1、畢業設計（論文）外文翻譯外文題目: development of a cutting tool condition monitoring system for high speed turning operation by vibration and strain analysis譯文題目：刀貝狀態監測系統高速車削振動應變分析文獻出處- the interrmtiorml journal of advaneed manufactirring technology，2008, 37(37):471-485外文作者： ii. chclladurai, v. k. j且in, n. s. vyas字

2、數統計：英文2186單詞，11662字符；中文3552漢字外文文獻:development of a cutting tool condition monitoring system for high speed turning operation by vibration and strain analysis1 introductionin the last three decades or so, there have been tremendous improvements and technical revolutions in manufacturing industries, n

3、amely computer integrated manufacturing process, robot controlled machining processes, and others. today customer demands high quality products for lowest possible price. to meet customers' such demands and to face global competition, modem industries are facing various challenges towards achiev

4、ing high dimensional accuracy with mirror surface finish on the products. to achieve such goals the manufacturers are focusing on the technical problems namely, how to achieve uninterrupted automated machining process for longer duration with least human supervision. cutting tool wear condition moni

5、toring is an important technique that can be useful especially in automated cutting processes and unmanned factories to prevent any damage to the machine tool and workpiece. in any metal cutting operation, one of the major hurdles in realizing its complete automation is that of the cutting toolstate

6、 prediction, where tool-wear is a critical factor in productivity. cutting tool condition monitoring can help in on-line realization of the tool wear, tool breakage, and workpiece surface roughness.researchers and engineers have been trying to evolve a cutting tool condition monitoring system with h

7、igh reliability. there is a need for reliable, universal cutting tool condition monitoring (tcm) system, which is suitable for industrial applications. various sensing techniques have been reported in the literature by various investigators which deal with the issues of detecting edge chipping, frac

8、ture, tool wear and surface finish many sensors were adopted in the area of metal cutting tool condition monitoring system namely, touch sensors, power sensors, acoustic emission sensors, vibration sensors, torque sensors, force sensors, vision sensors and so on. in any automation process, sensors a

9、nd their signal interpretation play an important role. the processing and analysis of signals is important because it will improve production capacity, reliability, reduced downtime and improved machining quality. sensors and their utilization were implemented in many areas like machine tool, automo

10、tive, and tool manufacturing. byrne et al. reported that 46 % of the sensors monitoring systems were fully functional, 16% had limited functionality, 25% of the systems were non-functional due to technical limitations and 13% were replaced by or switch over to alternate systems. it should be noted t

11、hat, in sensors based systems the most critical decision is prediction of cutting tool condition using signal response. in many cases wrong interpretation of the sensor signals by an operator leads to the wrong decision to switch off the machine tool which affects the quality of the product as well

12、as production rate. the training of the personnel also plays a vital role in successful implementation of tool condition monitoring systems.generally, machining processes are non-linear and stochastic in nature, and it is difficult to build a mathematical model, which requires suitable assumptions a

13、nd may not be matching with real world metal cutting process an intensive research has been carried out related to tcm system covering various metal cutting processes such as turning, milling, drilling and grinding, over the past two decades or so. a good cutting tool condition monitoring system sho

14、uld be characterized by (a) fast detection of impact or collisions, (i.e., unwanted movement between tool and workpiece, or tool and any other component of the machine tool), (b) tool chipping (cutting edge breakage), and (c) gradual tool wear (crater and flank) caused by abrasion due to friction be

15、tween cutting tool and workpiece (flank wear) and cutting tool and chip (crater wear).tool wear sensing techniques are broadly classified into two categories: direct and indirect as shown in table 1. the direct tool wear monitoring methods can be applied when cutting tools are not in contact with th

16、e work piece like radioactive, microscope, camera vision and so on. however, direct methods of measuring tool wear have not been easily adaptable for shop floor application. they are not suitable for on-line condition monitoring system however they can be easily applied to offline measurements and i

17、t consumes more time. indirect tool sensing methods use relationship between cutting conditions and response of machining process which is a measurable quantity through sensor signals output (such as force, acoustic emission, vibration, or current) and may be used to predict the condition of the cut

18、ting tool. these indirect methods are used extensively by various researchers and the detailed analyses have been carried out in the past two decades. these indirect methods can be implemented to an industrial problem, but they have a lower sensitivity compared to direct methods. nowadays, availabil

19、ity of computational power and reliability of electronics help in the development of a reliable condition monitoring system by using indirect methods. however, a problem in tcm system is selection of proper sensor and its location. the sensors have to be placed as close as possible to the target loc

