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Relevant bibliographies by topics / Multi-Fault

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Academic literature on the topic 'Multi-Fault'

Author: Grafiati

Published: 1 February 2025

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Journal articles on the topic "Multi-Fault"

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Levitin, Gregory, and Suprasad V. Amari. "Multi-state systems with multi-fault coverage." Reliability Engineering & System Safety 93, no. 11 (November 2008): 1730–39. http://dx.doi.org/10.1016/j.ress.2007.12.004.

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Zhang, Zhou Suo, Minghui Shen, Wenzhi Lv, and Zheng Jia He. "Multi-Fault Classifier Based on Support Vector Machine and Its Application." Key Engineering Materials 293-294 (September 2005): 483–92. http://dx.doi.org/10.4028/www.scientific.net/kem.293-294.483.

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Aiming at problem on limiting development of machinery fault intelligent diagnosis due to needing many fault data samples, this paper improves a multi-classification algorithm of support vector machine, and a multi-fault classifier based on the algorithm is constructed. Training the multi-fault classifier only needs a small quantity of fault data samples in time domain, and does not need signal preprocessing of extracting signal features. The multi-fault classifier has been applied to fault diagnosis of steam turbine generator, and the results show that it has such simple algorithm, online fault classification and excellent capability of fault classification as advantages.

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Jiménez, Laura, and C. Verde. "Multi-Fault Discrimination with Fault Model and Periodic Residual." IFAC Proceedings Volumes 45, no. 20 (January 2012): 49–54. http://dx.doi.org/10.3182/20120829-3-mx-2028.00087.

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Yan, Hehua, Jinbiao Tan, Yixiong Luo, Shiyong Wang, and Jiafu Wan. "Multi-Condition Intelligent Fault Diagnosis Based on Tree-Structured Labels and Hierarchical Multi-Granularity Diagnostic Network." Machines 12, no. 12 (December 6, 2024): 891. https://doi.org/10.3390/machines12120891.

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The aim of this study is to improve the cross-condition domain adaptability of bearing fault diagnosis models and their diagnostic performance under previously unknown conditions. Thus, this paper proposes a multi-condition adaptive bearing fault diagnosis method based on multi-granularity data annotation. A tree-structured labeling scheme is introduced to allow for multi-granularity fault annotation. A hierarchical multi-granularity diagnostic network is designed to automatically learn multi-level fault information from condition data using feature extractors of varying granularity, allowing for the extraction of shared fault information across conditions. Additionally, a multi-granularity fault loss function is developed to help the deep network learn tree-structured labels, improving intra-class compactness and reducing hierarchical similarity between classes. Two experimental cases demonstrate that the proposed method exhibits robust cross-condition domain adaptability and performs better in unseen conditions than state-of-the-art methods.

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Wen, Weigang, Jingqi Qin, Xiangru Xu, Kaifu Mi, and Meng Zhou. "A Model-Driven Approach to Extract Multi-Source Fault Features of a Screw Pump." Processes 12, no. 11 (November 17, 2024): 2571. http://dx.doi.org/10.3390/pr12112571.

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Screw pumps’ faulty working conditions affect the stability of oil production. At project sites, different sensors are used simultaneously to collect multi-dimensional signals; the data fault labels and location are not clear, and how to comprehensively use multi-source information in effective fault feature extraction has become an urgent issue. Existing diagnostic methods use a single signal or part of a signal and do not fully utilize the acquired signal, which makes it difficult to achieve the required accuracy of diagnostic results. This paper focuses on the model-driven approach to extract multi-source fault features of screw pumps. Firstly, it constructs a fault data model (FDM) by analyzing the fault mechanism of the screw pump. Secondly, it uses the FDM to select an effective data set. Thirdly, it constructs a multi-dimensional fault feature extraction model (MDFEM) to extract featured signal features and data features, for which we also comprehensively used multi-source signals in effective fault feature extraction, while other traditional methods only use one or two signals. Finally, after feature selection, unsupervised fault diagnosis was achieved by using the k-means method. After experimental verification, the method can comprehensively use multi-source information to construct an effective data set and extract multi-dimensional, effective fault features for screw pump fault diagnosis.

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Meng, Hongbing. "Soft Fault Detection Algorithms for Multi-Parallel Data Streams Under the Cloud Computing." Journal of Advanced Computational Intelligence and Intelligent Informatics 22, no. 7 (November 20, 2018): 1114–19. http://dx.doi.org/10.20965/jaciii.2018.p1114.

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In the fault detection of multi-parallel data streams, the error probability of traditional methods is large, which cannot effectively meet the soft fault detection for multi-parallel data stream, causing the problem of low detection efficiency. A soft fault detection algorithm based on adaptive multi-parallel data stream is proposed. The soft fault feature in the data stream is extracted, and the adaptive soft fault detection algorithm is used to detect the fault of the multi-parallel data stream, which can overcome the disadvantages of traditional methods, effectively improve the efficiency, safety and the accuracy. Experimental results showed that the proposed method can effectively improve the efficiency of fault detection.

