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In electronics and signal processing, signal conditioning is the manipulation of an analog signal in such a way that it meets the requirements of the next stage for further processing. In an analog-to-digital converter (ADC) application, signal conditioning includes voltage or current limiting and anti-aliasing filtering .
Digital signal conditioning in process control means finding a way to represent analog process information in digital format. [2] Use of in control system is particularly valuable number of other reasons, however: A computer can control multivibrator process-control system. Nonlinearities in sensor output can be linearized by the computer.
Signal processing is an electrical engineering subfield that focuses on analyzing, modifying and synthesizing signals, such as sound, images, potential fields, seismic signals, altimetry processing, and scientific measurements. [1]
Optical filters were originally developed for purposes other than signal processing such as lighting and photography. With the rise of optical fiber technology, however, optical filters increasingly find signal processing applications and signal processing filter terminology, such as longpass and shortpass, are entering the field.
Signal conditioning may be necessary if the signal from the transducer is not suitable for the DAQ hardware being used. The signal may need to be filtered, shaped, or amplified in most cases. Various other examples of signal conditioning might be bridge completion, providing current or voltage excitation to the sensor, isolation, and linearization.
The Nyquist–Shannon sampling theorem is an essential principle for digital signal processing linking the frequency range of a signal and the sample rate required to avoid a type of distortion called aliasing. The theorem states that the sample rate must be at least twice the bandwidth of the signal to avoid aliasing.
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When the input signal has a high amplitude and a wide frequency spectrum this is the case. [16] In this case a 16-bit ADC has a maximum signal-to-noise ratio of 98.09 dB. The 1.761 difference in signal-to-noise only occurs due to the signal being a full-scale sine wave instead of a triangle or sawtooth.
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