METHOD FOR DIAGNOSIS OF TECHNICAL CONDITION OF MACHINES ON INDIRECT INDICATORS Russian patent published in 2017 - IPC F04B51/00 G01M15/00 

Abstract RU 2610366 C1

FIELD: measurement technology.

SUBSTANCE: invention relates to vibration monitoring of the machines and mechanisms and can be used for the vibration monitoring of the machines. The process for diagnostic of the machines on indirect indicators, mainly on housing vibration, includes measurement of vibration in the informative point of the machine frame, the restoration of the likelihood of vibration of the distribution function, according to the parameters of which judge on the availability and level of faults and/or defects of the machine, remember the time realization of vibration, convert it into implementation, the value of which corresponds to the optimum for the diagnosis of vibration parameters, reduced probability distribution function of instantaneous values optimal for the diagnosis of the vibration option in the current measurement, determine the value of a sample quantile parameter vibration for a given value of the probability distribution function for which judge on the availability and level of faults and/or defects of the machine. Then build a knowledge base in the form of a table depending on linking the place of vibration measurement node of the diagnosed machine, malfunction class, quantile of the distribution function of the parameter of vibration specified level and its importance for the various levels of malfunctions of evaluations and/or defects in the machine due to cause-and-effect relationships between them and the state of the machine. The length of the time series is selected depending on the required reliability of determining quintile. Allows to determine the status of the relevant assemblies and parts of piston machine.

EFFECT: improved diagnostics.

11 dwg, 2 tbl

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RU 2 610 366 C1

Authors

Kostyukov Vladimir Nikolaevich

Naumenko Aleksandr Petrovich

Bojchenko Sergej Nikolaevich

Kostyukov Aleksej Vladimirovich

Dates

2017-02-09Published

2016-01-11Filed