Electrical Spark Short-Circuit Anomaly Event Detection Dataset

With the rapid development of industrial automation, the frequency of using electrical equipment continues to increase, yet the frequent occurrence of short-circuit events seriously affects the safety and reliability of the equipment. Existing monitoring systems mostly rely on traditional sensors, which cannot timely and accurately identify short-circuit anomaly events, leading to potential hazards not being eliminated in time. This dataset aims to address the issues of accuracy and real-time detection of short-circuit events, meeting the needs of industrial safety monitoring. The dataset contains short-circuit event videos from different devices, captured in high resolution to ensure video quality. Data collection is conducted with professional camera equipment, and the environment is set in an industrial site to ensure the authenticity and validity of the data. To ensure data quality, the labeling process adopts a multi-round review mechanism to ensure consistency and accuracy. Data is stored in MP4 format, organized by event type classification.