Intelligent identification method for vibration characteristics of rotating mechine

Abstract

The invention relates to an intelligent identification method for vibration characteristics of a rotating machine, and the intelligent identification method sequentially comprises the following steps:1, converting a speed or acceleration time domain signal of mechanical vibration into a frequency domain envelope spectrum through signal processing, and extracting a frequency upper limit value fmaxof the envelope spectrum; 2, at least screening out high-energy harmonics with the frequency range within fmax / Nmax through amplitude comparison, wherein Nmax is the upper limit multiple of frequencymultiplication for frequency multiplication verification of the high-energy harmonics; 3, sequentially extracting at least one group of characteristic parameters, based on respective amplitudes and / or frequencies, of the peak values of the frequency doubling regions from 1 to Nmax of the high-energy harmonics, wherein the peak value of the frequency doubling region of the high-energy harmonics isthe high-energy harmonics; and 4, inputting the at least one group of characteristic parameters of each high-energy harmonic into a machine learning intelligent algorithm one by one for training andcalculation. By the adoption of the intelligent identification method, the recognition efficiency and accuracy of mechanical faults can be greatly improved, and real-time online monitoring can be conducted on the rotating machine.

Description

technical field [0001] The invention relates to an intelligent identification method for the vibration characteristics of a rotating machine based on an envelope spectrum, in particular to an intelligent diagnosis method for a rotating machine failure. Background technique [0002] Frequency domain analysis is a common method for diagnosing mechanical faults, which is generally achieved by converting mechanical vibration signals (such as speed or acceleration time domain signals) into frequency domain signals. Mechanical failures in rotating machines, such as damaged rotors, gears, or bearings, can cause systemic vibrations or shocks. The frequency response in the envelope spectrum reflects the nature and intensity of such shocks and shocks, so it can be used to accurately identify various faults of rotating machines. Specifically, vibration and shock induce defect harmonic families in the frequency spectrum. The harmonic family includes fundamental defect harmonics whose ...

AI Technical Summary

Problems solved by technology

Limited by personal ability and experience, its reliability and accuracy are difficult to meet the needs of reality

Not only that, manual diagnosis cannot monitor the equipment in real time, especially in the early stage of failure, it is often difficult to identify with the naked eye, and it is easy to miss the best and low maintenance time, leading to accidents

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