Statistical Analysis of SHM Passive Sensing Systems

2015 ◽  
Vol 665 ◽  
pp. 241-244
Author(s):  
Marco Thiene ◽  
Zahra Sharif Khodaei ◽  
M.H. Aliabadi
Keyword(s):  
Statistical Analysis ◽  
Health Monitoring ◽  
Sensor Failure ◽  
Impact Detection ◽  
Sensing Systems ◽  
Detection And Identification ◽  
Passive Sensing ◽  
Service Load ◽  
Reliability And Robustness ◽  
Load Conditions

Structural Health Monitoring (SHM) techniques have gained an increased interest to be utilised alongside NDI techniques for aircraft maintenance. However, to take the SHM methodologies from the laboratory conditions to actual structures under real load conditions requires them to be assessed in terms of reliability and robustness. In this work, a statistical analysis is carried out for a passive SHM system capable of impact detection and identification. The sensitivity of the platform to parameters such as noise, sensor failure and in-service load conditions has been investigated and reported.

Uncertainty Analysis of Active SHM System

2015 ◽  
Vol 665 ◽  
pp. 249-252
Author(s):  
Marco Thiene ◽  
Zahra Sharif Khodaei ◽  
M.H. Aliabadi
Keyword(s):  
Statistical Analysis ◽  
Structural Health Monitoring ◽  
Uncertainty Analysis ◽  
Damage Detection ◽  
Health Monitoring ◽  
Composite Structures ◽  
Sensor Failure ◽  
Laboratory Conditions ◽  
Reliability And Robustness ◽  
Load Conditions

Structural Health Monitoring (SHM) techniques have gained an increased interest to be utilised alongside NDI techniques for aircraft maintenance. However, to take the SHM methodologies from the laboratory conditions to actual structures under real load conditions requires them to be assessed in terms of reliability and robustness. In this work, a statistical analysis is carried out for an SHM system for damage detection and characterisation in composite structures. The sensitivity of the platform to parameters such as noise, sensor failure, placement tolerances and bonding has been investigated and reported.

scholarly journals Recent Advances in Wearable Devices for Non-Invasive Sensing

2021 ◽  
Vol 11 (3) ◽  
pp. 1235
Author(s):  
Su Min Yun ◽  
Moohyun Kim ◽  
Yong Won Kwon ◽  
Hyobeom Kim ◽  
Mi Jung Kim ◽  
...  
Keyword(s):  
Health Monitoring ◽  
Data Transmission ◽  
Wearable Sensors ◽  
Wearable Devices ◽  
Wireless Power ◽  
Non Invasive ◽  
Sensing Systems ◽  
Recent Advances ◽  
Wearable Systems ◽  
Precise Diagnosis

The development of wearable sensors is aimed at enabling continuous real-time health monitoring, which leads to timely and precise diagnosis anytime and anywhere. Unlike conventional wearable sensors that are somewhat bulky, rigid, and planar, research for next-generation wearable sensors has been focused on establishing fully-wearable systems. To attain such excellent wearability while providing accurate and reliable measurements, fabrication strategies should include (1) proper choices of materials and structural designs, (2) constructing efficient wireless power and data transmission systems, and (3) developing highly-integrated sensing systems. Herein, we discuss recent advances in wearable devices for non-invasive sensing, with focuses on materials design, nano/microfabrication, sensors, wireless technologies, and the integration of those.

Continuous missing data imputation with incomplete dataset by generative adversarial networks–based unsupervised learning for long-term bridge health monitoring

2021 ◽  
pp. 147592172110219
Author(s):  
Huachen Jiang ◽  
Chunfeng Wan ◽  
Kang Yang ◽  
Youliang Ding ◽  
Songtao Xue
Keyword(s):  
Missing Data ◽  
Health Monitoring ◽  
Signal Transmission ◽  
Imputation Accuracy ◽  
Generative Adversarial Networks ◽  
Data Imputation ◽  
Sensor Failure ◽  
Generative Adversarial Network ◽  
Missing Data Imputation ◽  
Adversarial Network

Wireless sensors are the key components of structural health monitoring systems. During the signal transmission, sensor failure is inevitable, among which, data loss is the most common type. Missing data problem poses a huge challenge to the consequent damage detection and condition assessment, and therefore, great importance should be attached. Conventional missing data imputation basically adopts the correlation-based method, especially for strain monitoring data. However, such methods often require delicate model selection, and the correlations for vehicle-induced strains are much harder to be captured compared with temperature-induced strains. In this article, a novel data-driven generative adversarial network (GAN) for imputing missing strain response is proposed. As opposed to traditional ways where correlations for inter-strains are explicitly modeled, the proposed method directly imputes the missing data considering the spatial–temporal relationships with other strain sensors based on the remaining observed data. Furthermore, the intact and complete dataset is not even necessary during the training process, which shows another great superiority over the model-based imputation method. The proposed method is implemented and verified on a real concrete bridge. In order to demonstrate the applicability and robustness of the GAN, imputation for single and multiple sensors is studied. Results show the proposed method provides an excellent performance of imputation accuracy and efficiency.

scholarly journals Fibre Bragg Grating Based Acoustic Emission Measurement System for Structural Health Monitoring Applications

Materials ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 897
Author(s):  
Sagar Jinachandran ◽  
Ginu Rajan
Keyword(s):  
Acoustic Emission ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Market Potential ◽  
Bragg Grating ◽  
Fibre Bragg Grating ◽  
Emission Measurement ◽  
Structural Health ◽  
Sensing Systems ◽  
Recent Trends

Fiber Bragg grating (FBG)-based acoustic emission (AE) detection and monitoring is considered as a potential and emerging technology for structural health monitoring (SHM) applications. In this paper, an overview of the FBG-based AE monitoring system is presented, and various technologies and methods used for FBG AE interrogation systems are reviewed and discussed. Various commercial FBG AE sensing systems, SHM applications of FBG AE monitoring, and market potential and recent trends are also discussed.

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