bluuebunny/crossref_metadata_2025 huggingface dataset:
Kontrol Kestabilan Suhu Ruangan Menggunakan Sensor DS18DB20 Berbasis Mikrokontroller ATMEGA 328
Authors: Sumardiono Arif
Published: March 2024

Kontrol kestabilan suhu pada ruangan sangat di butuhkan terutama pada ruangan khusus yang membutuhkan kestabilan suhu tertentu, misalnya ruangan buat penetasan telur pada peternakan, fermentasi makanan, serta ruang untuk isolasi makanan agar tidak cepat membusuk. Pada penelitian ini di buat control kestabilan suhu ruangan menggunakan sensor suhu DS18B20 berbasis mikrokontroler ATmega 328 yang berfungsi agar suhu tetap stabil sesuai dengan suhu setpoint yang ditentukan pada pemogramannya. Berdasarkan hasil penelitian sensor suhu di bandingkan dengan thermometer output errornya dari 0.5 % hingga 1.1 % sehingga kalibrasinya masih baik. Ketika di aplikasikan untuk control kestabilan suhu kipas akan berhenti jika suhu terdeteksi di bawah 320 dan akan berjalan jika di atas 320 sesuai dengan setpoint yang di tentukan pada mikrokontroler.
Aplikasi Brosur Virtual Universitas Singaperbangsa Karawang Menggunakan Teknologi Augmented Reality (Studi Kasus : Universitas Singaperbangsa Karawang)
Authors: Nugraha Aditya Putra , Komarudin Oman , Suharso Aries
Published: March 2024

Kendala yang dibutuhkan bagi calon mahasiswa baru maupun masyarakat umum untuk mendapakan informasi tentang lembaga pendidikan Universitas Singaperbangsa Karawang yang berasal dari brosur kurang begitu lengkap secara detail dalam bentuk visualisasi 3 dimensi. Dengan menggunakan metode Multimedia Development Life Cycle (MDLC), dengan tool 3D Max sebagai pengolah 3D Objek serta aplikasi Photoshop dalam pengolahan 2D dibuatlah aplikasi brosur virtual dengan menggunakan aplikasi Unity 3D engine dan tools Vuforia SDK. Berdasarkan hasil kuesioner yang didapat dari responden yang telah mencoba teknologi informasi Augmented Reality serta penggabungan dengan teknologi Smartphone untuk menampilkan informasi Universitas Singaperbangsa Karawang dalam bentuk visualisasi 3 dimensi, diperoleh sebanyak 76,7% dari 30 responden dengan kriteria sangat setuju bahwa aplikasi brosur virtual Universitas Singaperbangsa Karawang interaktif.
Analisa Pola Penjualan Obat Menggunakan Algoritma Apriori Pada Apotek Zam-Zam Bogor
Authors: Asri Utami Lilyani , Ishaq Ahmad , Mariana Siti
Published: March 2024

Apotek merupakan suatu tempat untuk melakukan pembuatan, pengolahan, peracikan, penyimpanan dan penyaluran obat-obatan kepada masyarakat secara bebas maupun resep dari dokter. Peran apotek sangat penting bagi masyarakat, namun dengan adanya perkembangan teknologi dan sistem informasi yang begitu pesat, menuntut apotek untuk dapat mengikuti perkembangan teknologi guna memenuhi kebutuhan masyarakat secara cepat dan tepat. Banyak yang belum tahu jika laporan yang dihasilkan dari sistem informasi dapat dimanfaatkan untuk mencari pola kecenderungan pembelian obat dengan menggunakan Data Mining. Data Mining memiliki banyak metode, salah satunya adalah Algoritma Apriori. Algoritma Apriori adalah suatu metode untuk mencari pola hubungan antar satu atau lebih item dalam suatu dataset. Dengan mencari pola kecenderungan pembelian obat, maka akan didapatkan informasi mengenai obat apa saja yang banyak dibeli dan yang sering dibeli secara bersamaan oleh konsumen. Dengan diketahui obat yang sering dibeli, maka Apotek Zam-zam Farma Bogor dapat mengembangkan strategi pemasaran, mengatur stok obat agar tidak terjadi penumpukan obat maupun kekosongan obat dan mengatur tata letak penyimpanan obat yang sering dibeli secara bersamaan untuk mempermudah apoteker dalam mencari obat yang dibutuhkan guna mengoptimalkan pelayanan.
Agro morphological variability of cassava varieties cultivated in five regions of Côte d’Ivoire based on quantitative traits
Authors: Adjoua Kouakou Dorcas , Kouamé Koffi Kevin , Angui Chia Michelle Valérie , Komenan Any  Olivier , Zoro Bi Arsène Irié
Published: March 2024

