刀具磨损的小波检测

通过建立刀具磨损时的切削力信号奇异性指数与刀具磨损状态的对应关系 ,利用小波变换对切削力信号进行分析 ,实现了对刀具磨损的间接测量     

基于小波分析的切削力信号奇异性检测

利用小波变换模的极大值和信号奇异点的关系,分析了用Lip指数来描述的切削力信号局部奇异性.通过观察奇异点的位置等信息得到切削刀具的磨损情况.通过对实际刀具磨损的在线监测数据分析,证明了采用小波变换检测刀具磨损这一方法的有效性.     

基于小波变换的刀具磨损状态检测

分析切削加工过程中刀具磨损的规律以及在不同的刀具磨损阶段切削力信号的奇异性指数 (即Lipschitz指数 )的变化规律。根据这一变化规律 ,提出自动化生产过程中刀具磨损状态的在线检测的方法。     

Lipschitz指数对刀具磨损的状态监测

针对Lipschitz指数的变化可跟踪量化刀具磨损程度的奇异性问题,提出了一种基于Lipschitz指数的刀具磨损状态监测方法。该方法在小波模极大值与Lipschitz指数关系的基础上,利用线性回归原理推导出Lipschitz指数的计算表达式,克服了传统方法计算Lipschitz指数的精度与鲁棒性不稳定问题。以刀具锋利与磨损的声发射信号为例,实测出不同切削条件下刀具声发射信号的Lipschitz指数变化特性,进而辨识出刀具磨损的状态程度。实验结果表明,提出的Lipschitz指数求解模型以及相应的奇异性辨别方法具有合理性,可准确判断出刀具磨损声发射信号的奇异性与刀具磨损阶段,适合在线应用。     

刀具磨损监测与车削仿真研究

金属加工过程中,切削刀具的状态对于生产效率和表面加工质量有重要影响,因此刀具磨损监测具有重要意义。刀具磨损监测是柔性制造系统研究工程的一个重要课题。切削力信号作为加工过程中最稳定和最可靠的信号,和刀具磨损密切相关。从实验上分析切削力与刀具磨损的相关性,提出刀具切削力变化与磨损变化是一致的。基于有限元分析软件对车削加工进行仿真研究,模拟了切削力的大小分布,并将模拟结果与实验结果进行了比较分析,为实际工艺参数的选择提供了理论指导。     

铣削力模型的频域特性研究

根据铣刀刀齿渐进磨损过程中切削力信号的变化特点 ,分析了切削力与刀齿后刀面磨损带面积 (AVB)间模型的频域统计特性 ,提取了反映刀具磨损状态的频域统计原始特征参数并进行了相关试验研究     

刀具磨损过程中切削力动态分量信号分形维数的变化规律研究

研究了刀具磨损过程中切削力动态分量信号分形维数的变化规律 ,发现分形维数在刀具初期磨损和剧烈磨损阶段较正常磨损阶段高。由于切削力信号动态分量的分形维数随刀具磨损状态的变化而变化 ,使得它可以作为切削过程中判断刀具工作状态的一个参数     

铣削508Ⅲ钢硬质合金刀具敏感性分析

508Ⅲ钢材料应用于核岛AP1000蒸发器水室封头中,是一种高强度、高硬度和高断面收缩率的低碳合金钢。硬质合金刀具在切削508Ⅲ钢时,会产生较大的切削力以及切削振动,从而影响刀具使用寿命。本文进行硬质合金刀具铣削508Ⅲ钢试验,探究切削力以及切削振动信号对刀具磨损敏感性的变化趋势的影响,并运用互相关函数分析切削力以及切削振动信号对硬质合金刀具磨损形态的敏感程度。试验结果表明:切削力较切削振动相比,对刀具磨损形态的影响较大,并在切削速度为298m/min时,切削力、切削振动对刀具磨损形态互相关程度较高。为进一步研究通过切削力等信号检测刀具磨损状态提供试验及理论参考。     

基于硬态切削力信号刀具切削状态的分析

阐述了小波分析及小波去噪的基本理论 ,针对付氏变换和短时付氏变换的缺点 ,提出了基于小波变换的切削力信号分析方法。小波多分辨分析能够实现PCBN刀具的切削力信号的任意精度与尺度的时频域分解 ,从而判断PCBN刀具的切削状态 ,根据切削力信号的不同特征及时调整切削参数 ,减少刀具破损的发生 ,并能够揭示典型切削力信号的分布特征     

基于小波变换切削力信号监控PCBN刀具破损的研究

阐述了小波分析及小波去噪的基本理论，针对傅氏变换和短时傅氏变换的缺点，提出了基于小波变换的切削力信号分析方法。小波多分辨分析能够实现PCBN刀具切削力信号的任意精度与尺度的时一频域分解，从而判断PCBN刀具的切削状态，根据切削力信号的不同特征及时调整切削参数，减少刀具破损的发生，并能够揭示典型切削力信号的分布特征。     

Intelligent monitoring and prediction of tool wear in CNC turning by utilizing wavelet transform

