Proposing an intelligent approach for measuring the thickness of metal sheets independent of alloy type

Nazemi, Ehsan; Aminipour, M.; Olfateh, A.; Golgoun, S. M.; Davarpanah, Mohammad Reza

doi:10.1016/j.apradiso.2019.03.023

Cited by 11 publications

(2 citation statements)

References 31 publications

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“…References [3,4] expand on the work of the aforementioned writers on the subject of metal thickness meters. A straightforward and intelligent gamma-ray-based system that makes use of AI was reported in [5] for the purpose of online thickness measuring of metal sheets made of a variety of alloys. Aluminum sheets were the focus of the research in this article.…”

Section: Introductionmentioning

confidence: 99%

Combination of a Nondestructive Testing Method with Artificial Neural Network for Determining Thickness of Aluminum Sheets Regardless of Alloy’s Type

Mayet,

Shah,

Hanus

et al. 2023

Electronics

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Non-destructive and reliable radiation-based gauges have been routinely used in industry to determine the thickness of metal layers. When the material’s composition is understood in advance, only then can the standard radiation thickness meter be relied upon. Errors in thickness measurements are to be expected in settings where the actual composition of the material may deviate significantly from the nominal composition, such as rolled metal manufacturers. In this research, an X-ray-based system is proposed to determine the thickness of an aluminum sheet regardless of its alloy type. In the presented detection system, an X-ray tube with a voltage of 150 kV and two sodium iodide detectors, a transmission detector and a backscattering detector, were used. Between the X-ray tube and the transmission detector, an aluminum plate with different thicknesses, ranging from 2 to 45 mm, and with four alloys named 1050, 3050, 5052, and 6061 were simulated. The MCNP code was used as a very powerful platform in the implementation of radiation-based systems in this research to simulate the detection structure and the spectra recorded using the detectors. From the spectra recorded using two detectors, three features of the total count of both detectors and the maximum value of the transmission detector were extracted. These characteristics were applied to the inputs of an RBF neural network to obtain the relationship between the inputs and the thickness of the aluminum plate. The trained neural network was able to determine the thickness of the aluminum with an MRE of 2.11%. Although the presented methodology is used to determine the thickness of the aluminum plate independent of the type of alloy, it can be used to determine the thickness of other metals as well.

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Section: Introductionmentioning

confidence: 99%

Combination of a Nondestructive Testing Method with Artificial Neural Network for Determining Thickness of Aluminum Sheets Regardless of Alloy’s Type

Mayet,

Shah,

Hanus

et al. 2023

Electronics

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“…Esta radiación puede ser de tres clases: α, las cuales son poco penetrantes; β son que más penetrantes que las partículas α; y las γ, que es el tipo más penetrante de radiación. La radiactividad se aprovecha en varias disciplinas como la medicina [6], con aplicaciones en la toma de imágenes diagnósticas, radioterapia y medicina nuclear [6]; en la industria [7], la radiación es utilizada en la esterilización de materiales [8], para hallar medidas de espesores y densidades [9], etc. Es evidente que la radiación se emplea con mucha frecuencia y que resulta sumamente peligroso exponerse a ella [10,11], por eso es importante tener un dispositivo que ayude a medir la radiación, como es el caso del contador de partículas radiactivas.…”

Section: Introductionunclassified

Detección de partículas a nivel de educación básica. Usando hardware y software libre.

et al. 2021

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En el presente artículo se demuestra la factibilidad de enseñar los principios básicos de la física experimental de altas energías en instituciones de educación media, usando equipos de bajo costo. Se enfatiza en el uso de hardware y software libre para el estudio de diferentes tipos de radiación. Se construye una caja oscura para analizar la respuesta de un foto-multiplicador de silicio a un pulso de luz.Descriptores: Foto-sensor; contador Geiger; radiación. This article demonstrates the feasibility of teaching in secondary education institutions, the basic principles of high-energy experimental physics using low-cost equipment. The use of free hardware and software is emphasized for the study of different types of radiation. A dark box is constructed to study the response of a silicon photo-multiplier to a pulse of light.

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Prediction of Liquid Density by Gamma-Ray Measurement for Materials with Low Atomic Number

Golgoun

Sardari

Sadeghi

et al. 2020

MAPAN

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Proposing an intelligent approach for measuring the thickness of metal sheets independent of alloy type

Cited by 11 publications

References 31 publications

Combination of a Nondestructive Testing Method with Artificial Neural Network for Determining Thickness of Aluminum Sheets Regardless of Alloy’s Type

Combination of a Nondestructive Testing Method with Artificial Neural Network for Determining Thickness of Aluminum Sheets Regardless of Alloy’s Type

Detección de partículas a nivel de educación básica. Usando hardware y software libre.

Prediction of Liquid Density by Gamma-Ray Measurement for Materials with Low Atomic Number

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