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公开(公告)号:US11238371B2
公开(公告)日:2022-02-01
申请号:US16441028
申请日:2019-06-14
Applicant: ABB Schweiz AG
Inventor: Benjamin Kloepper , Benedikt Schmidt , Mohamed-Zied Ouertani
Abstract: A computer system can be configured to: receive, in a low-precision mode, first status data generated by one or more sensors, the first status data reflecting technical parameters of a technical system, the first status data exhibiting a first precision level; apply a low-precision machine learning model to analyze the first status data for one or more indicators of an abnormal technical status, the machine learning model having been trained with data exhibiting the first precision level; send, based on an abnormal technical status being indicated, instructions for the one or more sensors to generate second status data exhibiting a second precision level, the second precision level being associated with greater accuracy than the first precision level; receive the second status data exhibiting the second precision level based on the sent instructions; providing the second status data to a data analyzer.
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公开(公告)号:US20180336019A1
公开(公告)日:2018-11-22
申请号:US15985127
申请日:2018-05-21
Applicant: ABB Schweiz AG
Inventor: Benedikt Schmidt , Jeff Harding , Thomas Goldschmidt
Abstract: A system for reusing program code from a first completed application in a second under-development application based on identified patterns matching between the types of data accessed by the first and second applications. The system has an information model database, a pattern database, an API and applications which query the information model through the API, resulting in stored raw access data. The raw access data is extracted and patterns are generated based on similarity of the abstracted patterns as between the first and second applications. Application programmers access the pattern database to create new programs and implement prior computer code in the new program based on a pattern match on data accessed by a prior-developed application.
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33.
公开(公告)号:US20250053879A1
公开(公告)日:2025-02-13
申请号:US18928369
申请日:2024-10-28
Applicant: ABB Schweiz AG
Inventor: Dawid Ziobro , Benjamin Kloepper , Marcel Dix , Benedikt Schmidt , Arzam Muzaffar Kotriwala , Yemao Man , Divyasheel Sharma , Gayathri Gopalakrishnan , Joakim Astrom
IPC: G06N20/00
Abstract: A method for enabling user feedback and summarizing return of investment for machine learning systems includes providing a training data set and an initial machine learning model; providing a result of the initial machine learning model; receiving feedback on the result of the initial machine learning model from a user enriching the training dataset based on the feedback to an enriched data set; and retraining the initial machine learning model to a retrained machine learning model based on an enriched data set.
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公开(公告)号:US11880192B2
公开(公告)日:2024-01-23
申请号:US17228730
申请日:2021-04-13
Applicant: ABB Schweiz AG
Inventor: Dennis Janka , Moncef Chioua , Pablo Rodriguez , Mario Hoernicke , Benedikt Schmidt , Benjamin Kloepper
IPC: G05B19/418 , G06F30/18 , H04L41/12 , H04L41/14
CPC classification number: G05B19/41865 , G05B19/4183 , G05B19/4185 , G05B19/41885 , G06F30/18 , H04L41/12 , H04L41/145
Abstract: A method for determining an interdependency between a plurality of elements in an industrial processing system includes: providing a process flow diagram (PFD) of a topology of the processing system; transforming the PFD into a directed graph, each element of the plurality of elements being transformed into a node and each relation between the plurality of elements being transformed into a directed edge; selecting one node of the plurality of nodes as a starting node; and constructing a subgraph, the subgraph including all the nodes that are forward-connected from the starting node so as to show at least one interdependency between the plurality of elements in the subgraph.
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35.
公开(公告)号:US20240005232A1
公开(公告)日:2024-01-04
申请号:US18448535
申请日:2023-08-11
Applicant: ABB Schweiz AG
Inventor: Benedikt Schmidt , Jens Doppelhamer , Pablo Rodriguez , Benjamin Kloepper , Reuben Borrison , Marcel Dix , Hadil Abukwaik , Arzam Muzaffar Kotriwala , Sylvia Maczey , Dawid Ziobro , Simon Hallstadius Linge , Marco Gaertler , Divyasheel Sharma , Chandrika K R , Gayathri Gopalakrishnan , Matthias Berning
IPC: G06Q10/0631
CPC classification number: G06Q10/063112 , G06Q10/06312
Abstract: A method for generating and/or augmenting an execution protocol for an SOP in an industrial plant includes providing at least one SOP of the plant, which includes a plurality of steps; providing measurement data; for each step of the SOP, determining from the measurement data a subset of the measurement data that is indicative of actions performed for the purpose of executing this particular step of the SOP; and aggregating the subset of the measurement data determined for each step of the SOP into at least one instruction for executing this particular step of the SOP, wherein this instruction is part of the sought protocol.
