A Fault Feature Extraction Method for Rotating Machinery Based on Fractional Holography Principle

Abstract

The invention discloses a method for extracting fault features of rotating machinery based on the principle of fractional-order holography, which comprehensively utilizes the ability of fractional-order Fourier transform to process non-stationary signals and the ability of holographic spectrum to accurately reflect the state of the unit, and is applied to the information of the start-stop process of rotating machinery extraction and troubleshooting. This method fuses the fractional Fourier transform and the holographic spectrum from the data layer, reconstructs the two-dimensional and three-dimensional holographic spectrum and the holographic waterfall image and applies them to the processing of the unsteady state information of the rotor starting and stopping, and realizes the multiple start and stop signals. The extraction of a variety of characteristic parameters expands the scope of application of traditional holographic spectra, breaks through the limitations of Bode diagram analysis in traditional situations, expands the level and scope of fault monitoring and diagnosis of rotating machinery, and provides a powerful tool for the healthy and reliable operation of rotating machinery. support.

Description

Technical field [0001] The invention belongs to the field of mechanical equipment fault diagnosis, and particularly relates to a method for extracting fault features of rotating machinery based on the principle of fractional Fourier transform-holographic spectrum. Background technique [0002] The starting and stopping of rotating machinery is an accident-prone stage during unit operation. During the start-stop process, the unit experienced an unsteady state process. The start-stop process contains a wealth of unit status information, which is not available under normal steady-state operation. At present, the unbalance information of rotary machinery is basically extracted from the steady-state process, and the research on extracting the unbalance information from the vibration signal of the starting and stopping process is relatively rare. How to make full use of the vibration information in the start-stop process, analyze the Bode diagram, force and force couple decomposition,...

AI Technical Summary

Problems solved by technology

[0004] However, holographic spectrum technology also has some shortcomings: the main analysis object is the steady-state signal of fixed speed, it is difficult to analyze the speed fluctuation and the non-stationary signal in the process of speed up and down, which greatly limits the scope of application

In the past, the traditional order ratio analysis method had a complicated process when extracting the multiplier component, and required high accuracy for the calculation of the rotational speed, and it was difficult to determine the parameters such as the number of filter stages and bandwidth. Fractional Fourier transform can be more simple and effective Processing of Chirp Signals

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