Cracks in reinforced concrete (RC) structures can be detrimental as they grow beyond the limits. Cracks should be included in structural assessment methods to ensure the durability and load capacity of existing structures. However, conventional models used in the assessment of existing structures do not reflect the real cracking condition which implies that advanced assessment methods are required. In this study, pre-existing cracks were introduced into finite element analysis to identify the ductility, failure characteristics, and ultimate capacity of cracked structures. A beam specimen taken from the edge beams of an existing bridge had been subjected to a four-point bending test, and the results are used in this study for validation purposes. The specimens showed varying levels of cracking due to loading as well as reinforcement corrosion during the service life. Five different analyses were carried out to account for the effect of loading cracks and corrosion cracks based on two crack modeling approaches, namely weakened element approach and weakened bond-slip relation approach. The results showed that the failure of the beams was caused by anchorage failure. The differences in the load capacity predicated by different models are discussed. It was observed that incorporating pre-existing cracks by using weakened elements and weakened bond-slip relation approaches can be a practical method to model and assess cracked RC beams.
{"title":"INCORPORATING PRE-EXISTING CRACKS IN STRUCTURAL ASSESSMENT OF RC STRUCTURES","authors":"Ke Yu, Jiangpeng Shu, K. Zandi","doi":"10.12783/shm2021/36322","DOIUrl":"https://doi.org/10.12783/shm2021/36322","url":null,"abstract":"Cracks in reinforced concrete (RC) structures can be detrimental as they grow beyond the limits. Cracks should be included in structural assessment methods to ensure the durability and load capacity of existing structures. However, conventional models used in the assessment of existing structures do not reflect the real cracking condition which implies that advanced assessment methods are required. In this study, pre-existing cracks were introduced into finite element analysis to identify the ductility, failure characteristics, and ultimate capacity of cracked structures. A beam specimen taken from the edge beams of an existing bridge had been subjected to a four-point bending test, and the results are used in this study for validation purposes. The specimens showed varying levels of cracking due to loading as well as reinforcement corrosion during the service life. Five different analyses were carried out to account for the effect of loading cracks and corrosion cracks based on two crack modeling approaches, namely weakened element approach and weakened bond-slip relation approach. The results showed that the failure of the beams was caused by anchorage failure. The differences in the load capacity predicated by different models are discussed. It was observed that incorporating pre-existing cracks by using weakened elements and weakened bond-slip relation approaches can be a practical method to model and assess cracked RC beams.","PeriodicalId":180083,"journal":{"name":"Proceedings of the 13th International Workshop on Structural Health Monitoring","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126765469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Funmilola Nwokocha, Andrei N. Zagrai, David Hunter, Dale Amon, N. Demidovich
Reusable space vehicles nowadays are regularly used to ferry payloads to space. The structural health monitoring (SHM) systems could be used to further improve safety of the vehicle and reduce operational costs. This contribution describes design, development and implementation of a realtime data acquisition SHM experiment for suborbital spaceflight. The aim of suborbital experiment is to demonstrate successful collection, spatial distribution, on board processing and storage of environmental, structural (SHM) and flight data. In this contribution, details of payload design and operation are provided focusing on SHM application in space environment. Due to space and mass limitation of the payload, a SHM experiment was designed with minimum use of hardware and materials. A miniaturized Canary impedance measurement unit was developed to include the real-time data analysis and communication capabilities as well as a raw data storage on a SD card. A small cantilever beam with an attached piezoelectric sensor was selected as a structural specimen for the in-flight electro-mechanical impedance test. The specimen was modeled analytically and compared to experimental data obtained in laboratory tests. The systems’ ability to process impedance data in near-real time was also validated. The results demonstrate ability of the developed SHM system to acquire, store, analyze and communicate the electro-mechanical impedance information to enable a new generation of smart space structures.
