Investigating Feasibility of Drive-by Bridge Monitoring by Laboratory Experiments

A potentially powerful drive-by bridge inspection approach was proposed to inspect bridge conditions utilizing the vibrations of a test vehicle while it passes over the target bridge. This approach suffers from the effect of roadway surface roughness and two solutions were proposed in previous studies: one is to subtract the responses of two vehicles (time-domain method) before spectral analysis and the other one is to subtract the spectrum of one vehicle from that of the other (frequency-domain method). Although the two methods were verified theoretically and numerically, their practical effectiveness is still an open question.Furthermore, whether the outcome spectra processed by those methods could be used to detect potential bridge damage is of our interests. In this study, a laboratory experiment was carried out with a test tractor-trailer system and a scaled bridge. It was observed that, first, for practical applications, it would be preferable to apply the frequency-domain method, avoiding the need to meet a strict requirement in synchronizing the responses of the two trailers in time domain; second, the statistical pattern of the processed spectra in a specific frequency band could be an effective anomaly indicator incorporated in drive-by inspection methods.

Achievable rates and outage probability of cognitive radio with dynamic frequency hopping under imperfect spectrum sensing

In this study, the authors propose simple methods to evaluate the achievable rates and outage probability of a cognitive radio (CR) link that takes into account the imperfectness of spectrum sensing. In the considered system, the CR transmitter and receiver correlatively sense and dynamically exploit the spectrum pool via dynamic frequency hopping. Under imperfect spectrum sensing, false-alarm and miss-detection occur which cause impulsive interference emerged from collisions due to the simultaneous spectrum access of primary and cognitive users. That makes it very challenging to evaluate the achievable rates. By first examining the static link where the channel is assumed to be constant over time, they show that the achievable rate using a Gaussian input can be calculated accurately through a simple series representation. In the second part of this study, they extend the calculation of the achievable rate to wireless fading environments. To take into account the effect of fading, they introduce a piece-wise linear curve fitting-based method to approximate the instantaneous achievable rate curve as a combination of linear segments. It is then demonstrated that the ergodic achievable rate in fast fading and the outage probability in slow fading can be calculated to achieve any given accuracy level.