Strain sensitivity enhancement of broadband ultrasonic signals in plates using spectral phase filtering.

The focused signal obtained by the time-reversal or the cross-correlation techniques of ultrasonic guided waves in plates changes when the medium is subject to strain, which can be used to monitor the medium strain level. In this paper, the sensitivity to strain of cross-correlated signals is enhanced by a post-processing filtering procedure aiming to preserve only strain-sensitive spectrum components. Two different strategies were adopted, based on the phase of either the Fourier transform or the short-time Fourier transform. Both use prior knowledge of the system impulse response at some strain level. The technique was evaluated in an aluminum plate, effectively providing up to twice higher sensitivity to strain. The sensitivity increase depends on a phase threshold parameter used in the filtering process. Its performance was assessed based on the sensitivity gain, the loss of energy concentration capability, and the value of the foreknown strain. Signals synthesized with the time–frequency representation, through the short-time Fourier transform, provided a better tradeoff between sensitivity gain and loss of energy concentration

Machine learning-based corrosion-like defect estimation with shear-horizontal guided waves improved by mode separation

Shear Horizontal (SH) guided waves have been extensively used to estimate and detect defects in structures like plates and pipes. Depending on the frequency and plate thickness, more than one guided-wave mode propagates, which renders signal interpretation complicated due to mode mixing and complex behavior of each individual mode interacting with defects. This paper investigates the use of machine learning models to analyse the two lowest order SH guided modes, for quantitative size estimation and detection of corrosion-like defects in aluminium plates. The main contribution of the present work is to show that mode separation through machine learning improves the effectiveness of predictive models. Numerical simulations have been performed to generate time series for creating the estimators, while experimental data have been used to validate them. We show that a full mode separation scheme decreased the error rate of the final model by 30% and 67% in defect size estimation and detection respectively

Application of one-bit time reversal technique to mechanical strain monitoring in plates

This paper presents the application of the one-bit\ud time reversal technique to a longitudinal strain sensor. The setup\ud consists of a pair of piezoelectric transducers bonded in the\ud extremities of a strip of aluminum plate. When the plate is\ud subjected to traction, time reversal focalization is performed, the\ud mismatch between the impulse response at initial and strained\ud levels causes loss in the focusing quality. The strain can be\ud evaluated by measuring either the time of flight shift or the\ud amplitude decrease in the focused signal. One-bit time reversal\ud can simplify the electronic device to perform the proposed\ud technique. In this work, the results using one-bit and normal time\ud reversal implementation were compared. Experiments were\ud performed using three different 2-2 piezocomposite transducers\ud pairs at 500, 1000 and 2250 kHz. The longitudinal strain was\ud applied up to 150 u- strain using a strain gauge as a reference.\ud The time reversal energy efficiency was used as a spectrum figure\ud of merit and obeys the sensitivity behavior. The one-bit time\ud reversal variation provided good focused signal for all\ud experiments and no significant loss in focus quality. Moreover,\ud every configuration showed a higher sensitivity than its normal\ud time reversal version, at least 10% depending on the transducer.\ud The one-bit technique reveals an important enhancement for the\ud method; it holds the natural advantage of being simpler and the\ud benefit of higher sensitivity.CNPq, FAPESP, and PETROBRAS/AN

Development of a mechanical strain sensor based on time reversal of ultrasonic guided waves

The development of a strain sensor based on the time reversal focusing technique is presented. The sensor is composed by a strip of aluminum plate with two ultrasonic piezocomposite transducers bonded at the ends of the plate. The time reversal technique acts as a dispersion compensator of the guided waves propagating in the plate, allowing time recompression of the waves. When the plate is subjected to a longitudinal traction, a time reversal focusing is performed between the transducers in order to detect the change in the focus due to strain. The strain can be evaluated by measuring the change of the amplitude and shift in the time of flight, and comparing them with a reference signal obtained at zero strain state. In order to improve the systems sensitivity, 2-2 piezocomposite transducers designed to operate between 0.2 to 3.0 MHz are used. Experiments are conducted by applying strain up to 150 μ-strain. The results show an increase in sensitivity when compared with the results of the conventional mono-element transducer greater than 200%. Results presented here can be used in the project of stress monitoring transducers and structural health systems