THE AUTO-SYNCHRONIZED WAVELET TRANSFORM ANALYSIS FOR AUTOMATIC ACOUSTIC QUALITY CONTROL
✍ Scribed by S. GÜTTLER; H. KANTZ
- Publisher
- Elsevier Science
- Year
- 2001
- Tongue
- English
- Weight
- 489 KB
- Volume
- 243
- Category
- Article
- ISSN
- 0022-460X
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✦ Synopsis
A new feature vector for automatic acoustic quality control is presented and applied to the classi"cation of electric sliding sunroofs at the quality control point by analyzing the sliding noise. The speci"c features of the sound signals (signatures) which distinguish products of di!erent quality are not explicitly sought, because these signatures are highly speci"c for each application. Instead, the property is used that the relevant information about the sound signals can be resolved by the ears of experts. The time-frequency resolution of the ear is approximated by a wavelet transform of the signals. As a new approach to the important problem of noise reduction the concept of auto-synchronized wavelet transforms is introduced which allows wavelet transforms (and more general time}frequency representations) to be averaged in the time domain without losing the time-resolved information in the signals. By this averaging process, statistical #uctuations (noise, parameter drifts) can be reduced signi"cantly to reveal the characteristic features of the signals. The classi"cation can then be performed by a next neighbour search on a training set. The concept of auto-synchronized wavelet transforms is developed in a mathematically formal way and the properties of the feature vectors obtained are studied by using arti"cial noisy signals before applying this method to the experimental data.