سال انتشار: ۱۳۹۱
محل انتشار: دومین کنفرانس بین المللی آکوستیک و ارتعاشات
تعداد صفحات: ۸
Touraj Taghikhany – Assistant Professor, Civil Engineering, Amirkabir University of Technology, Tehran, Iran,
Mohsen Tehranizadeh – Professor, Civil Engineering, Amirkabir University of Technology, Tehran, Iran,
Nastaran Dabiran – MSc student, Civil Engineering, Amirkabir University of Technology, Tehran, Iran,
Abouzar Dolati –
Structural health monitoring (SHM) is an emerging field in civil engineering, offering the poten-tial for continuous and periodic assessment of the safety of civil structures; and therefore industrial-ized nations have an intense exertion in this field, on which our lives rely. SHM of civil engineering structures faces with many impediments on installation and maintenance of wired systems. However, wireless smart sensor network (WSSN) can effectively remove the disadvantages associated with current wire-based sensing systems. WSSN recorded data sets may have relative time-delays due to interference in radio transmission or inherent internal sensor clock errors. For structural system iden-tification and damage detection purposes, sensor data require that they are time synchronized. In this study, the application of auto-regressive moving average vector (ARMAV) for measurement data synchronization is investigated. As the structure is excited by ambient excitation, where the excita-tion cannot be measured, ARMAV models constructed from output signals and the time-delay be-tween them is evaluated. Results from the identification of structural modal parameters show that frequencies and damping ratios are not influenced by the asynchronous data; however, the error in identifying structural mode shapes can be significant. The introduced method also allows the estima-tion of modal parameter uncertainties. Based on these uncertainties, a statistically based damage detection scheme is performed and it becomes possible to assess whether changes of modal parame-ters are caused by, e.g. some damage or simply by estimation inaccuracies.