bluuebunny/crossref_metadata_2025 huggingface dataset:
A EJA na Amazônia brasileira: a produção intelectual na ANPED/Norte
Authors: Francisca de Medeiros Adriana , dos Santos Pereira Silvane
Published: March 2024

No cenário educacional, a Educação de Jovens e Adultos (EJA) é pauta de discussão em fóruns, seminários e congressos. O objetivo desta pesquisa foi mapear a produção intelectual sobre Educação de Jovens e Adultos nos eventos da Associação Nacional de Pós-graduação – ANPED/Norte. Buscou-se analisar o que caracterizam essas produções, o que investiga e os seus principais resultados. A pesquisa contou com uma abordagem qualitativa, do tipo documental. O estudo foi realizado no período de setembro e outubro de 2020, por meio da página https://anped.org.br/. Por conseguinte, os dados construídos revelaram que as pesquisas contemplam vários aspectos da modalidade: políticas públicas, inclusão, currículo entre outros, configurando-se uma área interdisciplinar.
DAMPAK PERKEMBANGAN TEKNOLOGI TERHADAP HUKUM SEBAGAI TANTANGAN DIMENSI BARU KEAMANAN SIBER
Authors: Mahesa Sautaqi Izfahany , Garnida Dewanti Ayu , Effendi Rifqi Fauzi
Published: March 2024

ABSTRAK
 Definisi Kerugian Keuangan negara adalah konsep atau tindakan yang mengacu pada contoh tertentu dari keadaan keuangan negara, yang secara umum dipahami merujuk pada organisasi tertentu yang didirikan oleh seorang penguasa sekaligus berdaulat, dalam hal ini adalah bangsa. Kasus pengembalian hasil korupsi kepada negara tidak sedikit yang beranggapan bahwa tidak terpenuhinya dakwaan penuntut umum akan suatu tindak pidana korupsi dengan dipulihkan nya unsur kerugian negara membuat tidak terpenuhinya dakwaan penuntut umum pada tindak pidana korupsi. Meskipun transaksi tersebut mungkin dimulai dengan langkah yang benar, secara moral, sangat sulit untuk dibenarkan. Kajian kali ini menggunakan metodologi normatif yuridis dengan pendekatan status (status approach) atau pendekatan yuridis, yaitu kajian produk-produk yang berkaitan dengan hukum. Upaya pengembalian kerugian keuangan negara atas terjadinya tindak pidana korupsi secara yuridis dilaksanakan dari tahap penyidikan, tahap penuntutan dan tahap eksekusi atau pelaksanaan putusan pengadilan diatur dalam KUHAP.
Kata Kunci: Korupsi, Pengembalian, Ganti Rugi Keuangan.
ABSTRACT
 The definition of State Financial Loss is a concept or action that refers to a particular example of the state's financial situation, which is generally understood to refer to a certain organization founded by a ruler who is also sovereign, in this case the nation. In the case of returning the proceeds of corruption to the state, there are not a few who think that the public prosecutor's indictment of a criminal act of corruption has not been fulfilled by restoring the element of state losses, making the public prosecutor's indictment of a criminal act of corruption unfulfilled. While the transaction may have started on the right foot, morally speaking, it is very difficult to justify. This study uses a juridical normative methodology with a status approach or a juridical approach, namely the study of products related to law. Efforts to recover state financial losses due to the occurrence of criminal acts of corruption are legally carried out from the investigation stage, the prosecution stage and the execution stage or implementation of court decisions regulated in the Criminal Procedure Code.
Keywords: Corruption, Returns, Financial Compensation.
Organizational approaches to the formation of the financial control system in the activities of financial market participants
Authors: Kladnytska Tetyana , Artimonova Iryna , Kemenyash Iryna , Svynous Nadia
Published: March 2024

Introduction. The modern economy is characterized by the introduction of integrated business process management systems that allow optimizing the process of making and controlling management decisions based on the formation and use of an information-analytical model, which contributes to the optimal use of the company's investment resources in the long term. In this, when regulating financial market processes, there is an urgent need to implement a controlling system that allows you to take into account the above circumstances and build a system of effective management of investment resources.
Goal. Based on the generalization of research by scientists and the practical experience of business entities, offer practical recommendations on the formation of a financial controlling system for financial market participants.
Method (methodology). The methods of system analysis and theoretical generalization, comparative analysis and synthesis, historical-logical and functional-systemic approach were used to solve the problems.
The results. The concept of financial controlling, proposed by the author, defines financial controlling as a process-type system, which is a mechanism of interconnected, mutually complementary elements to realize the goal of the functioning of an economic entity - increasing the efficiency of the functioning of an economic entity in the conditions of a constantly changing external environment, and also maximizing the ownership of its shareholders.
Investment policy of the enterprise
Authors: Stefaniv Ihor
Published: March 2024

