Measurement最新文献_第6页

Physics-based feature engineering for simultaneous classification of bovine meat type and freshness by bioimpedance spectroscopy 基于物理特征工程的牛肉种类和新鲜度生物阻抗谱同时分类

IF 5.6 2区工程技术

Measurement Pub Date : 2026-05-05 Epub Date: 2026-03-06 DOI: 10.1016/j.measurement.2026.121041

Mahdi Guermazi , Ahmed Yahia Kallel , Olfa Kanoun

{"title":"Physics-based feature engineering for simultaneous classification of bovine meat type and freshness by bioimpedance spectroscopy","authors":"Mahdi Guermazi , Ahmed Yahia Kallel , Olfa Kanoun","doi":"10.1016/j.measurement.2026.121041","DOIUrl":"10.1016/j.measurement.2026.121041","url":null,"abstract":"<div><div>In this paper, we propose a systematic, physics-based feature engineering methodology that can classify muscle type and freshness in bovine meat simultaneously using a single neural network. We identify a minimal, yet highly informative set of features extracted from bioimpedance spectra based on observed spectral behavior and underlying physical principles. Feature selection in this study is primarily based on significant parameter variation measured over a 14-day period, particularly between days 2 or 3 and day 14 for a binary classification of meat in the two classes safe-to-sell and not-safe-to-sell. This variation serves as a strong indicator of sensitivity and contributes to achieving a high classification rate. The key features selected include parameters from the modified Fricke model and characteristic points in the α and β frequency bands (Rex, Rin, C, Im1, Im2 and Im3). We validate the stability of these features and assess the model’s interpretability. Our analysis highlights the consistent relevance of these parameters, enabling a classification accuracy of up to 91,5% using both neural networks and SVM models. The evolution of these parameters aligns with biological fundamentals, confirming the relevance of the selected features.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"272 ","pages":"Article 121041"},"PeriodicalIF":5.6,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147388336","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}

引用次数: 0

Deep learning-based phase retrieval with SE-SwinUNet architecture in fringe projection 3D measurement 基于SE-SwinUNet结构的深度学习相位检索在条纹投影三维测量中的应用

IF 5.6 2区工程技术

Measurement Pub Date : 2026-05-05 Epub Date: 2026-03-06 DOI: 10.1016/j.measurement.2026.121044

Qinkui Ma, Jianhua Wang, Huixin Sun, Tong Shao, Mengmeng Wang

{"title":"Deep learning-based phase retrieval with SE-SwinUNet architecture in fringe projection 3D measurement","authors":"Qinkui Ma, Jianhua Wang, Huixin Sun, Tong Shao, Mengmeng Wang","doi":"10.1016/j.measurement.2026.121044","DOIUrl":"10.1016/j.measurement.2026.121044","url":null,"abstract":"<div><div>Fringe projection three-dimensional (3D) measurement is an important non-contact measurement technique, and the precision of 3D reconstruction largely depends on the accuracy of phase retrieval. With the development of deep learning (DL), phase retrieval based on deep neural network (DNN) has been widely studied. The performance of neural networks plays a decisive role in determining the accuracy of phase demodulation in fringe projection profilometry (FPP). Currently, most deep learning-based wrapped phase extraction methods are built upon the U-Net architecture. Nevertheless, the hierarchical skip-connection mechanism of U-Net presents inherent limitations in global information transmission and feature fusion, which in turn restricts further improvements in phase retrieval accuracy. For this purpose, we propose a method for phase demodulation grounded in a novel multi-scale feature fusion network, referred to as SE-SwinUNet. The network combines the advantages of the Swin Transformer and residual connections, incorporating an asymmetric design in both the encoder and decoder. Through enhanced global information modeling and local detail refinement, it markedly improves the efficiency of feature propagation and utilization. Furthermore, by incorporating a channel attention mechanism (Squeeze-and-Excitation layer, SE), the network is capable of adaptively allocating appropriate weights to multi-scale features, thereby effectively reinforcing its focus on the most salient features. Experimental results demonstrate that SE-SwinUNet achieves higher accuracy in phase demodulation tasks compared to the conventional U-Net, exhibiting particularly pronounced advantages in complex scenarios.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"272 ","pages":"Article 121044"},"PeriodicalIF":5.6,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147388350","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}

引用次数: 0

Torque stability of direct torque control in induction motors based on fuzzy PI adaptive control 基于模糊PI自适应控制的异步电动机直接转矩控制的转矩稳定性

IF 5.6 2区工程技术

Measurement Pub Date : 2026-05-05 Epub Date: 2026-03-04 DOI: 10.1016/j.measurement.2026.121024

