Patents by Inventor Zhanpan Zhang
Zhanpan Zhang 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: 20230317293Abstract: A method for determining a recurrence of a disease in a patient is presented. The method includes generating a plurality of medical images of an organ of the patient and determining a plurality of recurrence probabilities from the plurality of medical images. A recurrence of the disease is determined based on the plurality of recurrence probabilities and clinicopathological data of the patient using a Bayesian network.Type: ApplicationFiled: March 31, 2022Publication date: October 5, 2023Inventors: Sanghee Cho, Zhanpan Zhang, Soumya Ghose, Fiona Ginty, Cynthia Elizabeth Landberg Davis, Jhimli Mitra, Sunil S. Badve, Yesim Gokmen-Polar
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Publication number: 20230309836Abstract: A method for determining a recurrence of a disease in a patient is presented. The method includes generating a plurality of medical images of an organ of the patient and determining a plurality of recurrence probabilities from the plurality of medical images. A recurrence of the disease is determined based on the plurality of recurrence probabilities and clinicopathological data of the patient using a Bayesian network.Type: ApplicationFiled: November 7, 2022Publication date: October 5, 2023Applicant: The Trustees of Indiana UniversityInventors: Souyma Ghose, Zhanpan Zhang, Sanghee Cho, Fiona Ginty, Cynthia Elizabeth Landberg Davis, Jhimli Mitra, Sunil S. Badve, Yesim Gokmen-Polar, Elizabeth Mary McDonough
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Patent number: 11728654Abstract: A system and method are provided for operating a power generating asset. Accordingly, at least one external data set indicative of a plurality of variables affecting the performance of the power generating asset is received by the controller. The controller also receives at least one operational data set indicative of the performance of the power generating asset. A plurality of production-assessment models for the power generating asset are generated and trained based on the data sets. A performance prediction is then generated for each of a plurality of model-variable combinations and a control action is implemented based on one of the performance predictions.Type: GrantFiled: March 19, 2021Date of Patent: August 15, 2023Assignee: General Electric Renovables Espana, S.L.Inventors: Zhanpan Zhang, Scott Charles Evans, Peter Alan Gregg, Matthew David Pepple, Manuel Rodolfo Valdez, David William Eldridge, Ricardo Zetina Benignos, Andrew T. Ferree
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Publication number: 20220302705Abstract: A system and method are provided for operating a power generating asset. Accordingly, at least one external data set indicative of a plurality of variables affecting the performance of the power generating asset is received by the controller. The controller also receives at least one operational data set indicative of the performance of the power generating asset. A plurality of production-assessment models for the power generating asset are generated and trained based on the data sets. A performance prediction is then generated for each of a plurality of model-variable combinations and a control action is implemented based on one of the performance predictions.Type: ApplicationFiled: March 19, 2021Publication date: September 22, 2022Inventors: Zhanpan Zhang, Scott Charles Evans, Peter Alan Gregg, Matthew David Pepple, Manuel Rodolfo Valdez, David William Eldridge, Ricardo Zetina Benignos, Andrew T. Ferree
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Publication number: 20220292666Abstract: A system and method including receiving historical time series sensor data associated with operation of an industrial asset; generating visual representation images of scatter plots based on the historical time series sensor data based on a reference to a digitized knowledge domain associated with the industrial asset; assigning a root cause label to each image; generating a convolutional neural network (CNN) model trained and tested using subsets of the labeled images; and processing, by the CNN model, a real-time image to detect at least one anomaly in the real-time image and one or more root causes associated with the at least one anomaly.Type: ApplicationFiled: August 27, 2020Publication date: September 15, 2022Inventors: Zhanpan ZHANG, Guangliang ZHAO, Jin XIA, John MIHOK, Peter Alan GREGG, Bouchra BOUQATA
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Patent number: 11378063Abstract: A method of correcting turbine underperformance includes calculating a power production curve using monitored data, detecting changes between the monitored data and a baseline power production curve, generating operability curves for paired operational variables from the monitored data, detecting changes between the operability curves and corresponding baseline operability curves, comparing the changes to a respective predetermined metric, and if the change exceeds the metric, providing feedback to a turbine control system identifying at least one of the paired operational variables for each paired variable in excess of the metric. A system and a non-transitory computer-readable medium are also disclosed.Type: GrantFiled: February 21, 2020Date of Patent: July 5, 2022Assignee: General Electric CompanyInventors: Zhanpan Zhang, Peter Alan Gregg, Jin Xia, John Mihok, Guangliang Zhao, Bouchra Bouqata
