Intelligent self-adaptive tractor PTO loading system based on machine learning and control method

Through the intelligent adaptive tractor PTO loading system based on machine learning, the problem that traditional testing methods cannot fully simulate the actual working conditions is solved, and multi-dimensional loading and dynamic control of tractor PTO is realized, which improves the accuracy and reliability of the test, and provides a sufficient basis for optimizing design and reliable operation.

CN120160828APending Publication Date: 2025-06-17HENAN UNIV OF SCI & TECH
0 Cites 0 Cited by

Patent Information

Application Number
CN202510322168.2
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-03-19
Publication Date
2025-06-17

AI Technical Summary

Technical Problem

The traditional tractor PTO performance testing method cannot fully simulate the various load conditions of the tractor under actual complex working conditions, resulting in untrue test results and cannot provide sufficient basis for optimized design and reliable operation.

Method used

The intelligent adaptive tractor PTO loading system based on machine learning is adopted. Through the loading device module, sensor module, control system module, machine learning module, upper computer and human-computer interaction module, multi-dimensional loading and dynamic control of the tractor is realized, and the actual operating process in the field is simulated.

Benefits of technology

Accurate simulation of tractor PTO is achieved, the accuracy and reliability of the test are improved, and the performance of the tractor can be truly reflected, providing a sufficient basis for optimized design and reliable operation.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

The invention relates to an intelligent self-adaptive tractor PTO loading system based on machine learning and a control method, and aims to solve the problem that a traditional tractor PTO test method cannot comprehensively simulate actual complex working conditions. The system is composed of a loading device module, a sensor module, a control system module, a machine learning module, an upper computer and a man-machine interaction module. Through the multi-dimensional loading device, various loads such as vibration, temperature, humidity and torque can be applied at the same time, and complex stress conditions and environmental factors of the tractor in actual operation are comprehensively simulated. The system adopts a machine learning algorithm, and dynamically adjusts loading parameters according to the real-time operation state of the tractor. And the upper computer realizes remote monitoring and data analysis of the test process through a wireless communication technology. The system has the advantages of improving test precision, response speed and test safety, comprehensively simulating actual working conditions and the like, and provides sufficient basis for optimization design and reliable operation of the tractor.
Need to check novelty before this filing date? Find Prior Art