Big Model Strategy for Bridge Structural Health Monitoring Based on Data-Driven, Adaptive Method and Convolutional Neural Network (CNN) Group

This study introduces an innovative“Big Model”strategy to enhance Bridge Structural Health Monitoring(SHM)using a Convolutional Neural Network(CNN),time-frequency analysis,and fine element analysis.Leveraging ensemble methods,collaborative learning,and distributed computing,the approach effectively manages the complexity and scale of large-scale bridge data.The CNN employs transfer learning,fine-tuning,and continuous monitoring to optimize models for adaptive and accurate structural health assessments,focusing on extracting meaningful features through time-frequency analysis.By integrating Finite Element Analysis,time-frequency analysis,and CNNs,the strategy provides a comprehensive understanding of bridge health.Utilizing diverse sensor data,sophisticated feature extraction,and advanced CNN architecture,the model is optimized through rigorous preprocessing and hyperparameter tuning.This approach significantly enhances the ability to make accurate predictions,monitor structural health,and support proactive maintenance practices,thereby ensuring the safety and longevity of critical infrastructure.

Review and Prospect of Research on Structural Health Monitoring Technology for Bridges

As a crucial infrastructure in the transport system,the safe operation of bridges is directly related to all aspects of people’s daily lives.The development of bridge structural health monitoring technology and its application play an important role in ensuring the safety and extending the service life of bridges.This paper carries out in-depth research and analysis on the related technology of bridge structural health monitoring.Firstly,the existing monitoring technologies at home and abroad are sorted out,and the advantages and problems of various methods are compared and analyzed,including nondestructive testing,stress measurement,vibration characteristic identification,and other commonly used monitoring technologies.Secondly,the key technologies and equipment in the bridge health monitoring system,such as sensor technology,data acquisition,and processing technology,are introduced in detail.Finally,the development trend in the field of bridge health monitoring is prospected from both theoretical research and technical application.In the future,with the development of emerging technologies such as big data,cloud computing,and the Internet of Things,it is expected that bridge health monitoring with intelligent and systematic features will be more widely applied to provide a stronger guarantee for the safe and efficient operation of bridges.

Fatigue Safety Assessment of Concrete Continuous Rigid Frame Bridge Based on Rain Flow Counting Method and Health Monitoring Data

The fatigue of concrete structures will gradually appear after being subjected to alternating loads for a long time,and the accidents caused by fatigue failure of bridge structures also appear from time to time.Aiming at the problem of degradation of long-span continuous rigid frame bridges due to fatigue and environmental effects,this paper suggests a method to analyze the fatigue degradation mechanism of this type of bridge,which combines long-term in-site monitoring data collected by the health monitoring system(HMS)and fatigue theory.In the paper,the authors mainly carry out the research work in the following aspects:First of all,a long-span continuous rigid frame bridge installed with HMS is used as an example,and a large amount of health monitoring data have been acquired,which can provide efficient information for fatigue in terms of equivalent stress range and cumulative number of stress cycles;next,for calculating the cumulative fatigue damage of the bridge structure,fatigue stress spectrum got by rain flow counting method,S-N curves and damage criteria are used for fatigue damage analysis.Moreover,it was considered a linear accumulation damage through the Palmgren-Miner rule for the counting of stress cycles.The health monitoring data are adopted to obtain fatigue stress data and the rain flow counting method is used to count the amplitude varying fatigue stress.The proposed fatigue reliability approach in the paper can estimate the fatigue damage degree and its evolution law of bridge structures well,and also can help bridge engineers do the assessment of future service duration.

Operational modal identification of suspension bridge based on structural health monitoring system

An output-only modal identification method by a combination use of the peak-picking method and the cross spectrum methods are presented. Meanwhile, a novel mode shape optimum method of the deck is proposed. The methods are applied to the operational modal identification system of the Runyang Suspension Bridge, which can be used to obtain the modal parameters of the bridge from out-only data sets collected by its structural health monitoring system （SHMS）. As an example, the vibration response data of the deck, cable and tower recorded during typhoon Matsa excitation are used to illustrate the program application. Some of the modal frequencies observed from deck vibration responses are also found in the vibration responses of the cable and the tower. The results show that some modal shapes of the deck are strongly coupled with the cable and the tower. By comparing the identification results from the operational modal system with those from field measurements, a good agreement between them is achieved, but some modal frequencies identified from the operational modal identification system （OMIS）, such as L1 and L2, obviously decrease compared with those from the field measurements.