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Li-jia, LIU, HU Jian-wang, and SUN Hui-xian. "Fault Diagnosis Reasoning Algorithm Based on Multi-signal Model." MATEC Web of Conferences 173 (2018): 03022. http://dx.doi.org/10.1051/matecconf/201817303022.

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The multi-signal model is modeled in the fault space and combines the structural model and the dependent model of the system. The modeling work is easy to implement in different layers and is very suitable for fault modeling and fault diagnosis of the Command and control system. After the model is established, how to meet the requirements of fault coverage and fault isolation rate, fault diagnosis reasoning algorithm is particularly important. The system dependency matrix is obtained by establishing a multi-signal model. Based on this, the fault diagnosis reasoning algorithm is studied. The fault diagnosis of Apollo spacecraft before launch is taken as an example to verify the effectiveness of fault diagnosis inference algorithm based on multi-signal model.

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Wang, Yang, Rui-Qian Sun, and Lin-Feng Gou. "Two-Stage Hyperelliptic Kalman Filter-Based Hybrid Fault Observer for Aeroengine Actuator under Multi-Source Uncertainty." Aerospace 11, no. 9 (September 8, 2024): 736. http://dx.doi.org/10.3390/aerospace11090736.

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An aeroengine faces multi-source uncertainty consisting of aeroengine epistemic uncertainty and the control system stochastic uncertainty during operation. This paper investigates actuator fault estimation under multi-source uncertainty to enhance the fault diagnosis capability of aero-engine control systems in complex environments. With the polynomial chaos expansion-based discrete stochastic model quantification, the optimal filter under multi-source uncertainty, the Hyperelliptic Kalman Filter, is proposed. Meanwhile, by treating actuator fault as unknown input, the Two-stage Hyperelliptic Kalman Filter (TSHeKF) is also proposed to achieve optimal fault estimation under multi-source uncertainty. However, considering that the biases of the model are often fixed for the individual, the TSHeKF-based fault estimation is robust and leads to inevitable conservativeness. By adding the additional estimation of the unknown deviation in state function caused by probabilistic system parameters, the hybrid fault observer (HFO) is proposed based on the TSHeKF and realizes conservativeness-reduced estimation for actuator fault under multi-source uncertainty. Numerical simulations show the effectiveness and optimality of the proposed HFO in state estimation, output prediction, and fault estimation for both single and multi-fault modes, when considering multi-source uncertainty. Furthermore, Monte Carlo experiments have demonstrated that the HFO-based optimal fault estimation is less conservative and more accurate than the Two-stage Kalman Filter and TSHeKF, providing better safety and more reliable aeroengine operation assurance.

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Yan, Wen, Haiyan Tu, Peng Qin, and Tao Zhao. "Interval Type-II Fuzzy Fault-Tolerant Control for Constrained Uncertain 2-DOF Robotic Multi-Agent Systems with Active Fault Detection." Sensors 23, no. 10 (May 17, 2023): 4836. http://dx.doi.org/10.3390/s23104836.

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This study proposed a novel adaptive interval Type-II fuzzy fault-tolerant control for constrained uncertain 2-DOF robotic multi-agent systems with an active fault-detection algorithm. This control method can realize the predefined-accuracy stability of multi-agent systems under input saturation constraint, complex actuator failure and high-order uncertainties. Firstly, a novel active fault-detection algorithm based on pulse-wave function was proposed to detect the failure time of multi-agent systems. To the best of our knowledge, this was the first time that an active fault-detection strategy had been used in multi-agent systems. Then, a switching strategy based on active fault detection was presented to design the active fault-tolerant control algorithm of the multi-agent system. In the end, based on the interval type-II fuzzy approximated system, a novel adaptive fuzzy fault-tolerant controller was proposed for multi-agent systems to deal with system uncertainties and redundant control inputs. Compared with other relevant fault-detection and fault-tolerant control methods, the proposed method can achieve predefinition of stable accuracy with smoother control input. The theoretical result was verified by simulation.

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Wang, Dazhi, Yi Ning, and Cuiling Zhang. "An Effective Ground Fault Location Scheme Using Unsynchronized Data for Multi-Terminal Lines." Energies 11, no. 11 (October 30, 2018): 2957. http://dx.doi.org/10.3390/en11112957.

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Traveling-wave-based methods perform poorly for the fault location of multi-terminal lines as a result of the limitation introduced by being a highly branched structure. The requirement for multi-terminal time synchronization is also a drawback and needs to be improved. In this paper, an effective fault location method for use on multi-terminal lines is proposed, and it does not require the data from each terminal to be synchronized. The method is based on the arrival time differences in the ground and aerial mode waves detected at each terminal. First, fault section identification rules for a three-terminal line are proposed. Then, a multi-terminal topological structure in this paper will be deemed as one consisting of multiple three-terminal lines. Thus, a whole scheme to identify any fault section in a multi-terminal line is presented. Consequently, the fault distance is calculated using the fault distance ratios in the corresponding fault section. The advantage of the proposed scheme is that complete coverage of multi-terminal lines fault location can still be achieved once some synchronized devices are out of operation. To evaluate the performance of the proposed method, many fault cases under different conditions are implemented. The simulation results show that the proposed method can identify the fault section correctly and locate the fault more accurately and reliably than existing methods.

