Disclosed herein are a probe for a nondestructive testing device using a crossed gradient induced current and a method of manufacturing an induction coil for a nondestructive testing device. The probe for a nondestructive testing device using a crossed gradient induced current includes an induction coil formed to have a predetermined width and to generate first and second induced currents in a direction crossing each other when a current is applied from a power supply, and a magnetic sensor part installed adjacent to the induction coil so as to measure the first and second induced currents induced from the induction coil.

A material defect detection device that detects a material defect in a predetermined region of metallic equipment using a magnetic field distribution in the predetermined region measured by a magnetic sensor array including a plurality of magnetic sensors, the material defect detection device including: a processor that calculates a density distribution of magnetic dipoles in the predetermined region based on the magnetic field distribution and calculates a depth distribution of material defect in the predetermined region based on the density distribution of the magnetic dipoles.

A method for estimating a pipe property for a plurality of nested tubulars. The method may comprise disposing an electromagnetic (EM) logging tool in a wellbore. The electromagnetic logging tool may comprise a transmitter disposed on the electromagnetic logging tool and a receiver disposed on the electromagnetic logging tool. The method may further comprise transmitting an electromagnetic field from the transmitter into one or more tubulars, measuring the eddy current in the pipe string with the receiver on at least one channel to obtain a plurality of measurements, forming an EM log from the plurality of measurements, extracting data and distinct features from the EM log, forming a relationship between the EM log data and a database, wherein the database is formed from one or more high-resolution measurements, and producing a mapping function between the EM log and the database.

Systems and methods include a computer-implemented method for inspection. Sensors are installed on locations susceptible to high temperature hydrogen attack (HTHA) on equipment used in hydrocarbon facilities. Attachment uses adaptable hybrid pads. Surface data captured using permanent sensors includes surface temperatures, per hydrogen (pH) measurements, and methane measurements for methane escaping from external surfaces of the equipment. Stress cracks in the equipment base metal are detected. An HTHA susceptibility analysis of the equipment is performed based on the presence of the cracks and by analyzing surface data and mapping potential HTHA cracks and locations of early signs of methane formation, including monitoring heat-affected zones (HAZ) and fusion lines of welds. Locations of the detected stress cracks caused by HTHA in metals are determined. An inspection result and assessment are generated, including a final analysis of assessment reports indicating a likelihood of cracks propagation and fissuring inside the equipment base metal.

Examples of the present subject matter provide techniques for gathering inspection data (e.g., c-scan) from a plurality of probes, such as ECA probes. Each probe may generate inspection data obtained from different in-plane probe orientations on a surface, such as providing indications from disturbances or flaws located in different in-plane directions relative to a probe sensitivity axis. The inspection data may then be combined while indications at different orientations may be preserved and then merged to generate a composite. Pattern recognition using templates defining flaws or abnormalities may then be performed to determine the type of indication, e.g., detrimental flaw or non-detrimental abnormality.

A method for identifying indications in an object via non-destructive testing using inspection equipment comprising a probe is described. The method includes: recording test data corresponding to a signal measurement acquired by the probe; processing the test data using a first analysis machine learning algorithm trained to output a list of detected landmarks; processing the list of detected landmarks to identify regions in the object based on the landmarks; processing the test data and the identified regions using a second analysis machine learning algorithm to output a list of detected indications; processing the list of indications to automatically classify each indication according to one of a plurality of predefined indication types; and outputting the classified indications in a report specifying positions of the classified indications in the object. A corresponding system and non-transitory computer-readable medium are also described.

A system and method for determining fiber orientation within a layered composite using an eddy current probe is discussed. The eddy current probe includes an array of coils that are excited such that an effective pole of the end effector of the probe moves in a ring pattern. The eddy current probe is moved across the surface of a part such that a two-dimensional scan of the part is generated, analogous to a C-scan in ultrasonic testing. The eddy current probe is able to be used to determine the fiber orientation of a layered composite material by scanning at a single point on the material. The eddy current data is able to be fused with data from an ultrasonic transducer to produce a comprehensive view of the part.

Disclose is a system and method for real-time measurement and feedback of metrology and metallurgical data during additive manufacturing (AM) part fabrication. This solution promises to provide higher performance, lower cost AM parts. A sensor is placed either in the rake/roller or following the rake/roller so that it has no impact on the process efficiency and can be used to provide real-time feedback and an archived digital map of the entire part volume. The solution provides non-contact sensing of AM layer's electrical conductivity in a high-temperature environment, metallurgical property verification, porosity imaging, local defect detection and sizing, local material temperature monitoring, and grain anisotropy imaging. Part geometry, the AM powder, and the laser/material interface are monitored in real-time. Dual mode sensing using magnetoquasistatic and optical sensors enhance results. Real-time nonlinear control of the AM fabrication process is performed based on the sensor data.

Disclose is a system and method for real-time measurement and feedback of metrology and metallurgical data during additive manufacturing (AM) part fabrication. This solution promises to provide higher performance, lower cost AM parts. A sensor is placed either in the rake/roller or following the rake/roller so that it has no impact on the process efficiency and can be used to provide real-time feedback and an archived digital map of the entire part volume. The solution provides non-contact sensing of AM layer's electrical conductivity in a high-temperature environment, metallurgical property verification, porosity imaging, local defect detection and sizing, local material temperature monitoring, and grain anisotropy imaging. Part geometry, the AM powder, and the laser/material interface are monitored in real-time. Dual mode sensing using magnetoquasistatic and optical sensors enhance results. Real-time nonlinear control of the AM fabrication process is performed based on the sensor data.

A method for identifying indications in an object via non-destructive testing using inspection equipment comprising a probe is described. The method includes: recording test data corresponding to a signal measurement acquired by the probe; processing the test data using a first analysis machine learning algorithm trained to output a list of detected landmarks; processing the list of detected landmarks to identify regions in the object based on the landmarks; processing the test data and the identified regions using a second analysis machine learning algorithm to output a list of detected indications; processing the list of indications to automatically classify each indication according to one of a plurality of predefined indication types; and outputting the classified indications in a report specifying positions of the classified indications in the object. A corresponding system and non-transitory computer-readable medium are also described.