=Paper=
{{Paper
|id=Vol-3896/short17
|storemode=property
|title=Principles of construction of an adaptive multilevel system of monitoring and diagnostics of complex technical objects
|pdfUrl=https://ceur-ws.org/Vol-3896/short17.pdf
|volume=Vol-3896
|authors=Nadiia Marchenko,Olena Monchenko,Hanna Martyniuk,Larysa Chubko,Tetiana Scherbak
|dblpUrl=https://dblp.org/rec/conf/ittap/MarchenkoMMCS24
}}
==Principles of construction of an adaptive multilevel system of monitoring and diagnostics of complex technical objects==
https://ceur-ws.org/Vol-3896/short17.pdf
Principles of construction of an adaptive
multilevel system of monitoring and
diagnostics of complex technical objects
Nadiia Marchenko1,*,†, Olena Monchenko1,† , Hanna Martyniuk2,†, Larysa Chubko1,†
and Tetiana Scherbak1,†
1 1
National Aviation University, Liubomura Huzara ave.1, Kyiv, 03058, Ukraine
2
Mariupol State University, Preobrazhenska ave. 6, Kyiv, 03037, Ukraine
Abstract
Thіs thesis is devoted to issues of development and research of the basis of the model for building
an adaptive system of multi-level monitoring and diagnostics of complex technical objects. The
requirements of the adaptive system of multi-level monitoring and diagnostics of complex technical
objects are formulated. The scientific problem was posed, the requirements for adaptive systems were
determined, taking into account the principle of maximum use of system resources.
The organization, architecture, principles of construction, work modes, technical and economic
prerequisites for ensuring quality monitoring of the parameters of complex technical objects in real
time, and the selection of the model of the research object were studied.
One of the distinctive features of the systems under consideration is that the function of adapting
the operation modes of the diagnostics subsystem to changes in the characteristics of objects is
included in the presented functional composition. A generalized structural and functional scheme of
the system of multi-level monitoring and diagnostics of complex technical objects has been developed.
The paper presents the development of a generalized criterion for assessing the effectiveness of
research into multi-level monitoring and diagnosis systems of complex technical objects and partial
criteria for the monitoring subsystem and the diagnostics subsystem, and presents a model basis for
building a multi-level monitoring and diagnosis system.
Keywords ⋆1
Automated control systems, multi-level monitoring and diagnostic systems, adaptive multi-level
monitoring and diagnostic systems, efficiency evaluations, the method of least squares, subsystems
of control, diagnostics, forecasting and decision-making.
⋆
ITTAP’2024: 4th International Workshop on Information Technologies: Theoretical and Applied Problems, October 23-
25, 2024, Ternopil, Ukraine, Opole, Poland
1∗
Corresponding author.
†
These authors contributed equally.
nadiiamar4@gmail.com (N. Marchenko); monchenko_olena@ukr.net (O. Monchenko),
ganna.martyniuk@gmail.com (H. Martyniuk), chubkolarysssa@gmail.com (L. Chubko); tais2004@i.ua (T.
Scherbak).
0000-0001-5008-4116 (N. Marchenko); 0000-0002-8248-5704 (O. Monchenko); 0000-0003-4234-025X (H.
Martyniuk); 0000-0003-4647-3156 (L. Chubko); 0000-0003-1170-8154 (T. Scherbak).
© 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
ceur-ws.org
Workshop ISSN 1613-0073
Proceedings
1. Introduction
Thіs thesis is devoted to issues of development and research of the basis of the model for
building an adaptive system of multi-level monitoring and diagnostics (SMMD) of complex
technical objects. Based on the analysis of the characteristics of controlled objects, presented in
works [1, 2], a class of complex technical objects is defined, the main features of which are the
complexity for monitoring and diagnosis, which is due to the stochasticity and multi-level
processes, the complexity of the design, the impossibility of access to all units of the unit
without its disassembly, as well as a lack of information for control. This class includes, in
particular, hydroelectric power plants, thermal power plants and nuclear power plants.
