【摘要】 架空绝缘导线在配电网中应用比例逐年提升，单相断线故障发生的几率呈增大趋势。本文首先建立配电网单相断线故障模型，分析断口首末端电压的变化情况与波形的变化规律，并选取合适的稳态特征组合作为输入特征向量。然后，提出一种改进的深度森林算法实现故障分类，所提方法通过对同构森林输出的类分布向量实施均值池化操作，实现特征维度线性缩减，并将初始特征向量与之前每一级森林输出的平均值进行拼接，确保深层语义关联的持续传递。最后，采用PSCAD仿真，通过多种算法的对比与消融实验，验证了所提方法的有效性和准确性。更多还原

【Abstract】 The application proportion of overhead insulated conductors in distribution networks has been increasingly growing year by year, leading to a rising probability of single-phase line break faults. This study first establishes a single-phase line break fault model for distribution networks, analyzing voltage variations and waveform change patterns at both terminals of the breakpoint. A suitable combination of steady-state characteristics is selected as the input feature vector. Subsequently, an improved deep forest algorithm is proposed for fault classification. The proposed method employs mean pooling operations on class distribution vectors output by homogeneous forests to achieve linear reduction of feature dimensions. It concatenates the initial feature vector with averaged outputs from previous forest levels, thereby ensuring the continuous propagation of deep semantic correlations. Finally, PSCAD simulations are conducted to validate the effectiveness and accuracy of the proposed method through comparative analyses with various algorithms and ablation experiments.更多还原