Article(id=1240594157887091409, tenantId=1146029695717560320, journalId=1227999626482147330, issueId=1240594155198534488, articleNumber=null, orderNo=null, doi=10.16579/j.issn.1001.9669.2025.03.002, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1725292800000, receivedDateStr=2024-09-03, revisedDate=1729612800000, revisedDateStr=2024-10-23, acceptedDate=null, acceptedDateStr=null, onlineDate=1773710296365, onlineDateStr=2026-03-17, pubDate=1741968000000, pubDateStr=2025-03-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773710296365, onlineIssueDateStr=2026-03-17, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773710296365, creator=13701087609, updateTime=1773710296365, updator=13701087609, issue=Issue{id=1240594155198534488, tenantId=1146029695717560320, journalId=1227999626482147330, year='2025', volume='47', issue='3', pageStart='1', pageEnd='158', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1773710295724, creator=13701087609, updateTime=1773714468205, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1240611655898420098, tenantId=1146029695717560320, journalId=1227999626482147330, issueId=1240594155198534488, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1240611655902614403, tenantId=1146029695717560320, journalId=1227999626482147330, issueId=1240594155198534488, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=11, endPage=22, ext={EN=ArticleExt(id=1240594158176498386, articleId=1240594157887091409, tenantId=1146029695717560320, journalId=1227999626482147330, language=EN, title=Stability analysis method of high-speed milling considering feed rate influence, columnId=1228282192162390694, journalTitle=Journal of Mechanical Strength, columnName=Experimental Research·Testing Technology, runingTitle=null, highlight=null, articleAbstract=

High-speed machining technology by improving the cutting speed and feed rate to improve the material cutting rate, machining accuracy and machining quality, is one of the main ways of modern processing. Therefore, to ensure the stability of high-speed machining is the basis of application of high-speed machining. Firstly, based on the traditional stability analysis, the influence of feed rate on the static cutting thickness was further considered, the stability model related to feed rate and radial cutting depth ratio of tool was established, and the stability of high-speed milling was analyzed by combining stability variance ratio. Secondly, based on the single factor variable feed rate test, a filter was designed to filter the frequency component of the spindle speed. The variance ratio between the filtered signal sequence and the original signal sequence was used to analyze the milling stability changes of the continuous variable axial depth test, and the validity of the analysis method considering the feed rate to affect the stability of high-speed milling was verified. The results show that the proposed method can determine milling stability more accurately for high-speed machining with small radial cutting depth. And the axial cutting depth of unstable cutting limit changes slightly with the increase of feed rate, and the feed rate will aggravate the instability of milling system.

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GUO Miaoxian, E-mail:
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高速加工技术通过提升切削速度和进给速度提高材料的切除率、加工精度、加工质量,是现代加工的主要方式之一。因此,保证高速加工的稳定性是高速加工的应用基础。首先,在传统稳定分析的基础上,进一步考虑了进给量对静态切削厚度的影响,建立了与进给量、刀具径向切深比相关的稳定性模型,并结合稳定性方差比分析了高速铣削加工的稳定性。然后,在单因素变进给速度试验的基础上,设计了滤除主轴转速频率分量的滤波器,并使用滤波信号序列与原始信号序列的方差比分析连续变轴向切深试验的铣削稳定性变化,验证了考虑进给速度影响高速铣削加工稳定性分析方法的有效性。结果表明,针对小径向切深的高速加工,所提方法可以更准确地实现铣削的稳定性判定。并且不稳定切削的极限轴向切深会随着进给量的增加而小幅度变化,进给速度会加剧铣削系统的不稳定程度。

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郭淼现,男,1988年生,浙江永嘉人,博士,副教授,博士研究生导师;主要研究方向为先进制造技术;E-mail:
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韩琛潼,男,2000年生,河南许昌人,在读硕士研究生;主要研究方向为振动测试与诊断;E-mail:

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韩琛潼,男,2000年生,河南许昌人,在读硕士研究生;主要研究方向为振动测试与诊断;E-mail:

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韩琛潼,男,2000年生,河南许昌人,在读硕士研究生;主要研究方向为振动测试与诊断;E-mail:

