Deep Learning Based Structural Health Monitoring Framework with Electromechanical Impedance Method

2019 ◽  
pp. 13-24
Author(s):  
Alex W. H. Choy ◽  
Daniel P. K. Lun
Keyword(s):  
Deep Learning ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Impedance Method ◽  
Electromechanical Impedance ◽  
Structural Health ◽  
Monitoring Framework

Nonlinear Modeling of Cracked Beams for Impedance Based Structural Health Monitoring

2017 ◽  
Author(s):  
Naserodin Sepehry ◽  
Firooz Bakhtiari-Nejad ◽  
Mahnaz Shamshirsaz ◽  
Weidong Zhu
Keyword(s):  
Structural Health Monitoring ◽  
Linear System ◽  
Frequency Response ◽  
Frequency Domain ◽  
Health Monitoring ◽  
Impedance Method ◽  
Breathing Crack ◽  
Electromechanical Impedance ◽  
Structural Health ◽  
System Equations

One of the main objectives of the structural health monitoring by piezoelectric wafer active sensor (PWAS) using electromechanical impedance method is continuously damage detection applications. In present work impedance method of beam structure is considered and the effect of early crack using breathing crack modeling is studied. In order to model the effect of a crack in beam, the beam is connected with a rotational spring in crack location. The Rayleigh–Ritz method is used to generate ordinary differential equation of cracked beam. Firstly, only open crack is considered that this is leads to linear system equation. In linear system, time domain system equations are converted to frequency domain, and then impedance of PWAS in frequency domain is calculated. Secondly, the breathing crack is modeled to be fully open or fully closed. This phenomenon leads to the nonlinear system equations. These nonlinear equations are solved using pseudo-arc length continuation scheme and collocation method for any harmonic voltage applied to actuator. Then impedance of PWAS is calculated. Two methods are used to detect early crack using breathing crack modeling on PWAS impedance. At the first, frequency response of breathing crack in the frequency range with its sub-harmonics is calculated. Second, only frequency response of one harmonic is computed with its super-harmonics. Finally, the detection method of linear is compared with nonlinear model.

scholarly journals Data-Driven Structural Health Monitoring and Damage Detection through Deep Learning: State-of-the-Art Review

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2778 ◽  
Author(s):  
Mohsen Azimi ◽  
Armin Eslamlou ◽  
Gokhan Pekcan
Keyword(s):  
Deep Learning ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
High Speed ◽  
Deep Neural Networks ◽  
State Of The Art ◽  
Data Driven ◽  
Structural Health ◽  
Promising Tool ◽  
Significant Attention

Data-driven methods in structural health monitoring (SHM) is gaining popularity due to recent technological advancements in sensors, as well as high-speed internet and cloud-based computation. Since the introduction of deep learning (DL) in civil engineering, particularly in SHM, this emerging and promising tool has attracted significant attention among researchers. The main goal of this paper is to review the latest publications in SHM using emerging DL-based methods and provide readers with an overall understanding of various SHM applications. After a brief introduction, an overview of various DL methods (e.g., deep neural networks, transfer learning, etc.) is presented. The procedure and application of vibration-based, vision-based monitoring, along with some of the recent technologies used for SHM, such as sensors, unmanned aerial vehicles (UAVs), etc. are discussed. The review concludes with prospects and potential limitations of DL-based methods in SHM applications.

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.

Validation of Impedance-Based Structural Health Monitoring in a Simulated Biomedical Implant System

2018 ◽  
Author(s):  
Robert I. Ponder ◽  
Mohsen Safaei ◽  
Steven R. Anton
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Orthopedic Implants ◽  
The United States ◽  
The State ◽  
Piezoelectric Transducers ◽  
Bone Implant ◽  
Electromechanical Impedance ◽  
Structural Health ◽  
Number Of Patients

Total Knee Replacement (TKR) is an important and in-demand procedure for the aging population of the United States. In recent decades, the number of TKR procedures performed has shown an increase. This pattern is expected to continue in the coming decades. Despite medical advances in orthopedic surgery, a high number of patients, approximately 20%, are dissatisfied with their procedure outcomes. Common causes that are suggested for this dissatisfaction include loosening of the implant components as well as infection. To eliminate loosening as a cause, it is necessary to determine the state of the implant both intra- and post-operatively. Previous research has focused on passively sensing the compartmental loads between the femoral and tibial components. Common methods include using strain gauges or even piezoelectric transducers to measure force. An alternative to this is to perform real-time structural health monitoring (SHM) of the implant to determine changes in the state of the system. A commonly investigated method of SHM, referred to as the electromechanical impedance (EMI) method, involves using the coupled electromechanical properties of piezoelectric transducers to measure the host structure’s condition. The EMI method has already shown promise in aerospace and infrastructure applications, but has seen limited testing for use in the biomechanical field. This work is intended to validate the EMI method for use in detecting damage in cemented bone-implant interfaces, with TKR being used as a case study to specify certain experimental parameters. An experimental setup which represents the various material layers found in a bone-implant interface is created with various damage conditions to determine the ability for a piezoelectric sensor to detect and quantify the change in material state. The objective of this work is to provide validation as well as a foundation on which additional work in SHM of orthopedic implants and structures can be performed.

Structural Health Monitoring With Piezoelectric Active Sensors

2000 ◽  
Author(s):  
Howard A. Winston ◽  
Fanping Sun ◽  
Balkrishna S. Annigeri
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Structural Damage ◽  
Electromechanical Coupling ◽  
Low Cost ◽  
Piezoelectric Element ◽  
Impedance Spectrum ◽  
Active Sensors ◽  
Electromechanical Impedance ◽  
Structural Health

A technology for non-intrusive real-time structural health monitoring using piezoelectric active sensors is presented. The approach is based on monitoring variations of the coupled electromechanical impedance of piezoelectric patches bonded to metallic structures in high-frequency bands. In each of these applications, a single piezoelectric element is used as both an actuator and a sensor. The resulting electromechanical coupling makes the frequency-dependent electric impedance spectrum of the PZT sensor a good mapping of the underlying structure’s acoustic signature. Moreover, incipient structural damage can be indicated by deviations of this signature from its original baseline pattern. Unique features of this technology include its high sensitivity to structural damage, non-intrusiveness to the host structure, and low cost of implementation. These features have potential for enabling on-board damage monitoring of critical or inaccessible aerospace structures and components, such as aircraft wing joints, and both internal and external jet engine components. Several exploratory applications will be discussed.

Structural Health Monitoring Framework Based on Internet of Things: A Survey

2017 ◽  
Vol 4 (3) ◽  
pp. 619-635 ◽  
Author(s):  
C. Arcadius Tokognon ◽  
Bin Gao ◽  
Gui Yun Tian ◽  
Yan Yan
Keyword(s):  
Structural Health Monitoring ◽  
Internet Of Things ◽  
Health Monitoring ◽  
Structural Health ◽  
Monitoring Framework
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