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1. 发明授权

US08756181B2 System and method employing a self-organizing map load feature database to identify electric load types of different electric loads 有权
标题翻译：系统和方法采用自组织映射负载特征数据库来识别不同电负载的电负载类型
公开(公告)号：US08756181B2
公开(公告)日：2014-06-17
申请号：US13304758
申请日：2011-11-28
申请人： Bin Lu , Ronald G. Harley , Liang Du , Yi Yang , Santosh K. Sharma , Prachi Zambare , Mayura A. Madane
发明人： Bin Lu , Ronald G. Harley , Liang Du , Yi Yang , Santosh K. Sharma , Prachi Zambare , Mayura A. Madane
IPC分类号： G06F17/30
CPC分类号： G06N3/088 , Y04S20/38
摘要： A method identifies electric load types of a plurality of different electric loads. The method includes providing a self-organizing map load feature database of a plurality of different electric load types and a plurality of neurons, each of the load types corresponding to a number of the neurons; employing a weight vector for each of the neurons; sensing a voltage signal and a current signal for each of the loads; determining a load feature vector including at least four different load features from the sensed voltage signal and the sensed current signal for a corresponding one of the loads; and identifying by a processor one of the load types by relating the load feature vector to the neurons of the database by identifying the weight vector of one of the neurons corresponding to the one of the load types that is a minimal distance to the load feature vector.
摘要翻译：一种方法识别多个不同电负载的电负载类型。该方法包括提供多个不同电负载类型和多个神经元的自组织映射负载特征数据库，每个负载类型对应于多个神经元; 对每个神经元采用权重向量; 感测每个负载的电压信号和电流信号; 从所感测的电压信号和所感测的电流信号中确定负载特征矢量，所述载荷特征矢量包括至少四个不同的负载特征，用于对应的一个负载; 以及通过将负载特征向量与数据库的神经元相关联来识别负载类型之一，通过识别对应于与负载特征向量的最小距离的一个负载类型的一个神经元的权重向量，来由处理器识别负载类型之一。

2. 发明申请

US20130138669A1 SYSTEM AND METHOD EMPLOYING A HIERARCHICAL LOAD FEATURE DATABASE TO IDENTIFY ELECTRIC LOAD TYPES OF DIFFERENT ELECTRIC LOADS 审中-公开
标题翻译：使用分层负载特征数据库识别不同电力负载的电力负载类型的系统和方法
公开(公告)号：US20130138669A1
公开(公告)日：2013-05-30
申请号：US13304783
申请日：2011-11-28
申请人： BIN LU , Yi Yang , Santosh K. Sharma , Prachi Zambare , Mayura A. Madane
发明人： BIN LU , Yi Yang , Santosh K. Sharma , Prachi Zambare , Mayura A. Madane
IPC分类号： G06F17/30
CPC分类号： G06N3/088
摘要： A method identifies electric load types of a plurality of different electric loads. The method includes providing a hierarchical load feature database having a plurality of layers; including with each of a plurality of the layers a corresponding load feature set, the corresponding load feature set of at least one of the layers being different from the corresponding load feature set of at least another one of the layers; including with one of the layers a plurality of different electric load types; sensing a voltage signal and a current signal for each of the different electric loads; determining at least four different load features from the sensed voltage signal and the sensed current signal for a corresponding one of the different electric loads; and identifying by a processor one of the different electric load types by relating the different load features to the hierarchical load feature database.
摘要翻译：一种方法识别多个不同电负载的电负载类型。该方法包括提供具有多个层的分层负载特征数据库; 包括多个层中的每一层具有相应的负载特征集合，所述层中的至少一个层的对应的负载特征集不同于所述层中的至少另一层的相应的负载特征集合; 包括其中一层具有多种不同的电负载类型; 感测每个不同电负载的电压信号和电流信号; 从所感测的电压信号和所感测的电流信号确定至少四个不同的负载特征，用于相应的一个不同的电负载; 以及通过将不同的负载特征与分层负载特征数据库相关联，由处理器识别不同的电负载类型之一。

