Patents by Inventor Gabor Solymosi
Gabor Solymosi 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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Publication number: 20230418998Abstract: An example method utilizing different pipelines of a prediction system, comprises receiving event and alarm data from event logs, failure data, and asset data from SCADA system(s), retrieve patterns of events, receiving historical sensor data from sensors of components of wind turbines, training a set of models to predict faults for each component using the patterns of events and historical sensor data, each model of a set having different observation time windows and lead time windows, evaluating each model of a set using standardized metrics, comparing evaluations of each model of a set to select a model with preferred lead time and accuracy, receive current sensor data from the sensors of the components, apply the selected model(s) to the current sensor data to generate a component failure prediction, compare the component failure prediction to a threshold, and generate an alert and report based on the comparison to the threshold.Type: ApplicationFiled: September 11, 2023Publication date: December 28, 2023Applicant: Utopus Insights, Inc.Inventors: Yajuan Wang, Gabor Solymosi, Ede Szarka, Younghun Kim
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Patent number: 11803676Abstract: An example method utilizing different pipelines of a prediction system, comprises receiving event and alarm data from event logs, failure data, and asset data from SCADA system(s), retrieve patterns of events, receiving historical sensor data from sensors of components of wind turbines, training a set of models to predict faults for each component using the patterns of events and historical sensor data, each model of a set having different observation time windows and lead time windows, evaluating each model of a set using standardized metrics, comparing evaluations of each model of a set to select a model with preferred lead time and accuracy, receive current sensor data from the sensors of the components, apply the selected model(s) to the current sensor data to generate a component failure prediction, compare the component failure prediction to a threshold, and generate an alert and report based on the comparison to the threshold.Type: GrantFiled: March 23, 2021Date of Patent: October 31, 2023Assignee: Utopus Insights, Inc.Inventors: Yajuan Wang, Gabor Solymosi, Ede Szarka, Younghun Kim
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Publication number: 20230342521Abstract: An example method comprises receiving historical sensor data from sensors of components of wind turbines, training a set of models to predict faults for each component using the historical sensor data, each model of a set having different observation time windows and lead time windows, evaluating each model of a set using standardized metrics, comparing evaluations of each model of a set to select a model with preferred lead time and accuracy, receive current sensor data from the sensors of the components, apply the selected model(s) to the current sensor data to generate a component failure prediction, compare the component failure prediction to a threshold, and generate an alert and report based on the comparison to the threshold.Type: ApplicationFiled: July 5, 2023Publication date: October 26, 2023Applicant: Utopus Insights, Inc.Inventors: Yajuan Wang, Gabor Solymosi, Younghun Kim
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Patent number: 11734474Abstract: An example method comprises receiving historical sensor data from sensors of components of wind turbines, training a set of models to predict faults for each component using the historical sensor data, each model of a set having different observation time windows and lead time windows, evaluating each model of a set using standardized metrics, comparing evaluations of each model of a set to select a model with preferred lead time and accuracy, receive current sensor data from the sensors of the components, apply the selected model(s) to the current sensor data to generate a component failure prediction, compare the component failure prediction to a threshold, and generate an alert and report based on the comparison to the threshold.Type: GrantFiled: March 31, 2021Date of Patent: August 22, 2023Assignee: Utopus Insights, Inc.Inventors: Yajuan Wang, Gabor Solymosi, Younghun Kim
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Publication number: 20210232731Abstract: An example method utilizing different pipelines of a prediction system, comprises receiving event and alarm data from event logs, failure data, and asset data from SCADA system(s), retrieve patterns of events, receiving historical sensor data from sensors of components of wind turbines, training a set of models to predict faults for each component using the patterns of events and historical sensor data, each model of a set having different observation time windows and lead time windows, evaluating each model of a set using standardized metrics, comparing evaluations of each model of a set to select a model with preferred lead time and accuracy, receive current sensor data from the sensors of the components, apply the selected model(s) to the current sensor data to generate a component failure prediction, compare the component failure prediction to a threshold, and generate an alert and report based on the comparison to the threshold.Type: ApplicationFiled: March 23, 2021Publication date: July 29, 2021Applicant: Utopus Insights, Inc.Inventors: Yajuan Wang, Gabor Solymosi, Ede Szarka, Younghun Kim
