Bearings are crucial components in rotating machines,which have direct effects on industrial productivity and safety.To fast and accurately identify the operating condition of bearings,a novel method based on multi⁃sc...Bearings are crucial components in rotating machines,which have direct effects on industrial productivity and safety.To fast and accurately identify the operating condition of bearings,a novel method based on multi⁃scale permutation entropy(MPE)and morphology similarity distance(MSD)is proposed in this paper.Firstly,the MPE values of the original signals were calculated to characterize the complexity in different scales and they constructed feature vectors after normalization.Then,the MSD was employed to measure the distance among test samples from different fault types and the reference samples,and achieved classification with the minimum MSD.Finally,the proposed method was verified with two experiments concerning artificially seeded damage bearings and run⁃to⁃failure bearings,respectively.Different categories were considered for the two experiments and high classification accuracies were obtained.The experimental results indicate that the proposed method is effective and feasible in bearing fault diagnosis.展开更多
Event region detection is the important application for wireless sensor networks（WSNs）, where the existing faulty sensors would lead to drastic deterioration of network quality of service.Considering single-moment n...Event region detection is the important application for wireless sensor networks（WSNs）, where the existing faulty sensors would lead to drastic deterioration of network quality of service.Considering single-moment nodes fault-tolerance, a novel distributed fault-tolerant detection algorithm named distributed fault-tolerance based on weighted distance（DFWD） is proposed, which exploits the spatial correlation among sensor nodes and their redundant information.In sensor networks, neighborhood sensor nodes will be endowed with different relative weights respectively according to the distances between them and the central node.Having syncretized the weighted information of dual-neighborhood nodes appropriately, it is reasonable to decide the ultimate status of the central sensor node.Simultaneously, readings of faulty sensors would be corrected during this process.Simulation results demonstrate that the DFWD has a higher fault detection accuracy compared with other algorithms, and when the sensor fault probability is 10%, the DFWD can still correct more than 91% faulty sensor nodes, which significantly improves the performance of the whole sensor network.展开更多
Fracture-fissure systems found at mid-ocean ridges are dominating conduits for the circulation of metallogenic fluid.Ascertaining the distribution area of active faults on both sides of mid-ocean ridges will provide a...Fracture-fissure systems found at mid-ocean ridges are dominating conduits for the circulation of metallogenic fluid.Ascertaining the distribution area of active faults on both sides of mid-ocean ridges will provide a useful tool in the search for potential hydrothermal vents,thus guiding the exploration of modern seafloor sulfides.Considering the MidAtlantic Ridge 20°N–24°N(NMAR)and North Chile Rise(NCR)as examples,fault elements such as Fault Spacing(?S)and Fault Heave(?X)can be identified and quantitatively measured.The methods used include Fourier filtering of the multi-beam bathymetry data,in combination with measurements of the topographic slope,curvature,and slope aspect patterns.According to the Sequential Faulting Model of mid-ocean ridges,the maximal migration distance of an active fault on either side of mid-ocean ridges—that is,the distribution range of active faults—can be measured.Results show that the maximal migration distance of active faults at the NMAR is 0.76–1.01 km(the distance is larger at the center than at the ends of this segment),and at the NCR,the distribution range of active faults is 0.38–1.6 km.The migration distance of active faults on the two study areas is positively related to the axial variation of magma supply.In the NCR study area,where there is an abundant magma input,the number of faults within a certain distance is mainly affected by the variation of lithospheric thickness.Here a large range of faulting clearly corresponds to a high proportion of magmatism to seafloor spreading near mid-ocean ridges(M)value,and in the study area of the NMAR,there is insufficient magmatism,and the number of faults may be controlled by both lithospheric thickness and magma supply,leading to a less obvious positive correlation between the distribution range of active faults and M.展开更多
