2.3.1. Remote Monitoring at the Crane Maintenance Area

Remote monitoring at the Crane Maintenance Location was performed from 10 September 2014 (commencement of test) through 25 August 2015. A cellular connection was utilized to remotely operate the wired system. Data loss due to a power outage at the system occurred between 18 December 2014 and 20 January 2015. The raw data was analyzed and appropriate filters were used to reject data arising from signals not related to the initiation or the growth of cracks such as wave reflections. The filters are primarily parameter-based filters that were developed based on visual inspection of AE waveforms, which is similar to those described in ElBatanouny et al. (2014a). The first is a Duration-Amplitude filter (D-A), which is also referred to as a Swansong II type filter, while the second is a Rise Time-Amplitude filter (R-A), which is described in Table 2. Additional filters known as Duration and RMS filters were developed during this study to minimize electrical noise. The additional filters were developed based on data collected from the concrete block discussed in the following sections.


**Table 2.** Data rejection limits.

Figures 5 and 6 show the AE activity detected at the three monitored locations in the crane maintenance area for the resonant and broadband sensors, respectively. As shown in the figures, AE activity at the locations associated with visually observable damage ('vertical column to roof interface location' and 'horizontal beam location') was significantly higher than the AE activity at the control location. This indicates that the filters used were suitable for this application and also that intrinsic noise such as that potentially caused by electro-magnetic interference is not an obstacle for this application. The relatively high levels of AE activity indicate that damage (corrosion and related cracking) associated with the aging of reinforced concrete is progressing at the vertical column to roof interface and the horizontal beam locations.

Rain and temperature data were provided by SRNL to investigate the effect of environmental conditions on AE activity. Seasonal temperature fluctuations affected the data more significantly than daily temperature fluctuations. This may be attributed to the low coefficient of thermal expansion of concrete, which causes volumetric changes to be associated with prolonged exposure to temperature differentials. As a general statement, increased AE activity was recorded when temperatures decreased during the winter months. Rain events were not as closely correlated to AE activity as were temperature fluctuations. However, associated moisture and repeated wet/dry cycling from rain events may lead to acceleration of the degradation process. During one of the site visits, remnants of a crack sealing material were found on the floor of the 105-C building, which indicates one potential source of moisture intrusion in this area.

**Figure 5.** Amplitude and temperature versus time for resonant sensors: (**a**) Vertical column to roof interface location, (**b**) horizontal beam location, (**c**) control location, and (**d**) rain versus time.

**Figure 6.** Amplitude and temperature versus time for broadband sensors: (**a**) Vertical column to roof interface location, (**b**) horizontal beam location, (**c**) control location, and (**d**) rain versus time.

The wired AE system was inactive between 18 December 2014 and 20 January 2015 due to a moisture-related event that adversely affected the laptop. Sensors corresponding to channels 9 and 11 (both at the vertical column to roof interface location) detached from the concrete surface on 27 November 2014 and 23 November 2014, respectively. Localized spalling that occurred at these locations during this time period is presumed to be the cause of the detachment. Both sensors were reattached on 8 April 2015.

Three seismic events occurred during the monitoring period: 14 September 2014 (M2.2), 19 September 2014 (M2.6), and 22 May 2015 (M1.96). Close inspection of data collected during this period did not reveal a correlation between these events and the AE data. Referring to the definition of acoustic emission (transient stress waves caused by a rapid release of energy within a material, [13], AE sensors would potentially be capable of detecting crack growth events caused by a seismic event provided the crack growth event or events that occurred within the range of sensitivity of the sensors. In the application at 105-C, the range of sensitivity for minor crack growth events (similar in energy to that caused by a pencil lead break) is in the range of 3 to 10 feet from each sensor. Due to the frequency range of AE sensors (30 kHz to 300 kHz), the sensors are not sensitive to global structural vibrations such as those potentially related to seismic activity.
