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机器人辅助轮带磨削作为一种确定性加工方式,为了保证加工过程的稳定性,需要稳定的去除函数。在自由曲面的轮带磨削加工中,由于其上各点的曲率是变化的,磨削工具要想保证始终垂直于接触面,进行法向跟随加工,其姿态必然会一直发生变化,如图2所示。
在实际的轮带磨削加工过程中,受磨削装置本身悬臂结构重力的影响,当磨削工具发生姿态变化时,磨削装置接触轮末端输出压力会发生较为明显的变化,导致去除函数发生改变。因此,需要对机器人辅助轮带磨削进行力控制,在加工过程中保证输出法向压力的稳定,即需要对由悬臂结构自身重力带来的影响进行补偿。
进行力控制首先需要对加工过程进行不同位置的受力分析,建立重力分量模型。如图3所示,以工件接触区域中心O为原点,以竖直方向为z轴建立固定坐标系O-xyz坐标系;当磨削工具以任意姿态接触工件表面时,以接触区域中心O′为原点,以磨削装置悬臂方向为w轴,建立工具坐标系O′-uvw坐标系。当两坐标系只发生相对转动时,可视为O-xyz固定坐标系分别绕z轴旋转$\psi $角度,绕y轴旋转$\theta $角度,绕x轴旋转$\gamma $角度后,得到O′-uvw工具坐标系。
任意空间矢量$ \vec p $在固定坐标系和工具坐标系中可分别表示为$\overrightarrow {OP} $和$\overrightarrow {O'P} $,两个空间矢量的关系如下:
$$ \overrightarrow {OP} = R \cdot \overrightarrow {O'P} $$ (1) 其中
$$ \begin{split} R =& {R_1} \cdot {R_2} \cdot {R_3}{\text{ }} = \left[ {\begin{array}{*{20}{c}} {\cos \psi }&{ - \sin \psi }&0 \\ {\sin \psi }&{\cos \psi }&0 \\ 0&0&1 \end{array}} \right]\\ & \left[ {\begin{array}{*{20}{c}} {\cos \theta }&0&{\sin \theta } \\ 0&1&0 \\ { - \sin \theta }&0&{\cos \theta } \end{array}} \right]\left[ {\begin{array}{*{20}{c}} 1&0&0 \\ 0&{\cos \gamma }&{ - \sin \gamma } \\ 0&{\sin \gamma }&{\cos \gamma } \end{array}} \right] \end{split}$$ (2) 考虑悬臂杆重力分量对输出压力的影响时,在固定坐标系中悬臂杆重力矢量可视为$\overrightarrow {OP} = {\left[ {0,0,G} \right]^{\rm{T}}}$。轮带磨削工具旋转任意角度后,重力矢量变成:
$$ \overrightarrow {O'P} = {R^{ - 1}}{\left[ {0,0,G} \right]^{\rm{T}}} = \left[ \begin{gathered} - G \cdot \sin \theta \\ G \cdot \cos \theta \cdot \sin \gamma \\ G \cdot \cos \theta \cdot \cos \gamma \\ \end{gathered} \right] $$ (3) 其中,重力矢量在工具坐标系中沿w方向的分量为:
$$ \overrightarrow {O'Pw} = G \cdot \cos \theta \cdot \cos \gamma $$ (4) 接触轮输出压力Foutput可以表示为:
$$ F_{output}=F_{cylinder}+G\cdot \mathrm{cos}\theta \cdot \mathrm{cos}\gamma -2F_{belt} $$ (5) 式中:$ F_{cylinder} $为主动气缸输出压力;$ F_{belt} $为磨削砂带张紧力;$G$为悬臂组件重力。
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重力补偿控制系统由姿态传感器、执行元件、控制器等组成,以实现MQQTB10-10D低摩擦直线气缸输出压力的快速调整。重力补偿控制系统工作原理如图4所示,整个重力补偿系统基于自适应控制的工作原理,通过识别机器人的姿态变化,获取控制系统的输入与输出信号,对比当前输出值与期望输出值的偏差,并做出相应的决策,在线调整系统的输入信号,使系统输出值趋于期望值。具体的控制过程如下:重力补偿控制系统工作时,上位机与姿态传感器以及DA转换模块实时通信,接收由姿态传感器发出的角度变化信号,并根据重力补偿算法进行数据处理,进而给DA转换模块发出相应的信号使电气比例阀作出响应动作,控制电流并输出补偿后的气压值,实现MQQTB10-10D低摩擦直线气缸输出压力的稳定。
姿态传感器和电气比例阀安装在机器人末端轮带磨削工具的支撑组件上。六轴机械臂负载能力有限,因此在重力补偿系统硬件选型时要综合考虑其性能和质量。同时,要考虑上位机与下位机实现通信需要线路布局,选取的硬件必须尽可能简单、稳定且可靠。基于此,选用SINDT02倾角传感器作为姿态传感器,以低摩擦直线气缸为执行元件,以ITV2000电气比例阀和DAM-3202C转换模块、开发的上位机组成控制器,对气路、电路和软件控制方案进行正确设置,完成末端执行器重力变化补偿控制系统样机的硬件组装和软件调试。样机实物如图5所示。
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为了进行重力补偿系统的性能测试,需要对系统输出的恒力范围进行标定,如图6所示。公-自转机器人辅助轮带磨削装置可实现在0~63 N范围内的恒力输出。
磨削装置自身决定了输出恒力的范围,而上位机控制输出压力的精确性反映整个重力补偿系统性能,所以需要对装置绕X轴和Y轴旋转的重力补偿控制精度进行测试。如图7所示,电气比例阀设置常用的工作气压为0.2 MPa,操作机械臂示教器使轮带磨削工具进行旋转,绕X轴旋转记为Rx,绕Y轴旋转记为Ry。