Introduction. The state of development of the economic system of Ukraine, the need to function in the conditions of martial law requires enterprises to search for more effective mechanisms for managing their own business, to achieve their goals faster, optimizing asset management processes, improving technological aspects of activity, effectively managing information. The increased level of riskiness of economic activity requires significant changes in the resource management system in order to ensure the stability of the production of goods and the processes of providing services in order to obtain an optimal level of profit. One of the areas of activity that can normalize profitability under conditions of uncertainty is investing.
Working under the conditions of a reduced level of demand, trying to preserve the stability of economic processes, economic relations with the rest of the business entities enterprises maximize their own efforts to maintain stable sales volumes and the amount of their own income, constantly searching for optimal forms of capital management, ensuring a relative level of financial stability.
Goal. The purpose of the research is to find ways to optimize the processes of managing investment activities, financial, material and informational resources to ensure the sustainability of economic processes.
Methodology. The methods of analysis and synthesis, generalization and comparison, scientific abstraction were used in the process of work.
Results. The article evaluates the effectiveness of capital management processes, outlines the main forms of investment activity, methods of resource concentration, directions for increasing the turnover of enterprise assets.
The factors that influence the effectiveness of investment processes, the formation of investment policy and the acceleration of the turnover of resources are identified. Assessment of the needs of financial resources for the implementation of investment projects, forms of use of loan capital is carried out. The forms of optimization of investment activity of enterprises, methods of selection and concentration of resources, directions of increasing the level of their liquidity are outlined. The effects that can be obtained as a result of the implementation of individual investment projects are defined. Attention is focused on the ability of investments to ensure the stability of the company's financial system and ensure sustainable development. The need to solve the problems of information provision of investment activity, selection of methods of obtaining information, forms of its management is noted.
The directions for the development of the scientific potential of enterprises, the forms of its use and the components of the optimal system of resource management are defined.
The forms of influence of investment processes on the level of profitability of activity, liquidity of assets and solvency, methods of optimizing the turnover of assets, forms of increasing the efficiency of activity due to the introduction of innovations are outlined.
Theoretical and methodological approaches to determining the development of regions
Authors: Kondratenko Nataliia , Prunenko Dmytro , Kovalenko Liudmyla , Khalil Khalilzade Orkhan
Published: March 2024

Introduction. It has been proven that the transformations taking place in the economy, the deepening of the negative impact of external and internal factors, the consequences of Russian aggression, require the formation of a foundation for changing existing trends and ensuring the development of regions. In this context, it should be pointed out the reduction of the gross regional product, the number of population, business entities, and the decrease in the main indicators of their activity. issues of ensuring regional development in the conditions of Russian aggression are insufficiently resolved, taking into account the influence of economic, security, functional, potential, strategic, stakeholder, regulatory and management factors. Moreover, there are no uniform approaches to determining the development of regions.
Goal. Definition of regional development, taking into account the current extraordinary economic conditions.
Method (methodology). To conduct research and obtain results, general scientific methods (theoretical substantiation, systematization) and special methods (identification of factors of regional development, formation of a categorical definition of regional development) are used.
The results. Theoretical and methodological approaches to determining the development of regions are distinguished: factorial, systemic, functional, goal-oriented, strategic, security, potential, stakeholder.
The concept of «development of regions» has been improved, which is defined by system characteristics that ensure the interaction of economic, functional, strategic, security, potential, stakeholder factors on the basis of the formation of a quantitative basis of regional development for the adoption of justified management decisions by state institutions regarding the formation of a new more favourable environment, the growth of investment attractiveness, competitiveness and standard of living of the population.
The influence of corporate management on the optimization of business processes
Authors: Miroshnychenko Ihor , Bradul Oleksandr
Published: March 2024

Cite as: Miroshnychenko I., and Bradul, O. (2023). The influence of corporate management on the optimization of business processes. Economic analysis, 33 (4), 253-260. DOI: https://doi.org/10.35774/econa2023.04.253

The relevance of the study is due to the fact that today the economic situation in Ukraine in connection with the military aggression of a neighboring country has acquired a rather critical state, as a result of which many domestic corporations are losing production ties, key suppliers and sales markets, reducing business performance indicators processes. Therefore, the main task of corporate management is to find ways to optimize business processes in the existing conditions and direct all the potential of the corporation to maintain and preserve the business. The purpose of the study is to determine the specifics of the impact of corporate governance on the optimization of the enterprise's business processes. The object of the research is cooperative management and its influence on the optimization of the corporation's business processes. The theoretical analysis within the scope of this study was carried out on the basis of the methods of analysis, systematization, generalization and comparison of the theoretical provisions of various researchers regarding the definition of the essence and content of corporate management, as well as its influence on the optimization of the enterprise's business processes. Based on the results of a critical review of scientific works on the essence of corporate governance, the following scientific approaches to its interpretation were distinguished: classical, managerial, regulatory, controlling, strategic, effective, shareholder stakeholder. The author's vision of a complex system of interaction of such approaches based on their systematization into three groups (interest, management, effect) is proposed. At the same time, interest-group approaches are distinguished by a greater attention of scientists to the issues of satisfying the interests of participants in corporate relations, management - an emphasis on management functions and tasks of corporate management, and the effect - on obtaining the desired results from such management in a strategic perspective. The definition of corporate governance is proposed as a system of managing corporate relations in an organization that functions in order to realize its strategic goals by ensuring the effectiveness of the mechanism for making effective decisions based on the regulation and control of corporate rights and monitoring the results of activities to ensure the balance of interests of participants in corporate relations. The content of the concept of "optimization of business processes" in the environment of corporate management is proposed, which is based on the key role of corporate management, which develops a strategy aimed at the result.
Development of ferroelectricity with crystallographic phase transformation in Hf0.5Zr0.5O2 thin films upon initial stimulation of an electric field exceeding the coercive field
Authors: Morita Yukinori , Onaya Takashi , Asanuma Shutaro , Ota Hiroyuki , Migita Shinji
Published: March 2024