This paper presents an ANN （artificial neural networks）-based technique for improving the performance of distance relays against open-circuit faults in transmission networks. The technique utilizes the small capacit...This paper presents an ANN （artificial neural networks）-based technique for improving the performance of distance relays against open-circuit faults in transmission networks. The technique utilizes the small capacitive current measured in the open-phase plus the currents in the two healthy phases in calculating the open-circuit fault distance. The results obtained show that a distance relay with the proposed scheme will not only be able to detect the open-conductor condition in HVTL （high voltage transmission line） but also to locate the place of this fault regardless the value of the pre-fault current loading. There is no need for especial communication schemes since the existing media could work properly for the needs of the proposed technique.展开更多
The new techniques were presented for preventing undesirable distance relay maloperation during voltage collapse and power swings in transmission grids. Initially, the work focused on the development of a fast detecti...The new techniques were presented for preventing undesirable distance relay maloperation during voltage collapse and power swings in transmission grids. Initially, the work focused on the development of a fast detection of voltage collapse and a three-phase fault at transmission lines by using under impedance fault detector (UIFD) and support vector machine (SVM). Likewise, an intelligent approach was developed to discriminate a fault, stable swing and unstable swing, for correct distance relay operation by using the S-transform and the probabilistic neural network (PNN). To illustrate the effectiveness of the proposed techniques, simulations were carried out on the IEEE 39-bus test system using the PSS/E and MATLAB software.展开更多
针对传统局部线性嵌入算法在挖掘局部流形结构时未充分考虑样本邻居分布信息,且在降维过程中默认样本具有相同的重要性导致提取鉴别特征不明显的问题,提出基于共享近邻的加权局部线性嵌入(weighted local linear embedding based on sha...针对传统局部线性嵌入算法在挖掘局部流形结构时未充分考虑样本邻居分布信息,且在降维过程中默认样本具有相同的重要性导致提取鉴别特征不明显的问题,提出基于共享近邻的加权局部线性嵌入(weighted local linear embedding based on shared neighbors,SN-WLLE)算法,并用于滚动轴承故障诊断.该算法首先使用余弦距离划分样本邻域;其次计算样本邻域对相似度用以评估样本共享近邻信息,并结合样本的6种邻居分布修正局部结构挖掘,提高多共享近邻的k近邻重构准确性;接着从多流形的角度评估样本点与近邻点间的稀疏分布一致性,以获得样本的重要性指标,并在低维空间保持该信息,进而提取准确的鉴别特征;最后结合KNN分类器构建出完备的轴承故障诊断模型.采用凯斯西储大学轴承数据集和实验室测试平台轴承数据集,从可视化评估、定量聚类评估、故障识别精度评估及鲁棒性评估等方面进行分析.结果表明:SN-WLLE算法的F值保持在108以上水准,平均故障识别精度最低可达0.9734,不仅具有较好的类内紧致性与类间可分性,还对近邻参数k具有低敏感性.展开更多
基金Sponsored by the National Natural Science Foundation of China(Grant No.51505100)
文摘Bearings are crucial components in rotating machines,which have direct effects on industrial productivity and safety.To fast and accurately identify the operating condition of bearings,a novel method based on multi⁃scale permutation entropy(MPE)and morphology similarity distance(MSD)is proposed in this paper.Firstly,the MPE values of the original signals were calculated to characterize the complexity in different scales and they constructed feature vectors after normalization.Then,the MSD was employed to measure the distance among test samples from different fault types and the reference samples,and achieved classification with the minimum MSD.Finally,the proposed method was verified with two experiments concerning artificially seeded damage bearings and run⁃to⁃failure bearings,respectively.Different categories were considered for the two experiments and high classification accuracies were obtained.The experimental results indicate that the proposed method is effective and feasible in bearing fault diagnosis.
基金supported by the National Science Foundation for Outstanding Young Scientists (60425310)the Science Foundation for Post-doctoral Scientists of Central South University (2008)
文摘Event region detection is the important application for wireless sensor networks（WSNs）, where the existing faulty sensors would lead to drastic deterioration of network quality of service.Considering single-moment nodes fault-tolerance, a novel distributed fault-tolerant detection algorithm named distributed fault-tolerance based on weighted distance（DFWD） is proposed, which exploits the spatial correlation among sensor nodes and their redundant information.In sensor networks, neighborhood sensor nodes will be endowed with different relative weights respectively according to the distances between them and the central node.Having syncretized the weighted information of dual-neighborhood nodes appropriately, it is reasonable to decide the ultimate status of the central sensor node.Simultaneously, readings of faulty sensors would be corrected during this process.Simulation results demonstrate that the DFWD has a higher fault detection accuracy compared with other algorithms, and when the sensor fault probability is 10%, the DFWD can still correct more than 91% faulty sensor nodes, which significantly improves the performance of the whole sensor network.
