| NSF Org: |
TI Translational Impacts |
| Recipient: |
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| Initial Amendment Date: | September 16, 2022 |
| Latest Amendment Date: | September 16, 2022 |
| Award Number: | 2131373 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Mara E. Schindelholz
marschin@nsf.gov (703)292-4506 TI Translational Impacts TIP Directorate for Technology, Innovation, and Partnerships |
| Start Date: | October 1, 2022 |
| End Date: | July 31, 2024 (Estimated) |
| Total Intended Award Amount: | $256,000.00 |
| Total Awarded Amount to Date: | $256,000.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
1450 S ROLLING RD HALETHORPE MD US 21227-3863 (410)926-0520 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
1000 Hilltop Circle Baltimore MD US 21250-0002 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | STTR Phase I |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.084 |
ABSTRACT
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) project seeks to provide an integrated monitoring solution for wind turbine blades. Continuous and reliable monitoring within the blade has been a challenge, primarily due to the lack of reliable energy for the wireless sensor (e.g., batteries need to be replaced and can be expensive and logistically difficult to replace inside the blade and power lines inside the blade are hard to install and require frequent maintenance). The proposed solution seeks to overcome current technical challenges by providing a long-lasting, maintenance-free, self-powered, integrated solution for wind turbine blade monitoring and analytics. If successfully commercialized, the solution can be deployed for autonomous sensing and smart maintenance scheduling based on big data analysis. This project may contribute to significantly and permanently reducing existing blade monitoring costs, decreasing downtime for manual monitoring and battery changes and reducing catastrophic failures with better monitoring information. By reducing the operational costs, the solution may make large-scale wind energy more competitive, reducing the world?s dependence on environmentally-harmful sources of energy. In addition, the technology may reduce the risk of injury to humans as compared to current operational processes, making wind energy safer to operate.
This STTR Phase I project proposes to develop an integrated, self-powering sensor node for wind turbine blade monitoring by overcoming the following technical hurdles: lack of reliable energy for the sensor/transmitter system deep inside the blade, logistical challenges to replacing batteries inside the blade for a large number of sensors at different intervals, and difficulites with long wire-runs inside the blade as those are hard to install and require frequent maintenance. To handle these technical hurdles, this project aims to prototype an integrated, self-powered, wireless sensor node and perform field tests. This project plans to: (1) develop a mechanism for the harvester module that reliably produces electrical voltage and power regardless of the blade rotational speed, (2) develop a power management circuit with autonomous sleep/wakeup and without impedance tracking to increase charging efficiency, and (3) perform indoor and in-field test for verification of power harvesting and data transmission performance. This technolology seeks to address the fundamental weaknesses of vibration energy harvesters while integrating various components (e.g., energy harvester, sensor, transmitter, receiver, and analytics software) for an optimized solution.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
Overview
The objective of this proposal is to develop an integrated, self-powered wireless sensor node for wind turbine blade monitoring by capturing otherwise wasted kinematic and/or vibrational energy from the blades. This innovative solution eliminates the need for frequent battery replacements (every 2-4 years), reducing blade monitoring costs by 80%. It enhances operational safety and provides real-time data for blade performance analysis and proactive maintenance. The wind turbine doesn’t need to be stopped for battery replacement, increasing uptime and profits. Additionally, reliable and more frequent blade condition data is delivered to the Operation and Maintenance (O&M) system, which enables pro-active blade maintenance and prevents catastrophic failures (e.g., structural breakdown due to excessive vibration, unbalance due to ice, lightning damage). Overall, we expect our innovation to pay for itself within 3-4 years and add 1.5% profit annually to an owner’s bottom line, making wind energy even more economically competitive.
This project was focused on three major objectives: (i) the design of energy harvesting transducer for varying blade speeds, (ii) the construction of a power management circuit to charge energy from the transducer and provide power to the wireless sensor, (iii) the validation of the prototype via field testing, and (iv) wireless data acquisition platform connected to cloud storage was built for future data analytics so that preventive blade failure detection and proactive maintenance scheduling is enabled.
Major accomplishments
(1) Harvesting Transducer: We developed a new pendulum-driven harvesting transducer, a kind of frequency-up converter that effectively captures a low-speed mechanical rotation into high-frequency vibration of a piezoelectric cantilever beam. We demonstrate the improved power density from the proposed concept compared to the previous disk-driven frequency-up converters.
(2) Power Management Circuit: A compact sized (3x2 cm) power management circuit was developed for efficient power charging. It has the basic functions for power charging (rectification, impedance matching, buck-boost converter, voltage regulator), and an on-board supercapacitor for power charging. We additionally implemented a switching circuit that actively controls the on/off sequence of the sensor to save more power.
(3) System Integration: A total combined solution of a self-powering sensor unit was built by integrating the transducer, the power management circuit with the switching circuit, and a commercial wireless vibration sensor. All the components were assembled in a small 3D printed case (10x10x15cm scale), a viable size to be installed inside wind turbine blades. The overall diagram of the self-powering wireless sensor unit.
(4) Field Test: A field test was performed on an outdoor small wind turbine (10 ft tall) where the sensor units were installed, to realize the real time vibration sensing and save data to the cloud for data analytics and conditional monitoring.
(5) Data Acquisition and Analytics Platform: We created the data acquisition system, analytics platform, as well as the web portal. That will enable us to use the same infrastructure to develop and deploy solutions for similar monitoring problems in several industries.
Intellectual Merit
The self-powering sensor node for wind turbine blade monitoring developed in this project can overcome the following technical hurdles: (1) lack of reliable energy for the sensor/transmitter system inside the blade; (2) logistical challenge to replace batteries inside the blade for a large number of sensors at different intervals; and (3) avoiding long wire-runs inside the blade as those are hard to install and require frequent maintenance. The prototyped self-powered wireless sensor node and the receiver were tested on a mid-sized wind turbine blade (several MW level) and we verified the following contributions: (1) the efficient mechanism of harvester module produces electrical voltage at a fixed frequency regardless of the blade rotational speed, (2) the power management circuit with autonomous sleep/wakeup and without impedance tracking was able to increase charging efficiency. This project is innovative because it resolves the fundamental weakness of vibration energy harvesters – “small” power. That is, the proposed harvester mechanism significantly reduces power management circuit topology and improves overall charging circuit efficiency.
Broader/Commercial Impact
Our solution provides an innovative, first of a kind, integrated solution that overcomes current technical challenges by providing safe, long-lasting, maintenance-free self-powered wireless sensors for wind turbine blade monitoring. If successfully commercialized, several of these sensor nodes can be deployed inside a wind turbine blade – hard to monitor by humans – for autonomous sensing and smart maintenance scheduling based on big data analysis. This project contributed to (1) significantly and permanently reduce existing blade monitoring cost (2) decrease downtime for manual monitoring and battery changes, and (3) significantly reduce catastrophic failures with better monitoring information. By reducing the operational costs, our solution makes large scale wind energy more competitive compared to fossil and nuclear energy, thereby reducing the world’s dependence on environmentally harmful sources of energy. Also, our solution reduces the risk of injury to humans as compared to current operational processes, thereby making wind energy safer to operate.
Last Modified: 10/09/2024
Modified by: Soobum Lee
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