Research on automatic deformation detection system of subway tunnel?

1, research background and project source

Subway is a kind of transportation equipment that can quickly transport highly dense people in a narrow space, and the narrow space determines the difficulty and complexity of its management measures. High-speed operation highlights the importance of system coordination in many aspects, and every detail of each system may be a factor affecting safety; The high population density determines that once an accident occurs in rail transit, it will be a great danger and disaster; The safety of rail transit is closely related to all stages of planning, construction and operation, which determines the systematicness and integrity of rail transit safety management. All these factors pose new challenges to the safety management of subway, and at the same time, it also shows that once a safety accident occurs in urban rail transit, the consequences will be extremely serious.

Structural safety monitoring includes tunnel structural erosion monitoring, structural deformation monitoring, structural internal force monitoring and environmental monitoring, among which structural deformation monitoring is very important, and its monitoring contents mainly include cross-section settlement, lateral displacement and cross-section convergence deformation of the tunnel along the longitudinal direction.

Excessive deformation of subway tunnel structure will cause disasters, and the preventive measures are mainly deformation monitoring, which can be divided into construction stage and operation stage. In order to improve the safety of tunnel construction and operation at the same time, reliable detection and data processing methods are needed. However, due to the interference of construction and the limitation of detection methods and equipment, the traditional measurement technology can only record intermittently, which is not suitable for monitoring the operation of the tunnel after its completion. In the process of tunnel construction, the deformation of the whole tunnel and section can be observed and monitored in real time by means of manual measurement or automatic measurement, but this is often only effective to ensure the quality of tunnel construction. As for the automatic measurement method, because its automatic measuring instrument (total station) is very expensive, it is difficult to distribute points all over the line, and its automatic measurement is generally only effective for the advancing surface of construction, and its benchmark measurement needs manual periodic measurement, so it is not suitable for the detection of operating tunnels. After the construction, these equipments were evacuated from the site, and the deformation of the subway tunnel after it was put into operation could not be detected and monitored.

At present, the monitoring technology of tunnel construction at home and abroad is relatively mature, but the monitoring in the process of tunnel operation is far from enough. In fact, due to the long time span, complex influencing factors and great social impact after the disaster, the health monitoring of operating tunnels should be paid more attention.

According to the settlement observation data of the built subway tunnel, it is found that the longitudinal settlement of the tunnel in soft soil stratum will increase continuously during the long-term operation, and this settlement is the main part of the total settlement. The uneven settlement of the tunnel will lead to the bending deformation of the tunnel, affect the smoothness of the track and the comfort of passengers, and lead to the opening of the tunnel joints, further aggravate the infiltration and even mud leakage, threatening the structure, joints and normal operation of the tunnel. Therefore, it is necessary to pay attention to the overall deformation of tunnel structure in long-term operation, and comprehensively control and control it from the aspects of design, construction, engineering prevention and control, and surrounding environmental impact.

The deformation of operating subway tunnel includes the displacement of tunnel longitudinal axis along the cross section and the change of tunnel cross section shape. When the tunnel deformation is too large, it will affect the safe operation of the subway. The purpose of this project is to develop and operate a tunnel deformation detection and analysis system, collect real-time data of tunnel deformation according to the gradual and long-term nature of tunnel deformation, and establish long-term basic data. Through the integration of data in time and space, it is ready for the realization of network release of tunnel deformation and the establishment of tunnel deformation early warning mechanism. This topic belongs to an important part of the comprehensive technology research and application of rail transit network operation safety.

2. Main research contents.

Aiming at this topic, the project team has done a lot of preliminary basic research work. Based on the principle of multi-group stereo cameras and close-range photogrammetry, the deformation monitoring of building model is realized. Based on the vehicle-mounted multi-sensor mobile spatial data acquisition equipment, the integration and processing of sensors such as GPS, INS, CCD stereo camera and laser scanning are realized. Tunnel safety monitoring and collection vehicle is a successful example of close-range stereo photogrammetry, panorama camera and cross-section scanning integration and data fusion, with data management and real-time publishing functions. With the support of space multi-sensor network and other technologies, the positioning accuracy is as high as 5mm, which provides a strong support for the smooth progress and complete success of this scientific research plan.

