【作者】 吴立帅；

【导师】 葛玻；

【作者基本信息】 河南科技大学 ， 电力电子与电力传动， 2013， 硕士

【摘要】 本文以变压器油中溶解气体为载体，通过分析变压器故障产生机理，采用人工智能算法对变压器故障进行诊断研究。根据变压器内部故障机理及故障类型，建立分层诊断模型，根据油中溶解气体组分对诊断的重要度，采用基于遗传算法的粗糙集约简方法对数据样本进行约简，得到多个特征子集。提出一种约简集选择算法，对多个特征子集进行筛选，得到最优特征子集，减少对每个特征子集进行训练与测试的工作量。采用二叉树原理建立多级分层的变压器故障诊断模型，将复杂的变压器故障诊断问题分步细化，避免了区域不可分问题的存在。采用支持向量机对故障数据进行训练建立故障诊断模型，通过调整惯性权重对粒子群优化算法进行改进，不但加速了支持向量机的惩罚因子C和核参数的寻优过程，同时提高了诊断精度。利用所提出的算法对某发电公司的两起变压器事故进行故障诊断，诊断结果与工程实际相符。对变压器进行在线监测是电网智能化的必然趋势，对变压器进行状态检修，首先要对其进行状态监测，状态监测分为离线监测与在线监测。通过变压器色谱智能监测系统的研制，对系统的油气分离单元、气体检测单元、微机控制及诊断单元的工作原理及结构进行研究，将所提出的算法通过系统软件的开放接口接入监控系统，并在某电厂两台主变压器监测系统上运行，结果表明采用本文算法的诊断结果与常规检测结果一致，且系统具有测试周期短、性能稳定等特点。更多还原

【Abstract】 This dissertation taking the dissolved gas in transformer’s oil as thecarrier,through analysing the transformer’s fault mechanism,using artificial intelligencealgorithm to diagnose and research transformer’s fault. According to the transformer’sinternal fault mechanism and fault types, establish layered diagnosis model.Accordingto the importance of the various oil dissolved gas for diagnosis, reduct the sample databased on genetic algorithm for reduction of knowledge method,get more featuresubset.This dissertation puts forward a reduction set selection algorithm, the multiplefeature subset screening,get the optimal feature subset,and reduce the workload of therate of each feature subset for training and testing.Use the binary tree principle toestablish multistage stratified transformer fault diagnosis model,make the complextransformer fault diagnosis problem detailed step by step,avoid the problem of regionalimpartibility.By adjusting the inertia weight to improve the particle swarmoptimization(PSO) algorithm, not only accelerate optimization process of thesupport vector machine (SVM), spenalty factor and nuclear parameter,but alsoimprove the diagnosis accuracy.By using the algorithm to diagnose two transformer’saccident fault of one power generation company’s, diagnostic results shows that thisalgorithm applied to engineering practice better.To overhaul the transformer,the first to carry on the condition monitoring.Thecondition monitoring is divided into off-line monitoring and on-line monitoring,tomonitor the transformer online is the inevitable trend of intelligentized grid.Throughparticipating in the chromatogram intelligent monitoring system of transformer’sdesign,research the system of oil and gas separation unit,gas detection unit,themicrocomputer control and diagnosis unit ’s structure and working principle,and put itinto operation on the two transformer,the operation of the system status andconventional test results show that the system has the short test cycle,stableperformance, etc.更多还原