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American Society for Testing and Materials

A review of recent research on mechanics of multifunctional composite materials and structures

The paper provides a state of the art review of guided wave based structural health monitoring (SHM). First, the fundamental concepts of guided wave propagation and its implementation for SHM is explained. Following sections present the different modeling schemes adopted, developments in the area of transducers for generation, and sensing of wave, signal processing and imaging technique, statistical and machine learning schemes for feature extraction. Next, a section is presented on the recent advancements in nonlinear guided wave for SHM. This is followed by section on Rayleigh and SH waves. Next is a section on real-life implementation of guided wave for industrial problems. The paper, though briefly talks about the early development for completeness,. is primarily focussed on the recent progress made in the last decade. The paper ends by discussing and highlighting the future directions and open areas of research in guided wave based SHM.

https://iopscience.iop.org/article/10.1088/0964-1726/25/5/053001/pdf

Guided wave based structural health monitoring: A review

Electrospun nanofiber reinforced composites: a review

Data fusion and machine learning for industrial prognosis: Trends and perspectives towards Industry 4.0

Artificial damage in the form of a through-thickness hole in a composite panel of five stiffeners is identified using a guided wave-based damage diagnostic algorithm, which is based on the probability of the presence of damage in the monitoring area estimated using correlation coefficients of Lamb wave signals from an active sensor network. Without defining the detail features of individual wave components, this diagnostic algorithm focuses on the calibrated changes in wave signals due to the presence of damage. The probability of the presence of damage at each grid in the monitoring area is estimated. The area consisting of grids with probability values for the presence of damage above a threshold is subsequently identified for damage identification. The effect of networks of sensing paths and shapes of the affected zone of individual sensing paths on identifying the damage in the composite panel is investigated. The results demonstrate that the diagnostic algorithm, being computationally efficient and amenable to automated processing, can be used to identify damage in highly complex structures.

Probability of the presence of damage estimated from an active sensor network in a composite panel of multiple stiffeners

A New Method for the Estimation of Lost Gas During the Measurement of the Gas Content of Coal

Molecular Dynamics Simulations of Graphene Pull-Out from Calcium Silicate Hydrate

The propagation characteristics of Lamb waves activated and collected by an active piezoelectric (PZT) sensor network in a CF/EP composite panel of five stiffeners were investigated. In particular, wave attenuation in terms of propagation distance and wave energy loss induced by reinforced stiffeners were evaluated. The interaction between Lamb wave modes and a through-thickness hole of 11.9 mm diameter was subsequently examined. Given the complexity of the captured wave signals, an inverse algorithm based on correlation between wave signals in the benchmark and damaged structures was developed. Different combinations of actuator-sensor paths were used to estimate the location of damage. The diagnostic results demonstrate that the proposed approach has a good capability for defining location of damage using the probability of occurrence of damage.

Ye Lu

Papers

Probability of the presence of damage estimated from an active sensor network in a composite panel of multiple stiffeners

A New Method for the Estimation of Lost Gas During the Measurement of the Gas Content of Coal

Molecular Dynamics Simulations of Graphene Pull-Out from Calcium Silicate Hydrate

Damage detection in a large composite panel of five stiffeners using Lamb wave signals

Advanced numerical simulations considering crack orientation for fatigue damage quantification using nonlinear guided waves.