Sensor placement of long-term health monitoring for large bridges based on the real-time correction of finite element model

The process of optimized placement of long-term health monitoring sensors for large bridges generally begins with finite element models, but there will arise great discrepancies between theoretically-calculated results and actual measurements.Therefore, rectified finite element models need to be rectified by virtue of model rectifying technology. Firstly, the result of construction monitoring and finished state load test is used to real-time modification of finite element model. Subsequently, an accurate finite element model is established. Secondly, the optimizing the layout of sensor with following orthogonality guarantees orthogonal property and linear independence for the measured data. Lastly, the effectiveness and feasibility of method in the paper is tested by real-time modifying finite element model and optimizing the layout of sensor for Nujiang Bridge.

Structural condition assessment of long-span suspension bridges using long-term monitoring data

This paper focuses on developing an online structural condition assessment technique using long-term monitoring data measured by a structural health monitoring system. The seasonal correlations of frequency-temperature and beam-end displacement-temperature for the Runyang Suspension Bridge are performed, first. Then, a statistical modeling technique using a six-order polynomial is further applied to formulate the correlations of frequency-temperature and displacement-temperature, from which abnormal changes of measured frequencies and displacements are detected using the mean value control chart. Analysis results show that modal frequencies of higher vibration modes and displacements have remarkable seasonal correlations with the environmental temperature and the proposed method exhibits a good capability for detecting the micro damage-induced changes of modal frequencies and displacements. The results demonstrate that the proposed method can effectively eliminate temperature complications from frequency and displacement time series and is well suited for online condition monitoring of long-span suspension bridges.

Structural health monitoring of long-span suspension bridges using wavelet packet analysis

During the service life of civil engineering structures such as long-span bridges, local damage at key positions may continually accumulate, and may finally result in their sudden failure. One core issue of global vibration-based health monitoring methods is to seek some damage indices that are sensitive to structural damage, This paper proposes an online structural health monitoring method for long-span suspension bridges using wavelet packet transform （WPT）. The WPT- based method is based on the energy variations of structural ambient vibration responses decomposed using wavelet packet analysis. The main feature of this method is that the proposed wavelet packet energy spectrum （WPES） has the ability to detect structural damage from ambient vibration tests of a long-span suspension bridge. As an example application, the WPES-based health monitoring system is used on the Runyang Suspension Bridge under daily environmental conditions. The analysis reveals that changes in environmental temperature have a long-term influence on the WPES, while the effect of traffic loadings on the measured WPES of the bridge presents instantaneous changes because of the nonstationary properties of the loadings. The condition indication indices VD reflect the influences of environmental temperature on the dynamic properties of the Runyang Suspension Bridge. The field tests demonstrate that the proposed WPES-based condition indication index VD is a good candidate index for health monitoring of long-span suspension bridges under ambient excitations.

Features of long-term health monitored strains of a bridge with wavelet analysis

This paper analyses the five years’ monitored strains collected from a long-term health monitoring system installed on a bridge with wavelet transform.In the analysis,the monitored strains are pre-processed,features of the monitored data are summarized briefly.The influences of the base functions on the results of wavelet analysis are studied simultaneously.The results show that the db wavelet is a good mother wavelet function in the analysis,and the order N should be larger than 20,but less than 46 in decomposing the monitored strains of the bridge.According to the strain variation features of concrete bridge,the proper decomposition level is 4 in the wavelet multi-resolution analysis.With the present method,the strains caused by random loads and daily sunlight can be accurately extracted from the monitored strains.The decomposed components of the monitored strains show that the amplitudes of the strains caused by random loads,daily sunlight,and annual temperature effect,are about 5 με,25 με,and 50 με respectively.The structural response under random load is smaller than the other parts.

