A method, system and device for extracting mechanical vibration characteristic indexes

Abstract

The invention discloses a method, system and device for extracting mechanical vibration characteristic indexes. The method comprises the steps of a mechanical original vibration signal, performing time synchronous averaging on the mechanical original vibration signal to obtain a time synchronous averaging signal, obtaining a frequency spectrum of the time synchronous averaging signal, obtaining afirst gear characteristic index set and a second gear characteristic index set according to the time synchronous average signal and the frequency spectrum of the time synchronous averaging signal, andthus obtaining gear characteristic indexes. The system comprises functional modules such as a signal acquisition submodule. The device comprises a memory storing at least one program and a processorexecuting the at least one program. According to the invention, corresponding preprocessing and extraction processing are performed on the mechanical original vibration signal, the signal-to-noise ratio of the original vibration signal is improved, vibration characteristic indexes which are applicable to describing a gear are extracted, the extracted vibration characteristic indexes reflect healthconditions of the gear comprehensively and effectively, thereby being convenient for performing fault diagnosis, and especially early-stage fault diagnosis. The method, system and device disclosed bythe invention can be widely applied to the technical field of mechanical fault diagnosis.

Description

technical field [0001] The invention belongs to the technical field of mechanical vibration monitoring, in particular to the technical field of helicopter health use monitoring. Background technique [0002] Explanation of terms: [0003] FFT: Fast Fourier Transformation, fast Fourier transform; [0004] TSA: Time Synchronous Averaging, time domain synchronous averaging; [0005] RMS: Root Mean Square, root mean square value; [0006] MA: Mean Amplitude, average amplitude; [0007] RA: Root Amplitude, square root amplitude; [0008] Kur: Kurtosis of signal, kurtosis; [0009] SF: shape Factor, waveform index; [0010] CF: crest Factor, peak factor; [0011] IF: Impulse FaCtor, pulse indicator; [0012] CLF: clearance Factor, margin indicator; [0013] KV: Kurtosis Value, kurtosis index; [0014] XPP: peak to peak of signal, peak-to-peak signal; [0015] M6A: Statistical moment (order 6), 6th order moment; [0016] M8A: Statistical moment (order 8), 8th order mome...

AI Technical Summary

Problems solved by technology

When the gear fails, there will be side frequency components of the gear meshing frequency and its multiplier in the vibration signal spectrum, and the spectrum structure is complex

[0020] In addition, for the vibration monitoring of bearings, since the installation position of the sensor is often far away from the bearing, the bearing fault features in the collected vibration signals are not obvious, especially in the early fault stage of the bearing, the fault feature signals are more likely to be overwhelmed by noise

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