bluuebunny/crossref_metadata_2025 huggingface dataset:
Digital transformation of territorial communities of Ukraine: challenges and prospects in the conditions of martial law
Authors: Belova Iryna , Homotiuk Andrii , Yaroshchuk Oleksiy
Published: March 2024

Introduction. The article focuses on the analysis of the impact of digital transformation on the development of territorial communities of Ukraine under martial law, revealing the main challenges and prospects of this process. The role of digitalization in increasing management efficiency, transparency and involvement of citizens in solving local problems is determined.
Goal. The purpose of the article is to analyze the impact of digital transformation on the development of territorial communities of Ukraine in the context of martial law, to highlight the main challenges and prospects, as well as to develop recommendations for the further development of digital initiatives of local communities.
Method (methodology). The research uses case study methods to analyze specific examples of successful digital transformation, comparative analysis to identify general trends and challenges, as well as document analysis and literature review to evaluate theoretical approaches and existing strategies.
The results. The study demonstrates that digital transformation helps to strengthen the interaction between local authorities and citizens, increases the level of cyber security and ensures stable access to critical services in difficult conditions. However, challenges such as limited access to the Internet, insufficient digital literacy of the population and mistrust of digital services require a comprehensive approach and the involvement of international assistance. Recommendations include infrastructure development, digital literacy, and the development of new digital initiatives with an emphasis on supporting military personnel and veterans, as well as the development of e-commerce and other areas of community life.
Energy management: DSTU ISO 50001:2020 and conditions of martial law
Authors: Brych Vasyl , Tkach M.
Published: March 2024

The authors of the article emphasize the relevance of the issue of energy management system functioning and its role for the country's economy and business entities. As the authors point out, this problem becomes particularly acute in the conditions of martial law in Ukraine. The article highlights that effective management of energy resources can contribute to the stabilization and development of the national economy, reduce dependence on imported energy, and diversify energy sources. The authors also emphasize the importance of investing in renewable energy sources and developing innovative technologies to improve energy efficiency, which contributes to environmental preservation.
The article also stresses the need to adapt energy management practices to the challenging conditions of war based on the provisions and principles of DSTU ISO 50001:2020. It is emphasized that modern energy management faces a multitude of specific and critically important tasks, especially in wartime. These tasks include ensuring a stable energy supply, the rapid restoration of damaged infrastructure, promoting energy conservation, protecting energy infrastructure, and effective management of energy resources. Collaboration with government organizations and military structures is crucial, and communication with the public is also significant. All of this requires quick decision-making and flexibility, which are key to successful energy management in times of war.
Particular attention should be paid to the consideration of strategies and decisions that can help overcome these challenges, including the wider adoption of renewable energy, energy conservation, and energy efficiency in the activities of businesses.
In conclusion, the authors emphasize the need for a comprehensive approach and rapid adaptation to changing wartime conditions for effective energy management. They point out that such an approach will not only help Ukraine overcome current challenges but also ensure a sustainable energy future. This, in turn, will contribute to economic growth, environmental improvement, and national security.
Decentralization and sustainable development of rural areas: institutional regulation
Authors: Petrukha Serhiy
Published: March 2024

Introduction. The article is devoted to the study of the impact of decentralization on the sustainable development of rural areas of Ukraine through the prism of institutional regulation. The main theoretical approaches and practical initiatives implemented at the local level are considered in order to determine the optimal ways to achieve economic prosperity, social justice and environmental sustainability.
Goal. The purpose of the article is to analyze the impact of decentralization on the sustainable development of rural areas through institutional regulation, with the aim of identifying optimal ways to achieve economic prosperity, social justice and environmental sustainability.
Method (methodology). The research uses complex scientific methods, including analysis of existing literature, synthesis of data from various sources, comparative analysis of development strategies of united territorial communities, as well as empirical research methods to study specific examples of successful implementation of institutional innovations.
The results. The study confirmed that decentralization contributes to the sustainable development of rural areas in Ukraine, giving communities more opportunities to independently solve problems. The analysis of the strategies of the united territorial communities revealed that the successful implementation of sustainable development requires active participation of the public, strategic planning and adaptation of proven practices. The use of e-democracy and participatory budgeting has shown effectiveness in involving citizens in governance and ensuring transparency of local government actions. Cooperation with international organizations and innovative projects increases the effectiveness of sustainable development strategies, which leads to improved quality of life, economic growth and environmental sustainability. Recommendations include strengthening collaboration between sectors, expanding open governance practices, engaging the private sector, and increasing investment in local sustainable infrastructure.
Features of administrative responsibility for violation of customs rules
Authors: Vasylchyshyn Oleksandra , Tytor Volodymyr , Kekish Ihor
Published: March 2024

