دورية أكاديمية
Identification and Adjustment of Guide Rail Geometric Errors Based on BP Neural Network
العنوان: | Identification and Adjustment of Guide Rail Geometric Errors Based on BP Neural Network |
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المؤلفون: | He Gaiyun, Huang Can, Guo Longzhen, Sun Guangming, Zhang Dawei |
المصدر: | Measurement Science Review, Vol 17, Iss 3, Pp 135-144 (2017) |
بيانات النشر: | Sciendo, 2017. |
سنة النشر: | 2017 |
المجموعة: | LCC:Mathematics |
مصطلحات موضوعية: | guide rail geometric error, stress, the test plate, finite element model, bp neural network, Mathematics, QA1-939 |
الوصف: | The relative positions between the four slide blocks vary with the movement of the table due to the geometric errors of the guide rail. Consequently, the additional load on the slide blocks is increased. A new method of error measurement and identification by using a self-designed stress test plate was presented. BP neural network model was used to establish the mapping between the stress of key measurement points on the test plate and the displacements of slide blocks. By measuring the stress, the relative displacements of slide blocks were obtained, from which the geometric errors of the guide rails were converted. Firstly, the finite element model was built to find the key measurement points of the test plate. Then the BP neural network was trained by using the samples extracted from the finite element model. The stress at the key measurement points were taken as the input and the relative displacements of the slide blocks were taken as the output. Finally, the geometric errors of the two guide rails were obtained according to the measured stress. The results show that the maximum difference between the measured geometric errors and the output of BP neural network was 5 μm. Therefore, the correctness and feasibility of the method were verified. |
نوع الوثيقة: | article |
وصف الملف: | electronic resource |
اللغة: | English |
تدمد: | 1335-8871 2017-0017 |
Relation: | https://doaj.org/toc/1335-8871 |
DOI: | 10.1515/msr-2017-0017 |
URL الوصول: | https://doaj.org/article/5bab9ff9843c4137a463412761ba19e2 |
رقم الأكسشن: | edsdoj.5bab9ff9843c4137a463412761ba19e2 |
قاعدة البيانات: | Directory of Open Access Journals |
تدمد: | 13358871 20170017 |
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DOI: | 10.1515/msr-2017-0017 |