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21.发明公开
公开(公告)号：EP4354231A1
公开(公告)日：2024-04-17
申请号：EP23202527.0
申请日：2023-10-09
IPC分类号： G05B9/02 , G05B13/02 , G05B19/418
CPC分类号： G05B13/0265 , G05B19/418
摘要： A method performed by an Advanced Physical Layer (APL)-based edge device with power constraints is provided. The method includes applying an event-driven framework that is compliant with power constraints of the APL-based edge device to receive input data; applying the event-driven framework to the input data to invoke a machine learning (ML) model that is trained to analyze the input data and make inferences about one or more aspects of an industrial system based on the input data, and applying the invoked machine learning model to analyze the input data and make an inference about the one or more aspects of the industrial system based on the input data. The input data is received by the APL-based edge device from one or more source field devices of the industrial system and/or the inference is used make a decision and cause an action to be applied to the industrial system.
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公开(公告)号：EP4300230A3
公开(公告)日：2024-03-27
申请号：EP23210388.7
申请日：2020-03-24
IPC分类号： G05B19/042
摘要： Systems and methods for controlling industrial process automation and control systems can automatically, through the use of machine learning (ML) models and algorithms, extract plant assets from engineering diagrams and other plant engineering data sources. The systems and methods can establish asset relationships to create a plant asset registry and build an asset hierarchy from the plant assets. The systems and methods can generate an ontological knowledge base from the plant asset hierarchy, and provide an HMI for controlling the industrial process based on the plant asset hierarchy and the ontological knowledge base.
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公开(公告)号：EP4300230A2
公开(公告)日：2024-01-03
申请号：EP23210388.7
申请日：2020-03-24
IPC分类号： G05B19/418
摘要： Systems and methods for controlling industrial process automation and control systems can automatically, through the use of machine learning (ML) models and algorithms, extract plant assets from engineering diagrams and other plant engineering data sources. The systems and methods can establish asset relationships to create a plant asset registry and build an asset hierarchy from the plant assets. The systems and methods can generate an ontological knowledge base from the plant asset hierarchy, and provide an HMI for controlling the industrial process based on the plant asset hierarchy and the ontological knowledge base.
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公开(公告)号：EP4287046A1
公开(公告)日：2023-12-06
申请号：EP23161040.3
申请日：2023-03-09
发明人： REDMOND, James , NEAVE, Stephen
IPC分类号： G06F21/10 , G06Q10/0631 , G06Q10/087 , G06Q50/04
摘要： Method and system for provisioning industrial assets. A provisioning server processes location data and an identifier associated with a selected industrial asset for verifying a presence of the asset within a predefined area and for determining a feature set for the asset. The location data is indicative of a location of the asset and the identifier identifies the asset and has the feature set associated therewith. The provisioning server then retrieves a license and/or configuration corresponding to the feature set for the asset from the repository in response to the asset being located within the predefined area. The provisioning server provisions the asset with the retrieved license and/or configuration.
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25.发明公开
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公开(公告)号：EP4254870A1
公开(公告)日：2023-10-04
申请号：EP23161043.7
申请日：2023-03-09
发明人： REDMOND, James
摘要： A multi-factor authentication method and system enabling secure access to an industrial asset. A higher level of authentication to access a selected privileged operation of the industrial asset requires verification of two or more multi-factor access credentials.
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公开(公告)号：EP4217801A1
公开(公告)日：2023-08-02
申请号：EP21880901.0
申请日：2021-10-12
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28.发明公开
公开(公告)号：EP4207003A1
公开(公告)日：2023-07-05
申请号：EP22210980.3
申请日：2022-12-02
发明人： Gondhi, Dinesh , Sinha, Bhaskar , Patil, Ashish Bhaskarrao , Mahendran, Niranjana , Namburu, Kalyana Srinivas , Gavande, Vinod Krushna
IPC分类号： G06N5/022 , G06N20/00 , G06N5/04 , G05B19/042 , G06N3/0442 , G06N5/01 , G06N20/20 , G06N3/09
摘要： A method of automating engineering design is provided. The method includes receiving a training set including pairings of control loop data for respective control loops identified in digitized design data and templates that were instantiated using the control loop data of the respective control loops and training, using machine learning, a knowledge base, based on the training set. The knowledge base, once trained, is configured to be queried with digitized new control loop data, predict a template to pair with the digitized new control loop data, and the predicted template, and the predicted template is configured to be instantiated with the new control loop data for implementation of a control loop in an engineering system.
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29.发明公开
公开(公告)号：EP4194976A1
公开(公告)日：2023-06-14
申请号：EP22202879.7
申请日：2022-10-21
IPC分类号： G05B19/05
摘要： A method for managing soft errors associated with one or more safety programmable logic controllers (PLCs) 104(1)...104(X) is provided. The method includes receiving an expected soft error rate for type(s) of input/output (I/O) modules 110(1)...110(n) over time, receiving respective soft error data that was aggregated by the respective safety PLCs104(1)...104(X) based on soft errors detected by I/O modules 110(1)...110(n) coupled to the respective safety PLCs 104(1)...104(X). Actual soft error rates are determined per I/O module type based on the received soft error data, and soft error rates are predicted for the safety PLC(s) per I/O module type. The actual and/or predicted soft error rates are compared to the expected soft error rate per I/O module type. The method further includes taking one or more actions in response to a threshold deviation between the actual and/or predicted soft error rates relative to the expected soft error rate for the corresponding I/O module type.
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公开(公告)号：EP4187453A1
公开(公告)日：2023-05-31
申请号：EP22201397.1
申请日：2022-10-13
IPC分类号： G06N20/00
摘要： Monitoring an industrial process by building a training dataset of system data representative of status of industrial process parameters and training a custom query engine based on the training dataset. Models are generated using the custom query engine for matching query terms to the system data in response to user input representative of the system data that the user intends to access. Executing one of the models based on the input from the user generates an output retrieving the selected system data from the data tables for visualization.
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