Research on a Comprehensive Monitoring System for Tunnel Operation based on the Internet of Things and Artificial Intelligence Identification Technology

This article proposes a comprehensive monitoring system for tunnel operation to address the risks associated with tunnel operations.These risks include safety control risks,increased traffic flow,extreme weather events,and movement of tectonic plates.The proposed system is based on the Internet of Things and artificial intelligence identification technology.The monitoring system will cover various aspects of tunnel operations,such as the slope of the entrance,the structural safety of the cave body,toxic and harmful gases that may appear during operation,excessively high and low-temperature humidity,poor illumination,water leakage or road water accumulation caused by extreme weather,combustion and smoke caused by fires,and more.The system will enable comprehensive monitoring and early warning of fire protection systems,accident vehicles,and overheating vehicles.This will effectively improve safety during tunnel operation.

Comparative Analysis of ARIMA and LSTM Model-Based Anomaly Detection for Unannotated Structural Health Monitoring Data in an Immersed Tunnel

Structural Health Monitoring(SHM)systems have become a crucial tool for the operational management of long tunnels.For immersed tunnels exposed to both traffic loads and the effects of the marine environment,efficiently identifying abnormal conditions from the extensive unannotated SHM data presents a significant challenge.This study proposed amodel-based approach for anomaly detection and conducted validation and comparative analysis of two distinct temporal predictive models using SHM data from a real immersed tunnel.Firstly,a dynamic predictive model-based anomaly detectionmethod is proposed,which utilizes a rolling time window for modeling to achieve dynamic prediction.Leveraging the assumption of temporal data similarity,an interval prediction value deviation was employed to determine the abnormality of the data.Subsequently,dynamic predictive models were constructed based on the Autoregressive Integrated Moving Average(ARIMA)and Long Short-Term Memory(LSTM)models.The hyperparameters of these models were optimized and selected using monitoring data from the immersed tunnel,yielding viable static and dynamic predictive models.Finally,the models were applied within the same segment of SHM data,to validate the effectiveness of the anomaly detection approach based on dynamic predictive modeling.A detailed comparative analysis discusses the discrepancies in temporal anomaly detection between the ARIMA-and LSTM-based models.The results demonstrated that the dynamic predictive modelbased anomaly detection approach was effective for dealing with unannotated SHM data.In a comparison between ARIMA and LSTM,it was found that ARIMA demonstrated higher modeling efficiency,rendering it suitable for short-term predictions.In contrast,the LSTM model exhibited greater capacity to capture long-term performance trends and enhanced early warning capabilities,thereby resulting in superior overall performance.

Distributed fiber optic sensors for tunnel monitoring:A state-of-the-art review

Distributed fiber optic sensors(DFOSs)possess the capability to measure strain and temperature variations over long distances,demonstrating outstanding potential for monitoring underground infrastructure.This study presents a state-of-the-art review of the DFOS applications for monitoring and assessing the deformation behavior of typical tunnel infrastructure,including bored tunnels,conventional tunnels,as well as immersed and cut-and-cover tunnels.DFOS systems based on Brillouin and Rayleigh scattering principles are both considered.When implementing DFOS monitoring,the fiber optic cable can be primarily installed along transverse and longitudinal directions to(1)measure distributed strains by continuously adhering the fiber to the structure’s surface or embedding it in the lining,or(2)measure point displacements by spot-anchoring it on the lining surface.There are four critical aspects of DFOS monitoring,including proper selection of the sensing fiber,selection of the measuring principle for the specific application,design of an effective sensor layout,and establishment of robust field sensor instrumentation.These four issues are comprehensively discussed,and practical suggestions are provided for the implementation of DFOS in tunnel infrastructure monitoring.