Introduction. The article is devoted to the analysis of the features and effectiveness of the application of administrative responsibility for committing a violation of customs rules in Ukraine, taking into account the current political situation and challenges related to armed aggression and the introduction of a legal regime of martial law in Ukraine.
The aim of the study. The main goal of the study is the analysis of the application of administrative responsibility for committing a violation of customs rules in order to ensure the appropriate level of national security of Ukraine, taking into account the challenges of introducing martial law in the country.
Method (methodology). A comprehensive approach was used for the analysis, which includes a review of legal acts, analysis of statistical data, and comparative analysis. The basis of the research is the methods of critical analysis, synthesis, as well as the methods of legal research to assess the effectiveness of countering the violation of customs rules due to administrative responsibility.
The results. This study confirms the significant role of the appropriate level of customs security for ensuring the national security of Ukraine, as well as the presence in the national legislative field of a well-balanced algorithm for the imposition of administrative responsibility for violations of customs rules by subjects of customs relations. A number of features of administrative responsibility for violation of customs rules and the growth of these violations during the period of armed aggression and the introduction of the legal regime of martial law in Ukraine, which requires increased control over manifestations of corruption in the customs system, have been identified. It is suggested that further research on this issue focus on the analysis of the impact of international anti-corruption practices, create incentives to counter this type of violations for the sake of economic revival of the country after the war, and develop innovative mechanisms for detecting and eliminating violations of customs rules to stimulate socially responsible behavior of citizens and ensure the national security of Ukraine.
Conclusions. The article contains an analysis of the features of administrative liability for violation of customs rules and an assessment of their effectiveness.
Analisis Keuntungan Usaha Kacang Sangrai UD. Merpati Di Desa Tombasian Atas Kecamatan Kawangkoan Barat
Authors: Mundung Fabio G.B. , Kapantow Gene Henfried Meyer , Tangkere Ellen Grace
Published: March 2024

This study aims to analyze the profitability of the roasted peanut industry at UD. Merpati in Tombasian Atas Village. The research lasted for three months from June to August 2023. The research was conducted at Merpati Roasted Peanuts, Tombasian Atas Village, West Kawangkoan District. Data collection methods used in this study were obtained through primary data and secondary data. Data analysis used in this research is business profit analysis, then the data collected is described descriptively to determine the amount of production costs incurred from the business being run. The results showed that UD Merpati roasted peanuts have 3 types of packaging with different prices and for the price installed with 250 gr packaging with a selling price of IDR20.000 while for 400 gr packaging with a selling price of IDR 30,000 and for 800 gr packaging has a selling price of IDR60.000. UD roasted peanut business. Merpati despite the increase in raw material prices obtained good results with a profit of IDR41.463.194.
Analisis Risiko Usahatani Padi Sawah Di Desa Radey Kecamatan Tenga Kabupaten Minahasa Selatan
Authors: Kesek Theofany , Baroleh Jenny , Jocom Sherly Gladys
Published: March 2024

The purpose of the study was to analyze the risk of wet-rice farming in Radey Village, Tenga Subdistrict, South Minahasa Regency. The research lasted for 2 months from September to October 2023. The research was conducted in Radey Village, Tenga District, South Minahasa Regency. Data collection methods in this study were collected through primary data obtained through direct interviews with wet-rice farmers in Radey Village using questionnaires. Secondary data were taken from village and sub-district offices as well as previous research reports, journals, and from the internet related to the research. The sampling method was purposive sampling. The number of samples in this study were 20 respondents who owned farmland (owners) to determine priority risks. Data analysis used in this research is the FMEA (Failure Mode and Effect Analysis) method. Criteria in assessing risk refers to The Basic of FMEA by McDermott with a scale of 1 to 3. Calculate the priority level of each risk source based on the Risk Priority Number (RPN) value. The results showed that there are 2 sources of risk faced by rice farmers that are directly related to rice plants and affect rice farming, namely the risk of production risk sources and price and marketing risks, production risks as many as 4 risks, namely strong winds, pest and disease attacks, erratic weather and climate, high rainfall intensity. Price and marketing risks are 2 difficulties in the process of selling grain, and expensive fertilizer prices. Based on the calculation of the RPN (Risk Priority Number) value, there are 3 risks out of 6 risks faced by rice farmers that must be prioritized. The first risk that must be prioritized first is uncertain weather/climate with an RPN value of 14.25, the second risk of high rainfall intensity with an RPN value of 12.16, and the third risk of strong winds with an RPN value of 10.72.
Spring constant of an AFM cantilever with a thin-film plasmonic waveguide formed at its end
Authors: Ito Masanao , Lang Lang , Zhang Kaifeng , Kobayashi Kei
Published: March 2024

Atomic-force-microscope (AFM)-based tip-enhanced Raman spectroscopy (TERS) is a promising analytical technique that can identify the physical and chemical properties of a sample’s surface. In the conventional TERS setup, the tip is directly irradiated by an incident light, which causes degradation of the contrast of the TERS signal due to the Raman scattered light from the surface area around the tip. We recently developed an AFM cantilever for indirect illumination AFM-TERS by milling the tip of the conventional cantilever to form a thin-film waveguide. Since the thin-film waveguide is considered as another cantilever attached at the end of the original cantilever, the waveguide cantilever can be treated as cantilevers connected in series. We then analyzed the static spring constant of the waveguide cantilever by both analytical and numerical methods and found that the static spring constant of the waveguide cantilever is lower than that of the original cantilever, which is advantageous in reducing the contact damage during the TERS measurements. We also proposed procedures to experimentally calibrate the static spring constant of the waveguide cantilever.
Benchmarking the Vehicle Integrated Prognostic Reasoner
Authors: Koutsoukos Xenofon , Biswas Gautam , A. Mylaraswamy Dinkar , Hadden George D. , Mack Daniel , Hamilton Doug
Published: March 2024

