Multi-centric radius focusing is used to inspect a radiused surface of a radiused part having a varying radius without mechanically adjusting the array sensor. A plurality of focal laws are designed to electronically steer and focus ultrasound at respective focal points corresponding to centers of curvature of a simulated radiused surface having a varying radius. The mechanical probe that carries the array sensor is located to two physical places that are outside of the radiused area and have a spatial relationship that varies less than the radius of the radiused surface varies. As the probe is moved along the radiused part, the probe maintains the array sensor at a constant location relative to the radiused part. As the array sensor scans the radiused part, the array sensor is electronically adjusted to focus at the respective focal points in sequence.

A method and system for ultrasonic testing of adhesion within a sample, which provides ultrasonic bursts of different frequencies to the sample and maintains a predetermined phase difference between echoes returned from the sample and representative reference signals of the bursts supplied to the sample until a spectrum of the phase differences versus frequency is obtained and from which properties of the adhesion at an interface reflecting the echoes are derivable.

Techniques for compensating a TFM delay computation live (e.g., during acquisition) as a function of the measured thickness along the scan axis of a probe of an acoustic inspection system. At various scan positions, the acoustic inspection system can measure the thickness of the object under test. With the measured thickness, the acoustic inspection system can compute the delays used for the TFM computation to reflect the actual thickness at that particular scan position of the probe.

An elastic matrix determination method and a vibration analysis method for a laminated iron core, with which it is possible to optimally determine an elastic modulus of a laminated iron core. When a vibration analysis of a laminated iron core obtained by laminating steel sheets is performed by using a configuration expression indicating a relationship between stress and strain in a matrix display by using an elastic matrix, a shear modulus in two surfaces including a laminating direction of the laminated iron core included in the elastic matrix in the configuration expression is determined in consideration of slip between laminated steel sheets.

A system for inspecting flexible pipelines comprises a data analyzer, a data collector and an ultrasonic transducer. Further, the ultrasonic transducer is adapted to propagate shear wave into the annulus of the flexible pipeline. The data collector further comprises a data store and a communicator. Further, the system is capable of differentiating flooding and non-flooding condition of the annulus of the flexible pipeline which is subjected to high pressure. Using the system, an indicator of a flooded or non-flooded condition within the flexible pipeline may be calculated using transmitted and detected reflective waves or the lack of detected reflective waves.

A method of non-destructive evaluation of mechanical properties of a material using ultrasonic waves in a monostatic configuration is disclosed. The method comprises remotely scanning a sample of the material without directly contacting the sample, measuring an acoustic impedance of the scanned sample, and calculating mechanical properties of the material using the acoustic impedance.

Embodiments provide systems and methods for utilizing acoustic sensors to detect defects via online or in situ monitoring of additive manufacturing (AM) processes. Sensors may capture acoustic waves associated with AM manufacturing operations. The acoustic emissions in combination with other sensing data, such as cameras or thermometers, may be used to characterize the state of the AM process, such as to detect a defect has occurred or confirm a defect has not occurred. When defects are detected, the AM process may be stopped to prevent further processing of a defective part. When defects are predicted as likely to occur, operational parameters of the AM device or process may be adjusted to mitigate the occurrence of a defect. The techniques disclosed herein enable detection of defects that occur underneath the surface of the part being manufactured, as well as correct issues with the AM device or process before a defect occurs.

Disclosed herein is a method for depth-profiling of samples including a target region including a lateral structural feature. The method includes projecting an optical pump pulse on a semiconductor device comprising a target region, such as to produce an acoustic pulse which propagates within the target region of the semiconductor device, wherein a wavelength of the pump pulse is at least two times greater than a lateral extent of a lateral structural feature of the semiconductor device along at least one lateral direction, projecting an optical probe pulse on the semiconductor device, such that the probe pulse undergoes Brillouin scattering off the acoustic pulse within the target region, detecting a scattered component of the probe pulse to obtain a measured signal, and analyzing the measured signal to obtain a depth-dependence of at least one parameter characterizing the lateral structural feature.

This disclosure generally relates to the field of structural health monitoring, and, more particularly, to a method and system for evaluating residual life of components made of composite materials. Existing methods require performing computational methods such as Finite Element Analysis (FEA) on the results of Non-Destructive Testing (NDT) every time a component is inspected. This makes the process expensive and time-consuming. Thus, embodiments of present disclosure provide a method wherein NDT is performed using different sensing methods such as ultrasound, ultrasound pulse echo, thermography to determine type of defect, location of defect and depth of defect in a test component which are then fed into a pre-trained machine learning model to predict residual life of the component. Testing time is greatly reduced since the pre-trained machine learning model is trained offline using results of the computational methods.

Embodiments provide systems and methods for utilizing acoustic sensors to detect defects via online or in situ monitoring of additive manufacturing (AM) processes. Sensors may capture acoustic waves associated with AM manufacturing operations. The acoustic emissions in combination with other sensing data, such as cameras or thermometers, may be used to characterize the state of the AM process, such as to detect a defect has occurred or confirm a defect has not occurred. When defects are detected, the AM process may be stopped to prevent further processing of a defective part. When defects are predicted as likely to occur, operational parameters of the AM device or process may be adjusted to mitigate the occurrence of a defect. The techniques disclosed herein enable detection of defects that occur underneath the surface of the part being manufactured, as well as correct issues with the AM device or process before a defect occurs.