Tunnel, Infrastructure Convergences/Monitoring and Engineering Role

Worldwide we see that the construction industry is expanding, requiring new directions, new perspectives that can help reduce time, cost, and make transportation easy, safe, and affordable. For decades now, most of the large cities have completed their surface infrastructure. It has become urgent to address their issues for overpopulated cities where nowadays all infrastructure is overwhelmed, these issues must be addressed, solved and have vision to build underground infrastructure. Developed countries are focused on expanding their infrastructure for road systems, subway network, railway, storm, and sanitary systems. The emergency for underground infrastructure development requires more large-scale projects to be built and it is becoming more crucial building tunnels/underground structures for the future than ever before. Engineering focus, scientific searches are looking to develop their ideas for designing and delivering project underground, but government, agencies and engineers are concerned about the safety, durability, functionality, and the lifetime of this structures planned to be functional for decades. To address all this concerns this study provides information of how to identify the risk on tunnels and underground structures by capturing data from the beginning phases of construction, to analyze, evaluate and produce bulletins and engineering reports through convergences and monitoring. Convergences are the key factor on development of infrastructure underground as it is the only way to explore and analyze the rock mass disturbance during excavation. Convergences and monitoring in infrastructure are the safety coefficient for building underground, preventing accidents, and assessing real risks associated with tunnel/mine works and ensuring progress of the construction in underground structures. This study delves into the engineering role of convergence monitoring, during construction activities on project excavated using New Austrian Tunnelling method and Sequential Excavation Method. The primary objective of convergence monitoring is to gather critical information on ground movements and disturbances, thereby enhancing safety measures during tunnel construction. The monitoring process serves as an early warning system offering evidence of the real risks associated with underground infrastructure, bringing results and engineering data to be used for the design as key coefficient for structural design, type of material, type and strength of the concrete, rebars, concrete mix design. By using the convergence and monitoring system on underground infrastructure this study represents information that can contribute to risk assessment, structural analysis, and the lifetime of a project.

Design of Signal Lamp Filament Monitoring Alarm Instrument

To improve the reliability of the light emitting diode(LED)signal lamp filament current monitoring alarm instrument for metro systems,a new type of hot standby online monitoring apparatus was developed which is based on synchronous transmission data(STD)bus technology.In this system,a double hot standby mode can be achieved by adopting bus arbitration.In addition,to detect the effective value of alternating current which is from 0 to 200 mA in the signal lamp lighting circuit,a precision rectifier signal conditioning circuit and an isolated acquisition circuit were designed.This new type of alarm instrument has high detection accuracy and could meet the functional requirements for metro signal systems after comparing it with some industry products that were applied on the spot.

Discussion on Structural Health Monitoring of Urban Underground Road Tunnel

The number of urban underground road tunnels in China is increasing year by year,and health monitoring of tunnels is an effective management method to ensure their structural integrity.However,for shorter underground road tunnel projects,insufficient investment often leads to less frequent application of health monitoring systems.The application of intelligent structural health monitoring means can not only reduce the project cost but also help workers fully understand the actual situation of the tunnel structure.Therefore,this paper analyzes the characteristics,problems,and design of the urban underground road tunnel structural health monitoring system,and discusses the implementation of the urban underground road tunnel structural health monitoring system.

Establishment of Nanchang Honggu Tunnel health monitoring and assessment system

Based on the background of the Nanchang Honggu Tunnel,which is the largest inland river immersed tunnel to date in China,some research work on the construction of the Nanchang Honggu Tunnel health monitoring and assessment system is introduced.The platform of the health monitoring and assessment system is established with a relatively mature structure,including the sensor subsystem,data acquisition subsystem,data transmission subsystem,database subsystem,data processing and control subsystem,and health assessment and pre-warning subsystem.Monitoring index selection,sensor selection and sensor layout are fully considered in the health monitoring design and technology scheme.The fuzzy-AHP(analytic hierarchy process)evaluation method is employed to establish the Honggu Tunnel health assessment model,and the index weight determination method and grading control criterion are investigated and given.Then,the functions of the software system are achieved with advanced cloud platform technology,and the running costs of the system is reduced greatly.In summary,the establishment of the Nanchang Honggu Tunnel health monitoring and assessment system is described and such a system can realize real-time monitoring of the Honggu Tunnel and make it more convenient for implementing health assessment,pre-warning,and some other functions.Managers can operate the system using PCs and cell phones.At the same time,the relevant work on this system can provide a good reference for other immersed tunnels.

Non-contact monitoring and analysis system for tunnel surrounding rock deformation of underground engineering

It is very important to monitor surrounding rock deformation in tunnel construction. The principle, function, development and application of the system composed of a total station and computer for monitoring and analyzing surrounding rock deformation were discussed. The new methods of two free station of 3D measurement and its mathematic adjustment mode were presented. The development of software for total station on-board and post for computer were also described. Without centering it and measuring its height, the total station controlled by the software on-board can fulfill the whole measurements to target points. Monitoring data can be processed by the post software and results of regression analysis, forecasting information of the tunnel surrounding rock deformation can be provided in time. The practical use shows that this system is practicable, highly accurate and efficient. It satisfies the needs of safety and information construction in tunnel construction of underground engineering.

