Dokumentenidentifikation 
EP1798548 02.08.2007 
EPVeröffentlichungsnummer 
0001798548 
Titel 
Verfahren zur Einstellung von auf der Spannungswellengeschwindigkeit basierenden Vorhersagen der Holzfestigkeit und der Wölbungstendenz einer auf Nutzholz basierenden Rohmaterialgruppe 
Anmelder 
Weyerhaeuser Co., Federal Way, Wash., US 
Erfinder 
Huang, ChihLin, Bellevue, Washington 98005, US; Floyd, Stanley L., Enumclaw, Washington 98022, US 
Vertreter 
derzeit kein Vertreter bestellt 
Vertragsstaaten 
AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HU, IE, IS, IT, LI, LT, LU, LV, MC, NL, PL, PT, RO, SE, SI, SK, TR 
Sprache des Dokument 
EN 
EPAnmeldetag 
08.12.2006 
EPAktenzeichen 
062562806 
EPOffenlegungsdatum 
20.06.2007 
Veröffentlichungstag im Patentblatt 
02.08.2007 
IPCHauptklasse 
G01N 29/07(2006.01)A, F, I, 20070522, B, H, EP

IPCNebenklasse 
G01N 29/44(2006.01)A, L, I, 20070522, B, H, EP
G01N 3/30(2006.01)A, L, I, 20070522, B, H, EP
G01N 33/46(2006.01)A, L, I, 20070522, B, H, EP

Beschreibung[en] 
This invention relates generally to a method for adjusting
stress wave velocity based predictions of wood product properties to compensate
for growth rate differences.
It is generally known that acoustic measurement can be
used to determine properties of a wood product, such as a log, tree, board, or the
like. These properties may include, for example, stiffness, strength, shrinkage,
and other characteristics. In some embodiments, in which properties of a wood product
are being ascertained, a stress wave is induced into the wood product. Next, a measurement
is taken with respect to the time in which the stress wave travels from a first
end to a second end of the wood product. From this time interval, a velocity of
the stress wave can be determined via the equation:
$$\mathrm{v}=\mathrm{d}/\mathrm{t}$$
Where "v" is velocity of the stress wave; "d" is the distance
traveled by the stress wave; and "t" is the time period of travel. This method of
determining velocity is commonly referred to as a "timeofflight" method. The velocity
can, for example, be correlated to a modulus of elasticity ("MOE") for the wood
product, which is an indicator of the stiffness of the wood product. The velocity
can also be correlated to warp potential for the wood product.
These types of measurements are most commonly taken on
the outer wood, or mature wood, of a standing tree to assess stiffness and warp
propensity of the lumber converted from a preharvest forest stand. Trees and stands
demonstrating high values for stress wave velocity ("SWV") generally will produce
lumber that is stiff and stable, as well as less prone to warp.
Juvenile wood, or wood comprising approximately the first
1015 growth rings has low stiffness, has a steep shrinkage gradient, and is more
prone to warp than mature wood. As a result, the outer wood measurement of stress
wave velocity will overestimate the stiffness and underestimate the warp propensity
of the recovered lumber which contains a large amount of juvenile wood. Figures
1 and 2 illustrate the growth rate effect on measurement of stress wave velocity
versus actual stiffness of lumber derived from a log via a cant (i.e. the stress
wave velocity estimation problems associated with logs and trees). In addition to
the diverse site and genetic factors, plantation stands have different silvicultural
prescriptions during their long rotation. Thus, although the diameter, or the age,
or both, of preharvest stands may be the same, the growth ring patterns of the
trees could be very different. Previous studies have taught mathematical corrections
for both diameter and SWV for the evaluation of MOE of logs. However, these corrections
do not compensate for the impact of a percentage of juvenile wood in a sample.
It is known that stiffness is the one of the most deficient
properties for structure wood products, and straightness is one of the most important
factors in a lumber buying decision for builders. Therefore, stiffness and warp
propensity are important properties of trees and logs used to manufacture wood products.
Stiffness and warp propensity varies significantly within and between forest stands,
and this offers an opportunity to rank and sort the trees and stands for genetic
improvement and for allocating a particular material to the appropriate manufacturer
to optimize the value through the forest cycle. Visual characteristics such as size
and morphology of crown, stem, and branches may offer some indications of wood properties;
however, trees or stands with identical morphologies often have very different stiffness
and warp propensity levels. Rapid, nondestructive methods have been applied to sort
and rank internal wood properties such as stiffness and warp propensity of trees,
logs, stems or forest stands. However, these methods often cannot predict or rank
MOE or warp propensity sufficiently because they do not compensate for growth rate
differences.
