| 汤伟,贺瑜,王孟效,杨雅斐,费旭勇,张诚.基于“418模型”的造纸工业智能化升级的路径探索[J].中国造纸,2026,45(8):112-124 |
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| 基于“418模型”的造纸工业智能化升级的路径探索 |
| Exploration of Intelligent Upgrading Pathways for Paper Industry Based on 418 Model |
| 收稿日期：2026-06-22 修订日期：2026-07-10 |
| DOI：10.11980/j.issn.0254-508X.2026.08.012 |
| 关键词: 418模型 造纸工业 智能化升级 双网络双服务器 人工智能 |
| Key Words:418 Model paper industry intelligent upgrading dual-network dual-server artificial intelligence |
| 基金项目:国家自然科学基金（62073206）。 |
| 作者 | 单位 | 邮编 | | 汤伟* | 1陕西科技大学电气与控制工程学院,陕西西安,710021 | 710021 | | 贺瑜* | 1陕西科技大学电气与控制工程学院,陕西西安,710021 | 710021 | | 王孟效 | 2陕西西微测控工程有限公司,陕西咸阳,712081 | 712081 | | 杨雅斐 | 1陕西科技大学电气与控制工程学院,陕西西安,710021 | 710021 | | 费旭勇 | 3仙鹤股份有限公司,浙江衢州,324000 | 324000 | | 张诚 | 3仙鹤股份有限公司,浙江衢州,324000 | 324000 |
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| 摘要:针对造纸工业智能化升级过程中目标导向、系统架构与智能算法融合不足等问题，本文以“工业4.0”和“418模型”为分析框架，结合造纸工业制浆、造纸和水处理工段的过程特征，阐述计算机集成过程系统（CIPS）的基础功能及其智能化升级要求，提出双网络双服务器（DNDS）智能控制架构的造纸工业控制体系，并探讨人工智能与先进控制技术的应用路径。在该控制体系中，CIPS可为过程控制、生产执行和资源管理集成提供技术基础，但在跨层数据服务、连续运行保障和智能应用承载方面仍需增强；DNDS可通过网络分域、系统冗余和智能服务环境配置，提高数据贯通能力、控制可靠性和算法部署能力；人工智能算法可依托多源数据关联和受控接口，支持状态感知、质量预测、运行优化和在线控制。 |
| Abstract:In this study， aiming at the problem of insufficient integration among goal orientation， system architecture， and intelligent algorithms during the intelligent upgrading of paper industry， the basic functions of computer integrated process system (CIPS) and its intelligent upgrading requirements were described， combining with the characteristics of pulping， papermaking， and water treatment processes in paper enterprises， with ‘Industry 4.0’ and the ‘418 Model’ as the analytical framework. The dual-network dual-server (DNDS) intelligent control architecture was proposed to introduce to paper industry control system， and the application paths of artificial intelligence and advanced control technology were discussed. In the control system， CIPS could provide a technical foundation for the integration of process control， production execution， and resource management， but needed to be enhanced in terms of cross-layer data services， continuous operation assurance， and intelligent application hosting. DNDS could improve data connectivity， control reliability， and algorithm deployment capabilities through network partitioning， system redundancy， and intelligent service environment configuration. Artificial intelligence algorithms could rely on multi-source data correlation and controlled interfaces to serve for state perception， quality prediction， operation optimization， and online control. |
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