Signal Analysis and Pattern Identification

Diagnosing the health of turbine aircraft engines is a form of preventive activity which is aimed at, among others, for the early detection of safety hazards in aircraft operation.
The subject literature presents several methods and techniques of performing diagnostic research, including measurement signal analysis algorithms and automated diagnostic reasoning. Only some of these methods have been implemented into operation, demonstrating a sufficient detection sensitivity of diagnostic symptoms encountered in actual service conditions, as well as demonstrating a sufficient resistance to the scatter of structural properties, and also to the influence of human error. These aspects are frequently neglected in theoretical considerations.
Most of the implemented diagnostic methods are focused only on the detection of a problem narrow in scope, most often related to the actual technical condition of critical components. Such manner of action, typical for the Non Destructive Inspection methods, is a form of “passive” anticipation of the effects of the monitored fatigue process, without recognizing its underlying causes. Such a diagnostic approach reduces the risk of an air accident, but also increases the costs borne by the operator.
      In order to simultaneously reduce the risk of material fatigue, as well as the costs of preventive testing and research, author has proposed a new diagnostic approach. Its essence is the detection of causes of accelerated fatigue, as well as the active control of material fatigue. Author has shown that material fatigue is an anthropotechnical process, therefore it is possible to control the intensity of adverse dynamic phenomena - still at the stage of reversible changes.
The novel concept of fatigue control has been presented and based on the example of steel and titanium compressor blades of the SO-3 and TW3-117 engines and utilizing the author’s over 15 year-long experience gained in cooperating with the military operator of aircraft engines and with the repair facilities. In analyzing the problem, the author took into account the existing aircraft engine maintenance systems, and has showcased typical fatigue cases, observed in military as well as civil aviation.
In his theoretical considerations the author included the bimodal description of the fatigue curve, as well as the phenomenon of gigacycle fatigue (Very High Cycle Fatigue
- VHCF). In the paper, author described the idea of an innovative approach to the problem of fatigue, identified the research requirements, and also defined three research tasks, which include early detection of fatigue risks in compressor blades during operation and overhaul, as well as a complex engine diagnostics system based on a single state observer. Author has selected and verified three research methods needed for carrying out these tasks: Metal Magnetic Memory (MPM), Experimental Modal Analysis (EMA) and rotating blades-based engine monitoring (TTM), for which methods he provided a theoretical description, and also presented the accompanying physical phenomena. Based on a number of passive and active experiments performed on statistically reliable population of engines, the author has presented a practical ability of implementing the  concept of active fatigue control.
The EMA and TTM methods have been introduced in Poland for the overhaul and maintenance technology of aircraft engines.

Real-time vibration monitoring and diagnostics system is developed and supplied for the 5 stand 4-h tandem cold rolling mill 2030 NLMC. Mechanism of chatter regeneration due to high frequency strip thickness variation and stands synchronization in the tandem rolling mills are considered. Methods for chatter passive damping and active suppression are considered. Work rolls hydraulic bending system influence on bearings vibration and chatter is discussed. The new methods are used for the 3rd octave chatter early diagnostics and model based mill control.

The monitoring systems presently available for vibration observation of civil engineering struc-tures are normally based on networks of accelerometers and strain gages distributed along the structure connected to one or more central computer. 1, 2 This computer launches the acquisition and stores and transmits the collected data. Depending on the dimensions of the structure and the extensiveness of the monitoring system, one common issue with most widely used monitoring systems is the use of electrical cables to power sensors and ...

