| Topic title |
Possible scientific supervisors |
Source of funding |
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Ultrasonic measurement and X-ray tomography for non-destructive testing, technical and medical diagnostic methods:
1. Detection and characterization of defects in complex structures using artificial intelligent algorithms (prof. L. Mažeika);
2. 3D visualization of internal structures using multi-dimensional x-ray and ultrasonic data fusion (prof. E. Jasiūnienė);
3. Application of artificial intelligence methods for analysis and classification of ultrasonic diagnostic images (prof. R. Raišutis).
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prof. dr. Liudas MAŽEIKA |
state-funded |
Research Topic Summary.
The main scope of the research carried on at Prof. K. Baršauskas Ultrasound Research Institute is "Ultrasonic and X-ray methods for measurement of non-electrical quantities, non-destructive testing and technical diagnostics”.
The efficiency and actuality of development of such methods are caused by rapid industrial and business evolution, which leads to the complexity of implementations of higher-level technologies. These technologies require innovative measurement and monitoring methods, enabling fast automatic decision-making. Ultrasonic measurements is one of the technology allowing a relatively higher degree of automation, however, it requires innovative, integrated solutions for the electronics and signal processing, the implementation of which is particularly complicated under operating conditions of high temperature and pressure, or the complicated structure of the objects itself. The research topic covers areas such as:
? ultrasonic imaging methods under extreme conditions;
? ultrasonic transducers for special applications (high temperature, air-coupled);
? Multi-dimensional x-ray and ultrasonic data fusion
? ultrasonic testing methods of composite materials;
? application of ultrasonic guided waves for non-destructive testing of planar and tubular engineering structures;
? ultrasonic monitoring methods of potentially dangerous objects;
? application of ultrasonic waves and X-ray for imaging and measurement of spatial properties of solid and liquid materials;
? ultrasonic measurement and imaging methods in biology and medicine;
? Application of artificial intelligence methods for analysis and classification of ultrasonic diagnostic images
The aim of the proposed work is to create and improve the new measurement, diagnostic and monitoring technologies in industry and medicine for solving the mentioned problems.
The problem-solving tasks include investigation of ultrasonic and X-ray waves in different environments using modelling and experiments, measurement of characteristics and performance of ultrasonic transducers, development of novel measurement methods, design of electronic solutions and development of signal processing methods.
The experience of Prof. K. Baršauskas Ultrasound Research Institute: 24 FP program projects, 2 Eurostars projects, 1 Lithuanian-Swiss project supported by Research Council, contracts with international business partners. 2 LMT projects, 1 MITA project. Interdisciplinary projects: 5 KTU-LUHS 1 KTU- LUHS -VDU and 6 KTU-KTU. In addition, 3 H2020 projects are carried on now. Still waiting for evaluation results of 2 H2020 projects applications. Currently, in Ultrasound Research Institute are studying 10 PhD students. In 2020 1 PhD student successfully defended PhD theses.
The joint PhD programme together with international institution “TWI-The Welding Institute” from UK is carried on. Duration of studies is 1 year in Lithuania, 3 years of research in United Kingdom (Cambridge).
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| Development of non-invasive technologies for prevention of brain functions‘ impairments during surgeries with general anesthesia (cardiac surgery, transplantation of organs and etc.). |
prof. dr. Arminas RAGAUSKAS
vyr.m.d. dr. Vytautas PETKUS |
state-funded |
| Development and research of monitoring technology for diagnosis and treatment of Normal Tension Glaucoma |
prof. dr. Arminas RAGAUSKAS
vyr.m.d. dr. Vytautas PETKUS |
state-funded |
| Energy Efficient Smart City Controllers Networks for Remote Monitoring |
prof. dr. Darius ANDRIUKAITIS |
state-funded |
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Efficient signal excitation and processing technologies for ultrasonic measurements and imaging
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prof. dr. Linas SVILAINIS |
state-funded |
Research Topic Summary.
Measurement and imaging resolution demand for reliable signals separation, but limited bandwidth is causing the signals to overlap. Research is aimed to develop the efficient signal excitation and processing techniques for ultrasonic imaging and measurements.
Reliable time of flight and reflection amplitude estimation, imaging resolution and contrast are improved thanks to binary excitation spread spectrum signals application. Overlapping reflections are resolved either by spectroscopic or iterative deconvolution techniques. Correlation sidelobes, signal bandwidth can be optimized/corrected thanks to innovative excitation signals. Excitation is not limited to conventional acoustic sources, but also photoacoustics can be used. Laser ultrasound excitation can use spread spectrum signals which in turn can be adapted to spectral/correlation properties requirements. Reference signals can be made adaptable in order to increase the deconvolution efficiency. New signal quality is obtained thanks to efficient excitation and processing, which in turn enhances the possibilities for imaging and measurements. Results are planned to apply for non-contact and air coupled measurements in cooperation with research groups from Spain, Italy, UK. Envisaged applications are plants, nanocomposite parameters measurement, flow measurement, food industry or non-destructive evaluation of plastic components or even evaluation of ultrasonic transducers quality.
