2,149 research outputs found

    Design and development of prognostic and health management system for fly-by-wire primary flight control

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    Electro-Hydraulic Servo Actuators (EHSA) is the principal technology used for primary flight control in new aircrafts and legacy platforms. The development of Prognostic and Health Management technologies and their application to EHSA systems is of great interest in both the aerospace industry and the air fleet operators. This Ph.D. thesis is the results of research activity focused on the development of a PHM system for servovalve of fly-by-wire primary flight EHSA. One of the key features of the research is the implementation of a PHM system without the addition of new sensors, taking advantage of sensing and information already available. This choice allows extending the PHM capability to the EHSAs of legacy platforms and not only to new aircrafts. The enabling technologies borrow from the area of Bayesian estimation theory and specifically particle filtering and the information acquired from EHSA during pre-flight check is processed by appropriate algorithms in order to obtain relevant features, detect the degradation and estimate the Remaining Useful Life (RUL). The results are evaluated through appropriate metrics in order to assess the performance and effectiveness of the implemented PHM system. The major objective of this contribution is to develop an innovative fault diagnosis and failure prognosis framework for critical aircraft components that integrates effectively mathematically rigorous and validated signal processing, feature extraction, diagnostic and prognostic algorithms with novel uncertainty representation and management tools in a platform that is computationally efficient and ready to be transitioned on-board an aircraft

    A global survey on the current state of practice in Zero Defect Manufacturing and its impact on production performance

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    To be competitive in dynamic and global markets, manufacturing companies are continuously seeking to apply innovative production strategies and methods combined with advanced digital technologies to improve their flexibility, productivity, quality, environmental impact, and cost performance. Zero Defect Manufacturing is a disruptive concept providing production strategies and methods with underlying advanced digital technologies to fill the gap. While scientific knowledge within this area has increased exponentially, the current practices and impact of Zero Defect Manufacturing on companies over time are still unknown. Therefore, this survey aims to map the current state of practice in Zero Defect Manufacturing and identify its impact on production performance. The results show that although Zero Defect Manufacturing strategies and methods are widely applied and can have a strong positive impact on production performance, this has not always been the case. The findings also indicate that digital technologies are increasingly used, however, the potential of artificial intelligence and extended reality is still less exploited. We contribute to theory by detailing the research needs of Zero Defect Manufacturing from the practitioner’s perspective and suggesting actions to enhance Zero Defect Manufacturing strategies and methods. Further, we provide practical and managerial suggestions to improve production performances and move towards sustainable development and zero waste.publishedVersio

    Design and debugging of multi-step analog to digital converters

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    With the fast advancement of CMOS fabrication technology, more and more signal-processing functions are implemented in the digital domain for a lower cost, lower power consumption, higher yield, and higher re-configurability. The trend of increasing integration level for integrated circuits has forced the A/D converter interface to reside on the same silicon in complex mixed-signal ICs containing mostly digital blocks for DSP and control. However, specifications of the converters in various applications emphasize high dynamic range and low spurious spectral performance. It is nontrivial to achieve this level of linearity in a monolithic environment where post-fabrication component trimming or calibration is cumbersome to implement for certain applications or/and for cost and manufacturability reasons. Additionally, as CMOS integrated circuits are accomplishing unprecedented integration levels, potential problems associated with device scaling – the short-channel effects – are also looming large as technology strides into the deep-submicron regime. The A/D conversion process involves sampling the applied analog input signal and quantizing it to its digital representation by comparing it to reference voltages before further signal processing in subsequent digital systems. Depending on how these functions are combined, different A/D converter architectures can be implemented with different requirements on each function. Practical realizations show the trend that to a first order, converter power is directly proportional to sampling rate. However, power dissipation required becomes nonlinear as the speed capabilities of a process technology are pushed to the limit. Pipeline and two-step/multi-step converters tend to be the most efficient at achieving a given resolution and sampling rate specification. This thesis is in a sense unique work as it covers the whole spectrum of design, test, debugging and calibration of multi-step A/D converters; it incorporates development of circuit techniques and algorithms to enhance the resolution and attainable sample rate of an A/D converter and to enhance testing and debugging potential to detect errors dynamically, to isolate and confine faults, and to recover and compensate for the errors continuously. The power proficiency for high resolution of multi-step converter by combining parallelism and calibration and exploiting low-voltage circuit techniques is demonstrated with a 1.8 V, 12-bit, 80 MS/s, 100 mW analog to-digital converter fabricated in five-metal layers 0.18-µm CMOS process. Lower power supply voltages significantly reduce noise margins and increase variations in process, device and design parameters. Consequently, it is steadily more difficult to control the fabrication process precisely enough to maintain uniformity. Microscopic particles present in the manufacturing environment and slight variations in the parameters of manufacturing steps can all lead to the geometrical and electrical properties of an IC to deviate from those generated at the end of the design process. Those defects can cause various types of malfunctioning, depending on the IC topology and the nature of the defect. To relive the burden placed on IC design and manufacturing originated with ever-increasing costs associated with testing and debugging of complex mixed-signal electronic systems, several circuit techniques and algorithms are developed and incorporated in proposed ATPG, DfT and BIST methodologies. Process variation cannot be solved by improving manufacturing tolerances; variability must be reduced by new device technology or managed by design in order for scaling to continue. Similarly, within-die performance variation also imposes new challenges for test methods. With the use of dedicated sensors, which exploit knowledge of the circuit structure and the specific defect mechanisms, the method described in this thesis facilitates early and fast identification of excessive process parameter variation effects. The expectation-maximization algorithm makes the estimation problem more tractable and also yields good estimates of the parameters for small sample sizes. To allow the test guidance with the information obtained through monitoring process variations implemented adjusted support vector machine classifier simultaneously minimize the empirical classification error and maximize the geometric margin. On a positive note, the use of digital enhancing calibration techniques reduces the need for expensive technologies with special fabrication steps. Indeed, the extra cost of digital processing is normally affordable as the use of submicron mixed signal technologies allows for efficient usage of silicon area even for relatively complex algorithms. Employed adaptive filtering algorithm for error estimation offers the small number of operations per iteration and does not require correlation function calculation nor matrix inversions. The presented foreground calibration algorithm does not need any dedicated test signal and does not require a part of the conversion time. It works continuously and with every signal applied to the A/D converter. The feasibility of the method for on-line and off-line debugging and calibration has been verified by experimental measurements from the silicon prototype fabricated in standard single poly, six metal 0.09-µm CMOS process

