@article {Hamzaoui:2015:0736-2935:1011,
title = "Indicators of real gear transmission defects using sound perception",
journal = "INTER-NOISE and NOISE-CON Congress and Conference Proceedings",
parent_itemid = "infobike://ince/incecp",
publishercode ="ince",
year = "2015",
volume = "251",
number = "1",
publication date ="2015-04-13T00:00:00",
pages = "1011-1017",
itemtype = "ARTICLE",
issn = "0736-2935",
url = "https://ince.publisher.ingentaconnect.com/content/ince/incecp/2015/00000251/00000001/art00080",
author = "Hamzaoui, Nacer and Younes, Ramdane and Ouelaa, Nouredine",
abstract = "Monitoring and diagnosing the defects of rotating machines are performed in the framework of conditional maintenance, and are 75% based on vibration analysis. Regarding maintenance procedures, interventions can be classified into two levels: 1. the first level is devoted to monitoring
and uses scalar indicators (total level, Peak factor, Kurtosis, Factor K, etc.) to signal the presence of a defect, 2. the second level, characterized by the diagnosis, intervenes after the monitoring stage and uses much more detailed indicators (Spectrum, Zoom, Envelope, Cepstrum, etc.),
in order to locate the nature and position of the defect more precisely. The use of these indicators still comes up against difficulties of interpretation in the case of complex industrial machines, which can have several defects. Many researchers still work on the improvement or the development
of indicators resulting from vibratory or acoustic signals. Feedback from experience is based mainly on the competence of the maintenance agent and more especially on acoustical and vibratory perception related to mechanical defects. We use an acoustic approach to perception in order to optimize
monitoring indicators and improve the detection of defects. The aim of this paper is to use sound perception to study gear defects liable to occur on rotating machines. Acoustic sounds were acquired using the processing software DynamX V.7 and analysed with the paired comparison method to
find a correlation between the sound perception and scalar indicators. The results show that perception tests allowed classifying gear defect sounds in an order of degradation. The correlation between objective and subjective aspects highlights an important relationship between scalar indicators
(kurtosis, Crest Factor, the spectral centre of gravity (SCG), root mean square (RMS)) and the difference between gear sounds characterized by their distance in proximity space. Vibratory analysis is also performed to monitor gear degradation state and confirm the sound perception results
obtained by the approach proposed.",
}