{"title":"ELECTRO-MECHANICAL IMPEDANCE EXPERIMENT AND REAL-TIME DATA ACQUISITION FOR SUBORBITAL SPACEFLIGHT","authors":"Funmilola Nwokocha, Andrei N. Zagrai, David Hunter, Dale Amon, N. Demidovich","doi":"10.12783/shm2021/36303","DOIUrl":"https://doi.org/10.12783/shm2021/36303","url":null,"abstract":"Reusable space vehicles nowadays are regularly used to ferry payloads to space. The structural health monitoring (SHM) systems could be used to further improve safety of the vehicle and reduce operational costs. This contribution describes design, development and implementation of a realtime data acquisition SHM experiment for suborbital spaceflight. The aim of suborbital experiment is to demonstrate successful collection, spatial distribution, on board processing and storage of environmental, structural (SHM) and flight data. In this contribution, details of payload design and operation are provided focusing on SHM application in space environment. Due to space and mass limitation of the payload, a SHM experiment was designed with minimum use of hardware and materials. A miniaturized Canary impedance measurement unit was developed to include the real-time data analysis and communication capabilities as well as a raw data storage on a SD card. A small cantilever beam with an attached piezoelectric sensor was selected as a structural specimen for the in-flight electro-mechanical impedance test. The specimen was modeled analytically and compared to experimental data obtained in laboratory tests. The systems’ ability to process impedance data in near-real time was also validated. The results demonstrate ability of the developed SHM system to acquire, store, analyze and communicate the electro-mechanical impedance information to enable a new generation of smart space structures.","PeriodicalId":180083,"journal":{"name":"Proceedings of the 13th International Workshop on Structural Health Monitoring","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123981544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
UAVs face some critical challenges in pervasive applications, such as navigation in GPS-denying areas, obstacle avoidance, and tradeoff between payload and flight time. The INSPIRE UTC at Missouri S&T is developing a clamping UAV, a hybrid flying and traversing robot, to make it possible that the UAV flies under a bridge girder, grabs the girder, and moves along the girder for inspection. This heavy UAV is difficult to control underneath the deck when equipped with multiple cameras. In this study, CFD modeling and simulation are conducted to understand the flight behavior and ceiling effect of the UAV under the bridge deck. First, 3D scanning and reverse engineering are used to build CFD models. Second, a series of single propeller tests are conducted to validate the process of CFD modeling and the simulation results. Third, based on the workflow and technique validated through single propeller CFD analysis, the CFD model of an entire UAV is established and analyzed to predict the behavior of the UAV and understand its interaction with upper boundaries as it approaches the bridge ceiling vertically. The CFD simulation results show that the ceiling effect of the designed clamping UAV is insignificant when the UAV approaches the standard bridge deck with enough depth. These results provide a technical reference for the design and control of the clamping UAV for bridge inspection.
{"title":"THE CEILING EFFECT AND FLIGHT INSIGHT OF UNMANNED AERIAL VEHICLES DURING PROXIMITY INSPECTION OF BRIDGES VIA COMPUTATIONAL FLUID DYNAMICS MODELING AND SIMULATIONS","authors":"Pu Jiao, Bo Shang, Liujun Li, Ge-wei Chen","doi":"10.12783/shm2021/36338","DOIUrl":"https://doi.org/10.12783/shm2021/36338","url":null,"abstract":"UAVs face some critical challenges in pervasive applications, such as navigation in GPS-denying areas, obstacle avoidance, and tradeoff between payload and flight time. The INSPIRE UTC at Missouri S&T is developing a clamping UAV, a hybrid flying and traversing robot, to make it possible that the UAV flies under a bridge girder, grabs the girder, and moves along the girder for inspection. This heavy UAV is difficult to control underneath the deck when equipped with multiple cameras. In this study, CFD modeling and simulation are conducted to understand the flight behavior and ceiling effect of the UAV under the bridge deck. First, 3D scanning and reverse engineering are used to build CFD models. Second, a series of single propeller tests are conducted to validate the process of CFD modeling and the simulation results. Third, based on the workflow and technique validated through single propeller CFD analysis, the CFD model of an entire UAV is established and analyzed to predict the behavior of the UAV and understand its interaction with upper boundaries as it approaches the bridge ceiling vertically. The CFD simulation results show that the ceiling effect of the designed clamping UAV is insignificant when the UAV approaches the standard bridge deck with enough depth. These results provide a technical reference for the design and control of the clamping UAV for bridge inspection.","PeriodicalId":180083,"journal":{"name":"Proceedings of the 13th International Workshop on Structural Health Monitoring","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115169541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rushil Mojidra, Jian Li, Ali Mohammadkhorasani, F. Moreu, William N. Collins, C. Bennett
Fatigue constitutes a critical limit state affecting the safety of civil infrastructure. Under repetitive loading, structural members are susceptible to fatigue cracking under stresses much lower than the yield strength of the material. In this study, computer vision-based fatigue crack detection using a short video stream taken from a nonstationary camera is presented. Videos taken from a hand-held camera, or an unmanned aerial vehicle (UAV) contain two types of movements: 1) true object movements, and 2) unwanted camera movement due to hand shaking or UAV hovering. In most vision-based structural health monitoring research, feature-based motion compensation techniques are used that require manual selection of fixed objects in the video for feature point selection. Feature point selection from true moving objects in the video could produce inaccuracy in video stabilization. In this study, we propose to use hierarchical model-based motion estimation for global motion compensation, which does not require manual selection of fixed objects. First, we construct a pyramid of target and reference images and then estimate motion from top to bottom of the pyramid while accumulating the geometric transformation, by which the camera movement can be removed. Then, we detect salient feature points in the region of interest and track the motion of feature points throughout the video using the Kanade-Lucas-Tomasi (KLT) feature tracking algorithm. Subsequently, a crack detection, and localization algorithm is applied to search for differential point movements caused by fatigue crack opening and closing. To evaluate effectiveness of the proposed method, a laboratory experiment was conducted on a C(T) specimen with an in-plane fatigue crack. Results show that proposed method was able to effectively compensate the camera motion and detect the presence of the fatigue crack.