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industrial application, figureFileSmall=HZPFmjfywG51Kyhybt9Z6Q==, figureFileBig=GLwlf05gcltJbS5ATQ2QeA==, tableContent=null), ArticleFig(id=1240594175259898203, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1240594157887091409, language=CN, label=图13, caption=实际工业应用流程图, figureFileSmall=HZPFmjfywG51Kyhybt9Z6Q==, figureFileBig=GLwlf05gcltJbS5ATQ2QeA==, tableContent=null), ArticleFig(id=1240594175343784289, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1240594157887091409, language=EN, label=Tab.1, caption=

Milling test parameters

, figureFileSmall=null, figureFileBig=null, tableContent=
试验编号
Test number
试验机床
Test machine tool
加工参数Machining parameter
主轴转速
Spindle speed/(r/min)
径向切深
Radial cutting depth/mm
轴向切深
Axial cutting depth/mm
进给速度
Feed rate/(mm/min)
Test 1DMC 650V15 0000.112.51 000~14 000
(间隔 Interval 1 000)
Test 2FGV 1060L15 0000.112.51 000~14 000
(间隔 Interval 1 000)
Test 3DMC 650V15 00050.14 000~22 000
(间隔 Interval 2 000)
Test 4FGV 1060L15 00050.14 000~22 000
(间隔 Interval 2 000)
Test 5CarverS 600B7 20010~12.5300~1 200
(间隔 Interval 300)
Test 6CarverS 600B9 60010~12.5300~1 200
(间隔 Interval 300)
), ArticleFig(id=1240594175448641892, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1240594157887091409, language=CN, label=表1, caption=

铣削试验参数

, figureFileSmall=null, figureFileBig=null, tableContent=
试验编号
Test number
试验机床
Test machine tool
加工参数Machining parameter
主轴转速
Spindle speed/(r/min)
径向切深
Radial cutting depth/mm
轴向切深
Axial cutting depth/mm
进给速度
Feed rate/(mm/min)
Test 1DMC 650V15 0000.112.51 000~14 000
(间隔 Interval 1 000)
Test 2FGV 1060L15 0000.112.51 000~14 000
(间隔 Interval 1 000)
Test 3DMC 650V15 00050.14 000~22 000
(间隔 Interval 2 000)
Test 4FGV 1060L15 00050.14 000~22 000
(间隔 Interval 2 000)
Test 5CarverS 600B7 20010~12.5300~1 200
(间隔 Interval 300)
Test 6CarverS 600B9 60010~12.5300~1 200
(间隔 Interval 300)
), ArticleFig(id=1240594175540916586, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1240594157887091409, language=EN, label=Tab.2, caption=

Test variance ratio of each group at milling length of 100 mm

, figureFileSmall=null, figureFileBig=null, tableContent=
试验编号
Test number
主轴转速
Spindle speed/(r/min)
进给速度Feed rate/(mm/min)
3006009001 200
Test 57 2000.590.641.141.34
Test 69 6000.380.610.890.92
), ArticleFig(id=1240594175641579884, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1240594157887091409, language=CN, label=表2, caption=

铣削长度100 mm时各组试验方差比

, figureFileSmall=null, figureFileBig=null, tableContent=
试验编号
Test number
主轴转速
Spindle speed/(r/min)
进给速度Feed rate/(mm/min)
3006009001 200
Test 57 2000.590.641.141.34
Test 69 6000.380.610.890.92
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考虑进给速度影响的高速铣削稳定性分析方法
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韩琛潼 , 郭淼现 , 江小辉 , 卫守恒 , 罗世金
机械强度 | ·实验研究·测试技术· 2025,47(3): 11-22
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机械强度 | ·实验研究·测试技术· 2025, 47(3): 11-22
考虑进给速度影响的高速铣削稳定性分析方法
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韩琛潼 , 郭淼现 , 江小辉, 卫守恒, 罗世金
作者信息
  • 上海理工大学 机械工程学院,上海 200093
  • 韩琛潼,男,2000年生,河南许昌人,在读硕士研究生;主要研究方向为振动测试与诊断;E-mail:

通讯作者:

郭淼现,男,1988年生,浙江永嘉人,博士,副教授,博士研究生导师;主要研究方向为先进制造技术;E-mail:
Stability analysis method of high-speed milling considering feed rate influence
Chentong HAN , Miaoxian GUO , Xiaohui JIANG, Shouheng WEI, Shijin LUO
Affiliations
  • College of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
出版时间: 2025-03-15 doi: 10.16579/j.issn.1001.9669.2025.03.002
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高速加工技术通过提升切削速度和进给速度提高材料的切除率、加工精度、加工质量,是现代加工的主要方式之一。因此,保证高速加工的稳定性是高速加工的应用基础。首先,在传统稳定分析的基础上,进一步考虑了进给量对静态切削厚度的影响,建立了与进给量、刀具径向切深比相关的稳定性模型,并结合稳定性方差比分析了高速铣削加工的稳定性。然后,在单因素变进给速度试验的基础上,设计了滤除主轴转速频率分量的滤波器,并使用滤波信号序列与原始信号序列的方差比分析连续变轴向切深试验的铣削稳定性变化,验证了考虑进给速度影响高速铣削加工稳定性分析方法的有效性。结果表明,针对小径向切深的高速加工,所提方法可以更准确地实现铣削的稳定性判定。并且不稳定切削的极限轴向切深会随着进给量的增加而小幅度变化,进给速度会加剧铣削系统的不稳定程度。

进给速度  /  径向切深  /  铣削稳定性  /  静态切削厚度  /  稳定性识别

High-speed machining technology by improving the cutting speed and feed rate to improve the material cutting rate, machining accuracy and machining quality, is one of the main ways of modern processing. Therefore, to ensure the stability of high-speed machining is the basis of application of high-speed machining. Firstly, based on the traditional stability analysis, the influence of feed rate on the static cutting thickness was further considered, the stability model related to feed rate and radial cutting depth ratio of tool was established, and the stability of high-speed milling was analyzed by combining stability variance ratio. Secondly, based on the single factor variable feed rate test, a filter was designed to filter the frequency component of the spindle speed. The variance ratio between the filtered signal sequence and the original signal sequence was used to analyze the milling stability changes of the continuous variable axial depth test, and the validity of the analysis method considering the feed rate to affect the stability of high-speed milling was verified. The results show that the proposed method can determine milling stability more accurately for high-speed machining with small radial cutting depth. And the axial cutting depth of unstable cutting limit changes slightly with the increase of feed rate, and the feed rate will aggravate the instability of milling system.

