10.14489/td.2018.08.pp.004-012

2018, 08 August

DOI: 10.14489/td.2018.08.pp.004-012

Sokolova A. G., Balitsky F. Yа., Ivanova M. A., Shirman A. R.
REGRESSION FUNCTIONS AND OTHER PROBABILITY CHARACTERISTICS OF VIBRATIONS AS TOOLS TO ENHANCE CONDITION MONITORING SYSTEMS OF CENTRIFUGAL COMPRESSORS. Part 1
(pp. 4-12)

Abstract. The paper is dedicated to enhancing the depth and authenticity of rotor machinery diagnosing by using some symptoms, additional to typical sign listing, based as a rule on Fast Furie Transform use. Machinery faults emergence and development lead inevitably to nonlinear vibration features appearance/intensification, so frequency performances are becoming the inadequate diagnostic tool. The substantiation of necessity to apply not very widespread (but sometimes very useful) methods of vibration probabilistic characteristics analysis, including parameters of stochastic interdependence of vibrations in different measurement points is given. The results of usage probabilistic characteristics of shaft relative vibration in the journal bearings in two mutually perpendicular directions, including one-dimensional and two-dimensional probability distribution of instantaneous amplitude values, conditional distribution laws, shapes of regression functions are presented. On the example of vibroacoustical characteristics statistical analysis for centrifugal five-stage compressor in journal bearings in preemergency status, and immediately after the repair, the possibility to comprehensively evaluate the operational damage of the contacting surfaces of bearing assemblies and to judge the quality of their installation during the repair work is shown.

Keywords: vibration diagnostics, rotary machinery, journal bearing, relative shaft vibration, probability distribution density, stochastic interaction (liaison), cross regression function.

+ - About the Authors Click to collapse

A. G. Sokolova, F. Yа. Balitsky, M. A. Ivanova (Federal Budget-Funded Research Institute for Machine Science named after A. A. Blagonravov of Russian Academy of Sciences (IMASH RAN), Moscow, Russia) Email: Данный адрес e-mail защищен от спам-ботов, Вам необходимо включить Javascript для его просмотра. , Данный адрес e-mail защищен от спам-ботов, Вам необходимо включить Javascript для его просмотра.
A. R. Shirman (The Limited Liability Company “Spectrum Engineering”, Moscow, Russia) Email: Данный адрес e-mail защищен от спам-ботов, Вам необходимо включить Javascript для его просмотра.

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