=Paper=
{{Paper
|id=Vol-3039/paper42
|storemode=property
|title=nCode GlyphWorks Software Use for Test Data Processing
|pdfUrl=https://ceur-ws.org/Vol-3039/paper42.pdf
|volume=Vol-3039
|authors=Mykola Stashkiv,Oleksandr Matsiuk
|dblpUrl=https://dblp.org/rec/conf/ittap/StashkivM21
}}
==nCode GlyphWorks Software Use for Test Data Processing==
https://ceur-ws.org/Vol-3039/paper42.pdf
nCode GlyphWorks Software Use for Test Data Processing
Mykola Stashkiv, Oleksandr Matsiuk
Ternopil Ivan Puluj National Technical University, 56 Ruska street, Ternopil 46001, Ukraine
Abstract
Some technique and results of experimental data processing on the stress-and-strain state
study of wide-spray field sprayer boom parts have been described in the paper under
discussion. The test data have been corrected to remove the data drift effect. Two approaches
have been applied to correct the test data, namely the use of high frequency filter and the
removal of the data array average values. The results of test data correction by the above-
mentioned methods have intercommunicated very well. The data have been processed by
nCode GlyphWorks software aimed at preparation for the further use of the obtained results
to estimate the structure durability.
Keywords 1
Experiment, test data, signal, processing, software, glyph, data correction
1. Introduction
Measurement, i.e. experimental determination of the values of physical quantities by special
hardware, namely measuring apparatuses, is the basic way to obtain some information about the
environment and the processes occurring in it. The measurements are the only way to prove or reject
any statements or conclusions of theoretical models describing the real objects behavior.
Any experimental research has always involved some complex and time-consuming procedures
dealing with data collecting and processing, analysis of the obtained information and construction of
processes models and fields of various nature. Two approaches have been known to provide the
analogue measuring signals recording aimed at further processing by digital methods [1].
One of the approaches is based on specialized complex systems use involving the equipment of
analogue-digital conversion, microprocessors of digital processing and devices of information
transformation. Another approach is based on the use of interface devices of data collection and
universal computer systems.
As for the advantages of the second approach, based on the use of some additional interface
modules and signals digital processors as parts of a personal computer, we can list the following ones:
flexibility of a measurement system regarding the implementation of different algorithms of
processing; functional completeness of the system (the tasks of data input, processing, management,
analysis, visualization, measurements data and analysis results storage are being solved); good
metrological characteristics.
In various spheres of reality, in particular, in economics, biology, medicine, technology etc are
widespread conditional cyclic random processes and phenomena. The study of cyclical processes
involving modern information systems requires the preliminary development of adequate
mathematical models for them. Many different mathematical models of cyclic processes are known
today, including harmonic, periodic and almost periodic deterministic functions, periodically
correlated and periodically distributed random processes, linear periodic random process, almost
periodically correlated random process, cyclic random process [2-6].
ITTAP’2021: 1nd International Workshop on Information Technologies: Theoretical and Applied Problems, November 16–18, 2021,
Ternopil, Ukraine
EMAIL: stashkiv@tntu.edu.ua (M. Stashkiv); oleksandr.matsiuk@mail.com (O. Matsiuk);
ORCID: 0000-0002-7325-8016 (M. Stashkiv); 0000-0003-0204-3971 (O. Matsiuk)
©️ 2021 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
In particular, the work [7] is devoted to the development of mathematical modeling of digital
cyclic signals with double stochasticity, namely, the construction of their mathematical model in the
form of a conditional cyclic random process of discrete argument.
In the paper [8] considers the unified approach to the modeling and processing signals of electrical,
magnetic and acoustic (mechanical) nature based on the model of the theory of cyclic random
functions, namely, using cyclic random process and vector of cyclic rhythmically related random
processes.
In the paper [9] the new methods of statistical analysis of heart rhythm based on its generalized
mathematical model in a form of random rhythm function, that allows to increase the informativeness
and detailed analysis of heart rhythm in cardiovascular information systems are offered.
Nowadays, there is a great number of hardware and software for signals obtaining, segmentation,
statistical analysis, processing and modeling. Although, many scientists have developed their own
software to solve certain problems. It can be either a single-purpose software [10, 11, 12] or the whole
program complexes [13].
