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A Fast Detection and Localization Approach to Monitoring Cables in Underground…

Award Information

Agency:
Department of Energy
Branch:
N/A
Award ID:
99363
Program Year/Program:
2010 / SBIR
Agency Tracking Number:
94870
Solicitation Year:
N/A
Solicitation Topic Code:
57 b
Solicitation Number:
N/A
Small Business Information
SIGNAL PROCESSING, INC.
9700 Great Seneca Highway Rockville, MD -
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Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 2010
Title: A Fast Detection and Localization Approach to Monitoring Cables in Underground Power Distribution Network
Agency: DOE
Contract: DE-FG02-10ER85997
Award Amount: $99,999.00
 

Abstract:

Short-circuit and arcing faults commonly occur in underground power networks. Short-circuit normally occur at distribution feeders. Consolidated Edison of New York (Con Edison) experiences more than 1600 failures on its distribution feeders each year. Arcing faults also occur frequently in power cables. Con Edison experiences more than 1000 arcing faults on its secondary distribution system each year. We propose an integrated approach to detect and localize short-circuit and arcing faults in underground power networks. The proposed framework consists of hardware and software. Voltage and current sensors are needed. The software has noise filtering and fault detection and localization algorithms. Our framework is modular in nature and each module can be independently modified and updated. In Phase 1, laboratory demonstrations will be performed. In Phase 2, we will build real-time prototype and evaluate its performance in a underground power network. Commercial Applications and Other Benefits: The technology can be used in power network fault diagnostics, including underground networks. The research results of this project will lay down a solid foundation for future commercialization effort with the above applications. Our team has strong tie with Con Edison. We anticipate this market will be at least 50 million dollars over the next decade

Principal Investigator:

Chiman Kwan
Dr.
3013152322
chiman.kwan@signalpro.net

Business Contact:

Chiman Kwan
Dr.
3013152322
chiman.kwan@signalpro.net
Small Business Information at Submission:

Signal Processing, Inc.
13619 Valley Oak Circle Rockville, MD 20850

EIN/Tax ID: 134320631
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No