Feed rate  /  Radial cutting depth  /  Milling stability  /  Static cutting thickness  /  Stability identification
韩琛潼, 郭淼现, 江小辉, 卫守恒, 罗世金. 考虑进给速度影响的高速铣削稳定性分析方法. 机械强度, 2025 , 47 (3) : 11 -22 . DOI: 10.16579/j.issn.1001.9669.2025.03.002
Chentong HAN, Miaoxian GUO, Xiaohui JIANG, Shouheng WEI, Shijin LUO. Stability analysis method of high-speed milling considering feed rate influence[J]. Journal of Mechanical Strength, 2025 , 47 (3) : 11 -22 . DOI: 10.16579/j.issn.1001.9669.2025.03.002
高速切削技术是一种在高速和高效率下进行金属加工的先进加工方法。提高进给速度可以减少切削时间、降低生产成本,但同时也会增加铣削系统的振动风险,从而降低加工精度和表面质量。因此考虑机床进给速度对不同径向切深铣削稳定性的影响尤为重要。
分析机床进给速度对不同径向切深铣削稳定性的影响,需要结合主轴转速、轴向切深等其他加工参数分析进给速度对铣削系统稳定性的影响。基于切削过程动力学建模,稳定性分析获取稳定性叶瓣图,并根据稳定性叶瓣图选择优化的切削参数,为普遍的研究方法。这些研究大多认为切削过程稳定性主要与主轴转速、轴向切深有关,不受进给量影响[1-4][5]117368[6]718-722。但进给速度对铣削过程影响的相关研究表明,进给速度会对铣削力造成非线性影响[7],使得部分线性稳定区域不安全,导致参数选择不足以维持铣削稳定性。考虑进给速度对铣削力模型中瞬时切屑厚度的非线性影响,并建立描述机床振动的非线性延迟微分方程是研究这一现象的主要途径。FAASSEN等[8]等提出了一种非线性切削力模型,该模型具有指数表达式,并结合了次摆线齿轨,用于准确预测低浸入切削的稳定性凸角。LONG等[9]等建立与进给速度相关的可变时间延迟的铣削过程模型,恒定延迟系统获得的稳定性图与可变延迟系统获得的稳定性图之间具有明显差异。YAN等[10]提出了一个基于组合高阶全离散方法的单延迟铣削稳定性叶瓣图(Stability Lobe Diagram, SLD)算法,该算法具有计算量小、精度高等优点。YAN等[11]将通过流域稳定性估计与延迟初始切割状态近似傅里叶级数和基于蒙特卡洛原理产生的系数作为铣削安全性的指标,研究线性稳定边界层受非线性的影响。
在小径向切深下,进给速度对瞬时切削厚度的非线性影响更加明显,部分学者针对这一现象进行研究。DAI等[12]提出了一种基于时间不变转移矩阵的小径切削铣削加工表面定位误差预测方法,该方法不受时间变化的影响,从而减轻了大量的计算负担。WANG等[13]针对连续的小径向切深铣削,提出了一种将试验测量与导纳耦合法相结合的快速获得工件时变模态参数的方法,实现工件-刀具四自由度铣削系统稳定性预测。LIU等[14]提出了一种基于精细积分的修正数值积分方法,能有效地识别小径向切深下的SLD。
大多数基于动力学模型仿真获得稳定性叶瓣图的研究缺乏在线颤振检测策略,只能检测充分发生的颤振,即便检测到颤振,也为时已晚,工件表面或刀具已损坏,因此需设计铣削稳定性识别方法,研究实际加工工况下进给速度的影响。YAO等[15]基于预先获得的三维稳定性叶瓣图,采用高频带具有较高灵敏度的相对小波包能量熵和局部离群因子算法对颤振进行早期检测。李超等[16]11-23提出综合振动信号能量比和幅值标准差的铣削颤振实时监测方法,用于薄壁结构件铣削加工过程中颤振的判别。CAO等[17]消除齿间通过频率及其谐波的干扰,采用奇异值分解方法对TF矩阵进行压缩,计算1阶奇异值作为颤振指标。张智等[18]以小波包能量熵值为指标,对铣削加工的稳定状态及振动形式进行识别。陈云等[19]考虑实际切削厚度的时域仿真法,并结合相关系数的无量纲颤振判定准则,用于铣削仿真结果加工状态的判定。
本文首先基于高进给量状态下的瞬时切削厚度,建立考虑静态铣削厚度的铣削系统动力学模型,通过变进给速度的单因素试验验证进给速度对不同径向切深铣削造成不同影响的原因;其次,设计可过滤主轴转速相关频率分量的滤波器,处理连续变轴向切深试验中的铣削信号,验证综合考虑多因素的实际加工工况下,进给速度对高速铣削加工稳定性的影响。
