A neural network clamping force model for bolt tightening of wind turbine hubs

Emanuele Lindo Secco, Atulya Nagar, Christian Deters, Helge Wurdemann, Hak Keung Lam, Kaspar Althoefer

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

1 Citation (Scopus)

Abstract

Industrial manufacturing of large-scale wind turbines requires the accurate tightening of multiple bolts and nuts, which connect the ball bearings - supporting wind turbine blades - with the hub, a huge mechanical component supporting blades pitch motion. An accurate tightening of bolts and nuts requires uniformly distributed clamping forces along flanges and surfaces of contact between hub and bearings. Due to the role of friction forces and the dynamics of the phenomenon, this process is nonlinear and currently performed manually; it is also time consuming, requiring high-cost equipment and expert operators. This paper proposes a set of neural networks, which infer the clamping force achievable with a tightening tool while fastening M24 nuts on bolts. The tool embeds a torque sensor and shaft encoder, therefore two types of inputs of the neural networks are considered in order to fit the clamping force output: the time signals of (a) the applied torque of the tool and (b) the combination of the torque and of the angular speed of the tool. According to results, neural networks properly model the clamping force, both during the training stage and when exposed to unseen testing data. This approach could be generalized to other industrial processes and specifically to those requiring repetitive tightening tasks and involving highly nonlinear aspects, such as friction forces.

Original languageEnglish
Title of host publicationProceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages288-296
Number of pages9
ISBN (Print)9781509001545
DOIs
Publication statusPublished - 22 Dec 2015
Event15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015 - Liverpool, United Kingdom
Duration: 26 Oct 201528 Oct 2015

Conference

Conference15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015
Country/TerritoryUnited Kingdom
CityLiverpool
Period26/10/201528/10/2015

Keywords

  • Bolt tightening
  • Neural network
  • Self-adaptive manufacturing
  • Wind turbine

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