Advanced device for the welding training based on simulation with Augmented reality and with remote updates that allows the simulation of: all the industrial welding types—s electrode stick (SMAW), MIG/MAG (GMAW, FCAW) and TIG (GTAW)—; all the materials; all the joint types and, also all the welding positions (1Fa 4F, 1G a 6G, 6GR, etc.). It offers an accurate simulation of a real welding equipment thanks to the use of the Augmented Reality technology, which allows the interaction between different elements in several layers. All this is implemented by a monitoring and student evaluating system that allows the teacher to control remotely what is happening in the classroom in real time and without the necessity of being physically present in the training.

An example weld training system includes: an orientation device; a mobile device; and a mount configured to attach the mobile device to a welding accessory, wherein the mobile device comprises: one or more sensors including at least a camera; a processor; and a machine readable storage device storing machine readable instructions which, when executed by the processor, cause the processor to: recognize identifiers on the orientation device based on images captured via the camera; determine at least one of position information or orientation information for a welding torch with respect to the orientation device based on the recognized identifiers; and display, via a display of the mobile device, a welding operation based on the at least the position information or the orientation information.

An example welding system includes: a welding power supply configured to convert input power to welding power; a wire feeder configured to feed welding wire to a welding torch; and control circuitry configured to: in response to an initiation of a welding process, control the wire feeder to feed the welding wire at a first rate while controlling the welding power supply to output the welding power to initiate a welding arc; in response to initiation of the welding arc, control the wire feeder to increase a feed rate of the wire feeder from the first rate to a second rate; and in response to determining that a temperature profile of a heated portion of the welding wire has stabilized, control the wire feeder to change the feed rate of the wire feeder from the second rate to a target wire feed speed.

Methods and apparatus to synergically control a welding-type output during a welding-type operation are disclosed. An example welding-type power supply includes a power conversion circuit configured to convert input power to welding-type power and to output the welding-type power to a welding-type torch; a communication circuit configured to receive a control signal from a remote control device during a welding-type operation; and a control circuit configured to synergically control a voltage of the welding-type power and a wire feed speed based on the control signal.

A robot control apparatus for a more precise seam tracking operation, includes: a storage unit in which teaching data is stored; an accepting unit that accepts a sensing result of a laser sensor, from a robot including a working tool and the laser sensor attached to the working tool and configured to detect a shape of a working target before an operation of the working tool; and a control unit that moves the working tool based on the teaching data, corrects the movement of the working tool based on the sensing result, and adjusts an angle about a tool axis such that an operation point indicated by the sensing result is at a center of a field of view of the laser sensor. Accordingly, an operation line can be detected near the center of the field of view of the laser sensor, and thus more precise detection is possible.

A system and method of enhanced automated welding of a first workpiece and a second workpiece are provided. The method comprises providing a system for intelligent robot-based welding of the first workpiece and the second workpiece. The method further comprises determining a geometrical location of the first workpiece and the second workpiece to be welded at a welding sequence based a predetermined process variable. The method further comprises adjusting the predetermined process variable based on the geometrical location of the first and second workpieces to define an actual process variable. The method further comprises welding a first portion of the first and second workpieces with the actual process variable to define a first welded portion. The method further comprises determining a weld quality of the first welded portion.

In preparing a built-up object by depositing beads, in a step of dividing into the bead model, a trapezoidal bead model a cross section of which is a trapezoidal shape is applied to a position where the bead is formed in a portion not adjacent to an existing bead, and a parallelogram bead model a cross section of which is a parallelogram is applied to a position where the bead is formed adjacent to a bead that is already formed, in the parallelogram bead model opposite sides in the deposition direction of the bead being parallel to each other, and opposite sides in the bead arrangement direction being parallel to a side of another bead mode that is adjacent.

Systems and methods for learning management systems with shared weld training results are described. In some examples, weld training results may be shared with a learning management system and/or associated with a particular learning activity of the learning management system. In some examples, the weld training results (and/or a networked location where the weld training results are accessible) may be encoded in a machine readable graphic (e.g., a one dimensional, two dimensional, and/or matrix barcode). In some examples, the machine readable graphic may be read and/or decoded by a user device to obtain the weld training results. In some examples, a particular learning activity may also be encoded in the machine readable graphic.

Systems and methods for learning management systems with shared weld training results are described. In some examples, weld training results may be shared with a learning management system and/or associated with a particular learning activity of the learning management system. In some examples, the weld training results (and/or a networked location where the weld training results are accessible) may be encoded in a machine readable graphic (e.g., a one dimensional, two dimensional, and/or matrix barcode). In some examples, the machine readable graphic may be read and/or decoded by a user device to obtain the weld training results. In some examples, a particular learning activity may also be encoded in the machine readable graphic.

Systems are disclosed relating to a mobile device mounted to a welding helmet such that a wearer of the welding helmet can see a display of the mobile device when wearing the welding helmet. In some examples, the mobile device is mounted such that a camera of the mobile device is unobscured and positioned at approximately eye level, facing the same way the wearer's eyes are facing. In some examples, the simulated training environment may be presented to the user via the display screen of the mobile device, using images captured by the camera of the mobile device, when the mobile device is so mounted to the welding helmet.