Abstract:
Systems and methods for distributed weld monitoring using jobs and job sessions are described. In some examples, a distributed monitoring system comprises a central monitoring station in communication with a user device and a local monitoring station. A user may use the user device to enter weld monitoring data that is subsequently received by the central monitoring station and stored in a central data repository. The central data repository may associate the weld monitoring data with welding data received from a welding device, as well as with a job session that is, in turn, associated with a job.
Abstract:
Systems and methods for distributed weld monitoring using jobs and job sessions are described. In some examples, a distributed monitoring system comprises a central monitoring station in communication with a user device and a local monitoring station. A user may use the user device to enter weld monitoring data that is subsequently received by the central monitoring station and stored in a central data repository. The central data repository may associate the weld monitoring data with welding data received from a welding device, as well as with a job session that is, in turn, associated with a job.
Abstract:
Systems and methods for distributed weld monitoring using jobs and job sessions are described. In some examples, a distributed monitoring system comprises a central monitoring station in communication with a user device and a local monitoring station. A user may use the user device to enter weld monitoring data that is subsequently received by the central monitoring station and stored in a central data repository. The central data repository may associate the weld monitoring data with welding data received from a welding device, as well as with a job session that is, in turn, associated with a job.
Abstract:
Systems and methods for distributed weld monitoring using jobs and job sessions are described. In some examples, a distributed monitoring system comprises a central monitoring station in communication with a user device and a local monitoring station. A user may use the user device to enter weld monitoring data that is subsequently received by the central monitoring station and stored in a central data repository. The central data repository may associate the weld monitoring data with welding data received from a welding device, as well as with a job session that is, in turn, associated with a job.
Abstract:
Systems and methods for labeling non-welding time periods using machine learning techniques are described. In some examples, a weld monitoring system may collect various data from sensors and/or welding equipment in a welding area over a time period. The data may evaluated to divide the time period into welding time periods and non-welding time periods. The weld monitoring system may use one or more machine learning models and/or techniques in combination with the collected data to determine what non-welding activities took place during the non-welding time periods. In some examples, the machine learning models may be continuously trained, updated, and/or improved using feedback from operators and/or other individuals, data from ongoing welding and/or non-welding activities, as well as data from other weld monitoring systems and/or machine learning models.
Abstract:
Systems and methods for using drones in dispersed welding applications are disclosed. In some examples, drones may be used in large and/or dispersed welding environments to quickly navigate the large distances and/or reach areas that might be more difficult for a person to reach. In some examples, the drones may use one or more attached devices to locate, identify, and/or collect information from welding equipment, welding workpieces, and/or welds within a (e.g., large and/or dispersed) welding environment.
Abstract:
Systems and methods for welding are described. The welding system can include, for example, a welding power source, a welding torch, and a computer. The computer and the welding torch can be operatively coupled to the power source. A first weld is performed and its signature is saved by the computer. It is considered a high quality weld and is selected as a weld reference. A second weld is performed and its signature is saved by the computer. The computer then computes a single weld confidence result for the second weld based on a comparison between the signature data of the second weld and the signature data of the reference weld. A weld fault condition is triggered based on the single weld confidence result which causes the welding system to stop or to modify the welding operation, and/or which causes the welding system to send out communications relating to the triggering of the weld fault condition.
Abstract:
Systems and methods for welding are described. The welding system can include, for example, a welding power source, a welding torch, and a computer. The computer and the welding torch can be operatively coupled to the power source. A first weld is performed and its signature is saved by the computer. It is considered a high quality weld and is selected as a weld reference. A second weld is performed and its signature is saved by the computer. The computer then computes a single weld confidence result for the second weld based on a comparison between the signature data of the second weld and the signature data of the reference weld. A weld fault condition is triggered based on the single weld confidence result which causes the welding system to stop or to modify the welding operation, and/or which causes the welding system to send out communications relating to the triggering of the weld fault condition.
Abstract:
Systems and methods for welding are described. The welding system can include, for example, a power source, a computer, and a welding torch. The computer and the welding torch can be operatively coupled to the power source. The power source controls a wire feed and one of a current or a voltage to the welding torch. When the welding torch is performing pulsed welding, the computer is configured to receive a weld signature. The computer is configured to synthesize features from the weld signature and to analyze the features for each pulse of the weld signature to determine whether particular limits have been exceeded or met. If particular limits are exceed or met, a weld fault condition is triggered which causes the welding system to stop or to modify the pulsed welding operation, and/or which causes the welding system to send out communications relating to the triggering of the weld fault condition.