The numerical simulation using Finite Element (FE) method is a main activity in the design - validation process of mechanical products. Using this method and CAD tools can give an efficient advantage in the CAD - Analysis loop. The geometric model (mesh) used in the FE method is mainly obtained from the CAD model (CSG, B-Rep). In order to reduce the analysis time without bringing precision on computation results, we propose to integrate a new link in the design and analysis interoperability process. This link is named Idealization or simplification of CAD model. So, the automation of the idealization task is important in the CAD-Analysis integration process. In this paper, we propose an idealization approach which mainly depends on the geometry, the solicitations and the behavior of material. According to the analysis goal, the designer can have several alternatives of analysis models which depend on the level of eliminated details and the abstraction level (1D, 2D or 3D). The non manifold models should not be a barrier to the considered analysis model. We start with a positioning of several geometry simplification methods for CAD models in order to generate analysis models adapted with the considered analysis point of view. Based on this state of the art, we present the idealization approach in an integrated design context. Then, we propose our general method of the CAD geometry idealization. This one is based on an original algorithm witch integrate tow alternatives approach (selective approach and automatic approach). In order to emphasize our contribution, we present some examples of idealized form features (parallelepiped, cylinder, and wedge) implemented with OpenCacade code. Finally, an example of mechanical part using implemented form features is developed. The output of the algorithm is some proposed analysis models based on the CAD model of the part.

http://www.designsociety.org/publication/25383/idealization_of_cad_geometry_using_design_and_analysis_integration_features_models

Dans le but de concevoir un système de diagnostic des défauts d'un moteur diesel 4 temps à combustion interne, l'incidence d'un défaut de distribution sur la vibration du moteur a été étudié. Ce défaut a été simulé en modifiant les jeux entre les cames et les poussoirs en contact avec les queues des soupapes.

The following I listed some of computer science  IEEE Journals that are relevant to our current works at Faculty of Computer Science, Universitas Indonesia.
All links to the paper are given in the Journal Names. I also computed the average on each column.
I randomly select 5 most popular and recent “Regular” papers from each Journal to compute Review Time, Revision Time, and Publication Time.
Sometimes, the Revised date or the Publication date were not given in the paper but only the Accepted date (thus adaptation is necessary).

The relentless competition among automotive companies and increased demands from customers for driver assistance functions, dynamically-controlled safety systems, driving comfort and infotainment services in vehicles are creating mounting time-to-market pressures and, consequently, shortened development times. With the shortened development times and increased vehicle complexity, guaranteeing hardware-software integrity and, hence, vehicle performance has become a salient issue. This is because poor vehicle performance increases maintenance costs to customers and warranty costs to automotive manufacturers; which, in turn, result in customer dissatisfaction and reduced competitiveness of US automotive industry. The development of methods for enhancing the reliability of embedded systems of heterogeneous components that are designed and implemented by different suppliers, and vehicle diagnostics and prognostics are of vital interest to US automotive industry.

Deep learning and image processing are two areas of great interest to academics and industry professionals alike. The areas of application of these two disciplines range widely, encompassing fields such as medicine, robotics, and security and surveillance. The aim of this book, 'Deep Learning for Image Processing Applications', is to offer concepts from these two areas in the same platform, and the book brings together the shared ideas of professionals from academia and research about problems and solutions relating to the multifaceted aspects of the two disciplines. The first chapter provides an introduction to deep learning, and serves as the basis for much of what follows in the subsequent chapters, which cover subjects including: the application of deep neural networks for image classification; hand gesture recognition in robotics; deep learning techniques for image retrieval; disease detection using deep learning techniques; and the comparative analysis of deep data and big data. The book will be of interest to all those whose work involves the use of deep learning and image processing techniques