高速铣削下,瞬时切削厚度会产生动态变化,本节考虑进给速度对铣削系统稳定性的影响,基于与进给量相关的瞬时切削厚度,包含静态切削厚度和动态切削厚度,建立考虑进给量的高速铣削系统动力学模型,求解获得与进给量、刀具径向切深比相关的系统稳定性极限图。
考虑铣刀在进给方向和垂直进给方向的振动,第j个刀齿瞬时切削力与瞬时切削厚度满足指数关系。
式中,ap为轴向切削深度;ktkr分别为切向和径向切削力系数;q为切削常数;ktkrq通过铣削系数试验获得[20]hj(t)为瞬时切削厚度;hj,s(t)为静态切削厚度;hj,d(t)为动态切削厚度。
大多稳定性分析忽略了静态切削厚度的影响,DEFANT等[5]117368提出的铣削模型,认为由于进给而引起的刚体运动不影响稳定性,并且是可以忽略的静态贡献,即忽略了式(1)中的静态切削厚度。由式(2)可知,静态切削厚度是进给速度影响铣削系统的主要因素,忽略了静态切削厚度,也就忽略了进给速度对铣削稳定性的影响。当刀具径向切深较小时,由于刀齿与工件接触角相对较小,进给量产生的静态切削厚度相对于瞬时切削厚度不可以忽略[21],因此,在建立瞬时切削厚度模型时必须考虑进给量的影响,即
式中,τ为时间延迟;ω为转动角速度;fz为每齿进给量;Δx、Δy分别为刀具在X方向和Y方向前后相邻两齿的相对振动位移;ϕj(t)为第j个刀齿的位置,如图1所示。大多数学者在研究铣削稳定性时不考虑进给量的影响,忽略了式中的进给项fz。但通过仿真及试验证明,在研究不同刀具径向切深比铣削时,需要考虑式中的进给项。
本文试验均为顺铣,顺铣切入角及切出角分别为
式中,ϕst为切入角;ϕex为切出角;a为刀具径向切深;D为刀具直径;a/D即为径向切深比。
铣削过程并非连续加工过程,刀具上的刀齿与工件发生间断的接触。当j刀齿转角ϕj在切入角ϕst、切出角ϕex之间时,刀齿处于切削状态。当j刀齿转角ϕj在切入角ϕst、切出角ϕex之外时,刀齿处于脱离状态。建立函数g[ϕj(t)]表示刀齿切削状态,为
综合考虑以上多种因素,将z个刀齿上切向和径向瞬时切削力求和并沿X方向和Y方向分解,则
式中,s表示sin[ϕj(t)];c表示cos[ϕj(t)]。
基于FAASSEN等[22]提出的非线性周期系统的线性化理论,其中u(tt-τ)=u(t)-u(t-τ)可以在u=0附近线性化,这对应于没有颤振的稳定铣削。结果是F=F(u=0)+ΔF。线性化的力ΔF可以写为
式中,q为切削常数,0<q≤1。q=1时不考虑每齿进给量fz的影响,0<q<1时考虑每齿进给量fz的影响。
图1所示,建立刀具-工件2自由度铣削力模型,基于半离散化方法求解。该系统代表一个刀具和一个加工零件,工具被视为具有2个自由度的质量-弹簧-阻尼器系统,铣削系统动力学运动方程可简写为
式中,M为系统质量矩阵;C为系统阻尼矩阵;K为系统刚度矩阵。对北京精雕Carver S600B机床进行频响试验获得模态参数[23-24]。其中,
图2为考虑不同进给量、不同径向切深比的稳定极限图。在a/D=0.5,即大径向切深情况下,不考虑进给量(q=1)与考虑进给量(q=0.85)的铣削系统稳定性的差别不明显,且不同进给量几乎不对铣削系统的稳定性造成影响。在a/D=0.1,即小径向切深情况下,不考虑进给量(q=1)与考虑进给量(q=0.85)的铣削系统稳定性极限差别较为明显,针对小径向切深的高速加工,不稳定切削极限轴向切深随着进给量的增加小幅度变化。相比于大径向切深铣削,进给速度对小径向切深铣削加工稳定性的影响较为明显。
为验证图2中不同进给量、不同径向切深比对铣削系统稳定性的影响,开展径向切深比分别为1%(a/D=0.01)、50%(a/D=0.5)的单因素变进给速度铣削试验。选择在三轴加工中心德玛吉DMC 650V(最高转速为20 000 r/min、最快进给速度为42 000 mm/min)、阿帕斯FGV 1060L(最高转速为24 000 r/min、最快进给速度为60 000 mm/min)进行该铣削试验。刀具选用大山EUP系列高光镜面铝用立铣刀(直径为10 mm、刃长为25 mm的三齿圆柱立铣刀),刀具安装时,悬长为40 mm。工件为铝合金6061。
