Image processing for displacement measurements

Since the invention of photography humans have been using images to capture, store and analyse the act that they are interested in. With the developments in this field, assisted by better computers, it is possible to use image processing technology as an accurate method of analysis and measurement. Image processing's principal qualities are flexibility, adaptability and the ability to easily and quickly process a large amount of information. Successful examples of applications can be seen in several areas of human life, such as biomedical, industry, surveillance, military and mapping. This is so true that there are several Nobel prizes related to imaging. The accurate measurement of deformations, displacements, strain fields and surface defects are challenging in many material tests in Civil Engineering because traditionally these measurements require complex and expensive equipment, plus time consuming calibration. Image processing can be an inexpensive and effective tool for load displacement measurements. Using an adequate image acquisition system and taking advantage of the computation power of modern computers it is possible to accurately measure very small displacements with high precision. On the market there are already several commercial software packages. However they are commercialized at high cost. In this work block-matching algorithms will be used in order to compare the results from image processing with the data obtained with physical transducers during laboratory load tests. In order to test the proposed solutions several load tests were carried out in partnership with researchers from the Civil Engineering Department at Universidade Nova de Lisboa (UNL)

In vitro assessment of the primary stability of the acetabular component in hip arthroplasty

In Europa, più di 700'000 interventi di artroplastica d’anca vengono effettuati annualmente. Il tasso di fallimento della chirurgia è del 2-8 % (a 10 anni). Di questo, più del 50% è dovuto alla mobilizzazione asettica della componente acetabolare (più che ad un fallimento legato alla componente femorale). Lo scopo centrale di questo progetto di tesi è quello di creare un pilot-test per la valutazione in vitro della stabilità primaria di una componente acetabolare commerciale, impiantata in una emipelvi sintetica (senza cemento, attraverso la procedura chirurgica press-fit). La valutazione dei micromovimenti prevede un approccio multiplo, costituito dall’utilizzo della Digital Image Correlation (DIC) e di sensori lineari di spostamento. Per adeguare e migliorare le prestazioni dei due strumenti di misura, lo studio prevede: (1.a) l’ottimizzazione delle misure ottenute dalla correlazione di immagini, (1.b) creare ed effettuare la procedura di calibrazione interna dei sensori di spostamento e l’ottimizzazione delle misure ottenute dai sensori stessi come monitor dell’intero pilot-test. La seconda parte del lavoro si prone di implementare una metodologia affidabile per il calcolo delle roto-traslazioni relative tra coppa e osso. La creazione di un algoritmo dedicato, prevede, quindi, di valutare: (2.a) la migrazione permanente e (2.b) i micromovimenti inducibili dai picchi di carico.L’utilizzo della correlazione di immagini è risultato un gran punto di forza dello studio. Grazie al potere della DIC nell’elaborare spostamenti e deformazioni a tutto campo, senza contatto e in stereofotogrammetria, per la prima volta è stato possibile ottenere informazioni 3D del vettore migrazione della coppa. Inoltre, creando una procedura ottimizzata dell’allineamento del provino sotto la macchina, si sono potute riferire tutte le misure ottenute dal pilot-test, all’Aneterior Pelvic Plane (sistema di riferimento di rilevanza clinica)

Failure Diagnosis and Prognosis of Safety Critical Systems: Applications in Aerospace Industries

Many safety-critical systems such as aircraft, space crafts, and large power plants are required to operate in a reliable and efficient working condition without any performance degradation. As a result, fault diagnosis and prognosis (FDP) is a research topic of great interest in these systems. FDP systems attempt to use historical and current data of a system, which are collected from various measurements to detect faults, diagnose the types of possible failures, predict and manage failures in advance. This thesis deals with FDP of safety-critical systems. For this purpose, two critical systems including a multifunctional spoiler (MFS) and hydro-control value system are considered, and some challenging issues from the FDP are investigated. This research work consists of three general directions, i.e., monitoring, failure diagnosis, and prognosis. The proposed FDP methods are based on data-driven and model-based approaches. The main aim of the data-driven methods is to utilize measurement data from the system and forecast the remaining useful life (RUL) of the faulty components accurately and efficiently. In this regard, two dierent methods are developed. A modular FDP method based on a divide and conquer strategy is presented for the MFS system. The modular structure contains three components:1) fault diagnosis unit, 2) failure parameter estimation unit and 3) RUL unit. The fault diagnosis unit identifies types of faults based on an integration of neural network (NN) method and discrete wavelet transform (DWT) technique. Failure parameter estimation unit observes the failure parameter via a distributed neural network. Afterward, the RUL of the system is predicted by an adaptive Bayesian method. In another work, an innovative data-driven FDP method is developed for hydro-control valve systems. The idea is to use redundancy in multi-sensor data information and enhance the performance of the FDP system. Therefore, a combination of a feature selection method and support vector machine (SVM) method is applied to select proper sensors for monitoring of the hydro-valve system and isolate types of fault. Then, adaptive neuro-fuzzy inference systems (ANFIS) method is used to estimate the failure path. Similarly, an online Bayesian algorithm is implemented for forecasting RUL. Model-based methods employ high-delity physics-based model of a system for prognosis task. In this thesis, a novel model-based approach based on an integrated extended Kalman lter (EKF) and Bayesian method is introduced for the MFS system. To monitor the MFS system, a residual estimation method using EKF is performed to capture the progress of the failure. Later, a transformation is utilized to obtain a new measure to estimate the degradation path (DP). Moreover, the recursive Bayesian algorithm is invoked to predict the RUL. Finally, relative accuracy (RA) measure is utilized to assess the performance of the proposed methods

