Unlike other electronic equipment, sensors mount in the application environment. For factory applications, this immediately demands some level of ruggedness. Sensing in automotive and construction vehicles, as well as outdoor applications, also dictate ruggedness requirements.
To reliably detect moving or stationary cars, trains, trucks and cargo under wind, rain, humidity and extreme temperatures, Banner Engineering mounted its R-GAGE QT50R radar sensor in an International Electrotechnical Commission (IEC) IP67-rated housing. Using Frequency Modulated Continuous Wave (FMCW) radar for detection, the sensor operates under harsh weather conditions.
“The QT50R's robust housing features a 30-mm threaded mounting base to provide versatile installation options,” says Mike Dean, product manager, Banner Engineering.
Another sensing area that can prove challenging for ruggedness is photoelectric sensors. ifm efector has dealt with this challenge in its OG-Cube photoelectric sensor line. In addition to metal M18 mounting threads that will not strip during installation, a common occurrence with plastic threads, the sensor's standard M12 connector resists high torque levels and provides a quick wiring connection. The newest thru-beam model has a 20m range.
Radar and photoelectric sensors demonstrate ruggedness requirements but they are just the beginning. This section addresses rugged position and pressure sensors. The position sensing subsection provides more information on IEC ratings for harsh environments.
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For industrial control applications, or even a simple assembly line, that machine can go almost 24/7 without a break. But what happens when the task is a little more complex? That’s where the “smart” machine would come in. The smart machine is one that has some simple (or complex in some cases) processing capability to be able to adapt to changing conditions. Such machines are suited for a host of applications, including automotive, aerospace, defense, medical, computers and electronics, telecommunications, consumer goods, and so on. This discussion will examine what’s possible with smart machines, and what tradeoffs need to be made to implement such a solution.