Hybrid modelling for linear actuator diagnosis in absence of faulty data records
| Autor: | Meritxell Gómez-Omella, Cristobal Ruiz-Carcel, Susana Ferreiro, Aitor Arnaiz, Kerman López de Calle-Etxabe, Andrew Starr, Basilio Sierra |
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| Rok vydání: | 2020 |
| Předmět: |
Data records
0209 industrial biotechnology General Computer Science Computer science Condition-based maintenance General Engineering Condition monitoring Diagnostic algorithms Feature selection 02 engineering and technology Linear actuator computer.software_genre Synthetic data 020901 industrial engineering & automation 0202 electrical engineering electronic engineering information engineering sort 020201 artificial intelligence & image processing Data mining computer |
| Zdroj: | Computers in Industry. 123:103339 |
| ISSN: | 0166-3615 |
| DOI: | 10.1016/j.compind.2020.103339 |
| Popis: | The advantages of condition based maintenance over alternative maintenance strategies have been widely proven. Detection, diagnosis and prognostic algorithms enable the optimization of repair schedules while avoiding breakdowns and downtimes. However, some industrial limitations complicate the development of diagnostic monitoring algorithms, particularly in scenarios with unique or non-mass-produced machines, as obtaining faulty data records is difficult. This work proposes an approach that combines the data from physical models with data-based models (or hybrid modelling) to sort out the lack of faulty data records in the condition monitoring of a linear actuator. A test rig was built and used to collect data from healthy and faulty cases (the later only used for validation purposes), in addition to a physical model that simulated nominal (healthy) and faulty conditions to generate synthetic data. Synthetic and real measured data were combined with an improved fusion by means of a feature selection method. A diagnostic model was developed and the algorithm was validated in the detection of real faulty cases. Additionally, this approach is also valuable to detect unseen operating conditions. The results obtained in this work prove the validity of hybrid models for those cases in the industry where there are physical or economical limitations to obtain data records that difficult the implementation of diagnostic algorithms. |
| Databáze: | OpenAIRE |
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