A need, therefore, exists for a method for adjusting property
calculations based on stress wave velocity measurements to compensate for growth
rate differences amongst timberbased raw material groups.
Embodiments of the present invention are described in detail
below with reference to the following drawings.
 FIGURE 1 is a perspective view of a log or tree having a low percentage of mature
wood and the corresponding cant which may be derived from the log or tree;
 FIGURE 2 is a perspective view of a log or tree having a high percentage of
mature wood and the corresponding cant which may be derived from the log or tree;
 FIGURE 3 is a chart of data taken in a study of logs and lumber;
 FIGURE 4 is a plot of modulus of elasticity ("MOE") versus measured stress wave
velocity for the stands listed in the chart of FIGURE 3;
 FIGURE 5 is a plot of measured modulus of elasticity versus predicted modulus
of elasticity in which the data has been adjusted using the method of the present
invention;
 FIGURE 6 is a plot of crook versus measured stress wave velocity for the stands
listed in the chart of FIGURE 3; and
 FIGURE 7 is a plot of measured crook versus predicted crook in which the data
has been adjusted using the method of the present invention.
The present invention relates to methods for predicting
properties based on stress wave velocity measurements, such as modulus of elasticity
and/or warp potential of trees and/or logs and/or stems, for a timberbased raw
material group. The term "timberbased raw material group" ("TBRMG") may be interpreted
to encompass, for example, stands of timber, individual stems, collections of individual
stems, individual logs, groups of logs, or the like. The methods provide a formula
allowing compensation for growth rate differences between TBRMGs. Accordingly, the
present invention prevents underestimation or overestimation of MOE and/or warp
potential.
The present invention may be practiced using known tools
for determining stress wave velocity within a wood product or specimen, such as
a standing tree, log, board, or the like. In an embodiment, the stress wave velocity
is measured at the cambium layer. Among these devices may be a FAKOPP® or a
Director ST300® device. These types of devices involve the use of a first probe
placed at a first location along a wood product and a second probe placed at a second
location along the wood product. The first probe senses the initial pulse created
by contact with the wood product, or other methods of stress wave inducement into
the wood product. The second probe senses the pulse at the second location. This
is commonly referred to as a "pitchandcatch", or single pass, measurement. For
standing trees, the pitchandcatch method is one of the most commonly practiced
methods due to the lack of a welldefined boundary of a standing tree.
Other devices which may be utilized in the practice of
the present invention are, for example, devices such as a diameter tape or a caliper
for determining log and/or tree diameter. In addition, devices such a Resistograph®
or a Sibtec DmP (Digital microProbe) which detect decay and/or record the drilling
depth and the crossing of high resistance latewood bands while drilling to determine
ring patterns may be utilized. It is also contemplated that, in other embodiments,
stress wave velocity may be determined via the use of resonance frequency. Methods
and systems for making these types of determinations are known to those skilled
in the art, such as for example, the HITMAN® or HM 200, and other resonance
frequency measuring devices.
The present invention requires a determination or estimation
of the amount of juvenile wood (the first 1015 rings) within a tree, log, stem,
or the like. This may be estimated by the percentage of stem's cross sectional area
that is comprised of the first 1015 rings.
It is generally known that stress wave velocity, also referred
to as acoustic velocity, increases with ring age. Velocity that is measured using
a standing tree stresswave tool corresponds to travel of the wave through/across
the rings that occupy approximately the outer 13 centimeters of growth. This outerwood
acoustic velocity correlates well with MOE for stands of the same age provided that
the numbers of rings in that outer zone are more or less the same, such as, for
example, a "typical" southern pine plantation stand which is managed to produce
relatively uniform ring spacing through its cycle. A reasonably accurate relationship
between a FAKOPP reading and the MOE of a stand can be expected for all "typical"
stands of the same age. However, a Fakopp/MOE relationship (or, MOE calculation
based on FAKOPP measurements) developed for this typical stand will overestimate
the MOE of a tree whose outer growth has stagnated and will underestimate the MOE
of a tree with enhanced outer growth.
