Concrete beams are elements used in many civil structures; unfortunately, they can contain cracks that lead to the collapse of the structures if those defects are not detected early enough. In this article, a new method to determine the structural condition of concrete beams subjected to bending is proposed. In general, it is based on the processing of the acoustic emissions (AE) signals, which are generated during the application of a load, by using the mathematical tool called wavelet transform (WT). The sound of the internal energy/crack is recorded as a hit or AE signal event; then, those signals acquired as waveforms are post-processed with the continuous WT (CWT); then, the wavelet energy (WE) is calculated for each hit by using an adequate scale range and the most convenient mother wavelet. Thus, with this method, it is possible to determine the structural condition (healthy or damaged) of concrete beams subjected to bending just by calculating the WE of any hit at any time and, even more, it is possible to define more precisely the stage of the structural condition as a healthy condition, micro-cracks appearance, the manifestation of a principal crack (hit with the highest WE), propagation of the principal crack, and final rupture. This method is experimentally validated in the laboratory, and additionally, ultrasonic pulse velocity tests (UPVT) are performed for some specimens to confirm the change between healthy and damaged conditions. The results are promising in order to apply this effective method in concrete beams of real-life structures.

In recent years, Interferometric Synthetic Aperture Radar (InSAR) technology has been able to determine the semi-static behavior of bridges. However, most of the research about the use of InSAR in the monitoring of bridges has been applied only in deterministic assessments of their performance. Therefore, in the current manuscript, the Usumacinta Bridge, located in Mexico, was evaluated based on a probabilistic methodology to define structural reliability using images from Sentinel-1. In addition, a controlled experiment was developed using a corner reflector (CR) to evaluate the capabilities of InSAR for determining vertical displacements. In the trial, the CR was designed, oriented, and implemented, finding discrepancies concerning leveling of less than 2 mm. On the other hand, the case of the alternative probabilistic approach integrates the reliability of structures theory and probability density functions (PDFs) of displacements obtained via InSAR technology. In summary, the proposed study focused on the analysis of two years of vertical displacements and monthly velocities; then, implementing the alternative probabilistic approach, the reliability index (β) and probability of risk (P_R) of the bridge were extracted, respectively. Based on the results of the experimental part of the paper, the displacements indicated maximum and minimum values of reliability index of 8.1 and 3.4, respectively. Within this context, the mean and standard deviation obtained were 5.9 and 1.4, respectively. On the other hand, the monthly velocities showed a maximum probability of risk of 2.61%, minimum value of 1.5 × 10⁻⁵%, mean of 0.4%, and standard deviation of 0.8%. Hence, the above-documented results indicate that the Usumacinta Bridge did not suffer any damage during its overloading condition period.

Large civil structures such as bridges must be permanently monitored to ensure integrity and avoid collapses due to damage resulting in devastating human fatalities and economic losses. In this article, a wavelet-based method called the Wavelet Energy Accumulation Method (WEAM) is developed in order to detect, locate and quantify damage in vehicular bridges. The WEAM consists of measuring the vibration signals on different points along the bridge while a vehicle crosses it, then those signals and the corresponding ones of the healthy bridge are subtracted and the Continuous Wavelet Transform (CWT) is applied on both, the healthy and the subtracted signals, to obtain the corresponding diagrams, which provide a clue about where the damage is located; then, the border effects must be eliminated. Finally, the Wavelet Energy (WE) is obtained by calculating the area under the curve along the selected range of scale for each point of the bridge deck. The energy of a healthy bridge is low and flat, whereas for a damaged bridge there is a WE accumulation at the damage location. The Rio Papaloapan Bridge (RPB) is considered for this research and the results obtained numerically and experimentally are very promissory to apply this method and avoid accidents.

Commonly, accelerometers are used to determine the tension force in cables through an indirect process; however, it is necessary to know the mechanical parameters of each element, such as mass and length. Typically, obtaining or measuring these parameters is not feasible. Therefore, this research proposed an alternative methodology to indirectly estimate them based on historical information about the so-called classic instruments (accelerometers and hydraulic jack). This case study focused on the Rio Papaloapan Bridge located in Veracruz, Mexico, a structure that has experienced material casting issues due to inadequate heat treatment in some cable top anchor over its lifespan. Thirteen cables from the structure were selected to evaluate the proposed methodology, yielding results within 3.8% of difference compared to direct tension estimation generated by a hydraulic jack. Furthermore, to enhance data collection, this process was complemented using a computer vision methodology. This involved remotely measuring the vibration frequency of cables from high-resolution videos recorded with a smartphone. The non-contact method was validated in a laboratory using a vibrating table, successfully estimating oscillation frequencies from video-recording with a fixed camera. A field test on eight cables of a bridge was also conducted to assess the performance and feasibility of the proposed method. The results demonstrated an RMS Error of approximately 2 mHz and a percentage difference in the tension force estimation below 3% compared to an accelerometer measurement approach. Finally, it was determined that this composed methodology for indirect tension force determination is a viable option when: (1) cables are challenging to access; (2) there is no line of sight between the camera and cables outside the bridge; (3) there is a lack of information about the mechanical parameters of the cables.

This study assesses ground subsidence and surface angular distortion along the Lerma–Zinacantepec segment of the Mexico-Toluca Intercity Railway. A multitemporal Interferometric Synthetic Aperture Radar (InSAR) framework using the Short Baseline Subset (SBAS) algorithm processed Sentinel-1 imagery (2022–2024), validated against the MXTO Global Navigation Satellite Systems (GNSS) station ($R^2$ of 0.86 and 0.80 for descending and ascending tracks, respectively). Kinematic vector decomposition revealed a mean vertical ground subsidence rate of −2 cm/year. To evaluate geohazard susceptibility, angular distortion was computed from these decomposed vertical displacements using a fixed 160 m spatial baseline. By explicitly integrating intrinsic InSAR measurement uncertainty into the classification, localized steep gradients initially flagged by mathematical models were discarded as statistically negligible artifacts. Consequently, results show widespread ground stability, with the evaluated 16-km segment falling within low-risk thresholds. Corroborating this, in-situ visual inspections revealed no structural damage induced by differential subsidence. Due to Sentinel-1 pixel-mixing limitations, the measured signals represent ground subsidence rather than direct structural deformation. Future monitoring should integrate higher-resolution SAR sensors or localized structural health instrumentation to isolate the behavior of the railway superstructure from regional subsidence.

Existing bridges represent a significant challenge for structural engineering due to aging, increased traffic demands, and lack of original design information. This paper presents an investigation of the structural behavior of the Miguel Hidalgo Bridge, located in Culiacán, Sinaloa, México, which has remained in service for over a century. A preliminary visual inspection identified deterioration mechanisms, including cracking, exposed reinforcement, damaged bearings, and localized structural deformations. Given the absence of original design documentation, a structural health monitoring (SHM) strategy was implemented to assess its condition. The SHM methodology integrates field instrumentation using accelerometers for operational modal analysis under ambient vibration and GPS receivers for displacement measurements, complemented by a geometric survey and material characterization through non-destructive techniques. These data were used to develop and calibrate a three-dimensional finite element (FE) model, which was employed to evaluate structural performance under service loads in accordance with AASHTO provisions. Results indicate that the bridge satisfies serviceability criteria; however, certain components exhibit deficiencies in load-carrying capacity. These findings highlight the importance of integrating monitoring data with numerical modeling to support decision-making related to maintenance, rehabilitation, and extension of service life in existing bridge infrastructure.