在重力补偿系统关闭状态下操作示教器使轮带磨削工具分别绕固定坐标系X轴、Y轴旋转0°~72°,每间隔9°记录测力仪的压力值分别为F1、F3。接通24 V稳压直流电源,分别给ITV2000电气比例阀和DAM-3202C转换模块供电,打开重力补偿控制系统上位机,运行软件控制程序,再次操作示教器,使轮带磨削工具分别绕固定坐标系X轴、Y轴旋转0°~72°,每间隔9°记录测力仪的压力值分别为F2、F4。记录实验数据如表1、表2所示。
表 1 绕X轴旋转输出压力对比
Table 1. Comparison of output pressure during rotation around the X-axis
Rx/(°) F1/N F2/N 0 19.75 19.75 9 19.45 19.75 18 18.95 19.55 27 18.49 19.52 36 17.73 19.68 45 16.60 19.60 54 16.50 19.68 63 15.64 19.56 72 15.21 19.39 表 2 绕Y轴旋转输出压力对比
Table 2. Comparison of output pressure during rotation around the Y-axis
Ry/(°) F3/N F4/N 0 19.71 19.71 9 19.21 19.47 18 19.61 19.68 27 19.13 19.65 36 19.09 19.53 45 18.69 19.42 54 18.05 19.54 63 16.44 19.55 72 15.61 19.44 如图8所示,绕X轴旋转0°,0.2 MPa气压下输出19.75 N。无重力补偿时,输出压力随轮带磨削工具绕X轴旋转角度增大而衰减。在旋转72°时产生最大误差4.54 N,与旋转0°时输出压力相比,衰减22.99%。有重力补偿时,并未出现明显的压力衰减现象。在旋转72°时最大压力误差为0.36 N,与旋转0°时输出压力相比仅相差1.82%。
如图9所示,绕Y轴旋转0°,0.2 MPa的气压输出19.71 N的压力。在无重力补偿时,输出压力随轮带磨削工具绕Y轴旋转角度增大而衰减。在旋转72°时产生最大误差4.10 N,与旋转0°的输出压力相比衰减20.80%。当重力补偿控制系统运行,有重力补偿时,并未出现明显的压力衰减现象。在旋转72°时最大压力误差为0.29 N,与旋转0°的输出压力相比,仅相差1.47%。
当末端执行器姿态变化时,通过对有无重力补偿下输出压力的变化对比,发现文中设计的重力补偿控制系统有较好的补偿效果,能够在姿态变化过程中实现0~63 N范围输出压力的稳定性。同时,综合考虑SINDT02倾角传感器、ITV2000电气比例阀和DAM-3202C转换模块自身的响应频率高于100 Hz以及上位机读取写入的延时,通过测试,重力补偿装置响应时间小于300 ms。
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根据图10建立坐标系,砂带绕Xt轴自转角速度为ωo,绕Zt轴公转角速度为ωe,磨削装置的自转和公转角速度矢量可以表示为:
$$ \overrightarrow{{\omega }_{x}}={\omega }_{{{o}}}\left(\mathrm{cos}\psi \cdot \mathrm{cos}\theta \text{,}\mathrm{sin}\psi \cdot \mathrm{cos}\theta \text{,}\mathrm{sin}\theta \right) $$ (6) $$ \begin{split} \overrightarrow {{\omega _z}} =& {\omega _{{e}}}( \cos \psi \cdot \sin \theta \cdot \cos \gamma + \sin \psi \cdot \sin \gamma ,\sin \psi \cdot \sin \theta \cdot \\ & \cos \gamma - \cos \psi \cdot \sin \gamma ,\cos \theta \cdot \cos \gamma ) \end{split} $$ (7) Oo-XoYoZo光学元件坐标系中,点A(X,Y,Z)位置处的相应速度可以表示为相应角速度矢量和位置矢量的叉积。在接触区域中,只有磨削工具和光学元件表面之间的切向相对速度对去除函数有影响。因此,只需要考虑Xo轴和Yo轴方向的速度。Xo轴和Yo轴方向的切向速度为:
$$ \left\{ {\begin{array}{*{20}{c}} {{{\vec v}_{tx}} = \vec v \times {{\vec n}_{tx}} = \dfrac{1}{{\sqrt {1 + {{\left(\dfrac{{\partial z}}{{\partial x}}\right)}^2}} }}\left({v_x} + {v_z}\dfrac{{\partial z}}{{\partial x}}\right)} \\ {{{\vec v}_{ty}} = \vec v \times {{\vec n}_{ty}} = \dfrac{1}{{\sqrt {1 + {{\left(\dfrac{{\partial z}}{{\partial y}}\right)}^2}} }}\left({v_y} + {v_z}\dfrac{{\partial z}}{{\partial y}}\right)} \end{array}} \right. $$ (8) 式中:$ \vec v $=(vx,vy,vz)为自转和公转线速度的矢量和;$ {\vec n_{tx}} $和$ {\vec n_{ty}} $分别为Xo轴和Yo轴的单位矢量。因此,A(X,Y,Z)在接触区域任意一点的速度分布为:
$$ v\left( {x,y} \right) = \sqrt {{v_{tx}}^2 + {v_{ty}}^2} $$ (9) 最终可得到简化后的相对速度分布模型为:
$$ v\left( {x,y,t} \right) = \sqrt {{{\left( { - {\omega _o}{R_1}\sin {\omega _e}t - {\omega _e}y} \right)}^2} + {{\left( {{\omega _o}{R_1}\cos {\omega _e}t + {\omega _e}x} \right)}^2}} $$ (10) 其中