In an embodiment of the present invention, a method has
been formulated for adjusting the measured stress wave velocity for a stand and,
thereby, the calculated MOE. It is appreciated that the formula below is an example
of an embodiment and that the term "TBRMG" could be substituted for the term "Stand"
in the formula to encompass for example, stands of timber, individual stems, collections
of individual stems, individual logs, groups of logs, or the like. The method includes
the formula below:
$$\mathrm{Stand\; MOE}\mathrm{=}{\mathrm{K}}_{\mathrm{1}}\mathrm{+}{\mathrm{K}}_{\mathrm{2}}\mathrm{*}{\mathrm{SWV}}_{\mathrm{Test\; Stand}}\mathrm{+}{\mathrm{K}}_{\mathrm{3}}\mathrm{*}\mathrm{J}{\mathrm{W}}_{\mathrm{c}}$$
Where:
 K1 is the intercept and K2 and K_{3} are regression coefficients of
the regression equation.
 SWV_{Test} Stand = Average stress wave velocity (unit = meter per second)
of the stand being tested (average of standing tree stress wave velocities taken
at breast height using a FAKOPP or similar device)
 JW_{c} = The difference between the percentage of juvenile wood of the
stand currently being tested and the average percentage of the juvenile wood of
all the stands being compared (%JW_{Average}  %JW_{Test} Stand).
The regression equation is determined using least squares
estimation. The regression determination involves performing a regression determination
utilizing modulus of elasticity as a dependent variable, and stress wave velocity
and JW_{c} as independent variables.
Stand average diameter at the breast height, or "DBH" recorded
in inventory data at the time of an age 1015 silviculture operation such as thinning
can be used as the juvenile core diameter to estimate the percentage of juvenile
wood. The percentage of juvenile wood is equal to 100*(thinning diameter^2/ Log
diameter ^2). The correction factor JWc is the difference between the percentage
of juvenile wood of an individual stand and the mean of the population of the stands
being compared. Although %JW_{Test Stand} can be used directly in the regression
to improve MOE prediction, the use of the term (%JW_{Average}  %JW_{Test
Stand}) provides additional information on overestimation or underestimation
of an individual stand. For example, a stand with fast early growth and stagnant
late growth (tight outer rings) yields a timeofflight SWV measurement that overestimates
the average MOE of lumber recovered form the center cant. Such a stand has a high
percentage of juvenile wood or a negative value for JW_{c}, which reduces
the effects of the overestimation.
An advantage of the present invention is that the parameters
%JW_{Test} Stand and %JW_{Average} can be estimated from inventory
records if that data includes reliable diameter data (or estimates) at various ages.
Alternatively, those parameters can be estimated using increment cores or arborist
tools, such as a Sibtec DmP or a Resistograph®, or other devices which measure
ringwidth pattern or wood decay. Those parameters also can be measured directly
from log ends.
A similar equation may apply for determination of warp
potential. For example, MOE can be replaced by lumber crook in the equation. It
is understood that the term crook is used in the embodiment described below; however,
other forms of warp, such as bow, twist, cup, or the like may be substituted in
the equation below in a manner known to those skilled in the art. Further, it is
appreciated that the formula below is an example of an embodiment and that the term
"TBRMG" could be substituted for the term "Stand" in the formula to encompass for
example, stands of timber, individual stems, collections of individual stems, individual
logs, groups of logs, or the like. A large magnitude of adjustment may be necessary,
for example (%JW_{Average}  %JW_{Test Stand})^{3}, for
warp prediction because the impact of a steep shrinkage gradient of juvenile wood
on warp is stronger than that on MOE. The formula may then appear as follows:
$$\mathrm{Lumber\; Crook}\mathrm{=}{\mathrm{K}}_{\mathrm{1}}\mathrm{+}{\mathrm{K}}_{\mathrm{2}}\mathrm{*}{\mathrm{SWV}}_{\mathrm{Test\; Stand}}\mathrm{+}{\mathrm{K}}_{\mathrm{3}}\mathrm{*}\mathrm{J}{\mathrm{W}}_{\mathrm{c}}$$
Where:
 K1 is the intercept and K2 K_{3} are regression coefficients of the
regression equation.
 SWV_{Test Stand} = Average stress wave velocity of the stand being tested
(average of standing tree stress wave velocities taken at breast height using a
FAKOPP or similar device).
 JW_{c}= Cube of the difference between the percentage of juvenile wood
of the stand currently being tested and the average percentage of juvenile wood
of all the stands being compared (%JW_{Average}  %JW_{Test Stand})^{3}.
(%JW =100 x (Diameter of the stand at age 1015 years)^{2} ÷ (Diameter
of the stand at current age)^{2}.
