With the increase of bridge-required demolition/dismantling for reconstruction or modification, the early warning of construction emergencies is greatly needed for monitoring the structural safety of bridges under construction. In this paper, based on the multi-source data of nearby construction and demolition construction of a large-span RC arch bridge in China, the Analytic Hierarchy Process (AHP) method is adopted to analyze the multi-source data and set the early warning threshold for bridge safety in construction. According to the analytical results, a reasonable evaluation of AHP factors can improve the accuracy and timeliness of safety early warning in the structural safety monitoring of bridges during the construction process. The weight of the monitoring data in AHP should be assigned according to its reliability, stability, and importance. Bridge safety assessment of nearby construction having harmful vibration should prioritize dynamic bridge monitoring by cooperating with multi-source data, including stress, and deformation monitoring of the bridge is necessary. The assessment results proved that multi-source data, including but not limited to structural stress and deformation monitoring data, vibration data, theoretical prediction data, environment data such as temperature data, and construction/maintenance history data, are necessary for safety monitoring and early warning of construction with specifications related to bridge construction. The early warnings triggered by the evaluation results successfully ensure the safety status of the bridge during nearby construction and demolition construction, which shows the proposed method can provide a guideline for comprehensively evaluating and early warning of the status of bridge construction.

Ground vibrations caused by the construction of impact drilling piles may affect adjacent bridges, so corresponding prediction and monitoring are necessary to ensure the safety of bridges. In this study, the construction near an existing long-span double-convex arch bridge is taken as a case study to investigate different layouts of construction machines emanating harmful ground vibrations to the existing adjacent bridge by numerical simulations and monitoring. The peak acceleration and velocity acquired from numerical simulations, and monitoring were successfully used to implement impact drilling pile construction near the existing bridge. The results show that there are good consistencies between the monitoring and numerical simulation results, and the vibration acceleration of the foundation of abutments and piers are mainly derived from the vibration caused by the construction within a distance of 50 m, while the construction beyond 50 m has little effect on the old bridge. The numbers and locations of machines near the same foundation may have a weakening or strengthening effect on the peak acceleration and velocity due to destructive and constructive interference of waves, which can help to control the effects of the vibrations of the existing adjacent bridge.

In this investigation, an improved Rayleigh–Ritz method is put forward to analyze the free vibration characteristics of arbitrary‐shaped plates for the traditional Rayleigh–Ritz method which is difficult to solve. By expanding the domain of admissible functions out of the structural domain to form a rectangular domain, the admissible functions of arbitrary‐shaped plates can be described conveniently by selecting the appropriate admissible functions. Adopting the spring model to simulate the general boundary conditions, the problems of vibration of the arbitrary plate domain can be solved perfectly. Then, a numerical method is introduced to figure out the structure strain energy, kinetic energy, and elastic potential energy of the boundary. Finally, comparing the result with the simulation results and reference examples, the accuracy and convergence of this method are testified. Therefore, an effective new method is proposed for the guidance of the related research and practical engineering problems.

Rail stress in continuously welded railway (CWR) is a quite difficult problem for track maintenance and how to measure the temperature stress in the rail accurately is an important topic. In this paper, the wave number finite element method for a periodic structure is adopted to investigate this problem. This method combines the Fourier transform method with the periodic theory, so that it can be used to analyse the periodicity characteristics of track structure. Based on this method, two different single-layer beam track models under axial force are established, that is, the continuously supported model and the periodic discretely supported model. In both models, the rail is regarded as a Timoshenko beam and the elasticity of the other parts under the rail is represented by a dynamic receptance matrix, [H(ω)]. By changing the magnitude of the temperature stress, the influence of the temperature stress on vertical vibration characteristics of the track structure is analysed.

The monitoring of urban rail transit vibration and structural-borne noise can well solve the problem of small amount of data and large discreteness in traditional evaluation tests. In this study, a monitoring system is utilized to collect and preprocess vibration and noise signals. By employing cellular network and cloud-based services, real-time acquisition and analysis of vibration and noise signals are achieved. In this article, it is proposed to normalize the vibration data obtained after edge computing. After treatment, the gray correlation analysis method was used to determine the correlation between each vibration data component and vibration data classification. Combining frequency domain analysis of vibration data, the data components with high correlation are used as inputs to an improved K-nearest neighbours (KNN) model. Additionally, the correlation of each data component is introduced into the distance calculation formula. The improved KNN model shows improvements in recall rate, precision rate, F-measure, and accuracy compared to the original KNN model, with increases of 0.76 per cent, 2.76 per cent, 1.81 per cent, and 1.61 per cent respectively. Through practical measurements, it is found that different vehicles cause significant variations in vibration, with differences of up to 11 dB in tunnel wall vibration. The differences in tunnel wall vibration caused by the same vehicle at different passenger loads do not exceed 5 dB. Combining practical application cases, the rail transit environmental noise monitoring system established in this study demonstrates its applicability in monitoring vibration and noise-sensitive areas, as well as analysing the effectiveness of vibration reduction and noise control measures.