基于LLM模型的AI误差分析MOSFET测试系统OA

To address the challenges of traditional MOSFET testing,such as cumbersome procedures,reliance on bulky instruments,and a low degree of intelligence,this paper presents an automated test system integrating a Large Language Model(LLM)with the"Yuzhu S"portable hardware.Centered around the"Yuzhu S"instrument,the system performs characteristic curve,threshold voltage and conduction resistance tests using an integrated PCB carrier board.It innovatively leverages the Gemini API to empower the soft-ware,enabling automatic parsing of PDF datasheets,intelligent recommendation of test parameters,and in-depth error analysis of the results.The test results for an IRF7401 device demonstrate that the key static and dynamic parameters obtained by the system show ex-cellent agreement with datasheet specifications and simulation values,thus validating the accuracy and feasibility of the proposed solu-tion.This research provides an efficient,intelligent,and portable new method for end-users to evaluate device performance.