$$ {R_1} \approx \sqrt {{R^2} - {r^2}} $$ 式中:R为接触轮半径;r为接触区域半径。
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在公转-自转轮带磨削装置的磨削过程中,磨削砂带被接触轮的压力贴合在光学元件的表面上。然而,由于接触轮的表面硬度比磨削砂带的表面硬度小得多,接触问题可以简化为接触轮和光学元件之间的接触。此时,总接触压力F可以定义为[19]:
$$ F = {\vec Z_t} \cdot {\vec Z_o} \oiint_S {P(x,y){\rm{d}}x{\rm{d}}y} $$ (11) 式中:$ {\vec Z_t} $为自转轴的方向矢量;$ {\vec Z_o} $为公转轴的方向矢量;P(x, y)为压强分布模型。
根据赫兹接触理论,接触轮和光学元件在压力下会形成一个三维椭圆接触区域。椭圆形接触区域中的压强分布遵循公式(12)[19]:
$$ P\left( {x,y} \right) = \frac{{3{F_{}}}}{{2\pi ab}}{\left[ {1 - \left( {\frac{{{x^2}}}{{{a^2}}} + \frac{{{y^2}}}{{{b^2}}}} \right)} \right]^{\tfrac{3}{2}}} $$ (12) 式中:a为椭圆区域的长轴;b为椭圆区域的短轴。
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据广义Preston方程,根据之前建立的砂带磨削装置的磨削压强分布和速度分布模型,对其进行积分可以得到时间t内的材料去除量z(x,y)[20]:
$$ z\left( {x,y} \right) = K\int_0^t {P{{\left( {x,y} \right)}^\alpha }v{{\left( {x,y,t} \right)}^\beta }{\rm{d}}t} $$ (13) 式中:K为广义Preston系数;P(x, y)为接触区域的压强分布;v(x, y, t)为接触区域的速度分布;α为压力拟合系数,β为速度拟合系数。对z(x, y)进一步计算得到去除函数R(x,y):
$$ \begin{split} R\left(x,y\right)=&{K}_{I}{\left[1-\left(\frac{{x}^{2}}{{a}^{2}}+\frac{{y}^{2}}{{b}^{2}}\right)\right]}^{\tfrac{3\alpha }{2}}\times\\ &{\int }_{0}^{t}{[{\left({\omega }_{o}{R}_{1}\right)}^{2}+{\left({\omega }_{e}r\right)}^{2}+2{\omega }_{o}{\omega }_{e}{R}_{1}\left(x \cos\left({\omega }_{e}t\right)+\right.}\\ & {\left. y \sin\left({\omega }_{e}t\right)\right)]}^{\tfrac{\beta }{2}}{\rm{d}}t \end{split} $$ (14) 式中:${K_I} = \dfrac{{KP}}{T}$;$P = \dfrac{{5 F}}{{2\pi ab}}$。
去除函数的仿真结果如图11所示。
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基于上述理论建模和求解出的去除函数,为了验证轮带磨削工具对光学曲面的修形能力,对碳化硅(SiC)曲面和硫化锌(ZnS)非球面进行磨削实验。正弦曲面的截面线公式可以表示为:
$$ z=-0.005 \sin \left(\frac{\pi x}{5}\right) $$ (15) x的取值范围是[0, 20] mm,y的取值范围是[0, 20] mm,加工后的理想正弦曲面如图12所示。
用GBS SmartWLI 白光干涉仪检测初始表面,如图13所示,Ra值为0.168 μm,表面质量较差。
首先采用3 μm粒度金刚石砂带,主动气缸压力设置为0.28 MPa,砂带线速度为350 mm/s,冷却液采用1∶20稀释的金刚石磨削冷却液,对初始平面进行平面加工修形。加工后的碳化硅平面白光检测结果如图14所示,Ra值为9.565 nm。
以加工修形后的碳化硅平面为初始平面加工正弦曲面,主动气缸压力设置为0.28 MPa,砂带线速度为350 mm/s,冷却液采用1∶20稀释的金刚石磨削冷却液,分别采用3 μm和1 μm粒度金刚石砂带迭代两次进行修形加工。计算轮带磨削去除余量分布,如图15所示。通过驻留时间算法生成光栅路径扫描轨迹机械臂数控文件并导入机械臂控制器。
对加工后的工件采用轮廓仪测量,使用数据处理软件对比理论轮廓和实际轮廓,结果如图16所示。正弦曲面的最终加工PV值为1.414 μm。
待加工硫化锌非球面的方程如公式(16)所示,非球面参数如表3所示。
$$ Z = \frac{{{{c}}{{{y}}^2}}}{{R(1 + \sqrt {1 - (1 + K){\text{c}}{y^2}} )}} + A{y^4} + B{y^6} + C{y^8} + D{y^{10}} $$ (16) 如图17(a)所示,用Taylor Hobson PGI 1240轮廓仪进行检测,硫化锌非球面的面形误差如图18所示,其初始面型PV值为8.4 μm,Ra值为0.492 μm。
在修形算法中导入硫化锌非球面的轮廓测量数据,采用8000#氧化铝磨削带,配合20 nm粒度的二氧化硅抛光液进行磨削加工,公转速度40 r/min,气缸压力为2 N。如图17(b)所示,修形后硫化锌非球面的面形轮廓与初始面形轮廓相比数据波动明显降低,PV值收敛至2.7 μm,表面轮廓粗糙度显著降低,Ra值收敛到10.2 nm,图19为修形加工后的硫化锌非球面。
表 3 硫化锌非球面参数
Table 3. ZnS aspheric parameters
R c K A B C D 509.25 0.001 963 7 0 −1.273 631E-06 3.062 490E-10 −4.732 41E-14 4.979 344E-18 图 17 轮廓仪检测图像。(a) 硫化锌非球面初始面形轮廓;(b) 硫化锌非球面修形后面形轮廓