ABSTRACT Objective: The objective of this study was to assess the morphological variability of cassava accessions from five regions of Côte d'Ivoire based on quantitative criteria. Methodology and Results: The material used was composed of cuttings from 200 cassava accessions collected in five agro-ecological zones of Côte d'Ivoire. The experimental set-up was a complete block randomised to one factor (accessions), and established on a fallow plot in the Haut Sassandra region (Daloa/Gosea). Fourteen quantitative descriptors were measured at different stages of plant development. The data collected were subjected to statistical tests. The principal component analysis applied to the 200 accessions showed a variability of 37.018 % revealed by the first two axis. The dendrogram produced by the UPGMA method highlighted three groups of accessions based on the 12 characters. These three groups were generally constituted independently of the agro-ecological zones of collection. Conclusion and Application of results: At the end of this study, it should be noted that the 200 cassava accessions collected in the five agro-ecological zones of Côte d'Ivoire are characterised by a strong morphological variability. This variability was structured into three distinct agro morphological groups with the height of the first branching and the number of branches of the plant as distinctive characters. The genetic variability observed between groups constituted by the accessions is important for varietal selection work. Key words: Agronomical, cassava, morphological, variability
PENGARUH TIMBAL ASETAT (Pb (CH3COO)2) TERHADAP PERTUMBUHAN MIKROALGA LAUT Nannochloropsis oculata
Authors: Mailoor Joshua W.T. , Kemer Kurniati , Rumengan Antonius P. , Gerung Grevo S. , Kaligis Erly Y. , Warouw Veibe
Published: March 2024

Microalgae are simple unicellular or multicellular microorganisms that are able to bind CO2 andcan absorb solar energy for the process of photosynthesis so that microalgae can convert inorganiccompounds into organic compounds. The organic compounds contained in microalgae arecarbohydrates, proteins, nucleic acids, and fats. The purpose of this study was to determine the growthand density of the microalgae Nannochloropsis oculata from the start of the culture to the exponentialphase and then proceed with the administration of lead acetate with 3 different concentrations. Thedensity of microalgae cells from the beginning of the culture to the exponential phase was on the 11day of observation. In the exponential phase, microalgae gave lead acetate treatment to 3 containerswith concentrations of 30 ppm, 50 ppm, 80 ppm and 1 control container without treatment. The growthof Nannochloropsis oculata cell density with lead acetate administration experienced a decrease ingrowth when compared to the control container (without lead acetate treatment).Keywords: Microalgae, Nannochloropsis oculata, Lead Acetate

ABSTRAKMikroalga merupakan mikroorganisme uniseluler atau multiseluler sederhana yang mampumengikat CO2 dan dapat menyerap energi matahari untuk proses fotosintesis sehingga mikroalga dapatmengubah senyawa anorganik menjadi senyawa organik. Senyawa organik yang terkandung dalammikroalga yaitu karbohidrat, protein, asam nukleat, dan lemak. Tujuan dari penelitian ini adalah untukmengetahui pertumbuhan dan kepadatan mikroalga Nannochloropsis oculata dari awal kultur sampaipada fase eksponensial kemudian dilanjutkan dengan perlakuan pemberian timbal asetat dengan 3konsentrasi yang berbeda. Kepadatan sel mikroalga dari awal kultur sampai pada fase eksponensialyaitu pada hari ke-11 pengamatan. Pada fase eksponensial, mikroalga diberikan perlakuan timbalasetat ke dalam 3 wadah dengan konsentrasi 30 ppm, 50 ppm, 80 ppm serta 1 wadah kontrol tanpaperlakuan. Pertumbuhan kepadatan sel Nannochloropsis oculata dengan pemberian timbal asetatmengalami penurunan pertumbuhan jika dibandingkan dengan wadah kontrol (tanpa perlakuan timbalasetat).

Kata kunci : Mikroalga, Nannochloropsis oculata, Timbal Asetat
KEANEKARAGAMAN DAN KELIMPAHAN ECHINODERMATA DI PANTAI PANCURAN PULAU LEMBEH
Authors: Christianti Yudith A. , Boneka Farnis B. , Kaligis Erly Y. , Sinjal Chatrien A.L. , Wagey Billy Th. , Lasabuda Ridwan
Published: March 2024

Echinodermata are found quite commonly in the tidal areas of Lembeh Island but their diversityand abundance have not been well documented. The purpose of this study was to determine the typesof Echinoderms and their abundance at Pancuran Beach, Lembeh Island, Bitung City. Samples weretaken at two stations using the Lincoln-Smith Transect method 2 x 50 m which was stretchedperpendicular to the beach with three replications. Samples were identified in situ and the number ofindividuals of each species was noted. The results showed that in Pancuran Beach there were 18species of phylum Echinodermata; with details of 7 species from the Asteroidea class, 5 species ofEchinoidea, 4 species of Ophiuroidea, 2 species of Holothuroidea. The results of the analysis using thediversity index show that the diversity of Echinodermata at both stations is in the medium category,characterized by the value of H' = 2.06 for station I and H'= 2.35 for station II. At station 1, the type ofOphiocoma erinaceus has the highest density of 15 ind/100m2 and a relative abundance of 23.68%. Atstation II Echinothrix diadema has the highest abundance of 12 ind/100m2 with a relative abundance of17.14%. Common species found in both stations are Diadema setosum, Echinometra mathaei,Echinothrix diadema, Holothuria atra, Ophiocoma erinaceus, and Ophiocoma scolopendrina.Keywords: Lembeh Island, Diversity, Abundance, Echinoderms

