The internal micro-structure of glass and carbon fibre-reinforced polymer (FRP) rebars subjected to tensile loading was investigated using micro computed tomography (μCT) and scanning electron microscopy (SEM) images. Three dimensional (3D) and two dimensional (2D) reconstructed μCT images were used to study and quantify the void volume and its distribution along with FRP rebar samples after being subjected to tensile loads. The void volume was observed to increase in all samples as the tensile load on the samples was increased. Acoustic emission (AE) monitoring during the tensile loading was also employed to establish a correlation between the AE parameters and damage evolution in the FRP samples. Cumulative energy of AE signal in frequency domain was used to monitor the progression of the internal damage in the FRP reinforcing rebars. A high correlation was observed between the void volume measured by μCT and SEM and the cumulative energy of the AE signal.

Fibre reinforced polymer (FRP) rods are widely used as corrosion-resistant reinforcing in civil structures. However, developing a method to determine the loads on in-service FRP rods remains a challenge. In this study, the entropy of acoustic emission (AE) emanating from FRP rods is used to estimate the applied loads. As loads increased, the fraction of AE hits with higher entropy also increased. High entropy AE hits are defined using the one-sided Chebyshev’s inequality with parameter k = 2 where the histogram of AE entropy up to 10–15% of ultimate load was used as a baseline. According to the one-sided Chebyshev’s inequality, when more than 20% (k = 2) of AE hits that fall further than two standard deviations away from the mean are classified as high entropy events, a new distribution of high entropy AE hits is assumed to exist. We have found that the fraction of high AE hits. In glass FRP and carbon FRP rods, a high entropy AE hit fraction of 20% was exceeded at approximately 40% and 50% of the ultimate load, respectively. This work demonstrates that monitoring high entropy AE hits may provide a useful means to estimate the loads on FRP rods.

Acoustic emission (AE) signal has proved to be a useful tool for monitoring structures reinforced with FRP composites such as Fiber Reinforced Polymer (FRP) reinforced beams, carbon FRP (CFRP) sheets, or steel fiber reinforced concrete. This work focuses on studying the behavior of pultruded FRP bars, which have been manufactured using continuous fibers. Different configurations of CFRP and glass FRP (GFRP) bar specimens subjected to tensile load were monitored using AE technique. Several algorithms were used for signal processing to analyze AE signals in the time domain and in the time–frequency domain. The signal processing techniques extracted the amplitude, cumulative events, duration, energy, rise time, number of counts, cumulative counts, and frequency peaks of the acoustic signals. The frequency maxima were determined for different amplitude signals using short-time Fourier transform (STFT). Cumulative counts of AE signals showed significant changes in the slope during the tension test, while the stress–strain relationship of the FRP rods showed virtually no deviation from linearity. CFRP bars recorded higher amplitude signals and lower duration, than GFRP bars. The acoustic emission characteristics presented in this work show strong correlations with ultimate load and may prove useful for damage prediction.

Fibre reinforced polymer (FRP) rods have seen increasing use in civil infrastructure applications. FRP rods are corrosion resistant and are easier to handle than steel. They have been used in over 190 projects including many bridge decks and traffic barriers. However, at sufficiently high loads (more than ~25% of the ultimate load) FRP rods can become susceptible to creep failure. In addition, FRP rods have linear stress strain relationships up to failure and hence mechanical property changes to do provide a reliable indicator of failure. To study and monitor failure in FRP rods acoustic emission has been used as a diagnostic tool. Acoustic emission signals characteristics can be correlated with the level of stress within the FRP rod. For example, signal entropy has proven to be a good indicator of the stress level in glass and carbon FRP rods. However, due to the high sampling rates in AE signal acquisition, signal analysis has required post processing of signals. For longer term field and long-term laboratory studies, it is not practical to record and post process the data from the AE signals, which is produced at several megabytes per second. In this work we describe a system that uses triggered recording of the AE signals so that only the signal for a few milliseconds are logged in the vicinity of each AE event. The system is microcontroller based and allows for sampling at ~700k samples per second, with logging to SD cards. The system is suitable for deployment at a large number of nodes. Examples of the system being applied to AE monitoring of glass FRP rods will be shown. The system will be used for longterm laboratory studies of FRP rods at low load levels (less than 50% of ultimate).

Fiber reinforced polymer (FRP) rods are used for pre-stressing and reinforcing in civil engineering applications. Damage in FRP rods can lead to sudden brittle failure, therefore, a reliable method that provides indicators of damage progression and potential failure in FRP rods is highly desirable. Acoustic emission (AE) signal analysis has been used for damage detection and monitoring of FRP materials. In this study, a new AE event detection algorithm, utilizing the root mean square envelope of AE signal, is applied to AE data to isolate each AE event separately, even when AE events are nearly coincident. A fuzzy c-means (FCM) clustering algorithm is used to classify these isolated AE events into 3 clusters. Scanning electron microscopy images of FRP rod cross-sections also show 3 types of damage. The hypothesis in this study is that each cluster represents a damage mechanism. The number of events in each cluster is monitored versus the percent of the ultimate load. The ratio of the number of AE events in one of the FCM clusters to the number of AE events in another FCM cluster was useful for providing an indication of when the stress levels have reached the point where the loads may cause the FRP rod to fail. The results of applying this parameter to four FRP rods show a significant slope change (factor of 10) in this ratio at around 40% and 60% of the ultimate load for glass FRP rods and carbon FRP rods, respectively. This method may prove useful in damage progression and failure prediction of the FRP rods in prefabricated structures where pre-stressed FRP is used and in field monitoring of FRP materials.