Publication | Closed Access
Vibration-based damage detection in civil engineering: excitation sources and temperature effects
387
Citations
7
References
2001
Year
Modal AnalysisDamage MechanismEarthquake EngineeringEngineeringExcitation SourcesVibration-based Damage DetectionCivil EngineeringExcitation SourceDamage EvolutionStructural Health MonitoringRandom VibrationStructural IdentificationStructural DynamicStructural MechanicsCivil Engineering StructuresVibration ControlStructural EngineeringStructural Vibration
Vibration‑based damage detection monitors changes in dynamic characteristics such as eigenfrequencies, damping ratios, and mode shapes to infer structural health, but excitation and temperature also affect these measurements. The study examines how excitation source and temperature influence vibration‑based health monitoring of civil engineering structures. The authors compare band‑limited shaker noise, drop‑weight impacts, and ambient wind/traffic excitations, and propose a method to separate temperature‑induced frequency shifts from genuine damage signatures. The proposed method was validated on a bridge dataset, successfully distinguishing temperature effects from damage after one year of monitoring.
This paper discusses two very relevant practical issues in the application of vibration-based health monitoring to civil engineering structures: the excitation source and the effect of temperature. The idea of vibration-based damage detection is to measure dynamic characteristics such as eigenfrequencies, damping ratios and mode shapes on a regular basis. The state, and eventually degradation, of the structure is reflected in the evolution of these characteristics. Unfortunately, it is not only the health of a structure that influences its measurable dynamics, but also the applied excitation and the changing temperature are important factors and may erode the damage detection potential. In the first part, the results of different excitation types are compared: band-limited noise generated by shakers, an impact from a drop weight and ambient sources such as wind and traffic. In the second part, the undeniable effect of temperature on measured eigenfrequencies is demonstrated and a methodology is proposed to distinguish these temperature effects from real damage events. The method could be validated on a unique data set from a bridge that was artificially damaged after a one-year monitoring period.
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