为解决因地下水相关因素未考虑充分而导致的模型对地下水位预测不准确的问题,提出观测井的空间位置距离聚类方法、水文地质属性聚类方法和距离-属性混合聚类方法,验证观测井间连通性在地下水位预测中的重要性。设计4种模型并分别对济南...为解决因地下水相关因素未考虑充分而导致的模型对地下水位预测不准确的问题,提出观测井的空间位置距离聚类方法、水文地质属性聚类方法和距离-属性混合聚类方法,验证观测井间连通性在地下水位预测中的重要性。设计4种模型并分别对济南岩溶水域的地下水位进行模拟和预测并与实际观测值对比。预测结果表明:考虑岩溶含水层连通性特征的联合模型ConvLSTM(convolution-long short term memory)要优于传统的长短期记忆网络模型(long short term memory, LSTM)。其中考虑距离-属性混合聚类结果的同类别井(连通性强)的模型(mix-multivariate-convolution-long short term memory, M-MV-ConvLSTM)预测结果精度最高、误差最小,其平均均方根误差约为0.457,纳什效率系数约为0.216,预测准确度高于传统的LSTM预测模型。研究成果可为岩溶水域的实时地下水位预测提供借鉴。展开更多
Based on inspection data,the authors analyze and summarize the main types and distribution characteristics of tunnel structural defects.These defects are classified into three types:surface defects,internal defects,an...Based on inspection data,the authors analyze and summarize the main types and distribution characteristics of tunnel structural defects.These defects are classified into three types:surface defects,internal defects,and defects behind the structure.To address the need for rapid detection of different defect types,the current state of rapid detection technologies and equipment,both domestically and internationally,is systematically reviewed.The research reveals that surface defect detection technologies and equipment have developed rapidly in recent years.Notably,the integration of machine vision and laser scanning technologies have significantly improved detection efficiency and accuracy,achieving crack detection precision of up to 0.1 mm.However,the non-contact rapid detection of internal and behind-the-structure defects remains constrained by hardware limitations,with traditional detection remaining dominant.Nevertheless,phased array radar,ultrasonic,and acoustic vibration detection technologies have become research hotspots in recent years,offering promising directions for detecting these challenging defect types.Additionally,the application of multisensor fusion technology in rapid detection equipment has further enhanced detection capabilities.Devices such as cameras,3D laser scanners,infrared thermal imagers,and radar demonstrate significant advantages in rapid detection.Future research in tunnel inspection should prioritize breakthroughs in rapid detection technologies for internal and behind-the-structure defects.Efforts should also focus on developing multifunctional integrated detection vehicles that can simultaneously inspect both surface and internal structures.Furthermore,progress in fully automated,intelligent systems with precise defect identification and real-time reporting will be essential to significantly improve the efficiency and accuracy of tunnel inspection.展开更多
The wide-field electromagnetic method is widely used in hydrocarbon exploration,mineral deposit detection,and geological disaster prediction.However,apparent resistivity and normalized field amplitude exceeding 2048 H...The wide-field electromagnetic method is widely used in hydrocarbon exploration,mineral deposit detection,and geological disaster prediction.However,apparent resistivity and normalized field amplitude exceeding 2048 Hz often exhibit upward warping in data,making geophysical inversion and interpretation challenging.The cumulative error of the crystal oscillator in signal transmission and acquisition contributes to an upturned apparent resistivity curve.To address this,a high-frequency information extraction method is proposed based on time-domain signal reconstruction,which helps to record a complete current data sequence;moreover,it helps estimate the crystal oscillator error for the transmitted signal.Considering the recorded error,a received signal was corrected using a set of reconstruction algorithms.After processing,the high-frequency component of the wide-field electromagnetic data was not upturned,while accurate high-frequency information was extracted from the signal.Therefore,the proposed method helped effectively extract high-frequency components of all wide-field electromagnetic data.展开更多
文摘为解决因地下水相关因素未考虑充分而导致的模型对地下水位预测不准确的问题,提出观测井的空间位置距离聚类方法、水文地质属性聚类方法和距离-属性混合聚类方法,验证观测井间连通性在地下水位预测中的重要性。设计4种模型并分别对济南岩溶水域的地下水位进行模拟和预测并与实际观测值对比。预测结果表明:考虑岩溶含水层连通性特征的联合模型ConvLSTM(convolution-long short term memory)要优于传统的长短期记忆网络模型(long short term memory, LSTM)。其中考虑距离-属性混合聚类结果的同类别井(连通性强)的模型(mix-multivariate-convolution-long short term memory, M-MV-ConvLSTM)预测结果精度最高、误差最小,其平均均方根误差约为0.457,纳什效率系数约为0.216,预测准确度高于传统的LSTM预测模型。研究成果可为岩溶水域的实时地下水位预测提供借鉴。
文摘Based on inspection data,the authors analyze and summarize the main types and distribution characteristics of tunnel structural defects.These defects are classified into three types:surface defects,internal defects,and defects behind the structure.To address the need for rapid detection of different defect types,the current state of rapid detection technologies and equipment,both domestically and internationally,is systematically reviewed.The research reveals that surface defect detection technologies and equipment have developed rapidly in recent years.Notably,the integration of machine vision and laser scanning technologies have significantly improved detection efficiency and accuracy,achieving crack detection precision of up to 0.1 mm.However,the non-contact rapid detection of internal and behind-the-structure defects remains constrained by hardware limitations,with traditional detection remaining dominant.Nevertheless,phased array radar,ultrasonic,and acoustic vibration detection technologies have become research hotspots in recent years,offering promising directions for detecting these challenging defect types.Additionally,the application of multisensor fusion technology in rapid detection equipment has further enhanced detection capabilities.Devices such as cameras,3D laser scanners,infrared thermal imagers,and radar demonstrate significant advantages in rapid detection.Future research in tunnel inspection should prioritize breakthroughs in rapid detection technologies for internal and behind-the-structure defects.Efforts should also focus on developing multifunctional integrated detection vehicles that can simultaneously inspect both surface and internal structures.Furthermore,progress in fully automated,intelligent systems with precise defect identification and real-time reporting will be essential to significantly improve the efficiency and accuracy of tunnel inspection.
基金Project(42004056)supported by the National Natural Science Foundation of ChinaProject(ZR2020QD052)supported by the Natural Science Foundation of Shandong Province,ChinaProject(2019YFC0604902)supported by the National Key Research and Development Program of China。
文摘The wide-field electromagnetic method is widely used in hydrocarbon exploration,mineral deposit detection,and geological disaster prediction.However,apparent resistivity and normalized field amplitude exceeding 2048 Hz often exhibit upward warping in data,making geophysical inversion and interpretation challenging.The cumulative error of the crystal oscillator in signal transmission and acquisition contributes to an upturned apparent resistivity curve.To address this,a high-frequency information extraction method is proposed based on time-domain signal reconstruction,which helps to record a complete current data sequence;moreover,it helps estimate the crystal oscillator error for the transmitted signal.Considering the recorded error,a received signal was corrected using a set of reconstruction algorithms.After processing,the high-frequency component of the wide-field electromagnetic data was not upturned,while accurate high-frequency information was extracted from the signal.Therefore,the proposed method helped effectively extract high-frequency components of all wide-field electromagnetic data.
