This paper proposes a probabilistic approach for acoustic emission (AE) source localization in isotropic plate-like structures based on an extended Kalman filter (EKF). The proposed approach consists of two main stages. During the first stage, time-of-flight (TOF) measurements of Lamb waves are carried out by a continuous wavelet transform (CWT), accounting for systematic errors due to the Heisenberg uncertainty; the second stage uses an EKF to iteratively estimate the AE source location and the wave velocity. The advantages of the proposed algorithm over the traditional methods include the capability of: (1) taking into account uncertainties in TOF measurements and wave velocity and (2) efficiently fusing multi-sensor data to perform AE source localization. The performance of the proposed approach is validated through pencil-lead breaks performed on an aluminum plate at systematic grid locations. The plate was instrumented with an array of four piezoelectric transducers in two different configurations.

This work presents a new approach based on fractal analysis of guided ultrasonic waves (GUWs) for monitoring the corrosion evolutionary path in post-tensioned systems. Fractal analysis is a new scientific paradigm that has been used successfully in many fields including biological and physical sciences. However, its application in the SHM community has been modest. The proposed approach utilizes piezoelectric transducers, permanently attached to the steel tendon, to transmit and receive GUWs. The corrosion monitoring is performed through the examination of the fractal dimension of GUW measurements over time. Accelerated corrosion tests were carried out on two 7 wire steel strands embedded in two concrete blocks to validate the proposed system. Finally, an outlier detection algorithm is proposed to enhance the sensitivity of the technique to the corrosion-induced damage.

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This article proposes an adaptive multisensor fusion algorithm for acoustic emission source location in isotropic platelike structures in noisy environments. Overall, the approach consists of the following four main stages: (a) feature extraction, (b) sensor selection based on a binary hypothesis testing, (c) sensor weighting based on a well-defined reliability function, and (d) estimation of the acoustic emission source location based on the extended Kalman filter. The performance of the proposed algorithm is validated through pencil lead breaks performed on an aluminum plate instrumented with a sparse array of piezoelectric sensors. Two experimental setups have been used to simulate a highly noisy environment. In the first setup, the experimental signals have been artificially corrupted with different levels of noise generated by a Monte Carlo simulation. In the second setup, two piezoelectric transducers have been used to continuously generate high-power white noise during testing. The results show the capability of the proposed algorithm for inflight structural health monitoring of metallic aircraft panels in highly noisy operational situation.

This paper presents a novel vibration-based piezoelectric energy harvester capable of passively tuning its resonant frequency to a wide range of frequencies. The device comprises a dual bimorph with a mass at its free end. A novel sliding mechanism, consisting of two oblique springs connected to the tip mass, is proposed to widen the resonance frequency of the device even to very low frequencies. The application of two oblique springs results in an additional stiffness and axial load that are introduced within the system, such that the resonance frequency of the device is now a function of both the stiffness and axial load associated with the spring forces. An operator can manually change the resonance frequency of the harvester just by small adjustments of the sliding mechanism. Further, the device allows one to tune the resonance frequency of the beam to match very low frequencies without the requirement of having a large proof mass. The analytical solution of an axially loaded cantilevered piezoelectric energy harvester with tip stiffness, using Euler–Bernoulli beam assumptions, is presented. A parametric case study is presented to demonstrate the performance of the device.