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Understanding DAQ - 1/8

Understanding Data Acquisition - Data That Matters - 59059 Understanding Data Acquisition - Data that Matters

In February of 1473, when Nicolaus Copernicus was born, the common definition of astronomy was: “the study of how the sun, moon, stars and celestial objects revolve around the earth.” Today, we know that the very definition of astronomy given in those days precluded scientists from ever understanding the true nature of our solar system and universe. In fact, more than 100 years later, when Galileo was able to prove Copernicus’ theories with his new telescope, the idea that the earth revolved around the sun was considered heretical. Galileo was banished and put on house arrest for over 10 years for his observations. Today, a surprisingly similar situation exists in the Data Acquisition (DAQ) world. By definition, Data Acquisition Systems are designed to gather and store data. However, this definition has led many plant managers and engineers to spend substantial amounts of money on systems that do just that - gather data - but are good for little else.In reality, data acquisition is not the purpose of DAQ systems - obtaining Mission Critical Information (MCI), is. Industrial plants, manufacturers, and producers do not need to simply know the temperature, pressure, or production volume of any given piece of equipment in their plant; they need to know what that data means and how it relates to their operations. In other words, the data, in- and-of-itself, is useless, unless it meets these three criteria:

The true purpose of a DAQ system is not to gather data - it is to obtain Mission Critical Information. Data obtained through a DAQ must meet 3 criteria: It must be accurate, clean, and useful. 1.

Accurate - When information is initially recorded at the source, how, exactly, does the reading match the real-life environment it is recording? As we will see in a minute, accuracy is determined almost wholly by the transducers in your DAQ system and their physical placement.

2.

Clean - Most industrial environments are harsh and noisy, offering extensive opportunities for data transmissions to pick up interference of one type or another. This interference causes data corruption, making your end reading “dirty.” Keeping your data clean is the job that your transmission, filtering and sampling systems, and DAQ hardware must fulfill.

3.

Useful - As was previously mentioned, data delivered by a DAQ system is meaningless until it is converted into Mission Critical Information. Analyzing, converting, and storing this information is accomplished by your software drivers, application software, data storage systems, and, of course,

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