機械設計制造專業(yè)畢業(yè)設計中英翻譯--一殘余應力針對不同的材料車削的建模方法

1、<p>　　A method of modeling residual stress distribution in turning for different materials </p><p>　　M.H. El-Axir </p><p>　　Department of Production Engineering and Mechanical Design, Menou

2、fia University, Shebin El-Kom, Egypt </p><p>　　Received 10 July 2001; received in revised form 7 March 2002; accepted 12 March 2002 </p><p><b>　　Abstract </b></p><p>　　T

3、his paper introduces a more comprehensive experimental model which has the capability of predicting residual stress profile. The main advantage of this model over the existing models that it provides the effect of machin

4、ing parameters on maximum residual stress and determines both the location and depth of this maximum residual stress. Five different materials namely; stainless steel304, steel-37, 7001 and 2024-aluminum alloys and brass

5、 were machined by turning utilizing one of experimental des</p><p>　　1. Introduction </p><p>　　Fatigue life is an important dynamic property and it is strongly affected by the surface condition

6、produced during machining [1]. The fatigue crack, in general, nucleates at the surface of the part, and then propagates into the bulk. As the crack extends the resistant section is reduced, and when the residual section

7、can no longer withstand the applied load component fatigue occurs. Consequently, it is the state of stress at the surface, where the crack nucleates, that is of paramount importance</p><p>　　It has been show

8、n [2–4] that residual stresses may be compressive at the surface and tensile just below the surface or vice versa. Compressive residual stresses are generally improve component performance and life because they reduce se

9、rvice (working) tensile stresses and inhibit crack nucleation. On the other hand, tensile residual stresses can significantly increase service (working)stresses which can lead to premature failure of components [5–10]. S

10、igwart and Fessenmeyer [11], for example, re</p><p>　　Accordingly, It is very clear that the information concerning residual stresses profile (magnitude and direction along the depth) of the machined surface

11、 region will be valuable in the design and manufacture of parts. Therefore, it is important that the effect of the machining process parameters on the residual stress profile is determined, and subsequently, such machini

12、ng parameters may be chosen which would enhance fatigue life by inducing favorable residual stress (compressive stress). </p><p>　　The majority of the research existing in literature on the effect of machini

13、ng parameters on the residual stress profile are experimental in nature. Very few analytical models are available. Liu and Barash [14,15] explained the formation of residual stress by considering the stress strain histor

14、y that the surface layer experienced due to the movement of the cutting tool. Lin et al. [9] used finite element techniques to determine residual stress profiles in orthogonal machining. Wu and Matusmoto </p><

15、p>　　This paper introduces a more comprehensive experimental model to predict surface and subsurface residual stress profiles in turning of five different materials. With the help of this knowledge it will become possi

16、ble to optimize machining parameters such that the surface integrity of the machined component for these five different materials is maximized under service conditions. </p><p>　　2. Experimental details <

17、/p><p>　　2.1. Workpiece materials </p><p>　　Workpieces of stainless steel 304, steel37, aluminum alloy 7001, aluminum alloy 2024, and brass were utilized. These materials were selected because they

18、 have different machining characteristics and are important in industry. Moreover, both of aluminum alloys 7001 and 2024 are particularly well suited for parts and structures requiring high strength-to-weight ratios. The

19、 chemical compositions in weight percent and tensile strength are given in Table 1. The tool material employed was high-speed s</p><p>　　2.2. Workpiece preparation </p><p>　　The five different m

20、aterials were machined into ring shapes with the dimensions shown in Fig. 1a. Fig. 1b shows the tested ring mounted on its mandrel. It is probable that residual stresses are induced in the surface region of the workpiece

21、 because of the machining involved in preparation, hence it was necessary to remove these stresses by annealing the workpieces. </p><p>　　Stainless steel 304, steel 37, Al. 7001, Al. 2024 and free machining

22、brass workpieces were heated to 800, 595, 340, 340, and 260°C for 3, 6, 2, 2 and 1 h, respectively, and then cooled in air or in furnace. </p><p>　　In this investigation, the specimens were machined usi

23、ng one of the experimental designs. According to a central composed second-order rotatable design with three independent variables, the total number of experiments, N, was determined to be 20. The cutting conditions and

24、their coded are summarized in Table 2. </p><p>　　The residual stress distribution in the machined surface was determined utilizing a deflection etching technique where the residual stresses in the removal la