Using the formalized approach of theory of automata, a functional-logical model of complex
technical objects [3] was built and described, which allows to determine approaches for creating
simulation models of complex technical objects, methods of their control, and to formulate
requirements for multi-level monitoring and diagnostics.
Based on the analysis of works [4,5,6], the main principles of construction and properties of
adaptive self-organizing technical systems are defined.
Among the large number of works aimed at solving the above-mentioned problems, it is
possible to single out, for example, publications [9, 10], each of which considers certain issues
related to the use of monitoring and diagnostic systems. Therefore, the main drawback of the
presented multi-level monitoring systems is the difficulty of realizing their technical advantages
in combination with acceptable cost and application adaptation [1, 11].
The purpose of the work is to study the organization, architecture, principles of construction,
work modes, technical and economic prerequisites to ensure quality monitoring of the
parameters of complex technical object (СTO) in real time, to select a model of the research
object. To achieve the goal, the following scientific tasks were solved:
- analyze the subject area and determine the main characteristics of the adaptive system
of multi-level monitoring and diagnostics of complex technical objects. Conduct a scientific
problem statement, determine requirements for adaptive systems, taking into account the
principle of maximum use of system resources;
- apply the method of two-stage modeling of the СTO automatic and simulation models
of the object.
2. The main characteristics and functions of the
adaptive system of multi-level monitoring and
diagnostics of complex technical objects
Modern SMMDs are the result of the integration of previously existing subsystems of control,
diagnosis, forecasting and decision-making for the prevention of emergency situations and
liquidation of the consequences of unregulated conditions. SMMD are multi-level systems for
monitoring man-made systems of complex industrial objects (CIO). Fig. 1 defines and presents a
generalized structural and functional scheme of the SMMD CIO.
Figure 1: Structural and functional scheme of the SMMD of complex industrial facilities
The monitoring subsystem contains blocks to perform the following functions:
• control of the state of the technical system (CSTS);
• forecasting the state of the technical system (FSTS);
• adaptation of the modes of operation of functional blocks of the diagnostics
subsystem (A) to changes in the characteristics of the СTO;
• selection of a global strategy and elimination of consequences from unregulated
conditions of objects at the level of the technical system (SGS).
The diagnostics subsystem contains blocks to perform the following functions:
• control of the state of the industrial object (CSIO);
• multi-level monitoring and diagnostics (MMD);
• forecasting the residual resource of the object (FRRO);
• selection of a local strategy for liquidation of a specific identified unregulated
state (SLS). All results are sent to the automated control system of the technological
process (ACSTP).
One of the distinctive features of the systems under consideration is that the function of
adapting the operation modes of the diagnostics subsystem to changes in the characteristics
of objects is included in the presented functional composition [9, 12]. As a result, SMMD is
provided with parametric adaptability at the system level. At the same time, the adaptation
block initiates self-organization of the system to create the effect of coordinated interaction
of its subsystems in order to implement the principle of maximum use of system resources.
3. A model basis for building a system of multi-level
monitoring and diagnostics
The analysis of the system structure, information flows and time modes of operation, the
SMMD under study was presented in the form of a single-channel multiphase mass service
system and was discussed in detail in the paper [1]. In this paper, we will focus on the
characteristics of the service station model. As a result of studies of modern approaches to the
construction of models of complex objects [9, 11], a two-stage method of construction of CTO
models was determined, according to which, at the first stage, a conceptual model of the object
consisting of two subsystems is developed: • automatic;
• imitation.
The automatic one determines the algorithm of transition of object states, and the simulated
one reproduces signals from the object corresponding to the transition states.
At the second stage, based on the canonical design method, a system of nested automata is
developed to simulate object state transitions and signal simulators for each state [3, 7]. The
model of each nested automaton (𝑁A) is described by the following expression:
NA = {𝑋, 𝑉, 𝐶, 𝑌, 𝑆, 𝛿, 𝜆, 𝑠0},
where 𝑋, 𝑉, 𝐶 – are the corresponding vectors of controlling, disturbing and correlating
parameters of the model, which collectively form a set of input data for each 𝑁A; 𝑌 – is a vector
of initial values, 𝑌 = {𝑦1, 𝑦2, … 𝑦𝑖𝑖, … 𝑦𝑁𝑁}; 𝑆 – is a vector of states; δ, λ – state transition and output
functions, respectively; 𝑠0 – is the initial state of 𝑁A.
