The DOI matches its Crossref record.
MEMS Multi Sensor Intelligent Damage Detection for Wind Turbines by Using IOT
Open accessAbstract
Abstract Maintenance and monitoring of wind turbines have become a promising challenge for large dimension turbines. Even a small damage can result in integrity of the system. This paper gives a solution using nondestructive SHM technique to recognize the damages of turbine along with the difference in the properties before and after damage. The information obtained from the sensor helps in robust reading of condition of the blades and produces alarm sound at the stage of severe damage.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Other than the authors' work, no MEMS multi-sensor array for wind turbines is present in the literature or in commercial products.
“Although previous analysis [4], [12] has shown the potential of using inexpensive MEMS sensors for SHM applications, other than our work, no MEMS multi-sensor array for wind turbines is present in the literature, nor in commercial products.”
From Aerosense: A Self-Sustainable and Long-Range Bluetooth Wireless Sensor Node for Aerodynamic and Aeroacoustic Monitoring on Wind Turbines (2023) · cites this paper as [12]
The Introduction describes this published paper's own MEMS-based, multi-sensor system for monitoring wind-turbine damage, providing a counterexample to the claimed absence of such work in the literature. The paper does not address whether commercial products exist. In the printed sentence, however, the citations follow the earlier statement about MEMS sensors' potential; the absence claim appears to be the citing authors' own assertion. (LLM, conf=0.82)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
No references could be resolved yet.
Research works printed but not linked: 2
- Haldorai, 2020, Security and channel noise management in cognitive radio networks, Computers & Electrical Engineering, 87, 10.1016/j.compeleceng.2020.106784 · DOI
- Haldorai, 2020, Canonical Correlation Analysis Based Hyper Basis Feedforward Neural Network Classification for Urban Sustainability, 10.1007/s11063-020-10327-3 · DOI
Cited by
Sorted by citations
Polonelli, T., Muller, H., Kong, W., Fischer, R., Benini, L., & Magno, M. (2023) · IEEE Sensors Journal · doi:10.1109/jsen.2022.3224307 · Cited by 35
Metadata
- Authors
- Majidha Fathima, K. M., Raj, R. S., Rahul Prasad, K., & Guru Balan, S.
- Venue
- Journal of Physics: Conference Series
- Publisher
- IOP Publishing
- Published
- 2021-05-01
- Volume
- 1916
- Issue
- 1
- Pages
- 012045
- ISSN
- 1742-6588 (ISSN-L)
- 1742-6596
- OpenAlex
- W3170330455
- Cited by
- 10
- References
- 0
- Citations by year
- 2023: 2 · 2022: 8
- FWCI
- 7.15
- Type
- conference paper
- Language
- en
- Status
- Retracted
- Update notices
- Open access
- diamond
- doi.org
- Licence
- Locations
- Journal of Physics Conference Series (publishedVersion, cc-by)
- Topics
- Physical Sciences › Engineering › Civil and Structural Engineering › Structural Health Monitoring Techniques
- Physical Sciences › Engineering › Mechanics of Materials › Ultrasonics and Acoustic Wave Propagation
- Physical Sciences › Engineering › Control and Systems Engineering › Machine Fault Diagnosis Techniques
- Keywords
- structural health monitoring, MEMS sensors, Internet of Things, wind turbine blades, condition monitoring, damage detection, alarm system, non-destructive testing
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
