Patents by Inventor Jee Hun Park

Jee Hun Park 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).

  • Patent number: 11182515
    Abstract: An apparatus and method for diagnosing analysis is provided. The apparatus includes an analytic layer to divide a peripheral space of a target component into a plurality of cells and to derive analytic data by performing a numerical analysis iteration according to computational fluid dynamics for the plurality of cells; a model layer to derive an analytic model that simulates the numerical analysis iteration; a predictive layer to derive predictive data by predicting a result of the numerical analysis iteration by using the analytic model; and a diagnostic layer to diagnose an abnormality condition of numerical analysis by comparing the analytic data and predictive data during the numerical analysis iteration performed by the analytic layer. The diagnostic layer includes an early alarm to generate early alarm information by sorting a cell satisfying an early alarm condition; and an abnormality diagnostic device to determine whether the numerical analysis iteration is abnormal.
    Type: Grant
    Filed: September 17, 2019
    Date of Patent: November 23, 2021
    Inventors: Jee Hun Park, Jae Hyeon Park, Sang Jin Lee, Hyun Sik Kim
  • Patent number: 11171332
    Abstract: The present invention relates to a method for producing silicon-based active material particles for a secondary battery and silicon-based active material particles. A method for producing silicon-based active material particles for a secondary battery according to an embodiment of the present invention may comprise: a step of providing silicon powder; a step of providing a pre-pulverization mixture in which the silicon powder is dispersed in a solvent for dispersion comprising an antioxidant; a step of applying mechanical compression and shear stress to the silicon powder of the pre-pulverization mixture to refine the silicon powder, thereby forming silicon particles having an oxygen content controlled by the antioxidant; and a step of drying the resulting material comprising the silicon particles to obtain silicon-based active material particles.
    Type: Grant
    Filed: August 23, 2017
    Date of Patent: November 9, 2021
    Assignee: Nexeon Ltd.
    Inventors: Seung Chul Park, Eui Joon Song, Min Young Cheong, Jong Hun Lee, Young Tai Cho, Yong Gil Choi, Seon Park, Sung Hwan Kang, Hee Young Seo, Jee Hye Park, Tae Jin Yang
  • Patent number: 11156131
    Abstract: The present disclosure relates to an exhaust gas cooling device and method, and more particularly, to a device and method for installing an exhaust gas cooling device on the upper end of a duct of a heat recovery steam generator to cheaply cool the exhaust gas without occupying an additional dedicated area. An object of the present disclosure is to reduce the costs using a cheap cooling device in the cooling path for cooling the exhaust gas. In one aspect, the exhaust gas cooling device includes an exhaust gas cooling unit located on the upper end of a duct of a heat recovery steam generator connected with a gas turbine and for cooling the exhaust gas discharged from the gas turbine; and a control unit for controlling the exhaust gas cooling unit to lower the increase rate of the energy of the exhaust gas flowed into the heat recovery steam generator through the duct.
    Type: Grant
    Filed: July 26, 2017
    Date of Patent: October 26, 2021
    Assignee: DOOSAN HEAVY INDUSTRIES & CONSTRUCTION CO., LTD.
    Inventors: Hyun Sik Kim, Jee Hun Park, Seung Gyun Cheong
  • Patent number: 11144046
    Abstract: A fault signal recovery apparatus and method for collecting signals obtained in a plant and recovering normal signals from fault signals contained in the measured signals through a machine learning method includes receiving an input X including only normal signals for a plurality of tags, an input U including fault signals for a first group of tags among the plurality of tags and normal signals for a second group of tags, and an input S having information on the first group of tags including fault signals, and estimating and recovering normal signals for the first group of tags including fault signals based on feature information F, recovery model information P, and ensemble learning.
    Type: Grant
    Filed: November 15, 2017
    Date of Patent: October 12, 2021
    Assignee: DOOSAN HEAVY INDUSTRIES & CONSTRUCTION CO., LTD.