Finite element model updating of existing steel bridge based on structural health monitoring

Based on the physical meaning of sensitivity,a new finite element(FE) model updating method was proposed. In this method,a three-dimensional FE model of the Nanjing Yangtze River Bridge(NYRB) with ANSYS program was established and updated by modifying some design parameters. To further validate the updated FE model,the analytical stress-time histories responses of main members induced by a moving train were compared with the measured ones. The results show that the relative error of maximum stress is 2.49% and the minimum relative coefficient of analytical stress-time histories responses is 0.793. The updated model has a good agreement between the calculated data and the tested data,and provides a current baseline FE model for long-term health monitoring and condition assessment of the NYRB. At the same time,the model is validated by stress-time histories responses to be feasible and practical for railway steel bridge model updating.

Engineering approach to in-situ bridge health monitoring with fiber bragg gratings

In this presentation the feasibility and capability of fiber Bragg gratings （FBG） employed in bridge health monitoring are demonstrated on a real bridge. FBG＇ s wavelength shift depending on strain variance has been tested. The technique of FBG installation on bridges has been developed. 12 FBG strain sensors and 3 temperature sensors have been successfully embedded in the prestressed concrete box girder during the construction of Heilongjiang Hulan River Bridge. The prestressing tension process and quasi-static loading process of the girder were monitored with those sensors before it was installed onto the bridge. After the bridge was completed, the FBG sensors embedded have been utilized to monitor the strain shift of the beam under quasi-static load, traffic load and temperature. The results show that the traffic fluxes, possible tatigue damage and deflection of the bridge can be revealed conveniently through strain measurements with these FBG sensors, which provide key information for structural health diagnosis. The fact that the FBG strain sensors have withstood the ordeal of harsh construction process and lasted for more than one year proves that their durability and stability can satisfy the requirements for bridge health monitoring. It is also shown that the FBG strain sensor is more adaptive to long-term structural health monitoring than the electric resistance strain gauge.

Fatigue damage reliability analysis for Nanjing Yangtze river bridge using structural health monitoring data

To evaluate the fatigue damage reliability of critical members of the Nanjing Yangtze river bridge, according to the stress-number curve and Miner’s rule, the corresponding expressions for calculating the structural fatigue damage reliability were derived. Fatigue damage reliability analysis of some critical members of the Nanjing Yangtze river bridge was carried out by using the strain-time histories measured by the structural health monitoring system of the bridge. The corresponding stress spectra were obtained by the real-time rain-flow counting method. Results of fatigue damage were calculated respectively by the reliability method at different reliability and compared with Miner’s rule. The results show that the fatigue damage of critical members of the Nanjing Yangtze river bridge is very small due to its low live-load stress level.

Health monitoring and comparative analysis of time-dependent effect using different prediction models for self-anchored suspension bridge with extra-wide concrete girder

The structural health status of Hunan Road Bridge during its two-year service period from April 2015 to April 2017 was studied based on monitored data.The Hunan Road Bridge is the widest concrete self-anchored suspension bridge in China at present.Its structural changes and safety were evaluated using the health monitoring data,which included deformations,detailed stresses,and vibration characteristics.The influences of the single and dual effects comprising the ambient temperature changes and concrete shrinkage and creep(S&C)were analyzed based on the measured data.The ANSYS beam finite element model was established and validated by the measured bridge completion state.The comparative analyses of the prediction results of long-term concrete S&C effects were conducted using CEB-FIP 90 and B3 prediction models.The age-adjusted effective modulus method was adopted to simulate the aging behavior of concrete.Prestress relaxation was considered in the stepwise calculation.The results show that the transverse deviations of the towers are noteworthy.The spatial effect of the extra-wide girder is significant,as the compressive stress variations at the girder were uneven along the transverse direction.General increase and decrease in the girder compressive stresses were caused by seasonal ambient warming and cooling,respectively.The temperature gradient effects in the main girder were significant.Comparisons with the measured data showed that more accurate prediction results were obtained with the B3 prediction model,which can consider the concrete material parameters,than with the CEB-FIP 90 model.Significant deflection of the midspan girder in the middle region will be caused by the deviations of the cable anchoring positions at the girder ends and tower tops toward the midspan due to concrete S&C.The increase in the compressive stresses at the top plate and decrease in the stresses at the bottom plate at the middle midspan will be significant.The pre-deviations of the towers toward the sidespan and pre-lift of the midspan girder can reduce the adverse influences of concrete S&C on the structural health of the self-anchored suspension bridge with extra-wide concrete girder.