Shuanglong Wu , Shubin Chen , Xiaoxing Ye , Jiajun Rao , Yijie He , Yushen Huang , Caixia Lin , Long Qi

{"title":"Torque stability of direct torque control in induction motors based on fuzzy PI adaptive control","authors":"Shuanglong Wu , Shubin Chen , Xiaoxing Ye , Jiajun Rao , Yijie He , Yushen Huang , Caixia Lin , Long Qi","doi":"10.1016/j.measurement.2026.121024","DOIUrl":"10.1016/j.measurement.2026.121024","url":null,"abstract":"<div><div>To address the issues of large torque fluctuations, poor low-speed performance, and low control accuracy in traditional DTC for induction motors (IMs), this paper proposes a torque control strategy for IMs based on fuzzy logic control (FLC) combined with space vector pulse width modulation (SVM). First, SVM technology is introduced to optimize the stator flux vector control method, an SVM-DTC control system is designed to mitigate the significant torque fluctuations caused by hysteresis control. Subsequently, based on fuzzy control theory, a hybrid membership function fuzzy PI adaptive torque controller was designed. After parameter fitting, it is integrated into the SVM-DTC system to establish the FL-SVM-DTC control system. This approach mitigates inconsistent torque fluctuation suppression under varying load conditions and reduces excessive torque overshoot during load transients. Root Mean Squared Error (RMSE) is adopted as the torque evaluation metric. Finally, variable-load torque tests were conducted on the IM using an experimental motor test platform. Test results demonstrate that, under the torque controller designed in this paper, the FL-SVM-DTC achieves an average reduction of 70.46% in torque fluctuations compared to the traditional DTC, and an average reduction of 32.48% compared to the SVM-DTC. This validates the reliability and effectiveness of the proposed controller.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"272 ","pages":"Article 121024"},"PeriodicalIF":5.6,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147388354","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}

引用次数: 0

Robust five-degree-of-freedom error measurement in complex environments using composite sensing and SLM-based beam modulation 基于复合传感和slm波束调制的复杂环境下鲁棒五自由度误差测量

IF 5.6 2区工程技术

Measurement Pub Date : 2026-05-05 Epub Date: 2026-03-02 DOI: 10.1016/j.measurement.2026.121031

Chuanzhi Tang , Wenzheng Liu , Fajie Duan , Jinfeng Lan , Jinlai Zhang , Chenhui Deng , Jiawei Chu

{"title":"Robust five-degree-of-freedom error measurement in complex environments using composite sensing and SLM-based beam modulation","authors":"Chuanzhi Tang , Wenzheng Liu , Fajie Duan , Jinfeng Lan , Jinlai Zhang , Chenhui Deng , Jiawei Chu","doi":"10.1016/j.measurement.2026.121031","DOIUrl":"10.1016/j.measurement.2026.121031","url":null,"abstract":"<div><div>The continuous advancement of high-end equipment manufacturing toward higher precision and enhanced robustness has imposed significant challenges on geometric error measurement under complex environments and long-range conditions. To address the significant impact of beam quality degradation on laser collimation measurement performance, a laser-based five-degree-of-freedom (5-DOF) error measurement method incorporating composite sensing and spatial light modulator (SLM)-based beam modulation is proposed in this paper for operation under complex conditions. A charge-coupled device (CCD) is employed as an auxiliary observation channel to enable real-time monitoring of critical beam characteristics, such as spot centroid drift, shape distortion, and energy non-uniformity. Combined with high-accuracy centroid data acquired from a quadrant photodiode (QPD) and a position-sensitive detector (PSD), a multi-sensor fusion-based composite perception model is established. On this basis, a beam deviation fusion estimation algorithm with dynamic weighting is developed to improve the accuracy and robustness of multi-source data integration. Furthermore, a dual-loop feedback control framework is designed to coordinate beam quality optimization and drift compensation, driving the SLM for composite phase modulation and achieving high-precision laser 5-DOF error measurement over extended distances. Experimental validation demonstrates that within a 3 m measurement range, the proposed method reduces translational drift from 37.31 μm to 3.38 μm and angular drift from 24.35 μm to 1.56 μm, enhances beam rotational symmetry to 0.949, and maintains energy concentration above 0.56. The proposed method has been validated to achieve high measurement precision, system stability, and environmental adaptability, providing a robust technical foundation for high-accuracy optical metrology under complex operational conditions.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"272 ","pages":"Article 121031"},"PeriodicalIF":5.6,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147387986","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}

