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WO2016075641A1 - Évaluation d'arbres et de branches d'arbres et/ou de grumes - Google Patents

Évaluation d'arbres et de branches d'arbres et/ou de grumes Download PDF

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Publication number
WO2016075641A1
WO2016075641A1 PCT/IB2015/058727 IB2015058727W WO2016075641A1 WO 2016075641 A1 WO2016075641 A1 WO 2016075641A1 IB 2015058727 W IB2015058727 W IB 2015058727W WO 2016075641 A1 WO2016075641 A1 WO 2016075641A1
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WO
WIPO (PCT)
Prior art keywords
stand
log
logs
mean value
trees
Prior art date
Application number
PCT/IB2015/058727
Other languages
English (en)
Inventor
Peter Charles Stratton Carter
Nigel James Sharplin
Original Assignee
Fibre Gen Holdings Limited
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Fibre Gen Holdings Limited filed Critical Fibre Gen Holdings Limited
Publication of WO2016075641A1 publication Critical patent/WO2016075641A1/fr

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Classifications

    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01G—HORTICULTURE; CULTIVATION OF VEGETABLES, FLOWERS, RICE, FRUIT, VINES, HOPS OR SEAWEED; FORESTRY; WATERING
    • A01G23/00—Forestry
    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01G—HORTICULTURE; CULTIVATION OF VEGETABLES, FLOWERS, RICE, FRUIT, VINES, HOPS OR SEAWEED; FORESTRY; WATERING
    • A01G23/00—Forestry
    • A01G23/02—Transplanting, uprooting, felling or delimbing trees
    • A01G23/08—Felling trees
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
    • B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
    • B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
    • B07C5/04—Sorting according to size
    • B07C5/12—Sorting according to size characterised by the application to particular articles, not otherwise provided for
    • B07C5/14—Sorting timber or logs, e.g. tree trunks, beams, planks or the like
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/46—Wood

Definitions

  • the invention relates to the ranking and/or selection of logs derived from a stand of trees for wood quality dependent purposes.
  • logs refers to logs cut from a tree or tree stem but can in certain circumstance also be applicable to the tree stem itself, cants cut therefrom, beams, boards, etc. It is of course possible to assign different destinies to different logs to be cut from the same stem of a felled tree which will maximise the extracted value of harvesting of the particular tree. This has been recognised in New Zealand and elsewhere by software packages such as those of the New Zealand Forest Research Institute (i.e. the AVISTM Software) or previously used by LIRO (i.e. the New Zealand Logging Industry Research Organisation).
  • New Zealand Patent Specification 533153 discloses hand held apparatus where two spiked probes are linked via an electronic unit with a timing device whereby stress waves imparted through one probe and its spike is timed in its passage to the second spiked probe thereby to enable the travel time of the stress wave from the first probe to the second probe to be determined for tree assessment purposes.
  • Such apparatus is dependent upon manual positioning and manual activation to input the stress wave e.g. using an impact.
  • US patent 7043990 discloses a method of evaluating a timber comprising the acts of:
  • MOE modified modulus of elasticity
  • US patent 6026689 (Snyder et al) relates to a system relating a measured speed of a stress wave to maximise the value of wood products produced.
  • the present invention envisages a useful advantage to be derived from an encounter between a harvester with its harvesting head and a still standing tree, the tree as it is being felled and/or a recently felled tree.
  • a merchandiser may alternatively be used to carry out the same or similar function.
  • harvester refers to a machine having a felling head and/or processing head and/or a merchandiser of any of the kinds contemplated in the aforementioned patent specification or as otherwise understood in the tree felling art as being a harvester or merchandiser.
  • the term "processor” could in less preferred forms be a pruning head but in more preferred forms a harvester/processor combination.
  • the present invention also and/or alternatively recognises that there is an advantage to be derived immediately prior to felling, during felling and/or soon after felling to have characterised a particular part of the tree stem and immediately to mark the tree stem as to a characteristic, fate or the like dependent on the physical measure or to immediately process in part the tree stem using a harvester head or merchandiser.
