Pinhole corrosion is difficult to discover through conventional ultrasonic guided waves inspection,particularly for micro-sized pinholes less than 1 mm in diameter.This study proposes a new micro-sized pinhole inspect...Pinhole corrosion is difficult to discover through conventional ultrasonic guided waves inspection,particularly for micro-sized pinholes less than 1 mm in diameter.This study proposes a new micro-sized pinhole inspection method based on segmented time reversal(STR)and high-order modes cluster(HOMC)Lamb waves.First,the principle of defect echo enhancement using STR is introduced.Conventional and STR inspection experiments were conducted on aluminum plates with a thickness of 3 mm and defects with different diameters and depths.The parameters of the segment window are discussed in detail.The results indicate that the proposed method had an amplitude four times larger than of conventional ultrasonic guided waves inspection method for pinhole defect detection and could detect micro-sized pinhole defects as small as 0.5 mm in diameter and 0.5 mm in depth.Moreover,the segment window location and width(5-10 times width of the conventional excitation signal)did not affect the detection sensitivity.The combination of low-power and STR is more conducive to detection in different environments,indicating the robustness of the proposed method.Compared with conventional ultrasonic guided wave inspection methods,the proposed method can detect much smaller defect echoes usually obscured by noise that are difficult to detect with a lower excitation power and thus this study would be a good reference for pinhole defect detection.展开更多
Time series segmentation has attracted more interests in recent years,which aims to segment time series into different segments,each reflects a state of the monitored objects.Although there have been many surveys on t...Time series segmentation has attracted more interests in recent years,which aims to segment time series into different segments,each reflects a state of the monitored objects.Although there have been many surveys on time series segmentation,most of them focus more on change point detection(CPD)methods and overlook the advances in boundary detection(BD)and state detection(SD)methods.In this paper,we categorize time series segmentation methods into CPD,BD,and SD methods,with a specific focus on recent advances in BD and SD methods.Within the scope of BD and SD,we subdivide the methods based on their underlying models/techniques and focus on the milestones that have shaped the development trajectory of each category.As a conclusion,we found that:(1)Existing methods failed to provide sufficient support for online working,with only a few methods supporting online deployment;(2)Most existing methods require the specification of parameters,which hinders their ability to work adaptively;(3)Existing SD methods do not attach importance to accurate detection of boundary points in evaluation,which may lead to limitations in boundary point detection.We highlight the ability to working online and adaptively as important attributes of segmentation methods,the boundary detection accuracy as a neglected metrics for SD methods.展开更多
Multi-components sinusoidal engineering signals who are non-stationary signals were considered in this study since their separation and segmentations are of great interests in many engineering fields. In most cases, t...Multi-components sinusoidal engineering signals who are non-stationary signals were considered in this study since their separation and segmentations are of great interests in many engineering fields. In most cases, the segmentation of non-stationary or multi-component signals is conducted in time domain. In this paper, we explore the advantages of applying joint time-frequency (TF) distribution of the multi-component signals to identify their segments. The Spectrogram that is known as Short-Time Fourier Transform (STFT) will be used for obtaining the time-frequency kernel. Time marginal of the computed kernel is optimally used for the signal segmentation. In order to obtain the desirable segmentation, it requires first to improve time marginal of the kernel by using two-dimensional Wiener mask filter applied to the TF kernel to mitigate and suppress non-stationary noise or interference. Additionally, a proper choice of the sliding window and its overlaying has enhanced our scheme to capture the discontinuities corresponding to the boundaries of the candidate segments.展开更多
By computing and classifying the data of gully offset obtained from field surveys along the Tianjingshan fault zone and estimating the ages of three types of gullies,the strike-slip rates along the fault zone are disc...By computing and classifying the data of gully offset obtained from field surveys along the Tianjingshan fault zone and estimating the ages of three types of gullies,the strike-slip rates along the fault zone are discussed in different time intervals and fault segments.The results suggest that the intensity of activity along the fault zone is not strong,but the differences between different time intervals and fault segments since the late Pleistocene have been obvious.The average rates range from 0.23 mm/a to 1.62 mm/a.The largest average rate is 1.40 mm/a,which occurred in the early and middle of late Pleistocene along the western segment of the fault zone.Since the late stage of the late Pleistocene,the center of faulting activity of the fault zone has shifted to the middle segment,and the average slip rates range have changed from 1.30 mm/a to 1.63 mm/a.展开更多
Patterned-based time series segmentation (PTSS) is an important task for many time series data mining applications. In this paper, according to the characteristics of PTSS, a generalized model is proposed for PTSS. Fi...Patterned-based time series segmentation (PTSS) is an important task for many time series data mining applications. In this paper, according to the characteristics of PTSS, a generalized model is proposed for PTSS. First, a new inter-pretation for PTSS is given by comparing this problem with the prototype-based clustering (PC). Then, a novel model, called clustering-inverse model (CI-model), is presented. Finally, two algorithms are presented to implement this model. Our experimental results on artificial and real-world time series demonstrate that the proposed algorithms are quite effective.展开更多
In this study, we propose a novel discrete-time coupled model to generate oscillatory responses via periodic points with a high periodic order. Our coupled system comprises one-dimensional oscillators based on the Rul...In this study, we propose a novel discrete-time coupled model to generate oscillatory responses via periodic points with a high periodic order. Our coupled system comprises one-dimensional oscillators based on the Rulkov map and a single globally coupled oscillator. Because the waveform of a one-dimensional oscillator has sharply defined peaks, the coupled system can be applied to dynamic image segmentation. Our proposed system iteratively transforms the coupling of each oscillator based on an input value that corresponds to the pixel value of an input image. This approach enables our system to segment image regions in which pixel values gradually change with respect to a connected region. We conducted a bifurcation analysis of a single oscillator and a three-coupled model. Through simulations, we demonstrated that our system works well for gray-level images with three isolated image regions.展开更多
基金National Natural Science Foundation of China(Grant No.62071433)National Key R&D Program of China(Grant No.2022YFC3005002)。
文摘Pinhole corrosion is difficult to discover through conventional ultrasonic guided waves inspection,particularly for micro-sized pinholes less than 1 mm in diameter.This study proposes a new micro-sized pinhole inspection method based on segmented time reversal(STR)and high-order modes cluster(HOMC)Lamb waves.First,the principle of defect echo enhancement using STR is introduced.Conventional and STR inspection experiments were conducted on aluminum plates with a thickness of 3 mm and defects with different diameters and depths.The parameters of the segment window are discussed in detail.The results indicate that the proposed method had an amplitude four times larger than of conventional ultrasonic guided waves inspection method for pinhole defect detection and could detect micro-sized pinhole defects as small as 0.5 mm in diameter and 0.5 mm in depth.Moreover,the segment window location and width(5-10 times width of the conventional excitation signal)did not affect the detection sensitivity.The combination of low-power and STR is more conducive to detection in different environments,indicating the robustness of the proposed method.Compared with conventional ultrasonic guided wave inspection methods,the proposed method can detect much smaller defect echoes usually obscured by noise that are difficult to detect with a lower excitation power and thus this study would be a good reference for pinhole defect detection.
