电缆的绝缘状态通常可以分为良好、不好、差和故障等几种，以电缆的日常检修数据、试验数据和在线监测数据为基础，对电缆的状态进行判断是一个非常有意义的课题。采用决策树分类技术来对电缆的绝缘状态进行分类，分别对各种类型数据形成子树，然后通过子树合成技术形成最终的决策树，从而对电缆的绝缘状态进行判断。通过一个实际电缆的各种数据，采用SPSS软件进行实际应用，最终的仿真结果说明决策树技术是一种非常有效的电缆绝缘状态分类技术。

The insulation state of cable can be split into well, bad, worse and fault. The estimation for cable state is a significant topic based on overhaul data, test data and monitor data of the cables. The decision tree is employed to classify the insulation state. The subtrees can be formed by all kinds of data, then the final decision tree is composed of the subtrees, by which the insulation state can be estimated. The application by SPSS with practical data of the cable is carried on. The simulation result for t(he insulation state estimation of cable shows the effectiveness of the approach.

孙秋野（1971－），男，辽宁沈阳市人，东北大学讲师，研究方向为配电系统分析，故障诊断