Ground-based interferometric synthetic aperture radar(GB-InSAR)can take deformation measurement with a high accuracy.Partition of the GB-InSAR deformation map benefits analyzing the deformation state of the monitoring...Ground-based interferometric synthetic aperture radar(GB-InSAR)can take deformation measurement with a high accuracy.Partition of the GB-InSAR deformation map benefits analyzing the deformation state of the monitoring scene better.Existing partition methods rely on labelled datasets or single deformation feature,and they cannot be effectively utilized in GBInSAR applications.This paper proposes an improved partition method of the GB-InSAR deformation map based on dynamic time warping(DTW)and k-means.The DTW similarities between a reference point and all the measurement points are calculated based on their time-series deformations.Then the DTW similarity and cumulative deformation are taken as two partition features.With the k-means algorithm and the score based on multi evaluation indexes,a deformation map can be partitioned into an appropriate number of classes.Experimental datasets of West Copper Mine are processed to validate the effectiveness of the proposed method,whose measurement points are divided into seven classes with a score of 0.3151.展开更多
The traditional grey incidence degree is mainly based on the distance analysis methods, which is measured by the displacement difference between corresponding points between sequences. When some data of sequences are ...The traditional grey incidence degree is mainly based on the distance analysis methods, which is measured by the displacement difference between corresponding points between sequences. When some data of sequences are missing (inconsistency in the length of the sequences), the only way is to delete the longer sequences or to fill the shorter sequences. Therefore, some uncertainty is introduced. To solve this problem, by introducing three-dimensional grey incidence degree (3D-GID), a novel GID based on the multidimensional dynamic time warping distance (MDDTW distance-GID) is proposed. On the basis of it, the corresponding grey incidence clustering (MDDTW distance-GIC) method is constructed. It not only has the simpler computation process, but also can be applied to the incidence comparison between uncertain multidimensional sequences directly. The experiment shows that MDDTW distance-GIC is more accurate when dealing with the uncertain sequences. Compared with the traditional GIC method, the precision of the MDDTW distance-GIC method has increased nearly 30%.展开更多
传统动态时间规整算法(Dynamic Time Warping,DTW)及其变种算法被广泛应用于多维时间序列的相似性分析,但它们通常只关注单个时间点的信息而忽略了上下文信息,从而很可能匹配两个形状完全不同的点。因此提出一种结合形状特征及其上下文...传统动态时间规整算法(Dynamic Time Warping,DTW)及其变种算法被广泛应用于多维时间序列的相似性分析,但它们通常只关注单个时间点的信息而忽略了上下文信息,从而很可能匹配两个形状完全不同的点。因此提出一种结合形状特征及其上下文的多维DTW算法(Multi-Dimensional Contextual Dynamic Time Warping,MDCDTW)。该算法首先计算多维时间序列的一阶梯度,然后对其进行采样处理,并以多维梯度矩阵表示当前时间点的形状信息及其上下文信息,最后利用DTW求解多维时间序列间的最短匹配路径。为检测算法设计的合理性,对算法进行了定性分析和定量分析,实验结果表明MDC-DTW算法设计是合理的;为检测MDC-DTW的性能,选用5个多维时间序列数据集,并与4个优异的多维DTW算法进行对比实验,实验结果表明MDC-DTW具有较高的准确率和运行效率。展开更多
针对深孔加工质量检测难、效率低和成本高等问题,提出一种基于振动监测信号分割的改进动态时间规整算法,实现深孔加工质量一致性快速无损检测。首先,以啄钻间歇进给式加工采集的振动信号为研究对象,利用抗噪性能优良的双窗双谱算法对其...针对深孔加工质量检测难、效率低和成本高等问题,提出一种基于振动监测信号分割的改进动态时间规整算法,实现深孔加工质量一致性快速无损检测。首先,以啄钻间歇进给式加工采集的振动信号为研究对象,利用抗噪性能优良的双窗双谱算法对其进行分割;其次,对分割信号在时域和频域内进行特征降维;然后,针对信号长度不等引起的特征不等情况,采用改进的动态时间规整算法(dynamic time warping,简称DTW)进行规整对齐,同时达到减小时间复杂度和防止病态规整的目的;最后,利用求得的累积最短距离评估啄钻阶段振动信号的相似性程度,从而判别啄钻加工质量的一致性。仿真和试验结果表明,该方法能快速有效完成对深孔加工质量一致性无损检测,振动信号分析结果与实际物理检测结果相吻合。展开更多