20、ation (close to the tool tip) being monitored.table iwear sensing methodsdirect mcthcxjsindirect niethcxls-electrical resistanceoptical nieasurements -radio activecontact sensing-torque and power-tenifxrrature-vibration & acoustic emission -culling forces & strain nieasurementsit is interest

21、ing to note that an indirect tcm system consists of four steps: (i) collection of data in terms of signals from sensors such as cutting force, vibration, temperature, acoustic emission and/or motor current, (ii) extraction of features from the signals, (iii) classification or estimation of tool wear

22、 using pattern recognition, fuzzy logic, neural networks, or regression analysis, and (iv) development of an adaptive system to control the machining process based on information from the sensors.there have been many investigations on tool wear based on periodic measurements of wear levels using opt

23、ical microscope. in the present study, artificial wear has been created (externally) using electric discharge machining (edm) process in a controlled manner. this is similar to a real flank wear experienced by the tool during machining process. using this (artificially worn) cutting tool, cutting ex

24、periments are performed and signals are captured. this paper aims to develop a systematic feature extraction procedure from the output responses (accelerometers and strain gauges) of a machining process these features are then fed as inputs to the back propagation feed forward neural networks, for c

25、lassification or estimation of tool wear. same experimental data were fed as inputs to the analysis of variance (anova) to test the level of significance the regression empirical models have been developed and validated with experimental results2 creation of artificial wearthe cutting tool failure c

26、an be classified into two categories: (a) gradual wear due to loss of material on an asperity or micro contact between cutting tool and workpiece which causes friction and leads to tool failure after a certain time interval, and (b) premature cutting edge failure due to chipping which occurs suddenl

27、y due to improper selection of machining parameters or tool material defect, or both if a cutting tool approaches towards the end of its useful life, surface quality of the machined work piece is likely to deteriorate. characteristics of the surface topography of a machined work piece depend on the

28、condition of the cutting tool including tool geometry, cutting tool material, work piece material, cutting conditions (with or without cooling) and machining parameters (cutting speed, feed rate and depth of cut). in general, the single point turning tool is subjected to different types of wear such

29、 as flank wear, crater wear, nose wear and chipping. out of these wears, flank wear is considered in the present work although others are equally important under different machining conditions. while creating artificial flank wear, the following important cutting tool geometrical parameters are take

30、n into consideration like rake angle, clearance angle, length of the flank wear and radial wear length.xyfig. 1 flank wear formsthe relation between flank wear and radial wear is given (fig. 1) by(1)h f tan a(rf =:1 一 tan tan a(where, rf is radial wear, hf is flank wear, is clearance angle and is ra

31、ke angleaccording to eq. (1)，the value of depth of cut ( h f ) and radial distance (ty ) are calculated to create flank wear in the range of 0.2 mm to 0.5 mm. edm experimental setup is used to create artificial flank wear. the replica of the flank wear is first produced in the copper rod by turning

32、operation and then the copper rod is used in the edm process as a tool (cathode) to replicate the flank wear on the cutting tool. during edm, the tungsten carbide cutting tool (used as a work piece in edm operation) is made as an anode machining parameters values are chosen in terms of feed rate as

33、well as depth of cut to create exact shape of flank wear as shown in fig. 2. the measurement of wear can be carried out using one of the three categories of sensors, namely proximity sensors, radioactive sensors and vision sensors. most of the researchers use an optical microscope to determine worn

34、out areas, like flank wear length and crater wear lengthin this study, optical usb port microscope (scalar) is used to capture the image of worn out area with magnification factor of 50x. before measurements, insert is mounted on a stand, made of perspex having included angle of 55° as shown in

35、 fig. 3.it covers the entire portion of nose and flank face. through out the measurements, position of the stand and focal distance arc kept constant so that uniform measurements are achieved without any variation. in this microscope, built-in software (namely usb digital scale) is used to measure t

36、he flank wear.lank wear = 0.2 mmfig. 2 artificial flank wear created by edm processfig. 3 flank wear measurements3 experimentationexperiments were carried out on a cnc gildemeister ctx 400 serie 2 turning centre the experimental setup is shown in fig. 4 experiments were conducted on en-8 steel using

37、 dnmg 150608 insert with scco tool holder pdjnr 2020 k15 without cutting fluid. the tool is instrumented with strain gauges (tml-120q) and two accelerometers (np- 3331 -ono-sokki). the strain gauge signals are taken to apxi system and accelerometer signals are taken to an onosokki fft analyzer. the

