Detection of Water and Ice on Bridge Structures by AC Impedance and Dielectric Relaxation Spectroscopy (Phase III) - FY10 NATSRL

Principal Investigator:

John Evans, Professor, UMD-Chemistry and Biochemistry

Project Summary:

In the interest of improved public safety, researchers are developing low-cost sensing systems to monitor surface conditions on bridge and road decks. During Phase I of this project, the researchers conducted preliminary evaluation of a novel approach to low-cost sensing systems for monitoring ice, water, and deicing solutions on road bridge deck surfaces. Initial approaches included the techniques of alternating current impedance and dielectric relaxation spectroscopy of responses from simple passive metal sensors. These preliminary results indicated that the second approach of dielectric relaxation spectroscopy was far more promising. Furthermore, likely implementations would be significantly more economical using lower-cost electronics modules connected to passive sensors.

The choice for implementation of dielectric relaxation spectroscopy is based on the measurement of high-frequency components of pulse waveforms reflected from the sensor and using time domain reflectometry (TDR). The information content of these waveforms is strongly influenced by the dielectric properties of the media of interest (ice, water, or aqueous solutions of deicing chemicals) in contact with or in close proximity (microns) with passive metal conductors, which comprise the sensor. These high-frequency dielectric relaxation measurements using TDR probe the physical state of precipitation and deicing chemicals on the deck or road surface by the detailed examination of the frequency response waveforms returned after the application of a fast rise-time excitation pulse. Signal processing of the acquired waveforms involves taking the derivative of the response followed by digital filtering and subsequent wavelet analysis to emphasize and distinguished low- versus high-frequency components of the waveforms reflected from the sensors.

Determination of the state and nature of the precipitation, solutions, or air in contact with a given sensor is made on a statistical basis via correlation of responses to calibration waveforms collected under known conditions for a given sensor. The software to carry out these signal processing tasks is implemented using LabVIEW.

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