Ранжування технічного стану повітряних суден за даними діагностування конструкції планера
Analysis of the data obtained through non-destructive testing of the power elements of the airframe structure enables the division of the studied aircraft into separate groups based on operational methods and, accordingly, predicts the probability of trouble-free operation of the airframe structure....
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The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute"
2025
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System research and information technologies| _version_ | 1867334447509012481 |
|---|---|
| author | Bolohin, Andrii Bolohina, Yuliya Tymchuk, Yurii |
| author_facet | Bolohin, Andrii Bolohina, Yuliya Tymchuk, Yurii |
| author_institution_txt_mv | [
{
"author": "Andrii Bolohin",
"institution": "State Research Institute of Aviation, Kyiv"
},
{
"author": "Yuliya Bolohina",
"institution": "State Research Institute of Aviation, Kyiv"
},
{
"author": "Yurii Tymchuk",
"institution": "4993rd Military Representation of the Ministry of Defense of Ukraine, Odesa"
}
] |
| author_sort | Bolohin, Andrii |
| baseUrl_str | http://journal.iasa.kpi.ua/oai |
| collection | OJS |
| datestamp_date | 2025-07-25T15:56:08Z |
| description | Analysis of the data obtained through non-destructive testing of the power elements of the airframe structure enables the division of the studied aircraft into separate groups based on operational methods and, accordingly, predicts the probability of trouble-free operation of the airframe structure. Based on a bionic logical analysis of data on the technical condition of the aircraft’s airframe design, the article considers methodological approaches to building the author’s mathematical model of ranking the aircraft fleet. The ranking of the technical condition of aircraft serves as the basis for solving the problem of preparation, making a decision on extending the service life and taking into account the aging of the airframe design in operating conditions. The application of the proposed set of methods will create and establish a practical and effective system of intelligent support for decision-making on aircraft operations. |
| doi_str_mv | 10.20535/SRIT.2308-8893.2025.2.06 |
| first_indexed | 2025-07-27T04:04:06Z |
| format | Article |
| fulltext |
Publisher IASA at the Igor Sikorsky Kyiv Polytechnic Institute, 2025
98 ISSN 1681–6048 System Research & Information Technologies, 2025, № 2
TIДC
МАТЕМАТИЧНІ МЕТОДИ, МОДЕЛІ,
ПРОБЛЕМИ І ТЕХНОЛОГІЇ ДОСЛІДЖЕННЯ
СКЛАДНИХ СИСТЕМ
UDC 623.7, 519.2
DOI: 10.20535/SRIT.2308-8893.2025.2.06
RANKING OF THE TECHNICAL CONDITION
OF AIRCRAFT ACCORDING TO THE DIAGNOSTIC
DATA OF THE GLIDER DESIGN
A. BOLOHIN, Yu. BOLOHINA, Yu. TYMCHUK
Abstract. Analysis of the data obtained through non-destructive testing of the power
elements of the airframe structure enables the division of the studied aircraft into
separate groups based on operational methods and, accordingly, predicts the prob-
ability of trouble-free operation of the airframe structure. Based on a bionic logical
analysis of data on the technical condition of the aircraft’s airframe design, the arti-
cle considers methodological approaches to building the author’s mathematical
model of ranking the aircraft fleet. The ranking of the technical condition of aircraft
serves as the basis for solving the problem of preparation, making a decision on ex-
tending the service life and taking into account the aging of the airframe design in
operating conditions. The application of the proposed set of methods will create and
establish a practical and effective system of intelligent support for decision-making
on aircraft operations.
Keywords: technical condition of the airframe, strength, operation of aircraft, con-
trol systems, decision-making.
INTRODUCTION
Digital systems with classical methods of management, which are mainly focused
on practice, except for the frequent productivity of micro-processing systems.
A significant increase in the efficiency of such systems can be reached by the im-
plementation of adaptive control algorithms. Adaptation of a living organization,
which is designed to change the internal and external minds, is an analogue for
the construction of the structures of technical systems with the establishment of
the system of control for the change of internal and external parameters up to the
criterion of regulation. Based on the classical methods of management, for the
implementation of an adaptive control system, the necessary visibility of the great
need for the analysis of the preliminary information for the skin-specific regula-
tor, to develop a mathematical model and an adequate algorithm for assessing the
parameters of the model, which is to add a folding problem for traditional ap-
proaches.
