Wireless Structural Monitoring Under Real-World Constraints: Quantifying the Impact of Data Loss and Time Synchronization Errors on Damage Detectability - Wei Zhang Wei Zhang; Liang Chen Liang Chen (Techne: Journal of Engineering, Technology and Industrial Applications, 2025)
This article develops a quantitative, engineering-oriented framework to evaluate how data loss and synchronization errors propagate through an operational monitoring pipeline and influence damage detectability, false alarm rate, and time-to-detection under rolling decision windows. The study models both independent packet loss and burst loss, represents synchronization error as a combination of clock drift and jitter, and assesses their effects on frequency-domain indicators, operational modal analysis outputs, and multivariate damage indices calibrated under false-alarm constraints. Using generic structural archetypes that represent common civil and building dynamics, the results show that (i) moderate average packet loss can be tolerated when loss is approximately independent, but comparable loss rates become materially harmful under bursty conditions because they reduce effective record length and degrade spectral averaging, (ii) synchronization jitter introduces phase inconsistency that disproportionately damages cross-sensor coherence and mode-shape estimation, causing multivariate indicators to lose discriminative power even when single-sensor frequency estimates remain stable, (iii) combined loss and timing errors can shift optimal thresholds and inflate nuisance alarms unless baseline distributions are constructed under matching network conditions, and (iv) mitigation strategies such as local buffering, time-stamping discipline, drift correction, and modest redundancy can recover most decision performance at far lower cost than upgrading sensors alone. The findings translate into practical design rules for wireless SHM deployments, including allowable loss and timing budgets as functions of the monitored frequency band, window length, and decision criticality, thereby supporting reliability-aware monitoring architectures suitable for applied engineering practice.