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<article xmlns:xlink="http://www.w3.org/1999/xlink">
  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Diagnostic method development when weapons characteristics measuring based on spectral analysis for signals phase shift determination</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Vasyl Lytvyn</string-name>
          <email>vasyl.v.lytvyn@lpnu.ua</email>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Victoria Vysotska</string-name>
          <email>Victoria.A.Vysotska@lpnu.ua</email>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Sergey Tyshko</string-name>
          <email>sergeytyshko57@gmail.com</email>
          <xref ref-type="aff" rid="aff2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Oleksandr Lavrut</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Tetiana</string-name>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Lavrut</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Mariia Nazarkevych</string-name>
          <email>mariia.a.nazarkevych@lpnu.ua</email>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Hetman Petro Sahaidachnyi National Army Academy</institution>
          ,
          <addr-line>Heroes of Maidan 32, 79026Lviv</addr-line>
          ,
          <country country="UA">Ukraine</country>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>Lviv Polytechnic National University</institution>
          ,
          <addr-line>S. Bandera 12, 79013Lviv</addr-line>
          ,
          <country country="UA">Ukraine</country>
        </aff>
        <aff id="aff2">
          <label>2</label>
          <institution>State Scientific Research Institute of Armament and Military Equipment Testing and Certification</institution>
          ,
          <addr-line>18001 Cherkasy</addr-line>
          ,
          <country country="UA">Ukraine</country>
        </aff>
      </contrib-group>
      <abstract>
        <p>The analysis of known methods that have found wide application in measuring technology and are designed to control the technical and operational characteristics associated with the measurement of phase shift during the development, manufacture and operation of weapons and military equipment, has been carried out. Based on this analysis, it was determined that measuring systems designed to determine the phase shift of two harmonic signals have two information transmission channels. A measurement task was set to determine the phase shift of two harmonic signals, using the spectral analysis of the signal obtained by summing the harmonic signals after performing their two-semiperiod transformation. The assumptions necessary list for the analytical ratios synthesis, which establishes the relationship between the phase spectra and the amplitudes (power) of the signal obtained by summing harmonic signals after carrying out their two-semiperiod transformation and phase shift of two harmonic signals, are determined. Analytical relations are proposed that establish the relationship between the abovementioned characteristics. It is shown that the values of the spectrum of phases and amplitudes calculated using the proposed expressions and ratios for calculating the Fourier series coefficients differ by no more than 0.1%. The application of the proposed approach in the artificial intelligence system to diagnose and determine the state of modern weapons and military equipment will allow us to reduce the requirements for measuring equipment without reducing the accuracy of measurements.</p>
      </abstract>
      <kwd-group>
        <kwd>eol&gt;decision-making system</kwd>
        <kwd>complex system</kwd>
        <kwd>phase shift</kwd>
        <kwd>harmonic signal</kwd>
        <kwd>spectral analysis1</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>1. Introduction</title>
      <p>Today, the Defense Forces of Ukraine actively use various types of weapons and military
equipment. An important component of solving the task of effective defence of the state is
ensuring the serviceable state of the anti-aircraft defence system, which is part of the units
and units of the defence forces, as well as its further modernization, as well as the
development of the latest types of weapons. The assessment of the technical condition of
the weapons and military equipment (WME) sample, or the decision on admission to the
supply of the latest weapons to the Armed Forces, is made based on tests, by analyzing its
technical characteristics for compliance with regulatory and technical documents (technical
task, technical conditions, operating instructions, repair documentation sets ). Defects are
an important technological operation during the capital repair works of WME. As you know,
the task of this technological operation is to determine the possibility of using components
from the composition of the sample subject to restoration. For mechanical components,
