아크용점파형의 구간통계처리법에 의한 결함 검출 알고리즘 연구

Abstract

The effect of defects in FCAW using CO2 gas is not only the deterioration of the quality of the welded part, but also the overall Q-cost increase due to maintenance and welding. Destructive inspection and non-destructive inspection are two methods for detecting defects, but these methods are costly and time consuming. There is also a method of confirming defects using a welding waveform as a more advanced technique. However, when checking the unprocessed welding waveform, it is difficult to distinguish between normal and abnormal waveforms according to the metal transfer mode. This is because the waveforms are significantly different when a short circuit occurs and when it does not occur. Therefore, an algorithm that can detect defects from waveforms regardless of the presence or absence of a short is required. The purpose is to develop an algorithm that can detect defects using welding waveforms. In this study, we provide a method to detect defects by using the interval statistical processing method according to the time series of welding data displayed in the welding monitoring system.