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Back propagation (BP) neural network based method for predicting service life of rubber absorber

A BP neural network and rubber shock absorber technology, which is applied in the field of rubber shock absorber life prediction, can solve the problems of affecting the prediction results, fatigue life limitations, and inaccurate prediction results of the overall aging life of rubber products, so as to overcome the inaccurate prediction accurate effect

Inactive Publication Date: 2015-08-12
QINGDAO UNIV OF SCI & TECH
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Problems solved by technology

Whether it is based on "HG-T3087-2001 Rapid Determination Method for Storage Period of Static Seal Rubber Parts" and "GBT 20028-2005 Application of Arrhenius Diagram to Estimate Life and Maximum Service Temperature of Vulcanized Rubber or Thermoplastic Rubber", the Arrhenius equation is used to predict In the Arrhenius equation, the activation energy E is regarded as an invariant at each temperature, and the selection of a value in the empirical formula also greatly affects the prediction results, which cause the distortion of the rubber material life prediction life model question
At the same time, for rubber products such as rubber shock absorbers, the elongation at break of rubber samples is directly used to characterize the performance of rubber products, which will lead to inaccurate prediction results of the overall aging life of rubber products.
[0005] When studying the fatigue life of rubber, the crack growth energy criterion based on fracture mechanics is mostly used to characterize the fatigue life of rubber, but the research is based on the standard specimen of crack growth. The fatigue life of the product has certain limitations

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  • Back propagation (BP) neural network based method for predicting service life of rubber absorber
  • Back propagation (BP) neural network based method for predicting service life of rubber absorber
  • Back propagation (BP) neural network based method for predicting service life of rubber absorber

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[0038] Below in conjunction with specific embodiment, further set forth the present invention, should understand that these embodiments are only used in the present invention and are not intended to limit the scope of the present invention, after reading the present invention, those skilled in the art will make various equivalent modifications of the present invention All fall within the scope defined by the appended claims of this application.

[0039] BP neural network is a multi-layer feed-forward network trained by the error back propagation algorithm, and it is one of the most widely used neural networks at present. The BP network has the ability to learn and store a large number of input-output pattern mapping relationships without revealing the mathematical equations describing this mapping relationship in advance. Utilizing this characteristic of BP neural network, it is possible to predict on the basis of only determining the factors that affect the service life, ther...

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Abstract

The invention discloses a back propagation (BP) neural network based method for predicting service life of a rubber absorber. According to the method, a BP neural network model of aging life of the rubber absorber is created firstly; according to the created BP neural network model of the aging life of the rubber absorber as well as fatigue life, a BP neural network model of the service life of the rubber absorber is created; and finally, the service life of the rubber absorber is predicted through the BP neural network model of the service life. In the method, aging factors and fatigue factors affecting the use of the rubber absorber are combined, a service life prediction model of the rubber absorber is reasonably created, the service life of the rubber absorber affected by both aging and fatigue is accurately predicted, and the defect of inaccurate prediction of service life of the rubber absorber due to separate research of aging life and fatigue life is overcome.

Description

technical field [0001] The invention relates to the technical field of life prediction of rubber shock absorbers, in particular to a method for predicting the service life of rubber shock absorbers based on BP neural network. Background technique [0002] Rubber shock absorbers have adjustable elastic parameters, can attenuate and absorb low-frequency, high-frequency vibration and noise, impact stiffness is greater than dynamic stiffness and static stiffness, and have the advantages of small size, light weight, and maintenance-free, so they are widely used in various fields. use. However, in the actual use of the rubber shock absorber, due to the fatigue damage of stress and strain and the aging of the rubber material, there is a problem of service life. The service life of the rubber shock absorber is also restricted by the aging of the shock absorber and the interaction of fatigue. . Once fatigue damage and aging of the rubber material occurs, the stiffness and damping p...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
Inventor 曾宪奎孙延奎韩广文苗清郝建国
Owner QINGDAO UNIV OF SCI & TECH
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