various parameters are measured, including geometric dimensions, and physical and
chemical properties of the material. To reduce the time and increase the accuracy of
measurements, predicting the state of the WME, it is necessary to use intelligent diagnostic
systems [16]. The use of artificial intelligence in such systems for processing measurement
results, and forecasting (simulation) of the future state of WME is an integral component of
the development of this field. The measurement of the above-mentioned characteristics of
small arms, artillery and missile-artillery weapons, and wheeled and tracked military
equipment is based on non-destructive control methods. Non-destructive control methods
include radiography, ultrasonic flaw detection, magnetic resonance research methods, and
others. Measuring systems that implement the specified measurement methods widely use
phaseometry methods [1, 2, 17, 34]. Also, phase measurement methods are widely used in
radar and radio navigation, aviation and space engineering, geodesy, mechanical
engineering, communication and many other fields [7, 21-27]. The phase-measuring
transformation of various physical processes into the phase shift of harmonic signals
ensures high metrological characteristics. Therefore, phaseometry, as a method of
transformation and measurement, has long gone beyond the traditional use in radio
engineering, navigation and communication and is successfully used in experimental
physics, radio physics, experimental medicine, modern fields of science and technology
when carrying out precision measurements [3-5, 13-15, 17-20, 37-39]. Based on the above,
in [2, 5], a list of WME parameters, which should be converted into a phase shift when
measured during sample manufacturing and testing, is defined. These parameters can
include: electrical and magnetic conductivity, permeability, geometric dimensions,
movement parameters, microdisplacement, capacity, element inductance, liquid level,
liquid or gas consumption, angle of rotation, speed of rotation, electric voltage and current,
temperature, distance, angle, delay time. Thus, conducting scientific research to find new
principles for determining the phase shift, which will allow to reduce the cost of performing
work on the control of the characteristics of the latest and modernized weapons at the
stages of development and production, is relevant.</p>
    </sec>
    <sec id="sec-2">
      <title>2. Related works</title>
      <p>For harmonic signals, such concepts as phase, initial phase, phase shift and delay time are
used in measuring technology. The most complete classification of methods for measuring
phase shifts of harmonic signals is given in works [2, 5, 6, 13, 14, 15].</p>
      <p>According to the principle of measurement, the methods of phaseometry are divided into
compensatory methods and methods of converting the phase shift into other values
voltage, time interval, and geometric parameters of oscillographic images of the
investigated signals. These methods differ from each other in technical implementation,
complexity and accuracy. Compensation methods [2, 5, 6, 13, 14] are based on the process
of balancing (compensating) the phase shift Δφ∈[0,2π) between the measured harmonic
signals, that is, reducing the phase shift to zero by adjusting the phase of one of the signals
using an adjustable phase shifter (measures of phase shift). This method ensures the
achievement of high measurement accuracy, close to the accuracy of a phase shifter.
Measurement methods based on the transformation of the phase shift into other signals [2,
5, 6, 13, 14, 15] allow determining the value of the phase shift of the signals after their
transformation into other intermediate values that are convenient to use for measurement.
These intermediate values include voltage, current, displacement of the electron beam of
the oscilloscope, and time values. The disadvantages of known methods include [2, 5, 6]:




a significant impact on the accuracy of measuring the phase shift of the error
component, which is caused by the phase asymmetry of the signal transmission
channels;
the presence of two channels for conducting analogue-to-digital conversion of input
signals, which leads to the need for mutual synchronization of the frequency of clock
generators for each of the channels;
significant impact on the accuracy of external and internal noise measurement;
non-linear nature of the scale.</p>
      <p>At present, one of the effective and widespread ways of reducing the impact of external
and internal noise on the quality of solving problems of analyzing and processing signals of
various natures is the use of spectral analysis [35-36]. As is known, a periodic signal of any
form can be decomposed into harmonic signals whose frequencies are multiples of the
frequency (period) of the analyzed signal. A similar research method is called spectral
