Damage warning of suspension bridges based on neural networks under changing temperature conditions

This paper aims at successive structural damage detection of long-span bridges under changing temperature conditions.First,the frequency-temperature correlation models of bridges are formulated by means of artificial neural network techniques to eliminate the temperature effects on the measured modal frequencies.Then,the measured modal frequencies under various temperatures are normalized to a reference temperature,based on which the auto-associative network is trained to monitor signal damage occurrences by means of neural-network-based novelty detection techniques.The effectiveness of the proposed approach is examined in the Runyang Suspension Bridge using 236-day health monitoring data.The results reveal that the seasonal change of environmental temperature accounts for variations in the measured modal frequencies with averaged variances of 2.0%.And the approach exhibits good capability for detecting the damage-induced 0.1% variance of modal frequencies and it is suitable for online condition monitoring of suspension bridges.

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.

Effective LiDAR Damage Detection:Comparing Two Detection Algorithms

The health conditions of highway bridges is critical for sustained transportation operations.US federal government mandates that all bridges built with public funds are to be inspected visually every two years. There is a growing consensus that additional rapid and non-intrusive methods for bridge damage evaluation are needed.This paper explores the potential of applying ground-based laser scanners for bridge damage evaluation. LiDAR has the potential of providing high-density,full-field surface static imaging.Hence,it can generate volumetric quantification of concrete corrosion or steel erosion.By recording object surface topology,LiDAR can detect different damages on the bridge structure and differentiate damage types according to the surface flatness and smoothness.To determine the effectiveness of LiDAR damage detection,two damage detection algorithms are presented and compared using scans on actual bridge damages.The results demonstrate and validate LiDAR damage quantification,which can be a powerful tool for bridge condition evaluation.

Damage detection of long-span bridges using stress influence lines incorporated control charts

Numerous long-span bridges have been built throughout the world in recent years.These bridges are progressively damaged by continuous usage throughout their long service life.The failure of local structural components is detrimental to the performance of the entire bridge,furthermore,detecting the local abnormality at an early stage is difficult.This paper explores a novel damage detection method for long-span bridges by incorporating stress influence lines(SILs)in control charts,and validates the efficacy of the method through a case study of the Tsing Ma Suspension Bridge.Damage indices based on SILs are subsequently proposed and applied to hypothetical damage scenarios in which one or two critical bridge components are subjected to severe damage.The comparison study suggests that the first-order difference of SIL change is an accurate indicator for location of the damage.To some extent,different levels of damage can be quantified by using SILs incorporating with X-bar control chart.Results of this study indicate that the proposed SIL-based method offers a promising technique for damage detection in long-span bridges.

Multiple damage detection in complex bridges based on strain energy extracted from single point measurement

Strain Energy of the structure can be changed with the damage at the damage location.The accurate detection of the damage location using this index in a force system is dependent on the degree of accuracy in determining the structure deformation function before and after damage.The use of modal-based methods to identify damage in complex bridges is always associated with problems due to the need to consider the effects of higher modes and the adverse effct of operational conditions on the extraction of structural modal parameters.In this paper,the deformation of the structure was determined by the concept of influence line using the Betti-Maxwell theory.Then two damage detection indicators were developed based on strain energy variations.These indices were presented separately for bending and torsion changes.Finite element analysis of a five-span concrete curved bridge was done to validate the stated methods.Damage was simulated by decreasing stiffness at different sections of the deck.The response regarding displacement ofa point on the deck was measured along each span by passing a moving load on the bridge at very low speeds.Indicators of the strain energy extracted from displacement influence line and the strain energy extracted from the rotational displacement influence line(SERIL)were calculated for the studied bridge.The results show that the proposed methods have well identified the location of the damage by significantly reducing the number of sensors required to record the response.Also,the location of symmetric damages is detected with high resolution using SERIL.

