Automated real-time characterization of resistance spot welds using ultrasound-based nondestructive evaluation requires a computational process and system to accurately and rapidly interpret the ultrasonic data in real time. Such a process can be automatically learned using artificial intelligence, from a dataset of exemplary ultrasonic data from nondestructive evaluation of resistance spot welds for which a corresponding ideal evaluation of each weld is provided. The process can then be implemented into a system to automatically interpret data from non-destructive evaluation in real-time. The ideal evaluation of each weld requires identification a large set of features that are observable in the ultrasonic signature and comprehensively characterize the corresponding weld process.

A weld coupon destructive test device includes a support base. A plunger connected to the support base and movable between a first position and a second position along a length of the support base. A handle to operate the plunger between the first position and the second position. A header on the support base, the header configured to press a weld coupon between the header and the plunger, the header having a first support end and a second support end, the header having a depression formed between the first support end and the second support end. The weld coupon rests between the first support end and the second support end of the header, and the weld coupon is pressed into the depression formed between the first support end and the second support end of the header.

A method for producing a three-dimensional component by means of a laser melting process, in which the component is produced by consecutively solidifying individual layers made of building material by melting the building material, wherein said building material can be solidified by the action of radiation, wherein the melting area produced by a punctiform and/or linear energy input is detected by a sensor device and sensor values are derived therefrom in order to evaluate the component quality. The sensor values detected in order to evaluate the component quality are stored together with the coordinate values that locate the sensor values in the component and are displayed by means of a visualization unit in two- and/or multi-dimensional representation with respect to the detection location of the sensor values in the component.

A method for checking a component to be produced in an additive manner, having the steps of mechanically exciting at least one additively constructed layer of the component during the additive production of the component, measuring a mechanical response signal of the component, and displaying a warning and/or interrupting the additive production of the component if the mechanical response signal lies outside of a specified tolerance range. A device for the additive production of a component, includes a device for mechanically exciting the at least one additively constructed layer of the component, a measuring unit for measuring the mechanical response signal of the component, and a control unit. The control unit is designed to display the warning and/or interrupt the additive production if the mechanical response signal lies outside of a specified tolerance range.

Methods are provided for joint performance validation and include preparing a coupon from a blank by bending the blank to have a pair of legs disposed at substantially ninety degrees relative to each other. Another coupon is prepared by forming an opening in a segment of another blank and bending the segment approximately ninety degrees. The segment is disposed adjacent an end of the second blank. A test sample is prepared by joining the coupons together at a joint with a leg attached to the segment approximately at a center of the leg. The test sample is subjected to a force test to generate data for the performance validation.

A method and a system for controlling a welding operation is provided by a welding machine controlled by an automatic motion generating mechanism. The method includes the steps of acquiring a set of welding data during the welding operation; computing at least a first part of the set of welding data and at least a second part of the set of welding data providing computed data, wherein the computed data indicate an abnormality; and transferring an abnormality output to a robot controller, which is controlling the welding machine and the automatic motion generating mechanism.

The present invention discloses a quantitative evaluation method for sensitivity of welding transverse cold cracks in a typical joint of a jacket, including following steps: S1, performing macroscopic analysis, metallographic analysis, fracture analysis and hardness analysis on cracks of a failed component to obtain main causes of cold crack failure; and S2, designing and processing a dedicated sample, and performing rigid restraint crack tests on the dedicated sample at different preheating temperatures to obtain a cracking/non-cracking critical restraint stress σ1cr of the sample. According to the method, a rigid restraint crack test is applied to evaluation of sensitivity of welding transverse cracks, so that external restraint conditions borne by a welding joint can be accurately simulated, a stress state of the welding joint in an actual working condition can be truly reflected, the overall evaluation precision is greatly improved, and a foundation is laid for accurately evaluating sensitivity of welding cold cracks in a tube joint. Furthermore, a welding technology (base material, welding material, welding process and restraint level) is designed to restrain cold cracks from cracking, and the method has important theoretical significance and engineering value.

Provided is image processing unit that causes computer to perform: a spatter candidate region detection step of performing, for each of input images obtained by capturing workpiece during arc welding, detection of a spatter candidate region based on a pixel value indicating brightness of a pixel included in the input images; a reflected light region identification step of identifying, in the spatter candidate region detected in the spatter candidate region detection step, a reflected light region in which reflected light of arc light is shown, based on color information of a reference pixel included in the spatter candidate region; and a spatter number identification step of identifying, as the number of spatters, the number of spatter candidate regions obtained by removing the reflected light region identified in the reflected light region identification step in the spatter candidate region detected in the spatter candidate region detection step.

A laser soldering system and a method for monitoring a laser soldering process by means of a monitoring device of the laser soldering system, wherein a solder ball is dispensed onto a solderable surface of a substrate by means of a solder ball feeding device of the laser soldering system, wherein the solder ball is at least partially melted by means of a laser device of the laser soldering system, wherein, during the laser soldering process, a light signal is formed which is detected by means of an optical detection unit of the monitoring device, wherein the light signal is dispersed into a spectrum of the light signal by means of a spectroscope device of the monitoring device, wherein the spectrum is analyzed by means of a processing device of the monitoring device, and it is identified on the basis of a composition of the spectrum whether or not a burning of the substrate has occurred during the laser soldering process.

According to one embodiment, a processing system teaches an operation to a robot. The robot includes a detector including detection elements arranged along first and second directions, and a manipulator to which the detector is mounted. The processing system performs position teaching processing. The position teaching processing includes causing the detector to perform a probe of a weld portion of a joined body. The probe includes a transmission of an ultrasonic wave and a detection of a reflected wave. The position teaching processing includes calculating a center position of the weld portion in a first plane based on first intensity data of an intensity of the reflected wave, setting a teaching point of the robot based on a first position of the detector, and moving the detector along the first plane to a second position, and setting the teaching point based on the second position.