analysis, the mathematical basis of which is the Fourier series [8, 31-33].</p>
      <p>Fourier series of arbitrary periodic signals can contain an infinitely large number of
terms. One of the advantages of the Fourier transform is that when limiting the Fourier
series to any finite number of its terms, it provides the best mean square error of
approximation to the original function (for a given number of terms). The convenience of
using the frequency representation of signals lies in the fact that harmonic functions are
eigenfunctions of operations of transfer, integration, differentiation and other linear
operations invariant in coordinates. They pass through linear systems without changing the
shape and frequency of the harmonics, only the initial phase and amplitude of the
oscillations change. In the general case, when expanding into a Fourier series of a periodic
signal with a period   , it is possible to use an interval [− Тс⁄ , Тс⁄ ].</p>
      <p>If we denote the angular frequency through  с then since  с = 2 , then for the function
 ( ) on the interval [− Тс⁄2 , Тс⁄2], the Fourier series has the form:</p>
      <p>Expressions for determining the coefficients of the Fourier series   ,   have the form:
 ( ) =
2</p>
      <p>0 + ∑{  
,
( = 0,1,2, . . . ,  )
( = 1,2, . . . ,  ).</p>
      <p>
        (
        <xref ref-type="bibr" rid="ref1">1</xref>
        )
(2)
(3)
      </p>
      <p>
        Series (
        <xref ref-type="bibr" rid="ref1">1</xref>
        ) represents the decomposition of the periodic signal f(t) into the sum of real
elementary harmonic functions (cosine and sine) with weighting coefficients, the geometric
sum of whose values (that is, the values of   and   are nothing but the real amplitudes of
the corresponding harmonic oscillations with frequencies   с. The set of amplitude values
of these harmonics forms a one-sided physically real (only for positive frequencies
  с signal spectrum.
      </p>
      <p>The goal of the work. To propose the scientific and technical basis of the alternative
principle of determining the phase shift, the mathematical basis of which is possible to
consider analytical relations that establish the relationship between the phase shift of two
harmonic signals and the spectral characteristics of the signal obtained when summing
them after carrying out a two-semiperiod transformation, which will allow to significantly
reduce the error component, due to the phase asymmetry of the signal transmission
channels and the influence of external and internal noise during monitoring of the
characteristics (parameters) of the WME.</p>
    </sec>
    <sec id="sec-3">
      <title>3. Methods and models</title>
      <p>At present, the determination of the phase shift is of greatest interest to phasometry. Phase
shift [9, 28-30] refers to the modulus of the difference between the initial phases of two
harmonic signals of the same frequency. As a rule, the measurement of phase shifts of
signals is based on the model of a harmonic signal, which is specified without changes in its
parameters over an infinite time interval. This model is ideal, and in practice, a model with
a finite time window is used, that is, measurements are carried out on a finite time interval.</p>
      <p>Then, based on the above, we will formulate the problem of determining the phase shift
using the spectral analysis of the signal obtained as a result of the summation of two
harmonic signals, after carrying out their two-half-period transformation. Let's consider the
initial data necessary to solve the specified measurement problem.</p>
      <p>Let there be two harmonic signals  1( ) and  2( ), which have a phase shift relative to
the other equal to  , in the interval from 0 to 2 . Based on the fact that phase shift</p>
      <p>Synthesis of time diagrams that describe the order of formation of the signal
 ∑/ ( ) using relations (4) and (5) will be carried out in the Matlab environment using the
Simulink tool application. To do this, we synthesize the scheme shown in Fig. 1. In this
scheme, the synthesis of signal u1(t) is carried out by the harmonic signal generator "Sine
Wave", and the signal u2(t) by the generator "Sine Wave 1". From the "Sine Wave" output,
the signal enters the "Abs" block and the oscilloscope marked "Scope", which is designed to
form the time diagram of the  1( ) signal. According to the "Sine Wave 1" output, the signal
enters the "Abs 1" block and the oscilloscope marked "Scope 2", which is designed to form
/
the timing diagram of the u2(t) signal. At the output of the "Abs" block, a signal  1( ) is
formed, which is fed to the first input of the summation device "Add" and "Scope 1". "Scope
/
1" forms a time diagram of the signal  1( ). Similarly, at the output of the "Abs 1" block, a
signal  2/( ) is formed, which is fed to the second input of the summation device "Add" and