This paper builds on work relating to pattern languages for social change, such as in the papers titled Fourth generation pattern languages-patterns as epistemic threads for systemic orientation, and Pattern Literacy in support of Systems Literacy presented to the Systems Science and Pattern Language communities between 2015 and 2017. It is part of an endeavor to bring pattern thinking and systems thinking, or pattern science and systems science, closer to each other, in order to further introduce pattern thinking and pattern language in the design, assessment and orientation of our socio-technological and socio-environmental systems, large or small, to better address the societal issues of our time. It complements several initiatives to put pattern languages at the service of sustainability and societal change, and to introduce pattern thinking and pattern language into systems thinking and systemic design. My broader aim is to enhance the innate patterning capability of human beings and thus an overall pattern literacy in support of systems literacy. Pattern literacy manifests our ability to grasp, learn, assemble, represent and mobilize patterns to make-sense of, converse about and shape our world(s). Systems literacy manifests our ability to interrogate and attempt to understand the relationships among systems wholes and parts, and the mechanisms that affect and shape our world(s), in part or as a whole. In this paper, I explore how a systemic approach to patterns and pattern language could support systemic inquiry and systemic design, and more generally the advancement of pattern language. In particular, I discuss the extension of the act of design to encompass the systemic inquiry that motivates a design and the ongoing monitoring of the fitness of a design to its intended purpose. I examine the multiple facets and understandings of the concept of pattern and show how they can be reconciled to include both the inquiry or observational/informational aspects and the design aspects of patterns in a larger systems framework. In this light, I reexamine the appropriateness of the pattern expressed in problem-solution form in the context of complex systems, and the notion of generativity, and I propose ways forward for extended definitions and pattern forms.

D e c e m b e r 2 0 0 8 The ultimate measure of a man is not where he stands in moments of comfort and convenience, but where he stands at times of challenge and controversy (Martin Luther King) -This thesis is dedicated to who has made me a man

Even though prognostics has been defined to be one of the most difficult tasks in Condition Based Maintenance (CBM), many studies have reported promising results in recent years. The nature of the prognostics problem is different from diagnostics with its own challenges. There exist two major approaches to prognostics: data-driven and physics-based models. This paper aims to present the major challenges in both of these approaches by examining a number of published datasets for their suitability for analysis. Data-driven methods require sufficient samples that were run until failure whereas physics-based methods need physics of failure progression.

In my Plop 2018 paper, I proposed to consider patterns more assertively in their broad definition, as mediators between objects or events in the world and the ways we represent and interpret them. The objective being to better focus on their observational and communicative aspects in the context of systemic inquiry and design, and to enable coordination of action across identity and knowledge boundaries. Here I dive deeper in the biological and biosemiotic underpinnings of "Patterning" and "Languaging", to explore the nature and "timeless properties" of patterns as signs and their role in the emergence of human cognition and language from an evolutionary perspective. In particular I examine their involvement in 'habit taking'' in nature and its extension in culture, and in the coordination of unself-conscious action and creative processes, such as evoked by Christopher Alexander. The fact that patterns in their extended definition are omnipresent should not deter us and lead us to think that if everything is a pattern, nothing actually is… on the contrary. I will show how the development of a pattern literacy around patterns seen as basic units for the coordination of action and the understanding of the world can be used for the study of socio-ecological and socio-technological systems and provide insights on the way to design sustainable systems, and I will suggest how pattern languages could be understood and applied towards this objective.

‫پژمان‬ ‫چرانی‬ ‫رضایتی‬ -‫ارشد‬ ‫کارشناسی‬ ‫دوره‬ ‫مدرس‬ ‫تربیت‬ ‫دانشگاه‬ ، ‫راهنما:‬ ‫استاد‬ ‫دکتر‬ ‫سعید‬ ‫نجفی‬ ‫کاظمی‬ ‫گزارش‬ ‫چوب‬ ‫صنایع‬ ‫در‬ ‫مخرب‬ ‫غیر‬ ‫آزمونهای‬ ‫کاربرد‬ ‫درس‬ -3131 ‫گزارش‬ ‫چوب‬ ‫صنایع‬ ‫در‬ ‫مخرب‬ ‫غیر‬ ‫آزمونهای‬ ‫کاربرد‬ ‫درس‬ -3131 2 ‫گزارش‬ ‫چوب‬ ‫صنایع‬ ‫در‬ ‫مخرب‬ ‫غیر‬ ‫آزمونهای‬ ‫کاربرد‬ ‫درس‬ -3131 3 ‫گزارش‬ ‫چوب‬ ‫صنایع‬ ‫در‬ ‫مخرب‬ ‫غیر‬ ‫آزمونهای‬ ‫کاربرد‬ ‫درس‬ -3131 5 ‫گزارش‬ ‫چوب‬ ‫صنایع‬ ‫در‬ ‫مخرب‬ ‫غیر‬ ‫آزمونهای‬ ‫کاربرد‬ ‫درس‬ -3131 21

