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Relevant bibliographies by topics / Modal parameter identification

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Academic literature on the topic 'Modal parameter identification'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 July 2025

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Journal articles on the topic "Modal parameter identification"

1

Ren, Wei-Xin, and Wei-Hua Hu. "Cable Modal Parameter Identification. II: Modal Tests." Journal of Engineering Mechanics 135, no. 1 (2009): 51–61. http://dx.doi.org/10.1061/(asce)0733-9399(2009)135:1(51).

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He, Can, Jian Chun Xing, and Xun Zhang. "A New Method for Modal Parameter Identification Based on Natural Excitation Technique and ARMA Model in Ambient Excitation." Advanced Materials Research 1065-1069 (December 2014): 1016–19. http://dx.doi.org/10.4028/www.scientific.net/amr.1065-1069.1016.

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Due to the interference of strong vibration signal, a big error exists in modal parameter identification based on traditional ARMA model. In order to solve this problem, a new method for modal parameter identification based on natural excitation technique (NExT) and ARMA model is presented. Firstly, NExT is used to obtain cross-correlation function of different response sequences. Then, ARMA model of cross-correlation function is established, and the parameters of ARMA model are estimated by least squares method. Finally, the modal parameter identification is achieved using the relationship be

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Mickleborough, N. C., and Y. L. Pi. "Modal parameter identification usingZ-transforms." International Journal for Numerical Methods in Engineering 28, no. 10 (1989): 2307–21. http://dx.doi.org/10.1002/nme.1620281008.

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Pei, Qiang, and Long Li. "Structural Modal Parameter Identification Based on ARMA Model." Applied Mechanics and Materials 477-478 (December 2013): 736–39. http://dx.doi.org/10.4028/www.scientific.net/amm.477-478.736.

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Structural parameter identification is a significant technology to show certain characteristics and material damage of earthquake resistant structures or building materials in structural engineering and seismic engineering field. ARMA time-series method is belonged to time-domain method. ARMA time-series method for estimating the modal parameters of structure is presented in this paper. In order to verify the accuracy of the method, analytical simulation studies are performed for a frame structure model on the basis of simulated data under white-noise excitation conditions. And the results are

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Zhou, Yulin, Xulei Jiang, Mingjin Zhang, Jinxiang Zhang, Hao Sun, and Xin Li. "Modal parameters identification of bridge by improved stochastic subspace identification method with Grubbs criterion." Measurement and Control 54, no. 3-4 (2021): 457–64. http://dx.doi.org/10.1177/0020294021993831.

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In the wind tunnel test of a long-span bridge model, to ensure that the dynamic characteristics of the model can satisfy the test design requirements, it is particularly important to accurately identify the modal parameters of the model. First, the stochastic subspace identification algorithm was used to analyze the modal parameters of the model in the wind tunnel test; then, Grubbs criterion was introduced to effectively eliminate outliers in the damping ratio matrix. Stochastic subspace identification algorithm with Grubbs criterion improved the accuracy of the modal parameter identification

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Solbeck, Jason A., and Laura R. Ray. "Damage Identification Using Sensitivity-Enhancing Control and Identified Models." Journal of Vibration and Acoustics 128, no. 2 (2005): 210–20. http://dx.doi.org/10.1115/1.2159037.

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This paper investigates a coherence approach for locating structural damage using modal frequencies and transfer function parameters identified from input-output data using Observer/Kalman filter identification (OKID). Autonomous damage identification using such forward methods generally require (i) a structural model by which to relate measured and predicted modal properties induced by damage, and (ii) good sensitivity of modal parameter changes to damage states. Using the coherence approach, a damage parameter vector comprised of a finite set of modal frequencies and transfer function parame

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Liu, Xiaoteng, Zirui Dong, Hongxia Ji, Zhenjiang Yue, and Jie Kang. "Uncertainty-Based Fusion Method for Structural Modal Parameter Identification." Sensors 25, no. 14 (2025): 4397. https://doi.org/10.3390/s25144397.

