Using Data Mining Approaches for Force Prediction of a Dynamically Loaded Flexible Structure

Meik Schlechtingen, Sofiane Achiche, Tiago Lourenco Costa, Ilmar Santos

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

This paper presents the results obtained from a research work investigating the performance of different Adaptive models developed to predict excitation forces on a dynamically loaded flexible structure. For this purpose, a flexible structure is equipped with acceleration transducers at each degree of freedom and a force transducer for validation and training. The models are trained using data obtained from applying a random excitation force on the flexible structure. The performance of the developed models is evaluated by analyzing the prediction capabilities based on a normalized prediction error. The frequency domain is considered to analyze the similarity of the frequencies in the predicted and the original force signal. For a selection of the best models, a more advanced performance analysis is carried out. This includes application of the trained models to deterministic and non-deterministic excitation forces with different excitation frequencies and amplitudes. Additionally, the influence of the sampling frequency and sensor location on the model performance is investigated. The results obtained in this paper show that most data mining approaches can be used, when a certain degree of inaccuracy is accepted. Furthermore, the comparison study points out that the transducer location is crucial for the model performance. However, there exists no general solution for the final selection of models.
Original languageEnglish
Title of host publicationProceedings of the ASME 2014 12th Biennial Conference on Engineering Systems Design and Analysis (ESDA 2014)
Number of pages10
PublisherAmerican Society of Mechanical Engineers
Publication date2014
Article numberESDA2014-20259
ISBN (Print)978-0-7918-4584-4
DOIs
Publication statusPublished - 2014
EventASME 2014 12th Biennial Conference on Engineering Systems Design and Analysis - Copenhagen, Denmark
Duration: 25 Jun 201427 Jun 2014
Conference number: 12
http://www.asmeconferences.org/ESDA2014/

Conference

ConferenceASME 2014 12th Biennial Conference on Engineering Systems Design and Analysis
Number12
CountryDenmark
CityCopenhagen
Period25/06/201427/06/2014
Internet address

Keywords

  • Data mining
  • Flexible structures

Cite this

Schlechtingen, M., Achiche, S., Lourenco Costa, T., & Santos, I. (2014). Using Data Mining Approaches for Force Prediction of a Dynamically Loaded Flexible Structure. In Proceedings of the ASME 2014 12th Biennial Conference on Engineering Systems Design and Analysis (ESDA 2014) [ESDA2014-20259] American Society of Mechanical Engineers. https://doi.org/10.1115/ESDA2014-20259