data acquisition

There are a variety of ways in which data (facts or mea-surements about the world) can be turned into a digital representation suitable for manipulation by a computer. For example, pressing a key on the keyboard sends a signal that is stored in a memory buffer using a value that represents the ASCII character code for the key pressed. Moving the mouse sends a stream of signals that are proportional to the rotation of the ball which in turn is calibrated into a series of coordinates and ultimately to a position on the screen where the cursor is to be moved. Digital cameras and scan-ners convert the varying light levels of what they “see” into a digital image.

Besides the devices that are familiar to most computer users, there are many specialized data acquisition devices (DAQs). Indeed, most instruments used in science and engineering to measure physical characteristics are now designed to convert their readings into digital form. (Some-times the instrument includes a processor that provides a representation of the data, such as a waveform or graph. In other cases, the data is sent to a computer for processing and display.)

Components of a Data Acquisition System

The data acquisition system begins with a transducer, which is a device that converts a physical phenomenon (such as heat) into a proportional electrical signal. Trans-ducers include devices such as thermistors, thermocouples, and pressure or strain gauges. The output of the transducer is then fed into a signal conditioning circuit. The purpose of signal conditioning is to make sure the signal fits into the range needed by the data processing device. Thus the signal may be amplified or its voltage may be adjusted or scaled to the required level. Another function of signal con-ditioning is to isolate the incoming signal from the com-puter to which the acquisition device is connected. This is necessary both to protect the delicate computer circuits from possible “spikes” in the incoming signal and to pre-vent “noise” (extraneous electromagnetic signals created by the computer itself) from distorting the signal, and thus the ultimate measurements. Various sorts of filters can be added for this purpose.

The conditioned signal is fed as an analog input into the data acquisition device, which is often a board inserted into a personal computer. The purpose of the board is to sample the signal and turn it into a stream of digital data. The digital data is stored in a buffer (either on the board or in the computer’s main memory). Software then takes over, analyz-ing the data and creating appropriate displays (such as digi-tal readings, graphs, or warning signals) as configured by the user. If the data is being displayed in real time, the speed of the software, the operating system, and the computer’s clock speed may become significant (see clock speed).

Performance Considerations

The sampling rate, or the number of times the signal is mea-sured per second, is of fundamental importance. A higher sampling rate usually means a more accurate representa-tion of the physical data (thus audio sampled at higher rates sounds more “natural”). The faster the sampling rate, the larger the amount of data to be processed and the greater the amount of computer resources needed. Thus, picking a sampling rate usually involves a tradeoff between accuracy and speed (for a real-time application, data must be pro-cessed fast enough so that whoever is using it can respond to it as it comes in).

Three internal factors determine the performance of a DAQ. The resolution is the number of bits available to quantify each measurement. Clearly the ability to measure thousands of voltage levels is useless if the resolution of a system is only 8 bits (256 possible values.) The range is the distance between the minimum and maximum voltage lev-els the DAQ can recognize. If a signal must be “squeezed” into too narrow a range, a corresponding amount of reso-lution will be lost. Finally, there is the gain or the ratio between changes in the measured quantity and changes in the signal strength.

Applications

Data acquisition systems are essential to gathering and pro-cessing the detailed data required by scientific and engi-neering applications. The automated control of chemical or biochemical processes requires the ability of the control software to assess real-time physical data in order to make timely adjustments to such factors as temperature, pressure, and the presence of catalysts, inhibitors, or other compo-nents of the process. The highly automated systems used in modern aviation and increasingly, even in ground vehicles, depend on real-time data acquisition. It is not surprising, then, that data acquisition is one of the fastest-growing fields in computing.