Fuzzy control is based on the rules formed by an expert who has some ex-
perience in a particular technical direction, and from the point of view of control
system technology, fuzzy control is a regulation with a nonlinear gear response.
Ranking of the technical condition of aircraft according to the diagnostic data of…
Системні дослідження та інформаційні технології, 2025, № 2 99
Thus, a management system based on fuzzy logic is not blind control using
one or another law of regulation, but management with a current analysis of the
situation and meaningful decision-making to issue a regulation signal, guided by
common sense, that is, the most adequate response to a comprehensively assessed
control error. These are minimal transients. This is high flexibility, reliability and
efficiency and simplification of control compared to adaptive and self-learning
control algorithms [1].
TASK STATEMENT
Management of the aircraft operation process requires the fulfillment of the con-
ditions for ensuring the required level of flight safety and involves the adoption of
organizational and technical decisions to maintain aircraft in good condition. The
resource and reliability of aircraft is largely determined by the technical condition
of the carrier elements (CE) of the airframe design. The results of the CE assess-
ment according to the control data allow distributing aircraft into separate groups
(classes), for which there are flight safety solutions obtained by performing
strength calculations and based on operational experience. In practice, the known
methods and algorithms for making decisions on the further operation of aircraft
are reduced to the problem of formal choice of an alternative [2].
When making decisions, three main tasks are solved:
ordering alternatives;
distribution of alternatives by classes of solutions;
highlighting a better alternative.
For example, such classes and, accordingly, solutions can be:
aircraft meet flight safety requirements and do not require additional res-
toration work;
it is necessary to carry out restoration work of various purposes and scope
(repair at aircraft repair enterprises, extension of the assigned service life, transfer
to operation according to technical condition, etc.);
further operation of the aircraft is inexpedient due to the loss of the neces-
sary operational characteristics of the CE of the airframe design.
The imperfection of the known methods of decision-making lies in the fact
that information about the technical condition of the aircraft is characterized by
the peculiarity of incompleteness and limited volumes of operational data, which
significantly affects the validity of decisions in the management of the aircraft
operation process.
Problematic issues of classification of aircraft into separate groups depend-
ing on the results of airframe control carried out in the conditions of operating
parts have not been studied in technical diagnostics. Therefore, there is a need to
develop methods for classifying aircraft that will increase the reliability of deci-
sions made by an official (decision-maker – hereinafter referred to as DM) for a
specific situation based on the results of control inspections of the airframe.
One of the directions for the development of methods for classifying air-
frame is the development of a mathematical model of bionic processing of ex-
perimental data, which simulates the mechanisms of functioning of biological sys-
tems and allows DM to understand the validity and expediency of various options
for decisions when making decisions.
A. Bolohin, Yu. Bolohina, Yu. Tymchuk
ISSN 1681–6048 System Research & Information Technologies, 2025, № 2 100
ANALYSIS OF RECENT RESEARCH AND PUBLICATIONS
Decision support systems are a qualitatively new level of automation of manage-
ment processes in various areas of human activity.
Thus, in the work [3], a classification model has been developed that is able
to accurately identify diseases and provide appropriate recommendations for pa-
tients. The proposed system uses a multi-level classification mechanism with ap-
propriate prediction of changes in the patient’s vital parameters.
In the process of operation of aviation equipment, as a result of control in-
spections, many values of parameters are determined that characterize and allow
to assess the strength of the aircraft airframe structure.
In geometric interpretation, the technical condition of the airframe can be
represented as a point in multidimensional space, the coordinate axes of which
correspond to the control parameters.
The mathematical model of such a description of the technical condition of
the airframe does not allow to provide the DM with the necessary data on the reg-
ularities of the airframe operation process in an accessible visual form, since it
does not take into account the peculiarities of the mechanisms of human informa-
tion processing.
The paper [4] shows that a person perceives the environment with the help of
an internal figurative representation, his imaginary model is aimed at analyzing
information by generalizing, identifying the dependence between its individual
parts, searching for associative connections with previously made decisions.
The internal model of DM is difficult to identify and formally describe the
transformations that are carried out when generalizing the acting factors and
forming images, transforming multidimensional data and obtaining estimates of
objects in a one-dimensional scale of values (from “minimum” to “maximum”,
from “bad” to “good”, etc.).