3. 发明授权

US08918346B2 System and method employing a minimum distance and a load feature database to identify electric load types of different electric loads 有权
标题翻译：采用最小距离的系统和方法和负载特征数据库来识别不同电力负载的电负荷类型
公开(公告)号：US08918346B2
公开(公告)日：2014-12-23
申请号：US13304834
申请日：2011-11-28
申请人： Bin Lu , Yi Yang , Santosh K. Sharma , Prachi Zambare , Mayura A. Madane
发明人： Bin Lu , Yi Yang , Santosh K. Sharma , Prachi Zambare , Mayura A. Madane
IPC分类号： G06F15/18 , G06E1/02 , G06G7/10
CPC分类号： H02J13/00 , H02J3/00
摘要： A method identifies electric load types of a plurality of different electric loads. The method includes providing a load feature database of a plurality of different electric load types, each of the different electric load types including a first load feature vector having at least four different load features; sensing a voltage signal and a current signal for each of the different electric loads; determining a second load feature vector comprising at least four different load features from the sensed voltage signal and the sensed current signal for a corresponding one of the different electric loads; and identifying by a processor one of the different electric load types by determining a minimum distance of the second load feature vector to the first load feature vector of the different electric load types of the load feature database.
摘要翻译：一种方法识别多个不同电负载的电负载类型。该方法包括提供多种不同电负载类型的负载特征数据库，每种不同的电负载类型包括具有至少四个不同负载特征的第一负载特征向量; 感测每个不同电负载的电压信号和电流信号; 确定第二负载特征向量，其包括来自所感测的电压信号的至少四个不同的负载特征和用于所述不同电负载中的相应一个的感测的电流信号; 以及通过确定所述第二负载特征向量与所述负载特征数据库的不同电负载类型的所述第一负载特征向量的最小距离，由处理器识别所述不同电负载类型之一。

4. 发明申请

US20130138661A1 SYSTEM AND METHOD EMPLOYING A MINIMUM DISTANCE AND A LOAD FEATURE DATABASE TO IDENTIFY ELECTRIC LOAD TYPES OF DIFFERENT ELECTRIC LOADS 有权
标题翻译：使用最小距离的系统和方法和负载特征数据库来识别不同电力负载的电力负载类型
公开(公告)号：US20130138661A1
公开(公告)日：2013-05-30
申请号：US13304834
申请日：2011-11-28
申请人： BIN LU , Yi Yang , Santosh K. Sharma , Prachi Zambare , Mayura A. Madane
发明人： BIN LU , Yi Yang , Santosh K. Sharma , Prachi Zambare , Mayura A. Madane
IPC分类号： G06F17/30
CPC分类号： H02J13/00 , H02J3/00
摘要： A method identifies electric load types of a plurality of different electric loads. The method includes providing a load feature database of a plurality of different electric load types, each of the different electric load types including a first load feature vector having at least four different load features; sensing a voltage signal and a current signal for each of the different electric loads; determining a second load feature vector comprising at least four different load features from the sensed voltage signal and the sensed current signal for a corresponding one of the different electric loads; and identifying by a processor one of the different electric load types by determining a minimum distance of the second load feature vector to the first load feature vector of the different electric load types of the load feature database.
摘要翻译：一种方法识别多个不同电负载的电负载类型。该方法包括提供多种不同电负载类型的负载特征数据库，每种不同的电负载类型包括具有至少四个不同负载特征的第一负载特征向量; 感测每个不同电负载的电压信号和电流信号; 确定第二负载特征向量，其包括来自所感测的电压信号的至少四个不同的负载特征和用于所述不同电负载中的相应一个的感测的电流信号; 以及通过确定所述第二负载特征向量与所述负载特征数据库的不同电负载类型的所述第一负载特征向量的最小距离，由处理器识别所述不同电负载类型之一。

5. 发明申请

US20130138651A1 SYSTEM AND METHOD EMPLOYING A SELF-ORGANIZING MAP LOAD FEATURE DATABASE TO IDENTIFY ELECTRIC LOAD TYPES OF DIFFERENT ELECTRIC LOADS 有权
标题翻译：使用自组织地图负载特征数据库识别不同电力负载的电力负载类型的系统和方法
公开(公告)号：US20130138651A1
公开(公告)日：2013-05-30
申请号：US13304758
申请日：2011-11-28
申请人： BIN LU , Ronald G. Harley , Liang Du , Yi Yang , Santosh K. Sharma , Prachi Zambare , Mayura A. Madane
发明人： BIN LU , Ronald G. Harley , Liang Du , Yi Yang , Santosh K. Sharma , Prachi Zambare , Mayura A. Madane
IPC分类号： G06F17/30
CPC分类号： G06N3/088 , Y04S20/38
摘要： A method identifies electric load types of a plurality of different electric loads. The method includes providing a self-organizing map load feature database of a plurality of different electric load types and a plurality of neurons, each of the load types corresponding to a number of the neurons; employing a weight vector for each of the neurons; sensing a voltage signal and a current signal for each of the loads; determining a load feature vector including at least four different load features from the sensed voltage signal and the sensed current signal for a corresponding one of the loads; and identifying by a processor one of the load types by relating the load feature vector to the neurons of the database by identifying the weight vector of one of the neurons corresponding to the one of the load types that is a minimal distance to the load feature vector.
摘要翻译：一种方法识别多个不同电负载的电负载类型。该方法包括提供多个不同电负载类型和多个神经元的自组织映射负载特征数据库，每个负载类型对应于多个神经元; 对每个神经元采用权重向量; 感测每个负载的电压信号和电流信号; 从所感测的电压信号和所感测的电流信号中确定负载特征矢量，所述载荷特征矢量包括至少四个不同的负载特征，用于对应的一个负载; 以及通过将负载特征向量与数据库的神经元相关联来识别负载类型之一，通过识别对应于与负载特征向量的最小距离的负载类型之一的神经元中的一个的权重向量来识别处理器之一。

