Today, digital computers and other microprocessorbased devices have replaced analog recording and display technologies in all but the simplest data acquisition applications. And while computers have had an undeniably positive impact on the practice of data acquisition, they speak only a binary language of ones and zeroes. Manufacturing processes and natural phenomena, however, are still by their very nature analog. That is, natural processes tend to vary smoothly over time, not discontinuously changing states from black to white, from on to off.
To be meaningfully recorded or manipulated by a computer then, analog measurements such as pressure, temperature, flow rate, and position must be translated into digital representations. Inherently digital events, too, such as the tripping of a motor or a pulse generated by a positive displacement flowmeter, must be made interpretable as a transistortotransistor logic (TTL) level changes in voltage. Hence, the origination and ongoing development of input/output (I/O) systems (Figure 11) for converting analog and digital information about realworld processes and events into the language of computers.

Figure 11: Functional Diagram for Data Acquisition & Control 
Resolution & Aliasing
Most sensors for measuring temperature, pressure, and other continuous variables provide a continuously varying electrical output to represent the magnitude of the variable in question. To make this signal interpretable by a microprocessor, it must be converted from a smooth continuous value to a discrete, digital number (Figure 12).

Figure 12: The Analogt0Digital Interface 
This analogtodigital (A/D) conversion process poses two primary challenges: one of quantization and one of sampling in time (Figure 13). Quantization refers to the uncertainty introduced upon conversion of an analog voltage to a digital number. Measurement transducers or transmitters typically provide continuously varying signals between 010 V dc, ±5 V dc, 0100 mV dc, or 420 mA dc. Thermocouples and resistance temperature devices (RTDs) are other common low voltage inputs.

Figure 13: A/D Conversion Compromises 
When this analog value is represented as a digital number, however, this essentially continuous resolution is limited to discrete steps. This resolution of an A/D conversion often is stated in terms of bitsthe more bits the finer the resolution. The number of bits determines the number of divisions into which a fullscale input range can be divided to approximate an analog input voltage. For example, 8bit resolution of a 010 V input signal means that the range is divided into 28 = 256 steps. This yields a step, or interval, size of 10 V/256 = 0.039 V. Thus, a 10V input is equal to the digital number 255 and a 0V input corresponds to 0. Each 0.039V change in the input is indicated by adding or subtracting 1 from the previous number. (For example, 9.961 V is digitally represented by 254.)
Digital data acquisition systems not only quantize data in terms of magnitude; time, too, is parceled into discrete intervals (Figure 13). In general, there is no information about the behavior of the process between data points gathered. Special precautions, then, must be taken to ensure no meaningful data is lost and interpolation between recorded points remains a valid assumption.
The Nyquist theorem defines the necessary relationship between the highest frequency contained in a signal and the minimum required sampling speed. Nyquist stated that the sample rate must be at least twice the highest frequency component contained within the input signal. So, to sample a 1Hz sine wave, the sample rate should be at least 2 Hz. (But a rate of 816 Hz would be much better for resolving the true shape of the wave.)
The primary implications of ignoring the Nyquist criterion include not only missing high frequency information but of introducing aliasing; if the sample rate is not fast enough, the presence of totally nonexistent frequencies may be indicated (Figure 14). It is aliasing that makes a helicopter's rotors or a car's wheels appear to turn slowly backwards when seen in a movie. Lowpass, or antialiasing filters can be used to limit the measured waveform's frequency spectrum so that no detectable component equals or exceeds half of the sampling rate.

Figure 14: Aliasing Due to Slow Sample Rate 
Designing or specifying a device for A/D conversion consists of a series of tradeoffs. As will be amply demonstrated in the next section, more resolution (more bits) means more accurate conversion but more expensive hardware. Similarly, slower sample rates mean cheaper A/D conversion, but the Nyquist criterion must still be satisfied.