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Dissertations / Theses on the topic "Multi-Fault"

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Black, Natanya Maureen. "Fault length, multi-fault rupture, and earthquakes in California." Diss., Restricted to subscribing institutions, 2008. http://proquest.umi.com/pqdweb?did=1581647191&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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Navarro, Martin. "Fault roughness and fault complexity field study, multi-scale analysis and numerical fault model /." [S.l.] : [s.n.], 2002. http://deposit.ddb.de/cgi-bin/dokserv?idn=966415809.

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Roman, Felipe de Fraga. "Fault supervision for multi robotics systems." Pontifícia Universidade Católica do Rio Grande do Sul, 2015. http://hdl.handle.net/10923/7732.

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Made available in DSpace on 2015-12-09T01:03:58Z (GMT). No. of bitstreams: 1 000476572-Texto+Completo-0.pdf: 1895232 bytes, checksum: d360d64653c8369496f6a15db1b7c15f (MD5) Previous issue date: 2015
As robotics becomes more common and people start to use it in routine tasks, dependability becomes more and more relevant to create trustworthy solutions. A commonly used approach to provide reliability and availability is the use of multi robots instead of a single robot. However, in case of a large teams of robots (tens or more), determining the system status can be a challenge. This work presents a runtime monitoring solution for Multi Robotic Systems. It integrates Nagios IT Monitoring tool and ROS robotic middleware. One of the potential advantages of this approach is that the use of a consolidated IT infrastructure tool enables the reuse of several relevant features developed to monitor large datacenters. Another important advantage of that this solution does not require additional software at the robot side. The experimental results demonstrate that the proposed monitoring system has a small performance impact on the robot and the monitoring server can easily support hundreds or even thousands of monitored robots.
À medida que a robótica se torna mais comum e as pessoas começam a utilizá-la em suas tarefas de rotina, dependabilidade torna-se cada vez mais importante para a construção de uma solução digna de confiança. Uma abordagem comum de prover confiabilidade e disponibilidade é o uso de multi robôs ao invés de um único robô devido a sua redundância intrísica. Entretanto, no caso de um grande time de robôs (dezenas ou mais), uma tarefa aparentemente simples como a determinação do status do sistema pode se tornar um desafio. Este trabalho apresenta uma ferramenta de monitoramento de sistemas multi robôs em tempo de execução. Esta solução integra a ferramenta de monitoramento de TI Nagios com o middleware robótico ROS sem a necessidade de instalação de software adicional no robô. O uso de uma ferramenta de TI consolidada permite o reuso de diversas funcionalidades relevantes já empregadas amplamente no monitoramento de datacenters. Os resultados experimentais demonstram que a solução proposta tem um baixo impacto no desempenho do robô e o servidor de monitoramento pode facilmente monitorar centenas ou até milhares de robôs ao mesmo tempo.

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Covella, Vito Vincenzo. "Multi-node Fault Classification using Machine Learning." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/22867/.

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An HPC system, a system with much more computational power than general computing systems, is a complex system made up of different sections and many computing nodes. In such systems failures can arise for different reasons: because of the interactions among the components, because of the specific technologies used or because of bugs in the software. In order to reach Exascale performances and guarantee availability and reliability it is important to detect and recover from these anomalies. In this thesis we propose a fault classification method based on machine learning. Other researchers have worked in this field, but their work mainly relies on per-node models. However per-node models are impractical because they require too much data and fault injection would be hard to control. For this reason our research involves single multi-node models, since for single general models there’s less operational effort for training and mantaining the model over time is easier. More specifically our methodology is focused not only on metaparameter exploration, but also on understanding how many nodes are necessary for training and which specific nodes are the best candidates. For these reasons, we compare two approaches: incremental training with nodes selected randomly and incremental training with nodes which are representative of a chosen number of clusters. In both cases the end result is a single general model that can be used on different nodes for fault detection. Using the dataset provided by LRZ, about 32 compute nodes, we show that the classification performances stabilize when using a small subset of compute nodes as training set and both the previously discussed selection methods outperform node-specific classifiers when using more than one training node. Finally we show that the clustering approach is more reliable and stable when using more training nodes, while the random approach gives better performances when using a lower number of training nodes.

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Herdeiro, Teixeira André. "Multi-Agent Systems with Fault and Security Constraints." Thesis, KTH, Reglerteknik, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-106224.

