Pub Date : 2026-02-03DOI: 10.1109/TIM.2025.3636680
Weiguo Hu;Yabin Zhang;Bowen Xu;Mingyu Dong;Tao Liu;Tianxu Hao;Min Liu
Various disturbances and uncertainties existing in actual industrial production environments can degrade the measurement accuracy of soft sensors based on single-value deterministic estimation. In addition, outliers caused by operational errors or recording mistakes may affect the generalization ability of soft sensors. Inspired by this, two Bayesian twin extreme learning machines based on symmetric skewed distributions, BTELM-ALD and BTELM-STD, are proposed. Both soft sensing methods perform parameter learning in a Bayesian framework and train a pair of twin models based on combined weights to provide estimation intervals for key indicators. They use skewed heavy-tailed distributions to model the residuals, which enhances robustness to outliers. BTELM-ALD uses an asymmetric Laplace distribution (ALD) instead of Gaussian distribution and constructs a pair of twin models based on the combined weights ($p$ , $1-p$ ). The introduction of suitable surrogate functions makes the posterior distribution and marginal likelihood easy to solve. In BTELM-STD, a univariate skewed t-distribution (STD) is presented and written as a hierarchical representation. The corresponding twin models are constructed based on the combined weights ($s$ , $-s$ ), and then variational inference and the Newton method are used to optimize the parameters. Experimental results on several cases including an actual PTA oxidation process illustrate the validity and advantages of our proposed methods.
{"title":"Two Industrial Twin Soft Sensing Methods With Estimation Interval Based on Symmetric Skewed Distributions and Combined Weights","authors":"Weiguo Hu;Yabin Zhang;Bowen Xu;Mingyu Dong;Tao Liu;Tianxu Hao;Min Liu","doi":"10.1109/TIM.2025.3636680","DOIUrl":"https://doi.org/10.1109/TIM.2025.3636680","url":null,"abstract":"Various disturbances and uncertainties existing in actual industrial production environments can degrade the measurement accuracy of soft sensors based on single-value deterministic estimation. In addition, outliers caused by operational errors or recording mistakes may affect the generalization ability of soft sensors. Inspired by this, two Bayesian twin extreme learning machines based on symmetric skewed distributions, BTELM-ALD and BTELM-STD, are proposed. Both soft sensing methods perform parameter learning in a Bayesian framework and train a pair of twin models based on combined weights to provide estimation intervals for key indicators. They use skewed heavy-tailed distributions to model the residuals, which enhances robustness to outliers. BTELM-ALD uses an asymmetric Laplace distribution (ALD) instead of Gaussian distribution and constructs a pair of twin models based on the combined weights (<inline-formula> <tex-math>$p$ </tex-math></inline-formula>, <inline-formula> <tex-math>$1-p$ </tex-math></inline-formula>). The introduction of suitable surrogate functions makes the posterior distribution and marginal likelihood easy to solve. In BTELM-STD, a univariate skewed t-distribution (STD) is presented and written as a hierarchical representation. The corresponding twin models are constructed based on the combined weights (<inline-formula> <tex-math>$s$ </tex-math></inline-formula>, <inline-formula> <tex-math>$-s$ </tex-math></inline-formula>), and then variational inference and the Newton method are used to optimize the parameters. Experimental results on several cases including an actual PTA oxidation process illustrate the validity and advantages of our proposed methods.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"75 ","pages":"1-11"},"PeriodicalIF":5.9,"publicationDate":"2026-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146169933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-03DOI: 10.1109/TIM.2026.3660409
Jiani Zhou;Chen Chen;Yong Zhang;Jun Lin;Heng Piao;Feng Sun
Methane is the primary component of natural gas. The accurate detection of methane leakage points and concentration is crucial to ensuring safety and environmental protection. However, traditional active gas concentration detection methods are susceptible to interference from dynamic backgrounds, which makes concentration detection challenging. This article presents a passive method for detecting gas cloud concentration distributions based on a self-developed passive infrared imaging system operating in the 3.2–$3.4~mu $ m wavelength band. A methane detection model considering multiple influencing factors was established. During the model development, an adaptive factor was incorporated into the prediction and tracking framework of the Kalman filter to mitigate the effect of time-varying light sources on gas concentration detection performance. Experimental results demonstrate that the detection limit is 0.79%, and the relative error is less than 1.00%. The system enables real-time methane concentration detection and validates its potential for natural gas leakage detection through its industrial application in complex environments. The field test videos and the core code of the proposed method have been made publicly available at: https://github.com/1996Eric/AT-EKF
