Scanning schemes in white light photoelasticity – Part II: Novel fringe resolution guided scanning scheme

Ramakrishnan, Vivek; Ramesh, K.

doi:10.1016/j.optlaseng.2016.05.010

Cited by 28 publications

(8 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…BP (backpropagation) algorithm of multilayer convolutional neural network calculates the weight and threshold of neural network based on neural learning rules [ 18 ]. This algorithm can converge when the step size of the network weight and threshold is adjusted infinitely every time, and the introduction of momentum factor can speed up the calculation [ 19 ].…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Optimization of Personnel Placement Scheme and Big Data Analysis Based on Multilayer Variable Neural Network Algorithm

2021

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

People usually use the method of job analysis to understand the requirements of each job in terms of personnel characteristics, at the same time use the method of psychological measurement to understand the psychological characteristics of each person, and then put the personnel in the appropriate position by matching them with each other. With the development of the information age, massive and complex data are produced. How to accurately extract the effective data needed by the industry from the big data is a very arduous task. In reality, personnel data are influenced by many factors, and the time series formed by it is more accidental and random and often has multilevel and multiscale characteristics. How to use a certain algorithm or data processing technology to effectively dig out the rules contained in the personnel information data and explore the personnel placement scheme has become an important issue. In this paper, a multilayer variable neural network model for complex big data feature learning is established to optimize the staffing scheme. At the same time, the learning model is extended from vector space to tensor space. The parameters of neural network are inversed by high-order backpropagation algorithm facing tensor space. Compared with the traditional multilayer neural network calculation model based on tensor space, the multimodal neural network calculation model can learn the characteristics of complex data quickly and accurately and has obvious advantages.

show abstract

Section: Introductionmentioning

confidence: 99%

[Retracted] Optimization of Personnel Placement Scheme and Big Data Analysis Based on Multilayer Variable Neural Network Algorithm

2021

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

show abstract

“…This means that test data is obtained faster and it is more precise, but the theory and underlying concepts of the photoelasticity remain the same. Further research and development of the method was mostly related to the automation of the data acquisition and analysis process, so that various new scanning schemes were developed (Digendranath, Binu, P, & Annamala, 2015), (Kale & Ramesh, 2013), (Yao, Jian, Xu, Jin, & Yeh, 2005), (Digendranath, Jeby, & Annamala, 2014), (Ramakrishnan & Ramesh, 2017a), (Ramakrishnan & Ramesh, 2017b) and new methods for extracting the stress data from the acquired images have been presented, for instance (Ramji & Ramesh, 2008).…”

Section: Discussionmentioning

confidence: 99%

Photoelaticity and Its Application to Structural Analysis. A Review Based on Professor Vlatko Brčić Achievements

Hedrih¹,

Paunović²

2018

JSSCM

View full text Add to dashboard Cite

Professor Vlatko Brčić was a very prominent scientist-theoretician, researcher and engineer, and he had a profound scientific influence on the development of civil engineering and stress analysis of civil engineering structures in the Western Balkans. This paper presents a brief overview of the scientific results and engineering activity of prof. Brčić, as well as a report on his research regarding the improvement and application of the photoelasticity method in stress state analysis of various engineering structures, while the results and influence of his work are discussed in more detail.

show abstract

“…Evidentemente, al ser el valor que será referencia para asignar a los pixeles vecinos (que a su vez serán referencia para otros pixeles y así sucesivamente), no posee un referente para su elección. De manera que hay que tener en mente dicha asignación, por lo que se han propuesto varios esquemas de escaneo [30,31,32].…”

Section: Elección De Semillaunclassified

Software de fotoelasticidad RGB en placas de materiales birrefringentes al esfuerzo

2021

View full text Add to dashboard Cite

La fotoelasticidad digital utiliza el fenómeno de la birrefringencia para el análisis y descripción de la distribución de esfuerzos a través de imágenes digitales y del procesamiento digital de las mismas. En este trabajo se presenta el desarrollo y diseño de un código, abierto y gratuito, en MATLAB que adopta la metodología de la fotoelasticidad RGB para determinar la distribución de la diferencia de esfuerzos principales en una probeta plana de un material fotoelástico, sometida a cargas mecánicas en un estado de esfuerzos planos. Esto mediante el procesamiento de una imagen digital a color de un espécimen de material birrefringente al esfuerzo, colocado dentro de un polariscopio circular en su configuración de campo oscuro. Se presenta la generación de imágenes artificiales representativas del fenómeno con el fin de tener datos de entrada para el desarrollo del algoritmo y una forma de validarlo. Se muestran también los pasos necesarios para la metodología de la fotoelasticidad RGB que incluyen la preparación de una base de datos o tabla de búsqueda y el análisis de la imagen fotoelástica. Se compara, además, el resultado del cálculo de la diferencia de esfuerzos principales con resultados de elemento finito, en lo cual se obtuvo un buen grado de confiabilidad en las imágenes utilizadas.

show abstract

Scanning schemes in white light photoelasticity – Part II: Novel fringe resolution guided scanning scheme

Cited by 28 publications

References 13 publications

[Retracted] Optimization of Personnel Placement Scheme and Big Data Analysis Based on Multilayer Variable Neural Network Algorithm

[Retracted] Optimization of Personnel Placement Scheme and Big Data Analysis Based on Multilayer Variable Neural Network Algorithm

Photoelaticity and Its Application to Structural Analysis. A Review Based on Professor Vlatko Brčić Achievements

Software de fotoelasticidad RGB en placas de materiales birrefringentes al esfuerzo

Contact Info

Product

Resources

About