    Inventors: Jee Hun Park, Hyun Sik Kim
  • Patent number: 11113360
    Abstract: A system and method predict whether or not a plant is abnormal and perform an accurate prediction even if a modeling is executed in a state where the understanding for a target to abnormality determination is low, or when a person unfamiliar with system designs a prediction model. The system includes a correlation coefficient calculation unit for calculating a correlation coefficient for each of two tags among a plurality of tags; a relevant tag determination unit for determining a relevant tag for each tag of the plurality of tags by comparing the correlation coefficient with a reference value; and an independent tag determination unit for determining one or more among the plurality of tags as an independent tag based on the relevant tag. The relevant tag determination unit includes primary and second tag extraction sections for extracting primary and second tags for each tag of the plurality of tags.
    Type: Grant
    Filed: December 24, 2018
    Date of Patent: September 7, 2021
    Assignee: DOOSAN HEAVY INDUSTRIES & CONSTRUCTION C
    Inventors: Hyun Sik Kim, Jee Hun Park
  • Patent number: 11092952
    Abstract: The present disclosure provides a plant abnormality detection system and method, which can learn the plant data collected in real time through a plurality of prediction models having different characteristics to generate a prediction value having the highest accuracy to diagnose the abnormality thereof, thus detecting accurately the abnormality of the plant to early provide alarm.
    Type: Grant
    Filed: August 26, 2016
    Date of Patent: August 17, 2021
    Assignee: DOOSAN HEAVY INDUSTRIES & CONSTRUCTION CO., LTD.
    Inventors: Jee Hun Park, Young Min Kim, In Suk Cho
  • Publication number: 20210247742
    Abstract: A failure prediction model generating apparatus and method thereof are provided. The failure prediction model generating apparatus includes a memory configured to store a plurality of failure prediction models derived previously; and a processor configured to predict a failure of the plant, wherein the processor is configured to collect data measured from the plant, select at least one failure prediction model from among the plurality of failure prediction models using the collected data, and predict a failure of the plant using the selected failure prediction model.
    Type: Application
    Filed: February 2, 2021
    Publication date: August 12, 2021
    Inventors: Jee Hun Park, Hyun Sik Kim, Sang Gun Na, Jun Woo Yoo
  • Publication number: 20210208030
    Abstract: An apparatus for diagnosing failure of a plant is provided. The apparatus for diagnosing failure of a plant includes: a data analyzer configured to provide data analysis information, which is information requiring analysis to diagnose failure of the plant, and a comprehensive diagnostic device configured to diagnose the failure using each of an algorithm-based diagnosing technique and a domain knowledge-based diagnosing technique based on the data analysis information, and to derive comprehensive diagnosis information for the failure by summarizing results of the algorithm-based diagnosing technique and the domain knowledge-based diagnosing technique.
    Type: Application
    Filed: December 23, 2020
    Publication date: July 8, 2021
    Inventors: Jee Hun PARK, Hyun-Sik Kim, Sang Gun Na, Jun Woo Yoo
  • Publication number: 20210199024
    Abstract: The present disclosure relates to an exhaust gas cooling device and method, and more particularly, to a device and method for installing an exhaust gas cooling device on the upper end of a duct of a heat recovery steam generator to cheaply cool the exhaust gas without occupying an additional dedicated area. An object of the present disclosure is to reduce the costs using a cheap cooling device in the cooling path for cooling the exhaust gas. In one aspect, the exhaust gas cooling device includes an exhaust gas cooling unit located on the upper end of a duct of a heat recovery steam generator connected with a gas turbine and for cooling the exhaust gas discharged from the gas turbine; and a control unit for controlling the exhaust gas cooling unit to lower the increase rate of the energy of the exhaust gas flowed into the heat recovery steam generator through the duct.
    Type: Application
    Filed: July 26, 2017
    Publication date: July 1, 2021
    Inventors: Hyun Sik KIM, Jee Hun PARK, Seung Gyun CHEONG
  • Publication number: 20210157308
    Abstract: Disclosed is a fault signal recovery system including a data processor configured to generate a signal subset U* by removing, from a signal set U for a plurality of tags, some tags including a fault signal, and a first learning signal subset X* by removing tags disposed at positions corresponding to the some tags from a learning signal set X containing only tags of normal signals, a modeling unit configured to generate feature information F extractable from the first learning signal subset X* and recovery information P on a plurality of recovery models usable for restoring the fault signal, and a recovery unit configured to estimate and recover normal signals for the some tags based on the signal subset U*, the first learning signal subset X*, the feature information F, the recovery information P on the plurality of recovery models, and similarity Z.
