Ijciet 10 01_190-2-3-4

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International Journal of Civil Engineering and Technology (IJCIET)
Volume 10, Issue 01, January 2019, pp. 2104-2123, Article ID: IJCIET_10_01_190
Available online at http://www.iaeme.com/ijciet/issues.asp?JType=IJCIET&VType=10&IType=01
ISSN Print: 0976-6308 and ISSN Online: 0976-6316
© IAEME Publication Scopus Indexed
NON-DESTRUCTIVE TESTING OF INTERNAL
STRUCTURE OF THE LOW-QUALITY WOOD
Igor Grigorev*
Doctor of Technical Sciences, Professor, Department of Technology and Equipment of Forest
Complex, Yakut State Agricultural Academy, 677007, Sergelyakhskoye highway, 3rd km,
house 3, Yakutsk, Russian Federation
Ivan Frolov
Applicant, Department of Forest Industry, Metrology, Standardization and Certification,
Federal State Budget Educational Institution of Higher Education "Voronezh State University
of Forestry and Technologies named after G. F. Morozov", 394087, Timiryazev street, house
8, Voronezh, Russian Federation
Ol'ga Kunickaya
Doctor of Technical Sciences, Professor, Department of Technology and Equipment of Forest
Complex, Yakut State Agricultural Academy, 677007, Sergelyakhskoye highway, 3rd km,
house 3, Yakutsk, Russian Federation
Olga Burmistrova
Doctor of Technical Sciences, Professor, Department Technology and Harvesting Machines,
Ukhta State Technical University, 169300, Pervomaiskaya 13, Ukhta, Republic of Komi,
Russia
Andrei Manukovskii
Doctor of Technical Sciences, Professor, Department of Industrial Transport, Construction
and Geodesy, University Federal State Budget Educational Institution of Higher Education
"Voronezh State University of Forestry and Technologies named after G. F. Morozov",
394087, Timiryazev Street, house 8, Voronezh, Russian Federation
Edward Hertz
Doctor of Engineering, Professor, Department of Technologies and Equipment of Timber
Industry, Ural State Forest Engineering University, 620100, Sibirskiy trakt, 37,
Yekaterinburg, Russian Federation

Igor Grigorev, Ivan Frolov, Ol'ga Kunickaya, Olga Burmistrova, Andrei Manukovskii, Edward
Hertz, Oscar Mueller, Lyudmila Kremleva, Svetlana Protasova and Ekaterina Mikhaylenko
Oscar Mueller
Doctor of Technical Sciences, Professor, Department of Ocean Technology and Power
Machines, Northern (Arctic) Federal University named after MV Lomonosov, 164500,
Captain Voronin Street, Severodvinsk, Arkhangelsk region, Russian Federation
Lyudmila Kremleva
Doctor of Technical Sciences, Professor, Department of Designing of Lifting-Transport and
Process Equipment, Northern (Arctic) Federal University named after MV Lomonosov,
164500, Captain Voronin Street, Severodvinsk, Arkhangelsk region, Russian Federation
Svetlana Protasova
Candidate of Technical Sciences, Assistant Professor, Department of Designing of Lifting-
Transport and Process Equipment, Northern (Arctic) Federal University named after MV
Lomonosov, 164500, Captain Voronin Street, Severodvinsk, Arkhangelsk region, Russian
Federation
Ekaterina Mikhaylenko
Candidate of Engineering Sciences, Assistant Professor, Ukhta State Technical University,
169300, 13 Pervomayskaya St., Ukhta, Republic of Komi, Russian Federation
*Corresponding author
ABSTRACT
Radiographic non-destructive examination of the round timber became a popular
technique in the middle of the twentieth century when radiography was first applied to
study the structure of materials.
The X-ray television testing equipment is widely used in non-destructive inspection
for a long time, but up to now, this equipment was not applied to find the heartwood rot
in wood sticks of any diameter.
This article analyzes the innovative method of non-destructive testing of low-quality
wood, which was performed using the portable X-ray television testing system.
Furthermore, it provides positive results of experimental investigations. In addition,
this article describes possibility of taking quality images of the internal structure of
wood, as well as possibility of the automated image processing.
Key words: low-quality wood, heartwood rot, X-ray television testing equipment,
non-destructive testing.
Cite this Article: Igor Grigorev, Ivan Frolov, Ol'ga Kunickaya, Olga Burmistrova,
Andrei Manukovskii, Edward Hertz, Oscar Mueller, Lyudmila Kremleva, Svetlana
Protasova and Ekaterina Mikhaylenko, Non-Destructive Testing of Internal Structure
of the Low-Quality Wood, International Journal of Civil Engineering and Technology,
10(01), 2019, pp. 2104–2123
http://www.iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=10&IType=01
1. INTRODUCTION
Low-quality wood (or junk wood) term is meant as the full-length logs and their sections, which
do not comply with the requirements of the standard on the commercial wood assortment [1].

