An Overview and Efficiency Analysis of Dominant Frequencies Estimation Methods with the Application of DIRECT Global Minimization Method

This report discusses the application of the following methods that are used to calculate maximum frequency of a spectrum: parabolic, modified parabolic by Rife and Vincent, the method according to Quinn from 1994 and the method according to Quinn from 1997. After introducing DIRECT global minimization method, the results obtained using previously mentioned methods are compared with the results obtained using DIRECT global minimization of the Lipschitz function. Determining vibration frequency and comparing to previously collected data or knowledge base data is a common procedure. In engineering practice it is often necessary to determine not one, but several so-called dominant frequencies or local maxima; the procedure is sometimes called multi peak detection and here we propose an algorithm for computerised multi peak detection

Digital generator protection

Imperial Users onl

OPTICAL SURFACE CHARACTERIZATION WITH THE STRUCTURE FUNCTION

It is important to characterize surface and transmitted wavefront errors in terms of the spatial content. The errors are typically analyzed in three spatial domains: figure, ripple (or mid-spatial frequency) and roughness. These errors can affect optical system performance. For example, mid-spatial frequency errors can lead to self-focusing and power loss in a high-power laser system. Currently, power spectral density (PSD) is used for the spatial content characterization in high-end optics, although there are potential pitfalls. For example, the low spatial content is removed before calculation, only a small fraction of surface data are used, and the results are sensitive to details like the windowing. As an alternative, the structure function (SF) does not have such problems. It is the expectation of the squared height difference as a function of separation. The linear SF has been used in astronomy and captures data of all spatial frequencies. However, it does not capture anisotropy on the surface. The two-quadrant area SF introduced in this dissertation obviates this problem. It is computationally correct for any arbitrary aperture over all spatial content with anisotropic information. This dissertation discusses some computational issues of the SF, which includes the calculation of the linear / area SF, sliding sampling method for large numbers of points within the aperture, analysis of periodic errors, and connection between the linear SF and area SF. Moreover, the relationships between the SF and other surface characterization echniques (Zernike polynomials, autocorrelation function (ACF), PSD, and RMS gradient) have been investigated. It turns out that the linear SF of the sum of the Zernike terms only equals to the sum of the linear SF of each of the Zernike polynomials with different azimuthal frequencies. However, this theorem does not apply to the area SF. For stationary surfaces, the SF contains similar information as ACF, but it provides better visualization. The SF is computationally correct for any arbitrary aperture shape without extra processing, while the PSD always needs additional mathematical processing. After connecting the SF to the RMS gradient, the SF slope at the origin has been evaluated. Use of a SF to specify optical surfaces over the full range of spatial frequencies of interest implies the combination of data from instruments with substantially different lateral resolutions. This research shows the combination of data from a Fizeau and a coherence scanning interferometer (CSI) for various precision surfaces. The investigation includes the connection method of the coordinate systems between the Fizeau data and the CSI sub-aperture data, the convergence of the averaged SF of sub-aperture samples, the uncertainty analysis, and the effect of the instrument transfer function (ITF). In addition, the SF was used to explore two typical noise contributions (electronic noise and air turbulence) in phase shifting interferometry. Based on dynamic measurements, the SF was used to analyze the spatial components of a diamond turned surface after the compensation machining. In summary, the SF is a useful tool to specify and characterize the spatial content of optical surfaces and wavefronts

Reliability Analysis of On-Demand High-Speed Machining

Current trends in high-speed machining aim to increase manufacturing efficiency by maximizing material removal rates and minimizing part cycle times. This project explores three related technologies and presents a system design for rapid production of custom machined parts. First a reliability analysis in high-speed machining of thin wall features is put forth with experimental results. Second an implementation of on-demand manufacturing is presented with emphasis on flexibility and automation. Finally innovative manufacturing cell design is used to drive costs down by optimizing material and information flow. The resulting high-speed on-demand machining cell design employs effective techniques to reduce production time, meet changing customer needs, and drive down costs

