Intelligent Detection of Complex Gaps in Live Working Based on Video Analysis

To avoid safety accidents, live work operators must maintain a correct posture to ensure their own complex gap within the limits of request body extension size. The traditional measurement of complex gaps of live working operators in training mainly depends on the subjective empirical judgment of the expert on the spot, which features strong subjectivity and safety risks. As for existing problems, this paper proposes a novel intelligent detection algorithm based on video analysis technology that uses multi-Gaussian background modeling, blob detection, and the foreground merged method. Taking a 500 KV tower as an example, the experimental results indicate that the proposed method can measure the real-time complex gap of an operator in a timely and accurate manner; moreover, the proposed method can standardize operations and improve the safety level of live working effectively.