The regression equation is determined using least squares
estimation. The regression determination involves performing a regression determination
utilizing warp potential as a dependent variable, and stress wave velocity and JW_{c}
as independent variables.
In an embodiment, the method may be performed via the following
steps. In a first step, a number of trees within a TBRMG may be measured for stress
wave velocity via any of the known methods mentioned above and readily understood
by those skilled in the art. This may provide a value which is representative of
the TBRMG. In an alternate embodiment, the trees may be felled and the resulting
logs may be examined for stress wave velocity. In an example, a butt log portion
is examined. In a following step, the percentage of juvenile wood may be determined
and/or estimated. In a first step, tree diameters at breast height at age 1015
(juvenile diameter) and at harvest age (log diameter) can be estimated from inventory
records. Alternatively, these diameters can be measured on standing trees using
increment cores or arborist tools, such as a Sibtec DmP or a Resistograph®,
or other devices which measure ringwidth pattern or wood decay. In an alternate
embodiment, these diameters can be measured directly from the end of a stem or from
the ends of a log. Percent juvenile wood of a tree or a log can be calculated as
100 times the ratio of the square of the juvenile diameter and the square of the
log diameter. The average percentage of juvenile wood of the sampled trees or logs
of the test TBRMG is the JW_{Test TBRMG}, and the average of juvenile wood
measured for all TBRMGs is the JW_{Average.} The adjustment variable, JWc,
is %JW_{Average}  %JW_{Test TBRMG}.
The following example provides an embodiment of the present
invention, but should not be considered to be entirely representative with respect
to steps such as velocity measuring, ring pattern determination, or related steps:
EXAMPLE 1
A study conducted in 1996 at a mill owned by Weyerhaeuser
Company examined five pruned stands of 26 year old loblolly pines. The specimens
had similar tree diameter at breast height ("DBH"). The DBH ranged from 13 inches
to 15 inches, with an average of 14 inches. Standing tree stress wave velocity was
measured on 25 trees per stand. The logs were processed and tracked through the
mill. Average lumber MOE and average crook of the recovered lumber of the stands
were measured. Average lumber MOE versus stress wave velocity is illustrated in
FIGURE 4. As shown in the plot, actual MOE of stands m and a are over or under the
values predicted by SWV measurement. FIGURE 5 illustrates a plot of predicted versus
measured MOE after adjustment of the data via the formula outlined above. As shown
in the plot, the standard error has decreased (.07 versus .01). This indicates an
increased accuracy of approximately 86%. Average lumber crook versus stress wave
velocity is illustrated in FIGURE 6. No relationship between lumber crook and SWV
was found according to the results. However, FIGURE 7 illustrates a plot of predicted
versus measured crook after adjustment of the data via the formula outlined above.
As shown in the plot, lumber crook can be reasonably predicted after the adjustment.
The results of the example demonstrated that using SWV alone to predict and to rank
MOE or warp propensity of timberbased raw material groups may not be sufficient.
A correction on the percentage of juvenile wood is necessary to improve the accuracy
and the predictions and to obtain a correct ranking.
While the embodiments of the invention have been illustrated
and described, as noted above, many changes can be made without departing from the
spirit and scope of the invention. Accordingly, the scope of the invention is not
limited by the disclosure of the embodiments. Instead, the invention should be determined
entirely by reference to the claims that follow.

Anspruch[en] 
A method for predicting modulus of elasticity of a timberbased raw
material group, the method comprising the steps of:
obtaining a stress wave velocity which is representative for each of
a first, second and third timberbased raw material group (hereinafter referred
to as "TBRMG");
obtaining an average diameter for each of the first, second and third
TBRMG;
obtaining an average diameter of juvenile wood for each of the first,
second and third TBRMG;
obtaining measured modulus of elasticity data for the first, second
and third TBRMG;
determining a percentage of juvenile wood for each of the first, second
and third TBRMG;
obtaining a correction factor JW_{c} for any of the first, second,
or third TBRMG which is equal to a difference between an average percentage of juvenile
wood for the first, second and third TBRMG, and a percentage of juvenile wood for
any of the first, second or third TBRMG, respectively;
performing a regression determination utilizing modulus of elasticity
as a dependent variable, and stress wave velocity and JW_{c} as independent
variables; and
predicting modulus of elasticity of the particular TBRMG from the equation:
$$\mathrm{TBRMG\; MOE}\mathrm{=}{\mathrm{K}}_{\mathrm{1}}\mathrm{+}{\mathrm{K}}_{\mathrm{2}}\mathrm{*}{\mathrm{SWV}}_{\mathrm{TESTTBRMG}}\mathrm{+}{\mathrm{K}}_{\mathrm{3}}\mathrm{*}\mathrm{J}{\mathrm{W}}_{\mathrm{c}}$$
Where:
K1 is the intercept and K2 and K_{3} are regression coefficients
of the regression equation;
SWV_{TESTTBRMG}=Average stress wave velocity of the TBRMG being
tested; and
JW_{c}= The difference between the percentage of juvenile wood
of the TBRMG currently being tested and the average percentage of the juvenile wood
of all the TBRMGs being compared (%JW_{Average}%JW_{TESTTBRMG)}.
