400 Townsend Drive
400 Townsend Drive
Liu W.,Michigan Technological University |
Chen B.,400 Townsend Drive |
Swartz R.A.,400 Townsend Drive
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2011
This paper compares the performance of various feature extraction methods applied to structural sensor measurements acquired in-situ, from a decommissioned bridge under realistic damage scenarios. Three feature extraction methods are applied to sensor data to generate feature vectors for normal and damaged structure data patterns. The investigated feature extraction methods include identification of both time domain methods as well as frequency domain methods. The evaluation of the feature extraction methods is performed by examining distance values among different patterns, distance values among feature vectors in the same pattern, and pattern recognition success rate. The test data used in the comparison study are from the System Identification to Monitor Civil Engineering Structures (SIMCES) Z24 Bridge damage detection tests, a rigorous instrumentation campaign that recorded the dynamic performance of a concrete box-girder bridge under progressively increasing damage scenarios. A number of progressive damage test case data sets, including undamaged cases and pier settlement cases (different depths), are used to test the separation of feature vectors among different patterns and the pattern recognition success rate for different feature extraction methods is reported. © 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).
Williams D.B.,University of Bristol |
Thomas H.E.,400 Townsend Drive
Geomatics, Natural Hazards and Risk | Year: 2011
Explosive volcanic eruptions have the potential to inject gases including sulphur dioxide (SO 2) and silicate ash into the upper and lower stratospheres, which not only has climatic implications but also poses a significant hazard for aircraft flying at these altitudes. The effects of volcanic ash on engines and the main airframe are well documented and although the effects of acidic gases on aircraft are less well known, both species have the potential to result in both hazardous and extremely costly damage. The 2009 eruption of Sarychev Peak, Kuril Islands, affected a large number of flights in the busy North Pacific (NOPAC) region. Here we observe the differential transportation of ash and SO 2 using the satellitebased sensors Atmospheric Infrared Sounders (AIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS), highlighting both the usefulness and limitations of these sensors and comparing the observed data to the predicted ash dispersion from the National Oceanic and Atmospheric Administration (NOAA) Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. Data are displayed using Google Earth, which allows a visual representation of the two species in relation to aircraft flight paths in the region, thus allowing an assessment of the threat to aviation due to this eruption. © 2011 Taylor & Francis.
Pacella N.,400 Townsend Drive |
Derouin A.,400 Townsend Drive |
Pereles B.,400 Townsend Drive |
Ghee Ong K.,400 Townsend Drive
Smart Materials and Structures | Year: 2015
The magnetoelastic sensor is a wireless, passive sensor platform typically comprised of a strip of magnetoelastic material that exhibits a mechanical vibration when under the excitation of a magnetic ac field. At the resonant frequency, the vibration of the sensor is most prominent, generating a significant secondary magnetic field that can be detected with a remotely located coil. Biological and chemical sensing can be realized by functionalizing a mass- or elasticity-changing coating on the magnetoelastic sensor, causing a shift in the resonant frequency when exposed to the target analyte. To date, most magnetoelastic sensors are rectangular and are designed to sense a uniform coating over the entire sensor surface. This paper presents a new magnetoelastic sensor design with higher sensitivity, achieved by applying non-uniform coatings and altering the sensor to a triangular shape. In addition, the new design allows the magnetoelastic sensor to form a sensor array that requires only a fraction of sample volume for multi-parameter sensing compared to the current sensor design. © 2015 IOP Publishing Ltd.