38、pxi system is equipped with a wheatstone bridge configuration and an amplifier. the magnitude of strain and amplitude of vibration depend upon various machining parameters and it is observed that they increase with depth of cut and feed rate, and decrease with cutting speed. while machining, the cut

39、ting tool is subjected to a state of stress. the resultant strain induces a voltage signal and it is measured with a half bridge configuration using labview.cnc control unitpxi ioll system with monitorworkpiecetail stock supportfig. 4 experimental setuptwo accelerometers were placed in the turning c

40、entre one was placed in the cutting direction on the tool holder, and the other one was placed in the feed direction on the backside of the turret for measuring vibration amplitude in terms of accelerations (g-levels).3k full factorial design with three levels for each value of factors k is used. th

41、e three levels of factors arc low (_1), intermediate (0), high (1). it forms 33 factorial designs and it contains 27 experiments with degrees of freedom equal to 26. a full factorial design was selected to allow all the three level interactions between the independent variables to be effectively inv

42、estigated. the independent variables in this study are cutting speed, feed rate and depth of cut. the artificial flank wear is the fourth independent variable kept at five different levels ranging from 0 to 0.5 mm asshown in table 2.table 2 lndq>cndcnt vanablesvanablcsunitixveh12345cutting speedm

43、min200350500feed ratemm min100300500depth of cutnun345flank wearmtn00.5the three responses or dependent variables (strain due to bending action of a cutting tool, acceleration in cutting direction and acceleration in feedl directions) are measured for various machining conditions. tungsten

44、carbide cutting tools equipped with throw-away inserts (dnmg 150608) were used in turning operation. based on the previous study, flank wear level is minimum at the tool corner radius of 0.8 mm. so, in this study, the insert nose radius has been chosen as 0.8 mm with an angle of 55° diamond sha

45、pe. the work piece material is en8 steel and is supported by a tailstock to avoid excessive overhang. a total number of 135 experiments were performed to include all combinations of the tour independent parameters.4 conclusionsthe development of practical and reliable condition monitoring system for

46、 detecting flank wear in turning operation is essential for realization of intelligent and flexible manufacturing systems- in this study, the problem of detection of flank wear in turning operation has been studied using vibration and strain measurement methods. based on the current study, the follo

47、wing conclusions can be drawn:artificial wear can be created in a controlled manner by using edm process, which emulates the real flank wearvibration and strain monitoring during turning operation can be useful for predicting flank wear for this purpose, frequency domain analyses have been carried o

48、ut and features were fed in to ann as input data. the response of ann is good enough to classify the flank wear at different levelsthe neural networks code was tested employing various training algorithms available in the matlab toolbox and finally optimum architecture (trial no 15) was selected. am

49、ong these algorithms, the trainrp was found to be most robust and easily applicable to classify the flank wear levels while using logsig and tansig as activation functions. a multiple regression model has been developed and validated with experimental results中文翻譯刀具狀態監測系統高速車削振動應變分析1前言在過去三十年左右的時間，制造行業

50、出現了巨大的改進和技術革命，即計算 機集成制造過程中，機器人控制加工過程等等。今天的客戶需求要高品質的產品 和盡可能低的價格。為滿足客戶的這種需求和面對全球競爭，現代工業所面臨的 各種挑戰，實現高尺寸精度與表面光潔度鏡子上的產品。實現這些目標的制造商 把重點放在技術問題，即如何實現不間斷的自動加工工藝的持續時間越長至少人 類與監督。刀具磨損狀態監測是一項重要的技術，可以有用，特別是在自動裁剪 過程和無人工廠，以防止任何破壞機床和工件。在任何金屬切削作業中一個主要 的障礙是以實現完全自動化的切割預測，在工具磨損的關鍵因素是生產力。刀具 狀態監測可以幫助在網上實現刀具磨損，刀具破損，和工件表面粗糙

51、度。研究人員和工程師一直在試圖尋找一個切削刀具狀態監測系統的高可靠性。 需要有可靠的，普遍的刀具狀態監測（tcm）系統，該系統適用于工業應用。各 種遙感技術已在文獻中報道的各種調查涉及的問題檢測邊緣切入，刀具磨損和表 面光潔度。許多傳感器通過在該方面的金屬切削刀具狀態監測系統，如觸摸傳感 器，電源傳感器，聲發射傳感器，振動傳感器，扭矩傳感器，力傳感器，視覺傳 感器等。在任何自動化過程中，傳感器和信號的解釋發揮了重要作用。處理和分 析的信號非常重要，因為這將提高生產能力，可靠性，減少停機時間，提高加工 質量。傳感器和執行器利用在許多領域一樣機床，汽車，工具制造業。byrne et al報告說46