Rigid Bridges Health Dynamic Monitoring Using 100 Hz GPS Single-Frequency and Accelerometers

This article presents the modal frequency recordings of a rigid bridge, monitored by the GPS receivers (Global Positioning System) with a data recording rate of 100 Hz and accelerometers. The GPS data processing was performed through the double-difference phase, using the adjusted interferometry technique (i.e. phase residue method—PRM&reg). In the method, the double-difference phase of the carrier L1 is realized by using two satellites only, one was positioned at the zenith of the structure and the other satellite was positioned near the horizon. The results of the parametric adjustment of the PRM observations were finalized through software Interferometry, mathematical algorithm were applied and compared with the accelerometer. The comparison served to validate the use of GPS as a fast and reliable instrument for the preliminary monitoring of the dynamic behavior of the bridge, road artworks which are common in several countries, especially in the Brazilian road network. The data time series from the GPS and accelerometers were processed using the Wavelet. The detection of frequencies means that the combination of 100 Hz GPS receivers and the PRM allows detecting vibrations up to 5 mm. It presented significant results which were never obtained by the Fourier Transform.

Application of Wireless Monitoring System to Structural Health Monitoring of Long-Spanned Cable-Stayed Bridge

The remote monitoring system applied to the construction control and health monitoring of the Nanjing Third Yangtze River Bridge is introduced. The System makes it possible to get the structure capabilities and environmental parameters of the bridge at the predetermined moment. It sends the collected data over a long distance to an assigned position for display and analysis. The related methods and working condition of the wireless monitoring system are discussed. The measured data during 48 h are employed to determine the feasibility for the closure of the bridge.

Long Term Application of a Vehicle-Based Health Monitoring System to Short and Medium Span Bridges and Damage Detection Sensitivity

Largest portion of the bridge stock in almost any country and bridge owning organisation consists on ordinary bridges that has short or medium spans and are now deteriorating due to aging, etc. Therefore, it is becoming an important social concern to develop and put to practical use simple and efficient health monitoring systems for existing short and medium span (10 - 30 m) bridges. In this paper, one practical solution to the problem for condition assessment of short and medium span bridges was discussed. A vehicle-based measurement with a public bus as part of a public transit system (called “Bus monitoring system”) has been developed to be capable of detecting damage that may affect the structural safety of a bridge from long term vibration measurement data collected while the vehicle (bus) crossed the target bridges. This paper systematically describes how the system has been developed. The bus monitoring system aims to detect the transition from the damage acceleration period, in which the structural safety of an aged bridge declines sharply, to the deterioration period by continually monitoring the bridge of interest. To evaluate the practicality of the newly developed bus monitoring system, it has been field-tested over a period of about four years by using an in-service fixed-route bus operating on a bus route in the city of Ube, Yamaguchi Prefecture, Japan. The verification results thus obtained are also described in this paper. This study also evaluates the sensitivity of “characteristic deflection”, which is a bridge (health) condition indicator used by the bus monitoring system, in damage detection. Sensitivity of “characteristic deflection” is verified by introducing artificial damage into a bridge that has ended its service life and is awaiting removal. As the results, it will be able to make a rational long-term health monitoring system for existing short and mediumspan bridges, and then the system helps bridge administrators to establish the rational maintenance strategies.

Health Monitoring-Based Assessment of Reinforcement with Prestressed Steel Strand for Cable-Stayed Bridge

This paper presents the method of reinforcing main girder of reinforced concrete cable-stayed bridge with prestressed steel strands.To verify the effectiveness of external prestressed strand reinforcement method.Static load tests and health monitoring-based assessment were carried out before and after reinforcement.Field load test shows that the deflection and stress values of the main girder are reduced by 10%~20%after reinforcement,and the flexural strength and stiffness of the strengthened beam are improved.The deflection and strain data of health monitoring of the specified section are collected.The deflection of the second span is 4 mm~10 mm,the strain range of the upper edge of the second span is-10με~-40με,and the strain range of the lower edge is 30με~75με.These values show the deflection and strain values fluctuate within a prescribed range,verifying the safety of the bridge.The reinforcement method of prestressed steel strand is feasible and effective.It can provide reference basis for the application of external prestressed strand reinforcement technology in similar projects.

