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17a: Comprehensive Wind Turbine Health Monitoring System

Award Information
Agency: Department of Energy
Branch: N/A
Contract: DE-SC0022762
Agency Tracking Number: 0000266052
Amount: $199,933.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: C54-17a
Solicitation Number: N/A
Solicitation Year: 2022
Award Year: 2022
Award Start Date (Proposal Award Date): 2022-06-27
Award End Date (Contract End Date): 2023-03-26
Small Business Information
301 1st Street SW, Suite 200
Roanoke, VA 24011-1921
United States
DUNS: 627132913
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Daniel Kominsky
 (540) 553-0865
Business Contact
 Maggie Hudson
Phone: (434) 220-1559
Research Institution
 University of Massachusetts Lowell
600 Suffolk Street, 2nd Floor South
Lowell, MA 01854-3692
United States

 Nonprofit College or University

Offshore wind turbines are a potential means of meeting the countries energy needs, but there is a deficit in the availability of suitable health monitoring solutions for these devices. A comprehensive system which can detect the degradation of key components and provide early warning can reduce unscheduled maintenance and lower the levelized cost of energy.
General statement of how this problem is being addressed:
Luna, partnered with the University of Massachusetts is proposing to develop and realize a comprehensive, cost effective, and highly multiplexed health monitoring solution for rotating elements of wind turbines based on the Hyperion fiber optic interrogator. The proposed monitoring uses a combination of Fiber Bragg Grating sensors that measure strain (1D and rosette), temperature, and Fabry Perot based accelerometers and acoustic emissions sensors. All these measurements can be achieved in parallel by multiplexing many sensors onto the 16 fiber channels supported by one Hyperion instrument mounted in the hub. The accelerometers and acoustic emissions sensors will provide information not only on the occurrence of damage but will also perform multilateration (time of flight analysis) to precisely localize the damage or sources of vibration. Additionally, the platform currently has edge computing capability to isolate events of significance and capture the relevant data in a cloud-computing-based platform for remote retrieval by turbine operators.
Phase I activity:
During Phase I, the team will develop an instrumentation architecture that provides a complete characterization of the blade health, demonstrate the feasibility of implementing that plan through scale testing, develop data management methodologies, and lay the groundwork for a comprehensive health monitoring solution. In Phase II, the team will move on to implementing the sensing capabilities in on full scale hardware.
Commercial applications and other benefits
Comprehensive remote health monitoring of offshore wind turbines can dramatically reduce the cost of ownership and operation by detecting nascent damage and enabling pre-emptive measures to protect the asset. This will reduce the cost of remedying issues, minimize unnecessary in-person inspections, and lower the total expense of a valuable renewable energy resource

* Information listed above is at the time of submission. *

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