Damage Detection for Simply Supported Bridge with Bending Fuzzy Stiffness Consideration

The benchmark of a simply supported beam with damage and bending fuzzy stiffness consideration is established to be utilized for damage detection. The explicit expression describing the Rotational Angle Influence Lines(RAIL) of the arbitrary section in the benchmark is presented as the nonlinear relation between the moving load and the RAIL appeared, when the moving load is located on the damage area. The damage detection method is derived based on the Difference of the RAIL Curvature(DRAIL-C) prior to and following arbitrarily section damage in a simply supported beam with bending fuzzy stiffness consideration. The results demonstrate that the damage position can be located by the DRAIL-C graph and the damage extent can be calculated by the DRAIL-C curve peak. The simply supported box girder as a one-dimensional model and the simply supported truss bridge as a three-dimensional model with the bending fuzzy stiffness are simulated for the validity of the proposed method to be verified. The measuring point position and noise intensity effects are discussed in the simply supported box girder example. This paper provides a new consideration and technique for the damage detection of a simply supported bridge with bending fuzzy stiffness consideration.

Damage alarming for bridge expansion joints using novelty detection technique based on long-term monitoring data

Damage alarming and safety evaluation using long-term monitoring data is an area of significant research activity for long-span bridges. In order to extend the research in this field, the damage alarming technique for bridge expansion joints based on long-term monitoring data was developed. The effects of environmental factors on the expansion joint displacement were analyzed. Multiple linear regression models were obtained to describe the correlation between displacements and the dominant environmental factors. The damage alarming index was defined based on the multiple regression models. At last, the X-bar control chart was utilized to detect the abnormal change of the displacements. Analysis results reveal that temperature and traffic condition are the dominant environmental factors to influence the displacement. When the confidence level of X-bar control chart is set to be 0.003, the false-positive indications of damage can be avoided. The damage sensitivity analysis shows that the proper X-bar control chart can detect 0.1 cm damage-induced change of the expansion joint displacement. It is reasonably believed that the proposed technique is robust against false-positive indication of damage and suitable to alarm the possible future damage of the expansion joints.

Damage alarming of long-span suspension bridge based on GPS-RTK monitoring

Structure damage identification and alarming of long-span bridge were conducted with three-dimensional dynamic displacement data collected by GPS subsystem of health monitoring system on Runyang Suspension Bridge.First,the effects of temperature on the main girder spatial position coordinates were analyzed from the transverse,longitudinal and vertical directions of bridge,and the correlation regression models were built between temperature and the position coordinates of main girder in the longitudinal and vertical directions;then the alarming indices of coordinate residuals were conducted,and the mean-value control chart was applied to making statistical pattern identification for abnormal changes of girder dynamic coordinates;and finally,the structural damage alarming method of main girder was established.Analysis results show that temperature has remarkable correlation with position coordinates in the longitudinal and vertical directions of bridge,and has weak correlation with the transverse coordinates.The 3%abnormal change of the longitudinal coordinates and 5%abnormal change of the vertical ones caused by structural damage are respectively identified by the mean-value control chart method based on GPS dynamic monitoring data and hence the structural abnormalities state identification and damage alarming for main girder of long-span suspension bridge can be realized in multiple directions.

Dynamic Detection of Reinforced Concrete Bridge Damage by Finite Element Model Updating

The present work consists of dynamic detection of damages in reinforced concrete bridges by using a MMUM （mathematical model updating method） from incomplete test data. A well suited finite element model of a repaired bridge is carried out. The diagnosis enables us to locate and detect the damage in a reinforced concrete bridge. Thus, developments of analytical predictions have been checked by modal testing techniques. Besides, the FTCS （finite time centered space） scheme is developed to solve the set of equations which can easily handle finite element matrices of a bridge model. It is shown in this study that the method is applied to detect damages as well as existing cracks in real time of a repaired bridge. To check the efficiency of the method, the repaired bridge of OuedOumazer in Algeria has been selected. It is proven that identification methods have been able to detect the exact location of damage areas to be corrected avoiding the inaccuracy from the finite element model for the mass, stiffness and loading.

DAMAGE ANALYSIS AND LOCATION OF RUNYANG BRIDGE USING MULTI-LAYER PERCEPTRON

A damage location method using multi-layer perceptron （MLP） is developed to diagnose the cable damage of a real long span cable-stayed bridge. Firstly, the damage patterns are defined based on dynamical calculation. The analysis of damage pattern reveals that the damage patterns caused by different damage locations have inherent distinctness, while the damage extent only linearly amplifies the damage pattern curves. And 4th, 6th and 7th order frequencies are canceled from the patterns because of their insensitiveness to cable damage. Then a MLP network is designed by trail-error method to describe the 7-D mapping space of damage pattern. Identification results prove that the properly organized MLP can grasp the damage pattern and identify the damage location.

