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Hybrid-driven ballastless track fatigue life prediction method and system

A technology of fatigue life prediction and ballastless track, applied in neural learning methods, details involving 3D image data, image data processing, etc., can solve problems such as poor persuasion and practicability, inaccuracy, long cycle, etc. Sufficient and highly predictive effects

Active Publication Date: 2020-10-30
CHINA RAILWAY SIYUAN SURVEY & DESIGN GRP
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although the cases of fatigue life analysis already exist, they all have certain limitations. For example, the empirical method is greatly affected by human factors, and it is very dependent on the mature structure in the past. The fatigue life of the product is evaluated by experience or static strength check method. lifetime, with large inaccuracies
The trial sample test mainly analyzes the fatigue life from the perspective of the test. Generally, a certain load or a further improved moving load is applied to the sensitive position at a certain loading frequency, and the load is repeated for a sufficient number of times to examine the track structural components. However, the fatigue test takes a lot of time and labor costs, is time-consuming and labor-intensive, the cycle is very long, and it also requires a lot of financial support; because the test takes a long time, it cannot reflect the fatigue life of the track structure in real time Condition
The method of finite element calculation and analysis of fatigue life is often studied in a purely theoretical way, which cannot be combined with the actual situation on site. The results obtained cannot reflect the actual situation of the track structure on site, and the convincing and practicality are poor

Method used

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  • Hybrid-driven ballastless track fatigue life prediction method and system
  • Hybrid-driven ballastless track fatigue life prediction method and system
  • Hybrid-driven ballastless track fatigue life prediction method and system

Examples

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Embodiment 1

[0050] This embodiment discloses a hybrid drive ballastless track fatigue life prediction method, such as figure 1 ,include:

[0051] S100. Obtain on-site monitoring data of the ballastless track, and judge the on-site monitoring data. If the on-site monitoring data is sufficient, perform step S200; if the on-site monitoring data is insufficient, perform steps S300-S400.

[0052] Specifically, the monitoring data includes temperature monitoring data, such as atmospheric temperature and the temperature of each structural layer of the ballastless track; stress and strain monitoring data, such as the stress and strain of steel rails and internal steel bars and concrete in the track structure, etc.; Relative displacement between structural layers, etc.; crack and interface separation monitoring data, including the number of cracks and separation, joint size, spacing, etc.

[0053] In some preferred embodiments, the monitoring data mainly comes from the on-site ballastless track u...

Embodiment 2

[0084] This embodiment discloses a hybrid drive ballastless track fatigue life prediction system, such as Figure 8 , including: monitoring data judgment module 1, monitoring data intelligent learning module 2, finite element theory numerical simulation analysis module 3, fatigue life damage prediction analysis module 4; wherein:

[0085] The monitoring data judgment module 1 receives the ballastless track monitoring data sent by the monitoring platform, uses preset rules to judge the monitoring data, and sends the monitoring data to the monitoring data intelligent learning module 2 and the finite element theory numerical simulation analysis module respectively according to the judgment results 3.

[0086] Specifically, the monitoring data judgment module 1 judges the monitoring data according to the following rules: if the on-site monitoring data is sufficient, the monitoring data is sent to the monitoring data intelligent learning module 2; if the on-site monitoring data is ...

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Abstract

A hybrid-driven ballastless track fatigue life prediction method comprises the following steps: S100, obtaining and judging ballastless track field monitoring data, and if the field monitoring data are sufficient, executing the step S200; if the field monitoring data is insufficient, executing the steps S300-S400; S200, obtaining a track structure fatigue prediction model based on data driving byusing the fatigue life neural network prediction model and taking sufficient field monitoring data as the input of the neural network model and the fatigue life of the ballastless track structure as the output; s300, taking insufficient field monitoring data as a load boundary condition of the finite element analysis model; obtaining a static analysis model of a temperature load effect and a dynamic analysis model of a train dynamic load effect, and performing numerical simulation calculation by utilizing the models to obtain a stress time history curve of each component of the ballastless track under the temperature and train fatigue load effects; and S400, according to the stress time-history curve, utilizing a fatigue damage theory and fatigue analysis software to predict the fatigue life of the ballastless track structure.

Description

technical field [0001] The invention belongs to the technical field of track fatigue life prediction, in particular to a hybrid drive ballastless track fatigue life prediction method and system. Background technique [0002] At present, my country has become the country with the longest high-speed rail mileage and the highest transportation density in the world. Ballastless track has become the most important track structure type of my country's high-speed railway in recent years due to its advantages of good ride comfort and small maintenance workload. The main components of the ballastless track are reinforced concrete structures. On-site investigations show that under the action of train dynamic load and temperature cycle load, the ballastless track in some sections has a certain degree of fatigue damage. Under the continuous action of external complex loads, fatigue damage continues to accumulate, and tiny cracks will be generated. As the cracks continue to expand, the...

Claims

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Application Information

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IPC IPC(8): G06F30/23G06F30/27G06N3/04G06N3/08G06T17/00G06F119/04G06F119/14
CPCG06F30/23G06F30/27G06T17/00G06N3/08G06F2119/14G06F2119/04G06T2200/04G06N3/045Y02T90/00
Inventor 孙立王森荣宋文祥朱彬李秋义张政林超任西冲周磊梅琴
Owner CHINA RAILWAY SIYUAN SURVEY & DESIGN GRP
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