We all know that electronic products are composed of one or countless electronic components interacting to complete specific functions. In our daily life, we use headphones and speakers to listen to audio, play digital synthesizers, and broadcast content with microphones. How do we achieve this?
In this process, the most important role is the analog-to-digital converter and the digital-to-analog converter. A/D converters are analog chips that can handle scale, read and process waveforms produced by language, temperature, audio and video. Its working steps include analog signal sampling, quantization, coding and conversion into digital signals. The sound we hear is a discrete digital signal that needs to be converted by a digital-to-analog converter into an analog signal that can be played through speakers or headphones.
In addition to audio, electronic thermometers, fingerprint recognition sensors, etc. that we are familiar with also rely on ADC to play a role. In fact, the application range of such ICs is very wide. In automotive applications, temperature sensors and pressure sensors often require the use of ADCs to convert analog signals into digital signals in binary format that the ECU can recognize.
As a bridge between the digital domain and the analog domain, ADC and DAC are the most difficult analog chips, and their performance often determines the upper limit of the performance of the entire system.
Texas Instruments is a major manufacturer of A/D converters, including High-speed ADCs, Precision ADCs, and Isolated ADCs. Different configurations of ADCs determine what the field of application is.
Usually we need to pay attention to its parameters when choosing an ADC, including sampling rate, resolution, conversion error, and conversion rate.
Sample Rate
The sampling rate is the number of times that can be sampled per unit time. The more sampling points, the more the original signal can be restored.
Resolution
The ability of the ADC to resolve the input signal is determined by the full-scale voltage and the number of bits of the ADC output binary number. In the case of ADCs with the same input range, the higher the resolution, the smaller the minimum change represented by one code value. If the output is an ADC with a 3-bit binary number and the input signal range is 0-10V, the converter should be able to distinguish the minimum voltage of the input signal as 1.25V. When the voltage change is smaller than this value, the ADC cannot capture this small change.
Conversion Error
The conversion error represents the difference between the digital quantity actually output by the A/D converter and the theoretical output digital quantity.
Slew Rate
Refers to the reciprocal of the time elapsed from the start of the ADC conversion control signal to the output of a stable digital signal. Different types of converters have very different conversion rates.
In practical applications, the selection of A/D converters should be comprehensively considered in terms of the total number of digits of system data, precision requirements, the range of input analog signals, and the polarity of input signals.
AD7606BSTZ DAS/ADC 16BIT
The signal-to-noise ratio (SNR) of a digital-to-analog converter is the ratio of the input signal power to the noise power and is used to quantify the noise within the data converter. SNR can also be measured using the RMS value of the signal amplitude and noise amplitude, in dB.
If an AC signal is applied to the input of an ideal A/D converter, the digital output will be noisy due to quantization errors. For an ideal converter, the maximum error for any given input is +/-ΩLSb. If a linear ramp signal is applied to the input of the converter and the output error produced by each analog input is plotted, the result is a sawtooth wave with a peak-to-peak value of 1LSb.
To find the actual SNR of the A/D converter, a sine wave with an amplitude slightly below full scale is applied to the converter input. SNR is defined as the ratio between the root mean square of the input signal and the root sum square value of all noise components in the FFT analysis except the DC component and harmonics of the input signal.
Signal-to-noise ratio and distortion (SINAD) can be measured by applying a sinusoidal signal near full scale at the input of the A/D converter. SINAD can be obtained by calculating the ratio between the root mean square of the input signal and the root sum square value of all noise and distortion components in the FFT analysis except the DC component. The SINAD value is a particularly useful performance metric because it includes the effects of all noise, distortion, and harmonics introduced by the A/D converter.