Invention Grant
US08694283B2 System and method for modeling conditional dependence for anomaly detection in machine condition monitoring
失效
在机器状态监测中对异常检测进行条件依赖建模的系统和方法
- Patent Title: System and method for modeling conditional dependence for anomaly detection in machine condition monitoring
- Patent Title (中): 在机器状态监测中对异常检测进行条件依赖建模的系统和方法
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Application No.: US13186538Application Date: 2011-07-20
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Publication No.: US08694283B2Publication Date: 2014-04-08
- Inventor: Chao Yuan
- Applicant: Chao Yuan
- Applicant Address: DE München
- Assignee: Siemens Aktiengesellschaft
- Current Assignee: Siemens Aktiengesellschaft
- Current Assignee Address: DE München
- Agent Michele L. Conover
- Main IPC: G06F17/18
- IPC: G06F17/18 ; G05B17/02

Abstract:
A method for predicting sensor output values of a machine sensor monitoring system includes providing a set of input sensor data X and a set of output sensor data Y for a plurality of sensors the monitor the performance of a machine, learning a functional relationship that maps the input sensor data to the output sensor data by maximizing a logarithm of a marginalized conditional probability function P(Y|X) where a dependence of the output sensor data Y with respect to unknown hidden machine inputs u has been marginalized, providing another set of input sensor data X′, and calculating expected values of the output sensor data Y′ using the input sensor data X′ and the marginalized conditional probability function P(Y|X′), where the calculated expectation values reflect the dependence of the output sensor data Y″ with respect to the unknown hidden machine inputs u.
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