引用次数: 0

Research of interactive sheep body size measurement based on 3D reconstruction 基于三维重建的交互式羊体尺寸测量方法研究

IF 5.6 2区工程技术

Measurement Pub Date : 2026-05-05 Epub Date: 2026-03-09 DOI: 10.1016/j.measurement.2026.121080

Lin Zhu , Lina Zhang , Fan Yang , Yuxing Wei , Hua Meng , Lu Yang , Kefan Shang , Jue Zhang , Xinhua Jiang

{"title":"Research of interactive sheep body size measurement based on 3D reconstruction","authors":"Lin Zhu , Lina Zhang , Fan Yang , Yuxing Wei , Hua Meng , Lu Yang , Kefan Shang , Jue Zhang , Xinhua Jiang","doi":"10.1016/j.measurement.2026.121080","DOIUrl":"10.1016/j.measurement.2026.121080","url":null,"abstract":"<div><div>Body sizes of sheep serve as a comprehensive indicator of their morphological profile, growth characteristics, genetic traits, and so on. Vision-based technologies offer a non-invasive, efficient, and precise approach to livestock body size measurement. Although substantial progress has been achieved in this field, several critical challenges remain. Automated body measurement still faces challenges arising from livestock posture variability, as well as morphological differences across breeds and age groups. Moreover, the required measurement parameters may differ among breeds. To address these limitations, this study proposed an interactive body size measurement approach. A multi-view depth vision imaging system was employed to capture body images, followed by a denoising process to reduce noise arising from fleece heterogeneity and environmental interference. A three-dimensional spatial model of each sheep was then reconstructed, and pose normalization was performed to standardize the spatial orientation for consistent measurements. To improve accessibility and operational efficiency, an interactive body measurement system was developed on the PyQt5 platform. This system supports multi-dimensional morphometric measurement, including body height, width, length, chest girth, surface area, and volume. Farm experiments on sheep of different breeds and ages demonstrated that the proposed method provides high measurement accuracy, with an average relative error below 5%. The method is simple and user-friendly, exhibiting strong adaptability to various imaging conditions and sheep postures, thereby enabling diversified phenotypic characterization of sheep. It therefore serves as a valuable complement to existing approaches for sheep body measurement and demonstrates potential for extension to other livestock species, such as pigs and cattle.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"272 ","pages":"Article 121080"},"PeriodicalIF":5.6,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147387726","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}

引用次数: 0

Dynamic modelling and vibration characteristic analysis of gear transmission system under the effect of time-varying misalignment from clearance of bearings 轴承间隙时变不对准影响下齿轮传动系统动力学建模及振动特性分析

IF 5.6 2区工程技术

Measurement Pub Date : 2026-05-05 Epub Date: 2026-02-25 DOI: 10.1016/j.measurement.2026.120961

Minmin Xu , Mingchun Wang , Yixuan Zeng , Yaoyao Han , Junming Huang , Wennian Yu , Fengshou Gu

{"title":"Dynamic modelling and vibration characteristic analysis of gear transmission system under the effect of time-varying misalignment from clearance of bearings","authors":"Minmin Xu , Mingchun Wang , Yixuan Zeng , Yaoyao Han , Junming Huang , Wennian Yu , Fengshou Gu","doi":"10.1016/j.measurement.2026.120961","DOIUrl":"10.1016/j.measurement.2026.120961","url":null,"abstract":"<div><div>Gear misalignment error is one of the most common errors in manufacturing or assembling process, which leads to uneven distribution of contact stress and increased vibration and noise due to the biased load. It also influences the diagnosis of gear local defects due to the coupling effect of them. To address the gear misalignment errors caused by discrepancies in bearing clearance at both ends of shaft, a coupled gear-shaft-bearing nonlinear dynamic model with 24 DOF is developed. Effect of time-varying misalignment errors on the characteristics of contact, stiffness and vibration are analyzed. Simulations are performed to evaluate the vibration response of the gear transmission system under the excitation of time-varying misalignment from bearing clearances and gear spall. Results indicate that discrepancies of bearing clearances reduce the time-varying meshing stiffness of the gear pair, which generates additional vibration and affects the vibration responses of the gear transmission system. Time-varying misalignment from bearing clearance also contributes the rising of shaft rotating frequency, which results in difficulty to detect early spalling faults on gear surface. Verification experiments are conducted to assess the precision of the enhanced gear-shaft-bearing model. New indicators are proposed to defect the change of gear misalignment error due to bearing clearances. The proposed coupling model contributes to a deeper insight on condition monitoring strategies and early fault diagnosis methodologies for gear transmission systems.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"272 ","pages":"Article 120961"},"PeriodicalIF":5.6,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147388104","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}