  • the present invention sees an advantage in value extraction from a plantation of reliance upon remote operation from a vehicle of testing apparatus in conjunction with the harvester head and thereafter immediately using the harvester head responsive to the physical measure and/or remotely activating some marking or log cutting procedure, or instructing some marking or log cutting procedure, or a combination of both.
  • harvesting heads are disclosed in, for example, Valmet US Patent 4537236, Waratah US Patent 4412569, and Haim US Patent 4382457, amongst many others.
  • the present invention also as an option recognises an advantage in, at the harvester head or merchandiser (and preferably under the control of the operator of the harvester), having an appropriate inputting of data to the harvester operator or any recording or optimising apparatus or both of the outcome of any such testing and/or the harvester head marking of tree products derived from a standing tree prior to, at and/or immediately post felling and/or harvester head processing.
  • US Patent Specifications 6182725 and 6341632 of Bengt Sorvik (both here included by way of reference) relates to a harvester being used in circumstances where data from pre-analysis of a forest region and location of individual trees in that region are tied to an accurate knowledge of the harvesting machine location of its harvesting head so as to appropriately harvest and/or harvesting machine process and mark tree parts immediately prior to felling, during felling or post felling. Such a system however is dependent on multiple inputs from diverse sources.
  • regression coefficients which are some function of stand categorisation and/or calibration, in relation to easy on site determinable individual tree features.
  • Another or alternative object is identifying/making/segregating a log or batch of logs to meet a target mean (average) MOE of resultant product (veneer, or lumber, or even pulp wood fibre).
  • the present invention can be said to broadly consist in A method of evaluating logs for wood quality dependent use, said logs to be derived from an eligible stand of trees, said method comprising :
  • attributed mean value a regression model relating an indicator of log stiffness to at least one log physical characteristic
  • present invention can be said to broadly consist in A
  • processing head of a tree harvesting apparatus comprising at least;
  • the present invention can be said to broadly consist in A method of evaluating a log to be derived from an eligible stand of trees, said method comprising :
  • a threshold considered eligible for the stand to provide logs for structural purposes eg structural timber, veneers, LVL, high strength pulp or paper, etc
  • the present invention can be said to broadly consist in A method of passing or notpassing logs being derived from a stand of trees as appropriate, or not, for a downstream use or a particular downstream use processing;
  • the present invention can be said to broadly consist in A method of passing or notpassing logs being derived from a stand of trees as appropriate, or not, for wood quality dependent use or wood quality dependent use processing; said method comprising :
  • a data set with a regression constant appropriate for such mean value such a data set providing a regression coefficient for stem or log physical measures or derivations thereof such as a regression coefficient for log position in the tree, a regression coefficient for each of at least one
  • the present invention can be said to broadly consist in A method of passing or notpassing logs being derived from a stand of trees as appropriate, or not, for wood quality dependent use or wood quality dependent use processing; said method comprising:
  • regression data providing :
  • a regression coefficient for log or notionalised log position in the tree a regression coefficient for each of at least one, or the, dimensional aspect of a log or notionalised log from such a tree
  • each log as derived from the stand, or from within the stand, reliant upon its log position in its tree, or a log position notionalised by reference to its extent and position in the tree stem, and at least one of its said dimensional aspects or the dimensional aspect.
  • the present invention can be said to broadly consist in A method of passing or notpassing logs being derived from a stand of trees as appropriate, or not, for wood quality dependent use or wood quality dependent use processing; said method comprising :
  • a data set with a regression constant appropriate for such mean value such a data set providing a regression coefficient for stem or log physical measures or derivations thereof such as a regression coefficient for log position in the tree, a regression coefficient for each of at least one
  • refreshed mean value of the stand of trees or some sample thereof representative of the stand that is an indicator of stiffness of logs to be extracted from or within the remainder of the stand, and (provided that refreshed mean value is above a threshold value to provide sufficient logs forwood quality dependent use or wood quality dependent use processing from the remainder of stand or within the remainder of the stand), e.
