IN-PROCESS TOOL CONDITION MONITORING USING ACOUSTIC EMISSION SENSOR IN MICROENDMILLING

Recently researchers and manufacturers have shown keen interest in fabricating micro-components through tool based mechanical micromachining processes namely micromilling, microdrilling, microturning, etc. In this scenario, microendmilling is used in the manufacture of micro-molds, micro-dies, micro-channel, micro-gear, etc. The major issue in microendmilling process is the unpredictable life of the micro-tool and its premature failure during operations. Therefore in this work, an attempt has been made to monitor the tool condition (in-process) using acoustic emission (AE) sensor in microendmilling of different materials such as aluminum, copper and steel alloys. From this study, it is observed that there is a strong relationship between the tool wear (flank wear) and acoustic emission (AE_RMS) signals, surface roughness (R_a) as well as chip morphology. In order to understand the mechanism of tool wear, SEM and EDAX analyses were carried out on the microendmill after machining. Scanning Electron Microscope (SEM) and energy dispersive X-ray spectroscopy (EDAX) analyses indicated occurrence of the tool wear mechanism such as adhesion and plastic deformation in all three materials. Coating delamination is also observed while machining steel alloy. This work provides significant and new knowledge on the usage of AE sensor in monitoring the tool condition and understanding the tool wear mechanism in microendmilling of different materials.     

SURFACE FINISH AND TOOL WEAR CHARACTERIZATION IN HARD TURNING USING A MATHEMATICAL CUTTING TOOL REPRESENTATION

The development of a general 3D model for a corner-radiused, chamfered, edge-honed cutting worn tool is elaborated. The surface of the cutting tool was constructed using one angular scalar specifying location on the corner radius and leading/trailing edges and another non-dimensional scalar for specifying location on the relief, edge-hone, chamfer and tool-top. Then, for given geometric parameters and cutting conditions, the angular extremities of contact on the corner radius and leading/trailing edges was obtained and validated. The kinematic surface finish on the workpiece surface including the Brammertz and sideflow effects was then simulated in typical hard turning. The model was expanded to allow wiper edges and flank wear. A simplified crater wear model was adopted for continuous hard turning to allow virtual cross-sectioning. Accurate estimation of flank and crater wear volume was also enabled. The model results for the fresh tool agreed with well-known trends from 2D modeling. Preliminary results indicate that there exists a geometric basis for higher R_a and R_t for a worn tool. The Brammertz effect simulation, though not in agreement with the data of Knuefermann (2003 Knuefermann , M.M.W. ( 2003 ) Machining surfaces of optical quality by hard turning, School of Applied Sciences, Cranfield University, Cranfield, Bedfordshire, UK . [Google Scholar]) corroborated the modification proposed therein.     

ANALYTICAL MODELING OF THE EFFECT OF THE TOOL FLANK WEAR WIDTH ON THE RESIDUAL STRESS DISTRIBUTION

Tool flank wear has significant effects on the cutting process, as it affects cutting forces, temperature and residual stresses. In this article, analytical models are developed to predict the cutting temperature and residual stresses in the orthogonal machining of a worn tool. In these models, measured forces, cutting conditions, tool geometry, and material properties are used as inputs. Stresses resulting from thermal stresses, fresh tool stresses and stresses due to tool flank wear are used in this analytical elasto-plastic model, and the residual stresses are determined by a relaxation procedure. The analytical model is verified experimentally with X-ray diffraction measurements. With the analytical model presented here, accurate residual stress profiles in worn tools are shown, while the computational time is significantly reduced from days, typical for finite-element method (FEM) models, to seconds.     