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Patent number: 11334834Abstract: The system and method described herein relate to production of power from the wind farm that incorporate tunable power production forecasts for optimal wind farm performance, where the wind farm power production is controlled at least in part by the power production forecasts. The system and method use a tunable power forecasting model to generate tunable coefficients based on asymmetric loss function applied on actual power production data, along with tuning factor(s) that tune forecast towards under forecasting or over forecasting. The power production forecasts are generated using the tunable coefficients 34 and power characteristic features that are derived from actual power production data. The power production forecasts are monitored for any degradation, and a control action to regenerate the coefficients or retune the model is undertaken if degradation is observed.Type: GrantFiled: May 22, 2017Date of Patent: May 17, 2022Assignee: General Electric CompanyInventors: Subhankar Ghosh, Abhirup Mondal, Necip Doganaksoy, Hongyan Liu, Zhanpan Zhang, Robert August Kaucic, Jay Zhiqiang Cao
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Publication number: 20220099532Abstract: A system and method are provided for operating a power generating asset. Accordingly, a plurality of operational data sets are received by a controller. The operational data sets include at least one indication of a performance anomaly. A plurality of predictive models are implemented by the controller to determine a plurality of potential root causes of the performance anomaly and a plurality of corresponding probabilities for each of the potential root causes. A consolidation model is generated for classifying the plurality of potential root causes and corresponding probabilities. The consolidation model is trained via a training data set to correlate the plurality of potential root causes to an actual root cause for the performance anomaly. The consolidation model is implemented by the controller to determine the actual root cause of the performance anomaly based on the plurality of potential root causes and corresponding probabilities.Type: ApplicationFiled: September 25, 2020Publication date: March 31, 2022Inventors: Zhanpan Zhang, Guangliang Zhao, Jin Xia, John Joseph Mihok, Frank William Ripple, JR., Kyle Raymond Barden, Alvaro Enrique Gil
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Patent number: 11242842Abstract: The present disclosure is directed to a system and method for forecasting a farm-level power output of a wind farm having a plurality of wind turbines. The method includes collecting actual operational data and/or site information for the wind farm. The method also includes predicting operational data for the wind farm for a future time period. Further, the method includes generating a model-based power output forecast based on the actual operational data, the predicted operational data, and/or the site information. In addition, the method includes measuring real-time operational data from the wind farm and adjusting the power output forecast based on the measured real-time operational data. Thus, the method also includes forecasting the farm-level power output of the wind farm based on the adjusted power output forecast.Type: GrantFiled: May 19, 2017Date of Patent: February 8, 2022Assignee: General Electric CompanyInventors: Robert August Kaucic, Zhanpan Zhang, Subhankar Ghosh, Hongyan Liu, Necip Doganaksoy
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Publication number: 20210262446Abstract: A method of correcting turbine underperformance includes calculating a power production curve using monitored data, detecting changes between the monitored data and a baseline power production curve, generating operability curves for paired operational variables from the monitored data, detecting changes between the operability curves and corresponding baseline operability curves, comparing the changes to a respective predetermined metric, and if the change exceeds the metric, providing feedback to a turbine control system identifying at least one of the paired operational variables for each paired variable in excess of the metric. A system and a non-transitory computer-readable medium are also disclosed.Type: ApplicationFiled: February 21, 2020Publication date: August 26, 2021Inventors: Zhanpan ZHANG, Peter Alan GREGG, Jin XIA, John MIHOK, Guangliang ZHAO, Bouchra BOUQATA
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Patent number: 10487804Abstract: The present disclosure is directed to systems and methods for validating wind farm performance improvements so as to optimize wind farm performance. In one embodiment, the method includes operating, via a controller, the wind farm in a first operating mode. Another step includes collecting a first set of operating data, via a processor, during the first operating mode. A further step includes operating, via the controller, the wind farm in a second operating mode. The method also includes collecting a second set of operating data, via the processor, during the second operating mode. Next, the method includes normalizing the first and second sets of operating data based on wind speed distributions. As such, another step includes comparing, via the processor, the normalized first and second sets of operating data so as to validate one or more wind farm performance measurements.Type: GrantFiled: March 11, 2015Date of Patent: November 26, 2019Assignee: General Electric CompanyInventors: Scott Charles Evans, Zhanpan Zhang, Peter Alan Gregg, Kevin Wayne Kinzie, William Arthur Flodder, Mark Nicolaas Jonkhof, Megan Michela Wilson
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Publication number: 20190203696Abstract: The present disclosure is directed to a system and method for forecasting a farm-level power output of a wind farm having a plurality of wind turbines. The method includes collecting actual operational data and/or site information for the wind farm. The method also includes predicting operational data for the wind farm for a future time period. Further, the method includes generating a model-based power output forecast based on the actual operational data, the predicted operational data, and/or the site information. In addition, the method includes measuring real-time operational data from the wind farm and adjusting the power output forecast based on the measured real-time operational data. Thus, the method also includes forecasting the farm-level power output of the wind farm based on the adjusted power output forecast.Type: ApplicationFiled: May 19, 2017Publication date: July 4, 2019Applicant: General Electric CompanyInventors: Robert August KAUCIC, Zhanpan ZHANG, Subhankar GHOSH, Hongyan LIU, Necip DOGANAKSOY
