- 专利标题: Abnormality detection system, abnormality detection method, abnormality detection program, and method for generating learned model
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申请号: US17716992申请日: 2022-04-08
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公开(公告)号: US11874723B2公开(公告)日: 2024-01-16
- 发明人: Daisuke Okanohara , Kenta Oono
- 申请人: Preferred Networks, Inc.
- 申请人地址: JP Tokyo
- 专利权人: PREFERRED NETWORKS, INC.
- 当前专利权人: PREFERRED NETWORKS, INC.
- 当前专利权人地址: JP Tokyo
- 代理机构: Foley & Lardner LLP
- 优先权: JP 15234923 2015.12.01
- 主分类号: G06F11/00
- IPC分类号: G06F11/00 ; G06F11/07 ; G06N3/08 ; G06N7/00 ; G06N3/045 ; G06N7/01 ; G06N3/04 ; G06V20/90
摘要:
A method and system that efficiently selects sensors without requiring advanced expertise or extensive experience even in a case of new machines and unknown failures. An abnormality detection system includes a storage unit for storing a latent variable model and a joint probability model, an acquisition unit for acquiring sensor data that is output by a sensor, a measurement unit for measuring the probability of the sensor data acquired by the acquisition unit based on the latent variable model and the joint probability model stored by the storage unit, a determination unit for determining whether the sensor data is normal or abnormal based on the probability of the sensor data measured by the measurement unit, and a learning unit for learning the latent variable model and the joint probability model based on the sensor data output by the sensor.
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