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1.
公开(公告)号:EP4057016B1
公开(公告)日:2024-09-18
申请号:EP21161923.4
申请日:2021-03-11
CPC分类号: G01R31/2874 , G05B23/0283 , G01R31/64 , G05B23/0254
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公开(公告)号:EP3667446B1
公开(公告)日:2024-08-28
申请号:EP19207619.8
申请日:2019-11-07
IPC分类号: G05B23/02
CPC分类号: G05B23/0243 , G05B23/0254
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公开(公告)号:EP4111270B1
公开(公告)日:2024-07-17
申请号:EP21709309.5
申请日:2021-02-11
CPC分类号: G05B23/0254 , G05B23/0283 , G05B2219/4507120130101
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公开(公告)号:EP3729040B1
公开(公告)日:2024-04-24
申请号:EP18808306.7
申请日:2018-11-22
CPC分类号: G01M13/04 , G05B23/0254 , F05B2240/5020130101 , F05B2260/8420130101 , F03D80/70 , F03D17/00 , Y02E10/72 , F16C17/246
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5.
公开(公告)号:EP3410308A1
公开(公告)日:2018-12-05
申请号:EP18170205.1
申请日:2018-04-30
申请人: Deere & Company
发明人: WU, Yifu
CPC分类号: G07C5/0808 , G05B23/0224 , G05B23/0254 , G05B2219/24064 , G05B2219/2637 , G06F17/16 , G06N5/04 , G07C5/008
摘要: A system for performing predictive analysis and diagnostics is disclosed. The system includes a plurality of sensors communicatively coupled to a vehicle electronics unit. The plurality of sensors are configured to generate at least one first signal indicative of a first sensed condition and at least one second signal indicative of a second sensed condition. A remote central processing system is coupled to the vehicle electronics unit. The remote central processing system comprises a remote processor and a remote data storage device, wherein the remote central processing system is configured to receive each of the at least one first and second signals. A predictive diagnostic unit is arranged in the remote data storage device and comprises machine readable instructions that, when executed by the remote processor, causes the system to partition the second signal into a predetermined number of successive time intervals; generate a similarity value based on a comparative analysis between the partitioned second signal and a stored first signal; and determine an estimated degree of failure of a machine component based in part on a computed average of the similarity value.
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公开(公告)号:EP3039497B1
公开(公告)日:2018-08-29
申请号:EP14790212.6
申请日:2014-10-01
CPC分类号: G07C5/002 , B64D31/06 , B64F5/60 , G05B23/0232 , G05B23/0254 , G05B23/0283 , G07C5/008 , G07C5/0841
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公开(公告)号:EP3353613A1
公开(公告)日:2018-08-01
申请号:EP17786256.2
申请日:2017-04-18
发明人: LI, Nan , YUEN, Woh Peng Aaron , NI, Wangdong , ZHAO, Zhengzhi , SIM, Kwee Hock
CPC分类号: C02F3/006 , C02F1/00 , C02F3/00 , C02F3/2846 , C02F3/30 , C02F2203/002 , C02F2209/005 , C02F2209/006 , C02F2209/20 , G01N33/1846 , G05B13/04 , G05B13/048 , G05B15/00 , G05B17/02 , G05B23/02 , G05B23/0243 , G05B23/0254
摘要: A system for wastewater treatment process control comprising a set of measuring means arranged to obtain a dataset, the dataset comprises a plurality of process variables related to a parameter of the wastewater treatment process; a prediction module arranged to receive the dataset and predict the parameter of wastewater treatment process based on a soft sensor; a troubleshooting module arranged to compare the predicted parameter with a predetermined criterion; wherein if the predicted parameter does not satisfy the predetermined criterion; the troubleshooting module is operable to identify at least one process variable from the plurality of process variables which causes the predicted parameter not to satisfy the predetermined criterion and determine whether the identified at least one process variable from the plurality of process variables is controllable. An optimisation module for use in a wastewater treatment system is also disclosed.
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8.
公开(公告)号:EP3296823A3
公开(公告)日:2018-06-13
申请号:EP17190727.2
申请日:2017-09-12
申请人: Honeywell Limited
发明人: LU, Qiugang , GOPALUNI, R. Bhushan , FORBES, Michael G. , LOEWEN, Philip D. , BACKSTROM, Johan U. , DUMONT, Guy A.
CPC分类号: G05B23/0243 , G05B13/04 , G05B13/041 , G05B13/048 , G05B17/02 , G05B23/0254 , G05B2219/25298
摘要: A method includes obtaining (402) operating data associated with operation of a cross-directional industrial process controlled by at least one model-based process controller (106, 204). The method also includes, during a training period (502a, 502b), performing (406) closed-loop model identification with a first portion of the operating data to identify multiple sets of first spatial and temporal models. The method further includes identifying (408) clusters (604) associated with parameter values of the first spatial and temporal models. The method also includes, during a testing period (504a, 504b), performing (410) closed-loop model identification with a second portion of the operating data to identify second spatial and temporal models. The method further includes determining (412) whether at least one parameter value of at least one of the second spatial and temporal models falls outside at least one of the clusters. In addition, the method includes, in response to such a determination (414), detecting that a mismatch exists between actual and modeled behaviors of the industrial process.
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公开(公告)号:EP2525087B1
公开(公告)日:2018-03-14
申请号:EP12168427.8
申请日:2012-05-17
发明人: Thulke, Matthias
CPC分类号: F03D7/045 , F03D7/0292 , F03D17/00 , F05B2260/84 , G05B17/02 , G05B23/0254 , G05B23/0286 , Y02E10/723
摘要: A method for monitoring a wind turbine is provided. The method includes defining (4010) at least one subsystem of the wind turbine and providing (4020) a simulation model for the at least one subsystem. During normal operation of the wind turbine, an input signal and an actual output signal of the at least one subsystem are received (4100). An expected output signal of the at least one subsystem is determined (4210) using the input signal as an input of the simulation model. The actual output signal and the expected output signal are compared (4300). Based on the comparison it is determined (4400), if the first subsystem operates within a given specification.
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公开(公告)号:EP3234870A1
公开(公告)日:2017-10-25
申请号:EP15823465.8
申请日:2015-12-18
CPC分类号: G05B23/0254 , G05B23/0294 , G06K9/00791 , G06K9/4628 , G06K9/6273 , G06K9/6289 , G06N3/0454 , G06N3/08 , G06T7/248
摘要: A method includes fusing multi-modal sensor data from a plurality of sensors having different modalities. At least one region of interest is detected in the multi-modal sensor data. One or more patches of interest are detected in the multi-modal sensor data based on detecting the at least one region of interest. A model that uses a deep convolutional neural network is applied to the one or more patches of interest. Post-processing of a result of applying the model is performed to produce a post-processing result for the one or more patches of interest. A perception indication of the post-processing result is output.
摘要翻译: 一种方法包括将来自多个预测和健康监测(PHM)传感器的时间序列数据转换为频域数据。 频域数据的一个或多个部分被标记为指示一个或多个目标模式以形成标记的目标数据。 包含深度神经网络的模型被应用于标记的目标数据。 应用该模型的结果被分类为与一个或多个目标模式相关联的一个或多个离散化PHM训练指标。 输出一个或多个离散化的PHM训练指示符。
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