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Over the last few years, a change in one of the classical paradigms in Control Systems has been happening. Partially due to the increase of the computational power, there exists now the possibility of having intelligent sensors and actuators which may take actions in a distributed fashion. This way, there is no longer the need for a centralized controller or data fusion station, which is really well suited for Networked Control Systems. This led the way to the development of distributed control and sensor fusion frameworks and there is still a a great amount of research to be done in this field. Since there is no longer a central station containing all the information but instead there are several distinct agents controlling or monitoring the system, communication between these agents is now necessary. Thus one important aspect in these kind of systems is security, regarding not only the communications between agents but also a possible malfunction of one or several agents. The scope of this thesis is to study methods to detect possible misbehaviors and security breaches in the communications between agents from a control theoretical perspective. In this sense, a specific kind of distributed controller - the consensus problem - will be analyzed under the effect of faults and communication attacks. A Fault Detection and Isolation method will be used in order to detect these events using only the local information available. An example regarding power systems will also be given, where a decentralized state estimator is used in order to detect faults within an area, requiring only local information.

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Kamiel, Berli Paripurna. "Vibration-based multi-fault diagnosis for centrifugal pumps." Thesis, Curtin University, 2015. http://hdl.handle.net/20.500.11937/1532.

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The thesis proposes a new method for vibration fault diagnosis of centrifugal pumps by combining statistical features, Symlet Wavelet transform, Principal Component Analysis and k-Nearest Neighbors. Six statistical features were extracted from the low frequency part of wavelet decomposition which was then used as input features for the PCA model. The fault detection utilised T2 and Q statistics while fault classification and identification were carried out using score matrices and k-Nearest Neighbors respectively.

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Abdelaal, Ahmed Abdelmalek Abdelhafez. "Active rectifier control for multi-phase fault-tolerant generators." Thesis, University of Manchester, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.489542.

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This research is concerned with the solid-state power conversion system that interfaces a multi-phase, fault-tolerant, permanent magnet generator to a high voltage DC bus. The generator is being developed for future aerospace application, it has five independent phases, a 3:1 speed range and a one per-unit output impedance.

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Ozcerit, Ahmet Turan. "Fault-tolerant embedded multi-processing system with bus switching." Thesis, University of Sussex, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.285122.

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Chaitanya, Deshpande. "Multi-Agent Based Fault Localizationand Isolation in Active DistributionNetworks." Thesis, KTH, Industriella informations- och styrsystem, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-169221.

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Liberalized electricity markets, increased awareness of clean energy resources and theirdecreasing costs have resulted in large numbers of distributed power generators beinginstalled on distribution network. Installation of distributed generation has altered thepassive nature of distribution grid. A concept of Active Distribution Network is proposedwhich will enable present day infrastructure to host renewable energy resources reliably.Fault management that includes fault localization, isolation and service restoration ispart of active management of distribution networks.This thesis aims to introduce a distributed protection methodology for fault localizationand isolation. The objective is to enhance reliability of the network. Faults are identifiedbased on root mean square values of current measurements and by comparing thesevalues with preset thresholds. The method based on multi-agent concept can be usedto locate the faulty section of a distribution network and for selection of faulty phases.The nodal Bus Agent controls breakers that are associated with it. Based on indicationof fault, adjacent bus Agents communicate with each other to identify location of fault.A trip signal is then issued to corresponding Breakers in adjacent Bus Agents, isolatingthe faulty section of line. A case study was carried out to verify suitability of the proposedmethod. A meshed network model and multi-agent based protection scheme wassimulated in Simulink SimPowerSystems. Considering nature of Distribution Network,separate breakers for each phase are considered. The distribution network protectionsystem identified fault introduced in the network correctly along with interrupting thefault current.Keywords

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Miller, Dawn Elizabeth. "Underground cable fault location using multi-element gas sensing." Thesis, University of Manchester, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.681492.

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Books on the topic "Multi-Fault"

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Potiron, Katia, Amal El Fallah Seghrouchni, and Patrick Taillibert. From Fault Classification to Fault Tolerance for Multi-Agent Systems. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5046-6.

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Potiron, Katia. From Fault Classification to Fault Tolerance for Multi-Agent Systems. London: Springer London, 2013.

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Meskin, Nader. Fault Detection and Isolation: Multi-Vehicle Unmanned Systems. New York, NY: Springer Science+Business Media, LLC, 2011.

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Gupta, Punit, and Pradeep Kumar Gupta. Trust & Fault in Multi Layered Cloud Computing Architecture. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-37319-1.

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He, Shuping, and Xiaoli Luan. Multi-model Jumping Systems: Robust Filtering and Fault Detection. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6474-5.

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United States. Army Aviation Research and Technology Activity. and United States. National Aeronautics and Space Administration., eds. Fault detection of helicopter gearboxes using the multi-valued influence matrix method. [Washington, DC]: National Aeronautics and Space Administration, 1993.

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Pakanen, Jouko. Prediction and fault detection of building energy consumption using multi-input, single-output dynamic model. Espoo: Technical Research Centre of Finland, 1992.

