scholarly journals Health monitoring of aging aerospace structures using the electromechanical impedance method

2002 ◽  
Author(s):  
Andrei N. Zagrai ◽  
Victor Giurgiutiu
Keyword(s):  
Health Monitoring ◽  
Impedance Method ◽  
Aerospace Structures ◽  
Electromechanical Impedance

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.

Truss Structure Health Monitoring Based on Electromechanical Impedance Method

2013 ◽  
Vol 330 ◽  
pp. 357-363
Author(s):  
Cun Fu He ◽  
Xiao Ming Cai ◽  
Shen Yang ◽  
Zeng Hua Liu ◽  
Bin Wu
Keyword(s):  
Neural Network ◽  
Health Monitoring ◽  
Truss Structure ◽  
Truss Structures ◽  
Impedance Method ◽  
Nonparametric Model ◽  
Impedance Spectra ◽  
Frequency Range ◽  
Electromechanical Impedance ◽  
Piezoelectric Elements

Truss structure is widely used in civil engineering applications for its advantages of easy transportation, convenient assembly and uniform loading. However, it is difficult to achieve real-time health monitoring because of connection diversity and complexity of truss structures. As a novel structural health monitoring technique, electro-mechanical impedance method could monitor the health state of one structure by measuring the spectra of impedance or admittance of the piezoelectric elements, which are bonded on the surface of this structure. This approach has the advantages of nonparametric model analysis, easy sensor installation and high local sensitivity, especially in sensitive frequency range. The damage information, which is tested and recorded by using electromechanical impedance method, could convert into intuitive results through neural network because of its good ability for nonlinear mapping. In this paper, a three-layer assembly truss structure was chosen as experimental object, piezoelectric elements were bonded on structure joints to measure structural impedance spectra, the change of these structural impedance spectra was tested and recorded under high frequency excitations when different truss bars were loosed, and then, one back-propagation (BP) neural network was built and trained by this damage information, which were treated as input samples. These results show that the sensitivity of impedance method is not the same to different frequency range and trained neural network could quickly identify loosen truss bars.

Electromechanical Impedance Method for Damage Detection of Typical Joint on Jacket Platform

2018 ◽  
Author(s):  
Boying Zhang ◽  
Hamad Hameed ◽  
Yuxin Xu ◽  
Chonglin Zhang ◽  
Yong Bai
Keyword(s):  
Health Monitoring ◽  
Mechanical Impedance ◽  
Theoretical Background ◽  
Impedance Method ◽  
Laboratory Measurements ◽  
Direct Evaluation ◽  
Jacket Platform ◽  
Health Monitoring System ◽  
Electromechanical Impedance ◽  
Experimental Works

Health monitoring of welded structural joints is a very important factor of the engineering community. Electro-mechanical impedance (EMI) technique allows the direct evaluation of structural dynamics by evaluating its E/M impedance or admittance signatures. This paper first gives a brief introduction of the theoretical background on the described method. Then, the described EMI technique is applied to recognize the presence of damage by executing experimental works where the damage in the form of crack is simulated with an impedance analyzer at various distances. Four typical welded metallic joints on a jacket platform successfully produced submillimeter cracks under cyclic loading and root mean square deviation (RMSD) is used to evaluate the degree of crack damage. Finally, an outcome of laboratory measurements performed with developed structural health monitoring system based on the electromechanical impedance phenomenon is presented.

An embeddable spherical smart aggregate for monitoring concrete hydration in very early age based on electromechanical impedance method

2020 ◽  
pp. 1045389X2096317
Author(s):  
Shuli Fan ◽  
Shaoyu Zhao ◽  
Qingzhao Kong ◽  
Gangbing Song
Keyword(s):  
Health Monitoring ◽  
Hydration Process ◽  
Impedance Method ◽  
Early Age ◽  
Curing Process ◽  
Electromechanical Impedance ◽  
Smart Aggregate ◽  
Stiffness Variation ◽  
Concrete Hydration ◽  
Host Structure