    Time domain analysis of switching transient fields in high voltage substations

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    Switching operations of circuit breakers and disconnect switches generate transient currents propagating along the substation busbars. At the moment of switching, the busbars temporarily acts as antennae radiating transient electromagnetic fields within the substations. The radiated fields may interfere and disrupt normal operations of electronic equipment used within the substation for measurement, control and communication purposes. Hence there is the need to fully characterise the substation electromagnetic environment as early as the design stage of substation planning and operation to ensure safe operations of the electronic equipment. This paper deals with the computation of transient electromagnetic fields due to switching within a high voltage air-insulated substation (AIS) using the finite difference time domain (FDTD) metho

    Maintenance Management of Wind Turbines

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    “Maintenance Management of Wind Turbines” considers the main concepts and the state-of-the-art, as well as advances and case studies on this topic. Maintenance is a critical variable in industry in order to reach competitiveness. It is the most important variable, together with operations, in the wind energy industry. Therefore, the correct management of corrective, predictive and preventive politics in any wind turbine is required. The content also considers original research works that focus on content that is complementary to other sub-disciplines, such as economics, finance, marketing, decision and risk analysis, engineering, etc., in the maintenance management of wind turbines. This book focuses on real case studies. These case studies concern topics such as failure detection and diagnosis, fault trees and subdisciplines (e.g., FMECA, FMEA, etc.) Most of them link these topics with financial, schedule, resources, downtimes, etc., in order to increase productivity, profitability, maintainability, reliability, safety, availability, and reduce costs and downtime, etc., in a wind turbine. Advances in mathematics, models, computational techniques, dynamic analysis, etc., are employed in analytics in maintenance management in this book. Finally, the book considers computational techniques, dynamic analysis, probabilistic methods, and mathematical optimization techniques that are expertly blended to support the analysis of multi-criteria decision-making problems with defined constraints and requirements

    Electronic Circuits Diagnosis Using Artificial Neural Networks

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    When we expect  about something that does not treat as it should be,  we are initiating the  process of diagnosis. Diagnosis is a commonly used activity in our everyday lives (Benjamins & Jansweijer, 1990). Complicated systems are always prone to faults or failures. In the simplest term, a fault is every change in a system that prevents it from operating in the proper manner. We define diagnosis as the task of identifying the cause and location of a fault manifested by some observed behaviour. Basically this is  two-stage process: first the fact that fault has occurred must be recognized – this is referred to as fault detection. That is, in general, achieved by testing. Secondly, the nature and location should be determined such that appropriate remedial action may be initiated

    Application of advanced technology to space automation

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    Automated operations in space provide the key to optimized mission design and data acquisition at minimum cost for the future. The results of this study strongly accentuate this statement and should provide further incentive for immediate development of specific automtion technology as defined herein. Essential automation technology requirements were identified for future programs. The study was undertaken to address the future role of automation in the space program, the potential benefits to be derived, and the technology efforts that should be directed toward obtaining these benefits
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