  • a data set with a regression constant appropriate for such refreshed mean value such a data set providing a regression coefficient for stem or log physical measures or derivations thereof such as a regression coefficient for log position in the tree, a regression coefficient for each of at least one dimensional aspect of a log from such a tree and a regression constant, and f, passing or not passing each log as derived from the remainder of the stand, or from within the remainder of the stand, reliant upon its log position in its tree, and at least one of its said dimensional aspects.
  • the present invention can be said to broadly consist in A method of streaming logs of lengths a, b, and c ( and d, or e etc if desired ) derived from trees of a stand, said method comprising or including
  • regression data set has historically been derived , whether with logs of that length series or not;
  • the present invention can be said to broadly consist in a method of ranking and/or selecting logs to be derived from a stand of (preferably same species and same or similar age) trees but with a mix (as arises when there is growth variation amongst the trees of a stand) of diameters or other observable physical characteristic(s), such ranking and/or selecting to be of a degree to provide commercial benefit, the method comprising or including :
  • the invention is a method of ranking and/or selecting logs to be derived from a stand of (preferably same species and same or similar age) trees but with a mix of diameters or other observable physical characteristic(s), such ranking and/or selecting to be of a degree to provide commercial benefit, the method comprising or including :
  • the invention is a method of ranking and/or selecting logs to be derived from a stand of (preferably same species and same or similar age) trees but with a mix of diameters or other observable physical characteristic(s), such ranking and/or selecting to be of a degree to provide commercial benefit, the method comprising or including :
  • the invention is a method of ranking and/or selecting logs to be derived from a stand of same species (and preferably same or similar age) trees but of a mix of diameters or other observable physical characteristic(s), such ranking and/or selecting to be of a degree to provide commercial benefit, the method comprising or including :
  • the invention is a method of ranking and/or selecting logs to be derived from a stand of same species (and preferably same or similar aged) trees but of a mix of diameters or other observable physical characteristic(s), such ranking and/or selecting to be of a degree for commercial benefit, the method comprising or including : from a sampling of the stand to be representative of the stand for stiffness, deriving at least one value using a regression analysis relatabie as a coefficient or as coefficients, by some observable physical characteristic(s) for each non sampled tree to provide a predictor of stiffness for at least one log (preferably at least two logs) above the butt or butt log of each nonsampled tree, and
  • the invention is a method of ranking and/or selecting logs to be derived from a stand of the same species (and preferably same or similar aged) trees but with a mix of diameters or other observable physical characteristic(s), such ranking and/or selecting to be of a degree for commercial benefit, the method comprising or including : from a sampling of the stand to be representative of the stand for stiffness, deriving a coefficient or coefficients each relatabie by some observable physical characteristic(s) for each non sampled tree to provide a predictor of stiffness for one log (preferably at least two logs) above the butt or butt log of each nonsampled tree, and (provided the sampling has not excluded the stand as insufficiently stiff for structural purposes)
  • the invention is a method of evaluating a log to be derived from an eligible stand of trees, said method comprising :
  • the mean value attributed is above a threshold considered eligible for the stand to provide logs for structural purposes (eg structural timber, veneers, LVL, high strength pulp or paper, etc), using a data set providing a coefficient for log position in the tree, a coefficient for some dimensional aspect of each such log (eg LED), and a regression constant all for that mean value attributed, either passing as structural or failing as structural each log derived from the stand by reference to its log position and its dimensional aspect.
  • a threshold considered eligible for the stand to provide logs for structural purposes (eg structural timber, veneers, LVL, high strength pulp or paper, etc)
  • a data set providing a coefficient for log position in the tree, a coefficient for some dimensional aspect of each such log (eg LED), and a regression constant all for that mean value attributed, either passing as structural or failing as structural each log derived from the stand by reference to its log position and its dimensional aspect.
  • the eligibility/calibration step may involve measuring and calculating a mean, for example HM200 Hitman acoustic resonance-based velocity as an indication of stiffness from a sample of logs from the sand; for instance logs which could have been extracted during road line salvage a year or two prior to the stand harvest operation.
