scholarly journals Structural Health Monitoring Methods for the Evaluation of Prestressing Forces and Prerelease Cracks

2016 ◽  
Vol 2 ◽  
Author(s):  
Hiba Abdel-Jaber ◽  
Branko Glisic
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Monitoring Methods ◽  
Structural Health

Review of piezoelectric impedance based structural health monitoring: Physics-based and data-driven methods

2021 ◽  
pp. 136943322110384
Author(s):  
Xingyu Fan ◽  
Jun Li ◽  
Hong Hao
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Structural Damage ◽  
Low Frequency ◽  
Data Driven ◽  
Mode Shapes ◽  
Monitoring Methods ◽  
Destructive Testing ◽  
Electromechanical Impedance ◽  
Structural Health

Vibration based structural health monitoring methods are usually dependent on the first several orders of modal information, such as natural frequencies, mode shapes and the related derived features. These information are usually in a low frequency range. These global vibration characteristics may not be sufficiently sensitive to minor structural damage. The alternative non-destructive testing method using piezoelectric transducers, called as electromechanical impedance (EMI) technique, has been developed for more than two decades. Numerous studies on the EMI based structural health monitoring have been carried out based on representing impedance signatures in frequency domain by statistical indicators, which can be used for damage detection. On the other hand, damage quantification and localization remain a great challenge for EMI based methods. Physics-based EMI methods have been developed for quantifying the structural damage, by using the impedance responses and an accurate numerical model. This article provides a comprehensive review of the exciting researches and sorts out these approaches into two categories: data-driven based and physics-based EMI techniques. The merits and limitations of these methods are discussed. In addition, practical issues and research gaps for EMI based structural health monitoring methods are summarized.

scholarly journals Review of Structural Health Monitoring Methods Regarding a Multi-Sensor Approach for Damage Assessment of Metal and Composite Structures

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 826 ◽  
Author(s):  
Christoph Kralovec ◽  
Martin Schagerl
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Damage Assessment ◽  
Composite Structures ◽  
Joint Damage ◽  
Ultrasonic Waves ◽  
Physical Models ◽  
Monitoring Methods ◽  
Structural Health ◽  
Different Levels

Structural health monitoring (SHM) is the continuous on-board monitoring of a structure’s condition during operation by integrated systems of sensors. SHM is believed to have the potential to increase the safety of the structure while reducing its deadweight and downtime. Numerous SHM methods exist that allow the observation and assessment of different damages of different kinds of structures. Recently data fusion on different levels has been getting attention for joint damage evaluation by different SHM methods to achieve increased assessment accuracy and reliability. However, little attention is given to the question of which SHM methods are promising to combine. The current article addresses this issue by demonstrating the theoretical capabilities of a number of prominent SHM methods by comparing their fundamental physical models to the actual effects of damage on metal and composite structures. Furthermore, an overview of the state-of-the-art damage assessment concepts for different levels of SHM is given. As a result, dynamic SHM methods using ultrasonic waves and vibrations appear to be very powerful but suffer from their sensitivity to environmental influences. Combining such dynamic methods with static strain-based or conductivity-based methods and with additional sensors for environmental entities might yield a robust multi-sensor SHM approach. For demonstration, a potent system of sensors is defined and a possible joint data evaluation scheme for a multi-sensor SHM approach is presented.

Study of Concrete Pump Truck Structural Health Monitoring

2010 ◽  
Vol 139-141 ◽  
pp. 2513-2516 ◽  
Author(s):  
Guang Jun Hua ◽  
Yun Xin Wu ◽  
Shuai Wang
Keyword(s):  
Structural Health Monitoring ◽  
Monitoring System ◽  
Health Monitoring ◽  
Evaluation Criteria ◽  
Monitoring Methods ◽  
Health Monitoring System ◽  
Structural Health ◽  
Structural Health Monitoring System ◽  
Concrete Pump Truck ◽  
Concrete Pump

Concrete pump truck is a kind of mobile construction machinery, with the characteristic of complex structure, poor working condition and difficult to maintenance. Therefore, adopting appropriate health monitoring methods, and accurate grasping the running status information of the pump truck is significant to the pump truck’s safety use and pre-judgment maintenance plan arrangement. In this paper, the traditional structural health monitoring methods was studied. And the structure, load and work environment characteristics of concrete pump truck were analyzed. Taking into account the economy and reliability of the structural health monitoring system, the technical route of the concrete pump truck structural health monitoring system and health evaluation criteria were proposed. The evaluation criteria takes into account both the cumulative health effect and timely health status of concrete pump truck structure.

