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Non‐Linear Signal Analysis Applied to Surface Wear Condition Monitoring in Reciprocating Sliding Testing Machines
When the surfaces of two elastic bodies present relative motions under certain amount of contact pressure the mechanical system can be unstable. Experiments conducted on elastic bodies in contact shown that the dynamic system is self-excited by the non-linear behavior of the friction forces. The mai...
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Published in: | Shock and vibration 2006-01, Vol.13 (4-5), p.327-341 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that cite this one |
Online Access: | Get full text |
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Summary: | When the surfaces of two elastic bodies present relative motions under certain amount of contact pressure the mechanical system can be unstable. Experiments conducted on elastic bodies in contact shown that the dynamic system is self-excited by the non-linear behavior of the friction forces. The main objective of this paper is to estimate the friction force using the vibrations signals, measured on a reciprocating wear testing machine, by the proposed non-linear signal analysis formulation. In the proposed formulation the system global output is the sum of two outputs produced by a linear path associated in parallel with a non-linear path. This last path is a non-linear model that represents the friction force. Since the linear path can be identified by traditional signal analysis, the non-linear function can be evaluated by the global input/output relationships. Validation tests are conducted in a tribological system composed by a sphere in contact with and a prismatic body, which has an imposed harmonic motion. The global output force is simultaneously measured by a piezoelectric and by a piezoresistive load cells. The sphere and prismatic body vibrations are measured by a laser Doppler vibrometer and by an accelerometer respectively. All signals are digitalized at the same time base and the data is transferred to a microcomputer. The non-linear signal analysis technique uses this data to identify the friction force. |
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ISSN: | 1070-9622 1875-9203 |
DOI: | 10.1155/2006/938951 |