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Hose equivalent volume elastic modulus calculation method based on generic regression neural network

A regression neural network, bulk elastic modulus technology, applied in the field of hydraulic accessories, can solve the problems of weakening elastic deformation ability, decreasing elastic coefficient, affecting the control performance of the system, etc., to achieve the effect of improving control accuracy

Pending Publication Date: 2022-01-28
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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Problems solved by technology

The hose model established by the traditional lumped parameter method using a set of fixed parameters is difficult to describe the change of the cavity in the whole working range, especially under higher pressure, when the hose reaches a certain amount of expansion, its elastic coefficient decreases and its elastic deformation ability weakens. Under the same pressure change, the change of hose volume is significantly reduced, which seriously affects the performance of model-based system control

Method used

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  • Hose equivalent volume elastic modulus calculation method based on generic regression neural network
  • Hose equivalent volume elastic modulus calculation method based on generic regression neural network
  • Hose equivalent volume elastic modulus calculation method based on generic regression neural network

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Embodiment Construction

[0049] Below in conjunction with accompanying drawing, technical scheme of the present invention is described in further detail:

[0050] This invention may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art. In the drawings, components are exaggerated for clarity.

[0051] refer to figure 1 Shown, a kind of hose equivalent volume elastic modulus calculation method based on pan-regression neural network of the present invention, comprises steps as follows:

[0052] Step 1), testing the double-cylinder device to obtain raw data;

[0053] like figure 2 As shown, the double-cylinder device includes a fixed piston cylinder, a moving piston cylinder, a test hose, and a functional hose, wherein the cylinder body and the piston rod of the fixed piston c...

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Abstract

The invention discloses a hose equivalent volume elastic modulus calculation method based on a generic regression neural network, and the method comprises the steps: testing the expansion of a hose through employing a double-cylinder device connected with the hose, and obtaining the displacement of a piston in each pressure interval and the cavity pressure of the corresponding testing hose; processing the original data to obtain the pressure change rate and the corresponding volume change rate of the test hose; and taking a pressure interval and the pressure change rate of the test hose as an input layer of the screened data, taking the volume change rate of the test hose as an output layer, training and testing the generic regression neural network, and establishing a hose model. According to the method, the hose deformation in a full working condition range can be described, the control precision is improved, compared with a model established by adopting a lumped parameter method, the change of the hose in actual work can be better described, and particularly under the working conditions of high pressure and hose elastic coefficient reduction, the identification of the volume change is more practical.

Description

technical field [0001] The invention relates to the technical field of hydraulic accessories, in particular to a method for calculating the equivalent volume elastic modulus of a hose based on a pan-regression neural network. Background technique [0002] Hose connections are commonly used between hydraulic components to achieve flexible assembly and disassembly and can absorb certain pressure oscillations. In occasions such as long-distance slender connections or precise control of high-output force actuators, the deformation of the hose has an important impact on its control, so it is necessary to establish a hose model. The hose model established by the traditional lumped parameter method using a set of fixed parameters is difficult to describe the change of the cavity in the whole working range, especially under higher pressure, when the hose reaches a certain amount of expansion, its elastic coefficient decreases and its elastic deformation ability weakens. Under the s...

Claims

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Application Information

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IPC IPC(8): G06F30/27F15B19/00G06F119/14
CPCG06F30/27F15B19/007G06F2119/14
Inventor 王彬马腾飞
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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