  • a mean for example HM200 Hitman acoustic resonance-based velocity as an indication of stiffness from a sample of logs from the sand; for instance logs which could have been extracted during road line salvage a year or two prior to the stand harvest operation.
  • a sample of the first say 30-50 logs extracted from a stand could be measured for acoustic speed with the Hitman HM200 tool, and an average velocity derived.
  • a stand may be prior categorised/calibrated for stiffness using other stand level measures such as age, stocking (stems per hectare), green crown ratio, site index, etc.
  • the associated regression coefficients could be derived from trial work (correlating stand measures to average stand MOE) or form a look-up table of mean stand MOE (or HM200 velocity equivalent) based on prior trial work.
  • the invention is a system for, and/or a method of, evaluating trees and/or tree stems and/or logs, using any of the methods identified as requiring a mean categorisation and for each log coefficients for that mean related to log position and some dimensional (or adjusted dimensional) aspect.
  • the invention is a method of evaluating trees and/or tree stems of a stand of trees as they are being broken down, or are to be broken down, into logs Log
  • PHi Processor head index (MOE; GPa)
  • the invention is a harvester/processor adapted by inputs, software and an embedded algorithm and related output(s) to perform a method of the present invention or to perform the mandatory steps (and optionally the optional steps) set out herein,
  • step a. If the mean value attributed in step a. does not satisfy a threshold considered eligible for the stand to provide logs for a particular wood quality dependent use or range of wood quality dependent uses, or
  • said dimensional characteristic is, or is derivative of, one or more selected from :
  • said indicator of log position in the stem is, or is derivative of, one or more selected from :
  • the regression model is a linear regression model.
  • said regression model is a multivariable model relating log stiffness to at least two log physical characteristics.
  • said regression model is a multivariable model which relates log stiffness to at least one dimensional characteristic and at least one indicator of log position in the stem .
  • deriving said regression model includes deriving at least two regression co-efficients, including a co-efficient for each of:
  • said reference data comprises one or more reference data sets, each data set relating one or more log physical characteristics to an indicator of log stiffness for a stand of trees, said stand of trees having been characterised according to a mean value that is an indicator of stiffness for that stand.
  • said reference data comprises at least two of said reference data sets.
  • said reference data comprises a library of reference data sets for different stands of trees, each having been characterised according to a mean value that is an indicator of stiffness for that stand.
  • comparing the attributed mean value to the reference data involves selecting one or more reference data sets relating to trees with similar stand characteristics to the stand from which logs are being derived.
  • comparing the attributed mean value to the reference data results in identifying that the attributed mean value is different to a characterising mean value of a stand of trees in the reference data, and deriving a regression model by interpolating accordingly from the regression relationships of the reference data. In some embodiments comparing the attributed mean value to the reference data results in either:
  • the mean value attributed to the stand of trees is, or has been, obtained by assessing or measuring physical characteristics of and/or conducting testing on a sample of trees taken to be representative of the stand. In some embodiments the mean value attributed to the stand of trees is obtained by testing the acoustic velocity of one or more trees.
  • acoustic velocity is tested using probes on the processing head of a tree harvesting apparatus.
  • evaluating suitability for wood quality dependent use involves determining whether for each log, the log stiffness predicted by the regression model satisfies a threshold considered to make the log eligible for a particular wood quality dependent use or range of wood quality dependent uses.
  • evaluating suitability for wood quality dependent use involves for each log, deriving said at least one physical characteristic of the log by
  • said at least one log physical characteristic is a dimensional characteristic
  • evaluating suitability for wood quality dependent use involves for each log, deriving said dimensional characteristic of the log by taking dimensional measurements of the log.
  • measurements are obtained from the logs at the harvesting site.
  • measurements are obtained from the logs using the processing head of a harvester.
  • measurements obtained from the logs are not a measure of acoustic speed by a time-of-flight or resonance technique.
  • the method is used to evaluate a series of logs.
  • steps d. to g . are performed at intervals over the series of logs evaluated.
