Patents by Inventor Joshua Brian Kidd
Joshua Brian Kidd has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11886155Abstract: Distributed industrial process monitoring and analytics systems and methods are provided for operation within a process plant. A plurality of distributed data engines (DDEs) may be embedded within the process plant to collect and store data generated by data sources, such as process controllers. Thus, the data may be stored in a distributed manner in the DDEs embedded throughout the process plant. The DDEs may be connected by a data analytics network to facilitate data transmission by subscription or query. The DDEs may be configured as a plurality of clusters, which may further include local and centralized clusters. The local clusters may obtain streaming data from data sources and stream selected data to a data consumer. The centralized cluster may register the local clusters, receive data therefrom, and perform data analytic functions on the received data. The analyzed data may be further sent to a data consumer.Type: GrantFiled: May 11, 2020Date of Patent: January 30, 2024Assignee: FISHER-ROSEMOUNT SYSTEMS, INC.Inventors: Mark John Nixon, Alper Turhan Enver, Noel Howard Bell, Joshua Brian Kidd, Paul R. Muston
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Patent number: 10866952Abstract: Techniques for requesting and providing process plant data using a source-independent standardized query are provided. A requesting device generates a standardized query to obtain data from one or more data sources, such as relational or non-relational databases. The query utilizes a standardized format that does not depend upon the data source, which query may be generated as a JSON file. The standardized query may not be directly usable for any data sources. Instead, a data device generates one or more source-specific queries upon receipt of the standardized query. The source-specific queries utilize syntax native to each data source to obtain data. In some instances, the received data must be further processed to adjust for different sample times or sampling rates, such as by interpolation. The resulting data from all data sources may be aggregated into a data frame prior to being returned to the requesting device.Type: GrantFiled: September 23, 2016Date of Patent: December 15, 2020Assignee: FISHER-ROSEMOUNT SYSTEMS, INC.Inventors: Mark John Nixon, Alper Turhan Enver, Noel Howard Bell, Joshua Brian Kidd, Paul R. Muston
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Publication number: 20200272116Abstract: Distributed industrial process monitoring and analytics systems and methods are provided for operation within a process plant. A plurality of distributed data engines (DDEs) may be embedded within the process plant to collect and store data generated by data sources, such as process controllers. Thus, the data may be stored in a distributed manner in the DDEs embedded throughout the process plant. The DDEs may be connected by a data analytics network to facilitate data transmission by subscription or query. The DDEs may be configured as a plurality of clusters, which may further include local and centralized clusters. The local clusters may obtain streaming data from data sources and stream selected data to a data consumer. The centralized cluster may register the local clusters, receive data therefrom, and perform data analytic functions on the received data. The analyzed data may be further sent to a data consumer.Type: ApplicationFiled: May 11, 2020Publication date: August 27, 2020Inventors: Mark J. Nixon, Alper Turhan Enver, Noel Howard Bell, Joshua Brian Kidd, Paul R. Muston
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Patent number: 10678225Abstract: A data analytics service for performing data analytics functions within a distributed process control environment is provided. The service may provide a user interface for creating a first diagram, representing a data model. The first diagram may be configured, compiled, and evaluated using off-line (i.e., historical) data from a distributed process control system, which may include data stored in distributed data engines (DDEs). Following evaluation, the first diagram may be automatically converted into a second diagram that is bound to on-line (i.e., real-time) data sources within the process control environment, which may then be compiled and executed to generate performance or predictive analytics data for the process. The diagrams may comprise a plurality of configurable function blocks or modules, connected logically via wires conveying outputs or inputs of the blocks or modules.Type: GrantFiled: September 23, 2016Date of Patent: June 9, 2020Assignee: FISHER-ROSEMOUNT SYSTEMS, INC.Inventors: Joshua Brian Kidd, Mark John Nixon, Alper Turhan Enver, Noel Howard Bell, Paul R. Muston
