Large-sized low-speed heavy-loaded gear box fault diagnosis method

A low-speed, heavy-duty, fault diagnosis technology, applied in machine gear/transmission mechanism testing, mechanical component testing, machine/structural component testing, etc., can solve problems such as problems that cannot be effectively solved for large-scale low-speed heavy-duty gearbox diagnosis , to achieve the effect of improving the fault diagnosis rate

Inactive Publication Date: 2009-07-01
BEIJING UNIV OF TECH
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Problems solved by technology

[0015] The purpose of the present invention is to solve the problem that the "double feature discrimination method" cannot effectively solve the problem of large-scale low-speed heavy-duty gearbox diagnosis, and proposes a method for fault diagnosis of large-scale low-speed heavy-duty gearbox

Method used

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  • Large-sized low-speed heavy-loaded gear box fault diagnosis method
  • Large-sized low-speed heavy-loaded gear box fault diagnosis method
  • Large-sized low-speed heavy-loaded gear box fault diagnosis method

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Embodiment Construction

[0049]Provide following embodiment in conjunction with the content of the inventive method:

[0050] image 3 It is the gearbox transmission diagram of the blooming mill of a steel mill. A set of monitoring system is assembled on the gear box of the blooming mill, and six measuring points are respectively arranged in different parts of the gear box. Due to external influences such as heavy load and impurities, the rolling elements of the C10 bearing suffered from pitting, wear and loosening. Until 18:45 on May 6, 2003, the outer ring ruptured under the sudden impact of rolling force during steel rolling. When the bearing is broken, the bottom of the shaft VI loses its support and cannot rotate on its center of rotation, resulting in unbalanced operation, the transmission relationship of the gears on it is destroyed, and the force on the tooth surface is uneven. Finally, under the action of various complex forces, Teeth on multiple gears were broken off.

[0051] (1) Use a p...

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Abstract

A method for fault diagnosis of a large low-speed heavy-duty gearbox belongs to the field of fault diagnosis of large low-speed heavy-duty gearboxes. It is a "three-feature discrimination method" based on the "double-feature discrimination method" combined with wavelet analysis to effectively extract fault features and diagnose. The "three-feature discrimination method" of the fault signal is: in the conventional Fourier spectrum The vibration signal characteristics of stationary power faults are analyzed on the graph, the vibration signal characteristics of impact power faults are analyzed on the resonance demodulation Fourier spectrum, and the vibration signal characteristics of impact faults are analyzed by wavelet. The adoption of the invention can effectively improve the fault diagnosis rate of the low-speed heavy-duty gearbox.

Description

technical field [0001] The invention relates to a method for fault diagnosis of a large-scale low-speed heavy-duty gearbox, which uses the shaft frequency fri and the meshing frequency fm of the shafts where two gears are located, considers the long-period and short-period faults of the gears, and compares the double-characteristic criteria for judgment, and The method of using wavelet analysis to judge more accurately belongs to the field of fault diagnosis of large low-speed and heavy-duty gearboxes. Background technique [0002] Enterprises carry out mechanical fault diagnosis, mainly to judge the degree of failure (deterioration) of mechanical parts. The steady power vibration is mainly composed of sinusoidal signals, quasi-sinusoidal signals and some random signals caused by insufficient shocks. This part of the signals is reflected in the conventional spectrogram as rods and lines of different frequencies or double frequency rods and lines. The vibration characteristi...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01M13/02G01M13/00G01M7/02G01N29/12
Inventor 高立新张雪松汤文亮张建宇胥永刚叶辉周兵魏厚培黄汉东彭世春吴丽娟李仁科李金玉李欣唐彦斌
Owner BEIJING UNIV OF TECH
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