This paper outlines a benchmarking approach for evaluating the diagnostic and prognostic capabilities of the Vehicle Integrated Prognostic Reasoner (VIPR), a vehicle-level reasoner and an architecture which aims to detect, diagnose, and predict adverse events during the flight of an aircraft. A number of diagnostic and prognostic metrics exist, but these standards are defined for well-circumscribed algorithms that apply to small subsystems. For layered reasoners, such as VIPR, the overall performance cannot be evaluated by metrics solely directed toward timely detection and accuracy of estimation of the faults in individual components. Among other factors, the overall vehicle reasoner performance is governed by the effectiveness of the communication schemes between the different monitors and reasoners in the architecture, and the ability to propagate and fuse relevant information to make accurate, consistent, and timely predictions at different levels of the reasoner hierarchy. To address these issues, we outline an extended set of diagnostic and prognostics metrics that can be used to evaluate the performance of layered architecture, and we discuss a software architecture*as well as an evaluation plan for benchmarking VIPR.
Remote Health Monitoring for Offshore Machines, using Fully Automated Vibration Monitoring and Diagnostics
Authors: Mjit Mustapha , J. Beaujean Pierre-Philippe , Vendittis David
Published: March 2024

This paper describes the use of vibration analysis with a fully automated diagnostics system to detect common machine faults such as imbalance and misalignment as well as bearing and gearbox faults of offshore machines. Other faults types, e.g. when a large object hits the propeller blades may be detected using the STFT. As the mechanical properties of the structure can change because of changes of temperature and oil quality, these (and other) state data are also stored. The data fusion process is currently under work. Experiments were performed on a home cooling fan system to demonstrate and illustrate the faults detection capability of the vibration and diagnostics system. Vibration data were also acquired from selected equipment on a small boat with different combinations (on/off status) of the engine, generator and hydraulic pump. The trending and alarm features were demonstrated for the different types of data. The vibration and diagnostics system is implemented with threshold limits for the alerts and alarms corresponding to each technique. The model also allows for automatic storing of raw data periodically and after any deviations from normal conditions; i.e., when alerts are on.
Structural Health Monitoring on Metallic Aircrafts Using Flexible and Bulk PZT Transducers: Case of Corrosion Detection and Crack Localization
Authors: Boukabache Hamza , Escriba Christophe , Zedek Sabeha , Fourniols Jean-Yves
Published: March 2024

This work focus on the structural health monitoring of aircrafts parts specimen structures made of 2024 Aluminum alloys. In this paper we demonstrate the feasibility of a new non destructive control method capable to probe very large structures within a short time. The method we developed is based through a wide piezoelectric sensors network on a smart comparison between two acoustic signatures: the healthy structure response captured before the commissioning of the plane and “an after flight” response. The sensors network exploits the capability of piezoelectric patches to generate/measure specific Lamb wave’s modes. The system is therefore dynamically configured to localize mechanicals flaws using an algorithm that operates using different techniques like pitch-catch and pulse-echo.

An analytic study is performed and tests to prove the proposed method feasibility on corroded structures specimens are provided at the end of this paper.
Particle Filter Prognostic Applied in Landing Gear Retraction
Authors: Olivio Cerdeira Paula Borges , Harrop Galvão Roberto Kawakami , Pedro Pinheiro Malère João
Published: March 2024

The PHM (Prognostics and Health Monitoring) applications play an increasingly important role on the aeronautical industry and can provide a wide range of benefits for complex systems, such as aircraft landing gears (LDG). Indeed forecasting the RUL (Remaining Useful Life) of the landing gear subsystems can enable condition–based maintenance, improve the aircraft availability and reduce unscheduled events. The purpose of this work is to investigate nominal and degraded simulated retraction times of a landing gear and to apply a prognostics approach, specifically the particle filter (PF) algorithm, from which the RUL can be predicted at a given confidence level.
Predictive Modeling of High-Bypass Turbofan Engine Deterioration
Authors: Brasco Christina , Eklund Neil , Shah Mohak , Marthaler Daniel
Published: March 2024

