High-speed train axle temperature prediction method based on a data-driven support vector machine

A support vector machine, data-driven technology, applied in the field of high-speed train-related data analysis, can solve problems such as being easily affected by external factors and unable to accurately provide axle temperatures.

Pending Publication Date: 2019-04-12
XIAN UNIV OF TECH
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  • Abstract
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Problems solved by technology

[0005] The purpose of the present invention is to provide a high-speed train axle temperature prediction method based on data-driven support vector machine, realize the prediction of axle temperature, provide theoretical support for the axle temperature alarm of the vehicle, and ensure the safe running of the train; The method is easily affected by external factors, so it cannot accurately provide the temperature of the axle shaft

Method used

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  • High-speed train axle temperature prediction method based on a data-driven support vector machine
  • High-speed train axle temperature prediction method based on a data-driven support vector machine
  • High-speed train axle temperature prediction method based on a data-driven support vector machine

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Embodiment

[0096] Existing real-time data collected during the operation of a certain train, including historical data such as axle temperature, ambient temperature, speed, shaft speed, rotational speed, and air duct pressure.

[0097] In order to avoid the influence of the blank value and dimension on the experimental results, the blank value processing and data normalization were performed on the historical data. After the data preprocessing is completed, the mutual information value and mutual information coefficient between the axle temperature and the factors that may affect the axle temperature change are calculated by using the mutual information. The calculation results are shown in Table 1 and Table 2 respectively:

[0098] According to the results in Table 1 and Table 2, the factors with mutual information coefficients less than 0.85 were eliminated, that is, the factor of traction converter power was removed, and the remaining factors were retained as factors that had a signif...

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Abstract

The invention discloses a high-speed train axle temperature prediction method based on a data-driven support vector machine, and the method comprises the steps: firstly, collecting the temperature ofan axle and factors influencing the temperature change of the axle through a sensor, and carrying out the data preprocessing of the collected real-time data; secondly, correlation between the axle temperature and other factors influencing axle temperature change is obtained through mutual information and Pearson correlation coefficients, and factors with large correlation with axle temperature change and factors with small correlation are screened out; then, selecting a kernel function for the axle temperature prediction model by utilizing a support vector regression machine, and establishingthe axle temperature prediction model; and finally, substituting the to-be-measured data into the established axle temperature prediction model to obtain a predicted value of the axle temperature. Themethod disclosed by the invention can be used for analyzing factors with obvious influence on the temperature change of the axle, providing theoretical support for the work of the axle temperature alarm and simultaneously ensuring the safe operation of a train.

Description

technical field [0001] The invention belongs to the technical field of high-speed train related data analysis, and relates to a high-speed train axle temperature prediction method based on a data-driven support vector machine. Background technique [0002] In recent years, high-speed trains have been developed on a large scale at home and abroad by virtue of their advantages such as large capacity, safety and comfort, and environmental friendliness, and have been widely used. However, as the running speed of high-speed trains continues to increase, the operating mileage continues to increase, and the complexity and automation of trains are increasing, the safe operation of trains is facing a huge challenge. [0003] As an important part that affects the safe operation of the train, the train axle bears almost all the load of the train and the impact caused by vibration during the running process, which also makes the axle one of the most vulnerable parts of the train. The c...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06F17/50
CPCG06Q10/04G06F30/20
Inventor 马维纲谭思雨娄霄黑新宏谢国柳宇何文娟陈玄娜
Owner XIAN UNIV OF TECH
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