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.

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 The role of dynamic response parameters in damage prediction

2019 ◽  
Vol 233 (13) ◽  
pp. 4620-4636 ◽  
Author(s):  
Behzad Ahmed Zai ◽  
MA Khan ◽  
Kamran A Khan ◽  
Asif Mansoor ◽  
Aqueel Shah ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Dynamic Response ◽  
Health Monitoring ◽  
Structural Damage ◽  
Mode Shapes ◽  
Future Research ◽  
Modal Parameter ◽  
Structural Health ◽  
Structural Applications

This article presents a literature review of published methods for damage identification and prediction in mechanical structures. It discusses ways which can identify and predict structural damage from dynamic response parameters such as natural frequencies, mode shapes, and vibration amplitudes. There are many structural applications in which dynamic loads are coupled with thermal loads. Hence, a review on those methods, which have discussed structural damage under coupled loads, is also presented. Structural health monitoring with other techniques such as elastic wave propagation, wavelet transform, modal parameter, and artificial intelligence are also discussed. The published research is critically analyzed and the role of dynamic response parameters in structural health monitoring is discussed. The conclusion highlights the research gaps and future research direction.

Research on Miniaturized and Portable Impedance-Measuring Device for Structural Health Monitoring

2011 ◽  
Vol 230-232 ◽  
pp. 587-591
Author(s):  
Yu Xiang Zhang ◽  
Dong Dong Wen ◽  
Hua Cheng Li ◽  
Fu Hou Xu
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Structural Damage ◽  
Electric Impedance ◽  
Measuring Device ◽  
Line System ◽  
Electromechanical Impedance ◽  
Structural Health ◽  
Impedance Technique ◽  
On Line

Electromechanical impedance technique which based on smart material is a new method for structural damage detection, and it could be widely applied in structural health monitoring field. However, a very expensive and bulky analyzer is being used to measure the impedance, which is not practical for on-line system. Therefore, this paper developed a device that can measure the electric impedance using small modular electric components and reasonable circuit. Experiments are carried out to test the aluminum beam crack. Results indicate that the device can measure the electric impedance and detect the damage effectively. The proposed method provides a solution to miniaturize the impedance-measuring equipment and reduce the cost of measurement.

Structural Health Monitoring With Piezoelectric Active Sensors

2000 ◽  
Vol 123 (2) ◽  
pp. 353-358 ◽  
Author(s):  
H. A. Winston ◽  
F. Sun ◽  
B. 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 of existing structures and infrastructures combining on-site and satellite data

2020 ◽  
Author(s):  
Felice Carlo Ponzo ◽  
Rocco Ditommaso
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Structural Damage ◽  
Rapid Evolution ◽  
Mode Shapes ◽  
Operational Conditions ◽  
Structural Health ◽  
Existing Structures ◽  
Research Fields ◽  
Over Time

<p>In the last years, existing structures and transport infrastructures, especially those made using reinforced concrete, have experienced significant safety criticalities implying also a relevant social and economic impacts. Structural Health Monitoring techniques represent a reliable response to the problem available to scientists and engineers. A multidisciplinary approach combing knowledge from several research fields and using different kind of technologies would be preferable for this type of application. Most of developed methods for structural damage detection on civil structures and infrastructures is generally based on the evaluation of displacements, eigenfrequencies, damping factors, mode shapes, etc., and their variation over time, by means of on-site installed sensors. In recent years, thanks to the rapid evolution of interferometric SAR processing techniques, a large amount of “satellite measurements” are available for both geophysical phenomena and building monitoring in terms of displacement rate over time. This paper presents an overview on the 2019-2021 WP6 Reluis Project aiming to contribute to the discussion about the opportunity and the modalities to merge information retrieved both by on-site and remote sensing measurements and to define a shared strategy to detect damage on existing structures and infrastructures in operational conditions.</p>

scholarly journals Experimental Evaluation of Miniature Impedance Board for Loosening Monitoring of the Threaded Pipe Connection

2021 ◽  
Vol 9 ◽  
Author(s):  
Yabin Liang ◽  
Yixuan Chen ◽  
Zuocai Zhang ◽  
Qian Feng
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Structural Damage ◽  
Damage Identification ◽  
Low Cost ◽  
Impedance Measurement ◽  
Measurement Procedure ◽  
Practical Applications ◽  
Electromechanical Impedance ◽  
Structural Health

