From Transmission Error Measurements to Angular Sampling in Rotating Machines with Discrete Geometry
Author(s) -
Didier Rémond,
Jarir Mahfoud
Publication year - 2004
Publication title -
shock and vibration
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.418
H-Index - 45
eISSN - 1875-9203
pISSN - 1070-9622
DOI - 10.1155/2005/205291
Subject(s) - sampling (signal processing) , harmonics , transmission (telecommunications) , signal (programming language) , encoder , acoustics , noise (video) , amplitude , observational error , rotary encoder , computer science , optics , mathematics , physics , detector , statistics , telecommunications , computer vision , quantum mechanics , voltage , image (mathematics) , programming language
The benefits of angular sampling when measuring various signals in rotating machines are presented and discussed herein. The results are extracted from studies on transmission error measurements with optical encoders in the field of power transmissions and can be broadened to include phase difference measurements, such as torsional vibrations, and applied to control, monitoring and measurement in rotating machines with discrete geometry. The main conclusions are primarily that the use of angular sampling enables the exact location of harmonics and, consequently, the obtaining of spectral amplitude components with precision. This is always true even if the resolution of encoders is not directly related to the studied discrete geometry. It then becomes possible to compare these harmonics under different operating conditions, especially when speed varies, without changing any parameters in spectral analysis (window length, spectral resolution, etc.). Moreover, classical techniques of improving signal to noise ratio by averaging become fully efficient in the detection of defective elements. This study has been made possible thanks to the technique of transmission error measurement with optical encoders that allows the comparison of sampling procedures, based on the same raw data
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