A Super-Resolution Reconstruction Driven Helmet Detection Workflow

The degrading of input images due to the engineering environment decreases the performance of helmet detection models so as to prevent their application in practice. To overcome this problem, we propose an end-to-end helmet monitoring system, which implements a super-resolution (SR) reconstruction driven helmet detection workflow to detect helmets for monitoring tasks. The monitoring system consists of two modules, the super-resolution reconstruction module and the detection module. The former implements the SR algorithm to produce high-resolution images, the latter performs the helmet detection. Validations are performed on both a public dataset as well as the realistic dataset obtained from a practical construction site. The results show that the proposed system achieves a promising performance and surpasses the competing methods. It will be a promising tool for construction monitoring and is easy to be extended to corresponding tasks.

Analysis of Construction Monitoring and Control of Tunnels Crossing Broken Faults and Water-rich Geology

In view of the poor geology such as tunnel engineering crossing faults or passing faults, the construction of surrounding rock and support is complicated. During construction, it is necessary to ensure the stability of the surrounding rock and supporting system, and ensure the timing of the secondary lining construction. For this reason, through the analysis and processing of monitoring data, the law of stratum change is mastered, and the supporting parameters and construction methods are adjusted and revised at the same time, so as to provide the best information for the tunnel surrounding rock and supporting lining construction.

The Construction Countermeasures of Shallow-Buried Small Spacing Tunnel Undercrossing Cultural Relic Buildings: A Case Study

Based on the background of the reconstruction project from Changqing Chenzhuang-Pingyin section of G220 east-deep line in China, a special tunnel structure and construction plan was carried out according to the construction measures of the shallow-buried small spacing tunnel passing underneath cultural relic buildings, and a comprehensive deformation control scheme of “CRD construction method single-arm excavation + surface grouting prereinforcement + advanced large pipe shed presupport” was put forward. The results of numerical simulation and on-site construction monitoring showed that the overall deformation of aqueduct foundation generally increases first, then decreases and increases again, and finally tends to be stable. The effects of surface grouting prereinforcement and advance large pipe shed presupport are obvious. The comprehensive deformation control scheme can ensure the safety of the existing construction and meet the safety prevention and control requirements.

IoT and 5G enabled construction detection model

The Fourth Industrial Revolution (4IR) introduced positive changes to some industries, while for most construction industries it is still enthusiastically anticipated. The 4IR focusing on the construction industry in literature is known as Construction 4.0. The Construction 4.0 concept is invoked to transform the current ways the construction industry operates while ensuring benefits, such as reduced overall construction projects’ costs and duration, improved quality and work safety, etc. Due to the increasing web usage, it is anticipated that the 4IR technologies will achieve full potentials by the uprising of the fifth generation technology standard for broadband cellular networks (i.e. 5G). One of the most important 4IR technologies is found to be the Internet of Things (IoT). In this perspective, a construction monitoring approach, more precisely a model for construction detection and object spatial/time positioning, is presented in this paper. While still in its initial phase, the model was tested and verified in the laboratory environment for small-scale object detection. It was found that the quality of the model will be significantly improved with the use of the 5G network, while the objects’ pool, as big data required for the model’s deep learning, is highly dependent on the IoT.

Design and Research on the Intelligent System of Urban Rail Transit Project based on BIM+GIS

Building Information Modeling (BIM) technology has been widely used in the construction industry, especially in the field of civil construction. BIM standards, basic software and management platforms are relatively mature. The urban rail transit projects are linear projects, they not only span long lines, multiple regions, involve multiple disciplines, and are difficult to coordinate, but also have complex surrounding environments and high safety requirements. Therefore, their needs for integrated construction and operation applications are more concentrated. In order to solve the problems of data isolation, single display form, abnormal situation notification and delayed processing in urban rail transit construction monitoring, combined with GIS+BIM technology, a complete set of construction monitoring information management process and data organization plan is proposed, and the development is oriented. The construction monitoring system of project construction management focuses on solving the problems of the integration, display, early warning and secondary early warning of construction monitoring data. The system realizes the functions of input, storage, processing, three-dimensional display and early warning of measuring point information and daily measurement information. It is integrated with the GIS+BIM management and control platform, and the project is carried out in the construction project of Qingdao Rail Transit Line 8. Application, interact with functions such as model browsing, schedule control, engineering quantity management, video monitoring, etc., to improve the management efficiency and safety quality level of on-site construction.The mainstream GIS and BIM data based research on construction monitoring data standards promote the in-depth integration of construction monitoring data and improve the data entry and association efficiency.

Intelligent Active Correction Technology and Application of Tower Displacement in Arch Bridge Cable Lifting Construction

In order to control the tower deviation in the cable hoisting process of long-span concrete-filled steel tubular arch bridge during construction monitoring, a practical method of tower deviation correction was studied and established. In the paper, based on the studies about the deviation error formation mechanism of tower in the process of cable lifting, the relevant formulas of the arch rib elevation changes caused by the change of tower state were deduced. The traditional control methods including increase of tower stiffness and strength of the anchor cable, are not effective, costly, and require a longer construction period. To overcome these defects, in virtue of the Beidou GNSS measurement system and hydraulic jack active control system, the active control technology of the CFST (Concrete Filled Steel Tube) arch bridge tower deviation was thoroughly studied. Besides, a perfect active control theory was established. Finally, the author puts forward the idea of reverse pulling tower deviation. The field measurement and comparative study show that after the optimization of this method, the tower deviation is within 2 cm, and the error meets the specification requirements. The proposed method can accurately control the tower deviation in the process of arch bridge cable hoisting, and establish a set of perfect active control related systems and theories, which is especially suitable for the construction monitoring and adjustment in the construction stage of arch bridge, and can provide reference for the construction control of tower deviation of the same type of bridge.