基金supported by the National Natural Science Foundation of China(61971037,61960206009,61601031)the Natural Science Foundation of Chongqing,China(cstc2020jcyj-msxm X0608,cstc2020jcyj-jq X0008)。
文摘Ground-based interferometric synthetic aperture radar(GB-InSAR)can take deformation measurement with a high accuracy.Partition of the GB-InSAR deformation map benefits analyzing the deformation state of the monitoring scene better.Existing partition methods rely on labelled datasets or single deformation feature,and they cannot be effectively utilized in GBInSAR applications.This paper proposes an improved partition method of the GB-InSAR deformation map based on dynamic time warping(DTW)and k-means.The DTW similarities between a reference point and all the measurement points are calculated based on their time-series deformations.Then the DTW similarity and cumulative deformation are taken as two partition features.With the k-means algorithm and the score based on multi evaluation indexes,a deformation map can be partitioned into an appropriate number of classes.Experimental datasets of West Copper Mine are processed to validate the effectiveness of the proposed method,whose measurement points are divided into seven classes with a score of 0.3151.
基金supported by the National Natural Science Foundation of China(6153302061309014)the Natural Science Foundation Project of CQ CSTC(cstc2017jcyj AX0408)
文摘The traditional grey incidence degree is mainly based on the distance analysis methods, which is measured by the displacement difference between corresponding points between sequences. When some data of sequences are missing (inconsistency in the length of the sequences), the only way is to delete the longer sequences or to fill the shorter sequences. Therefore, some uncertainty is introduced. To solve this problem, by introducing three-dimensional grey incidence degree (3D-GID), a novel GID based on the multidimensional dynamic time warping distance (MDDTW distance-GID) is proposed. On the basis of it, the corresponding grey incidence clustering (MDDTW distance-GIC) method is constructed. It not only has the simpler computation process, but also can be applied to the incidence comparison between uncertain multidimensional sequences directly. The experiment shows that MDDTW distance-GIC is more accurate when dealing with the uncertain sequences. Compared with the traditional GIC method, the precision of the MDDTW distance-GIC method has increased nearly 30%.
文摘传统动态时间规整算法(Dynamic Time Warping,DTW)及其变种算法被广泛应用于多维时间序列的相似性分析,但它们通常只关注单个时间点的信息而忽略了上下文信息,从而很可能匹配两个形状完全不同的点。因此提出一种结合形状特征及其上下文的多维DTW算法(Multi-Dimensional Contextual Dynamic Time Warping,MDCDTW)。该算法首先计算多维时间序列的一阶梯度,然后对其进行采样处理,并以多维梯度矩阵表示当前时间点的形状信息及其上下文信息,最后利用DTW求解多维时间序列间的最短匹配路径。为检测算法设计的合理性,对算法进行了定性分析和定量分析,实验结果表明MDC-DTW算法设计是合理的;为检测MDC-DTW的性能,选用5个多维时间序列数据集,并与4个优异的多维DTW算法进行对比实验,实验结果表明MDC-DTW具有较高的准确率和运行效率。
文摘针对深孔加工质量检测难、效率低和成本高等问题,提出一种基于振动监测信号分割的改进动态时间规整算法,实现深孔加工质量一致性快速无损检测。首先,以啄钻间歇进给式加工采集的振动信号为研究对象,利用抗噪性能优良的双窗双谱算法对其进行分割;其次,对分割信号在时域和频域内进行特征降维;然后,针对信号长度不等引起的特征不等情况,采用改进的动态时间规整算法(dynamic time warping,简称DTW)进行规整对齐,同时达到减小时间复杂度和防止病态规整的目的;最后,利用求得的累积最短距离评估啄钻阶段振动信号的相似性程度,从而判别啄钻加工质量的一致性。仿真和试验结果表明,该方法能快速有效完成对深孔加工质量一致性无损检测,振动信号分析结果与实际物理检测结果相吻合。
