花崗巖銑削刀具加工效能的系統(tǒng)研究
發(fā)布時間：2019-06-18 14:29
【摘要】：隨著計算機技術在花崗巖銑削加工中的應用,使得花崗巖雕刻制品在實際生活中已得到了大量的應用,同時也具有著更廣闊的應用前景。目前花崗巖加工機械設備技術已比較成熟,但刀具的使用效能成為了困擾花崗巖銑削加工的難題,其加工工藝參數(shù)一直使用經驗的工藝參數(shù),不適當?shù)募庸すに噮?shù)經常導致刀具磨損,甚至斷裂,縮短刀具使用壽命。而銑削力是影響刀具使用效能的關鍵因素,同時刀具的磨損也對加工效能有較大的影響。目前在花崗巖加工領域針對金剛石鋸片的研究成果較多,為實際加工提供了參考和依據(jù),但對花崗巖銑削加工刀具的研究較少,阻礙了花崗巖銑削技術的迅速發(fā)展和應用。因此,本文針對花崗巖銑削加工刀具加工效能關鍵因素進行了系統(tǒng)研究,所做的工作主要包括：(1)從壓痕斷裂理論入手,通過分析尖銳壓頭擠壓花崗巖的接觸應力及裂紋形成過程,研究花崗巖銑削加工的機理。運用ANSYS/LS-DYNA軟件進行壓痕仿真,模擬了金剛石顆粒在壓入花崗巖時裂紋的產生及應力狀態(tài),通過不同進給速度的加載,獲得了花崗巖和金剛石的最大應力,得出當切入深度一定時,金剛石的最大應力隨進給速度的增加而增大。并利用尖銳壓頭進行了壓痕實驗,通過顯微照片進一步對裂紋的構成和特征做了進一步描述和分析。(2)根據(jù)建立的加工模型,分析金剛石顆粒銑削花崗巖的幾何學參數(shù),推導了花崗巖銑削加工中工件與刀具相互作用弧長、平均切削厚度的理論公式。從切削前后切削體積相等入手,微觀上分析了單顆粒金剛石的受力情況,理論上建立了相關的特征因素的計算公式。主要包括銑刀單位長度靜態(tài)有效磨粒數(shù)N1、單位面積靜態(tài)有效磨粒數(shù)Ns和動態(tài)有效磨粒數(shù)Nd。同時進行了系統(tǒng)的公式推導,從宏觀理論上分析了一般銑削條件下的銑刀受力的情況,并結合實際花崗巖雕刻中的典型加工,建立了花崗巖雕刻的加工模型,推導花崗巖雕刻中銑削力公式。分析結果表明花崗巖銑削加工中銑削力大小與加工參數(shù)切削深度成比例增大,與進給速度成接近1/2的指數(shù)增長,與主軸轉速成接近1/2的指數(shù)遞減。(3)為了對理論分析結果進一步驗證,同時為后續(xù)的預測分析提供建模樣本數(shù)據(jù),搭建了花崗巖銑削力在線檢測的硬件系統(tǒng),并利用VC++6.0軟件開發(fā)了對應的檢測系統(tǒng)軟件,實現(xiàn)對加工過程中銑削力的動態(tài)檢測。(4)在搭建的檢測實驗臺上進行了花崗巖銑削力的實驗,完成了金剛石銑刀加工花崗巖的單因素實驗、正交實驗和刀具斷裂實驗。重點考察加工工藝參數(shù)主軸轉速n (r/min)、進給速度vf(mm/min)和切削深度αp (mm)對銑削力的影響。單因素實驗測量出對應加工工藝參數(shù)下的100組實驗樣本；做正交實驗并測量出對應加工工藝參數(shù)下的9組實驗樣本；做金剛石銑刀斷裂實驗并測出金剛石銑刀斷裂時所受的最大銑削力,獲得刀具斷裂的臨界銑削力。根據(jù)實驗數(shù)據(jù)進行了相關分析,同時獲得的實驗數(shù)據(jù)也為后續(xù)的神經網絡建模和驗證提供了樣本數(shù)據(jù)。(5)分別采用BP神經網絡和RBF神經網絡對花崗巖雕刻過程中的銑削力建立了預測模型,通過對MATLAB神經網絡工具箱中相關函數(shù)的調用實現(xiàn)了網絡設計、權值初始化和網絡訓練以及仿真等,通過實驗數(shù)據(jù)驗證了預測模型的可行性,使模型能夠根據(jù)不同的加工參數(shù)比較準確的預測銑削力。并根據(jù)實驗數(shù)據(jù)對兩種神經網絡的預測準確性做了比較。結果表明,利用BP神經網絡預測的銑削力雖然能夠保證其預測值的平均誤差低于6%,但單體誤差的波動較大,且與銑削力的理論計算值的平均誤差較大；相比之下,利用RBF神經網絡的預測模型預測的銑削力不僅平均誤差低于BP神經網絡,而且單體誤差波動比較穩(wěn)定,與銑削力的實驗值平均誤差為2.5173%,相比BP神經網絡誤差更小,更接近實際情況,切實可行,能根據(jù)加工工藝參數(shù)更準確的預測出花崗巖雕刻加工中金剛石銑刀的銑削力。(6)針對花崗巖加工中銑刀表面磨損情況進行了分析。從銑刀的磨損量和銑刀表面微觀的磨損形式進行了研究。分析銑刀磨損量與加工工藝參數(shù)：主軸轉速n(r/min)、進給速度vf (mm/min)和切削深度αp (mm)間的影響關系和規(guī)律；對銑刀表面微觀形態(tài)進行觀察分析研究其主要的磨損形式和對刀具壽命的影響。結合刀具的磨損情況,進行了新型刀具的探索實驗,將等離子熱噴涂技術引入到花崗巖加工刀具的制備中,并對制備的刀具進行了相關的刀具磨損實驗,并對實驗結果給出了較詳細的分析。本文最后結合RBF神經網絡預測模型、刀具斷裂實驗結果和刀具磨損分析,給出了花崗巖銑削加工過程中提高刀具加工效能,優(yōu)選加工工藝參數(shù)的步驟,該方法在保證刀具可靠加工的情況下,通過優(yōu)選加工參數(shù)提高材料去除率,從加工效率和刀具兩方面降低產品成本,通過石材企業(yè)的實際應用驗證了該方法的可行性。并給出了具體的應用實例,為花崗巖銑削加工中工藝參數(shù)的選擇提供了參考的方法和依據(jù)。通過優(yōu)選加工參數(shù),對花崗巖銑削加工中降低生產成本、提高加工效率具有一定的指導意義。
[Abstract]:With the application of computer technology in the process of granite surface cutting, the granite carving product has been widely used in the actual life, and has a wider application prospect. At present, the technology of the granite processing and mechanical equipment has been relatively mature, but the use efficiency of the tool has become a difficult problem for the processing of the granite of the granite, the processing process parameters of the tool have been using the process parameters of the experience, and the improper machining process parameters often cause the tool to wear and even break, And the service life of the cutter is shortened. The cutting force is a key factor that affects the efficiency of the tool, and the wear of the tool has a great effect on the processing efficiency. At present, the research results of the diamond saw blade in the field of granite processing are much more, and the reference