ABSTRAKEchinodermata ditemukan cukup umum di daerah pasang surut Pulau Lembeh namunkeanekaragaman dan kelimpahannya belum sepenuhnya didokumentasikan dengan baik. Tujuanpenelitian ini adalah untuk mengetahui jenis-jenis Echinodermata dan kelimpahannya di PantaiPancuran, Pulau Lembeh Kota Bitung. Sampel diambil pada dua stasiun dengan menggunakan metodeLincoln-Smith Transect 2 x 50 m yang dibentangkan tegak lurus ke arah pantai dengan tiga replikasi.Sampel diidentifikasi secara insitu dan jumlah individu tiap spesies dicatat. Hasil menunjukkan bahwadi Pantai Pancuran terdapat 18 spesies filum Echinodermata; dengan rincian 7 spesies dari kelasAsteroidea, 5 spesies Echinoidea, 4 spesies Ophiuroidea, 2 spesies Holothuroidea. Hasil analisamenggunakan indeks keanekaragaman menunjukkan bahwa diversitas Echinodermata pada keduastasiun dalam kategori sedang, ditandai dengan nilai H' = 2,06 untuk stasiun I dan H'= 2,35 untukstasiun II. Pada stasiun 1, jenis Ophiocoma erinaceus paling tinggi densitasnya yakni 15 ind/100m2dan kelimpahan relatif 23,68%, Pada stasiun II Echinothrix diadema memiliki kelimpahan tertinggi yakni12 ind/100m2 dengan kelimpahan relatif 17,14%. Jenis yang umum terdapat pada kedua stasiun adalahDiadema setosum, Echinometra mathaei, Echinothrix diadema, Holothuria atra, Ophiocoma erinaceus,dan Ophiocoma scolopendrina.

Kata kunci: Pulau Lembeh, Keanekaragaman, Kelimpahan, Echinodermata
Peningkatan Kompetensi dan Etika Bekerja Melalui Pelatihan Bahasa Jepang di PT Toray International Matsuoka Winner
Authors: Prasetya Dany Buyung Yudha , Oesman Andy Moorad , Sunahrowi
Published: March 2024

Work ethics and foreign language skills are essential for the professional, especially in a multinational corporate environment, where people who work have different cultures, languages, and nationalities. That is confirmed by observations at PT Toray International Matsuoka Winner Industries Semarang (PT TIMW). With daily interactions with Japanese clients and college, an understanding of the work ethics of Japanese corporations and proficiency in Japanese is necessary. The participants first studied Japanese corporate work ethics to improve PT TIMW staff's professional skills. Furthermore, ethical knowledge is covered by studying Japanese, which correlates to the office and business activities carried out by PT TIMW. The Japanese class training was attended by related department staff with the highest intensity of interacting with Japanese colleges and clients. Pair conversation activities were carried out to support the simulation of work situations related to production quantities and activities that indicate time. The tricky part was when the participants communicated by using numbers because there were differences in how to count between Indonesian and Japanese. The training showed good results where the participants could answer the mini-tests in each session. Pictures in textbook show an excellent impact in helping participants to imagine concepts and assist conversational activities in Japanese.
Optimizing Classification Methods for Online Buyers' Purchase Intentions in Bangladesh
Authors:   Department of CSE, CCN University of Science and Technology, 3500 Cumilla, Bangladesh., Ahmed Ikbal , Hoque Md Mahmudul ,   Department of CSE, CCN University of Science and Technology, 3500 Cumilla, Bangladesh., Banik Nayan ,   Department of CSE, Comilla University, 3500 Cumilla, Bangladesh., Rahman Atiqur ,   School of Science Engineering, Chittagong Independent University, Jamal Khan, Bangladesh., Nur-E-Alam Mohammad ,   Institute of Sustainable Energy, Universiti Tenaga Nasional, Jalan IKRAM- UNITEN, 43000 Kajang, Selangor, Malaysia, Islam Mohammad Aminul ,   Department of Electrical Engineering, Faculty of Engineering, Universiti Malaya, 50603 Kuala Lumpur, Malaysia.
Published: March 2024

The classification of online buyers' purchasing intentions is of paramount importance, especially in the context of the period of the COVID-19/post-COVID-19 pandemic, as it carries significant implications for the business industry. However, effectively managing the diverse ever-changing intentions of individual Internet customers remains a challenging task. This study aims to improve the classification techniques used to classify different sorts of online buyers' purchasing intents in Bangladesh. A comprehensive analysis of different classification algorithms reveals that the Random Forest algorithm outperformed other methods, achieving exceptional accuracy rates of 99.9% in training and 89.7% in testing. Conversely, the Gaussian Naive Bayes algorithm demonstrated comparatively lower accuracy, with training testing accuracies of 80% and 79%, respectively. This study contributes not only to a better understanding of online buyers' purchase intentions in Bangladesh but also provides valuable insights into the business industry. Moreover, our work highlights the potential for future investigations in recognizing Bangla numerals throug gestures to enhance the accuracy of categorizing online buyers' intended purchases. This research serves as a stepping stone for further advancements in classifying and understanding online buyers' purchase intentions, ultimately fostering more accurate decision-making in the realm of E-commerce in Bangladesh.
A Decentralized Service Based Architecture for Design and Modeling of Fault Tolerant Control Systems
Authors: Nyberg Mattias , Svärd Carl
Published: March 2024

