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河南理工大学本科毕业设计（论文）中期检查表指导教师： 焦锋 职称： 副教授 所在系部（单位）： 机械动力与工程学院 教研室（研究室）： 机制教研室 题 目卧式超声珩磨机床设计学生姓名王宏亮专业班级 机制03-3班 学号03080084一、选题质量（主要从以下四个方面填写：1、选题是否符合专业培养目标，能否体现综合训练要求；2、题目难易程度；3、题目工作量；4、题目与生产、科研、经济、社会、文化及实验室建设等实际的结合程度）1， 该选题为卧式超声珩磨机设计，可以对我们大学四年所学知识进行一次大而全面的练习。2， 这将对我们以后工作起到十分有效的帮助，也能达到一个综合训练的效果，又加强了实际的动手动脑能力。3， 题目的难易程度很适中，对我们既是一个挑战也是一个很好的锻炼提高过程。4， 题目的工作量：要求完成2.5张以上的A0图纸，2.53万字的说明书一份。5， 选题不但能紧密的结合生产和实践，也是在我们所学习过的范围之类，对我们 以后不管是科研还是从事实际的工作对有很大的帮助。二、开题报告完成情况在老师指导和同学们的帮助之下，我顺利的开始我本次毕业设计。我在自己经过一些查阅资料的前提下，慢慢的摸索出了一些门道。 由于我们这次是第一次独立的卧式超声珩磨机床设计，在以前接触这方面的知识较少，所以在刚开始就不是很顺利，甚至感到有些无从下手，但是经过和指导老师的提示和与本组同学的商量之后， 我逐渐找到是设计的切入点，顺利的完成了开题报告。并有了一定的成果和进行了一些前期的工作，并使本次设计有了一个良好的开始。最后我在查阅了一些资料以后，现在已经进入了计算设计过程，我将在以后工作中继续努力，认真完成这次毕业设计。 三、阶段性成果 1通过对机床系统的学习，在加上老师的仔细讲解，我收集了大量的资料和文献，为设计的顺利完成打下了坚实的基础。 2. 在老师的指导和同学的帮助下找到了设计的基本方法，开始了一些基本的原理设计，并取得了一定成果。 3. 完成了开题报告。 4进行了前期的一些工作和设计，对整个设计有了一个大体的方案。四、存在主要问题 由于我们这次是第一次独立的机床装置，所以在刚开始就不是很顺利，对做一个毕业设计的基本知识都没有认识，后来找了指导老师，老师给我在他去年指导毕业设计的基础上，针对我们本科生以前存在的问题，进行了仔细的讲解，然后我再与本组其他同学的商量之后，我慢慢的自己逐渐找到是设计的切入点，我觉得这对我以后有很大的作用。 但是随着设计的逐渐进行我有遇到了许多的新的和更加复杂的问题，这些问题使我充分认识到了自己在以前学习中的不足和自己与一些同学的差距，所以我要以本次设计问契机加强自己在学习上薄弱环节，争取使我的毕业设计能够取得好的成绩，也能够使我所学的知识能够在以后的工作中发挥更大的作用。五、指导教师对学生在毕业实习中，劳动、学习纪律及毕业设计（论文）进展等方面的评语指导教师： （签名） 年 月 日ELSEVIER Journal of Materials Processing Technology 62 (1996) 403-407 Journal of Materials Processing Technology Effect of grinding parameters on acoustic emission signals while grinding ceramics Javad Akbari, Yoshio Saitob, Tadaaki a n a o k a , Shizuichi i u c h i , and Shinzo EnomotoC Faculty of Mechanical Engineering, Sharif University of Technology, P.O. Box 11365-9567 Tehran, Iran baculty of Engineering, Chiba University, 1-33 Yayoi-cho, Inage-ku, Chiba 263, Japan GINTIC Institute of Manufacturing Technology, Nanyang Technological University, Singapore Abstract Grinding process of engineering ceramics is always accompanied by cracking. For automation of machining process it is necessary that a reliable sensing system be devised to detect the workpiece cracking during grinding. In this paper an acoustic emission (AE) sensor was examined for in-process detection of workpiece conditions. Different grinding conditions were performed for evaluation of sensitivity of AE and understanding the effect of each grinding parameter.on AE activities during grinding process of alumina ceramics. The results of experiments indicate that AE activities increase with increasing wheel depth of cut and table speed, however when the wheel speed increases, AE activities decrease. As a result, it is shown that AE is basically a function of abrasive grain depth of cut which is in turn, the main factor for determining the surface integrity of fine ceramics. Keywords: Grinding, Acoustic Emission, Ceramics, Machining Damage, Grinding Mode 1. Introduction Under certain controlled conditions it is now possible to grind brittle materials such as engineering ceram- ics so that material is removed by plastic flow, leaving crack-free surfaces I. Such a damage-free grinding occurs when the volume of materials stressed by each grit of the grinding wheel is small enough to yield rather than exhibit brittle frac- ture, i.e. cracking. In practice, this means maintaining the grain depth of cut (undeformed chip thickness) to below the ductile-brittle transition value. In order to reduce the machining times and costs ex- tremely, automatic machines and systems are applied. For automation of ductile-mode grinding of fine ceram- ics the machine tool must be equipped with sensors of enough sensitivity to ceramic part cracking. Acoustic emission technology has a long history in studies relating to materials research, material evalu- ation, nondestructive testing and manufacturing pro- cesses. Using AE for inspection of machining process was intensified during the last decade. Wakada and Inasaki 2, for instance, used AE sensor to monitor chatter vibrations and wear of a CBN grinding wheel. Some workers such as Eda, et al. 3, Bifano and Yi 4 and Akbari, et al. 5 have used AE for monitoring the machining process of brittle materials. The results of our previous experiments 6, 7 1 indicate that AE is sen- sitive enough to detect surface damage of fine ceramics. It was also shown during grinding of fine ceramics that AE activities increase when the abrasive grain depth of cut, g , increases 8. The objective of present article is to evaluate the sen- sitivity of AE to different grinding parameters such as wheel depth of cut, table speed and wheel speed. In this way the main factor which controls the AE activities in ceramic materials during grinding is determined. In order to solve the problem of noises which is the most important precondition for using acoustic emis- sion signal analysis, different strategies are introduced. 