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Novel Method for Identifying and Assessing Rattle Noise on Vehicle Seatbelt Retractors Based on Time-Frequency Analysis State Key Laboratory of Vehicle NVH and Safety Technology

SAE Technical Papers (1906-current) Available online

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Format:
Book
Conference/Event
Author/Creator:
Liang, Linyuan, author.
Contributor:
Chen, Shuming
Lee, Micky
Conference Name:
Automotive Technical Papers (2021-01-01 : Warrendale, Pennsylvania, United States)
Language:
English
Physical Description:
1 online resource cm
Place of Publication:
Warrendale, PA SAE International 2021
Summary:
Rattle noise as an error state of cabin noise in vehicles has become an important topic both in research and application. In engineering, the commonly used method to evaluate and detect rattle issues is greatly dependent on experts' personal auditory perception. People judge a noise simply as "loud" and "not loud" or "qualified" and "unqualified." A more objective method needs to be developed to eliminate the randomness of subjective evaluation. In this paper, a rig test of the seatbelt retractors was performed, and simulated random excitation was applied to the test samples through the MB vibration test bench in a semi-anechoic chamber. The rattle noises were recorded by HEAD SQuadriga II. Various methods were employed to identify and assess the severity of rattle noise on seatbelt retractors. The Akaike Information Criterion (AIC) accompanying a sample entropy (SE)-based empirical mode decomposition denoising method was adopted to identify the rattle and calculate the rattle occurrence automatically. Psychoacoustic analysis, time-domain statistic method, and Hilbert-Huang transform were introduced to extract the acoustic and non-acoustic features of the rattle noises. On this basis, an objective rattle-assessing model was established to evaluate the rattle noise on the seatbelt retractor efficiently. The proposed method can well reflect the subjective evaluation and, therefore, can be extended to evaluate the rattle noise objectively
Notes:
Vendor supplied data
Publisher Number:
2021-01-5015
Access Restriction:
Restricted for use by site license

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