High‐Accuracy Recognition Triboelectric Nanogenerator System for Shooting Report and Ballistic Analysis

Abstract

The accuracy and efficiency of shooting reports constitute indispensable cornerstones in modern military training and shooting fields. However, traditional shooting report systems struggle to offer precise and sensitive instant feedback, especially in rare scenarios, such as multiple piercing and shots on the ring boundaries. Simultaneously, ballistic analysis as a pivotal approach in criminal investigations, confronts similar challenges including high costs, complex data processing, and strong professional dependency. Thus, a flexible, high‐temperature resistant, and high‐accuracy recognition intelligent target reporting and ballistic analysis (ITBA) system is designed based on the mechanism of triboelectric nanogenerator (TENG), which recognizes multiple bullet piercings and delivers bullet velocity through a time‐difference algorithm combined with shooting angle to accurately determine the shooting position. Thanks to the novel structural design and preparation method, the ITBA system achieves remarkable integration, lightweight, and industrialization, ensuring exceptional stability even in harsh environments. Furthermore, the ITBA system integrates machine learning techniques to achieve 100% accuracy in bullet material recognition and 97% accuracy in determining shooting angles, providing a solid foundation for enhancing the precision of military training and the scientific rigor of forensic investigations.