Research team

Industrial Vision Lab (InViLab)

Expertise

Experimental mechanics: vibration engineering, acoustics, strain measurement, experimental fluid mechanics. Optical measurement techniques, sensors. Industrial vision. Signal and image processing. System identification.

Automated Open Precision Farming Platform (Utopia) 01/03/2021 - 29/02/2024

Abstract

Precision-farming needs large-scale adoption to increase production at such a level that it significantly contributes to minimizing the gap between actual and required world-production of food. Increasing the measurement and actuation intervals of e.g. monitoring for pests and watering are expected to contribute to e.g. increased yields. Sensing is an important element to quantify productivity, product quality and to make decisions. Applications, such as mapping, surveillance, exploration and precision agriculture, require a reliable platform for remote sensing. In precision agriculture, the goal is to gather and analyze information about the variability of soil/water and plant conditions in order to maximize the efficiency of the farm field. This would also increase the burden on the farmer, as the measurement-time and data-processing time increases significantly. This can be mitigated with Automated (cooperative) Precision Farming with the use of autonomous driving vehicles, vessels, drones and dedicated installations mounted on regular agri-machinery. For the cooperative robotic missions, the data will be tagged with accurate position information and merged with other data in order to create a digital map. To achieve good performance for an intelligent system in autonomous navigation tasks we will also build a 3D world model which will be integrated with a digital twin at plant level in order to improve the local path such that we obtain accurate information. To integrate the data from heterogeneous sensors, a platform will be developed to determine the practicality of the available sensors for the optimization of the spatio-temporal interpolation. This project will focus on a single (standardized) platform where (robotic)paths, monitoring strategies can be set and the drones/USV's/AGV's automatically deployed when certain conditions are met. The measurement data will be available for different stakeholders in the same platform.

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Nexor - Cyber-Physical Systems for the Industry 4.0 era 01/01/2021 - 31/12/2026

Abstract

The fourth industrial revolution (Industry 4.0 as it is commonly referred to) is driven by extreme digitalization, enabled by tremendous computing capacity, smart collaborating machines and wireless computer networks. In the last six years, Nexor — a multi-disciplinary research consortium blending expertise from four Antwerp research labs — has built up a solid track record therein. We are currently strengthening the consortium in order to establish our position in the European eco-system. This project proposal specifies our 2021 - 2026 roadmap, with the explicit aim to empower industrial partners to tackle their industry 4.0 challenges. We follow a demand driven approach, convincing industrial partners to pick up our innovative research ideas, either by means of joint research projects (TRL 5—7) or via technology licenses.

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Tales from the horned – Exploring the functionality and evolutionary history behind horn occurrence in vipers. 01/11/2020 - 31/10/2022

Abstract

Some species of snakes carry horn-like appendages either on the snout or above the eyes. Interestingly, these structures have evolved independently in multiple clades of vipers (Viperidae). Pioneer herpetologists have speculated wildly on the function of these enigmatic appendages, but nobody has studied them in detail. In this project, I will test the putative role of rostral and supra-ocular horns in concealment, water uptake, mechanosensation and thermoregulation. To that end, I will carry out a combination of behavioural observations, visual modelling, vibrometry, thermography, (electron) microscopy, histology, µ-CT scanning and 3D image reconstructions, on a selection of specimens of different species. In a final step of the project, I will combine information obtained from the functional analyses with data on the distribution, ecology and natural history of viperid species (as available in the literature and online databases) to test ideas on the ecological drivers of horn evolution.

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D Thermal imaging of people using statistical shape models. 01/10/2020 - 30/09/2022

Abstract

In this project, we will develop an easy to use method to monitor the thermal condition of a person as a function of time, with potential applications entailed in physical treatment or a sports activity. The method employs amongst others thermal imaging. To that end, we create a virtual 3D model of the person of interest. The proposed technique will enable the development of a flexible and mobile measurement system, which can be used in labs, hospitals, rehabilitation centers, sports training facilities, etc.