2. Experimental procedure Experiments were carried out on a horizontal spindle surface grinder with variable wheel speed, table speed, and down feed control. Table 1 shows the grinding con- 0924-0136/96/$15,00 1996 Elsevier Science S.A. All rights reserved PU 0924-0136(96)02443-0 404 J. Akbari et al.Nourna1 of Materials Processing Technology 62 (1996) 403407 Table 1 Grinding conditions and mechanical properties of workpiece Grinding conditions Workpiece properties (WT% 99.7 Alz03) Grinding method One-pass, up- and wet surface grinding Bending strength 374 Mpam1j2 Grinding wheel ASD200R.l00B, (NORTON) Hardness 1590 HVlO Truer Rotary type DD-205, (FSK) Fracture toughness 4.5 M a m Dresser GC dressing stick, 360H, (FSK) Wheel speed, V , m/min 700, 900, 1100, 1300, 1500, 1700 Table speed, v , m/rnin 0.06, 0.12, 0.18, 3, 6, 9 Depth of cut, t , p m 2.5, 5, 10, 15, 20, 25 Fig. 1. Experimental setup for grinding tests ditions and mechanical property of the normal sintered A1203 which served as test material. The AE measurement apparatus and data process- ing system which is schematically shown in Figure 1 was used. Acoustic emission signal was detected us- ing a piezoelectric transducer of 140 kHz resonance fre- quency which was attached to the opposite side of the grinding surface below the workpiece using a wax-type couplant. The detected signal then was passed through a low-noise preamplifier with 40 dB gain and the main amplifier to total gain of 60 dB. There are different sources of noise during grinding process. To determine the characteristics of each noise, the noise was gener- ated separately or combined with other noises, then it was recorded and analyzed. The noises from grinding wheel and grinding fluid were the most serious noises. For filtering the noises, different filtering strategies were used in order to diminish the noise effect. Most of the noises generated by peripheral sources such as machine Fig. 2. Schematic of typical AE signal vibration and wheel rotation were easily omitted us- ing high-pass filters with cut-off frequency of 200 kHz. Just before starting to record AE, the grinding fluid was stopped to avoid the high level fluid noise. This method was successful because the noise level decreased consid- erably and the workpiece and the wheel were enough wet for the short period of engagement. Each experi- ment was repeated 3 times. The data analysis software let us to select the AE events within two predefined limits of amplitude, dura- tion, rise time or oscillations. Figure 2 introduces some expressions of AE which are used in this work. Discriminating level was set at 0.8-1.7 volts, depend- ing on the background noise level; however, for data processing, an amplitude window of 2-5.1 volts was used. The data processing time window was 5 seconds for the data of all experiments. After the grinding pro- cess, grinding mode and surface damage were studied by SEhl micrography. 3. Results and discussion For analysis of acoustic emission signals different methods based on waveform power spectrum (FFT) and AE event counting wt:re examined. As explained in previous works 6, 71, for quantitative comparison J. Akbari et al./Journal of Materials Processing Technology 62 (1996) 403407 405 I I ii x High amplitude 0 Long duration High oscillation I 2% I 10 20 30 Depth of cut, t, pm Fig. 3. Percentage of events of high amplitude, long duration, and high oscillation vs. wheel depth of cut. between the results of distribution plots such as ampli- tude distribution, duration distribution and oscillation distribution during each grinding experiment, it is suit- able to choose a limit line on the graph and make a basis on the number of events on each side of this limit for evaluation as higher or lower. The limit line is preferably determined using the experience for transi- tion from ductile to brittle mode. Using this method, the percentage of events more or less than the thresh- old, give a unique value which can be plotted on a graph by one point. In grinding experiments, the threshold was decided 3 V for amplitude distribution, 20 psec for duration distribution and 20 cycle/event for oscillation distribution. Thus, the values more than these limits were called high amplitude, long duration and high os- cillation. Figure 3 indicates that the percentage of events of high amplitude, long duration and high oscillation increase with increasing the wheel depth of cut, t. Generally, the results of previous studies showed that these parameters increase