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籽棉清理机数字孪生监测系统设计与实现

闫文斌 张若宇 吴超 陈明晓 徐健康 李玉林

农业机械学报2026,Vol.57Issue(4):72-83,12.
农业机械学报2026,Vol.57Issue(4):72-83,12.DOI:10.6041/j.issn.1000-1298.2026.04.008

籽棉清理机数字孪生监测系统设计与实现

Design and Implementation of Digital Twin Monitoring System for Seed Cotton Cleaning Machine

闫文斌 1张若宇 2吴超 2陈明晓 1徐健康 1李玉林1

作者信息

  • 1. 石河子大学机械电气工程学院,石河子 832003||农业农村部西北农业装备重点实验室,石河子 832003
  • 2. 石河子大学机械电气工程学院,石河子 832003||兵团智慧农场数字化装备技术创新中心,石河子 832003
  • 折叠

摘要

Abstract

The seed cotton cleaning machine,as the core of cotton processing,faces operational challenges that limit overall efficiency.These include the inability to monitor equipment status in real time,delayed and passive fault alerts,and loosely defined operation and maintenance strategies during the impurity removal process.Such limitations have constrained further improvements in cotton processing quality,production efficiency,and overall enterprise profitability.To address these issues,digital twin technology was applied to create a virtual replica of the physical seed cotton cleaning machine.Based on a detailed analysis of the machine's operational principles and mechanical structure,a high-fidelity digital twin model was constructed.This model established a dynamic,bidirectional mapping mechanism between the physical machine and its virtual counterpart,enabling seamless data exchange and state synchronization.Using the Unity platform,a comprehensive digital twin monitoring system was developed for the seed cotton cleaning machine.This system integrated real-time data acquisition,simulation,and analysis capabilities.It allowed for real-time monitoring of the machine's operational status,facilitated proactive fault warnings through predictive analytics,and supported dynamic optimization of process decisions based on simulated scenarios.Performance evaluations of the system demonstrated strong stability and reliability with key metrics,including a data packet loss rate of 0,a CPU usage rate of approximately 5%,an average GPU memory occupancy of around 4%,and an average motion simulation frame time of 20.416 ms.The system was verified to possess excellent stability,reliability and robustness.

关键词

数字孪生/籽棉清理机/监测系统/故障预警

Key words

digital twin/seed cotton cleaning machine/monitoring system/fault early warning

分类

农业科技

引用本文复制引用

闫文斌,张若宇,吴超,陈明晓,徐健康,李玉林..籽棉清理机数字孪生监测系统设计与实现[J].农业机械学报,2026,57(4):72-83,12.

基金项目

兵团财政科技计划项目(2020AB006) (2020AB006)

农业机械学报

1000-1298

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