What Is an ADC?

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The physical world is analogue, continuously changing over time. To understand it, machines use feedback from sensors, which must then be translated into a digital binary language of zeros and ones. Analog-to-digital converters (ADCs) perform this task, helping to bridge the physical and digital worlds.

Sensors measuring a physical parameter produce a voltage signal proportional to the varying input. ADCs take samples of the analogue voltage signal at regular intervals and calculate discrete values to approximate the changing signal.

The Nyquist Criterion Minimises Aliasing

The Nyquist criterion, also known as the Nyquist–Shannon sampling theorem, dictates that a signal can be accurately reconstructed from its samples if the sampling rate is at least twice the highest-frequency component in the signal. In essence, it provides the minimum sampling rate necessary to capture all the information in a signal without losing detail, preventing a phenomenon called aliasing. This implies that sampling frequencies must vary in most applications based on how quickly the physical parameter changes.

An ADC's resolution, which is measured in bits, represents the number of discrete amplitude levels available in its digital output. The higher the resolution, the smaller the input voltage change required to alter the digital output by one least significant bit (LSB). The LSB in a binary number is the rightmost bit, representing the smallest power of two in that number.

Some physical signals, such as seismic waves, are very small, while others, like a motor's vibration, can be much larger. In both cases, the smaller the changes in the input signal, the higher the resolution required.

ADC Accuracy

Due to the discrete values available at the output of an ADC, a difference between the analogue input signal and the digital output appears. These differences are called quantisation errors or quantisation noise. The ratio between this noise and the desired signal is called the signal-to-noise ratio (SNR), measured in decibels (dB). Any value above 1dB denotes more of the desired signal than noise.

The output of an accurate ADC is a close representation of the original signal. ADCs' accuracy can be improved by increasing the sampling rate, which increases the maximum frequency that can be measured, or by increasing the resolution, which improves accuracy in measuring the amplitude of an analogue signal.

Types of ADCs

There are three main types of ADCs:

• Sigma-delta (ΣΔ) ADCs are used for precision industrial measurements such as pressure and temperature monitoring.
• Successive approximation register (SAR) ADCs are particularly suitable for multi-channel, real-time applications like wearable sensors or motor control.
• Pipelined ADCs, due to their high sampling rate, are used for communication systems, radar applications, and medical imaging.

Conclusion

ADCs are a vital part of the signal measurement chain and the primary interface between (digital) electronics and the (analogue) real world. Engineers must choose a suitable conversion technology and the required resolution for the intended application.