  • This invention may also be said broadly to consist in the parts, elements and features referred to or indicated in the specification of the application, individually or collectively, and any or all combinations of any two or more of said parts, elements or features.
  • stress wave envisages any sound, compression or other type wave that might be created by a suitable impact or sound input and which will run along and across the tree or tree stem, log or the like, and whether measured by a resonance technique for speed or by elapsed time.
  • elapsed time relates to the time of passage or time of flight of a stress wave between sensors irrespective of whether or not one of those sensors is the input for the stress wave.
  • MOE means modulus of elasticity and also refers to related measures of stiffness, strength, and wood fibre characteristics.
  • tree or “trees” is not restricted to conifers.
  • Conifer species includes Radiata Pine, Loblolly Pine, Slash Pine, Hoop Pine, Parana Pine, Brazilian Pine, Yellow Pine, etc and non pine conifers such as Douglas Fir, Spruce, etc. Species may include outside of the conifers, hardwoods such as Aspen, Sweetgum, Eucalyptus and others.
  • Structural purposes include structural timber, veneer, high strength pulp or paper, LVL, etc.
  • Non structural purposes can be low strength pulp or paper, non structural timber, etc. See our WO05/072314.
  • LED is large end diameter of a log and includes large end diameter adjusted relative to a standard mean diameter according to variation in mean diameter of logs from a stand or logs representative of a stand.
  • dimensional characteristic/s and “physical characteristic/s” includes measures of stem or log dimension and measures of stem or log dimension adjusted relative to a standard mean according to variation in that mean measure of logs from a stand or logs representative of a stand.
  • Figure 1 shows a tree, to be cut into logs dependent upon log number from the butt and large end diameter (LED),
  • Figure 2 shows variation in the stiffness of boards from different longitudinal positions along a tree stem, plotted for five different radial distances from the heart of the tree stem (taken from Ping Xu, J. C. F, Walker (2004) Stiffness gradients in radiata pine trees, Wood Science and Technology 03/2004; 38(1): 1-9. )
  • Figure 3 shows a graph plotting stem diameter at breast height (cm) relative to the number of stems per hectare in stands of trees at two different locations (taken from Christoph Krieger (1998), The Effects of Tree Spacing on Diameter, Height and Branch Size in White Spruce, Management Notes No 13, P.E.I. Department of Agriculture and Forestry, Forestry Division, Prince Edward Island, Canada).
  • Figure 4 shows a regression analysis of large end diameter against end product stiffness for logs derived from two different stands of radiata pine trees, a first located in Nelson and a second located on the West Coast.
  • Figure 5 shows a regression analysis of log diameter against actual lumber Modulus of Elasticity for logs derived from three different stands of loblolly pine trees, each located in the Southern USA.
  • Figure 6 shows an exemplary harvester with a processor head, as can be employed in carrying out the method of the present invention
  • Figure 7 shows, an exemplary processor head, as can be employed in carrying out the method of the present invention, with probes for measuring acoustic velocity.
  • Figure 8 shows, in plan view, an further exemplary processor head, as can be employed in carrying out the method of the present invention with an articulable arm for obtaining dimensional measurements.
  • the use of a pre-measured stand average acoustic speed, or even a predicted stand average stiffness based on other stand measures such as site index, age, green crown ratio (depth of green crown relative to total tree height), can be adequate calibration or categorisation from which to derive a regression model.
  • the regression model can subsequently enable effective segregation of logs to be carried out within stand at a log-by-log level using physical parameters (such as diameter and position within stem) alone.
  • Wood quality is required for different end-uses of a felled tree stem, for example LVL veneer, plywood, structural lumber, appearance lumber, fibre cement pulp, or low coarseness pulp wood fibre. Wood quality pertains not only to structural stiffness but also high or low measures of related fibre properties.
  • acoustic velocity can be indicative of suitability for wood quality dependent use.
  • acoustic velocity may be used to identify a tree stem suitable for a particular end use, for example a "structural' (high stiffness) use, a fibre cement "high pulp strength' use, a Now pulp coarseness' use, or other wood quality dependent use of commercial significance.
