Adaptability Analysis of Distributed Motor Measurement and Control System Based on Electronic Information Technology

Abstract

In this paper, the adaptability of distributed motor control system in window motor is investigated, aiming at improving the accuracy and efficiency of the system. The accuracy and efficiency of traditional methods are insufficient. Then, intelligent automation systems combining high-precision instruments and advanced algorithms are used to better simulate real-world situations and enhance noise analysis. The research method combines random position control technology and noise analysis mechanism. The experiment is carried out by simulating various working conditions of window motor to measure the rotation angle error, signal acquisition difference, and sound quality change. The results showed that the rotation angle error was less than 2 degrees, the signal acquisition error was less than 0.8%, and the amplitude error was kept below 2%, indicating that the system had good performance and significantly improved the reliability and accuracy of the test. The results showed that the integration of modern electronic information technology and intelligent algorithm significantly improved the adaptability, accuracy, and noise evaluation ability of distributed motor measurement and control system. The paper lays a foundation for the future development of motor test system and suggests further exploration of machine learning model and real-time data processing technology.

Keywords

• BP neural network
• distributed motor
• control system
• random control
• sound quality