SBIR/STTR Research Award

Embedded Multiplexed Fiber-Optic Sensing for Turbine Control & ProgNostic Health Management (PHM)

Award identifier 07e0cb84a3545e5ead5f84dc85db3e525a26dc93ee763c91a8e67b3688033743Awarding agency Department of Energy

Award amount

$999,898

Program and phase

SBIR · Phase II

Award year

2019

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
Department of Energy
Branch
Not reported
Recipient company
INTELLIGENT FIBER OPTIC SYSTEMS CORP
Proposal award date
2019-05-28
Contract end date
2021-05-27
UEI
HCXHVBD9HKN9
Solicitation number
DE-FOA-0001975
Topic code
19c

Research abstract

DOE seeks innovative embedded sensing to enhance control of industrial gas turbines (GTs). Although advanced sensor technology has been demonstrated in development turbine systems, the vast majority of sensors do not meet the requirements for deployment to production turbines. This prevents optimization of control using real-time, in situ sensor data. Combined-cycle plant operation brings clear plant-level efficiency benefits, but it also increases the cost of GT downtime; the number of assets idled due to GT downtime is greater than for simple-cycle plants, and the there is a risk of cascading failure across interconnected turbines and generators. The importance of health monitoring, diagnostics, and prognostics for reliability is therefore magnified. IFOS proposes development of an innovative, embedded-sensor-enabled control approach for industrial GTs. The IFOS concept leverages existing advanced fiber-optic sensing technology including ultra-thin optical fibers. IFOS’s innovation will enable measurement of turbine blade temperature and stress parameters that are closer to the harshest of turbine environments, and use this real-time sensing information to augment existing control schemes to decrease margins and thereby increase system efficiency and reduce cost of ownership. Conventional electronic sensors are relatively bulky and require multiple lead wires. Few sensors are able to be deployed on production turbines. In IFOS’s approach, there are no ‘active’ components on the turbine blade or shaft – all optical signal processing and post-detection electronics are situated on stationary components in a relatively benign environment, removing the need for expensive ultra-high-temperature electronics. IFOS will develop a methodology that can be matured to a production system, enabling long-term benefits to the GT industry by supporting better controls, lower emissions, longer life, and lower lifetime operating costs. IFOS demonstrated concept feasibility on a simulated turbine engine system featuring blades with surface- mounted fiber-optic sensors. A custom controller program was developed to demonstrate the utility of measured data in controller turbine operating parameters. IFOS held discussions on technology integration pathways with major OEMs and planned for Phase II testing on high fidelity GT testbeds. The 3 proposed technical objectives were accomplished. In collaboration with its university test partner and GT OEMs, during Phase II IFOS will demonstrate Turbine*Sense™ performance in testbeds of increasing environmental fidelity. Phase II will establish a clear path forward to full-scale GT instrumentation testing. Commercial Applications and Other Benefits: IFOS’s ultimate vision is intake-to-exhaust GT intelligence using embedded, hair-thin fiber-optic sensor networks benefiting control, diagnostics, and prognostics simultaneously.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

172 SBIR/STTR records share this UEI (1994–2025). Reported award amounts total $61,008,158. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Defense, National Aeronautics and Space Administration, Department of Energy, Department of Health and Human Services, National Science Foundation, Department of Agriculture

Agency intelligence

Department of Energy

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.