The paper presents a hierarchical architecture for fault tolerant control of mechatronic systems. In the architecture, both the diagnosis and the reconfiguration are completely decentralized according to the structure of the control system. In each module of the control system, diagnosis and reconfiguration are included and use only locally available signals. Therefore, no extra dependencies are added to the control system software, something which is important to facilitate efficient engineering of large scale system. All this is achieved by using a purely service oriented view of the system including both hardware and software. The service view with no cyclic dependencies is further used to obtain Bayesian networks for modeling the system.
Large-scale signal reconstruction for sensor monitoring and diagnostics in nuclear power plants
Authors: Gola Giulio , Roverso Davide , Hoffmann Mario
Published: March 2024

On-line sensor monitoring and diagnostics systems aim at detecting anomalies in sensors and reconstructing their correct signals during operation. Since 1994, research at the OECD Halden Reactor Project has focused on the problem of sensor monitoring and diagnostics, eventually leading to the development of the PEANO system for signal validation and reconstruction. PEANO combines empirical techniques like Fuzzy Clustering and Auto- Associative Neural Networks and has proved to be successful in a variety of practical applications. Nevertheless, using one single empirical model sets a limit to the number of signals that can be handled at a time. Recently, efforts have been made to extend the applicability of PEANO to the whole plant, which requires the validation and reconstruction of thousands of signals. This has entailed moving from a single-model to an ensemble-of-model approach which has involved the investigation of new issues. This paper presents the method hereby developed for on-line, large scale sensor monitoring and signal reconstruction and a practical application of the method to the reconstruction of signals measured at nuclear power plants.
Fault diagnosis in databases for business processes
Authors: Go ́mez-Lo ́pez M. Teresa , M. Gasca Rafael
Published: March 2024

Business processes involve data that can be modified or updated by various activities. These data must satisfy the business rules associated to the process. As the information treated in a business process tends to be extensive, data are normally stored in a relational database, and hence the database has to be analyzed to determine whether the business rules are satisfied and what values are incorrect. This paper proposes the use of model-based diagnosis in the business processes scenario. This scenario combines business processes, business rules, relational databases and where the faults are the instances of the variables introduced by the users. These considerations make it necessary to introduce a new way for representing the model, and the design of new algorithms to solve it. This model provides a means for the detection of incorrect tuples of different tables of the database by avoiding the analysis of the full database. Furthermore, in order to manage the current business rules, the use of a constraint paradigm is proposed and by using Max- CSPs to isolate incorrect values.
A Structural Algorithm for Finding Testable Sub-models and Multiple Fault Isolability Analysis
Authors: Krysander Mattias , Aslund Jan , Frisk Erik
Published: March 2024

Structural methods have previously been used to perform isolability analysis and ﬁnding testable sub-models, so called Minimal Structurally Overdetermined (MSO) sets, Analytical Redundancy Relations (ARR), or Possible Conﬂicts (PC). The number of MSO sets grows exponentially in the degree of redundancy making the task of computing MSO sets intractable for systems with high degree of redundancy. This paper describes an eﬃcient graph-theoretical algorithm for computing a similar, but smaller, set of testable submodels called Test Equation Supports (TES). A key diﬀerence, compared to an MSO based approach, is that the inﬂuence of faults is taken into account and the resulting number of testable models as well as the computational complexity of ﬁnding them can be reduced signiﬁcantly without reducing the possible diagnosis performance. It is shown that the TESs in a direct way characterize the complete multiple fault isolability property of a model and thus extends previous structural approaches from the single-fault case.
A Discussion of the Prognostics and Health Management Aspects of Embedded Condition Monitoring System
Authors: I. Grosvenor Roger , W. Prickett Paul
Published: March 2024

This paper presents a review of embedded condition monitoring research carried out at Cardiff University. A variety of application areas are described, along with a discussion of the evolution of the hardware platforms used. The current operating philosophies of the Intelligent Process Monitoring and Management (IPMM) research group and the deployed hierarchical and distributed architectures are described. The paper sets out to discuss the on-going trend towards such monitoring systems needing to provide more than fault detection and diagnostic capabilities. System requirements such as tracking operational settings, performance and efficiency measures and providing limp-home facilities are seen to be consistent with prognostics and health management ideals. The paper concludes with a discussion of new and future developments and applications.
Multiple Fault Diagnostic Strategy for Redundant System
Authors: Peng Yang , Jing Qiu , Guan-jun Liu , Ke-hong Lv
Published: March 2024