{"title":"A Passive Detection Method of Gas Cloud Concentration Distributions for Leaking Alkane Gas","authors":"Jiani Zhou;Chen Chen;Yong Zhang;Jun Lin;Heng Piao;Feng Sun","doi":"10.1109/TIM.2026.3660409","DOIUrl":"https://doi.org/10.1109/TIM.2026.3660409","url":null,"abstract":"Methane is the primary component of natural gas. The accurate detection of methane leakage points and concentration is crucial to ensuring safety and environmental protection. However, traditional active gas concentration detection methods are susceptible to interference from dynamic backgrounds, which makes concentration detection challenging. This article presents a passive method for detecting gas cloud concentration distributions based on a self-developed passive infrared imaging system operating in the 3.2–<inline-formula> <tex-math>$3.4~mu $ </tex-math></inline-formula>m wavelength band. A methane detection model considering multiple influencing factors was established. During the model development, an adaptive factor was incorporated into the prediction and tracking framework of the Kalman filter to mitigate the effect of time-varying light sources on gas concentration detection performance. Experimental results demonstrate that the detection limit is 0.79%, and the relative error is less than 1.00%. The system enables real-time methane concentration detection and validates its potential for natural gas leakage detection through its industrial application in complex environments. The field test videos and the core code of the proposed method have been made publicly available at: <uri>https://github.com/1996Eric/AT-EKF</uri>","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"75 ","pages":"1-12"},"PeriodicalIF":5.9,"publicationDate":"2026-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146169935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-03DOI: 10.1109/TIM.2026.3653168
{"title":"IEEE Instrumentation and Measurement Society","authors":"","doi":"10.1109/TIM.2026.3653168","DOIUrl":"https://doi.org/10.1109/TIM.2026.3653168","url":null,"abstract":"","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"C3-C4"},"PeriodicalIF":5.9,"publicationDate":"2026-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11371489","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-30DOI: 10.1109/TIM.2026.3659678
Chunyang Pang;Feng Wang;Yangze Dong
Two-dimensional direction-of-arrival (2D-DOA) estimation plays a key role in array signal processing by providing accurate azimuth and elevation information. This full spatial awareness is critical for applications including 3-D acoustic imaging, target localization, and autonomous sensing. With the growing demand for device miniaturization, in resource-constrained miniature devices, physical space limitations restrict the array aperture and the number of elements, thereby reducing angular resolution. Enlarging the interelement spacing to improve resolution, however, may cause phase ambiguity in sparse arrays and consequently reduce estimation robustness. To address these challenges, this article proposes a 2D-DOA estimation method for small-scale sparse arrays through co-optimization of waveform design, array configuration, and signal processing algorithms. First, inspired by the biosonar mechanism of Hipposideros pratti, a wideband transmit waveform with a unique harmonic structure is designed, which demonstrates superior robustness in reverberant environments compared to conventional signals. Second, a sparse triangular array structure with interelement spacing exceeding the Rayleigh limit is constructed, significantly improving spatial resolution while meeting miniaturization requirements. Finally, an end-to-end network architecture based on multitask learning (MTL) is developed, where collaborative optimization of azimuth and elevation estimation branches effectively enhances estimation accuracy and efficiency. Based on these innovations, a triple-element sparse array DOA estimation system is implemented. Experimental results using measured data demonstrate that the proposed method achieves better estimation accuracy and robustness than existing wideband direction-finding approaches under the same array configuration.