The deterioration of high-bypass turbofan aircraft engines is an area of study that has the potential to provide valuable information to both engine manufacturers and users. Differences in deterioration between engines corresponding to different airlines, climates or flight patterns offer insight into ideal maintenance patterns and fine-tuned estimates on engine lifetime for airlines that operate over a wide range of conditions. In this paper, a model of high-bypass turbofan aircraft engine deterioration – based on cycle frequency, air quality, relative passenger mass and climate – and its possible application as a predictor of engine health and lifetime is described. Because the quantity of interest was long-term changes in engine health, the data set was mid- flight snapshot data, grouped as a set of time-series corresponding to different engines. Ultimately, a simple model was derived which can be used to predict how long a high-bypass turbofan engine will last under given conditions. Since all of the engines used in this study were the same configuration and model, the numeric results will be most valid when predicting health of engines of that variety. However, the approach outlined here could be used for any type of engine with enough available data. The results will allow manufacturers to provide better maintenance recommendations to owners of the assets.
A Stochastic Modeling Approach of Quantized Systems with Application to Fault Detection and Isolation of an Automotive Electrical Power Generation Storage System
Authors: Mohon Sara , Pisu Pierluigi
Published: March 2024

This paper introduces a stochastic modeling approach for a quantized system for the purpose of fault detection and isolation in an automotive alternator system. Three common alternator faults including belt slip, diode failure, and incorrect reference voltage for the voltage controller are considered and analyzed. A continuous nonlinear model of the alternator system is quantized into discrete states in order to simplify diagnostic efforts. The paper describes a stochastic modeling approach that creates a time-varying probability transition matrix that can be computed in real- time without the need for Monte Carlo simulation. Fault detection and isolation occurs through comparison of the most probable state from the transition matrix and the quantized output state.
Advanced Methods for Determining Prediction Uncertainty in Model-Based Prognostics with Application to Planetary Rovers
Authors: Daigle Matthew , Sankararaman Shankar
Published: March 2024

Prognostics is centered on predicting the time of and time un- til adverse events in components, subsystems, and systems. It typically involves both a state estimation phase, in which the current health state of a system is identified, and a pre- diction phase, in which the state is projected forward in time. Since prognostics is mainly a prediction problem, prognostic approaches cannot avoid uncertainty, which arises due to several sources. Prognostics algorithms must both characterize this uncertainty and incorporate it into the predictions so that informed decisions can be made about the system. In this paper, we describe three methods to solve these problems, including Monte Carlo-, unscented transform-, and first-order reliability-based methods. Using a planetary rover as a case study, we demonstrate and compare the different methods in simulation for battery end-of-discharge prediction.
An Efficient Model-based Diagnosis Engine for Hybrid Systems using Structural Model Decomposition
Authors: Bregon Anibal , Narasimhan Sriram , Roychoudhury Indranil , Daigle Matthew , Pulido Belarmino
Published: March 2024

Complex hybrid systems are present in a large range of engineering applications, like mechanical systems, electrical circuits, and embedded computation systems. The behavior of these systems is made up of continuous and discrete event dynamics that increase the difficulties for accurate and timely online fault diagnosis. The Hybrid Diagnosis Engine (HyDE) architecture offers flexibility to the diagnosis application designer to choose the modeling paradigm and the reasoning algorithms. The HyDE architecture supports the use of multiple modeling paradigms at the component and system level. How- ever, HyDE faces some problems regarding performance in terms of time and space complexity. This paper focuses on developing efficient model-based methodologies for online fault diagnosis in complex hybrid systems. To do this, we propose a diagnosis framework where structural model decomposition is integrated within the HyDE diagnosis framework to reduce the computational complexity associated with the fault diagnosis of hybrid systems. As a case study, we apply our approach to a diagnostic benchmark problem, the Advanced Diagnostics and Prognostics Testbed (ADAPT), using real data.
Qualitative Event-Based Fault Isolation under Uncertain Observations
Authors: Daigle Matthew , Roychoudhury Indranil , Bregon Anibal
Published: March 2024

For many systems, automatic fault diagnosis is critical to ensuring safe and efficient operation. Fault isolation is performed by analyzing measured signals from the system, and reasoning over the system behavior to determine which faults have occurred, based on models of predicted faulty behavior. For dynamic systems, reasoning may be performed using qualitative analysis of the differences between measured signals and their predicted values, in which observations take the form of qualitative symbols. Such an approach is quick to isolate faults, but depends critically on correct generation of the qualitative symbols from the signals. In this paper, we develop an approach to qualitative event-based fault isolation for dynamic systems that is robust to incorrect qualitative observations. Observations are treated as uncertain, where multiple interpretations of an observation, each with its own probability, are considered. By interpreting observed symbols in a probabilistic manner, the approach degrades gracefully as the number of incorrectly-generated symbols increases. The approach is demonstrated on an electrical power system testbed, and experiments using real data obtained from the hardware demonstrate the improved fault isolation performance in the presence of incorrect symbol generation.
Evolving Fuzzy Classifier based on Clustering Algorithm and Drift Detection for Fault Diagnosis Applications
Authors: Inacio Maurilio , Lemos Andre , Caminhas Walmir
Published: March 2024

