研究层室温的虚拟收集方法,以满足数字双胞胎系统的施工要求
Yuchen Jia1, Lihua Li2, Liai Gao1
1Hebei Agricultural University, Baoding, Hebei 071000, China; Key Laboratory of Intelligent Equipment and New Energy Utilization in Livestock and Poultry Farming of Hebei Province, Baoding, Hebei 071000, China.
Poultry science
|January 9, 2025
概括
一种新的虚拟获取方法使用历史数据和参考点为畜牧场创建数字双胞胎系统. 这种方法可以减少传感器网络的拥堵,并确保可靠的温度数据收集.
科学领域:
- 农业工程 农业工程
- 数字系统 数字系统
- 环境监测 环境监测
背景情况:
- 强化畜牧和家禽养殖需要先进的数字管理和数字双胞胎系统.
- 传感器网络的拥堵对这些系统的实时数据采集构成了重大挑战.
- 准确的环境数据对于优化牲畜住房条件至关重要.
研究的目的:
- 为数字双胞胎系统提出一种新的虚拟采集方法,以克服传感器网络的局限性.
- 准确预测畜牧设施未被监控区域的环境数据.
- 为了降低数据采集成本并提高数字双胞胎建模的效率.
主要方法:
- 计算流体动力学 (CFD) 模拟用于分析层房内的温度分布和环境特征.
- 灰色相关度和共弦相似度分析被用来确定与未监测区域高度相关的关键参考点.
- 为虚拟数据采集,开发了一种由鱼优化算法 (WOA) 优化的双向长期短期内存 (BiLSTM) 模型,与 XGBoost 算法集成.
主要成果:
- WOA-BiLSTM模型成功预测了虚拟收集点中的温度值.
- 实地测试表明,虚拟和实际数据之间的平均绝对误差小于0.25°C.
- 该研究分析了数据量需求,证实了虚拟收集在数字双胞胎构建中的支持作用.
结论:
- 拟议的虚拟采集方法有效地解决了畜牧业数字双胞胎系统中的传感器网络拥堵问题.
- WOA-BiLSTM模型提供了一种可靠和准确的方法来预测环境数据,确保数据完整性.
- 虚拟数据收集是支持农业数字双胞胎系统的开发和可扩展性的可行策略.
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