Impact location detection from accelerometer data
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I have accelerometer data coming from a accelerometer sensor which is mounted on top of handle of a cricket bat, I have played some shots some are missed and some hit, now I want to detect which shots are missed shots and which shots are hit shots. So how I can detect impact location or collide between cricket bat and ball. I guess there should be some algorithm or procedures by which we can get clue of impact location. Do matlab provide any script for it or how I can get help regarding this.
5 Comments
Mathieu NOE
on 4 Mar 2024
hello again
can you comment your graph and describes what you habe done to generate that data ? we needto make the correlation between the graph and the events
Answers (1)
Mathieu NOE
on 8 Mar 2024
Edited: Mathieu NOE
on 8 Mar 2024
hello
so this would be my suggestion
I hope my conclusion is not completely wrong !
At the end it seems I can clearly see 3 sharp and high amplitude peaks (above 5 g's ) corresponding to good hits; the other minor peaks are either missed hits or you shaking the baseball
code :
filename = "data1.csv";
data = importfile(filename);
% data = readtable('data1.csv') ; %
% data format :
% x,"y","z","timestamp"
% 0.10,"-1.69","9.85","14:58:30:267"
x = data.x;
y = data.y;
z = data.z;
timestamp = data.timestamp;
tmp = split(timestamp,':');
h = str2double(tmp(:,1)); % h column
m = str2double(tmp(:,2)); % m column
s = str2double(tmp(:,3)); % s column
ms = str2double(tmp(:,4)); % ms column
ts = h*3600 + m*60 + s + ms/1e3; % time in seconds
ts = ts - ts(1);
% plot(diff(ts)) ; % Nb the non constant sampling interval
% resample the data on a constant time interval time vector
tt = linspace(ts(1),ts(end),numel(ts));
x = interp1(ts,x,tt);
y = interp1(ts,y,tt);
z = interp1(ts,z,tt);
dt = mean(diff(tt));
Fs = 1/dt;
figure(1)
plot(tt,x,tt,y,tt,z);
legend('x','y','z')
% some high pass filtering to remove DC / low frequency signals
flow = 1;
[b,a] = butter(2,flow*2/Fs,'high');
xf = filtfilt(b,a,x);
yf = filtfilt(b,a,y);
zf = filtfilt(b,a,z);
figure(2)
plot(tt,yf,tt,zf);
legend('y','z')
figure(3)
% combine x,y,z signals into one rms signal
% see x direction contribution is neglectable , we can focus on y and z
% components only
rms_xyz = sqrt(xf.^2 + yf.^2 + zf.^2);
rms_yz = sqrt(yf.^2 + zf.^2);
plot(tt,rms_yz,tt,rms_xyz);
title('RMS (X) Y and Z acceleration');
xlabel('time (s)');
ylabel('amplitude (g)');
legend('rms(yz)','rms(xyz)')
3 Comments
Mathieu NOE
on 5 Apr 2024 at 11:37
hello again
do you have access to matlab ? if yes , and if you are new to it , I would suggest to look at some tutorials :
all the best
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