To address the low-resolution imaging problem in relation to traditional Range Doppler(RD)algorithm,this paper intends to propose a new algorithm based on Fractional Fourier Transform(FrFT),which proves highly advanta...To address the low-resolution imaging problem in relation to traditional Range Doppler(RD)algorithm,this paper intends to propose a new algorithm based on Fractional Fourier Transform(FrFT),which proves highly advantageous in the acquisition of high-resolution Synthetic Aperture Radar(SAR)images.The expression of the optimal order of SAR range signals using FrFT is deduced in detail,and the corresponding expression of the azimuth signal is also given.Theoretical analysis shows that,the optimal order in range(azimuth)direction,which turns out to be very unique,depends on the known imaging parameters of SAR,therefore the engineering practicability of FrFT-RD algorithm can be greatly improved without the need of order iteration.The FrFT-RD algorithm is established after an analysis of the optimal time-frequency transform.Experimental results demonstrate that,compared with traditional RD algorithm,the main-lobe width of the peak-point target of FrFT-RD algorithm is narrow in both range and azimuth directions.While the peak amplitude of the first side-lobe is reduced significantly,those of other side-lobes also drop in various degrees.In this way,the imaging resolution of range and azimuth can be increased considerably.展开更多
Arrhythmias are a frequently occurring phenomenon in clinical practice,but how to accurately dis-tinguish subtle rhythm abnormalities remains an ongoing difficulty faced by the entire research community when conductin...Arrhythmias are a frequently occurring phenomenon in clinical practice,but how to accurately dis-tinguish subtle rhythm abnormalities remains an ongoing difficulty faced by the entire research community when conducting ECG-based studies.From a review of existing studies,two main factors appear to contribute to this problem:the uneven distribution of arrhythmia classes and the limited expressiveness of features learned by current models.To overcome these limitations,this study proposes a dual-path multimodal framework,termed DM-EHC(Dual-Path Multimodal ECG Heartbeat Classifier),for ECG-based heartbeat classification.The proposed framework links 1D ECG temporal features with 2D time–frequency features.By setting up the dual paths described above,the model can process more dimensions of feature information.The MIT-BIH arrhythmia database was selected as the baseline dataset for the experiments.Experimental results show that the proposed method outperforms single modalities and performs better for certain specific types of arrhythmias.The model achieved mean precision,recall,and F1 score of 95.14%,92.26%,and 93.65%,respectively.These results indicate that the framework is robust and has potential value in automated arrhythmia classification.展开更多
Existing elevator fault diagnosis algorithms have limited engineering applicability due to variations in working conditions and differences in equipment structures.To address this limitation,this study proposes an uns...Existing elevator fault diagnosis algorithms have limited engineering applicability due to variations in working conditions and differences in equipment structures.To address this limitation,this study proposes an unsupervised subdomain adaptation method based on a time-frequency feature attention mechanism,LMMD-based subdomain alignment,and contrastive local alignment.This enables the application of the diagnosis model across different working conditions and equipment types.First,a novel time-frequency feature attention mechanism assigns weights to vibration signals of varying dimensions.Second,the time series is transformed to obtain a three-channel time-frequency diagram.This diagram is input into the proposed dimension-segmentation cross-channel multihead self-attention framework to extract high-dimensional frequencydomain fault features.These features are concatenated with the time-domain features to obtain a global feature representation.Then,the extracted high-dimensional features are sent to the classification module to obtain the predicted labels for the source and target domains.Finally,after confidence filtering,the true labels from the source domain and the prediction labels from the target domain are fed into a dynamically weighted multilevel feature alignment module to promote proximity between similar fault features across domains while enhancing separation among different fault types.The validity and superiority of the proposed method were demonstrated through simulation experiments conducted on two types of manned escalator systems under multiple working conditions.For the most challenging transfer task,the proposed method achieved higher accuracy on the target domain test set than DANN,ADDA,C-CLCN,TFA-CCN,and TFA-LCN by 26.87%,24.72%,11.44%,28.94%,and 16.85%,respectively.展开更多
