Online Diagnosis of Thermal Performance of Insulation Materials Based on Edge Computing
基于边缘计算的保温材料热工性能在线诊断

摘要

建筑与工业设备保温材料长期服役过程中，易受环境侵蚀、结构老化、施工缺陷影响出现热工性能衰减，传统离 线抽检、云端集中诊断模式存在滞后性、实时性差、现场适配度低等问题，难以满足常态化、精细化运维需求。本文 依托边缘计算技术架构，结合保温材料传热特性与现场运行工况，构建本地化、低延迟的热工性能在线诊断体系，重 点阐述边缘计算赋能保温材料性能诊断的核心优势、系统架构搭建、关键诊断逻辑及工程落地应用路径，解决传统检 测方式依赖人工、数据传输冗余、故障响应滞后等行业痛点，实现保温材料热工缺陷实时识别、性能状态动态研判、 隐患问题即时预警，为建筑节能、工业设备保温运维提供智能化落地方案。 

Abstract

During long-term service in buildings and industrial equipment, insulation materials are prone to thermal performance degradation due to environmental erosion, structural aging, and construction defects. Traditional offline sampling inspection and cloud-based centralized diagnosis models suffer from delays, poor real-time performance, and low on-site adaptability, making it difficult to meet the needs of normalized and refined operation and maintenance. Based on an edge computing technology architecture, this paper combines the heat transfer characteristics of insulation materials with on-site operating conditions to construct a localized, low-latency online diagnosis system for thermal performance. It focuses on the core advantages of edge computing in empowering insulation material performance diagnosis, system architecture construction, key diagnostic logic, and engineering application paths. The proposed system addresses industry pain points such as reliance on manual inspection, redundant data transmission, and delayed fault response in traditional detection methods. It realizes real-time identification of thermal defects in insulation materials, dynamic assessment of performance status, and immediate early warning of hidden risks, providing an intelligent implementation solution for building energy conservation and insulation operation and maintenance of industrial equipment.