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1935-, Lasker G. E., International Institute for Advanced Studies in Systems Research and Cybernetics., and International Conference on Systems Research, Informatics and Cybernetics (13th : 2001 : Baden-Baden, Germany), eds. Advances in database and expert systems: Data mining and data warehousing techniques, similarity search for reusable database components, performance assessment of learning algorithms, estimation of models for expert systems, complexity evaluation of software processes, multi-agent systems, multi-agent approach to coalition formation, communication between software agents in distributed information systems, expert systems for fault diagnosis, parameter modulated fractals generators, information management in Intranet and Extranet environments. Windsor, Ont: International Institute for Advanced Studies in Systems Research and Cybernetics, 2001.

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Chopin, Kate. Complete novels and stories: At Fault / Bayou Folk / A Night in Acadie / The Awakening / Uncollected Stories. New York: Library of America, 2002.

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Meskin, Nader, and Khashayar Khorasani. Fault Detection and Isolation: Multi-Vehicle Unmanned Systems. Springer, 2011.

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Book chapters on the topic "Multi-Fault"

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Potiron, Katia, Amal El Fallah Seghrouchni, and Patrick Taillibert. "Multi-Agent System Properties." In From Fault Classification to Fault Tolerance for Multi-Agent Systems, 5–10. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5046-6_2.

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Potiron, Katia, Amal El Fallah Seghrouchni, and Patrick Taillibert. "Fault Classification." In From Fault Classification to Fault Tolerance for Multi-Agent Systems, 11–19. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5046-6_3.

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Potiron, Katia, Amal El Fallah Seghrouchni, and Patrick Taillibert. "Fault Classification Attributes as an Ontology to Build Fault Tolerant MAS." In From Fault Classification to Fault Tolerance for Multi-Agent Systems, 59–74. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5046-6_6.

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Potiron, Katia, Amal El Fallah Seghrouchni, and Patrick Taillibert. "Introduction." In From Fault Classification to Fault Tolerance for Multi-Agent Systems, 1–3. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5046-6_1.

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Potiron, Katia, Amal El Fallah Seghrouchni, and Patrick Taillibert. "Refinement of the Fault Classification for MAS." In From Fault Classification to Fault Tolerance for Multi-Agent Systems, 21–35. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5046-6_4.

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Potiron, Katia, Amal El Fallah Seghrouchni, and Patrick Taillibert. "Fault Tolerance for MAS Specific Faults." In From Fault Classification to Fault Tolerance for Multi-Agent Systems, 37–57. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5046-6_5.

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Potiron, Katia, Amal El Fallah Seghrouchni, and Patrick Taillibert. "Conclusion." In From Fault Classification to Fault Tolerance for Multi-Agent Systems, 75–80. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5046-6_7.

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Campana, Tiziana, and Gregory M. P. O’Hare. "Intellectus: Multi-Hop Fault Detection Methodology." In Smart Sensors, Measurement and Instrumentation, 171–90. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-12898-6_9.

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Zhang, Jiantao, Zhan Gao, Jianyu Lan, Fuze Cheng, Wenbo Zhao, and Chunbo Zhu. "Fault-Tolerant Multi-coil WPT System." In Lecture Notes in Electrical Engineering, 539–46. Singapore: Springer Nature Singapore, 2024. https://doi.org/10.1007/978-981-97-8816-3_56.

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Zhu, Huafei. "Distributed Multi-user, Multi-key Searchable Encryptions Resilient Fault Tolerance." In Trusted Systems, 17–31. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31550-8_2.

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Conference papers on the topic "Multi-Fault"

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Zhang, Pu, Huifeng Xue, and Shan Gao. "Fault-tolerant Control for Multi-agent with Actuator Fault." In 2020 39th Chinese Control Conference (CCC). IEEE, 2020. http://dx.doi.org/10.23919/ccc50068.2020.9188757.

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Xu, Sihan, Ya Gao, Xiangrui Cai, Zhiyu Wang, and Hua Ji. "Effective Multi-Fault Localization Based on Fault-Relevant Statistics." In 2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC). IEEE, 2021. http://dx.doi.org/10.1109/compsac51774.2021.00135.

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Jiang, Hao, Xinyu Ren, and Xiaojian Fang. "Aeroengine Multi-Fault Diagnosis Based on Hierarchical Multi-mode Filtering." In GPPS Xi'an21. GPPS, 2022. http://dx.doi.org/10.33737/gpps21-tc-136.

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Carry out model-based online fault diagnosis for aero-engine sensors, actuators and components. Traditional methods use a set of filters to estimate the current state of the engine, and then process the estimated residuals of each filter to obtain the diagnosis result. For single engine faults, this method has a good diagnostic effect, but when double engine faults are considered, the amount of calculation will greatly increase, and the accuracy and real-time performance of fault diagnosis cannot meet the requirements. In this regard, this paper proposes a fault diagnosis algorithm based on hierarchical multi-mode filtering, which combines the advantages of hybrid Kalman filtering and multi-mode adaptive filtering algorithms, and uses a hierarchical diagnosis architecture for fault diagnosis. First, establish a hybrid Kalman filter bank of sensors, actuators and components, and then layer them. The first layer diagnoses the normal state of the engine and single fault conditions, and the second layer diagnoses the double fault conditions on the basis of the first layer fault diagnosis, and finally outputs the diagnosis results comprehensively. This method can meet the real-time and accuracy requirements for single and double fault diagnosis of the engine.

