<p>As a core protective device in low-voltage distribution systems, the micro circuit breaker (MCB) is susceptible to degradation phenomena such as internal component wear under frequent switching operations. Severe degradation can even lead to switching failure, directly impacting system reliability. Addressing issues of low detection accuracy and excessive reliance on simulation in MCB degradation analysis, this paper proposes a degradation analysis method based on non-contact dynamic measurement of characteristic parameters. Firstly, building upon the YOLOv11 framework, a deformable large kernel attention mechanism (D-LKA) is introduced to enhance feature extraction for small and irregular components. Combined with the unified intersection over union (UIoU) loss function to improve bounding box regression accuracy, the improved YOLOv11-DAU model achieves a 1.96% increase in mAP@0.5s and an F1-score of 92.2% in component detection tasks, demonstrating significantly superior performance compared to the baseline model. Secondly, a dynamic measurement method for characteristic parameters, including the closing angle, overtravel angle, and average opening speed, during the switching process is proposed. Finally, by analyzing the relationship between contact wear, breaking spring fracture, and the characteristic parameters, dynamic degradation analysis is completed by setting thresholds based on the observed parameter variation patterns. This approach provides effective data support for the reliability analysis of MCB.</p>