    Type: Application
    Filed: January 5, 2021
    Publication date: May 27, 2021
    Inventors: Jee Hun Park, Hyun Sik Kim
  • Patent number: 10976729
    Abstract: A data prediction method and apparatus generate plant normal state prediction data based on measurement data of multiple tags and a plant prediction model, to enhance accuracy of anomaly/fault prediction by providing precise prediction data in the normal state even in a plant anomaly/fault condition. The method includes generating primary prediction data by performing primary prediction based on the measurement data and the plant prediction model; selecting an anomalous state tag among the multiple tags, the selected anomalous state tag determined as data of an anomalous state based on measurement data corresponding to the primary prediction data; updating the plant prediction model by using the measurement data of only normal state tags; and generating secondary prediction data by performing secondary prediction based on the measurement data of the normal state tags and the updated plant prediction model. Secondary prediction is performed only when an anomalous state tag is selected.
    Type: Grant
    Filed: June 26, 2018
    Date of Patent: April 13, 2021
    Assignee: Doosan Heavy Industries Construction Co., Ltd
    Inventors: Jee Hun Park, Hyun Sik Kim
  • Patent number: 10915097
    Abstract: Disclosed is a fault signal recovery system including a data processor configured to generate a signal subset U* by removing, from a signal set U for a plurality of tags, some tags including a fault signal, and a first learning signal subset X* by removing tags disposed at positions corresponding to the some tags from a learning signal set X containing only tags of normal signals, a modeling unit configured to generate feature information F extractable from the first learning signal subset X* and recovery information P on a plurality of recovery models usable for restoring the fault signal, and a recovery unit configured to estimate and recover normal signals for the some tags based on the signal subset U*, the first learning signal subset X*, the feature information F, the recovery information P on the plurality of recovery models, and similarity Z.
    Type: Grant
    Filed: April 10, 2018
    Date of Patent: February 9, 2021
    Assignee: Doosan Heavy Industries Construction Co., Ltd
    Inventors: Jee Hun Park, Hyun Sik Kim
  • Patent number: 10884404
    Abstract: A method of predicting plant data in a system generates prediction data based on a plant prediction model and for detecting anomalies of the plant by comparing the prediction data with measurement data. The method can provide precise prediction data in a normal state even though the measurement data contains data in an anomalous state. Anomaly/fault prediction accuracy is enhanced by providing precise prediction data in the normal state. An apparatus using the method includes a plant modeling unit for generating a plant prediction model based on k-nearest neighbors (k-NN) by modeling a plant based on measurement data of multiple tags; and a prediction data generating unit for measuring similarity between the plant prediction model and the measurement data, determining a parameter k value based on the similarity, and generating plant normal state prediction data based on the determined parameter k value and the measured similarity.
    Type: Grant
    Filed: June 15, 2018
    Date of Patent: January 5, 2021
    Assignee: Doosan Heavy Industries Construction Co., Ltd
    Inventors: Jee Hun Park, Hyun Sik Kim
  • Publication number: 20200191380
    Abstract: A system and method for configuring a boiler combustion model are provided. The system for configuring the boiler combustion model may include a model generator configured to generate the boiler combustion model using, as input/output data, data obtained based on measured data, analysis data, and controller information, a model simulator configured to simulate the generated boiler combustion model and output simulated results, and a model modifier configured to evaluate the boiler combustion model based on the simulated results and generate modification information for modifying the boiler combustion model based on the generated boiler combustion model and corresponding evaluated results.
    Type: Application
    Filed: December 9, 2019
    Publication date: June 18, 2020
    Inventors: Jee Hun Park, Sang Gun Na, Hyun Sik Kim
  • Publication number: 20200175435
    Abstract: A system for controlling a boiler apparatus in a power plant to combust under optimized conditions, and a method for optimizing combustion of the boiler apparatus using the same are provided.
