Real-world environmental occurrences such as temperature, pressure, flow
or light usually require a specialized sensor to adequately capture an
ecological status or change. Although sensors can convert these physical
occurrences adequately to a small signal resistance, voltage, or
current, they lack the ability to convert their output electrical
signals to a final digital representation, let alone perform
amplification, filtering, offset adjustments, or other electrical
Designers use a variety of devices to bring analog signal to an
accessible level with processing functions. However, at the end of the
signal path an ADC usually helps tie the sensor information into a final
digital result. This article is the first of a multi-part series that
discusses SAR and delta-sigma ADC topologies, appropriate systems for
these devices, and a comprehensive error analysis in various application
In this Part 1, we will examine the frequency ranges
and their required resolutions for various analog sensors. We will look
at the more popular sensor frequency ranges and map the capabilities of
the SAR and delta-sigma ADC to sensors that handle temperature, level,
pressure, flow, displacement, and optical events.
Where sensors touch the real-world
The most common type of physical data collected from the environment is
temperature. The temperature ranges of these systems span from our
environment here on Earth to out-of-this-world, ultra-hot or ultra-cold
environments. Numerous sensors can respond to absolute temperature or
changes in temperature. A short list of these types of sensors includes
Integrated silicon, thermocouples, resistive-temperature-devices (RTD),
thermistors, infrared, and thermopiles. As shown in Figure 1,
the actual temperature in various test environments changes at a
relatively slow pace (below 10 Hz). However, designers are interested in
a range of accuracy and precision from a few bits up to 20 bits.
Twenty-bits of noise free resolution means that the converter in the
system generates 220 (1,048,576) clean, unvarying bits of data.
Figure 1. Real-world entities in relation to noise-free resolution versus bandwidth.
Pressure sensors monitor air or gas pressure. A sub-class of the
pressure sensor is the load cell. Load cells can sense the weight of
various objects, from multi-tons to the weight of an eye lash (or
smaller). For these sensors, models basically are diamond-shaped,
four-element resistive network. The frequency range of these sensors is
higher than the temperature sensors; up to ~100 Hz.
Temperature, pressure, or audio sensors (microphones) effectively sense the flow of fluids, gasses, or liquids. Figure 1
shows that physical changes in the flow of gases or liquids are relatively slow and noise-free-bit requirements are relaxed.
The output signals produced from the above sensors can come in the form
or resistance, voltage, and current. In most cases these sensors create
small level signals that may require further signal conditioning.
As you move to higher bandwidths (Figure 1
displacement, proximity, and photo-sensing circuits have lower precision
requirements. Photosensing applications can range from low-frequency,
high noise-free-bit requirements (medical scans) to higher frequency
digital sensing, such as a bar code scanner. The photodetector signal
path requires higher frequency converters, such as SAR or high-speed
If a system designer requires a finished digital representation of these
physical occurrences, these entities and consequently these sensors
have successive-approximation-register (SAR) ADCs or delta-sigma (
??) ADCs at the end of their signal paths. You can see this relationship in the next section of this article.
Tying sensors to an ADC
The most common ADCs for the frequency bandwidths that cater to the sensors described earlier are delta-sigma and SAR. Figure 2
shows the relationship between the delta-sigma and SAR converter
architectures regarding converter resolution and conversion rate.
Delta-sigma converters operate in the lower frequency ranges; up to
approximately 10 kHz. Most engineers know these converters for their
extremely high resolution.
Figure 2. Converter resolution versus conversion rate for the delta-sigma and SAR ADCs
Delta-sigma ADCs determines its digital output word by oversampling the
analog input signal. The delta-sigma input modulator stage oversamples
the analog input signal and converts it to a 1-bit digital data stream.
Next a digital filter samples by collecting the data from this 1-bit
data stream and converts it to a multibit output word.
Delta-sigma converters are capable of producing output bit ranges from
16 to 24, which in and of itself is impressive. The advantages of the
delta-sigma converter include low power, extremely high resolution, and
high stability, at a low cost. The overall performance of the
delta-sigma ADC allows the designer to reduce the number of analog
signal-conditioning chips prior to ADC input. The disadvantages for this
type of converter usually include low speed. In some converters, there
is a greater than zero cycle-latency. We will learn more about this
converter and its inner workings in a future article.