Research on defect identification of chemical battery electrode based on voiceprint and AI analysis technology

doi:10.19799/j.cnki.2095-4239.2024.0783

Energy Storage Science and Technology ›› 2024, Vol. 13 ›› Issue (10): 3669-3671.doi: 10.19799/j.cnki.2095-4239.2024.0783

• Energy Storage Test: Methods and Evaluation • Previous Articles Next Articles

Research on defect identification of chemical battery electrode based on voiceprint and AI analysis technology

Miao LI¹(), Fengying ZHOU¹, Huishan CUI², Lan FANG², Wenya LI²

^1.School of Mechatronic Engineering, Beijing Polytechnic College, Beijing 100042, China
^2.Department of Rail Transit, Beijing Jiaotong Vocational Technical College, Beijing 102200, China

Received:2024-08-22 Revised:2024-09-23 Online:2024-10-28 Published:2024-10-30
Contact: Miao LI E-mail:m15810251260@163.com

Abstract

Abstract:

With the rapid development of the new energy industry, chemical batteries, as its core components, are crucial for the stability and safety of the overall system in terms of their performance and quality. As an important component of batteries, the defects in the preparation process of chemical battery electrodes directly affect the electrochemical performance and safety of the battery. This article reviews the research on defect recognition methods for chemical battery electrodes using voiceprint and AI analysis techniques. By combining these two technologies, the accuracy and efficiency of defect detection can be improved, providing strong support for quality control in battery production processes.

Key words: voiceprint technology, battery, defects

CLC Number:

TM 911

Miao LI, Fengying ZHOU, Huishan CUI, Lan FANG, Wenya LI. Research on defect identification of chemical battery electrode based on voiceprint and AI analysis technology[J]. Energy Storage Science and Technology, 2024, 13(10): 3669-3671.

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Research on defect identification of chemical battery electrode based on voiceprint and AI analysis technology

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