This study demonstrates a drastic transformation of ferroelectricity and crystallographic phase in Hf0.5Zr0.5O2 (HZO) thin films through the first stimulation of an electric field larger than the coercive field in metal-ferroelectric-metal (MFM) capacitors. Initially, capacitance–voltage (C–V) measurements in fresh MFM capacitors with voltage sweep smaller than the coercive field indicated constant capacitance value without hysteresis. Applying the electric field exceeding the coercive field subsequently, the C–V behavior changed to a typical dual-peak ferroelectric feature in positive and negative sweeps. X-ray diffraction analysis of the HZO layers before and after a single electric-field application revealed small-angle shifts in diffraction peaks, confirming a crystallographic phase transformation induced by the single electric-field stimulation exceeding the coercive field. These results suggest a possibility that the first electric field apply initiates development of ferroelectric phase transformation from a non-ferroelectric phase.
Hydrogen-included plasma-assisted reactive sputtering for conductivity control of ultra-wide bandgap amorphous gallium oxide
Authors: Takenaka Kosuke , Komatsu Hibiki , Sagano Taichi , Ide Keisuke , Toko Susumu , Katase Takayoshi , Kamiya Toshio , Setsuhara Yuichi
Published: March 2024

Conductivity control of a-Ga2Ox films by cation/anion off-stoichiometry such as oxygen vacancy formation and hydrogen doping have been achieved by hydrogen-included plasma-assisted reactive sputter deposition system and physical and electrical properties of a-Ga2Ox films formed by this system have been investigated. The change in resistivity of a-Ga2Ox thin films deposited by the hydrogen-included plasma-assisted reactive sputtering was then investigated by changing the H2 flow rate ratio H2/(Ar + H2). The a-Ga2Ox thin films with semiconducting properties with a resistivity as low as 102 Ωcm was demonstrated using the plasma-assisted reactive sputtering system with addition to H2. Along with the low resistivity, the a-GaOx thin films with high film density and band gap energy of 5.2 g cm−3 and 4.8 eV were realized. The electrical resistivity of the a-Ga2Ox thin films can be controlled from 102 Ωcm to 105 Ωcm by appropriately controlling the amount of hydrogen introduced from the plasma. The results indicate that the hydrogen acts as a shallow donor, which increases the carrier concentration, can be efficiently introduced by using the plasma-assisted reactive sputtering system with addition to H2.
Twist angle dependence of graphene-stacked junction characteristics
Authors: Murakami Hayate , Fukunaga Fumiya , Ohi Motoki , Kubo Kosuke , Nakagawa Takeru , Kageshima Hiroyuki , Ohno Yasuhide , Nagase Masao
Published: March 2024

Vertically stacked graphene diodes are fabricated using epitaxially grown graphene with twist angles ranging from 0° to 30°. Their switching behavior and negative differential conductance are observed at all the measured angles. The junction conductance in the initial state does not indicate clear angle dependence and is almost constant, i.e. 231 μS for all devices. The junction conductance in the high-bias region exhibits a steep peak at 12°. The on/off ratio of the stacked junction diode indicates a maximum value of 142 at 12°. Therefore, the fabricated stacked graphene device with a simple structure exhibits strong nonlinear electrical properties and negative differential conductance at all twist angles. The on/off ratio of the stacked junction diodes is controlled by the twist angle between two single-crystal graphene layers.
Synthesis of Pd/WO3 and Pt/WO3 composite particles by sonochemical reactions and evaluation of their photocatalytic performance
Authors: Sato Kei , Yamashita Hironaga , Kojima Yoshihiro
Published: March 2024

In this study, precious metal/tungsten trioxide (WO3) composite particles in which palladium (Pd) and platinum (Pt) were loaded on WO3 particles were synthesized via the ultrasonic reduction method. The surface observation of the synthesized composite materials was performed and their photocatalytic performance under visible light irradiation was evaluated from the decomposition rate of methylene blue in aqueous solution. From the TEM image, it was found that the Pd/WO3 composite particles synthesized by the ultrasonic reduction method had a structure in which Pd nanoparticles were supported on WO3 particles. The photocatalytic performance of Pd/WO3 and Pt/WO3 increased with increasing contents of Pd and Pt. When synthesizing Pd(0.5 wt%)/WO3 particles by ultrasonic reduction method, the photocatalytic activity was improved by feeding Pd equivalent to 0.17 wt% per feed three times at regular time intervals, rather than by feeding 0.5 wt% of Pd at a time.
Method for measuring time waveforms of minute sinusoidal displacements using continuous waves with a network analyzer
Authors: Komatsu Yuya , Mori Shohei , Arakawa Mototaka , Kanai Hiroshi
Published: March 2024