Quantitative detection of sleeve grouting compactness is a technical challenge in civil engineering testing.This study explores a novel quantitative detection method based on ultrasonic time-frequency dual-domain anal...Quantitative detection of sleeve grouting compactness is a technical challenge in civil engineering testing.This study explores a novel quantitative detection method based on ultrasonic time-frequency dual-domain analysis.It establishes a mapping relationship between sleeve grouting compactness and characteristic parameters.First,this study made samples with gradient defects for two types of grouting sleeves,G18 and G20.These included four cases:2D,4D,6D defects(where D is the diameter of the grouting sleeve),and no-defect.Then,an ultrasonic input/output data acquisition system was established.Three-dimensional sound field distribution data were obtained through an orthogonal detection layout and pulse reflection principles.Finally,a novel quantification detection with a comprehensive defect index(DI)was established by comprehensively considering eight feature parameters,such as time-frequency domain Kurtosis factor(KU),Skewness factor(SK),Formfactor(FF),Crest factor(CF),Impulse factor(IF),Clearance factor(CLF),Wavelet packet energy entropy(WPEE),and Hilbert energy peak(HEP).Construct a DI index by quantifying the difference between defect signals and defect free signals in the time-frequency domain.Experimental results show that,under no-defect conditions,the values of feature parameters are significantly lower than those under defect conditions.Among these,the KU,FF,CF,WPEE and HEP exhibit strong correlations with grout sleeve compactness.The proposed DI index in both types of grout sleeves showed good universality with a linear fit goodness of 0.847–0.962.However,G20 the larger inner diameter and length of the sleeve result in a more complex medium effect during ultrasonic propagation,making its DI index more sensitive to defects than the G18 sleeve.Therefore,the presented method is effective for quantitative detection and analysis of the compactness of grouting sleeves.展开更多
The ground roll and body wave usually show significant differences in arrival time, frequency content, and polarization characteristics, and conventional polarization filters that operate in either the time or frequen...The ground roll and body wave usually show significant differences in arrival time, frequency content, and polarization characteristics, and conventional polarization filters that operate in either the time or frequency domain cannot consider all these elements. Therefore, we have developed a time-frequency dependent polarization filter based on the S transform to attenuate the ground roll in seismic records. Our approach adopts the complex coefficients of the S transform of the multi-component seismic data to estimate the local polarization attributes and utilizes the estimated attributes to construct the filter function. In this study, we select the S transform to design this polarization filter because its scalable window length can ensure the same number of cycles of a Fourier sinusoid, thereby rendering more precise estimation of local polarization attributes. The results of applying our approach in synthetic and real data examples demonstrate that the proposed polarization filter can effectively attenuate the ground roll and successfully preserve the body wave.展开更多
In this paper, it is described that the time-frequency resolution of geophysical signals is affected by the time window function attenuation coefficient and sampling interval and how such effects are eliminated effect...In this paper, it is described that the time-frequency resolution of geophysical signals is affected by the time window function attenuation coefficient and sampling interval and how such effects are eliminated effectively. Improving the signal resolution is the key to signal time-frequency analysis processing and has wide use in geophysical data processing and extraction of attribute parameters. In this paper, authors research the effects of the attenuation coefficient choice of the Gabor transform window function and sampling interval on signal resolution. Unsuitable parameters not only decrease the signal resolution on the frequency spectrum but also miss the signals. It is essential to first give the optimum window and range of parameters through time-frequency analysis simulation using the Gabor transform. In the paper, the suggestions about the range and choice of the optimum sampling interval and processing methods of general seismic signals are given.展开更多
针对地图综合中建筑多边形化简方法依赖人工规则、自动化程度低且难以利用已有化简成果的问题,本文提出了一种基于Transformer机制的建筑多边形化简模型。该模型首先把建筑多边形映射至一定范围的网格空间,将建筑多边形的坐标串表达为...针对地图综合中建筑多边形化简方法依赖人工规则、自动化程度低且难以利用已有化简成果的问题,本文提出了一种基于Transformer机制的建筑多边形化简模型。该模型首先把建筑多边形映射至一定范围的网格空间,将建筑多边形的坐标串表达为网格序列,从而获取建筑多边形化简前后的Token序列,构建出建筑多边形化简样本对数据;随后采用Transformer架构建立模型,基于样本数据利用模型的掩码自注意力机制学习点序列之间的依赖关系,最终逐点生成新的简化多边形,从而实现建筑多边形的化简。在训练过程中,模型使用结构化的样本数据,设计了忽略特定索引的交叉熵损失函数以提升化简质量。试验设计包括主试验与泛化验证两部分。主试验基于洛杉矶1∶2000建筑数据集,分别采用0.2、0.3和0.5 mm 3种网格尺寸对多边形进行编码,实现了目标比例尺为1∶5000与1∶10000的化简。试验结果表明,在0.3 mm的网格尺寸下模型性能最优,验证集上的化简结果与人工标注的一致率超过92.0%,且针对北京部分区域的建筑多边形数据的泛化试验验证了模型的迁移能力;与LSTM模型的对比分析显示,在参数规模相近的条件下,LSTM模型无法形成有效收敛,并生成可用结果。本文证实了Transformer在处理空间几何序列任务中的潜力,且能够有效复用已有化简样本,为智能建筑多边形化简提供了具有工程实用价值的途径。展开更多
基金supported by the 13th Five-Year Plan for Jiangsu Education Science(D/2020/01/22)JSPIGKZ(JSPI19GKZL405)Natural Science Research Projects of Colleges and Universities in Jiangsu Province(19KJB510022).
