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M. Lo, N. Valot, F. Maraninchi, and P. Raymond, Implementing a realtime avionic application on a many-core processor, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01718139

M. Lo, N. Valot, F. Maraninchi, and P. Raymond, Real-time on-board manycore implementation of a health monitoring system: Lessons learnt, 9th European Congress Embedded Real-time Software and Systems, 2018.

, Computemodule(fftw_complex * result, int length,double * module) { 2 3 int i; 4 for (i = 0; i < length

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. *-*-m2, variance 9 * nb_samples_rev: number of vibration samples of the current monitored shaft revolution

, // counter of samples since the beginning of the acquisition session 16 17 nb_samples_start ++

*. M2= and . Nb_samples_start,

P. Bieber, F. Boniol, M. Boyer, E. Noulard, and C. Pagetti, New challenges for future avionic architectures, AerospaceLab, issue.4, p.1, 2012.
URL : https://hal.archives-ouvertes.fr/hal-01184101

. Wtilesmachinery, Corrective versus preventive maintenance: What is the difference and where is the value?, 2018.

B. Christopher, R. Watkins, and . Walter, Transitioning from federated avionics architectures to integrated modular avionics, Digital Avionics Systems Conference, 2007. DASC'07. IEEE/AIAA 26th, 2007.

J. W. Ramsey, Integrated modular avionics: Less is more, 2007.

Y. Moy, E. Ledinot, H. Delseny, V. Wiels, and B. Monate, Testing or formal verification: Do-178c alternatives and industrial experience, IEEE software, vol.30, issue.3, pp.50-57, 2013.

J. Nowotsch, M. Paulitsch, D. Bühler, H. Theiling, S. Wegener et al., Multi-core interference-sensitive wcet analysis leveraging runtime resource capacity enforcement, Real-Time Systems (ECRTS), pp.109-118, 2014.

H. Rihani, Many-Core Timing Analysis of Real-Time Systems, 2017.
URL : https://hal.archives-ouvertes.fr/tel-01875711

. Wikihow, Comment déterminer un rapport de transmission, 2018.

. Wikipedia and . Accelerometer, , vol.2, 2018.

. Bodycote, , 2018.

, Principle of gearing and types of gear boxes, 2018.

Y. Shen, T. Shan, X. Li, H. Wang, C. Sun et al., A method of health evaluation for the gear of helicopter main gearbox, Prognostics and System Health Management Conference (PHM-Chengdu), pp.1-5, 2016.

H. William, . Press, A. Saul, . Teukolsky, T. William et al., Numerical recipes in C, vol.2, 1996.

S. Lab, Rotor imbalance detection from automated 1p analysis and measurement : Real case study during a long period for different large size wtg, 2014.

L. Arebi, F. Gu, and A. Ball, Rotor misalignment detection using a wireless sensor and a shaft encoder, 2010.

A. Majidian and M. H. Saidi, Comparison of fuzzy logic and neural network in life prediction of boiler tubes, International Journal of Fatigue, vol.29, issue.3, pp.489-498, 2007.

R. Lazcano, D. Madroñal, R. Salvador, K. Desnos, M. Pelcat et al., Porting a pca-based hyperspectral image dimensionality reduction algorithm for brain cancer detection on a manycore architecture, Journal of Systems Architecture, vol.77, pp.101-111, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01622064

W. Mathworld, Floor function, vol.02, 2018.

. Wikipedia, , vol.8, p.2017

S. Ahmad, Fft spectral leakage and windowing, 2015.

V. Michael and . Cook, Flight dynamics principles: a linear systems approach to aircraft stability and control, 2012.

. Apache, Class linearinterpolator, 2016.

P. Bourke, Interpolation methods, 1999.

. Fftw, Complex one-dimensional transforms tutorial, 2018.

. Springer, , 2010.

S. Stupar, A. Simonovic, and M. Jovanovic, Measurement and analysis of vibrations on the helicopter structure in order to detect defects of operating elements, Scientific Technical Review, vol.62, issue.1, pp.58-63, 2012.

H. Donald-e-knuth, T. Saitou, S. Nagao, T. Matui, H. Matui et al., The Art of Computer Programming, Seminumerical Algorithms, vol.2, 2004.

T. Finch, Incremental calculation of weighted mean and variance, vol.4, pp.11-16, 2009.

. Wikipedia, Algorithms for calculating variance, 2018.

R. Robert and . Schaller, Moore's law: past, present and future, IEEE spectrum, vol.34, issue.6, pp.52-59, 1997.

. Wikipedia and . Moore&apos;s-law, , vol.7, 2015.

J. Fred and . Pollack, New microarchitecture challenges in the coming generations of cmos process technologies (keynote address), Proceedings of the 32nd annual ACM/IEEE international symposium on Microarchitecture, 1999.