{"title":"Multitask Learning-Based Broadband Multiharmonic Signal 2D-DOA Estimation Using Sparse Arrays","authors":"Chunyang Pang;Feng Wang;Yangze Dong","doi":"10.1109/TIM.2026.3659678","DOIUrl":"https://doi.org/10.1109/TIM.2026.3659678","url":null,"abstract":"Two-dimensional direction-of-arrival (2D-DOA) estimation plays a key role in array signal processing by providing accurate azimuth and elevation information. This full spatial awareness is critical for applications including 3-D acoustic imaging, target localization, and autonomous sensing. With the growing demand for device miniaturization, in resource-constrained miniature devices, physical space limitations restrict the array aperture and the number of elements, thereby reducing angular resolution. Enlarging the interelement spacing to improve resolution, however, may cause phase ambiguity in sparse arrays and consequently reduce estimation robustness. To address these challenges, this article proposes a 2D-DOA estimation method for small-scale sparse arrays through co-optimization of waveform design, array configuration, and signal processing algorithms. First, inspired by the biosonar mechanism of Hipposideros pratti, a wideband transmit waveform with a unique harmonic structure is designed, which demonstrates superior robustness in reverberant environments compared to conventional signals. Second, a sparse triangular array structure with interelement spacing exceeding the Rayleigh limit is constructed, significantly improving spatial resolution while meeting miniaturization requirements. Finally, an end-to-end network architecture based on multitask learning (MTL) is developed, where collaborative optimization of azimuth and elevation estimation branches effectively enhances estimation accuracy and efficiency. Based on these innovations, a triple-element sparse array DOA estimation system is implemented. Experimental results using measured data demonstrate that the proposed method achieves better estimation accuracy and robustness than existing wideband direction-finding approaches under the same array configuration.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"75 ","pages":"1-17"},"PeriodicalIF":5.9,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146169930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-30DOI: 10.1109/TIM.2026.3659638
Jiaxin Li;Shangwen Li;Weijia Shi;Xinqi Tian;Lianwei Sun;Bo Zhao;Jiubin Tan
Real-time and accurate detection of in-orbit spacecraft leakage is crucial for ensuring operational safety but remains a significant challenge due to weak, irregular signals often obscured by intense background noise. Traditional methods, lacking prior frequency information, struggle to consistently identify these subtle leakage signatures. In this article, we introduce a novel frequency-domain stability analysis framework utilizing an refined synchrosqueezing transform (SST). The key contributions of this work are: 1) a refined SST-based spectral processing technique designed to achieve superior time–frequency resolution; and 2) the introduction of the central frequency dispersion index (CFDI) combined with dual-segment consistency verification enables automatic identification of candidate stable frequency bands. The proposed method is rigorously validated through experiments simulating leakage scenarios on 5A06 aluminum alloy plates (2.5 mm thick), featuring both a precise 0.2 mm microhole and irregular leakage geometries. Experimental results demonstrate the method’s outstanding performance, achieving over 90% identification accuracy for different kinds of leaks, while effectively suppressing false positives induced by impact signals. This work provides a significantly more accurate and robust solution for spacecraft leakage monitoring and holds strong potential for broader applications in weak, irregular signal detection within noisy environments.
{"title":"Identification of Weak Gas Leaks Using Dual-Segment Consistency Verification Based on Center Frequency Dispersion Index","authors":"Jiaxin Li;Shangwen Li;Weijia Shi;Xinqi Tian;Lianwei Sun;Bo Zhao;Jiubin Tan","doi":"10.1109/TIM.2026.3659638","DOIUrl":"https://doi.org/10.1109/TIM.2026.3659638","url":null,"abstract":"Real-time and accurate detection of in-orbit spacecraft leakage is crucial for ensuring operational safety but remains a significant challenge due to weak, irregular signals often obscured by intense background noise. Traditional methods, lacking prior frequency information, struggle to consistently identify these subtle leakage signatures. In this article, we introduce a novel frequency-domain stability analysis framework utilizing an refined synchrosqueezing transform (SST). The key contributions of this work are: 1) a refined SST-based spectral processing technique designed to achieve superior time–frequency resolution; and 2) the introduction of the central frequency dispersion index (CFDI) combined with dual-segment consistency verification enables automatic identification of candidate stable frequency bands. The proposed method is rigorously validated through experiments simulating leakage scenarios on 5A06 aluminum alloy plates (2.5 mm thick), featuring both a precise 0.2 mm microhole and irregular leakage geometries. Experimental results demonstrate the method’s outstanding performance, achieving over 90% identification accuracy for different kinds of leaks, while effectively suppressing false positives induced by impact signals. This work provides a significantly more accurate and robust solution for spacecraft leakage monitoring and holds strong potential for broader applications in weak, irregular signal detection within noisy environments.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"75 ","pages":"1-12"},"PeriodicalIF":5.9,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147362259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-28DOI: 10.1109/TIM.2026.3655897
