Embodiments described herein utilize Non-Destructive Inspection (NDI) scan data obtained during a process performed on a surface of a structure to update a location of an NDI scanner on the surface. A subsurface feature within the structure is detected based on the NDI scan data, which are correlated with pre-defined position data for the subsurface feature. A measured location of the NDI scanner on the surface is corrected based on the pre-defined position data for the subsurface feature.

A crawler maps a structure by moving at least longitudinally or circumferentially on the structure. A probe scans the structure to generate scan data corresponding to the structure. A distance measuring unit measures a distance of the probe from a landmark extending circumferentially around the structure. An orientation sensor determines an orientation of the crawler on the structure. A processor generates a map of the scan data of the structure indexed by the distance and orientation.

A crawler maps a structure by moving at least longitudinally or circumferentially on the structure. A probe scans the structure to generate scan data corresponding to the structure. A distance measuring unit measures a distance of the probe from a landmark extending circumferentially around the structure. An orientation sensor determines an orientation of the crawler on the structure. A processor generates a map of the scan data of the structure indexed by the distance and orientation.

Systems and methods are disclosed for conducting an ultrasonic-based inspection. The systems and methods perform operations comprising: receiving, by one or more processors, data indicative of a detected tag on a specimen, the tag associated with one or more ultrasonic-based inspections that were previously performed on the specimen; retrieving, by the one or more processors, based on the detected tag, configuration data for a non-destructive testing (NDT) instrument, the configuration data being associated with the one or more ultrasonic-based inspections that were previously performed on the specimen; generating, by the one or more processors, new configuration data for the NDT instrument to perform a new inspection of the specimen at least in part using the received configuration data; and performing the new inspection of the specimen based on spatially positioning the NDT instrument relative to a position of the tag on the specimen.

In a method and apparatus for automated inspection, an image is acquired of an object under inspection and a difference image is generated showing the difference between the acquired image and a reference image of a defect-free object of the same type. Characteristics of the difference image, or detected isolated regions of the difference image, are passed to an automated defect classifier to classify defects in the object under inspection. The characteristics of the difference image may be pixels of the difference image or features determined therefrom. The features may be extracted using a neural network, for example. The automated defect classifier is trained using difference images and may be further trained, in operation, based on operator classifications and using simulated images of defects identified by an operator.

In a method and apparatus for automated inspection, an image is acquired of an object under inspection and a difference image is generated showing the difference between the acquired image and a reference image of a defect-free object of the same type. Characteristics of the difference image, or detected isolated regions of the difference image, are passed to an automated defect classifier to classify defects in the object under inspection. The characteristics of the difference image may be pixels of the difference image or features determined therefrom. The features may be extracted using a neural network, for example. The automated defect classifier is trained using difference images and may be further trained, in operation, based on operator classifications and using simulated images of defects identified by an operator.

The present disclosure provides a system and method for real-time visualization of a material during ultrasonic non-destructive testing. The system includes a graphical user interface (GUI) capable of showing a three-dimensional (3-D) image of a composite laminate constructed of a series of two-dimensional (2-D) cross sections. The GUI is capable of displaying the 3-D image as each additional 2-D cross section is scanned by an ultrasonic testing apparatus in real time or near real time, including probable defect regions that contain a flaw such as a hole, crack, wrinkle, or foreign object within the composite. Furthermore, in one embodiment, the system includes an artificial intelligence capable of highlighting defect areas within the 3-D image in real time or near real time and providing data regarding each defect area, such as the depth, size, and/or type of each defect.

The present disclosure provides a system and method for real-time visualization of a material during ultrasonic non-destructive testing. The system includes a graphical user interface (GUI) capable of showing a three-dimensional (3-D) image of a composite laminate constructed of a series of two-dimensional (2-D) cross sections. The GUI is capable of displaying the 3-D image as each additional 2-D cross section is scanned by an ultrasonic testing apparatus in real time or near real time, including probable defect regions that contain a flaw such as a hole, crack, wrinkle, or foreign object within the composite. Furthermore, in one embodiment, the system includes an artificial intelligence capable of highlighting defect areas within the 3-D image in real time or near real time and providing data regarding each defect area, such as the depth, size, and/or type of each defect.

The present disclosure provides a system and method for real-time visualization of a material during ultrasonic non-destructive testing. The system includes a graphical user interface (GUI) capable of showing a three-dimensional (3-D) image of a composite laminate constructed of a series of two-dimensional (2-D) cross sections. The GUI is capable of displaying the 3-D image as each additional 2-D cross section is scanned by an ultrasonic testing apparatus in real time or near real time, including probable defect regions that contain a flaw such as a hole, crack, wrinkle, or foreign object within the composite. Furthermore, in one embodiment, the system includes an artificial intelligence capable of highlighting defect areas within the 3-D image in real time or near real time and providing data regarding each defect area, such as the depth, size, and/or type of each defect.

The present disclosure provides a system and method for real-time visualization of a material during ultrasonic non-destructive testing. The system includes a graphical user interface (GUI) capable of showing a three-dimensional (3-D) image of a composite laminate constructed of a series of two-dimensional (2-D) cross sections. The GUI is capable of displaying the 3-D image as each additional 2-D cross section is scanned by an ultrasonic testing apparatus in real time or near real time, including probable defect regions that contain a flaw such as a hole, crack, wrinkle, or foreign object within the composite. Furthermore, in one embodiment, the system includes an artificial intelligence capable of highlighting defect areas within the 3-D image in real time or near real time and providing data regarding each defect area, such as the depth, size, and/or type of each defect.