Technical Analysis of Safety Monitoring and Evaluation of Existing Bridge Structures

Bridge structure safety monitoring and assessment has been a great concern for the government and the public,and bridge structure safety monitoring and assessment technology has also developed rapidly over the years.Its goal is to equip relevant organizations and professionals with a deep understanding of the principles and practical applications of these technologies.By doing so,it seeks to facilitate the effective implementation of safety monitoring and assessment practices in bridge management.Ultimately,the aim is to foster the constructive development of road and bridge construction and operational management at a broader level.

Smart industrial IoT empowered crowd sensing for safety monitoring in coal mine

The crowd sensing technology can realize the sensing and computing of people,machines,and environment in smart industrial IoT-based coal mine,which provides a solution for safety monitoring through distributed intelligence optimization.However,due to the difficulty of neural network training to achieve global optimality and the fact that traditional LSTM methods do not consider the relationship between adjacent machines,the accuracy of human body position prediction and pressure value prediction is not high.To solve these problems,this paper proposes a smart industrial IoT empowered crowd sensing for safety monitoring in coal mine.First,we propose a Particle Swarm Optimization-Elman Neural Network(PE)algorithm for the mobile human position prediction.Second,we propose an ADI-LSTM neural network prediction algorithm for pressure values of machines supports in underground mines.Among them,our proposed PE algorithm has the lowest average cumulative prediction error,and the trajectory fit rate is improved by 24.1%,13.9%and 8.7%compared with Kalman filtering,Elman and Kalman plus Elman algorithms,respectively.Meanwhile,compared with single-input ARIMA,RNN,LSTM,and GRU,the RMSE values of our proposed ADI-LSTM are reduced by 36.6%,52%,32%,and 13.7%,respectively;and the MAPE values are reduced by 0.0003%,0.9482%,1.1844%,and 0.3620%,respectively.

Genetic Regression Model for Dam Safety Monitoring

Under-fitting problems usually occur in regression models for dam safety monitoring.To overcome the local convergence of the regression, a genetic algorithm (GA) was proposed using a real parameter coding, a ranking selection operator, an arithmetical crossover operator and a uniform mutation operator, and calculated the least-square error of the observed and computed values as its fitness function. The elitist strategy was used to improve the speed of the convergence. After that, the modified genetic algorithm was applied to reassess the coefficients of the regression model and a genetic regression model was set up. As an example, a slotted gravity dam in the Northeast of China was introduced. The computational results show that the genetic regression model can solve the under-fitting problems perfectly.

Structural safety monitoring for Nanjing Yangtze River Bridge

In order to evaluate objectively and accurately the integrity, safety and operating conditions in real time for the Nanjing Yangtze River Bridge, a large structural safety monitoring system was described. The monitoring system is composed of three parts: sensor system, signal sampling and processing system, and safety monitoring and assessment system. Combining theoretical analysis with measured data analysis, main monitoring contents and layout of measuring points were determined. The vibration response monitoring was significantly investigated. The main contents of safety monitoring on vibration response monitoring are vibration of the main body of the Nanjing Yangtze river bridge, collision avoidance of the bridge piers, vibration of girders on high piers for the bridge approach and earthquake. As a field laboratory, the safety monitorying system also provides information to investigate the unknown and indeterminate problems on bridge structures and specific environment around bridges.

Binocular Vision Positioning Method for Safety Monitoring of Solitary Elderly

In nowadays society,the safety of the elderly population is becoming a pressing concern,especially for those who live alone.There might be daily risks such as accidental falling or treatment attack on them.Aiming at these problems,indoor positioning could be a critical way to monitor their states.With the rapidly development of the imaging techniques,wearable and portable cameras are very popular,which could be set on human individual.And in view of the advantages of the visual positioning,the authors propose a binocular visual positioning algorithm to real-timely locate the elderly indoor.In this paper,the imaging model has been established with the corrected image data from the binocular camera;then feature extraction has been completed to provide reference to adjacent image matching based on the binary robust independent elementary feature(BRIEF)descriptor,finally the camera movement and the states of the elderly have been estimated to distinguish their falling risk.In the experiments,the real-sense D435i sensors were adopted as the binocular cameras to obtain indoor images,and three experimental scenarios have been carried out to test the proposed method.The results show that the proposed algorithm can effectively locate the elderly indoor and improve the real-time monitoring capability.

