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公开(公告)号:EP3887647B1
公开(公告)日:2024-10-30
申请号:EP20752242.6
申请日:2020-02-03
发明人: MAUS, Stefan , WILLERTH, Marc Ernest , DEVERSE, Jarrod Shawn , MITKUS, Alexander Michael , GEE, Timothy William , RICE, Jason Truman , CHISHOLM, Jeshurun Micaiah , FITZGERALD, Ann Kamel , KULAVIK, Richard , STOKELD, Brian Eugene , BENSON, Todd W. , LIU, Qianlong
IPC分类号: E21B47/022 , G05B13/04 , E21B7/04 , E21B44/00
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公开(公告)号:EP4443249A2
公开(公告)日:2024-10-09
申请号:EP24195243.1
申请日:2020-10-19
发明人: Du, Haibo
IPC分类号: G05B13/04
CPC分类号: A47J36/32 , G05B19/0426 , G05B2219/264320130101 , G05B15/02
摘要: A control method and device for a cooking equipment, the cooking equipment and a storage medium. The method comprises: acquiring image information of a cooking material (S102); identifying the image information, and determining category information and volume information of the cooking material (S104); and according to the category information and the volume information, determining the doneness corresponding to the cooking material (S106). According to the control method, the volume information and the category information of the cooking material are obtained by identifying the image information, the volume change amount of the cooking material in the cooking process is calculated by using the initial volume and the current volume of the cooking material, and according to the volume change amount of the cooking material, the doneness corresponding to the cooking material is determined in a pre-trained doneness model; thus, the volume change of the cooking material can be monitored in real time, an automatic doneness recognition function is achieved by using the volume change amount, the observation time of a user is greatly saved, and accuracy is higher compared with the solution that in the prior art, the food doneness is determined purely according to surface states such as colors, etc.
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公开(公告)号:EP4398050A3
公开(公告)日:2024-10-09
申请号:EP24177209.4
申请日:2022-03-22
发明人: Zhuo, Liu , Kanokogi, Hiroaki , Takami, Go , Furukawa, Yota , Gotou, Hirotsugu
CPC分类号: G05B13/0265 , G05B13/041 , G06N20/00
摘要: There is provided a control apparatus (100) comprising: an input data acquisition unit (10) configured to acquire an indicated variable and a process variable of a predetermined system, which are measured by a sensor in an equipment (300); a controlling data acquisition unit (20) configured to acquire controlling data that is generated using a control model which has been made to learn to output a manipulated variable corresponding to a combination of the indicated variable and the process variable and that indicates a correspondence relation of the combination of the indicated variable and the process variable to the manipulated variable which is output corresponding to the combination; a calculation unit (30) configured to calculate the manipulated variable corresponding to the combination of the indicated variable and the process variable using the controlling data; and an output unit (40) configured to output the manipulated variable to a predetermined controlled object.
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公开(公告)号:EP3977049B1
公开(公告)日:2024-09-25
申请号:EP20815372.6
申请日:2020-05-27
CPC分类号: F23K1/00 , F23N2221/1020200101 , F23K2201/50120130101 , F23K2900/0500420130101 , F23N1/002 , G05B13/048
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公开(公告)号:EP3985459B1
公开(公告)日:2024-09-18
申请号:EP21200027.7
申请日:2021-09-30
IPC分类号: G05B13/02
CPC分类号: G05B13/024 , A21C9/08 , Y02P90/02
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公开(公告)号:EP4429184A1
公开(公告)日:2024-09-11
申请号:EP23160983.5
申请日:2023-03-09
申请人: ABB SCHWEIZ AG
发明人: SCHLAKE, Jan Christoph , AMARLINGAM, Madapu , PLATENIUS-MOHR, Marie Christin , SARKAR, Santonu , BORRISON, Reuben
IPC分类号: H04L41/14 , H04L41/16 , G05B13/00 , G06N20/00 , G06N3/08 , H04L41/0631 , H04L41/147
CPC分类号: H04L41/0631 , H04L41/14 , H04L41/16 , G06N20/00 , H04L41/147 , G06N3/08 , H04W4/24 , H04M15/8044
摘要: The present invention relates to a method (100) for an efficient performance monitoring of a system (200) in a hierarchical network (70) of distributed edge devices (72, 74, 76) comprising at least one master edge (72), at least a first client edge (74), wherein the at least first client edge (74) is connected via a first communication interface (50) with the at least one master edge (72), at least a second client edge (76) connected via the first communication interface (51) to the at least one master edge (72), and wherein the at least one master edge (72) is connected to the system (200), comprising:
- receiving (102) sensor data (10) from the at least first client edge (74) sent by at least one sensor device (78) via a second communication interface (52);
- determining (104) a first local model parameter (14) representing a machine learning (ML) model (12) of the at least first client edge (74) based on the sensor data (10);
- storing (106) the first local model parameter (14) in a data storage (80) of the at least first client edge (74);
- collecting (108), by the at least one master edge (72), the first local model parameter (12) from the at least first client edge (74); and
- generating (110), by the at least one master edge (72) a global ML model (20) based on the at least first local model parameter (14), wherein the global ML model (20) is used for monitoring a system performance or a condition of the system (200).
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