This study proposes a method for precise measurement of time waveforms of minute sinusoidal displacements using continuous waves. The technique involves measuring the S-parameter of ultrasonic waves reflected from an object undergoing sinusoidal vibration with a network analyzer. When the sinusoidal displacement is not sufficiently small, second-order side peaks emerge in its inverse Fourier transform, alongside the main and first-order side peaks. This method, which incorporates second-order side peaks previously overlooked, enhances the accuracy of measurements. It facilitates precise measurement of sinusoidal displacements ranging from 0.3 to 50 μm at frequencies between 10 and 300 Hz.
Redox-induced changes in nanostructures and electron densities of connected Pt–Fe catalysts for fuel cells revealed via in situ coherent X-ray diffraction
Authors: Takayama Yuki , Itoh Takanori , Imai Hideto , Kuroki Hidenori , Yamaguchi Takeo
Published: March 2024

In a sustainable society, polymer electrolyte fuel cells are one of the promising energy devices for automobiles and residential uses because of their high energy efficiency. On the other hand, the current cathode catalysts are mainly made of precious metals such as Pt, and their activity and durability have become an issue for their widespread use. Carbon-free, connected Pt–Fe-alloy catalysts have been developed to solve this problem. However, their catalytic mechanism has not yet been clarified. In this study, redox-induced changes in the nanostructures and electron density distributions of the catalyst were investigated via coherent X-ray diffraction imaging.
Three-step field-plated β-Ga2O3 Schottky barrier diodes and heterojunction diodes with sub-1 V turn-on and kilovolt-class breakdown
Authors: Gilankar Advait , Islam Ahmad Ehteshamul , McCartney Martha R. , Katta Abishek , Das Nabasindhu , Smith David J. , Kalarickal Nidhin Kurian
Published: March 2024

A unique field termination structure combining a three-step field plate with nitrogen ion implantation to enhance the reverse breakdown performance of Pt/β-Ga2O3 Schottky barrier diodes (SBDs) and NiO/β-Ga2O3 heterojunction diodes (HJDs) is reported. The fabricated devices showed a low R
on,sp of 6.2 mΩ cm2 for SBDs and 6.8 mΩ cm2 for HJDs. HJDs showed a 0.8 V turn-on voltage along with an ideality factor of 1.1 leading to a low effective on-resistance of 18 mΩ cm2. The devices also showed low reverse leakage current (<1 mA cm−2) and a breakdown voltage of ∼1.4 kV. These results offer an alternative, simpler route for fabricating high-performance kilovolt-class β-Ga2O3 diodes.
Drift suppression of solution-gated graphene field-effect transistors through electrolyte submersion
Authors: Ushiba Shota , Tokuda Yuka , Nakano Tomomi , Ono Takao , Tani Shinsuke , Kimura Masahiko , Matsumoto Kazuhiko
Published: March 2024

In solution-gated graphene FETs (SG-GFETs), cations in electrolyte solutions can intercalate between graphene and SiO2. Such permeation affects substrate-induced hole doping effects, resulting in drifts in the charge neutrality point (CNP) of SG-GFETs. In this study, we investigated the effect of submerging GFETs in electrolyte solutions on CNP values. The results revealed that the CNP decreased considerably from approximately 180 mV to nearly zero with the increase in the immersion period. The CNP drifts during electrical measurements were also suppressed by the prolonged submersion. These insights can be used for developing improved SG-GFETs.
Physical and Environmental Factors Influencing Accessibility to Sanitation and Hygiene Services Among People Living with Disabilities in Kitui County, Kenya
Authors: Moko James , Mwanzo Isaac , Nyang’echi Edna
Published: March 2024

This study aimed to find out the physical and environmental factors influencing accessibility to sanitation and hygiene services among PLWD in Kitui County, Kenya. The study employed a cross sectional survey method. Disability status varied, with 44.2% having physical/mobility disabilities, 34.4% with visual disabilities, and 21.4% with hearing disabilities. In terms of physical and environmental factors, 95.6% had access to latrines, Improved pit latrines were the most common (52.3%). 93.3% reported sufficient space inside latrines, challenges included slippery floors (28.2%) and limited privacy (23%). Inferential statistics, employing logistic regression, identified significant associations. The logistic regression analysis elucidated significant factors influencing hygiene and sanitation accessibility among people with disabilities in Kitui County, Kenya. Socio-economic variables, including occupation (B = -0.212, p = 0.032), income (B = -1.068, p = 0.184), and education level (B = 0.457, p < 0.001), exhibited notable associations. Physical and environmental factors, such as latrine design for people with disabilities (B = -0.566, p = 0.077), played a crucial role. This study identified substantial challenges hindering people with disabilities (PLWD) from accessing adequate sanitation and hygiene, revealing critical issues related to physical and environmental barriers.
Multiple Faults Isolation for Hybrid Systems with Unknown Fault Pattern
Authors: Yu Ming , Wang Danwei , Luo Ming , Zhang DanHong
Published: March 2024