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Publication number: 20210216682Abstract: An example method comprises receiving historical sensor data from sensors of components of wind turbines, training a set of models to predict faults for each component using the historical sensor data, each model of a set having different observation time windows and lead time windows, evaluating each model of a set using standardized metrics, comparing evaluations of each model of a set to select a model with preferred lead time and accuracy, receive current sensor data from the sensors of the components, apply the selected model(s) to the current sensor data to generate a component failure prediction, compare the component failure prediction to a threshold, and generate an alert and report based on the comparison to the threshold.Type: ApplicationFiled: March 31, 2021Publication date: July 15, 2021Applicant: Utopus Insights, Inc.Inventors: Yajuan Wang, Gabor Solymosi, Younghun Kim
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Patent number: 10984154Abstract: An example method comprises receiving historical sensor data from sensors of components of wind turbines, training a set of models to predict faults for each component using the historical sensor data, each model of a set having different observation time windows and lead time windows, evaluating each model of a set using standardized metrics, comparing evaluations of each model of a set to select a model with preferred lead time and accuracy, receive current sensor data from the sensors of the components, apply the selected model(s) to the current sensor data to generate a component failure prediction, compare the component failure prediction to a threshold, and generate an alert and report based on the comparison to the threshold.Type: GrantFiled: December 27, 2018Date of Patent: April 20, 2021Assignee: Utopus Insights, Inc.Inventors: Yajuan Wang, Gabor Solymosi, Younghun Kim
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Patent number: 10956632Abstract: An example method utilizing different pipelines of a prediction system, comprises receiving event and alarm data from event logs, failure data, and asset data from Supervisory Control and Data Acquisition (SCADA) system(s), retrieving patterns of events, receiving historical sensor data from sensors of components of wind turbines, training a set of models to predict faults for each component using the patterns of events and historical sensor data, each model of a set having different observation time windows and lead time windows, evaluating each model of a set using standardized metrics, comparing evaluations of each model of a set to select a model with preferred lead time and accuracy, receiving current sensor data from the sensors of the components, applying the selected model(s) to the current sensor data to generate a component failure prediction, comparing the component failure prediction to a threshold, and generating an alert and report based on the comparison to the threshold.Type: GrantFiled: December 27, 2018Date of Patent: March 23, 2021Assignee: Utopus Insights, Inc.Inventors: Yajuan Wang, Gabor Solymosi, Ede Szarka, Younghun Kim
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Publication number: 20200210538Abstract: An example method utilizing different pipelines of a prediction system, comprises receiving event and alarm data from event logs, failure data, and asset data from SCADA system(s), retrieve patterns of events, receiving historical sensor data from sensors of components of wind turbines, training a set of models to predict faults for each component using the patterns of events and historical sensor data, each model of a set having different observation time windows and lead time windows, evaluating each model of a set using standardized metrics, comparing evaluations of each model of a set to select a model with preferred lead time and accuracy, receive current sensor data from the sensors of the components, apply the selected model(s) to the current sensor data to generate a component failure prediction, compare the component failure prediction to a threshold, and generate an alert and report based on the comparison to the threshold.Type: ApplicationFiled: December 27, 2018Publication date: July 2, 2020Applicant: Utopus Insights, Inc.Inventors: Yajuan Wang, Gabor Solymosi, Ede Szarka, Younghun Kim
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Publication number: 20200210537Abstract: An example method comprises receiving historical sensor data from sensors of components of wind turbines, training a set of models to predict faults for each component using the historical sensor data, each model of a set having different observation time windows and lead time windows, evaluating each model of a set using standardized metrics, comparing evaluations of each model of a set to select a model with preferred lead time and accuracy, receive current sensor data from the sensors of the components, apply the selected model(s) to the current sensor data to generate a component failure prediction, compare the component failure prediction to a threshold, and generate an alert and report based on the comparison to the threshold.Type: ApplicationFiled: December 27, 2018Publication date: July 2, 2020Applicant: Utopus Insights, Inc.Inventors: Yajuan Wang, Gabor Solymosi, Younghun Kim