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Squeak and rattle (S&R) noises are undesirable noises caused by friction-induced vibration or impact between surfaces. While several computer programs have been developed to automatically detect and rate S&R events over the years, no reported work has been found that can detect squeak and rattle noises and distinguish them. Because the causes of squeak noises and rattle noises are different, knowing if it is a squeak noise or rattle noise will be very helpful for automotive engineers to choose an appropriate measure to solve the problem. The authors have developed a new algorithm to differentiate squeak noises and rattle noises, and added it to the S&R detection algorithm they had developed previously. The new algorithm utilizes a combination of sound quality metrics, specifically sharpness, roughness, and fluctuation strength.

Squeak and rattle (S&R) problems in body structure and trim parts have become serious issues for automakers because of their influence on the initial quality perception of consumers. In this study, various CAE and experimental methods developed by Hyundai Motors for squeak and rattle analysis of door systems are reported. Friction-induced vibration and noise generation mechanisms of a door system are studied by an intelligent combination of experimental and numerical methods. It is shown that the effect of degradation of plastics used in door trims can be estimated by a numerical model using the properties obtained experimentally. Effects of changes in material properties such as Young's modulus and loss factor due to the material degradation as well as statistical variations are predicted for several door system configurations. As a new concept, the rattle and squeak index is proposed, which can be used to guide the design.

A new algorithm to detect and to quantify the seriousness of the detected squeak and rattle (S&R) events was developed. A T-F analysis technique called AWT, the Zwicker loudness model and leaky integration are employed to define new concepts we called transient specific loudness time histories and perceived transient loudness time history. The detection threshold of the perceived transient loudness was identified by a clever interpretation of jury test results. The proposed algorithm showed a good promise producing results that are well correlated with the jury tests. The new algorithm developed in this work will be able to automate detection and rating of the S&R events with good accuracy and with minimum possibility of false alarm under normal operating conditions

The analytic wavelet transform (AWT) is a wavelet transform that works much like a transient Fourier transform. Therefore the AWT enables utilizing advantages of both the wavelet transform and Fourier transform. A special form of AWT developed for transient vibration and acoustics signal analyses is applied to various engineering signals in this paper. Application examples include a general time-frequency (T-F) analysis, analysis of exposures to impulsive vibrations and noises, and estimation of reverberation times. Some new definitions such as the T-F noise reduction and frequency weighted time history are defined by taking the advantage of unique capabilities of the AWT. Possible automotive applications of these new concepts are briefly discussed.

This paper is intended to describe some of the advances in automotive NVH research and applications based on recent developments in the Structural Dynamics Research Laboratory (SDRL) at the University of Cincinnati. State-of-the-art vibro-acoustic research capabilities and infrastructure ranging from advanced vibration modal analysis and spectral techniques for linear and nonlinear automotive systems to computational tools for structure-borne acoustic noise generation, transmission and synthesis problems are discussed. These systems have been devised with the intent of integrating a versatile set of experimental, computational and analytical approaches in order to be able to investigate a variety of crucial automotive NVH concerns. The materials will be grouped into three separate but closely related sets of applications consisting of (i) powertrain noise and vibration control, (ii) analysis and control vehicle system dynamics, and (iii) NVH and sound quality.