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Metrology
Special Issues
Novel Dynamic Measurement Methods and Systems
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Novel Dynamic Measurement Methods and Systems

A special issue of Metrology (ISSN 2673-8244).

Deadline for manuscript submissions: 30 June 2024 | Viewed by 3230

Special Issue Editors

Dr. Lukasz Scislo

E-Mail Website
Guest Editor
Faculty of Electrical and Computer Engineering, Cracow University of Technology, 31-155 Cracow, Poland
Interests: structural health monitoring; machinery fault diagnosis; finite element modelling; uncertainty quantification of manufacturing processes and dynamic systems; reliability analysis and robust design optimization; smart structures and sensing technologies including full non-contact methods
Special Issues, Collections and Topics in MDPI journals
Dr. Nina Szczepanik-Scislo

E-Mail Website
Guest Editor
1.European Organization for Nuclear Research (CERN), 1211 Meyrin, Switzerland
2.Laboratory of Heating, Ventilation, Air-Conditioning and Refrigeration, Cracow University of Technology, 31-155 Kraków, Poland
Interests: computational fluid dynamics; finite element modelling; flow measurements; sensing technologies for fluid and gas systems; environmental engineering; energy consumption; contaminant distribution in the air; air quality measurements; cooling and ventilation systems design; HVAC systems; cryogenics
Prof. Dr. Serge Demidenko

E-Mail Website
Guest Editor
School of Engineering and Technology, Sunway University, Petaling Jaya 47500, Malaysia
Interests: electronic design and test; signal generation and processing; instrumentation and measurement

Special Issue Information

Dear Colleagues,

An array of measuring instruments can be used to make dynamic measurements of quantities with time-dependent values. Quantities with rapidly changing values, such as vibrations, torque, pressure, force, or flow, are typical examples.

A number of metrology areas now require dynamic measurements instead of the traditional steady-state or static characterisations of a sensor’s performance that were used in the past.  Measurement and calibration methods, as well as methods for evaluating uncertainty and correcting sensor outputs, may be required to meet these challenges.

The main, current topics of investigation include: 
•    New or improved sensors;
•    Non-contact measurement methods;
•    Dynamic calibration and shock testing;
•    Methods for improving the quality of the results;
•    Methods for acquiring information and conecton with finite element models (spectrum analysis, parametrical identification, and modal analysis);
•    Special application areas, such as vibrations and vibro-acoustics, biomechanics of human movement, full-scale monitoring of civil structures, aerodynamics and wind tunnel testing, fluid dynamics, and image-based measurements.

This Special Issue aims to review the mathematical theory, signal processing, and elements of metrology. In addition, special attention will be paid to novel measurement systems, especially non-contact ones. 

Areas of interest include, but are not limited to: 
•    Sound and vibration measurements;
•    Seismic measurements;
•    Gas and fluid dynamic measurements; 
•    Three-dimensional optical sensors and devices (e.g., 3D laser vibrometry, particle image velocimetry, high-speed cameras);
•    Data acquisition and signal processing;
•    Artificial-intelligence-assisted techniques;
•    Analysis of dynamic measuring errors;
•    Diagnostics of the machines;
•    Computational methods for dynamic measurements;
•    Modelling and identification of dynamical systems;
•    Dynamics of machinery and rotating systems;
•    Transport systems, vehicles, and measuring problems;
•    Structural dynamics and vibrations of composite material structures;
•    Dynamic measurement problems in environmental engineering; 
•    Flow and flow-induced vibrations, and fluid–structure interactions; 
•    Dynamic behaviour of isolation elements and systems.

Both review papers and in-depth research papers on new developments in this field will be collected in this Special Issue.

Dr. Lukasz Scislo
Dr. Nina Szczepanik-Scislo
Prof. Dr. Serge Demidenko
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Metrology is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • dynamic measurements
  • transfer function
  • vibration measurement
  • condition monitoring
  • finite element modelling
  • structural health monitoring
  • modal analysis
  • FFT
  • dynamic calibration
  • flow measurements

Published Papers (3 papers)