In this paper we propose an approach for testing time-domain properties of analog and mixed-signal circuits. The approach is based on an adaptation of a recently developed test generation technique for hybrid systems and a new concept of coverage for such systems. The approach is illustrated by its application to some benchmark circuits.

In this work we investigate the different sensing schemes for detection of four targets as observed through a vector Poisson and Gaussian channels when the sensing time resource is limited and the source signals can be observed through a variety of sum combinations during that fixed time. For this purpose we can maximize the mutual information or the detection probability with respect to the time allocated to different sum combinations, for a given total fixed time. It is observed that for both Poisson and Gaussian channels; mutual information and Bayes risk with 0 − 1 cost are not necessarily consistent with each other. Concavity of mutual information between input and output, for certain sensing schemes, in Poisson channel and Gaussian channel is shown to be concave w.r.t given times as linear time constraint is imposed. No optimal sensing scheme for any of the two channels is investigated in this work.

This paper proposed a method that combines Polar Fourier Transform, color moments, and vein features to retrieve leaf images based on a leaf image. The method is very useful to help people in recognizing foliage plants. Foliage plants are plants that have various colors and unique patterns in the leaf. Therefore, the colors and its patterns are information that should be counted on in the processing of plant identification. To compare the performance of retrieving system to other result, the experiments used Flavia dataset, which is very popular in recognizing plants. The result shows that the method gave better performance than PNN, SVM, and Fourier Transform. The method was also tested using foliage plants with various colors. The accuracy was 90.80% for 50 kinds of plants.

The dermatoglyphical science analyses an individual’s innate potentials and talents based on the study of their fingerprints, soles and feet skin ridges.  Since the fingers are connected to different lobes of the brain, responsible for coordinating different functions, it is important to correctly acquire an image of the fingerprints. A phase only correlation based technique provides an easy and fast method for automatic pattern matching and classification of fingerprints.

The detection of misfire in an internal combustion diesel engine by vibration analysis has been investigated. In the experimental study, a diesel engine with six cylinders in line and cylinder head in 6 parts has been used. Vibration signal has been measured, successively, at seven positions of engine structure and analyzed in the time domain to extract statistical features sensitive to the engine misfire.

Automatic routines are the most difficult to change. However, they play a key role in the way individuals use electricity in their homes. Recognizing the impact of routines in electricity usage decisions, the research work presented in this thesis, focuses on the discovery of patterns of daily electricity in households. The research is based upon the data collected at a small-scale experiment, which resembles a utility automated meter infrastructure (AMI) deployment. Computer software provided historical and real-time information to individuals. The data visualization and transmission architecture relied on the home area network of the households.
The fundamental contributions of the present research are the following: a) a methodology that recognizes daily patterns of consumption, b) a methodology that generates typical load curves that are specific of a combination of external conditions such as outdoor weather temperature, working day / weekend and month of the year. Both methodologies should be tested with larger samples, but may define a building block to improve consumer driven programs based upon segmentation by actual electricity consumption behaviors and personalized feedback.
Other contributions include verifying the circumstances in which routine patterns are more probable, which specifically include the presence of young children, and how these tend to be less predictable when children grow older. Previous research recognizes that feedback is an essential component of learning. However, insights from qualitative interviews show that learning is an incremental process and it is possible that individuals don’t relate the cause and the effect when discussing how their practices have changed across the duration of the experiment.

