Abstract:

This article summarizes the innovative application of AI assisted dynamic voiceprint analysis strategy in battery pack anomaly recognition. The article first outlines the foundation of voiceprint recognition theory, and then provides a detailed introduction to the theoretical framework of artificial intelligence (AI), including key technologies such as machine learning and deep learning, as well as how these technologies demonstrate powerful capabilities in complex data processing, pattern recognition, and other areas. The article focuses on exploring battery pack anomaly detection strategies based on AI and voiceprint technology. By integrating high-precision sound collection equipment, advanced signal processing technology, and optimized AI algorithms, this strategy can monitor the sound changes during the operation of the battery pack in real time, and use dynamic voiceprint analysis technology to extract key sound features for abnormal pattern recognition and classification. The new technology not only improves the accuracy and real-time performance of anomaly recognition, but also effectively addresses complex and variable abnormal situations that may occur during the operation of battery packs.

Key words: artificial intelligence, voiceprint, anomaly detection