CONDITION MONITORING FOR INDEXABLE CARBIDE END MILL USING ACCELERATION DATA

In order to automate machining operations, it is necessary to develop robust tool condition monitoring techniques. In this paper, a tool monitoring strategy for indexable tungsten carbide end milling tools is presented based on the Fourier transform and statistical analysis of the vibrations of the tool during the machining operations. Using a low-cost, tri-axial piezoelectric accelerometer, the presented algorithm demonstrates the ability to accurately monitor the condition of the tools as the wear increases during linear milling operations. One benefit of using accelerometer signals to monitor the cutting process is that the sensor does not limit the machine's capabilities, as a workpiece mounted dynamometer does. To demonstrate capabilities of the technique, four tool wear life tests were conducted under various conditions. The indirect method discussed herein successfully tracks the tool's wear and is shown to be sensitive enough to provide sufficient time to replace the insert prior to damage of the machine tool, cutter, and/or workpiece.     

大型机床用无锡耐磨青铜的研究

本文在实验室和工厂条件下研究了一种大型机床用无锡耐磨轴承材料,考虑了不同合金元素对该材料的显微组织和力学性能的影响。结果表明,该材料的技术性能指标超过了锡青铜ZCuSn10P1和ZCuSn6PbZn3两种牌号的技术指标。     

A GEOMETRICAL APPROACH FOR REDUCTION OF TOOL SHAPE DEGENERATION IN ELECTRIC DISCHARGE MACHINING (EDM)

In this study, the geometric wear characteristics of tool electrodes were obtained for various pulse time, discharge current and machining depth settings in electric discharge machining. Different forms of protrusions were machined on the front surface of the tool to reduce the geometric wear. Significant reductions in original tool geometric wear characteristics (front wear, side wear and edge wear) were obtained with the use of square cross-section protrusions. The dimensions of the square cross-section protrusions were modeled mathematically in terms of machining parameters used in the experiments.     

APPLICATION OF WAVELET PACKET ANALYSIS IN DRILL WEAR MONITORING

In this work, an attempt has been made to develop a drill wear monitoring system which is independent to cutting conditions of the drilling process. A cost effective Hall-effect current sensor, which does not interfere with the process, has been used for acquiring motor current signature during drilling under different cutting conditions. An advanced signal processing technique, the wavelet packet transform has been used on the acquired current signature to extract features for indirect representation to the amount of drill wear. Experimental sensitivity analysis reveals that in comparison to time domain features, wavelet packet features are more sensitive to flank wear and less sensitive to the cutting conditions. A multilayer neural network model has then been developed to correlate the extracted wavelet packet features with drill flank wear. Experimental results show that the proposed drill wear monitoring system can successfully predict the flank wear with acceptable accuracy.     

APPLICATION OF WAVELET PACKET ANALYSIS IN DRILL WEAR MONITORING

In this work, an attempt has been made to develop a drill wear monitoring system which is independent to cutting conditions of the drilling process. A cost effective Hall-effect current sensor, which does not interfere with the process, has been used for acquiring motor current signature during drilling under different cutting conditions. An advanced signal processing technique, the wavelet packet transform has been used on the acquired current signature to extract features for indirect representation to the amount of drill wear. Experimental sensitivity analysis reveals that in comparison to time domain features, wavelet packet features are more sensitive to flank wear and less sensitive to the cutting conditions. A multilayer neural network model has then been developed to correlate the extracted wavelet packet features with drill flank wear. Experimental results show that the proposed drill wear monitoring system can successfully predict the flank wear with acceptable accuracy.     

用于CNC位置环测量的外差激光干涉仪的研究

提出了用声光调制器实现的外差干涉仪,采用了相位变化整数周期和周期测量的外差干涉信号处理方法,不仅使干涉仪的测量分辨率提高到λ/2000,同时提高了测量镜允许运动速度,解决了用于大动态范围位移的态动测量问题。该外差干涉测量系统可以用作精密数控中位置环的测量手段。     

混联机床的静刚度实验测量

机床的静刚度是保证其工作性能的重要指标,用理论模型对机床静刚度进行研究难免产生偏差,因此有必要对其进行实验研究.文中针对一台近期研发成功的混联机床,利用力传感器和千分表对其进行静刚度的实验研究.对实验数据进行最小二乘直线拟合,得到该机床在工作空间内9个位姿的各方向静刚度.为了研究该机床静刚度的变化情况,计算同一水平面或竖直面内的静刚度变化率.文中方法和结论为该类型机床的静刚度理论研究和仿真提供实验依据.     

