Analysis of Friction Noise Mechanism in Lead Screw System of Autonomous Vehicle Seats and Dynamic Instability Prediction Based on Deep Neural Network.

deep neural network (DNN) friction noise mode-coupling mechanism squeal instability estimation squeal sensitivity map

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
05 Jul 2023
Historique:
received: 07 06 2023
revised: 29 06 2023
accepted: 04 07 2023
medline: 17 7 2023
pubmed: 14 7 2023
entrez: 14 7 2023
Statut: epublish

Résumé

This study investigated the squeal mechanism induced by friction in a lead screw system. The dynamic instability in the friction noise model of the lead screw was derived through a complex eigenvalue analysis via a finite element model. A two degree of freedom model was described to analyze the closed solutions generated in the lead screw, and the friction noise sensitivity was examined. The analysis showed that the main source of friction noise in the lead screw was the bending mode pair, and friction-induced instability occurred when the ratio of the stiffness of the bending pair modes was 0.9-1. We also built an architecture to predict multiple outputs from a single model using deep neural networks and demonstrated that friction-induced instability can be predicted by deep neural networks. In particular, instability with nonlinearity was predicted very accurately by deep neural networks with a maximum absolute difference of about 0.035.

Identifiants

pubmed: 37448018
pii: s23136169
doi: 10.3390/s23136169
pmc: PMC10346787
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Ministry of Trade, Industry and Energy
ID : 20004965

Références

Sensors (Basel). 2020 Jan 22;20(3):
pubmed: 31979141

Auteurs

Jaehyeon Nam (J)

AI & Mechanical System Center, Institute for Advanced Engineering, Youngin-si 17180, Republic of Korea.

Soul Kim (S)

AI & Mechanical System Center, Institute for Advanced Engineering, Youngin-si 17180, Republic of Korea.

Dongshin Ko (D)

AI & Mechanical System Center, Institute for Advanced Engineering, Youngin-si 17180, Republic of Korea.

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