  • MoE Elasticity While acoustic velocity, density and MoE are related to a number of commercially relevant properties of wood, for the purposes of the present invention it is of particular interest to note that they are indicators of stiffness.
  • MoE is the modulus of elasticity in GPa
  • V is the speed at which sound travels through the wood in km/s
  • p is the density of the wood in kg/m 3
  • a tree has a number of other physical characteristics which may impact on, be related to, or be correlated with its wood quality. For example the species, age, location, climate, altitude, soil type, nutrition, and genetics can all affect tree growth.
  • Some of the physical characteristics are dimensional characteristics, for example the height of the tree, diameter, height to base of green crown, green crown ratio (depth of green crown relative to total tree height), taper and closeness of growth rings in the tree stem.
  • the stem 6 of a tree 5 can be cut at cut positions, for example those indicated as 7, to provide a butt log 1, and one or more subsequent logs 2, 3, 4 etc.
  • the physical characteristics of the tree stem vary over its height, thus the subsequent logs, 2, 3, 4 etc will have differing wood properties to those of the butt log 1, and be devoid of the convergence (taper) extremes common with butt logs 1.
  • the logs 2, 3, 4 etc may also have differing wood properties amongst themselves and some lesser convergence tapering to smaller diameters higher up the tree stem 6.
  • the large end diameter (LED) of each log may be taken at its wider end 8, while the small end diameter (SED) may be taken at the end 9 which is less wide due to taper.
  • Figure 2 shows the stiffness of boards cut from logs of a tree stem at different log positions of the tree, plotted for five different radial distances from the cross sectional centre of the tree stem.
  • the position of a log within the tree stem may be given by assigning to a butt log the log number 1, and the subsequent logs (2, 3, 4 etc) may be assigned corresponding log numbers according to their proximity to the butt log.
  • the log position in the tree stem may instead be expressed as a distance measurement.
  • a stand may encompass a group of trees within a defined geographic location, however typically stands are also defined to encompass trees with some of the same or similar physical characteristics. These result in stand characteristics which are indicative of the population of trees within the stand as a whole. For example, a stand may be defined to encompass a group of trees within a geographical boundary that are:
  • Figure 3 demonstrates the effect of tree spacing on the average mean diameter of the trees within a stand of the same species, there being a greater mean diameter for trees which are less densely stocked.
  • the method of the present invention may be used to derive logs of a specified wood quality from a stand of (preferably same species and same or similar age) trees but with a mix (as arises when there is growth variation amongst the trees of a stand) of diameters or other observable physical or dimensional characteristic(s).
  • a stand of preferably same species and same or similar age
  • a mix arises when there is growth variation amongst the trees of a stand
  • a trial was run to see whether, despite the growth variation in a stand of trees of the same species, logs with wood quality suitable for LVL veneer could be selected from the stand using a method according to some aspects of the present invention.
  • the log physical characteristic of particular interest was log diameter.
  • the small end diameter (SED) and large end diameter (LED) of each log was measured over what bark was remaining (generally very little bark was left on the logs).
  • the log position (e.g. log 1, log 2, log 3 etc) was also recorded.
  • logs were selected based on whether or not they were of a quality suitable for veneer.
  • an arbitrary desired average veneer stiffness greater than 9.246 kN/mm 2 (log supply target stiffness) was chosen. This corresponds to a batch of logs selected from within the trial sample and having HM200 acoustic velocity of greater than 3.1 km/s.
  • Physical characteristics such as LED and log position are characteristics which can be measured on site during harvesting.
  • the regression coefficients could be used (in conjunction with a processor/harvester to obtain real time, onsite measurements) as an input with log large end diameter (or large end diameter adjusted according to mean LED of the stand being harvested relative to mean LED of the trial stand) and log position for the assessment of stiffness of the logs from each stem, and to determine whether or not the logs meet the log supply target stiffness.
