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Current characteristic frequency extraction method of machine tool transmission system with immune random resonance

A technology of characteristic frequency and transmission system, applied in the direction of frequency measurement device, gene model, etc., to achieve the effect of sensorless detection and improve the quality of system optimization

Inactive Publication Date: 2011-09-07
XI AN JIAOTONG UNIV
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Problems solved by technology

[0005] In order to overcome the above-mentioned shortcomings of the prior art, the object of the present invention is to provide a method for extracting the current characteristic frequency of the transmission system of a machine tool immune to stochastic resonance, which solves the problem of stochastic resonance of the secondary sampling of the large parameter signal of the servo motor current, thereby achieving the ideal system output, and extract the characteristic frequency components in the current

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  • Current characteristic frequency extraction method of machine tool transmission system with immune random resonance
  • Current characteristic frequency extraction method of machine tool transmission system with immune random resonance
  • Current characteristic frequency extraction method of machine tool transmission system with immune random resonance

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[0034] The present invention will be described in detail below in conjunction with the accompanying drawings.

[0035] refer to figure 1 , a method for extracting the characteristic frequency of the current of a machine tool transmission system immune to stochastic resonance, comprising the following steps:

[0036] 1) Use the current sensor to collect the current signal x(n) of the servo drive motor in the transmission system, where n is the number of sampling points, and n is an integer greater than zero;

[0037] 2) Calculate the rotation frequency f of the output shafts at all levels in the transmission system r and meshing frequency f n ,in,

[0038] f r =f i *Z (1)

[0039] f n =f r *m (2)

[0040] f i is the input frequency of the transmission system (the rotation frequency of the input shaft at all levels), Z is the transmission ratio, and m is the number of teeth of the rotating shaft, then the characteristic frequency component of the transmission system in...

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Abstract

The invention relates to a current characteristic frequency extraction method of a machine tool transmission system with immune random resonance comprises the following steps: collecting a current signal of a servo driving motor of the transmission system by a current sensor; calculating the gyro frequency and the meshing frequency of each output shaft of the transmission system; processing the collected current signal by a Butterworth filter-type bandpass filter; processing the filtered current signal by frequency shift; optimizing the current signal processed by frequency shift by a multi-mode immune clonal selection method to obtain secondary sampling random resonance system parameter; selecting a parameter with the largest affinity as the optimal secondary sampling scale and structuresystem parameter; finally, achieving the compression of the input signal according to the optimal secondary sampling scale, wherein the largest peak component of the corresponding spectrum can be transformed to the characteristic frequency component of the machine tool transmission system. By using the current characteristic frequency extraction method, the optimization quality of a secondary sampling random resonance system of the current signal of the servo motor with large frequency scale can be improved, and the weak characteristic frequency of the transmission system can be effectively extracted.

Description

technical field [0001] The invention relates to the technical field of machine tool transmission feature extraction, in particular to a method for extracting current feature frequency of a machine tool transmission system immune to stochastic resonance. Background technique [0002] One of the main gaps between domestic high-end CNC machine tools and similar foreign machine tools is the problem of precision maintenance, and an important factor leading to abnormal precision and loss is the operation defect of functional components. Although the self-diagnosis function of the CNC system can detect most of the electrical system faults, it can't do anything about the problems that cause organic faults during the operation of the machine tool, such as the vibration of the spindle of the machine tool and the wear of the lead screw. Therefore, how to detect machine tool faults caused by the motion system has become a bottleneck problem that restricts the stability of machine tool m...

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Application Information

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IPC IPC(8): G01R23/02G06N3/12
Inventor 梁霖徐光华刘飞张熠卓
Owner XI AN JIAOTONG UNIV
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