A method as claimed in claim 1, wherein the stress wave velocity is
based on an acoustic velocity measurement taken near a cambium layer of one or more
trees or logs within the TBRMG.
A method as claimed in claim 1 or claim 2, wherein the determination
of juvenile wood is based on measurement of growth ring patterns at one or more
cross sections.
A method as claimed in claim 1 or claim 2, wherein the determination
of juvenile wood is based on examination of an extracted increment core.
A method as claimed in claim 1 or claim 2, wherein the determination
of juvenile wood is performed by a device which measures ring width pattern or wood
decay.
A method of claim 1 or claim 2, wherein the determination of juvenile
wood is based on TBRMG growth records.
A method of any of claims 1 to 6, wherein the stress wave velocity is
based on an ultrasonic velocity measurement taken near a cambium layer of one or
more trees or logs within the TBRMG.
A method for predicting warp potential of a timberbased raw material,
the method comprising the steps of:
obtaining a stress wave velocity which is representative for each of
a first, second and third TBRMG;
obtaining an average diameter for each of the first, second and third
TBRMG;
obtaining an average diameter of juvenile wood for each of the first,
second and third TBRMG;
obtaining measured warp data for the first, second and third TBRMG;
determining a percentage of juvenile wood for each of the first, second
and third TBRMG;
obtaining a correction factor JW_{c} for any of the first, second,
or third TBRMG which is equal to the cube of a difference between an average percentage
of juvenile wood for the first, second and third TBRMG, and a percentage of juvenile
wood for any of the first, second or third TBRMG, respectively;
performing a regression determination utilizing warp potential as a
dependent variable, and stress wave velocity and JW_{c} as independent variables;
and
predicting warp potential of the particular TBRMG from the equation:
$$\mathrm{Warp\; Potential}\mathrm{=}{\mathrm{K}}_{\mathrm{1}}\mathrm{+}{\mathrm{K}}_{\mathrm{2}}\mathrm{*}{\mathrm{SWV}}_{\mathrm{TESTTBRMG}}\mathrm{+}{\mathrm{K}}_{\mathrm{3}}\mathrm{*}\mathrm{J}{\mathrm{W}}_{\mathrm{c}}$$
Where:
K1 is the intercept and K2 and K_{3} are regression coefficients
of the regression equation;
SWV_{TESTTBRMG}=Average stress wave velocity of the TBRMG being
tested; and
JW_{c}= Cube of the difference between the percentage of juvenile
wood of the TBRMG currently being tested and the average percentage of juvenile
wood of all the TBRMGs being compared (%JW_{AVERAGE}%JW_{TESTTBRMG})^{3}.
A method as claimed in claim 8, wherein the warp is in the form of crook.
A method as claimed in claim 8, wherein the warp is in the form of bow.
A method as claimed in claim 8, wherein the warp is in the form of twist.
A method as claimed in claim 8, wherein the warp is in the form of cup.
A method as claimed in any of claims 8 to 12, wherein the stress wave
velocity is based on an acoustic velocity measurement taken near a cambium layer
of one or more trees or logs with the TBRMG.
A method as claimed in any of claims 8 to 12, wherein the stress wave
velocity is based on an ultrasonic velocity measurement taken near a cambium layer
of one or more trees or logs within the TBRMG.
A method as claimed in any of claims 8 to 14, wherein the determination
of juvenile wood is based on measurement of growth ring patterns at one or more
cross sections.
A method as claimed in any of claims 8 to 14, wherein the determination
of juvenile wood is based on examination of an extracted increment core.
A method as claimed in any of claims 8 to 14, wherein the determination
of juvenile wood is performed by a device which measures ring width pattern or wood
decay.
A method as claimed in any of claims 8 to 14, wherein the determination
of juvenile wood is based on TBRMG growth records.


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