and the basis for the actual processing are provided. However, the research on the granite cutting and processing tool is less, and the rapid development and application of the granite cutting technology are hindered. In this paper, a systematic study on the key factors of the machining efficiency of the cutting tool for granite is carried out. The main work is as follows: (1) from the theory of indentation fracture, the contact stress and the crack formation process of the granite are analyzed by the analysis of the sharp pressure head. In this paper, the mechanism of granite cutting and processing is studied. By using the software of ANSYS/ LS-DYNA to simulate the indentation, the generation and stress state of the crack during the press-in of the granite by the diamond particles are simulated, the maximum stress of the granite and the diamond is obtained through the loading of different feeding speeds, and when the cut-in depth is fixed, The maximum stress of the diamond increases with the increase in the feed rate. The formation and characteristics of the crack were further described and analyzed by the micrographs. (2) According to the established machining model, the geometric parameters of the diamond particles and the granite are analyzed, and the theoretical formula of the interaction arc length and the average cutting thickness of the workpiece and the tool in the granite cutting process is derived. Starting from the cutting volume before and after cutting, the stress condition of single-grain diamond is analyzed, and the relevant characteristic factors are theoretically established. The static and effective abrasive grain number N1, the static effective abrasive grain number Ns and the dynamic effective abrasive grain number Nd of the unit area are mainly included, and the formula derivation of the system is also carried out, Combining with the typical processing in the granite carving, the processing model of the granite carving is established, and the formula of the cutting force in the granite carving is derived. The results show that the size of the cutting force of the granite in the cutting process is increased in proportion to the cutting depth of the machining parameter, and the index with the feeding speed close to 1/2 is increased, and the index with the rotation speed of the main shaft is close to 1/2 is decreased. and (3) in order to further verify the theoretical analysis result, the data is provided for subsequent prediction analysis, a hardware system for on-line detection of the granite cutting force is built, and a corresponding detection system software is developed by using the VC ++ 6.0, And the dynamic detection of the cutting force in the machining process is realized. (4) The experiment of granite shearing force was carried out on the built-up test bench, and the single-factor experiment, the orthogonal experiment and the tool fracture experiment of the diamond cutter-processed granite were completed. The influence of the spindle speed n (r/ min), the feeding speed vf (mm/ min) and the cutting depth (p (mm) on the cutting force of the machining process parameters is mainly studied. a single-factor experiment is used to measure 100 groups of experimental samples corresponding to the processing process