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CDBCAPTURE Scheda tecnica(PDF) 5 Page - Cirrus Logic |
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CDBCAPTURE Scheda tecnica(HTML) 5 Page - Cirrus Logic |
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5 / 10 page ![]() CDBCapture+ DS327F1 5 Using the same sine wave acquired data, a Fre- quency Domain Analysis can be performed and is shown in Figure 4, below. The Frequency Domain Analysis is performed by selecting "FFT" under the TEST window. The results of this analysis are displayed to the left and bottom of the graph. The graph shows the magnitude vs. frequency spectrum from DC to one half the sampling frequency, with the number of frequency bins equal to one half the number of samples taken. The fundamental and first four harmonics are defined by numbers on the graph while the fundamental frequency and its magnitude are shown below the graph. Four basic statistics relating to the FFT are shown to the left of the graph, these being Signal to Peak Noise (S/PN), Signal to Noise and Distortion (SINAD), Signal to Distortion (S/D), and Signal to Noise Ratio (SNR). The software allows the user to select the number of samples (binary numbers) to be used in acquir- ing the data for the FFT. Note: if the number of samples selected is too small or if the input fre- quency is set too low, it may not be possible for the FFT to discern the fundamental from the DC bins. In this case the software will display the following recommendation: "The test signal frequency falls within the DC bins and is therefore indistinguish- able. Either increase the number of samples or in- crease the frequency of the test signal. Then acquire and try the FFT test again." The software offers the user the option of perform- ing a FFT frequency analysis without having to ap- ply a sine wave signal input. By grounding the input and telling the computer what the maximum A/D count is for a full scale signal, the software will sample the grounded input and assume a full scale signal was applied, providing a theoretical Signal to Noise Ratio based on the internal noise of the system and converter. The display for a grounded input FFT is shown in Figure 5. Figure 4. Frequency Domain Analysis |
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