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公开(公告)号：US11378108B2
公开(公告)日：2022-07-05
申请号：US16329345
申请日：2017-08-30
发明人： Yang Seok Kim , Dae Woong Kim , Bum Nyun Kim , Young Sheop Park , Chi Yong Park , Jong Seog Kim , Hyoung Kyun Kim , Byoung Oh Lee , Ji In Kim , Nam Woo Choi , Yong Hoon Park , Hee Seung Chang , You Soo Shin
摘要： Method for diagnosing a pneumatic control valve by using a positioner model includes: establishing relational expression for outputting valve stem displacement according to control pressure, the relational expression including parameters for the characteristics of a positioner, an actuator, and a valve, determining initial parameter value by adjusting the values of the parameters until the difference between a measured value for a normal operation of the pneumatic control valve and output value obtained by the relational expression is smaller than predetermined error limit, determining diagnostic parameter value by adjusting the values of the parameters until the difference between a measured value for a diagnostic operation of the pneumatic control valve and an output value obtained by the relational expression is smaller than a predetermined error limit, and comparing the initial parameter value and the diagnostic parameter value so as to determine whether the pneumatic control valve has abnormality.
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公开(公告)号：US11307566B2
公开(公告)日：2022-04-19
申请号：US16328650
申请日：2017-08-30
发明人： Yang Seok Kim , Bum Nyun Kim , Dae Woong Kim , Ji In Kim , Nam Woo Choi , Ju Hyung Kang , Young Sheop Park , Chi Yong Park , Jong Seog Kim , Hyoung Kyun Kim , Byoung Oh Lee , Hee Seung Chang , You Soo Shin
IPC分类号： G01M13/003 , G05B23/02
摘要： System for diagnosing pneumatic control valve online include a sensor set having sensors, attached to a pneumatic control valve, for measuring the state of the pneumatic control valve, a smart data analyzer for processing sensor signal acquired in real time from the sensor set and generating pneumatic control valve state information for online automatic diagnosis of the pneumatic control valve, a data server for transmitting, to an online analysis server, the pneumatic control valve state information received in real time from the smart data analyzer and storing the pneumatic control valve state information for predetermined time period, the online diagnostic server for, by comparing the pneumatic control valve state information with pre-stored normal state data of the pneumatic control valve, determining whether the pneumatic control valve is in abnormal state and generating diagnostic information, and a client computer for displaying the diagnostic information received from the online diagnostic server.
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公开(公告)号：US12014837B2
公开(公告)日：2024-06-18
申请号：US16328588
申请日：2017-08-29
发明人： Dae Woong Kim , Yang Seok Kim , Bum Nyun Kim , Young Sheop Park , Chi Yong Park , Jong Seog Kim , Hyoung Kyun Kim , Byoung Oh Lee , Ji In Kim , Nam Woo Choi , Jae Hun Shin , Jae Min An , Yong Chan Kim
摘要： The present invention provides a method for integrated online monitoring and a system for integrated online monitoring from a remote location for a nuclear power plant. The method includes a first step of collecting machine monitoring data of a plurality of units in the nuclear power plant selectively from the local data acquisition device via the monitoring data relay device, and a second step of collecting machine diagnostic data of a plurality of units in the nuclear power plant selectively from the local data acquisition device via the diagnostic data relay device.
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公开(公告)号：US11276300B2
公开(公告)日：2022-03-15
申请号：US16328645
申请日：2017-08-29
发明人： Dae Woong Kim , Nam Woo Choi , Bum Nyun Kim , Hyoung Kyun Kim , Ji In Kim , Ju Hyung Kang , Yong Hoon Park , Gun Woong Shin , Yang Seok Kim , Young Sheop Park , Chi Yong Park , Byoung Oh Lee , Jong Seog Kim
摘要： The present invention provides a method for learning latest data considering external influences in an early warning system, and the early warning system for same. The method for learning latest data considering external influences comprises the steps of: an early warning processing device categorizing device monitored variables according to external influences; and the early warning processing device differently applying a pattern learning method for each of the categorized monitored variables.
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