A. Paolillo, P. Rodriguez, N. Veshchikov, J. Goossens, and B. Rodriguez, Quantifying energy consumption for practical fork-join parallelism on an embedded real-time operating system, Proceedings of the 24th International Conference on Real-Time Networks and Systems, pp.329-338, 2016.

D. Li, J. Wu, K. Li, and K. Hwang, Energy-aware scheduling on multiprocessor platforms with devices, Cloud and Green Computing (CGC), 2013 Third International Conference on, pp.26-33, 2013.

N. Sakharnykh, Tridiagonal solvers on the gpu and applications to fluid simulation, NVIDIA GPU Technology Conference, 2009.

M. France, Simuler l'évolution du climat, 2009.

, Top 500 supercomputers. top500.org, 2017.

A. Vajda, Programming many-core chips, 2011.

S. Saidi, R. Ernst, S. Uhrig, H. Theiling, and B. Dupont-de-dinechin, The shift to multicores in real-time and safety-critical systems, Proceedings of the 10th International Conference on Hardware/Software Codesign and System Synthesis, pp.220-229, 2015.

R. Das, R. Ausavarungnirun, O. Mutlu, A. Kumar, and M. Azimi, Application-to-core mapping policies to reduce memory interference in multi-core systems, Proceedings of the 21st international conference on Parallel architectures and compilation techniques, pp.455-456, 2012.

H. Rihani, M. Moy, C. Maiza, I. Robert, S. Davis et al., Response time analysis of synchronous data flow programs on a many-core processor, Proceedings of the 24th International Conference on Real-Time Networks and Systems, pp.67-76, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01406145

M. Berezecki, E. Frachtenberg, M. Paleczny, and K. Steele, Many-core key-value store, Green Computing Conference and Workshops (IGCC), 2011 International, pp.1-8, 2011.

B. Yuan, J. Dou-fan, and B. Liu, Cooperative mechanism of local memory and cache in network processors, In Applied Mechanics and Materials, vol.380, pp.1969-1972, 2013.

M. Fakhfakh, Réconcilier performance et prédictibilité sur un many-coeur en utilisant des techniques d'ordonnancement hors-ligne, vol.6, 2014.

A. Olofsson, Epiphany-v: A 1024 processor 64-bit risc system-on-chip, 2016.

A. Olofsson, T. Nordström, and Z. Ul-abdin, Kickstarting high-performance energyefficient manycore architectures with epiphany, 2014.

J. Held, ;. Guarracino, . Mr, F. Vivien, . Träff et al., Single-chip cloud computer, an IA Tera-Scale Research Processor, p.85, 2010.

J. Howard, S. Dighe, Y. Hoskote, S. Vangal, D. Finan et al., A 48-core ia-32 message-passing processor with dvfs in 45nm cmos, Solid-State Circuits Conference Digest of Technical Papers (ISSCC), pp.108-109, 2010.

L. Dagum and R. Menon, Openmp: an industry standard api for shared-memory programming, IEEE computational science and engineering, vol.5, issue.1, pp.46-55, 1998.

W. Gropp, R. Thakur, and E. Lusk, Using MPI-2: Advanced features of the message passing interface, 1999.

B. D. De-dinechin, R. Ayrignac, P. Beaucamps, P. Couvert, B. Ganne et al., A clustered manycore processor architecture for embedded and accelerated applications, High Performance Extreme Computing Conference (HPEC), pp.1-6, 2013.

D. Benoît-dupont-de-dinechin, M. Van-amstel, G. Poulhiès, and . Lager, Time-critical computing on a single-chip massively parallel processor, Design, Automation and Test in Europe Conference and Exhibition (DATE), pp.1-6, 2014.

T. Ungerer, C. Bradatsch, M. Gerdes, F. Kluge, R. Jahr et al., Bert Böddeker, et al. parmerasa-multi-core execution of parallelised hard real-time applications supporting analysability, Digital System Design (DSD), pp.363-370, 2013.

J. P. Richard-l-alena, K. I. Ossenfort, A. Laws, F. Goforth, and . Figueroa, Communications for integrated modular avionics, Aerospace Conference, pp.1-18, 2007.

J. Paul and . Prisaznuk, Arinc 653 role in integrated modular avionics (ima), IEEE/AIAA 27th Digital Avionics Systems Conference, 2008.

, Aircraft data network, part 1: Systems concepts and overview, Aeronautical Radio Inc. Arinc, vol.664, 2002.

S. Cochard, Étude des bus avioniques. Travail d'Étude et de Recherche UBO, 2002.

A. Mairaj and R. Tahir, Swap reduction: vital for choice of avionics architecture. Pakistan Aeronautical Complex, Avionics Production Factory, International Conference on Engineering and Emerging Technologies, 2014.

Q. Perret, P. Maurère, É. Noulard, C. Pagetti, P. Sainrat et al., Temporal isolation of hard real-time applications on many-core processors, 2016 IEEE RealTime and Embedded Technology and Applications Symposium (RTAS), pp.1-11, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01585055

G. Graunke and S. Thakkar, Synchronization algorithms for shared-memory multiprocessors, Programming languages for parallel processing, pp.26-35, 1995.