Yang Liu;Kun Shang;Danlei Qiao;Chuanqing Zhou
In the field of automated parking system, achieving precise detection of parking slot edge only through ultrasonic sensors remains the fundamental challenge for implementing an ultrasonic-only parking system. In this work, an adaptive spatial positioning (ASP) algorithm is proposed utilizing a single ultrasonic sensor based on the principle of multiple reflections of ultrasonic waves at the same obstacle edge, enabling precise edge detection. The edge detection results from ipsilateral ultrasonic sensors are subsequently fused through a decision tree algorithm, followed by noise reduction via clustering methods to eliminate discrete outliers, ultimately achieving accurate parking space detection. The proposed ASP algorithm demonstrates superior computational efficiency, exhibiting a memory footprint of 420 bytes and an execution time of $44~mu $ s. Ultimately, the ultrasonic-only slot detection system is tested in real-world scenarios, demonstrating an 87.5% obstacle (vehicle) edge correction rate, 86.4% bilateral slot between vehicles (100% for slot between vehicle and pillar) detection rate, and 100% unilateral slot detection rate, with an average positioning error of <25 cm. It demonstrates its applicability in an ultrasonic-only parking system.
{"title":"An Adaptive Spatial Positioning Algorithm for Ultrasonic-Only Parking Slot Detection System","authors":"Yang Liu;Kun Shang;Danlei Qiao;Chuanqing Zhou","doi":"10.1109/TIM.2026.3655897","DOIUrl":"https://doi.org/10.1109/TIM.2026.3655897","url":null,"abstract":"In the field of automated parking system, achieving precise detection of parking slot edge only through ultrasonic sensors remains the fundamental challenge for implementing an ultrasonic-only parking system. In this work, an adaptive spatial positioning (ASP) algorithm is proposed utilizing a single ultrasonic sensor based on the principle of multiple reflections of ultrasonic waves at the same obstacle edge, enabling precise edge detection. The edge detection results from ipsilateral ultrasonic sensors are subsequently fused through a decision tree algorithm, followed by noise reduction via clustering methods to eliminate discrete outliers, ultimately achieving accurate parking space detection. The proposed ASP algorithm demonstrates superior computational efficiency, exhibiting a memory footprint of 420 bytes and an execution time of <inline-formula> <tex-math>$44~mu $ </tex-math></inline-formula>s. Ultimately, the ultrasonic-only slot detection system is tested in real-world scenarios, demonstrating an 87.5% obstacle (vehicle) edge correction rate, 86.4% bilateral slot between vehicles (100% for slot between vehicle and pillar) detection rate, and 100% unilateral slot detection rate, with an average positioning error of <25 cm. It demonstrates its applicability in an ultrasonic-only parking system.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"75 ","pages":"1-9"},"PeriodicalIF":5.9,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146169932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-28DOI: 10.1109/TIM.2026.3656041
Li Yafeng;Xue Qilong;Qu Jun;Jia Jianbo;Guo Huijuan;Ji Guodong
The downhole high-frequency measurement is critical for preventing costly failures of push-the-bit rotary steerable systems (PTB-RSSs). However, the differences in the fatigue life under multimode vibrations have not been clearly identified using existing measurement and interpretation methods. This study establishes a multiboundary coupled dynamics model of PTB-RSS, validated with field measurements, which incorporates the steering force friction, bit–rock interaction, and bottom hole assembly (BHA)–borehole contact mechanisms. Validation using high-frequency field data showed a Pearson correlation coefficient of 0.933 for rotational speed, close agreement in acceleration spectral characteristics, and an average error of only 6.13% in steering displacement compared with theoretical values, confirming the model’s high fidelity in reproducing key downhole vibration patterns. Stress signals obtained from the validated model were processed using the rainflow counting method. The results indicate that stick–slip vibration reduces the fatigue life of BHA by at least 68.38%, while high-frequency whirl and torsional vibrations reduce it by more than 90%. Moreover, when the steering force approaches 30 kN, it readily excites the high-frequency vibration in BHA, significantly shortening its service life. The core methodological innovation of this study lies in establishing a validated dynamics model that serves as a virtual sensor. This model enables the first translation of measurable vibration patterns into quantified fatigue life differences, thereby providing an operable, measurement-driven technical framework for predicting BHA fatigue life based on high-frequency dynamic signal measurements.