Non-Destructive Testing of Internal Structure of the Low-Quality Wood
In addition, "low-quality wood" term is applied in respect of the round timber sticks,
including those full-length logs, which do not comply with the requirements of the standards
or technical conditions concerning commercial wood in respect of their quality parameters or
dimensional characteristics, but which can be used for manufacture of the commercial wood
assortments with the help of additional treatment or processing (for example, with the purpose
of manufacture of pulping and chipable chips). Druxiness is the most commonly encountered
flaw in the wood, in accordance with which a wood raw material is treated as the low-quality
wood [2].
Upon attainment of the exploitable age, the soft-wooded broadleaved species are frequently
suffered to druxiness due to their biological characteristic properties [3]. In addition, the wood
of the soft-wooded broadleaved species (that is to say, the coarse-grained wood) is frequently
treated as the low-quality wood due to bad mechanical-and-physical properties of these species.
The soft-wooded broadleaved species are the leafy wood species, which are characterised by
small density of the wood. It is common practice to treat quaking aspen, alder, silver birch, and
white birch as the coarse-grained species [4].
Content of the heartwood rot within the coarse-grained wood can exceed 50% of the total
volume of wood. Therefore, utilisation of such wood can be profitable if only such wood will
be processed in accordance with an automated and highly efficient process [5].
Utilisation of the coarse-grained (low-quality) wood will help to decrease intensity and
temps of logging of the coniferous species. Technological schemes of majority of the wood
processing enterprises are already obsolescent ones, because of only external flaws in the wood
are taken into account in the course of crosscutting of wood in the majority of cases (and these
flaws are visually assessable by operators in the course of cutting), while internal flaws in the
wood to be processed are not assessed [6].
Utilisation of the internal non-destructive testing on the basis of various non-destructive
methods [7, 8], including both the X-ray television equipment and acoustic methods [9, 10,
11], will make it possible to increase quality of the output products, as well as to ensure use of
automatic machines in the course of the non-destructive testing, sorting and crosscutting of the
round timber trunk. No less important is the protection of personnel from harmful factors of
production. Wood dust is one of the major hazards in the woodworking industry. Wood dust
from wood processing is a suspension with inclusions of abrasive powder with an average
particle size of 250 microns. The content of abrasive material in wood dust can be up to 1% by
weight. [12]. currently, there are many technologies that contribute to the reduction of dusting
in wood processing, but we believe that information about the quality of raw wood will allow
planning the processing rationally. This, in turn, will reduce the number of unproductive
operations, and thereby the dust pollution in the workshops.
Modern approaches to automation of the main technological operations in the course of
processing of the round timber trunk are based on utilisation of various methods and facilities
for recognition of patterns, as well as on performance of the magnetic resonance imaging [13,
14]. However, up to now there are no articles, which are dedicated to substantiation of the
optimum method of recognition of patterns of the image, which was obtained with the help of
the X-ray television equipment, with respect to problems of assessment of the round timber
trunk with the purpose of increase of the wood raw material quality, for example, for
transformation of the round timber trunk into the chipped wood.
Engagement of a man/operator in the course of revealing the internal and external flaws in
the wood creates complexities in respect of management of the technological process. If it is
necessary to make changes in the technological process or in the plan of the products output,

