| Title |
Research on Image Processing Systems to Identify Causes such as Mechanical Equipment Failures or Defects |
| Authors |
Min-Sik Kim ; Eun-Hyeok Choi |
| DOI |
https://doi.org/10.5207/JIEIE.2026.40.3.182 |
| Keywords |
Black box; OPC UA; RTSP; Smart factory |
| Abstract |
Identifying the causes of failures or defects in mechanical equipment during operation is often difficult when using conventional continuous video recording systems. Such systems generate excessive data and are not effectively linked with control devices, which limits their usefulness for fault analysis. This paper presents an event-driven video monitoring and recording platform that integrates RTSP-based video streams with OPC UA-based control signals to support efficient fault and defect analysis in mechanical equipment. Unlike conventional continuous recording approaches, the system records only video segments around control events, reducing unnecessary data storage. Through experimental validation, synchronization between control events and video data was maintained within tens of milliseconds, while the recorded video size was approximately 1.41MB per event. These results show that the proposed approach can effectively support real-time monitoring and fault analysis in smart manufacturing environments. |