Measurement最新文献_第2页

ALDNet: A two-stage method with deep aggregation and multi-scale fusion for apple leaf disease spot segmentation 基于深度聚集和多尺度融合的两阶段苹果叶片病斑分割方法

IF 5.2 2区工程技术

Measurement Pub Date : 2025-05-12 DOI: 10.1016/j.measurement.2025.117706

Jixiang Cheng, Zujian Song, Yuan Wu, Jiayue Xu

{"title":"ALDNet: A two-stage method with deep aggregation and multi-scale fusion for apple leaf disease spot segmentation","authors":"Jixiang Cheng, Zujian Song, Yuan Wu, Jiayue Xu","doi":"10.1016/j.measurement.2025.117706","DOIUrl":"10.1016/j.measurement.2025.117706","url":null,"abstract":"<div><div>Deep learning has been successfully applied in plant leaf disease segmentation in simple environments. However, complex environments pose challenges like blurred boundaries and small disease spots. To tackle these issues, this paper proposes ALDNet, a two-stage method utilizing PBGNet for leaf segmentation and PDFNet for disease spot extraction. PBGNet incorporates a deep aggregation (DA) module to generate an initial segmentation map enriched with global contextual information, and the features guided by the reverse attention (RA) are fused to the shallowest levels to enhance target leaf boundary precision. PDFNet combines residual path and multi-scale fusion (MSF) to enhance feature representation and fuse semantic and scale features from different branches, facilitating small spot extraction. ALDNet outperforms state-of-the-art methods in complex environments, achieving 94.53% IoU and 98.13% PA for leaf segmentation, and 77.41% mIoU and 84.1% mPA for disease segmentation. ALDNet provides a reliable solution for accurate severity grading of apple leaf diseases.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"253 ","pages":"Article 117706"},"PeriodicalIF":5.2,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144069270","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

Effective visual measurement system for SPT hammer energy measurement 有效的SPT锤击能量可视化测量系统

IF 5.2 2区工程技术

Measurement Pub Date : 2025-05-12 DOI: 10.1016/j.measurement.2025.117777

M E Yadhunandan, Panjamani Anbazhagan

{"title":"Effective visual measurement system for SPT hammer energy measurement","authors":"M E Yadhunandan, Panjamani Anbazhagan","doi":"10.1016/j.measurement.2025.117777","DOIUrl":"10.1016/j.measurement.2025.117777","url":null,"abstract":"<div><div>The Standard Penetration Test (SPT) is prone to variability due to complex energy transfer dynamics and equipment inconsistencies. Traditional force and acceleration measurements provide valuable data but fail to fully capture the multidimensional movement of SPT components. Therefore, visual measurements of SPT components using a Line-scan and High-Speed Camera (HSC) with target markers have been attempted, but these are limited to 2-dimensional movements. To address these limitations, this study presents a novel HSC system integrated with circular target markings, offering the measurement of movement of SPT component assembly in all three dimensions and Energy Transfer Ratio (ETR). Controlled laboratory SPT tests were conducted to validate the approach. Experiments were carried out for various range of N-values (N = 5 to R), where vertical displacement corresponds to varying soil relative densities (∼15–90 %) and penetration depths (∼60–3 mm) for a consistent ∼60 % input ETR. ETR was estimated using the proposed method and compared with traditional force and acceleration measurements obtained from the SPT Hammer Energy Measurement Apparatus (SPT-HEMA) at both the anvil and sampler levels. The vertical displacement from HSC matched within ± 0.1 mm of manual vernier-caliper measurements. The Comparison reveals strong agreement on displacement, velocity, and ETR values for all penetration resistance. The standard error in ETR values between HSC and SPT-HEMA was below 0.5 %. For the same rod length, lower N-values exhibit longer displacement and ETR durations, while higher N-values show shorter displacement duration and concentrated energy dissipation. The proposed approach improves accuracy in SPT dynamics and testing methodologies.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"253 ","pages":"Article 117777"},"PeriodicalIF":5.2,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143947181","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

