Operator`s manual

SECTION 10. PROCESSING INSTRUCTIONS
10-6
PAR. DATA
NO. TYPE DESCRIPTION
01: 4 Input location no. of atmospheric
pressure in kilopascals
[PRESSURE]
02: 4 Input location no. of dry-bulb temp.
[DB TEMP.]
03: 4 Input location no. of wet-bulb
temp. [WB TEMP.]
04: 4 Dest. input location for vapor
pressure [VP or Z]
Input locations altered: 1
*** 58 LOW PASS FILTER ***
FUNCTION
Apply a numerical approximation to an analog
resistor capacitor (RC) low pass (LP) filter using
the following algorithm.
F(X
i
) = W*X
i
+ F(X
i-1
) * (1-W)
Where, X = input sample,
W = user entered weighting function,
O< W <1
If W=O, F(Xi)=X
1
; if W=1, F(Xi)=X,
F(Xi-1) = output calculated for previous sample.
The equivalent RC time constant is given by
T/W, where T is the sampling time in seconds.
For values of W less than 0.25, the analogous
"cut off" frequency (the frequency where the
ratio of output to input is .707) is accurately
represented by W/(2∏T). For larger values of W,
this "analog" estimate of the cutoff frequency
becomes less representative.
On the first execution after compiling, F(x) is set
equal to X.
PAR. DATA
NO. TYPE DESCRIPTION
01: 2 Repetitions [REPS]
02: 4 First input location for input data
[X]
03: 4 Dest. input location for filtered
data
[F(X) or Z]
04: FP Weighting function, W [W]
Input locations altered: 1 for each repetition
*** 59 BRIDGE TRANSFORM ***
FUNCTION
This instruction is used to aid in the conversion
of a ratiometric Bridge measurement by
obtaining the value for R
s
which is equivalent to
R
f
[X/(1-X)], where X is the value derived by the
standard 21X Bridge Measurement Programs
(with appropriate multiplier and offset, Section
13.5) and R
f
represents the MULTIPLIER value.
The result of Instruction 59 is stored in the
same location that X was.
PAR. DATA
NO. TYPE DESCRIPTION
01: 2 Repetitions [REPS]
02: 4 Starting input location and
destination [X]
03: FP Multiplier (Rf) [MULT.]
Input locations altered: 1 for each repetition
*** 60 FAST FOURIER TRANSFORM ***
THEORY
Instruction 60 performs a Fast Fourier
Transform (FFT) on a set of data contained in
contiguous locations in Input Storage. The FFT
is used to obtain information on the relative
magnitudes and phases of the various frequency
components in a time varying signal. FFT theory
requires that the signal be sampled at a
frequency that is at least two times faster than
the highest frequency component in the signal.
For example, a signal representing ocean waves
with a maximum frequency of 0.125 Hz would
need to be sampled at a rate of 0.25 Hz or
greater. The measurements must be made at
the appropriate sampling rate and stored in
contiguous input locations before the FFT can
be applied. The measured data stored in
sequential input locations is also referred to as
the "original time series data".
The results of the FFT can be expressed as: 1)
the real and imaginary components, 2) the
magnitude and phase components, or 3) the
power spectra. The real and imaginary results
are analogous to the orthogonal (east and north)
representation of a wind vector. The magnitude
and phase results are analogous to the polar
(speed and direction) representation of a wind
vector. The power spectra results indicate the