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Publication number: 20170337495Abstract: The system and method described herein relate to production of power from the wind farm that incorporate tunable power production forecasts for optimal wind farm performance, where the wind farm power production is controlled at least in part by the power production forecasts. The system and method use a tunable power forecasting model to generate tunable coefficients based on asymmetric loss function applied on actual power production data, along with tuning factor(s) that tune forecast towards under forecasting or over forecasting. The power production forecasts are generated using the tunable coefficients 34 and power characteristic features that are derived from actual power production data. The power production forecasts are monitored for any degradation, and a control action to regenerate the coefficients or retune the model is undertaken if degradation is observed.Type: ApplicationFiled: May 22, 2017Publication date: November 23, 2017Inventors: Subhankar GHOSH, Abhirup MONDAL, Necip DOGANAKSOY, Hongyan LIU, Zhanpan ZHANG, Robert August KAUCIC, Jay Zhiqiang CAO
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Patent number: 9644612Abstract: The present disclosure is directed to systems and methods for validating and/or identifying wind farm performance measurements so as to optimize wind farm performance. The method includes measuring operating data from one or more wind turbines of the farm. Another step includes generating a plurality of baseline models of performance of the wind farm from at least a portion of the operating data. Thus, each of the baseline models of performance is developed from a different portion of operating data so as to provide comparable models. The method also includes selecting an optimal baseline model and comparing the optimal baseline model with actual performance of the wind farm. In a particular embodiment, the actual performance of the wind farm is determined after one or more wind turbines of the wind farm is modified by one or more upgrades.Type: GrantFiled: September 23, 2014Date of Patent: May 9, 2017Assignee: General Electric CompanyInventors: Scott Charles Evans, Zhanpan Zhang, Peter Alan Gregg, Satish G. Iyengar
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Publication number: 20160265513Abstract: The present disclosure is directed to systems and methods for validating wind farm performance improvements so as to optimize wind farm performance. In one embodiment, the method includes operating, via a controller, the wind farm in a first operating mode. Another step includes collecting a first set of operating data, via a processor, during the first operating mode. A further step includes operating, via the controller, the wind farm in a second operating mode. The method also includes collecting a second set of operating data, via the processor, during the second operating mode. Next, the method includes normalizing the first and second sets of operating data based on wind speed distributions. As such, another step includes comparing, via the processor, the normalized first and second sets of operating data so as to validate one or more wind farm performance measurements.Type: ApplicationFiled: March 11, 2015Publication date: September 15, 2016Inventors: Scott Charles Evans, Zhanpan Zhang, Peter Alan Gregg, Kevin Wayne Kinzie, William Arthur Flodder, Mark Nicolaas Jonkhof, Megan Michela Wilson
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Publication number: 20160147816Abstract: According to some embodiments, a system includes a communication device operative to communicate with a user to receive a data set including a plurality of samples at a clustering module; a clustering module to receive the data set, store the data set, and calculate one or more clusters of samples using a clustering strategy; an optimization module to receive and store the one or more clusters of samples from the clustering module and generate one or more samples from the one or more clusters of samples using an optimization strategy; a memory for storing program instructions; at least one sample selection platform processor, coupled to the memory, and in communication with the clustering module and the optimization module and operative to execute program instructions to: calculate one or more clusters of samples based on the clustering strategy by executing the clustering module; analyze the data associated with the one or more clusters received from the clustering module using the optimization strategy assoType: ApplicationFiled: November 21, 2014Publication date: May 26, 2016Inventors: Jerrold Allen Cline, Kete Long, Rui XU, Zhanpan Zhang
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Publication number: 20160084233Abstract: The present disclosure is directed to systems and methods for validating and/or identifying wind farm performance measurements so as to optimize wind farm performance. The method includes measuring operating data from one or more wind turbines of the farm. Another step includes generating a plurality of baseline models of performance of the wind farm from at least a portion of the operating data. Thus, each of the baseline models of performance is developed from a different portion of operating data so as to provide comparable models. The method also includes selecting an optimal baseline model and comparing the optimal baseline model with actual performance of the wind farm. In a particular embodiment, the actual performance of the wind farm is determined after one or more wind turbines of the wind farm is modified by one or more upgrades.Type: ApplicationFiled: September 23, 2014Publication date: March 24, 2016Inventors: Scott Charles Evans, Zhanpan Zhang, Peter Alan Gregg, Satish G. Iyengar