P. Marwedel, Embedded system design, vol.1, 2006.

R. David and . Butenhof, Programming with POSIX threads, 1997.

M. Desnoyers and M. Dagenais, Lttng: Tracing across execution layers, from the hypervisor to user-space, Linux symposium, vol.101, 2008.

T. Carle, M. Djemal, D. Potop-butucaru, R. D. Simone, and Z. Zhang, Static mapping of real-time applications onto massively parallel processor arrays, Application of Concurrency to System Design (ACSD), pp.112-121, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01095130

R. Budruk, D. Anderson, and T. Shanley, PCI express system architecture, 2004.

, Theoretical vs. actual bandwidth: Pci express and thunderbolt, vol.9, p.2013

A. Goldhammer and J. Ayer, Understanding performance of pci express systems, Xilinx WP350, 2008.

M. Vaidehi and . Nair, Multicore applications in real time systems, 2010.

M. Trishul, B. Chilimbi, J. R. Davidson, and . Larus, Cache-conscious structure definition, ACM SIGPLAN Notices, vol.34, pp.13-24, 1999.

S. Suesse, Dynamic rotor blade displacement tracking with fiber-optical sensors for a health and usage monitoring system, 18th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, p.3659, 2017.

. Wikipedia, Facteur de charge (aérodynamique, 2018.

, Avionics. Hums technology, 2012.

. Sikorsky, Sikorsky, phi, metro demo real-time hums on s-92, 2017.

, Real-time hums goes operational on phi's s-92, 2017.

, Statistics how to, 2018.

A. Elizabeth, K. Cudney, K. M. Paryani, and . Ragsdell, Applying the mahalanobistaguchi system to vehicle handling, Concurrent Engineering, vol.14, issue.4, pp.343-354, 2006.

. Wikipedia, Predictive maintenance, 2011.

, Accelix Community Accelix Community Accelix community. What is predictive main

S. Marsland, Machine learning: an algorithmic perspective, 2011.

R. Collobert, K. Kavukcuoglu, and C. Farabet, Torch7: A matlab-like environment for machine learning, BigLearn, NIPS workshop, number EPFL-CONF-192376, 2011.

K. Shvachko, H. Kuang, S. Radia, and R. Chansler, The hadoop distributed file system, Mass storage systems and technologies (MSST), 2010 IEEE 26th symposium on, pp.1-10, 2010.

M. Zaharia, R. S. Xin, P. Wendell, T. Das, M. Armbrust et al., Apache spark: a unified engine for big data processing, Communications of the ACM, vol.59, issue.11, pp.56-65, 2016.

, Airports Council International North America. Industry white paper aircraft operating and delay cost per enplanement, 2014.

, Amiral Technologies. À propos d'amiral technologies, 2018.

, Amiral technologies met l'intelligence artificielle au service de la maintenance industrielle, 2018.

D. Madroñal, R. Lazcano, R. Salvador, H. Fabelo, S. Ortega et al., Svm-based real-time hyperspectral image classifier on a manycore architecture, Journal of Systems Architecture, vol.80, pp.30-40, 2017.

A. K. Johan, J. Suykens, and . Vandewalle, Least squares support vector machine classifiers. Neural processing letters, vol.9, pp.293-300, 1999.

S. Kabwama, H. Bulters, H. Bulstrode, . Fabelo, G. M. Ortega et al., Intra-operative hyperspectral imaging for brain tumour detection and delineation: Current progress on the helicoid project, International Journal of Surgery, vol.36, p.140, 2016.

W. Sun, H. Cassé, C. Rochange, H. Rihani, and C. Ma?za, Using execution graphs to model a prefetch and write buffers and its application to the bostan mppa

A. K. Johan, T. Suykens, J. Van-gestel, B. D. Vandewalle, and . Moor, A support vector machine formulation to pca analysis and its kernel version, IEEE Transactions on neural networks, vol.14, issue.2, pp.447-450, 2003.

, Xilinx Virtex. Fpga family, p.7

T. Kitamoto, Approximate eigenvalues, eigenvectors and inverse of a matrix with polynomial entries, Japan journal of industrial and applied mathematics, vol.11, issue.1, pp.73-85, 1994.

L. Sj, An overview of bearing vibration analysis. Maintenance & asset management, vol.23, pp.32-42, 2008.

I. Agirre, J. Abella, M. Azkarate-askasua, and F. J. Cazorla, On the tailoring of cast-32a certification guidance to real cots multicore architectures, 12th IEEE International Symposium on, pp.1-8, 2017.

P. Bieber, F. Boniol, Y. Bouchebaba, J. Brunel, C. Pagetti et al., A model-based certification approach for multi/many-core embedded systems, ERTS 2018, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01700857