Pattern discovery is an essential computational music analysis method for revealing intra-opus repetition and inter-opus recurrence. This chapter applies pattern discovery to a corpus of songs for the bagana, a large lyre played in Ethiopia. An important and unique aspect of this repertoire is that frequent and rare motifs have been explicitly identified and used by a master bagana teacher in Ethiopia. A new theorem for pruning of statistically under-represented patterns from the search space is used within an efficient pattern discovery algorithm. The results of the chapter show that over- and under-represented patterns can be discovered in a corpus of bagana songs, and that the method can reveal with high significance the known bagana motifs of interest.

An ambient vibration survey of the Humber Bridge was carried out in July 2008 by a combined team from the UK, Portugal and Hong Kong. The exercise had several purposes that included the evaluation of the current technology for instrumentation and system identification and the generation of an experimental dataset of modal properties to be used for validation and updating of finite element models for scenario simulation and structural health monitoring. The exercise was conducted as part of a project aimed at developing online diagnosis capabilities for three landmark European suspension bridges.

A strategy for adaptive control and energetic optimization of aerobic fermentors was implemented, with both air flow and agitation speed as manipulated variables. This strategy is separable in its components: control, optimization, estimation. We optimized parameter’s estimation (from the usual KLa correlation) using sinusoidal excitation of air flow and agitation speed. We have implemented parameter’s estimation trough recursive least squares algorithm with forgetting factor. We carried separate essays on control, optimization and estimation algorithms. We carried our essays using an original computational simulation environment, with noise and delay generating facilities for data sampling and filtering.

Our results show the convergence and robustness of the estimation algorithm used, improved with use of both forgetting factor and KLa dead-band facilities. Control algorithm used in our work compares favorably with PID using the integrated area criteria for deviation between oxygen molarity and critical molarity (set point). Optimization algorithm clearly reduces energetic consumption, respecting critical molarity. Integration of control, optimization and adaptive algorithms was implemented, but future work is needed for stability. Methods were defined and implemented for stability improvement. We have implemented data acquisition and computer manipulation of air flow and agitation speed for actual fermentors.

During the last years, a number of techniques aimed at the experimental identification of the dynamic characteristics of structures has been developed. Their use has progressively extended to various fields, such as aerospace, automotive and civil structures. Besides the traditional techniques based on input knowledge, increasing interest is observed for techniques based on environmental vibrations that do not need any expensive excitation device.

Experimental estimation of damping is currently not a comprehensively solved problem. Although modal frequencies and mode shapes can be confidently and quite easily measured by means of dynamic tests on civil structures, an accurate identification of damping ratios needs further development. Experimental values can be characterized by large error bounds mainly because damping is strongly influenced by the magnitude of the dynamic response of a structure. In this paper the main issues concerning identification of modal damping ratios are discussed in order to define methods for a reliable estimation, reduce uncertainties and characterize error bounds. According to this aim, a literature review has been carried out to find best practice criteria for modal parameter identification, in particular damping. A procedure for optimized modal parameter estimation via Stochastic Subspace Identification is also proposed. These efforts aim at standardization of testing and data processing techniques. The final objective is a decrease of the level of uncertainty associated to the estimated modal parameters and, above all, damping ratios. Reduction of scatter and standardization of data processing procedures finally give the opportunity to build a reliable database for calibration of empirical formulations to be used, in the framework of structural and seismic design, for modal damping prediction.

The spacecraft and ground systems monitoring processes at the Jet Propulsion Laboratory are described, focusing on the monitoring of spacecraft telecommunications subsystem health and telecommunications link status operations. A system based on artificial intelligence technology that seeks to overcome many of these limitations is described. The system, called the Spacecraft Health Automated Reasoning Prototype (SHARP), is designed to automate health and status analysis for multimission spacecraft and ground data systems operations. The use of SHARP during the Voyager encounter with Neptune is evaluated. It has proved to be effective for detecting and analyzing potential spacecraft and ground systems problems by performing real-time analysis of spacecraft and ground data systems engineering telemetry. Four principal areas where benefits from the use of SHARP and its descendants, namely, safety, workforce savings, reliability, and productivity, are discussed

