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

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.

Author(s):  
Liuxian Zhao ◽  
Lingyu Yu ◽  
Mattieu Gresil ◽  
Michael Sutton ◽  
Siming Guo

Electromechanical impedance (EMI) method is an effective and powerful technique in structural health monitoring (SHM) which couples the mechanical impedance of host structure with the electrical impedance measured at the piezoelectric wafer active sensor (PWAS) transducer terminals. Due to the electromechanical coupling in piezoelectric materials, changes in structural mechanical impedance are reflected in the electrical impedance measured at the PWAS. Therefore, the structural mechanical resonances are reflected in a virtually identical spectrum of peaks and valleys in the real part of the measured EMI. Multi-physics based finite element method (MP-FEM) has been widely used for the analysis of piezoelectric materials and structures. It uses finite elements taking both electrical and mechanical DOF’s into consideration, which allows good differentiation of complicated structural geometries and damaged areas. In this paper, MP-FEM was then used to simulate PWAS EMI for the goal of SHM. EMI of free PWAS was first simulated and compared with experimental result. Then the constrained PWAS was studied. EMI of both metallic and glass fiber composite materials were simulated. The first case is the constrained PWAS on aluminum beam with various dimensions. The second case studies the sensitivity range of the EMI approach for damage detection on aluminum beam using a set of specimens with cracks at different locations. In the third case, structural damping effects were also studied in this paper.. Our results have also shown that the imaginary part of the impedance and admittance can be used for sensor self-diagnosis.


2020 ◽  
Vol 31 (16) ◽  
pp. 1898-1909
Author(s):  
Qijian Liu ◽  
Yuan Chai ◽  
Xinlin Qing

A variety of structural health monitoring techniques have been developed to support the efficient online monitoring of structural integrity. Moreover, Lamb wave and electromechanical impedance methods are increasingly used for structural health monitoring applications due to their high sensitivity and effectiveness in detecting damage. However, these techniques require transducers to be permanently attached to structures because of the usage of baselines recorded under the condition without damage. In this study, a reusable piezoelectric lead zirconate titanate transducer for monitoring corrosion damage on the aluminum plate is introduced, which can be removed from the test specimen and reused with the repeatability of signals. The reusable piezoelectric lead zirconate titanate transducer is bonded on the aluminum plate using the ethylene-acrylic acid copolymer with an aluminum enclosure. A series of experiments are conducted on an aluminum plate, including the investigation for repeatability of signals and the capability of corrosion detection of the designed piezoelectric lead zirconate titanate transducer through the Lamb wave and electromechanical impedance methods. The simulated corrosion defect with the area of 15 × 15 mm2 is detected during experiments. The experimental results confirm that the reusable piezoelectric lead zirconate titanate transducer can effectively evaluate the corrosion damage to plate structure and can be reused many times.


2021 ◽  
pp. 147592172199341
Author(s):  
A Francisco G Tenreiro ◽  
António M Lopes ◽  
Lucas FM da Silva

The article presents a literature review of electromechanical impedance spectroscopy for structural health monitoring, with emphasis in adhesively bonded joints. The concept behind electromechanical impedance spectroscopy is to use variable high-frequency structural vibrations with piezoelectric elements to monitor the local area of a structure for changes in mechanical impedance that may indicate imminent damage. Various mathematical models that correlate the structural impedance with the electric response of the piezoelectric sensors are presented. Several algorithms and metrics are introduced to detect, localize, and characterize damage when using electromechanical impedance spectroscopy. Applications of electromechanical impedance spectroscopy to study adhesive joints are described. Research and development of alternative hardware for electromechanical impedance spectroscopy is presented. The article ends by presenting future prospects and research of electromechanical impedance spectroscopy–based structural health monitoring, and, while advances have been made in algorithms for damage detection, localization, and characterization, this technology is not mature enough for real-world applications.


2012 ◽  
Vol 19 (5) ◽  
pp. 811-823 ◽  
Author(s):  
L.V. Palomino ◽  
K.M. Tsuruta ◽  
J.R.V. Mour Jr ◽  
D.A. Radea ◽  
V. Steffen Jr. ◽  
...  

Structural Health Monitoring (SHM) is the process of damage identification in mechanical structures that encompasses four main phases: damage detection, damage localization, damage extent evaluation and prognosis of residual life. Among various existing SHM techniques, the one based on electromechanical impedance measurements has been considered as one of the most effective, especially in the identification of incipient damage. This method measures the variation of the electromechanical impedance of the structure as caused by the presence of damage by using piezoelectric transducers bonded on the surface of the structure (or embedded into it). The most commonly used smart material in the context of the present contribution is the lead zirconate titanate (PZT). Through these piezoceramic sensor-actuators, the electromechanical impedance, which is directly related to the mechanical impedance of the structure, is obtained as a frequency domain dynamic response. Based on the variation of the impedance signals, the presence of damage can be detected. A particular damage metric can be used to quantify the damage. For the success of the monitoring procedure, the measurement system should be robust enough with respect to environmental influences from different sources, in such a way that correct and reliable decisions can be made based on the measurements. The environmental influences become more critical under certain circumstances, especially in aerospace applications, in which extreme conditions are frequently encountered. In this paper, the influence of electromagnetic radiation, temperature and pressure variations, and ionic environment have been examined in laboratory. In this context, the major concern is to determine if the impedance responses are affected by these influences. In addition, the sensitivity of the method with respect to the shape of the PZT patches is evaluated. Conclusions are drawn regarding the monitoring efficiency, stability and precision.


2018 ◽  
Vol 29 (9) ◽  
pp. 1799-1817 ◽  
Author(s):  
Hamidreza Hoshyarmanesh ◽  
Ali Abbasi

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.


2021 ◽  
pp. 136943322110384
Author(s):  
Xingyu Fan ◽  
Jun Li ◽  
Hong Hao

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.


Author(s):  
Robert I. Ponder ◽  
Mohsen Safaei ◽  
Steven R. Anton

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.


Author(s):  
Howard A. Winston ◽  
Fanping Sun ◽  
Balkrishna S. Annigeri

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.


Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2955 ◽  
Author(s):  
Mario de Oliveira ◽  
Andre Monteiro ◽  
Jozue Vieira Filho

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.


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