A welding training system includes a welding surface, a computer configured to execute a welding training software, and a calibration device. The welding training system also includes a sensor communicatively coupled to the computer and configured to sense a position of the calibration device, an orientation of the calibration device, or some combination thereof. The sensor is also configured to provide calibration data to the welding training software to calibrate a location of the welding surface relative to the sensor. The calibration data includes the position of the calibration device, the orientation of the calibration device, or some combination thereof.

A resistance spot welding device that joins predetermined parts to be welded includes: a storage configured to store a time variation of an instantaneous amount of heat generated per unit volume and a cumulative amount of heat generated per unit volume in test welding that precedes actual welding; and an adaptive controller and an electrode force controller configured to, in the case where the time variation of the instantaneous amount of heat generated per unit volume in the actual welding differs from a time variation curve stored as the target value, respectively control the current or a voltage during current passage and the electrode force to the parts to be welded to compensate for the difference within a remaining welding time so that the cumulative amount of heat generated per unit volume in the actual welding matches the cumulative amount of heat generated per unit volume stored in the storage.

According to one embodiment, a control device controls a welding device performing resistance welding. When an inspection value satisfies a first condition, the control device modifies a setting value for the resistance welding and causes the welding device to perform the resistance welding. The inspection value is obtained by an inspection of a weld zone formed by the resistance welding. The control device does not cause the welding device to perform the resistance welding when the inspection value satisfies a second condition.

A method and apparatus for ultrasonic in-process monitoring and feedback of resistance spot weld quality uses at least one transducer located in the electrode assembly transmitting through a weld tip into an underway weld. Analysis of the spectrum of ultrasonic waves provides the operator with an indication of the size, thickness, location, dynamics of formation and quality of the spot weld. The method presents a fundamentally new physical approach to the characterization of the spot weld quality. Together with transmission mode it includes new modes of operation of ultrasonic probes such as a reflection mode and simultaneous use of transmission and reflection modes, and a new physical interpretation of the signal analysis results.

A method for monitoring welding of an electric resistance welded steel pipe of the present invention includes: an image acquisition step in which, when an electric resistance welded steel pipe is welded, a V-convergence portion including an edge detection area and a V-convergence point, and a welding portion including a position where a molten steel starts to be discharged from an inside of a wall thickness and a bead, are imaged to obtain a captured image; a determination information acquisition step in which the captured image is image-processed, and a molten length from the V-convergence point to the position where the molten steel starts to be discharged or a molten width of the welding portion or a combination thereof is acquired as a determination information; and a determining step in which it is determined whether a cold welding has occurred by comparing the determination information with a determination threshold value set in advance for each wall thickness of the electric resistance welded steel pipe.

A welding system according to one aspect includes: a welding device; a welding monitor device configured output monitoring information about welding by the welding device; a learning device configured to accept the input of welding result information associated with welding results obtained after welding and feature information extracted from the monitoring information at the time of welding when the welding results were obtained as teaching data, and create and output a welding result estimation model on the basis of the teaching data; and a welding result determination device configured to extract feature information from monitoring information output at the time of welding for which a welding result is to be determined, input the feature information as data for estimation into the welding result estimation model, and output a quality determination result for the welding, wherein the learning device is configured to detect the values of a preset plurality of feature elements from the monitoring information which includes time series data, calculate the contribution to the welding result, and determine the feature information on the basis of the calculated contribution.

Provided is a welding monitoring apparatus that monitors a welding state of a V-convergence region in which a strip-shaped metal sheet is converged in a V-shape, when the metal sheet is cylindrically formed while being conveyed, and both side edges of the metal sheet are heated and melted in a manner of being butted each other while being converged in the V-shape, such that an electric resistance welded steel pipe is manufactured. This welding monitoring apparatus includes an image capturing unit that captures images of a region including the V-convergence region in time series; and an image processing unit that extracts a welding point based on the images captured in time series and detects the presence or absence and a position of irregular arcing at the welding point or on an upstream side of the welding point.