Figure 17. Profile gauge inspection image. (a) Initial profile of aspheric ZnS surface; (b) Surface profile of aspheric ZnS after machining
通过对碳化硅曲面和硫化锌非球面的加工表明,在公自转轮带磨削工具与所设计的重力补偿系统协同作用下,能够有效地提升复杂曲面元件的表面质量。
Design of gravity compensation and machining process for robotic belt grinding (invited)
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摘要: 机器人辅助轮带磨削是一种基于计算机控制光学成形技术的确定性加工方法,具有成本低、柔性好、智能程度高且操作空间大的优点,因此机器人辅助轮带磨削作为一种较低成本的高精度、多自由度加工方法逐渐受到关注。文中介绍了所设计的机器人辅助轮带磨削系统结构及其加工原理,装置通过气动系统进行输出压力的柔顺控制。研究了任意加工姿态下机器人辅助轮带磨削中的恒力加载问题,分析了轮带磨削工具悬臂组件重力分量对其末端输出接触力的影响,建立了末端执行器的重力分量模型,并提出了基于姿态传感器的重力补偿控制方法,能够实现0~63 N范围内的恒力控制,并且最大压力波动小于1.82%,重力补偿系统的响应时间小于300 ms,实现了轮带磨削工具在任意姿态下的恒力加载。最后,根据Hertz接触理论和Preston方程完成了磨削工具在工件接触区域内的压强分布和速度分布分析,建立了轮带磨削工具的去除函数模型,并对碳化硅曲面与硫化锌非球面进行修形磨削实验,验证了装置加工的稳定性。Abstract:
Objective The application of complex surfaces in aerospace, optical engineering, shipbuilding, and other fields is becoming increasingly widespread. The surface roughness of complex surface components directly affects their performance, efficiency, and lifespan. Improving the surface quality of complex surface components has a significant impact on enhancing their operational performance. The substantial demand for high-precision machining imposes higher requirements on the surface accuracy and complexity of related optical elements. To address the challenges in machining difficult optical elements, such as processing deep cavities and high steepness optical components, this paper proposed a robot-assisted wheel abrasive belt grinding method. Additionally, a gravity compensation system for the wheel abrasive belt grinding device was designed, and the constant force loading and smooth control problems in robot-assisted wheel abrasive belt grinding under arbitrary processing orientations were investigated. Methods This paper proposed a robot-assisted wheel abrasive belt grinding method (Fig.1) and analyzed the influence of the end effector's gravity component on the output pressure. A gravity compensation system for the wheel abrasive belt grinding device was designed (Fig.4), and a physical prototype of the device was built (Fig.5). The performance of the gravity compensation system was tested. Based on Hertz contact theory and Preston equation, the removal function of the wheel abrasive belt grinding device was established (Fig.11). The effectiveness of the device was validated through grinding experiments on a sinusoidal silicon carbide (SiC) surface (Fig.16) and a zinc sulfide (ZnS) aspheric surface (Fig.19). Results and Discussions Due to the influence of the gravity from the cantilever structure of the grinding device itself, when the grinding tool undergoes changes in posture, the output pressure at the end of