then (as practice shows), operator cannot quickly change his /her methods of work, and he/she
begins to make mistakes [15].
In accordance with the performed investigations (with the purpose of automation of the
round timber trunk barking [16]), rationality of utilisation of Otsu's method with the purpose
of revealing of the percentage ratio of the patterns, which were obtained in accordance with the
relevant image, was confirmed and proved.
Low manufacturability of these processes can result in sufficient losses. Having necessary
facilities and computing devices, an enterprise feels deficit in investigations and in elaboration
of the mathematical support of the high-technology solutions and complexes, which make it
possible to prevent a number of the above-listed losses at the earliest stages of production.
Performance of the non-destructive testing of the internal flaws in the wood in conjunction
with scanning of geometrical arrangements of full-length logs, as well as in combination with
automation of the line for production of the pulping and chipable chips from the low-quality
wood will help to decrease expenditures for energy resources and reduce the processing chain.
In addition, with the help of the portable X-ray television complex it would be possible to
decrease expenditures for transportation of the round timber trunk, which contain druxiness
[17, 21, 22].
2. MATERIALS AND METHODS
Main difficulties in the course of making the automated decision concerning inclusion of the
raw materials to one or another class of quality are connected with processing of the digital
image, which is obtained with the help of the X-ray television equipment. Within the
framework of solving this problem, relevant facility is adjusted in such a manner in order to
ensure that defect areas would seem darker than the commercial wood. Process of finding the
percentage ratio content of the druxiness in the wood on the basis of the image, which was
obtained with the help of the X-ray television equipment, includes several stages: separation of
the background from the investigation object, binarisation of the relevant image, segmentation,
calculation of the percentage ratio, and inclusion of the raw materials to one or another class.
It is worth to note that in our case development of the graphical and analytical model with the
purpose of revealing the pattern of the heartwood rot is reduced to incorporating this grapho-
analytical model into the problem that is to be solved.
Method of presentation of the digital image as the unoriented graph appears to be the most
successful one.
If one would present an image as the function img=I(x,y),x ∈ [0;W], while y ∈ [0;H], where
W is the image width and H is the image height, then the graphical and analytical model (graph
model) for this image will be presented as the unoriented graph:
( ) { } { }1 2, , , , 1 , 2 1 ,i iG V E V v E e i W H i K= = = ∈ × ∈ …
(1)
Where W is the image width, H is the image height, V is the multitude of edges of this
graph, and E is the multitude of nodes of this graph.
Pixels of the original image are used as the nodes of the graphical and analytical model.
Edges of the graph present connection of pixels between each other. Formula for construction
of the graph from the original image would be presented as follows:
( ) ( ) ( ) ( ){ }, , 1 , , , ,k i j k i j k k rP x y img k WxH G V P x y E P P +∀ ∈ = … = ∪ ∪
Where: x, y – coordinates of the pixel Pk, i= 1…W, j=1…H.

First and foremost, it is necessary to introduce a number of the special notions, with the
help of which it would be possible to describe process of analysis of the image of the wood
dimension part, which has the heartwood druxiness.
Definition 1. Colour of the graph node is the colour of the image pixel, which corresponds
to the relevant node.
Definition 2. We will call the node that represents the pixel, brightness of which is equal to
zero (of black colour), as the zero node
( )n
subG G G ,= ×
Where n is the enumeration definition of a colour.
Definition 3. Segmentation of the graph in respect of its colour characteristics is separation
of the subgraph, which combines the nodes of the prescribed colour.
Definition 4. We will call the node, which represents the pixel of the original image with
the highest value of brightness, as the graph maximum
( ) ( )max max .G V=
Taking into account definition for V in the formula (1).
Definition 5. We will call the operation, result of which will be the product of the brightness
values of those pixels, which are represented in the relevant nodes, as multiplication of nodes.
Definition 6. Mask is the graph, colour of nodes of which only takes on values of the black
colour (brightness 0) or white colour (brightness 1).
Definition 7. Segmentation in accordance with mask is matching the mask upon an arbitrary
colour graph of the same configuration provided that colour of nodes of the resulting graph is
defined as the result of multiplication of the nodes on the relevant positions.
.G G B′ = ×
Definition 8. We will call the operation, which will cause change in the value of the node
brightness into the reciprocal value, as the invert conversion of the node. In these cases, we
will treat the figure of one as the reciprocal value for the zero values, and we will treat the
number zero as the reciprocal value for the nonzero values.
( )
1 0
inv e
0 0.
e
e
=
= 
>
Definition 9. We will call the invert conversion operation of all nodes of the colour graph
as the invert conversion. It is worth to note that the idempotency condition is not fulfilled for
this operation, and it is only applicable in the case of searching the mask for its utilisation in
future.
( )( )
( )( )
B inv G
G inv B .
=
≠
Definition 10. We will call the operation, which causes replacement of all nodes of the first
graph, which have the zero brightness, by the nonzero nodes of the second graph, if such nodes
would be found on the relevant positions, as the combination of colour graphs.
( ) ( )1 3 (2)
1 2 3, , 0:i i iG G G i W H v v v= ∀ ∈ × = =∪
where W is the image width, H is the image height, vn is the node of the graph Gn.

