Review of piezoelectric impedance based structural health monitoring: Physics-based and data-driven methods

Abstract

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.

Sandwich Face Layer Debonding Detection and Size Estimation by Machine-Learning-Based Evaluation of Electromechanical Impedance Measurements

“…Classical statistical damage metrics typically do not allow reliable damage identification [ 9 ]. However, recently, with the development and increasing distribution of novel statistical methods like machine learning (ML), and the availability of large computational power, new potential to solve the issue has been identified by the scientific community [ 13 ]. This has been similarly reported by Avci [ 14 ] for “vibration-based methods”, by a review of a number of selected journals.…”

“…This has been similarly reported by Avci [ 14 ] for “vibration-based methods”, by a review of a number of selected journals. Furthermore, numerous recent review articles have highlighted the application and the advances of ML-based measurement data evaluation for vibration-based damage monitoring methods, such as the EMI [ 13 , 14 , 15 , 16 ]. Fan [ 13 ] classified EMI measurement data evaluation methods into data-based and physics-based methods.…”

“…The latter was also supported by the findings of Lopes [ 17 ], who stated that feature engineering, i.e., the selection of meaningful features of the raw data, often (i) highlights dynamic characteristics of the evaluation objective, and (ii) strongly reduces the required amount of training data. For a summary of the key contributions to data-driven and ML-based EMI measurement data, see Fan [ 13 ].…”

“…Shuai [ 34 ] and Kralovec [ 9 ] demonstrated this approach by the identification of the crack location and severity in a simple metallic beam, and the debonding size in an aluminum sandwich panel, respectively. However, physics-based methods are still limited to a low-frequency range or simple mechanical structures (mostly beams are investigated), as computational accuracy and efficiency are still issues [ 13 ].…”

Impedance-based damage assessment of steel-ECC composite deck using piezoelectric transducers

“…The basic principle of the impedance method is that the structural damage will cause the change of its mechanical impedance. The mechanical and electrical coupling characteristics of the PZT sensor and the main structure are used to reflect the change of mechanical impedance of the structure through electrical impedance signal of the piezoelectric sensor, so as to identify the structural damage at an early stage (Annamdas and Radhika, 2013;Na and Baek, 2018;Fan et al, 2021).…”