可靠性设计大作业测试题目:基于应力-强度理论,完成某机械装备系统的可靠性设计。
已知:动力源为37KW 的四级电机,通过三级减速齿轮传动至工作机;系统可靠性R S= 0.93,系统传递效率η= 0.985 × 0.975 × 0.965,工作机输入转速为 120rpm。
1、1.1查资料可知四极电机的额定转速n1=1450r/min,而工作机输入转速为n6= 120r/min,由此可知总传动比为:i=i1+ i2+i3=n1n4=1450120=12.083对于多级减速传动,可按照“前小后大”(即由高速级向低速级逐渐增大)的原则分配传动比,且相邻两级差值不要过大。
这种分配方法可使各级中间轴获得较高转速和较小的转矩,因此轴及轴上零件的尺寸和质量下降,结构较为紧凑。
i2=√i3=2.29469477 ,为了便于计算,i2取2.3,i1取1.7,i3取3.1 1.2、三级减速器的运动和参数计算Ⅰ轴(与电动机直接相连)P1=P0=37KWn1=1450r/minT1=9549P1n1=243.66N∙mⅡ轴P2=P1η1=36.445KWn2=n11=852.94r/minT2=9549P2n2=408.02N∙mⅢ轴P3=P2η2=35.534KWn3=n2i2=370.84r/minT3=9549P3n3=914.99N∙mⅣ轴(工作轴)P4=P3η3=34.29KWn4=n3i3=119.63r/minT4=9549P4n4=2737.07N∙m1.3. 齿轮的设计三级减速器选择外啮合直齿圆柱齿传动,对于第一级,小齿轮模数为6mm,齿数为10,大齿轮模数为6mm,齿数为17;对于第二级,小齿轮模数为5mm,齿数为10,大齿轮模数为5mm,齿数为23;对于第三级,小齿轮模数为7mm,齿数为10,大齿轮模数为7mm,齿数为31。
三级减速器模型如图所示。
2、对于30CrMnSiA钢σr(R)=σr−Z RσσrR=0.5时,σr(0.5)=σr−Z Rσσr,查标准正态分布表可得Z R=0,则具体参数与上表相同R=0.999时,σr(0.999)=σr−Z Rσσ,查标准正态分布表可得Z R=3,具体参数如r下表所示,MATLAB作图Code:clear allSm=[0;180.73;456.15;1200];Sa=[241.3;147.87;152.05;0];Sm1=[0;180.73;456.15;1200];Sa1=[241.3;147.87;152.05;0];Sm2=[0;166.22;556.19;1150];Sa2=[213.85;217.9;185.02;0];figuresubplot(2,2,1);%点图h_;Sm=Sm(:);Sa=Sa(:);h_=line(Sm,Sa,'Color',[0.1 0.50.1],'linestyle','None','LineWidth',1,'Marker','+','MarkerSize',10);hold on%拟合图线line_;ok_=isfinite(Sm)&isfinite(Sa);if ~ all(ok_)warning('GenerateMFile:IgnoringNansAndInfs','IgnoringNaNs and Infs in data');endlin_=fittype('pchipinterp');cf_=fit(Sm(ok_),Sa(ok_),lin_);line_=plot(cf_,'fit',0.95);set(line_,'color','yellow','LineStyle','--','LineWidth',2,'Marker','None','MarkerSize',2);%legend label and title设置;legend([h_,line_],'Sa vs. Sm','fit1');xlabel('Sm');ylabel('Sa');title('均值疲劳极限线图');subplot(2,2,2);Sm1=Sm1(:);Sa1=Sa1(:);%点图h_;h_=line(Sm1,Sa1,'Color',[0 0 0],'linestyle','None','LineWidth',1,'Marker','o','MarkerSize',10);hold on%拟合图线line_;ok_=isfinite(Sm1)&isfinite(Sa1);if ~ all(ok_)warning('GenerateMFile:IgnoringNansAndInfs','IgnoringNaNs and Infs in data');endlin_=fittype('pchipinterp');cf_=fit(Sm1(ok_),Sa1(ok_),lin_);line_=plot(cf_,'fit',0.95);set(line_,'color','red','LineStyle','-','LineWidth',2,'Marker','None','MarkerSize',2);%legend label and title设置;legend([h_,line_],'Sa1 