Among the whole range of various software for the work with experimental data the software
nCode made by the company HBM Prenscia [14, 15] has been of great interest, which was designed
to process the signals, to work with large volumes of test data and calculation of the fatigue durability
of the products.
nCode GlyphWorks software has a convenient object-oriented graphical interface and it is
optimized for the complex work with large volumes of multi-channel data. The software functional
includes a wide range of tools for temporary, frequency and statistical analysis of signals. Moreover,
some tools are available to assess both the resource and fatigue durability of the products and
synchronized reproduction of GPS signals, video and other data obtained during the tests, and also a
convenient mechanism for automated creation of reports has been implemented.
nCode GlyphWorks software has a module system which enables us to create the required feature
set either by means of large embedded libraries or by the use of language Python. Working templates
in nCode GlyphWorks can be prepared in advance and can be found in the specified library to provide
reliability and high speed of calculation. Thus, the users do not need to create the required feature set
by themselves.
For effective work with such software it is necessary to have large sets of experimental data. The
formation of such test data sets is an important phase of any scientific research, especially in modeling
the dynamic load of parts and components of large mobile agricultural machinery.
Carrying out full-scale field tests of agricultural machinery involves significant costs and certain
organizational problems, especially during a COVID-19 pandemic.
One of the ways to solve this problem is to conduct laboratory tests. However, such studies do not
allow for a full set dynamic loading research of the large mobile agricultural machinery bearing
structures.
To solve this problem the authors [16] developed a test bed for stationary semi-natural studies of
the dynamic loading of wide-spray field sprayer booms. The test bed design is protected by a utility
model patent [16]. Description of the design of the test bed for the study of the wide-spray field
sprayer booms load dynamics and methods of semi-natural research are presented in [17].
The results of any measurements, despite the accuracy of the procedure, are likely to have some
errors. It may be caused by the impact of different external factors on the measurement process result
in an offset on the sensor output. This effect should be taken onto account as it may cause some errors
in the results. In this case, the analysis of obtained results and errors of measurement has been an
essential part of any scientific experiment, so a researcher must be able to apply some methods of test
data correction.
2. Test data obtaining and correcting
The results of digital processing of the test data obtained by the authors [17] whilst studying the
stress-and-strain state of a wide-spray field sprayer boom on purpose designed and made test bed to
study the dynamic loading of mobile machinery [16] by nCode GlyphWorks software tools [15] are
presented in the paper under discussion.
nCode GlyphWorks is a data processing system that contains a comprehensive set of standard and
specialized tools for performing durability analysis and other insightful tasks such as digital signal
processing. Designed to handle huge amounts of data, GlyphWorks provides a graphical, process–
oriented environment that contains leading analysis capabilities for research of various processes.
2.1. Means of obtaining test data
Test data of any change in stress-and-strain state of a sprayer boom parts have been obtained by
tensometric method with incoming signals recorded by the developed universal measuring system
(fig. 1) fitted with analogue-digital converter (ADC) with the total number of measuring channels – 8,
where the number of universal measuring channels – 5; the number of vibro-measuring channels – 2;
the number of channels for angular velocity measurement – 1.
Universal measuring channels have provided the work with different resistive sensors and sensors
with an outcoming signal as direct current voltage. Some possible work with different connection
diagrams of resistive sensors has been provided as well: bridge, half bridge, quarter bridge,
potentiometric ones. Discretization frequency can be specified within the range from 1Hz to 2 kHz.
The minimal value of discretization period is 500 µs (the same for all channels).
Power supply to the apparatuses has been provided by the alternative current mains of voltage
220 V 50 Hz or by the direct current mains of voltage 12 V.
The universal measuring system (UMS) has operating properly under the following environmental
conditions: temperature of operation – from + 5 to + 55º C; storage temperature – from -10 to + 55º C;
relative humidity – from 5 to 90 %.
Figure 1: Recording block of universal measuring system (UMS)
Whilst operating with an external computer a crate-controller is connected to a free port of a
computer by a standard cable. Whilst operating in autonomous mode a crate-controller is connected to
a parallel port plug-and-socket of a microcomputer by a bridge cable (fig. 1). The apparatuses are
controlled in autonomous mode by a set of functional buttons.
The preset operation parameters of the universal measuring system include: gain ratio, cutoff
frequency of low frequency, a mode of measurement, connection diagram of the channel, power
supply voltage of sensors, values of zero shift (by default equals to 2048), a period of discretization (is
set the same for all channels) and a kind of separating characters between the recorded data. These
parameters are prescribed before the start of the measurements by means of MODE.DAT file
formation and bringing it into the system memory where the codes of the system operation parameters
values are recorded in columns for all eight channels of the system (a separate column corresponds to
each channel). MODE.DAT file view illustration of universal measuring system settings to test the
sprayer boom is shown on fig. 2.
