Device control using processed sensor data corresponding to unexpected operations

    公开(公告)号:US11762371B1

    公开(公告)日:2023-09-19

    申请号:US17734670

    申请日:2022-05-02

    CPC classification number: G05B19/4155 G05B2219/31368

    Abstract: 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.

    Systems and methods for variable processing of streamed sensor data

    公开(公告)号:US11709482B2

    公开(公告)日:2023-07-25

    申请号:US17410579

    申请日:2021-08-24

    CPC classification number: G05B19/4185 G05B19/4183 G05B19/4188

    Abstract: A system may include sensor device comprising a sensor configured to measure sensor data indicating an operational parameter of industrial automation equipment associated with an industrial automation process. The system may also include communication circuitry configured to transmit the sensor data. Additionally, the system includes a processor configured to receive the sensor data. Further, the system includes a non-transitory computer-readable medium comprising computer-executable instructions that, when executed, are configured to cause the processor to perform operations including identifying an operational state of the industrial automation equipment based on the sensor data. The operations may also include determining a discrepancy between the sensor data and the operational state. Further, the operations may include modifying an operation of the processor from a first operational mode to a second operational mode of a plurality of operational based on the comparison.

    Systems and methods for controlling industrial devices based on modeled target variables

    公开(公告)号:US11609557B2

    公开(公告)日:2023-03-21

    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.

    SYSTEMS AND METHODS FOR VARIABLE PROCESSING OF STREAMED SENSOR DATA

    公开(公告)号:US20230069365A1

    公开(公告)日:2023-03-02

    申请号:US17410579

    申请日:2021-08-24

    Abstract: A system may include sensor device comprising a sensor configured to measure sensor data indicating an operational parameter of industrial automation equipment associated with an industrial automation process. The system may also include communication circuitry configured to transmit the sensor data. Additionally, the system includes a processor configured to receive the sensor data. Further, the system includes a non-transitory computer-readable medium comprising computer-executable instructions that, when executed, are configured to cause the processor to perform operations including identifying an operational state of the industrial automation equipment based on the sensor data. The operations may also include determining a discrepancy between the sensor data and the operational state. Further, the operations may include modifying an operation of the processor from a first operational mode to a second operational mode of a plurality of operational based on the comparison.

    Systems and methods for controlling industrial devices based on modeled target variables

    公开(公告)号:US10795347B2

    公开(公告)日:2020-10-06

    申请号:US16146664

    申请日:2018-09-28

    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.

    Systems and methods for variable processing of streamed sensor data

    公开(公告)号:US12292732B2

    公开(公告)日:2025-05-06

    申请号:US18352849

    申请日:2023-07-14

    Abstract: A system may include sensor device comprising a sensor configured to measure sensor data indicating an operational parameter of industrial automation equipment associated with an industrial automation process. The system may also include communication circuitry configured to transmit the sensor data. Additionally, the system includes a processor configured to receive the sensor data. Further, the system includes a non-transitory computer-readable medium comprising computer-executable instructions that, when executed, are configured to cause the processor to perform operations including identifying an operational state of the industrial automation equipment based on the sensor data. The operations may also include determining a discrepancy between the sensor data and the operational state. Further, the operations may include modifying an operation of the processor from a first operational mode to a second operational mode of a plurality of operational based on the comparison.

    INDUSTRIAL ARTIFICIAL INTELLIGENCE CONFIGURATION PARSING

    公开(公告)号:US20250044752A1

    公开(公告)日:2025-02-06

    申请号:US18363186

    申请日:2023-08-01

    Abstract: Various systems and methods are presented regarding monitoring and controlling operation of a process. A visual representation of the process can be created based on a supermodel comprising models (representing one or more devices) and nodes (representing respective device variables and constraints). Further, the process can be represented by levels, wherein devices at each level can be self-aware and have onboard artificial intelligence, such that a device at any level can auto-configure itself in accordance with a requirement placed upon it. Field-level devices (IFLDs) can be smart devices which auto-configure based upon a requirement from a higher-level device. Accordingly, system awareness can be incorporated across all levels of the process enabling overall and device-specific optimization of the process. IFLDs can auto-configure to collect and transmit data in accordance with an instruction from a higher-level device, leading to efficient data collection, reduced data bandwidth/processing, and expedited system optimization.

    INDUSTRIAL ARTIFICIAL INTELLIGENCE MODEL INTERDEPENDENCY LEARNING AND DEPLOYMENT

    公开(公告)号:US20250044746A1

    公开(公告)日:2025-02-06

    申请号:US18363133

    申请日:2023-08-01

    Abstract: Various systems and methods are presented regarding monitoring and controlling operation of a process. A visual representation of the process can be created based on a supermodel comprising models (representing one or more devices) and nodes (representing respective device variables and constraints). Further, the process can be represented by levels, wherein devices at each level can be self-aware and have onboard artificial intelligence, such that a device at any level can auto-configure itself in accordance with a requirement placed upon it. Field-level devices (IFLDs) can be smart devices which auto-configure based upon a requirement from a higher-level device. Accordingly, system awareness can be incorporated across all levels of the process enabling overall and device-specific optimization of the process. IFLDs can auto-configure to collect and transmit data in accordance with an instruction from a higher-level device, leading to efficient data collection, reduced data bandwidth/processing, and expedited system optimization.

    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.

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