General Information
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Analog outputs are then connected to the T7:
U - channel 1 - AIN0
V - channel 2 - AIN1
W - channel 3 - AIN2
sonic speed - channel 4 - AIN3
Sample Dataset taken over 10 min:
And zoomed in to ~half a second of data taking:
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Code for taking data
Note: this will take data for 10 minutes. It also takes data at a rate of 1 kHz, which is unecessary, as the anemometer takes data at 32 Hz.
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# -*- coding: utf-8 -*- """ Created on TueFri NovOct 3015 0213:1155:0610 2021 @author: brodi, elanaku """ # saves anemometer data from datetime import datetime, timedelta import pandas as pd from labjack import ljm from sqlalchemy import create_engine import def load_pd(db_fi: str, table: str) -> pd.DataFrame: """ loads pandas df from db given table name """ engine = create_engine(db_fi, echo = False) with engine.connect() as sqlite_connection: df = pd.read_sql(table, sqlite_connectiontime DEVICE = None PIN_VX = "AIN0" PIN_VY = "AIN1" PIN_VZ = "AIN2" PIN_VSONIC = "AIN3" sample_time = .001 db_fi = 'sqlite:///anemometer.db' start = datetime.now() end = start + timedelta(seconds=60*10) def readout(PIN_VX, PIN_VY, PIN_VZ, PIN_VSONIC): vx = ljm.eReadName(handle, PIN_VX) vy = ljm.eReadName(handle, PIN_VY) vz = ljm.eReadName(handle, PIN_VZ) vsonic = ljm.eReadName(handle, PIN_VSONIC) return df |
If database file is named anemometer, for instance, you can load it into a dataframe and then convert the relevant voltage measurements into wind speed and temperature with:
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# Load datafile into pandas data frame
db_fi = r"sqlite:///anemometer.db"
df = load_pd(df_fi, "anem")
# Add columns in correct units
# because the units are +/- 5 m/s, 0 to 5 V
df['vx_ms'] = (df.vx - 2.5) * 2
df['vy_ms'] = (df.vy - 2.5) * 2
df['vz_ms'] = (df.vz - 2.5) * 2
# because sonic temperature is measured on a scale of 0 to 5 V
# from -40 to 70 C
df['tsonic'] = -40 + df.vsonic/5 * 110
#Plot data
plt.plot(df.t, df.vx_ms, label = 'Vx')
plt.plot(df.t, df.vy_ms, label = 'Vy')
plt.plot(df.t, df.vz_ms, label = 'Vz')
# plt.plot(df.t, df.tsonic/8 - np.mean(df.tsonic/8), label = 'Temp')
plt.legend()
plt.xlabel('Time')
plt.ylabel('Wind Speed (m/s)')
plt.show()
plt.plot(df.t, df.tsonic)
plt.xlabel('Time')
plt.ylabel(r'Sonic Temperature ($^o$C)')
plt.show() |
...
(datetime.now(), vx, vy, vz, vsonic)
try:
handle = ljm.openS("Any","Any","Any")
engine = create_engine(db_fi, echo = False)
sqlite_connection = engine.connect()
options = {"index": False, "if_exists": "append"}
while datetime.now() < end:
it = 200
i = 0
res = []
while i < it:
res.append(readout(PIN_VX, PIN_VY, PIN_VZ, PIN_VSONIC))
time.sleep(sample_time)
i += 1
anem = pd.DataFrame(res, columns = ["t", "vx", "vy", "vz", "vsonic"])
anem.to_sql("anemometer", sqlite_connection, **options)
finally:
ljm.close(handle)
sqlite_connection.close() |
Relevant code for analyzing binary datafile
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# -*- coding: utf-8 -*-
"""
Created on Tue Nov 30 02:11:06 2021
@author: brodi
"""
import pandas as pd
from sqlalchemy import create_engine
def load_pd(db_fi: str, table: str) -> pd.DataFrame:
"""
loads pandas df from db given table name
"""
engine = create_engine(db_fi, echo = False)
with engine.connect() as sqlite_connection:
df = pd.read_sql(table, sqlite_connection)
return df |
If database file is named anemometer, for instance, you can load it into a dataframe and then convert the relevant voltage measurements into wind speed and temperature with:
| Code Block | ||
|---|---|---|
| ||
# Load datafile into pandas data frame
db_fi = r"sqlite:///anemometer.db"
df = load_pd(df_fi, "anem")
# Add columns in correct units
# because the units are +/- 5 m/s, 0 to 5 V
df['vx_ms'] = (df.vx - 2.5) * 2
df['vy_ms'] = (df.vy - 2.5) * 2
df['vz_ms'] = (df.vz - 2.5) * 2
# because sonic temperature is measured on a scale of 0 to 5 V
# from -40 to 70 C
df['tsonic'] = -40 + df.vsonic/5 * 110
#Plot data
plt.plot(df.t, df.vx_ms, label = 'Vx')
plt.plot(df.t, df.vy_ms, label = 'Vy')
plt.plot(df.t, df.vz_ms, label = 'Vz')
# plt.plot(df.t, df.tsonic/8 - np.mean(df.tsonic/8), label = 'Temp')
plt.legend()
plt.xlabel('Time')
plt.ylabel('Wind Speed (m/s)')
plt.show()
plt.plot(df.t, df.tsonic)
plt.xlabel('Time')
plt.ylabel(r'Sonic Temperature ($^o$C)')
plt.show() |
Which gives the first plots in the previous section.
