Blind adaptive extraction of impulsive signatures from sound and vibration signals
Başlık çevirisi mevcut değil.
- Tez No: 508369
- Danışmanlar: Prof. JOHAN E. CARLSON, Dr. PATRIK PAAJARVI
- Tez Türü: Doktora
- Konular: Elektrik ve Elektronik Mühendisliği, Electrical and Electronics Engineering
- Anahtar Kelimeler: Belirtilmemiş.
- Yıl: 2017
- Dil: İngilizce
- Üniversite: Luleå University of Technology
- Enstitü: Yurtdışı Enstitü
- Ana Bilim Dalı: Belirtilmemiş.
- Bilim Dalı: Belirtilmemiş.
- Sayfa Sayısı: 180
Özet
Özet yok.
Özet (Çeviri)
The two main questions in science,“why”and“how,”are answered here in the context of statistical signal processing applied to vibration analysis and ultrasonic testing for fault detection and characterization in critical materials such as rolling bearings and thin layered media. Both types of materials are of interest in industrial processes. In such processes, it is important to ensure the best operating conditions for rolling bearings and good product quality for thin layered materials. The methods defended in this thesis are designed for the retrieval of impulsive signals, which represent either faults or responses to excitation, arising from such equipment and materials. Because the measurements collected via sensors usually consist of signals masked by unknown systems and noise, retrieving the information-rich portion of such a signal is often challenging. By exploiting the statistical characteristics of these signals due to their natural structure, a linear system is designed to recover the signals of interest in different scenarios. The primary approach is to suppress undesired components while enhancing impulsive events through iterative adaptation of a filter. Signal recovery is accomplished by optimizing an objective (skewness) that quantify the presumed characteristics, raising the questions of the objective surface topology and the probability of ill convergence. To address these questions, mathematical proofs, experimental evidence and comprehensive discussions are presented in the presented contributions, each aiming to answer a specific question. The purpose of the theoretical study is to fill a gap in signal processing research by providing analytical and numerical results, especially on skewness surface characteristics, for a signal model (periodic impulses) built based on harmonically related sinusoids. With an understanding of the inner workings and the sufficient conditions, the same approach is applied to different classes of signals encountered during ultrasonic testing, such as aperiodic finite energy signals (material impulse response) and very-short-duration impulses acting as excitations. A similar approach aimed at enhancing another attribute, sparseness, is investigated through numerical experiments on ultrasonic echoes as a case study. In summary, an objective quantifying a certain characteristic is optimized to recover the signal portions that carry valuable information buried in noisy vibrations and ultrasonic measurements. Considering that research is deemed successful if it creates more questions than it answers and allows ideas to flourish, thereby creating scientific value, the presented work aims to achieve this in the context of statistical signal processing. Analytical derivations supplemented by experiments form the basis for observations, discussions and further questions to be studied with regard to similar phenomena arising from different sources in nature.
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