试验装置如图3所示,使用到的测力仪为Kistler 9139,加速度传感器作为振动传感器固定在机床主轴、工件夹具上。加速度传感器型号均为Kistler 8763B100BB,输出信号为XYZ三个方向的加速度信号,通过SMB接口连接到NET 2412集成采集板卡上。测力仪电荷放大器输出信号为Fx12Fx34Fy14Fy23Fz1Fz2Fz3Fz4八个方向的分力信号,XYZ三个方向的铣削力信号为对应方向分力之和,通过BNC-SMB接口连接到NET 2412集成采集板卡上。力信号、加速度信号通过NET 2412集成采集板卡在LabView界面上同步采集,采样频率均为2 500 Hz。
铣削试验刀具径向切深比分别为1%、50%。加工参数如表1所示,铣削方式均为顺铣,无切削液,每组进行4次试验。
分析采集到的试验信号,Test 1、Test 2、Test 3、Test 4均为稳定铣削,未出现颤振造成的不稳定铣削。选取稳定切削阶段信号进行分析,将铣削力信号的平均值作为试验的准静态力Fs,此外,对力信号进行20~1 024 Hz带通滤波,将计算滤波后的均方根值(Root Mean Square, RMS)作为试验的动态力(Fd)。
图4为铣削准静态力Fs、动态力Fd及静态力占比P,计算式为
小径向切深试验时,随着进给速度的增加铣削准静态力增加明显;大径向切深试验相比小径向切深试验,静态力增加平缓。图5为进给方向的1%、50%切宽比铣削静态力占比。小径向切深下静态力占比随进给速度的增加而增加,而大径向切深下静态力占比几乎不受进给速度影响。
本次试验结果可以验证图2中进给量对不同径向切深比下的稳定性造成不同影响的原因。小径向切深情况下,刀具与加工工件的接触角较小,式(2)中受进给量影响的静态切削厚度在瞬时切削厚度中的占比较大,静态切削厚度不可忽略。在大径向切深时,情况相反。因此,在针对小径向切深的高速加工下应考虑进给速度对铣削稳定性的影响。
虽然一定范围内的进给速度对铣削稳定性的影响不大,但是这并不能说明提高加工效率(或材料切除率)、进给量选取得越大越好,图6所示为测量加工后的面铣工件的表面粗糙度,随着进给速度的增加,表面粗糙度逐渐增加。
进给速度的选取应综合考虑主轴转速、切向切深等工艺参数。进给速度增大后,刀具每齿进给量增加,直接影响工件表面质量,且刀齿受力增大,特别是在小径向切深、大轴向切深下,刀具所受静态力增加明显,刀齿的冲击效应增大,长时间下刀具产生严重磨损、破损。
上述单因素试验仅能证明铣削过程中进给速度对小径向切深铣削的准静态铣削力有显著影响,但试验过程中并未出现明显的不稳定铣削,不足以证明考虑综合因素的实际加工工况下,进给速度对铣削稳定性的影响,因此本节对小径向切深的铣削稳定性进行分析,采用不同进给速度进行连续变轴向切深铣削试验,验证实际加工工况下进给速度对小径向切深铣削稳定性的影响。
加工试验平台如图3所示,连续变轴向切深试验工件长120 mm,连续轴向切深分为两段,0~100 mm阶段轴向切深参数从0~12.5 mm连续增加、100~120 mm阶段轴向切深参数从12.5~0 mm连续减小,如图7所示。本次试验使用北京精雕Carver S600B数控铣床(最高转速20 000 r/min、最快进给速度12 000 mm/min),刀具型号、刀具伸长量及工件材料与上述试验相同,采集设备的采样频率为10 000 Hz,加工参数如表1中Test 5、Test 6所示,考虑到本次试验的径向切深为1 mm、最大轴向切深为12.5 mm,因此本次试验未采用过高的进给速度。
分别对加工过程中铣削力、主轴振动、工件振动信号进行分析,判断加工过程中铣削稳定性的变化。图7为Test 6中进给速度为600 mm/min参数下的铣削力信号,随着轴向切深的增加,铣削系统从稳定铣削转变为不稳定铣削。对原始信号进行低通10 Hz滤波,低频铣削力信号的变换趋势与轴向切深相同。选取两处时域信号分别代表稳定铣削、不稳定铣削,将图中对应时刻的信号高通10 Hz滤波并添加汉宁窗,进行快速傅里叶变换(Fast Fourier Transform, FFT),得到图中对应时刻的频域图。主轴振动的频率图中转频及转频倍数信号较为明显[6]718-722,即使在图7(f)中也很难观察到不稳定铣削引起的非转频信号。相比之下,工件振动信号和铣削力信号的频域图更能观察到两时刻的铣削稳定性差异,如图7(h)所示。在图7(h)中出现了2 225.5 Hz的非转频信号,该幅值高过其他转频相关信号,图7(j)中出现了1 427.7、2 223.5 Hz两处非转频信号,上述非转频信号均与轴向切深过大导致的不稳定铣削相关,此外其对应频率与铣削系统的固有频率有关[16]11-23
