基于T-S模糊模型的HVAS涂层耐磨性能辨识

陈彬; 刘阁; 张贤明; 王旭东

English Version

计算机应用技术 | 浏览量 : 26 下载量: 48 CSCD: 0

导出
分享给微信好友或者朋友圈

分享
收藏
专辑

基于T-S模糊模型的HVAS涂层耐磨性能辨识
Identification of Wear Resistance of HVAS （High Velocity Arc Spraying） Coating Based on T-S Fuzzy Model
- 角色： First author 第一作者
- 机构：
  重庆工商大学废油资源化技术与装备教育部工程研究中心
陈彬
1 ，
- 机构：
  重庆工商大学废油资源化技术与装备教育部工程研究中心
刘阁
1 ，
- 机构：
  重庆工商大学废油资源化技术与装备教育部工程研究中心
张贤明
1 ，
- 机构：
  重庆工商大学废油资源化技术与装备教育部工程研究中心
王旭东
1
2011年31卷第6期页码：520-524
纸质出版日期： 2011 ，
DOI：

扫描看全文

引用
[1]陈彬,刘阁,张贤明,王旭东.基于T-S模糊模型的HVAS涂层耐磨性能辨识[J].特种铸造及有色合金,2011,31(06):520-524.

Chen Bin, Liu Ge, Zhang Xianming, et al. Identification of Wear Resistance of HVAS （High Velocity Arc Spraying） Coating Based on T-S Fuzzy Model[J]. Special Casting & Nonferrous Alloys, 2011,31(6):520-524.
[1]陈彬,刘阁,张贤明,王旭东.基于T-S模糊模型的HVAS涂层耐磨性能辨识[J].特种铸造及有色合金,2011,31(06):520-524. DOI：

Chen Bin, Liu Ge, Zhang Xianming, et al. Identification of Wear Resistance of HVAS （High Velocity Arc Spraying） Coating Based on T-S Fuzzy Model[J]. Special Casting & Nonferrous Alloys, 2011,31(6):520-524. DOI：

摘要

针对大型轴类零件的高速电弧喷涂（HVAS）修复的复杂性、非线性和难以用明确数学模型表达的特点,采用模糊C均值聚类算法得出输入空间的划分和聚类中心,最后结合递推最小二乘法辨识后建参数,建立了涂层耐磨性能与喷涂工艺参数的T-S模糊模型。将该辨识算法对实测数据进行了验证,在试验范围内,误差在-8.6%⁵.8%之间。结果表明,该T-S辨识模型具有较高的辨识精度及较强的泛化能力。利用所建的模糊辨识结果,分析了喷涂工艺参数对涂层耐磨性能的影响规律,并获得了涂层硬度（HRC）极大值为92.04的最佳喷涂工艺参数。

译

Abstract

Aiming at the characteristics of complexity, non-linear and multi-model of HVAS recovery for large shaft, by using fuzzy C-means clustering algorithm to obtain input space location and the clustering center, T-S model of wear resistance with spraying parameters of the coating was established based on the least square method identifying consequent parameters. The T-S fuzzy model was verified with the experimental data. The results show that the error is in range of -8.6%⁵.8% in experimental range. The T-S fuzzy model exhibits the higher identification precision and desirable generation ability. Effects of spraying parameters on wear resistance of the coating were analyzed by the established model, and the maximum value of hardness of the coating, such as HRC 92.4, was presented with the optimized spraying parameters.

译

关键词

T-S模糊模型; 耐磨性能; C均值聚类; 模糊辨识

译

Keywords

T-S Fuzzy Model; Wear Resistance; Fuzzy C-means; Fuzzy Identification

译

摘要

针对大型轴类零件的高速电弧喷涂（HVAS）修复的复杂性、非线性和难以用明确数学模型表达的特点

采用模糊C均值聚类算法得出输入空间的划分和聚类中心

最后结合递推最小二乘法辨识后建参数

建立了涂层耐磨性能与喷涂工艺参数的T-S模糊模型。将该辨识算法对实测数据进行了验证

在试验范围内

误差在-8.6%

.8%之间。结果表明

该T-S辨识模型具有较高的辨识精度及较强的泛化能力。利用所建的模糊辨识结果

分析了喷涂工艺参数对涂层耐磨性能的影响规律

并获得了涂层硬度（HRC）极大值为92.04的最佳喷涂工艺参数。

Abstract

Aiming at the characteristics of complexity

non-linear and multi-model of HVAS recovery for large shaft

by using fuzzy C-means clustering algorithm to obtain input space location and the clustering center

T-S model of wear resistance with spraying parameters of the coating was established based on the least square method identifying consequent parameters. The T-S fuzzy model was verified with the experimental data. The results show that the error is in range of -8.6%

.8% in experimental range. The T-S fuzzy model exhibits the higher identification precision and desirable generation ability. Effects of spraying parameters on wear resistance of the coating were analyzed by the established model

and the maximum value of hardness of the coating

such as HRC 92.4

was presented with the optimized spraying parameters.