## 4 Multi-Module Measurement Validation of MANTiS-32
### Validation of Modal Sensing Performance of the MANTiS-32 System  
To rigorously evaluate the modal sensing performance of the MANTiS-32 wireless structural health monitoring system, a total of four MANTiS-32 units and twenty-six MANTiS-6050 accelerometers were deployed on the scaled cable-stayed bridge model. As depicted in Figure 21, twenty-four accelerometers (designated N1 through N12 on the north side and S1 through S12 on the south side) were uniformly distributed along both sides of the bridge deck, excluding 0.6 m from each end. Additionally, two reference sensors were symmetrically installed near the mid-span of the bridge deck to serve as baseline indicators. All sensor nodes were connected to their respective MANTiS-32 hubs and synchronized using integrated GPS modules. The acceleration data were transmitted in real time to a central PBM computer via a wireless AP. Data acquisition was performed continuously for 20 min at a sampling rate of 50 Hz (corresponding to a 10 ms interval), enabling verification of time synchronization among the four hubs and evaluation of potential data transmission bottlenecks. To induce low-amplitude dynamic responses appropriate for output-only modal analysis, ambient vibrations, primarily those generated by human footfalls in the vicinity, were utilized as the excitation source. This experimental setup allowed for a realistic assessment of the system's ability to capture and transmit synchronized dynamic responses from a distributed sensor network in real time.  
Real-time modal analysis was conducted on the ambient vibration data using the Time Domain Decomposition (TDD) technique, as previously demonstrated in Section 3.4.3, following the approach proposed by [PERSON] (2005) [26].  
From the measured acceleration time histories, as illustrated in Figure 22a, the cross-correlation functions between sensor signals were computed, as shown in Figure 22b. Subsequently, the Power Spectral Density (PSD) was estimated, as presented in Figure 22c, to identify the dominant frequency bands associated with the structure's natural modes. Based on the PSD peaks, the first four modal frequencies were determined to be 3.504 Hz, 4.238 Hz, 6.170 Hz, and 7.280 Hz, respectively.  
Figure 21: Sensor location of MANTiS-32 (MANTiS-6050).  
Figure 22: Dynamic response signals captured by MANTiS-6050 sensors.  
The extracted modal frequencies were identified as 3.504 Hz for the first mode, 4.238 Hz for the second, 6.170 Hz for the third, and 7.280 Hz for the fourth mode (Figure 23). When compared with the results of the FE analysis, the discrepancies were within 1.6%, demonstrating high accuracy. Moreover, all identified mode shapes were consistent with the FE analysis results, exhibiting bending mode characteristics. To quantitatively assess the similarity of the mode shapes, a Modal Assurance Criterion (MAC) analysis, as defined in Equation (2), was conducted, and the results are presented in Figure 24.  
The MAC analysis across all identified modes yielded high correlation values ranging from 90% to 99%, confirming strong agreement between the mode shapes obtained from experimental measurements and those derived from the finite element model. These findings validate the capability of the MANTiS-32 wireless sensing system to reliably acquire real-time modal parameters--both eigenvalues and eigenvectors--essential for performance-based damage assessment in PBM systems. The system demonstrated robust multi-sensor synchronization and data transmission without bottlenecks, even under complex structural configurations, affirming its suitability for high-fidelity structural health monitoring of cable-stayed bridge models.