An optic-fiber based dynamic pressure sensor is described here to measure weight-in-motion of vehicles. In the research reported herein, a Michelson interferometer with specially designed hardware and software were developed and experimentally subjected to dynamic compressive loads of different magnitudes, and loading rates. Experiments showed that both output fringe number and fringe period could be used to indicate the dynamic load. A calibration technique was put forward to calibrate the sensor. Both the dynamic weight and static weight of the vehicle passed can be obtained. The findings that resulted from these studies developed an understanding for the behavior of interferometer sensor under dynamic compressive states of stress and are fundamental to the application of fiber optic sensors for the monitoring of truck vehicle weights while in motion.

Adopting wide-band Lamb wave based active monitoring technology, this study focuses on a neural network method based on a new damage signature for on-line damage detection applied to thin-walled composite structures. Honeycomb sandwich and carbon fiber composite structures are studied. Two kinds of damage are considered: delamination and impact damage. A new damage signature is introduced to determine the presence and extent of damage in composites, while eliminating the influence of different distances between the actuator and sensor. Neural network method is researched to take advantage of this new damage signature combined with several other signatures to decide the damage mode. Kohonen neural network is developed. The proposed method is shown to be effective, reliable, and straightforward for the specimens considered in the present study, which are composed of ifferent materials and suffer various levels of damage.

A reliable understanding of the properties of 3-D braided composites is of primary importance for the successful utilization of these materials. A new method is introduced to study the mechanical performance of braided composite materials using embeddedoptic fiber sensors. Experimental research is performed to devise a method of incorporating the optic fiber into a 3-D braided composite structure. The efficacy of this new testing method is evaluated on two counts. First, the optical performance of the optic fiber is studied before and after incorporation into the 3-D braided composites, as well as after completion of the manufacturing process for the 3-D braided composites, to validate the ability of the optic fiber to survive the manufacturing process. On the other hand, the influence of incorporated optic fiber to the original braided composite is also researched by tension and compression experiments. Second, two kinds ofoptic fiber sensors are co-embedded into 3-D braided composites to evaluate their respective ability to measure internal strain. Experimental results show that multipleoptic fiber sensors can be co-braided into the 3-D braided composites to determine its internal strain which is difficult to be fulfilled by other current existing methods.

Damage characterization takes place by comparing single mode sensor signals collected before and after the damage event. By subtracting the signals of both conditions from each other, a scatter signal is produced which can be used for damage localization. By using Gabor wavelet to analyze single mode Lamb wave recorded before damage and scatter signal, the difference of time-of-flight can be obtained. Combining with the ellipse technique, the localization experiment on fiberglass plate of dimension 100

This study focuses on an active monitoring method for damage detection applied to composite structures. Honeycomb sandwich and carbon fiber composite structures are studied. Two kinds of damage are considered: delamination and impact damage. Wavelet analysis methods are adopted to postprocess the raw monitored signal. A new damage signature is introduced to determine the presence and extent of damage in composites, while eliminating the influence of different distances between the active actuator and active monitoring elements. The proposed method is shown to be effective, reliable, and straightforward for the specimens considered in the present study, which are composed of different materials and suffer various levels of damage. An online real-time active monitoring system for damage detection is described that is based on this research.