Power transformer insulation systems are subjected to many stresses during normal operation due to lightning and switching.If the spectrum of incoming surge voltage matches the winding one,the corresponding resonance ...Power transformer insulation systems are subjected to many stresses during normal operation due to lightning and switching.If the spectrum of incoming surge voltage matches the winding one,the corresponding resonance will be excited.Therefore external transients occurring in power systems might trigger internal overvoltages with large maximum value in transformer windings.Overvoltages having such characteristic have been the root cause of many power transformer failures.The paper presents an approach to the identification of sensitive zones in the transformer windings based on the measurements of overvoltages inside windings and frequency dependences of admittance of the power transformer.The frequency characteristic of the transformer winding may determine those regions in the frequency spectrum.The presented approach might be used both for design optimization and diagnostics of distribution and power transformers.展开更多
Ant colony optimization(ACO)is a random search algorithm based on probability calculation.However,the uninformed search strategy has a slow convergence speed.The Bayesian algorithm uses the historical information of t...Ant colony optimization(ACO)is a random search algorithm based on probability calculation.However,the uninformed search strategy has a slow convergence speed.The Bayesian algorithm uses the historical information of the searched point to determine the next search point during the search process,reducing the uncertainty in the random search process.Due to the ability of the Bayesian algorithm to reduce uncertainty,a Bayesian ACO algorithm is proposed in this paper to increase the convergence speed of the conventional ACO algorithm for image edge detection.In addition,this paper has the following two innovations on the basis of the classical algorithm,one of which is to add random perturbations after completing the pheromone update.The second is the use of adaptive pheromone heuristics.Experimental results illustrate that the proposed Bayesian ACO algorithm has faster convergence and higher precision and recall than the traditional ant colony algorithm,due to the improvement of the pheromone utilization rate.Moreover,Bayesian ACO algorithm outperforms the other comparative methods in edge detection task.展开更多
目的 探讨三维酰胺质子转移加权(three-dimensions amide proton transfer weighted,3D-APTw)成像在评估肝细胞癌(hepatocellular carcinoma,HCC)病理分级中的价值。材料与方法 前瞻性招募2020年10月至2023年4月经手术病理证实为HCC并进...目的 探讨三维酰胺质子转移加权(three-dimensions amide proton transfer weighted,3D-APTw)成像在评估肝细胞癌(hepatocellular carcinoma,HCC)病理分级中的价值。材料与方法 前瞻性招募2020年10月至2023年4月经手术病理证实为HCC并进行Edmondson-Steiner四级(Ⅰ~Ⅳ)分级的患者共43例。将Ⅰ级和Ⅱ级HCC定为低级别HCC,Ⅲ级和Ⅳ级病变定为高级别HCC。采用飞利浦3.0 T MRI设备在术前对患者进行扫描,分别采集T1WI、T2WI、弥散加权成像、酰胺质子转移加权(amide proton transfer weighted,APTw)及多期增强图像。由两位经验丰富的放射科医生独立测量HCC及正常肝实质的APTw值。采用Mann-Whitney U非参数检验分析组间差异。采用受试者工作特征(receiver operating characteristic,ROC)曲线分析APTw值的诊断效能,计算曲线下面积(area under the curve,AUC)、阈值及其敏感度和特异度。采用Spearman相关分析,评估APTw与HCC的组织学分级之间的相关性。结果 低级别HCC的APTw值(2.15%±0.13%)低于高级别HCC(2.63%±0.13%),差异具有统计学意义(P=0.03)。APTw值鉴别高级别及低级别HCC的AUC为0.69(95%CI:0.53~0.82),最佳阈值为1.85%时,敏感度和特异度分别为90.00%和42.31%。Spearman相关性分析结果显示APTw值与HCC病理分级呈正相关,相关系数r=0.43(P=0.003)。结论 APTw值可用于鉴别高级别及低级别HCC,3D-APTw成像在术前预测HCC病理分级中有一定的价值。展开更多
文摘Power transformer insulation systems are subjected to many stresses during normal operation due to lightning and switching.If the spectrum of incoming surge voltage matches the winding one,the corresponding resonance will be excited.Therefore external transients occurring in power systems might trigger internal overvoltages with large maximum value in transformer windings.Overvoltages having such characteristic have been the root cause of many power transformer failures.The paper presents an approach to the identification of sensitive zones in the transformer windings based on the measurements of overvoltages inside windings and frequency dependences of admittance of the power transformer.The frequency characteristic of the transformer winding may determine those regions in the frequency spectrum.The presented approach might be used both for design optimization and diagnostics of distribution and power transformers.
基金supported by the National Natural Science Foundation of China(62276055).
文摘Ant colony optimization(ACO)is a random search algorithm based on probability calculation.However,the uninformed search strategy has a slow convergence speed.The Bayesian algorithm uses the historical information of the searched point to determine the next search point during the search process,reducing the uncertainty in the random search process.Due to the ability of the Bayesian algorithm to reduce uncertainty,a Bayesian ACO algorithm is proposed in this paper to increase the convergence speed of the conventional ACO algorithm for image edge detection.In addition,this paper has the following two innovations on the basis of the classical algorithm,one of which is to add random perturbations after completing the pheromone update.The second is the use of adaptive pheromone heuristics.Experimental results illustrate that the proposed Bayesian ACO algorithm has faster convergence and higher precision and recall than the traditional ant colony algorithm,due to the improvement of the pheromone utilization rate.Moreover,Bayesian ACO algorithm outperforms the other comparative methods in edge detection task.
文摘目的 探讨三维酰胺质子转移加权(three-dimensions amide proton transfer weighted,3D-APTw)成像在评估肝细胞癌(hepatocellular carcinoma,HCC)病理分级中的价值。材料与方法 前瞻性招募2020年10月至2023年4月经手术病理证实为HCC并进行Edmondson-Steiner四级(Ⅰ~Ⅳ)分级的患者共43例。将Ⅰ级和Ⅱ级HCC定为低级别HCC,Ⅲ级和Ⅳ级病变定为高级别HCC。采用飞利浦3.0 T MRI设备在术前对患者进行扫描,分别采集T1WI、T2WI、弥散加权成像、酰胺质子转移加权(amide proton transfer weighted,APTw)及多期增强图像。由两位经验丰富的放射科医生独立测量HCC及正常肝实质的APTw值。采用Mann-Whitney U非参数检验分析组间差异。采用受试者工作特征(receiver operating characteristic,ROC)曲线分析APTw值的诊断效能,计算曲线下面积(area under the curve,AUC)、阈值及其敏感度和特异度。采用Spearman相关分析,评估APTw与HCC的组织学分级之间的相关性。结果 低级别HCC的APTw值(2.15%±0.13%)低于高级别HCC(2.63%±0.13%),差异具有统计学意义(P=0.03)。APTw值鉴别高级别及低级别HCC的AUC为0.69(95%CI:0.53~0.82),最佳阈值为1.85%时,敏感度和特异度分别为90.00%和42.31%。Spearman相关性分析结果显示APTw值与HCC病理分级呈正相关,相关系数r=0.43(P=0.003)。结论 APTw值可用于鉴别高级别及低级别HCC,3D-APTw成像在术前预测HCC病理分级中有一定的价值。