{"title":"VIDEO MOTION COMPENSATION FOR FATIGUE CRACK DETECTION IN STEEL STRUCTURES","authors":"Rushil Mojidra, Jian Li, Ali Mohammadkhorasani, F. Moreu, William N. Collins, C. Bennett","doi":"10.12783/shm2021/36308","DOIUrl":"https://doi.org/10.12783/shm2021/36308","url":null,"abstract":"Fatigue constitutes a critical limit state affecting the safety of civil infrastructure. Under repetitive loading, structural members are susceptible to fatigue cracking under stresses much lower than the yield strength of the material. In this study, computer vision-based fatigue crack detection using a short video stream taken from a nonstationary camera is presented. Videos taken from a hand-held camera, or an unmanned aerial vehicle (UAV) contain two types of movements: 1) true object movements, and 2) unwanted camera movement due to hand shaking or UAV hovering. In most vision-based structural health monitoring research, feature-based motion compensation techniques are used that require manual selection of fixed objects in the video for feature point selection. Feature point selection from true moving objects in the video could produce inaccuracy in video stabilization. In this study, we propose to use hierarchical model-based motion estimation for global motion compensation, which does not require manual selection of fixed objects. First, we construct a pyramid of target and reference images and then estimate motion from top to bottom of the pyramid while accumulating the geometric transformation, by which the camera movement can be removed. Then, we detect salient feature points in the region of interest and track the motion of feature points throughout the video using the Kanade-Lucas-Tomasi (KLT) feature tracking algorithm. Subsequently, a crack detection, and localization algorithm is applied to search for differential point movements caused by fatigue crack opening and closing. To evaluate effectiveness of the proposed method, a laboratory experiment was conducted on a C(T) specimen with an in-plane fatigue crack. Results show that proposed method was able to effectively compensate the camera motion and detect the presence of the fatigue crack.","PeriodicalId":180083,"journal":{"name":"Proceedings of the 13th International Workshop on Structural Health Monitoring","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124961236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A very promising solution in airframe design is a new trend in application based on intelligent online condition monitoring known as Structural Condition/Health Monitoring/Management System, which has evolved towards Integrated System Health Management to cover the whole System-of-Systems architecture. This paper focuses on how to reduce Big Data with reference to a comprehensive model for designing future airframe heath monitoring system, including the problem of assessing the diversity of various sensors used in the assessment of the technical condition/health of an airframe, which generates big data sets with different records of measurement data that must be reduced for effective using. The paper summarizes the research on the assessment of sensors in terms of their suitability and effectiveness in monitoring the airframe condition, including metal and composite, and refers to the complexity of the problem by integrating the technical condition/health of the engine unit and the airframe. Integration issue of the reliability serial connection of the airframe and engine for airworthiness assessment were mentioned. A new method based on the rough set paradigm, including hybrid variants, for the reduction of big data of health monitoring into their effective management were postulated and advantages were demonstrated. The proposed method in the form of listed issues is complementary to the currently used method and is aimed at supporting the design of the airframe at the preliminary assessment stage. That method is strongly recommended to increase security and reduce computational cost and operational cost including maintenance cost in aircraft life-cycle costs.