Figure 2: Universal measuring system (UMS) settings file to test the sprayer boom
The results of measurements are recorded as a 12-bit code and are given by the universal
measuring system as DATA.DAT file where the data of each channel is recorded in a row as digital
codes separated by a separating character whose form is prescribed in previous settings of the system
in MODE.DAT file. Thus, in the obtained data array the information from each specific channel of the
universal measuring system is recorded in every eighth log. These data flow is a set of different digital
codes which should be given in more convenient for calculations form. To achieve this goal there is a
special technique of preliminary processing of test data prior to their possible use in further
calculations.
A special software providing the data sorting of the obtained array to certain channels and reducing
the digital codes of each channel to the real physical quantities with dimensional units (such as, for
example, deformation (mm) or stress (МРА)) has been developed [12] for test data preliminary
processing. The program interface view illustration (interface is in Ukrainian) is shown on fig. 3.
Figure 3: Program interface to converting test data array obtained from UMS
Converting of the digital codes of data array to the real physical quantities with dimensional units
has been provided by formula (see the program interface on fig. 3) by means of taking into account a
number of coefficients: zero level of data (Нуль =); tensosensors calibration test coefficient,
amplification factor, and others (К1–К4); coefficient of static stress level (К5). The level of static
stress should be taken into account when tensosensors are installed on preliminary loaded parts of a
bearing structure. For analytical determination of static stress level in the components of the boom
structure under discussion a mathematical model has been developed which describes the distribution
of internal efforts in the sprayer boom parts on the basis of the potential energy of deformation
minimizing method [18].
Due to the test data array processing by the developed program [12] we have obtained eight files
ChannelN.txt (where N = 1 – 8 matches the channel order number) with the data prepared for the
signal processing from each channel. The data from the first four separate tensometric channels of the
universal measuring system (fig. 4) is a function of time, their amplitude and level are constantly
varying.
Channel 1 Channel 2
Channel 3 Channel 4
Figure 4: Test data of tensometric channels of UMS at test of the sprayer boom
Despite the curves start from the nominal zero, a so-called drift (offset) can be observed here
which varies between the channels and non-linearly over time. It has been caused by the impact of
different external factors (change in temperature, screen grid guidance, contacts reduction due to the
vibration action, humidity etc.) on the measurement process resulted in an offset on the sensor output.
This caused a final value displacement at the end of the test that is no longer the expected zero
value. This effect should be taken onto account as it may cause some errors in the results which are
important in assessment of the structure fatigue durability.
2.2. Test data correction
Under test data digital processing conditions by specialized software tools the data drift effect has
been corrected by the use of various linear filters with maximal flat amplitude-frequency
characteristic in the range of transmission.
A method of test data correction has been used to remove the drift effect in the paper under
discussion. The above-mentioned method consists in separation of average values from the data array
so that to reduce the curves to the nominal zero level. Data correction will be provided by software
tools nCode GlyphWorks aimed at their preparation for further use in the structure durability
assessment by software tools nCode DesignLife.
GlyphWorks is a multi-file, multi-channel, multi-format environment for processing large amounts
of data. GlyphWorks represents data analysis processes graphically. It lets drag and drop graphical
representations of interactive data analysis processes that allow create and save sophisticated working
projects for later re-use.
The basic analysis building blocks used in GlyphWorks are termed glyphs. Glyphs are connected
by pipes, which contain the data that passes between glyphs and attach at the glyph’s pads (different
types of I / O pads are marked with different colors).
In fact, Glyph is a calculation module (template) with specified algorithms of certain functions
performance and with possible setting of different parameters of its properties. A set of glyphs with
functional connections is the detailed design of the research.
The general view of Interface nCode GlyphWorks is shown on fig. 5. These are the main windows
of the GlyphWorks interface (there are several other windows that can be turned on using the View
menu):
1. Analysis Workspace — Where the process is created
2. Available Data — Data that can be analyzed
3. Diagnostics — List of process, error messages, etc.
4. Glyph Palette — Glyphs available for processing
1
2
4
3
Figure 5: The main windows of the GlyphWorks interface
GlyphWorks glyphs are classified according to their functionality. The glyphs are available in the
glyph palette (the window on the right side на рис. 5). There are sections in the glyph palette for
glyphs that input data, perform basic digital signal processing (DSP), display results, and so on.