It is difficult to diagnose the faults, especially multiple faults, in redundant systems by traditional diagnostic strategies. So the problem of multiple fault diagnostic strategy for redundant system was researched in this paper. Firstly, the typical characters of multiple faults (minimal faults) were analyzed, and the problem was formulated. Secondly, a pair of two-tuples were applied to denote the possible and impossible diagnostic conclusion at different diagnostic stages respectively, and a multiple fault diagnostic inference engine was constructed based on Boolean logic. The inference engine can determine the system diagnostic conclusions after executing each test, and determine whether a repair action was needed, and further determine whether a next test was needed. Thirdly, a method determining the next best test was presented. Based on the proposed inference engine and test determining method, a multiple fault diagnostic strategy was constructed. Finally, a simulation case and a certain flight control system were applied to illustrate the proposed diagnostic strategy. The simulation and practical data computational results show that the presented diagnostic strategy can diagnose multiple faults in redundant systems effectively and it is of certain application value.
Bayesian fatigue damage and reliability analysis using Laplace approximation and inverse reliability method
Authors: Guan Xuefei , He Jingjing , Jha Ratneshwar , Liu Yongming
Published: March 2024

This paper presents an efficient analytical Bayesian method for reliability and system response estimate and update. The method includes additional data such as measurements to reduce estimation uncertainties. Laplace approximation is proposed to evaluate Bayesian posterior distributions analytically. An efficient algorithm based on inverse first-order reliability method is developed to evaluate system responses given a reliability level. Since the proposed method involves no simulations such as Monte Carlo or Markov chain Monte Carlo simulations, the overall computational efficiency improves significantly, particularly for problems with complicated performance functions. A numerical example and a practical fatigue crack propagation problem with experimental data are presented for methodology demonstration. The accuracy and computational efficiency of the proposed method is compared with simulation-based methods.
Comparison of Parallel and Single Neural Networks in Heart Arrhythmia Detection by Using ECG Signal Analysis
Authors: Sadat Hosseini Rooteh Ensieh , Zhang Youmin , Tian Zhigang
Published: March 2024

In this study, we have presented a method for detecting four common arrhythmias by using wavelet analysis along with the neural network algorithms. The method firstly includes the extraction of feature vectors with wavelet analysis. Then, the vectors will be categorized by means of the neural network into four classes. Input signals are recorded from two different leads. In addition, we have used both continuous and discrete wavelet analyses simultaneously for feature extraction. This results into increasing the accuracy of feature vectors extraction. Also, using the continuous wavelet in a specific scale can lead to better extraction of coefficients as well as more accurate data. In order to decrease the computational efforts and increase the training speed, the dimensions of the feature vectors have been reduced by substituting the wavelet coefficients with their statistical parameters. Furthermore, two approaches are introduced in classification of feature vectors. The first approach comprises four neural networks in the parallel form for detection of four classes, while the second approach makes use of one network for four classes. Numerical simulation results show that in comparison with the previous studies, the proposed methods are more accurate and faster. In addition, it is observed that the second approach has better capabilities in classification of data than the first one. On the other hand, the first approach is believed to have a good function for complicated data spaces.
A Testbed for Real-Time Autonomous Vehicle PHM and Contingency Management Applications
Authors: Tang Liang , Hettler Eric , Zhang Bin , DeCastro Jonathan
Published: March 2024

Autonomous unmanned vehicles are playing an increasingly important role in support of a wide variety of present and future critical missions. Due to the absence of timely pilot interaction and potential catastrophic consequence of unattended faults and failures, a real-time, onboard health and contingency management system is desired. This system would be capable of detecting and isolating faults, predicting fault progression and automatically reconfiguring the system to accommodate faults. This paper presents a robotic testbed that was developed for the purpose of developing and evaluating real-time PHM and Automated Contingency Management (ACM) techniques on autonomous vehicles. The testbed hardware is based on a Pioneer 3-AT robotic platform from Mobile Robots, Inc. and has been modified and enhanced to facilitate the simulations of select fault modes and mission-level applications. A hierarchical PHM-enabled ACM system is being developed and evaluated on the testbed to demonstrate the feasibility and benefit of using PHM information in vehicle control and mission reconfiguration. Several key software modules including a HyDE-based diagnosis reasoner, particle filtering-based prognosis server and a prognostics-enhanced mission planner are presented in this paper with illustrative experimental results. This testbed has been developed in hope of accelerating related technology development and raising the Technology readiness level(TRL)ofemergingACM techniques for autonomous vehicles.
Adaptive Load-Allocation for Prognosis-Based Risk Management
Authors: Bole Brian , Tang Liang , Goebel Kai , Vachtsevanos George
Published: March 2024

It is an inescapable truth that no matter how well a system is designed it will degrade, and if degrading parts are not repaired or replaced the system will fail. Avoiding the expense and safety risks associated with system failures is certainly a top priority in many systems; however, there is also a strong motivation not to be overly cautious in the design and maintenance of systems, due to the expense of maintenance and the undesirable sacrifices in performance and cost effectiveness incurred when systems are over designed for safety. This paper describes an analytical process that starts with the derivation of an expression to evaluate the desirability of future control outcomes, and eventually produces control routines that use uncertain prognostic information to optimize derived risk metrics. A case study on the design of fault-adaptive control for a skid-steered robot will illustrate some of the fundamental challenges of prognostics-based control design.
E2GK-pro: An Evidential Evolving Multimodeling Approach for Systems Behavior Prediction
Authors: Serir Lisa , Ramasso Emmanuel , Zerhouni Noureddine
Published: March 2024

