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公开(公告)号：US11836636B2
公开(公告)日：2023-12-05
申请号：US16443914
申请日：2019-06-18
申请人： ABB Schweiz AG
发明人： Andrew Cohen , Marcel Dix
IPC分类号： G05B19/4155 , G05B23/02 , G06N5/02 , G06N7/01
CPC分类号： G06N5/02 , G05B19/4155 , G05B23/0254 , G06N7/01 , G05B2219/33139
摘要： Disclosed is a computer-implemented method for generating a prediction model. The model can be for use in processing machine event data to predict behavior of a plurality of industrial machines under supervision. The prediction model can be configured to determine current and future states of the industrial machines. The method can include: extracting event features from event codes and structuring the event features into feature vectors; and generating the prediction model by clustering the feature vectors into a plurality of vector clusters, the vector clusters being assigned to respective machine states. The prediction model can be constructed based on event data from a first industrial machine and be applied to control an operating state of a second industrial machine.
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公开(公告)号：US20210149385A1
公开(公告)日：2021-05-20
申请号：US17159177
申请日：2021-01-27
申请人： ABB Schweiz AG
发明人： Andrew Cohen , Martin Hollender , Nuo Li , Moncef Chioua , Matthieu Lucke
IPC分类号： G05B23/02 , G06F16/245 , G08B29/02
摘要： An apparatus for alarm information determination includes: an input unit; a processing unit; and an output unit. The input unit provides the processing unit with historical process control data, the process control data including a plurality of data signals, a plurality of alarm data, and data relating to an event of interest. The processing unit determines a plurality of correlation scores for the plurality of data signals paired with the plurality of alarm data, a correlation score being determined for a data signal paired with an alarm data, a high correlation score indicating a higher degree of correlation than a low correlation score. The processing unit identifies at least one first alarm data from the plurality of alarm data, the identification including utilization of the data relating to the event of interest.
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公开(公告)号：US20210209189A1
公开(公告)日：2021-07-08
申请号：US17207854
申请日：2021-03-22
申请人： ABB Schweiz AG
发明人： Moncef Chioua , Matthieu Lucke , Emanuel Kolb , Martin Hollender , Nuo Li , Andrew Cohen
摘要： A computer-implemented method for determining an abnormal technical status of a technical system includes: receiving, from the technical system, a plurality of signals, each signal being sampled over time and reflecting the technical status of at least one system component; computing, for each signal with associated high and low alarm thresholds obtained from an alarm management system, at every sampling time point, a univariate distance to its associated alarm thresholds as a maximum of the distances between a value of the respective signal and its associated alarm thresholds to quantify a degree of abnormality for the respective at least one system component; computing, at every sampling time point, based on the univariate distances at the respective sampling time points, an aggregate abnormality indicator reflecting the technical status of the technical system; and providing, to an operator, a comparison of the aggregate abnormality indicator with a predetermined abnormality threshold.
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公开(公告)号：US11069356B2
公开(公告)日：2021-07-20
申请号：US16988732
申请日：2020-08-10
申请人： ABB Schweiz AG
发明人： Andrew Cohen , Benedikt Schmidt , Benjamin Kloepper , Marco Gaertler , Arzam Kotriwala , Marcel Dix , Sylvia Maczey
IPC分类号： G10L15/22 , G10L15/30 , G05B19/042
摘要： A computer system for controlling a dialogue between a user and the computer system, the computer system being communicatively coupled with an industrial control system controlling an industrial system, the computer system including: an interface for receiving intent inputs representing a respective desired interaction with the computer system; an intent determination module for determining the desired interactions of received intent inputs; a data storage for storing one or more directed graphs, each graph specifying an industrial control domain specific dialogue, a particular graph defining a dialogue state machine with a plurality of nodes representing states of the dialogue, and with edges representing transitions between the states, each state transition from a first state to a second state depending on at least one precondition, the desired interaction of a received intent input corresponding to a target node to be reached from a current node of the particular graph.
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公开(公告)号：US20210166684A1
公开(公告)日：2021-06-03
申请号：US16988732
申请日：2020-08-10
申请人： ABB Schweiz AG
发明人： Andrew Cohen , Benedikt Schmidt , Benjamin Kloepper , Marco Gaertler , Arzam Kotriwala , Marcel Dix , Sylvia Maczey
IPC分类号： G10L15/22 , G10L15/30 , G05B19/042
摘要： A computer system for controlling a dialogue between a user and the computer system, the computer system being communicatively coupled with an industrial control system controlling an industrial system, the computer system including: an interface for receiving intent inputs representing a respective desired interaction with the computer system; an intent determination module for determining the desired interactions of received intent inputs; a data storage for storing one or more directed graphs, each graph specifying an industrial control domain specific dialogue, a particular graph defining a dialogue state machine with a plurality of nodes representing states of the dialogue, and with edges representing transitions between the states, each state transition from a first state to a second state depending on at least one precondition, the desired interaction of a received intent input corresponding to a target node to be reached from a current node of the particular graph.