Design and Implementation of Environment Monitoring and Alarm System for Broiler Breeding Based on Internet of Things

Environment plays a vital role in the breeding process of broilers. In order to effectively monitor and control the breeding environment of broilers, a broiler breeding environment monitoring and alarm system based on internet of things is studied and established. The system adopts the narrow band internet of things communication technology, and can transmit the temperature, humidity, illumination and ammonia and other environ-mental data in the chicken house remotely through terminal collection unified interface device. Meantime, it realizes the control of fans, wet cur-tains, small windows and illumination in the chicken house by threshold method. The system software is designed and implemented by C#, SQL Server, WeX5 and other development tools, including platform terminal and enterprise terminal. Since its operation, the system is featured by stable state, reliable data and timely alarm, which solves the problem of unified control of different sensors and realizes the effective control of house envi-ronment.

Real-time prediction of mechanical behaviors of underwater shield tunnel structure using machine learning method based on structural health monitoring data

Predicting the mechanical behaviors of structure and perceiving the anomalies in advance are essential to ensuring the safe operation of infrastructures in the long run.In addition to the incomplete consideration of influencing factors,the prediction time scale of existing studies is rough.Therefore,this study focuses on the development of a real-time prediction model by coupling the spatio-temporal correlation with external load through autoencoder network(ATENet)based on structural health monitoring(SHM)data.An autoencoder mechanism is performed to acquire the high-level representation of raw monitoring data at different spatial positions,and the recurrent neural network is applied to understanding the temporal correlation from the time series.Then,the obtained temporal-spatial information is coupled with dynamic loads through a fully connected layer to predict structural performance in next 12 h.As a case study,the proposed model is formulated on the SHM data collected from a representative underwater shield tunnel.The robustness study is carried out to verify the reliability and the prediction capability of the proposed model.Finally,the ATENet model is compared with some typical models,and the results indicate that it has the best performance.ATENet model is of great value to predict the realtime evolution trend of tunnel structure.

Fiber optic sensing and performance evaluation of a water conveyance tunnel with composite linings under super-high internal pressures

For long-distance water conveyance shield tunnels in operation,the high internal water pressure may cause excessive deformation of composite linings,affecting their structural integrity and serviceability.However,the deformation and failure characteristics of lining structures under internal water pressure are not well investigated in the literature,particularly for three-layer composite linings.This study presents an in situ experimental investigation on the response of two types of composite linings(i.e.separated and combined lining structures)subjected to internal pressures,in which a fiber optic nerve system(FONS)equipped with distributed strain and displacement sensing nerves was employed to monitor the performance of the two composite linings during testing.The experimental results clearly show that the damage of the tunnel lining under different internal pressures was mainly located in the self-compaction concrete layer.The separated lining structure responded more aggressively to the variations in internal pressures than the combined one.Moreover,two evaluation indices,i.e.radial displacement and effective stiffness coefficient,are proposed for describing the changes in the structural bearing performance.The effective stiffness coefficients of the two types of lining structures were reduced by 39.4%and 29.5%,respectively.Considering the convenience of field monitoring,it is suggested that the average strains at different layers can be used as characteristic parameters for estimating the health conditions of lining structures in service.The analysis results provide a practical reference for the design and health evaluation of water conveyance shield tunnels with composite linings.

Automatic Sensing and Detection for Subway Tunnel Pathologies

Subway tunnels often suffer from surface pathologies such as cracks,corrosion,fractures,peeling,water and sand infiltration,and sudden hazards caused by foreign object intrusions.Installing a mobile visual pathology sensing system at the front end of operating trains is a critical measure to ensure subway safety.Taking leakage as the typical pathology,a tunnel pathology automatic visual detection method based on Deeplabv3+(ASTPDS)was proposed to achieve automatic and high-precision detection and pixel-level morphology extraction of pathologies.Compared with similar methods,this approach showed significant advantages and achieved a detection accuracy of 93.12%,surpassing FCN and U-Net.Moreover,it also exceeded the recall rates for detecting leaks of FCN and U-Net by 8.33%and 8.19%,respectively.

Doppler Radar Fault Judgment System and Remote Monitoring Platform

The Doppler weather radar fault judging system and remote monitoring platform were introduced.Through the real-time scanning of radar alarm information coding,the platform can realize dynamic monitoring and real-time alarm of Doppler radar equipment components,so as to improve the reliability of equipment operation,and truly realize"unattended"remote monitoring.