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Investigations of parametric imaging and monitoring technologies based on cardiovascular dynamics
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v.m.d. dr. Rytis JURKONIS |
state-funded |
Research Topic Summary.
The cardiovascular system determines the functions of human tissues and organs and their pathologies. The dynamics of this system are an underused source of information in the development of imaging and monitoring technologies for early diagnosis, tissue characterization, and monitoring of quantitative changes and risks. The scientific problem is to obtain reliable quantitative diagnostic information about tissue structure and physiological changes using cardiovascular system dynamics recording and analysis tools.
The aim of the research is to develop innovative signal flow processing algorithms, monitoring and ultrasonic parametric imaging technologies using the dynamic characteristics of the cardiovascular system - parameters of heart rate and pulsation in blood vessels and tissues and their relationship with tissue perfusion and microstructure changes. To achieve this goal, it is planned to develop and test algorithms and software for recording physiological signals characterising the cardiovascular system, to compare the results with the development of quantitative ultrasonic methods to record dynamic changes in tissue structure and organs morphology. Utilize the identified synergies and offer biomarkers for early diagnosis of pathologies and risk warning. The main expected results are innovative methods and algorithms for processing and parametric imaging of radio frequency ultrasound and photoplethysmographic signals for a new generation of ultrasound scanners and continuous monitoring systems. Algorithms are to be implemented in the form of software modules and plugins. The methods developed will be adapted to collect big data for machine learning and decision support using artificial intelligence. Applications in gastroenterology, cardiology, endocrinology, characterization of biotissue are waranted.
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Research of Non-invasive Remote Error Monitoring Techniques for Smart Energy Meters
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prof. dr. Žilvinas NAKUTIS |
state-funded |
Research Topic Summary.
The reliability of energy metering equipment and the timely detection of degrading of metrological performance are more relevant than ever in the light of the post-pandemic energy crisis and the EU's Green Deal policy. Also, with the intensification of digitalization solutions in energy metering systems, data flows generated by smart meters open up new possibilities to quickly detect anomalies in power consumption profiles caused by changes in measurement equipment characteristics, energy thefts, changes technical losses or cyber attacks. The changes in the working conditions of energy meters and the changes in the quality of electricity caused by the accelerating penetration of renewable energy sources in electricity distribution grid pose no less challenges. As the requirements for better protection of electricity consumers increase, one of the solutions is continuous remote surveillance of smart meter errors in-service. However, the scientific problem related to the lack of knowledge how to monitor meter errors non-invasively and how to determine estimated meter error uncertainty in real distribution grids. The aim of the research is to prove the assumptions for the development of a non-invasive remote monitoring method for smart meters and to characterize the monitoring uncertainty together with influencing sources. As data anomalies may be caused not only by changes in metrological characteristics of meters but also by electricity thefts, technical losses or other causes, the task will extend not only to the quantitative assessment of the change in characteristics but also to the classification according to the causes of the symptoms. Therefore, the application of machine learning methods is likely to address this challenge. The expected result is a new non-invasive method of remotely monitoring meter errors that is suitable for use even when anomalous changes are due to various influencing factors affecting power consumption profiles. Requirements for candidate: modeling of electric systems, digital signal processing, measurement of electrical quantities, embedded systems design.
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Optimal control of sensor-less electric drive for bio-engineering application
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prof. dr. Renaldas URNIEŽIUS |
state-funded |
Research Topic Summary.
The aim of this project is to develop optimal control of sensor-less electric drive for bioengineering
application. The programming control will be based on the noninvasive oxygen
uptake rate feedback from the cell culture (microbial, mammalian or stem cells).
The developed biotechnological process optimal control algorithms and systems would represent
new results in bio-process state estimation and control practice. New knowledge in the soft
sensors development and applications will be obtained and the software technologies for
realization of the soft sensor systems will be developed and tested.
KTU Dept. of Automation, as a project partner, is currently performing a scientific research grant
“Substrate continuous dosing device for programming control of bioprocesses” (No. 01.2.2-
LMT-K-718-03-0039), under which there are opportunities for new researchers to simultaneously
perform their research and participate in the compensated application development for biopharmaceutical
industry.
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