Zr基大块非晶合金低速切削性能试验研究

为研究大块非晶合金Zr_(41.2)Ti_(13.8)Cu_(12.5)Ni_(10.0)Be_(22.5)的切削性能,通过使用扫描电镜对加工后合金表面和切屑形貌进行分析。结果表明:切削速度越低、切削深度越小,工件表面粗糙度值越小,切屑表面越平整,切削过程越稳定。说明在低速切削条件下,非晶合金具有较好的切削性能。     

大块非晶合金的形成准则及应用进展

综述了形成大块非晶合金的经验准则和评估非晶形成能力的经验判据，并简要评述了大块非晶合金的力学性能、电学性能、磁学性能及其应用。大块非晶合金的形成能力是目前和今后研究非晶合金的热点，通过研究非晶的形成，有望开发出更多的新型大块非晶合金体系。     

锆基非晶合金冰冻切削加工特征及其无晶化加工工艺研究

锆基非晶合金切削过程中的高切削热会导致工件表面晶化,使非晶合金优异性能丧失.提出将冰冻盘夹具用于非晶合金铣削加工,提升切削散热能力,实现非晶合金冰冻切削加工.研究了非晶合金冰冻铣削过程中的燃烧发光特征及其影响因素;分析了冰冻切削工艺(切削速度、进给量和刀具涂层材料)对非晶切削力的影响规律;优化了适用于非晶合金无晶化加工的冰冻切削工艺参数,并揭示了涂层刀具的磨损失效形式.结果 表明,锆基非晶合金切屑燃烧发光是导致非晶冰冻切削加工表面晶化和表面粗糙度增大的根本原因;引起切屑燃烧发光的主要因素包括高切削速度、小进给量以及因切削长度增加导致的刀具磨损积累,改变刀具涂层不会导致切屑燃烧发光;切削力主要受切削速度影响,对进给量不敏感;TiSiN、TiAlN、CrSiN和AlCrN四种涂层刀具的失效形式均为后刀面黏结磨损、前刀面涂层剥落以及刀尖崩缺;CrSiN涂层具有最佳的抗黏结磨损能力,可获得最小切削力和最低表面粗糙度.通过优化冰冻切削工艺,可以实现锆基非晶合金的高速铣削加工,同时避免切屑燃烧发光,获得高质量的无晶化加工表面.     

大块非晶合金的性能和制备方法的研究

大块非晶合金有着独特的物理、化学和力学性能，因此，在科研和工程应用上有着较好的前景。本文通过对大块非晶合金制备方法的研究，重点探讨了新型块体非晶舍金放电等离子烧结制备方法。     

基于微细电阻焊接的Fe_(78)Si_9B_(13)非晶薄带块体化成型研究

本文采用逆变直流电阻焊机实现了厚度为25μm的Fe_(78)Si_9B_(13)非晶薄带的快速电阻焊接。X射线衍射测试表明,焊接接头仍保持非晶结构。探讨了焊接工艺参数对非晶接头力学性能的影响;从理论上探讨了电阻焊成型非晶合金块体的可行性及缺陷造成的原因,指出了焊接参数的选择是成型的关键因素。本文的研究对于解决非晶合金的焊接及大块化难题有很好的实践意义。     

铁基非晶合金涂层切削工艺参数优化和切削力预测

采用响应曲面法中的Box-Behnken 实验设计方法（BBD）,设计出四因素三水平的Fe基非晶合金涂层切削力实验方案,研究切削参数（切削速度、进给量和切削深度）和刀具结构参数的变化对Fe基非晶合金涂层切削力的影响规律和影响因素,运用方差分析法获取了影响切削力分量的显著性水平,得到低切削速度下Fe基非晶合金涂层的最佳切削工艺参数。通过对实验数据的多元二次拟合,建立了Fe基非晶合金切削力最小二乘回归预测模型,并通过实例验证了Fe基非晶合金涂层切削力预测模型的可行性和实用性。     