"Scope 3", which forms a time diagram of the signal  2/( ). At the output of the "Add" block,
we will receive the signal  ∑/ ( ). The signal  ∑ ( ) is fed to "Scope 4", which will form its
signal time diagram</p>
    </sec>
    <sec id="sec-4">
      <title>4. Experiments, results and discussion</title>
      <p>Fig. 2 shows the time diagrams of the signals  1( )/ 2( ),  1/( )/ 2/( ) and  / ( ) at the
value  = 0, as well as the "Sine Wave" generator settings tab ” and “Sine Wave1”.</p>
      <p>According to the settings tabs, generators "Sine Wave" generates a sinusoidal signal with
an amplitude equal to 1, and "Sine Wave1" with an amplitude equal to 0.8, other settings of
the tabs are as follows: the constant component of the signals is 0, the frequency of the signal
is 1 rad/s, the initial phase of the signals is 0 rads, the quantization time is minimal for this
device, i.e. 0 on the tab. The timing diagram shown on "Scope" and "Scope 2" fully confirms
the settings on the tab. The time diagrams for the  ∑/ ( ) signal are shown on the "Scope 4"
tab. The analysis of this time diagram shows that the signal  ∑/ ( ) has a period equal to π
s, the maximum value is equal to 1.8, and the minimum value is equal to 0. The obtained
results correspond to the summation of two harmonic signals, after carrying out their
twoand-a-half period transformation.</p>
      <p>Fig. 3 shows the time diagrams of signals  1( ) and  2( ),  1/( ) and  2/( ) and  / ( ), at
the value of  = 0,9 rad, as well as the generator settings tab "Sine Wave" and "Sine
Wave1". According to the configuration tabs, the "Sine Wave" generator generates a
sinusoidal signal with an amplitude equal to 1, the constant component of the signal is 0,
the frequency of the signal is 1 rad/s, the initial phase of the signal is 0 rad, the quantization
time is minimal for this device, i.e. 0 on the tab.</p>
      <p>According to the settings tabs, the "Sine Wave1" generator generates a sinusoidal signal
with an amplitude equal to 0.8, the constant component of the signal is 0, the frequency of
the signal is 1 rad/s, the initial phase of the signal is 0.9 rad, the quantization time is minimal
/ /
for this device, i.e. 0 at tab. The time diagrams for signals  1( ) and  2( ) are shown in the
"Scope 1" and "Scope 3" tabs. The analysis of the data of the time diagrams shows that they
have a period equal to π s, the maximum values of  1( ) are equal to 1, and  2/( ) is 0.8, also
/
the  2/( ) signal precedes the  1( ) about 0.9. The time diagrams for the  ∑/ ( ) signal is
/
shown on the "Scope 4" tab. Analysis of this time diagram shows that the signal  ∑/ ( ) has
a period equal to π s. In the time interval from 0 to (π-0.9) s, the maximum value is
approximately 1.65, and the minimum value is approximately 0.78. In the time interval from
( − 0,9) to π, the maximum value is approximately 0.8, and the minimum value is 0.6.</p>
      <p>Fig. 4 shows the time diagrams of the signals  1( )/ 2( ),  1/( )/ 2/( ), and  / ( ) at the
value of  = 1.2 rad, as well as the tab for setting the generator "Sine Wave”/“Sine Wave1”.</p>
      <p>According to the configuration tabs, the "Sine Wave" generator generates a sinusoidal
signal with an amplitude equal to 1, the constant component of the signal is 0, the frequency
of the signal is 1 rad/s, the initial phase of the signal is 0 rad, the quantization time is
minimal for this device, i.e. 0 on the tab. According to the settings tabs, the "Sine Wave1"
generator generates a sinusoidal signal with an amplitude equal to 0.8, the constant
component of the signal is 0, the frequency of the signal is 1 rad/s, the initial phase of the
signal is 1.2 rad, the quantization time is minimal for this device, i.e. 0 on the tab. The time
/ /
diagrams for signals  1( ) and  2( ) are shown in the "Scope 1" and "Scope 3" tabs. The
analysis of the data of the time diagrams shows that they have a period equal to  s, the
maximum values of  1( ) are equal to 1, and  2/( ) is 0.8, also the  2/( )signal precedes the
/
/
 1( ) about 1.2 rad. The time diagrams for the  ∑ ( ) signal are shown on the "Scope 4"
tab. Analysis of this time diagram shows that the signal  ∑/ ( ) has a period equal to π s. In
the time interval from 0 to ( − 1.2) s, the maximum value is approximately 1.5, and the



 2
 1
has two local maxima  1</p>
      <p>and two breaks  1
 2, respectively;
minimum value is 0.95. In the time interval from ( − 1.2) to π, the maximum value is
approximately 1.05, and the minimum value is 0.75.</p>
      <p>From Fig. 4, it can be seen, and it is also shown in [10, 11] that  ∑/ ( ) depending on the
value of Δφ of the input signals  1( ) and  2( ):
is a periodic signal with a period of T   1
2
== ;
Т
2
a change in the value of the phase shift angle 
leads to a change in the values of
,  2
,  1
end  2
and time parameters  1
,  2</p>
      <p>end  2.
