Railway tunnel inspection is crucial to railway construction and operation.The inspection technologies include acoustic wave inspection,online monitoring,and electromagnetic wave inspection.With the continuous progress of science&technology and the increasing application of new technologies,as well as in response to investigate the interpretation of data obtained from ground penetrating radar,the TR-1 intelligent radar system is developed based on the technologies such as artificial intelligence,big data,and the Internet,so as to address the existing challenges related to digitalization and intelligence in tunnel lining inspection.The trial application of the TR-1 intelligent radar system on tunnel construction sites demonstrates its capability to facilitate convenient inspections,digital management,and intelligent identification,which can effectively enhance the quality and efficiency of tunnel lining inspections.
Since the introduction of the world's first tunnel boring machine(TBM)in 1825,this safe and efficient engineering mechanical equipment has enhanced the technical capabilities of tunnel construction and facilitated significant progress in the construction of tunnels and other underground works.However,TBM tunnel construction encounters challenges in complex geological environments.The presence of abnormal geological formations often leads to water or mud gushing from the working face and instability of excavation face,causing the TBM to"overturn"or"sink".To avoid the risk of excessive surface settlement or TBM during tunnel construction,it is essential to adopt scientific and effective methods for advanced geological prediction ahead of the TBM.In the TBM tunnel construction of Sifanghe-Zaojiaojing section of Guiyang Metro Line 3,the tunnel DOSO advanced geological prediction system was adopted.A total of 9 tests for advanced geological prediction were conducted on the left and right tracks.The prediction results were verified through spoil sampling and opening inspection based on the total thrust,speed,and torque of TBM tunneling.The verification results demonstrate that the DOSO system can enhance the efficiency and accuracy of advanced geological prediction for tunnels,serving as a valuable reference for advanced geological prediction in TBM tunneling and similar projects.
In order to carry out the green construction in difficult mountain areas,assist in the construction of plateau railways and railways in extremely cold areas,and support the national"dual carbon"goals,the R&D and manufacturing of electric intelligent excavators have become an inevitable trend.This paper elaborates on the design scheme of an electric intelligent excavator and its subsystems,mainly including performance indicators,general layout and battery,motor and drive,integrated heat dissipation,software design,intelligent remote control,charging system,etc.,and analyzes the design principles and innovative advantages of each part in detail.Through statistics of preliminary test,this paper compares and verifies the actual application of the product,which proves that the electric intelligent excavator fully meets the design requirements and puts forward a prospect for future improvement.
Due to the extremely complex terrain conditions and climate characteristics,the railway construction in plateau high-altitude areas is challenging.It is critical to study the use of new energy equipment in plateau railway construction in order to meet the standards of"scientific,safe and green construction"and the national policy for carbon peaking and carbon neutrality.By analyzing the difficulties of construction in plateau areas,this paper puts forward the overall design scheme for the implementation of green energy,examines the feasibility of the scheme based on environmental and industrial values,and proposes the replacement of traditional diesel engineering machinery with pure electric engineering equipment,the integration of PV power generation and energy storage,the construction of charging and battery swapping stations,and the application of unmanned driving based on electric engineering equipment.The feasibility of the scheme is verified through the demonstration project of PV power generation + energy storage system + charging and battery swapping station.The implementation of this scheme can effectively reduce carbon emissions and costs.In particular,PV power generation and charging and battery swapping stations can continue to be put into use in stations or towns along the line after the plateau railway construction is completed,facilitating the subsequent station construction.
Cold joint is a disease caused by improper construction,which will reduce the mechanical performance of lining.In order to explore an effective cold joint inspection method,after analyzing the causes and characteristics of cold joints and investigating potential inspection methods,it is found that the cold joint inspection method based on impact elastic wave has certain technical advantages.This paper deeply analyzes its inspection principle and evaluation index algorithm,proposes the on-site inspection implementation plan,and verifies the feasibility of this inspection technology in combination with on-site destructive test.Taking GN Railway as an example,through on-site destructive test and statistical analysis of soundness index,the judgment of cold joints is divided into 3 categories:obvious cold joints,slight cold joints and non-cold joints.In view of the"duck tongue"/"wedge"type cold joint in arch crown,this paper puts forward that IAE method can be used as a supplementary inspection method,analyzes the field coring experience and the genesis characteristics of cold joints,and summarizes the key points of cold joint coring verification.The non-destructive testing of cold joints can greatly reduce the on-site destructive test,which has reference significance for future cold joint inspection of tunnel lining.
