ANN-based estimation of MEMS diaphragm response: An application for three leaf clover diaphragm based Fabry-Perot interferometer

buir.contributor.authorAydemir, Umut
buir.contributor.orcidAydemir, Umut|0000-0001-5396-4610
dc.citation.epage111534- 9en_US
dc.citation.spage111534- 1en_US
dc.citation.volumeNumber199en_US
dc.contributor.authorYigit, E.
dc.contributor.authorHayber, Ş. E.
dc.contributor.authorAydemir, Umut
dc.date.accessioned2023-02-15T05:46:43Z
dc.date.available2023-02-15T05:46:43Z
dc.date.issued2022-06-23
dc.departmentInstitute of Materials Science and Nanotechnology (UNAM)en_US
dc.description.abstractIn this study, an artificial neural network (ANN) based model is developed for MEMS diaphragm analysis, which does not require difficult and time-consuming FEM processes. ANN-based estimator is generated for static pressure response (d) and dynamic pressure response (f) analysis of TLC (three leaf clover) diaphragms for Fabry-Perot interferometers as an example. TLC is one of the unsealed MEMS design diaphragms formed by three leaves of equal angles. The diaphragms used to train ANNs are designed with SOLIDWORKS and analyzed with ANSYS. A total of 1680 TLC diaphragms are simulated with eight diaphragm parameters (3 for SiO2 material, 4 for geometry, and 1 for pressure) to create a data pool for ANN’s training, validation, and testing processes. 80% of the data is used for training, 15% for validation, and the remaining for testing. Only four geometric parameters are used as input in the ANN estimator, and the material parameters are added to the model with an analytical multiplier. Thus, network models that estimate d and f values for all kinds of diaphragm materials are proposed, with a material-independently trained ANN structure. The performance of the ANN model is compared with the empirical equation suggested in the literature, and its superiority is demonstrated. In addition, the d and f parameters of TLC diaphragms designed with five different materials (Si, In2Se3, Ag, EPDM, Graphene) are estimated to be very close to the real ones. By using the proposed method, analyses of TLC diaphragms are quickly performed without the need for time-consuming and costly design and analysis programs.en_US
dc.description.provenanceSubmitted by Ezgi Uğurlu (ezgi.ugurlu@bilkent.edu.tr) on 2023-02-15T05:46:43Z No. of bitstreams: 1 ANN-based_estimation_of_MEMS_diaphragm_response_An_application_for_three_leaf_clover_diaphragm_based_Fabry-Perot_interferometer.pdf: 2371569 bytes, checksum: 09c4a7af8c7122e82198ca9f16cb0a30 (MD5)en
dc.description.provenanceMade available in DSpace on 2023-02-15T05:46:43Z (GMT). No. of bitstreams: 1 ANN-based_estimation_of_MEMS_diaphragm_response_An_application_for_three_leaf_clover_diaphragm_based_Fabry-Perot_interferometer.pdf: 2371569 bytes, checksum: 09c4a7af8c7122e82198ca9f16cb0a30 (MD5) Previous issue date: 2022-06-23en
dc.embargo.release2024-06-23
dc.identifier.doi10.1016/j.measurement.2022.111534en_US
dc.identifier.eissn1873-412X
dc.identifier.issn0263-2241
dc.identifier.urihttp://hdl.handle.net/11693/111283
dc.language.isoTurkishen_US
dc.publisherElsevier BVen_US
dc.relation.isversionofhttps://doi.org/10.1016/j.measurement.2022.111534en_US
dc.source.titleMeasurementen_US
dc.subjectMachine learningen_US
dc.subjectMEMSen_US
dc.subjectDiaphragm designen_US
dc.subjectFEMen_US
dc.subjectFabry-perot interferometeren_US
dc.titleANN-based estimation of MEMS diaphragm response: An application for three leaf clover diaphragm based Fabry-Perot interferometeren_US
dc.typeArticleen_US

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