公开(公告)号：US20240310817A1

公开(公告)日：2024-09-19

申请号：US18212725

申请日：2023-06-22

Applicant: ABB Schweiz AG

Inventor： Martin Hollender ,  Benedikt Schmidt

IPC: G05B19/418

CPC classification number: G05B19/41875 ,  G05B19/4183 ,  G05B2219/13011

Abstract: A method for automatic identification of important batch events for a batch execution alignment algorithm, including receiving historical batch data of a batch process, wherein the historical batch data comprises a plurality of batch executions, and wherein each of the plurality of batch executions comprises a plurality of batch events, indicating a specific event of the batch process, and at least one time series of a process variable, indicating a development of the process variable during the batch process; determining a distance between the at least one time series of the plurality of the batch executions for each of the plurality of batch events; and identifying at least one important batch event for a batch execution alignment algorithm with a smallest distance using the determined distances.

公开(公告)号：US20240310797A1

公开(公告)日：2024-09-19

申请号：US18672276

申请日：2024-05-23

Applicant: ABB Schweiz AG

Inventor： Benjamin Kloepper ,  Benedikt Schmidt ,  Reuben Borrison

IPC: G05B13/02

CPC classification number: G05B13/027

Abstract: A method for determining an appropriate sequence of actions to take during operation of an industrial plant includes obtaining values of a plurality of state variables that characterize an operational state of the plant (or a part thereof); encoding by at least one trained state encoder network the plurality of state variables into a representation of the operating state of the plant; mapping by a trained state-to-action network the representation of the operating state to a representation of a sequence of actions to take in response to the operating state; and decoding by a trained action decoder network the representation of the sequence of actions to the sought sequence of actions to take.

公开(公告)号：US12092526B2

公开(公告)日：2024-09-17

申请号：US17465889

申请日：2021-09-03

Applicant: ABB Schweiz AG

Inventor： Ralf Gitzel ,  Subanatarajan Subbiah ,  Benedikt Schmidt

IPC: G01J5/80 ,  G01J5/00 ,  G06N3/08 ,  G06T5/70 ,  G06V10/143 ,  G06V10/30 ,  G06V10/764 ,  G06V10/82 ,  H02B13/025 ,  G06N3/045 ,  H02B3/00

CPC classification number: G01J5/80 ,  G01J5/0066 ,  G01J5/0096 ,  G06N3/08 ,  G06T5/70 ,  G06V10/143 ,  G06V10/30 ,  G06V10/764 ,  G06V10/82 ,  H02B13/025 ,  G01J2005/0077 ,  G06N3/045 ,  G06T2207/10048 ,  G06V2201/06 ,  H02B3/00

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 the 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 infra-red images. The plurality of training infra-red images include a plurality of modified infra-red images generated from a corresponding plurality of infra-red images, each of the modified infra-red images having been modified to remove an effect of obscuration in the image. The output unit outputs information relating to the one or more anomalous hot spots.

公开(公告)号：US20240302831A1

公开(公告)日：2024-09-12

申请号：US18669696

申请日：2024-05-21

Applicant: ABB Schweiz AG

Inventor： Hadil Abukwaik ,  Divyasheel Sharma ,  Benjamin Kloepper ,  Arzam Muzaffar Kotriwala ,  Pablo Rodriguez ,  Benedikt Schmidt ,  Ruomu Tan ,  Chandrika K R ,  Reuben Borrison ,  Marcel Dix ,  Jens Doppelhamer

IPC: G05B23/02

CPC classification number: G05B23/024 ,  G05B23/0251

Abstract: A method for determining the state of health of an industrial process executed by at least one industrial plant comprising an arrangement of entities, and the state of each such entity, includes obtaining values of the entity state variables; providing the values to a model to obtain a prediction of the state of health; determining propagation paths for anomalies between said entities; determining importances of the states of health of the individual entities for the overall state of health of the process; and aggregating the individual states of health of the entities to obtain the overall state of health of the process.

公开(公告)号：US20240160160A1

公开(公告)日：2024-05-16

申请号：US18455340

申请日：2023-08-24

Applicant: ABB Schweiz AG

Inventor： Ruomu Tan ,  Marco Gaertler ,  Benjamin Kloepper ,  Sylvia Maczey ,  Andreas Potschka ,  Martin Hollender ,  Benedikt Schmidt

IPC: G05B13/02

CPC classification number: G05B13/027

Abstract: A method for detecting change points, CPs, in a signal of a process automation system, includes, in an offline learning phase, unsupervised, candidate CPs on at least one offline signal using unsupervised detection method are detected, CPs are selected from the candidate CPs; the selected CPs are provided to a supervised process; in the supervised process, an offline machine-learning (ML) system is trained to refine CPs from the selected CPs using a supervised machine learning method; a training data set for an online ML system is created using the offline ML system by projecting the refined CPs on the signal; the online ML system is trained in a supervised manner, using the created training data set; and after the offline learning phase, CPs are detected using the trained online ML system.

