Thanks for this information. We however are using the UPD to get the counts and calculate in another computer the velocity and acceleration in real time continously.
Therefore we prefer to start from the counts and obtain the acceleration and the velocity using the relation between counts and acceleration or velocity
In the Technical specification we have found the following
Sensitivity: V6: 3.9965E+08/meter/second
Is it correct that in reality should be
V6=3.9965E8 / (meter/second) ?
So that if we have 34560 counts, it corresponds to:
v=34560/3.9965E08 m/s=8.64e-5 m/s
Similarly, as you pointed out in another post, for the acceleration (ENE, etc), it would be if the counts are 67234, the acceleration would be:
acc=67234/2.845e5= 0.167 m/s2 -> 0.017 g
I would really appreciate your comment
instead of providing just the formula for this type of conversion, i would like to direct you to the following online resource which provides a complete explanation of what you are looking for:
Thanks Richard, very useful. My assumptions were correct
Hi iannesbit, i know this is far bit late of a reply, but can I ask for the code if I want to get the the max value in counts?
Hello TUPRS4D, and welcome back to the community!
Here’s a working example of your request:
from obspy.clients.fdsn import Client
from obspy.core import UTCDateTime, Stream
rs = Client('https://data.raspberryshake.org')
# set the station name and download the response information
stn = 'R24FA' # your station name
inv = rs.get_stations(network='AM', station=stn, level='RESP')
# set data start/end times
start = UTCDateTime(2020, 3, 7, 2, 40, 45) # (YYYY, m, d, H, M, S)
end = UTCDateTime(2020, 3, 7, 2, 42, 0) # (YYYY, m, d, H, M, S)
# set the FDSN server location and channel names
channels = ['EHZ'] # ENx = accelerometer channels; EHx or SHZ = geophone channels
# get waveforms and put them all into one Stream
trace = rs.get_waveforms('AM', stn, '00', ch, start, end)
# here you will plot raw counts for all four channels
# max absolute value
abscountmax = abs(trace.data).max()
# max positive value
countmax = trace.data.max()
# max negative value
countmin = trace.data.min()
I was not sure about what max value you were interested it, so I printed all three:
- absolute max value
- positive max value
- negative max value
Hope this will be of help.