Nonlinear dynamic systems identification and nonlinear dynamic behavior prediction are important tasks in several areas of industrial applications. Multiple works proposed multimodel-based approaches to model nonlinear systems. Multimodeling permits to blend different model types together to form hybrid models. It advocates the use of existing, well known model types within the same model structure. Recently, a multi modeling strategy based on belief functions theory was developed based on a fuzzy rule based system. We propose a different approach of this latter taking advantage of new efficient evidential clustering algorithms for the determination of the local models and the assessment of the global model. In particular, we propose an online procedure based on the Evidential Evolv- ing Gustafsson-Kessel (E2GK) algorithm that ensures an evolving partitioning of the data into clusters that correspond to operating regions of the global system. Thus the estimation of the local models is dynamically performed by upgrading and modifying their parameters while the data arrive. Each local model is weighted by a belief mass provided by E2GK, and the global model (multimodel) is a combination of all the local models.
Optimization of fatigue maintenance strategies based on prognosis results
Authors: Xiang Yibing , Liu Yongming
Published: March 2024

A general approach to determine the optimal set of maintenance alternatives for fatigue safety is introduced in this paper. The optimal maintenance alternatives are the solutions to maximize the fatigue reliability of aircrafts fleet subject to maintenance budget. A novel equivalent stress transformation model and the first-order-reliability method (FORM) are adopted to determine the failure probability or reliability associated with future fatigue loading. The equivalent stress transformation model is capable to transform future random loading to an equivalent constant loading, and does not require cycle-by-cycle simulation. First-order-reliability-method can resolve the computational complexity. Optimal maintenance solution can be efficiently found considering the future fatigue loading. Numerical examples are performed to demonstrate the application of the proposed approach.
Health Monitoring of a Power Supply Using Multivariate Regression
Authors: Ramos Rodrigues Leonardo , Paulo Pordeus Gomes João , Yoneyama Takashi , Kawakami Harrop Galvão Roberto
Published: March 2024

Due to the increasing use of electronics in critical aircraft control systems, it has become more and more important in the aerospace industry to understand how the degradation process of electronic devices occurs. Power supplies are devices of special interest since their internal components such as diodes, capacitors, MOSFETs (Metal Oxide Semiconductor Field Effect Transistor) and IGBTs (Insulated Gate Bipolar Transistors) operate under continuous stress conditions and often present elevated failure rates. The aim of this work is to present a methodology for detecting the gradual health degradation of a COTS (Commercial off-the-shelf) power supply. An accelerated aging process for power MOSFETs was conducted. During this experiment, power MOSFETs were subjected to thermal overstress in order to increase die- junction temperature above rated value through large current from drain to source. Multivariate regression analysis was applied to the raw data collected during the tests in order to assess the power supply health status.
Multi-turbine Associative Model for Wind Turbine Performance Monitoring
Authors: Uluyol Onder , Parthasarathy Girija
Published: March 2024

Comparing the performance parameters of a set of wind turbines in a single region will provide insights that prevent raising unnecessary alarm, while confirming actual faults. Wind turbines operating in a wind farm experience similar operating and environmental conditions that could indicate either normality for that group or failures that manifest in those conditions. These norms and failures are an orthogonal set of data rich in information that can be utilized in performance monitoring algorithms to supply better prediction accuracy and low false positives. In this paper, we describe the use of an associative model (AM) for fault detection in a population. An associative model maps system parameters to an identical set of virtual parameters. The AM-based approach can be used to capture the underlying correlation of an observable system, such as performance parameters of a set of wind turbines in a wind farm. The residuals between the model output and the input can then be used to detect anomalies and isolate faults.
Use of COTS Functional Analysis Software as an IVHM Design Tool for Detection and Isolation of UAV Fuel System Faults
Authors: Niculita Octavian , Irving Phil , K Jennions Ian
Published: March 2024

This paper presents a new approach to the development of health management solutions which can be applied to both new and legacy platforms during the conceptual design phase. The approach involves the qualitative functional modelling of a system in order to perform an Integrated Vehicle Health Management (IVHM) design – the placement of sensors and the diagnostic rules to be used in interrogating their output. The qualitative functional analysis was chosen as a route for early assessment of failures in complex systems. Functional models of system components are required for capturing the available system knowledge used during various stages of system and IVHM design. MADeTM (Maintenance Aware Design environment), a COTS software tool developed by PHM Technology, was used for the health management design. A model has been built incorporating the failure diagrams of five failure modes for five different components of a UAV fuel system. Thus an inherent health management solution for the system and the optimised sensor set solution have been defined. The automatically generated sensor set solution also contains a diagnostic rule set, which was validated on the fuel rig for different operation modes taking into account the predicted fault detection/isolation and ambiguity group coefficients. It was concluded that when using functional modelling, the IVHM design and the actual system design cannot be done in isolation. The functional approach requires permanent input from the system designer and reliability engineers in order to construct a functional model that will qualitatively represent the real system. In other words, the physical insight should not be isolated from the failure phenomena and the diagnostic analysis tools should be able to adequately capture the experience bases. This approach has been verified on a laboratory bench top test rig which can simulate a range of possible fuel system faults. The rig is fully instrumented in order to allow benchmarking of various sensing solution for fault detection/isolation that were identified using functional analysis.
Health management system for the pantographs of tilting trains
Authors: Jacazio Giovanni , Sorli Massimo , Bolognese Danilo , Ferrara Davide
Published: March 2024