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PhairywinD project 01/03/2020 - 28/02/2025

Abstract

In this PhD research we will develop a non-destructive testing technique for the automated and quantitative inspection of bare and coated steel structures during manufacturing and operation, using a hyperspectral camera. Whereas the human eye and color cameras perceive three colors in the visible range, a hyperspectral camera is able to capture several tens of images over a wider wavelength range. This facilitates observation of phenomena that cannot be observed with traditional cameras. Although hyperspectral cameras have already proven their merit in quality control of food products, their use for non-destructive testing is still at its infancy. The main limitation of hyperspectral imaging is the limited spatial resolution. We will develop an image processing technique to artificially increase the spatial resolution of hyperspectral images. We will deploy a technique to continuously scan over the surface of the structure in order to reduce inspection times and we will apply the hyperspectral NDT technique to deblur images.

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Investigating fundamental plasma effects on tumor microenvironment through development of a controlled plasma treatment system for clinical cancer therapy. 01/01/2020 - 31/12/2023

Abstract

Non-thermal plasma technology is gaining attention as a novel cancer therapeutic. In the clinic, plasma has been applied to patients with head and neck squamous cell carcinoma, the 6th most common cancer worldwide with long-term survival below 50%. While initial studies are promising (e.g. partial remission, decreased levels of pain, no reported side-effects), a critical issue became apparent when translating plasma technology from the laboratory to the clinic: low reproducibility of treatment. Current plasma devices are handheld and require the operator (clinician) to make a judgement as to how long to treat the patient. This leads to large variability, which becomes even more pronounced when the clinician must move the plasma applicator over a large area of treatment. We aim to develop a robotic plasma treatment system that will enable us to investigate fundamental plasma effects on the tumor for clinical cancer therapy. We will use multiple sensors to detect the patient environment, artificial intelligence to 'learn and predict' patient disturbance patterns (e.g. breathing), and a robotic arm to deliver plasma. We will test our developed system in 3D and mouse cancer models and study the consequence of plasma treatment in the tumor, and to the survival of the animal. Altogether, our project will progress plasma technology for clinical translation by elucidating previously unknown biological responses to plasma and addressing issues in the clinic.

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Automated inspection of infrastructure using drones (AutoDrone) 01/10/2019 - 30/09/2021

Abstract

In this project we will use drones to detect and monitor damage in infrastructure: wind turbines, bridges, buildings, solar panels, pavements, etc. Firstly, an overview of available path planning tools will be given. Secondly, we will develop machine learning tools to automatically detect damage (cracks, potholes, corrosion). The third aim of the project is the development of a methodology to allow a systematic comparison of repeated drone based camera measurements. During the project 9 case studies will be performed. The project is performed by UAntwerpen and WTCB together with a large consortium of companies active in drone based inspections or owners of infrastructure.

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High-Precision Hybrid Laser-based Additive & Subtractive Manufacturing (Hi-PAS). 01/01/2019 - 31/12/2022

Abstract

The consortium aims to achieve two main goals with this SBO project. First, through a rigorous research methodology to better understand how the roughness fatigue life of additive-made metallic components can be significantly improved. We anticipate this by rolling out a multidisciplinary approach, i.e. in terms of surface and shape metrology, non-invasive quantification of the residual stress and mapping of the process parameters that have an influence on the corrosion mechanisms. Moreover, a strong asset in this project is the possibility to also investigate the interrelationships between phenomena. The second main goal is to build up fundamental knowledge on how the laser-based hybrid production process can be substantially improved: In particular to be able to make complex-shaped metallic components with high precision and this without further intensive post-processing (in particular also known as " first-time-right approach).

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Inspection of road pavements 01/11/2018 - 31/10/2019

Abstract

In this research project we want to take a further step in refining and concretising techniques for an automatic road surface quality inspection for application in the Flemish region, in order to simplify road management and save costs by having the road surface at the right times at the right times to renovate or renew places.