In order to realize an intelligent CNC machine, this research proposed the in-process tool wear monitoring system regardless of the chip formation in CNC turning by utilizing the wavelet transform. The in-process prediction model of tool wear is developed during the CNC turning process. The relations of the cutting speed, the feed rate, the depth of cut, the decomposed cutting forces, and the tool wear are investigated. The Daubechies wavelet transform is used to differentiate the tool wear signals from the noise and broken chip signals. The decomposed cutting force ratio is utilized to eliminate the effects of cutting conditions by taking ratio of the average variances of the decomposed feed force to that of decomposed main force on the fifth level of wavelet transform. The tool wear prediction model consists of the decomposed cutting force ratio, the cutting speed, the depth of cut, and the feed rate, which is developed based on the exponential function. The new cutting tests are performed to ensure the reliability of the tool wear prediction model. The experimental results showed that as the cutting speed, the feed rate, and the depth of cut increase, the main cutting force also increases which affects in the escalating amount of tool wear. It has been proved that the proposed system can be used to separate the chip formation signals and predict the tool wear by utilizing wavelet transform even though the cutting conditions are changed.     

车刀前刀面温度的计算及参数调整

分析了车刀前刀面温度分布的计算方法及影响因素 ,认为车刀前刀面温度分布与切削力关系密切 ,而切削力不仅与切削速度而且与车刀位置有关。提出并通过计算实例证明合理调整车刀温度计算经验公式中的参数可显著提高计算精度     

非圆车削的解析测力方法

针对最小相位及非最小相位受控系统,分别提出了相应算法,根据系统输出位置信号及输入的控制力信号,辨识出动态切削力信息。不使用测力传感器,从而消除了附加测力传感器所产生的不利因素,为深入研究数控非圆车削加工特性及动态切削力误差补偿提供了一种新手段。     

模糊数据融合的刀具磨损状态智能识别

为实现高速加工时刀具渐变磨损状态的在线准确识别,提出了一种集合多种智能的间接检测刀具磨损状态方法的模糊数据融合方法。尽管这些方法具有算法实现较为简单、处理速度较快的优点,但单一的信号检测及单一的智能建模方法难以获得全面的加工状态信息和准确的识别结果。为此,利用F推理技术对上述方法的冗余和互补信息进行数据融合,应用Makino—Fanuc 74-A20型加工中心的测试数据验证了该方案的可行性,并将刀具后刀面磨损的预测值与基于机器视觉检测的实测值进行比较。实验结果分析表明,多参数模糊融合识别方法能快速获得切削刀具磨损状态更加准确的预测值。     

Effect of tool edge wear on the cutting forces and vibrations in high-speed finish machining of Inconel 718: an experimental study and wavelet transform analysis

High-speed machining has been receiving growing attention and wide applications in modern manufacture. Extensive research has been conducted in the past on tool flank wear and crater wear in high-speed machining (such as milling, turning, and drilling). However, little study was performed on the tool edge wear??the wear of a tool cutting edge before it is fully worn away??that can result in early tool failure and deteriorated machined surface quality. The present study aims to fill this important research gap by investigating the effect of tool edge wear on the cutting forces and vibrations in 3D high-speed finish turning of nickel-based superalloy Inconel 718. A carefully designed set of turning experiments were performed with tool inserts that have different tool edge radii ranging from 2 to 62???m. The experimental results reveal that the tool edge profile dynamically changes across each point on the tool cutting edge in 3D high-speed turning. Tool edge wear increases as the tool edge radius increases. As tool edge wear dynamically develops during the cutting process, all the three components of the cutting forces (i.e., the cutting force, the feed force, and the passive force) increase. The cutting vibrations that accompany with dynamic tool edge wear were analyzed using both the traditional fast Fourier transform (FFT) technique and the modern discrete wavelet transform technique. The results show that, compared to the FFT, the discrete wavelet transform is more effective and advantageous in revealing the variation of the cutting vibrations across a wide range of frequency bands. The discrete wavelet transform also reveals that the vibration amplitude increases as the tool edge wear increases. The average energy of wavelet coefficients calculated from the cutting vibration signals can be employed to evaluate tool edge wear in turning with tool inserts that have different tool edge radii.     

陶瓷刀具高速干切削等温淬火球铁(ADI)磨损性能研究

采用陶瓷刀具(CC650)对等温淬火球墨铸铁(以下简称AD I)进行干式高速切削试验,用带有X射线能谱分析的扫描电镜观察刀具表面的磨损形貌,并对刀具磨损微区和工件表面成分进行定性分析,用X射线衍射仪对刀具、工件和切屑等试样进行物相分析,研究高速切削时陶瓷刀具磨损性能及磨损机制。结果表明:切削速度是影响刀具寿命的主要因素;CC650刀具高速干切削AD I时形成的刀具主后刀面和前刀面的磨损形态基本类似中、低速条件下磨损形态,主要区别在其磨损区域紧靠切削刃,最大磨损部位位于切削刃附近;CC650刀具高速切削AD I时切削温度高,其磨损是机械磨损与化学磨损综合作用的结果,磨损机制主要包括磨料磨损、扩散磨损、粘结磨损和微崩。     

高速干切削时金属陶瓷刀具磨损的试验研究

对金属陶瓷刀具高速干切削45钢时的磨损情况进行了试验和分析。结果表明,进给量对金属陶瓷刀具后刀面磨损的影响与切削速度和刀具磨损形态密切相关,对刀具寿命的影响与低速湿切削时存在较大差异。