大块非晶体材料的研究动向

综合评述了大块非晶体材料的发展历史及研究现状，详细介绍了新型块体非晶合金的形成原理、成分设计原则和结构特征、大块非晶合金的性能及应用。同时简单介绍了熔体水淬法、爆炸焊接法等制备技术。     

冷却速率对(Zr_(56)Co_(28)Al_(16))_(98)Y_2非晶合金显微结构和力学性能的影响

以纯金属为原料,采用磁悬浮熔炼-铜模吸铸法制备了直径不同(即冷却速率不同)的块状(Zr_(56)Co_(28)Al_(16))_(98)Y_2非晶合金,同时采用冷却速率更高的甩带法制备了同成分的条带状非晶合金,研究了冷却速率对该合金显微结构和力学性能的影响。结果表明:随着冷却速率降低,块状非晶合金的塑性降低,硬度增大,非晶合金中冻结的自由体积减小,非晶合金基体内逐渐有纳米晶析出,但这并没有提高合金的塑性;自由体积更多的合金具有更高的塑性。     

采用小波包能量熵的铣削振动状态分析方法研究

颤振是影响机床加工质量的重要原因之一。为实现切削颤振的实时在线识别与评价,采用加速度传感器,获取主轴振动信号,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。通过多传感器对加工过程进行监测,确定加工的稳定性;对主轴振动信号进行频谱分析,了解不同加工状态下的信号频谱特点,分析其振动形式。对信号进行小波包分解,发现在不同的振动状态下,信号的能量分布有显著规律。试验表明,切削从稳定状态到不稳定状态,本质上是强迫振动和颤振的能量强度和分布发生了变化。能量熵描述能量分布的变化,是识别切削状态和振动状态变化的有效方法。     

非晶合金变压器短路阻抗计算研究

为提高非晶合金变压器短路阻抗求解精度和效率,推导出了采用能量法求解非晶合金变压器短路阻抗的计算公式。同时在完成非晶合金油浸式变压器(以下简称"非晶油变")优化设计的基础上研究工程上的短路阻抗计算方法。对比分析两种方法的计算结果与国标中标准值的区别,结果表明能量法的求解精度比工程计算法高。     

Tool wear monitoring in drilling using force signals

Utilization of force signals to achieve on-line drill wear monitoring is presented in this paper. A series of experiments were conducted to study the effects of tool wear as well as other cutting parameters on the cutting force signals and to establish the relationship between force signals and tool wear as well as other cutting parameters when drilling copper alloy. These experiments involve four independent variables; spindle rotational speed ranging from 600 to 2400 rev min⁻¹, feed rate ranging from 60 to 200 mm min⁻¹, drill diameter ranging from 5 to 10 mm, and average flank wear ranging from 0.1 to 0.9 mm. A statistical analysis provided good correlation between average thrust and drill flank wear. The relationship between cutting force signals and cutting parameters as well as tool wear is then established. The relationship can then be used for on-line drill flank wear monitoring. Feasibility studies show that the use of force signal for on-line drill flank wear monitoring is feasible.     

Experimental investigations of cutting parameters influence on cutting forces in turning of Fe-based amorphous overlay for remanufacture

Fe-based amorphous alloy is a new-type material dedicated to the remanufacture due to its unique property. Fe-based amorphous alloy is deposited on the abrased, fatigued, and fractured surface for resuming and upgrading its performance. In the present research, properties of amorphous alloy overlay, such as the microstructure, the phase content, thermal behavior, and mechanical property were evaluated and its machinability with respect to machining forces was experimentally investigated. Based on the response surface methodology and Box–Behnken design, four-factor (cutting speed, feed, depth of cut, and rake angle) three-level experiments were applied and analysis of variance (ANOVA) was performed. It is found that depth of cut is the dominant cutting parameter that affects the machining force components. Rake angle and interaction of feed rate and depth of cut can provide secondary significance to machining forces. Cutting speed, alone, has insignificant influence on machining force components. Predicting model for machining forces is established. ANOVA indicates that a linear model best fits the radial force and while a quadratic model best describes the axial force and cutting force. The optimal cutting parameters under these experimental conditions are searched.     

