Ultrasonic inspection techniques and non-destructive tests are widely applied in evaluating products and equipment in the oil, petrochemical, steel, naval, and energy industries. These methods are well established and efficient for inspection procedures at room temperature. However, errors can be observed in the positioning and sizing of the flaws when such techniques are used during inspection procedures under high working temperatures. In such situations, the temperature gradients generate acoustic anisotropy and consequently distortion of the ultrasonic beams. Failure to consider such distortions in ultrasonic signals can result, in extreme situations, in mistaken decision making by inspectors and professionals responsible for guaranteeing product quality or the integrity of the evaluated equipment. In this scenario, this work presents a mathematical tool capable of mitigating positioning errors through the correction of focal laws. For the development of the tool, ray tracing concepts are used, as well as a model of heat propagation in solids and an experimentally defined linear approximation of dependence between sound speed and temperature. Using the focal law correction tool, the relative firing delays of the active elements are calculated considering the temperature gradients along the sonic path, and the results demonstrate a reduction of more than $68\%$ in the error of flaw positioning.

In Nondestructive Evaluation (NDE), ultrasound imaging is a useful tool for detecting flaws or measuring corrosion in metal pipes. Phased-array systems are becoming standard in NDE, as well as post-processing imaging techniques such as the Total Focusing Method. These techniques require knowledge of parameters such as distance between transducer elements, times of arrival and sound speed to produce sharp images. A deviation in sound speed, for instance, may compromise image accuracy. In this paper, we propose a sound speed estimator based on image quality metrics. The approach consists in generating several reconstructed images from the same acquisition signals, but using a set of candidate sound speeds. The speed value that yields the sharpest image is then chosen as the estimated sound speed. Estimates made on data obtained by simulation of a typical scenario presented relative combined uncertainties as low as 0.0166%. The results, obtained in both simulated and real scenarios, show good agreement with expected speeds. The proposed method can be considered a reference-free sound speed calibration method aimed at field applications.

Ultrasonic imaging is a common technique in nondestructive evaluation, as it presents advantages such as low cost and safety of operation. In many industries, the interior inspection of objects with complex geometry has become a necessity. This kind of inspection requires the transducer to be coupled to the object with the use of some technique, such as immersing the object in water. When doing so, the geometry of the object surface must be known a priori or estimated. Recent methods for surface estimation start with an image of the interface between water and the specimen. Then, the surface is estimated by processing the image using different strategies. In this article, the strategy to extract the surface profile is based on an analysis-based inverse problem, hence named surface estimation via analysis method (SEAM). The problem formulation aims to reduce the noise in the estimate and also, by including priors, reach more accurate estimates. By using a second-order total variation regularization, which favors piecewise linear functions, the proposed method can describe a great range of surface profiles. Experiments were performed to evaluate the proposed method on surface profile estimation and results show good agreement with references and lower errors than methods in the literature. In addition, the estimated profiles enhance the imaging of the interior of objects, allowing better visualization of internal defects.