METHODS OF DIAGNOSIS OF DIFFERENT STRUCTURES OF TRIBOSYSTEMS BY ACOUSTIC EMISSION METHOD
DOI:
https://doi.org/10.18372/0370-2197.2(91).15525Keywords:
tribosystem, acoustic emission, cluster analysis, informative frequency, informative amplitude, diagnostic technique, peak factor to signal, wear rate, coefficient of frictionAbstract
In the presented work, a technique for diagnosing various designs of tribosystems using acoustic emission methods has been developed. The development of the methodology is based on the following assumptions. The activity of acoustic emission during the operation of the tribosystem will depend on the rate of deformation of materials on the spots of actual contact. The total acoustic signal from the friction zone is formed as a result of the interference of the primary acoustic signals from the spots of actual contact with the friction surface, satisfying the coherence condition. Based on these assumptions, the paper presents an expression for calculating the informative frequency, which will be generated by the tribosystem during operation. The diagnostic technique contains the following steps: determination of the informative frequencies at which it is necessary to register the amplitudes; determination of amplitude values that carry maximum information; dividing the general acoustic signal into clusters and establishing a functional relationship between the values of the peak factor of the clusters and the values of the friction coefficient, wear rate and running-in time of tribosystems in online mode. The work substantiates the values of the informative amplitudes of various clusters in relation to the base cluster. It is shown that an increase in the informative frequency from 250 to 500 kHz, increases the value of the informative amplitude by 17,6…43,75%. The results obtained indicate that this fact must be taken into account when developing methods for diagnosing tribosystems. The use of the developed technique will increase the robustness of the tribosystem diagnostics method and identify surface processes during wear.
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