vs. Sm1','fit2');xlabel('Sm1');ylabel('Sa1');title('R=0.5疲劳极限线图');subplot(2,2,3);Sm2=Sm2(:);Sa2=Sa2(:);h_=line(Sm2,Sa2,'Color',[0.3 0 0.7],'linestyle','None','LineWidth',1,'Marker','^','MarkerSize',10 );hold on%拟合图线line_;ok_=isfinite(Sm2)&isfinite(Sa2);if ~ all(ok_)warning('GenerateMFile:IgnoringNansAndInfs','IgnoringNaNs and Infs in data');endlin_=fittype('pchipinterp');cf_=fit(Sm2(ok_),Sa2(ok_),lin_);line_=plot(cf_,'fit',0.95);set(line_,'color','green','LineStyle',':','LineWidth',2,'Marke r','None','MarkerSize',2);%legend label and title设置;legend([h_,line_],'Sa2 vs. Sm2','fit3');xlabel('Sm2');ylabel('Sa2');title('R=0.999疲劳极限线图');suptitle('疲劳极限线图 S1802W0148 李祯平')3、3.1 由第一问计算可知T1=9549P11=243.66N∙mT~N(μT,σT),μT=243.66N∙m,σT=24.366N∙m δ~N(μσ,σδ),μσ=614MPa,σδ=45.8MPaR=0.999,F=0.001σr=α3r,α=0.03查正态分布表可知Z R=3.09应力表达式为μτ=2Tπr3στ=√σT2(ðτ)2+στ2(ðτ)2=√4σT226+36T2σr228由此可以求出 r=0.7166mm,d=1.4321mmMATLAB 求解Problem31 Code:clear allsyms rformat shortR=0.999;zr=norminv(R);n=2000;sj=randn(n,8);T=243.66;sgmaT=24.366;T_mt=T+sgmaT*sj(:,1); %N.mD=614;sgmaD=45.8;D_mt=D+sgmaD*sj(:,2); %MPaalpha=0.03;sgmar=alpha*r/3;r_mt=r+sgmar*sj(:,3); %mmr_ave=mean(r_mt);r_ave=vpa(r_ave,5);r=r_ave;tao_mt=2*T_mt/pi/r^3;tao_ave=mean(tao_mt);tao_ave=vpa(tao_ave,5); tao_var=sum((tao_ave-tao_mt).^2)/n;tao_var=vpa(tao_var,5);ft=@(r)((D-eval(tao_ave))/sqrt(sgmaD^2+eval(tao_var))-zr);r=fsolve(ft,[2])d=2*r3.2 由3.1的代码可以依次计算可靠度R=[0.999;0.997;0.995;0.993;0.991;0.989;0.987;0.985;0.983;0.981]直径为d=[1.4333;1.4132;1.4040;1.3967;1.3941;1.3867;1.3837;1.3816;1.3783;;1.3757]Problem32 Code:clear alld=[1.4333;1.4132;1.4040;1.3967;1.3941;1.3867;1.3837;1.3816;1.3783;;1.3757];R=[0.999;0.997;0.995;0.993;0.991;0.989;0.987;0.985;0.983;0.981];d=d(:);R=R(:);h_=line(d,R,'Color',[0.1 0.50.1],'linestyle','None','LineWidth',1,'Marker','+','MarkerSize',10); hold onok_=isfinite(d)&isfinite(R);if ~ all(ok_)warning('GenerateMFile:IgnoringNansAndInfs','IgnoringNaNs and Infs in data');endlin_=fittype('pchipinterp');cf_=fit(d(ok_),R(ok_),lin_);line_=plot(cf_,'fit',0.95);set(line_,'color','yellow','LineStyle','--','LineWidth',2,'Marker','None','MarkerSize',2);legend([h_,line_],'d vs. R','fit1');xlabel('d/mm');ylabel('可靠度');title('可靠度直径曲线');有由图可知,当可靠度低于0.999时,直径参数对可靠度印象较大,且可靠度随着直径的增大增加的幅度在减小,趋势慢慢的变缓。