A framework for evaluating the impact of structural health monitoring on bridge management

2010 ◽  
pp. 161-161 ◽  
Author(s):  
M Pozzi ◽  
D Zonta ◽  
W Wang ◽  
G Chen
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Bridge Management ◽  
Structural Health ◽  
The Impact

scholarly journals Structural Health Monitoring for cultural heritage constructions: a resilience perspective

2019 ◽  
Author(s):  
Maria Pina Limongelli ◽  
Zehra Irem Turksezer ◽  
Pier Francesco Giordano
Keyword(s):  
Structural Health Monitoring ◽  
Cultural Heritage ◽  
Health Monitoring ◽  
Social Value ◽  
Specific Reference ◽  
Structural Health ◽  
Heritage Constructions ◽  
The Impact ◽  
Support Decision Making ◽  
Over Time

<p>Disturbances or disruptive events may induce reductions of functionality of the built environment. For Cultural Heritage (CH) structures, functionalities may range from technical, to economic ones linked to touristic activities, up to intangible functionalities related to the cultural and social value of these constructions. Resilience can be defined as the capability of a system overcome a disturbance with the minimum total loss of functionality over time. Structural Health Monitoring (SHM) may enhance resilience by providing information that can support decision making, aiming to reduce the impact of the disturbances. In this paper, the benefits of SHM systems as means for improving resilience of CH structures are addressed and discussed with specific reference to the three different decision situations; before, during and after events of disturbances. Examples of real applications of SHM for CH structures and its effect on the resilience of the system conclude the paper.</p>

An Impact-Based Experimental Setup for Evaluation of Rapid Electromechanical Impedance-Based Structural Health Monitoring

2020 ◽  
Author(s):  
Mohammad Alshaikh Ali ◽  
Eric C. Nolan ◽  
Steven R. Anton ◽  
Mohsen Safaei
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Sampling Rate ◽  
Frequency Resolution ◽  
Experimental Setup ◽  
Frequency Bandwidth ◽  
Electromechanical Impedance ◽  
Excitation Signal ◽  
Structural Health ◽  
The Impact

Abstract This work investigates the application of structural health monitoring (SHM) in a dynamic environment with the electromechanical impedance (EMI) method. Classically, the EMI method monitors civil or mechanical structures for damage in static environments. Advances in data acquisition (DAQ) now allow the possibility of rapid damage detection in dynamic environments. An impact-based experimental setup is developed to create a repeatable dynamic event through a collision between a pneumatically actuated striker bar and a static incident bar instrumented with a piezoelectric transducer. The EMI method is employed to detect the change of state at the interface of the two colliding bars. Experimental results prove the pneumatic launching system is capable of repeatable dynamic events, but the duration of contact is only 0.03 ms and the current DAQ system is incapable of detecting the event. A 3D printed programming material interface is placed at the location of impact to increase the duration of contact to approximately 1 ms. An excitation signal is created to continuously sweep a 0.5 ms chirp signal with a frequency bandwidth from 60–70 kHz (previously identified damage sensitive frequency bandwidth from static testing) for 7.5 seconds. Results indicate that due to the sampling rate and sweep time of the excitation signal, the frequency resolution is not adequate to properly assess if the impact is detected. Improvements in the DAQ hardware must be considered for future work.

Impact Detection Using an Array of Piezoelectric Wafer Active Sensors and a Microcontroller Unit

2010 ◽  
Author(s):  
Abraham Light-Marquez ◽  
Andrei Zagrai
Keyword(s):  
Structural Health Monitoring ◽  
Sensor Network ◽  
Health Monitoring ◽  
Detection System ◽  
Active Sensors ◽  
Structural Health ◽  
Impact Detection ◽  
Piezoelectric Wafer Active Sensors ◽  
Piezoelectric Wafer ◽  
The Impact

This report discusses the development of an embeddable impact detection system utilizing an array of piezoelectric wafer active sensors (PWAS) and a microcontroller. Embeddable systems are a critical component to successfully implement a complete and robust structural health monitoring system. System capabilities include impact detection, impact location determination and digitization of the impact waveform. A custom algorithm was developed to locate the site of the impact.. The embedded system has the potential for additional capabilities including advanced signal processing and the integration of wireless functionality. For structural health monitoring applications it is essential to determine the extent of damage done to the structure. In an attempt to determine these parameters a series of impact tests were conducted using a ball drop tower on a square aluminum plate. The response of the plate to the impact event was recorded using a piezoelectric wafer sensor network attached to the surface of the plate. From this testing it was determined that several of the impact parameters are directly correlated with the features recorded by the sensor network.

