MCP6SX2DM-PCTLPD Microchip Technology, MCP6SX2DM-PCTLPD Datasheet - Page 22

BOARD DAUGHTER PICTAIL MCP6SX2

MCP6SX2DM-PCTLPD

Manufacturer Part Number
MCP6SX2DM-PCTLPD
Description
BOARD DAUGHTER PICTAIL MCP6SX2
Manufacturer
Microchip Technology
Series
PICtail™r

Specifications of MCP6SX2DM-PCTLPD

Sensor Type
Light, Current Output
Interface
Analog
Sensitivity
850nm
Voltage - Supply
2.5 V ~ 5.5 V
Embedded
No
Utilized Ic / Part
MCP6001, MCP6S22, MCP6S92
Processor To Be Evaluated
MCP6Sx2
Lead Free Status / RoHS Status
Lead free / RoHS Compliant
Sensing Range
-
Lead Free Status / Rohs Status
Lead free / RoHS Compliant
Other names
MCP6SX2DM-PCTLPDR
MCP6SX2DM-PCTLPDR

Available stocks

Company
Part Number
Manufacturer
Quantity
Price
Part Number:
MCP6SX2DM-PCTLPD
Manufacturer:
MICROCHIP
Quantity:
12 000
Signal Analysis PICtail™ Daughter Board User’s Guide
2.6
DS51476A-page 18
FFT (FAST FOURIER TRANSFORM)
The FFT displays the Fast Fourier Transformation of the data in the frequency domain.
This display is typically used to analyze AC signals or to help locate the source of AC
noise.
FIGURE 2-11:
The size of the data set of the FFT analysis determines the resolution and accuracy of
the FFT. The accuracy is equal to:
Where:
In instances where the input signal is not periodic with respect to the sampling fre-
quency of the converter (as is the case with this tool), windowing algorithms are advan-
tageous when looking at FFT results. The windows that are available with the Signal
Analysis Application are the Blackman, Hamming, Hanning and Rectangular. Basically,
an FFT window is multiplied times the measured signal data set taken during the spec-
ified length of time of the conversion. Typically this multiple reduces the magnitude of
the beginning and end of the sample and consequently minimizing discontinuities seen
with the FFT calculation.
Blackman – Window has a bell-shaped characteristic similar to the Blackman-Harris
window. The peak resolution of this window is not as fine as the Hanning, but the
responses flares out less and the rejection of the sidelobes is better.
Hamming – Window has a bell-shaped characteristic. The initial samples from the
conversion data are multiplied by a small number as are the last samples. With this
window, the side lobes adjacent to the main lobes are lower than the results from the
Hanning Window.
Hanning – Window has a bell-shaped characteristic. The initial samples are multiplied
by zero as well a the latest samples. The samples between the beginning and end are
multiplied with the Hanning bell-shape curve. The side lobes of this window are farther
from main lobe as compared to the Hanning Windows. This window is typically used
for harmonic analysis of continuous time signals as well as random noise.
n = number of converted bits
N = number of data points
FFT Window Selection
FFT Accuracy = (4/(n√N)dB)
FFT DISPLAY
 2004 Microchip Technology Inc.

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