公开(公告)号：US20250138509A1

公开(公告)日：2025-05-01

申请号：US18926585

申请日：2024-10-25

Applicant: ABB Schweiz AG

Inventor： Nicolai Schoch ,  Benedikt Schmidt ,  Mario Hoernicke

IPC: G05B19/4155

Abstract: A computer-implemented method for providing an automated chat output with respect to an industrial plant environment includes obtaining a prompt input from a user; selecting at least one related industrial plant document from a provided document database of a plurality of industrial plant documents, wherein the at least one related industrial plant document is related to the obtained prompt input; determining an enhanced prompt using the obtained prompt input and the selected at least one related industrial plant document; and determining a chat output by inputting the enhanced prompt into a first large language model.

公开(公告)号：US20250130563A1

公开(公告)日：2025-04-24

申请号：US19007799

申请日：2025-01-02

Applicant: ABB Schweiz AG

Inventor： Taisuke Minagawa ,  Diego Vilacoba ,  Ido Amihai ,  Martin Wolfgang Hoffmann ,  Benjamin Kloepper ,  Benedikt Schmidt

IPC: G05B23/02

Abstract: A method for detecting an anomaly includes obtaining a time-series of historical process variables within a predefined time span; determining a cycle time of the historical process variables; clustering the historical process variables into clusters based on cycle time; arranging the clusters into a tree; storing the tree; obtaining a time-series of a plurality of current process variables, which correspond to the historic process variables; and detecting the anomaly of at least one device by identifying a cycle time of a current process variable that is longer than the cycle time of a corresponding historic variable.

公开(公告)号：US20250086514A1

公开(公告)日：2025-03-13

申请号：US18929807

申请日：2024-10-29

Applicant: ABB Schweiz AG

Inventor： Benjamin Kloepper ,  Dawid Ziobro ,  Divyasheel Sharma ,  Benedikt Schmidt ,  Yemao Man ,  Gayathri Gopalakrishnan ,  Joakim Astrom ,  Marcel Dix ,  Arzam Muzaffar Kotriwala

IPC: G06N20/00

Abstract: A method for deciding on a machine learning model result quality based on the identification of distractive samples in the training data includes providing a first result of the model based on initial training data; determining a first performance of the first result of the model; logging input data; providing a second result of the model based on initial training data and the input data, determining a second performance of the second result of the model and thereon based identifying erroneous data within the input data and/or the training data.

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.