Doing More with Analog Input (Data Acquisition Toolbox)

Data Acquisition Toolbox

Example: Performing a Linear Conversion

This example illustrates how to configure the engineering units properties for an analog input object connected to a National Instruments PCI-6024E board.

An accelerometer is connected to a device which is undergoing a vibration test. Your job is to measure the acceleration and the frequency components of the device while it is vibrating. The accelerometer has a range of ±50 g's, a voltage sensitivity of 99.7 mV/g, and a resolution of 0.00016 g.

The accelerometer signal is input to a Tektronix TDS 210 digital oscilloscope, and to channel 0 of the data acquisition board. By observing the signal on the scope, the maximum expected range of data from the sensor is ±200 mV, which corresponds to approximately ±2 g's. Given this constraint, you should configure the board's input range to the ±500 mV, which is the closest input range that encompasses the expected data range.

You can run this example by typing daqdoc5_8 at the MATLAB command line.

1. Create a device object - Create the analog input object AI for a National Instruments board. The installed adaptors and hardware IDs are found with daqhwinfo.

AI = analoginput('nidaq',1);

2. Add channels - Add one hardware channel to AI.

chan = addchannel(AI,0);

3. Configure property values - Configure the sampling rate to 200 kHz and define a two second acquisition.

duration = 2;
ActualRate = setverify(AI,'SampleRate',200000);
set(AI,'SamplesPerTrigger',duration*ActualRate)

Configure the engineering units properties. This example assumes you are using a National Instruments PCI-6024E board or an equivalent hardware device. SensorRange is set to the maximum accelerometer range in volts, and UnitsRange is set to the corresponding range in g's.

set(chan,'SensorRange',[-5 5])
set(chan,'InputRange',[-0.5 0.5])
set(chan,'UnitsRange',[-50 50])
set(chan,'Units','g''s (1g = 9.80 m/s/s)')

4. Acquire data - Start the acquisition and wait until all the data is acquired.

start(AI)
while strcmp(AI.Running,'On')
end

Extract and plot all the acquired data.

data = getdata(AI);
subplot(2,1,1),plot(data)

Calculate and display the frequency information.

Fs = ActualRate;
blocksize = duration*ActualRate;
[f,mag]= daqdocfft(data,Fs,blocksize);
subplot(2,1,2),plot(f,mag)

5. Clean up - When you no longer need AI, you should remove it from memory and from the MATLAB workspace.

delete(AI)
clear AI

Linearly Scaling the Data: Engineering Units Analog Output