引用次数: 0

Waveform-based clustering of fatigue cracking acoustic signatures 基于波形的疲劳裂纹声特征聚类

IF 5.6 2区工程技术

Measurement Pub Date : 2026-05-05 Epub Date: 2026-03-05 DOI: 10.1016/j.measurement.2026.120965

Théotime de la Selle , Stéphanie Deschanel , Jérome Weiss

{"title":"Waveform-based clustering of fatigue cracking acoustic signatures","authors":"Théotime de la Selle , Stéphanie Deschanel , Jérome Weiss","doi":"10.1016/j.measurement.2026.120965","DOIUrl":"10.1016/j.measurement.2026.120965","url":null,"abstract":"<div><div>Identifying signatures of fatigue crack growth and detecting early warnings in service in Non-Destructive Testing applications remain major challenges for research and industry alike. To address these issues, we propose a waveform-based signal processing technique applied to Acoustic Emission (AE) data. This study explores how a fully unsupervised, data-driven approach can cluster acoustic signals based on their physical emission mechanisms associated with fatigue cracking. Using AE datasets recorded during fatigue crack growth tests on compact tension specimens made of aluminum or steel alloys, we demonstrate that hierarchical clustering of acoustic multiplets – signatures of a unique source – is consistent with the phenomenological classification of multiplets previously established distinguishing multiplets generated by local contacts between crack surfaces from those associated with fatigue crack growth at crack tip. Here we show that we can assign physical emission mechanisms to each multiplet solely based on acoustic information through waveform-based dissimilarity measures — unlike standard AE signal processing techniques. Furthermore, by taking advantage of the multiple levels of analysis offered by hierarchical clustering, we significantly improve multiplets detection by reducing dependency on user-parameters. This improvement opens the possibility of developing a more automated Non-Destructive Testing architecture for fatigue cracking signatures detection, thus reducing computational complexity.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"272 ","pages":"Article 120965"},"PeriodicalIF":5.6,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147388105","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}

引用次数: 0

Non-invasive rotor fault measurement in pumped storage systems via enhanced energy entropy analysis and hybrid deep learning with metrological validation 基于增强能量熵分析和混合深度学习的抽水蓄能系统转子无创故障测量

IF 5.6 2区工程技术

Measurement Pub Date : 2026-05-05 Epub Date: 2026-03-07 DOI: 10.1016/j.measurement.2026.121069

Qingqi Lan , Hui Sun , Kang Hu , Qiaorui Si , Yu Wu , Shouqi Yuan

{"title":"Non-invasive rotor fault measurement in pumped storage systems via enhanced energy entropy analysis and hybrid deep learning with metrological validation","authors":"Qingqi Lan , Hui Sun , Kang Hu , Qiaorui Si , Yu Wu , Shouqi Yuan","doi":"10.1016/j.measurement.2026.121069","DOIUrl":"10.1016/j.measurement.2026.121069","url":null,"abstract":"<div><div>To advance measurement methodologies for rotor health monitoring in pumped storage systems, this study proposes a novel non-invasive measurement framework integrating Motor Current Signature Analysis (MCSA) with hybrid deep learning. This method quantifies energy entropy shifts by employing Cyclic Autocorrelation Function (CAF) and Empirical Mode Decomposition (EMD), thereby addressing key metrological challenges including signal noise suppression and uncertainty propagation. Principal Component Analysis (PCA) is rigorously applied to reduce feature dimensionality while preserving measurement integrity. A novel SCSO-CNN-BiLSTM-Attention model is proposed, combining CNN’s spatial feature extraction, BiLSTM’s temporal dependency modeling, and attention-based critical weighting, optimized via Sand Cat Swarm Optimization (SCSO) for hyperparameter tuning with traceable uncertainty budgets. Validated on seven fault conditions, the model achieves 95.24% testing accuracy, outperforming traditional methods in both metrological robustness and computational efficiency. Key innovations include IMF1’s high-frequency sensitivity and IMF4’s low-frequency discriminability. T-SNE visualization confirms enhanced clustering through integrated RMS and IMF entropy features. Despite residual errors in cavitation-coupled faults, the framework demonstrates robust generalizability and real-time potential. This work provides a physics-informed AI solution for centrifugal pump health monitoring, balancing diagnostic precision with computational efficiency for industrial deployment.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"272 ","pages":"Article 121069"},"PeriodicalIF":5.6,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147388165","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}

引用次数: 0

Application of ensemble-based machine learning models for investigating the importance of asphalt pavement design factors on IRI 应用基于集成的机器学习模型研究沥青路面设计因素对IRI的重要性