Research on in situ stress inversion of deep-buried tunnel based on pressure/tension axis mechanism and geological structure

The investigation of the in situ stress distribution has always been a key condition for engineering design of deep tunnels and analysis of surrounding rock stability.In this paper,a comprehensive judgment method coupled with pressure/tension(P/T)axis mechanism and geological structure is proposed to invert the in situ stress in the Duoxiongla tunnel in Tibet.In the process of TBM tunnel excavation,3887 groups of microseismic events were collected by means of microseismic monitoring technology.By studying the temporal and spatial distribution of 3887 groups of microseismic events,42 groups of microseismic data were selected for in situ stress inversion.Then the focal mechanisms of 42 groups of microseisms were inverted.Combined with the analysis of the previous geological survey,the inversion results of the in situ stress were analyzed.According to the focal mechanism of the tunnel area,the linear in situ stress inversion method was used to invert the in situ stress in the source area.Finally,according to the PTGS(pressure/tension axis mechanism and geological structure)comprehensive judgment method proposed in this paper,the in situ stress of the tunnel microseismic region was determined.The results show that there are mainly three groups of fissures and joint surfaces in the tunnel area,and the in situ stress is dominated by the horizontrun tectonic stress;the main driving force of the rupture surface in the excavation process of Duoxiongla tunnel is the horizontal tectonic stress;the distribution of the maximum and minimum principal stress obtained by the inversion is consistent with the distribution of the P/T axis;combined with the linear in situ stress inversion method and the comprehensive judgment of PTGS,the azimuth and dip angles of the three principal stresses are finally determined as N90.71°E,4.06°,N5.35°W,3.06°,and N8.10W,85.32°,respectively.The study verifies the feasibility of microseismic inversion of in situ stress.

Formation mechanism of rockburst in deep tunnel adjacent to faults:Implication from numerical simulation and microseismic monitoring

Rockbursts were frequently encountered in the construction of deeply buried tunnels at the Jinping-II hydropower station, Southwest China. In those cases, the existence of large structural planes, such as faults, was usually observed near the excavation boundaries. The formation mechanism of the “11·28” rockburst, which was a typical rockburst and occurred in a drainage tunnel under a deep burial depth, high in-situ stress state and complex geological conditions, has been difficult to explain. Realistic failure process analysis(RFPA3D) software was adopted to numerically simulate the whole failure process of the surrounding rock mass around the tunnel subjected to excavation. The spatial distribution of acoustic emission derived from numerical simulation contributed to explaining the mechanical responses of the process. Analyses of the stress, safety reserve coefficient and damage degree were performed to reveal the effect of faults on the formation of rockbursts in the deep tunnel. The existence of faults results in the formation of stress anomaly areas between the tunnel and the fault. The surrounding rock mass failure propagates toward the fault from the initial failure, to different degrees. The relative positions and angles of faults play significant roles in the extent and development of surrounding rock mass failure, respectively. The increase in the lateral stress coefficient leads to the aggravation of the surrounding rock mass damage, especially in the roof and floor of the tunnel. Moreover, as the rock strength-stress ratio increases, the failure mode of the near-fault tunnel gradually changes from the stress-controlled type to the compound-controlled type. These findings were consistent with the microseismic monitoring results and field observations, which was helpful to understand the mechanical behavior of tunnel excavation affected by faults. The achievements of this study can provide some references for analysis of the failure mechanisms of similar deep tunnels.

Assessing the deformation response of double-track overlapped tunnels using numerical simulation and field monitoring

The unprecedented rate of metro construction has led to a highly complex network of metro lines.Tunnels are being overlapped to an ever-increasing degree.This paper investigates the deformation response of double-track overlapped tunnels in Tianjin,China using finite element analysis(FEA)and field monitoring,considering the attributes of different tunneling forms.With respect to the upper tunneling,the results of the FEA and field monitoring showed that the maximum vertical displacements of the ground surface during the tail passage were 2.06 mm,2.25 mm and 2.39 mm obtained by the FEA,field monitoring and Peck calculation,respectively;the heaves on the vertical displacement curve were observed at 8 m(1.25D,where D is the diameter of the tunnel)away from the center of the tunnel and the curve at both sides was asymmetrical.Furthermore,the crown and bottom produce approximately0.38 mm and 1.26 mm of contraction,respectively.The results of the FEA of the upper and lower sections demonstrated that the tunneling form has an obvious influence on the deformation response of the double-track overlapped tunnel.Compared with the upper tunneling,the lower tunneling exerted significantly less influence on the deformation response,which manifested as a smaller displacement of the strata and deformation of the existing tunnel.The results of this study on overlapped tunnels can provide a reference for similar projects in the future.