{"title":"A NEW METHOD IN CONCEPTUAL DESIGN OF THE SHM AIRFRAME USING ROUGH SETS","authors":"K. Kustroń","doi":"10.12783/shm2021/36354","DOIUrl":"https://doi.org/10.12783/shm2021/36354","url":null,"abstract":"A very promising solution in airframe design is a new trend in application based on intelligent online condition monitoring known as Structural Condition/Health Monitoring/Management System, which has evolved towards Integrated System Health Management to cover the whole System-of-Systems architecture. This paper focuses on how to reduce Big Data with reference to a comprehensive model for designing future airframe heath monitoring system, including the problem of assessing the diversity of various sensors used in the assessment of the technical condition/health of an airframe, which generates big data sets with different records of measurement data that must be reduced for effective using. The paper summarizes the research on the assessment of sensors in terms of their suitability and effectiveness in monitoring the airframe condition, including metal and composite, and refers to the complexity of the problem by integrating the technical condition/health of the engine unit and the airframe. Integration issue of the reliability serial connection of the airframe and engine for airworthiness assessment were mentioned. A new method based on the rough set paradigm, including hybrid variants, for the reduction of big data of health monitoring into their effective management were postulated and advantages were demonstrated. The proposed method in the form of listed issues is complementary to the currently used method and is aimed at supporting the design of the airframe at the preliminary assessment stage. That method is strongly recommended to increase security and reduce computational cost and operational cost including maintenance cost in aircraft life-cycle costs.","PeriodicalId":180083,"journal":{"name":"Proceedings of the 13th International Workshop on Structural Health Monitoring","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123339952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Because the maglev guideway is a vital infrastructure of high-speed maglev train, it is of great significance for the guideway structure to analyze dynamic response and assess structural health of the guideway in research. This paper proposed a model updating method of the high-speed maglev guideway based on wavelet transform(WT) and optimization algorithm, which are used to analyze the dynamic response and assess health. Taking the 600 km/h high-speed maglev test vehicle as the excitation, the field test was carried out on the High-speed Maglev Test Line. The measured dynamic responses of the guideway were obtained, and the measured modal parameters were identified by WT. The finite element(FE) model of guideway was established, considering the elastic boundary conditions and material properties, and the initial modal parameters of the guideway were obtained. Based on the FE model, the response surface model of the guideway was constructed and the objective function of the simulated modal parameters and the measured modal parameters was established. Considering the constraint conditions, the optimal solution of the objective function was found by the optimization algorithm, and the elastic boundary conditions and material properties of the FE model were optimized and updated. The research results indicated that the dynamic response of the updated FE model was highly correlated with the measured dynamic response and proved strongly the effectiveness of the proposed method. A more accurate model updating method for the dynamic response analysis and health assessment of the high-speed maglev guideway was provided by this paper.
{"title":"RESEARCH ON MODEL UPDATING METHOD OF HIGH- SPEED MAGLEV GUIDEWAY BASED ON WAVELET TRANSFORM AND OPTIMIZATION ALGORITHM","authors":"Zhihong Fang, Jingyu Huang, Xiaonong Wang, Liang Zhao, Shuowei Wang, Ziyang Zhang, Dexiang Li","doi":"10.12783/shm2021/36290","DOIUrl":"https://doi.org/10.12783/shm2021/36290","url":null,"abstract":"Because the maglev guideway is a vital infrastructure of high-speed maglev train, it is of great significance for the guideway structure to analyze dynamic response and assess structural health of the guideway in research. This paper proposed a model updating method of the high-speed maglev guideway based on wavelet transform(WT) and optimization algorithm, which are used to analyze the dynamic response and assess health. Taking the 600 km/h high-speed maglev test vehicle as the excitation, the field test was carried out on the High-speed Maglev Test Line. The measured dynamic responses of the guideway were obtained, and the measured modal parameters were identified by WT. The finite element(FE) model of guideway was established, considering the elastic boundary conditions and material properties, and the initial modal parameters of the guideway were obtained. Based on the FE model, the response surface model of the guideway was constructed and the objective function of the simulated modal parameters and the measured modal parameters was established. Considering the constraint conditions, the optimal solution of the objective function was found by the optimization algorithm, and the elastic boundary conditions and material properties of the FE model were optimized and updated. The research results indicated that the dynamic response of the updated FE model was highly correlated with the measured dynamic response and proved strongly the effectiveness of the proposed method. A more accurate model updating method for the dynamic response analysis and health assessment of the high-speed maglev guideway was provided by this paper.","PeriodicalId":180083,"journal":{"name":"Proceedings of the 13th International Workshop on Structural Health Monitoring","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129913846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nondestructive Evaluation (NDE) technologies are increasingly used for structural condition assessments. Over the lifespan of a structure, a variety of NDE techniques may be employed, leading to a scenario where a structure’s life-cycle time history is depicted through a variety of complex and heterogeneous measurements. Therefore, improved understanding of the statistical associations between NDE data sources would allow engineers to integrate these data sources for analysis purposes. It would also provide new insights into the fundamental information shared between heterogeneous NDE observations, potentially leading to new forms of structural monitoring and assessment. This paper explores the correlations between NDE data types through an encoder-decoder neural network architecture. The network is designed to take in one type of NDE measurement as input, generating a synthetic measurement from a second NDE measurement as output. At the center of the encoder is a dimensionally reduced latent representation of the information that is shared between two associated NDE data sources. Additionally, this paper shows how transforming waveform NDE data into 2D time-frequency images using a Continuous Wavelet Transform (CWT) facilitates network training and representation of these shared fundamental data features. To illustrate this concept, the results from a series of laboratory scale tests are presented, representing how this network architecture would represent information collected from NDE of bridge decks.