and  2
and  2
, which correspond to the moments of  1
, which correspond to the moments of time  1,</p>
      <p>A change in the values of the above characteristics of the signal  ∑/ ( ) leads to a change
in its shape, which in turn will lead to a change in the values of the coefficients   and   of
the Fourier series depending on the change in the magnitude of the phase shift 
.</p>
      <p>When conducting spectral analysis, such concepts as amplitude spectrum, power
spectrum and phase spectrum are used. When conducting spectral analysis, such concepts
as amplitude spectrum, power spectrum and phase spectrum are used. According to [12],
the spectrum of amplitudes is understood as the set of absolute values of the coefficients  
( = 0,1,2, . . . ,  ), which are determined from the known values of   and   by the ratio:
|  | =
√ 2 +  2</p>
      <p>2</p>
      <p>The value |  | indicates the value of the amplitude of the k-th harmonic signal when
expanded into a Fourier series. The power spectrum is understood as a set of arguments of
the values |  |2. The spectrum of phases means the set of arguments ∠  ( = 0,1,2, . . . ,  ),
which are determined by the known values of   and   by the ratio:</p>
      <p>The value of ∠  indicates the value of the initial phase of the k-th harmonic signal when
expanded into a Fourier series. Then, based on the above, we will formulate the task of
determining the phase shift using Fourier series decomposition, as a synthesis of analytical
relations that describe the relationship between the change in the spectrum of amplitudes
(power) and the spectrum of the phases of the signal  ∑/ ( ) depending on the change in
 . Synthesis of relations that determine the relationship between the value of 
and the
characteristics of the spectrum of amplitudes (power) and the spectrum of phases of the
signal  ∑/ ( ) using the following assumptions. As can be seen from (4), the signal
 ∑/ ( ) is formed by summing two signals  1( ) and  2/( ). These signals are formed by
/
signals  1( ) and  2( ), while the amplitude of   1 differs from the amplitude of   2 by v
times, and have a phase shift  .</p>
      <p>Then it can be stated that the signal  1( ) precedes the signal  2( )by a certain time
interval τ, i.e.  2( ) =   1( −  ). According to the known values of 
and T, the time
interval τ is determined by the ratio:
 =</p>
      <p>Т.</p>
      <p>As shown in [12], the shift of the signal in the time domain by some interval τ leads to a
change in the phase spectrum, but the spectrum of the signal amplitudes remains
unchanged. Taking into account expressions (7) and (8) provided that   1. and   2. are
the amplitude values of the  -th harmonics of signals  1( ) and  2/( ), respectively, and  1.к
/
and  2.к values of the initial phases of the  -th harmonics of the signals  1( ) and  2( ),
respectively, the Fourier series for the signal  ∑/ ( ) will have appearance:
/

u/ (t)    1.0 + ∑ =1[  1. 
( 2</p>
      <p>+  1. )] +   2.0 +

 =1
+ ∑[  2. 
(2</p>
      <p>+  2. )] =
= (  1.0 +   2.0) + [  1.1  (2
+  1.1) +   2.1  ( 2
+  2.1)] +
+[  1.2 
+[  1. 
