Data Acquisition Handbook

CHAPTER 1: Intro to Data Acquisition and Signal Conditioning
Please Note: Figures have been omitted from online excerpts.

All industrial processing systems, factories, machinery, test facilities, and vehicles consist of hardware components and computer software whose behavior follow the laws of physics as we understand them. These systems contain thousands of mechanical and electrical phenomena that are continuously changing; they are not steady state. The measurable quantities that represent the characteristics of all systems are called variables. The proper functioning of a particular system depends on certain events in time and the parameters of these variables. Often, we are interested in the location, magnitude, and speed of the variables, and we use instruments to measure them. We assign the variables units of measure such as volts, pounds, and miles per hour, to name a few.

Most variables must be measured with a device that converts the phenomena into a form that a human can perceive such as a visual display, a transducer for sound, or vibrations to stimulate physical sensations. The conversion devices are called transducers or sensors, and they translate the physical phenomena to electrical signals (or vice versa) to be measured with electronic instruments. These instruments have traditionally been ammeters, voltmeters, and various other gages, and the variables can be observed in real time. But an increasing need to record and preserve these phenomena and analyze them at a later time forced engineers to develop data recorders and data acquisition systems.

Variables may be classified in many ways, but generally, most experts prefer two classifications: by characteristic and by type of measurement signal. Variables classified by characteristic include thermal, radiation, force, rate, quantity, time, geometric, physical properties, chemical composition, and electrical. Those classified by measurement signal include motion, force, electrical, and time-modulated. Measurement signals for variables often are hard to differentiate from the measuring system. Four factors require close consideration for measurement signals and systems: the types of transducers available for converting variables to measurement signals, transmission characteristics, data acquisition system input matching, and transducers available to convert from one type of measurement signal to another measurement signal.

Data acquisition systems have evolved over time from electromechanical recorders containing typically from one to four channels to all-electronic systems capable of measuring hundreds of variables simultaneously. Early systems used paper charts and rolls or magnetic tape to permanently record the signals, but since the advent of computers, particularly personal computers, the amount of data and the speed with which they could be collected increased dramatically. However, many of the classical data-collection systems still exist and are used regularly.

Early, expensive mainframe computers were used extensively for gathering multiple channels of data, primarily in large industrial or scientific applications. They were seldom used in small projects because of their relatively high cost. But the introduction of small rack-mounted minicomputers that developed in the 1960’s and later desktop personal-type computers that housed microprocessors and proliferated in the 1970’s justified their use for smaller projects. Soon, data acquisition plug-in cards (as well as hundreds of other types of plug-in cards) for these small computers were a common means to collect and record data of all types.

Plug-in cards for computers did not always perform to the user’s expectations, however. Internal noise from rotating devices such as drives and electromagnetic and electrostatic noise from the computer’s internal bus structure often interfered with the measured variable, particularly in data acquisition cards. Isolation and shielding have helped to solve the problem in most cases, but many data acquisition manufacturers also provide signal conditioning and signal processing circuits in small, stand-alone, shielded enclosures. The separate box provides isolation by distance, expansion for hundreds of channels, and portability with laptop computers that desktop personal computers with plug-in cards don’t possess.

All PC-based data acquisition systems will record extremely accurate, repeatable, reliable, and error-free data provided they are connected and operated according to the manufacturer’s recommended practices. These practices include selecting the correct sensors for the application, the proper wire and shielded cable; capturing the signals in proper magnitude, range, and frequency; and paying close attention to grounding and shielding – particularly eliminating ground loops. Additional items include choosing the correct impedance and using doubled-ended (differential) inputs instead of single-ended where possible. The environment should also be considered, especially for extremes of ambient temperature, shock, and vibration. And herein lies the major goal of this publication – to inform users of the most needed recommended practices based upon a fundamental knowledge of the internal workings of data acquisition system instrumentation.

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