An Alias By Any Other Name

Generally speaking, an alias can be a problematic thing. In the world of Data Acquisition, Aliasing is equally problematic. As with an alias, aliasing is a bit of a fake, a phony, a confusing situation where the data that you capture is not indicative of the true signal that is being measured.

Data acquisition relies on sampling, or taking a single measurement of a signal, at regular intervals. If the signal is changing more slowly than the sampling rate, an accurate representation of the signal can be represented by the individual measured samples. To be precise, the sampling rate should be at least twice the frequency of the signal that is being measured.

Aliasing occurs when the sampling rate is less than two times the frequency of the signal being measured. The actual signal frequency is mistakenly measured as a lower frequency when the sampling rate is too low. There is no way to identify that the signal being measured is actually an alias frequency.

To prevent aliasing, a traditional DAQ system will employ anti-aliasing filters which will limit the frequency of the signal being measured to less than one-half of the acquisition rate. This method can be effective, but does suffer from some drawbacks, such as:

• Additional circuitry for the filtering function
• Fixed filter frequency
• Multiple filters required for different acquisition rates
• In multi-channel, scanned systems, each channel requires individual filters

One of the key principals of OpenDAQ is to employ hardware that is as simple as possible. To that end, OpenDAQ utilizes one analog to digital converter per channel. And, to address the aliasing problem, the analog to digital converters utilize over-sampling to perform digital filtering. This ensures that aliasing can’t occur. More importantly, the additional circuitry required to performing anti-aliasing is not required.

What is not apparent in this discussion thus far, is that acquiring samples at varying sample rates requires anti-aliasing filters with different filter frequencies. If one were to need to acquire data at different rates, some sort of programmable filter would be required for each channel in a data acquisition system.

The OpenDAQ approach ensures that there is no need for complex filtering systems. This keeps the circuitry simple and clean. The over-sampling nature of the analog to digital converters means that the filter automatically adjusts to the sampling rate. Any sampling rate is supported and is guaranteed to filter out signals that could alias.

In addition to the benefits of simple circuitry and automatic filtering based on sample rate, this approach also ensures that each channel in the DAQ system is sampled at the same time. In a scanned DAQ system, where there is only a single analog to digital converter, sample and hold amplifiers must be used to capture the signal on all of the channels, then hold it temporarily while each channel is scanned separately by the single analog to digital filter. Using an analog to digital converter for each channel eliminates the need to use the sample and hold circuitry to allow for simultaneous capture and acquisition of all channels in the DAQ system.

The OpenDAQ approach to analog to digital capture and conversion keeps the circuitry simple, and also ensures that all channels in the DAQ system are sampled simultaneously. The added costs involved in using a single analog to digital converter per channel are mostly offset by eliminating programmable anti-aliasing filters on each channel. And when considering the costs to implement simultaneous sample and hold circuitry, individual analog to digital converters per channel are actually a cost-effective solution to many problems that need to be considered in data acquisition systems.