CUTTING PERFORMANCE AND WEAR MECHANISM OF Si3N4-BASED NANOCOMPOSITE CERAMIC CUTTING TOOL IN MACHINING OF CAST IRON

A type of Si₃N₄-based nanocomposites ceramic cutting tool material was prepared by the addition of nano-scale Si₃N_4W whisker and nano-scale TiN particle. Cutting performance of the Si₃N₄/Si₃N_4W/TiN nanocomposite ceramic tool in machining of cast iron was investigated in comparison with a commercial sialon ceramic tool, and the tool wear mechanism was studied. The two types of cutting tools have similar cutting performance at relatively low cutting parameters, while Si₃N₄/Si₃N_4W/TiN nanocomposite tool exhibits a better wear resistance than sialon tool at the relatively high cutting parameters. The wear of sialon ceramic cutting tool is dominated by the plastic deformation, abrasive action, microcracking, pullout of grains and chemical action at the higher cutting parameters. The higher mechanical properties, and the refined matrix grains, intragranular TiN grains and dislocation in the microstructure improve the resistances to plastic deformation, microcracking, and pullout of grains for Si₃N₄/Si₃N_4W/TiN nanocomposite ceramic cutting tool. The wear of Si₃N₄/Si₃N_4W/TiN nanocomposite ceramic cutting tool is dominated by the abrasive and chemical actions at the higher cutting parameters.     

35CrMo钢离子氮化与激光相变硬化复合处理及真耐磨性的研究

介绍了３５ＣｒＭｏ钢氮化加激光相变复合处理后组织及硬度分布的规律，并在各种工艺和材料条件下进行了滑动磨粒磨损试验。结果证明：复合处理的淬硬层深度大于非氮化激光处理的硬化层。在滑动磨粒磨损条件下，与３５ＣｒＭｏ钢氮化或激光相变硬化相比，复合工艺可获得更好的耐磨性，基本与ＧＣｒ１５钢淬火、低温回火相当。     

旋转机械状态监测中提高FFT线性谱精度的一种方法

针对旋转机械状态监测中振动信号一般以离散频率成分为其主要频率构成的特点，讨论一种改善ＦＦＴ线性谱精度的方法。应用该方法对代表某谐和分量的谱峰参数进行适当修正，能获得该分量较精确的频率、幅值和相位。其中相位分析误差小于５°     

DESIGN AND IMPLEMENTATION OF A WEARABLE,MULTIPARAMETER PHYSIOLOGICAL MONITORING SYSTEM FOR THE STUDY OF HUMAN HEAT STRESS,COLD STRESS,AND THERMAL COMFORT

This article describes the design and implementation of a wearable, multiparameter physiological monitoring system called the Sensing Belt system, which consists of multiple sensors integrated into fabric that communicates with a physiological data acquisition unit (PDAU) that in turn transmits these data to a remote monitoring center (RMC) for analysis. A number of vital signs can be acquired by the system, including electrocardiography (ECG), respiratory inductance plethysmograph (RIP), posture/activity, multipoint skin temperature (T_SK), and rectal temperature (T_RC). The physiological data can be stored on a MicroSD card or transmitted to the RMC, where specialized analysis will be provided to extract parameters such as heart rate (HR), respiratory rate (RR), respiratory sinus arrhythmia (RSA), and human energy expenditure. The RMC can receive physiological data from up to 16 Sensing Belt users simultaneously. A medical validation test was carried out to compare the accuracy of the physiological data obtained from the Sensing Belt system with data obtained concurrently from traditional, calibrated laboratory physiological monitoring instruments. The results showed that most of the variables measured by the Sensing Belt are within acceptable error limits. The mean temperature on two trials (walking and running) showed significantly higher mean differences than on other trials, but the correlation coefficient (r) remained high (0.985 and 0.989, respectively). This study demonstrates the accuracy of the Sensing Belt system for the monitoring of these physiological parameters and suggests that it could be used to provide a complete human physiological monitoring platform for the study of human heat stress, cold stress, and thermal comfort.