Fatigue in aerostructures—where structural health monitoring can contribute to a complex subject

2006 ◽  
Vol 365 (1851) ◽  
pp. 561-587 ◽  
Author(s):  
Christian Boller ◽  
Matthias Buderath
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Structural Integrity ◽  
Aircraft Design ◽  
Jet Engines ◽  
Structural Health ◽  
Fatigue Design ◽  
The Impact ◽  
Maintenance Process ◽  
Complex Subject

An overview of the aircraft design and maintenance process is given with specific emphasis on the fatigue design as well as the phenomenon of the ageing aircraft observed over the life cycle. The different measures taken to guarantee structural integrity along the maintenance process are addressed. The impact of structural health monitoring as a means of possibly revolutionizing the current aircraft structural monitoring and design process is emphasized and comparison is made to jet engines and helicopters, where health monitoring has already found the respective breakthrough.

Structural Health Monitoring for Steel Structures

2013 ◽  
Vol 351-352 ◽  
pp. 1088-1091
Author(s):  
Xin Wang ◽  
Wei Bing Hu
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Damage Identification ◽  
Steel Structures ◽  
Fingerprint Analysis ◽  
Structural Health ◽  
Network Methods ◽  
Different Types ◽  
The Impact ◽  
Identification Strategy

The process of implementing a damage identification strategy for aerospace, civil and mechanical engineering infrastructure is referred to as structural health monitoring. Many different types and degrees accidents take place, especially some important collapse accidents, the significance of steel structural health monitoring has been recognized. The introduction begins with a brief research status of steel structural health monitoring in china and the world. The paper analyzes the projects and contents of steel structures monitoring from nine aspects and summarizes the diagnosis methods of steel structural damages which include power fingerprint analysis, the methods of model correction and system identification, neural network methods, genetic algorithm and wavelet analysis, it provides us theoretical guidence. In conclusion, structural health monitoring for steel structures could reduce the impact of such disasters immediately after natural hazards and man-made disasters both economically and socially, thus it is becoming increasingly important.

scholarly journals On the Influence of Capillary-Based Structural Health Monitoring on Fatigue Crack Initiation and Propagation in Straight Lugs

Materials ◽  
2019 ◽  
Vol 12 (18) ◽  
pp. 2965 ◽  
Author(s):  
Marc Moonens ◽  
Eric Wyart ◽  
Dieter De De Baere ◽  
Michaël Hinderdael ◽  
Julien Ertveldt ◽  
...  
Keyword(s):  
Fatigue Crack ◽  
Structural Health Monitoring ◽  
Finite Elements ◽  
Crack Initiation ◽  
Health Monitoring ◽  
Fatigue Behavior ◽  
Fatigue Crack Initiation ◽  
Structural Health ◽  
Initiation And Propagation ◽  
The Impact

This paper addresses the influence on the fatigue life induced by the implementation of a capillary-based structural health monitoring methodology, patented under the name eSHM. It consists in integrating structurally small and pressurized capillaries into the component, so that when a fatigue crack breaches the capillary network, it results in a leak flow to the open atmosphere and loss of pressure in the galleries which is detected by a pressure sensor. The novelty of the proposed system resides in the opportunity to locate the capillary according to the designer’s need, as one resorts to additive manufacturing for the part production. However, the presence of these galleries in highly stressed regions raises concerns about crack initiation at the capillary itself and accelerated fatigue crack growth. This paper aims at the quantification of the influence the eSHM has on the fatigue behavior of the component and the determination whether this influence is significant or not. To that purpose, numerical simulations on a straight lug component, using the finite elements and eXtended Finite Elements Methods (XFEM), are performed. Various capillary sizes and shapes are assessed, so as to enable a general conclusion on the impact of the eSHM methodology in straight lugs.

A Gaussian process–based approach to cope with uncertainty in structural health monitoring

2016 ◽  
Vol 16 (2) ◽  
pp. 174-184 ◽  
Author(s):  
Hessamodin Teimouri ◽  
Abbas S. Milani ◽  
Jason Loeppky ◽  
Rudolf Seethaler
Keyword(s):  
Pattern Recognition ◽  
Structural Health Monitoring ◽  
Gaussian Process ◽  
Health Monitoring ◽  
Network Models ◽  
Neural Network Models ◽  
Structural Health ◽  
Covariance Functions ◽  
Industrial Sectors ◽  
The Impact

Structural health monitoring is widely applied in industrial sectors as it reduces costs associated with maintenance intervals and manual inspections of damage in sensitive structures, while enhancing their operation safety. A major concern and current challenge in developing “robust” structural health monitoring systems, however, is the impact of uncertainty in the input training parameters on the accuracy and reliability of predictions. The aim of this article is to adapt an advanced statistical pattern recognition technique capable of considering variations in input parameters and arriving at a new structural health monitoring system more immune to the effect of uncertainty. Gaussian processes have been implemented to predict the state of damage in a typical composite airfoil structure. Different covariance functions were evaluated during the training stage of structural health monitoring. Results through a case study showed a remarkable capability of the Gaussian process–based approach to deal with uncertainty in the pattern recognition problem in structural health monitoring of a multi-layer composite airfoil structure. To illustrate robustness advantage of the approach as compared to conventional neural network models, the damage size and location prediction accuracy of the Gaussian process structural health monitoring has been compared to multi-layer perceptron neural networks. Some practical insights and limitations of the approach have also been outlined.

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