US2018128598A9PendingUtilityA9
System and method for orientating point cloud data relative to base reference data
Est. expiryDec 20, 2026(~0.4 yrs left)· nominal 20-yr term from priority
G01B 11/105G06T 2207/30136G06T 7/75G06T 2207/10028
46
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Claims
Abstract
A system for orientating point cloud data of a first surface relative to base reference data of a structure includes an input source generator adapted to provide the point cloud data, a tilt-correction means for orientating the point cloud data relative to the base reference data, a data editing means to filter spurious point data from the point cloud data, and a volume measurement means to measure the volume of objects that are non-fixably connected to the surface to segment the non-fixably connected objects from the point cloud data. The first surface is the surface of a wear liner. After orientation of the point cloud data with the base reference data, the surface displacement of the first surface to a second surface of the base reference substantially distinct from the first surface can be calculated to identify the thickness of the wear liner.
Claims
exact text as granted — not AI-modifiedWhat is claimed is:
1 . A system for orientating point cloud data of a first surface relative to base reference data of a structure, the first surface being the surface of a wear liner(s), the base reference data being referenced to a co-ordinate system related to the geometry of the structure, the system comprising:
an input source generator in the form of a scanner adapted to provide said point cloud data of the first surface, a co-ordinate system of the first surface being referenced to a reference point of the scanner; a tilt-correction means for orientating said point cloud data of the first surface relative to the base reference data of the structure, wherein the tilt-correction means includes a point cloud data orientation means, such that the co-ordinate system of the point cloud data aligns with the co-ordinate system of the base reference data; a data editing means to filter spurious point data from the point cloud data of the first surface; a non-fixably connected volume measurement means, to measure the volume of objects that are non-fixably connected to said surface to segment the non-fixably connected objects from the point cloud data; and wherein said base reference data of the structure comprises key reference data which describes the geometry of the base reference of that structure, the base reference having a second surface, the second surface of the base reference being substantially distinct from the first surface, whereby after orientation of the point cloud data with the base reference data the surface displacement of the first surface to the second surface of the base reference of the structure can be calculated to identify the thickness of the wear liner(s).
2 . A system as claimed in claim 1 , wherein the base reference represents a substantially cylindrical shell with opposing ends, the base reference further comprises critical parameters defining the location of the central longitudinal axis of the shell, the radius of the shell, and the length of the cylindrical portion of the shell.
3 . A system as claimed claim 2 , wherein said data editing means further includes partitioning means to partition said point cloud data into discrete segments corresponding to different geometrically described sections of said surface.
4 . A system as claimed in claim 3 wherein said data editing means includes at least one or more of the following processes:
(i) a scanner structure filter to remove points attributable to any supporting means used to situate, stabilise or protect the scanning means;
(ii) an intensity filter to remove any point in the point cloud data above a threshold intensity value; and
(iii) a range filter to remove any point less than a minimum or greater than a maximum threshold in the point cloud data.
5 . A system as claimed in claim 4 , where said base reference data includes radius and length variables, and wherein said range filter derives the threshold from said radius and said length.
6 . A system as claimed in claim 3 wherein said partitioning means includes at least one or more of the following processes:
(i) an opposing-end segmentation means wherein said opposing-end segmentation means includes at least one or more of the following processes:
a) a planar-end segmentation means to segment points in the point cloud data when said base reference data denotes a substantially planar end; and
b) a conical-end segmentation means to segment points in the point cloud data when said base reference data denotes a substantially conical end;
(ii) a floating-object segmentation means to segment points in the point cloud data attributable to objects that are non-fixably connected to said surface; and
(iii) a belly segmentation means to segment points in the point cloud data attributable to said cylindrical shell;
wherein said planar-end segmentation means and conical-end segmentation means includes an end segmentation software utility comprising:
a frequency calculator process to calculate the frequency of each longitudinal co-ordinate within the point cloud data;
a greatest frequency calculator process to determine the greatest said frequency of positive and negative longitudinal co-ordinates;
a threshold addition process to add a threshold value to said greatest negative and positive frequency values; and
whereby said conical-end segmentation means further comprises:
a minima locations calculator process to scan said longitudinal co-ordinate frequencies to determine minima locations from said greatest negative and positive frequency values as towards the location of said scanner;
a segmentation process to segment the points in the point cloud data attributable to the planar ends according to said minima locations; and
whereby said conical-end segmentation means uses the greatest negative and positive frequency values of the minima locations calculator process to segment the points in the point cloud data attributable to the conical ends.