Glyphs are organized into the following categories (palettes), according to their functionality:
Input; Function; BasicDSP;Signal; DesignLife; Frequency; Fatigue; AcceleratedTesting; Optimized
Testing; GlyphBuilder; SuperGlyph; Display and Output.
Glyphs and input files, etc., can be dragged onto the workspace from their respective palettes.
In GlyphWorks, a process is defined as a combination of glyphs that define a data flow. A process
typically starts with an input glyph to define the data to be processed. Additional glyphs define
subsequent steps in the process for calculation, display, or writing output.
To implement the procedure of test data correction a detailed design has been developed
(fig. 6) containing the following structural elements (glyphs): Exel Input, Multi-Column To
Time Series, Running Statistics, Arithmetic, Time Series Output, XY Display. Functional
purpose, parameters settings of these glyphs and structural relations between glyphs are
described lower.
Structural elements (glyphs) with relations can be combined conditionally into functional
blocks (fig.6) where the successive steps of test data correction procedure are taking place
and the obtained results are represented as curves:
І – a block of incoming data input,
ІІ – a block of incoming data statistical processing,
ІІІ – a block of mathematical operations on incoming data,
ІV – a block of results analysis and comparison,
V – a block of results saving.
I
II
III
V IV
Figure 6: The process flow that removes running mean of the sprayer boom test data (completed)
To input some test data into the detailed design an executable file .xls has been formed where the
data columns from binary files were added including the results of primary processing of four
tensometric channels (fig.4). Above each data column the lines are located with channel name
(Channel1- Channel4) and units of measurements (МРА).
The obtained executable file .xls was uploaded to the glyph of multicolumn data ExelInput1 (fig.6,
block І). For correct representation of the uploaded data in glyph ExelInput1 settings it is necessary
(fig. 7):
– in section Column Title Cells the tape cells with channels name should be specified;
– in section Column Units Cells the tape cells with dimensional values should be specified;
– in section Value Cells the tape cells with the initial data of the columns should be specified;
– Process rows up to first empty row should be specified.
Figure 7: ExelInput1 glyph properties
MultiColumnToTimeSeries glyph (fig.6, block І) is used for the conversion of multi-column data
into the data of temporal series. The glyph is connected to the orange output pad on ExcelInput1.
The following parameters should be specified in the properties of this glyph (fig. 8):
Method → Resample;
SampleRate → 500 (fig. 2);
Interpolation → Linear.
Figure 8: MultiColumn to Time Series glyph properties
XY Display glyph has been used to show the incoming data. On fig. 6 it is renamed as Time Series
Data. This glyph input is connected with the glyph MultiColumnToTimeSeries output. The incoming
data representation results of are shown on fig. 9.
Figure 9: Incoming data curves
A special glyph Running Statistics has been used for incoming data statistical processing enabling
us to process the data by methods of mathematical statistics using the special methods nCode. This
glyph input is connected with the glyph MultiColumnToTimeSeries output.
In the settings of calculation template RunningStats1 in Tab General (fig. 10) we have chosen a
type of data statistical processing Мean (by average value). The parameter ProcessingMethod
determines how the current data will be processed. We have chosen the method PointByPoint where
each value of test data will be processed in a series resulted in a set of sequential measurements and
the general statistics of the experiment will be formed on their basis. Such method guarantees that the
source file with processed data will have the same amount of data that the initial original file contains.
In the tab WindowLength we have specified the number of displayed points in the parameters of
visualization – 1000.
Figure 10: Running Statistics glyph properties
The results of statistical processing of test data from Channel 3 by their average value are shown
on fig. 11. On fig. 6 this glyph is renamed as Running Mean Calculated. The first input of this glyph
is connected with the output of MultiColumnToTimeSeries and the second input is connected with
RunningStats1. Thus, the upper curve shows the data incoming array from Channel 3, and the lower
one represents their average values. It has made possible to follow the data offset on the curves and to
estimate the drift of the most important values of the results.
Figure 11: Running Mean Calculated glyph
Glyph Arithmetic1 makes possible to perform mathematical operations on the data prepared in
advance. The first stroke of this glyph is connected with the output MultiColumnToTimeSeriesand the
second output is connected with RunningStats1.
In settings of the glyph Arithmetic1 (fig. 12) in the tab General in section Operator we have chosen
the type of arithmetical operation Equation. In section EquationDefinition we write the parameter
Equation as «Test 1 – Test 2» (difference in incoming and processed in the module RunningStats1
data array).