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The structural modal parameter identification method can be classified into time-domain and frequency-domain methods. Practically, two types of methods are characterized by different advantages, and the estimated modal parameters are always subjected to statistical uncertainties due to measurement noise. In this work, an uncertainty-based fusion method for structural mode identification is proposed to merge the advantages of different methods. The extensively applied time-domain AutoRegressive (AR) and frequency-domain Left-Matrix Fraction (LMF) models are expressed in a unified parametric mod

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Chiang, Dar-Yun, and Si-Tsong Huang. "Modal Parameter Identification Using Simulated Evolution." AIAA Journal 35, no. 7 (1997): 1204–8. http://dx.doi.org/10.2514/2.215.

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Kasai, Tokio, Keiji Komatsu, and Masa Sano. "Modal Parameter Identification of Controlled Structures." Journal of Guidance, Control, and Dynamics 20, no. 1 (1997): 184–86. http://dx.doi.org/10.2514/2.4014.

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Chiang, Dar-Yun, and Ming-Si Cheng. "Modal Parameter Identification from Ambient Response." AIAA Journal 37, no. 4 (1999): 513–15. http://dx.doi.org/10.2514/2.745.

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Dissertations / Theses on the topic "Modal parameter identification"

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Drexel, Michael V. "Modal parameter identification using mode isolation." Diss., Georgia Institute of Technology, 2001. http://hdl.handle.net/1853/17239.

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Zhou, Wenliang. "Multivariate analysis in vibration modal parameter identification /." View online ; access limited to URI, 2006. http://0-digitalcommons.uri.edu.helin.uri.edu/dissertations/AAI3248248.

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Furness, Charles Zachary. "Parameter identification of a flexible beam using a modal domain optical fiber sensor." Thesis, Virginia Tech, 1990. http://hdl.handle.net/10919/42058.

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<p>An optical fiber sensor is used for identification of a cantilevered beam under conditions of various concentrated mass loadings. A model of the sensor as well as the dynamic system is developed and used to test the reliability of the identification. Input/output data from an experiment is gathered and used in the identification. A survey of the existing areas of damage detection and parameter identification is included, along with suggestions for incorporating fiber optic sensors into existing techniques. The goal of this research was to show that the fiber sensor can be used for identific

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陶冬玲 and Dong-ling Tao. "Modal parameter identification for non-linear systems using the time-domain fourier filter output method." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1997. http://hub.hku.hk/bib/B31236169.

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Tao, Dong-ling. "Modal parameter identification for non-linear systems using the time-domain fourier filter output method /." Hong Kong : University of Hong Kong, 1997. http://sunzi.lib.hku.hk/hkuto/record.jsp?B19013310.

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Buke, Fatih. "An Investigation On The Application Of Operational Modal Analysis." Master's thesis, METU, 2006. http://etd.lib.metu.edu.tr/upload/2/12607529/index.pdf.

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Modal parameter identification of a structure is done through modal testing and modal analysis using various system identification methods. These methods employ linear input-output relationships to extract the modes of a structure. There are cases where laboratory testing of a structure is not possible or information about the structure under operating conditions is seeked. A set of techniques called Operational Modal Analysis have been developed for modal parameter identification in operating conditions of a structure. These techniques use only response measurements to extract the modes. The

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Bornitz, Matthias, Thomas Zahnert, Hans-Jürgen Hardtke, and Karl-Bernd Hüttenbrink. "Identification of Parameters for the Middle Ear Model." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-135790.

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This paper presents a method of parameter identification for a finite-element model of the human middle ear. The parameter values are estimated using a characterization of the difference in natural frequencies and mode shapes of the tympanic membrane between the model and the specimens. Experimental results were obtained from temporal bone specimens under sound excitation (300–3,000 Hz). The first 3 modes of the tympanic membrane could be observed with a laser scanning vibrometer and were used to estimate the stiffness parameters for the orthotropic finite-element model of the eardrum. A furth

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Fahey, Sean O'Flaherty. "Parameter Estimation of Structural Systems Possessing One or Two Nonlinear Normal Modes." Diss., Virginia Tech, 2000. http://hdl.handle.net/10919/29477.