7 . A system as claimed in claim 6 , wherein said floating-object segmentation means includes a floating-object software utility, that operates after said opposing-end segmentation means has been effected on said point cloud data, said floating-object software utility comprising:
a radius frequency calculator process to calculate the frequency of each cylindrical radius value in point cloud data; a peak value determinative process to determine a peak value of the frequencies of cylindrical radii and segmenting points based on said peak value; a segmentation fitting process to fit all segmented points to a plane by eigenvalue-based decomposition; a point cloud translation process to translate point cloud data of m points to the centroid
(
x
′
y
′
z
′
)
i
=
(
x
y
z
)
i
-
(
x
_
y
_
z
_
)
where
(
x
_
y
_
z
_
)
=
1
m
∑
i
=
1
m
(
x
y
z
)
i
an eigenvalue decomposition process, to determine the eigenvalue decomposition of the covariance matrix
Λ
=
MCM
T
where
C
=
∑
i
=
1
n
(
x
′
y
′
z
′
)
i
(
x
′
y
′
z
′
)
i
a plane model is given by ax+by+cz−d=0 where (a, b, c) are the elements of the eigenvector corresponding to the smallest eigenvalue, and
d
=
(
a
b
c
)
(
x
_
y
_
z
_
)
a residual deviation calculation process, to calculate the residual deviation, v, from the best-fit plane for each point: ax i +by i +cz i −d=v i
a points discardal process, to discard points above the plane based on the standard deviation of residuals.
8 . A system as claimed in claim 6 wherein said belly segmentation means includes a belly segmentation software utility, comprising:
a centroid refiner process, to refine the centroid of point cloud on the longitudinal axis by calculating the mean value at either end of said substantially cylindrical shell using an equal number of points
x
_
L
=
1
p
-
∑
i
=
1
p
-
x
i
-
such
that
p
-
n
≥
t
p
and
x
_
R
=
1
p
+
∑
i
=
1
p
+
x
i
+
such
that
p
+
n
-
p
-
n
≤
t
where − and + refer to points from the left and right ends of the belly liner point cloud, respectively;
a point cloud translation process to translate the entire point cloud data by the mean of these two means
x
i
′
=
x
i
-
x
_
where
x
_
=
x
_
L
+
x
_
R
2
;
a circle definition process, to define a circle at each end of said substantially cylindrical shell, said circle being the circle of intersection of cylindrical belly surface of said base reference data and the conical or planar end surface of base reference data;
a cone definition process, to define a cone with this circle as the base and apex on the belly side of the circle having half-apex angle of 45°;
a point assignment process, to assign each point within the cone to a given end of said substantially cylindrical shell and to assign each point outside of the code to said cylindrical shell.
9 . A system as claimed in claim 6 , wherein said belly segmentation means comprises a cylinder-fit process, wherein said cylinder-fit process includes a cylinder-fit software utility that operates after said opposing-end segmentation means and said floating-object segmentation means have been effected on said point cloud data, said cylinder-fit software utility comprises:
an equation forming process, to form the following equation for each point in the point cloud data ∥({right arrow over (p)} i −{right arrow over (q)})×{right arrow over (n)}∥−r=0 where the observation point vector is given by {right arrow over (p)}=(x i y i z i ) T , the cylinder position vector is given by {right arrow over (q)}=(0 y c z c ) T and the cylinder axis vector is given by {right arrow over (n)}(a b c) T a weighted constraint addition process, to add the weighted constraint a 2 +b 2 +c 2 −1=0 and solving in parametric least squares a cylinder position translation process, to translate the entire scan point cloud by the cylinder position vector
(
x
′
y
′
z
′
)
i
=
(
x
y
z
)
i
-
(
0
y
c
z
c
)
a rotation value calculator process, to calculate the rotation angles, φ and κ
φ
=
arctan
(
c
a
)
and
κ
=
arctan
(
-
b
a
)
;
and
a mint cloud transformation process, to transform the entire point cloud
(
x
″
y
″
z
″
)
i
=
M
T
(
x
′
y
′
z
′
)
i
where M=R 3 (κ)R 2 (φ).
10 . A system as claimed in claim 2 , wherein said non-fixably connected volume measurement means further comprises a ball size measurements means to measure the size of a set of balls within the cylindrical shell.
