SYSTEM AND METHODS FOR LABELING WELD MONITORING TIME PERIODS USING MACHINE LEARNING TECHNIQUES

摘要

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.