A CWT-based method to calculate transmission coefficients of different Lamb waves using individual LEU signals. A neural network was trained to accurately predict WPDs based on the transmission coefficients of selected Lamb waves and the LEU signal energy. The method is capable of inspecting WPDs quickly along welds in thin structures.

A method is disclosed provide a method of collecting a group of scan data files and organizing those files for batch data processing to produce a weld indications table for each scan data file in a prioritized manner. The invention also provides a procedure for controlling the pre-processing of each file by extracting meta-data held in an ultrasonic data file and from such data determine whether the testing data is valid for review. A series of rules may be used by a selection engine to control a batch list of files for data processing and for review after data processing so that time by a weld inspector may be optimized for each construction project.

A system is disclosed that increases the efficiency of a weld inspector by reducing the amount of weld data that needs to be examined for any non-destructive (NDT) phased array and time-of-flight, diffraction ultrasonic testing of welds. The system reads ultrasonic testing data from an NDT scan of a series of metal welds and creates a table of target weld indications ranked by a series of filters representative of predetermined exclusion and significance criteria. The invention acts as a weld analysis concentrator by focusing the attention of an inspector on potential weld flaws that merit their attention, thereby increasing the efficiency of the inspector. The process typically reduces 95% to 98% of the ultrasonic weld testing data that must be reviewed by the inspector, while retaining flaw indications necessary for an inspector's competent review in conformity with various code requirements and regulations.

The present invention relates to a semi-automatic scanner for ultrasonic inspection of a branch pipe weld that has a small size and is able to perform an inspection while moving in a state of being attached to a test object by a magnetic force, thereby being applied to fittings having various shapes, such as a branch pipe and an elbow. The semi-automatic scanner for ultrasonic inspection according to the present invention includes a probe configured to inspect a weld by irradiating ultrasonic waves onto a surface of a test object, a probe holder configured to couple the probe by applying an elastic force so as to be pressed against the surface of the test object, an installation bracket having a rod shape, to which the probe holder is coupled so as to be laterally movable, four wheel units installed on both front and rear side surfaces of the installation bracket so as to be vertically slidable, and four magnet parts, each of which is installed on one of the four wheel units and presses the one of the wheel units against the test object with a magnetic force.

A wedge for on-line inspection of a weld includes a wedge body defining a coolant channel and at least one couplant channel, and a coolant input port in fluid connection with a first end of the coolant channel. The wedge body has a surface for disposing a phased array ultrasonic transducer comprising an array of ultrasonic elements. The coolant channel is formed in proximity to the surface for disposing the phased array ultrasonic transducer such that coolant flowing through the coolant channel maintains the phased array ultrasonic transducer below a predetermined temperature without obstructing the array of ultrasonic elements.

A smart acoustic information recognition-based welded weld impact quality determination method and system, comprising: controlling a tip of an ultrasonic impact gun (1) to perform impact treatment on a welded weld with different treatment pressures, treatment speeds, treatment angles and impact frequencies, obtaining acoustic signals during the impact treatment, calculating feature values of the acoustic signals, and constructing an acoustic signal sample set including various stress conditions; marking the acoustic signal sample set according to impact treatment quality assessment results for the welded weld; establishing a multi-weight neural network model, and using the marked acoustic signal sample set to train the multi-weight neural network model; obtaining feature values of welded weld impact treatment acoustic signals to be determined, inputting the feature values into the trained multi-weight neural network model, and outputting determination results for welded weld impact treatment quality to be determined.

A buoyancy module for use with a water environment robotic system of the type having an underwater robotic vehicle having a winch has a buoyancy configuration which can be selectively altered. The system includes a module that is configured to be repeatedly, selectively buoyantly engaged and buoyantly disengaged with the underwater robotic vehicle. A tether is connected to the module and is extendable and retractable in response to operation of the winch. Extending and retracting the module can buoyantly engage or buoyantly disengage the buoyancy module with the underwater robotic vehicle according to the operation of a state controller. By engaging and disengaging the buoyancy module, the buoyancy of the underwater robot can be selectively altered. A method is also disclosed.

A two-part, selectively dockable robotic system having counterbalanced stabilization during performance of an operation on an underwater target structure is provided. The robotic system includes a first underwater robotic vehicle that is sized and shaped to at least partially surround the underwater target structure. A second underwater robotic vehicle is sized and shaped to at least partially surround the underwater target structure and selectively dock with the first underwater robotic vehicle. The first and second robotic vehicles include complimentary docking mechanisms that permit the vehicles to selectively couple to each other with the underwater target structure disposed at least partially therebetween. One robot includes a tool that can act upon the target structure and the other robot includes a stabilization module that can act upon the target structure in an opposite manner in order to counterbalance the force of the tool.

An ultrasonic flaw detection apparatus includes: a seam detection unit that captures a thermal image of a welded seam portion of an electric resistance welded pipe; an ultrasonic flaw detection sensor head that includes an ultrasonic probe that performs ultrasonic flaw detection on the welded seam portion; a seam position calculation unit that calculates a seam position and a bead cutting position of the electric resistance welded pipe; a bead cutting band detection unit that detects a bead cutting band of the electric resistance welded pipe; a bead cutting position calculation unit that calculates a bead cutting position of the electric resistance welded pipe; a tracking movement amount calculation unit that calculates a tracking movement amount of the ultrasonic flaw detection sensor head; and a sensor head driving unit that moves the ultrasonic flaw detection sensor head to track the welded seam portion according to the tracking movement amount.

The invention relates to non-destructive ultrasonic testing of flat-bottom rails, laid on track, and can be used for detection of defects in tips of the rail foot on aluminothermic welded joints, performed by the intermediate casting method.

During the ultrasonic testing of aluminothermic welded joints, at least two zones for ultrasonic testing were determined with selecting one of at least two zones on the weld bead (reinforcing bead) from the lateral surface of the tip of the rail foot. At least two specific zones are grinded on the weld collar (reinforcing collar) with creation of at least two flat areas, which are able to ensure acoustic contact. The ultrasonic transducer is placed on every flat area of the collar, which is connected to at least one ultrasonic flaw detector. Ultrasonic testing of weld is performed using at least one flaw detector Delta-method or echo-method.

As a result of the invention implementation, there is no any blind zone in the base of the rail welded joint. The described invention ensures higher accuracy in detection of welds defects within the tips of the rail foot area. 2 z.p. f-ly, 8 il.