Tilting trains are provided with the ability of rotating their carbodies of several degrees with respect to the bogies about the longitudinal axis of the train. This permits a train to travel at a high speed while maintaining an acceptable passenger ride quality with respect to the lateral acceleration, and the consequent lateral force, received by the passengers when the train travels on a curved track at a speed in excess of the balance speed built into the curve geometry. When the carbody is tilted with respect to the bogie, the train pantograph needs to remain centered with respect to the overhead catenary, which is aligned with the track. The conventional solution is to mechanically link the pantograph to the bogie, but recent tilting trains have the pantograph connected to the carbody roof while a position servoloop continuously control the pantograph position such to keep it centered with the catenary. The merit of this design is to allow a gain of the useful volume inside the carbody. The pantograph position servoloop uses two position sensors providing a redundant position information to close the pantograph feedback loop and perform system monitoring.The monitoring functions presently implemented in pantograph position controls are able to detect the servocontrol failures, but in case of conflicting information from the two position transducers they are not always able to sort out which of the two transducer is failed because some failures of the position transducers cannot be detected by simply looking at the output signals of the transducer. As a result, if a difference between the output signals of the two position transducers is detected, the tilting function is disabled and the train speed is reduced. Also, the entire pantograph is then removed and replaced because the functionality of each individual transducer can only be checked at shop level.Developing better diagnostic techniques for the pantograph position control system have been encouraged by the train companies, but no work on this subject has so far been performed. A research activity was hence conducted by the Authors, that was aimed at developing an advanced diagnostic system that can both identify the presence of a failure and recognize which of the two position transducers is the failed one. In case of a transducer failure it is thus possible to isolate the failed transducer and keep the pantograph position control operational, thereby retaining the train tilting function. A further merit of the advanced diagnostic system is the reduction of maintenance time and costs because the failed transducer can be replaced without removing the entire pantograph from the train.The general architecture of this innovative diagnostic system, the associated algorithms, the mathematical models for the system simulation and validation, the simulation results and the possible future developments of this health management system are presented in the paper.
Unscented Kalman Filter with Gaussian Process Degradation Model for Bearing Fault Prognosis
Authors: Anger Christoph , Schrader Robert , Klingauf Uwe
Published: March 2024

The degradation of rolling-element bearings is mainly stochastic due to unforeseeable influences like short term overstraining, which hampers the prediction of the remaining useful lifetime. This stochastic behaviour is hardly describable with parametric degradation models, as it has been done in the past. Therefore, the two prognostic concepts presented and examined in this paper introduce a nonparametric approach by the application of a dynamic Gaussian Process (GP). The GP offers the opportunity to reproduce a damage course according to a set of training data and thereby also estimates the uncertainties of this approach by means of the GP’s covariance. The training data is generated by a stochastic degradation model that simulates the aforementioned highly stochastic degradation of a bearing fault. For prediction and state estimation of the feature, the trained dynamic GP is combined with the Unscented Kalman Filter (UKF) and evaluatedin the context of a case study. Since this prognostic approach has shown drawbacks during the evaluation, a multiple model approach based on GP-UKF is introduced and evaluated. It is shown that this combination offers an increased prognostic performance for bearing fault prediction.
Diagnostics Driven PHM The Balanced Solution
Authors: Lauffer Jim
Published: March 2024

Much effort has been made to develop technologies and define metrics for Prognostics Health Management (PHM). The problem is that most of this effort has focused on theoretical and high risk concepts of Prognostics performance while ignoring the real needs in “System Health Management”. In the wake of this technological attention, the importance of true Integrated Systems Health Management (ISHM) has been masked by the focus on single failure mode physics of failure solutions. The critical PHM metrics, derived from Integrated Systems Diagnostics Design (ISDD) have mostly been ignored. These critical metrics include Reliability, Safety, Testability, and System Maintainability & Sustainment, as well as the impact of prognostics performance on Systems Diagnostics. A key point to be made is that the ISDD process is much larger than just developing metrics. ISDD results in a well-designed system that meets true health management needs, as well as significantly lowering development costs, and the cost of ownership. Another point that needs to be made is that the core of ISDD is a proven and highly effective analysis solution in Model Based Diagnostics. This paper discusses the approach of using Model Based Diagnostics in the ISDD process to determine the best balance of the Health Management design. It will be shown how the impact and effectiveness of prognostics as integrated with the ISDD process provides true value to performance and cost avoidance.
Closed-loop Control System for the Reliability of Intelligent Mechatronic Systems
Authors: Meyer Tobias , Sextro Walter
Published: March 2024

