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Gear Shape Parameter Measurement Using a Model-Based Scanning Multi-Distance Measurement Approach
To reduce wind turbine failures by defective drive trains, deviations in the geometry of large gears (diameter ≳ 1 m) must be extensively determined with single-digit micrometer uncertainties. Fixed measuring volumes limit standard measuring methods like coordinate and gear measuring instruments for...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7412203/ https://www.ncbi.nlm.nih.gov/pubmed/32674308 http://dx.doi.org/10.3390/s20143910 |
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author | Pillarz, Marc von Freyberg, Axel Fischer, Andreas |
author_facet | Pillarz, Marc von Freyberg, Axel Fischer, Andreas |
author_sort | Pillarz, Marc |
collection | PubMed |
description | To reduce wind turbine failures by defective drive trains, deviations in the geometry of large gears (diameter ≳ 1 m) must be extensively determined with single-digit micrometer uncertainties. Fixed measuring volumes limit standard measuring methods like coordinate and gear measuring instruments for large gear measurements. Therefore, a model-based scanning multi-distance measurement approach for gear shape parameters is presented. The measurement approach has a scalable design and consists of a confocal-chromatic sensor, rotary table as a scanning unit and model-based signal processing. A preliminary study on a midsize spur gear demonstrates the general feasibility of the model-based scanning multi-distance measurement approach. As a result, the mean base circle radius as the fundamental gear shape parameter is determined with an uncertainty of <5 μm. The calibration and adjustment of the sensor arrangement were performed with a known calibration gear. Scalability is not experimentally validated in this article. However, simulations verify the scalability of the measurement approach in a first step. For gears with 1 m in diameter and varying tooth flank geometries, the estimated achievable uncertainty of the mean base circle radius is still <5 μm. Therefore, the model-based scanning multi-distance measurement approach is a promising alternative for gear inspection. |
format | Online Article Text |
id | pubmed-7412203 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-74122032020-08-17 Gear Shape Parameter Measurement Using a Model-Based Scanning Multi-Distance Measurement Approach Pillarz, Marc von Freyberg, Axel Fischer, Andreas Sensors (Basel) Article To reduce wind turbine failures by defective drive trains, deviations in the geometry of large gears (diameter ≳ 1 m) must be extensively determined with single-digit micrometer uncertainties. Fixed measuring volumes limit standard measuring methods like coordinate and gear measuring instruments for large gear measurements. Therefore, a model-based scanning multi-distance measurement approach for gear shape parameters is presented. The measurement approach has a scalable design and consists of a confocal-chromatic sensor, rotary table as a scanning unit and model-based signal processing. A preliminary study on a midsize spur gear demonstrates the general feasibility of the model-based scanning multi-distance measurement approach. As a result, the mean base circle radius as the fundamental gear shape parameter is determined with an uncertainty of <5 μm. The calibration and adjustment of the sensor arrangement were performed with a known calibration gear. Scalability is not experimentally validated in this article. However, simulations verify the scalability of the measurement approach in a first step. For gears with 1 m in diameter and varying tooth flank geometries, the estimated achievable uncertainty of the mean base circle radius is still <5 μm. Therefore, the model-based scanning multi-distance measurement approach is a promising alternative for gear inspection. MDPI 2020-07-14 /pmc/articles/PMC7412203/ /pubmed/32674308 http://dx.doi.org/10.3390/s20143910 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Pillarz, Marc von Freyberg, Axel Fischer, Andreas Gear Shape Parameter Measurement Using a Model-Based Scanning Multi-Distance Measurement Approach |
title | Gear Shape Parameter Measurement Using a Model-Based Scanning Multi-Distance Measurement Approach |
title_full | Gear Shape Parameter Measurement Using a Model-Based Scanning Multi-Distance Measurement Approach |
title_fullStr | Gear Shape Parameter Measurement Using a Model-Based Scanning Multi-Distance Measurement Approach |
title_full_unstemmed | Gear Shape Parameter Measurement Using a Model-Based Scanning Multi-Distance Measurement Approach |
title_short | Gear Shape Parameter Measurement Using a Model-Based Scanning Multi-Distance Measurement Approach |
title_sort | gear shape parameter measurement using a model-based scanning multi-distance measurement approach |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7412203/ https://www.ncbi.nlm.nih.gov/pubmed/32674308 http://dx.doi.org/10.3390/s20143910 |
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