Temperature and axial stress effects in electromechanical-impedance-method-based structural health monitoring

2014 ◽  
Author(s):  
Xuan Zhu ◽  
Francesco Lanza Di Scalea ◽  
Mahmood Fateh
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Axial Stress ◽  
Impedance Method ◽  
Electromechanical Impedance ◽  
Structural Health ◽  
Stress Effects

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.

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.

scholarly journals A New Structural Health Monitoring Strategy Based on PZT Sensors and Convolutional Neural Network

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2955 ◽  
Author(s):  
Mario de Oliveira ◽  
Andre Monteiro ◽  
Jozue Vieira Filho
Keyword(s):  
Neural Network ◽  
Structural Health Monitoring ◽  
Convolutional Neural Network ◽  
Lead Zirconate Titanate ◽  
Health Monitoring ◽  
Lead Zirconate ◽  
Industrial Applications ◽  
Electromechanical Impedance ◽  
Structural Health

Preliminaries convolutional neural network (CNN) applications have recently emerged in structural health monitoring (SHM) systems focusing mostly on vibration analysis. However, the SHM literature shows clearly that there is a lack of application regarding the combination of PZT-(lead zirconate titanate) based method and CNN. Likewise, applications using CNN along with the electromechanical impedance (EMI) technique applied to SHM systems are rare. To encourage this combination, an innovative SHM solution through the combination of the EMI-PZT and CNN is presented here. To accomplish this, the EMI signature is split into several parts followed by computing the Euclidean distances among them to form a RGB (red, green and blue) frame. As a result, we introduce a dataset formed from the EMI-PZT signals of 720 frames, encompassing a total of four types of structural conditions for each PZT. In a case study, the CNN-based method was experimentally evaluated using three PZTs glued onto an aluminum plate. The results reveal an effective pattern classification; yielding a 100% hit rate which outperforms other SHM approaches. Furthermore, the method needs only a small dataset for training the CNN, providing several advantages for industrial applications.

Method for removing temperature effect in impedance-based structural health monitoring systems using polynomial regression

2020 ◽  
pp. 147592172091712 ◽  
Author(s):  
Bárbara M Gianesini ◽  
Nicolás E Cortez ◽  
Rothschild A Antunes ◽  
Jozue Vieira Filho
Keyword(s):  
Structural Health Monitoring ◽  
Damage Detection ◽  
Temperature Effect ◽  
Health Monitoring ◽  
Monitoring Systems ◽  
Electromechanical Impedance ◽  
Structural Health ◽  
Detection Systems ◽  
Impedance Technique ◽  
Health Monitoring Systems

Structural health monitoring systems are employed to evaluate the state of structures to detect damage, bringing economical and safety benefits. The electromechanical impedance technique is a promising damage detection tool since it evaluates structural integrity by only measuring the electrical impedance of piezoelectric transducers bonded to structures. However, in real-world applications, impedance-based damage detection systems exhibit strong temperature dependence; therefore, variations associated with temperature changes may be confused as damage. In this article, the temperature effect on the electrical impedance of piezoelectric ceramics attached to structures is analyzed. Besides, a new methodology to compensate for the temperature effect in the electromechanical impedance technique is proposed. The method is very general since it can be applied to nonlinear (polynomial) temperature and/or frequency dependences observed on the horizontal and vertical shifts of the impedance signatures. A computer algorithm that performs the compensation was developed, which can be easily incorporated into real-time damage detection systems. This compensation technique is applied successfully to two aluminum beams and one steel pipe, minimizing the effect of temperature variations on damage detection structural health monitoring systems in the temperature range from −40°C to 80°C and the frequency range from 10 to 90 kHz.

scholarly journals Temperature Effects on Electromechanical Response of Deposited Piezoelectric Sensors Used in Structural Health Monitoring of Aerospace Structures

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2805 ◽  
Author(s):  
Hamidreza Hoshyarmanesh ◽  
Mojtaba Ghodsi ◽  
Minjae Kim ◽  
Hyung Hee Cho ◽  
Hyung-Ho Park
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Mechanical Impedance ◽  
Peak Shift ◽  
Aluminum Plate ◽  
Distinct Advantage ◽  
Compressor Blades ◽  
Turbine Engine ◽  
Electromechanical Impedance ◽  
Structural Health

Turbomachine components used in aerospace and power plant applications preferably require continuous structural health monitoring at various temperatures. The structural health of pristine and damaged superalloy compressor blades of a gas turbine engine was monitored using real electro-mechanical impedance of deposited thick film piezoelectric transducers at 20 and 200 °C. IVIUM impedance analyzer was implemented in laboratory conditions for damage detection in superalloy blades, while a custom-architected frequency-domain transceiver circuit was used for semi-field circumstances. Recorded electromechanical impedance signals at 20 and 200 °C acquired from two piezoelectric wafer active sensors bonded to an aluminum plate, near and far from the damage, were initially utilized for accuracy and reliability verification of the transceiver at temperatures >20 °C. Damage formation in both the aluminum plate and blades showed a peak shift in the swept frequency along with an increase in the amplitude and number of impedance peaks. The thermal energy at 200 °C, on the other hand, enforces a further subsequent peak shift in the impedance signal to pristine and damaged parts such that the anti-resonance frequency keeps reducing as the temperature increases. The results obtained from the impedance signals of both piezoelectric wafers and piezo-films, revealed that increasing the temperature somewhat decreased the real impedance amplitude and the number of anti-resonance peaks, which is due to an increase in permittivity and capacitance of piezo-sensors. A trend is also presented for artificial intelligence training purposes to distinguish the effect of the temperature versus damage formation in sample turbine compressor blades. Implementation of such a monitoring system provides a distinct advantage to enhance the safety and functionality of critical aerospace components working at high temperatures subjected to crack, wear, hot-corrosion and erosion.

An open database for benchmarking guided waves structural health monitoring algorithms on a composite full-scale outer wing demonstrator

2019 ◽  
Vol 19 (5) ◽  
pp. 1524-1541 ◽  
Author(s):  
Alessandro Marzani ◽  
Nicola Testoni ◽  
Luca De Marchi ◽  
Marco Messina ◽  
Ernesto Monaco ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Damage Detection ◽  
Monitoring System ◽  
Health Monitoring ◽  
Guided Wave ◽  
Full Scale ◽  
Composite Panel ◽  
Health Monitoring System ◽  
Electromechanical Impedance ◽  
Structural Health

This article reports on the creation of an open database of piezo-actuated and piezo-received guided wave signals propagating in a composite panel of a full-scale aeronautical structure. The composite panel closes the bottom part of a wingbox that, along with the leading edge, the trailing edge, and the wingtip, forms an outer wing demonstrator approximately 4.5 m long and from 1.2 to 2.3 m wide. To create the database, a structural health monitoring system, composed of a software/hardware central unit capable of controlling a network of 160 piezoelectric transducers secondarily bonded on the composite panel, has been realized. The structural health monitoring system has been designed to (1) perform electromechanical impedance measurement at each transducer, in order to check for their reliability and bonding strength, and (2) to operate an active guided wave screening for damage detection in the composite panel. Electromechanical impedance and guided wave measurements were performed at four different testing stages: before loading, before fatigue, before impacts, and after impacts. The database, freely available at http://shm.ing.unibo.it/ , can thus be used to benchmarking, on real-scale structural data, guided wave algorithms for loading, fatigue, as well as damage detection, characterization, and sizing. As an example, in this work, a delay and sum algorithm is applied on the post-impact data to illustrate how the database can be exploited.

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