Introduction to Mechanical Vibrations. Ronald J. Anderson. Читать онлайн. Newlib. NEWLIB.NET

Автор: Ronald J. Anderson
Издательство: John Wiley & Sons Limited
Серия:
Жанр произведения: Физика
Год издания: 0
isbn: 9781119053644
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images is a small angle. Since images is a constant, we differentiate to find that images and images. Substituting into Equation 1.58 gives

      We use the trigonometric identities

equation equation

      along with the linearizing approximations for the small angle images

equation equation

      to get the linearized forms

equation equation

      Then, the term images which appears in Equation 1.59 can be approximated by the product of these two expressions

      (1.60)equation

      We then say that the nonlinear images term can be neglected as being negligibly small compared to the linear term images since images is a small angle. This is at the heart of the linearization process. The linearized EOM becomes

      (1.61)equation

      Now we rearrange this to separate the constant terms from the terms with images and its derivatives. The result is

      (1.62)equation

      It remains to pick a suitable equilibrium state from the three we found in Subsection 1.2.2. Of these, the most interesting is the one where the bead is not below or above point images. That is, consider the case where

equation

      With a little effort and use of one trigonometric identity, you can show that the linear equation of motion about this state can be written as

      1.3.2 Nonlinear Structural Elements

      The equilibrium solution to the nonlinear equation of motion will place the system in equilibrium at images (the point labeled operating point on Figure 1.6). Once there, we consider motions images away from the operating point and use a Taylor's Series expansion for the nonlinear function images

      (1.64)equation

      For small values of images, we can neglect the higher order terms and write

      (1.65)equation

Graph depicting the linearization of functions about operating points to find the local slope of the function proving that small deviations away from the point can be approximated by points lying on a straight line.

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