Vibration analysis in milling titanium alloy based on signal processing of cutting force

In metal cutting processes, the chatter may cause fast wear of tools and poor surface quality of the processed parts; it can happen on different cutting parameters, but how do we identify the chatter and how do we select suitable cutting parameters to avoid chatter at high material removal rate (MRR). In this paper, the signal processing methods such as time domain, frequency domain, and time–frequency domain analysis are introduced. The signals of cutting force that were collected in milling titanium alloy Ti–6Al–4V at variable cutting speeds varied from 80 to 360 m/min; signal analysis methods such as time domain, frequency domain, and time–frequency domain were put forward. Further analysis results reveal that the chatter occur when cutting speeds are 240 and 360 m/min, when the maximum value of cutting forces increase by 61.9–66.8%, the standard deviation increase by 84.1–86.1%, and the surface roughness increase by 34.2–40.5% compared with that of at 80 m/min. Detail signal d2 is employed to monitor cutting stability state from the result of wavelet analysis.     

CONDITION MONITOR OF DEEP-HOLE DRILLING BASED ON MULTI-SENSOR INFORMATION FUSION

A condition monitoring method of deep-hole drilling based on multi-sensor information fusion is discussed. The signal of vibration and cutting force are collected when the condition of deep-hole drilling on stainless steel OCr17Ni4Cu4Nb is normal or abnormal. Four eigenvectors are extracted on time-domain and frequency-domain analysis of the signals. Then the four eigenvectors are combined and sent to neural networks to dispose. The fusion results indicate that multi-sensor information fusion is superior to single-sensor information, and that cutting force signal can reflect the condition of cutting tool better than vibration signal.     

Monitoring of diamond disk wear in stone cutting by means of force or acceleration sensors

The application of sensor systems is becoming more commonplace in improving productivity, automation, and reliability. The sensors employed in such systems possess signal and information ability for enhancing the monitoring and control of machining processes. Although measuring force and acceleration signals have been commonly used for the monitoring of metal machining processes, their application to stone cutting has not been well developed, which is perhaps due to the complexity of the interaction between the stone and the diamond disk. In order to enhance knowledge in this area of applications, a multi-sensor system was developed and installed for the monitoring of stone cutting by diamond mill. The signals acquired and analysed by the system include force and acceleration under different machining conditions. The measured signal data was used to perform time-domain analysis. The results indicate the feasibility of using the RMS features of force or acceleration signals along z-axis for the monitoring of disk wear.     

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。     

Prediction of tool breakage in face milling using support vector machine

A new approach is proposed using a support vector machine (SVM) to classify the feature of the cutting force signal for the prediction of tool breakage in face milling. The cutting force signal is compressed by averaging the cutting force signals per tooth to extract the feature of the cutting force signal due to tool breakage. With the SVM learning process, the output of SVM’s decision function can be utilized to identify a milling cutter with or without tool breakage. Experimental results are presented to verify the feasibility of this tool breakage prediction system in milling operations.     

基于卷积型小波包变换的切削力信号消噪

为了消除切削力信号中的随机噪声干扰,本文提出了一种基于卷积型小波包变换的消噪算法,给出了算法的详细步骤。对两个切削力信号的消噪实例结果表明:随机噪声已完全被去除,获得了准确的力信号。     

基于改进高斯随机测量矩阵的切削力信号压缩感知方法

高速加工过程中，依据传统Nyquist-Shannon采样定理进行信号采集通常会面临海量数据的存储、传输和处理难题。基于压缩感知理论提出了一种切削力信号采集新方法，实现信号压缩式采集。选择高斯随机矩阵作为基础测量矩阵，并结合近似正交三角分解和最小相关系数法对高斯随机矩阵进行重新设计，提高其压缩测量性能，再借助高效的压缩采样匹配追踪算法从测量值中恢复得到原始切削力信号。实验结果表明，改进的高斯随机测量矩阵具有更高的重构精度和稳定性，所提出的压缩感知方法在保证切削力数据重构效率和精度的同时，显著减少了数据量。