In the same work, it is noted that when processing control data with statisti-
cal methods of pattern recognition, intuitive and understandable judgments of
people about the trends in changing the parameters of the processes under study
are used, that is, there is a transition to one-dimensional scales. In the works on
psychology, the position that reveals the features of human processing of informa-
tion in the form of images is substantiated. This pattern allows you to develop the
structure of the bionic model, consisting of an interconnected set of modules that
take into account subjective aspects and allow you to simulate the processing of
information in the semantic image space of the subject area of the environment.
PRESENTATION OF THE MAIN MATERIAL
When solving the problems of monitoring the technical condition of the CE of the
airframe structure, the subject area consists of numerical and linguistic values of
the database on crack sizes, depth and area of corrosion, dimensions of deforma-
tion of the CE, coordinates of the damage site, normative data on tolerances, ser-
vice life, etc.
The use of identification procedures in the assessment of technical condition
allows you to evaluate parameters when their dimensionality is precisely known.
At the same time, the calculation of the difference between the reference and the
actual state, i.e. the performance of a comparison, is a necessary operation of the
process of localization of the technical state. In addition, the number of parame-
ters that characterize the technical condition is often unknown. Therefore, the dis-
Ranking of the technical condition of aircraft according to the diagnostic data of…
Системні дослідження та інформаційні технології, 2025, № 2 101
advantages of existing diagnostic technologies and decision-making systems in-
clude the need to form requirements for experimental information about dynamic
changes in the system, the use of which will allow classification and comparison
of possible technical states.
The structure of the bionic model, consisting of separate modules, shown in
Figure 1, uses the principles of vector information processing by a universal
mathematical model for biological systems, as well as the principles of logical
transformations of information performed by a person during the solution of intel-
lectual problems [5].
To solve the problems of classification of aircraft according to the data of
airframe parameter control, three vector spaces F1, F2, F3 are needed, the dimen-
sionality of which is determined by the number of parameters of the subject area
of control.
The first space F1 is created by estimates of the indicators of loss of strength
of the CE based on the data of visual and non-destructive testing means of each
individual CE, the results of computational and experimental studies of the
strength of the CE (Fig. 1).
Due to the incompleteness and limited volume of operational data, the re-
sults of assessments of CE strength loss indicators are characterized by the pres-
ence of intervals of uncertainty of values. In addition, the assessments contain
errors due to the subjective experience of a person working with control materials.
Therefore, final decisions on strength loss assessments require amendments and
adjustments.
Such clarifications can be carried out taking into account the use of psycho-
logical qualities of a person, use the criterion of approximate similarity of objects,
i.e. vague logical conclusions when searching for such objects. The work [6]
Airframe Control Database:
Logical analysis
of normative data
Fuzzy logical analysis of images of control
parameters of power elements СЕ
1 ,
СЕ
2 , …,
СЕ
N
Fuzzy logical analysis
of glider strength images
Cluster analysis of airframe
control data images
Determination of thresholds
for distribution into ranks
Solution options
Space F1
Space F2
Space F3
Ranking of the technical condition
of the airframe according to CE
Decision-maker
Crack Sizes;
CE deformation dimensions;
depth and area of corrosion;
coordinates of the place of damage;
regulatory data of the aircraft.
Fig. 1. Structure of the bionic model of data analysis
A. Bolohin, Yu. Bolohina, Yu. Tymchuk
ISSN 1681–6048 System Research & Information Technologies, 2025, № 2 102
shows that the property of fuzziness of logical thinking helps a person to solve
practical problems.
In the modules of the bionic model, which solve the problem of estimating
the indicators of loss of strength of CE, operators for processing fuzzy logical de-
pendencies based on the methods of fuzzy set theory are used [7]. Performing
a fuzzy analysis of the control results allows you to transform the multidimen-
sional description of the control data and move to a one-dimensional rating scale.
The model provides for the use of the second vector space F2, where, based on
the results of the control of individual CE, a generally fuzzy logical analysis of data
images of the technical condition of the entire airframe structure is performed.
Determination of cases in which the values of the strength factors go beyond
the tolerances is carried out using the methods of mathematical binary logic,
which uses logical operators for calculating predicates.
In the space F2 the property of a person to group and rank CE according to
control data is simulated. The dimension of the space F2 is determined by the
number N – the total number of CE.