Metody przetwarzania sygnału EOG na użytek pomiaru stopnia zmęczenia osób Streszczenie. Celem prac raportowanych w artykule było zbadanie możliwości wykorzystania uproszczonego rejestratora EOG do detekcji i parametryzacji mrugnięć. Wykryte i opisane współczynnikami mrugnięcia mają posłużyć w późniejszych badaniach, jako cechy umożliwiające określenie stopnia zmęczenia osoby. Opracowane metody detekcji oraz algorytmy wyznaczania parametrów mrugnięć przetestowano dla 26 osób. Skuteczność detekcji mrugnięć wynosi 91%. Zaproponowany algorytm umożliwia automatyczne opisanie pojedynczego mrugnięcia z wykorzystaniem 6 wiarygodnych współczynników. Abstract. The purpose of the work reported in this article was to investigate the possibility of using a simplified EOG recorder for the detection and parameterization of blinks. The detected and reported batting coefficients are to be used in later studies as features to determine the degree of fatigue of a person. Developed detection methods and algorithms for determination blinking parameters, have been tested for 26 people. Blink detection is 91% effective. The proposed algorithm enables automatic single blink analysis using 6 reliable coefficients. Investigations of the possibility of using a simplified EOG recorder for the detection and parameterization of blinks Słowa kluczowe: wykrywanie zmęczenia, identyfikacja mrugnięć, EOG, selekcja cech.

7th International Conference on Signal Processing and Pattern Recognition (SIPR 2021) is a forum for presenting new advances and research results in the fields of Digital Processing and Pattern Recognition. The conference will bring together leading researchers, engineers and scientists in the domain of interest from around the world.

Dans le but de concevoir un système de diagnostic des défauts d'un moteur diesel 4 temps à combustion interne, l'incidence d'un défaut de distribution sur la vibration du moteur a été étudié. Ce défaut a été simulé en modifiant les jeux entre les cames et les poussoirs en contact avec les queues des soupapes.

This paper describes a unified data-driven prognostic framework that combines failure time data, static parameter data and dynamic (time-series) data. The approach employs Cox proportional hazards model (Cox PHM) and soft dynamic multiple fault diagnosis algorithm (DMFD) for inferring the degraded state trajectories of components and to estimate their remaining useful life (RUL). This framework takes into account the cross-subsystem fault propagation, a case prevalent in any networked and embedded system. The key idea is to use Cox proportional hazards model to estimate the survival functions of error codes and symptoms (soft test outcomes/prognostic indicators) from failure time data and static parameter data, and use them to infer the survival functions of components via a soft DMFD algorithm. The average remaining useful life and its higher-order central moments (e.g., variance, skewness, kurtosis) can be estimated from these component survival functions. The proposed prognostic framework has the potential to be applicable to a wide variety of systems, ranging from automobiles to aerospace systems.

Petri Nets is a technique used to model systems, and most of the references that can be found in the literature are related to computing systems. This Paper presents an explanation of the characteristics of Petri Nets and how they can be used as an approach to fault analysis. Also it presents a comparison with Fault Tree Analysis through a case study. Additional characteristics of this method are presented through examples.

A new multi-channel dynamic monitoring system was recently installed in a long span concrete arch bridge that crosses the Douro River in the city of Porto, Portugal: the "Infante D. Henrique" bridge. This paper describes the experimental and numerical studies developed shortly after construction of the bridge, characterizes the installed monitoring system and presents the results achieved with the software developed to process the data that is continuously received through the Internet. Preliminary studies included the development of an ambient vibration test and the construction of a numerical model of the bridge that was "tuned" to fit the bridge dynamic properties identified by the ambient vibration test. The routines implemented include the on-line automatic identification of the bridge's natural frequencies with the Frequency Domain Decomposition method, enabling the tracking of the bridge's first 12 natural frequencies. This unique feature is only possible due to the combination of high-quality acquisition equipment with state of the art processing algorithms.