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In this Dissertation, we develop, and provide proof of principle for, parameter identification techniques for structural systems that can be described in terms of one or two nonlinear normal modes. We model the dynamics of these modes by second-order ordinary-differential equations based on the principles of mechanics, past experience, and engineering judgment. We perform a number of separate experiments on a two-mass structure using several different types of excitation. For the linear tests, the theoretical system response is known in closed-form. For the nonlinear test, we use the metho

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Idehara, Sergio Junichi. "Identificação de parametros modais de estruturas e maquinas rotativas atraves da filtragem adaptativa." [s.n.], 2007. http://repositorio.unicamp.br/jspui/handle/REPOSIP/263784.

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Orientador: Milton Dias Junior<br>Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecanica<br>Made available in DSpace on 2018-08-10T08:27:27Z (GMT). No. of bitstreams: 1 Idehara_SergioJunichi_D.pdf: 6234443 bytes, checksum: 5071d7a2383df6369dbeaf00f65fb511 (MD5) Previous issue date: 2007<br>Resumo: Este trabalho consiste na investigação de algoritmos da filtragem adaptativa utilizados no contexto da identificação de parâmetros. Apesar de ainda ser uma técnica pouco explorada na engenharia mecânica, os algoritmos adaptativos, com destaque para o método dos mínim

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Baby, Arun Paul. "Comparison of Modal Parameter Estimation using State Space Methods (N4SID) and the Unified Matrix Polynomial Approach." University of Cincinnati / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1613731964598438.

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Books on the topic "Modal parameter identification"

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Longman, Richard W. Variance and bias confidence criteria for ERA modal parameter identification. American Institute of Aeronautics and Astronautics, 1988.

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Dilworth, Brandon J., Timothy Marinone, and Michael Mains, eds. Topics in Modal Analysis & Parameter Identification, Volume 8. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-05445-7.

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Dilworth, Brandon J., Timothy Marinone, and Michael Mains, eds. Topics in Modal Analysis & Parameter Identification, Volume 9. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-34942-3.

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Dilworth, Brandon J., Timothy Marinone, and Jon Furlich, eds. Topics in Modal Analysis & Parameter Identification, Vol. 9. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-68180-6.

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Quach, Tai. A study of techniques for rotorcraft model identification. Aerospace Science and Engineering, 1989.

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Thomas, Banks H., and Langley Research Center, eds. The identification of a distributed parameter model for a flexible structure. NASA Langley Research Center, 1986.

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Thomas, Banks H., and Langley Research Center, eds. The identification of a distributed parameter model for a flexible structure. NASA Langley Research Center, 1986.

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Center, Langley Research, ed. Comparing parameter estimation techniques for an electrical power transformer oil temperature prediction model. National Aeronautics and Space Administration, Langley Research Center, 1999.

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9

Huang, Jen-Kuang. Single-mode projection filters for modal parameter identificatio n for flexible structures: Final report for the period ended December 31, 1987. Old Dominion University Research Foundation, 1988.

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Chung-Wen, Chen, and United States. National Aeronautics and Space Administration., eds. Single-mode projection filters for modal parameter identificatio n for flexible structures: Final report for the period ended December 31, 1987. Old Dominion University Research Foundation, 1988.

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Book chapters on the topic "Modal parameter identification"

1

Elkafafy, Mahmoud, and Bart Peeters. "Robust Identification of Stable MIMO Modal State Space Models." In Topics in Modal Analysis & Parameter Identification, Volume 8. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-05445-7_10.

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Stein, Dalton, He-Wen-Xuan Li, and David Chelidze. "Sub-Band Decomposition Based-Linear Normal Mode Identification." In Topics in Modal Analysis & Parameter Identification, Volume 8. Springer International Publishing, 2012. http://dx.doi.org/10.1007/978-3-031-05445-7_16.

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Beltrán-Carbajal, F., G. Silva-Navarro, and L. G. Trujillo-Franco. "Evaluation of On-Line Algebraic Modal Parameter Identification Methods." In Topics in Modal Analysis II, Volume 8. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04774-4_14.