when the surface cracking and chipping increase. The increasing rate of high am- plitude events at smaller depth of cut are more, but decreasing with increasing the depth. This may occur because of sinking the diamond abrasive grains into the resinoid bond of the wheel which is a controlling factor for the grain depth of cut. It is interesting to compare this results with the re- sults of grinding of Sic ceramic (Fig. 4) I. These data were obtained for quantitative evaluation of the finished surface of the ceramic workpiece, using the area per- centage of fracture surface, Sf. For this purpose, an . Rmax - - - x 1 3. -*- x- -x % 5 10 15 Wheel depth of cut, t, pm Fig. 4. Effects of actual wheel depth of cut on percent- age of surface fracture and surface roughness of Sic. ll image analyzing instrupent was used on a secondary electron image of a 2000 times magnified SEM photo- graph (The average of 10 times measurements was used as Sf for each sample). The percentage of surface frac- tures and surface roughness of ceramics increase with increasing wheel depth of cut. In this case also it is possible to suggest a threshold for transition from ductile to brittle mode. Moreover, the results of previous works especially in scratching tests 6 confirm that with decreasing depth of cut, we will have a condition of ductile mode material removal. Thus AE can be used in place of microscopic obser- vation for in-process monitoring of grinding mode of ceramics. Similarly, the percentage of high-amplitude, long- duration and high-oscillation AE events can be plotted against table speed, v, (Fig. 5) and peripheral wheel speed, V, (Fig. 6). From Fig. 5 it can be seen that these AE parame- ters are much sensitive to table speed when grinding is performing in creep feed mode, while in normal speed grinding this sensitivity decreases. In Fig. 6, however, all of the percentages decrease with increasing the wheel speed. Investigation reports that increasing the table speed or decreasing the wheel speed would increase the surface fracture and machining damages of ceramic ma- terials I. Based on these facts, Fig. 5 and Fig. 6 indicate that increasing damages are accompanied by events of longer life, higher amplitude and more os- cillations. This fact was also confirmed previously in scratching tests. 406 J. Akbari et al./Journal of Materials Processing Technology 62 (1996) 403407 Fig. 5. Percentage of events of high amplitude, long Fig. 6. Percentage of events of high amplitude, long duration and high oscillation vs. table speed. duration and high oscillation vs. wheel speed 4. Effect of the coefficient of grain depth of cut on AE High amplitude v = 0.18 m/min High oscillation 70- The effects of grinding parameters on AE activities indicate that AE signals can be characterized by an- other basic parameter which is the coefficient of grain depth of cut, q 5 , ( Eq. 1 ). 4 , in Eq. 1 is a dimension- less value derived from grinding conditions. This factor which mainly controls the mode of grinding process, can be expressed by following equation: , . t = 5 p m _ -*- -* - - - - - - % - - - - - % - - - - - % - - . - + - -_E_o I _ - _ I _ 1. The percentage of events of high amplitude, long duration and more oscillation which indicate sur- face cracking increase with increasing depth of cut and table speed but decrease as the wheel speed increases. AE parameters also show good correlation with the coefficient of grain depth of cut, 4 , . When 4 , is kept constant, the AE activities dont change at different grinding contlitions. Confirming the relationship between AE and dg will let us to use AE for monitoring the grinding mode of fine ceramics. J. Akbari et al./Journal of Materials Processing Technology 62 (1996) 403-407 407 * High amplitude 0 Long duration I High oscillation 0 0 4 8 12 x lo4 Coef. of grain depth of cut, $g 600 1000 1400 1800 Wheel speed, V, m/min 80- Fig. 7. Percentage of events of high amplitude, long du- Fig. 8. Percentage of AE parameters at constant coef- ration and high oscillation vs. coefficient of grain depth ficient of grain depth of cut of cut. 4, = 6 X I O - * High amplitude t = 5 p m ( Long duration Table speed, v, is shown in m/min High oscillation - References I Y. Ichida, K. Kishi,Y. Hasuda and J. Akbari, Study on Mirror Finish Grinding of Fine Ceramics (1st. Report) -Fundamental Consideration on Mechanism of Surface Generation, Int. J. Japan Soc. for Pre- cis. Eng., 1991, Vol. 57, No. 8, pp. 1406-1412. In Japanese 2 M. Wakada and I. Inasaki, Detection of Malfunction in Grinding, 4th World Meeting on Acoustic Emis- sion (AEWG-35) and 1st Int. Conf. on Acoustic Emission in Manufactur