Smart Monitoring System for Detection of Damage in Structural Parts by EMI and ANSYS

Jayachitra, T.; Priyadarshini, Rashmi

doi:10.14445/22315381/ijett-v69i2p219

IJETT

2021

DOI: 10.14445/22315381/ijett-v69i2p219

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Smart Monitoring System for Detection of Damage in Structural Parts by EMI and ANSYS

T. Jayachitra¹,

Rashmi Priyadarshini²

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2023

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Damage detection method of automobile hub based on image texture feature

Wang¹

2023

JCM

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With the rapid growth in the number of motor vehicles worldwide, the general public is beginning to attach importance to the quality inspection of wheels before they leave the factory. The current wheel defect detection systems are often cumbersome to operate and have low practical performance. Therefore, this research will use dynamic image segmentation, image texture feature extraction and Back Propagation neural network classification based on wheel image defect feature analysis algorithm to achieve automatic intelligent detection of automotive wheel defects. In this study, an intelligent detection system for automotive wheel defects is also designed, and finally the performance of the detection system is tested experimentally to illustrate its practicality. The experimental results show that the proposed intelligent detection system for automotive wheel defects based on image texture features identifies defects in wheel castings with a correct rate of 96% and a false positive rate of only 2%. This illustrates that the detection system proposed in this study has a high recognition rate and can provide a useful reference for the automotive industry inspection.

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Damage detection method of automobile hub based on image texture feature

Wang¹

2023

JCM

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Smart Monitoring System for Detection of Damage in Structural Parts by EMI and ANSYS

Cited by 1 publication

References 15 publications

Damage detection method of automobile hub based on image texture feature

Damage detection method of automobile hub based on image texture feature

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