52、%的傳感器監測系統全功能，16%的功能有限，25%的系統都不起作 用，由于技術上的局限性和13%的人所取代或切換到備用系統。應當指出的是， 在傳感器的系統最重要的是預測刀具條件的信號反應。在許多情況下，錯誤的解 釋，傳感器信號的運營商將導致錯誤的決定關掉機床影響產品的質量以及生產速 度。該培訓的人員也發揮了重要作用，成功地實施刀具狀態監測系統。一般來說，加工過程的非線性和隨機的性質，很難建立一個數學模型，這 就需要適當的假設和可能不匹配的現實世界金屬切削過程。在過去二十年里，密 集的研究已進行了tcm相關的系統中涵蓋各種金屬切削加工過程，如車削，銃削， 鉆孔和磨削。一個良好的切削刀具狀態監測系

53、統的特點應當是大家g）快速檢 測的影響或碰撞，（即不想要的運動工具和工件之間，或任何其他工具和組成 部分機床），（b）工具切（切邊緣破損），（c）逐步刀具磨損（彈坑和側翼）磨損 造成的磨擦而刀具和工件（刀面磨損）和切割工具和芯片（彈坑磨損）。刀具磨損遙感技術大致分為兩類：直接和間接，如表1所示。直接刀具磨損 監測方法可用于切割工具時不接觸工件像放射性，顯微鏡，照相機遠景等等。但 是，直接測量方法的刀具磨損尚未容易適應的車間應用。他們是不適合的在線狀 態監測系統但是他們可以很容易地適用于離線測量和消費有更多的時間。間接工 具使用遙感方法切削條件之間的關系和反應的加工過程是一個可以衡量的數量, 通

54、過傳感器信號輸出（如力量，聲發射，振動，或電流），可用于預測的狀況 刀具。這些間接的方法，在過去20年里廣泛用于各種研究和詳細的分析已經開 展了。這些間接的方法來執行一個工業問題，但他們有一個比較低靈敏度。如今， 提供計算能力和可靠性的電子有助于制定可靠的狀態監測系統采用間接方法。然 而，一個問題是tch系統選擇適當的傳感器的位置。這些傳感器必須置于盡可能 接近目標位置（靠近刀尖）進行監測。表1刀具磨損檢測方法宜接方法間接方法電阻餐矩和功宇光學測量放射性振動和聲發射接鮭傳感切削力和應變測量值得注意的是，一個間接的tcm系統包括四個步驟：（一）收集數據方面 的信號傳感器，如切削力，振動，溫度，聲

55、發射和/或電機電流，（二）提取功 能從信號，（三）分類或估計刀具磨損利用模式識別，模糊邏輯，神經網絡，或 冋歸分析，以及（四）發展的一個自適應系統控制加工過程的資料的基礎上的傳 感器。有許多調查研究的基礎上刀具磨損定期測量磨損程度使用光學顯微鏡。在 本研究中，人為的磨損已創建（外部）用屯火花加工（edm）過程始終處于受控 的方式。這是一個真正的類似經歷的刀面磨損的工具在加工過程。使用此（人為 磨損）切削刀具，切削實驗和信號進行捕獲。本文旨在建立一個系統的特征提取 的程序從輸出響應（加速度計和應變計）的加工過程。這些功能然后聯儲的投入 反向傳播前饋神經網絡，分類或估計刀具磨損。相同的實驗數據進行

56、了美聯儲作 為投入，方差分析（方差分析）來測試水平的意義。冋歸實證模型已經開發并驗 證與實驗結果。2建立人工磨損刀具故障可分為兩類：（a）逐漸磨損由于物質損失的粗糙或微生物z間的 接觸刀具和工件引起摩擦，并導致工具失敗后，在一定的時間間隔，（b）早產尖 端失敗，由于發生突然插話，由于不適當的選擇加工參數或刀具材料的缺陷，或 兩者兼而有之。如果刀具的使用壽命結束時，表面質量的加工工件有可能惡化。特征表面形貌的加工工件依賴的狀況，包括工具，刀具幾何形狀，刀具材料，工 件材料，切削條件（有或沒有冷卻）和加工參數（切削速度，進給速度和深度削 減）。一般來說，單點車刀受到不同類型的磨損，如刀面磨損，磨損刀口，到鼻 磨損和剝落。其中刀面磨損被認為是本工重要的部分，根據不同的加工條件創造 人工刀面磨損，下列重要的刀具幾何參數考慮到像前角，后角，長度刀面