多信息融合的变压器实时状态评估

Real-time Status Evaluation of Transformer with Multi-information Fusion Technology

随着变压器状态监测技术的发展,获得的变压器状态信息种类也越来越多。为此,提出了多信息融合的变压器健康状态评估方法。该方法通过融合粗糙集、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。

More the status monitoring technology of transformers applying,more status information of transformers it can get.It directly influences the safe operation of the whole power system,a new method of transformer state evaluation based on multi-information fusion is proposed.Combining the neural network,rough set 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.