文摘To address the low-resolution imaging problem in relation to traditional Range Doppler(RD)algorithm,this paper intends to propose a new algorithm based on Fractional Fourier Transform(FrFT),which proves highly advantageous in the acquisition of high-resolution Synthetic Aperture Radar(SAR)images.The expression of the optimal order of SAR range signals using FrFT is deduced in detail,and the corresponding expression of the azimuth signal is also given.Theoretical analysis shows that,the optimal order in range(azimuth)direction,which turns out to be very unique,depends on the known imaging parameters of SAR,therefore the engineering practicability of FrFT-RD algorithm can be greatly improved without the need of order iteration.The FrFT-RD algorithm is established after an analysis of the optimal time-frequency transform.Experimental results demonstrate that,compared with traditional RD algorithm,the main-lobe width of the peak-point target of FrFT-RD algorithm is narrow in both range and azimuth directions.While the peak amplitude of the first side-lobe is reduced significantly,those of other side-lobes also drop in various degrees.In this way,the imaging resolution of range and azimuth can be increased considerably.
基金supported by the Innovative Human Resource Development for Local Intel-lectualization program through the Institute of Information&Communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(No.IITP-2026-2020-0-01741)the research fund of Hanyang University(HY-2025-1110).
文摘Arrhythmias are a frequently occurring phenomenon in clinical practice,but how to accurately dis-tinguish subtle rhythm abnormalities remains an ongoing difficulty faced by the entire research community when conducting ECG-based studies.From a review of existing studies,two main factors appear to contribute to this problem:the uneven distribution of arrhythmia classes and the limited expressiveness of features learned by current models.To overcome these limitations,this study proposes a dual-path multimodal framework,termed DM-EHC(Dual-Path Multimodal ECG Heartbeat Classifier),for ECG-based heartbeat classification.The proposed framework links 1D ECG temporal features with 2D time–frequency features.By setting up the dual paths described above,the model can process more dimensions of feature information.The MIT-BIH arrhythmia database was selected as the baseline dataset for the experiments.Experimental results show that the proposed method outperforms single modalities and performs better for certain specific types of arrhythmias.The model achieved mean precision,recall,and F1 score of 95.14%,92.26%,and 93.65%,respectively.These results indicate that the framework is robust and has potential value in automated arrhythmia classification.
基金supported by the National Natural Science Foundation of China(Grant Nos.52375255,51935007)the Shanghai Rising-Star Program(Grant No.24QB2705000)。
文摘Existing elevator fault diagnosis algorithms have limited engineering applicability due to variations in working conditions and differences in equipment structures.To address this limitation,this study proposes an unsupervised subdomain adaptation method based on a time-frequency feature attention mechanism,LMMD-based subdomain alignment,and contrastive local alignment.This enables the application of the diagnosis model across different working conditions and equipment types.First,a novel time-frequency feature attention mechanism assigns weights to vibration signals of varying dimensions.Second,the time series is transformed to obtain a three-channel time-frequency diagram.This diagram is input into the proposed dimension-segmentation cross-channel multihead self-attention framework to extract high-dimensional frequencydomain fault features.These features are concatenated with the time-domain features to obtain a global feature representation.Then,the extracted high-dimensional features are sent to the classification module to obtain the predicted labels for the source and target domains.Finally,after confidence filtering,the true labels from the source domain and the prediction labels from the target domain are fed into a dynamically weighted multilevel feature alignment module to promote proximity between similar fault features across domains while enhancing separation among different fault types.The validity and superiority of the proposed method were demonstrated through simulation experiments conducted on two types of manned escalator systems under multiple working conditions.For the most challenging transfer task,the proposed method achieved higher accuracy on the target domain test set than DANN,ADDA,C-CLCN,TFA-CCN,and TFA-LCN by 26.87%,24.72%,11.44%,28.94%,and 16.85%,respectively.
基金supported in part by the National Natural Science Foundation of China Grant 11962006the Natural Science Foundation of Jiangxi Province of China Grant 20232BAB204067.
