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To address the problem that low-energy acoustic emission (AE) signals account for an excessively high proportion during the fracture process of water-soaked coal-rock, high-energy critical information to be easily masked, resulting in insufficient accuracy in failure precursor identification, synchronous uniaxial compression and acoustic emission tests were conducted on coal-rock specimens under natural conditions and after 120 h of water-soaked. Based on the energy contribution rate and damage stress, a novel AE signal screening method was developed to extract dominant signals during coal-rock failure and investigate their precursory characteristics. The results show that water-soaked significantly decreases the uniaxial compressive strength of coal-rock. Compared with specimens under natural conditions, the average uniaxial compressive strength of water-soaked coal-rock decreases by 14.79%. Cracks exhibite multidirectional propagation behavior, thereby aggravating the final failure of the coal-rock. The cumulative AE count of coal-rock specimens under natural conditions reach 4×10⁶, while that of water-soaked specimens decrease to 2×10⁶. Moreover, the evolution of the cumulative AE count shows good agreement with the stress-strain behavior of the coal-rock. The AE dominant signal extraction method based on the energy contribution rate and damage-stress time window effectively identifies dominant signals during the failure process of water-soaked coal-rock. Compared with coal-rock under natural conditions, the extracted dominant signals exhibite lower energy thresholds but higher signal proportions. Furthermore, the extracted dominant signals show strong correspondence with the failure precursors of water-soaked coal-rock. These findings provide a theoretical basis for engineering stability prediction.

, authors=Haiyan Su^{1, 2, 3}, Jun Zhu^{1, 2}, Ziming Liu^{1, 2}, Yuanjun Ma⁴, Yong Zhang⁵, authorsList=Haiyan Su, Jun Zhu, Ziming Liu, Yuanjun Ma, Yong Zhang, authorCompany=null, correspAuthors=Jun Zhu, 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=1321893325435687565, articleId=1321893325045617291, tenantId=1146029695717560320, journalId=1225396423026438145, language=CN, title=基于声发射优势信号筛选的浸水煤岩破坏前兆研究, columnId=1226462295417598973, journalTitle=矿业研究与开发, columnName=矿山安全与环保, runingTitle=null, highlight=null, articleAbstract=

针对浸水煤岩破裂过程中低能声发射（AE）信号占比过高、高能关键信息易被掩盖，导致破坏前兆识别精度不足的难题，开展了自然状态与浸水120 h煤岩的单轴压缩与声发射同步试验。基于能量贡献率与损伤应力构建了AE信号筛选新方法，提取煤岩破裂的优势信号并分析其前兆特征。结果表明：浸水显著降低了煤岩的单轴抗压强度，相比自然状态煤岩，浸水煤岩平均单轴抗压强度降低14.79%，裂纹呈现多向扩展特征，加剧了煤岩的最终破裂程度；自然状态煤岩的累计AE计数达到4×10⁶次，而浸水煤岩的累计AE计数降至2×10⁶次，累计AE计数与煤岩的应力-应变曲线具有较好的一致性；基于能量贡献率与损伤应力时间窗口构建的声发射优势信号提取方法，可有效提取浸水煤岩破裂过程中的优势信号，其能量阈值低于自然状态煤岩，但优势信号占比更高，提取的优势信号与浸水煤岩破坏前兆高度一致。研究结果可为工程稳定性预测提供理论依据。

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苏海燕（1997—），女，四川攀枝花人，硕士，主要从事岩石（体）损伤智能监测与量化评估研究。E-mail:suhaiyan@imde.ac.cn

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苏海燕（1997—），女，四川攀枝花人，硕士，主要从事岩石（体）损伤智能监测与量化评估研究。E-mail:suhaiyan@imde.ac.cn

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