Rails maintenance is becoming a critical issue because of the increase of the traffic and the train speed, which amplify the risk of catastrophic failures. A methodology, based on wave propagation theory, aimed at detecting damage in rails is presented in this paper. The damage detection algorithm is based on the assumption that the rails behave as a wave guides and stress waves may travel alongside the rail length without being reflected unless they meet discontinuities (damages). The Wave Propagation Based Damage Detection (WPBDD) algorithm proposed is a two steps technique. In the first step the travel time of a perturbation wave, generated by a train passage, from its arrival to the sensor locations to the discontinuity and back to the sensor, is measured by a Time Correlation Function (TCF) evaluated using the wavelet transform. The second algorithm locates the damage sites using a Ray-Tracing (RT) algorithm. The WPDDD algorithm has been designed to use indifferently either body waves (P and S waves) or surface waves (Rayleigh waves). The technique proposed aimed at the identification of single and multi-site rolling contact fatigue damages was tested on a numerical test case.
Studies have been conducted on the identification of modal parameters including natural frequencies, damping coefficients and mode shapes of the Nottingham Wilford Bridge using ambient excitation. An approach to estimate modal parameters, from only output data (in the time domain) using the wavelet transform, is presented. Displacements responses of this structural system are used in the wavelet transform to identify its dynamic characteristics. To measure real-time displacement of the bridge a global positioning system (GPS) sensor network was designed and installed on the bridge. The modal properties were extracted using a two-step methodology. In the first step, the random decrement method was used to transform random signals in free vibration responses. Finally, the Eigensystem Realization Algorithm and a Wavelets based technique were used to extract natural frequencies and to determine the mode shapes of the structure.
Health monitoring systems set up to assure the safe operation of structures require linking sensors with computational tools able to interpret sensor data in terms of structural performance. Although intensive development continues on innovative sensor systems, there is still considerable uncertainty in deciding on the number of sensors required and their location in order to obtain adequate information on structural behavior. This paper considers the problem of locating sensors on a bridge structure with the aim of maximizing the data information so that structural dynamic behavior can be fully characterised. Four different optimal sensor placement techniques, two based on the maximisation of the Fisher Information Matrix and two on energetic approaches, have been investigated. Mode shape displacements are taken as the measured data set and two comparison criteria were employed. The first was based on the mean square error between the FE model and the cubic spline interpolated mode shapes. The second criterion measured the information content of each sensor location to investigate on the strength of the acquired signals and their ability to withstand the noise pollution keeping intact the information relative to the structure properties. The results highlight that the Effective Independence Driving-Point Residue (EFI-DPR) method provides an effective method for optimal sensor placement to identify vibration characteristics of the studied bridge.
The present work relates to the assessment and testing of a multifunctional intelligent system, based upon the use of piezoelectric devices, devoted both to the active noise and vibration control and to damage detection f the structure. In the control application, the piezoelectric devices (in form of patches) play the role of actuators; their induced secondary vibration field has the target to reduce the primary one through a specific control algorithm and system. In the health monitoring application, the piezo devices play both the roles of actuators and sensors. In fact the developed technique is primarily based upon the evaluation and comparison of the structure Frequency Response Functions (FRF) that intrinsically contains all the information regarding the structural properties whose change may be correlated with incipient damages. The aforementioned application were investigated and experimentally assessed with good results with reference to a typical partial fuselage structure (three frames, eight stringers and the skin panels: 1.2 m x 1.7 m). On the noise control application side, a height sensors/height actuators control architecture was then assessed and experimentally tested whose results may be synthesized in a 30 dB vibration level reduction at sensors locations and more than 20 dB of reduction of the associated noise field. In the optic of a multifunctional intelligent system, the aforementioned set of piezo's was decided to be used also for health monitoring application. As a preliminary activity, an extensive monitoring was performed on the integer structure to verify the sensibility of the system and the stability of the defined Damage Index (DI) in respect to environmental factor not related to structural real modification. To verify the sensibility of the technique to reveal and locate a typical shear clip damage, a set of rivets were successively cut in the area surrounding the frame shear clip, and relative FRF's were acquired and relative DI calculated. The analysis of the data showed a good sensibility of the system to identify the presence of a damage with maximum values of the DI in the sensor closest to the damage location and with an absolute value of the index growing up with damage extension.