(4
( 2
+  1.2) +   2.2</p>
      <p>( 4
+  1. ) +   2. 
(2
+  2.2)] + ⋯ +
+  2. )]</p>
      <p>To synthesize analytical relations for determining the values of the amplitude   / ∑1and
the initial phase  / ∑1of the first harmonic of the signal  ∑/ ( ), we will construct the vector
/
diagram of the first harmonics of the signals  1( ) and  2 ( )in the presence of a phase shift
equal to</p>
      <p>of the signals  1( ) and  2( ), provided that the initial phase of the signal
 1( ) is zero, taking into account the following remarks and assumptions:




it is known that the frequency of the first harmonic of the signal is equal to the
frequency of the signal;
it is shown in [10, 11] and it can be seen in Figs. 2...4 that  1( ),  2( ) and
/
 ∑ ( )have a period that is two times shorter than  1( ) and  2( );
it can be asserted that  2( ) =   1( −  ) and  2/( ) =   1( −  ), that is, the time
/
interval of the shift τ between the signals  1( ) and  2( ), and the shift time interval
/
/
/
/
τ between signals  1( ) and  2( ) is the same;
based on relation (9) and the above remarks, it can be seen that the value of the
phase shift of the first harmonics of signals  1( ) and  2( )will be equal to 2 , if
there is a phase shift equal to Δφ of signals  1( ) and  2( ).
/
/</p>
      <p>The above vector diagram is shown in Fig. 5. From Fig. 5, it can be seen that for the
calculation of the values of the characteristics of the vector of the first harmonic of the signal
 ∑/ ( ) according to the vectors of the first harmonics of the signals  1/( ) and  2/( ), the
parallelogram method was used.
(9)</p>
      <p>/
(10)
harmonic of the signal u/ (t)</p>
      <p>Thus, the value of the amplitude  /</p>
      <p>∑1of the first harmonic of the signal
 ∑ ( ) according to the known values of the amplitudes of the first harmonics   1.1 and
  2.1 =  з 2.1of the signals  1( ) and  2/( ) in the presence of a phase shift equal to 
/
of
signals  1( ) and  2( ) is determined by the ratio:
/
/
 1. = 2  ′</p>
      <p>′ ∫−2 ′|
 1. = 2
2
 ′
 ′ ∫−2 ′|</p>
      <p>2
Then the value of the amplitude  /</p>
      <p>∑ of the k-th harmonic of the signal
 ∑ ( ) according to the known values of the amplitudes   1. and   2. of the k-th
harmonics of the signals  1( ) and  2/( ) at a phase shift value equal to 
/
of signals  1( )
and  2( ) is calculated using the ratio:
 /

∑ = √ 2 1. +  2 2. + 2  1.   2. 
. ( = 0,1,2, . . . ,  )</p>
      <p>
        The synthesis of analytical ratios for calculating the values of   1. will be carried out in
the following order. Let's determine the spectrum of amplitudes for the signal  1( ) under
the condition   1 = 1. The relations for calculating the coefficients of the Fourier series  1.
/
/
и  1. of the signal  1( ) are as follows:
 /
 ∑1 = √ 2 1.1 +  2 2.1 + 2  1.1  2.1 
2 
Based on the known values of  1. and  1. , the value of   1(
        <xref ref-type="bibr" rid="ref1">1</xref>
        ). is calculated by the ratio:
( )| 
(2
      </p>
      <p>) . ( = 0,1,2, . . . ,  )
(  )| 
( 2</p>
      <p>
        ) , ( = 1,2, . . . ,  )
  1(
        <xref ref-type="bibr" rid="ref1">1</xref>
        ). =
      </p>
      <p>(11)
(12)
(13)
(14)
(15)</p>
      <p>
        The values of   1(
        <xref ref-type="bibr" rid="ref1">1</xref>
        ). were calculated using the universal mathematical package
MathCAD, the results are presented in Fig. 6. Using the property of the linearity of the
Fourier series, the relationship for determining the value of the amplitude   / ∑
k-th
harmonic of the signal  ∑/ ( ) based on the known values of the amplitudes   1 and   2
at the value of the phase shift of the initial signals  1( ) and  2( ), which is equal to  , is
calculated using the relationship:
 /
      </p>
      <p>To synthesize analytical relations to determine the values of the initial phase  / ∑1of the
first harmonic of the signal  ∑/ ( ), we will use the theorem of sines for the triangle formed
by the sides   1.1,  р 2.1 and   / ∑1 on the vector diagram of the first harmonics of the
signals  1( ) and  2/( ) in the presence of a phase shift equal to 
/
of the signals  1( ) and
 2( ), we write</p>
      <p>
        Solving this equation relative to  / ∑1based on the fact that

 2.1 =   2.1 =   1(
        <xref ref-type="bibr" rid="ref1">1</xref>
        ).1  2,
 = 2
−  / ∑1
.