parameters, And the critical cutting force of the tool fracture is obtained. The relevant analysis is carried out according to the experimental data, and the obtained experimental data also provides the sample data for subsequent neural network modeling and verification. and (5) using the BP neural network and the RBF neural network to set up a prediction model for the cutting force in the granite carving process, and the network design, the weight initialization and the network training and the simulation are realized through the call of the related functions in the MATLAB neural network toolbox, The feasibility of the prediction model is verified by the experimental data, so that the model can accurately predict the cutting force according to different machining parameters. And the prediction accuracy of the two neural networks is compared according to the experimental data. The results show that the average error of the predicted value is lower than 6% by using the BP neural network, but the fluctuation of the monomer error is large, and the average error of the theoretical calculation value of the cutting force is large; in contrast, The prediction model of the RBF neural network not only has the average error lower than that of the BP neural network, but also the fluctuation of the monomer error is relatively stable, the average error of the experimental value with the cutting force is 2.5173%, and the error of the BP neural network is smaller and closer to the actual situation. The cutting force of the diamond cutting knife in the granite carving process can be predicted more accurately according to the processing process parameters. (6) The wear of the surface of the granite in the process of granite processing is analyzed. The wear and wear of the blade surface were studied. The influence relation and law of the wear and processing parameters of the cutting tool, the main shaft speed n (r/ min), the feeding speed vf (mm/ min) and the cutting depth (p (mm) were analyzed, and the main wear pattern and the influence on the life of the tool were studied. Combined with the wear of the tool, the new tool's exploration experiment is carried out, the plasma thermal spraying technology is introduced into the preparation of the granite processing tool, and the related tool wear experiment is carried out on the prepared tool, and the detailed analysis is given to the experimental results. In this paper, based on the prediction model of the RBF neural network, the experimental results of the tool fracture and the analysis of the wear of the tool, the step of improving the machining efficiency of the tool in the processing of the granite is given, and the process parameters are preferably processed. The material removal rate is improved by the preferred processing parameters, the product cost is reduced from the processing efficiency and the cutting tool, and the feasibility of the method is verified through the practical application of the stone enterprise. The specific application examples are given, and the reference method and the basis for the selection of the process parameters in the granite cutting process are provided. By optimizing the processing parameters, the production cost is reduced, and the processing efficiency is improved.