The transition functions 𝑠(𝑡′) and 𝑦(𝑡′) of the NA outputs in the automatic time 𝑡′ mode are
determined as follows:
𝑠(𝑡′) = 𝛿{𝑠(𝑡′ − 1), 𝑥(𝑡′), 𝑣(𝑡′), 𝑐(𝑡′)};
𝑦(𝑡′) = 𝜆{𝑠(𝑡′ − 1), 𝑥(𝑡′), 𝑣(𝑡′), 𝑐(𝑡′)}.
According to the value of the vector 𝑌 of each nested automaton in the simulation subsystem,
the appropriate model of the time series 𝑃𝑖(𝑡) of the CTO parameter is selected and adjusted in
the form of the following polyharmonic polynomial:
n
(
P i ( t )=a0 + ∑ ( ai cos 2 π K i
i=1
t
N ) t
+bi sin ( 2 π K i ))+d 0 +d 1 t
N
where 𝑛 is the number of harmonics during the training period of model 𝑁; 𝐾𝑖 – is the
coefficient that determines the harmonic number (𝑖 = 1, … 𝑛; 𝑛 = 𝑁/2); 𝑡 is the time interval
number, 𝑡 = 1,2,3 … . Model coefficients 𝑎0, 𝑎𝑖, 𝑏𝑖 are average statistical estimates of Fourier
coefficients [13] for time series of parameters obtained experimentally, and coefficients 𝑑0, 𝑑1 are
average statistical characteristics of the trend. All coefficients of the model are determined using
the method of least squares [14].
Thus, the output signal of the model corresponding to the generalized parameter 𝑃∗ for the
moment 𝑡𝑡 is determined as a superposition of the simulated signals 𝑃𝑖(𝑡) (𝑖 = 1, … 𝑚), i.e.:
m
P ( t ) =∑ P i ( t )
¿
i=1
The developed model has a wide range of functional capabilities, in comparison with known
analogues, has flexible settings, can adapt to changes in the structure of CTO and can be
implemented with available hardware [8, 15].
The main features of the presented methodological basis include the following characteristics:
- the presented methods and tools can be used at all stages of designing the SMMD,
starting with the pre-project study of the system, ending with their implementation in
production and recommendations for maintenance;
- the main concept of methodological developments is the synthesis of project solutions
based on adaptive work modes and subsystem self-organization.
Based on the analysis of the characteristics of the studied objects, a class of complex technical
objects was determined, the main feature of which is the complexity for monitoring and
diagnostics, which is due to the stochasticity of the processes taking place, the complexity of the
design, and the lack of information available for control. Typical representatives of CTO are
hydroelectric power plants, thermal power plants, nuclear power plants, metallurgical facilities
and oil refining enterprises.
With the use of the formalized approach of automata theory, a functional-logical model of
CTO is built and described, which allows to determine approaches for creating simulation
models of CTO and methods of their control.
The basic concept of scientific research and development for the creation of a single system
of methods and means of construction of the SMMD CTO has been determined, the main aspects
of which include:
- the creation of adaptive SMMD, in which the management of the operating modes of the
diagnosis subsystem, which is located at the lower level, is performed at the upper level by the
subsystem of monitoring the state of the objects of the entire technical system;
- diagnosis of CTO according to the principle of necessity, taking into account
assessments of the real state of objects obtained as a result of monitoring;
- the selection of a strategy for the elimination of unregulated states of CTO is based on
the results of the work of both subsystems;
- development of well-known and planning of new effective methods of control of CTO
on the basis of modern information technologies and increasing the level of intellectualization
of hardware and software tools of SMMD.
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