antennas. When it stops it heats a section of the deck. The next time it stops to heat a section, the IR camera is analyzing the preheated deck section while preparing for the next section. Because the data is being continually collected using this method, the UGV can survey the entire deck in an efficient and timely manner.

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