基金supported by the grant of China Ocean Mineral Resources R&D Association(DY135-S2-1-01)
文摘Fracture-fissure systems found at mid-ocean ridges are dominating conduits for the circulation of metallogenic fluid.Ascertaining the distribution area of active faults on both sides of mid-ocean ridges will provide a useful tool in the search for potential hydrothermal vents,thus guiding the exploration of modern seafloor sulfides.Considering the MidAtlantic Ridge 20°N–24°N(NMAR)and North Chile Rise(NCR)as examples,fault elements such as Fault Spacing(?S)and Fault Heave(?X)can be identified and quantitatively measured.The methods used include Fourier filtering of the multi-beam bathymetry data,in combination with measurements of the topographic slope,curvature,and slope aspect patterns.According to the Sequential Faulting Model of mid-ocean ridges,the maximal migration distance of an active fault on either side of mid-ocean ridges—that is,the distribution range of active faults—can be measured.Results show that the maximal migration distance of active faults at the NMAR is 0.76–1.01 km(the distance is larger at the center than at the ends of this segment),and at the NCR,the distribution range of active faults is 0.38–1.6 km.The migration distance of active faults on the two study areas is positively related to the axial variation of magma supply.In the NCR study area,where there is an abundant magma input,the number of faults within a certain distance is mainly affected by the variation of lithospheric thickness.Here a large range of faulting clearly corresponds to a high proportion of magmatism to seafloor spreading near mid-ocean ridges(M)value,and in the study area of the NMAR,there is insufficient magmatism,and the number of faults may be controlled by both lithospheric thickness and magma supply,leading to a less obvious positive correlation between the distribution range of active faults and M.
文摘This paper presents an ANN （artificial neural networks）-based technique for improving the performance of distance relays against open-circuit faults in transmission networks. The technique utilizes the small capacitive current measured in the open-phase plus the currents in the two healthy phases in calculating the open-circuit fault distance. The results obtained show that a distance relay with the proposed scheme will not only be able to detect the open-conductor condition in HVTL （high voltage transmission line） but also to locate the place of this fault regardless the value of the pre-fault current loading. There is no need for especial communication schemes since the existing media could work properly for the needs of the proposed technique.
文摘The new techniques were presented for preventing undesirable distance relay maloperation during voltage collapse and power swings in transmission grids. Initially, the work focused on the development of a fast detection of voltage collapse and a three-phase fault at transmission lines by using under impedance fault detector (UIFD) and support vector machine (SVM). Likewise, an intelligent approach was developed to discriminate a fault, stable swing and unstable swing, for correct distance relay operation by using the S-transform and the probabilistic neural network (PNN). To illustrate the effectiveness of the proposed techniques, simulations were carried out on the IEEE 39-bus test system using the PSS/E and MATLAB software.
文摘针对传统局部线性嵌入算法在挖掘局部流形结构时未充分考虑样本邻居分布信息,且在降维过程中默认样本具有相同的重要性导致提取鉴别特征不明显的问题,提出基于共享近邻的加权局部线性嵌入(weighted local linear embedding based on shared neighbors,SN-WLLE)算法,并用于滚动轴承故障诊断.该算法首先使用余弦距离划分样本邻域;其次计算样本邻域对相似度用以评估样本共享近邻信息,并结合样本的6种邻居分布修正局部结构挖掘,提高多共享近邻的k近邻重构准确性;接着从多流形的角度评估样本点与近邻点间的稀疏分布一致性,以获得样本的重要性指标,并在低维空间保持该信息,进而提取准确的鉴别特征;最后结合KNN分类器构建出完备的轴承故障诊断模型.采用凯斯西储大学轴承数据集和实验室测试平台轴承数据集,从可视化评估、定量聚类评估、故障识别精度评估及鲁棒性评估等方面进行分析.结果表明:SN-WLLE算法的F值保持在108以上水准,平均故障识别精度最低可达0.9734,不仅具有较好的类内紧致性与类间可分性,还对近邻参数k具有低敏感性.