As one of the common diseases in high speed railway tunnel,lining void threatens the safety of vehicles and personnel.At present,the inspection of lining void in high speed railway tunnel is mostly judged by manual knocking and listening,which is greatly influenced by subjective factors and may affect the accuracy.Based on the principle of traditional percussion method and in combination with sound recognition technology,this paper studies the intelligent identification of lining void in high speed railway tunnel.This paper collects 270 samples of knocking sound from a tunnel on Beijing-Guangzhou high speed railway during knocking inspection,and analyzes the time domain and frequency domain characteristics under dense and void conditions.It is found that there are significant differences in the time domain waveform characteristics and short-term energy between dense and void conditions behind the lining.The dominant frequency and subdominant frequency are about 6 200 Hz under dense conditions,and about 800 Hz under void conditions.The 36-dimensional Mel frequency cepstrum coefficient(MF-CC)is extracted and used as a machine learning dataset after dimensionality reduction.In this paper,extreme gradient boosting(XGBoost)algorithm is used for training and testing to establish an intelligent identification model of high speed railway tunnel lining void based on MFCC.Compared with the optimized support vector machine(CV-SVM)model and gradient boosting decision tree(GBDT)model,the identification accuracy is higher,reaching 96.87%.The model can be used for qualitative identification of void behind the lining.Compared with manual inspection,the level of intelligence and informatization is greatly improved,which is of great significance for intelligent and automatic diagnosis of void defects in high speed railway tunnel lining.
In order to improve the concrete quality control level of railway tunnel lining in high-altitude areas,this paper adopts information technology combined with IoT unique identification to achieve full lifecycle quality tracking of concrete,including raw material mobilization,mix proportion design,concrete production,delivery inspection,concrete transportation,witness sampling on construction sites and laboratory testing,thus getting rid of the isolated data island phenomenon of concrete mixing station,construction site and on-site testing laboratory.Concrete test blocks,as quality testing sample,originally lacked an effective means of data tracking during the sampling and witnessing process.By implanting IoT unique identification(QR code),this paper realizes electronic identity labeling of sample entities and image recognition technology based on IoT identification,which effectively connects the 2 processes from on-site ready-mixed concrete sampling to laboratory testing,ensures the unique correspondence of the batch of concrete mixture-the batch of concrete test blocks-the concrete test report,and eliminates the problems of omissions,inadequacies and errors in testing.Meanwhile,test results can be retrieved in time using a unique identification number,and the unqualified test blocks can be fed back and tracked in real time.
Drainage system is the"blood vessel"of railway tunnel,and its blockage is one of the important factors restricting the service safety of tunnels.In order to find out and evaluate the blockage of tunnel drainage system and improve the operation and maintenance level of tunnel drainage system,this paper studies and puts forward the visual endoscope detection of drainage blind pipe behind railway tunnel lining and the blockage detection technology of robot patrol inspection for drainage ditch in tunnels through investigation and selection,equipment development,on-site inspection and evaluation research and based on robot miniaturization,data visualization and convenient operation.This paper collects and analyzes blockage conditions of tunnel drainage system,summarizes blockage type proportion and high-frequency blockage points of tunnel drainage system,etc.The results show that blockage of railway tunnel drainage system is common,dominated by crystallization blockage,and drainage blind pipe blockage is the most likely to occur at pipe connections;based on the experience of municipal drainage evaluation,the method of combining the maximum value and the distribution density of blockage is put forward to evaluate the degree and type of blockage in tunnel drainage system.
Using 3D laser scanning technology allows for the acquisition of ten million vector point clouds within a short period of time,covering a tunnel length of approximately 60 meters.The TK-PCAS system,a domestic tunnel point cloud post-processing software,enables the generation of holographic point cloud results in diverse scenarios through a series of processes,including the initialization of tunnel alignment data and section,point cloud noise reduction,and section registration.Making overbreak,underbreak and intrusion of tunnels clear,the 3D laser point cloud inspection can be used to measure overbreak volume,thus providing an effective basis for concrete cost control.Limited by available technical techniques,tunnel flatness inspection cannot obtain accurate and comprehensive flatness condition of primary support.Based on 3D laser scanning,holographic inspection is carried out with a virtual measuring ruler of the software to reveal the flatness of primary support through chromatograms.The reinforcement of primary support of tunnels is concealed works,and the 3D laser enables storage of the reinforcement point cloud in computer,so that the geometric information of the reinforcement can be measured at any time.The 3D laser scanning can obtain the holographic deformation of tunnels,especially unsymmetrical loading tunnels with large deformation in soft rock and shallow buried sections,and reflects the deformation condition of surrounding rock of tunnels,thus ensuring construction safety.