【學位授予單位】：東北大學
【學位級別】：博士
【學位授予年份】：2015
【分類號】：TG714
本文編號：2501555
[Abstract]:With the application of computer technology in the process of granite surface cutting, the granite carving product has been widely used in the actual life, and has a wider application prospect. At present, the technology of the granite processing and mechanical equipment has been relatively mature, but the use efficiency of the tool has become a difficult problem for the processing of the granite of the granite, the processing process parameters of the tool have been using the process parameters of the experience, and the improper machining process parameters often cause the tool to wear and even break, And the service life of the cutter is shortened. The cutting force is a key factor that affects the efficiency of the tool, and the wear of the tool has a great effect on the processing efficiency. At present, the research results of the diamond saw blade in the field of granite processing are much more, and the reference and the basis for the actual processing are provided. However, the research on the granite cutting and processing tool is less, and the rapid development and application of the granite cutting technology are hindered. In this paper, a systematic study on the key factors of the machining efficiency of the cutting tool for granite is carried out. The main work is as follows: (1) from the theory of indentation fracture, the contact stress and the crack formation process of the granite are analyzed by the analysis of the sharp pressure head. In this paper, the mechanism of granite cutting and processing is studied. By using the software of ANSYS/ LS-DYNA to simulate the indentation, the generation and stress state of the crack during the press-in of the granite by the diamond particles are simulated, the maximum stress of the granite and the diamond is obtained through the loading of different feeding speeds, and when the cut-in depth is fixed, The maximum stress of the diamond increases with the increase in the feed rate. The formation and characteristics of the crack were further described and analyzed by the micrographs. (2) According to the established machining model, the geometric parameters of the diamond particles and the granite are analyzed, and the theoretical formula of the interaction arc length and the average cutting thickness of the workpiece and the tool in the granite cutting process is derived. Starting from the cutting volume before and after cutting, the stress condition of single-grain diamond is analyzed, and the relevant characteristic factors are theoretically established. The static and effective abrasive grain number N1, the static effective abrasive grain number Ns and the dynamic effective abrasive grain number Nd of the unit area are mainly included, and the formula derivation of the system is also carried out, Combining with the typical processing in the granite carving, the processing model of the granite carving is established, and the formula of the cutting force in the granite carving is derived. The results show that the size of the cutting force of the granite in the cutting process is increased in proportion to the cutting depth of the machining parameter, and the index with the feeding speed close to 1/2 is increased, and the index with the rotation speed of the main shaft is close to 1/2 is decreased. and (3) in order to further verify the theoretical analysis result, the data is provided for subsequent prediction analysis, a hardware system for on-line detection of the granite cutting force is built, and a corresponding detection system software is developed by using the VC ++ 6.0, And the dynamic detection of the cutting force in the machining process is realized. (4) The experiment of granite shearing force was carried out on the built-up test bench, and the single-factor experiment, the orthogonal experiment and the tool fracture experiment of the diamond cutter-processed granite were completed. The influence of the spindle speed n (r/ min), the feeding speed vf (mm/ min) and the cutting depth (p (mm) on the cutting force of the machining process parameters is mainly studied. a single-factor experiment is used to measure 100 groups of experimental samples corresponding to the processing process parameters, And the critical cutting force of the tool fracture is obtained. The relevant analysis is carried out according to the experimental data, and the obtained experimental data also provides the sample data for subsequent neural network modeling and verification. and (5) using the BP neural network and the RBF neural network to set up a prediction model for the cutting force in the granite carving process, and the network design, the weight initialization and the network training and the simulation are realized through the call of the related functions in the MATLAB neural network toolbox, The feasibility of the prediction model is verified by the experimental data, so that the model can accurately predict the cutting force according to different machining parameters. And the prediction accuracy of the two neural networks is compared according to the experimental data. The results show that the average error of the predicted value is lower than 6% by using the BP neural network, but the fluctuation of the monomer error is large, and the average error of the theoretical calculation value of the cutting force is large; in contrast, The prediction model of the RBF neural network not only has the average error lower than that of the BP neural network, but also the fluctuation of the monomer error is relatively stable, the average error of the experimental value with the cutting force is 2.5173%, and the error of the BP neural network is smaller and closer to the actual situation. The cutting force of the diamond cutting knife in the granite carving process can be predicted more accurately according to the processing process parameters. (6) The wear of the surface of the granite in the process of granite processing is analyzed. The wear and wear of the blade surface were studied. The influence relation and law of the wear and processing parameters of the cutting tool, the main shaft speed n (r/ min), the feeding speed vf (mm/ min) and the cutting depth (p (mm) were analyzed, and the main wear pattern and the influence on the life of the tool were studied. Combined with the wear of the tool, the new tool's exploration experiment is carried out, the plasma thermal spraying technology is introduced into the preparation of the granite processing tool, and the related tool wear experiment is carried out on the prepared tool, and the detailed analysis is given to the experimental results. In this paper, based on the prediction model of the RBF neural network, the experimental results of the tool fracture and the analysis of the wear of the tool, the step of improving the machining efficiency of the tool in the processing of the granite is given, and the process parameters are preferably processed. The material removal rate is improved by the preferred processing parameters, the product cost is reduced from the processing efficiency and the cutting tool, and the feasibility of the method is verified through the practical application of the stone enterprise. The specific application examples are given, and the reference method and the basis for the selection of the process parameters in the granite cutting process are provided. By optimizing the processing parameters, the production cost is reduced, and the processing efficiency is improved.
【學位授予單位】：東北大學
【學位級別】：博士
【學位授予年份】：2015
【分類號】：TG714
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