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Development of a New Algorithm for Automatic Detection and Rating of Squeak and Rattle Events in Automobiles

Kuttan Chandrika, Unnikrishnan
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1248893155

Abstract Details

2009, MS, University of Cincinnati, Engineering : Mechanical Engineering.
Squeak and rattle (S and R) performance is one of the main factors which affect the perceived NVH performance of a vehicle. Historically, squeak and rattles were detected and analyzed using subjective methods. In addition to inherent subjective nature, high cost and long test durations are major drawbacks of subjective methods. This thesis aims to arrive at a procedure for automatic detection and rating of the S and R events. The proposed algorithm uses the wavelet transform technique to extract the time-frequency information and the Zwicker’s loudness model to obtain a perceptional squeak and rattle metric. Instantaneous values of specific loudness distribution obtained from Zwicker’s loudness model are used along with a leaky integration procedure to obtain the transient specific loudness time histories, from which the perceived transient loudness time history is obtained. The detection threshold of the S and R event was identified by a clever interpretation of the jury test results using the perceived transient loudness as the metric. The proposed algorithm showed a good promise in detecting S and R events, showing well correlated results with the jury tests. A varied form of the perceived transient loudness was developed and used for the purpose of quantitative rating of severity of S and R events. Subjective tests showed the rating metric is correlated fairly well with the subjective rating of S and R events except those with energy distribution predominantly in low frequencies. The new algorithm developed in this work will be able to automate detection and rating of the S and R events with good accuracy.
Jay Kim, PhD (Committee Chair)
Randall Allemang, PhD (Committee Member)
Allyn Phillips, PhD (Committee Member)
61 p.
Electrical Engineering; Engineering; Mechanical Engineering
squeak; rattle; detection algorithm; analystic wavelets; percieved transient loudness

Recommended Citations

Citations

  • Kuttan Chandrika, U. (2009). Development of a New Algorithm for Automatic Detection and Rating of Squeak and Rattle Events in Automobiles [Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1248893155

    APA Style (7th edition)

  • Kuttan Chandrika, Unnikrishnan. Development of a New Algorithm for Automatic Detection and Rating of Squeak and Rattle Events in Automobiles. 2009. University of Cincinnati, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1248893155.

    MLA Style (8th edition)

  • Kuttan Chandrika, Unnikrishnan. "Development of a New Algorithm for Automatic Detection and Rating of Squeak and Rattle Events in Automobiles." Master's thesis, University of Cincinnati, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1248893155

    Chicago Manual of Style (17th edition)

ucin1248893155
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© 2009, all rights reserved.
This open access ETD is published by University of Cincinnati and OhioLINK.