scholarly journals Structural Health Monitoring of the Rebecca Street (William Anderson) Bridge

2021 ◽  
Author(s):  
Canon Shafieyan
Keyword(s):  
Structural Health Monitoring ◽  
Shear Wave ◽  
Health Monitoring ◽  
Prediction Models ◽  
Condition Index ◽  
Structural Condition ◽  
Analytical Models ◽  
Accurate Information ◽  
Structural Health ◽  
The Future

This research investigation is to employ a Structural Health Monitoring (SHM) strategy for the Rebecca Street Bridge to provide accurate information regarding the structural behavior and performance of the bridge during regular operation. The research investigation included visual inspection and structural assessment using the MIRA 3D shear wave tomographer to evaluate the bridge structural condition. The overall structural condition of the bridge is good and no major deterioration was noted. However, the voids detected during the shear wave scans could form void clusters in the future, leading to potential cracking and delamination. A monitoring strategy was developed based on the crack width and moment curvature of the concrete cross section using reliability analytical models that would allow for lifetime monitoring. The prediction models used the Bridge Condition Index (BCI) to evaluate the structural condition of the bridge. The future works for the Rebecca Street Bridge includes periodic monitoring as recommended.

scholarly journals Structural Health Monitoring of the Rebecca Street (William Anderson) Bridge

2021 ◽  
Author(s):  
Canon Shafieyan
Keyword(s):  
Structural Health Monitoring ◽  
Shear Wave ◽  
Health Monitoring ◽  
Prediction Models ◽  
Condition Index ◽  
Structural Condition ◽  
Analytical Models ◽  
Accurate Information ◽  
Structural Health ◽  
The Future

This research investigation is to employ a Structural Health Monitoring (SHM) strategy for the Rebecca Street Bridge to provide accurate information regarding the structural behavior and performance of the bridge during regular operation. The research investigation included visual inspection and structural assessment using the MIRA 3D shear wave tomographer to evaluate the bridge structural condition. The overall structural condition of the bridge is good and no major deterioration was noted. However, the voids detected during the shear wave scans could form void clusters in the future, leading to potential cracking and delamination. A monitoring strategy was developed based on the crack width and moment curvature of the concrete cross section using reliability analytical models that would allow for lifetime monitoring. The prediction models used the Bridge Condition Index (BCI) to evaluate the structural condition of the bridge. The future works for the Rebecca Street Bridge includes periodic monitoring as recommended.

scholarly journals SHMnet: Condition assessment of bolted connection with beyond human-level performance

2019 ◽  
Vol 19 (4) ◽  
pp. 1188-1201 ◽  
Author(s):  
Tong Zhang ◽  
Suryakanta Biswal ◽  
Ying Wang
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Structural Condition ◽  
Steel Frame ◽  
Mode Shapes ◽  
Repeated Impact ◽  
Traditional Methods ◽  
Bolted Connection ◽  
Structural Health ◽  
Sensor Locations

Deep learning algorithms are transforming a variety of research areas with accuracy levels that the traditional methods cannot compete with. Recently, increasingly more research efforts have been put into the structural health monitoring domain. In this work, we propose a new deep convolutional neural network, namely SHMnet, for a challenging structural condition identification case, that is, steel frame with bolted connection damage. We perform systematic studies on the optimisation of network architecture and the preparation of the training data. In the laboratory, repeated impact hammer tests are conducted on a steel frame with different bolted connection damage scenarios, as small as one bolt loosened. The time-domain monitoring data from a single accelerometer are used for training. We conduct parametric studies on different layer numbers, different sensor locations, the quantity of the training datasets and noise levels. The results show that the proposed SHMnet is effective and reliable with at least four independent training datasets and by avoiding vibration node points as sensor locations. Under up to 60% additive Gaussian noise, the average identification accuracy is over 98%. In comparison, the traditional methods based on the identified modal parameters inevitably fail due to the unnoticeable changes of identified natural frequencies and mode shapes. The results provide confidence in using the developed method as an effective structural condition identification framework. It has the potential to transform the structural health monitoring practice. The code and relevant information can be found at https://github.com/capepoint/SHMnet .

A Simplified Methodology for Condition Assessment of Bridge Bearings Using Vibration Based Structural Health Monitoring Techniques

2021 ◽  
pp. 2150133
Author(s):  
Babar Nasim Khan Raja ◽  
Saeed Miramini ◽  
Colin Duffield ◽  
Shilun Chen ◽  
Lihai Zhang
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Structural Condition ◽  
Condition Assessment ◽  
Concrete Bridges ◽  
Traffic Loading ◽  
Structural Health ◽  
Vibration Data ◽  
Bridge Bearing ◽  
Bridge Bearings

The mechanical properties of bridge bearings gradually deteriorate over time resulting from daily traffic loading and harsh environmental conditions. However, structural health monitoring of in-service bridge bearings is rather challenging. This study presents a bridge bearing condition assessment framework which integrates the vibration data from a non-contact interferometric radar (i.e. IBIS-S) and a simplified analytical model. Using two existing concrete bridges in Australia as a case study, it demonstrates that the developed framework has the capability of detecting the structural condition of the bridge bearings in real-time. In addition, the results from a series of parametric studies show that the effectiveness of the developed framework is largely determined by the stiffness ratio between bridge bearing and girder ([Formula: see text], i.e. the structural condition of the bearings can only be effectively captured when the value of [Formula: see text] ranges from 1/100 and 100.