对铣削过程中的工件振动信号进行希尔伯特-黄变换,根据图7中的工件振动频域信息进行经验模态分解,将信号分解为7个不同中心频率的内涵模态分量(Intrinsic Mode Function, IMF)[25],如图8(a)所示。对分解后的内涵模态分量进行希尔伯特变换获得内涵模态分量的时频图,如图8(b)所示。IMF1~IMF7对应的中心频率从高频到低频,其中IMF1、IMF2为非转频信号及不稳定铣削信号,IMF3~IMF7对应转频信号及稳定铣削信号。相比于图7中的快速傅里叶变换得到频域信息,希尔伯特-黄变换得到的时频信息可更直观地观察铣削系统稳定性变化。
图7可知,稳定铣削时,频域图中较大的幅值主要分布在主轴转频及转频倍数上,随着轴向切深增大,加工系统进入不稳定铣削阶段,非主轴转频倍数的频率处会出现较大的幅值,且该频率与铣削系统的固有频率相关。结合这一现象可设计滤波器,过滤稳定铣削过程中的主轴转频及转频倍数上的信号并放大不稳定铣削过程中的非主轴转频倍数上的信号,以此来识别加工过程中的铣削稳定性[26]Habs滤波器对应的计算式为
式中,f0为机床主轴的转动频率;n为机床主轴转速;A为滤波器的倍数,取值为2;Habs为设计的滤波器,如图9所示。
图9中的原始数据为Test 6中进给速度为600 mm/min的工件振动信号,处理数据为经过滤波器滤波后的工件振动信号,选择图中时刻的信号并进行快速傅里叶变换,处理后的工件振动信号频域[图9(f)]中主轴转频及转频倍数上的信号(Nf0)被缩小,同时非主轴转频信号(Non-Nf0)被放大,该滤波器可有效地过滤掉稳定铣削过程中的主轴转频及转频倍数上的信号并放大不稳定铣削过程中的非主轴转频倍数上的信号。最后,每1 000个数据点计算一次处理信号与原始信号的方差比值,可发现随着轴向切深的增加,加工系统由稳定铣削逐渐变为不稳定铣削,图9中的方差比值也逐渐增大,因此后续使用处理信号序列与原始信号序列的稳定性方差比值对加工系统的铣削稳定性进行识别。
图10所示,VAR为本文中的稳定性方差比(Variance Ratio, VAR),NER_1为FU等[27]提出的最大IMF的归一化能量比(Normalized Energy Ratio,NER),根据图8中的工件振动信号希尔伯特-黄变换,对IMF进行能量归一化,取VAR相同间隔点数计算当前最大IMF归一化能量比,在不稳定铣削发生前,最大IMF在IMF3~IMF7,得到的是中心频率与转频相关的IMF归一化能量比,该比值不能代表当前铣削稳定程度,直至不稳定铣削发生后最大IMF转变为中心频率与非转频相关的IMF1~IMF2,因此提出NER_2,计算中心频率与非转频相关的IMF1、IMF2归一化能量比之和,NER_2解决了NER_1在不稳定铣削发生前无法代表当前铣削稳定程度的问题。
将本文中的稳定性方差比与内涵模态分量归一化能量比进行对比,VAR、NER_2比值几乎在同一时刻上升,两方法均可判断铣削系统稳定性的变化。相比于NER_2中的希尔伯特-黄变换,VAR仅需进行快速傅里叶变换,在算法实现上更加简单。
表1中Test 5、Test 6每齿进给量区间为0.010 4~0.055 6 mm,将进给量0.010 4、0.055 6 mm输入到铣削模型仿真中获得稳定性极限图,如图11所示。图11中每齿进给量0.010 4 mm与0.055 6 mm的稳定极限图差距并不明显,非高进给速度下,进给速度对极限轴向切深的影响不明显。
使用上述铣削稳定性识别方法对连续变轴向切深铣削Test 5、Test 6试验中的工件振动信号进行铣削稳定性识别,每组试验的进给速度不同导致加工过程中的铣削时间不同,将加工过程的时间替换为铣削长度,如图12所示。
在径向切深为1 mm,铣刀直径为10 mm的小径向切深的铣削,不同主轴转速、相同进给条件下,发生不稳定铣削对应的极限轴向切深不同。造成极限轴向切深不同的主要因素为主轴转速,进给速度对极限轴向切深的影响不明显。
相同主轴转速、不同进给条件下,轴向切深小于极限轴向切深时,进给速度对稳定铣削段方差比值的影响较小;随着轴向切深增大,轴向切深大于极限轴向切深时,进给速度对不稳定铣削段的方差比值影响明显(表2)。以铣削长度为100 mm为例,稳定性方差比会随着进给速度的增加而增加,如表2所示。因此,当铣削系统处于不稳定铣削段时,增加进给速度会加剧铣削系统的不稳定程度。
