commit 1895895637899bca6beecc257289ce4460b28c84
parent 8de7706efd49562eaa0187806597c7feb8908947
Author: Ivan Gankevich <i.gankevich@spbu.ru>
Date: Sun, 18 Apr 2021 10:49:15 +0300
Anemometer verification.
Diffstat:
4 files changed, 81 insertions(+), 11 deletions(-)
diff --git a/Makefile b/Makefile
@@ -22,6 +22,7 @@ build/main.pdf: build/gnuplot/velocity-xy-dist-max.eps
build/main.pdf: build/gnuplot/velocity-xy-dist-min.eps
build/main.pdf: build/gnuplot/direction-dist.eps
build/main.pdf: build/gnuplot/acf.eps
+build/main.pdf: build/gnuplot/hold-peak.eps
#build/main.pdf: build/gnuplot/anemometer.eps
#build/main.pdf: build/gnuplot/anemometer.svg
build/main.pdf:
diff --git a/R/hold-peak.R b/R/hold-peak.R
@@ -62,31 +62,36 @@ for (i in 1:nrow(hp_intervals)) {
lc_velocity <- all_lc_velocity[all_lc_velocity$timestamp>=t0 & all_lc_velocity$timestamp<=t1,]
hp_velocity <- select_hold_peak_samples(t0, t1-t0)
velocity <- merge(lc_velocity, hp_velocity, by=c("timestamp"))
+ velocity$timestamp = velocity$timestamp - min(velocity$timestamp)
# scale samples
t <- c(1:length(velocity$speed.x))
- reg <- lm(velocity$speed.x-velocity$speed.y~t)
- #print(coef(reg))
+ model <- nls(speed.y ~ a*speed.x, data=velocity)
+ velocity$speed.x <- velocity$speed.x * summary(model)$coefficients[[1]]
+ lo <- loess.smooth(velocity$timestamp, velocity$speed.x, span=0.5)
new_row <- nrow(result)+1
result[new_row,"rmse"] <- normalized_rmse(velocity$speed.x, velocity$speed.y)
result[new_row,"urmse"] <- rmse(velocity$speed.x, velocity$speed.y)
result[new_row,"start"] <- t0
result[new_row,"end"] <- t1
- velocity$speed.x <- velocity$speed.x - reg$fitted.values
- #print(lc_velocity)
- t_origin <- max(min(velocity$timestamp),min(velocity$timestamp))
- plot(velocity$timestamp-t_origin, velocity$speed.x)
- lines(velocity$timestamp-t_origin, velocity$speed.y)
+ scatter.smooth(velocity$timestamp, velocity$speed.x)
+ #plot(velocity$timestamp, velocity$speed.x)
+ lines(velocity$timestamp, velocity$speed.y, col='red')
+ #lines(lo)
make_directory(file.path("build","hold-peak"))
- write.table(data.frame(timstamp=velocity$timestamp,
+ filename <- file.path("build","hold-peak",sprintf("%d",t0))
+ write.table(data.frame(timestamp=velocity$timestamp,
speed_lc=velocity$speed.x,
speed_hp=velocity$speed.y),
- file.path("build","hold-peak",sprintf("%d",t0)),
- row.names=FALSE, quote=FALSE)
+ filename, row.names=FALSE, quote=FALSE)
+ write("\n",file=filename,append=TRUE)
+ write.table(data.frame(timestamp=lo$x,speed=lo$y), filename,
+ row.names=FALSE, quote=FALSE, append=TRUE)
}
print(result[result$rmse==max(result$rmse),])
print(result[result$rmse==min(result$rmse),])
sorted_result <- result[order(result$rmse),]
+print(sorted_result)
gnuplot <- function (file, str, ...) {
cat(sprintf(str, ...), file=file, append=TRUE)
@@ -106,4 +111,4 @@ gnuplot_all <- function (filename, prefix, rmse_column, row_min, row_max, row_lo
gnuplot_all("build/gnuplot/hold_peak_rmse.gnuplot", "speed", "rmse",
result[result$rmse == min(result$rmse),],
result[result$rmse == max(result$rmse),],
- sorted_result[2,])
+ result[2,])
diff --git a/gnuplot/hold-peak.gnuplot b/gnuplot/hold-peak.gnuplot
@@ -0,0 +1,45 @@
+set terminal svg size 450,450/2 font 'Free Serif, 10' enhanced round dynamic
+set xtics nomirror out offset 0,0.5
+set ytics nomirror out offset 0.5,0
+set border 1+2 back
+unset key
+
+set output 'build/gnuplot/hold-peak.svg'
+
+set xlabel offset 0,1.0
+set xlabel 'Time, s'
+set ylabel 'Wind speed, m/s' offset 1.5,0
+set title offset 0,-1
+set lmargin 5
+set rmargin 2
+set tmargin 4.0
+set multiplot layout 1,2
+
+round(x) = floor(x+0.5)
+filename(timestamp) = sprintf('build/hold-peak/%d', timestamp)
+
+load "build/gnuplot/hold_peak_rmse.gnuplot"
+
+set yrange [0:5]
+set ytics 0,1,5
+set xtics 0,30
+
+set title sprintf('RMSE = %.1f%%', (speed_rmse_max*100))
+plot \
+filename(speed_rmse_max_timestamp) index 0 using 1:2 with points pt 6 lc '#404040',\
+'' index 0 using 1:3 with lines lw 2 lc '#c04040',\
+'' index 1 using 1:2 with lines lw 2 lc '#c0c040'
+
+set key Left reverse at screen 0.80, screen 1.00
+
+set title sprintf('RMSE = %.1f%%', (speed_rmse_min*100))
+plot \
+filename(speed_rmse_min_timestamp) index 0 using 1:2 with points pt 6 lc '#404040' title 'Load cell data',\
+'' index 0 using 1:3 with lines lw 2 lc '#c04040' title 'HP-866A data',\
+'' index 1 using 1:2 with lines lw 2 lc '#c0c040' title 'Smoothed load cell data'
+
+# set title sprintf('RMSE_x = %.1f%%', (speed_rmse_longest*100))
+# plot \
+# filename(speed_rmse_longest_timestamp) index 0 using 1:2 with points pt 6 lc '#404040',\
+# '' index 0 using 1:3 with lines lw 2 lc '#c04040',\
+# '' index 1 using 1:2 with lines lw 2 lc '#40c040'
diff --git a/main.tex b/main.tex
@@ -502,6 +502,25 @@ are presented in figure~\ref{fig-direction-distributions}.
\label{fig-direction-distributions}}
\end{figure}
+In order to verify that our anemometer produces correct time series we
+performed synchronous measurements with commercial anemometer HP-866A. Two
+anemometers were placed in the open field near the shore. The commercial
+anemometer directed towards the mean wind direction as it measures the speed
+only. The data from the two anemometers was recorded synchronously. From the
+data we selected intervals with wind gusts and compared the measurements of the
+two anemometers. To compare them we scaled load cell anemometer measurements to
+minimise RMSE of the difference between the two time series to compensate for
+the errors in calibration coefficients. The results showed that there is good
+correspondence between the measurements of the two anemometers
+(figure~\ref{fig-hold-peak}).
+
+\begin{figure}
+ \centering
+ \includegraphics{build/gnuplot/hold-peak.eps}
+ \caption{Comparison of measurements obtained from three-axis and HP-866A
+ anemometers.\label{fig-hold-peak}}
+\end{figure}
+
%TODO asymmetry
Finally, we computed autocovariance for each axis as
