G00代码是FANUC()数控车床系统的基本功能。 A: Oi B: OTE—A C: 6T D: 16M
G00代码是FANUC()数控车床系统的基本功能。 A: Oi B: OTE—A C: 6T D: 16M
证明 :若[tex=3.214x1.143]vHw/oydKZZRcQ6Ha7IOolg==[/tex], 则不等式 [tex=10.143x1.357]JvMrRuj+zJvf2QebJgjpS7arSupmBK6sozKybzwW6FTdJa05RgKctPsj6LokVSTa[/tex] 为真, 且仅当 [tex=1.857x1.0]bOlCq/PHWhsSVMaVf7Obdg==[/tex] 时,等号成立.
证明 :若[tex=3.214x1.143]vHw/oydKZZRcQ6Ha7IOolg==[/tex], 则不等式 [tex=10.143x1.357]JvMrRuj+zJvf2QebJgjpS7arSupmBK6sozKybzwW6FTdJa05RgKctPsj6LokVSTa[/tex] 为真, 且仅当 [tex=1.857x1.0]bOlCq/PHWhsSVMaVf7Obdg==[/tex] 时,等号成立.
质量为 [tex=4.714x1.429]H+jPEFBikLcpIj720UHUdJa+45gXaCRNWOkltox7Kd4=[/tex] 的质点受力作用作直线运动,力与时间成正比,且与质点的运动速度成正比,在 [tex=2.643x1.0]RlojybW0yVj/MkvvgkbMrA==[/tex] 时,速度等于 [tex=3.143x1.357]l5/S6J90QttIwSKlD1WXDg==[/tex] 所受力为 [tex=4.786x1.429]EsdCj1odt0vX+w1hHT0PYTbLwMJ3t9HwalYgZblXuJQ=[/tex] 问运动开始后 [tex=1.5x1.0]8GU1wCt+v1Btt7/otE+vhw==[/tex] 质点的速度是多少。
质量为 [tex=4.714x1.429]H+jPEFBikLcpIj720UHUdJa+45gXaCRNWOkltox7Kd4=[/tex] 的质点受力作用作直线运动,力与时间成正比,且与质点的运动速度成正比,在 [tex=2.643x1.0]RlojybW0yVj/MkvvgkbMrA==[/tex] 时,速度等于 [tex=3.143x1.357]l5/S6J90QttIwSKlD1WXDg==[/tex] 所受力为 [tex=4.786x1.429]EsdCj1odt0vX+w1hHT0PYTbLwMJ3t9HwalYgZblXuJQ=[/tex] 问运动开始后 [tex=1.5x1.0]8GU1wCt+v1Btt7/otE+vhw==[/tex] 质点的速度是多少。
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