PVA fiber dispersion evaluation method based on grey co-occurrence Matrix Theory

CAO Yuanwen; WU Chunyang; ZHENG Tingting; XIAO Wei; XIA Zhulin; ZHENG Nanxiang

doi:10.11918/j.issn.0367-6234.201801093

Chinese

您当前的位置：

首页 >

文章列表页 >

PVA fiber dispersion evaluation method based on grey co-occurrence Matrix Theory

更新时间：2026-10-23

- PVA fiber dispersion evaluation method based on grey co-occurrence Matrix Theory
- Vol. 51, Issue 1, Pages: 157-161(2019)
- 作者机构：
  
  1. 重庆交通大学机电与车辆工程学院,重庆,400074
  2. 济祁高速公路(砀山段)项目办公室,安徽,宿州,235300
  3. 长安大学公路工程学院,西安,710064
- 作者简介：
- 基金信息：
- DOI：10.11918/j.issn.0367-6234.201801093
  CLC： U415.5
- Published：2019
- 稿件说明：
移动端阅览
CAO Yuanwen, WU Chunyang, ZHENG Tingting, et al. PVA fiber dispersion evaluation method based on grey co-occurrence Matrix Theory[J]. 2019, 51(1): 157-161.
DOI：

CAO Yuanwen, WU Chunyang, ZHENG Tingting, et al. PVA fiber dispersion evaluation method based on grey co-occurrence Matrix Theory[J]. 2019, 51(1): 157-161. DOI： 10.11918/j.issn.0367-6234.201801093.

摘要

为了有效地评价PVA纤维束的均匀性

基于灰度共生矩阵理论

并以PVA纤维束搅拌分散后图像的角二阶矩和熵值为主要特征参数

建立PVA纤维束分散评价方法

给出了PVA纤维束的均匀性评价指标（f1和f2）

分析了在不同种类分散剂、不同搅拌速度、不同搅拌桨的搅拌参数下PVA纤维束分散效果

绘制了PVA纤维束分散后的角二阶矩和熵值曲线图. 结果表明:均匀性评价方法可以评价PVA纤维束分散的均匀性；利用均匀性评价指标分析获得最佳搅拌分散参数

可实现对PVA纤维分散性的快速准确评价.

Abstract

In order to study how to evaluate the dispersion of PVA fiber bundles uniformly

a variety of agitation and dispersion parameters were tested

and based on the theory of gray coexistence matrix

the dispersion evaluation method of PVA fiber was established. The dispersion effect of PVA fiber under different mixing factors

different stirring speed and different stirring blades was analyzed and the angular second moment of PVA fiber bundle and the entropy value of the line graph was plotted. The result shows that the dispersion of PVA fiber bundles can be evaluated by the method well

which provides a theoretical basis for the study of the dispersion uniformity of PVA fiber bundles.

关键词

Keywords

references

Views

331

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

An incremental intrusion detection method based on contrastive learning and relational distillation

Improved vehicle tracking framework optimized by dingo algorithm

Fusion of CBAM with bidirectional recurrent gated residual network for image Copy-Move forgery detection

Incremental intrusion detection mechanism considering cost-sensitive

Efficient time series forecasting model for feature selection

Related Author

No data

Related Institution

No data

AI问答

Postal code：100079
Tel：（010）53879206 Email：tmw@bjxintong.com.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09082226号-64 京公网安备11010602201714号
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