A Study on NVH Monitoring Automation using AI/DS

AI/DS-based innovation is taking place in all industries with the aim of maximizing technological innovation and work efficiency, vehicle NVH fields are no exception. In the vehicle NVH test field, NVH development automation and NVH monitoring automation are being carried out with the aim of integrated test automation, and this study is about NVH monitoring automation. The analysis process and results of PG(Proving Ground) driving monitoring automation were examined, and it was confirmed that the NVH performance analysis using one long driving data can be reliably automated. In addition, necessary AI models for outside driving monitoring automation and the expected analysis results are summarized. A methodology for predicting road noise performance is explained using NVH vehicle models using driving big data and deep learning, and the prediction result was represented.

Authors

Institutions

Publication Details

Journal
NOISE-CON proceedings
Published
2025-10-22
DOI
https://doi.org/10.3397/in_2025_1075717
Citations
1
Primary Topic
Vehicle Noise and Vibration Control
Type
article
Field-Weighted Citation Impact
0.68
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Study on NVH Monitoring Automation using AI/DS

Daehun Song, Cheolkeun Ha, Jun‐Ho Jang, M. S. Lee
1 citations
NOISE-CON proceedings
Vehicle Noise and Vibration Control
0.68
article

A Study on NVH Monitoring Automation using AI/DS

Daehun Song, Cheolkeun Ha, Jun‐Ho Jang, M. S. Lee
article en
1 citations

Abstract

AI/DS-based innovation is taking place in all industries with the aim of maximizing technological innovation and work efficiency, vehicle NVH fields are no exception. In the vehicle NVH test field, NVH development automation and NVH monitoring automation are being carried out with the aim of integrated test automation, and this study is about NVH monitoring automation. The analysis process and results of PG(Proving Ground) driving monitoring automation were examined, and it was confirmed that the NVH performance analysis using one long driving data can be reliably automated. In addition, necessary AI models for outside driving monitoring automation and the expected analysis results are summarized. A methodology for predicting road noise performance is explained using NVH vehicle models using driving big data and deep learning, and the prediction result was represented.

NOISE-CON proceedingsVol. 272(2)
Hyundai Motors (South Korea) (KR)
Openalex Percentile: Top 24%
Vehicle Noise and Vibration Control
0.68
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.