Deformation mechanism and collapse treatment of the rock surrounding a shallow tunnel based on on-site monitoring

When tunnels are constructed at shallow depths in areas with poor geological conditions,such as portal sections,valleys and hillsides in regions with granitic bedrock,considerable excavation-induced deformation of the surrounding rock may occur,potentially resulting in tunnel collapses.The main reason for these problems is the lack of understanding of the deformation mechanism and evolution of the soft granitic rock surrounding the tunnel and the adoption of inappropriate construction technology and methods.This article analyzes the deformation mechanism of the rock surrounding a shallow tunnel based on in situ monitoring data as a case study and suggests that certain measures should be taken to effectively control the deformation of the surrounding rock and to minimize the potential for tunnel collapse.The results show that the deformation of the granitic soil surrounding the tunnel can be divided into three stages:the rapid deformation stage,the slow deformation stage and the stabilization stage.Appropriate construction methods should be carefully selected to ensure safety during tunnel excavation in the first stage.To avoid secondary disasters caused by tunnel collapses,three treatment measures may be implemented as part of safety management:enhancing the monitoring of the surrounding rock deformation,adjusting the construction methods and optimizing the support systems.In particular,accurate monitoring data and timely information feedback play a vital role in tunnel construction.Therefore,engineers with considerable engineering experience and professional knowledge are needed to analyze the monitoring data and make accurate predictions of tunnel deformation to ensure that reasonable measures are taken in the process of shallow tunnel excavation.

An ECG Monitoring and Alarming System Based On Android Smart Phone

ECG monitoring in daily life is an important means of treating heart disease. To make it easier for the medical to monitor the ECG of their patients outside the hospital, we designed and developed an ECG monitoring and alarming system based on Android smart phone. In our system, an ECG device collects the ECG signal and transmits it to an Android phone. The Android phone detects alarms which come from the ECG devices. When alarms occur, Android phone will capture the ECG images and the details about the alarms, and sends them to the cloud Alarm Server (AS). Once received, AS push the messages to doctors’ phone, so the doctors could see the ECG images and alarm details on their mobile phone. In our system, high resolution ECG pictures are transmitted to doctors’ phone in a user-friendly way, which can help doctors keep track of their patient’s condition easily.

An Automatic Monitoring and Alarming Method for the Power Supply of Weather Radars

As weather radar stations require headroom environment to operate,they were mostly built on highlands which are usually unattended.The mains supply is relatively poor,and the risk of radar stoppages due to power outage is therefore ever-present.As such,the radar construction program is used to build a complementary security video monitoring system.By collecting monitoring images of the regulated power supply in real-time from power supply auto transfer systems in distribution rooms and radar transceiver rooms,using Spearman’s rank correlation coefficient to analyse pixel variation trends,and supplementing statistical analysis of pixel characteristics difference to eliminate misjudgments resulting from low image contrast in special scenarios,a software can be developed through C#.It has the function of automatically monitoring mains supply and alerting staff on duty to handle the power outage in a timely manner via text message so that any potential risk is neutralised before it can cause damage.This monitoring and auto-alerting approach is generally applicable to unattended rooms with large amounts of electronical equipment.

The Monitoring with Video and Alarm System Based on Linux Router

As one of important safeguarded measures in security field, the video monitoring system have been applied in extensive ways such as building’s security,information’s acquisition and medical treatment. In current time, the intelligent home systems as well as the Internet of Things are forming a more and more mature industrial chain. With abundant of new technology applications, this industrial chain is developing towards to a more intelligent way. One of the most important applications is the video monitoring system developed by new technology. Deploy an appropriate design of video monitoring system in the several fields such as public security, traffic schedule, systems control and so on, is a major technological medium which can guarantee not wasting an amount of manpower resource as well as keeping the system in a good running status. This article based on the preponderance of the Linux system, especially the character of open source of it. Combine the Linux system and some particular routers;designing a real-time and efficient video monitoring system. It’s functional and in the meantime it can discriminate abnormal information or the situation automatically and then raise the alarm. This system use matured B/S mode in software’s framework, which is also lightweight class. In addition, this system manages the expenses in hardware cost more commendably.