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公开(公告)号：US12105507B2
公开(公告)日：2024-10-01
申请号：US17463159
申请日：2021-08-31
发明人： Bijan Sayyarodsari , Kadir Liano , Wei Dai
IPC分类号： G05B23/02 , G05B19/418
CPC分类号： G05B23/0281 , G05B19/4183 , G05B19/4184 , G05B23/0218 , G05B23/0289 , G05B23/024 , G05B2219/37337
摘要： A computer-readable medium may include instructions that may cause a processor to perform operations that may include receiving audio data representative of sound waves generated by industrial devices and extracting features from the audio data. The features may be representative of a portion of the audio data. The operations may also include identifying a subset of the features based on distances between each of the plurality of features in an information space. The information space may include known clusters. The operations may then include determining that the subset of the features corresponds to an unknown cluster in the information space, performing a constrained classification operation based on each feature of the subset of the features to identify a new known cluster for the information space, and modifying operations of the industrial devices based on the new known cluster.
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公开(公告)号：US11604442B2
公开(公告)日：2023-03-14
申请号：US17358389
申请日：2021-06-25
摘要： System and method for improving operation of an industrial automation system, which includes a control system that controls operation of an industrial automation process. The control system includes a feature extraction block that determines extracted features by transforming process data determined during operation of an industrial automation process based at least in part on feature extraction parameters; a feature selection block that determines selected features by selecting a subset of the extracted features based at least in part on feature selection parameters, in which the selected features are expected to be representative of the operation of the industrial automation process; and a clustering block that determines a first expected operational state of the industrial automation system by mapping the selected features into a feature space based at least in part on feature selection parameters.
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公开(公告)号：US20230016084A1
公开(公告)日：2023-01-19
申请号：US17932113
申请日：2022-09-14
IPC分类号： G05B23/02 , G05B19/418
摘要： A method for operating an industrial automation system may involve receiving, via a first module of a plurality of modules in a control system, an indication that an error between a measurement associated with a target variable that corresponds with at least a portion of the industrial automation system and a modeled value for the target variable. The method may then involve determining, via the first module, whether the error is within a first range of values and retraining a model used to generate the modeled value for the target variable based on a portion of a plurality of sets of data points acquired via a plurality of sensors disposed in the industrial automation system in response to the error being within the first range of values.
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公开(公告)号：US11449047B2
公开(公告)日：2022-09-20
申请号：US16146681
申请日：2018-09-28
IPC分类号： G05B23/02 , G05B19/418
摘要： A method for operating an industrial automation system may involve receiving, via a first module of a plurality of modules in a control system, an indication that an error between a measurement associated with a target variable that corresponds with at least a portion of the industrial automation system and a modeled value for the target variable. The method may then involve determining, via the first module, whether the error is within a first range of values and retraining a model used to generate the modeled value for the target variable based on a portion of a plurality of sets of data points acquired via a plurality of sensors disposed in the industrial automation system in response to the error being within the first range of values.
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公开(公告)号：US20210390160A1
公开(公告)日：2021-12-16
申请号：US17462102
申请日：2021-08-31
摘要： An analytics engine is provided for industrial automation applications. The engine may be modular, and may be instantiated upon receipt of a data structure, such as containing annotated data from or relating to a monitored and/or controlled machine or process. The module may be data-driven so that it is instantiated only as needed, upon receipt of the input data structure. The module then carries out analysis on the data, and outputs a data structure that can be used for further analysis, or directly by other modules for modeling, classification, optimization and/or control.
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公开(公告)号：US11169494B2
公开(公告)日：2021-11-09
申请号：US14659003
申请日：2015-03-16
摘要： System and method for modeling a nonlinear process. A combined model for predictive optimization or control of a nonlinear process includes a nonlinear approximator, coupled to a parameterized dynamic or static model, operable to model the nonlinear process. The nonlinear approximator receives process inputs, and generates parameters for the parameterized dynamic model. The parameterized dynamic model receives the parameters and process inputs, and generates predicted process outputs based on the parameters and process inputs, where the predicted process outputs are useable to analyze and/or control the nonlinear process. The combined model may be trained in an integrated manner, e.g., substantially concurrently, by identifying process inputs and outputs (I/O), collecting data for process I/O, determining constraints on model behavior from prior knowledge, formulating an optimization problem, executing an optimization algorithm to determine model parameters subject to the determined constraints, and verifying the compliance of the model with the constraints.
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公开(公告)号：US10528038B2
公开(公告)日：2020-01-07
申请号：US14995977
申请日：2016-01-14
发明人： Bijan Sayyarrodsari , Celso Axelrud , Kadir Liano
IPC分类号： G05B19/00 , G05B19/418 , G05B13/04 , G06F8/30 , G06F17/13
摘要： In one embodiment, a model predictive control system for an industrial process includes a processor to execute an optimization module to determine manipulated variables for the process over a control horizon based on simulations performed using an objective function with an optimized process model and to control the process using the manipulated variables, to execute model modules including mathematical representations of a response or parameters of the process. The implementation details of the model modules are hidden from and inaccessible to the optimization module. The processor executes unified access modules (UAM). A first UAM interfaces between a first subset of the model modules and the optimization module and adapts output of the first subset for the optimization module, and a second UAM interfaces between a second subset of the model modules and the first subset and adapts output of the second subset for the first subset.
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公开(公告)号：US20190102360A1
公开(公告)日：2019-04-04
申请号：US15720582
申请日：2017-09-29
摘要： An analytics engine is provided for industrial automation applications. The engine may be modular, and may be instantiated upon receipt of a data structure, such as containing annotated data from or relating to a monitored and/or controlled machine or process. The module may be data-driven so that it is instantiated only as needed, upon receipt of the input data structure. The module then carries out analysis on the data, and outputs a data structure that can be used for further analysis, or directly by other modules for modeling, classification, optimization and/or control.
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公开(公告)号：US11762371B1
公开(公告)日：2023-09-19
申请号：US17734670
申请日：2022-05-02
发明人： Bijan SayyarRodsari , Jakob Methfessel , Kadir Liano , Hanyu Shi , Dongzuo Tian
IPC分类号： G05B19/4155
CPC分类号： G05B19/4155 , G05B2219/31368
摘要： A non-transitory computer-readable medium comprising computer-executable instructions that, when executed, cause a processor to perform operations including receiving a first dataset from a first automation component, the first dataset corresponds to raw data acquired by a first sensor; receiving a second dataset from a second automation component, the second dataset corresponds to raw data acquired by a second sensor; receiving data indicating an expected operation related to operations of an industrial automation system including the first and second automation components; determining a signature based on the first and second datasets and the data indicating the expected operation, wherein the signature indicates an unexpected operation as compared to the expected operation; performing a root cause analysis using the signature to determine a relationship indicating a first set of changes of the first dataset corresponding to a second set of changes in the data indicating the expected operation.
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公开(公告)号：US11662719B2
公开(公告)日：2023-05-30
申请号：US15720692
申请日：2017-09-29
CPC分类号： G05B23/0281 , G06F18/23 , G06F18/24137 , G06F17/11 , G06F17/13
摘要： A modular analysis engine provided classification of variables and data in an industrial automation environment. The module may be instantiated upon receipt of an input data structure, such as containing annotated data for any desired variables related to the machine or process monitored and/or controlled. The data may be provided in a batch or the engine may operate on streaming data. The output of the module may be a data structure that can be used by other modules, such as for modeling, optimization, and control. The classification may allow for insightful analysis, such as for textual classification of alarms provided in the automation setting.
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