3. RESULTS AND DISCUSSION
Problem of performance of the high-quality segmentation is in direct dependence on the image
preparation to the subsequent processing. There are several stages of preparation of a
photograph to the binarisation. In the cases, where there are any other objects on the photograph
in addition to the object under investigation, it is necessary to separate background from the
object. In our case, it is possible to do this operation with the help of one of the binarisation
methods, for example, with the help of the threshold processing method, because of interface
of the relevant programme separates the background from the object in accordance with their
colours. Example of such image is presented in Fig. 1.
a)
b)
Figure 1. X-ray photograph of the timber stock, which includes the heartwood druxiness and which is
already prepared to segmentation and to binarisation:
a) image, which requires preparation to binarisation; b) the same image following binarisation.
In our case, binarisation of image is performed in accordance with the Otsu's method, and
such binarisation is the necessary part of the work, which makes it possible to reveal patterns
of the heartwood rot. Binarisation is necessary in order to ensure simplification of the machined
processing of an image. As a rule, the zones of the heartwood rot, in which we are interested
in, are situated near edges of the timber stock or these zones have distinct differences in respect
of their values of brightness. Therefore, the main problem is connected with performance of
the high-quality segmentation and binarisation. Segmentation is the process of division of an
image by many pixels. Binarisation is the process of assignment of the relevant colour to each
segment depending on definition of brightness: this colour is assigned as the black colour or
the white colour and it is used as the condition of the brightness threshold. In our case, this
brightness threshold is determined in accordance with the Otsu's method.

In accordance with results of the relevant investigations [18, 19, 20], the brightness
threshold, which is determined in accordance with the Otsu's method, is the variable value that
is defined within the limits from 0.5 to 1.5t*.
In order to separate multitude of nodes of the graph by two classes (black and white), we
will use the method of revealing the threshold in accordance with the Otsu's method. The
resulting graph BG0 (binary graph) makes it possible to separate the object from the
background in the image.
2. Having performed segmentation of the original graph CG0 with the help of the mask,
which was found at the previous stage:
0 1 1,CG BG CG× =
we will obtain the desired object in the image along with the uniform (black) background.
3. Let us construct the temporary graph TG0, which would be the same as the original graph
(CG0) in respect of its dimensionality and configuration. Then we will define maximum of the
graph CG1 with the help of values of all nodes:
{ }0 1): max( ,iTG i W H v CG= ∀ ∈ × =
where W is the image width, H is the image height, and vi is a component of the graph.
4. Let us perform segmentation of the graph TG0 with the help of the mask, which was
found at the previous stage. We will obtain the following graph
( )1 1 0 .TG TG inv BG= ×
5. Having combined graph TG1 and graph CG1. We will obtain the original object along
with the uniform nonzero background:
2 1 1.CG TG CG= ∪
Necessity of such construction will be shown below.
6. Let us repeat paragraph 1 for graph CG2. Then it would be possible to separate the
darkened edges of the image, which were obtained as the result of specific features of the X-
ray snap shooting the dimension part. In the cases, where the nodes, which represent pixels of
the image background, would stay zero ones, we could not use the repeated threshold
binarisation.
7. Let us repeat paragraphs 5–7 for graph CG2 in order to ensure complete separation of the
non-informative section of the image. Then we will obtain mask BG1 and graph CG3.
8. Let us repeat paragraph 1 for graph CG3, then we will obtain graph BG1, which can be
segmented in respect of its colour characteristics and therefore we can separate the desired area,
which is potentially defective one:
( )0
1 0BG G UG× = .
1. In order to assess the obtained result, we will use the obtained graphs BG1 (for
calculation of the object area) and BG2 (for calculation of the potentially defective area).
2. Let us segmentize graph BG1 in respect of its colour characteristics (white) and we will
obtain quantity of nodes с1, which are present within the resulting area.
3. Let us segmentize graph BG2 in respect of its colour characteristics (black) and we will
obtain quantity of nodes с2, which exist within the resulting area.
4. Taking into account relevant operations (which were performed before construction of
the graph BG2), as well as taking into account noises of the original image, it is necessary to