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公开(公告)号：US12019432B2
公开(公告)日：2024-06-25
申请号：US17207854
申请日：2021-03-22
申请人： ABB Schweiz AG
发明人： Moncef Chioua , Matthieu Lucke , Emanuel Kolb , Martin Hollender , Nuo Li , Andrew Cohen
CPC分类号： G05B23/0213 , G06F17/15 , G06F17/18 , G06F18/22 , G06F2218/12
摘要： A computer-implemented method for determining an abnormal technical status of a technical system includes: receiving, from the technical system, a plurality of signals, each signal being sampled over time and reflecting the technical status of at least one system component; computing, for each signal with associated high and low alarm thresholds obtained from an alarm management system, at every sampling time point, a univariate distance to its associated alarm thresholds as a maximum of the distances between a value of the respective signal and its associated alarm thresholds to quantify a degree of abnormality for the respective at least one system component; computing, at every sampling time point, based on the univariate distances at the respective sampling time points, an aggregate abnormality indicator reflecting the technical status of the technical system; and providing, to an operator, a comparison of the aggregate abnormality indicator with a predetermined abnormality threshold.
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公开(公告)号：US20240062077A1
公开(公告)日：2024-02-22
申请号：US18498413
申请日：2023-10-31
申请人： ABB Schweiz AG
发明人： Andrew Cohen , Marcel Dix
IPC分类号： G06N5/02 , G05B19/4155 , G05B23/02 , G06N7/01
CPC分类号： G06N5/02 , G05B19/4155 , G05B23/0254 , G06N7/01 , G05B2219/33139
摘要： Disclosed is a method for generating a prediction model. The model can be used in processing machine event data to predict behavior of a plurality of industrial machines under supervision. The prediction model can be configured to determine current and future states of the industrial machines. The method can include extracting event features from event codes and structuring the event features into feature vectors. A first dimension of a first feature vector corresponds to a first event feature, and a second dimension of the first feature vector corresponds to a second event feature. The method can also include generating the prediction model by clustering the feature vectors into a plurality of vector clusters, the vector clusters assigned to respective machine states. The prediction model can be constructed based on event data from a first industrial machine and be applied to control an operating state of a second industrial machine.
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公开(公告)号：US20230050321A1
公开(公告)日：2023-02-16
申请号：US17977355
申请日：2022-10-31
申请人： ABB Schweiz AG
发明人： Benedikt Schmidt , Marcel Dix , Martin Hollender , Andrew Cohen , Arzam Muzaffar Kotriwala , Marco Gaertler , Sylvia Maczey , Benjamin Kloepper
IPC分类号： G05B19/042
摘要： A method for generating a process model modeling a manual mode procedure instance of a plant process includes providing log events of operational actions; selecting related sequences of manual mode operational actions from the log events; filtering the related sequences according to an individual plant section; identifying a sequential order from the filtered related sequences; determining statistical properties of values of related process variables and/or statistical properties of values of related set point changes to each sequential ordered manual mode operational action from the filtered related sequences; generating the process model of the manual mode procedure instance by arranging related manual mode operational actions with the sequential order of each operational action assigned with the statistical properties of the values of related process variables and/or assigned with the statistical properties of the values of the related set point changes.
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公开(公告)号：US20190311273A1
公开(公告)日：2019-10-10
申请号：US16443914
申请日：2019-06-18
申请人： ABB Schweiz AG
发明人： Andrew Cohen , Marcel Dix
IPC分类号： G06N5/02 , G06N7/00 , G05B19/4155
摘要： Disclosed is a computer-implemented method for generating a prediction model. The model can be for use in processing machine event data to predict behavior of a plurality of industrial machines under supervision. The prediction model can be configured to determine current and future states of the industrial machines. The method can include: extracting event features from event codes and structuring the event features into feature vectors; and generating the prediction model by clustering the feature vectors into a plurality of vector clusters, the vector clusters being assigned to respective machine states. The prediction model can be constructed based on event data from a first industrial machine and be applied to control an operating state of a second industrial machine.
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