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Yongwei, Lv, Tian Muqin, and Wang Xiaoling. "Multi-fault Diagnosis Information Fusion." In 2009 International Conference on New Trends in Information and Service Science (NISS). IEEE, 2009. http://dx.doi.org/10.1109/niss.2009.38.

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Su, Lili, and Nitin H. Vaidya. "Fault-Tolerant Multi-Agent Optimization." In PODC '16: ACM Symposium on Principles of Distributed Computing. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2933057.2933105.

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Momose, Atsuki, and Ling Ren. "Multi-Threshold Byzantine Fault Tolerance." In CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3460120.3484554.

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Tsai, Posheng, Kamal Mannar, and Darek Ceglarek. "Fault Localization Analysis for Multiple Fault Diagnosis in Multi-Station Assembly Systems." In ASME 2007 International Manufacturing Science and Engineering Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/msec2007-31139.

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Modern large scale multi-station manufacturing systems require effective variation reduction to improve the final assembly dimensional quality. One critical measure is to diagnose the fault in the process using knowledge-based root cause identification, which can be very challenging due to the complexity of the system. The paper investigates the need of data-driven fault localization to enhance the diagnosability within the context of multiple-fault scenario(s) in multi-station assembly processes where multivariate measurements are used. The paper proposes three types of fault-signal transmission in assembly system and illustrates the nature of structured noise. Moreover, the impact of structured noise on the diagnosability is illustrated on two major fault isolation methods, namely, Principal Component Analysis and Independent Component Analysis. We then propose to use data-driven fault localization to reduce the structured noise effect and enhance the diagnosability. A simulation case study based on automotive panel assembly model is provided to illustrate the impact of structured noise and the need for data-driven localization.

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Desineni, R., T. J. Vogels, K. N. Dwarakanath, T. Zanon, R. D. Blanton, and W. Maly. "A Multi-Stage Approach to Fault Identification Using Fault Tuples." In ISTFA 2003. ASM International, 2003. http://dx.doi.org/10.31399/asm.cp.istfa2003p0496.

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Abstract We present a generalized method to attack fault diagnosis at the logic level that aims at localizing and differentiating fault types. In particular, we present an application of this method that aids in distinguishing opens and two-line shorts. While past work has addressed distinction between shorts and opens, we present an algorithm to generate more test patterns to narrow down the diagnosis callout based on type or location. In general, we are not limited to a few fault models as our description of the logic misbehavior is built on fault tuples. This becomes important in the area of fault and defect characterization. Results based on logic validation and SPICE simulations of extracted netlists indicate the usefulness and efficiency of our approach.

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Subbarao, Kamesh, and Arun Vemuri. "Fault Isolation Using Extrinsic Curvature For Multi-Input-Multi-Output Systems With Nonlinear Fault Models." In 2007 American Control Conference. IEEE, 2007. http://dx.doi.org/10.1109/acc.2007.4282918.

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Cao, Yunpeng, Yinghui He, Fang Yu, Jianwei Du, Shuying Li, Qingcai Yang, and Rui Liu. "A Two-Layer Multi-Model Gas Path Fault Diagnosis Method." In ASME Turbo Expo 2018: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/gt2018-75368.

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This paper presents a two-layer multi-model gas path fault diagnosis method for gas turbines that includes a fault detection layer and a fault isolation layer. A health model and a gas path fault model based on a back propagation neural network are used for the real-time estimation of the output parameters of a gas turbine in the fault detection layer and the output parameter residual in the fault isolation layer, respectively. A fault detection algorithm is proposed based on fuzzy inference, and the fuzzy membership function of the output parameters residual is realized using data statistics. A similarity distance method is used to realize fault isolation, and a fault probability algorithm based on the Mahalanobis distance is presented. Finally, the proposed method is verified by a three-shaft gas turbine simulation platform, and the simulation test results show that the two-layer multi-model gas path fault diagnosis method can detect and isolate the gas path fault accurately with a low calculation cost and good extensibility.

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Reports on the topic "Multi-Fault"

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Parker, L. E. ALLIANCE: An architecture for fault tolerant multi-robot cooperation. Office of Scientific and Technical Information (OSTI), February 1995. http://dx.doi.org/10.2172/34318.

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Scheidhauer, M., A. M. Trehu, and K. M. M. Rohr. Multi-channel seismic reflection survey over the northern Queen Charlotte fault. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1999. http://dx.doi.org/10.4095/210903.

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Parr, G. More fault tolerant approach to address resolution for a Multi-LAN system of Ethernets. RFC Editor, May 1988. http://dx.doi.org/10.17487/rfc1029.