This work is concerned with multiple faults isolation for hybrid systems based on Global Analytical Redundancy Relationships (GARRs) approach. GARRs are derived from the Hybrid Bond Graph (HBG) model of a hybrid system with a specified causality assignment procedure. In this article, multiple faults are considered in a complex hybrid system and these faults can develop during a mode when the faults are not detectable. Once a fault is detected, a fault candidates set is generated from mode dependent-fault signature matrix (MD-FSM) tables and a set of fault pattern hypothesis is created from the fault candidates set for further refinement. Fault isolation is carried out using a multiple nonlinear least square optimization (MNLSO) algorithm. The developed technique can deal with multiple faults with unknown pattern. The fault could be of incipient or abrupt nature. The simulation results show the effectiveness of the proposed method.
An Adaptive Anomaly Detector used in Turbofan Test Cells
Authors: Lacaille Jérôme , Gerez Valério , Zouari Rafik
Published: March 2024

Airplane engines use sophisticated technologies to improve their efficiency, reduce their weight, reduce fuel consumption, limit NOx generation and reduce the generated noise. On another hand, airlines want to decrease their maintenance costs. These changes may have an effect on engine reliability and there is a greater need to understand and control the behavior of the engine. This is the goal of PHM algorithms. However, if such algorithms are "easy" to build, V&V stay a challenge. To increase their readiness level, Snecma, as engine manufacturer, tests all engines on bench cells during development phases and before reception. Now Snecma chooses also to use PHM algorithms on bench tests. It helps the maturation of the code itself but it is also a way to monitor the bench cells.

The present document describes an implementation on a partial bench test cell of a generic abnormality detector. The first section gives an outlook at the implementation of some algorithms on a real test cell. The second section is the description of the main algorithm: an online abnormality detector able to automatically update when new recurrent usual observations appear. Finally the last section sketches some results obtained during the execution of the algorithm.
Intelligent Monitoring of Surface Integrity and Cutter Degradation in High-speed Milling Processes
Authors: Zhai L-Y , Er M-J , Li X , Gan O-P , Phua S-J , Huang S , Zhou J-H , San L , Torabi A.J.
Published: March 2024

In high-speed milling process, dynamic monitoring and detection of work-piece surface defects and cutter degradation is a very important and also an extremely difficult task. Due to the inconsistency and variability of cutter geometry/dimensions, the uncertainties of machine tool conditions, as well as the complexity of the cutting process itself, the modelling of cutting performance in high-speed milling process has remained a challenging issue for both academia and industry. This paper attempts to exploit a force-based approach to model the cutting performance and detect the surface integrity of high-valued work-pieces in high-speed milling process. Experiments on high-speed dry-milling of Titanium (Ti6Al4V) using ball-nose end mills were conducted to verify the proposed approach. Preliminary findings from the study have shown that the force-based modelling techniques proposed is able to establish the association between cutting force signals and the degradation of cutting performance and so as to eliminate surface defects of work-pieces.
Prognostics with Autoregressive Moving Average for Railway Turnouts
Authors: Guclu Adem , Yılboga Halis , F. Eker Omer , Camci Fatih , Jennions Ian
Published: March 2024

Turnout systems are one of the most critical systems on railway infrastructure. Diagnostics and prognostics on turnout system have ability to increase the reliability & availability and reduce the downtime of the railway infrastructure. Even though diagnostics on railway turnout systems have been reported in the literature, reported studies on prognostics in railway turnout system is very sparse. This paper presents autoregressive moving average model based prognostics on railway turnouts. The model is applied to data collected from real turnout systems. The failure progression is obtained manually using the exponential degradation model. Remaining Useful Life of ten turnout systems have been reported and results are very promising.
Stochastic Characterization and Update of Fatigue Loading for Mechanical Damage Prognosis
Authors: Ling You , Shantz Christopher , Sankararaman Shankar , Mahadevan Sankaran
Published: March 2024

Accurate characterization and prediction of loading, while properly accounting for uncertainty, are essential for probabilistic fatigue damage prognosis. Three different techniques, including rainflow counting, the Markov chain method, and autoregressive moving average (ARMA) method, are reviewed for stochastic characterization and reconstruction of the fatigue load spectrum for prognosis. The ARMA method is extended by introducing random coefficients and probabilistic weights, to account for the uncertainty in the selection of models, inherent variability of loading, and uncertainty due to sparse data. A continuous model updating framework based on usage monitoring data is developed and applied to all the three techniques mentioned above. The relation between prediction accuracy and updating period is evaluated quantitatively. A quantitative model validation metric is proposed for assessing the accuracy of load prediction
Maintenance Planning with Prognostics for Systems Located In Various Places
Authors: Camci F. , Sevkli M. , Karakas M. , K. Jennions I.
Published: March 2024