The tunnel lining quality is directly related to the railway construction and operation safety,so the quality inspection is very important.At present,the most commonly used inspection method is geological radar method which still stays in the stage of measurement by traditional manual antenna lifting,with high inspection cost and low work efficiency.Besides,there are safety risks in aerial work,making it difficult to meet the increasing needs for rapid inspection of tunnel lining quality.It is urgent to develop miniaturized and intelligent rapid inspection technology and equipment.With the rapid development of technologies such as UAV,robot,AI and IoT,an innovative intelligent inspection system of wall climbing robot combining rotor jacking and fixed-wing positive pressure has been proposed.The system adopts a combined positive pressure solution and can hover and stick to the wall at any wall surface and angle to efficiently complete tunnel lining quality inspection.The study mainly includes the system structure,jacking design,wall climbing design,control logic design and tunnel test.
Under conditions characterized by high geotemperature,frozen soil,and high geostress,it is difficult to realize rapid construction and safe operation of railway tunnels,and conventional inspection and monitoring methods cannot effectively assess the overall tunnel safety status.By studying the adaptability of existing inspection and monitoring technologies to unfavorable geological conditions,the reliability of measurement data can be ensured and the internal health status of tunnels can be more accurately revealed.The results show that the combination of probe thermometers and temperature sensors can be used for real-time early warning and long-term monitoring in high geotemperature sections.The inspection and monitoring technology combining InSAR technology and the remote real-time monitoring system for freezing-thawing circle of plateau frozen soil tunnel can be used at portals in frozen soil sections.On-line monitoring is adopted for high geostress sections by combining regional monitoring focusing on microseismic monitoring and displacement monitoring.The emerging MEMS technology is used to promote intelligent early warning of karst collapse in karst sections.The AOBT monitoring mode is adopted for multi-scale accurate monitoring of tunnels in water and mud inrush sections.An intelligent monitoring framework integrating tunnel cluster inspection,monitoring,identification and rapid diagnosis of structural defects can provide data support for smart operation and maintenance of railways in sections under unfavorable geological conditions.
Targeting at the current situation of railway tunnel lighting and the demand for real-time monitoring of tunnel safety risk status,an integration system of intelligent tunnel safety monitoring and green lighting is developed based on deep learning algorithm and multi-sensor integration technology.The tunnel anomaly detection algorithm based on the graph attention network is adopted to realize real-time monitoring of common diseases such as tunnel spalling,cracks and water seepage.Without adding trackside equipment,green lighting control,environmental perception and equipment fault self-diagnosis functions are available.The tunnel multiple image mosaic algorithm has been developed,and a visualization platform for intelligent tunnel safety monitoring has been built.The effectiveness of the system is proved by its application in a tunnel on Shanghai-Chengdu HSR.
With the rapid development of high speed railway construction in China,it is common for railway tunnels to be excavated in weak surrounding rocks.Excessive deformation of the tunnel bottom can result in cracking and damage to the tunnel lining,posing potential safety hazards in railway engineering.This paper conducts an extensive investigation of domestic and foreign literature,analyzing existing research results.It proposes that while focusing on the tunnel bottom structure,the monitoring and analysis of the surrounding rock's condition should not be ignored.Based on a case research of an high speed railway tunnel project,this paper presents a monitoring scheme and implementation process for coupling the tunnel bottom structure with the surrounding rock's condition.The monitoring data reveals that the pressure of the surrounding rock at the tunnel bottom remains relatively stable,with a maximum of 500 kPa.The tunnel arch bottom exhibits arching deformation without a convergence trend,and excessive deformation of the tunnel bottom leads to continuous deformation.This research holds practical significance in guiding the construction of high speed railway tunnels.
The stability and safety of tunnel structures and supporting systems are critical to tunnel construction.In order to ensure construction quality and safety and avoid accidents,it is necessary to monitor the tunnel construction process and take countermeasures in time.This paper studies the deformation measurement method of tunnel surrounding rock based on machine vision and structured light,adopts a measuring camera to collect the line-structured light image of the tunnel section in real time,extracts the structured light center,and forms a detection line.By comparing and analyzing the detection line with the historical detection line(reference line)as well as combining the fiducial contour structured light emitted by the reference structured light source,the displacement of the master station is corrected to obtain the deformation measurement results of the whole tunnel section.The system developed based on the above measurement technology has been tested and verified in a tunnel in southwest China.Its measurement values such as arch crown settlement and peripheral convergence are consistent with the deformation trend measured by the total station,and its measurement accuracy and real-time performance meet the requirements.It can be further promoted and applied to more tunnels under construction for automatic real-time monitoring and measurement of structural deformation of surrounding rock,so as to find out the risk of structural deformation in time and ensure the tunnel construction safety.