基金This work is supported by the National Key Research and Development Program of China(2022YFF1203001)National Natural Science Foundation of China(Nos.62072465,62102425)the Science and Technology Innovation Program of Hunan Province(Nos.2022RC3061,2023RC3027).
文摘Time series segmentation has attracted more interests in recent years,which aims to segment time series into different segments,each reflects a state of the monitored objects.Although there have been many surveys on time series segmentation,most of them focus more on change point detection(CPD)methods and overlook the advances in boundary detection(BD)and state detection(SD)methods.In this paper,we categorize time series segmentation methods into CPD,BD,and SD methods,with a specific focus on recent advances in BD and SD methods.Within the scope of BD and SD,we subdivide the methods based on their underlying models/techniques and focus on the milestones that have shaped the development trajectory of each category.As a conclusion,we found that:(1)Existing methods failed to provide sufficient support for online working,with only a few methods supporting online deployment;(2)Most existing methods require the specification of parameters,which hinders their ability to work adaptively;(3)Existing SD methods do not attach importance to accurate detection of boundary points in evaluation,which may lead to limitations in boundary point detection.We highlight the ability to working online and adaptively as important attributes of segmentation methods,the boundary detection accuracy as a neglected metrics for SD methods.
文摘Multi-components sinusoidal engineering signals who are non-stationary signals were considered in this study since their separation and segmentations are of great interests in many engineering fields. In most cases, the segmentation of non-stationary or multi-component signals is conducted in time domain. In this paper, we explore the advantages of applying joint time-frequency (TF) distribution of the multi-component signals to identify their segments. The Spectrogram that is known as Short-Time Fourier Transform (STFT) will be used for obtaining the time-frequency kernel. Time marginal of the computed kernel is optimally used for the signal segmentation. In order to obtain the desirable segmentation, it requires first to improve time marginal of the kernel by using two-dimensional Wiener mask filter applied to the TF kernel to mitigate and suppress non-stationary noise or interference. Additionally, a proper choice of the sliding window and its overlaying has enhanced our scheme to capture the discontinuities corresponding to the boundaries of the candidate segments.
基金This project was sponsored by the State Seismological Bureau (85-02-3-3), China
文摘By computing and classifying the data of gully offset obtained from field surveys along the Tianjingshan fault zone and estimating the ages of three types of gullies,the strike-slip rates along the fault zone are discussed in different time intervals and fault segments.The results suggest that the intensity of activity along the fault zone is not strong,but the differences between different time intervals and fault segments since the late Pleistocene have been obvious.The average rates range from 0.23 mm/a to 1.62 mm/a.The largest average rate is 1.40 mm/a,which occurred in the early and middle of late Pleistocene along the western segment of the fault zone.Since the late stage of the late Pleistocene,the center of faulting activity of the fault zone has shifted to the middle segment,and the average slip rates range have changed from 1.30 mm/a to 1.63 mm/a.
文摘Patterned-based time series segmentation (PTSS) is an important task for many time series data mining applications. In this paper, according to the characteristics of PTSS, a generalized model is proposed for PTSS. First, a new inter-pretation for PTSS is given by comparing this problem with the prototype-based clustering (PC). Then, a novel model, called clustering-inverse model (CI-model), is presented. Finally, two algorithms are presented to implement this model. Our experimental results on artificial and real-world time series demonstrate that the proposed algorithms are quite effective.
文摘In this study, we propose a novel discrete-time coupled model to generate oscillatory responses via periodic points with a high periodic order. Our coupled system comprises one-dimensional oscillators based on the Rulkov map and a single globally coupled oscillator. Because the waveform of a one-dimensional oscillator has sharply defined peaks, the coupled system can be applied to dynamic image segmentation. Our proposed system iteratively transforms the coupling of each oscillator based on an input value that corresponds to the pixel value of an input image. This approach enables our system to segment image regions in which pixel values gradually change with respect to a connected region. We conducted a bifurcation analysis of a single oscillator and a three-coupled model. Through simulations, we demonstrated that our system works well for gray-level images with three isolated image regions.