Predictive maintenance has been attracting researchers and industry in recent years, since maintenance and repair of assets is one of the most contributing factors of operating & support cost. Predictive maintenance proposes to maintain the assets only when necessary aiming to reduce the unnecessary repair and maintenance by monitoring the health of the assets. The expected time of the failure is estimated by analyzing the monitored signals and remaining useful life of the asset before failure is used to plan, get prepared and perform the maintenance. When one team is responsible for maintenance of systems that are located in various places, the travel time between these systems should also be incorporated in the maintenance planning. Off shore wind farms and railway switches are two examples of these systems. This paper presents formulation of the problem that incorporates travel times between systems and prognostics information obtained from each system.
Integrated fatigue damage diagnosis and prognosis under uncertainties
Authors: Peng Tishun , He Jingjing , Liu Yongming , Saxena Abhinav , Celaya Jose , Goebel Kai
Published: March 2024

An integrated fatigue damage diagnosis and prognosis framework is proposed in this paper. The proposed methodology integrates a Lamb wave-based damage detection technique and a Bayesian updating method for remaining useful life (RUL) prediction. First, a piezoelectric sensor network is used to detect the fatigue crack size near the rivet holes in fuselage lap joints. Advanced signal processing and feature fusion is then used to quantitatively estimate the crack size. Following this, a small time scale model is introduced and used as the mechanism model to predict the crack propagation for a given future loading and an estimate of initial crack length. Next, a Bayesian updating algorithm is implemented incorporating the damage diagnostic result for the fatigue crack growth prediction. Probability distributions of model parameters and final RUL are updated considering various uncertainties in the damage prognosis process. Finally, the proposed methodology is demonstrated using data from fatigue testing of realistic fuselage lap joints and the model predictions are validated using prognostics metrics.
Sensor Selection with Grey Correlation Analysis for Remaining Useful Life Evaluation
Authors: Yu Peng , Yong Xu , Datong Liu , Xiyuan Peng
Published: March 2024

Sensor selection in data modeling is an important research topic for prognostics. The performance of prediction model may vary considerably under different variable subset. Hence it is of great important to devise a systematic sensor selection method that offers guidance on choosing the most representative sensors for prognostics. This paper proposes a sensor selection method based on the improved grey correlation analysis. From empirical observation, all the continuous-value sensors with a consistent monotonic trend are firstly selected for data fusion, and a linear regression model is used to convert the multi-dimensional sensor readings into one-dimensional health factor (HF). The correlation between HF and each of the selected sensors is evaluated by calculating the grey correlation degree defined on two time series. The optimal sensor subset with a relatively large correlation degree is selected to execute the final fusion. The effectiveness of the proposed method was verified experimentally on the turbofan engine simulation data supplied by NASA Ames, using instance-based learning methodology, and the experimental results showed that RUL prediction with fewer sensor inputs can obtain a more accurate prognostics performance than using all sensors initially considered relevant.
Wireless Power and Data System for Integrated System Health Management of Systems Operating in the Harsh Environment of Deep Space
Authors: Miller Jim , Patterson Jon , Garbos Ray
Published: March 2024

Large and complex deep space platforms such as the Deep Space Habitat (DSH) being developed by NASA will require a robust, on-platform, Integrated System Health Management (ISHM) function. Currently the DSH is contemplated to be stationed at the L2 Lagrangian point outbound from the lunar orbit. This will provide a vantage point of the back side of the moon as well as to serve as a jumping off platform for manned trips to Mars, the Moon, or near Earth asteroids. The ISHM function includes the monitoring, diagnostics, prognostics, and failure mitigation strategies and capabilities for any viable failure modes of the DSH. To evaluate a prototype of this approach, NASA has assembled a full scale, ISS derived, DSH prototype at the Marshall Space Flight Center (MSFC), involving a wired ISHM sensor network of over 80 sensors located at various points where early system failure mechanisms may be detected and analyzed. However, it is anticipated that a wired, distributed architecture could involve many pounds of complex cable harnesses and connectors, along with the commonly encountered problems of accessibility, flexibility and maintainability. In the high likelihood that modifications or upgrades are needed, these complexities result in higher design and build cost along with increased operational costs as in-flight anomalies occur that could require the addition of different sensors or different sensor locations. To address these issues, the ISHM team at MSFC is studying a wireless, distributed architecture with on- platform, advanced prognostic and diagnostic capabilities. The approach being considered is based on the X-33 ISHM system which consisted of hardware identical remote health nodes (RHN) and a central vehicle health management computer. Each RHN was very flexible and reprogrammable to enable it to interface directly with all the health monitoring sensors. For application on the DSH, modifications to the RHN are being considered. These changes and resulting upgraded capabilities are described in this paper. As ISHM sensor technology gets smaller, more robust, and includes wireless interfaces for communication and power, the approach will be to connect these wireless sensors by adding state-of-the-art wireless technology to the X-33 developed RHN. This wireless approach eliminates connectors and cables, thus reducing development, installation and life cycle costs while improving reliability and flexibility of the ISHM systems.
Processing for Improved Spectral Analysis
Authors: Bechhoefer Eric , Van Hecke Brandon , He David
Published: March 2024

