Invention Grant
US08756181B2 System and method employing a self-organizing map load feature database to identify electric load types of different electric loads
有权
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
- Patent Title: System and method employing a self-organizing map load feature database to identify electric load types of different electric loads
- Patent Title (中): 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
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Application No.: US13304758Application Date: 2011-11-28
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Publication No.: US08756181B2Publication Date: 2014-06-17
- Inventor: Bin Lu , Ronald G. Harley , Liang Du , Yi Yang , Santosh K. Sharma , Prachi Zambare , Mayura A. Madane
- Applicant: Bin Lu , Ronald G. Harley , Liang Du , Yi Yang , Santosh K. Sharma , Prachi Zambare , Mayura A. Madane
- Applicant Address: US OH Cleveland US GA Atlanta
- Assignee: Eaton Corporation,Georgia Tech Research Corporation
- Current Assignee: Eaton Corporation,Georgia Tech Research Corporation
- Current Assignee Address: US OH Cleveland US GA Atlanta
- Agency: Eckert Seamans Cherin & Mellott, LLC
- Agent Kirk D. Houser
- Main IPC: G06F17/30
- IPC: G06F17/30

Abstract:
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.
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