To address the challenge of inspecting the front shield attitude of a double-shield tunnel boring machine(TBM),a guidance system for double-shield TBM was developed.This system is based on a laser target guidance system and binocular vision.In addition to the hardware of a conventional laser target guidance system,the system includes binocular cameras placed at the front of the support shields and a set of spatially arranged Mark lights at the tail of the front shield.This combination forms the double-shield TBM guidance system.The design,algorithm implementation,and precision error of the double-shield TBM guidance system were thoroughly studied.The construction verification system used on-site meets the overall precision requirements,providing an effective method for inspecting the front shield attitude of double shields.
The bedrock in Longgang District,Shenzhen is dominated by limestone.Affected by corrosion,the original deposition interface of the limestone layer has been corroded and reconstructed,resulting in changes in the depth of the bedrock surface.The stratum is soft at the upper part and hard at the lower part with sudden lithological change,which has a significant impact on tunnel shield construction.It is urgent to find a solution that can quickly and accurately identify the bedrock surface in the karst area.Taking the public utility tunnel project of Shenzhen Metro Line 16 as an example,microtremor HVSR method and microgravity method are combined to quickly identify stratum boundary.Through project application verification,the microgravity method can quickly describe the distribution characteristics of bedrock surface;fine structures such as bedrock surface and karst caves can be precisely identified by microtremor HVSR method;various attribute information of the measured stratum can be known from different angles through the combination of the two methods.This can avoid data uncertainty and multi-solution of inversion in terms of data analysis,meet the needs of refined exploration of urban underground space,with advantages of environmental protection,economy and convenient for construction,which are worthy of popularization and application.
With the development of new energy sources such as solar and wind energy vigorously advocated by the state,the practicability and application prospects of wind-solar-diesel hybrid power supply system are becoming more prominent.From the perspective of solving the power demand in the early stage of railway construction,this paper proposes the design scheme of wind-solar-diesel hybrid power supply system applied in non-power areas,especially in alpine and high-altitude areas.The paper also explains the design structure and principle of the hybrid power supply system,and introduces the design process,control strategy and optimization scheme.In addition,the adaptability of wind-solar-diesel hybrid power supply technology in railway power supply system is analyzed so as to provide new solution for railway construction and permanent power supply scheme in remote non-power areas,and enlightenment for new energy development and utilization.
Based on the technical development trend of electric excavator, according to the objective requirements of plateau tunnel conditions, this paper selects and analyzes the most critical battery system and motor system of electric excavator, establishes the electrical control scheme, analyzes the I/O information of VCU control system in detail, expounds the characteristics of CAN bus, defines the communication system architecture, preliminarily designs the control program flow and safety protection strategy, puts forward the VCU electrical control system of electric excavator; the pure electric excavator of plateau tunnel type with this electrical control system runs stably and reliably in practical application, and achieves the goals of environmental protection, energy saving, improvement of tunnel environment, low power loss at high altitude and low costs.
Given the quantity of high speed railway tunnels in service and the short maintenance window assigned,the paper studies the development of inspection equipment and the corresponding automatic control system,the design and coupling integration of core inspection instrument module,self-adaptive processing and intelligent identification of the tremendous amount of data at hand as well as other key technologies.Based on machine vision and geological penetrating radar,the development and application of onboard inspection equipment for tunnel lining are elaborated in detail.And with the introduction of inspection vehicle,the linings of several tunnels are inspected,reviewed and verified.The paper then concludes with the suggestions for future research on inspection technology of high speed railway tunnels,providing valuable reference for the development of key technologies for onboard inspection.
With high speed railway rapid development,tunnel safety issues have attracted increasing attention.This paper designs a set of intelligent monitoring system for high speed railway tunnel based on IoT technology to realize intelligent monitoring and real-time management of high speed railway tunnel health status.The system adopts sensor technology to collect various data in high speed railway tunnels,and analyzes and processes the data using cloud computing platform.In this way,the health information of high speed railway tunnels can be closely grasped to find potential safety hazards in time and provide strong technical support to ensure the safe operation and maintenance of high speed railway tunnels.The system will provide more efficient,accurate and reliable technical means for the management and maintenance of high speed railway tunnels,which is conducive to improving the quality and safety of high speed railway operation.
