An improved design for ferrous metal detection and removal with edge-aware adaptive algorithm in nonwoven fabric production lines

With the advancement of manufacturing toward intelligence and digitalization, automation technologies have become integral across various industries. However, the nonwoven fabric industry continues to face challenges such as high labor costs and low automation levels, creating an urgent need for technological innovation to enhance production efficiency and product quality. This study introduces an intelligent ferrous metal detection and removal automation system, designed specifically for industrial deployment in nonwoven fabric production lines. It integrates an optimized coil arrangement, an edge-aware adaptive cutting optimization algorithm, and a pneumatic–hydraulic driven removal device, ensuring high detection precision, minimal material waste, and seamless integration into continuous production workflows. The system employs a triangular coil arrangement to optimize magnetic field distribution, significantly improving detection sensitivity and accuracy. The edge-aware adaptive cutting algorithm precisely locates ferrous metal impurities while minimizing damage to material edges, thereby preventing twisting or deformation of the fabric during transport that could lead to machine jamming. In addition, a pneumatic–hydraulic driven removal device is designed to efficiently excise impurity areas with high precision. Experimental results demonstrate the system’s capability to detect and remove iron particles as small as 1.2 mm in diameter, substantially improving automation levels and production efficiency in nonwoven fabric manufacturing.