Carbon Fiber Reinforced Polymers (CFRP) are extensively utilized in high-performance engineering, yet localized structural discontinuities can severely compromise their integrity. This paper aims to achieve high-sensitivity characterization of such anomalies using a proposed acoustic shearography technique based on continuous acoustic excitation. A comprehensive finite element model (FEM) was developed to clarify the mechanical-energy coupling between the acoustic fields and localized surface strain field modulations. By exploiting ultrasonic energy coupling, the localized features of discontinuities were identified through full-field, non-contact optical measurement of localized phase distortions. Key parameters, including shearing amount, excitation frequency, driving voltage, and geometric characteristics of blind flat-bottom holes (BFBH), were systematically investigated. The results demonstrate a high correlation between FEM simulations and experimental observations quantitatively elucidating how defect diameter and hole depth modulate surface strain distributions. The proposed hybrid acoustic optical approach achieves near-instantaneous full field imaging within a millisecond timeframe typically under 200 ms. Additionally, the methodology leverages localized acoustic resonance to significantly boost the signal-to-noise ratio (SNR) resulting in highly quantified phase map contrast.

Speckle shearography is a powerful non-contact optical method for full-field strain measurement, yet its performance can be constrained by fluctuations in laser intensity. In this study, a Michelson-interferometer-based shearography system integrated with a coaxial circular optical attenuator is developed to regulate optical density (OD) and quantitatively evaluate fringe quality. By varying light transmittance while maintaining constant source coherence and imaging parameters, we analyze how fringe contrast and measurement reliability evolve under different shearing amounts and loading intensities. The gray-level co-occurrence matrix (GLCM) is employed to extract four statistical texture features, i.e. contrast, correlation, homogeneity, and energy, from both experimental and simulated fringe patterns. Results reveal that a moderate OD value of around 0.15 optimizes fringe visibility and measurement accuracy by balancing transmittance and noise suppression. The combined use of GLCM-based descriptors and heatmap visualization establishes a robust, objective framework for fringe-pattern assessment, providing new guidance for intelligent optical quality control in shearographic systems.