  • the regression equation derived above was used to predict the stiffness of each of the logs (as a processor head index), on the basis of LED and log position. Those logs with a predicted stiffness suitable to meet the log supply target of 3.1 km/sec were selected. The number of selected logs was recorded as the yield from the sample.
  • Such logs can be cut to any suitable length (eg 2.7 or 5.5 metres for LVL veneer as in this example).
  • Figure 3 shows growth variation between stands of the same species at two different locations: where at a first location, trees stocked at a density of 8000 stems/ha have an average diameter of 11 cm, whereas trees in a second location stocked at a density of 8000 stems/ha have an average diameter of 12.2 cm.
  • Figure 4 shows LED plotted against the end product MoE for the radiata pine trial stand in Nelson, and for another stand of radiata pine located on New Zealand's West Coast, with a regression line derived for each data set.
  • a log supply target stiffness of 10.1 GPa is shown by the line labelled 23. It can be seen that regardless of what physical measures (diameter) are chosen as a basis for selecting or segregating trees from the Nelson stand to meet the target stiffness, selecting or segregating trees of the same diameter from the West Coast stand will not give a batch of logs that meets the target stiffness.
  • the Nelson stand has a mean acoustic velocity of 3.24 km/sec (and can be characterised by this mean value), while the West Coast stand has a mean acoustic velocity of 2.46 km/sec (and can be characterised by this mean value).
  • regression lines for the Nelson and West Coast data sets we could generate regression lines for radiata pine stands with mean acoustic velocities intermediate of 3.24km/sec and 2.46 km/sec (or outside of these ranges by assuming a continuing data trend).
  • reference data may be stored as a library or collection containing data sets for a number of different stands, each characterised by its stand characteristics (e.g. age, species, location) and by a mean value which is an indicator of stiffness.
  • regression models could be employed.
  • the regression models are linear, and may be single or multivariable. It will be appreciated that in some cases a multivariable regression may give more accurate correlations from which to predict stiffness.
  • log physical characteristics used as inputs are chosen to be dimensional characteristics of the log which can be measured on site in real time (perhaps using the processing head of the harvester to take the measurements).
  • Logs from the first stand (stand A) had a mean acoustic velocity of 3.0 km/s and mean density of 0.46 kg/m 3 .
  • Logs from the second stand (stand B) had a mean acoustic velocity of 3.21 km/s and mean density of 0.48 kg/m 3 .
  • Logs from the third stand (stand C) had a mean acoustic velocity of 3.28 km/s and mean density of 0.49 kg/m 3 .
  • Figure 5 shows log diameter against stiffness (MoE) plotted for each log in each stand.
  • MoE stiffness
  • the mean stiffness value (for example as indicated by mean acoustic velocity, density, or some other measure) is used to categorise, characterise or rank the stand relative to the reference data sets, and an appropriate regression model is devised from the reference data taking the
  • the mean stiffness value is derived prior to harvesting from a sample of trees which are taken to be indicative of the stand.
  • the sampling may occur at a time prior to the harvest of the trees. For example, while stands will usually be clear felled, sampling may be of trees that have been removed from an original periphery of the stand at some stage earlier (for example, by track clearing or the like).
  • Obtaining a mean value for stiffness can be done in various ways including :
  • acoustic velocity can be obtained by using a HITMANTM ST300 standing tree tool, a HITMANTM HM200 log tool, or other time-of-flight or resonance device, or a bending stress test can be carried out on a sample from the stand).
  • an attempt to better characterise the mean average value of the stand may be ongoing as the stand is processed.
  • an indicator of stiffness may be measured as stems are cut (for example using probes on the harvester head for time-of-flight based acoustic measurement). This measurement is then fed into the calculation of an adjusted stiffness value for the stand which takes into account the acoustic velocity measurements from previously cut stems (i.e. a rolling average).
  • the adjusted value for stand stiffness is used to refresh or recalculate the regression model accordingly, and the adjusted regression model is used for predicting the stiffness of subsequent logs.
  • a harvester 10 with a head 11, for example as shown in Figure 2 can be used to cut the stem 6 to derive logs.
