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It is studied beforehand making use of the study

机译:事先利用研究进行研究

摘要

PPROBLEM TO BE SOLVED: To provide an abnormality detection device which makes it detectable that there is no specific abnormal status during operation of equipment, and an abnormality detection method. PSOLUTION: Existence of abnormalities of the equipment X is decided by a competitive learning type neural network 1 by using the feature amount of a target signal containing an oscillating component produced by an operation of the equipment X. A data set comprising a plurality of data of which categories are considered a specific abnormal condition is stored in a learning data storage part 6, and the competitive learning type neural network 1 is made to be learnt by this data set. A determination part 5 associates a belonging level to an Euclidean distance between a weight vector of a neuron of a category of a specific abnormal status and input data, and when the belonging level of the input data acquired during operation of the equipment X is not larger than a specified threshold, it is decided that the equipment X operates normally. PCOPYRIGHT: (C)2008,JPO&INPIT
机译:

要解决的问题:提供一种异常检测装置和异常检测方法,该异常检测装置使得可以检测到在设备运行期间没有特定的异常状态。解决方案:竞争性学习型神经网络1通过使用包含由设备X的操作产生的振荡成分的目标信号的特征量来确定设备X的异常存在。一个数据集包括多个将被认为是特定异常状况的类别的数据的一部分存储在学习数据存储部分6中,并且通过该数据集来学习竞争性学习型神经网络1。确定部5将所属级别与特定异常状态的类别的神经元的权重矢量和输入数据之间的欧几里得距离相关联,并且在设备X的操作期间获取的输入数据的所属级别不大时进行确定。如果超过规定的阈值,则判定设备X正常工作。

版权:(C)2008,日本特许厅&INPIT

著录项

  • 公开/公告号JP4605132B2

    专利类型

  • 公开/公告日2011-01-05

    原文格式PDF

  • 申请/专利权人 パナソニック電工株式会社;

    申请/专利号JP20060269509

  • 发明设计人 池田 和隆;

    申请日2006-09-29

  • 分类号G06N3;

  • 国家 JP

  • 入库时间 2022-08-21 18:16:55

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