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Gear sample database construction method

A construction method and database technology, applied in the field of gear sample database construction, can solve problems such as misclassification of a small number of instances, and achieve the effect of solving sampling difficulties and ensuring reliability

Pending Publication Date: 2019-07-16
CHONGQING TSINGSHAN IND +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This is because classifiers tend to favor most instances, leading to misclassification of few instances

Method used

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  • Gear sample database construction method
  • Gear sample database construction method
  • Gear sample database construction method

Examples

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Embodiment Construction

[0031] Embodiments of the technical solution of the present invention will be described in detail below. The following examples are only used to illustrate the technical solutions of the present invention more clearly, and therefore are only examples, rather than limiting the protection scope of the present invention.

[0032] It should be noted that, unless otherwise specified, the technical terms or scientific terms used in the present application shall have the usual meanings understood by those skilled in the art to which the present invention belongs.

[0033] like figure 1 As shown, this embodiment discloses a gear sample database construction method, including the following steps:

[0034] S1: Collect a predetermined number of actual gear parameters, determine labels according to the safety factor corresponding to each set of gear parameters, and count the number of categories of labels;

[0035] In this example, we obtain gear data from a transmission company's test ...

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Abstract

The invention provides a gear sample database construction method which comprises the following steps: firstly, collecting actual gear parameters, and determining a label; constructing a generator anda discriminator through a neural network, wherein the initial value of each layer of weight coefficient obeys uniform distribution; inputting a noise sequence signal and a set tag into the generatorto generate data; inputting the generated data and the original sampling data into the discriminator at the same time for classification and judgment; achieving dynamic balance by updating the weightof each neuron in the generator and the discriminator; performing sorting in an ascending order according to the distances; and sequentially selecting the different quantities of generated data from the generated data queues of each category, and fusing the generated data into the original sample data to serve as a final training database for a classifier to use. The method has the advantages thatthe requirement for the number of training samples of each category in a database can be met by generating new data under the condition that the sampling data is small, and the influence on the training effect of the classifier due to insufficient data volume is avoided.

Description

technical field [0001] The invention relates to database construction technology in the field of big data, in particular to a gear sample database construction method. Background technique [0002] As a key component in automobile transmission, gears seriously affect the stability and safety of automobiles. The gear system is complex and non-linear, and cannot directly reflect the relationship between mechanical failures and physical parameters. Many studies are devoted to improving the safety of gears, including improving its physical structure, looking for the relationship between its various physical parameters and safety factors, and so on. [0003] Traditional technology usually uses gear parameters to calculate its safety factor, and then obtains reliability by evaluating the safety factor. In these two steps, a large number of complex equations and assumptions are involved, resulting in large errors in reliability assessment. Therefore, using data-driven technology...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/04G06N3/08G06F16/21
CPCG06N3/08G06N3/045G06F18/214G06F18/241
Inventor 利节孙宇姜艳军龚为伦何宏黎刘垚
Owner CHONGQING TSINGSHAN IND
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