Electromechanical impedance (Electromechanical impedance)-based methods as potential nondestructive evaluation (NDT) techniques have been widely used in the field of structural health monitoring (SHM), especially for the civil, mechanical, and aerospace engineering fields. However, it is still difficult to apply in practical applications due to the limitations of the impedance measurement hardware, which is usually expensive, bulky, and heavy. In this paper, a small, lightweight, and low power consumption EMI-based structural health monitoring system combined with the low-cost miniature impedance board AD5933 was studied experimentally to investigate its quantifiable performance in impedance measurement and structural damage identification. At first, a simple impedance test with a free PZT patch was introduced to present the impedance calibration and measurement procedure of AD5933, and then its calibration performance was validated by comparing the signature with the one measured by a professional impedance analyzer (WK6500B). In order to further validate the feasibility and effectiveness of the AD5933 board in practical applications, a threaded pipe connection specimen was assembled in the laboratory and then connected with the AD5933 to acquire its impedance signatures under different loosening severities. The final results demonstrated that the impedance measured by the AD5933 show a good consistency with the measurements by the WK6500B, and the evaluation board could be successfully utilized for the loosening severities identification and quantitatively evaluation.

Diagnosis and validation of damaged piezoelectric sensor in electromechanical impedance technique

2016 ◽  
Vol 28 (7) ◽  
pp. 837-850 ◽  
Author(s):  
Demi Ai ◽  
Hui Luo ◽  
Hongping Zhu
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Structural Damage ◽  
Piezoelectric Sensor ◽  
Bonding Layer ◽  
The Real ◽  
Electromechanical Impedance ◽  
Structural Health ◽  
Validity Assessment ◽  
Impedance Technique

Piezoelectric sensor diagnosis and validity assessment as a prior component of structural health monitoring system are necessary in the practical application of electromechanical impedance technique. This article proposed an innovative sensor self-diagnosis process based on extracting the characterization of the real admittance (inverse of impedance) signature within a high-frequency range, which covered both diagnosis on damaged sensor after its installation and discrimination of sensor and structural damages during structural health monitoring process. Theoretical analysis was derived from the impedance model of piezoelectric-bonding layer-structure dynamic interaction system. Experimental investigations on piezoelectric sensor-bonded steel beam involved with structural damages of mass addition and notch damage were conducted to verify the process. It was found that the real admittance was reliable and critical in sensor diagnosis, and sensor faults of debonding, scratch, and breakage can be identified and differentiated from structural damage. Validity assessment of the diagnosed damaged sensor was addressed through resonant frequency shift method. The results showed that the validity of damaged sensor for structural health monitoring was inordinately depreciated by sensor damage. This article is expected to be useful for structural health monitoring application especially when damaged piezoelectric sensors existed.

scholarly journals An overview of 38 least squares–based frameworks for structural damage tomography

2019 ◽  
Vol 19 (1) ◽  
pp. 215-239 ◽  
Author(s):  
Danny Smyl ◽  
Sven Bossuyt ◽  
Waqas Ahmad ◽  
Anton Vavilov ◽  
Dong Liu
Keyword(s):  
Structural Health Monitoring ◽  
Least Squares ◽  
Health Monitoring ◽  
Structural Damage ◽  
Tomographic Imaging ◽  
Inverse Methods ◽  
One Dimension ◽  
Distributed Data ◽  
Structural Health ◽  
Static Elasticity

The ability to reliably detect damage and intercept deleterious processes, such as cracking, corrosion, and plasticity are central themes in structural health monitoring. The importance of detecting such processes early on lies in the realization that delays may decrease safety, increase long-term repair/retrofit costs, and degrade the overall user experience of civil infrastructure. Since real structures exist in more than one dimension, the detection of distributed damage processes also generally requires input data from more than one dimension. Often, however, interpretation of distributed data—alone—offers insufficient information. For this reason, engineers and researchers have become interested in stationary inverse methods, for example, utilizing distributed data from stationary or quasi-stationary measurements for tomographic imaging structures. Presently, however, there are barriers in implementing stationary inverse methods at the scale of built civil structures. Of these barriers, a lack of available straightforward inverse algorithms is at the forefront. To address this, we provide 38 least-squares frameworks encompassing single-state, two-state, and joint tomographic imaging of structural damage. These regimes are then applied to two emerging structural health monitoring imaging modalities: Electrical Resistance Tomography and Quasi-Static Elasticity Imaging. The feasibility of the regimes are then demonstrated using simulated and experimental data.

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.

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