make adjustments to the obtained results. The performed experiments have shown that in order
to ensure restoration of the objective pattern, it is necessary to introduce special coefficient of
correction CK of the revealed area. This coefficient is the computed one and it is calculated as
follows:
=
×
= ,
= ×
Necessity of introduction of the correction coefficient CK is connected with the fact that
the rotten section of the wood is adjacent to the section of the wood, which can be used as the
commercial wood, but this part of the wood is of low quality as well.
As the result, the formula for calculation of percentage of the darkened area of image will
be presented as follows:
О % =
× ×
!
,
where С2 – quantity of the nodes within the area of the object to be processed; С1 – quantity
of the nodes within the potentially defective area; CK – special coefficient of correction of the
darkened edges within the image.
The authors have developed the programme for implementation of the above-described
algorithm. They have also developed the mathematical model taking into account the Otsu's
method in respect of the brightness thresholds from 0.5t to 1.5t. See below the images, which
were obtained in the course of implementation of the above-mentioned programme in
accordance with the Otsu's method.
Table 1. Image of the druxiness and results of the image processing
Original

edges_cut
Now we are cutting the
edges
Final version of the image
Otsu's method
Table 2. Implementation of the programme within the round timber sticks without druxiness
Original
edges_cut
Now we are cutting the
edges

Final version of the
image
Otsu's method
As concerns images of the Table 1, the area, which was separated by the programme,
coincides with the existing area of the druxiness practically completely. Lines of the darker
colour near edges of the timber stock within these images are included into the CK coefficient
as well, because of the programme accepts these lines as a part of the druxiness, while they are
not the druxiness lines. Lines of the darker colour exist in the course of implementation of the
programme (cutting of edges). In the course of revealing the druxiness area, these lines make
it possible to perform processing of the image with the higher quality, because of diapason of
comparison of the thresholds is decreased along with decrease of dimensions of the dimension
part.
You can see absence of the heartwood rot within the images of the Table 2. At the same
time, this programme ensures processing of images of the wood, within which there is no the
heartwood druxiness.
Taking into account the fact that the darkened areas can represent the commercial wood as
well (particularly, more dense core of the wood) and confirm availability of knots, it is
necessary to determine boundaries of assessment of the obtained percentage ratio of the darker
sections in respect to the visible area of the entire object.
Problems of experimental investigations included checks of the developed algorithms for
assessment of content of the druxiness in the round timber sticks. Special experiments have
been made in order to confirm reasonableness of selection of the non-destructive testing
method in order to increase efficiency of processing of the low-quality wood with the help of
automation of the main technological operations. The following timber stocks were selected
for these experiments: patterns of the coarse-grained of wood, which have included the internal
druxiness and which were logged within the same wood cutting-area at the same time.
Essence of these experiments was as follows. A digital photo camera was used in order to
take photographs of images of the logged patterns of wood, which were obtained with the help
of the X-ray television equipment. Then proper graphic files have been downloaded into
computer and processed in accordance with the above-described algorithms.
Later on, images of the timber stocks have been separated from the background, and
fragments of these photographs have been processed with the help of the mathematical grapho-
analytical model, as well as with the help of the special programme (which was implemented
on the basis of this model) in accordance with the Otsu's method within the brightness
thresholds from 0.5t to 1.5t.
Results of processing these images have been compared with the natural measurements of
the druxiness. These measurements have been performed in accordance with the following
method: firstly, diameters of the druxiness from the sawn timber ends were measured, then
volume of the druxiness cylinder and volume of the entire dimension part were calculated,
because of these diameters were practically equal to each other. Then the dimension parts were
cut, and the authors have been determined availability of druxiness within these timber stocks,

as well as have been compared contours of druxiness in the images with the actual boundaries
of druxiness in the timber stocks.
In the course of processing of these experimental data, methods of the statistical analysis
have been used.
Results of assessment of the heartwood rot in the round timber sticks on the basis of the
photographs, which were obtained with the help of the X-ray television equipment, as well as
results of comparison of these assessments with the data of these experiments, have shown that
depending on the selected threshold of separation, the Otsu's method provides both the greater,
and the lesser assessments as compared with the experimental data. In this case, if the threshold
"t" is given in accordance with the Otsu's method, then these values will be close to the
experimental data (Fig. 2.)
Figure 2. Comparison of results of theoretical assessment of the percentage ratio of the heartwood rot
in the timber stocks in accordance with the Otsu's method (t) with the experimental values