Nowadays, in several areas, efficient fault diagnosis methods for complex machinery and equipments are required. Several fault diagnosis methods based on different theories and approaches have been proposed in the literature. In general, these methods use mathematical/statistical models, accumulated experience, or even process historical data to perform fault diagnosis. Although methods based on models or experience have shown to be effective, they have the disadvantage of requiring previous knowledge of the dynamic system in question. On the contrary, methods based on process historical data do not require a prior knowledge, they are based solely on data obtained directly from the dynamic system. The application of so-called “Evolving Intelligent Systems” to accomplish fault diagnosis from process data have been shown a promising approach. This paper proposes an evolving fuzzy classifier based on a new approach that combines a recursive clustering algorithm and a drift detection method and its application on dynamic systems fault diagnosis. The novel approach provides greater robustness to outliers and noise present in data from process sensors. The classifier is evaluated in fault diagnosis of an interacting tank system and the results are promising.
Investigating Vibration Properties of a Planetary Gear Set with a Cracked Tooth in a Planet Gear
Authors: Liang Xihui , J. Zuo Ming
Published: March 2024

Comparing with fixed shaft gearbox, vibration properties of planetary gearbox are much more complicated. In a planetary gearbox, there are multiple vibration sources as several pairs of sun-planet gears and several pairs of ring- planet gears mesh simultaneously. In addition, the signal transmission path changes due to the rotation of the carrier. To facilitate fault detection of a planetary gearbox and avoid catastrophic consequences caused by gear failures, it is essential to understand the vibration properties of a planetary gearbox. This paper aims to simulate vibration signals and investigate vibration properties of a planetary gear set when there is a cracked tooth in a planet gear. Displacement signals of the sun gear and the planet gear, and resultant acceleration signals of the whole planetary gear set will be simulated and investigated. Previous work mainly focuses on the vibration properties of a single component, like the sun gear, the planet gear or the carrier. This paper simulated the vibration signal of a whole planetary gear set when there is a cracked tooth in a planet gear. In addition, fault symptoms will be revealed, which can be utilized to detect the crack in the planet gear. Finally, the proposed approach is experimentally validated.
Standards for Prognostics and Health Management (PHM) Techniques within Manufacturing Operations
Authors: W. Vogl Gregory , A. Weiss Brian , Alkan Donmez M.
Published: March 2024

Prognostics and health management (PHM) technologies reduce time and costs for maintenance of products or processes through efficient and cost-effective diagnostic and prognostic activities. These activities aim to provide actionable information to enable intelligent decision-making for improved performance, safety, reliability, and maintainability. Thoughtful PHM techniques can have a dramatic impact on manufacturing operations, and standards for PHM system development, data collection and analysis techniques, data management, system training, and software interoperability need to exist for manufacturing. The National Institute of Standards and Technology (NIST) conducted a survey of PHM-related standards applicable to manufacturing systems to determine the needs addressed by such standards, the extent of these standards, and any commonalities as well as potential gaps among the documents. Standards from various national and international organizations are summarized, including those from the International Electrotechnical Commission, the International Organization for Standardization, and SAE International. Finally, areas for future PHM-related standards development are identified.
Verification of a Remaining Flying Time Prediction System for Small Electric Aircraft
Authors: F. Hogge Edward , M. Bole Brian , L. Vazquez Sixto , R. Celaya José , H. Strom Thomas , L. Hill Boyd , M. Smalling Kyle , C. Quach Cuong
Published: March 2024

This paper addresses the problem of building trust in online predictions of a battery powered aircraft’s remaining available flying time. A set of ground tests is described that make use of a small unmanned aerial vehicle to verify the performance of remaining flying time predictions. The algorithm verification procedure described here uses a fully functional vehicle that is restrained to a platform for repeated run-to-functional-failure experiments. The vehicle under test is commanded to follow a predefined propeller RPM profile in order to create battery demand profiles similar to those expected in flight. The fully integrated aircraft is repeatedly operated until the charge stored in powertrain batteries falls below a specified lower-limit. The time at which the lower- limit on battery charge is crossed is then used to measure the accuracy of remaining flying time predictions. Accuracy requirements are considered in this paper for an alarm that warns operators when remaining flying time is estimated to fall below a specified threshold.
Real-time Prognostics of a Rotary Valve Actuator
Authors: Daigle Matthew
Published: March 2024

Valves are used in many domains and often have system- critical functions. As such, it is important to monitor the health of valves and their actuators and predict remaining useful life. In this work, we develop a model-based prognostics approach for a rotary valve actuator. Due to limited observability of the component with multiple failure modes, a lumped damage approach is proposed for estimation and pre- diction of damage progression. In order to support the goal of real-time prognostics, an approach to prediction is developed that does not require online simulation to compute remaining life, rather, a function mapping the damage state to remain- ing useful life is found offline so that predictions can be made quickly online with a single function evaluation. Simulation results demonstrate the overall methodology, validating the lumped damage approach and demonstrating real-time prognostics.
Cyber Defense of Rotating Machinery Using an Integrated ‘Fuse’ Bearing
Authors: Cohen Evyatar , Bortman Jacob , Klein Renata
Published: March 2024

A new concept is proposed for protection against cyber-attacks aiming to create excessive loads that will eventually result in irreversible damage to critical rotating machines. This novel approach is used as an additional defense layer of cyber protection to prevent hostile entities from breaking into the control system of the critical machines.