11 . A system as claimed in claim 1 wherein the point cloud data orientation means comprises:
a temporary point removal means for temporarily removing points that are substantially longitudinally parallel with points removed by the scanner structure filter;
a rotation values means to calculate rotation values to be applied to the point cloud data;
a point cloud data rotation process; and
a point restoration means whereby points removed by the temporary point removal means are restored to the point cloud data.
12 . A system as claimed in claim 11 , wherein said point cloud data orientation means includes a rotation value software utility comprising:
a translator process to translate the point cloud data using centroid reduction
(
x
′
y
′
z
′
)
i
=
(
x
y
z
)
i
-
(
x
_
y
_
z
_
)
where
(
x
_
y
_
z
_
)
=
1
n
∑
i
=
1
n
(
x
y
z
)
i
;
and
a calculator process to determine rotation values via eigenvalue decomposition of the covariance matrix of the point cloud data
Λ
=
MCM
T
where
C
=
∑
i
=
1
n
(
x
′
y
′
z
′
)
i
(
x
′
y
′
z
′
)
i
.
wherein the rotation value software utility is adapted to rotate the point cloud data, said rotation value software utility comprising:
a rotation process to rotate values so that the x-longitudinal, y-transverse and z-height axes coincide
(
x
″
y
″
z
″
)
i
=
M
(
x
′
y
′
z
′
)
i
where M is a rotation value calculated by said rotation values means.
13 . A system as claimed in claim 1 , wherein the tilt-correction means includes a tilt-correction software utility for determining and correcting any residual tilt in the point cloud data about an axis comprising:
an extractor process to extract a temporary set of points (p) within a set of constraints:
| x i |<t x |y i |<t y z i >t z
a subtracter process to subtract a mean x co-ordinate from the temporary set of points:
x
i
′
=
x
i
-
x
_
where
x
_
=
1
p
∑
i
=
1
p
x
i
forming the following 2D line equation for each point in the resulting temporary set of points:
z i =mx i ′+b
a least-squares calculator to calculate the least-squares estimate of the slope, m, as:
m
=
∑
i
=
1
p
z
i
x
i
′
∑
i
=
1
p
(
x
i
′
)
2
a rotate angle calculator process to calculate a rotation angle φ as:
φ=arctan( m )
a scan point rotator process to rotate the scan point data:
(
x
′
y
′
z
′
)
i
=
R
2
(
φ
)
(
x
y
z
)
i
where
R
2
(
φ
)
=
(
cos
φ
0
-
sin
φ
0
1
0
sin
φ
0
cos
φ
)
.
14 . A system as claimed in claim 1 , further including a hole measurement means to measure the size of apertures in said surface.
15 . A system as claimed in claim 1 , wherein said non-fixably connected volume measurement means further comprises a ball-ore discrimination means to measure the ratio of a set of balls to non-ball materials.
16 . A system for orientating point cloud data of a first surface of a mill relative to base reference data to determine the mill's liner thickness, the first surface being the wear surface of the mill's wear liners, the base reference data being referenced to a co-ordinate system related to the geometry of the mill, the system comprising:
an input source generator in the form of a scanner adapted to provide said point cloud data of the first surface, a co-ordinate system of the first surface being referenced to a reference point of the scanner; a tilt-correction means for orientating said point cloud data of the first surface relative to the base reference data of the mill, wherein the tilt-correction means includes a point cloud data orientation means, such that the co-ordinate system of the point cloud data aligns with the co-ordinate system of the base reference data; a data editing means to filter spurious point data from the point cloud data of the first surface, the data editing means including identifying and segmenting a non-fixably connected volume; the volume of the non-fixably connected volume being measured by a non-fixably connected volume measurement means, the non-fixably connected objects being the ball charge, the volume measurement means comprising a ball-ore discrimination means to determine the ratio of balls to ore of the ball charge, wherein the ball-ore discrimination means conducts a curvature analysis of the ball charge to provide subsets of data comprising points on individual balls, and a number of subsets of data comprising points on ore, wherein the subset data results are used to estimate the composition of the matter below the surface scan, by factoring the distance between the liner and the surface of the ball charge, and the geometry of the surface; wherein said base reference data represents critical geometrical parameters of a base reference of the mill, the base reference being a second surface of the mill, the second surface being the surface against which the mill's liners are secured, or the surface aligning with the back of the mill's liners, and is substantially distinct from the first surface, whereby after orientation of the point cloud data with the base reference data the surface displacement of the first surface of the mill to the second surface of the mill can be calculated to identify the thickness of the wear liners.Cited by (0)
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