Online adaptive transfer learning for aeroengine on-board gas path modeling under domain shifts 领域移位下航空发动机机载气路建模的在线自适应迁移学习

IF 5.2 2区工程技术

Measurement Pub Date : 2025-05-12 DOI: 10.1016/j.measurement.2025.117834

Zepeng Wang, Jinghui Xu, Xizhen Wang, Kaiqiang Yang, Yongjun Zhao

{"title":"Online adaptive transfer learning for aeroengine on-board gas path modeling under domain shifts","authors":"Zepeng Wang, Jinghui Xu, Xizhen Wang, Kaiqiang Yang, Yongjun Zhao","doi":"10.1016/j.measurement.2025.117834","DOIUrl":"10.1016/j.measurement.2025.117834","url":null,"abstract":"<div><div>The on-board gas path model is crucial for gas path analysis and aero-engine health management. However, domain shifts caused by gas path degradation, component replacement, and engine differences challenge on-board modeling. Traditional offline transfer learning (TL) methods struggle with the online nature of sensor data. This paper proposes an online adaptive transfer learning (OATL) method integrating TL with online learning (OL) to enable real-time adaptation. Using a component-level model (CLM), a stacked LSTM network is trained under clean conditions. The OATL method combines online fine-tuning and dynamic weight adjustment between source and target domains for rapid adaptation. Validated on simulated and actual flight data, OATL significantly improves adaptability and prediction accuracy, outperforming traditional methods. It provides an effective solution for real-time aeroengine modeling under continuous domain transitions. It provides an effective solution for on-board gas path modeling in the complex operating environments of aeroengines under conditions of domain shifts.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"253 ","pages":"Article 117834"},"PeriodicalIF":5.2,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144069274","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

EYRINA: A device for automatic capture of extended retinal images 用于自动捕获扩展视网膜图像的设备

IF 5.2 2区工程技术

Measurement Pub Date : 2025-05-11 DOI: 10.1016/j.measurement.2025.117824

Petr Malaník , Martin Drahanský , Jan Kubíček , Tomáš Mňuk , Matylda Musilová , Jitka Mohelníková

引用次数: 0

Measurement uncertainty quantification for computer vision-based structural dynamic displacement monitoring 基于计算机视觉的结构动态位移监测测量不确定度量化

IF 5.2 2区工程技术

Measurement Pub Date : 2025-05-11 DOI: 10.1016/j.measurement.2025.117835

Shengfei Zhang , Pinghe Ni , Qiang Han , Jianian Wen , Xiuli Du , Jun Li

{"title":"Measurement uncertainty quantification for computer vision-based structural dynamic displacement monitoring","authors":"Shengfei Zhang , Pinghe Ni , Qiang Han , Jianian Wen , Xiuli Du , Jun Li","doi":"10.1016/j.measurement.2025.117835","DOIUrl":"10.1016/j.measurement.2025.117835","url":null,"abstract":"<div><div>The structural dynamic displacement response is a crucial indicator for assessing the condition and performance of structures. Computer vision-based structural dynamic displacement measurement (CV-SDDM) has emerged as a promising non-contact technique. However, a key aspect of promoting any measurement technology is the scientific assessment of its measurement uncertainty. This study develops a measurement uncertainty quantification model for CV-SDDM systems and proposes specific quantification methods. The proposed approach is validated through a bridge shaker experiment, demonstrating that the measurement errors of CV-SDDM consistently fall within the estimated uncertainty bounds. Quantitatively, the highest exceedance rate of measurements beyond the estimated uncertainty bounds was 2.03 %, while in most cases it remained below 1 %. Furthermore, this study analyzes the effects of hardware parameters and software algorithms on measurement uncertainty. CV-SDDM systems offer flexible hardware configurations for different monitoring scenarios. This study discusses how these configurations affect system performance and provides practical guidelines for researchers and engineers.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"253 ","pages":"Article 117835"},"PeriodicalIF":5.2,"publicationDate":"2025-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144070852","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