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Ropp, Michael, and Ujjwol Tamrakar. Impact of synchronous condensers on fault location and black start in multi-inverter isolated microgrids. Office of Scientific and Technical Information (OSTI), September 2024. http://dx.doi.org/10.2172/2462928.

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Pitarka, Arben. Multi Segment Fault Rupture Modeling and Strong Ground Motion Simulation Using Irikura, Japan Recipe: Implementation in the in SCEC BB Platform. Office of Scientific and Technical Information (OSTI), April 2019. http://dx.doi.org/10.2172/1544495.

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Wozniakowska, P., D. W. Eaton, C. Deblonde, A. Mort, and O. H. Ardakani. Identification of regional structural corridors in the Montney play using trend surface analysis combined with geophysical imaging. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/329795.

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Induced (anthropogenic) earthquakes are caused by reactivation of pre-existing faults due to human activities, including hydraulic fracturing and saltwater disposal. The Montney play, the pre-eminent shale gas play in Canada, contains localized regions with relatively high geological susceptibility to induced seismicity. Identification of potential seismogenic structures is hindered because published fault maps in the Montney play are often focused on small areas, leading to inconsistencies when these are compiled across the region. We have developed a regional framework based on structural corridors: complex, multi-strand faults systems. A three-step structural interpretation workflow was used, including seismic and structural interpretation along with trend surface analysis (TSA). This approach was used to identify 34 structural corridors in NE BC and NW Alberta.

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Hults, Chad, Jeffrey Coe, and Nikita Avdievitch. Fractures, scarps, faults, and landslides mapped using LiDAR, Glacier Bay National Park and Preserve, Alaska. National Park Service, 2023. http://dx.doi.org/10.36967/2300706.

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This map of fractures, scarps, faults, and landslides was completed to identify areas in Glacier Bay National Park and Preserve that may present a landslide-generated tsunami hazard. To address the potential of landslide and tsunami hazards in the park, the National Park Service (NPS) and the US Geological Survey (USGS) partnered to conduct a multi-year hazard assessment of Glacier Bay National Park and Preserve. To produce the map described in this report, we used the newly acquired (2019-2020) light detection and ranging (LiDAR) 0.5 to 1.0 m digital elevation models (DEMs) that cover all the coastal areas of the park and extend up to the ridgetops in places with steep slopes. A bare earth DEM was used to identify and map areas of incipient landslides (i.e., fractures and scarps), fault scarps, and areas where landslides have clearly occurred in the past (i.e., areas where scars and deposits are clearly visible). This map provides a baseline data set that can be used to aid forecasts of where landslides are most likely to occur in the future.

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Goeckeritz, Joel, Nathan Schank, Ryan L Wood, Beverly L Roeder, and Alonzo D Cook. Use of Urinary Bladder Matrix Conduits in a Rat Model of Sciatic Nerve Regeneration after Nerve Transection Injury. Science Repository, December 2022. http://dx.doi.org/10.31487/j.rgm.2022.03.01.

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Previous research has demonstrated the use of single-channel porcine-derived urinary bladder matrix (UBM) conduits in segmental-loss, peripheral nerve repairs as comparable to criterion-standard nerve autografts. This study aimed to replicate and expand upon this research with additional novel UBM conduits and coupled therapies. Fifty-four Wistar Albino rats were divided into 6 groups, and each underwent a surgical neurectomy to remove a 7-millimeter section of the sciatic nerve. Bridging of this nerve gap and treatment for each group was as follows: i) reverse autograft—the segmented nerve was reversed 180 degrees and used to reconnect the proximal and distal nerve stumps; ii) the nerve gap was bridged via a silicone conduit; iii) a single-channel UBM conduit; iv) a multi-channel UBM conduit; v) a single-channel UBM conduit identical to group 3 coupled with fortnightly transcutaneous electrical nerve stimulation (TENS); vi) or, a multi-channel UBM conduit identical to group 4 coupled with fortnightly TENS. The extent of nerve recovery was assessed by behavioural parameters: foot fault asymmetry scoring measured weekly for six weeks; electrophysiological parameters: compound muscle action potential (CMAP) amplitudes, measured at weeks 0 and 6; and morphological parameters: total fascicle areas, myelinated fiber counts, fiber densities, and fiber sizes measured at week 6. All the above parameters demonstrated recovery of the test groups (3-6) as being either comparable or less than that of reverse autograft, but none were shown to outperform reverse autograft. As such, UBM conduits may yet prove to be an effective treatment to repair relatively short segmental peripheral nerve injuries, but further research is required to demonstrate greater efficacy over nerve autografts.

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Goeckeritz, Joel, Nathan Schank, Ryan L Wood, Beverly L Roeder, and Alonzo D Cook. Use of Urinary Bladder Matrix Conduits in a Rat Model of Sciatic Nerve Regeneration after Nerve Transection Injury. Science Repository, December 2022. http://dx.doi.org/10.31487/j.rgm.2022.03.01.sup.