In this paper, a new embeddable spherical smart aggregate (SSA) was utilized to monitor concrete curing in very early age. Overcoming the limitation of the existing PZT-patch-based transducers, the SSA provides vital changing information in all directions of host structure. To verify the advantage of SSA in structural health monitoring (SHM), the sensitivities of SSA and smart aggregate (SA) in monitoring concrete cube deformation and stiffness variation were analyzed and compared by numerical simulation. The feasibility of SSA in monitoring the concrete hydration process was studied by experiments utilizing electromechanical impedance (EMI) technique. At last, four SSAs were embedded in a concrete column to study the practicality of SSA in monitoring the concrete curing process in very early age. The EMI signatures and the root mean square deviation (RMSD) values of the collected information from SSAs were analyzed. The results illustrate that the SSA is more sensitive than SA in monitoring the concrete deformation and stiffness variation. The data measured by SSA in monitoring the concrete hydration process fluctuates more obviously than the data recorded by SA. The new spherical transducer can effectively and reliably monitor the concrete hydration process.

Structural health monitoring of rotary aerospace structures based on electromechanical impedance of integrated piezoelectric transducers

2018 ◽  
Vol 29 (9) ◽  
pp. 1799-1817 ◽  
Author(s):  
Hamidreza Hoshyarmanesh ◽  
Ali Abbasi
Keyword(s):  
Structural Health Monitoring ◽  
Frequency Shift ◽  
Health Monitoring ◽  
Rotational Speed ◽  
Mechanical Impedance ◽  
Impedance Spectrum ◽  
Piezoelectric Transducers ◽  
Aerospace Structures ◽  
Electromechanical Impedance ◽  
Structural Health

Structural health monitoring of rotary aerospace structures is investigated in this research. A monitoring system is proposed based on the electromechanical impedance spectrum of piezoelectric transducers and a portable transceiver. To investigate the applicability and preliminary results of this method, a turbomachine prototype (laboratory device) is developed, and integrated composite piezoelectric films are deposited on the blades. Next, a self-diagnostic characterization is initially implemented to the piezo-films. Transceiver functionality and accuracy is verified using an Ivium impedance analyzer. The verified measuring path was used in structural health monitoring of pristine and damaged blades at rotational speed of 0 and 1000 r/min. The effects of damage formation and rotational speed on the impedance signature are discussed based on the variations in mechanical impedance using a two-dimensional model. Once damage occurs in a blade at each speed, it results in a frequency shift of the impedance signature at antiresonance peaks compared to the corresponding baseline. The results show a clear frequency shift of existing peaks and the appearance of new peaks as damage grows to a secure minimal detectable size. This achievement confirms the applicability of this method for incipient damage detection on rotary structures prior to any failure.

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.

Time-domain spectral element method for modelling of the electromechanical impedance of disbonded composites

2018 ◽  
Vol 29 (16) ◽  
pp. 3214-3221 ◽  
Author(s):  
Piotr Fiborek ◽  
Paweł H Malinowski ◽  
Paweł Kudela ◽  
Tomasz Wandowski ◽  
Wiesław M Ostachowicz
Keyword(s):  
Spectral Element Method ◽  
Spectral Element ◽  
Impedance Method ◽  
Adhesively Bonded ◽  
Destructive Testing ◽  
Electromechanical Impedance ◽  
Carbon Fibre Reinforced Polymer ◽  
Fibre Reinforced Polymer ◽  
Non Destructive ◽  
Element Method

The research focuses on the electromechanical impedance method. The electromechanical impedance method can be treated as non-destructive testing or structural health monitoring approach. It is important to have a reliable tool that allows verifying the integrity of the investigated objects. The electromechanical impedance method was applied here to assess the carbon fibre–reinforced polymer samples. The single and adhesively bonded samples were investigated. In the reported research, the electromechanical impedance spectra up to 5 MHz were considered. The investigation comprised of modelling using spectral element method and experimental measurements. Numerical and experimental spectra were analysed. Differences in spectra caused by differences in considered samples were observed.

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