IF 5.6 2区工程技术

Measurement Pub Date : 2026-05-05 Epub Date: 2026-03-09 DOI: 10.1016/j.measurement.2026.121087

Abdulraaof H. Al-Qaili, Abdullah I. Al-Mansour, Hamad Al-Solieman

{"title":"Application of ensemble-based machine learning models for investigating the importance of asphalt pavement design factors on IRI","authors":"Abdulraaof H. Al-Qaili, Abdullah I. Al-Mansour, Hamad Al-Solieman","doi":"10.1016/j.measurement.2026.121087","DOIUrl":"10.1016/j.measurement.2026.121087","url":null,"abstract":"<div><div>Asphalt pavement design factors play a critical role in determining the quality and longevity of pavements. Understanding how these factors affect the International Roughness Index (IRI) is essential for optimizing pavement performance and improving road quality. In this study, the importance of asphalt pavement design factors on IRI investigate using ensemble-based machine learning models, providing valuable insights for pavement design and maintenance strategies.</div><div>Ensemble models, specifically Random Forest (RF) and Gradient Boosting (GB), were used to analyze the importance of asphalt pavement design factors on the IRI. These algorithms combine the predictive power of multiple decision trees to increase accuracy and identify critical variables that affect IRI.</div><div>The results of the study demonstrated the influence of hyperparameters on model performance and highlighted the importance of parameter tuning for optimal results. Additionally, the study emphasizes the critical role of factors such as temperature, traffic volume, and pavement age in predicting IRI across different models. SHAP analysis revealed the primary factors influencing IRI, conforming the importance of environmental conditions and material properties.</div><div>This study provide valuable insights into the relationships between asphalt pavement design factors and IRI, offering a roadmap for evidence-based decision making in pavement design and management. The findings can guide stakeholders in prioritizing design factors to optimize pavement quality and overall road performance.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"272 ","pages":"Article 121087"},"PeriodicalIF":5.6,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147388161","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}

引用次数: 0

Ordered WO3-decorated ZrO2 nanotubes with efficient three-phase boundary towards highly sensitive detection of trace nitrogen dioxide 具有高效三相边界的有序wo3修饰ZrO2纳米管用于痕量二氧化氮的高灵敏度检测

IF 5.6 2区工程技术

Measurement Pub Date : 2026-05-05 Epub Date: 2026-03-03 DOI: 10.1016/j.measurement.2026.121022

Liang-Bo Bo , Xin-Feng Qiao , Xiao-Hong Zheng , Su-Yue Ren , Zhi-Lei Li , Jing-Wen Pan , Cheng-Yong Chen

{"title":"Ordered WO3-decorated ZrO2 nanotubes with efficient three-phase boundary towards highly sensitive detection of trace nitrogen dioxide","authors":"Liang-Bo Bo , Xin-Feng Qiao , Xiao-Hong Zheng , Su-Yue Ren , Zhi-Lei Li , Jing-Wen Pan , Cheng-Yong Chen","doi":"10.1016/j.measurement.2026.121022","DOIUrl":"10.1016/j.measurement.2026.121022","url":null,"abstract":"<div><div>Long-term exposure to high concentrations of nitrogen dioxide (NO<sub>2</sub>) poses severe risks to both the environment and human health, thereby creating an urgent need for gas sensors that enable sensitive and reliable detection at relatively low operating temperatures. However, most reported NO<sub>2</sub> sensors still suffer from either high operating temperatures or insufficient detection sensitivity, which severely limits their practical application in atmospheric monitoring. In this study, a potential NO<sub>2</sub> sensor based on a ordered WO<sub>3</sub>-decorated ZrO<sub>2</sub> nanotube film was fabricated via anodic oxidation and in-situ growth. The sensing properties, including a low optimum test temperature, low detection limit, high sensitivity, repeatability, and selectivity, were determined. The ordered WO<sub>3</sub>-decorated ZrO<sub>2</sub> nanotube film exhibited a high NO<sub>2</sub> sensitivity (134.8 mV/decade) toward 0.06–10 ppm NO<sub>2</sub> at a medium–low working temperature of 350°C. The high performance of the sensor is primarily attributed to Knudsen diffusion in the ordered nanotube structure and the perfect three-phase boundary (TPB) of the nanocomposite, as the results indicate. This study presents a novel strategy for designing ordered nanostructures and introduces an effective approach for detecting atmospheric NO<sub>2</sub> concentrations.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"272 ","pages":"Article 121022"},"PeriodicalIF":5.6,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147388296","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}

引用次数: 0