So-called reliability adaptive systems are able to adapt their system behavior based on the current reliability of the system. This allows them to react to changed operating conditions orfaults within the system that change the degradation behavior. To implement such reliability adaptation, self-optimization can be used. A self-optimizing system pursues objectives, of which the priorities can be changed at runtime, in turn changing the system behavior. When including system reliability as an objective of the system, it becomes possible to change the system based on the current reliability as well. This capability can be used to control the reliability of the system throughout its operation period in order to achieve a pre-defined or user-selectable system lifetime. This way, optimal planning of maintenance intervals is possible while also using the system capabilities to their full extent. Our proposed control system makes it possible to react to changed degradation behavior by selecting objectives of the self-optimizing system and in turn changing the operating parametersin a closed loop. A two-stage controller is designed which is used to select the currently required priorities of the objectives in order to fulfill the desired usable lifetime. Investigations using a model of an automotive clutch system serve to demonstrate the feasibility of our controller. It is shown that the desired lifetime can be achieved reliably.
Evolving the Data Management Backbone: Binary OSA-CBM and Code Generation for OSA-EAI
Authors: Löhr Andreas , Buderath Matthias
Published: March 2024

Integrated system health monitoring and management (ISHM) is a field of research and development where both academia and industry is highly focused on. Airbus Defence & Space has recognized that simulation is a key capability for developing ISHM technologies and is therefore in the process of developing a comprehensive simulation framework in that area. One significant building block is to invite 1st class technology providers, e.g. Universities and SMIs, to provide innovative technologies and support their integration into the simulation framework. This paper is a joint presentation of Airbus Defence & Space and Linova Software GmbH, an Airbus Defence & Space preferred software provider. The Open System Architecture for Condition-based Maintenance (OSA-CBM) and Open System Architecture for Enterprise Application Integration (OSA-EAI) are complementary reference architectures and represent an emerging standard for application domain-independent asset and condition data management. The architectures address several challenges in building Prognostic Health Management (PHM) systems, which are commonly composed of disparate and distributed hard- and software components. Therefore, a common challenge to PHM systems is to be confronted with vast amounts of data which are exchanged over a heterogeneous collection of communication channels. Any such system’s success depends upon an open, uniform, and performance-optimized solution for data management. A solution that includes: data definition, data communication, and data storage. We will follow up on previous work and report on our experiences from implementing our second generation data management backbone based on binary OSA-CBM transmission. We also aim at implementing a fully OSA-EAI compliant database. We confirmed the general feasibility of OSA-CBM and OSA-EAI by previous work. We have now migrated our data management backbone to the current release of OSA-CBM, which includes a standard binary transportation format. We report on our experience from implementing this format and discuss issues regarding message handling and Meta data overhead. In previous work we used a simplified and stripped-down implementation of OSA-EAI and our current goal was to be fully compliant with the OSA-EAI standard. In order to reach this goal, we have created a code generator which receives OSA-EAI-provided documentation artifacts as input. It produces compileable source code for a Java-based 3-tier OSA-EAI information system. We have identified issues with the OSA-EAI standard regarding completeness and handling, which we discuss, and suggest means for mitigation or enhancements to the standard. To underline the feasibility of our solutions, we provide empirical evidence drawn from our work. The conclusion is a summary of our experience and the direction of future work in the area of PHM system design for aircraft maintenance. In total, our contribution to the community is best seen from a practitioner’s perspective.
Remaining Useful Life Estimation for Air Filters at a Nuclear Power Plant
Authors: Saarela Olli , Einar Hulsund John , Taipale Aimo , Hegle Morten
Published: March 2024

The exhaust ventilation air from nuclear power plants and other nuclear facilities is carefully filtered, as aerosols are a potential vector of contamination. Monitoring the condition of the air filters improves radiation safety. In this paper the progression of differential pressures over air filters at a nuclear research reactor have been studied. Technical properties and possible environmental influences have been checked in order to understand the variation of the pressure over time. The differential pressure has been decomposed into different components as a result of an analysis of environmental conditions. The gradually increasing component, representing gradual accumulation of aerosol particles in the filter, is modeled as a gamma process and an estimate for determining the remaining useful life of the air filters has been computed.
Prognostics for Light Water Reactor Sustainability: Empirical Methods for Heat Exchanger Prognostic Lifetime Predictions
Authors: Welz Zachary , Nam Alan , Sharp Michael , Hines J. Wesley , Upadhyaya Belle R.
Published: March 2024

As the licenses of many nuclear power plants in the US and abroad are being extended, the accurate knowledge of system and component condition is becoming more important. The US Department of Energy (DOE) has funded a project with the primary goal of developing lifecycle prognostic methods that generate accurate and continuous remaining useful life (RUL) estimates as components transition through each stage of the component lifecycle. These stages correspond to beginning of life, operations at various expected and observed stress levels, the onset of detectable degradation, and degradation towards the eventual end of life. This paper provides an overview and application of a developed lifecycle prognostic approach and applies it to a heat exchanger fouling test bed under accelerated degradation conditions. The results of applying the lifecycle prognostic algorithms to the heat exchanger fouling experiment are given, followed by a discussion of the strengths and shortcomings of the developed techniques for this application.