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Development of a novel optical signal processing method for analyzing data of the deformations of the asphalt construction by using Fiber Bragg technology in order to design new asphalt model. 01/07/2018 - 31/12/2019

Abstract

This project focuses on collecting and verifying reliable deformation data of asphalt pavements by using Fiber Bragg Grating sensors. These sensors are already integrated in a bicycle path at the University of Antwerp (project CyPaTs at Campus Groenenborger). FBG is a new technology for measuring deformations in a material, e.g. by external loading. In asphalt pavement, the service life of the lower positioned asphalt layers is directly related to these deformations, loadings and rest periods between loadings. Nowadays, this service life is monitored by Falling Weight Deflection (FWD) measurements only for primary road network and each two years. These measurements are time-consuming, expensive and the road needs to be closed for a certain time. The FBG technology could give a solution to measure these deformations continuously for a lower cost. Moreover, FBG will give more insight in the deformation under all available conditions (temperature of the road, different loadings, rest periods). In order to predict service life, an asphalt response model needs to be developed, based on a monitoring program over at least 1 year. The project will allow to determine long-term ageing and healing properties of the pavement. In this project both technology domains will be used: FBG data will give the deformations in the structure in such a way that the parameters of a visco-elastic plastic asphalt model are optimized continuously. The installed FBG monitoring system of CyPats will be used in this project. Data will be gathered by means of a monitoring campaign in normal conditions (climate) and forced-conditioned on site; calibrated loadings and rest periods. These data will be used for fitting the parameters of a simple response model by Young modulus. The data can be used in future work for parametric fit in more complex models, e.g. a visco-elastic (Burgers) and a visco-elastic plastic model (Huet-Sayegh). A first step will be taken in this project. A challenge to be encountered is to distinguish the effect of ageing and healing, e.g. increase of resistance to deformation during a rest period after a loading set. In current models these are not taken into account and the expected service life has to be estimated by doing FWD tests with a lot of variance in results. Moreover, in the FBG setting, the ageing is monitored continuously. This will give insight in the ageing mechanism in time of asphalt pavements allowing to use this factor as fundamental knowledge. The ageing factor will be used in a complex response model and in a prediction model for estimated service life. Moreover in the future, with this knowledge, a new ageing method under laboratory conditions can be developed based on the measurements on site. The project work program consists of 3 workpackages. The first workpackage focuses on the signal processing of optical FBG spectra i.e. how to determine the peak shifts in order to obtain a correct strain value. workpackage 2 focuses on the identification of the Young modulus from FBG vibration measurements using the so-called inverse modelling approach to identify the mechanical material properties of the different layers of the asphalt, starting from a simple elastic Young's modulus model. Workpackage 3 deals with the monitoring of the Young modulus in time on the asphalt pavement structure of CyPaTs bicycle path during 24 months, and relating these to more complex models.

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Sensing and simulation for smart assembly and logistics (SENSALO) 01/10/2017 - 30/09/2019

Abstract

In the project we use 3D vision techniques in order to make the assembly process more efficient and safer. This is done by tracking people, products and machines (like cobots) in a manufacturing environment.

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Non-linear and time-varying data-based modeling of rotating machinery. 01/07/2016 - 31/12/2017