{"title":"NDE DATA CORRELATION USING ENCODE-DECODER NETWORKS WITH SCALOGRAM IMAGES","authors":"Mozhgan Momtaz Dargahi, D. Lattanzi","doi":"10.12783/shm2021/36328","DOIUrl":"https://doi.org/10.12783/shm2021/36328","url":null,"abstract":"Nondestructive Evaluation (NDE) technologies are increasingly used for structural condition assessments. Over the lifespan of a structure, a variety of NDE techniques may be employed, leading to a scenario where a structure’s life-cycle time history is depicted through a variety of complex and heterogeneous measurements. Therefore, improved understanding of the statistical associations between NDE data sources would allow engineers to integrate these data sources for analysis purposes. It would also provide new insights into the fundamental information shared between heterogeneous NDE observations, potentially leading to new forms of structural monitoring and assessment. This paper explores the correlations between NDE data types through an encoder-decoder neural network architecture. The network is designed to take in one type of NDE measurement as input, generating a synthetic measurement from a second NDE measurement as output. At the center of the encoder is a dimensionally reduced latent representation of the information that is shared between two associated NDE data sources. Additionally, this paper shows how transforming waveform NDE data into 2D time-frequency images using a Continuous Wavelet Transform (CWT) facilitates network training and representation of these shared fundamental data features. To illustrate this concept, the results from a series of laboratory scale tests are presented, representing how this network architecture would represent information collected from NDE of bridge decks.","PeriodicalId":180083,"journal":{"name":"Proceedings of the 13th International Workshop on Structural Health Monitoring","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130295674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Daniel S. Brennan, J. Gosliga, E. Cross, K. Worden
This paper is the second in a series in which the aim is to provide an underlying database technology for enabling the user interaction required for Population-Based Structural Health Monitoring (PBSHM). In the first paper in the series, the groundwork was laid for a PBSHM Schema which enabled the storage of channel data via a Time First approach. PBSHM considers grouping similar structures together to gain additional insights from the group, compared to a single entity. Part of the PBSHM process is being able to identify which structures, or substructures, are similar. To enable this a standardised method of representing each structure must be used; here, an Irreducible Element (IE) model is employed. This paper builds on the groundwork that has been laid in the creation of IE models and defines a standardised format and properties for an IE modal to enable graph matching algorithms to find similar structures. The standardised format has been implemented via an IE-model Schema within the PBSHM Schema.