{"title":"Quantification and Validation of Fatigue Life Differences in Push-the-Bit Rotary Steerable Systems via Vibration Pattern Measurement","authors":"Li Yafeng;Xue Qilong;Qu Jun;Jia Jianbo;Guo Huijuan;Ji Guodong","doi":"10.1109/TIM.2026.3656041","DOIUrl":"https://doi.org/10.1109/TIM.2026.3656041","url":null,"abstract":"The downhole high-frequency measurement is critical for preventing costly failures of push-the-bit rotary steerable systems (PTB-RSSs). However, the differences in the fatigue life under multimode vibrations have not been clearly identified using existing measurement and interpretation methods. This study establishes a multiboundary coupled dynamics model of PTB-RSS, validated with field measurements, which incorporates the steering force friction, bit–rock interaction, and bottom hole assembly (BHA)–borehole contact mechanisms. Validation using high-frequency field data showed a Pearson correlation coefficient of 0.933 for rotational speed, close agreement in acceleration spectral characteristics, and an average error of only 6.13% in steering displacement compared with theoretical values, confirming the model’s high fidelity in reproducing key downhole vibration patterns. Stress signals obtained from the validated model were processed using the rainflow counting method. The results indicate that stick–slip vibration reduces the fatigue life of BHA by at least 68.38%, while high-frequency whirl and torsional vibrations reduce it by more than 90%. Moreover, when the steering force approaches 30 kN, it readily excites the high-frequency vibration in BHA, significantly shortening its service life. The core methodological innovation of this study lies in establishing a validated dynamics model that serves as a virtual sensor. This model enables the first translation of measurable vibration patterns into quantified fatigue life differences, thereby providing an operable, measurement-driven technical framework for predicting BHA fatigue life based on high-frequency dynamic signal measurements.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"75 ","pages":"1-20"},"PeriodicalIF":5.9,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146169934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-23DOI: 10.1109/TIM.2026.3657509
Binwen Li;Bo Zhao;Jiaxin Li;Weijia Shi;Xinqi Tian;Jiubin Tan
The ultrasonic array is widely used for nondestructive evaluation (NDE) as it has a large inspection coverage and is sensitive to small defects. The time-reversal multisignal classification method can achieve super-resolution imaging (SRI) for defects whose size is below the Rayleigh diffraction limit with full-matrix capture (FMC) data. However, the FMC only uses a single element in the transmit stage and hence degrades the signal-to-noise ratio (SNR) of echo waves in multilayer structures, which lead to poor resolution ability of practical imaging. Additionally, the FMC consumes a long acquisition time and produces a large data volume, which decreases the scanning speed of automatic detection equipment. Focusing on these problems, a novel imaging method called virtual-source excitation SRI (VSE-SRI) is proposed. The VSE-SRI applies a group of elements to transmit energy, by adjusting the delay time of each element, the energy can be concentrated in the layer of detected material, which contains defects, and the energy attenuation in the transmit stage is greatly decreased, which improves the SNR of signals and the resolution ability of images. More importantly, with a higher SNR, equal resolution performance can be realized with fewer transmit times. Experiments demonstrate that the VSE-SRI can resolve the two 1 mm holes with a distance of 0.60 Rayleigh limit in a three-layer composite structure. Compared with traditional FMC-SRI, the peak-to-center intensity difference (PCID) increases from 1.02 to 8.38 dB, and the data volume decreases from $64times 64$ A-scan signals to $64times 3$ A-scan signals. It is promised that the proposed VSE-SRI method can achieve faster and more robust SRI for multilayer composite structures in high-speed automatic detection situations.
