# iccsa-21-wind

git clone https://git.igankevich.com/iccsa-21-wind.git
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commit b95abbeeda95adc3153c1ec7c2def7fc730939fe
parent dd50ae6b0655ca2543c683bc37f5a844215b74b6
Author: Ivan Gankevich <i.gankevich@spbu.ru>
Date:   Tue,  4 May 2021 13:31:09 +0300

balcony ftw

Diffstat:
main.tex | 72++++++++++++++++++++++++++++++++++++++----------------------------------

1 file changed, 38 insertions(+), 34 deletions(-)
diff --git a/main.tex b/main.tex
@@ -104,8 +104,8 @@ of which are determined from the spectrum, and phases are random variables:
\begin{align*}
& V(t) = \overline{V} + \sum\limits_{j=1}^{n}
\left( A_j \sin\omega_jt + B_j \cos\omega_jt\right), \\
-& A_j = \sqrt{\frac{1}{2} S_j \Delta\omega} \sin\phi_j, \\
-& B_j = \sqrt{\frac{1}{2} S_j \Delta\omega} \cos\phi_j.
+& A_j = \sqrt{\frac{1}{2} S_j \Delta\omega} \sin\phi_j, \quad
+ B_j = \sqrt{\frac{1}{2} S_j \Delta\omega} \cos\phi_j.
\end{align*}
Here $$S_j$$ is spectrum value at frequency $$\omega_j$$,
$$\phi_j$$ is random variable which is uniformly distributed in $$[0,2\pi]$$.
@@ -360,19 +360,34 @@ coefficient equals the raw sensor value that is equivalent to the wind speed of
m/s (table~\ref{tab-coefficients}).

\begin{table}
-    \centering
-    \caption{Calibration coefficients for each arm of three-axis anemometer:
-        $$C_1$$ is for negative values and $$C_2$$ is for positive values.
-    \label{tab-coefficients}}
-    \begin{tabular}{lll}
-        \toprule
-        Axis & $$C_1$$ & $$C_2$$ \\
-        \midrule
-        X & 11.19 & 12.31 \\
-        Y & 11.46 & 11.25 \\
-        Z & 13.55 & 13.90 \\
-        \bottomrule
-    \end{tabular}
+    \begin{minipage}[t]{0.35\textwidth}
+        \centering
+        \begin{tabular}{lll}
+            \toprule
+            Axis & $$C_1$$ & $$C_2$$ \\
+            \midrule
+            X & 11.19 & 12.31 \\
+            Y & 11.46 & 11.25 \\
+            Z & 13.55 & 13.90 \\
+            \bottomrule
+        \end{tabular}
+        \caption{Calibration coefficients for each arm of three-axis anemometer:
+            $$C_1$$ is for negative values and $$C_2$$ is for positive values.
+        \label{tab-coefficients}}
+    \end{minipage}
+    \begin{minipage}[t]{0.55\textwidth}
+        \centering
+        \begin{tabular}{ll}
+            \toprule
+            Time span & 36 days \\
+            Size & 122 Mb \\
+            No. of samples & 3\,157\,234 \\
+            No. of samples after filtering & 2\,775\,387 \\
+            Resolution & 1 sample per second \\
+            \bottomrule
+        \end{tabular}
+        \caption{Dataset properties.\label{tab-dataset}}
+    \end{minipage}
\end{table}

We noticed that ambient temperature affects values reported by our load cells:
@@ -429,20 +444,6 @@ for the purpose of the research.
\label{fig-intervals}}
\end{figure}

-\begin{table}
-    \centering
-    \begin{tabular}{ll}
-        \toprule
-        Time span & 36 days \\
-        Size & 122 Mb \\
-        No. of samples & 3\,157\,234 \\
-        No. of samples after filtering & 2\,775\,387 \\
-        Resolution & 1 sample per second \\
-        \bottomrule
-    \end{tabular}
-    \caption{Dataset properties.\label{tab-dataset}}
-\end{table}
-
\section{Results}

\subsection{Anemometer verification}
@@ -643,22 +644,25 @@ determinate its mean direction becomes, and the slower the flow is the more
indeterminate its mean direction is.

Three-axis anemometer disadvantages are the following.
-\begin{itemize}
-\item
The arm for the $$z$$ axis is horizontal, and snow and rain put additional load
on this cell distorting the measurements.
-\item
Also, thermal expansion and contraction of the material changes
the resistance of load cells and distorts the measurements.
-\item Pressure force on the arm is exerted by individual air particles and
+Pressure force on the arm is exerted by individual air particles and
is represented by choppy time series, as opposed to real physical signal
that is represented by smooth graph.
-\end{itemize}
The first two defficiences can be compensated in software by removing linear trend
from the corresponding interval. The last one make anemometer useful only for
offline studies, i.e.~it is useful to gather statistics, but is unable to measure
immediate wind speed and direction.

+We used a balcony for long-term measurements and open field for verification
+and calibration. We found no clues that the balcony affected the distributions
+and ACFs of wind speed. The only visible effect is that the wind direction is
+always parallel to the wall which agrees with physical laws. Since we measure
+pressure force directly, the mean wind direction does not affect the form
+of the distributions, but only their parameters.
+
\section{Conclusion}

In this paper we proposed three-axis anemometer that measures wind speed for