机械工程学报
機械工程學報
궤계공정학보
Journal of Mechanical Engineering
2015年
19期
197-205
,共9页
董新峰%张为民%孙嘉彬%刘朝晖
董新峰%張為民%孫嘉彬%劉朝暉
동신봉%장위민%손가빈%류조휘
不一致刀齿%理论铣削力系数%名义铣削力%实际铣削力系数%核偏最小二乘
不一緻刀齒%理論鐉削力繫數%名義鐉削力%實際鐉削力繫數%覈偏最小二乘
불일치도치%이론선삭력계수%명의선삭력%실제선삭력계수%핵편최소이승
asymmetrical teeth%theoretical milling force coefficient%nominal milling force%actual milling force coefficient%kernel partial least square regression
针对薄壁件铣削过程中刀齿半径不一致现象引起的铣削力系数计算失真问题,提出构造刀齿半径不一致时的实际铣削力系数,并采用核偏最小二乘法对不同铣削用量时的实际铣削力系数进行预测。针对两齿螺旋铣刀铣削过程推导理论铣削力系数,根据刀齿半径不一致铣削过程引入名义铣削力,推导刀齿半径误差,构造实际铣削力系数;基于核分析方法突出的非线性分析及预测能力,提出采用核偏最小二乘法在高维空间建立实际铣削力系数关于铣削用量及其组合量的预测模型,分析该方法中核主元个数、高斯核函数核参数对预测模型精度的影响并确定其取值范围。最后分析考虑刀齿半径误差与不考虑时的铣削力系数,并比较核偏最小二乘预测方法与偏最小二乘预测方法,结果表明所提铣削力系数构造过程及预测方法具有较高的计算精度和预测能力。
針對薄壁件鐉削過程中刀齒半徑不一緻現象引起的鐉削力繫數計算失真問題,提齣構造刀齒半徑不一緻時的實際鐉削力繫數,併採用覈偏最小二乘法對不同鐉削用量時的實際鐉削力繫數進行預測。針對兩齒螺鏇鐉刀鐉削過程推導理論鐉削力繫數,根據刀齒半徑不一緻鐉削過程引入名義鐉削力,推導刀齒半徑誤差,構造實際鐉削力繫數;基于覈分析方法突齣的非線性分析及預測能力,提齣採用覈偏最小二乘法在高維空間建立實際鐉削力繫數關于鐉削用量及其組閤量的預測模型,分析該方法中覈主元箇數、高斯覈函數覈參數對預測模型精度的影響併確定其取值範圍。最後分析攷慮刀齒半徑誤差與不攷慮時的鐉削力繫數,併比較覈偏最小二乘預測方法與偏最小二乘預測方法,結果錶明所提鐉削力繫數構造過程及預測方法具有較高的計算精度和預測能力。
침대박벽건선삭과정중도치반경불일치현상인기적선삭력계수계산실진문제,제출구조도치반경불일치시적실제선삭력계수,병채용핵편최소이승법대불동선삭용량시적실제선삭력계수진행예측。침대량치라선선도선삭과정추도이론선삭력계수,근거도치반경불일치선삭과정인입명의선삭력,추도도치반경오차,구조실제선삭력계수;기우핵분석방법돌출적비선성분석급예측능력,제출채용핵편최소이승법재고유공간건립실제선삭력계수관우선삭용량급기조합량적예측모형,분석해방법중핵주원개수、고사핵함수핵삼수대예측모형정도적영향병학정기취치범위。최후분석고필도치반경오차여불고필시적선삭력계수,병비교핵편최소이승예측방법여편최소이승예측방법,결과표명소제선삭력계수구조과정급예측방법구유교고적계산정도화예측능력。
Concentrated on the distortion problem of milling force coefficient calculation caused by the different cutter tooth radii in thin-walled parts milling, actual milling force coefficient is constructed, and is predicted through kernel partial least square regression method when milling parameters change. To construct actual milling force coefficient, theoretical milling force coefficient is deduced for two-teeth spiral milling cutter, nominal milling force is defined based on the milling process with cutter of different tooth radii, and cutter tooth radius error is deduced. Prediction model of actual milling force coefficient about milling parameters and their compositional variables, is established in high dimension space through kernel partial least square regression method based on the prominent nonlinear analysis and prediction ability of nuclear analysis; kernel parameters of Gaussian kernel function and the number of kernel principal components, whose impact on prediction model is analyzed, are set in certain value range in kernel partial least square regression method. At last, milling force coefficients are analyzed respectively when cutter tooth radius error is considered or not, and kernel partial least square regression prediction method and partial least square regression prediction method are compared; according to above data, the proposed construction and prediction methods of milling force coefficient have high calculation accuracy and prediction ability.