超声阵列具有检测范围大、对小缺陷敏感等优点，在无损检测中得到了广泛的应用。时间反转多信号分类方法可以利用全矩阵捕获（FMC）数据对尺寸小于瑞利衍射极限的缺陷实现超分辨率成像（SRI）。然而，FMC在发射级仅使用单个元件，从而降低了多层结构中回波的信噪比，导致实际成像的分辨率能力较差。此外，FMC采集时间长，产生的数据量大，降低了自动检测设备的扫描速度。针对这些问题，提出了一种新的成像方法——虚拟源激励SRI （VSE-SRI）。VSE-SRI采用一组元件传输能量，通过调整每个元件的延迟时间，可以将能量集中在含有缺陷的被检测材料层，大大降低了传输阶段的能量衰减，提高了信号的信噪比和图像的分辨能力。更重要的是，在更高的信噪比下，可以用更少的发射次数实现相同的分辨率性能。实验表明，VSE-SRI可以分辨出三层复合材料结构中两个距离为0.60瑞利极限的1 mm孔。与传统的FMC-SRI相比，峰心强度差（PCID）从1.02 dB增加到8.38 dB，数据量从64 × 64$ a -扫描信号减少到64 × 3$ a -扫描信号。在高速自动检测的情况下，本文提出的VSE-SRI方法可以实现多层复合材料结构更快、更鲁棒的SRI。
{"title":"Virtual-Source Excitation Super-Resolution Imaging: A Fast and Robust Method for Multilayer Structures","authors":"Binwen Li;Bo Zhao;Jiaxin Li;Weijia Shi;Xinqi Tian;Jiubin Tan","doi":"10.1109/TIM.2026.3657509","DOIUrl":"https://doi.org/10.1109/TIM.2026.3657509","url":null,"abstract":"The ultrasonic array is widely used for nondestructive evaluation (NDE) as it has a large inspection coverage and is sensitive to small defects. The time-reversal multisignal classification method can achieve super-resolution imaging (SRI) for defects whose size is below the Rayleigh diffraction limit with full-matrix capture (FMC) data. However, the FMC only uses a single element in the transmit stage and hence degrades the signal-to-noise ratio (SNR) of echo waves in multilayer structures, which lead to poor resolution ability of practical imaging. Additionally, the FMC consumes a long acquisition time and produces a large data volume, which decreases the scanning speed of automatic detection equipment. Focusing on these problems, a novel imaging method called virtual-source excitation SRI (VSE-SRI) is proposed. The VSE-SRI applies a group of elements to transmit energy, by adjusting the delay time of each element, the energy can be concentrated in the layer of detected material, which contains defects, and the energy attenuation in the transmit stage is greatly decreased, which improves the SNR of signals and the resolution ability of images. More importantly, with a higher SNR, equal resolution performance can be realized with fewer transmit times. Experiments demonstrate that the VSE-SRI can resolve the two 1 mm holes with a distance of 0.60 Rayleigh limit in a three-layer composite structure. Compared with traditional FMC-SRI, the peak-to-center intensity difference (PCID) increases from 1.02 to 8.38 dB, and the data volume decreases from <inline-formula> <tex-math>$64times 64$ </tex-math></inline-formula> A-scan signals to <inline-formula> <tex-math>$64times 3$ </tex-math></inline-formula> A-scan signals. It is promised that the proposed VSE-SRI method can achieve faster and more robust SRI for multilayer composite structures in high-speed automatic detection situations.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"75 ","pages":"1-11"},"PeriodicalIF":5.9,"publicationDate":"2026-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146175646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Traditional collision avoidance sonars perform a round-trip ranging measurement per operational cycle, where longer detection distances lead to longer cycle durations. The low propagation speed of acoustic signals increases their susceptibility to Doppler effects, which can ultimately degrade ranging accuracy or success rates and, in severe cases, lead to economic losses or even loss of life. To address this issue, we propose a ranging enhancement method for collision avoidance sonar inspired by integrated sensing and communication (ISAC) principles. At the signal level, we introduce a tail-flipping linear frequency-modulation (TF-LFM) waveform along with a Doppler channel estimation method to maintain stability under severe channel conditions. Simulation results demonstrate that the proposed waveform achieves robust measurement under strong Doppler distortions. With a remarkably low average peak-to-average power ratio (PAPR) of approximately 3.01 dB, the signal is easy to transmit and resilient to nonlinear distortion. At the processing level, we propose an adaptive sensing acceleration (ASA) mechanism that allows the sonar to emit new pulses before previous echoes return, thereby reducing ranging latency. In a field pool experiment, the upgraded sonar system achieved a 65.9% reduction in latency per ranging cycle using the proposed method, demonstrating a substantial enhancement in measurement efficiency.