Figure 12: Arithmetic glyph properties
The results of test data processing by glyph Arithmetic are shown on fig. 13. On fig. 6 this glyph is
renamed as Running Mean Removed. This glyph input is connected with the glyph Arithmetic1
output. The obtained data have not included “spurious” current data yet which can alter the general
operating characteristics of the unit under discussion.
Figure 13: Resulting data with running mean removed
In practice one should always be careful while using such techniques and manipulations with the
data arrays as a share of valid data can be lost after some mathematical operations resulted in the
distortion of the real process description. It is necessary to check and analyze the obtained results.
To check the adequacy of the obtained results we have compared them with the results of
incoming data processing by means of the standard procedure, such as, for example, the use of a filter
of high frequency which enables to isolate the low frequency signals from the data array.
In nCode GlyphWorks this possibility can be implemented by frequency filter based on the tool
ButterworthFilter. For this purpose, we have added the glyph ButterworthFilter from section
BasicDSP (basic digital signal processing) to the temporary field of the project. For the correct
connection of this filter to the detailed design we have connected the template
MultiColumnToTimeSeries output with the template ButterworthFilter input and we have connected
the template ButterworthFilter output with another input of the pattern Data Comparison. We have
connected the first input of this pattern with the output of the glyph Arithmetic1.
To set the calculating pattern ButterworthFilter we choose the type of filtration HighPass in its
characteristics, method of filtration – ForwardAndBackward, parameter Order (ranking) – 8, filtration
frequency Frequency1 – 0,1 and parameter DCWarning (percentage of errors) is specified as 0,01.
Figure 14: ButterworthFilter glyph properties
After calculations in the graphic glyph XY Display (entitled Data Comparison on fig. 6) two
curves will be displayed (fig. 15, а) obtained due to the incoming data array processing by two
different methods – by average values subtraction of the initial data array and using the filter of high
frequencies (the curves only from the first channel are shown on the figure). To draw the curves the
first input of the glyph Data Comparison was connected with the glyph Arithmetic1, the second one –
with the glyph ButterworthFilter2 output.
a) b)
Figure 15: Comparison of test data array correction by two methods
To make the comparison more convenient these curves have been superimposed (fig. 15, b).
As we can see on fig. 15 the results of test data correction by two methods intercommunicate very
well. Moreover, both methods from the engineering point of view correctly describe the conversion
procedure of the results obtained by the method of signals digital capture from the tensosensors
installed on the real structure. In these corrected data the drift of average values of the process indices
has already taken into account and we can be sure that the amplitude will vary correctly enabling to
determine the real number of cycles of the structure loading according to the techniques and
theoretical substantiation of the above-mentioned results [19].
The following ways are mostly used in calculations: of maximums, of ranges (amplitudes), of
augmented ranges, of complete cycles, "rain-flow" method. The main advantage of these ways is that
they do not restrict the schematized process, i.e. any mode of loading can be processed by these
methods [20].
By means of the glyph TSOutput2 the obtained results, which are the function in time, are
recorded in a separate file of the pattern *.s3t with the prefix _out. The obtained file with the
processed and prepared test data can be further used to calculate the fatigue durability of the structure.
3. Conclusion
The results of any experimental research dealing with data collecting and processing, are likely to
have some errors. The analysis of obtained results and errors of measurement is an essential part of
any scientific experiment, so a researcher must be able to apply some methods of test data correction.
At present, there is a great number of software for signals obtaining, segmentation, statistical
analysis and processing. The software nCode, which was designed to work with large volumes of test
data, makes possible to carry out processing of experimental signals, both by standard methods and by
the developed alternative techniques of data processing.
In the paper under discussion the drift of experimental data has been corrected so that to reduce the
test data curves to the nominal zero level. Two approaches have been applied to test data correction to
remove the drift effect, namely the use of high frequency filter and the removal of the data array
average values. The results of test data correction by two methods have intercommunicated very well.
Both methods from the engineering point of view correctly describe the conversion procedure of
the results obtained by the method of signals digital capture from the tensosensors installed on the real
structure. The obtained results can be used in carrying further out research of the structure durability.
4. Acknowledgements
I am very grateful to the company HBM Prenscia and the team nCode for the possibility to use
their software and for the information support. My special thanks to Lukasz Pieniak – Account
Manager Prenscia.
I highly appreciate the assistance of the managers of the company «Bohuslav agricultural
machinery» Havrylenko P.М. and Havrylenko М.P. in their cooperation with the department of
technical mechanics and agricultural machines of Ternopil Ivan Puluj national technical university
during the experimental studies of the dynamic loading of wide-spray field sprayer boom.
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