25、yer are relived and the remaining residual stresses are redistributed until a new equilibrium position is achieved. This change in shape can be measured from which residual stresses can be calculated. A layer of approxim

26、ately 15–25 μm was removed with the help of electrochemical etching. Layers were removed until the residual stress state b</p><p>　　3. Proposed model </p><p>　　The proposed model postulates that

27、 the residual stress profile as well as the depth of residual stress distribution are functions of the machining parameters. The model assumes that profile of residual stress along the depth is polynomial function of the

28、 depth. The profile can be represented as:</p><p>　　where: si is the residual stress, cni are the coefficients of the nth order polynomial term and z is the depth beneath the machined surface. </p>&l

29、t;p>　　Further, it is proposed that the coefficients of the polynomial are individual functions of the machining parameters. The relation of the coefficient to the machining parameters is</p><p>　　where Ci

30、 is the coefficient of polynomial for residual stress profile and bxi is the effect of factor (or interaction of factor) x. </p><p>　　The values of the code number of each parameter, x, can be obtained from

31、the following transformation equations.</p><p>　　where V, F and T are cutting speed, feed and tensile strength of the material, respectively. </p><p>　　The values of bxis are determined experime

32、ntally. The procedure is as follows: </p><p>　　1. Twenty specimens are cut using different combinations (Table 3) of the five levels of each parameter used in this work.。</p><p>　　2. The residua

33、l stress profiles and depth of distribution for each specimen are determined. </p><p>　　3. Polynomials of a pre-decided degree are fitted to the residual stress profiles for each specimen.</p><p&g

34、t;　　4. The coefficient (rli) of these polynomials are then used to determine the values of bxis with the help of the following expressions:</p><p>　　4. Construction of the proposed model </p><p>

35、;　　A visual inspection of the profiles obtained warranted that at least a fourth degree polynomial would be regarded as sufficient to fit the profile. Preliminary results with a fourth degree polynomial were not encourag

36、ing. Therefore, it was decided to use fifth degree polynomial to represent the residual stress profile. The coefficients (rlis) corresponding to the closest fit with fifth degree polynomial for different combinations are

37、 shown in Table 4. </p><p>　　It should be pointed out here that many attempts were carried out to deduce the best model that gives the smallest variation between the fitted polynomial and the proposed model

38、results. The best method that gives simple and reasonable coefficients was obtained when the normalized value of each experimented result was used. </p><p>　　Using the coefficient of fit polynomial equation

39、of each experiment, the values of bxis were determined. The calculated values of bxis are shown in Table 5. The bxis were used to predict cis which are the coefficients of the proposed model. The values of cis for variou

40、s cutting conditions are shown in Table 6. </p><p>　　4.1. How the proposed model is used </p><p>　　To show how the proposed model is used and also to verify the proposed model, two extra tests t

41、hat were not conducted through the 20 experiments, were made. The results of those two extra tests are shown in Fig. 4 which indicate a good agreement between the experiments data and proposed model data. This proves the

42、 validity of using the proposed model to predict the distribution of residual stress beneath the machined surface. Steps that would be followed to use the proposed model to predict the </p><p>　　4.1.1. Step

43、1 </p><p>　　Transfer the value of the three input parameters to coded value using the transformation eqs. (2)–(4). In the two extra tests, the actual and coded values are:</p><p>　　4.1.2. Step 2

44、</p><p>　　The c coefficients in the proposed model should be calculated by using the coded values of the three input parameters that were obtained in step 1 and using the bvalues that are shown in Table 5.&l

45、t;/p><p>　　For example: the coefficient Co can be obtained using the b values from Table 5 as follows:</p><p>　　The value of the c coefficients of the two extra tests are shown in Table 7.</p>

46、;<p>　　4.1.3. Step 3 </p><p>　　After obtaining the c values, eq. (5) that is a function in depth beneath surface, z, could be formed and the residual stress distribution beneath the machined surface c

47、an be determined. However, before substituting in this equation, the value of the depth beneath surface, z, must be transferred to a normalized value. </p><p>　　4.1.4. Step 4 </p><p>　　By substi

48、tuting in the s equation using any depth, z, the residual stress at this depth can be obtained. It should be pointed out here that this obtained residual stress is normalized. The latter value of residual stress has to b

49、e transferred to the actual value by the following equations. The material used in the two extra tests was Al7001 (the third relationship should be used).</p><p>　　4.1.5. Step 5 </p><p>　　The su