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Previous research has demonstrated the use of single-channel porcine-derived urinary bladder matrix (UBM) conduits in segmental-loss, peripheral nerve repairs as comparable to criterion-standard nerve autografts. This study aimed to replicate and expand upon this research with additional novel UBM conduits and coupled therapies. Fifty-four Wistar Albino rats were divided into 6 groups, and each underwent a surgical neurectomy to remove a 7-millimeter section of the sciatic nerve. Bridging of this nerve gap and treatment for each group was as follows: i) reverse autograft—the segmented nerve was reversed 180 degrees and used to reconnect the proximal and distal nerve stumps; ii) the nerve gap was bridged via a silicone conduit; iii) a single-channel UBM conduit; iv) a multi-channel UBM conduit; v) a single-channel UBM conduit identical to group 3 coupled with fortnightly transcutaneous electrical nerve stimulation (TENS); vi) or, a multi-channel UBM conduit identical to group 4 coupled with fortnightly TENS. The extent of nerve recovery was assessed by behavioural parameters: foot fault asymmetry scoring measured weekly for six weeks; electrophysiological parameters: compound muscle action potential (CMAP) amplitudes, measured at weeks 0 and 6; and morphological parameters: total fascicle areas, myelinated fiber counts, fiber densities, and fiber sizes measured at week 6. All the above parameters demonstrated recovery of the test groups (3-6) as being either comparable or less than that of reverse autograft, but none were shown to outperform reverse autograft. As such, UBM conduits may yet prove to be an effective treatment to repair relatively short segmental peripheral nerve injuries, but further research is required to demonstrate greater efficacy over nerve autografts.

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Seginer, Ido, Louis D. Albright, and Robert W. Langhans. On-line Fault Detection and Diagnosis for Greenhouse Environmental Control. United States Department of Agriculture, February 2001. http://dx.doi.org/10.32747/2001.7575271.bard.

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Background Early detection and identification of faulty greenhouse operation is essential, if losses are to be minimized by taking immediate corrective actions. Automatic detection and identification would also free the greenhouse manager to tend to his other business. Original objectives The general objective was to develop a method, or methods, for the detection, identification and accommodation of faults in the greenhouse. More specific objectives were as follows: 1. Develop accurate systems models, which will enable the detection of small deviations from normal behavior (of sensors, control, structure and crop). 2. Using these models, develop algorithms for an early detection of deviations from the normal. 3. Develop identifying procedures for the most important faults. 4. Develop accommodation procedures while awaiting a repair. The Technion team focused on the shoot environment and the Cornell University team focused on the root environment. Achievements Models: Accurate models were developed for both shoot and root environment in the greenhouse, utilizing neural networks, sometimes combined with robust physical models (hybrid models). Suitable adaptation methods were also successfully developed. The accuracy was sufficient to allow detection of frequently occurring sensor and equipment faults from common measurements. A large data base, covering a wide range of weather conditions, is required for best results. This data base can be created from in-situ routine measurements. Detection and isolation: A robust detection and isolation (formerly referred to as 'identification') method has been developed, which is capable of separating the effect of faults from model inaccuracies and disturbance effects. Sensor and equipment faults: Good detection capabilities have been demonstrated for sensor and equipment failures in both the shoot and root environment. Water stress detection: An excitation method of the shoot environment has been developed, which successfully detected water stress, as soon as the transpiration rate dropped from its normal level. Due to unavailability of suitable monitoring equipment for the root environment, crop faults could not be detected from measurements in the root zone. Dust: The effect of screen clogging by dust has been quantified. Implications Sensor and equipment fault detection and isolation is at a stage where it could be introduced into well equipped and maintained commercial greenhouses on a trial basis. Detection of crop problems requires further work. Dr. Peleg was primarily responsible for developing and implementing the innovative data analysis tools. The cooperation was particularly enhanced by Dr. Peleg's three summer sabbaticals at the ARS, Northem Plains Agricultural Research Laboratory, in Sidney, Montana. Switching from multi-band to hyperspectral remote sensing technology during the last 2 years of the project was advantageous by expanding the scope of detected plant growth attributes e.g. Yield, Leaf Nitrate, Biomass and Sugar Content of sugar beets. However, it disrupted the continuity of the project which was originally planned on a 2 year crop rotation cycle of sugar beets and multiple crops (com and wheat), as commonly planted in eastern Montana. Consequently, at the end of the second year we submitted a continuation BARD proposal which was turned down for funding. This severely hampered our ability to validate our findings as originally planned in a 4-year crop rotation cycle. Thankfully, BARD consented to our request for a one year extension of the project without additional funding. This enabled us to develop most of the methodology for implementing and running the hyperspectral remote sensing system and develop the new analytical tools for solving the non-repeatability problem and analyzing the huge hyperspectral image cube datasets. However, without validation of these tools over a ful14-year crop rotation cycle this project shall remain essentially unfinished. Should the findings of this report prompt the BARD management to encourage us to resubmit our continuation research proposal, we shall be happy to do so.

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