The number of CE classes that are formed depends on the values of the
thresholds set by the DM. Therefore, the corresponding module of the bionic
model also uses the method of fuzzy information processing, which takes into
account the subjective representations of the DM.
The CE classification module uses an algorithm based on the principles of
taxonomy of objects described in the paper [7] and takes into account that a per-
son perceives the results of classification regardless of the geometric shape of the
class in the multidimensional space of features.
Space F3 takes into account additional information about the airframe opera-
tion process, it is here that the ranking of the technical condition and the prepara-
tion of draft decisions are carried out. The dimension of the space F3 is deter-
mined by the number of normative numerical data and estimates of linguistic
variables obtained by calculation when controlling the loss of strength.
Next, the construction of a mathematical model of the ranking of the techni-
cal condition based on a fuzzy logical analysis of the parameters of the glider con-
trol is considered.
In the module of fuzzy logical analysis of images of control parameters CE, a
linguistic variable is introduced fd = “difference in strength CE from the norm”.
The universal set of fd is the segment [0 1], and the set of values for fd is the term set
},,,,{ 54321 GGGGGG , where 1G — practically coincide; 2G — small difference;
3G — average difference; 4G — big difference; 5G — the maximum difference.
The number of discrete states of the term set G is chosen in accordance
with the ability of the human operator to simultaneously perform operations with
5... 7 objects that belong to different images.
As a function of belonging )( fd , the formula (1) of a trapezoidal fuzzy
number ),,,( 4321 aaaad f :
;if,0
;if))),(exp(exp()(
;if,1
;if))),(exp(exp()(
;if,0
)(
4
432
32
211
1
ad
adaCdd
ada
adaCdd
ad
d
f
fff
f
fff
f
f (1)
Ranking of the technical condition of aircraft according to the diagnostic data of…
Системні дослідження та інформаційні технології, 2025, № 2 103
where 21, СС — the displacement coefficients of the function (1) along the axis fd .
The sides of the trapezoid are formed on the basis of the functional dependence
))(exp(exp)( ff dd . (2)
The dependence (2) approximates the assessment of observations in various
subject areas of the experimenters’ real decisions on the admissibility of research
results. Dependence (2) has the beneficial properties of continuity, monotony, and
smoothness.
The value of the belonging function )( fd is perceived as a measure of the
truth of the term iG , which is established by experts in the subject area of aircraft
operation. Fig. 2 shows the distribution of belonging functions to the linguistic
variable fd .
To analyze the dependence of the distance fd on the parameters of the iv of
the first vector space 1F , a linguistic variable iB is introduced, which, by analogy
with the term set G , consists of the following terms:
1iB — very small difference between the parameters of iv ;
2iB — a slight difference between the parameters of iv ;
3iB — average level of difference in iv parameters;
4iB — a significant difference between iv parameters;
5iB — a very significant difference between iv parameters.
The volume of the database used during processing is determined by the el-
ements of the set },...,,{ 21 lvvvV , where the list of parameters iv ),...,1( li .
The number of parameters l is set by experts taking into account informal meth-
ods of describing the subject area.
It is also assumed that each linguistic variable is described by a trapezoidal
fuzzy number ),,,( 4321 aaaavi . Thus, a two-dimensional array of fuzzy linguis-
tic variables )5,...,1;,...,1( кliВiк is created.
df —
Fig. 2. Membership functions of subsets of the term set G
A. Bolohin, Yu. Bolohina, Yu. Tymchuk
ISSN 1681–6048 System Research & Information Technologies, 2025, № 2 104
To form the rules for the transition from the values of the parameters to the
values of the variable itself fd in accordance with [7], an approximation of fuzzy
logical inference rules is carried out using the formula
кfk
k
f dhd
5
1
,
where l
i lkk lh 1 )/1( characterizes the influence of each term of the linguistic
variable kG ;
kfd — is the middle of the interval on the axisfd , at which the
values of the term ),( 41 kkk aaG are non-zero.
The module of fuzzy logical analysis of glider strength images is built by
the method of designing and debugging fuzzy knowledge bases, which are sets of
linguistic or logical operators.
The logical formula for determining the value of the loss of strength the
airflame is built on the basis of the logical operator “TA” )( and thevalues of
the term set G of individual iCE ( Ni ,...,1 ):
fi
N
i
d
1
min
.