A relatively small bearing is used as the "weak link", or the "fuse" mechanism, in the critical system. This mechanism allows rapid life degradation under harmful regimes, which leads to early detection of attack and finally to prevention of catastrophic damage to a critical machine. The detection of the fuse degradation process is based on techniques of machine health monitoring via vibrations signatures.

An analytical model was developed, allowing to design the 'fuse bearing'. The model examines the response of the fuse bearing, through its life degradation rate, by simulating a wide range of attack scenarios. The model integrates sub models: bearing life estimation models and a dynamic response of mechanical rotating machines model. In addition, a set of fatigue life experiments were conducted on a designated experimental test facility with the purpose of proving the early damage detection ability of the fuse bearing using vibration analysis.
Detection of pitch failures in wind turbines using environmental noise recognition techniques
Authors: Alexandros Skrimpas Georgios , S. Marhadi Kun , Gomez Robert , Walsted Sweeney Christian , Bech Jensen Bogi , Mijatovic Nenad , Holboell Joachim
Published: March 2024

Modern wind turbines employ pitch regulated control strategies in order to optimise the yielded power production. Pitch systems can be subjected to various failure modes related to cylinders, bearings and loose mounting, leading to poor pitching and aerodynamic imbalance. Early stage pitch malfunctions manifest as impacts in vibration signals recorded by accelerometers mounted in the hub vicinity, as for example on the main bearings or nacelle frame, depending on the installed condition monitoring system and turbine topology. Due to the location of the above mentioned vibration sensors, impacts of various origin, such as from loose covers, can be generated, complicating the assessment of the impact nature. In this work, detection of pitch issues is performed by analysing vibration impacts from main bearing accelerometers and applying environmental noise and speech recognition techniques. The proposed method is built upon the following three processes. Firstly, the impacts are identified using envelope analysis, followed by the extraction of 12 features, such as energy, crest factor and peak to peak amplitude and finally the classification of the events based on the above features. Eighty nine impacts are analysed in total, where 60 im- pacts are categorized as valid and 29 as invalid. It is shown that the frequency band of maximum crest factor presents the best classification performance employing K-means clustering, which is an unsupervised clustering technique. The high- est correct classification rate reaches 90%, providing useful information towards coherent and accurate fault detection.
Measurement Science for Prognostics and Health Management for Smart Manufacturing Systems: Key Findings from a Roadmapping Workshop
Authors: A. Weiss Brian , Vogl Gregory , Helu Moneer , Qiao Guixiu , Pellegrino Joan , Justiniano Mauricio , Raghunathan Anand
Published: March 2024

The National Institute of Standards and Technology (NIST) hosted the Roadmapping Workshop – Measurement Science for Prognostics and Health Management for Smart Manufacturing Systems (PHM4SMS) in Fall 2014 to discuss the needs and priorities of stakeholders in the PHM4SMS technology area. The workshop brought together over 70 members of the PHM community. The attendees included representatives from small, medium, and large manufacturers; technology developers and integrators; academic researchers; government organizations; trade associations; and standards bodies. The attendees discussed the current and anticipated measurement science challenges to advance PHM methods and techniques for smart manufacturing systems; the associated research and development needed to implement condition monitoring, diagnostic, and prognostic technologies within manufacturing environments; and the priorities to meet the needs of PHM in manufacturing.

This paper will summarize the key findings of this workshop, and present some of the critical measurement science challenges and corresponding roadmaps, i.e., suggested courses of action, to advance PHM for manufacturing. Milestones and targeted capabilities will be presented for each roadmap across three areas: PHM Manufacturing Process Techniques; PHM Performance Assessment; and PHM Infrastructure – Hardware, Software, and Integration. An analysis of these roadmaps and crosscutting themes seen across the breakout sessions is also discussed.
Method and System for Predicting Hydraulic Valve Degradation on a Gas Turbine
Authors: D’Amato James , Patanian John
Published: March 2024

This paper examines the development of a data-driven anomaly detection methodology for servo-actuated hydraulic valves installed in a gas turbine fuel delivery system. Degraded operation of these valves is a leading cause of unavailability for gas turbine driven power plants. Nearlyeighty potential features were generated from the limited raw sensors and control system signals through a combination of domain expertise, statistical feature extraction, and insight gains from prior physics-based simulations. Important features were down-selected by examining the behavior of the features using several years of operating data in conjunction with known field failures. Univariate statistical techniques were used to eliminate candidate features with limited capability to distinguish healthy from abnormal operation. A final machine learning model was generated using a process of recursive feature elimination. This paper will also touch on the practical implications of deploying a machine learning model in a real-time production environment.
System-level Prognostics for the National Airspace
Authors: Daigle Matthew , Sankararaman Shankar , Roychoudhury Indranil
Published: March 2024

