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Detection of Metallic Contaminant in Aluminium Soda Can Using TMR Sensor

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Intelligent Manufacturing & Mechatronics

Abstract

The contaminant is one of the big concerns in food processing industry and metallic objects can be one of the contaminant factors since most of the food processing equipment and tools are composed of metallic parts. Metal detector is used because these contaminant objects might cause injury to the consumers. Moreover, even the smallest particle of metals can lead to machinery failure. In this study, we have developed an inspection system for detecting the magnetic remanence of the contaminants. The system utilizes a Tunnel Magnetoresistance (TMR) Mag3110 magnetometer. An Arduino operating software was developed for data acquisition of Mag3110, and identification of the presence of the contaminant. In order to optimize the position of the magnetometer so that detection sensitivity can be enhanced, we performed a simulation based on magnetic moment dipole. The system performance was evaluated using stainless steel balls. The developed system could detect a stainless steel ball having diameter as small as 0.1 cm. The detected signal is sent to the control panel to analyze the presence of a metal object. The magnetic response with respect to position of the sensor, different size of metal objects and magnetization effect, is studied as well.

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Acknowledgements

This work was supported by Ministry of Higher Education of Malaysia under grant number of RDU160115 and Research Management Center of Universiti Malaysia Pahang under grant number of RDU170377.

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Correspondence to Mohd Mawardi Saari .

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Nadzri, N.A., Saari, M.M., Razali, S., Mohamed, M.R., Ahmad, H. (2018). Detection of Metallic Contaminant in Aluminium Soda Can Using TMR Sensor. In: Hassan, M. (eds) Intelligent Manufacturing & Mechatronics. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-10-8788-2_47

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  • DOI: https://doi.org/10.1007/978-981-10-8788-2_47

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-8787-5

  • Online ISBN: 978-981-10-8788-2

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