# Damage Identification in Warren Truss Bridges by Two Different Time-Frequency Algorithms
## 5 Conclusions  
This paper investigated the feasibility of drive-by methods for identifying the presence of damage in a Warren bridge, with single track, short span and a track with a wooden sleeper, which is a kind of bridge still present in regional railway lines. The study was carried out by means of the simulation of train/track/bridge interaction, considering specific defects consisting of loss of efficiency and till full failure of the connection between a generic diagonal member or cross-girder and the lower chord. The adoption of a model that reproduces the layout of the main structural members is a step forward in the field of drive-by methods. Two different time-frequency algorithms, namely the Continuous Wavelet and the Huang-Hilbert transforms are adopted, both of them being based on the comparison between the acceleration signals measured on healthy and damaged bridge, respectively. In order to introduce disturbing effects which may affect the feasibility of this approach, a change of irregularity is assumed in the healthy and damaged bridge simulations, to represent a rail degradation occurring with time between consecutive runs on the bridge. Two different damage scenarios are considered: the first one involves damage affecting the connection between the side wall diagonal members and the lower chord, while the second one regards the joint between the cross-girder and the lower chord. Different entities of the defect, different track profiles, travelling speeds and trains are considered in order to properly assess the capability of the algorithms to identify damage presence and position. Regarding the two time-frequency algorithms the main outcomes can be summarized in the following points:  
* Both the Continuous Wavelet (CWT) and the Huang-Hilbert (HHT) transforms show promising results in terms of damage identification in presence of a time-invariant track profile. This result might be of practical interest, since tracks directly linked to the bridge deck are likely to show a very contained degradation. * The damage-related frequencies identified by the two algorithms are in agreement with each other. They mainly depend on the zone of influence of the defect and are therefore dependent on the train speed. However, for some specific cases, the presence of the defect can generate local modes of vibration, whose natural frequency can be detected by bogie accelerations in the case of the damaged bridge. * The CWT is shown to be more robust than HHT to changes in the rail irregularity profiles. In fact, while the CWT also provides good results in the case of a varied irregularity profile in the cases of the healthy and the damaged bridge, the HHT becomes ineffective, not being able to identify the defect position with sufficient accuracy. * When considering a time-variant irregularity, the effectiveness of the proposed method depends on the damage severity and entity. In fact, when dealing with partial damages, the exploitability of the approach is a trade-off between the damage level and the entity of the variation of the irregularity profile. In other words, time-variant track profiles may hide the damage component, especially in the case of mild damages. * Another aspect that, according to authors, deserves to be further discussed is the effect that changes in terms of environmental condition could have on drive-by methods. It is true that the proposed indirect methods have the advantage of being non-modal parameter-based, and therefore they should be less affected by environmental changes as discussed in the introduction. Moreover, it is worth mentioning that the damage-related frequency (around 4 Hz) is far from the first bridge bending frequency (16 Hz). Anyway, a future outlook rising from this work could be represented by the investigation of the effect of environmental changes, such as temperature seasonality, on the vehicle-bridge interaction (VBI).