Evident Canada, Inc.

Olympus Scientific Solutions Americas Corp.

Olympus America Inc.

Olympus Ndt Canada Inc.

Evident Scientific, Inc.

Nicolas Badeau

Benoit Lepage

Guillaume Painchaud-April

Jinchi Zhang

Jason Habermehl

Chi-Hang Kwan

Guy Prefontaine

Acoustic data, such as a full matrix capture (FMC) matrix, can be reconstructed by applying a previously trained decoder machine learning model to one or more encoded acoustic images, such as the TFM image(s), to generate reconstructed acoustic data. A processor can use the reconstructed acoustic data, such as an FMC matrix, to recreate new encoded acoustic images, such as TFM image(s), using different generation parameters (e.g., acoustic velocity, part thickness, acoustic mode, etc.).

Techniques to reconstruct data from acoustically constructed images using machine learning

Systems and methods are disclosed for conducting an ultrasonic-based inspection. The systems and methods perform operations comprising: receiving a plurality of scan plan parameters associated with generating an image of at least one flaw within a specimen based on acoustic echo data obtained using full matrix capture (FMC); applying the plurality of scan plan parameters to an acoustic model, the acoustic model configured to determine a two-way pressure response of a plurality of inspection modes based on specular reflection and diffraction phenomena; generating, by the acoustic model based on the plurality of scan plan parameters, an acoustic region of influence (AROI) comprising an acoustic amplitude sensitivity map for a first inspection mode amongst the plurality of inspection modes; and generating, for display, a first image comprising the AROI associated with the first inspection mode for capturing or inspecting the image of the at least one flaw.

Acoustic model acoustic region of influence generation

Using various techniques, a position of a probe assembly of a non-destructive inspection system, such as a phase array ultrasonic testing (PAUT) system, can be determined using the acoustic capability of the probe assembly and an inertial measurement unit (IMU) sensor, e.g., including a gyroscope and an accelerometer, without relying on a complex encoding mechanism. The IMU sensor can provide an estimate of a current location of the probe assembly, which can be confirmed by the probe assembly, using an acoustic signal. In this manner, the data acquired from the IMU sensor and the probe assembly can be used in a complementary manner.

Free-encoder positioning system using acoustic features and IMU

A material profile can be determined by assuming an elliptical or circular arc geometry and by using acoustic noise generated by diffuse internal reflection and/or specular reflection on the internal (ID) or external (OD) interface of the material under inspection, such as a pipe or curved plate. A non-destructive testing (NDT) technique can acquire acoustic data of the material using an ultrasonic signal. The acquired acoustic data can be filtered such that the acoustic noise generated by diffuse internal reflection and/or specular reflection is separated from any flaws in the material. Positions of the acoustic noise can be determined and then a regression technique can be applied to the positions, which can generate an equation of a circle, for example, such as to provide a radius and thickness of the pipe or curved plate.

Material profiling for improved sizing accuracy

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.

Techniques for adapting time delays of ultrasound inspection system during data acquisition

Disclosed is a system and method for ultrasonic measurement of the average diameter and surface profile of a tube. A calibration block is used to calibrate the average tube diameter, and a correction is applied to account for any temperature difference of the couplant between calibration and test measurements. By using a linear probe, or a single probe with a finely pitched helicoidal scan, errors in diameter measurement due to presence of surface pits may be compensated.

Ultrasonic measurement of surface profile and average diameter of a tube

Examples of the present subject matter provide techniques for calculating amplitude fidelity (AF) for a variety of grid resolutions using a single TFM image of a specified flaw. Thus, the grid resolution may be set so that it yields a desired AF using a calculation process without performing a blind iterative process. Moreover, examples of the present subject matter may measure AF in more than one axis, improving accuracy.

Automated TFM grid resolution setup tools

Disclosed is a system and method of determining the test surface profile and compensating the gain amplitude when using time reversal focal laws in ultrasound non-destructive testing. Computer simulations are used to compute the diffraction field at time of incidence of the transmitted parallel wave front on the test surface. Knowledge of the surface profile and the diffraction field allows determination of coverage at the test surface and improved accuracy of flaw sizing.

System and method for ultrasound inspection with time reversal

Disclosed is an ultrasonic inspection probe assembly comprising a water wedge and a flexible probe array assembly having a flexible acoustic module. The wedge is machined to match a test surface to be inspected and is configured to shape the acoustic module so that the active surface of the acoustic module is parallel to the test surface. Different wedges may be machined to match different test surfaces, but the same flexible probe array assembly may be used for all such surfaces.

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Nicolas Badeau