{"title":"ON IMPLEMENTING AN IRREDUCIBLE ELEMENT MODEL SCHEMA FOR POPULATION-BASED STRUCTURAL HEALTH MONITORING","authors":"Daniel S. Brennan, J. Gosliga, E. Cross, K. Worden","doi":"10.12783/shm2021/36342","DOIUrl":"https://doi.org/10.12783/shm2021/36342","url":null,"abstract":"This paper is the second in a series in which the aim is to provide an underlying database technology for enabling the user interaction required for Population-Based Structural Health Monitoring (PBSHM). In the first paper in the series, the groundwork was laid for a PBSHM Schema which enabled the storage of channel data via a Time First approach. PBSHM considers grouping similar structures together to gain additional insights from the group, compared to a single entity. Part of the PBSHM process is being able to identify which structures, or substructures, are similar. To enable this a standardised method of representing each structure must be used; here, an Irreducible Element (IE) model is employed. This paper builds on the groundwork that has been laid in the creation of IE models and defines a standardised format and properties for an IE modal to enable graph matching algorithms to find similar structures. The standardised format has been implemented via an IE-model Schema within the PBSHM Schema.","PeriodicalId":180083,"journal":{"name":"Proceedings of the 13th International Workshop on Structural Health Monitoring","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127846124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Datta, Ranting Cui, Izabela Batista, F. L. Scalea
This paper presents a high-speed non-contact rail inspection technique that has been tested on the field at speeds up to 80 mph. The technique utilizes an array of capacitive air-coupled ultrasonic transducers in continuous recording mode to extract a reconstructed transfer function for a rail segment in a passive manner. The passive approach utilizes the ambient excitation of the rail induced by the wheels of the test car and eliminates the need of a controlled source. A normalized cross correlation operator with modified Welch’s periodogram technique is used to extract the transfer function which is independent of the frequency spectrum of the random excitation source (wheels). Presence of discontinuities in the rail reduces the signal-to-noise ratio of the reconstructed transfer function which is statistically tracked using an outlier analysis for multiple reconstructions along the inspected rail. Data from multiple transducer pairs are compounded in the statistical outlier analysis which ensures removal of bias from the data. An adaptive baseline model from pristine rail is used to compute a parameter called the Damage Index (DI) to determine if the probed rail segment has a discontinuity. Raw ultrasonic signals comprising of thousands of data points for a given recording time within a rail segment are therefore compressed statistically into a single DI parameter. Full-scale field tests were carried out at testing speeds of up to 80 mph. Discontinuity detection performance in terms of identifying joints, welds and known transverse defects through Receiver Operating Characteristic (ROC) curves were studied for a range of varying operational parameters such as raw signal strength, baseline length, and testing speeds. Data from multiple passes of the train over the same rail segment were compounded to further introduce redundancies and increase the rate of true detections and reduce the rate of false alarms.
{"title":"APPLICATION OF A HIGH-SPEED NON-CONTACT ULTRASONIC TECHNIQUE COUPLED WITH STATISTICAL DATA REDUNDANCY FOR RAIL INSPECTION","authors":"D. Datta, Ranting Cui, Izabela Batista, F. L. Scalea","doi":"10.12783/shm2021/36291","DOIUrl":"https://doi.org/10.12783/shm2021/36291","url":null,"abstract":"This paper presents a high-speed non-contact rail inspection technique that has been tested on the field at speeds up to 80 mph. The technique utilizes an array of capacitive air-coupled ultrasonic transducers in continuous recording mode to extract a reconstructed transfer function for a rail segment in a passive manner. The passive approach utilizes the ambient excitation of the rail induced by the wheels of the test car and eliminates the need of a controlled source. A normalized cross correlation operator with modified Welch’s periodogram technique is used to extract the transfer function which is independent of the frequency spectrum of the random excitation source (wheels). Presence of discontinuities in the rail reduces the signal-to-noise ratio of the reconstructed transfer function which is statistically tracked using an outlier analysis for multiple reconstructions along the inspected rail. Data from multiple transducer pairs are compounded in the statistical outlier analysis which ensures removal of bias from the data. An adaptive baseline model from pristine rail is used to compute a parameter called the Damage Index (DI) to determine if the probed rail segment has a discontinuity. Raw ultrasonic signals comprising of thousands of data points for a given recording time within a rail segment are therefore compressed statistically into a single DI parameter. Full-scale field tests were carried out at testing speeds of up to 80 mph. Discontinuity detection performance in terms of identifying joints, welds and known transverse defects through Receiver Operating Characteristic (ROC) curves were studied for a range of varying operational parameters such as raw signal strength, baseline length, and testing speeds. Data from multiple passes of the train over the same rail segment were compounded to further introduce redundancies and increase the rate of true detections and reduce the rate of false alarms.","PeriodicalId":180083,"journal":{"name":"Proceedings of the 13th International Workshop on Structural Health Monitoring","volume":"318 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124508257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kaveh Barri, Qianyun Zhang, Zhong Lin Wang, A. Alavi
Developing lightweight multifunctional structures with sensing, energy harvesting and mechanical tunability capabilities has been the holy grail for scientists. This study presents our vision toward the next stage of the technological revolution in multifunctional structures science where a so-called Engineered Self-aware Structure (ES2) can sense, empower and program itself using its constituent components. We discuss the creation of such smart structures through the fusion of advanced metamaterial and energy harvesting technologies. The ES2 concept is validated via designing a composite beam prototype. The results imply that the fabricated multifunctional beam can measure the amplitude of the applied load and harvest the energy from the mechanical excitations. We demonstrate the broad application of the proposed concept in aerospace, biomedical, and civil engineering areas for designing multiscale self-sensing and self-powering devices.
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