Abstract
This paper presents a systematic investigation of the effect of sensor location on the data quality and
subsequently, on the effectiveness of machine health monitoring. Based on an analysis of the signal propagation
process from the defect location to the sensor, numerical simulations using finite element modeling were
conducted on a bearing test bed to determine the signal strength at several representative sensor locations. The
results showed that placing sensors closely to the machine component being monitored is critical to achieving high
signal-to-noise ratio, thus improving the data quality. Using millimeter-sized piezoceramic plates, the obtained
results were evaluated experimentally. A comparison with a set of commercial vibration sensors verified the
developed structural dynamics-based sensor placement strategy. It further demonstrated that the proposed shock
wave-based sensing technique provided an effective alternative to vibration measurement, while requiring less
space for sensor installation.
Key Words
sensor placement strategy; embedded sensor design; shock wave-based sensing; bearing condition
monitoring; finite element modeling.
Address
Robert X. Gao and Shuangwen Sheng
Dept of Mechanical and Industrial Eng., Univ. of Massachusetts, Amherst, MA 01003, USA
Changting Wang
Global Research Center, General Electric Corporation, Niskayuna, NY 12309, USA
Abstract
A new design of distributed crack sensors based on the topological change of transmission line
cables is presented for the condition assessment of reinforced concrete (RC) structures during and immediately
after an earthquake event. This study is primarily focused on the performance of cable sensors under dynamic
loading, particularly a feature that allows for some ?emory?of the crack history of an RC member. This feature
enables the post-earthquake condition assessment of structural members such as RC columns, in which the
earthquake-induced cracks are closed immediately after an earthquake event due to gravity loads, and are visually
undetectable. Factors affecting the onset of the feature were investigated experimentally with small-scale RC
beams under cyclic loading. Test results indicated that both crack width and the number of loading cycles were
instrumental in the onset of the memory feature of cable sensors. Practical issues related to dynamic acquisition with
the sensors are discussed. The sensors were proven to be fatigue resistant from shake table tests of RC columns. The
sensors continued to show useful performance after the columns can no longer support additional loads.
Key Words
nondestructive testing; sensors; crack detection and localization; shake table tests; post-disaster
condition assessment.
Address
Genda Chen and Ryan McDaniel
Dept. of Civil, Architectural & Environmental Engineering, Univ. of Missouri-Rolla, Rolla, Missouri, USA
Shishuang Sun, David Pommerenke and James Drewniak
Dept. of Electrical and Computer Engineering, Univ. of Missouri-Rolla, Rolla, Missouri, USA
Abstract
The paper intends to summarize some guidelines for future smart structure system application in
military aircraft. This preview of system integration is based upon a review on approximately one and a half
decades of application oriented aerospace related smart structures research. Achievements in the area of structural
health monitoring, adaptive shape, adaptive load bearing devices and active vibration control have been reached,
potentials have been identified, several feasibility studies have been performed and some smart technologies have
been already implemented. However the realization of anticipated visions and previously initial timescales
announced have been rather too optimistic. The current development shall be based on a more realistic basis
including more emphasis on fundamental aircraft strength, stiffness, static and dynamic load and stability
requirements of aircraft and interdisciplinary integration requirements and improvements of integrated actors,
actuator systems and control systems including micro controllers.
Key Words
health monitoring systems; equipment vibration alleviation; dynamic load/vibration suppression;
semi active variable stiffness; passive and active aerodynamic shape/contour control.
Address
J. Becker
EADS Deutschland GmbH, Military Aircraft, 81663 Munchen, and Technical Univ. of Munich, Institute of Fluidmechanic, Germany
W. Luber, J. Simpson and K. Dittrich
EADS Deutschland GmbH, Military Aircraft, 81663 Munchen, Germany
Abstract
Advanced signal processing techniques have been long introduced and widely used in structural
health monitoring (SHM) and nondestructive evaluation (NDE). In our research, we applied several signal
processing approaches for our embedded ultrasonic structural radar (EUSR) system to obtain improved damage
detection results. The EUSR algorithm was developed to detect defects within a large area of a thin-plate
specimen using a piezoelectric wafer active sensor (PWAS) array. In the EUSR, the discrete wavelet transform
(DWT) was first applied for signal de-noising. Secondly, after constructing the EUSR data, the short-time
Fourier transform (STFT) and continuous wavelet transform (CWT) were used for the time-frequency analysis.
Then the results were compared thereafter. We eventually chose continuous wavelet transform to filter out from
the original signal the component with the excitation signal? frequency. Third, cross correlation method and
Hilbert transform were applied to A-scan signals to extract the time of flight (TOF) of the wave packets from
the crack. Finally, the Hilbert transform was again applied to the EUSR data to extract the envelopes for final
inspection result visualization. The EUSR system was implemented in LabVIEW. Several laboratory
experiments have been conducted and have verified that, with the advanced signal processing approaches, the
EUSR has enhanced damage detection ability.
Key Words
signal processing; wavelet transform; short-time Fourier transform; Hilbert transform; crosscorrelation;
damage detection; phased array; piezoelectric sensor; NDE, SHM.
Address
Lingyu Yu and Victor Giurgiutiu
Mechanical Engineering Department, University of South Carolina Columbia, SC 29208, USA
Abstract
Elastic and electromagnetic waves can be used to gather important information about particulate
materials. To facilitate smart geophysical characterization of particulate materials, their fundamental properties are
discussed and experimental procedures are presented for both elastic and electromagnetic waves. The first
application is related to the characterization of particulate materials using shear waves, concentrating on changes
in effective stress during consolidation, multi-phase phenomena with relation to capillarity, and microscale
characteristics of particles. The second application involves electromagnetic waves, focusing on stratigraphy
detection in layered soils, estimation of void ratio and its spatial distribution, and conduction in unsaturated soils.
Experimental results suggest that shear waves allow studying particle contact phenomena and the evolution of
interparticle forces, while electromagnetic waves give insight into the characteristics of the fluid phase and its
spatial distribution.