6. 发明申请

US20140067299A1 SYSTEM AND METHOD FOR ELECTRIC LOAD IDENTIFICATION AND CLASSIFICATION EMPLOYING SUPPORT VECTOR MACHINE 审中-公开
标题翻译：使用支持向量机的电力负载识别和分类系统与方法
公开(公告)号：US20140067299A1
公开(公告)日：2014-03-06
申请号：US13597324
申请日：2012-08-29
申请人： BIN LU , Ronald G. Harley , Liang Du , Yi Yang , Santosh K. Sharma , Prachi S. Zambare , Mayura A. Madane
发明人： BIN LU , Ronald G. Harley , Liang Du , Yi Yang , Santosh K. Sharma , Prachi S. Zambare , Mayura A. Madane
IPC分类号： G06F19/00 , G01R27/00 , G01R21/06 , G01R19/00 , G01R19/02
CPC分类号： G06K9/00536 , G06K9/0053 , Y04S20/38
摘要： A method identifies electric load types of a plurality of different electric loads. The method includes providing a support vector machine load feature database of a plurality of different electric load types; sensing a voltage signal and a current signal for each of the different electric loads; determining a load feature vector including at least six steady-state features with a processor from the sensed voltage signal and the sensed current signal; and identifying one of the different electric load types by relating the load feature vector including the at least six steady-state features to the support vector machine load feature database.
摘要翻译：一种方法识别多个不同电负载的电负载类型。该方法包括提供多种不同电负载类型的支持向量机负载特征数据库; 感测每个不同电负载的电压信号和电流信号; 根据感测到的电压信号和感测到的电流信号，确定包括至少六个稳态特征的负载特征向量与处理器; 以及通过将包括所述至少六个稳态特征的所述负载特征向量与所述支持向量机负载特征数据库相关联来识别不同的电负载类型之一。

7. 发明授权

US10325150B2 System and method for electric load identification and classification employing support vector machine 有权
公开(公告)号：US10325150B2
公开(公告)日：2019-06-18
申请号：US13597324
申请日：2012-08-29
申请人： Bin Lu , Ronald G. Harley , Liang Du , Yi Yang , Santosh K. Sharma , Prachi S. Zambare , Mayura A. Madane
发明人： Bin Lu , Ronald G. Harley , Liang Du , Yi Yang , Santosh K. Sharma , Prachi S. Zambare , Mayura A. Madane
IPC分类号： G06F11/30 , G06K9/00
摘要： A method identifies electric load types of a plurality of different electric loads. The method includes providing a support vector machine load feature database of a plurality of different electric load types; sensing a voltage signal and a current signal for each of the different electric loads; determining a load feature vector including at least six steady-state features with a processor from the sensed voltage signal and the sensed current signal; and identifying one of the different electric load types by relating the load feature vector including the at least six steady-state features to the support vector machine load feature database.

8. 外观设计

USD974458S1 Steel tongue drum 有权
公开(公告)号：USD974458S1
公开(公告)日：2023-01-03
申请号：US29847274
申请日：2022-07-22
申请人： Yi Yang
设计人： Yi Yang

9. 发明授权

US11499013B2 Zwitterionic poly(sulfobetaine arylene ether sulfone) polymer synthesis route and applications for desalination membranes 有权
公开(公告)号：US11499013B2
公开(公告)日：2022-11-15
申请号：US16374501
申请日：2019-04-03
申请人： Matthew Green , Yi Yang
发明人： Matthew Green , Yi Yang
IPC分类号： C08G75/23 , C08L81/06 , C02F1/44 , B01D71/68 , C02F103/08 , C08G65/40
摘要： A zwitterionic polysulfone formed from an allyl-containing monomer, a phenol-containing monomer, and an aryl-halide-containing monomer. The zwitterionic polysulfone may be incorporated into a desalination membrane.

10. 外观设计

USD936263S1 Sensor light 有权
公开(公告)号：USD936263S1
公开(公告)日：2021-11-16
申请号：US29773881
申请日：2021-03-12
申请人： Yi Yang
设计人： Yi Yang

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