文摘Quantitative detection of sleeve grouting compactness is a technical challenge in civil engineering testing.This study explores a novel quantitative detection method based on ultrasonic time-frequency dual-domain analysis.It establishes a mapping relationship between sleeve grouting compactness and characteristic parameters.First,this study made samples with gradient defects for two types of grouting sleeves,G18 and G20.These included four cases:2D,4D,6D defects(where D is the diameter of the grouting sleeve),and no-defect.Then,an ultrasonic input/output data acquisition system was established.Three-dimensional sound field distribution data were obtained through an orthogonal detection layout and pulse reflection principles.Finally,a novel quantification detection with a comprehensive defect index(DI)was established by comprehensively considering eight feature parameters,such as time-frequency domain Kurtosis factor(KU),Skewness factor(SK),Formfactor(FF),Crest factor(CF),Impulse factor(IF),Clearance factor(CLF),Wavelet packet energy entropy(WPEE),and Hilbert energy peak(HEP).Construct a DI index by quantifying the difference between defect signals and defect free signals in the time-frequency domain.Experimental results show that,under no-defect conditions,the values of feature parameters are significantly lower than those under defect conditions.Among these,the KU,FF,CF,WPEE and HEP exhibit strong correlations with grout sleeve compactness.The proposed DI index in both types of grout sleeves showed good universality with a linear fit goodness of 0.847–0.962.However,G20 the larger inner diameter and length of the sleeve result in a more complex medium effect during ultrasonic propagation,making its DI index more sensitive to defects than the G18 sleeve.Therefore,the presented method is effective for quantitative detection and analysis of the compactness of grouting sleeves.
基金supported by the National Science and Technology Major Project of China(Grant No.2011ZX05014 and 2011ZX05008-005)
文摘The ground roll and body wave usually show significant differences in arrival time, frequency content, and polarization characteristics, and conventional polarization filters that operate in either the time or frequency domain cannot consider all these elements. Therefore, we have developed a time-frequency dependent polarization filter based on the S transform to attenuate the ground roll in seismic records. Our approach adopts the complex coefficients of the S transform of the multi-component seismic data to estimate the local polarization attributes and utilizes the estimated attributes to construct the filter function. In this study, we select the S transform to design this polarization filter because its scalable window length can ensure the same number of cycles of a Fourier sinusoid, thereby rendering more precise estimation of local polarization attributes. The results of applying our approach in synthetic and real data examples demonstrate that the proposed polarization filter can effectively attenuate the ground roll and successfully preserve the body wave.
基金This work was funded by National Natural Science Foundation of China-（No. 40474044）.
文摘In this paper, it is described that the time-frequency resolution of geophysical signals is affected by the time window function attenuation coefficient and sampling interval and how such effects are eliminated effectively. Improving the signal resolution is the key to signal time-frequency analysis processing and has wide use in geophysical data processing and extraction of attribute parameters. In this paper, authors research the effects of the attenuation coefficient choice of the Gabor transform window function and sampling interval on signal resolution. Unsuitable parameters not only decrease the signal resolution on the frequency spectrum but also miss the signals. It is essential to first give the optimum window and range of parameters through time-frequency analysis simulation using the Gabor transform. In the paper, the suggestions about the range and choice of the optimum sampling interval and processing methods of general seismic signals are given.
文摘针对地图综合中建筑多边形化简方法依赖人工规则、自动化程度低且难以利用已有化简成果的问题,本文提出了一种基于Transformer机制的建筑多边形化简模型。该模型首先把建筑多边形映射至一定范围的网格空间,将建筑多边形的坐标串表达为网格序列,从而获取建筑多边形化简前后的Token序列,构建出建筑多边形化简样本对数据;随后采用Transformer架构建立模型,基于样本数据利用模型的掩码自注意力机制学习点序列之间的依赖关系,最终逐点生成新的简化多边形,从而实现建筑多边形的化简。在训练过程中,模型使用结构化的样本数据,设计了忽略特定索引的交叉熵损失函数以提升化简质量。试验设计包括主试验与泛化验证两部分。主试验基于洛杉矶1∶2000建筑数据集,分别采用0.2、0.3和0.5 mm 3种网格尺寸对多边形进行编码,实现了目标比例尺为1∶5000与1∶10000的化简。试验结果表明,在0.3 mm的网格尺寸下模型性能最优,验证集上的化简结果与人工标注的一致率超过92.0%,且针对北京部分区域的建筑多边形数据的泛化试验验证了模型的迁移能力;与LSTM模型的对比分析显示,在参数规模相近的条件下,LSTM模型无法形成有效收敛,并生成可用结果。本文证实了Transformer在处理空间几何序列任务中的潜力,且能够有效复用已有化简样本,为智能建筑多边形化简提供了具有工程实用价值的途径。