50、rface stresses were calculated using a separate model. This was made because at workpiece surface, the residual stress is small and suddenly reaches a maximum value at 20–40 μm beneath the surface which loosen the accura

51、cy of the derived model. </p><p>　　The surface residual stress model that was used to predict the value of residual stress in the machined surface at any value of each parameter within the range used in this

52、 work is as follows:</p><p>　　Where v, f, m are the cutting speed, feed, and tensile strength of workpiece material respectively, after being transferred to the coded value using the equation. </p>&l

53、t;p>　　In the extra two tests, the surface residual stress that were obtained using eq. (6) are 30.0871 and 32.485 MPa, respectively. </p><p>　　5. General discussion and summary </p><p>　　It c

54、an generally be seen from Fig. 2 that the residual stresses at the machined surface are low (tensile) and increase rapidly to a maximum (tensile) value with an increase in depth beneath the machined surface. The tensile

55、residual stresses then decrease gradually with a further increase in depth beneath the machined surface.</p><p>　　Complete analysis of the data showed that the residual stress continued to decrease across th

56、e section become either tensile or compressive at large depths. The maximum residual stresses always occur beneath the machined surface rather than on the nearest layer to the machined surface. The underlying assumption

57、in the entire model is that residual stress produced by identical conditions is also fairly identical. The variability of the profiles could be checked with standard variance techniques, </p><p>　　Models wit

58、h the capability of predicting residual stresses in machining operations are the critical link in the development of more complex models which can enable the concept of ‘custom manufacture’ machining of stainless steel,

59、steel, aluminum alloy, brass. Once such models are known, they can be used in conjunction with other models to provide information about the residual stress profile that would be most favorable in service conditions, and

60、 the used materials can be machined to maximize fa</p><p>　　In this paper an experimental model is described which has the capability of predicting residual stresses in five different materials as result of

61、turning operations. The proposed model fitted the experimental data with a high degree of accuracy as shown in Fig. 3. It should be pointed out here that this paper concentrates only on modeling the effect of machining p

62、arameters on residual stress distribution.</p><p><b>　　譯文</b></p><p>　　一殘余應力針對不同的材料車削的建模方法</p><p>　　M.H. El-Axir</p><p>　　生產(chǎn)技術部和機械設計Menoufia大學, Shebin El-Ko

63、m,埃及</p><p>　　獲得10項2001年7月通過日期2002年3月7日收到;接受2002年3月12日</p><p>　　摘要本文介紹了一種更全面的實驗模型，它有能力預測殘余應力剖面。這個數(shù)據(jù)提供了最大殘余應力對加工參數(shù)的影響，并確定雙方的位置和這個最高殘余應力深度現(xiàn)有模型的主要優(yōu)勢。五種不同的材料，即，不銹鋼steel304，鋼- 37，7001，2024鋁和黃銅合金是由轉

64、動利用實驗設計的響應面法的加工技術之一。這些材料的抗拉強度，切削速度和進給率被認為是三個輸入殘余應力分布參數(shù)的影響。在加工表面的殘余應力分布地區(qū)決心用偏轉蝕刻技術。這是這里提出的殘余應力剖面是三個輸入的參數(shù)確定的函數(shù)。另外，有人推測說，下表面沿深度的殘余應力剖面是一個表面深度下多項式函數(shù)和這個多項式的系數(shù)，反過來，輸入?yún)?shù)的功能。該模型已開發(fā)并已檢查的準確性。 。 2002年Elsevier科學有限公司保留所有權利。

65、</p><p>　　簡介疲勞壽命是一個重要的動力性能，而且在加工過程中的強烈[1]產(chǎn)生的表面狀況的影響。疲勞裂紋，在一般情況下，在形核部件的表面，然后大量傳播。由于抗裂紋擴展部分減少，剩余部分時不能再承受載荷的構件的疲勞發(fā)生。因此，它是在表面應力狀態(tài)，那里的裂紋形核，這是非常重要的。這種狀態(tài)是由于壓力和載荷的殘余應力（或自應力）在加工過程中產(chǎn)生的。殘余應力是各種機械和熱事件，這在表面區(qū)在加工過程中發(fā)生的結果。

