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Improving Measurement Quality with Signal Conditioning Download this white paper and learn about the most common types of signal conditioning used in data acquisition.
When measuring real-world physical phenomenon, signal conditioning is a prerequisite for correctly processing the electrical signals from the sensor and improving the overall quality of the data. Just as wheat grown in the field requires much processing before appearing as bags of flour in the grocery store, raw signals must be cleaned up, transformed, and properly adjusted to become a usable output that humans and machines can understand.
This white paper explains the best practices and proper application of the seven major signal conditioning types. Understanding the unique characteristics of each technique will help improve the measurement accuracy of your data acquisition system.