Computer Vision Based Structural Identification Framework for Bridge Health Mornitoring

The objective of this dissertation is to develop a comprehensive Structural Identification (St-Id) framework with damage for bridge type structures by using cameras and computer vision technologies. The traditional St-Id frameworks rely on using conventional sensors. In this study, the collected input and output data employed in the St-Id system are acquired by series of vision-based measurements. The following novelties are proposed, developed and demonstrated in this project: a) vehicle load (input) modeling using computer vision, b) bridge response (output) using full non-contact approach using video/image processing, c) image-based structural identification using input-output measurements and new damage indicators. The input (loading) data due vehicles such as vehicle weights and vehicle locations on the bridges, are estimated by employing computer vision algorithms (detection, classification, and localization of objects) based on the video images of vehicles. Meanwhile, the output data as structural displacements are also obtained by defining and tracking image key-points of measurement locations. Subsequently, the input and output data sets are analyzed to construct novel types of damage indicators, named Unit Influence Surface (UIS). Finally, the new damage detection and localization framework is introduced that does not require a network of sensors, but much less number of sensors. The main research significance is the first time development of algorithms that transform the measured video images into a form that is highly damage-sensitive/change-sensitive for bridge assessment within the context of Structural Identification with input and output characterization. The study exploits the unique attributes of computer vision systems, where the signal is continuous in space. This requires new adaptations and transformations that can handle computer vision data/signals for structural engineering applications. This research will significantly advance current sensor-based structural health monitoring with computer-vision techniques, leading to practical applications for damage detection of complex structures with a novel approach. By using computer vision algorithms and cameras as special sensors for structural health monitoring, this study proposes an advance approach in bridge monitoring through which certain type of data that could not be collected by conventional sensors such as vehicle loads and location, can be obtained practically and accurately

Stress polishing demonstrator for ELT M1 segments and industrialisation

After two years of research and development under ESO support, LAM and Thales SESO present the results of their experiment for the fast and accurate polishing under stress of ELT 1.5 meter segments as well as the industrialization approach for mass production. Based on stress polishing, this manufacturing method requires the conception of a warping harness able to generate extremely accurate bending of the optical surface of the segments during the polishing. The conception of the warping harness is based on finite element analysis and allowed a fine tuning of each geometrical parameter of the system in order to fit an error budget of 25nm RMS over 300μm of bending peak to valley. The optimisation approach uses the simulated influence functions to extract the system eigenmodes and characterise the performance. The same approach is used for the full characterisation of the system itself. The warping harness has been manufactured, integrated and assembled with the Zerodur 1.5 meter segment on the LAM 2.5meter POLARIS polishing facility. The experiment consists in a cross check of optical and mechanical measurements of the mirrors bending in order to develop a blind process, ie to bypass the optical measurement during the final industrial process. This article describes the optical and mechanical measurements, the influence functions and eigenmodes of the system and the full performance characterisation of the warping harness

Active production of large aspheric optics for astronomy

This thesis is devoted mainly to tackling the unsolved problem of producing secondary mirrors for 8 m telescopes, which will be up to 2-2.5 m in diameter and in excess of 1000 waves aspheric. This cannot be done by traditional methods. The project directly addresses the problem and forms part of the UK's R and D contributions to the Gemini USA/UK/Canada/Brazil/Chile/Argentina project to produce two 8 m telescopes. Its aim was to develop a new active method. The thesis starts with a review of astronomical implications of 8 m telescope projects currently being undertaken or planned worldwide and continues with discussions on technological challenges specifically in main optics production. The first stage of producing the mirror is generation of the aspheric surface profile by diamond milling. This has been directly addressed by developing a new computer-controlled profiler based on the existing manual hardware of the Grubb-Parsons 2.5 m machine. An essential part of the development also includes a computer controlled contact profilometer. The system performance is presented, including calibration, error profile and convergence of error compensation. The main part of the project was to develop polishing using a full size active lap, by which the pressure distribution and hence ablation rate are modulated in real time. The progress of the project is described, starting with a review of other approaches being developed world wide. The overall philosophy and design of active components are presented. Following this, experiments with a sub-diameter polisher and a prototype active lap of 85 cm in diameter, as built, are also described, including methods of testing, ablation algorithm and control theory. The final part of this section discusses the performance of the active polishing lap in terms of functionality at component and system levels. The conclusion briefly summarises the evaluation of the active method and its impact on large optics production. It also gives ideas for future improvements of performance, research work still needed and viable applications for the technique

Using Deep Learning to Predict Plant Growth and Yield in Greenhouse Environments

Funding Information: This work is part of EU Interreg SMARTGREEN project (2017-2021). We would like to thank all the growers (UK & EU), for providing the data. Their valuable feedback, suggestions and comments are highly appreciated to increase the overall quality of this work.Postprin