66、它通常發(fā)現(xiàn)的殘余應力的絕對值接近表面高減小，在深度加工下的表面不斷增加，最終消失。殘余應力，可拉??伸或壓縮和??強調(diào)層可能淺或深，經(jīng)切割條件，工作材料，刀具幾何形狀而定。它已被證明[2-4]的殘余應力可能只是表面以下，反之亦然壓在表面和拉伸。壓縮殘余應力的普遍提高組件的性能和壽命，因為它們減少了服務（工作）拉應力，抑制裂紋形核。另一方面，殘余拉應力可以顯著提高服務（工作）強調(diào)，可導致[5-10]元器件過早失效。 例如，報

67、告說，原來的42CrMo4鋼試樣進行疲勞試驗呈現(xiàn)高強度殘余應力（高達600:800兆帕）顯示，接近30％的疲勞極限降低。 [12]報道，采用AISI 4340鋼淬火后flycu</p><p>　　因此，這是非常清楚的信息有關的殘余應力（沿深度的大小和方向）的資料的加工表面區(qū)域?qū)⒃谠O計和制造的零部件價值。因此，重要的是，對加工過程的殘余應力剖面參數(shù)的影響是確定的，隨后，這些加工參數(shù)，可以選擇將有利于提高

68、誘導殘余應力（壓應力）的疲勞壽命。 現(xiàn)有的關于對加工殘余應力剖面參數(shù)的影響的研究大部分是實驗性質(zhì)的。很少有分析模型可用。 [14,15]解釋，考慮應力應變歷史經(jīng)驗的表面層由于刀具運動的殘余應力的形成等。 [9]利用有限元技術，以確定加工殘余應力分布正交。吳和Matusmoto [16]也利用有限元素來決定因素，影響加工淬硬鋼的殘余應力的形成。 Devarajan等。 [17]構建了表面的殘余應

69、力預測的實驗模型。雖然表面殘余應力是最重要的加工過程，次表層殘余應力至少同樣重要。 本文介紹了一種更全面的實驗模型預測五種不同材料車削表面的殘余應力分布和地下。隨著這方面的知識幫助它會成為加工參數(shù)進行優(yōu)化，這樣的為這五個不同的材料加工零件表面完整性的服務條件下最大化。 2。實驗細節(jié) 2.1。工件材料 不銹鋼304，steel37，鋁合金7001鋁合金2024和黃銅工件利用的情況。<

70、/p><p>　　2.2。工件準備 這五個不同的材料加工成戒指形狀與圖所示的尺寸。 1A條。圖。 1b顯示了它的測試環(huán)芯軸上。這是可能的殘余應力在籌備工作中，由于加工工件表面區(qū)域引起的，因此有必要消除這些應力退火的工件。 304不銹鋼，鋼37，鋁。 7001鋁。 2024年，無需加工黃銅工件被加熱到800，595，340，340，260 °

71、C的3，6，2，2和1小時，分別，然后在空氣中或在爐冷卻。 在本次調(diào)查中，標本，加工利用的實驗設計之一。據(jù)中央組成二階三個獨立變量，實驗，總數(shù)N，可旋轉設計被確定為20。切削條件及其編碼列于表2。 在加工表面殘余應力分布，確定利用蝕刻技術在偏轉的殘余應力是重溫拆除，其余層殘余應力重新分配，直到達到新的平衡位置。這種形狀的變化可以測量從中可以計算出殘余應力。阿約15-25微米層去除的電化學腐蝕的幫助。層被拆除的

72、殘余應力狀態(tài)，直到成為可以忽略不計。所得為按表3 20種不同組合的殘余應力分布如圖所示。 2。 3。建議模式 該模型假設，殘余應力剖面以及殘余應力分布的深度加工參數(shù)的功能。該模型假定沿深度的殘余應力剖面的深度是多項式函數(shù)。配置文件可以表示為：</p><p>　　其中：Si為殘余應力，巴西全國工業(yè)聯(lián)合會是n階多項式項的系數(shù)，z是下方的加工表面的深度。此外，建議，該多項式的系

73、數(shù)是個別功能的加工參數(shù)。該系數(shù)關系到加工參數(shù)</p><p>　　在次是殘余應力剖面多項式系數(shù)和bxi是因素的影響（或因子的相互作用）十對每個參數(shù)的代碼，它的取值，第十，可從下面的變換方程。</p><p>　　其中V，F(xiàn)和T是裁料速度，飼料和拉伸強度分別。對bxis實驗確定的值。該過程如下：1。二十標本切斷使用不同的組合（見表3）在此項工作中使用的每個參數(shù)的五個層次。<

