基于模糊神经网络的大型电力变压器风险评估方法研究

A Risk Assessment Method of Power Transformer Based on Fuzzy Analytic Hierarchy Process and Neural Network

为实时、客观地衡量在役变压器故障所带来的风险,从评估的准确性和快捷性的角度,提出了基于模糊层次分析法和人工神经网络相结合的变压器风险评估方法.通过分析影响变压器风险水平的风险因素,构建了变压器风险评估的层次分析模型,在模型中建立风险评估指标体系,并结合模糊一致判断矩阵,定量计算出变压器风险分析中各风险因素的权重;利用人工神经网络的自适应能力与非线性映射能力,将权重大的风险因素作为神经网络的输入,实现变压器风险的智能化量化评估.仿真结果表明,该方法提高了风险评估的速度和结果的准确度,能为变压器的风险管理与维修决策提供可行的决策依据.

For the real-time and objective measurement of the risk caused by on-line power transformer, a power transformer risk assessment method was put forward based on Fuzzy Analytic Hierarchy Process （FAHP） and Artificial Neural Network （ANN） from the perspective of the accuracy and quickness of risk assessment. An analytic hierarchy process model for transformer risk assessment was built by analyzing risk factors affecting transformer risk level. In this model, a risk index system was established and index weights were quantified. The weight relation of each risk factor in transformer risk calculation was ana- lyzed by applying fuzzy consistency judgment matrix. It took major risk factors as the input of the neutral network by making use of adaptive ability and nonlinear mapping ability of the ANN, thus realizing the in- telligent quantitative assessment of transformer risks. Simulation results have shown that this method in- creases the speed and result accuracy of risk assessment and can provide feasible decision basis for trans- former risk rn^n~,~, o^A ~：