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Patent number: 10649424Abstract: Distributed industrial process monitoring and analytics systems and methods are provided for operation within a process plant. A plurality of distributed data engines (DDEs) may be embedded within the process plant to collect and store data generated by data sources, such as process controllers. Thus, the data may be stored in a distributed manner in the DDEs embedded throughout the process plant. The DDEs may be connected by a data analytics network to facilitate data transmission by subscription or query. The DDEs may be configured as a plurality of clusters, which may further include local and centralized clusters. The local clusters may obtain streaming data from data sources and stream selected data to a data consumer. The centralized cluster may register the local clusters, receive data therefrom, and perform data analytic functions on the received data. The analyzed data may be further sent to a data consumer.Type: GrantFiled: September 23, 2016Date of Patent: May 12, 2020Assignee: FISHER-ROSEMOUNT SYSTEMS, INC.Inventors: Mark John Nixon, Alper Turhan Enver, Noel Howard Bell, Joshua Brian Kidd, Paul R. Muston
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Patent number: 10649449Abstract: A technique is provided for providing early fault detection using process control data generated by control devices in a process plant. The technique determines a leading indicator of a condition within the process plant, such as a fault, abnormality, or decrease in performance. The leading indicator may be determined using principal component analysis. A process signal indicating a process variable corresponding to the leading indicator is then obtained and analyzed. A rolling fast Fourier transform (FFT) may be performed on the process signal to generate time-series data with which to monitor the process plant. When the presence of the leading indicator is detected in the time-series data, an alert or other prediction of the condition may be generated. Thus, process faults may be identified using fluctuations and abnormalities as leading predictors.Type: GrantFiled: September 23, 2016Date of Patent: May 12, 2020Assignee: FISHER-ROSEMOUNT SYSTEMS, INC.Inventors: Noel Howard Bell, Mark John Nixon, Alper Turhan Enver, Joshua Brian Kidd, Paul R. Muston
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Publication number: 20190369607Abstract: A system for monitoring and analyzing data in a distributed process control system is provided. The system includes a user interface having a set of user controls for selecting and configuring data blocks to create a data diagram representing a data model. The data blocks are associated with data operations, such as data analytics functions, and may be configured by the user for particular instances of general blocks. The data blocks are interconnected by wires conveying outputs or inputs of the blocks, which may also connect data sources to the data blocks. The data sources may include on-line data (i.e., data streams) or off-line data (i.e., stored data) from the process control system. Additional user controls may be used to evaluate the data diagram or convert the data diagram from an off-line to an on-line version.Type: ApplicationFiled: August 19, 2019Publication date: December 5, 2019Inventors: Alper Turhan Enver, Mark John Nixon, Noel Howard Bell, Joshua Brian Kidd, Paul R. Muston
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Patent number: 10386827Abstract: A system for monitoring and analyzing data in a distributed process control system is provided. The system includes a user interface having a set of user controls for selecting and configuring data blocks to create a data diagram representing a data model. The data blocks are associated with data operations, such as data analytics functions, and may be configured by the user for particular instances of general blocks. The data blocks are interconnected by wires conveying outputs or inputs of the blocks, which may also connect data sources to the data blocks. The data sources may include on-line data (i.e., data streams) or off-line data (i.e., stored data) from the process control system. Additional user controls may be used to evaluate the data diagram or convert the data diagram from an off-line to an on-line version.Type: GrantFiled: September 23, 2016Date of Patent: August 20, 2019Assignee: FISHER-ROSEMOUNT SYSTEMS, INC.Inventors: Alper Turhan Enver, Mark John Nixon, Noel Howard Bell, Joshua Brian Kidd, Paul R. Muston
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Publication number: 20170102693Abstract: A data analytics service for performing data analytics functions within a distributed process control environment is provided. The service may provide a user interface for creating a first diagram, representing a data model. The first diagram may be configured, compiled, and evaluated using off-line (i.e., historical) data from a distributed process control system, which may include data stored in distributed data engines (DDEs). Following evaluation, the first diagram may be automatically converted into a second diagram that is bound to on-line (i.e., real-time) data sources within the process control environment, which may then be compiled and executed to generate performance or predictive analytics data for the process. The diagrams may comprise a plurality of configurable function blocks or modules, connected logically via wires conveying outputs or inputs of the blocks or modules.Type: ApplicationFiled: September 23, 2016Publication date: April 13, 2017Inventors: Joshua Brian Kidd, Mark John Nixon, Alper Turhan Enver, Noel Howard Bell, Paul R. Muston
