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Hai Y QiuHayward, CA

Known as:
Hai Yan Qui Hai Y Qin

Hai Qiu Phones & Addresses

Hayward, CA   

371 Klamath St, Brisbane, CA 94005    415-4683538   

El Cerrito, CA   

5839 Ralston Ave, Richmond, CA 94805   

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Hai Qiu Photo 14

Technical Leader At Cisco System

Position:
Technical Leader at Cisco Systems
Location:
San Francisco Bay Area
Industry:
Computer Networking
Work:
Cisco Systems since 1999
Technical Leader Motorola Inc 1997 - 1999
Sr. Firmware Engineer Savi Technology 1993 - 1997
Software Engineer
Education:
University of Missouri-Rolla
Master of Science (MS), Electrical and Electronics Engineering Graduate School, Chinese Academy of Sciences
Master of Science (MS), Computer Engineering Zhongshan University
Bachelor of Science (BS), Electrical and Electronics Engineering
Hai Qiu Photo 15

Hai Qiu

Publications & IP owners

Us Patents

System And Method For Damage Propagation Estimation

US Patent:
7933754, Apr 26, 2011
Filed:
Dec 7, 2006
Appl. No.:
11/608036
Inventors:
Kai Frank Goebel - Mountain View CA, US
Neil Holger White Eklund - Schenectady NY, US
Hai Qiu - Clifton Park NY, US
Weizhong Yan - Clifton Park NY, US
Assignee:
General Electric Company - Niskayuna NY
International Classification:
G06G 7/48
US Classification:
703 6
Abstract:
A method to estimate damage propagation is disclosed. The method includes making available a set of input parameters to a computational model, executing the computational model with defined changes within a range of an input parameter of the set of input parameters to define a range of at least one modeled output, receiving at least one signal responsive to and representative of a respective one of an actual sensor output, and estimating damage propagation based upon a correlation of the received signal to the modeled output.

System And Method For Equipment Life Estimation

US Patent:
2008014, Jun 12, 2008
Filed:
Dec 7, 2006
Appl. No.:
11/608076
Inventors:
Kai Frank Goebel - Mountain View CA, US
Piero Patrone Bonissone - Schenectady NY, US
Weizhong Yan - Clifton Park NY, US
Neil Holger White Eklund - Schenectady NY, US
Feng Xue - Clifton Park NY, US
Hai Qiu - Clifton Park NY, US
Assignee:
GENERAL ELECTRIC COMPANY - Schenectady NY
International Classification:
G06F 15/00
US Classification:
702183
Abstract:
A method to predict equipment life is disclosed. The method includes making available a set of input parameters, and defining a model of a health of the equipment as a function of the set of input parameters. The method continues with receiving at least one signal representative of a respective one of an actual sensor output relating to an actual operation attribute margin of the equipment, predicting a remaining useful equipment life based upon a sequence of outputs of the model of the health of the equipment, and generating a signal corresponding to the remaining useful equipment life.

Methods And Systems For Identifying A Precursor To A Failure Of A Component In A Physical System

US Patent:
2014018, Jul 3, 2014
Filed:
Dec 27, 2012
Appl. No.:
13/728572
Inventors:
- Schenectady NY, US
Anil Varma - San Ramon CA, US
Brock Estel Osborn - Niskayuna NY, US
James Kenneth Aragones - Clifton Park NY, US
Piero Patrone Bonissone - Schenectady NY, US
Naresh Sundaram Iyer - Saratoga Springs NY, US
Hai Qiu - Clifton Park NY, US
Assignee:
GENERAL ELECTRIC COMPANY - Schenectady NY
International Classification:
G06N 5/02
US Classification:
706 50
Abstract:
A computer-implemented system for identifying a precursor to a failure of a particular type of component in a physical system is provided. The physical system includes sensors coupled to the physical system. The computer-implemented system includes a computing device, a database, a processor, and a memory device. The memory device includes historical data including sensor measurements. When instructions are executed by the processor, the processor receives the historical data from the memory device. The processor generates a predictive model. The predictive model uses, as inputs, sensor measurements in the historical data. The predictive model is able to differentiate between sensor measurements taken before the repair event and those taken after the repair event without a time of the repair event being an input to the predictive model. The processor designates at least one sensor measurements used as inputs to the predictive model as precursors to the failure of the component.

Possible Relatives

David Qiu  Dai H Qiu  Dan F Qiu  Doris J Qiu  Eric T Qiu  Fang Qiu  Fei Qiu  Hai M Lam  Hai Le  Hai W Lim 

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