Method for detecting weaving density of three-dimensional woven fabric based on deep learning

A technology of density detection and deep learning, which is applied in machine learning, instrumentation, computing, etc., can solve problems such as time-consuming and labor-intensive, the impact of 3D fabric manufacturing quality, and relying on the subjective identification of inspectors, so as to improve quality and reduce human subjectivity The effect of interference and high accuracy

Active Publication Date: 2021-08-20
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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Problems solved by technology

Traditional weaving density detection uses manual calibration, which is time-consuming and laborious, and heavily relies on the subjective determination of the inspectors, which has a certain impact on the manufacturing quality of 3D weaving objects

Method used

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  • Method for detecting weaving density of three-dimensional woven fabric based on deep learning
  • Method for detecting weaving density of three-dimensional woven fabric based on deep learning
  • Method for detecting weaving density of three-dimensional woven fabric based on deep learning

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Embodiment Construction

[0024] The deep learning-based three-dimensional fabric weaving density detection method of the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0025] In the three-dimensional weaving density detection method based on deep learning of the present invention, the density calculation of vertical and horizontal lines is based on a deep learning network, and each vertical and horizontal line monomer can be accurately detected by analyzing the vertical and horizontal line categories and position coordinates , and then calculate the density value through the distribution of each vertical and horizontal line on the image.

[0026] A method for detecting the weaving density of three-dimensional fabrics based on deep learning, comprising the steps of:

[0027] Step 1. Collect the surface image of the three-dimensional fabric, mark the category and position of the collected surface image of the three-di...

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Abstract

The invention discloses a method for detecting the weaving density of a three-dimensional woven fabric based on deep learning. The method comprises the following steps: dividing a three-dimensional fabric surface data set into a training set and a verification set, and constructing a deep learning network model for training and verification; the deep learning network model can accurately detect the classification and position information of each longitudinal and transverse line monomer on the surface image of the three-dimensional fabric, then outputs a detection result based on the model, and calculates the density of the longitudinal and transverse lines by using a statistical method according to the coordinates of a prediction frame for longitudinal and transverse line detection. The method for detecting the knitting density of the three-dimensional knitted fabric is high in accuracy and efficiency, can achieve a real-time detection effect, reduces human subjective interference, improves the quality of the three-dimensional knitted fabric, and guarantees the reliability of product production. Meanwhile, the blank of the automatic detection technology for the weaving density of the three-dimensional woven fabric is filled, and the efficiency of detecting the consistency of the three-dimensional woven fabric is improved.

Description

technical field [0001] The invention belongs to the technical field of three-dimensional weaving performance consistency detection, and in particular relates to a three-dimensional weaving density detection method based on deep learning. Background technique [0002] With the continuous development of the automobile industry, because composite materials have special vibration damping properties, they can effectively reduce vibration and noise, and have excellent fatigue resistance, so they are very important for the manufacture of automobile bodies, stressed components, drive shafts and their interiors. The structure is highly developable. [0003] The use of three-dimensional fabrics as composite three-dimensional braided preforms is a hot research topic today. Three-dimensional textiles have been able to produce various composite material prefabricated parts according to actual needs. With the continuous development of the manufacturing technology of three-dimensional br...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06N20/00
CPCG06N20/00G06F18/214
Inventor 汪俊单忠德谢乾涂启帆
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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