Outlier Detection and Forecasting for Bridge Health Monitoring Based on Time Series Intervention Analysis

The method of time series analysis,applied by establishing appropriate mathematical models for bridge health monitoring data and making forecasts of structural future behavior,stands out as a novel and viable research direction for bridge state assessment.However,outliers inevitably exist in the monitoring data due to various interventions,which reduce the precision of model fitting and affect the forecasting results.Therefore,the identification of outliers is crucial for the accurate interpretation of the monitoring data.In this study,a time series model combined with outlier information for bridge health monitoring is established using intervention analysis theory,and the forecasting of the structural responses is carried out.There are three techniques that we focus on:(1)the modeling of seasonal autoregressive integrated moving average(SARIMA)model;(2)the methodology for outlier identification and amendment under the circumstances that the occurrence time and type of outliers are known and unknown;(3)forecasting of the model with outlier effects.The method was tested with a case study using monitoring data on a real bridge.The establishment of the original SARIMA model without considering outliers is first discussed,including the stationarity,order determination,parameter estimation and diagnostic checking of the model.Then the time-by-time iterative procedure for outlier detection,which is implemented by appropriate test statistics of the residuals,is performed.The SARIMA-outlier model is subsequently built.Finally,a comparative analysis of the forecasting performance between the original model and SARIMA-outlier model is carried out.The results demonstrate that proper time series models are effective in mining the characteristic law of bridge monitoring data.When the influence of outliers is taken into account,the fitted precision of the model is significantly improved and the accuracy and the reliability of the forecast are strengthened.

Field Load Test Based SHM System Safety Standard Determination for Rigid Frame Bridge

The deteriorated continuous rigid frame bridge is strengthened by external prestressing. Static loading tests wereconducted before and after the bridge rehabilitation to verify the effectiveness of the rehabilitation process. Thestiffness of the repaired bridge is improved, and the maximum deflection of the load test is reduced from 37.9 to27.6 mm. A bridge health monitoring system is installed after the bridge is reinforced. To achieve an easy assessmentof the bridge’s safety status by directly using transferred data, a real-time safety warning system is createdbased on a five-level safety standard. The threshold for each safety level will be determined by theoretical calculationsand the outcomes of static loading tests. The highest risk threshold will be set at the ultimate limit statevalue. The remaining levels, namely middle risk, low risk, and very low risk, will be determined usingreduction coefficients of 0.95, 0.9, and 0.8, respectively.

Development of IoT-Based Condition Monitoring System for Bridges

As of April 2019,India has 1,42,126 kilometres of National Highways and 67,368 kilometres of railway tracks that reach even the most remote parts of the country.Bridges are critical for both passenger and freight movement in the country.Because bridges play such an important part in the transportation system,their safety and upkeep must be prioritized.Manual Condition Monitoring has the disadvantage of being sluggish,unreliable,and inefficient.The Internet of Things has given structural monitoring a boost.Significant decreases in the cost of electronics and connection,together with the expansion of cloud platforms,have made it possible to collect large amounts of data remotely,aggregate it,and perform essential analysis to generate actionable insights.This research focuses on a scalable system for monitoring the state of bridges,such as vibration and loading,employing multimodal inputs,controllers,and Wi-Fi modules.The accelerometer and load cells were installed on the prototype,tested for a sample load(56.21 grams_(avg),590 grams_(max),and 147.66 grams_(rms))with induced vibration(5.87 m/sec^(2)_(avg),18 m/sec^(2)_(max),and 7.04 m/sec^(2)_(rms))that are processed,displayed on-board,and uploaded to ThingSpeak cloud service.This system will aid the maintenance personnel in remotely monitoring it.This system can send out notifications if any of these parameters exceeds their threshold value,allowing you to take preventive measures ahead of time.