Iterative Teager energy operator demodulation method and system

Abstract

The invention discloses an iterative Teager energy operator (TEO) demodulation method and an iterative TEO demodulation system. The demodulation method comprises the following steps of: acquiring an original signal; performing energy operator demodulation to obtain a signal energy function and a signal differential energy function of the signal, and performing energy separation to obtain an amplitude envelope and instantaneous frequency; performing low-pass filtration to obtain an instantaneous amplitude envelope and the instantaneous frequency of the signal; subtracting the calculated instantaneous amplitude envelope from the amplitude envelope to obtain a residual signal component; and comparing the energy of the residual signal component with the energy of the original signal to obtain an energy difference, continuing the energy operator demodulation if the energy difference is greater than a preset value, otherwise finishing the energy operator demodulation. The iterative TEO demodulation can be implemented through a hardware platform consisting of a digital circuit and an analogue circuit or through a software algorithm on the basis of combination of an energy demodulation algorithm, zero-phase low-pass filtration and energy judgment, and the finally obtained demodulation signal component can be stored and displayed by a selected personal computer (PC) according to the type of the signal or can be displayed in real time by an analogue oscilloscope.

Description

technical field [0001] The invention relates to a signal processing method and system, in particular to an iterative TEO demodulation method and system suitable for AM-FM signals. Background technique [0002] When the rotating mechanical components in the mechanical system have partial faults, the vibration signals of mechanical faults often appear in the form of modulation, such as rolling bearing fault vibration signals, gearbox fault vibration signals, and rotor rubbing fault vibration signals. The envelope and phase of these modulation signals contains a wealth of fault information, so demodulation analysis is an effective method for extracting fault features and diagnosing fault types. At present, in the field of mechanical fault diagnosis, commonly used demodulation methods are: Hilbert transform demodulation, energy operator separation algorithm (Energy operator separation algorithm, EOSA), high-pass absolute value analysis demodulation, detection filter demodulation...

AI Technical Summary

Problems solved by technology

Among them, the Hilbert-Huang transform and the EMD-based TEO demodulation method have good adaptability, but both have problems such as mode aliasing and boundary

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