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公开(公告)号:US20230074570A1
公开(公告)日:2023-03-09
申请号:US17899856
申请日:2022-08-31
Applicant: ABB Schweiz AG
Inventor: Andrea Macauda , Raja Sivalingam , Chandrika K R , Matthias Berning , Dawid Ziobro , Sylvia Maczey , Pablo Rodriquez , Benjamin Kloepper , Reuben Borrison , Marcel Dix , Benedikt Schmidt , Hadil Abukwaik , Arzam Muzaffar Kotriwala , Divyasheel Sharma , Gayathri Gopalakrishnan , Simon Linge , Marco Gaertler , Jens Doppelhamer
IPC: G05B23/02
Abstract: An industrial plant operator intervention system for use in an industrial plant includes a processing unit configured to monitor and analyze industrial plant operation data to detect an anomaly in the industrial plant operation data that warrants initiating an operator intervention, and in response to detecting the anomaly, automatically determine a user interface configuration of a user interface to be presented to a designated operator who is to perform the operator intervention. The user interface configuration is determined on the basis of technical context data, including industrial plant operation data associated with the anomaly, and on the basis of operator data pertaining to the designated operator, in such a manner that an anomaly-related and operator-specific user interface configuration is obtained.
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37.
公开(公告)号:US11567483B2
公开(公告)日:2023-01-31
申请号:US16850010
申请日:2020-04-16
Applicant: ABB Schweiz AG
Inventor: Benedikt Schmidt , Martin Hollender , Felix Lenders
IPC: G05B19/418
Abstract: A computer-implemented method to control technical equipment that performs a production batch-run of a production process, the technical equipment providing data in a form of time-series from a set of data sources, the data sources being related to the technical equipment, includes: accessing a reference time-series with data from a previously performed batch-run of the production process, the reference time-series being related to a parameter for the technical equipment; and while the technical equipment performs the production batch-run: receiving a production time-series with data, identifying a sub-series of the reference time-series, and comparing the received time-series and the sub-series of the reference time-series, to provide an indication of similarity or non-similarity, in case of similarity, controlling the technical equipment during a continuation of the production batch-run, by using the parameter as control parameter.
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公开(公告)号:US20230029400A1
公开(公告)日:2023-01-26
申请号:US17957609
申请日:2022-09-30
Applicant: ABB Schweiz AG
Inventor: Benedikt Schmidt , Ido Amihai , Arzam Muzaffar Kotriwala , Moncef Chioua , Dennis Janka , Felix Lenders , Jan Christoph Schlake , Martin Hollender , Hadil Abukwaik , Benjamin Kloepper
IPC: G06N20/00
Abstract: A method of hierarchical machine learning includes receiving a topology model having information on hierarchical relations between components of the industrial plant, determining a representation hierarchy comprising a plurality of levels, wherein each representation on a higher level represents a group of representations on a lower level, wherein the representations comprise a machine learning model, and training an output machine learning model using the determined hierarchical representations.
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公开(公告)号:US20230019404A1
公开(公告)日:2023-01-19
申请号:US17956117
申请日:2022-09-29
Applicant: ABB Schweiz AG
Inventor: Benjamin Kloepper , Benedikt Schmidt , Ido Amihai , Moncef Chioua , Jan Christoph Schlake , Arzam Muzaffar Kotriwala , Martin Hollender , Dennis Janka , Felix Lenders , Hadil Abukwaik
IPC: G06N20/20
Abstract: A computer-implemented method for automating the development of industrial machine learning applications includes one or more sub-methods that, depending on the industrial machine learning problem, may be executed iteratively. These sub-methods include at least one of a method to automate the data cleaning in training and later application of machine learning models, a method to label time series (in particular signal data) with help of other timestamp records, feature engineering with the help of process mining, and automated hyper-parameter tuning for data segmentation and classification.
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公开(公告)号:US20210397837A1
公开(公告)日:2021-12-23
申请号:US17465882
申请日:2021-09-03
Applicant: ABB Schweiz AG
Inventor: Subanatarajan Subbiah , Ralf Gitzel , Benedikt Schmidt
Abstract: An apparatus for monitoring a switchgear includes: an input unit; a processing unit; and an output unit. The input unit is provides the processing unit with a monitor infra-red image of a switchgear. The processing unit implements a machine learning classifier algorithm to analyse the monitor infra-red image and determine if there is one or more anomalous hot spots in the switchgear. The machine learning classifier algorithm has been trained based on a plurality of different training images, the plurality of training images including a plurality of synthetic infra-red images generated by an image processing algorithm. The output unit outputs information relating to the one or more anomalous hot spots.
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