Troubleshooting: Corrupted Data File
If for some reason the anemometer database file becomes corrupted so you can't open it or analyze the data, you can dump the data from that file into a new, uncorrupted file with the command:
$ sqlite3 old_file.db .recover | sqlite3 new_file.db
Relevant pin connections (all of which are copied from the manual)
Output pins from the anemometer (p. 15 of manual):
To change the analog output settings, connect a RS 432 serial port to a windows computer and to the anemometer outputs.
RS 432 serial port pin connections (p.32 of manual):
For the serial connector we were using, pin 2 was white, pin 3 was yellow, pin 5 was orange, but apparently this isn't necessarily generically true.
The windows computer should have WIND software downloaded on it. Follow p. 46 of the manual.
Mounting plate
through bolts are McMaster Carr
Super-cheap hot-wire anemometer for airflow in the dome:
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-10.0000 0.2040
-9.0000 0.2236
-8.0000 0.2432
-7.0000 0.2628
-6.0000 0.2824
-5.0000 0.3020
-4.0000 0.3216
-3.0000 0.3412
-2.0000 0.3608
-1.0000 0.3804
0 0.4000
1.0000 0.4196
2.0000 0.4392
3.0000 0.4588
4.0000 0.4784
5.0000 0.4980
6.0000 0.5176
7.0000 0.5372
8.0000 0.5568
9.0000 0.5764
10.0000 0.5960
11.0000 0.6156
12.0000 0.6352
13.0000 0.6548
14.0000 0.6744
15.0000 0.6940
16.0000 0.7136
17
17.0000 0.7332
18.0000 0.7528
19.0000 0.7724
20.0000 0.7920
21.0000 0.73328116
18 22.0000 0.75288312
19 23.0000 0.77248508
20 24.0000 0.79208704
21 25.0000 0.8116
22.0000 0.8312
23.0000 0.8508
24.0000 0.8704
25.0000 0.8900
Cabling
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Ribbon cable length is 1 foot. So we'll need to cut down the carbon fiber tubes.
DB-9 dimensions:
So we need to make a mechanical part to mount this on tail end of carbon stalk.
So sensor end is DB9 pins. If we use straight-through M to F DB9 cable (no swap of pins 2 and 3) then readout end is also DB9 pins. So we need DB9 male to breakout on far end.
Clamps for mounting 20mm OD tubing
Assembly:
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8900
Cabling
We can use DB9 hardware off the shelf. To connect unit to DB9 connector:
Ribbon cable length is 1 foot. So we'll need to cut down the carbon fiber tubes.
DB-9 dimensions:
So we need to make a mechanical part to mount this on tail end of carbon stalk.
So sensor end is DB9 pins. If we use straight-through M to F DB9 cable (no swap of pins 2 and 3) then readout end is also DB9 pins. So we need DB9 female on far end.
Easiest to just solder 4 wires into a panel mount DB9 connector.
Clamps for mounting 20mm OD tubing
Assembly:
- cut carbon tube to 10 inch length
- attach DB-9 connector to flange with two 4-40 screws. Use standoffs if it doesn't clear ID.
- feed ribbon cable through tube, and plug other end into sensor
- test electrical connections and functionality
- glue in both the connector flange and the sensor using 5 minute epoxy
- add mount clamp at midpoint
Mothership readout box
We need two channels of A/D conversion for each unit. Conservatively, each sensor consumes 60mA at 12V. Assume we deploying ten of them. That means we need a 1A, 12V power supply. There is on-board voltage regulation on the sensor so this doesn't need to be super-well regulated.
Box needs a power supply for the sensors as well as A/D converter function and a data collection computer. Labjack U3-LV has 16 single-ended inputs, enough for 8 devices with both wind and temperature. We should run it off a dedicated computer, NUC or R-Pi.
Scintillation coherence scale for acoustics
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