74、/p><p>　　2。殘余應力分布和每個樣本分布深度確定。3。一個預先決定多項式是安裝在每個試樣的殘余應力分布。4。系數(shù)（的RLI）這些多項式用來確定與下列用語的幫助bxis的值：</p><p>　　該模型的構建一個目視檢查的型材得到保證，至少有四分之一多項式將有足夠的證據(jù)認為適合個人資料。與第四次多項式的初步結果并不令人鼓舞。因此，決定使用第五次多項式來表示的殘余應力剖面。系數(shù)（rl

75、is）對應于不同的組合與最近五次多項式擬合見表4。應當指出，在這里進行了許多嘗試，推導出最佳的模型，給出了多項式之間的擬合模型結果和建議最小的變化。最好的方法，讓簡單合理系數(shù)時，得到各實驗結果采用標準值。利用適合每個實驗多項式方程系數(shù)，bxis值進行了測定。對bxis的計算值見表5。該bxis被用來預測獨聯(lián)體是該模型的系數(shù)。對于不同的切削條件獨聯(lián)體值列于表6。4.1。該模型是如何使用為了說明如何使用該模型，也驗證了提出的模

76、型，這兩個沒有通過實驗進行額外的測試20，發(fā)了言。這兩個額外的測試，結果顯示在圖。 4這表明實驗數(shù)據(jù)之間的數(shù)據(jù)模型，并提出很好的協(xié)議。這證明了使用該模型來預測殘余應力分布的加工表面下的有效性。步驟之后將使用該模型來預測下加工表面于表4-6所示的殘余應力分布。4.1.1。第1步轉讓的三個輸入?yún)?shù)使用轉換式于編碼值。 （2） - （4）。在這兩個額外的測試，實際和編</p><p>　　在該

77、模型的c系數(shù)應計算通過使用三個輸入在步驟1中獲取參數(shù)的編碼值，并使用了在表5所示bvalues??。</p><p>　　例如：系數(shù)有限公司可使用從表5中的b值如下：</p><p>　　在這兩個額外的測試值的C系數(shù)列于表7。</p><p>　　4.1.3。第3步在獲得C值，均衡器。 （5）這是一個在表面下深度函數(shù)坐標，可以形成和下方的加工表面殘余應力

78、分布才能確定。然而，在這個等式中代，下表面的深度值和Z，必須轉移到一個標準值。4.1.4。第4步通過在方程代使用任何深度，z時，在這個深度的殘余應力可以得到。應當指出，這里獲得的殘余應力，這是正常化。后者的殘余應力值已被轉移到由以下方程實際值。在這兩個額外的測試所使用的材料是Al7001（第三個關系應使用）。</p><p>　　4.1.5。第5步表面應力的計算使用一個單獨的模型。這是因為在工件表面制成，

79、殘余應力小，突然下達到在20-40微米的表面最高值，放松對衍生模型的準確性。表面殘余應力模型，被用來在每個參數(shù)值的任何預測，在加工表面的殘余應力值在這項工作中使用的范圍如下：</p><p>　　其中v，f，m是切割速度，飼料和工件材料的抗拉強度分別，后被轉移到編碼值使用公式。在加時賽中兩次測試，其表面的殘余應力得到了利用方程。 （6）30.0871和32.485MPa時。5。一般性討論和總

80、結 它通?？梢詮膱D。 2，殘余應力在加工表面低（拉伸），提高迅速，在深度加工表面之下增加至最高（張力）值。拉伸殘余應力，然后逐漸下降，在深度加工表面之下的進一步增加。</p><p>　　完整的數(shù)據(jù)分析表明，殘余應力在繼續(xù)減少或拉或壓在大深度成為一節(jié)。最大殘余應力總是出現(xiàn)下面的加工表面，而不是在最近層的加工表面。在整個模型的基本假設是，殘余應力相同的條件下生產(chǎn)也相當一致。該配置文件的變化可能與標準差

81、進行檢查技術，但是對于這個文件，被視為一種視覺檢查就足夠了。 與能力模型預測殘余應力在加工操作中的更復雜的模型發(fā)展的關鍵環(huán)節(jié)，可以使的'定制生產(chǎn)的不銹鋼，鋼，鋁合金，黃銅加工的概念。一旦這種模型是已知的，它們可以被用來與其他機型結合，提供有關的殘余應力剖面，將在條件最有利的信息服務，以及使用的材料可以加工最大限度的疲勞壽命。  在該文件中描述的實驗模型，它有能力預測殘余應力在五個不同的材料作為車削操作