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To improve the capability of Fiber Bragg Grating (FBG) sensors in mine safety monitoring systems to address the cross-sensitivity problem of temperature and strain, a high-precision cross-sensitivity decoupling monitoring model was constructed by integrating a dual-grating temperature compensation method and a Gaussian process regression modeling method improved by the particle swarm optimization algorithm. The experimental results indicate that the proposed method outperforms traditional methods in both wavelength shift data fitting and prediction accuracy. The monitoring system achieves high-precision measurement of temperature and strain data in the mine environment, with the minimum monitoring error being only 0.04 mm and the fitting degree R² reaches 0.912. The system realizes high-precision dual-parameter monitoring in the mine environment, where the monitoring accuracy of temperature and strain reaches 0.961, and the data transmission rate increases by 36% compared to photosensitive and electronic sensors. This demonstrates that FBG sensors possess certain advantages in the dimensions of acquisition accuracy and real-time performance. The research results provide a reusable theoretical framework for innovation in mine safety monitoring and lay a methodological foundation for the evolution of intelligent monitoring systems.

, authors=Yanfeng Sheng, authorsList=Yanfeng Sheng, authorCompany=null, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1321895066784871400, articleId=1321895066319303654, tenantId=1146029695717560320, journalId=1225396423026438145, language=CN, title=面向智慧矿山的光纤光栅安全监测与预警模型优化设计, columnId=1226462295946085268, journalTitle=矿业研究与开发, columnName=矿山机电与矿业智能化, runingTitle=null, highlight=null, articleAbstract=

为了提升矿山安全监测系统中FBG传感器对温度和应变交叉敏感问题的解决能力，通过融合双光栅温度补偿法与基于粒子群优化算法改进的高斯过程回归建模方法，构建了高精度交叉敏感解耦监测模型。试验结果表明，所提出的方法在波长漂移数据拟合与预测准确性方面均优于传统方法。监测系统在矿山环境中实现了高精度的温度和应变数据测量，监测误差最低仅为0.04 mm，拟合度R²达到0.912。系统在矿山环境中实现双参量高精度监测，温度/应变的监测准确率达0.961；数据传输速率较光敏/电子传感器提升36%。表明光纤光栅传感器在采集准确率与实时性维度具有一定优势。研究结果为矿山安全监测创新提供了一种可复用的理论架构，并为智能化监测系统演进奠定了方法论基础。

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生艳凤（1982—），女，河北沧州人，高级讲师，主要从事安全技术与管理方面的教学与研究。E-mail:hpym202312@163.com

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生艳凤（1982—），女，河北沧州人，高级讲师，主要从事安全技术与管理方面的教学与研究。E-mail:hpym202312@163.com

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