Electric heating – Metal heating – By arc
Reexamination Certificate
1999-11-02
2001-09-11
Shaw, Clifford C. (Department: 1725)
Electric heating
Metal heating
By arc
C219S109000
Reexamination Certificate
active
06288364
ABSTRACT:
TECHNICAL FIELD
This invention concerns weld quality measurement. In particular it concerns an apparatus and a process for measuring on-line, while the welding process is under way, the quality of the resulting weldment. The invention is applicable to gas-metal arc welding, tungsten-inert gas welding, pulsed welding, resistance welding, submerged arc welding and to other welding processes where there is an arc plasma.
BACKGROUND ART
The study of welding and cutting arc phenomena, involves the observation of both voltage and current signals having periods of milliseconds to seconds, or even micro-seconds. One way of monitoring these signals involves the use of high speed photography, and another is the use of oscillograms. The limitations inherent in the observation techniques and the difficulties in analysing the resulting data, make it difficult to provide a weld quality measurement in real time.
SUMMARY OF THE INVENTION
In a first aspect, the invention is an apparatus for measuring the quality of a weld. The apparatus comprises:
sampling means to sample either the welding current or the welding voltage to provide a series of values for a first signal.
A second sampling means may be employed to measure the other variable to provide a series of values for a second signal. Alternatively, a signal generating means uses the first signal to generate a series of values for an artificial second signal, which depends upon at least some values of the first signal either explicitly or through a recurrence relation. For example, where voltage V is measured, an artificial current I′ can be mathematically generated using:
I′
n
=e
−&Dgr;t/&tgr;
I′
n−1
−V
n
(1)
where &tgr; is a constant which may be selected, and n is the sample number.
This approximation can model the usual inductive-resistive circuit of a power supply but need not be an accurate model since the artificial signal need only provide information about the time history of the sequence.
Using the symbols D
n
for the real data sequence and A
n
for the artificial sequence, two useful possibilities are
A
n
=e
−&Dgr;t/&tgr;
(A
n−1
−D
n−1
) (2)
A
n
=D
n−k
(3)
where integer k>0. The first of these is similar to equation (1). The second possibility is a simple return variable.
Pairing means identify corresponding values of the first and second signals.
Collection means collect pairs of values which are useful for quality monitoring into groups or regions. The pairs collected could be visualised to be those that would fall within selected regions of a two dimensional scatter plot of the values of the first and second signals. The regions could be drawn on to such a visualisation.
The regions need not be of equal size, and they may be smaller where population density is greatest and may be exponentially greater in dimension, in both the voltage and current direction, as they progress away from the point of greatest population density. Once the regions are chosen they are fixed during the monitoring process.
In the case of ‘dip’ or short circuiting metal transfer in gas metal arc welding, there are large oscillations in voltage and current.
The regions selected will usually be those around the area of greatest density of sample points. However, the regions selected need not be contiguous.
The population of sample points for each selected region can be represented by a two dimensional population density function f
r
for a set of regions r=1 to m.
Multiplication means multiply the set of populations f
q
by weights w
qr
defined for the same set of regions, and sum means then sum the products to produce a set of new values for G
r
, where
G
r
=
∑
q
=
1
m
w
qr
f
q
.
.
.
r
=
1
to
m
(
4
)
To produce the final adjusted region populations P
r
a function F is applied to each of the G
r
values:
P
r
=F(G
r
) . . . r=1 to m (5)
F is a single-valued monotonic function.
The complete set {P
1
. . . P
m
} of the P
r
collected is the welding signature.
The weights w
qr
are chosen to produce a welding signature which contains as much information about the properties of the final weld as possible for a given sampling rate and size. This may be done experimentally, by trial and error adjustment or by knowledge of the physical process. Since there is some statistical noise in the sample, it is useful to choose the w
qr
to smooth the welding signature. The function F is chosen to maximise the sensitivity of the welding signature to changes in the quality of the final weld.
The sampling means repetitively provides a series of values and a new welding signature is produced for each series. Memory means retain a welding signature R={P
1
. . . P
m
} collected under welding conditions known to be satisfactory and producing a high quality weldment. This may be reference data saved for some time, or could be data collected at the start of a welding run. In the case of a robotic welding, where a sequence of welds is carried out under conditions which may vary, a sequence of reference signatures may be stored and recalled when needed.
The reference signature can also be calculated continuously during welding from previous sampling. In this case the reference is a weighted average of the x signatures S
1
, S
2
, S
3
. . . S
X
where S
1
is the most recent signature calculated, S
2
is the signature calculated before that and so on. The reference signature R is determined from the weighted average
r
j
=W
1
s
1j
+W
2
s
2j
+W
3
s
3j
+ . . . +W
x
s
xj
. . . j=1 to m (6)
where r
j
becomes the adjusted region population numbered j in the reference signature R; s
1j
to s
xj
are the adjusted region populations numbered j in the signatures S
1
to S
x
calculated from previous sampling; and W
1
to W
x
are signature weighting factors. The choice of the signature weighting factors W
1
to W
x
determines whether the reference represents an average of weld signature behaviour over a relatively long period of time or represents recent welding behaviour.
When signatures are multiplied or divided by a number, it is understood that every adjusted region population in the signature should be multiplied or divided by the number to produce a new signature. Similarly when signatures are added or subtracted, the matching adjusted region populations of each signature are added or subtracted, that is, the adjusted region population numbered j in one signature is added or subtracted from the adjusted region population numbered j in the other signature for j=1, 2 up to m. The equation above can then be written more succinctly as
R=W
1
S
1
+W
2
S
2
+W
3
S
3
+ . . . +W
x
S
x
(7)
Weld quality result calculation means then compare the welding signatures with the reference welding signature to produce a measure of weld quality.
The part U of a welding signature S which is does not match the reference signature R is given by
U
=
S
-
(
S
·
R
)
R
(
R
·
R
)
(
8
)
where A.B is the inner product of two signatures A and B. If U is zero there is a perfect match.
The quality factor q may be defined by
q
=
1
-
U
·
U
S
·
S
(
9
)
=
R
·
S
R
·
R
×
S
·
S
(
10
)
The quality q will be unity if U is zero and zero if U=S and S.R=0. A value of q=1 would indicate perfect quality. As welding conditions deviate from ideal due to any faults in the welding process, S will no longer match R and q<1.
The inner, or dot, product of any two signatures A and B is defined by:
A
·
B
=
∑
j
=
1
m
a
j
×
b
j
(
11
)
where a
j
and b
j
are the adjusted region populations P
r
of the signatures A and B respectively.
In another aspect, as currently envisaged, the invention provides a method of measuring weld quality comprising the s
Chauza, Esq. Roger N.
Howison, Chauza, Thoma, Handley & Arnott LLP
Shaw Clifford C.
The University of Sydney
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