The module for ranking the technical condition of gliders by CE selects such
homogeneous subsets in the initial multidimensional data so that the objects with-
in the groups are similar in known content to each other and have the same di-
mension, and the objects from different groups are not similar.
The module uses an algorithm that provides for the construction of the short-
est open path between the vertices of the graph in the space 2F . The distance between
the vertices of the graph is calculated by the method of potential functions [8].
Mathematical models of 3F space modules are developed using methods
that are used in 2F space modules.
Effective application of the proposed mathematical model in the existing op-
eration system can be, for example, when determining the timing of periodic
maintenance. Thus, depending on the actual technical condition and the results of
ranking by power elements, the deadline for work may be postponed. For exam-
ple, for a specific aircraft, the technical condition of which is characterized by
such variables as 1G , 1iB , i.e. loss of CE strength, there is no deterioration of the
condition, the design is ranked as serviceable, the airframe meets the requirements
of flight safety and does not require additional restoration work, the DM in the
technical condition management system decided to increase the terms of perform-
ance of the relevant periodic work from 3 months to 6. This made it possible to
save and efficiently allocate the resources necessary for the technical support of
the operation process.
CONCLUSION
The application of the developed mathematical model for classifying the ranking
of the technical condition on the basis of bionic logical analysis of airframe con-
trol data as part of the mathematical support information systems for managing
Ranking of the technical condition of aircraft according to the diagnostic data of…
Системні дослідження та інформаційні технології, 2025, № 2 105
the technical condition of aircraft will improve the quality of organizational and
technical decisions made.
REFERENCES
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Institute of Electrodynamics of the National Academy of Sciences of Ukraine, 2011.
2. B.М. Herasimov, W.М. Lokazyuck, О.G. Оhsiyuck, О.W. Pomorova, Intelligent de-
cision support systems. K.: Publishing House of the European University, 2007.
3. Vedna Sharma, Surender Singh Samant, “A multi-level decision-making frame-work
for heart-related disease prediction and recommendation,” System Research and Informa-
tion Technologies, no. 4, 2023. doi: https://doi.org/10.20535/SRIT.2308-8893.2023.4.01
4. E.Yu. Barzylovych, M.V. Savenkov, Statistical methods of assessing the state of
aviation technology. M.: Transport, 1987.
5. Yu.P. Shabanov-Kushnarenko, Theory of intelligence: Mathematical tools. Kharkiv:
Higher school. Publishing House at Kharkiv University, 1984.
6. Fuzzy sets in models of control and artificial intelligence; Edited by D.A. Pospelova.
M.: Nauka, 1986.
7. L.K. Konysheva, D.M. Nazarov, Fundamentals of the theory of fuzzy sets: Tutorial.
St. Petersburg: Pіter, 2011.
8. M.A. Aizerman, E.M. Braverman, L.I. Rozonoer, The method of potential functions
in the theory of machine learning. M.: Science, 1970.
Received 05.04.2024
INFORMATION ON THE ARTICLE
Andrii S. Bolohin, ORCID: 0000-0003-0656-7799, State Research Institute of Aviation,
Ukraine, e-mail: bolas@ukr.net
Yuliya O. Bolohina, ORCID: 0009-0004-7251-7137, State Research Institute of Aviation,
Ukraine, e-mail: jbologina@ukr.net
Yurii M. Tymchuk, ORCID: 0009-0002-0425-1985, 4993rd Military Representation of
the Ministry of Defense of Ukraine, Ukraine, e-mail: timab-d1972@ukr.net
РАНЖУВАННЯ ТЕХНІЧНОГО СТАНУ ПОВІТРЯНИХ СУДЕН ЗА ДАНИМИ
ДІАГНОСТУВАННЯ КОНСТРУКЦІЇ ПЛАНЕРА / А.С. Бологін, Ю.О. Бологіна,
Ю.М. Тимчук
Анотація. Аналіз даних, які отримують за допомогою засобів неруйнівного
контролю силових елементів конструкції планера, дозволяє розподілити дослі-
джені повітряні судна на окремі групи залежно від методів експлуатації і, від-
повідно, прогнозувати ймовірність безвідмовної роботи подальшої експлуата-
ції конструкції планера. На основі біонічного логічного аналізу даних про
технічний стан конструкції планера літака розглянуто методичні підходи по-
будови авторської математичної моделі ранжування парку повітряних суден.