the grinding device's contact wheel will experience noticeable variations. To address this, we established a model for the gravity component of the cantilever and designed a gravity compensation system. During the operation of the gravity compensation control system, real-time communication was established between the upper computer, attitude sensor, and DA conversion module. The system received angle change signals from the attitude sensor and processed the data using the gravity compensation algorithm. Subsequently, the system sent corresponding signals to the DA conversion module, triggering the electrical proportional valve to respond, control the current, and output the compensated air pressure, thus achieving a stable control of the output pressure for the MQQTB10-10D low-friction linear cylinder. The system was capable of achieving constant force control within the range of 0-63 N (Fig.6), with maximum pressure fluctuations less than 0.36 N. The response time of the gravity compensation system was less than 300 ms, enabling constant force loading of the wheel abrasive belt grinding tool under arbitrary postures. Conclusions In this paper, a constant force loading system was established for the public-self-rotation wheel abrasive belt grinding tool of the robot-assisted wheel abrasive belt grinding system. A gravity compensation system based on attitude sensors was designed. The wheel belt grinding process was applied to both atmospheric pressure sintered SiC and ZnS aspheric surfaces. For SiC, the Ra value decreased from 0.168 μm to 9.565 nm after machining, resulting in a sinusoidal surface with a PV value of 1.414 μm. As for ZnS aspheric, the Ra value reduced from 0.492 μm to 10.2 nm, and the PV value converged from 8.4 μm to 2.7 μm after the grinding process. This validated the processing stability of the wheel abrasive belt grinding tool and the rationality of the grinding algorithm. The study can provide theoretical guidance for robot-assisted grinding of complex surface optical elements and hold practical value in this field. -
表 1 绕X轴旋转输出压力对比
Table 1. Comparison of output pressure during rotation around the X-axis
Rx/(°) F1/N F2/N 0 19.75 19.75 9 19.45 19.75 18 18.95 19.55 27 18.49 19.52 36 17.73 19.68 45 16.60 19.60 54 16.50 19.68 63 15.64 19.56 72 15.21 19.39 表 2 绕Y轴旋转输出压力对比
Table 2. Comparison of output pressure during rotation around the Y-axis
Ry/(°) F3/N F4/N 0 19.71 19.71 9 19.21 19.47 18 19.61 19.68 27 19.13 19.65 36 19.09 19.53 45 18.69 19.42 54 18.05 19.54 63 16.44 19.55 72 15.61 19.44 表 3 硫化锌非球面参数
Table 3. ZnS aspheric parameters
R c K A B C D 509.25 0.001 963 7 0 −1.273 631E-06 3.062 490E-10 −4.732 41E-14 4.979 344E-18 -
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