In the National Airspace System (NAS), safety is assured through a set of rules, regulations, and procedures to respond to unsafe events. However, safety stands to benefit immensely from the introduction of tools and methodologies from Prognostics and Health Management (PHM). PHM will enable the NAS to stochastically predict unsafe states within the NAS, enabling a proactive preventative response strategy, as opposed to a reactive mitigative one. However, current PHM methods do not directly apply to the NAS for several reasons: they typically apply only at the component level, are implemented in a centralized manner, and are focused only on predicting remaining useful life. In this paper, we extend the model-based prognostics approach to PHM in order to provide a framework that can be applied to the NAS. We offer a system-level approach that supports a distributed implementation, and provide algorithms to predict the probability of an unsafe state, either at a specific time or within a time interval,and to predict the time of an unsafe state. Experimental results in simulation demonstrate the new approach.
Application of Multiple-imputation-particle-filter for Parameter Estimation of Visual Binary Stars with Incomplete Observations
Authors: Clavería Rubén M. , Acuña David , Méndez René A. , Silva Jorge F. , Orchard Marcos E.
Published: March 2024

In visual binary stars, mass estimation can be accomplished through the study of their orbital parameters –Kepler’s Third Law establishes a strict mathematical relation between orbital period, orbit size (semi-major axis) and the system total mass. Although, in theory, few observations on the plane of the sky may be enough to obtain a decent estimate for binary star orbits, astronomers must frequently deal with the problem of partial measurements (i.e.; observations having one component missing, either in (X; Y ) or (rho, theta) representation), which are often discarded. This article presents a particlefilter-based method to perform the estimation and uncertainty characterization of these orbital parameters in the context ofpartial measurements. The proposed method uses a multiple imputation strategy to cope with the problem of missing data. The algorithm is tested on synthetic data of relative position of binary stars. The following cases are studied: i) fully available data (ground truth); ii) incomplete observations are discarded; iii) multiple imputation approach is used. In comparison to a situation where partial observations are ignored,a significant reduction in the empirical estimation variance is observed when using multiple imputation schemes; with no numerically significant decrease on estimate accuracy.
PREVALENCE OF UNDIAGNOSED HEMOGLOBINOPATHIES AMONG PREGNANT WOMEN ATTENDING ANTENATAL CARE CLINIC AT TERTIARY CARE CENTER
Authors: Saradva Nidhi , Popat Vijay C. , Sultanbhai Sheikh Shamim , Dave Vandana , Hareshbhai Salot Param
Published: March 2024

Introduction: Hemoglobinopathies are the most common of all single gene inheritance (monogenic) autosomal
recessive diseases and the most severe include sickle cell disease and alpha/beta thalassemia major. As carriers are
typically asymptomatic and unaware of their carrier status, carrier couple often do not realize that with each pregnancy they face a 25% risk of
child with hemoglobinopathy. Pregnant women those who are carriers of hemoglobinopathy present with anemia of varying severity.
Aim And Objective:
Ÿ The aim of the study was to explore better strategies for hemoglobinopathy prevention in the preconception and antenatal phase in general
practice.
Ÿ The objective of this study was to determine the prevalence of undiagnosed hemoglobinopathy carriers in random sample of pregnant
women attending antenatal care clinic at tertiary care center.
Material And Method: We carried out a retrospective study in which 436 blood samples of pregnant women were analysed between August
2023 to October 2023 (3 months) in the department of pathology at tertiary care center. Total 436 blood samples of pregnant women were
analysed, genotype includes 21 case of beta thalassemia trait, 6 case of sickle cell trait, 1 case thalassemia intermedia, 1 case of delta-beta
thalassemia, 1 case of HbD heterozygous and 1 case of HbE heterozygous. Each blood sample was run in BIO-RAD HEMOGLOBIN
VARIANT- II HPLC machine. In present study, Prevalence of undiagnosed hemoglobinopathy carriers was Results: 7.11%. Out of which
4.81% were beta thalassemia trait, 1.38% sickle cell trait, 0.22% thalassmia intermedia, 0.22% delta- beta thalassemia, 0.22% HbD
heterozygous and 0.22% HbE heterozygous. This study reveals the high prevalence of undiagnosed hemog Conclusion: lobinopathy carriers
among pregnant women, indicating the need to immediately implement carrier screening and genetic counseling services across the country.
COMPARISON OF ULTRASONOGRAPHY AND COMPUTED TOMOGRAPHY TO EVALUATE THE CAUSES OF BILIARY OBSTRUCTION
Authors: Gafarbhai Khatri Imroz , Haider Abidi Syed Haleem , Tyagi Navjot
Published: March 2024