Key techniques for evaluation of safety monitoring sensors in water conservancy and hydropower engineering

For the evaluation of construction quality and the verification of the design of water conservancy and hydropower engineering projects, and especially for the control of dam safety operation behavior, safety monitoring sensors are employed in a majority of engineering projects. These sensors are used to monitor the project during the dam construction and operation periods, and play an important role in reservoir safety operation and producing benefits. With the changing of operating environments and run-time of projects, there are some factors affecting the operation and management of projects, such as a certain amount of damaged sensors and instability of the measured data. Therefore, it is urgent to evaluate existing safety monitoring sensors in water conservancy and hydropower engineering projects. However, there are neither standards nor evaluation guidelines at present. Based on engineering practice, this study examined some key techniques for the evaluation of safety monitoring sensors, including the evaluation process of the safety monitoring system, on-site detection methods of two typical pieces of equipment, the differential resistor sensor and vibrating wire sensor, the on-site detection methods of communication cable faults, and a validity test of the sensor measured data. These key techniques were applied in the Xiaolangdi Water Control Project and Xiaoxi Hydropower Project. The results show that the measured data of a majority of sensors are reliable and reasonable, and can reasonably reflect the structural change behavior in the project operating process, indicating that the availabilities of the safety monitoring sensors of the two projects are high

Safety monitoring and stability analysis of left abutment slope of Jinping Ⅰ hydropower station

Safety monitoring and stability analysis of high slopes are important for high dam construction in high mountainous regions or precipitous gorges. In this paper, deformation characteristics of toppling block at upper abutment, deforming tensile rip wedge in the middle part and deep fractures are comprehensively analyzed based on the geological conditions, construction methods and monitoring results of left abutment slope in Jinping Ⅰ hydropower station. Safety analyses of surface and shallow-buried rock masses and the corresponding anchorage system are presented. The monitoring results indicate that the global stability of the large wedge block in the left abutment is effectively under control, and the abutment slope is stable in a global sense. After the completion of excavation, the deformations of toppling block at the top of the slope and deep fracture zone continue at a very low rate, which can be explained as 'rock mass creep'. Further monitoring and analysis are needed.

Construction Technology and Safety Monitoring Measures of Road and Bridge Engineering

With the acceleration of urbanization and the continuous improvement of urban infrastructure construction,roads and bridges,as an important infrastructure content in China,directly affect people's daily travel.Therefore,the construction and management of roads and bridges must be improved to ensure the quality and safety of roads and bridges and effectively prevent safety accidents.Strengthen the management of road and bridge construction through safety monitoring,improve the safety factor of the project and ensure people's travel safety.This paper mainly analyzes the common diseases and construction technology of road and bridge engineering construction,and puts forward safety monitoring measures.

Development and engineering application of integrated safety monitoring systems for China’s high-speed trains

With the improvement of the running speed of China’s high-speed trains,the demands for running status monitoring and security assurance of High-speed Electric Multiple Units(EMU)have increased significantly.However,the current safety monitoring systems are independent,which is not conducive to the comprehensive monitoring and information sharing of the whole vehicle.The temperature monitoring of running gear is insensitive to early failures.How to develop a train operation safety monitoring system with strong engineering implementation and high integration is a key problem to be solved.For the monitoring of running stationarity,frame stability and running gear health of China’s high-speed trains,an integrated safety monitoring system framework is designed,and the logic and algorithm for the diagnosis of stationarity,stability and health states of rotating parts are constructed.Monitoring software which fused the temperature,high and low frequency vibration data is developed,and the design and installation of the vibration temperature composite sensors are completed.The research results have realized the integration and comprehensive processing of multiple monitoring systems,completed the improvement from single component and vehicle-level safety monitoring to multi-system,train-level and interactive monitoring.In the process of real vehicle application,the developed monitoring system acquires the vehicle operation status data accurately and in real time.The constructed diagnosis algorithm and logic evaluates the vehicle operation status accurately and in a timely manner,and avoids the progression from fault to accident.The research results show that the integrated safety monitoring system can provide technical support for train operation safety.

Singular value diagnosis in dam safety monitoring effect values

Based on the principal component analysis, principal components that have major influence on data variance are determined by the energy percentage method according to the correlation between monitoring effects. Then principal components are extracted through reconstructing multi effects. Moreover, combining with the optimal estimation theory, the method of singular value diagnosis in dam safety monitoring effect values is proposed. After dam monitoring information matrix is obtained, single effect state estimation matrix and multi effect fusion estimation matrix are constructed to make diagnosis on singular values to reduce false alarm rate. And the diagnosis index is calculated by PCA. These methods have already been applied to an actual project and the result shows the ability of the monitoring effect reflecting dam evolution behavior is improved as dam safety monitoring effect fusion estimation can take accurate identification on singular values and achieve data reduction, filter out noise and lower false alarm rate effectively.

Long-term dam safety monitoring of Punt dal Gall arch dam in Switzerland

The 130m high Punt dal Gall dam is located at the Swiss-Italian border in the South-eastern part of Switzerland and was completed in 1969.The dam is founded on highly folded and partially crushed dolomite and limestone formations.A grout curtain with an area of 120,000m^(2) was provided for controlling seepage.For the monitoring of the dam deformations five inverted pendulums were installed in the dam and three in the rock foundation of the right abutment outside of the dam.For a seasonal water level fluctuation in the reservoir of about 60 m the maximum amplitude of the radial displacement is 25 mm,which includes both the effects of the water load and temperature effects.Furthermore a comprehensive geodetic network was established,57 joint meters were installed and cracks in the crest gallery are monitored by crack meters.There are also thermometers,piczometers and rocmeters.Springs at the left and fight banks of the dam are monitored and chemical analyses of the seepage water and springs are performed regularly.The dam is equipped with strong motion instruments and several near-field earthquakes have been recorded in the past.The paper describes the long-term safety monitoring of this 42 years old arch dam.A short description of the Swiss practice in dam safety monitoring and emergency planning is also given.

