Daqarta
Data AcQuisition And Real-Time Analysis
Scope - Spectrum - Spectrogram - Signal Generator
Software for Windows
Science with your Sound Card!
The following is from the Daqarta Help system:

Features:

Oscilloscope

Spectrum Analyzer

Signal Generator
(Absolutely FREE!)

Spectrogram

Pitch Tracker

Pitch-to-MIDI

DaqMusic
(Free Music... Forever!)

Remote Operation

DC Measurements

True RMS Voltmeter

Sound Level Meter

Frequency Counter
    Period
    Event
    Spectral Event

    Temperature
    Pressure
    MHz Frequencies

Data Logger

Waveform Averager

Histogram

Post-Stimulus Time
Histogram (PSTH)

Macro System

Multi-Trace Arrays

Trigger Controls

Auto-Calibration

Spectral Peak Track

Spectrum Limit Testing

Direct-to-Disk Recording

Accessibility

Applications:

Frequency response

Distortion measurement

Speech and music

Microphone calibration

Loudspeaker test

Musical instrument tuning

Animal sound

Evoked potentials

Rotating machinery

Automotive

Product test

Contact us about
your application!

Voltmeter RMS

Controls: Options >> Voltmeter >> RMS
Macro : VoltMode=RMS

The Voltmeter RMS option computes the true Root Mean Square value of the waveform, over an integer number of waveform cycles. RMS is computed by taking the square of each data point, summing all the squares together, dividing by the number of data points, and then taking the square root of the result.

The RMS computation assumes that enough data points are included to get a good representation of the average value of the signal. For low-frequency repetitive waveforms, highest accuracy is obtained when the computation includes an integer number of cycles. In order to obtain this, the trace must be Triggered and the 1024 trace samples must include at least one full cycle of the waveform. The lowest frequency you can measure this way is thus the sample rate divided by 1024:

 48000    46.875  Hz
 44100    43.066
 22050    21.533
 11025    10.767

For still-lower frequencies, all 1024 samples are used and the reported value may fluctuate over time, as the readout shows the average value for any given 1024 samples.

All 1024 samples are also used if Trigger is off. Since there will not in general be an integer number of cycles, the accuracy of the reading may be reduced for low frequencies. Note that for a symmetrical wave, an integer number of half-cycles is as good as an integer number of cycles for ultimate accuracy. The worst case, assuming more than one cycle is present, is when there are 1.25 cycles included; the instantaneous error may be several percent. However, the displayed value is further smoothed using the same time constant (TC) as for trace cursors, so the reading will usually quickly settle down to an error of less than one percent using the default TC of 5. You can increase the effective averaging time by increasing the TC.

As the signal frequency increases, the error due to non-integer cycles diminishes because any fractional cycle is a smaller part of the total.

Random noise measurements should always be made with Trigger off.

The RMS option can be used with file data, but since there is no Trigger available for single-trace files, only long ( DDisk) files can use Trigger to get the most accurate reading... even though only waveforms that fit into 1024 samples will be able to take advantage of this.

Note that the RMS Voltmeter option is essentially the same process as the Sigma cursor readout option applied to the waveform, but RMS Voltmeter uses Trigger information instead of manual cursor positions to automatically set the optimal summation region.

For signal or noise bursts, note that the true RMS value ( effective heating energy) must consider the overall cycle time of the burst, including the dead time between bursts. For burst cycles that are shorter than 1024 samples, the RMS reading will be correct because every calculation will include at least one full cycle. That will be true whether Trigger is active or not.

However, for longer bursts or longer cycle times, you will need to turn Trigger off and rely upon the averaging effect of the Voltmeter Time Constant to get the true RMS value. This depends upon bursts falling randomly within the 1024-sample data set of each update; some updates may see only the On portion of the burst, and some may see only the Off portion, but the average of many updates should yield the true RMS value.


See also Voltmeter, Voltmeter Channel

GO:

Questions? Comments? Contact us!

We respond to ALL inquiries, typically within 24 hrs.
INTERSTELLAR RESEARCH:
Over 25 Years of Innovative Instrumentation
© Copyright 2007 - 2011 by Interstellar Research
All rights reserved