CN113688534A - 一种基于多特征融合模型寻找最优铣削参数的研究方法 - Google Patents
一种基于多特征融合模型寻找最优铣削参数的研究方法 Download PDFInfo
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Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
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CN114200308A (zh) * | 2021-12-03 | 2022-03-18 | 西安理工大学 | 一种基于特征融合的电池组参数不一致性在线评估方法 |
CN115082433A (zh) * | 2022-07-21 | 2022-09-20 | 深圳市信润富联数字科技有限公司 | 微铣削刀工作参数确定方法、装置、电子设备及存储介质 |
CN116679614A (zh) * | 2023-07-08 | 2023-09-01 | 四川大学 | 基于演化博弈的多特征刀具综合适配方法 |
Citations (16)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102609591A (zh) * | 2012-02-16 | 2012-07-25 | 华中科技大学 | 一种重型机床切削参数的优化方法 |
CN103761429A (zh) * | 2014-01-10 | 2014-04-30 | 大连理工大学 | 铣削加工工件表面粗糙度的预测方法 |
US20170013853A1 (en) * | 2015-07-17 | 2017-01-19 | Gay Lea Foods Co-Operative Ltd. | Smooth cottage cheese and cottage cheese product, process and method |
CN107193258A (zh) * | 2017-06-22 | 2017-09-22 | 重庆大学 | 面向能耗的数控加工工艺路线与切削参数优化模型与方法 |
CN109318055A (zh) * | 2018-09-11 | 2019-02-12 | 温州大学苍南研究院 | 一种铣削刀具磨损状态特征提取多目标优化方法 |
CN109571141A (zh) * | 2018-11-01 | 2019-04-05 | 北京理工大学 | 一种基于机器学习的刀具磨损状态监测方法 |
CN109753632A (zh) * | 2018-11-01 | 2019-05-14 | 北京理工大学 | 一种基于数据挖掘的表面粗糙度监测模型及构建方法 |
CN110153801A (zh) * | 2019-07-04 | 2019-08-23 | 西南交通大学 | 一种基于多特征融合的刀具磨损状态辨识方法 |
CN110334442A (zh) * | 2019-07-05 | 2019-10-15 | 江苏师范大学 | 一种加工tc4钛合金工件的车削参数预测方法 |
CN110728049A (zh) * | 2019-10-09 | 2020-01-24 | 江苏师范大学 | 一种刀具车削温度变化均值的组合预测模型建立方法 |
CN110842646A (zh) * | 2019-11-22 | 2020-02-28 | 江苏师范大学 | 一种基于多特征融合的铣削声压级监测及预测系统和方法 |
CN111143990A (zh) * | 2019-12-25 | 2020-05-12 | 西安交通大学 | 一种敏感测点选择及融合的机床铣刀剩余寿命预测方法 |
CN111644900A (zh) * | 2020-05-21 | 2020-09-11 | 西安交通大学 | 一种基于主轴振动特征融合的刀具破损实时监测方法 |
CN112475410A (zh) * | 2020-11-02 | 2021-03-12 | 江苏师范大学 | 一种铣削温度与多元影响因子的关联分析系统及方法 |
CN112757052A (zh) * | 2020-12-09 | 2021-05-07 | 江苏师范大学 | 不同磨损刀具的车削热与多元影响因子的相关性分析方法 |
CN112861728A (zh) * | 2021-02-07 | 2021-05-28 | 山东大学 | 一种多传感信号融合监测薄壁件铣削数据降维方法及系统 |
-
2021
- 2021-09-02 CN CN202111025388.7A patent/CN113688534B/zh active Active
Patent Citations (16)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102609591A (zh) * | 2012-02-16 | 2012-07-25 | 华中科技大学 | 一种重型机床切削参数的优化方法 |
CN103761429A (zh) * | 2014-01-10 | 2014-04-30 | 大连理工大学 | 铣削加工工件表面粗糙度的预测方法 |
US20170013853A1 (en) * | 2015-07-17 | 2017-01-19 | Gay Lea Foods Co-Operative Ltd. | Smooth cottage cheese and cottage cheese product, process and method |
CN107193258A (zh) * | 2017-06-22 | 2017-09-22 | 重庆大学 | 面向能耗的数控加工工艺路线与切削参数优化模型与方法 |
CN109318055A (zh) * | 2018-09-11 | 2019-02-12 | 温州大学苍南研究院 | 一种铣削刀具磨损状态特征提取多目标优化方法 |
CN109571141A (zh) * | 2018-11-01 | 2019-04-05 | 北京理工大学 | 一种基于机器学习的刀具磨损状态监测方法 |
CN109753632A (zh) * | 2018-11-01 | 2019-05-14 | 北京理工大学 | 一种基于数据挖掘的表面粗糙度监测模型及构建方法 |
CN110153801A (zh) * | 2019-07-04 | 2019-08-23 | 西南交通大学 | 一种基于多特征融合的刀具磨损状态辨识方法 |
CN110334442A (zh) * | 2019-07-05 | 2019-10-15 | 江苏师范大学 | 一种加工tc4钛合金工件的车削参数预测方法 |
CN110728049A (zh) * | 2019-10-09 | 2020-01-24 | 江苏师范大学 | 一种刀具车削温度变化均值的组合预测模型建立方法 |
CN110842646A (zh) * | 2019-11-22 | 2020-02-28 | 江苏师范大学 | 一种基于多特征融合的铣削声压级监测及预测系统和方法 |
CN111143990A (zh) * | 2019-12-25 | 2020-05-12 | 西安交通大学 | 一种敏感测点选择及融合的机床铣刀剩余寿命预测方法 |
CN111644900A (zh) * | 2020-05-21 | 2020-09-11 | 西安交通大学 | 一种基于主轴振动特征融合的刀具破损实时监测方法 |
CN112475410A (zh) * | 2020-11-02 | 2021-03-12 | 江苏师范大学 | 一种铣削温度与多元影响因子的关联分析系统及方法 |
CN112757052A (zh) * | 2020-12-09 | 2021-05-07 | 江苏师范大学 | 不同磨损刀具的车削热与多元影响因子的相关性分析方法 |
CN112861728A (zh) * | 2021-02-07 | 2021-05-28 | 山东大学 | 一种多传感信号融合监测薄壁件铣削数据降维方法及系统 |
Non-Patent Citations (1)
Title |
---|
隋秀凛: "虚拟数控铣削物理仿真关键技术研究", 中国博士学位论文全文数据库工程科技Ⅰ辑, no. 05, pages 022 - 44 * |
Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN114200308A (zh) * | 2021-12-03 | 2022-03-18 | 西安理工大学 | 一种基于特征融合的电池组参数不一致性在线评估方法 |
CN114200308B (zh) * | 2021-12-03 | 2024-03-15 | 西安理工大学 | 一种基于特征融合的电池组参数不一致性在线评估方法 |
CN115082433A (zh) * | 2022-07-21 | 2022-09-20 | 深圳市信润富联数字科技有限公司 | 微铣削刀工作参数确定方法、装置、电子设备及存储介质 |
CN116679614A (zh) * | 2023-07-08 | 2023-09-01 | 四川大学 | 基于演化博弈的多特征刀具综合适配方法 |
CN116679614B (zh) * | 2023-07-08 | 2024-02-02 | 四川大学 | 基于演化博弈的多特征刀具综合适配方法 |
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