发表机构
Mingyang Smart Energy Co., Ltd.（明阳智慧能源集团股份有限公司）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究工业健康管理中异构信息源集成问题，提出工业令牌化概念及联邦架构，将特定源分析输出转为工业令牌，以实现跨源推理。给出基于振动诊断输出等的端到端诊断令牌路径，定位工业令牌化为语义接口。
AI 中文摘要
工业健康管理越来越依赖于包括状态监测系统、监控与数据采集系统、维护记录、检查结果和预测模型等多种异构信息源。大语言模型虽为跨源推理带来新机遇，但工业数据和分析输出在结构、时间分辨率、物理意义和可靠性上差异很大。本文引入工业令牌化，将特定源分析输出转换为结构化且机器可解释的工业证据单元（工业令牌）。基于此概念提出联邦工业架构，异构分析子系统保持自治并向中央推理层暴露标准化工业令牌。作为初步实现，给出基于振动诊断输出、基于规则的事件聚合、结构化文本令牌生成和基于大语言模型解释的端到端诊断令牌路径，其他工业令牌留作未来扩展。该框架将工业令牌化定位为特定领域工业智能与基于大语言模型或智能体推理之间的语义接口，而非编码原始工业数据的另一种方法。
英文摘要
Industrial health management increasingly relies on heterogeneous information sources, including condition monitoring systems, supervisory control and data acquisition systems, maintenance records, inspection results, and prognostic models. Although large language models provide new opportunities for cross-source reasoning, industrial data and analytical outputs differ substantially in structure, temporal resolution, physical meaning, and reliability. Directly integrating such heterogeneous information into a monolithic model may reduce interpretability, traceability, and adaptability to equipment and data changes. This paper introduces Industrial Tokenization, a conceptual interface for transforming source-specific analytical outputs into structured and machine-interpretable units of industrial evidence, termed Industrial Tokens. Unlike numerical tokens used to encode raw time-series data, Industrial Tokens represent domain-grounded evidence together with source, temporal scope, operating context, analytical meaning, quality or confidence information, and provenance. Based on this concept, a federated industrial architecture is proposed, where heterogeneous analytical subsystems retain autonomy while exposing standardized Industrial Tokens to a central reasoning layer. As an initial implementation, this study presents an end-to-end DiagnosisToken pathway based on vibration-diagnostic outputs, rule-based event aggregation, structured textual token generation, and LLM-based interpretation. Other Industrial Tokens, including SCADA-based condition-monitoring tokens, maintenance tokens, and prognostic tokens, are reserved as future extensions. The proposed framework positions Industrial Tokenization as a semantic interface between domain-specific industrial intelligence and LLM- or agent-based reasoning, rather than another method for encoding raw industrial data.
Comments10 pages, 1 figure
