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A method for judging the correctness of bearing parameters and automatic multi-parameter diagnosis and matching

An automatic diagnosis, multi-parameter technology, applied in the field of rail transit vehicle fault diagnosis, safety protection and reliability design, can solve problems such as increased uncertainty, lack of synchronous update, bearing parameter change, etc., to prevent accidents and reduce misdiagnosis. , the effect of reducing maintenance

Active Publication Date: 2020-05-22
TANGZHI SCI & TECH HUNAN DEV CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

If it is a motor bearing, the locomotive manufacturer must also obtain it from the bearing manufacturer through the motor factory. During the transmission process of parameter information, it is inevitable that there will be errors due to human factors and other factors.
[0005] Second, based on some considerations, when designing and selecting bearings for existing locomotives and subway vehicles, bearings from multiple bearing manufacturers are selected at the same time, which leads to the possibility of multiple bearing parameters in the same position on the same model phenomenon, and without dismantling, even the locomotive and vehicle manufacturers cannot determine which parameter is actually used, so it increases the uncertainty for the monitoring and diagnosis system
For example, the drive motor is equipped with a set of cylindrical bearings and a set of ball bearings at the non-drive end to meet the requirements of radial load and axial load at the same time, which makes the fault information source of the measuring point where the sensor is located not unique
[0007] Fourth, existing locomotives do not have matching design requirements for bearing parameters, as long as the inner diameter, outer diameter and bearing width of the bearing meet the installation requirements, so the overhaul factory must ensure that the inner diameter, outer diameter and bearing width are the same during the maintenance process In some cases, it is likely to replace the original bearing with another brand or type of bearing, which may cause changes in bearing parameters (such as rolling diameter, number of rollers, etc.), but the bearing parameter configuration library of the monitoring system has not been updated synchronously , resulting in incorrect bearing parameters of the monitoring system
[0008] Although my country's bearing online monitoring technology has been at the forefront of the world, but for the above problems, there is no mature and effective online technology for engineering application

Method used

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  • A method for judging the correctness of bearing parameters and automatic multi-parameter diagnosis and matching
  • A method for judging the correctness of bearing parameters and automatic multi-parameter diagnosis and matching
  • A method for judging the correctness of bearing parameters and automatic multi-parameter diagnosis and matching

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0041] Embodiment 1, the automatic matching of multiple sets of different types of bearings installed at the sensor measuring point at the same time

[0042] Four sets of different types of bearings are installed at the input end of the gearbox of an EMU. figure 2 For the position of the measuring point, use the generalized resonance / resonance demodulation method and the speed tracking detection method to detect the impact signal samples of the bearing. The number of sampling cycles of the rotating shaft installed by the speed sensor is M=20.48. This measuring point is the rotating shaft installed by the non-speed sensor. The number of sampling cycles of the current axis M n It needs to be multiplied by the transmission ratio η=ZD / ZX=60 / 27=2.22, namely M n =M*η=45.51, so the characteristic clef of the current axis is P n =45.51. Among them, ZD is 60 teeth of the large gear, and ZX is 27 teeth of the small gear.

[0043] in the attached figure 2 In the spectrum of , it i...

Embodiment 2

[0044] Example 2, there may be automatic matching of different types of bearings at the sensor measuring point

[0045] There is a set of double-row bearings installed in the axle box of a certain HX locomotive, but there are two possible types of bearings in this position. Without dismantling, even the locomotive manufacturer cannot determine which one is actually used. . attached Figure 4 It is the position of the measuring point that uses the generalized resonance / resonance demodulation method and the speed tracking detection method to detect the impact signal sample of the bearing. The number of sampling cycles of the rotating shaft installed by the speed sensor is M=10.24. The measuring point of this sensor is the rotating shaft installed by the speed sensor. So the characteristic clef of the current axis is P n =10.24.

[0046] in the attached Figure 4 In the spectrum of , it is found that there is an obvious P=78.5 fault impact characteristic spectrum and its high...

Embodiment 3

[0047] Example 3, there may be automatic matching of different types of bearings at the sensor measuring point

[0048] There is a set of single-row bearings installed at the holding bearing position of a certain HX locomotive, but there are two possible types of bearings at this position. Without dismantling, even the locomotive manufacturer cannot determine which one is actually used. attached Image 6 It is the position of the measuring point that uses the generalized resonance / resonance demodulation method and the speed tracking detection method to detect the impact signal sample of the bearing. The number of sampling cycles of the rotating shaft installed by the speed sensor is M=10.24. The measuring point of this sensor is the rotating shaft installed by the speed sensor. So the characteristic clef of the current axis is P n =10.24.

[0049] in the attached Image 6 In the frequency spectrum, the automatic diagnosis software found that there is an obvious P=135.2 faul...

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Abstract

Provided is a bearing parameter correctness determining and automatic multi-parameter diagnosing and matching method. During online bearing fault monitoring, An expert system determines the default bearing parameter correctness in a measuring point which includes sets of bearings of different types or a measuring point which includes a single set of bearings but may include bearings, of differenttypes or provided by different manufacturers, of different parameters, and a practical parameter of a fault bearing is identified automatically according to a bearing parameter liabrary. Thus, diagnosis mistakes or omission due to improper parameter configuration can be prevented, the applicability of monitoring equipment is improved, and correct maintenance is guided.

Description

technical field [0001] The invention belongs to the technical field of rail transit vehicle fault diagnosis, safety protection and reliability design, and relates to a method for correctness judgment of bearing parameters and multi-parameter automatic diagnosis and matching. Background technique [0002] At present, in the field of online fault monitoring of bearings, my country's fault diagnosis technology based on generalized resonance / resonance demodulation is in the forefront of the world. However, new challenges have also emerged in the long-term application process. [0003] The realization of bearing online fault monitoring mainly involves two aspects of work: fault qualitative analysis and fault quantitative calculation. The fault qualitative analysis is to accurately locate the fault source according to the mechanical structure and motion law of the bearing, and it is the basis for precise diagnosis of the bearing. means. It is highly dependent on the geometric st...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01M13/04
CPCG01M13/04
Inventor 王智唐德尧
Owner TANGZHI SCI & TECH HUNAN DEV CO LTD