Ранжування технічного стану повітряних суден покладено в основу вирішення
завдання підготовки прийняття рішення про продовження терміну служби з
урахуванням старіння конструкції планера в умовах експлуатації. Застосуван-
ня запропонованого комплексу методів дозволить створити і налагодити дієву
та ефективну систему інтелектуального підтримання прийняття рішень про
експлуатацію повітряних суден.
Ключові слова: технічний стан планера, міцність, експлуатація літальних
апаратів, системи керування, прийняття рішень.
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| id | journaliasakpiua-article-320537 |
| institution | System research and information technologies |
| keywords_txt_mv | keywords |
| language | English |
| last_indexed | 2025-09-17T09:26:02Z |
| publishDate | 2025 |
| publisher | The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" |
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| spelling | journaliasakpiua-article-3205372025-07-25T15:56:08Z Ranking of the technical condition of aircraft according to the diagnostic data of the glider design Ранжування технічного стану повітряних суден за даними діагностування конструкції планера Bolohin, Andrii Bolohina, Yuliya Tymchuk, Yurii technical condition of the airframe strength operation of aircraft control systems decision-making технічний стан планера міцність експлуатація літальних апаратів системи керування прийняття рішень Analysis of the data obtained through non-destructive testing of the power elements of the airframe structure enables the division of the studied aircraft into separate groups based on operational methods and, accordingly, predicts the probability of trouble-free operation of the airframe structure. Based on a bionic logical analysis of data on the technical condition of the aircraft’s airframe design, the article considers methodological approaches to building the author’s mathematical model of ranking the aircraft fleet. The ranking of the technical condition of aircraft serves as the basis for solving the problem of preparation, making a decision on extending the service life and taking into account the aging of the airframe design in operating conditions. The application of the proposed set of methods will create and establish a practical and effective system of intelligent support for decision-making on aircraft operations. Аналіз даних, які отримують за допомогою засобів неруйнівного контролю силових елементів конструкції планера, дозволяє розподілити досліджені повітряні судна на окремі групи залежно від методів експлуатації і, відповідно, прогнозувати ймовірність безвідмовної роботи подальшої експлуатації конструкції планера. На основі біонічного логічного аналізу даних про технічний стан конструкції планера літака розглянуто методичні підходи побудови авторської математичної моделі ранжування парку повітряних суден. Ранжування технічного стану повітряних суден покладено в основу вирішення завдання підготовки прийняття рішення про продовження терміну служби з урахуванням старіння конструкції планера в умовах експлуатації. Застосування запропонованого комплексу методів дозволить створити і налагодити дієву та ефективну систему інтелектуального підтримання прийняття рішень про експлуатацію повітряних суден. The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" 2025-06-28 Article Article application/pdf https://journal.iasa.kpi.ua/article/view/320537 10.20535/SRIT.2308-8893.2025.2.06 System research and information technologies; No. 2 (2025); 98-105 Системные исследования и информационные технологии; № 2 (2025); 98-105 Системні дослідження та інформаційні технології; № 2 (2025); 98-105 2308-8893 1681-6048 en https://journal.iasa.kpi.ua/article/view/320537/324822 |
| spellingShingle | технічний стан планера міцність експлуатація літальних апаратів системи керування прийняття рішень Bolohin, Andrii Bolohina, Yuliya Tymchuk, Yurii Ранжування технічного стану повітряних суден за даними діагностування конструкції планера |
| title | Ранжування технічного стану повітряних суден за даними діагностування конструкції планера |
| title_alt | Ranking of the technical condition of aircraft according to the diagnostic data of the glider design |
| title_full | Ранжування технічного стану повітряних суден за даними діагностування конструкції планера |
| title_fullStr | Ранжування технічного стану повітряних суден за даними діагностування конструкції планера |
| title_full_unstemmed | Ранжування технічного стану повітряних суден за даними діагностування конструкції планера |
| title_short | Ранжування технічного стану повітряних суден за даними діагностування конструкції планера |
| title_sort | ранжування технічного стану повітряних суден за даними діагностування конструкції планера |
| topic | технічний стан планера міцність експлуатація літальних апаратів системи керування прийняття рішень |
| topic_facet | technical condition of the airframe strength operation of aircraft control systems decision-making технічний стан планера міцність експлуатація літальних апаратів системи керування прийняття рішень |
| url | https://journal.iasa.kpi.ua/article/view/320537 |
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