试验结果与图11稳定性极限图相同,主轴的极限轴向切深与试验中发生不稳定铣削时的轴向切深几乎相同。因此,结合动力学仿真模型与稳定性试验可以更准确地实现铣削稳定性判定。
图6可知,进给速度对粗糙度的影响非常明显。在实际工业的小径向切深下,确定径向切深比后,根据工件粗糙度要求确定对应的进给量,通过考虑进给速度的铣削力模型仿真,获得图2所示的对应要求径向切深比及进给量的稳定性极限图,从图中选取满足高切削效率的工艺铣削参数,至此完成初步铣削工艺参数的选取。使用选取的工艺铣削参数进行实际加工试验,并以稳定性方差比作为铣削稳定性判断依据,若系统处于稳定状态可将该加工参数作为实际加工参数,若系统处于不稳定状态,适当降低轴向切深直至铣削系统转变为稳定状态。此外,本文铣削稳定性判别方法需要获得机床实时的实际主轴转速信息,该信息可通过机床的通信功能来获得,流程如图13所示。
建立了进给量、刀具径向切深比相关的铣削稳定性模型,在单因素变进给速度试验的基础上,设计滤除主轴转速频率分量的滤波器。根据铣削稳定性模型中的极限轴向切深及滤波信号序列与原始信号序列的方差比分析连续变轴向切深试验的铣削稳定性变化。研究结果表明:
1)进给速度会影响静态切削厚度,从而直接影响切削力和切削稳定性,特别是对于小径向切深的高速加工,由于刀具与工件接触角较小,进给速度对系统稳定性的影响更为明显。
2)在传统主轴转速和轴向切深为主的稳定性判别方法的基础上,考虑进给速度对静态切削厚度影响的动力学模型,可以更有效地体现进给速度对系统稳定性的影响。
3)在稳定性模型的基础上,根据滤波信号序列与原始信号序列的方差比值可以直接判断连续变轴向切深铣削试验的稳定性,且结果表明轴向切深大于极限轴向切深后,进给速度的增加会导致稳定性方差比值增大。
4)综合考虑高速加工各因素影响,轴向切深、主轴转速是造成不稳定铣削的主要因素,不稳定切削极限轴向切深随着进给量的增加小幅度变化,且进给速度会加剧铣削系统的不稳定程度。
5)稳定性方差比法可实现与内涵模态分量归一化能量比法相似的铣削系统稳定性判别效果。相比于内涵模态分量归一化能量比法中的希尔伯特-黄变换,稳定性方差比法仅需进行快速傅里叶变换,在算法实现上更加简单。此外,该方法可结合机床通信功能获得机床实时主轴转频,实现铣削系统稳定性的实时判断,可应用于实际工业铣削稳定性的判断。
  • 上海市自然科学基金面上项目(22ZR1442900)
  • 国家自然科学基金面上项目(52275452)
  • 上海航天科创基金项目(SAST2023-063)
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2025年第47卷第3期
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doi: 10.16579/j.issn.1001.9669.2025.03.002
  • 接收时间:2024-09-03
  • 首发时间:2026-03-17
  • 出版时间:2025-03-15
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  • 收稿日期:2024-09-03
  • 修回日期:2024-10-23
基金
General Program of Natural Science Foundation of Shanghai(22ZR1442900)
上海市自然科学基金面上项目(22ZR1442900)
General Program of National Natural Science Foundation of China(52275452)
国家自然科学基金面上项目(52275452)
Shanghai Aerospace Science and Technology Innovation Fund(SAST2023-063)
上海航天科创基金项目(SAST2023-063)
作者信息
    上海理工大学 机械工程学院,上海 200093

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郭淼现,男,1988年生,浙江永嘉人,博士,副教授,博士研究生导师;主要研究方向为先进制造技术;E-mail:
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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