Algorithm 1: The Training Process of DamperYOLO.

Input: Original damper image set $I=\left\{I_1,\cdot \cdot \cdot ,I_N\right\}$ that each image contains dampers.

Output: DamperYOLO after training.

1: Initialize DamperYOLO with random weights;

2: repeat

3: for i in 1~epochs do 4:   for j in 1~N do 5:    Image augment for $I_j$;

6:   Extract feature map using ResNet101; 7:   Output detection results using YOLO;

8:   Calculate the penalty value via Formula (2), (5) and (6);

9:   Minimize Formula (1) to update the parameters of DamperYOLO; 10:  end for

11: end for

12: until DamperYOLO completes convergence

13: return