Undergrad Approximating and regression method

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The discussion focuses on determining the natural frequency of a crane lifting loads by identifying two constants related to the crane's stiffness and weight. The user conducted tests with different loads and positions, plotting the results to analyze the relationship. Despite calculating constants A and B manually, the values were inconsistent, prompting a search for more reliable mathematical approximation methods. Suggestions included using MATHCAD for nonlinear regression and Excel for linear regression calculations. The conversation emphasizes the need for accurate methods to derive these constants for better modeling of the crane's behavior.
Iqbal94
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Hi guys,

I did a few sets of test in determining the natural frequency of a crane lifting loads. From that, I tried to find two constant from its initial function.

upload_2016-4-5_20-30-10.png


a is the stiffness of the pole that was holding the crane
b is the weight of the crane
x is the weight of the load

The tests were completed by using three different loads on three different position. I plotted the graph as below.

upload_2016-4-5_20-36-7.png


From the obtained graph and the initial function, I tried to determine the value of constant A and B. By calculating manually, the value of A and B are not constant but it supposed to be constant. I tried using MATHCAD to find the value of the constants by using nonlinear regression method but I am not convince that is a right solution. Any of you know any mathematical approximation method that I can use?
 
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Iqbal94 said:
Any of you know any mathematical approximation method that I can use?
Excel does linear regression directly. If you want it mathematically, you must calculate:
  1. s_{1}=\sum x_{j}
  2. s_{2}=\sum x_{j}^{2}
  3. t_{1}=\sum y_{j}
  4. t_{2}=\sum y_{j}^{2}
  5. v_{1}=\sum x_{j}\cdot y_{j}
Assuming that you have n points, you then calculate a=\frac{t_{1}\cdot s_{2}-s_{1}\cdot v_{1}}{n\cdot s_{2}-s_{1}^{2}} and b=\frac{n\cdot v_{1}-s_{1}\cdot t_{1}}{n\cdot s_{2}-s_{1}^{2}}. The regression line is then given by y=a\cdot x + b.
 
Here is a little puzzle from the book 100 Geometric Games by Pierre Berloquin. The side of a small square is one meter long and the side of a larger square one and a half meters long. One vertex of the large square is at the center of the small square. The side of the large square cuts two sides of the small square into one- third parts and two-thirds parts. What is the area where the squares overlap?

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