An Evaluation of Damage Features Extraction from Attractors in Structural Health Monitoring

2011 ◽  
Vol 105-107 ◽  
pp. 738-741
Author(s):  
Chao Xu ◽  
Dong Wang
Keyword(s):  
Structural Health Monitoring ◽  
State Space ◽  
Health Monitoring ◽  
Prediction Error ◽  
Structural Response ◽  
Accurate Information ◽  
Variance Ratio ◽  
Damage Level ◽  
Structural Health ◽  
Local Variance

Structural health monitoring provides accurate information about structure’s safety and integrity. The vibration-based structural health monitoring involves extracting a feature which robustly quantifies damage induced change to the structure. Recent work has focused on damage features extracted from the state space attractor of the structural response. Some of these features involve prediction error and local variance ratio. In the present paper, a five degree of freedom spring damper system forced by a Lorenz excitation is used to evaluate these two typical damage features. Their ability of identification damage level and location is characterized and compared.

scholarly journals Documentation, structural health monitoring and numerical modelling for damage assessment of the Morris Island Lighthouse

2019 ◽  
Vol 377 (2155) ◽  
pp. 20190002 ◽  
Author(s):  
Anna Blyth ◽  
Rebecca Napolitano ◽  
Branko Glisic
Keyword(s):  
South Carolina ◽  
Structural Analysis ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Structural Damage ◽  
Distinct Element ◽  
Structural Condition ◽  
Present Condition ◽  
Cultural Significance ◽  
Structural Health

Heritage structures serve as invaluable records of cultural achievement that should be preserved for future generations. To ensure the successful preservation of these structures, there must be an affordable and effective way to conduct conservation. The objective of this work is to outline an efficient workflow for the structural analysis of preservation projects through a case study on the Morris Island Lighthouse in Charleston, South Carolina. Thorough documentation of the cultural significance and structural condition of the lighthouse was completed through archival research, photogrammetry and crack mapping. Structural Health Monitoring and Distinct Element Modelling were used to analyse past structural damage and the present condition. The behaviour of masonry and crack propagation was evaluated under gravity, wind, wave and seismic loading. The results of these analyses were summarized in a virtual tour and informational modelling environment, which allows the results to be accessed and associated with their physical location on the structure. The benefits and limitations of this process are discussed, and a standardized workflow for efficient structural analysis of cultural heritage is proposed. This article is part of the theme issue ‘Environmental loading of heritage structures’.

scholarly journals Establishment and Application of the Wind and Structural Health Monitoring System for the Runyang Yangtze River Bridge

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Hao Wang ◽  
Aiqun Li ◽  
Tong Guo ◽  
Tianyou Tao
Keyword(s):  
Structural Health Monitoring ◽  
Monitoring System ◽  
Health Monitoring ◽  
Yangtze River ◽  
Model Updating ◽  
Structural Condition ◽  
Condition Assessment ◽  
Health Monitoring System ◽  
Structural Health ◽  
Structural Health Monitoring System

Structural health monitoring can provide a practical platform for detecting the evolution of structural damage or performance deterioration of engineering structures. The final objective is to provide reasonable suggestions for structural maintenance and management and therefore ensure the structural safety according to the real-time recorded data. In this paper, the establishment of the wind and structural health monitoring system (WSHMS) implemented on the Runyang Yangtze River Bridge (RYRB) in China is introduced. The composition and functions of the WSHMS are presented. Thereinto, the sensory subsystem utilized to measure the input actions and structural output responses is introduced. And the core functions of the data management and analysis subsystem (DMAS) including model updating, structural condition identification, and structural condition assessment are illustrated in detail. A three-stage strategy is applied into the FE model updating of RYRB, and a two-phase strategy is proposed to adapt to structural health diagnosis and damage identification. Considering the structural integral security and the fatigue characteristic of steel material, the condition assessment of RYRB is divided into structural reliability assessment and structural fatigue assessment, which are equipped with specific and elaborate module for effective operation. This research can provide references for the establishment of the similar structural health monitoring systems on other cable-supported bridges.

scholarly journals A MODWT-Based Algorithm for the Identification and Removal of Jumps/Short-Term Distortions in Displacement Measurements Used for Structural Health Monitoring

IoT ◽  
2021 ◽  
Vol 3 (1) ◽  
pp. 60-72
Author(s):  
Davi V. Q. Rodrigues ◽  
Delong Zuo ◽  
Changzhi Li
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Signal To Noise Ratio ◽  
Structural Condition ◽  
Signal To Noise ◽  
Short Term ◽  
Structural Health ◽  
Noise Ratio ◽  
Displacement Measurements

Researchers have made substantial efforts to improve the measurement of structural reciprocal motion using radars in the last years. However, the signal-to-noise ratio of the radar’s received signal still plays an important role for long-term monitoring of structures that are susceptible to excessive vibration. Although the prolonged monitoring of structural deflections may provide paramount information for the assessment of structural condition, most of the existing structural health monitoring (SHM) works did not consider the challenges to handle long-term displacement measurements when the signal-to-noise ratio of the measurement is low. This may cause discontinuities in the detected reciprocal motion and can result in wrong assessments during the data analyses. This paper introduces a novel approach that uses a wavelet-based multi-resolution analysis to correct short-term distortions in the calculated displacements even when previously proposed denoising techniques are not effective. Experimental results are presented to validate and demonstrate the feasibility of the proposed algorithm. The advantages and limitations of the proposed approach are also discussed.

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