      </p>
      <p>
        We obtain that the value of the initial phase  / ∑1of the first harmonic of the signal
/
 ∑ ( )depending on the value of Δφ is determined by the following relation, provided that
the initial phase of the signal u_1 (t) is zero
 /
 ∑1 = 
[
  (2
) ⋅ (  1 + 
  2
( 2
))]
(17)
  1(
        <xref ref-type="bibr" rid="ref1">1</xref>
        ). =
      </p>
      <p>Taking into account (9), for the kth harmonic, the initial phase  / ∑ on the interval
[−  ⁄2 ,  ⁄2] of the signal  ∑/ ( )will be equal to:
spectrum of amplitudes and phases of the signal  ∑/ ( ) obtained using relations (17) and
(18) and the following expressions:
(19)
(20)
(21)
, ( = 0,1,2, . . . ,  )
, ( = 1,2, . . . ,  )</p>
      <p>.
  . =
,
2</p>
      <p>As an indicator of approximation of the spectrum of amplitudes, we use the difference
between the value of  / ∑ obtained using relation (16) and the value of   . calculated
using relations (19-21). The calculations were performed in the MathCAD mathematical
package, and the comparison results for some values of  ,   1 and   2 are presented in
Fig. 7a. These results show that the relative deviation of the amplitude spectrum obtained
using (17) differs from the values of the amplitude spectrum obtained using (19 ... 21) less
than 0.1%. As an indicator of approximation of the phase spectrum, we use the difference
between the value of  / ∑ obtained using relation (18) and the value of ∠  in the interval
[-π⁄2,π⁄2] calculated using relation (19, 20, 21).</p>
      <p>The results of the comparison for some values of Δφ are presented in Fig. 7b. These
results show that the relative deviation of the phase spectrum obtained using (19) differs
from the values of the phase spectrum obtained using (19, 20, 21) by less than 0.1%.</p>
    </sec>
    <sec id="sec-5">
      <title>5. Conclusions</title>
      <p>An analysis of the known principles of measuring phase shifts was carried out. The analysis
showed that a significant contribution to the final measurement error of phase shifts is
made by the component caused by the phase asymmetry of signal transmission channels
and the influence of external and internal noise. As an alternative approach to determining
the phase shift, it is proposed to use a signal obtained as a result of summing harmonic
signals after carrying out their two-semiperiod transformation followed by its spectral
analysis. Analytical relations are proposed that establish the relationship between the
phase shift and the characteristics of the spectrum of amplitudes and phases of the
considered signal. The adequacy of the proposed analytical ratios was checked. As a result
of the verification, it was established that the relative discrepancy between the
characteristics of the spectrum obtained using the proposed ratios and using the ratios for
calculating the coefficients of the Fourier series does not exceed 0.1%.</p>
      <p>These analytical relations can be considered as a mathematical basis for the synthesis of
methods for determining the phase shift of two harmonic signals using the spectral analysis
of the signal obtained as a result of their addition after carrying out their two-half-cycle
transformation. Further research should be directed to the development of intelligent
diagnostic systems, which will be built based on algorithms of artificial intelligence, which,
in turn, will reduce the time and increase the accuracy of measurements and forecasting the
state of modern WME.
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