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第 8期试题解答首先利用约利弹簧秤和砝码求出弹簧的劲度系数 (用作图法处理数据 ) ,然后得出待测物的质量 ;再求出待测物浸没在水中排开水的质量 ,进而由阿基米德定律求出其体积 ;知道了待测物的质量、总体积以及两种组分的密度 ,就可以算出每种材料的含量 .测量步骤为 :1 )弹簧挂在约利弹簧秤顶端 ,弹簧下端挂砝码盘 .盘内放不同质量的砝码时 ,记录约利弹簧秤弹簧伸长的读数 .以砝码质量为横坐标 ,伸长读数为纵坐标 ,做直线拟合数据 .2 )取出盘内砝码 ,放入待测物 .记录弹簧伸长读数 X,用拟合直线求出待测物质量 M.3 )将盛水烧杯放在约利… 相似文献
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橡皮筋滞后特性的实验分析 总被引:2,自引:2,他引:0
利用约利弹簧秤对橡皮筋的力的滞后特性进行了实验分析,并由此说明了不能用橡皮筋做测力计的物理机理,为检验弹簧的质量提供了一种实验途径及理论依据. 相似文献
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超重和失重现象是物理教学大纲所要求的演示实验,它的难度较大。通常的演示方法是让弹簧秤与物体一同在竖直方向作变速运动,并在这种快速运动中观察弹簧秤受力增大和减小的变化情况,以此来说明物体处于超重状态或失重状态的现象。这种演示方法有两个问题:第一,弹簧秤指针和弹簧秤刻度标尺以及作为研究物的物体都在同一竖直方向上作快速运动,弹簧秤指针的小幅度位移往往被系统同一方向上的大幅度运动所掩盖,学生难以观察到指针位移的变化。第二,弹簧秤从静止到急剧上升的过程中,弹簧秤首先上升作加速运动,物体则由于惯性,随后才向上作加速运动。二者的运动起始时刻不一致,加速度也不一致。甚至物体尚没运动,弹簧秤已经伸长读数值增大了。因此,这时弹簧秤增大的读值(或最大值)很难说是由于物体向上作加速运动而产生的。同理,弹簧秤急剧下降时也存在同样的问题。 相似文献
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初二物理安排了定滑轮的演示实验.按照课本中的插图去做实验,往往容易得出“拉力小于钩码的重力,能省力”的错误结论.原因是:用弹簧秤向下拉绳头提钩码时,弹簧秤外壳的重力通过滑轮平衡了钩码的一部分重力.但是,弹簧秤外壳在弹簧的上方,其重力不能使弹簧伸长,其大小不能显示在弹簧刻度上,总的拉力应该是弹簧秤上的读数加上弹簧秤外壳的重力,而进行数据处理时,往往疏忽了弹簧秤外壳的重力,只计入弹簧秤上的读数.这样拉力就变小了,从而得出定滑轮能省力的错误结论.图 1稍微改进后,可以避免这个错误.从一弹簧秤上卸下弹簧… 相似文献
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在实验数据的处理中。估算问接测得量的误差时。经常引用加减运算、乘除运算的代数误差公式。但是。代数误差公式并不是普遍适用的。本证明。代数误差公式适用的充分条件是取误差的各量相互独立。 相似文献
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天文导航的航向误差与水平基准、载体位置的精度密切相关,以天文导航三角形的物理意义分析了天文导航测定航向的原理,推导了天文导航测定航向的精度与水平基准误差、载体地理位置误差等环节之间的公式,为天文导航仪器选择测量天体和提高精度提供了理论依据. 相似文献
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光学神经网络中硬件误差对性能影响的分析 总被引:2,自引:2,他引:0
利用统计方法,分析了光学硬件误差对用Hopfield神经作联想记忆时出错率的影响,导了系统的误差与错率关第的近似公式,并给出了模拟结果。得到了一定限度的误差对出错率的影响并不显著的的结论,特别坚探讨测器阵列动态范围的要求,可以远远小于其探测到的最大值。这对光学神经网络系统的设计及硬件的选取,具有指导意义。 相似文献
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详细推导并统一了形状误差和误差运动高精度检测 分离技术中各类传感器的读数方程 ,包括传统的差动变压器式位移传感器、电涡流式位移传感器、电容式微位移传感器和近年来出现的激光微位移传感器、激光角位移传感器以及后两者组合成的组合式广义位移传感器。以统一的列表方式阐明了各传感器的读数贡献。其优点是 :根据选用的误差分离方法和与之适配的传感器 ,便可按列表方式快速、方便地排出用于直线、圆、圆柱度和平面度等误差分离的原始读数方程 ,并对误差分离的可行性作出了初步分析 相似文献
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分析了Hartmann-Shack传感器组装误差的种类,导出了旋转误差和倾斜误差的校正矩阵,在进行波前重构时乘以校正矩阵可以校正对应的组装误差。分析了两种由于组装误差导致的波前重构的相对误差的公式,并以含52个子孔径的圆形Hartmann-Shack传感器为例进行了数值模拟。研究结果表明:若不对两种组装误差进行校正,将会限制Hartmann-Shack传感器测量精度的进一步提高。为Hartmann-Shack传感器的装配提供了理论依据。 相似文献
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Pseudo-inverse calculations have been made within the operational and research meteorological communities to identify components of the error in the initial state that are responsible for a significant portion of the forecast error. These calculations are based on the assumptions of a perfect model and linear perturbation growth, conditions not realizable in operational forecasting. In this study, the impact of nonlinearities and model error on pseudo-inverse calculations is investigated within an idealized framework using a simple atmospheric model. Forecasts are run within the perfect and imperfect model frameworks, with initial errors of varying sizes. Model error is introduced by changing the model dissipation terms. It is found that for pseudo-inverses composed of a small subset of the leading singular vectors (SVs), the nonlinear forecast correction is often better than the expected theoretical correction, indicating the suppression of error growth both inside and outside the linear pseudo-inverse subspace. As the size of the pseudo-inverse is increased, the nonlinear forecast correction starts to degrade. This forecast degradation coincides with a degradation in the analysis correction. It is possible to improve the forecast by degrading the analysis in the presence of model error, especially when the initial error is very small. However, for initial errors of reasonable magnitude, this is unlikely to happen in instances when the nonlinear forecast correction is better than the theoretical correction. Just as improving the initial state may suppress errors outside of the linear SV subspace, degrading it may likewise increase errors outside the SV subspace. This suggests that the size of the nonlinear correction relative to the expected theoretical correction may be useful in determining when pseudo-inverse perturbations are likely to have improved the analyses. 相似文献
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Osamu Hirota 《Entropy (Basel, Switzerland)》2021,23(12)
In recent years, remarkable progress has been achieved in the development of quantum computers. For further development, it is important to clarify properties of errors by quantum noise and environment noise. However, when the system scale of quantum processors is expanded, it has been pointed out that a new type of quantum error, such as nonlinear error, appears. It is not clear how to handle such new effects in information theory. First of all, one should make the characteristics of the error probability of qubits clear as communication channel error models in information theory. The purpose of this paper is to survey the progress for modeling the quantum noise effects that information theorists are likely to face in the future, to cope with such nontrivial errors mentioned above. This paper explains a channel error model to represent strange properties of error probability due to new quantum noise. By this model, specific examples on the features of error probability caused by, for example, quantum recurrence effects, collective relaxation, and external force, are given. As a result, it is possible to understand the meaning of strange features of error probability that do not exist in classical information theory without going through complex physical phenomena. 相似文献