    Type: Application
    Filed: September 5, 2019
    Publication date: June 4, 2020
    Inventors: Sang Gun NA, Jwa Young MAENG, Hyun Sik KIM, Jee Hun PARK
  • Publication number: 20200175121
    Abstract: A system and method for predicting an analytical abnormality are provided. The method for predicting an analytical abnormality may include generating a signal generation model and an analysis model for a design object based on first analysis data, applying a signal generated by the signal generation model to the analysis model based on second analysis data to calculate one or more estimated values, comparing the estimated values and the second analysis data to generate a plurality of early warning information, and determining whether to output an early warning based on whether the plurality of early warning information satisfy a preset condition.
    Type: Application
    Filed: September 11, 2019
    Publication date: June 4, 2020
    Inventors: Jae Hyeon PARK, Sang Jin LEE, Hyun Sik KIM, Jee Hun PARK
  • Publication number: 20200166205
    Abstract: An apparatus for managing combustion optimization is provided. The apparatus for managing combustion optimization includes a data collector configured to collect real-time data that is measured in real time from a boiler system including a boiler and a combustion controller configured to control combustion of the boiler, a management configured to determine whether to perform combustion optimization of the boiler based on the real-time data, and an executor configured to generate a control command and transmit the control command to the combustion controller to perform the combustion optimization of the boiler in response to determining that the combustion optimization of the boiler is possible.
    Type: Application
    Filed: September 17, 2019
    Publication date: May 28, 2020
    Inventors: Sang Gun NA, Jwa Young MAENG, Jee Hun PARK
  • Publication number: 20200167592
    Abstract: An apparatus and method for generating learning data for combustion optimization is provided. The apparatus includes a data pre-processor to collect raw data including currently measured real-time data for boiler combustion and previously measured past data for the boiler combustion, and to perform pre-processing for the collected raw data, and a data analyzer to derive learning data from the raw data by analyzing the raw data. An apparatus for combustion optimization includes a management layer to collect currently measured real-time data for boiler combustion, to determine whether to perform combustion optimization, and to determine whether to tune a combustion model and a combustion controller; a data layer to derive learning data from raw data; a model layer to generate the combustion model/controller through the learning data; and an optimal layer to calculate a target value for combustion optimization and to output a control signal according to the calculated target value.
    Type: Application
    Filed: September 17, 2019
    Publication date: May 28, 2020
    Inventors: Hyun Sik KIM, Sang Gun NA, Jee Hun PARK
  • Publication number: 20200166206
    Abstract: An apparatus for combustion optimization is provided. The apparatus for combustion optimization includes a management layer configured to collect currently measured real-time data for boiler combustion, and to determine whether to perform combustion optimization and whether to tune a combustion model and a combustion controller by analyzing the collected real-time data, a data layer configured to derive learning data necessary for designing the combustion model and the combustion controller from the real-time data and previously measured past data for the boiler combustion, a model layer configured to generate the combustion model and the combustion controller through the learning data, and an optimal layer configured to calculate a target value for the combustion optimization by using the combustion model and the combustion controller, and to output a control signal according to the calculated target value.
    Type: Application
    Filed: September 18, 2019
    Publication date: May 28, 2020
    Inventors: Jee Hun PARK, Sang Gun NA, Hyun Sik KIM, Jwa Young MAENG
  • Publication number: 20200159885
    Abstract: An apparatus and method for diagnosing analysis is provided. The apparatus includes an analytic layer to divide a peripheral space of a target component into a plurality of cells and to derive analytic data by performing a numerical analysis iteration according to computational fluid dynamics for the plurality of cells; a model layer to derive an analytic model that simulates the numerical analysis iteration; a predictive layer to derive predictive data by predicting a result of the numerical analysis iteration by using the analytic model; and a diagnostic layer to diagnose an abnormality condition of numerical analysis by comparing the analytic data and predictive data during the numerical analysis iteration performed by the analytic layer. The diagnostic layer includes an early alarm to generate early alarm information by sorting a cell satisfying an early alarm condition; and an abnormality diagnostic device to determine whether the numerical analysis iteration is abnormal.
    Type: Application
    Filed: September 17, 2019
    Publication date: May 21, 2020
    Inventors: Jee Hun PARK, Jae Hyeon PARK, Sang Jin LEE, Hyun Sik KIM