Smart Sensor Monitoring in Machining of Difficult-to-cut Materials

The research activities presented in this thesis are focused on the development of smart sensor monitoring procedures applied to diverse machining processes with particular reference to the machining of difficult-to-cut materials. This work will describe the whole smart sensor monitoring procedure starting from the configuration of the multiple sensor monitoring system for each specific application and proceeding with the methodologies for sensor signal detection and analysis aimed at the extraction of signal features to feed to intelligent decision-making systems based on artificial neural networks. The final aim is to perform tool condition monitoring in advanced machining processes in terms of tool wear diagnosis and forecast, in the perspective of zero defect manufacturing and green technologies. The work has been addressed within the framework of the national MIUR PON research project CAPRI, acronym for “Carrello per atterraggio con attuazione intelligente” (Landing Gear with Intelligent Actuation), and the research project STEP FAR, acronym for “Sviluppo di materiali e Tecnologie Ecocompatibili, di Processi di Foratura, taglio e di Assemblaggio Robotizzato” (Development of eco-compatible materials and technologies for robotised drilling and assembly processes). Both projects are sponsored by DAC, the Campania Technological Aerospace District, and involve two aerospace industries, Magnaghi Aeronautica S.p.A. and Leonardo S.p.A., respectively. Due to the industrial framework in which the projects were developed and taking advantage of the support from the industrial partners, the project activities have been carried out with the aim to contribute to the scientific research in the field of machining process monitoring as well as to promote the industrial applicability of the results. The thesis was structured in order to illustrate all the methodologies, the experimental tests and the results obtained from the research activities. It begins with an introduction to “Sensor monitoring of machining processes” (Chapter 2) with particular attention to the main sensor monitoring applications and the types of sensors which are employed in machining. The key methods for advanced sensor signal processing, including the implementation of sensor fusion technology, are discussed in details as they represent the basic input for cognitive decision-making systems construction. The chapter finally presents a brief discussion on cloud-based manufacturing which will represent one of the future developments of this research work. Chapters 3 and 4 illustrate the case studies of machining process sensor monitoring investigated in the research work. Within the CAPRI project, the feasibility of the dry turning process of Ti6Al4V alloy (Chapter 3) was studied with particular attention to the optimization of the machining parameters avoiding the use of coolant fluids. Since very rapid tool wear is experienced during dry machining of Titanium alloys, the multiple sensor monitoring system was used in order to develop a methodology based on a smart system for on line tool wear detection in terms of maximum flank wear land. Within the STEP FAR project, the drilling process of carbon fibre reinforced (CFRP) composite materials was studied using diverse experimental set-ups. Regarding the tools, three different types of drill bit were employed, including traditional as well as innovative geometry ones. Concerning the investigated materials, two different types of stack configurations were employed, namely CFRP/CFRP stacks and hybrid Al/CFRP stacks. Consequently, the machining parameters for each experimental campaign were varied, and also the methods for signal analysis were changed to verify the performance of the different methodologies. Finally, for each case different neural network configurations were investigated for cognitive-based decision making. First of all, the applicability of the system was tested in order to perform tool wear diagnosis and forecast. Then, the discussion proceeds with a further aim of the research work, which is the reduction of the number of selected sensor signal features, in order to improve the performance of the cognitive decision-making system, simplify modelling and facilitate the implementation of these methodologies in a cloud manufacturing approach to tool condition monitoring. Sensor fusion methodologies were applied to the extracted and selected sensor signal features in the perspective of feature reduction with the purpose to implement these procedures for big data analytics within the Industry 4.0 framework. In conclusion, the positive impact of the proposed tool condition monitoring methodologies based on multiple sensor signal acquisition and processing is illustrated, with particular reference to the reliable assessment of tool state in order to avoid too early or too late cutting tool substitution that negatively affect machining time and cost

The Singing Tree : a novel interactive musical experience

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1997.Includes bibliographical references (p. 105-107).by William David Oliver.M.S

