Automated monitoring and control using updated streaming decision tree

    公开(公告)号:US12210326B2

    公开(公告)日:2025-01-28

    申请号:US18419161

    申请日:2024-01-22

    Abstract: A non-transitory computer-readable medium comprising computer-executable instructions that, when executed, are configured to cause a processor to perform operations that include receiving process input data associated with one or more automation devices, determining a plurality of operating conditions corresponding to the one or more automation devices; clustering the process input data based on the plurality of operating conditions, receiving a decision tree representative of the plurality of operating conditions and corresponding process input data, determining a splitting criterion for one or more nodes of the decision tree based on the clustered process input data, wherein the splitting criterion is configured to link the process input data to at least two operating conditions based on the decision tree, generating control logic for the one or more automation devices based on the decision tree and splitting criterion, and sending the control logic to the one or more automation devices.

    Computer vision model drawing interface

    公开(公告)号:US12205363B2

    公开(公告)日:2025-01-21

    申请号:US17817611

    申请日:2022-08-04

    Abstract: For updating a computer vision model, a method converts a user input drawing including a user annotation of a first image in a drawing format to a training format image in a training format for a computer vision model. The method generates a training-representation drawing from the training format image. The training-representation drawing includes an image inference for the first image. The method receives user feedback for the training-representation drawing in the drawing format. The method updates the computer vision model based on the user feedback. The method generates an image inference for a second image based on the updated computer vision model and generates model-health metrics, agreement-metrics, and a sortable image index to explain image inferences with respect to guided user annotation of the second image. The method caches partial results from the image-inferences to afford quicker updating of computer vision models, affording more iterative model-development than ad-hoc model-evaluation.

    Automated monitoring and control using augmented streaming decision tree

    公开(公告)号:US11886152B2

    公开(公告)日:2024-01-30

    申请号:US17374644

    申请日:2021-07-13

    CPC classification number: G05B13/042 G05B13/028 G05B13/048 G06N5/01

    Abstract: A non-transitory computer-readable medium comprising computer-executable instructions that, when executed, are configured to cause a processor to perform operations that include receiving operational parameters for one or more automation devices, wherein the one or more automation devices are configured to implement control logic generated based on a decision tree. The operations also include receiving an output by the decision tree based on the operational parameters. Further, the operations include determining the output is an anomalous output based on a constraint associated with the decision tree. Further still, the operations include generating an updated decision tree based on the anomalous output. Even further, the operations include generating updated control logic for the one or more automation devices based on the updated decision tree. Even further, the operations include sending the updated control logic to the one or more automation devices.

    AUTOMATED MONITORING DIAGNOSTIC USING AUGMENTED STREAMING DECISION TREE

    公开(公告)号:US20230013626A1

    公开(公告)日:2023-01-19

    申请号:US17374644

    申请日:2021-07-13

    Abstract: A non-transitory computer-readable medium comprising computer-executable instructions that, when executed, are configured to cause a processor to perform operations that include receiving operational parameters for one or more automation devices, wherein the one or more automation devices are configured to implement control logic generated based on a decision tree. The operations also include receiving an output by the decision tree based on the operational parameters. Further, the operations include determining the output is an anomalous output based on a constraint associated with the decision tree. Further still, the operations include generating an updated decision tree based on the anomalous output. Even further, the operations include generating updated control logic for the one or more automation devices based on the updated decision tree. Even further, the operations include sending the updated control logic to the one or more automation devices.

    SYSTEMS AND METHODS FOR LOCALLY MODELING A TARGET VARIABLE

    公开(公告)号:US20220171381A1

    公开(公告)日:2022-06-02

    申请号:US17650995

    申请日:2022-02-14

    Abstract: A method for operating an industrial automation system may include receiving, via a first module of a plurality of modules in a control system, a plurality of datasets via at least a portion of the plurality of modules. The plurality datasets may include raw values without context regarding the plurality datasets. The method may then include identifying a subset of the plurality of datasets that influences a value of a target variable by analyzing the data without regard to the context, modeling a behavior of the target variable over time based on the subset of the plurality of datasets, and adjusting one or more operations of an automation device based on the model.

    Systems and methods for locally modeling a target variable

    公开(公告)号:US11249469B2

    公开(公告)日:2022-02-15

    申请号:US16146647

    申请日:2018-09-28

    Abstract: A method for operating an industrial automation system may include receiving, via a first module of a plurality of modules in a control system, a plurality of datasets via at least a portion of the plurality of modules. The plurality datasets may include raw values without context regarding the plurality datasets. The method may then include identifying a subset of the plurality of datasets that influences a value of a target variable by analyzing the data without regard to the context, modeling a behavior of the target variable over time based on the subset of the plurality of datasets, and adjusting one or more operations of an automation device based on the model.

    Predictive monitoring and diagnostics systems and methods

    公开(公告)号:US11079726B2

    公开(公告)日:2021-08-03

    申请号:US16666011

    申请日:2019-10-28

    Abstract: 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.

    SYSTEMS AND METHODS FOR CONTROLLING INDUSTRIAL DEVICES BASED ON MODELED TARGET VARIABLES

    公开(公告)号:US20210011467A1

    公开(公告)日:2021-01-14

    申请号:US17039347

    申请日:2020-09-30

    Abstract: An industrial automation system may include an automation device and a control system communicatively coupled to the automation device. The control system may include a first module of a number of modules, such that the first module may receive an indication of a target variable associated with the industrial automation device. The first module may then receive parameters associated with the target variable, identify a portion of data points associated with controlling the target variable with respect to the parameters, generate a model of each data point of the portion over time with respect to the parameters based on the data points, determine functions associated with the model. The functions represent one or more relationships between the each data point of the portion with respect to controlling the target variable. The first module may then adjust one or more operations of the automation device based on the functions.

Patent Agency Ranking