基于模糊支持向量机的继电保护状态在线评价

继电保护状态评价工作一直以来都是状态检修的重点和难点。提出一种基于模糊支持向量机的继电保护状态评价方法。首先，获取智能变电站继电保护装置的历史数据，从中选择合适的状态评价因素，再对状态评价因素进行数据预处理，并根据状态巡视及故障记录计算装置在各巡视点的百分比剩余寿命，生成训练样本集。然后通过模糊支持向量机回归训练生成模型，利用在线巡视记录，对装置状态进行在线评估。并根据最差指标，判定装置的当前状态，作为最终的在线状态评价结果。仿真分析表明，方法通过引入样本权重，能够区分本装置样本和同型号装置样本的不同，使得算法能够兼顾装置的个性和家族性共性，并具备一定的抗噪能力。

Online condition evaluation of relay protection based on fuzzy support vector machine

Condition evaluation of relay protection has always been the focus and difficulty of condition based maintenance. This paper proposes a condition evaluation method for protection based on fuzzy support vector machine (FSVM). First, via acquiring historical data of relay protection devices in smart substations, condition evaluation factors are chosen appropriately which will be pretreated next, and training set is generated by calculating the remaining life in percentage according to the inspection and failure record. Then regression training of FSVM is conducted to generate a model for online condition evaluation by using online inspecting record, and the worst index will be used to represent the real-time state of the device. Simulations show that, by introducing the sample weights, the method can distinguish the difference between devices which makes the algorithm take both the device''s personality and family generality into account, and have certain anti-noise ability at the same time.