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Research

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16 pages, 5548 KiB  
Article
Deep Learning for Concrete Crack Detection and Measurement
by Mthabisi Adriano Nyathi, Jiping Bai and Ian David Wilson
Metrology 2024, 4(1), 66-81; https://doi.org/10.3390/metrology4010005 - 05 Feb 2024
Viewed by 755
Abstract
Concrete structures inevitably experience cracking, which is a common form of damage. If cracks are left undetected and allowed to worsen, catastrophic failures, with costly implications for human life and the economy, can occur. Traditional image processing techniques for crack detection and measurement [...] Read more.
Concrete structures inevitably experience cracking, which is a common form of damage. If cracks are left undetected and allowed to worsen, catastrophic failures, with costly implications for human life and the economy, can occur. Traditional image processing techniques for crack detection and measurement have several limitations, which include complex parameter selection and restriction to measuring cracks in pixels, rather than more practical units of millimetres. This paper presents a three-stage approach that utilises deep learning and image processing for crack classification, segmentation and measurement. In the first two stages, custom CNN and U-Net models were employed for crack classification and segmentation. The final stage involved measuring crack width in millimetres by using a novel laser calibration method. The classification and segmentation models achieved 99.22% and 96.54% accuracy, respectively, while the mean absolute error observed for crack width measurement was 0.16 mm. The results demonstrate the adequacy of the developed crack detection and measurement method, and shows the developed deep learning and laser calibration method promotes safer, quicker inspections that are less prone to human error. The method’s ability to measure cracks in millimetres provides a more insightful assessment of structural damage, which is, in comparison to traditional pixel-based measurement methods, a significant improvement for practical field applications. Full article
(This article belongs to the Special Issue Novel Dynamic Measurement Methods and Systems)
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26 pages, 10860 KiB  
Article
Organized Computational Measurement to Design a High-Performance Muffler
by Mehran Saadabadi, Mahdieh Samimi and Hassan Hosseinlaghab
Metrology 2023, 3(3), 254-279; https://doi.org/10.3390/metrology3030015 - 14 Jul 2023
Viewed by 1596
Abstract
Engine noise, as a source of sound pollution for humans and the environment, can be reduced by designing a high-performance muffler. This study presents a novel, organized design process of that muffler for the KTM390 engine as a case study. The acoustic simulation [...] Read more.
Engine noise, as a source of sound pollution for humans and the environment, can be reduced by designing a high-performance muffler. This study presents a novel, organized design process of that muffler for the KTM390 engine as a case study. The acoustic simulation analysis is performed in COMSOL software and aerodynamic analysis is performed in ANSYS Fluent. The features of the muffler considered in this designing process are the overall length of the muffler, the presence of baffles and related parameters (baffle distance, baffle hole diameter, and baffle hole offset), and the effects of extended tubes. In order to evaluate the acoustic performance of the muffler, an objective function has been defined and measured on two frequency ranges, 75–300 Hz and 300–1500 Hz. For evaluating the aerodynamic performance of that, the amount of backpressure is analyzed to achieve a maximum of 3.3 kilopascals for this muffler. The selection of the appropriate parameters includes comparing the resulting transmission loss curves and quantitative evaluation of objective functions (for transmission loss) and backpressure. This organized design process (i.e., tree diagram) leads to an increase in the efficiency of designing mufflers (for example, 41.2% improvement on backpressure). Full article
(This article belongs to the Special Issue Novel Dynamic Measurement Methods and Systems)
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Review

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24 pages, 9313 KiB  
Review
Combined Use of Acoustic Measurement Techniques with X-ray Imaging for Real-Time Observation of Laser-Based Manufacturing
by Mahdieh Samimi, Mehran Saadabadi and Hassan Hosseinlaghab
Metrology 2024, 4(2), 181-204; https://doi.org/10.3390/metrology4020012 - 08 Apr 2024
Viewed by 406
Abstract
Ensuring high-quality control in laser additive manufacturing and laser welding relies on the implementation of reliable and cost-effective real-time observation techniques. Real-time monitoring techniques play an important role in understanding critical physical phenomena, namely, melt pool dynamics and defect formation, during the manufacturing [...] Read more.
Ensuring high-quality control in laser additive manufacturing and laser welding relies on the implementation of reliable and cost-effective real-time observation techniques. Real-time monitoring techniques play an important role in understanding critical physical phenomena, namely, melt pool dynamics and defect formation, during the manufacturing of components. This review aims to explore the integration of acoustic measurement techniques with X-ray imaging for studying these physical phenomena in laser manufacturing. A key aspect emphasized in this work is the importance of time synchronization for real-time observation using multiple sensors. X-ray imaging has proven to be a powerful tool for observing the dynamics of the melt pools and the formation of defects in real time. However, X-ray imaging has limitations in terms of accessibility which can be overcome through combination with other more-accessible measurement methods, such as acoustic emission spectroscopy. Furthermore, this combination simplifies the interpretation of acoustic data, which can be complex in its own right. This combined approach, which has evolved in recent years, presents a promising strategy for understanding acoustic emission signals during laser processing. This work provides a comprehensive review of existing research efforts in this area. Full article
(This article belongs to the Special Issue Novel Dynamic Measurement Methods and Systems)
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