{"title":"Ranging Enhancement for Underwater Collision Avoidance Sonar via ISAC Waveform and Adaptive Sensing Acceleration","authors":"Shihui Liang;Weibo Mao;Dongdong Zhao;Peng Chen;Wei Zou;Fan Zhou;Wei Wu;Fuling Huang;Ronghua Liang","doi":"10.1109/TIM.2026.3655998","DOIUrl":"https://doi.org/10.1109/TIM.2026.3655998","url":null,"abstract":"Traditional collision avoidance sonars perform a round-trip ranging measurement per operational cycle, where longer detection distances lead to longer cycle durations. The low propagation speed of acoustic signals increases their susceptibility to Doppler effects, which can ultimately degrade ranging accuracy or success rates and, in severe cases, lead to economic losses or even loss of life. To address this issue, we propose a ranging enhancement method for collision avoidance sonar inspired by integrated sensing and communication (ISAC) principles. At the signal level, we introduce a tail-flipping linear frequency-modulation (TF-LFM) waveform along with a Doppler channel estimation method to maintain stability under severe channel conditions. Simulation results demonstrate that the proposed waveform achieves robust measurement under strong Doppler distortions. With a remarkably low average peak-to-average power ratio (PAPR) of approximately 3.01 dB, the signal is easy to transmit and resilient to nonlinear distortion. At the processing level, we propose an adaptive sensing acceleration (ASA) mechanism that allows the sonar to emit new pulses before previous echoes return, thereby reducing ranging latency. In a field pool experiment, the upgraded sonar system achieved a 65.9% reduction in latency per ranging cycle using the proposed method, demonstrating a substantial enhancement in measurement efficiency.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"75 ","pages":"1-14"},"PeriodicalIF":5.9,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146169931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-15DOI: 10.1109/TIM.2026.3654702
Xi Wang;Letian Gao;Zihao Huang;Xin Xia;You Li;Guangcai Wang;Lu Xiong
The initial alignment of a vehicular inertial navigation system (INS) is a critical process, where accuracy and convergence speed represent the primary performance challenges. This article addresses initial attitude estimation errors resulting from unreliable aiding information and limited observation time in complex environments, such as during global navigation satellite system (GNSS) signal outages or wheel slippage. To mitigate these issues, a novel dynamic initial alignment strategy aided by light detection and ranging (LiDAR) is proposed to overcome the limitations inherent to conventional GNSS- or odometer (OD)-aided methods. Furthermore, to achieve fast, high-precision alignment with sparse observation data, a dynamic alignment model employing chronological optimization is developed. The proposed algorithm is validated through both simulations and real-world vehicle experiments. Results demonstrate that, compared with existing state-of-the-art methods, the proposed strategy exhibits superior environmental adaptability and faster convergence speed under dynamic conditions.
{"title":"Fast In-Motion Alignment for LiDAR–Inertial in Challenging Scenarios","authors":"Xi Wang;Letian Gao;Zihao Huang;Xin Xia;You Li;Guangcai Wang;Lu Xiong","doi":"10.1109/TIM.2026.3654702","DOIUrl":"https://doi.org/10.1109/TIM.2026.3654702","url":null,"abstract":"The initial alignment of a vehicular inertial navigation system (INS) is a critical process, where accuracy and convergence speed represent the primary performance challenges. This article addresses initial attitude estimation errors resulting from unreliable aiding information and limited observation time in complex environments, such as during global navigation satellite system (GNSS) signal outages or wheel slippage. To mitigate these issues, a novel dynamic initial alignment strategy aided by light detection and ranging (LiDAR) is proposed to overcome the limitations inherent to conventional GNSS- or odometer (OD)-aided methods. Furthermore, to achieve fast, high-precision alignment with sparse observation data, a dynamic alignment model employing chronological optimization is developed. The proposed algorithm is validated through both simulations and real-world vehicle experiments. Results demonstrate that, compared with existing state-of-the-art methods, the proposed strategy exhibits superior environmental adaptability and faster convergence speed under dynamic conditions.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"75 ","pages":"1-12"},"PeriodicalIF":5.9,"publicationDate":"2026-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146026385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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