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4

Chiang, Dar-Yun, and Chang-Sheng Lin. "Modal-Parameter Identification From Nonstationary Ambient Vibration Data." In Experimental and Applied Mechanics, Volume 6. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4614-0222-0_21.

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Volvert, Martin, and Gaëtan Kerschen. "Numerical and Analytical Study of the Phase Resonances of a Duffing Oscillator." In Topics in Modal Analysis & Parameter Identification, Volume 8. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-05445-7_2.

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Sills, Joel W., and Arya Majed. "Accelerance Decoupling: An Approach for Removing the Influence of the Test Stand from the Integrated Modal Test." In Topics in Modal Analysis & Parameter Identification, Volume 8. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-05445-7_19.

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Colford, Greta P., and Daniel J. Inman. "Experimental Verification of 1D Lumped Parameter Model of Mass-Conserved Metastructure." In Topics in Modal Analysis & Parameter Identification, Volume 8. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-05445-7_17.

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Csurcsia, Péter Zoltán, Bart Peeters, and Tim De Troyer. "Frequency Response Function Estimation for Systems with Multiple Inputs Using Short Measurement: A Benchmark Study." In Topics in Modal Analysis & Parameter Identification, Volume 8. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-05445-7_7.

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Akar, Özge, and Kai Willner. "Investigating the Modal Behavior of a Violin Top and a Back Plate." In Topics in Modal Analysis & Parameter Identification, Volume 8. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-05445-7_5.

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Tsialiamanis, Georgios, Max D. Champneys, David J. Wagg, Nikolaos Dervilis, and Keith Worden. "On the Use of Cycle-Consistent Generative Adversarial Networks for Nonlinear Modal Analysis." In Topics in Modal Analysis & Parameter Identification, Volume 8. Springer International Publishing, 2012. http://dx.doi.org/10.1007/978-3-031-05445-7_6.

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Conference papers on the topic "Modal parameter identification"

1

Uehara, Daiju, Marc Eitner, and Jayant Sirohi. "Automated Operational Modal Identification of a Rotor Blade." In Vertical Flight Society 74th Annual Forum & Technology Display. The Vertical Flight Society, 2018. http://dx.doi.org/10.4050/f-0074-2018-12757.

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This study describes the deformation measurement and automated operational modal analysis (OMA) of a rotor blade in hover. Blade deformation of a 0.4 m-diameter two-bladed rotor was measured at two different root pitch angles and four rotational speeds up to 1500 RPM by a time-resolved digital image correlation technique (DIC). The DIC technique successfully measured the time history of 3D displacements over the entire rotor blade at approximately 900 measurement locations for the flap, lead-lag, and torsional degrees of freedom. The measured blade deformation data were then processed with the

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Zhu, Yangyang, Jie Zeng, Hainan Yang, et al. "Blade Modal Parameter Identification Based on Fiber Strain Sensing and Fitting Circle Method." In 2024 Global Reliability and Prognostics and Health Management Conference (PHM-Beijing). IEEE, 2024. https://doi.org/10.1109/phm-beijing63284.2024.10874726.

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M'Closkey, R. T., S. Gibson, and J. Hui. "Modal parameter identification of a MEMS gyroscope." In Proceedings of 2000 American Control Conference (ACC 2000). IEEE, 2000. http://dx.doi.org/10.1109/acc.2000.879491.

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Ye, Qingwei, Tingkai Zhao, Yu Zhou, and Xiaodong Wang. "Concentrated Modal Parameter Identification Based on Modal-Wavelet Continuous Transformation." In 2010 Chinese Conference on Pattern Recognition (CCPR). IEEE, 2010. http://dx.doi.org/10.1109/ccpr.2010.5659304.

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Gong, Maosheng, Jinping Ou, Jing Sun, and Lili Xie. "Modal parameter identification of model structure in shaking table test." In 2010 3rd International Congress on Image and Signal Processing (CISP). IEEE, 2010. http://dx.doi.org/10.1109/cisp.2010.5646395.

