scholarly journals Structural Health Monitoring of Bridges Using Advanced Non-destructive Testing Technique

2019 ◽  
pp. 963-972 ◽  
Author(s):  
Maizuar Maizuar ◽  
L. Zhang ◽  
Saeed Miramini ◽  
Priyan Mendis ◽  
Collin Duffield
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Testing Technique ◽  
Structural Health ◽  
Non Destructive

scholarly journals Chirplet Transform in Ultrasonic Non-Destructive Testing and Structural Health Monitoring: A Review

2019 ◽  
Vol 9 (1) ◽  
pp. 3778-3781
Author(s):  
M. S. Mohammed ◽  
K. Ki-Seong
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Ultrasonic Signal ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Structural Health ◽  
Chirplet Transform ◽  
Testing Signal ◽  
Short Time ◽  
Non Destructive

Ultrasonic non-destructive testing signal can be decomposed into a set of chirplet signals, which makes the chirplet transform a fitting ultrasonic signal analysis and processing method. Moreover, compared to wavelet transform, short-time Fourier transform and Gabor transform, chirplet transform is a comprehensive signal approximation method, nevertheless, the former methods gained more popularity in the ultrasonic signal processing research. In this paper, the principles of the chirplet transform are explained with a simplified presentation and the studies that used the transform in ultrasonic non-destructive testing and in structural health monitoring are reviewed to expose the existing applications and motivate the research in the potential ones.

scholarly journals Structural health monitoring through surface acoustic wave inspection deployed on capillaries embedded in additively manufactured components

2021 ◽  
Vol 349 ◽  
pp. 03010
Author(s):  
Michaël Hinderdael ◽  
Zoé Jardon ◽  
Julien Ertveldt ◽  
Patrick Guillaume
Keyword(s):  
Structural Health Monitoring ◽  
Acoustic Wave ◽  
Surface Acoustic Wave ◽  
Health Monitoring ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Health Monitoring System ◽  
Structural Health ◽  
Novel Approach ◽  
Non Destructive

Surface Acoustic Wave inspection is a well-known non-destructive testing technique that receives considerable attention to become implemented as a Structural Health Monitoring system. The current work presents a novel approach to embed Surface Acoustic Wave-based Structural Health Monitoring technology inside additively manufactured components. A capillary network is to be integrated inside the component and Surface Acoustic Wave inspection is then deployed on the free capillary surface during the component’s operation to warn upcoming failures.

scholarly journals Recent Advancements in Non-Destructive Testing Techniques for Structural Health Monitoring

2021 ◽  
Vol 11 (6) ◽  
pp. 2750 ◽  
Author(s):  
Patryk Kot ◽  
Magomed Muradov ◽  
Michaela Gkantou ◽  
George S. Kamaris ◽  
Khalid Hashim ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Fiber Optics ◽  
Health Monitoring ◽  
Civil Engineering ◽  
Machine Learning Algorithms ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Structural Health ◽  
Testing Techniques ◽  
Non Destructive

Structural health monitoring (SHM) is an important aspect of the assessment of various structures and infrastructure, which involves inspection, monitoring, and maintenance to support economics, quality of life and sustainability in civil engineering. Currently, research has been conducted in order to develop non-destructive techniques for SHM to extend the lifespan of monitored structures. This paper will review and summarize the recent advancements in non-destructive testing techniques, namely, sweep frequency approach, ground penetrating radar, infrared technique, fiber optics sensors, camera-based methods, laser scanner techniques, acoustic emission and ultrasonic techniques. Although some of the techniques are widely and successfully utilized in civil engineering, there are still challenges that researchers are addressing. One of the common challenges within the techniques is interpretation, analysis and automation of obtained data, which requires highly skilled and specialized experts. Therefore, researchers are investigating and applying artificial intelligence, namely machine learning algorithms to address the challenges. In addition, researchers have combined multiple techniques in order to improve accuracy and acquire additional parameters to enhance the measurement processes. This study mainly focuses on the scope and recent advancements of the Non-destructive Testing (NDT) application for SHM of concrete, masonry, timber and steel structures.