公开(公告)号：US20230393538A1

公开(公告)日：2023-12-07

申请号：US18452313

申请日：2023-08-18

Applicant: ABB Schweiz AG

Inventor： Dawid Ziobro ,  Jens Doppelhamer ,  Benedikt Schmidt ,  Simon Hallstadius Linge ,  Gayathri Gopalakrishnan ,  Pablo Rodriguez ,  Benjamin Kloepper ,  Reuben Borrison ,  Marcel Dix ,  Hadil Abukwaik ,  Arzam Muzaffar Kotriwala ,  Sylvia Maczey ,  Marco Gaertler ,  Divyasheel Sharma ,  Chandrika K R ,  Matthias Berning

IPC: G05B13/02 ,  G05B23/02

CPC classification number: G05B13/0265 ,  G05B23/0216 ,  G05B2223/02

Abstract: A method for providing a solution strategy for a current event in industrial process automation includes monitoring a process for events and recording manual user action data, upon occurrence of an event, acquiring the recorded data regarding manual user actions before, during, and after the occurrence of the event, learning a procedure for handling the event based on the acquired data, and applying the learnt procedure to a currently occurring event.

公开(公告)号：US20230237284A1

公开(公告)日：2023-07-27

申请号：US18193809

申请日：2023-03-31

Applicant: ABB Schweiz AG

Inventor： Benedikt Schmidt ,  Marco Gaertler ,  Sylvia Maczey ,  Pablo Rodriguez ,  Benjamin Kloepper ,  Arzam Muzaffar Kotriwala ,  Nuo Li

IPC: G06F40/58 ,  G06F40/30 ,  H04L67/50

CPC classification number: G06F40/58 ,  G06F40/30 ,  H04L67/535

Abstract: A method for controlling a virtual assistant for an industrial plant includes receiving by an input interface an information request, wherein the information request comprises at least one request for receiving information about at least part of the industrial plant; determining by a control unit a model specification using the received information request; determining by a model manager a machine learning model using the model specification; and providing by the control unit a response to the information request using the determined machine learning model.

公开(公告)号：US20230023896A1

公开(公告)日：2023-01-26

申请号：US17957592

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: G05B19/418 ,  G06N20/00

Abstract: A method of transfer learning for a specific production process of an industrial plant includes providing data templates defining expected data for a production process, and providing plant data, wherein the data templates define groupings for the expected data according to their relation in the industrial plant; determining a process instance and defining a mapping with the plant data; determining historic process data; determining training data using the determined process instance and the determined historic process data, wherein the training data comprises a structured data matrix, wherein columns of the data matrix represent the sensor data that are grouped in accordance with the data template and wherein rows of the data matrix represent timestamps of obtaining the sensor data; providing a pre-trained machine learning model using the determined process instance; and training a new machine learning model using the provided pre-trained model and the determined training data.

公开(公告)号：US20220035810A1

公开(公告)日：2022-02-03

申请号：US17500972

申请日：2021-10-14

Applicant: ABB SCHWEIZ AG

Inventor： Benedikt Schmidt ,  Martin Hollender ,  Sylvia Maczey

IPC: G06F16/2458 ,  G06F16/2455 ,  G06F16/23 ,  G05B19/418

Abstract: A control module is adapted to control technical equipment by processing batch-run data from the technical equipment. The control module operates according to parameters that are obtained by a parameter module. The module receives a reference plurality of multi-variate reference time series with data values from sources that are related to the equipment. There are time series with measurement values and time series with data that describes particular manufacturing operations during a batch-run time interval. The module splits the time interval into phases by determining transitions between the particular manufacturing operations, and divides the time series into particular phase-specific partial series. For each phase separately, and for the phase-specific partial series in combination, the module differentiates phase-specific time series into relevant partial time series or non-relevant partial time series and set the parameters accordingly.

公开(公告)号：US20210396584A1

公开(公告)日：2021-12-23

申请号：US17467295

申请日：2021-09-06

Applicant: ABB Schweiz AG

Inventor： Ralf Gitzel ,  Subanatarajan Subbiah ,  Benedikt Schmidt

IPC: G01J5/00 ,  G06N20/00 ,  G06N3/08 ,  G06T7/13

Abstract: An apparatus for monitoring a switchgear includes: an input unit; a processing unit; and an output unit. The input unit 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 infra-red images, the plurality of training infra-red images including a plurality of synthetic infra-red images generated from a corresponding plurality of visible images. The output unit outputs information relating to the one or more anomalous hot spots.