A Wavelet Analysis and Fast Fourier Transform-Based Defect Detection Method for Cigarette Package Aluminum Foil
Year: 2025
Type: conference-paper
Abstract: Given the critical role of aluminum foil integrity in cigarette packaging for product quality assurance, this study proposes a defect detection methodology for cigarette package aluminum foil by integrating wavelet analysis and Fast Fourier Transform (FFT). Wavelet analysis can effectively extract information from the signal and has excellent signal-to-noise separation function, and can perform noise reduction processing on the detected signal. The fast Fourier transform can generate a spectrogram to obtain specific frequencies and amplitudes. The detection signals were initially decomposed through wavelet transform to eliminate high-frequency noise components, followed by application of FFT to the denoised signals for systematic analysis of their spectral characteristics. The combination of these two methods accurately detects defects in the aluminum foil paper of cigarette boxes.
Authors: Pingli Mu, Yongqi Wang, Junjun Xie, Xiangyang Shi, Yang Lei, Qi Zhao, Yijian Liu, Yongdian Tong, Shengli Zhang
Institutions: China Tobacco, Zhengzhou University
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4414307176