National Semiconductor Corp.'s two
configurable sensor analog front-end (AFE) integrated circuits (ICs) work together with new
tools to fast-track signal path designs for a variety of sensors from major
global manufacturers. The first in a family of products, National's two
configurable sensor AFE products are each customized to a specific sensor
application and have a variety of features, including programmable current
sources, voltage reference options and adjustable sample rates. The LMP91000 is a fully configurable, low-power potentiostat that
provides a complete, integrated signal path solution between a sensor and
analog-to-digital converter (ADC). The LMP90100 is a multi-channel, low power, 24-bit sensor AFE with
true continuous background calibration and diagnostics for high performance
transmitter and transducer applications.
The configurable sensor AFE ICs and WEBENCH
Sensor AFE Designer enable the design
engineer to select a sensor, design and configure the solution and download
configuration data to the sensor AFE. A typical sensing application that today
may require several boards and up to 25 components is reduced to just one of
National's ICs and sensor system design is reduced.
According to a study by the National Institute of Standards and Technology, one of the factors in the collapse of the original World Trade Center towers on Sept. 11, 2001, was the reduction in the yield strength of the steel reinforcement as a result of the high temperatures of the fire and the loss of thermal insulation.
If you have a Gadget Freak project, we have a reader who wants to make it. And not only will you get your 15 minutes of fame on our website and social media channels, you will also receive $500 and be automatically entered into the 2015 Gadget Freak of the Year contest.
Robots are getting more agile and automation systems are becoming more complex. Yet the most impressive development in robotics and automation is increased intelligence. Machines in automation are increasingly able to analyze huge amounts of data. They are often able to see, speak, even imitate patterns of human thinking. Researchers at European Automation
call this deep learning.
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