COSTS
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Problem: Fully integrated measurement devices are high cost per channel.
Data Acquisition Processors have a higher initial cost, but then a much lower cost per channel, which turns into an economic advantage when you have lots of channels. The cost of adding a channel is roughly the cost of the extra wiring and sensor.
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PACKAGING
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Problem: Independently packaged measurement devices can fill a rack in a hurry.
Adding channels to a Data Acquisition Processor system requires only the additional panel space for your connectors.
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DISPLAY
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Problem: The built-in display that is a strong advantage for a single signal becomes a disadvantage when you have lots of channels.
Data Acquisition Processors can deliver the data for display in any manner that you wish, including software-controlled video graphics of your choosing.
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INTEGRATION
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Problem: Self-contained units offer limited options for interconnection.
Data Acquisition Processors bring measurements directly into your host system on a high-speed data bus. From there, you can apply the data management and networking features of your host system to send data anywhere.
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DIVERSITY
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Problem: Fully integrated devices work with limited device types, sometimes only with packages from one manufacturer.
Data Acquisition Processors work with any kind of device that produces an accessible voltage signal. You can account for the sensor type in your processing, mix and match, then present results in a common representation of your choosing.
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ACCURACY
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Problem: Most integrated instruments use generic "calibrations" that don't match sensors exactly.
DAPs allow true calibration. You can use generic curves but are not limited to them. DAPs can apply individualized corrections to each channel for best accuracy.
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SPEED
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Problem: Self-contained equipment is usually not intended to measure, deliver, or display results as fast as sensor devices can operate.
Data Acquisition Processors are intended for operation at rates orders of magnitude faster than the typical sensors. They can process every channel at maximum rate and deliver results immediately.
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NOISE IMMUNITY
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Problem: Filtering to reduce noise, from interference or the sensors themselves, makes response slow.
Data Acquisition Processors can use similar filtering, or a statistical approach. For example, measuring 1000 times, very fast, and computing an average, reduces random noise to about 3% of its original level.
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