Real World Instrumentation with Python
Category: Education (depraced!)
- views: 1 876
- date: 17 July 2011
- posted by: pool

pdf | 621 pages | 7.35 Mb
Sales page:
http://www.amazon.com/Real-World-Instrumentation-Python-Acquisition/dp/0596809565
This is a book about automated instrumentation, and the automated control systems used with automated instrumentation. We will look at how to use the Python programming language to quickly and easily implement automated instrumentation and control systems.
Automated instrumentation can be found in a wide variety of settings, ranging from research laboratories to industrial plants. As soon as people realized that collecting data over time was a useful endeavor, they also realized that they needed some way to capture and record the data. Of course, one could sit with a clock and a pad of paper, staring at thermometers, dials, and gauges, and write down numbers or other information every few minutes or so, but that gets tedious rather quickly. It’s much easier—and more reliable—if the process can be automated. Fortunately, technology has advanced significantly since the days of handwritten logbooks and clockwork-driven strip chart recorders.
Nowadays, one can purchase inexpensive instrumentation for a wide variety of physical phenomena and use a computer to capture the data. Once a computer is connected to instrumentation, the possibilities for data collection, analysis, and control begin to expand in all directions, with the only real limitations being the ability to implement the necessary software and the implementer’s creativity.
The primary objective of this book is to show you how to create software that you can use to get a capable and user-friendly instrumentation or control application up and running with a minimum of hassle. To this end, we will work through the steps necessary to create applications that incorporate low-level interfaces to the real world via various types of input/output hardware. We will also examine some proven methods for creating programs that are robust and reliable. Special attention will be paid to designing the algorithms necessary to acquire and process the data. Finally, we will see how to display the results to a user and accept command inputs. It is my desire that you will find ideas here that you might take away and creatively apply to meet your own needs in a wide variety of settings.
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