Study on the Application of Real-Time Drone Monitoring in Ordos Open-Pit Coal Mine

In the process of intelligent mine construction in open-pit mine, in order to improve the safety monitoring ability of mine transportation system, solve the problems of large human interference and blind Angle detection by existing conventional monitoring methods, this paper establishes an open-pit mine monitoring data set, and proposes a real-time intelligent monitoring model based on UAV. The reasoning component with strong computing power and low power consumption is selected, and the lightweight object detection model is selected for the experiment. A quantitative standard of dynamic energy consumption detection by evaluation algorithm is proposed. Through experimental comparison, it is found that YOLOv4-tiny has the highest comprehensive grade in detection accuracy, speed, energy consumption and other aspects, which is suitable for application in the above model.

Functionalized Hydrogel-Based Wearable Gas and Humidity Sensors

Breathing is an inherent human activity;however,the composition of the air we inhale and gas exhale remains unknown to us.To address this,wearable vapor sensors can help people monitor air composition in real time to avoid underlying risks,and for the early detection and treatment of diseases for home healthcare.Hydrogels with three-dimensional polymer networks and large amounts of water molecules are naturally flexible and stretchable.Functionalized hydrogels are intrinsically conductive,self-healing,self-adhesive,biocompatible,and room-temperature sensitive.Compared with traditional rigid vapor sensors,hydrogel-based gas and humidity sensors can directly fit human skin or clothing,and are more suitable for real-time monitoring of personal health and safety.In this review,current studies on hydrogel-based vapor sensors are investigated.The required properties and optimization methods of wearable hydrogel-based sensors are introduced.Subsequently,existing reports on the response mechanisms of hydrogel-based gas and humidity sensors are summarized.Related works on hydrogel-based vapor sensors for their application in personal health and safety monitoring are presented.Moreover,the potential of hydrogels in the field of vapor sensing is elucidated.Finally,the current research status,challenges,and future trends of hydrogel gas/humidity sensing are discussed.

Identifying and managing risks of AI-driven operations:A case study of automatic speech recognition for improving air traffic safety

In this work,the primary focus is to identify potential technical risks of Artificial Intel-ligence(AI)-driven operations for the safety monitoring of the air traffic from the perspective of speech communication by studying the representative case and evaluating user experience.The case study is performed to evaluate the AI-driven techniques and applications using objective metrics,in which several risks and technical facts are obtained to direct future research.Considering the safety–critical specificities of the air traffic control system,a comprehensive subjective evaluation is conducted to collect user experience by a well-designed anonymous questionnaire and a face-to-face interview.In this procedure,the potential risks obtained from the case study are confirmed,and the impacts on human working are considered.Both the case study and the evaluation of user experience provide compatible results and conclusions:(A)the proposed solution is promising to improve the traffic safety and reduce the workload by detecting potential risks in advance;(B)the AI-driven techniques and whole diagram are suggested to be enhanced to eliminate the possible distraction to the attention of air traffic controllers.Finally,a variety of strategies and approaches are discussed to explore their capability to advance the proposed solution to industrial practices.

China-made Monitoring Apparatus for Mine Safety

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Deformation Measurement of Glass Structure Using FBG Sensor

Glass has been widely used as an important component in structures such as reflection glass curtainwalls,high speed trains,and landscape glass bridges with advantages of transparent and easy to clean,which are exposed to extreme weather conditions and external loads.Over time,these factors can lead to a damage of glass.So the health status of glass structure is critical,which should be routinely monitored to improve safety and provide reliable maintenance strategy.In this paper,fiber Bragg grating(FBG)sensors are used to monitor glass damage based on the fact that the main components of both the optical fiber and the glass are silica,which hints that both optical fiber and glass have the similar mechanical properties.Furthermore,the diameter of FBG installed on the glass structure is small,which has little effect on the beauty of glass.In order to validate the feasibility of the damage monitoring method,one common glass panel model with two-side fixations is loaded impact and static loads respectively,on the upper and lower surfaces of which four FBG sensors and two resistance strain gages are installed.A comparison study among the measured strains from the FBG sensors,those from the resistance strain gages,and those calculated from finite element model(FEM)analysis is conducted and the result obtained with experiments agrees with the element result.Test results show that the FBG sensors can effectively measure the glass deformation or damage under the impact and static load.

Analysis method of thermal dam deformation

Based on the internal temperature variation of a dam lagging behind the ambient temperature variation,the ambient temperature of continuous variation is disctetized,and the functional expression of the thermal displacement component of the dam caused by single instantaneous temperature variation is obtained.Considering the temporal and spatial distribution law of the ambient temperature and its relation with air and water temperature,the function is expanded into a Taylor series.As a result,the improved thermal displacement component expression for a dam monitoring model is obtained.