Figure 3. Comparison of results of theoretical assessment of the percentage ratio of the heartwood rot
in the timber stocks in accordance with the Otsu's method with the experimental values
1), As it is shown in Figure 1, the closest values in respect of the computed values of the
percentage content of the heartwood rot were achieved at the selected "t" value of the brightness
threshold. Difference in the percentage content is equal to 4.49% on the average.
2) In accordance with Figure 3, it is possible to separate two zones of logging the timber
stocks – with and without the heartwood druxiness. These timber stocks have been compared
experimentally, because of the programme has been shown availability of not less than 30% of
the druxiness for those timber stocks, which had no the heartwood rot: this programme has
tried to separate other possible defects in the wood (such as knots, foreign deposits etc.) as the
druxiness. Therefore, the following categories were defined with the help of experiments:
1. The darkened areas occupy from 0% to 25% of the dimension part: it is possible to think
that the wood does not contain the heartwood rot, but it can contain knots, foreign deposits,
and the denser core of wood; therefore, such wood is treated as the commercial wood.
2. The darkened areas occupy 25-50% of the dimension part: it is possible to think that the
wood contains the heartwood rot druxiness, which can be processed; such wood is treated as
the low-quality wood.
3. The darkened areas occupy more than 50% of the dimension part: it is possible to think
that this wood is the fireplace wood.
In order to ensure practical implementation of the obtained results, authors of this article
have developed technological schemes of processing the low-quality wood with the help of the
X-ray television equipment as the equipment, which is intended for the wood sorting and for
the non-destructive testing of wood. These technological schemes were developed for the lines
with production capacity at the levels of 250 thou. m3
/year, 500 thou. m3
/year, and 1000 thou.
m3
/year of the wood to be processed, in respect of various kinds of the output products: the

debarked and unbarked timber assortments, chipped wood, and the sawn wood products (Fig.
4–6).
Figure 4. Functional block diagram of the automated system of crosscutting the debarked full-length
logs with the heartwood druxiness

Figure 5. Functional block diagram of the rough cutting and crosscutting of the full-length logs with
the heartwood druxiness without preliminary debarking

Figure 6. Functional block diagram of the rough cutting and crosscutting of the full-length logs with
the internal flaws in the wood with the preliminary sorting
In addition, the authors have developed the alternative version of utilisation of the portable
X-ray television complex (hereinafter to be referred to as the PXTC) as the defectoscope, which
will be used for the work along with the harvester head. The harvester head is the working
component of the harvester, which is the special machine that ensures logging the round timber
sticks within the cutting area. There exist harvester heads of two kinds: harvester heads, which
are equipped with the feeding wheels, and pulse harvester heads. In our case, we will analyse
the pulse harvester heads (cyclic harvester heads). Difference between the harvester head,
which is equipped with the feeding wheels, and the pulse harvester head is connected with the
fact that usual harvester head performs feeding of the stem by the wheels, which are driven by

motors, while pulse harvester heads are driven by hydraulic cylinders. Both harvester heads
perform operations of tree cutting and felling, removal of limbs from trees, as well as
crosscutting operations. Selection of the proper variant is performed depending on the value of
the wood species, required production capacity, as well as on the power of the machine, which
is intended for installation of the harvester head.
Figure 7. Installation of the PXTC on the pulse harvester head:
1 – place for installation of the screen/detector; 2 – place for installation of the portable X-ray
device
Principle of operation of the harvester head is as follows: from the very beginning the
harvester head embraces the tree by its debranching knives, performs cutting down and felling,
then the harvester head moves its front knives with the help of the hydraulic cylinders, while
back knives will hold the tree. When front knives have been moved and cut branches and knots
in the course of this movement, then capture of the tree was performed and back knives move
in order to come in the contact with the front knives. Later on, another capture is performed
and this cycle is repeated. When the upper knife is moved, the lower knife is not moved, and
the PXTC performs relevant measurement. Diagram of obtaining the image is as follows.
Distance between the knives, between which the PXTC will be installed in the extended
position, is equal to 1,100 mm, screen of the device is capable to process 650 mm, and a certain
area would not be captured (length of this area is equal to 450 mm).

Figure 8. Diagram of the non-destructive testing of full-length logs with the help of the X-ray
television equipment:
1 – nonprocessed zone; 2 – beginning of the zone of processing; 3 – end of the zone of processing; 4 –
processed zone
In accordance with the proposed scheme of construction of the model of possible line of
the druxiness (Fig. 8), the straight line is constructed between the end points of the processed
zones. Diagram of construction of the line within the zones, which are not processed by the
PXTC is presented in Fig. 9.
Figure 9. Diagram of construction of the line between the nonprocessed zones:
1 – zone of the nonprocessed wood; 2 – zone, within which druxiness was not revealed in
accordance with the constructed diagram; 3 – beginning of the zone of the non-destructive
testing; 4 – end of the zone of the non-destructive testing; 5 – zone of the non-destructive
testing; 6 – the heartwood druxiness.
In accordance with the proposed model of definition of the pattern of the druxiness with
the help of PXTC, the nonprocessed zone between the constructed straight line and actual curve
of the druxiness is not very big; therefore, this zone will not be taken into account.