Abstract

Rotating machines appear in many application fields ranging from large scale applications (e.g. wind turbines) to smaller ones (e.g. medical fluid pumps). The availability of a mathematical model for the dynamical behavior is of crucial importance for the design, prediction and control of these rotating systems. In the scientific domain of "system identification", the mathematical model of the system under test is retrieved through experimental input-output data. Since the dynamical characterization of rotating machines is non-linear as well as time-varying, it cannot be modeled adequately using classical existing estimation or identification methods. The aim of this project is then to develop a theoretical framework to model the time-varying and non-linear dynamical behavior of rotating machinery from experimental data. The proposed methodology consists of modeling the non-linear and time-varying dynamical character of rotating devices through a collection of linear periodically time-varying models. In this project, we will focus on the identification and validation of the non-linear and time-varying dynamics of a mechanical rotor suspended on hydrodynamic plain bearings. The novel approach consists of four main steps: (i) Construction of a non-linear and time-varying virtual model of "fluid-driven" bearing—rotor systems starting from the laws of physics; (ii) Development of a parametric identification technique; (iii) realization and adjustments of the controllable rotor—bearing setup; (iv) validation of the theoretical framework on the real-life rotor—bearing setup.

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Characterization of advanced materials using hybrid inverse modelling from full-field optical vibration measurements. 01/11/2015 - 31/10/2019

Abstract

Quantitative values for mechanical properties of materials are required in the simulation of the behavior of structures and systems in several engineering domains: civil engineering (buildings, bridges, roads, …), mechanical engineering (aircraft, cars, …), biomedical engineering (implants, scaffolds, etc.) and electronic engineering (semiconductor materials). In addition, the knowledge of these material properties provides a means to follow-up the health of a structure or system during operation and to estimate the remaining lifetime. The proposed novel hybrid material characterization method combines two distinct approaches to estimate mechanical material parameters, which has never been attempted before. By using laser Doppler vibrometry for the optical measurement of both resonating (at low frequencies) and propagating surface waves (at high frequencies), modal parameters and wave propagation characteristics can be derived simultaneously. By comparing these results with Finite Element and analytical models and by using an inverse modelling approach with intelligent optimization algorithms, it will be possible to identify more material parameters with an improved accuracy in a reduced measuring time. This will allow applications on more complex materials (e.g. layered poro-elastic road surface) in an in-situ environment. The proposed method will lead to several innovations, in the fields of measuring, data processing and optimization, and will be validated in three different applications: asphalt pavements (civil engineering), composite materials (mechanical engineering), and a tympanic membrane and bone material (biomedical engineering).

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3D imaging assisted vibration measurements for product testing and quality control. 01/10/2015 - 30/09/2019

Abstract

In this project we will develop a technique that combines information from 3D time-of-flight camera's and computer-aided-design drawings of a product in order to facilitate product testing and quality control. The proposed procedure firstly allows the test engineer to automatically determine the sensor positions on a product. Secondly, we develop a methodology to perform vibration measurements on moving components (wind turbines, wind screen wipers, etc. or products on a conveyor belt).

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Frequency domain identification of quasi time-periodic systems with applications in the mechanical and biomedical engineering. 01/10/2015 - 30/04/2017

Abstract

Quasi time-periodic phenomena show up in many engineering fields. One could think of wind turbines or helicopters with rotational speed fluctuations, the vibrations and acoustic noise generated in combustion engines, the electrical impedance of a living heart with heart rate variability for cardio-vascular monitoring, respiratory systems with breathing rate variability, to name a few. Those systems in engineering have the special property that their dynamic behavior changes quasi-periodically over time. The irregularity of the periodicity in the above-mentioned applications can be faithfully modeled by virtue of a periodically time-varying model with varying periodicity. This way of modeling bridges the gap between the well established identification framework for linear time-invariant systems and the more complex approaches for non-linear time-variant systems. The extraction of experimental quasi time-periodic models in the frequency domain meant for physical interpretation, analysis, prediction or control can be a useful step for the practicing engineer. Hence, the main focus of this project will be the development of a generalized identification framework for quasi time-periodic systems with applications in the mechanical and bio-medical engineering.

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Next generation of heterogeneous sensor networks (NEXOR). 01/01/2015 - 31/12/2020

Abstract

This project represents a research contract awarded by the University of Antwerp. The supervisor provides the Antwerp University research mentioned in the title of the project under the conditions stipulated by the university.

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