Time-space de-noising for distributed sensors
Aspects of the present disclosure describe systems, methods and structures employing time-space de-noising for distributed sensor.
1. A computer-implemented method for time-space de-noising of distributed sensor data configured as part of a distributed fiber optic sensing system (DFOS), said system comprising:
a length of optical sensing fiber;
a DFOS interrogator in optical communication with the length of optical sensing fiber, said DFOS interrogator;
said method comprising:
operating the DFOS interrogator such that a series of optical pulses are directed into the length of optical sensing fiber and back scattering light is received by the DFOS interrogator from the length of optical sensing fiber;
generating one or more sensor data (waterfall) plots from the received back scattering light; and
determining physical information at different locations along the length of the optical sensing fiber from the one or more waterfall plots; and
outputting an indicia of the physical information so determined;
wherein the waterfall plots include both time domain and spatial domain data;
wherein the time domain and spatial domain data are simultaneously de-noised;
wherein waterfall plot data is represented as a 2-dimensional array W(x i , t j ), where x i =x 1 , x 2 , . . . , x I and t j =t 1 , t 2 , . . . t J , x I and t J are the number of elements in the columns and rows of the waterfall, respectively;
wherein for each location at each time instant (one point on the waterfall plot called “point-of-interest” or POI), say (x k o , t l o ), a virtual time-space window is selected, with Δx points on the space domain (x-axis), and Δt points on the time domain (t-axis) and the POI (x k o , t l o ) is at the center;
the time-space window is represented as W(x k , t l ), where
x
k
=
x
k
o
-
Δ
x
2
,
…
,
x
k
o
+
Δ
x
2
and
t
l
=
t
l
o
-
Δ
t
2
,
…
,
t
l
o
+
Δ
t
2
;
and
within the time-space window, the amount of pixels with sensor data value (the z-axis value) exceeding a threshold (W th ) is counted, say p(x k o , t l o ), and the minimum value of p is 0, so that none of the pixels within the window exceeds the threshold, and the maximum value of p is Δx×Δt, indicating that all pixels exceed the threshold; and
the ratio of p and the window size is then calculated to obtain the percentage ratio r for this POI expressed as:
r
(
x
k
o
,
t
l
o
)
=
∑
x
k
∑
t
l
f
(
W
(
x
k
,
t
l
)
)
Δ
x
Δ
t
×
100
%
where
f
(
W
(
x
k
,
t
l
)
)
=
{
1
,
W
(
x
k
,
t
l
)
≥
W
th
0
,
W
(
x
k
,
t
l
)
<
W
th
and, the ratio r is output as the de-noised value for a particular location at a particular time instant.