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作 者:王婷婷[1,2] 徐华一 赵万春[3,4] 刘永胜 何增军[6] WANG Tingting;XU Huayi;ZHAO Wanchun;LIU Yongsheng;HE Zengjun(School of Electrical Engineering&Information,Northeast Petroleum University,Daqing 163318,China;Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control,Northeast Petroleum University,Daqing 163318,China;School of Petroleum Engineering,Northeast Petroleum University,Daqing 163318,China;Key Laboratory of Continental Shale Hydrocarbon Accumulation and Efficient Development,Ministry of Education,Northeast Petroleum University,Daqing 163318,China;Qian′an Oil Production Plant,Jilin Oilfield Company,PetroChina Company Limited,Songyuan 138000,China;Fuyu Oil Production Plant,Jilin Oilfield Company,PetroChina Company Limited,Songyuan 138000,China)
机构地区:[1]东北石油大学电气信息工程学院,黑龙江大庆163318 [2]东北石油大学黑龙江省网络与智能控制重点实验室,黑龙江大庆163318 [3]东北石油大学石油工程学院,黑龙江大庆163318 [4]东北石油大学陆相页岩油气成藏及高效开发教育部重点实验室,黑龙江大庆163318 [5]中国石油天然气股份有限公司吉林油田分公司乾安采油厂,吉林松原138000 [6]中国石油天然气股份有限公司吉林油田分公司扶余采油厂,吉林松原138000
出 处:《采矿与岩层控制工程学报》2024年第4期150-166,共17页Journal of Mining and Strata Control Engineering
基 金:国家自然科学基金资助项目(52174022,52074088);2020年度东北石油大学西部油田开拓专项资助项目(XBYTKT202001);黑龙江省博士后科研启动资助项目(LBH-Q21086);黑龙江省省属高校基本科研业务费:控制科学与工程团队专项资助项目(2022TSTD-04);黑龙江省“揭榜挂帅”科技攻关资助项目(DQYT-2022-JS-758);低渗透油气田勘探开发国家工程实验室2023年度开放课题(鄂尔多斯盆地西缘钻井提速技术攻关研究)资助项目。
摘 要:针对岩石破裂过程中产生的声发射(AE)信号夹杂大量噪声的问题,提出了一种基于斑马优化算法(ZOA)改进变分模态分解(VMD)并与改进的自适应小波阈值(IAWT)联合的声发射信号降噪算法。利用ZOA算法优选出影响VMD分解效果的模态个数K和二次惩罚因子α;通过相关系数将分解出的IMFs划分为有效分量、含噪分量和剔除分量;针对小波阈值(WT)降噪算法不具备自动调整小波基以及软、硬阈值函数存在偏差大和不连续的弊端,提出了IAWT算法去除IMFs中的噪声分量,并与有效分量合并重构,得到降噪后的AE信号。通过模拟和实测AE信号验证并与现有降噪算法对比,结果表明ZOA-VMD-IAWT降噪算法适合处理AE信号,信号的时频特征得以保留。研究结果可为岩石AE信号理论及实际工程应用提供参考。Aiming at the problem that acoustic emission(AE)signal generated in rock fracturing process contains a lot of noise,an acoustic emission(AE)signal noise reduction algorithm with the variational mode decomposition(VMD)and the improved adaptive wavelet threshold(IAWT)is proposed based on zebra optimization algorithm(ZOA).Using ZOA algorithm,the number of modes(K)and quadratic penalty factors(α)that affect the decomposition effect of VMD are selected.The decomposed IMFs are divided into effective,noisy and excluded components by correlation coefficient.In view of the shortcomings of the wavelet threshold(WT)denoising algorithm,which does not automatically adjust the wavelet basis and the large deviation and discontinuity of the soft and hard threshold functions,this paper proposes an IAWT algorithm to remove the noise component in IMFs and then the denoised AE signal is reconstructed with the effective component.Through the verification of simulated and measured AE signals and the comparison with existing denoising algorithms,the results show that the proposed noise reduction algorithm is suitable for processing AE signals,and the time-frequency characteristics of the signal can be retained.The research can provide a reference for AE signal theory and practical engineering applications.
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