A New Technology of Aircraft Structural Health Monitoring

2013 ◽  
Vol 764 ◽  
pp. 71-74
Author(s):  
Xiao Hua Lu ◽  
Hong Fu Zuo
Keyword(s):  
Structural Health Monitoring ◽  
Crack Initiation ◽  
Health Monitoring ◽  
New Technology ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Structural Health ◽  
A New Technique ◽  
Non Destructive ◽  
Growth Detection

A new technique of aircraft structural health monitoring so-called Comparative Vacuum Monitoring (CVM) is introduced in this paper. Compared with the traditional and some novel Non-Destructive Testing (NDT) techniques, it is capable of real-time crack initiation and growth detection reliably and accurately, and especially suitable to monitor the interior locations with hard accessibility. With the advantages of this technique, the aircraft manufacturers (such as Boeing, Airbus, Bombardier, Embraer, ect.) are much interested in applying it into aircraft structural health monitoring and have carried out verification tests on aircrafts or technology ready for the future usage. Through the use of CVM technique, it is possible to quickly, routinely and remotely monitor the integrity of a structure in service.

scholarly journals Special Issue: “Non-Destructive Testing of Structures”

Materials ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 4996
Author(s):  
Magdalena Rucka
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Structural Materials ◽  
Non Destructive Testing ◽  
Special Issue ◽  
Destructive Testing ◽  
Structural Health ◽  
Damage Imaging ◽  
Recent Developments ◽  
Non Destructive

The Special Issue “Non-Destructive Testing of Structures” has been proposed to present recent developments in the field of diagnostics of structural materials and components in civil and mechanical engineering. The papers highlighted in this editorial concern various aspects of non-invasive diagnostics, including such topics as condition assessments of civil and mechanical structures and connections of structural elements, the inspection of cultural heritage monuments, the testing of structural materials, structural health monitoring systems, the integration of non-destructive testing methods, advanced signal processing for the non-destructive testing of structures (NDT), damage detection and damage imaging, as well as modeling and numerical analyses for supporting structural health monitoring (SHM) systems.

scholarly journals Embedding eddy current sensors into LPBF components for structural health monitoring

2021 ◽  
Author(s):  
Philipp Stoll ◽  
Enrico Gasparin ◽  
Adriaan Spierings ◽  
Konrad Wegener
Keyword(s):  
Structural Health Monitoring ◽  
Eddy Current ◽  
Health Monitoring ◽  
Non Destructive Testing ◽  
Laser Powder Bed Fusion ◽  
Destructive Testing ◽  
Powder Bed ◽  
Structural Health ◽  
Non Destructive ◽  
Harsh Conditions

AbstractLaser powder bed fusion (LPBF) facilitates the integration of external elements like sensors into workpieces during manufacturing. These embedded components enable e.g. part monitoring, thus being a fundamental application of industry 4.0. This study assesses the feasibility of embedding eddy current (EC) sensors for non-destructive testing (NDT) into SLM components aiming at structural health monitoring (SHM). A reliable embedding process for EC sensors is developed, ensuring the survivability of the sensors for the LPBF process and its harsh conditions. The experiments conducted demonstrate the possibility to use the embedded EC sensor to observe and detect a controlled crack growth. The cracks are realized either with direct EDM cutting or on the course of a fatigue test of CT specimens. The data retrieved by the embedded EC sensors are proven to provide a direct information about the severity of a damage and its evolution over time for both approaches. Thus, supporting the validation of such an innovative and promising SHM concept.

Feasibility study of a multi-parameter probability of detection formulation for a Lamb waves–based structural health monitoring approach to light alloy aeronautical plates

2016 ◽  
Vol 16 (2) ◽  
pp. 225-249 ◽  
Author(s):  
Andrea Gianneo ◽  
Michele Carboni ◽  
Marco Giglio
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Guided Waves ◽  
Probability Of Detection ◽  
Mathematical Framework ◽  
Extensive Literature ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Structural Health ◽  
Non Destructive

In view of an extensive literature about guided waves–based structural health monitoring of plate-like structures made of metallic and composite materials, a lack of information is pointed out regarding an effective and universally accepted approach for characterizing capability and reliability in detecting, localizing and sizing in-service damages. On the other hand, in the frame of traditional non-destructive testing systems, capability is typically expressed by means of suitable ‘probability of detection’ curves based on Berens’ model, where a linear relationship is established between probability of detection and flaw size. Although the uncertain factors are usually different between a non-destructive inspection technique and a structural health monitoring approach, it seems that a similar mathematical framework could be assumed. From this point of view, this research investigates the feasibility of application of the very recent ‘multi-parameter’ probability of detection approach, developed within the traditional non-destructive testing field, to guided waves–based structural health monitoring. In particular, numerical simulations as well as experimental responses from flawed aluminium alloy plates were combined to bring about a ‘master’ probability of detection curve. Once established, this curve can be used to study the intrinsic capability of the system in terms of probability of detection curves, overcoming the intrinsic limitation of a single predictor (like the crack size) and a statistical model typically based upon a linear behaviour between the predictor and the response.

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