当前高压电容式电压互感器(capacitor voltage transformer,CVT)缺少有效的在线监测数据,辨识不足。利用在线监测多数据源存在线性相关的数据特性,提出了基于分析数据相关系数进行有效数据辨识的方法。针对目前高压CVT故障诊断普遍存在...当前高压电容式电压互感器(capacitor voltage transformer,CVT)缺少有效的在线监测数据,辨识不足。利用在线监测多数据源存在线性相关的数据特性,提出了基于分析数据相关系数进行有效数据辨识的方法。针对目前高压CVT故障诊断普遍存在信息单一、精度不高、局部放电在线监测装置故障信号检测受干扰因素影响较大、准确性差等问题,提出了基于多维信息融合的故障诊断方法。首先,利用因子分析对CVT的诊断指标进行数据层信息融合,提取各故障类型对应的公共因子方差贡献值,作为反映故障类型差异的特征值;然后,利用模糊理论进行特征层信息融合,将公共因子方差贡献值作为隶属函数的输入参数,识别CVT的故障类型,准确诊断高压CVT故障。案例验证了所提方法的有效性,为CVT故障诊断提供了理论参考和实践经验。展开更多
It is being widely studied how to extract knowledge from a decision table based on rough set theory. The novel problem is how to discretize a decision table having continuous attribute. In order to obtain more reasona...It is being widely studied how to extract knowledge from a decision table based on rough set theory. The novel problem is how to discretize a decision table having continuous attribute. In order to obtain more reasonable discretization results, a discretization algorithm is proposed, which arranges half-global discretization based on the correlational coefficient of each continuous attribute while considering the uniqueness of rough set theory. When choosing heuristic information, stability is combined with rough entropy. In terms of stability, the possibility of classifying objects belonging to certain sub-interval of a given attribute into neighbor sub-intervals is minimized. By doing this, rational discrete intervals can be determined. Rough entropy is employed to decide the optimal cut-points while guaranteeing the consistency of the decision table after discretization. Thought of this algorithm is elaborated through Iris data and then some experiments by comparing outcomes of four discritized datasets are also given, which are calculated by the proposed algorithm and four other typical algorithras for discritization respectively. After that, classification rules are deduced and summarized through rough set based classifiers. Results show that the proposed discretization algorithm is able to generate optimal classification accuracy while minimizing the number of discrete intervals. It displays superiority especially when dealing with a decision table having a large attribute number.展开更多
Environmental risk assessment of tailings reservoir assessment system is complex and has many index factors.In order to accurately judge surrounding environmental risks of tailings reservoirs and determinate the corre...Environmental risk assessment of tailings reservoir assessment system is complex and has many index factors.In order to accurately judge surrounding environmental risks of tailings reservoirs and determinate the corresponding prevention and control work,multi-hierarchical fuzzy judgment and nested dominance relation of rough set theory are implemented to evaluate them and find out the rules of this evaluation system with 14 representative cases.The methods of multi-hierarchical fuzzy evaluation can overall consider each influence factor of risk assessment system and their mutual impact,and the index weight based on the analytic hierarchy process is relatively reasonable.Rough set theory based on dominance relation reduces each index attribute from the top down,largely simplifies the complexity of the original evaluation system,and considers the preferential information in each index.Furthermore,grey correlation theory is applied to analysis of importance of each reducted condition attribute.The results demonstrate the feasibility of the proposed safety evaluation system and the application potential.展开更多
The correlation matrix, which is widely used in eigenvalue decomposition （EVD） or singular value decomposition （SVD）, usually can be denoted by R = E[yiy＇i]. A novel method for constructing the correlation matrix...The correlation matrix, which is widely used in eigenvalue decomposition （EVD） or singular value decomposition （SVD）, usually can be denoted by R = E[yiy＇i]. A novel method for constructing the correlation matrix R is proposed. The proposed algorithm can improve the resolving power of the signal eigenvalues and overcomes the shortcomings of the traditional subspace methods, which cannot be applied to low SNR. Then the proposed method is applied to the direct sequence spread spectrum （DSSS） signal＇s signature sequence estimation. The performance of the proposed algorithm is analyzed, and some illustrative simulation results are presented.展开更多
