Data-driven vibration prognosis using multiple-input finite impulse response filters and application to railway-induced vibration of timber buildings

Abstract

With this paper, we present a vibration prognosis method based on finite impulse responses. The impulse responses are identified using measurement data from an existing building and consider a multiple-input/multiple-output topology. Vibration prognosis in urban buildings is becoming increasingly important, since more and more buildings are being constructed close to urban infrastructure. Combined with modern and ecological choices of building materials and the low vibration levels required by current standards, serviceability in terms of structural dynamics becomes an issue. Sources of vibration in urban settings include railway and metro lines as well as road traffic. This work focuses on a method especially suited to the three- dimensional vibration state encountered in modern timber buildings. Under the assumption of linear time-invariant structural dynamic behaviour, we develop a time- domain identification approach. The novelties of this contribution lie in the formulation of a numerically efficient method to identify multiple-input finite impulse response filters and its application to measurement data of a timber building. We validate this data-driven prognosis method using measurement data from a building constructed from cross-laminated timber, considering the three-dimensional vibration behaviour. The accuracy and limitations are assessed using railway-induced vibrations as a typical source of disturbance by infrastructure. We show that vibration data from the foundation can be used for effective prognosis of the top floor slabs considering train types not included in the identification data set. Based on the prognosis method, a virtual sensor concept for long-term monitoring is presented.