Research Reports

Detection of Water and Ice on Bridge Structures by AC Impedance and Dielectric Relaxation Spectroscopy Phase II

Principal Investigator:

John F Evans

August 2013

Report no. CTS 13-25

Projects: Detection of Water and Ice on Bridge Structures by AC Impedance and Dielectric Relaxation Spectroscopy (Phase II) - FY09 NATSRL, Detection of Water and Ice on Bridge Structures by AC Impedance and Dielectric Relaxation Spectroscopy (Phase III) - FY10 NATSRL

Topics: Bridge design and sensing, Snow and ice control

During Phase I of this project, we have carried out preliminary evaluation of a novel approach to low-cost sensing systems for monitoring ice, water and deicing solutions on road bridge deck surfaces. Our 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.

Our 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 vs 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 in implemented using LabVIEW.

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