The Fast Fourier Transform (FFT) is the workhorse of condition monitoring analysis. The FFTs’ assumption of stationarity is often violated in rotating machinery. Even in a six second acquisition on a wind turbine, the shaft speed can change by 5%. For Shaft and Gear analysis, this is mitigated through the use of the time synchronous average. For general spectrum analysis, or bearing envelope analysis, there is no such mitigation: one hopes that the effect of variation in shaft speed is small. Presented is a time synchronous resampling algorithm which corrects for variation in shaft speed, preserving the assumption of stationarity. This allows for improved spectral analysis, such as used in bearing fault detection. This is demonstrated on a real world-bearing fault.
Distribution Free Prediction Interval for Uncertainty Quantification in Remaining Useful Life Prediction
Authors: Chen Huimin
Published: March 2024

Remaining useful life (RUL) prediction is an important component for system health monitoring and prognosis. Ideally, one expects the prediction algorithm to provide the complete distribution of the RUL prediction over time taking various uncertainties into account. However, the dynamic model be- ing used to characterize state estimation and future loading uncertainties is often simplified through various approximations, leading to non-credible predicted distribution. Nevertheless, certain algorithm may only provide a point estimate of the RUL, making it difficult to quantify the uncertainty of the prediction. In this paper, we focus on interval prediction with high probability that guarantees finite sample validity without the knowledge of statistical distribution of the noise. The key idea is to leverage the newly proposed conformal pre- diction framework with non-parametric conditional density estimation. Under certain regularity conditions, the proposed interval estimator converges to an oracle band at a minimax optimal rate. In addition, we apply a data driven method to automatically select the bandwidth in the kernel density estimator. We discuss practical approximations to speed up the computation. The proposed method can be used to predict the RUL interval with physics-based model in a distribution free manner. It can also be applied to assess the validity of other prognostic algorithms from experimental data. We demonstrate the effectiveness of the RUL prediction for Li-Ion batteries using both simulated and experimental data.
Novelty detection in airport baggage conveyor gear-motors using Synchro-squeezing transform and Self-organizing maps
Authors: Hazra Budhaditya , Pantula Shilpa , Narasimhan Sriram
Published: March 2024

A powerful continuous wavelet transform based signal processing tool named Synchro-squeezing transform (SST) has recently emerged in the context of non-stationary signal processing. Founded upon the premise of time-frequency (TF) reassignment, its basic objective is to provide a sharper representation of signals in the TF plane. Additionally, it can also extract the individual components of a non- stationary multi-component signal, which makes it attractive for rotating machinery signals. This work utilizes the decomposing power of SST transform to extract useful components from gear-motor signals in relevant sub-bands, followed by the application of standard rotating machinery condition indicators. For timely detection of faults in airport baggage conveyor gear-motors, a novelty detection technique based on the recently developed concepts of self-organizing maps (SOM) is applied on the condition indicators. This approach promises improved anomaly detection pow

er than that can be achieved by applying condition indicators and SOM directly to the inherently complex raw-data. Data collected from the airport baggage conveyor gear-motors provides the test bed to demonstrate the efficacy of the proposed approach.
Cost-Benefit Analysis and Specification of Component-level PHM Systems in Aircrafts
Authors: Ka ̈hlert Alexander , Giljohann Sebastian , Klingauf Uwe
Published: March 2024

Unplanned aircraft ground times caused by component failures create costs for the operator through delays and reduced aircraft availability. Unscheduled maintenance on the other hand also creates costs for Maintenance, Repair and Overhaul (MRO) companies. The use of PHM is considered to improve the planning of component-specific maintenance and thus reduces consequential costs of unscheduled events on both sides.This study assesses the component-specific costs and characteristics of today’s maintenance approach. A discrete event simulation represents all relevant aircraft maintenance processes and dependencies. For this purpose the Event-driven Process Chain (EPC) method and Matlab/SimEvents are used. The data input (process information, empirical data) is provided by a particular MRO company.Whereas recent approaches deal with stochastically processed data only, e.g. failure probabilities, the proposed method mainly uses deterministic data. Empirical data, representing particular dependencies, describes all relevant stages in the component lifecycle. This includes operation, line and component maintenance, troubleshooting, planning and logistics.By simulating different scenarios, various maintenance future states can be evaluated by analysing effects on costs. The obtained economical and technical constraints allow to specify component-level PHM design parameters, as minimum prognostic horizon or accuracy. Detailed process-specific information is provided as well, e.g. costs of non-productive MRO activities or no-fault-found (NFF) characteristics.
Anomaly Detection Techniques for the Condition Monitoring of Tidal Turbines
Authors: S. Galloway Grant , M. Catterson Victoria , Love Craig , Robb Andrew
Published: March 2024