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Publication number: 20170102696Abstract: A technique is provided for providing early fault detection using process control data generated by control devices in a process plant. The technique determines a leading indicator of a condition within the process plant, such as a fault, abnormality, or decrease in performance. The leading indicator may be determined using principal component analysis. A process signal indicating a process variable corresponding to the leading indicator is then obtained and analyzed. A rolling fast Fourier transform (FFT) may be performed on the process signal to generate time-series data with which to monitor the process plant. When the presence of the leading indicator is detected in the time-series data, an alert or other prediction of the condition may be generated. Thus, process faults may be identified using fluctuations and abnormalities as leading predictors.Type: ApplicationFiled: September 23, 2016Publication date: April 13, 2017Inventors: Noel Howard Bell, Mark John Nixon, Alper Turhan Enver, Joshua Brian Kidd, Paul R. Muston
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Publication number: 20170103103Abstract: Techniques for requesting and providing process plant data using a source-independent standardized query are provided. A requesting device generates a standardized query to obtain data from one or more data sources, such as relational or non-relational databases. The query utilizes a standardized format that does not depend upon the data source, which query may be generated as a JSON file. The standardized query may not be directly usable for any data sources. Instead, a data device generates one or more source-specific queries upon receipt of the standardized query. The source-specific queries utilize syntax native to each data source to obtain data. In some instances, the received data must be further processed to adjust for different sample times or sampling rates, such as by interpolation. The resulting data from all data sources may be aggregated into a data frame prior to being returned to the requesting device.Type: ApplicationFiled: September 23, 2016Publication date: April 13, 2017Inventors: Mark John Nixon, Alper Turhan Enver, Noel Howard Bell, Joshua Brian Kidd, Paul R. Muston
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Publication number: 20170102678Abstract: Distributed industrial process monitoring and analytics systems and methods are provided for operation within a process plant. A plurality of distributed data engines (DDEs) may be embedded within the process plant to collect and store data generated by data sources, such as process controllers. Thus, the data may be stored in a distributed manner in the DDEs embedded throughout the process plant. The DDEs may be connected by a data analytics network to facilitate data transmission by subscription or query. The DDEs may be configured as a plurality of clusters, which may further include local and centralized clusters. The local clusters may obtain streaming data from data sources and stream selected data to a data consumer. The centralized cluster may register the local clusters, receive data therefrom, and perform data analytic functions on the received data. The analyzed data may be further sent to a data consumer.Type: ApplicationFiled: September 23, 2016Publication date: April 13, 2017Inventors: Mark John Nixon, Alper Turhan Enver, Noel Howard Bell, Joshua Brian Kidd, Paul R. Muston
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Publication number: 20170102694Abstract: A system for monitoring and analyzing data in a distributed process control system is provided. The system includes a user interface having a set of user controls for selecting and configuring data blocks to create a data diagram representing a data model. The data blocks are associated with data operations, such as data analytics functions, and may be configured by the user for particular instances of general blocks. The data blocks are interconnected by wires conveying outputs or inputs of the blocks, which may also connect data sources to the data blocks. The data sources may include on-line data (i.e., data streams) or off-line data (i.e., stored data) from the process control system. Additional user controls may be used to evaluate the data diagram or convert the data diagram from an off-line to an on-line version.Type: ApplicationFiled: September 23, 2016Publication date: April 13, 2017Inventors: Alper Turhan Enver, Mark John Nixon, Noel Howard Bell, Joshua Brian Kidd, Paul R. Muston