Automated tilt compensation in acoustic microscopy

Scanning acoustic microscopy (SAM) is a potent and nondestructive technique capable of producing three-dimensional topographic and tomographic images of specimens. This is achieved by measuring the differences in time of flight (ToF) of acoustic signals emitted from various regions of the sample. The measurement accuracy of SAM strongly depends on the ToF measurement, which is affected by tilt in either the scanning stage or the sample stage. Hence, compensating for the ToF shift resulting from sample tilt is imperative for obtaining precise topographic and tomographic profiles of the samples in a SAM. In the present work, we propose an automated tilt compensation in ToF of acoustic signal based on proposed curve fitting method. Unlike the conventional method, the proposed approach does not demand manually choosing three separate coordinate points from SAM's time domain data. The effectiveness of the proposed curve fitting method is demonstrated by compensating time shifts in ToF data of a coin due to the presence of tilt. The method is implemented for the correction of different amounts of tilt in the coin corresponding to angles 6.67°, 12.65° and 15.95°. It is observed that the present method can perform time offset correction in the time domain data of SAM with an accuracy of 45 arcsec. The experimental results confirm the effectiveness of the suggested tilt compensation technique in SAM, indicating its potential for future applications.

Image denoising in acoustic microscopy using block-matching and 4D filter

Scanning acoustic microscopy (SAM) is a label-free imaging technique used in biomedical imaging, non-destructive testing, and material research to visualize surface and sub-surface structures. In ultrasonic imaging, noises in images can reduce contrast, edge and texture details, and resolution, negatively impacting post-processing algorithms. To reduce the noises in the scanned image, we have employed a 4D block-matching (BM4D) filter that can be used to denoise acoustic volumetric signals. BM4D filter utilizes the transform domain filtering technique with hard thresholding and Wiener filtering stages. The proposed algorithm produces the most suitable denoised output compared to other conventional filtering methods (Gaussian filter, median filter, and Wiener filter) when applied to noisy images. The output from the BM4D-filtered images was compared to the noise level with different conventional filters. Filtered images were qualitatively analyzed using metrics such as structural similarity index matrix (SSIM) and peak signal-to-noise ratio (PSNR). The combined qualitative and quantitative analysis demonstrates that the BM4D technique is the most suitable method for denoising acoustic imaging from the SAM. The proposed block matching filter opens a new avenue in the field of acoustic or photoacoustic image denoising, particularly in scenarios with poor signal-to-noise ratios.

High-Frequency Acoustic Imaging Using Adhesive-Free Polymer Transducer

The piezoelectric polymer PVDF and its copolymers have a long history as transducer materials for medical and biological applications. An efficient use of these polymers can potentially both lower the production cost and offer an environment-friendly alternative for medical transducers which today is dominated by piezoelectric ceramics containing lead. The main goal of the current work has been to compare the image quality of a low-cost in-house transducers made from the copolymer P(VDF-TrFE) to a commercial PVDF transducer. Several test objects were explored with the transducers used in a scanning acoustic microscope, including a human articular cartilage sample, a coin surface, and an etched metal film with fine line structures. To evaluate the image quality, C- and B-scan images were obtained from the recorded time series, and compared in terms of resolution, SNR, point-spread function, and depth imaging capability. The investigation is believed to provide useful information about both the strengths and limitations of low-cost polymer transducers.

Nonlocal Damage Mechanics for Quantification of Health for Piezoelectric Sensor

In this paper, a novel method to quantify the incubation of damage on piezoelectric crystal is presented. An intrinsic length scale parameter obtained from nonlocal field theory is used as a novel measure for quantification of damage precursor. Features such as amplitude decay, attenuation, frequency shifts and higher harmonics of guided waves are commonly-used damage features. Quantification of the precursors to damage by considering the mentioned features in a single framework is a difficult proposition. Therefore, a nonlocal field theory is formulated and a nonlocal damage index is proposed. The underlying idea of the paper is that inception of the damage at the micro scale manifests the evolution of damage at the macro scale. In this paper, we proposed a nonlocal field theory, which can efficiently quantify the inception of damage on piezoelectric crystals. The strength of the method is demonstrated by employing the surface acoustic waves (SAWs) and longitudinal bulk waves in Lithium Niobate (LiNbO3) single crystal. A control damage was introduced and its manifestation was expressed using the intrinsic dominant length scale. The SAWs were excited and detected using interdigital transducers (IDT) for healthy and damage state. The acoustic imaging of microscale damage in piezoelectric crystal was conducted using scanning acoustic microscopy (SAM). The intrinsic damage state was then quantified by overlaying changes in time of flight (TOF) and frequency shift on the angular dispersion relationship.

Numerical and Experimental Evaluation of High-Frequency Unfocused Polymer Transducer Arrays

High-frequency unfocused polymer array transducers are developed using an adhesive-free layer-by-layer assembly method. The current paper focuses on experimental and numerical methods for measuring the acoustic performance of these types of array transducers. Two different types of numerical approaches were used to simulate the transducer performance, including a finite element method (FEM) study of the transducer response done in COMSOL 5.2a Multiphysics, and modeling of the excited ultrasonic pressure fields using the open source software k-Wave 1.2.1. The experimental characterization also involves two methods (narrow and broadband pulses), which are measurements of the acoustic reflections picked up by the transducer elements. Later on, measurements were undertaken of the ultrasonic pressure fields in a water-scanning tank using a hydrophone system. Ultrasonic pressure field measurements were visualized at various distances from the transducer surface and compared with the numerical findings.

Material State Awareness for Composites Part II: Precursor Damage Analysis and Quantification of Degraded Material Properties Using Quantitative Ultrasonic Image Correlation (QUIC)

Material state awareness of composites using conventional Nondestructive Evaluation (NDE) method is limited by finding the size and the locations of the cracks and the delamination in a composite structure. To aid the progressive failure models using the slow growth criteria, the awareness of the precursor damage state and quantification of the degraded material properties is necessary, which is challenging using the current NDE methods. To quantify the material state, a new offline NDE method is reported herein. The new method named Quantitative Ultrasonic Image Correlation (QUIC) is devised, where the concept of microcontinuum mechanics is hybrid with the experimentally measured Ultrasonic wave parameters. This unique combination resulted in a parameter called Nonlocal Damage Entropy for the precursor awareness. High frequency (more than 25 MHz) scanning acoustic microscopy is employed for the proposed QUIC. Eight woven carbon-fiber-reinforced-plastic composite specimens were tested under fatigue up to 70% of their remaining useful life. During the first 30% of the life, the proposed nonlocal damage entropy is plotted to demonstrate the degradation of the material properties via awareness of the precursor damage state. Visual proofs for the precursor damage states are provided with the digital images obtained from the micro-optical microscopy, the scanning acoustic microscopy and the scanning electron microscopy.