Cognitive Sensor Monitoring of Machining Processes for Zero Defect Manufacturing

The topic of this thesis, focused on cognitive sensor monitoring of machining processes for zero defect manufacturing, has been addressed within the framework of the international research project EC FP7 CP-IP “IFaCOM – Intelligent Fault Correction and self Optimizing Manufacturing systems” (2011-2015; FoF NMP – 285489) and the national MIUR PON Project on “Development of eco-compatible materials and technologies for robotised drilling and assembly processes – STEP FAR” (2014-2016). The vision of the IFaCOM project is to achieve near zero defect level of manufacturing with particular emphasis on the production of high value, large variety and high performance products. This goal is achieved through the development of improved methodologies for monitoring and control of the performance of manufacturing processes with the aim to detect abnormal process conditions leading to defects on the produced parts. The overall aim of the STEP FAR project is the study of issues related to drilling and cutting techniques of advanced lightweight components, such as composite material parts, and their relative assembly, using cooperating anthropomorphic robots. The use of innovative materials and processes developed in this research will lead to a reduction in weight and environmental impact in the construction and maintenance of primary aircraft structures. At least a 5% reduction in weight of the structures is foreseen without increase of costs (a possible rise in the cost of raw materials is compensated with the reduction of process costs). In aeronautical industry the reduction of the weight of the aircraft is becoming an increasingly important aim both for environmental requirements (lower emissions) and contraction of the management costs (lower fuel consumption). Therefore new structural architectures through the use of innovative materials and technologies have been developed. One of the innovative processes analysed in this project is the drilling via machining of carbon fibre reinforced plastic (CFRP) stack-ups. In the framework of these projects, this thesis work is focused on the development of cognitive condition monitoring procedures for zero defect machining processes with reference to two different industrial manufacturing applications. The thesis is organized as follows: Chapter 2 reviews the general concept of sensor monitoring of manufacturing processes and provides a comprehensive survey of sensor technologies, advanced signal processing techniques, sensor fusion approach, and cognitive decision making strategies for process monitoring. In Chapter 3, the Strecon industrial case, as a partner of the IFaCOM project, is discussed and analysed. The STRECON end-user case is focused on improving repeatability and predictability of the surface finish produced by a Robot Automated Polishing (RAP) process. In order to establish a robust method for the detection of the polishing process end-point, i.e. the determination of the right moment for tool and abrasive paste change, STRECON sensor system selection focuses on monitoring the progress of the surface quality during the polishing process by means of variation in VQCs (Vital Quality Characteristics), i.e. roughness and gloss of the polished surface. The output data have been used to train a neural network. The employed NN learning procedure was the leave-k-out method where k cases from the training set are put aside in turn, while the other cases are used for NN training. In Chapter 4, the Alenia Aermacchi industrial case, as coordinator and partner of the STEP FAR project, is discussed and analysed. The Alenia Aermacchi user case is based on the analysis of drilling of stacks made of two overlaid carbon fibre reinforced plastic composite laminates. In this case, a neural network based cognitive paradigm based on a bootstrap procedure has been used for the identification of correlations with tool wear development and product hole quality. Finally, Chapter 5 reports the concluding remarks and future developments of this work

APPLICATIONS IN VIBROARTHROGRAPHY: ASSESSMENTS OF INSTABILITY IN TOTAL HIP ARTHROPLASTY, CAM-POST ENGAGEMENT IN TOTAL KNEE ARTHROPLASTY, AND VISCOSUPPLEMENTATION IN OSTEOARTHRITIC KNEES

Measurement of joint sounds and vibrations for non-invasive orthopaedic diagnostic purposes has slowly advanced since the 1960s. Most work has been focused in the development of methods for screening of abnormal knees. To date the technique has not gained clinical traction as is it fraught with various obstacles and skepticism. This doctoral thesis is neither an argument in favor of nor against the clinical use of vibroarthrography for musculoskeletal diagnostics in humans, but rather an exploration of its potential in cases of orthopaedic interest. These areas include 1) instability in total hip arthroplasty, 2) cam-post engagement in posterior stabilized total knee arthroplasty, and 3) viscosupplementation in osteoarthritic knees. It was expected that each of these unique cases would be characterized by dynamic phenomena that could be measured in the form of surface vibrations at the skin.Methods previously presented in various vibroarthrography research were adopted, modified, and expounded upon to best suit the needs of each experiment. In a mechanical hip simulator, it was found that vibroarthrography could be effectively used to distinguish the difference between 1 mm and 2 mm of hip separation. In posterior stabilized total knee arthroplasty subjects, it was found that multiple vibroarthrographic features may be used to approximate the occurrence of cam-post engagement, and that vibrations measured at the joint surface may be correlated to cam-post engagement velocity. In osteoarthritic knees, the relationship between clinical evidence, viscosupplementation, and vibroarthrography varied on a case by case basis.To the knowledge of the author, all three of these experiments are the first of their kind. Ultimately, the methods and results presented within provide new foundations for vibroarthrography that may be used to further explore the clinical potential of this noninvasive diagnostic

Interfacial Dissipative Phenomena in Tribomechanical Systems

The book is a collection of articles on the themes of contact mechanics and non-linear dynamics. In particular, the contribution focus on the mechanisms that lead to interfacial energy dissipation, which is a crucial quantity to determine in order to correctly predict the non-linear dynamic response of mechanical systems. The book is a collection of nine journal papers, among those one editorial, one review paper, and seven articles. The papers consider different dissipative mechanisms, such as Coulomb friction, interfacial adhesion, and viscoelasticity, and study how the system response and stability is influenced by the interfacial interactions. The review paper describes old and recent test rigs for friction and wear measurements, focusing on their performance and range of operability