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Kasai, T., K. Komatsu, and M. Sano. "Modal parameter identification of controlled flexible space structures." In Smart Structures and Materials: Second European Conference, edited by Alaster McDonach, Peter T. Gardiner, Ron S. McEwen, and Brian Culshaw. SPIE, 1994. http://dx.doi.org/10.1117/12.184837.

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Wang, Chunlin, Torodd Skjerve Nord, and Guoyuan Li. "Automated Modal Parameters Identification During Ice-Structure Interactions." In ASME 2022 41st International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/omae2022-81075.

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Abstract Offshore structures are prone to damage caused by ice-induced vibrations. It is presently unknown to what extent different ice conditions change the properties of the structure, such as natural frequency, damping ratio, and mode shape. Understanding the dynamic interaction between ice and structures are important for the operational ability of offshore structures. In this study, the covariance-driven stochastic subspace identification algorithm (SSI-cov) is introduced to identify modal parameters of a scale-model structure during ice-structure interactions. In order to reduce the numb

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Rebolho, Daniela, Eduardo Belo, and Carlos De Marqui Júnior. "The EERA Method for Real Time Modal Parameter Identification." In 49th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference
16th AIAA/ASME/AHS Adaptive Structures Conference
10t. American Institute of Aeronautics and Astronautics, 2008. http://dx.doi.org/10.2514/6.2008-2195.

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Zhou, Wenliang, and David Chelidze. "Generalized Eigenvalue Decomposition in Time Domain Modal Parameter Identification." In ASME 2006 International Mechanical Engineering Congress and Exposition. ASMEDC, 2006. http://dx.doi.org/10.1115/imece2006-14702.

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This paper is intended to point out the relationship among current time domain modal analysis methods by employing the generalized eigenvalue decomposition. Various well-known time domain modal analysis algorithms are reviewed. Ibrahim Time Domain (ITD), Least Square Complex Exponent (LSCE) and Eigensystem Realization Algorithm (ERA) methods are chosen to do the comparison. Reformulation to these original forms show these three methods can all be attributed to a generalized eigenvalue problem with different matrix pairs. With this general format, we can see that Single-Input Multi-Output (SIMO

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Teng, J., and Y. H. Zhu. "Parameters Optimization of Wavelet Transform in Modal Parameter Identification with Closely Spaced Modes." In 12th Biennial International Conference on Engineering, Construction, and Operations in Challenging Environments; and Fourth NASA/ARO/ASCE Workshop on Granular Materials in Lunar and Martian Exploration. American Society of Civil Engineers, 2010. http://dx.doi.org/10.1061/41096(366)227.

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Reports on the topic "Modal parameter identification"

1

Lohne, Arild, Arne Stavland, Siv Marie Åsen, Olav Aursjø, and Aksel Hiorth. Recommended polymer workflow: Interpretation and parameter identification. University of Stavanger, 2021. http://dx.doi.org/10.31265/usps.202.

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Injecting a polymer solution into a porous medium significantly increases the modeling complexity, compared to model a polymer bulk solution. Even if the polymer solution is injected at a constant rate into the porous medium, the polymers experience different flow regimes in each pore and pore throat. The main challenge is to assign a macroscopic porous media “viscosity” to the fluid which can be used in Darcy law to get the correct relationship between the injection rate and pressure drop. One can achieve this by simply tabulating experimental results (e.g., injection rate vs pressure drop).

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Kuropiatnyk, D. I. Actuality of the problem of parametric identification of a mathematical model. [б. в.], 2018. http://dx.doi.org/10.31812/123456789/2885.

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The purpose of the article is to study the possibilities of increasing the efficiency of a mathematical model by identifying the parameters of an object. A key factor for parametrization can be called the consideration of properties of the values of the model at a specific time point, which allows a deeper analysis of data dependencies and correlation between them. However, such a technique does not always work, because in advance it is impossible to predict that the parameters can be substantially optimized. In addition, it is necessary to take into account the fact that minimization reduces

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Bialasiewicz, Jan T. Advanced System Identification Techniques for Wind Turbine Structures with Special Emphasis on Modal Parameters. Office of Scientific and Technical Information (OSTI), 1995. http://dx.doi.org/10.2172/87043.

