分层式信息融合在变压器状态评估中的应用

变压器的健康状态直接影响着整个电力系统的安全运行,为此,提出了分层式信息融合的变压器健康状态评估方法.该方法通过融合神经网络和D-S证据理论,解决了因变压器信息参数繁多而造成的网络结构复杂和庞大等一系列问题,也为D-S证据理论中的基本可信度分配提供了有效的依据.实例表明,该方法具有较高的诊断准确性和可靠性.

Application of Hierarchical Information Fusion to Transformer State Evaluation

As the health status of transformers directly influences the safe operation of the whole power system,a new method of transformer state evaluation based on hierarchical information fusion is proposed.Combining the neural network and D-S evidence theory,the method has solved a series of problems that too many information parameters of transformers result in the complex and huge network structure,which also has provided the effective basis for basic credence assignment of D-S evidence theory.The examples have shown that the method is of higher diagnosis accuracy and reliability.