Structural health monitoring (SHM) is being widely evaluated by the aerospace industry as a method to improve the safety and reliability of aircraft structures and also reduce operational cost. Built-in sensor networks on an aircraft structure can provide crucial information regarding the condition, damage state and/or service environment of the structure. Among the various types of transducers used for SHM, piezoelectric materials are widely used because they can be employed as either actuators or sensors due to their piezoelectric effect and vice versa. This paper provides a brief overview of piezoelectric transducer-based SHM system technology developed for aircraft applications in the past two decades. The requirements for practical implementation and use of structural health monitoring systems in aircraft application are then introduced. State-of-the-art techniques for solving some practical issues, such as sensor network integration, scalability to large structures, reliability and effect of environmental conditions, robust damage detection and quantification are discussed. Development trend of SHM technology is also discussed.

Piezoelectric Transducer-Based Structural Health Monitoring for Aircraft Applications.

Piezoelectric sensors are increasingly being used in active structural health monitoring, due to their durability, light weight and low power consumption. In the present work damage detection and characterization methodologies based on Lamb waves have been evaluated for aircraft panels. The applicability of various proposed delay-and-sum algorithms on isotropic and composite stiffened panels have been investigated, both numerically and experimentally. A numerical model for ultrasonic wave propagation in composite laminates is proposed and compared to signals recorded from experiments. A modified delay-and-sum algorithm is then proposed for detecting impact damage in composite plates with and without a stiffener which is shown to capture and localize damage with only four transducers.

https://iopscience.iop.org/article/10.1088/0964-1726/23/7/075007/pdf

Assessment of delay-and-sum algorithms for damage detection in aluminium and composite plates

IEEE Standard on Piezoelectricity

In this paper, some recent piezoelectric wafer active sensors (PWAS) progress achieved in our laboratory for active materials and smart structures (LAMSS) at the University of South Carolina: http: //www.me.sc.edu/research/lamss/ group is presented. First, the characterization of the PWAS materials shows that no significant change in the microstructure after exposure to high temperature and nuclear radiation, and the PWAS transducer can be used in harsh environments for structural health monitoring (SHM) applications. Next, PWAS active sensing of various damage types in aluminum and composite structures are explored. PWAS transducers can successfully detect the simulated crack and corrosion damage in aluminum plates through the wavefield analysis, and the simulated delamination damage in composite plates through the damage imaging method. Finally, the novel use of PWAS transducers as acoustic emission (AE) sensors for in situ AE detection during fatigue crack growth is presented. The time of arrival of AE signals at multiple PWAS transducers confirms that the AE signals are originating from the crack, and that the amplitude decay due to geometric spreading is observed.

https://scholarcommons.sc.edu/cgi/viewcontent.cgi?article=1798&context=emec_facpub

Recent Advances in Piezoelectric Wafer Active Sensors for Structural Health Monitoring Applications

Viscoelastic Materials: Preface

Composite structures may be subjected to internal damages caused by impact events, which can seriously degrade the property of the structures. Hence, impact monitoring is of great importance to ensure the applications of composite, especially in aerospace engineering. This paper puts forward, for the first time, a new multi-response-based wireless sensor network (WSN) to realize the large-scale impact monitoring with the weight and complexity of the monitoring system reduced greatly. A novel multi-response-based global impact localization method that can unite multiple leaf nodes to solve the problems of localization confliction and mid-region localization is proposed for the WSN. Evaluations performed on large-scale complex composite structures have shown the advantages of the presented new methods.

A Multi-Response-Based Wireless Impact Monitoring Network for Aircraft Composite Structures

Structural health monitoring technology for aerospace structures has gradually turned from fundamental research to practical implementations. However, real aerospace structures work under time-varying conditions that introduce uncertainties to signal features that are extracted from sensor signals, giving rise to difficulty in reliably evaluating the damage. This paper proposes an online updating Gaussian Mixture Model (GMM)-based damage evaluation method to improve damage evaluation reliability under time-varying conditions. In this method, Lambwave-signal variation indexes and principle component analysis (PCA) are adopted to obtain the signal features. A baseline GMM is constructed on the signal features acquired under timevarying conditions when the structure is in a healthy state. By adopting the online updating mechanism based on a moving feature sample set and inner probability structural reconstruction, the probability structures of the GMM can be updated over time with new monitoring signal features to track the damage progress online continuously under time-varying conditions. This method can be implemented without any physical model of damage or structure. A real aircraft wing spar, which is an important load-bearing structure of an aircraft, is adopted to validate the proposed method. The validation results show that the method is effective for edge crack growth monitoring of the wing spar bolts holes under the time-varying changes in the tightness degree of the bolts.

https://iopscience.iop.org/article/10.1088/0964-1726/23/12/125001/pdf

On-line updating Gaussian mixture model for aircraft wing spar damage evaluation under time-varying boundary condition

Guided wave attenuation in composites due to material damping is strong, anisotropic, and cannot be neglected. Material damping is a critical parameter in selection of a particular wave mode for lo...

Guided wave excitation and propagation in damped composite plates

For aerospace application of structural health monitoring (SHM) technology, the problem of reliable damage monitoring under time-varying conditions must be addressed and the SHM technology has to be fully validated on real aircraft structures under realistic load conditions on ground before it can reach the status of flight test. In this paper, the guided wave (GW) based SHM method is applied to a full-scale aircraft fatigue test which is one of the most similar test status to the flight test. To deal with the time-varying problem, a GW-Gaussian mixture model (GW-GMM) is proposed. The probability characteristic of GW features, which is introduced by time-varying conditions is modeled by GW-GMM. The weak cumulative variation trend of the crack propagation, which is mixed in time-varying influence can be tracked by the GW-GMM migration during on-line damage monitoring process. A best match based Kullback–Leibler divergence is proposed to measure the GW-GMM migration degree to reveal the crack propagation. The method is validated in the full-scale aircraft fatigue test. The validation results indicate that the reliable crack propagation monitoring of the left landing gear spar and the right wing panel under realistic load conditions are achieved.

Hanfei Mei

Papers

Recent Advances in Piezoelectric Wafer Active Sensors for Structural Health Monitoring Applications

A Multi-Response-Based Wireless Impact Monitoring Network for Aircraft Composite Structures

On-line updating Gaussian mixture model for aircraft wing spar damage evaluation under time-varying boundary condition

Guided wave excitation and propagation in damped composite plates

Crack propagation monitoring in a full-scale aircraft fatigue test based on guided wave-Gaussian mixture model