Objective: to watch how an ultrasonography (USG) examination and a computed tomographic (CT) scan are used to
assess the reasons of biliary blockage. Materials And Methods: A total of 57 individuals who were clinically suspected
of having obstructive jaundice participated in this cross-sectional investigation. Results: The age range of 40 to 49 years old had the highest
incidence of biliary blockage and the mean (±SE) age of the patients was 48.4 ± 1.6 yearsAll patients had elevated levels of serum alkaline
phosphatase and serum bilirubin. USG revealed 42 true negative instances, 2 false negative cases, and 13 true positive cases with no false
positives for the assessment of pancreatic mass. According to this, a CT scan revealed a true positive in 15 instances and a false positive, false
negative, or true negative in 42 others. Sensitivity and specicity of USG in detecting pancreatic mass were 80 and 97.6%. CT scan showed 93.3%
sensitivity and 97.6% specicity. In case of gallbladder (GB) mass USG found true positive in 20 and 1 false positive. In 36 situations, there was
neither a true negative nor a false negative. Moreover, a CT scan showed improved sensitivity. The USG was unable to nd any periampulla cases.
Conclusion: Both USG and CT scans are highly accurate in identifying biliary tree dilatation; however, CT scans are somewhat more accurate
than USGs. With time, the cost differential between the two should narrow, making CT an even more appealing and practical imaging option for
the hepatobiliary system.
IS DISTAL LOCKING OF LONG PFNA NECESSARY IN STABLE INTERTROCHANTERIC FRACTURE OF FEMUR?
Authors: Goswami Hrishikesh , Bhuyan Sikhar Jyoti
Published: March 2024

Background : Stable intertrochanteric fracture of femur (AO 31-A1) is an extracapsular fracture with intact
posteromedial cortex. Recent trends shift towards use of intramedullary nails over extramedullary devices. Distal locking
screw of intramedullary nail, designed to provide axial and rotational stability. Though distal locking is often routinely done, it has certain
disadvantages. This study aims to determine whether distal locking is necessary for the treatment of stable intertrochanteric fracture. Materials
& Methods : 42 patients were selected and randomized equally into distal locked and distal unlocked group from August 2020 to August 2021.
Patient were assessed on basis of duration of operation, uoroscopy exposure, intraoperative blood loss and postoperative complications.
Outcomes were assessed on basis of Harris Hip score clincally and serial radiographs. Patients were followed up for 12 months. In distal Results:
unlocked group there was reduction in duration of operation (42.90 ±1.497 mins versus 63.19 ± 2.343 mins, p <0.0001), uoroscopy exposure
time (69.05 ± 1.925 secs versus 79.05 ±2.176 secs, p = 0.0014) and intra-operative blood loss (140.0± 7.003ml versus 168.1 ± 5.632 ml, p=
0.0033) compared to distal unlocked group. Union was seen in all 42 cases. 2 cases (1 from each group) had varus collapse. 1 case had breakage of
implant. There was no signicant advantages in terms of Harris hip score (88.31±5.654 versus 87.00 ± 6.990, p= 0.6465) By Conclusion:
abandoning the use of distal locking screw in long PFNA in stable intertrochanteric fracture of femur (AO 31-A1), there were advantages in terms
of reduction in duration of operation, uoroscopy exposure time and intra-operative blood loss which was statistically signicant. In terms of
union, Harris Hip Score and recovery, distal locking or unlocking has no signicant inuence.
A RANDOMISED CLINICAL TRIAL COMPARING TOPICAL ITRACONAZOLE 1% WITH TOPICAL NATAMYCIN 5% FOR THE TREATMENT OF FILAMENTOUS FUNGAL KERATITIS
Authors: Jain Bahubali , Firdos Khan Saba , Jain Vaibhav
Published: March 2024

Aim: To compare the clinical efcacy of itraconazole 1% eyedrops with natamycin 5% eyedrops for topical
monotherapy of lamentous fungal keratitis. Patients presenting with features suggestive of fungal Methods: keratitis
over a period of 24 months from January2022 to December 2023 underwent detailed clinical examination and microbiological investigation.
Eighty three eyes of eighty three patients with direct smear and/or culture-proven fungal keratitis were enrolled in the study after obtaining
informed consent. Forty three patients received primary therapy with topical natamycin hourly labelled as group 1,and forty patients received
topical itraconazole hourly labelled as group 2. Success of the treatment was dened as a healed or healing ulcer at nal visit, and failure as an
ulcer that worsened or remained same at nal visit. On the basis of direct microscopy and culture t Results: he most common fungal isolate found
is Fusarium in 43 cases (51.8%) followed by Aspergillus in 17 cases (20.4%). In thirty-one (72%) of 43 patients in group 1 and 24 (60%) of 40
patients in group 2, the ulcer resolved completely. In keratitis due to Fusarium spp, 18 (79%) of 23 patients showed a favorable response to
natamycin, whereas 8 (44%) of 20 patients showed a favorable response to itraconazole. However, no such difference was evident in keratitis due
to Aspergillus spp or Curvularia spp. Both antifungal formulations were generally well tolerated with no obvious adverse effects. Conclusions:
Topical 5% natamycin appears to be safe and effective therapy for the management of fungal keratitis and should be considered as the treatment
of choice for lamentous fungal keratitis, especially in cases affected with Fusarium spp. Topical itraconazole therapy could be considered ,
particularly if the infections are due to Aspergillus or Curvularia spp.