## 3 Materials and Methods
### Noise Reduction  
Servo-hydraulic machines are known to produce AE background noise of similar frequency and amplitude to damage-related AE signals making filtering the noise a difficult process. In order to reduce the noise effects, so-called filtering methods have been developed with various approaches [13; 24; 26; 28; 34; 42; 43; 44; 45]. The methods can be classified into pre- and post-processes. Pre-process prevents noise by using mechanical damper [42] or maps the AE signal source location by using multiple sensors and collects signals from the region of interest [28]. Post-process is filtering AE signals based on specific features such as instantaneous loading [45] or partitions AE clusters [42; 43; 44]. When AE signals are distinguished by load, higher load [4; 10; 12; 26] or lower load [44; 45] is chosen for meaningful signals. As another approach, AE signals are separated by loading and unloading periods [45]. Aligned with known pre-processing noise reduction techniques, filtering of AE signals based on signal arrival times [28] and on frequency [13; 26] was attempted, but neither of these methods have proven effective for this particular test setup. Specifically, the technique of locating AE sources within the specimens based on signal arrival times between two or more sensors would allow a user to reject AE signals that emitted from sources located away from the notch. This method theoretically would allow the user to set the AE threshold at a lower level where noise signals are collected along with damage-related signals, and then the signals would be filtered based on their source location. This technique proved successful during pencil lead break tests. However, when the method was applied for during cyclic loading and the threshold was set to a level that would allow collection of noise signals, the acquisition system was overloaded and ceased to function. The noise signals and damage-related signals also proved to have indistinguishable frequency spectrums, and filtering signals based on frequency could not be simply employed. Instead, in this research attempts were made to actively limit the noise signals from propagating through the specimens and to filter identified noise-related AE signals during post processing. First, the background noise amplitude, which reached as high as 65 dB in preliminary experiments, was reduced by a mechanical damping apparatus inspired from [PERSON]'s work [42]. After testing several different materials and configurations, the final apparatus consisted of four sets of clamped,  
Figure 5: Effect of AE hit length on instantaneous, average, and weighted average entropy showing that the entropy of AE signals with longer hit lengths have lower values than shorter hit lengths while the trends between the entropies are unaffected by the hit length. 1/4 inch thick, styrene-butadiene rubber blocks and four tightly-wrapped, 1/16 inch thick, neoprene strips attached to areas between the testing grips and specimen gauge length. These elastomers, shown in Figure 4, inhibited mechanical vibration and reduced the background noise by as much as 20 dB. In the end, AE signals from the AE sensor located above the notch were used for analysis because the threshold could be set to 45 dB with ease. Signals from the lower sensor were used only to validate the upper sensor's behavior because noise signals of up to 48 dB were detected by this sensor even with the mechanical damping apparatus Thus, the amplitude threshold for the lower sensor was adjusted to 48 dB to avoid overloading the data acquisition system. In turn, the source of the AE signals could not be located but only the AE signal behavior of the upper sensor could be verified. Despite reducing the AE background noise to amplitudes below 45 dB with the mechanical damping method, AE noise signals were still collected during some tests in the upper sensor. Thus, a filtering technique based on applied load at the instant of AE signals was implemented.