Harnessing the power of currents from the sea bed, tidal power has great potential to provide a means of renewable energy generation more predictable than similar technologies such as wind power. However, the nature of the operating environment provides challenges, with maintenance requiring a lift operation to gain access to the turbine above water. Failures of system components can therefore result in prolonged periods of downtime while repairs are completed on the surface, removing the system’s ability to produce electricity and damaging revenues. The utilization of effective condition monitoring systems can therefore prove particularly beneficial to this industry.This paper explores the use of the CRISP-DM data mining process model for identifying key trends within turbine sensor data, to define the expected response of a tidal turbine. Condition data from an operational 1 MW turbine, installed off the coast of Orkney, Scotland, was used for this study. The effectiveness of modeling techniques, including curve fitting, Gaussian mixture modeling, and density estimation are explored, using tidal turbine data in the absence of faults. The paper shows how these models can be used for anomaly detection of live turbine data, with anomalies indicating the possible onset of a fault within the system.
Estimation of Remaining Useful Life Based on Switching Kalman Filter Neural Network Ensemble
Authors: Lim Pin , Goh Chi Keong , Tan Kay Chen , Dutta Partha
Published: March 2024

The proposed method is an extension of an existing Kalman Filter (KF) ensemble method. While the original method has shown great promise in the earlier PHM 2008 Data Challenge, the main limitation of the KF ensemble is that it is only applicable to linear models. In prognostics, degradation of mechanical systems is typically non-linear in nature, therefore limiting the applications of KF ensemble in this area. To circumvent this problem, this paper propose to approximate non-linear functions with piecewise linear functions. When estimating the RUL, the Switching Kalman Filter (SKF) is able to choose the most probable degradation mode and thus make better predictions. The implementation of the proposed SKF ensemble method is illustrated by implementing on NASA’s C-MAPSS Dataset as well as the PHM 2008 Data Challenge Dataset. The results show the effectiveness of the SKF in detecting the switching point between various degradation modes as well as the improved accuracy of the SKF ensemble method compared to other available methods in literature.
A Low Frequency Uni-variate Model for the Effective Diagnosis and Prognosis of Bearing Signals Based Upon High Frequency Data
Authors: L. Godwin Jamie , Matthews Peter
Published: March 2024

Prognosis of rotating machinery is of vital importance to ensure ever increasing demands of availability, reduced maintenance expenditure and increased useful life are met. However, the prognosis of bearings typically employs techniques in the frequency or time-frequency domain due to the high frequency nature of the data involved (typically >20 KHz). This data quickly becomes unmanageable in practice and often has inferior prognostic horizons in comparison to those techniques which are based upon low frequency data analysis.This paper presents a novel methodology based upon the computation of the deviation from the empirically derived cumulative density function (CDF) of bearing data. For this purpose, the non-parametric, two sample, uni-variate Kolmogorov-Smirnov test is employed for the analysis. In particular, this paper focuses on mitigating the requirement of a-priori knowledge for bearing prognosis.Initially, assumptions regarding the underlying structure of high frequency bearing data are explored on publically available data, and found to deviate from what would be expected.Exploiting this, we use the non-parametric two-sample uni- variate Kolmogorov-Smirnov test to define normal operational behaviour, whilst mitigating the requirement for a-priori knowledge. This reduces the computational complexity of the system whilst having the prospect to reduce the inherent noise within the high frequency bearing signal.Strong trends of degradation which can be used to derive prognostic maintenance conditions are observed, with sound statistical analysis performed. In particular, statistically significant degradation is found to occur 75 hours before failure occurred (representing identification at 54.2% of bearing life). Both the Kolmogorov-Smirnov statistic and P -value are employed as health metrics to which degradation can be inferred from. A series of 4 experiments is presented, showing the versatility of the described technique and cases where the technique cannot be employed.The technique is validated on a failed bearing and then verified on an independent, healthy bearing, and is shown to correctly identify the bearing of question in each case, enabling the prioritisation of maintenance actions which can be used to assist in reducing overall maintenance expenditure.
Decentralized Approach for Fault Diagnosis of Three Cell Converters
Authors: Louajri Hanane , Sayed-Mouchaweh Moamar
Published: March 2024

In this paper, an approach for fault diagnosis of hybrid dynamic systems (HDS), in particular discretely controlled continuous system, is proposed. The goal is to construct a decentralized diagnosis structure, able to diagnose parametric and discrete faults. This approach considers the system as composed of a set of interacted hybrid components (HCs). Each HC is composed of a discrete component (Dc), e.g. on/off switches, with the continuous components (Ccs), e.g. capacitors, whose continuous dynamic behavior is influenced by the Dc discrete states. A local hybrid diagnosis module, called diagnoser, is associated to each HC in order to diagnose the faults occurring in this HC. In order to take into account the interactions between the different HCs, local diagnosis decisions are merged using a coordinator. The latter issues a final decision about the origin of the fault and identifies its parameters. The advantage of the proposed approach is that local hybrid diagnosers as well as the coordinator are built using local models. The proposed approach is applied to achieve the decentralized diagnosis of discrete and parametric faults of power electronic three-cell converters.