scholarly journals Use of damping identification technique for damage detection

2018 ◽  
Vol 148 ◽  
pp. 14004
Author(s):  
Vikas Arora
Keyword(s):  
Structural Health Monitoring ◽  
Damage Detection ◽  
Health Monitoring ◽  
Natural Frequencies ◽  
Monitoring Methods ◽  
Structural Health ◽  
Damping Matrix ◽  
Step Procedure ◽  
Damage Structure ◽  
Identification Technique

Stiffness-based structural health monitoring methods are widely used for detecting the damage in a structure. These stiffness-based structural health monitoring methods uses change in natural frequencies and modeshapes for damage detection. These methods are based on identifying the change in stiffness of the healthy and damage structure to predict the damage in the structure. These stiffness-based methods are not efficient for detecting a small damage in a structure as there is a negligible change in natural frequencies and modeshapes due to a small damage in a structure, however the damping characteristics of the structure are highly sensitive to the damage in a structure. In this paper, new damping-based damage detection procedure has been proposed. In the proposed procedure, the changes in damping matrix of the structure has been used to detect the damage in the structure. The proposed procedure is able (or can) to detect both the location of the damage and the extend of the damage in the structure. The proposed procedure of damping-based damage detection is a 2-step procedure. In the first step, damping matrices of both the healthy and damage structure are identified and in the second step, the identified damping matrices are used for damage detection. Numerical and experimental case studies are presented to demonstrate the effectiveness of the proposed procedure. The results have shown that the proposed damping-based damage detection procedure can be used for detecting damage in a structure with confidence.

scholarly journals Railway bridge structural health monitoring and fault detection: State-of-the-art methods and future challenges

2017 ◽  
Vol 17 (4) ◽  
pp. 971-1007 ◽  
Author(s):  
Matteo Vagnoli ◽  
Rasa Remenyte-Prescott ◽  
John Andrews
Keyword(s):  
Structural Health Monitoring ◽  
Fault Detection ◽  
Health Monitoring ◽  
Detection Methods ◽  
Health State ◽  
Railway Bridge ◽  
Monitoring Methods ◽  
Railway Bridges ◽  
Structural Health ◽  
Future Challenges

Railway importance in the transportation industry is increasing continuously, due to the growing demand of both passenger travel and transportation of goods. However, more than 35% of the 300,000 railway bridges across Europe are over 100-years old, and their reliability directly impacts the reliability of the railway network. This increased demand may lead to higher risk associated with their unexpected failures, resulting safety hazards to passengers and increased whole life cycle cost of the asset. Consequently, one of the most important aspects of evaluation of the reliability of the overall railway transport system is bridge structural health monitoring, which can monitor the health state of the bridge by allowing an early detection of failures. Therefore, a fast, safe and cost-effective recovery of the optimal health state of the bridge, where the levels of element degradation or failure are maintained efficiently, can be achieved. In this article, after an introduction to the desired features of structural health monitoring, a review of the most commonly adopted bridge fault detection methods is presented. Mainly, the analysis focuses on model-based finite element updating strategies, non-model-based (data-driven) fault detection methods, such as artificial neural network, and Bayesian belief network–based structural health monitoring methods. A comparative study, which aims to discuss and compare the performance of the reviewed types of structural health monitoring methods, is then presented by analysing a short-span steel structure of a railway bridge. Opportunities and future challenges of the fault detection methods of railway bridges are highlighted.

Vibration-response-only statistical time series structural health monitoring methods: A comprehensive assessment via a scale jacket structure

2019 ◽  
Vol 19 (3) ◽  
pp. 736-750 ◽  
Author(s):  
Nikos A Spanos ◽  
John S Sakellariou ◽  
Spilios D Fassois
Keyword(s):  
Time Series ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Vibration Signal ◽  
Small Scale ◽  
Laser Vibrometer ◽  
Monitoring Methods ◽  
Structural Health ◽  
Statistical Time ◽  
Prominent Response

Random-vibration-based statistical time series structural health monitoring methods utilize small-scale, compact, and data-based, time series stochastic representations of the structural dynamics for damage diagnosis. In this study, a comprehensive and critical assessment of the diagnostic performance of five prominent response-only methods is presented based on incipient, ‘minor’ to ‘mild’, damages on a lab-scale wind turbine jacket structure. Statistically reliable damage detection and identification results are obtained via a ‘rotation’ procedure resulting into thousands of test cases, with the performance analysed in terms of receiver operating characteristic curves and confusion matrices. The results indicate not only challenging of the methods’ capabilities, but also the achievement of good to excellent performance for the ‘minor’ to ‘mild’ damages, respectively, with the model parameter–based method offering the best performance. In addition, the use of a vibration signal measured via a laser vibrometer leads to slightly improved detection performance over that obtained via a classical accelerometer.

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