Time resolution of multipath delay profiles measured by using autocorrelation of pseudonoise (PN) code sequence is generally limited by the chip rate of the PN code sequence. In this paper, we propose a simple method ...Time resolution of multipath delay profiles measured by using autocorrelation of pseudonoise (PN) code sequence is generally limited by the chip rate of the PN code sequence. In this paper, we propose a simple method to improve the time resolution of delay profiles measured by the PN correlation method. Effectiveness of this method is demonstrated by indoor wireless propagation experiments.展开更多
文摘当前高压电容式电压互感器(capacitor voltage transformer,CVT)缺少有效的在线监测数据,辨识不足。利用在线监测多数据源存在线性相关的数据特性,提出了基于分析数据相关系数进行有效数据辨识的方法。针对目前高压CVT故障诊断普遍存在信息单一、精度不高、局部放电在线监测装置故障信号检测受干扰因素影响较大、准确性差等问题,提出了基于多维信息融合的故障诊断方法。首先,利用因子分析对CVT的诊断指标进行数据层信息融合,提取各故障类型对应的公共因子方差贡献值,作为反映故障类型差异的特征值;然后,利用模糊理论进行特征层信息融合,将公共因子方差贡献值作为隶属函数的输入参数,识别CVT的故障类型,准确诊断高压CVT故障。案例验证了所提方法的有效性,为CVT故障诊断提供了理论参考和实践经验。
文摘It is being widely studied how to extract knowledge from a decision table based on rough set theory. The novel problem is how to discretize a decision table having continuous attribute. In order to obtain more reasonable discretization results, a discretization algorithm is proposed, which arranges half-global discretization based on the correlational coefficient of each continuous attribute while considering the uniqueness of rough set theory. When choosing heuristic information, stability is combined with rough entropy. In terms of stability, the possibility of classifying objects belonging to certain sub-interval of a given attribute into neighbor sub-intervals is minimized. By doing this, rational discrete intervals can be determined. Rough entropy is employed to decide the optimal cut-points while guaranteeing the consistency of the decision table after discretization. Thought of this algorithm is elaborated through Iris data and then some experiments by comparing outcomes of four discritized datasets are also given, which are calculated by the proposed algorithm and four other typical algorithras for discritization respectively. After that, classification rules are deduced and summarized through rough set based classifiers. Results show that the proposed discretization algorithm is able to generate optimal classification accuracy while minimizing the number of discrete intervals. It displays superiority especially when dealing with a decision table having a large attribute number.
基金Project(51374242)supported by the National Natural Science Foundation of ChinaProject(200449)supported by National Outstanding Doctoral Dissertations Special Fund of ChinaProject(2012QNZT028)supported by the Free Exploration Fund of Central South University,China
文摘Environmental risk assessment of tailings reservoir assessment system is complex and has many index factors.In order to accurately judge surrounding environmental risks of tailings reservoirs and determinate the corresponding prevention and control work,multi-hierarchical fuzzy judgment and nested dominance relation of rough set theory are implemented to evaluate them and find out the rules of this evaluation system with 14 representative cases.The methods of multi-hierarchical fuzzy evaluation can overall consider each influence factor of risk assessment system and their mutual impact,and the index weight based on the analytic hierarchy process is relatively reasonable.Rough set theory based on dominance relation reduces each index attribute from the top down,largely simplifies the complexity of the original evaluation system,and considers the preferential information in each index.Furthermore,grey correlation theory is applied to analysis of importance of each reducted condition attribute.The results demonstrate the feasibility of the proposed safety evaluation system and the application potential.
文摘The correlation matrix, which is widely used in eigenvalue decomposition （EVD） or singular value decomposition （SVD）, usually can be denoted by R = E[yiy＇i]. A novel method for constructing the correlation matrix R is proposed. The proposed algorithm can improve the resolving power of the signal eigenvalues and overcomes the shortcomings of the traditional subspace methods, which cannot be applied to low SNR. Then the proposed method is applied to the direct sequence spread spectrum （DSSS） signal＇s signature sequence estimation. The performance of the proposed algorithm is analyzed, and some illustrative simulation results are presented.
文摘Time resolution of multipath delay profiles measured by using autocorrelation of pseudonoise (PN) code sequence is generally limited by the chip rate of the PN code sequence. In this paper, we propose a simple method to improve the time resolution of delay profiles measured by the PN correlation method. Effectiveness of this method is demonstrated by indoor wireless propagation experiments.