4. CONCLUSIONS
1. With the help of the X-ray television equipment, it is possible to reveal the
heartwood druxiness, as well as to ensure automated operation in the course
of sorting, crosscutting, and removal of the druxiness.
2. Results of investigation of the developed algorithm in the course of
processing the pattern with the heartwood druxiness demonstrate that this
algorithm makes it possible to estimate volume of the druxiness in the
round timber sticks with the help of the developed programme with
accuracy up to 4.5% in accordance with the Otsu's method and relevant
optimum threshold of brightness.
3. Comparison of results of theoretical and experimental investigations makes
it possible to state that the developed models of definition of the percentage
content of the heartwood rot in the round timber sticks are adequate and
relevant ones.
4. Results of the experiment confirm possibility of definition of the percentage
ratio of the heartwood rot in the round timber sticks with the help of the
proposed mathematical model and the developed programme, in
accordance with which the following classification is proposed:
5. 4.1) The darkened areas occupy from 0% to 25% of the dimension part. It
is possible to think that the wood does not contain the heartwood rot, but it
can contain knots, foreign deposits, and the denser core of wood; therefore,
such wood is treated as the commercial wood.
6. 4.2) The darkened areas occupy 25–50% of the dimension part. It is
possible to think that the wood contains the heartwood rot druxiness, which
can be processed; such wood is treated as the of low-quality wood.
7. 4.3) The darkened areas occupy more 50% of the dimension part. It is
possible to think that this wood is the fireplace wood.
8. Technical solutions, which were developed, make it possible to use the
portable X-ray television device that can be installed on the pulse harvester
head in order to ensure revealing the heartwood rot druxiness immediately
within the logging areas with the help of the developed programme for
revealing the heartwood rot druxiness.
9. Technical solutions, which were developed, make it possible to use the
proposed diagrams along with the developed programmes and the updated
X-ray television device in order to increase quality of processing the round
timber trunk, as well as to increase quality of their preparation for the
deeper processing.
REFERENCES
[1] Kunitskaia, O. A. Substantiation of directions of diversification of processing of the low-
quality commercial wood at the forest-industry complex enterprises with the help of
innovative technologies. Saint Petersburg: Saint Petersburg State Forest Technical
University, 2015, p. 250.
[2] Patiakin, V. I., Grigoriev, I. V., Redkin, A. K., Ivanov, V. A., Posharnikov, F. V.,
Shegelman, I. R., Shirnin, Yu. A., Katsadze, V. A., Valiazhonkov, V. D., Bit, Yu. A.,
Matrosov, A. V., Kunitskaia, O. A. Technology and machines for cutting area operations.
Textbook for institutions of higher education. Saint Petersburg State Forest Technical
University, 2012, p. 362.