火灾后斜拉桥斜拉索损伤检测与结构安全性能评定方法研究

为准确分析火灾后斜拉桥斜拉索损伤状况,评定桥梁结构安全性能,根据桥梁火灾应急检测工程需求,提出一套火灾后斜拉桥斜拉索损伤检测与结构安全性能评定方法。该方法包括火灾现场勘察、斜拉索烧损状况检查、斜拉索损伤检测分析和结构安全性能评定4个阶段。根据斜拉索火灾损伤特点,开展高温后斜拉索高强钢丝和高密度聚乙烯(HDPE)护套试件拉伸试验,研究其高温后表观特征和力学性能指标随历经温度的变化规律,建立斜拉索历经温度及损伤定量检测分析计算公式,并将该方法应用于某独塔预应力混凝土斜拉桥火灾后斜拉索损伤检测与结构安全性能评定。结果表明:高温后斜拉索高强钢丝和HDPE护套的表观特征、力学性能均随温度升高呈现出明显的规律性变化;随着温度升高,高温后斜拉索高强钢丝的抗拉强度、屈服强度先降低后升高,弹性模量衰减缓慢,HDPE护套断裂标称应变逐渐降低;火灾后斜拉索和主梁承载能力满足使用要求,结构整体安全;所提出的火灾后斜拉桥斜拉索损伤检测与结构安全性能评定方法科学、实用、有效,可为火灾后斜拉桥损伤检测评定、营运管理和维修处治提供技术借鉴。

结合逆非线性主成分分析和极值理论的桥梁损伤检测

为提高环境和运营变化(environmental and operational variations,EOV)影响下的桥梁损伤检测可靠性,结合逆非线性主成分分析(inverse nonlinear principal component analysis,INLPCA)和极值理论,提出一种新的桥梁损伤检测方法.该方法采用INLPCA对桥梁损伤特征进行建模,利用不完备健康监测数据的估计均方误差和添加神经网络训练惩罚项控制INLPCA的非线性程度.采用INLPCA对损伤特征的重构误差和马氏平方距离(Mahalanobis squared distance,MSD)建立损伤指标(ID),最后基于ID的广义极值(generalized extreme value,GEV)分布建立损伤检测阈值.以比利时KW51铁路桥和天津永和斜拉桥为例,验证所提方法的有效性.结果表明,所提方法能准确检测EOV影响下的桥梁损伤,且对不同桥型和不同损伤特征均有良好的适用性.

新型无监督聚类算法监测与评估桥梁结构健康状况

近年来,因车辆超载、结构设计缺陷、施工质量问题等原因导致的城市高架桥梁倒塌事故时有发生。因此,首次提出了一种可实时监测高架桥梁运行状况、通过改进K-means聚类算法实现对结构损伤实时检测、对数据驱动结构损伤进行检测的高效方法。该方法主要是对钢结构桥梁模型在结构完好状态下的振动数据进行采集,然后通过深度研究从这些数据中提取有效的结构损伤敏感特征值,最后利用改进的无监督聚类算法训练奇异值检测模型。试验结果表明,采用桥梁结构完好状况下的损伤敏感特征值作为训练数据,对数学模型加以训练后,可以有效检测并识别出桥梁结构在不同损伤状况下的测试结果。该新型检测方法可实现城市高架桥梁在长期运营阶段的结构健康实时监测。

基于改进贝叶斯网络方法的跨海悬索桥多灾害风险评估

为评估大跨度悬索桥在持续风荷载和偶发地震下的综合风险,将桥梁运营期间结构损伤概率的定量分析和损伤后果的定性评估相结合,提出了一种基于改进贝叶斯网络的跨海悬索桥风险评估框架.首先,分析桥位处的风灾和地震灾害,根据悬索桥的特点获取各构件的损伤程度;其次,利用结构可靠度理论,计算桥梁结构失效概率;最后,提出了基于改进贝叶斯网络的悬索桥风险评估模型,并对桥梁运营期风险进行评估.结果表明,考虑不同构件对桥梁的影响程度,根据桥梁的承灾能力将桥梁损伤分为4级.以伶仃洋大桥为例,采用所提方法得到多灾害风险下该桥最大风险等级为3级,需限制通行并进行检修,说明该方法能够指导跨海桥梁应对多风险灾害的应急管理策略.