  • the head 11 may have a saw 12 for cutting, optionally one or more probes 13 (hydraulically or otherwise actuated) which may be used for measuring characteristics of the log, and one or more sensors 14 for obtaining information.
  • the sensors 14 may be part of, or separate from the probe 13.
  • FIG. 7 An example of a suitable processor head 11 is shown in plan view in Figure 7, wherein the head has a an articulable arm 25 shown at two limits of its preferred movement with respect to a specific tree stem, such articulation being operable under the action of a hydraulic ram.
  • the arm 25 can embrace the tree stem to be felled, and in doing so can obtain measurements of the dimensional characteristics of the tree (for example its diameter).
  • the head 11 may have associated software for processing the predicted MoE (Phi) of the stem from the information measured/obtained by the head, and which may optionally reference stored data (stored at the head 11 or elsewhere on the harvester 10 or remotely).
  • the software should also incorporate the previously obtained indication of the mean stiffness of logs in the stand to be felled.
  • There may be input means, for example to permit an operator to manually enter at least some of the values needed for processing.
  • Head 11 clamps tree or stem (eg at lower end of butt log)
  • the probe output may contribute to a
  • Log grade (structural or non-structural) and audible output indicated in cab 15. Operator confirms log making decision (structural or non-structural) for log to be cut

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Abstract

La présente invention concerne un procédé d'évaluation de grumes à des fins d'utilisation en fonction de la qualité du bois, lesdites grumes devant être obtenues d'un peuplement éligible d'arbres, ledit procédé comprenant les étapes consistant à attribuer une valeur moyenne au peuplement d'arbres qui constitue un indicateur de rigidité de grumes susceptibles d'être prélevées ; comparer la valeur moyenne à des données de référence afin de dériver, pour ladite valeur moyenne attribuée, un modèle de régression associant un indicateur de rigidité de grumes à au moins une caractéristique physique de grumes ; et utiliser le modèle de régression pour évaluer le caractère approprié à une utilisation en fonction de la qualité du bois de chaque grume dérivée, ou à dériver, à partir du peuplement en référence à ladite au moins une caractéristique physique de ladite grume.
PCT/IB2015/058727 2014-11-12 2015-11-12 Évaluation d'arbres et de branches d'arbres et/ou de grumes WO2016075641A1 (fr)

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Publication number Priority date Publication date Assignee Title
CN106069585A (zh) * 2016-06-22 2016-11-09 山东省林业科学研究院 一种山丘林的景观提升方法
WO2020014719A1 (fr) * 2018-07-16 2020-01-23 Umweltdata G.M.B.H. Dispositif et procédé de récolte sélective de bois
WO2021026263A1 (fr) * 2019-08-05 2021-02-11 Innerview Technologies Limited Traitement mis en oeuvre par ordinateur pour l'évaluation non destructive d'un échantillon de bois
CN114092765A (zh) * 2021-11-24 2022-02-25 北京明略软件系统有限公司 一种木材质量检测方法、装置、电子设备及存储介质

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SE521560C2 (sv) * 1997-07-04 2003-11-11 Soedra Cell Tofte As Förfarande vid kvalitetssortering av trävirke och användning av förfarandet
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Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106069585A (zh) * 2016-06-22 2016-11-09 山东省林业科学研究院 一种山丘林的景观提升方法
WO2020014719A1 (fr) * 2018-07-16 2020-01-23 Umweltdata G.M.B.H. Dispositif et procédé de récolte sélective de bois
WO2021026263A1 (fr) * 2019-08-05 2021-02-11 Innerview Technologies Limited Traitement mis en oeuvre par ordinateur pour l'évaluation non destructive d'un échantillon de bois
US11619610B2 (en) 2019-08-05 2023-04-04 Volt Holdings Limited Computer-implemented processing for non-destructive evaluation of wooden specimen
CN114092765A (zh) * 2021-11-24 2022-02-25 北京明略软件系统有限公司 一种木材质量检测方法、装置、电子设备及存储介质

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