According to the characteristics and contents of the project, the project research can be divided into three parts:

A. overall deformation detection of tunnel: research on networked intelligent image sensor, which is used to monitor the deformation disaster of operating subway tunnel. This paper mainly studies the networked intelligent image sensor, the self-stabilizing device of intelligent image sensor, the relative displacement data of reference points obtained by image analysis and processing, the high-precision measurement of serial images of sensor networks by using data fusion and joint adjustment theory, the networking technology of sensor networks, 3D tunnel deformation image modeling and deformation early warning, etc.

B. Detection of local (cross-section) deformation of tunnel: develop monitoring instruments for measuring cross-section deformation of tunnel. According to the results of the previous part, the transmission system of tunnel axis positioning datum is established, which provides an accurate measurement datum for the tunnel section deformation measuring instrument. The tunnel section deformation measuring instrument scans and monitors the tunnel comprehensively, which provides more comprehensive and rich monitoring data for accurately analyzing and diagnosing the tunnel deformation state.

C, establishing a spatial database to store and publish the tunnel deformation information: storing and processing the measured data of the overall deformation and cross-section deformation of the tunnel, forming an early warning mechanism and publishing it through the network.

This project mainly studies the real-time detection of the longitudinal axis deformation of the operating tunnel in an experimental interval by using the networked intelligent image sensor, establishes the temporal and spatial distribution law of the overall lateral displacement of the tunnel, preliminarily establishes the tunnel deformation early warning mechanism through deformation analysis, and establishes the tunnel axis positioning benchmark transmission system, which provides accurate measurement benchmarks for the vehicle-mounted tunnel section deformation measuring instrument.

In this project, on-line real-time monitoring of the deformation of the operating subway tunnel based on network sensor technology and image recognition technology is proposed for the first time, and the tunnel deformation status is analyzed according to the tunnel deformation data, so as to predict the disasters caused by poor tunnel deformation status in time.

At the same time, on this basis, the transmission of tunnel axis positioning datum is carried out, which provides basic data for further monitoring the safety of tunnel structure by using tunnel section deformation measuring instrument.

This is a new type of non-contact real-time safety monitoring technology, which can make up for the shortcomings of traditional structural monitoring methods. It uses a non-contact, real-time online way to obtain structural information comprehensively, and realizes multi-sensor data fusion based on computer network communication technology. The test cost is low, the process is repeatable, and it has the characteristics of real-time, dynamic and high precision, which can improve the accuracy of local monitoring and the overall monitoring and analysis ability in time and space.

Image sensors are distributed at the top or side of tunnel sections at certain intervals, and one or more image sensors are arranged on each section. All sensors form a monitoring network, and the monitoring computers of each station collect and analyze data, and then realize real-time monitoring and early warning of the whole tunnel through the inter-station computer network. At present, the technology and system of tunnel structure safety monitoring through integrated image and sensor network have not been reported at home and abroad.

3. Main research results

innovate

(1) The scheme and theory of tunnel deformation monitoring and positioning datum transfer based on image analysis are put forward for the first time. Realize on-line monitoring of the overall deformation of the tunnel.

(2) An intelligent image sensor system for on-line monitoring of tunnel deformation based on image measurement technology is designed.

(3) A section scanning inspection vehicle is designed, which integrates laser ranging, precise angle control and electronic inclinometer.

(4) The attitude compensation method of intelligent image sensor is proposed, which solves the measurement error caused by sensor attitude.

(5) A set of data processing methods for multi-sensor and multi-point long-term monitoring is proposed.

(6) A feasible method of field calibration, maintenance and replacement of intelligent image sensor is proposed.

(7) A network communication protocol suitable for multi-sensor information exchange and meeting the requirements of multi-sensor synchronization in tunnel online detection is developed.

Through the research of this project, a multi-sensor monitoring network system of image sensor array and cross-section deformation measuring instrument is constructed, and a special sensor calibration framework for self-calibration is designed to realize high-precision time synchronization. The high-precision joint processing algorithm of multi-sensor data fusion is solved, and the high-precision calculation of monitoring point coordinates based on stereo sequence images is realized. A tunnel structure safety monitoring system based on multi-sensor monitoring network with independent intellectual property rights was developed, and the on-site monitoring demonstration of the tunnel in Shanghai experimental section was completed.

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