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Bammann, Douglas J., G. C. Johnson, Esteban B. Marin, and Richard A. Regueiro. On the formulation, parameter identification and numerical integration of the EMMI model :plasticity and isotropic damage. Office of Scientific and Technical Information (OSTI), 2006. http://dx.doi.org/10.2172/883488.

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Hunke, Elizabeth Clare, Jorge Rolando Urrego Blanco, and Nathan Mark Urban. Uncertainty, Sensitivity Analysis, and Causal Identification in the Arctic using a Perturbed Parameter Ensemble of the HiLAT Climate Model. Office of Scientific and Technical Information (OSTI), 2018. http://dx.doi.org/10.2172/1422910.

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Azimova, N. N., V. V. Baranichenko, M. V. Bedoidze, et al. COMPUTER PROGRAM «AUTOMATED IDENTIFICATION OF SINGLE-PARAMETER SIZE DISTRIBUTION OF INDUSTRIAL DUST COMPARYING SIMPLE AND CENTRAL MOMENTS WITH ONES FOR MODEL FUNCTIONS». Ailamazyan Program Systems Institute of Russian Academy of Sciences, 2023. http://dx.doi.org/10.12731/ofernio.2023.25239.

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Read, Matthew, and Dan Zhu. Fast Posterior Sampling in Tightly Identified SVARs Using 'Soft' Sign Restrictions. Reserve Bank of Australia, 2025. https://doi.org/10.47688/rdp2025-03.

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We propose algorithms for conducting Bayesian inference in structural vector autoregressions identified using sign restrictions. The key feature of our approach is a sampling step based on 'soft' sign restrictions. This step draws from a target density that smoothly penalises parameter values violating the restrictions, facilitating the use of computationally efficient Markov chain Monte Carlo sampling algorithms. An importance-sampling step yields draws from the desired distribution conditional on the 'hard' sign restrictions. Relative to standard accept-reject sampling, the method substantia

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Rahmani, Mehran, Xintong Ji, and Sovann Reach Kiet. Damage Detection and Damage Localization in Bridges with Low-Density Instrumentations Using the Wave-Method: Application to a Shake-Table Tested Bridge. Mineta Transportation Institute, 2022. http://dx.doi.org/10.31979/mti.2022.2033.

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This study presents a major development to the wave method, a methodology used for structural identification and monitoring. The research team tested the method for use in structural damage detection and damage localization in bridges, the latter being a challenging task. The main goal was to assess capability of the improved method by applying it to a shake-table-tested prototype bridge with sparse instrumentation. The bridge was a 4-span reinforced concrete structure comprising two columns at each bent (6 columns total) and a flat slab. It was tested to failure using seven biaxial excitation

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Engel, Bernard, Yael Edan, James Simon, Hanoch Pasternak, and Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, 1996. http://dx.doi.org/10.32747/1996.7613033.bard.

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The objectives of this project were to develop procedures and models, based on neural networks, for quality sorting of agricultural produce. Two research teams, one in Purdue University and the other in Israel, coordinated their research efforts on different aspects of each objective utilizing both melons and tomatoes as case studies. At Purdue: An expert system was developed to measure variances in human grading. Data were acquired from eight sensors: vision, two firmness sensors (destructive and nondestructive), chlorophyll from fluorescence, color sensor, electronic sniffer for odor detecti

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Miles, Gaines E., Yael Edan, F. Tom Turpin, et al. Expert Sensor for Site Specification Application of Agricultural Chemicals. United States Department of Agriculture, 1995. http://dx.doi.org/10.32747/1995.7570567.bard.

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In this work multispectral reflectance images are used in conjunction with a neural network classifier for the purpose of detecting and classifying weeds under real field conditions. Multispectral reflectance images which contained different combinations of weeds and crops were taken under actual field conditions. This multispectral reflectance information was used to develop algorithms that could segment the plants from the background as well as classify them into weeds or crops. In order to segment the plants from the background the multispectrial reflectance of plants and background were st

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