[3] Beliaeva, N. V., Grigorieva, O. I. Dependence of the successful natural forest reproduction
on the summary projective cover of the forest live cover within the clear-cut harvesting
objects and the objects for pre-drying of the quaking aspen. Forests of the Russia in the
XXI century - materials of the first international scientific and practical Internet conference.
2009, p. 7-10.
[4] Beliaeva, N. V., Grigorieva, O. I. Characteristics of the state of the young growth following
the clear-cut harvesting and "ring-girdling" of the quaking aspen. Agrarian Scientific
Magazine. 11, 2009, p. 5-9.
[5] Kunitskaia, O. A. Resources of the low-quality commercial wood within the subjects of the
Russian Federation. Science, education, innovations within the region near the State
frontier: materials of the Republican scientific and practical conference. Petrozavodsk.
OOO Verso, 2015, p. 15-17.
[6] Kunitskaia, O. A., Tikhonov, I. I., Kunitskaia, D. E., Grigoriev, I. V., Zemtsovskiy, A. E.
Optimisation of the process of crosscutting of full-length logs within the reloading-and-
sorting bases of the forest holdings in the course of sawing the raw materials for the mast-
steeping plants. News of the Higher Educational Institutions. Forest Magazine, 3, 2014, p.
86-93.
[7] Frolov, I. S., Grigoriev, I. V., Tikhonov, I. I., Kukhareva, D. S. Rational cutting of full-
length logs with the great share of the non-standard timber. Actual problems of
development of the forest complex: materials of the International scientific and technical
conference. Ministry of Education and Science of the Russian Federation; Government of
the Vologda Region; Department of the Forest Complex of the Vologda Region; Vologda
State University. Vologda: VoSU, 2015, p. 92-94.
[8] Frolov, I. S., Grigoriev, I. V., Tikhonov, I. I., Kukhareva, D. S. System of assessment of
the round timber trunk quality. Actual problems of development of the forest complex:
materials of the International scientific and technical conference. Ministry of Education and
Science of the Russian Federation; Government of the Vologda Region; Department of the
Forest Complex of the Vologda Region; Vologda State University. Vologda: VoSU, 2015,
p. 94-96.
[9] Witold, D., Mańkowski, P., Krzosek, S. Theoretical And Practical Usefulness Of Radiation
Methods For Wood Density Testing. Folia Forestalia Polonica–Series B 39, 2008, p. 31-
43.
[10] 8. Branco, J. M., Piazza, M., Cruz, P. J. Structural analysis of two King-post timber trusses:
Non-destructive evaluation and load-carrying tests. Construction and Building Materials,
24(3), 2010, p. 371-383
[11] Dzbeński, W., Wiktorski, T. Ultrasonic evaluation of mechanical properties of wood in
standing trees. In COST E 53 conference—quality control for wood and wood products,
Warsaw. 2007, p. 15-17.
[12] Kovshov, S., Nikulin, A., Kovshov, V., & Mracková, E. Application of equipment for
aerological researching of characteristics of wood dust. Acta Facultatis Xylologiae Zvolen
res Publica Slovaca, 57(1), 2015, p. 111.
[13] Lin, C. J., Kao, Y. C., Lin, T. T., Tsai, M. J., Wang, S. Y., Lin, L. D., Chan, M. H.
Application of an ultrasonic tomographic technique for detecting defects in standing trees.
International Biodeterioration & Biodegradation, 62(4), 2008, p. 434-441.
[14] Van Dyk, H., Rice, R. W. Ultrasonic wave velocity as a moisture indicator in frozen and
unfrozen lumber. Forest products journal, 55(6), 2005, p. 68.
[15] Grigoriev, I. V., Kunitskaia, O. A., Kunitskaia, D. E. Substantiation of the method for
recognition of the bark spots on the pulpwood with the purpose of automatic sorting in
accordance with the barking quality. Reference Book. Engineer Magazine along with
Appendix. 6(243), 2017, p. 43-45.

[16] Grigoriev, I. V., Kunitskaia, D. E., Kunitskaia, O. A., Lanskikh, Yu. V. Automation of
assessment of quality of the round timber debarking in the debarking drums. In the collected
book: Actual problems and prospects of development of the forest-industry complex.
Collection of scientific papers of the III International scientific and technical conference.
Federal State Budgetary Educational Institution of Higher Professional Education
"Kostroma State Technological University". 2015. p. 132-135.
[17] Grigoriev, I. V., Kunitskaia, D. E. 'Decrease of quantity of the waste of the main production
of the wood preparation yards due to automation of the main operations. Actual directions
of scientific investigations in the XXI century: theory and practice. 3(2-2), 2015, p. 13-2.
p. 409-412.
[18] Grigoriev, I. V., Kunitskaia, D. E. Model of recognition of the debarked pulpwood with the
help of the digital photograph. Actual directions of scientific investigations in the XXI
century: theory and practice. 3(5-4), 2015, p. 283-287.
[19] Grigoriev, I. V. Prospects of development of the forest utilization and engineering in the
Saint Petersburg State Forest Technical University. In the collected book: "Forests of the
Russia in the XXI century: Collection of scientific papers according to the conclusions of
the international scientific and practical Internet conference. 2015, p. 3-8.
[20] Grigoriev, I. V., Kunitskaia, D. E. Binarisation of image of the debarked pulpwood. In the
collected book: Forests of the Russia: policy, industry, science, and education - materials
of the scientific and technical conference. Saint Petersburg: Saint Petersburg State Forest
Technical University: 2016, p. 109-112.
[21] Gomez, H. F., Lozada, E. F., Martínez, C. E., Baño, F. P., Álvarez, G. A., Culque, W. V.,
. . . Cevallos, R. E. S. (2018). Introduction to the Analysis of Tourism Services through
Feelings Mining. Journal of Information Systems Engineering & Management, 3(4), 33.
[22] Maginga, T. J., Nordey, T., & Ally, M. (2018). Extension System for Improving the
Management of Vegetable Cropping Systems. Journal of Information Systems Engineering
& Management, 3(4), 29

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