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A Method for Extracting Characteristic Lines of Dynamic Unbalance of Train Cardan Shaft

A technology of dynamic unbalance and characteristic spectral lines, which is applied in the testing of machines/structural components, testing of mechanical components, instruments, etc., can solve problems such as unremoved noise signals, frequency aliasing, and indistinct characteristic frequencies, etc., to reduce Effects of noise, reducing noise interference, eliminating unwanted signals and highlighting characteristic spectral lines

Active Publication Date: 2019-08-23
SOUTHWEST JIAOTONG UNIV
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  • Abstract
  • Description
  • Claims
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Problems solved by technology

[0006] The purpose of the present invention is to: solve the technical problems such as frequency aliasing, characteristic frequency is not obvious, and noise signal is not eliminated in the existing characteristic spectral line extraction method

Method used

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  • A Method for Extracting Characteristic Lines of Dynamic Unbalance of Train Cardan Shaft
  • A Method for Extracting Characteristic Lines of Dynamic Unbalance of Train Cardan Shaft
  • A Method for Extracting Characteristic Lines of Dynamic Unbalance of Train Cardan Shaft

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Embodiment Construction

[0027] The present invention will be further described in detail below in conjunction with test examples and specific embodiments. However, it should not be understood that the scope of the above subject matter of the present invention is limited to the following embodiments, and all technologies realized based on the content of the present invention belong to the scope of the present invention.

[0028] Such as figure 1 Shown is the flow chart of the method for extracting the dynamic unbalance characteristic spectrum of the train cardan shaft of the present invention; wherein, the following steps are included:

[0029] Step S1: Perform dual-tree complex wavelet packet transformation on the collected cardan shaft vibration signals to obtain N equal frequency band component signals. Specifically, the number of layers of the dual-tree complex wavelet packet transform is 2-4.

[0030] Step S2: Construct a corresponding Hankel matrix according to each component signal, then perf...

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Abstract

The invention discloses a method for extracting characteristic spectral lines of the dynamic unbalance of the cardan shaft of a train. The method combines a double-tree complex wavelet packet, a singular value difference spectrum and an envelope spectrum. The complex wavelet packet transform can not only ensure the invariance of signal translation, but also not cause frequency aliasing and false frequency signals. Moreover, according to the difference spectrum, determining the number of reconstructions of singular values ​​can minimize noise and eliminate useless signals and highlight characteristic spectral lines. Therefore, the present invention can minimize noise interference and improve spectral line definition.

Description

technical field [0001] The invention relates to the field of dynamic unbalance fault diagnosis of a universal joint shaft of a train, in particular to a new method for extracting characteristic spectral lines of a dynamic unbalance of a universal joint shaft of a train based on a double-tree complex wavelet packet, a difference spectrum and an envelope spectrum. Background technique [0002] The dynamic performance of the train transmission system is an important factor for the safety of train operation, and its main components are traction motors, gearboxes, cardan shafts, wheelsets and safety devices. The cardan shaft is the core component of the transmission system, and its main function is to transmit the driving torque of the motor to the gearbox. The cardan shaft transmits the traction torque during the running of the train, which is prone to eccentricity. Moreover, with the increase of the train’s running mileage, the wear of the cardan shaft, the looseness of the ba...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01M13/028
Inventor 王开云李倩林建辉杨敏李艳萍
Owner SOUTHWEST JIAOTONG UNIV
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