# Entropy Wavelet-Based Method to Increase Efficiency in Highway Bridge Damage Identification
## 5 Experimental Results and Analysis  
Following the experimental procedure described in Section 2.2, as well as the damage detection methodology presented in Section 3.3, the entropy-CWT diagram is obtained for the analyzed damaged case (removed cable) and compared with the healthy scenario. Thus, the average SEI for the CWT coefficients considering all measurement points (sensors S1-S12 in Figure 4) is plotted in just a few seconds. In order to provide some examples of the type of experimental signals acquired/analyzed, in Figure 27, the experimental time-domain signals acquired from the RPB considering the total time duration of 1800 s for each sensor of the two scenarios (healthy and damaged RPB) are shown, whereas, in Figure 28, the corresponding entropy-CWT diagram for the damaged case is presented. As can be observed in Figure 28, the useful scale range, used to conduct the analysis and identify damage, is similar to the numerical cases. Therefore, for this experimental case, the scale range considered is from 200 onwards (200 to 1000). Subsequently, all the signals for the healthy and damaged cases are filtered and extended, taking into account the same type of filter and the parameters used for the numerical cases. After that, the average CWT coefficients for the scale range from 200 to 1000 are calculated for each of the 30 segments of 1 min for each sensor of the healthy bridge (12 sensors) and the damaged bridge (12 sensors). Lastly, the maximum value of the average CWT coefficients for the 720 files are registered; finally, for each sensor of each condition (healthy and damaged), a unique value of the maximum CWT coefficient is obtained considering the average of the 30 respective maximum values of each sensor/condition. These final maximum average values are indicated in Figure 29 thought solid circles, while  
Figure 26: Average CWT coefficients for the scale range from 181 to 1000 from the respective average of 3 measurement points (25%, 50%, and 75% of L) with signals filtered from noisy signals (15% Gaussian noise), extended to remove edge effects. Scenarios shown: healthy bridge and bridge with intermediate severity damage (30% intensity) at 75% L.  
the corresponding minimum and maximum values obtained for the respective 30 tests of each case are indicated with horizontal solid lines. Figure 27: Experimental time-domain signals acquired from the real-life RPB, considering the total time duration of 1800 s for each sensor (Sensor 1-Sensor 12) of the following two scenarios: (**a**) healthy RPB, and (**b**) damaged RPB with a removed cable. Thus, in the corresponding results presented in Figure 29, it is possible to observe that, for the damage case, the maximum value of the average CWT coefficients (solid circle) corresponds clearly with sensor S5, whose position on the bridge deck is the same as that of the lower anchoring of the removed cable. On the other hand, if the respective results of the healthy case are compared with the ones of the damaged cases, it is evident that the maximum values of the average CWT coefficients are always higher for the damaged cases. Moreover, there is also a clear tendency that, even when considering the minimum and maximum values obtained for each set of 30 tests, the CWT coefficients are much higher for the damaged RPB, and particularly for the sensor located in the position of damage (S5). Regardless of whether the experimental validation of a controlled test was not possible with the same conditions as the numerical simulations (just one vehicle crossing the bridge with a specific weight and a specific constant speed) or, conversely, whether the transit was random, the experimental results show good agreement with the numerical results, and they were obtained as fast as the numerical results were, thus validating and highlighting the advantages of this new method, focused mainly on the good precision, low computational burden, efficient obtaining of results, and low cost.