强噪背景下基于改进匹配追踪算法的桥梁缆索缺陷识别

为降低噪声对磁致伸缩导波信号的干扰,实现强噪背景下的桥梁缆索缺陷识别,提出了一种基于改进匹配追踪算法的桥梁缆索缺陷识别方法。首先,采用构建非对称Gabor函数作为原子字典,将相邻残差比作为迭代终止条件,对强噪背景下的导波信号进行匹配追踪。然后,通过缺陷回波包络峰值时刻,对桥梁缆索缺陷进行了定位。最后,对采用不同降噪方法时的桥梁缆索缺陷定位误差进行了比较。结果表明:未添加噪声时,采用缺陷回波包络峰值时刻定位桥梁拉索缺陷,最大误差仅为0.28%。当缺陷回波的信噪比高于-5 dB时,采用本文方法进行降噪,均方差E_(MSE)几乎为0,信噪比E_(SNR)增加到7.56 dB以上。采用本文方法对含噪导波信号进行降噪,其降噪精度和缺陷定位精度均优于小波阈值降噪、小波-EMD降噪和传统匹配追踪降噪。当导波信号信噪比为-5 dB及以下时,本文方法的优越性更为显著。即使导波信号信噪比达到-10 dB,采用本文方法进行降噪处理,拉索缺陷定位误差仍能达到1.5%以内。可见所提出的方法可以有效降低强噪声对实测导波的干扰,提高桥梁缆索缺陷识别精度。

频率法及千斤顶法在钢桁架悬索桥病害检测中的应用

文中以某钢桁架悬索桥工程为例,对其病害情况进行详细分析,对比主缆、钢桁架加劲梁变形及重要构件锈蚀状况的检测数据,提出维护建议。通过数据比对,文中采用千斤顶法、频率法测量与修正吊杆索力水平,借助空间节点平衡理论获取不同主缆段索力值。结果表明,主缆与吊杆索力、主缆与主桁架的空间变形关系密切。

钢管混凝土吊杆拱桥检测评估及加固改造探讨

文中以贵州省普通国省干线公路桥梁定期检查服务QLDJ-01标段钢管混凝土吊杆拱桥为例,对该桥的检测评估及加固改造方案进行分析;针对病害情况,提出更换吊杆、增设加劲纵梁、主拱圈灌浆、拱座加固、混凝土构件缺陷修复等加固改造方案,以提高桥梁结构安全性。

基于动力指纹识别桥梁损伤检测方法研究

桥梁作为交通网格的关键组成的部分,其结构安全性能日益受到关注。桥梁损伤检测是确保桥梁安全运营的关键环节。然而,长期运营过程中易受多种因素影响而出现结构损伤,及时准确地识别这些损伤对于保障桥梁安全运营至关重要。本文通过对动力指纹原理、频率、振型及曲率模态进行分析,旨在单损简支箱梁振型变化值与损伤程度无关,与梁的损伤位置有关,且对应损伤单元处有突变,识别桥梁损伤位置;而受损梁曲率模态分析,在1/2跨中单元(15#、16#)损伤的位置第一阶曲率模态曲线各有一段平台。

基于空陆两栖无人机的桁架桥梁构件损伤检测与识别研究

在运营使用过程中,桁架桥梁构件会出现不同程度的损伤,现有检测手段成本高,实施复杂,损伤评定较为粗糙。针对这一问题,文章结合前期发明的空陆两栖无人机设备与振动信号处理技术,通过提取的桥梁桁架模态参数获得其状态信息,采用傅里叶变换等信号处理方法对桥梁桁架损伤进行识别及定位,实现桥梁桁架损伤的智能化识别。

Damage assessment of a continuous beam bridge based on the strain mode

Based on the method of strain mode, damage identification of continuous beam bridges by comparing the variance of several curves of strain modes difference is studied. Three cases of numerical simulation demonstrate that the proposed method is applicable to detecting many a damage in a continuous beam bridge, which accurately identifies the damaged positions of the bridge, and detects the damage severity of an element by its according peak value of the curve of strain modes difference that is found to increase with the increasing damage severity.