Effect of E-waste on concrete during combined chlorination and compression loading using electro-mechanical impedance technique 利用机电阻抗技术研究氯化压缩复合加载过程中电子垃圾对混凝土的影响

IF 5.2 2区工程技术

Measurement Pub Date : 2025-05-11 DOI: 10.1016/j.measurement.2025.117832

Gaurav Kumar, Tushar Bansal, Dayanand Sharma

{"title":"Effect of E-waste on concrete during combined chlorination and compression loading using electro-mechanical impedance technique","authors":"Gaurav Kumar, Tushar Bansal, Dayanand Sharma","doi":"10.1016/j.measurement.2025.117832","DOIUrl":"10.1016/j.measurement.2025.117832","url":null,"abstract":"<div><div>This study investigates the effect of electronic waste (E-waste) on durability properties, resonance frequency, amplitude, statistical parameters and equivalent stiffness of concretes during combined chlorination action and compression loading using surface bonded piezo sensor (SBPS) based electro-mechanical impedance (EMI) technique. The experiment was conducted on prism specimens which are made up of conventional concrete and E-waste concrete (15 % replacement of natural aggregate by weight with E-waste). Several parameters including chloride penetration, chloride profiles, diffusion coefficient, and surface concentration are determined to understand the effect on chloride profiles. The EMI signatures and statistical parameters such as Root Mean Square Deviation (RMSD) are determined for qualitative and quantitative analysis of signatures. Further, the equivalent structural parameters such as mass and stiffness were identified to assess the deterioration of concrete in terms of mechanical parameters. Based on the results, it is found that the RMSD value of conventional concrete shows a steady increase in deterioration up to 13 % by day 19 before stabilizing, E-waste concrete experiences a more significant peak deviation of 32.83 % by day 23. E-waste concrete exhibits a more significant initial stiffness loss, dropping from 93.7 kNs/m to 57.48 kNs/m in just 9 days, whereas conventional concrete declines gradually from 21.84 kNs/m to 20.20 kNs/m. Thus, it is concluded that E-waste concrete exhibits higher initial deterioration, with significant stiffness and mass loss, as well as greater RMSD deviations.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"253 ","pages":"Article 117832"},"PeriodicalIF":5.2,"publicationDate":"2025-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143947143","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

Statistical correlation neural network for small sample data and its engineering application: Predicting maximum mises stress on ultrasonic-assisted grinding surfaces 小样本数据统计相关神经网络及其工程应用：超声辅助磨削表面最大应力预测

IF 5.2 2区工程技术

Measurement Pub Date : 2025-05-11 DOI: 10.1016/j.measurement.2025.117823

Jiling Chen , Xin Li , Jinyuan Tang , Tiancheng Li , Wen Shao , Yuqin Wen

{"title":"Statistical correlation neural network for small sample data and its engineering application: Predicting maximum mises stress on ultrasonic-assisted grinding surfaces","authors":"Jiling Chen , Xin Li , Jinyuan Tang , Tiancheng Li , Wen Shao , Yuqin Wen","doi":"10.1016/j.measurement.2025.117823","DOIUrl":"10.1016/j.measurement.2025.117823","url":null,"abstract":"<div><div>We propose a statistical correlation neural network applied to small sample data, which intuitively characterizes the statistical correlation between input and output variables, improves the generalization ability of the BP neural network, and reduces data dependency. As an engineering example, we apply the new model to construct a correlation model between rough surface characterization parameters and maximum mises stress in ultrasonic-assisted grinding. In particular, the correlation between the set of crucial characterization parameters in the virtual samples was characterized using the Johnson transformation method mathematical model, and the mises stress calculation was built using the ellipsoidal asperity fitting method. Then, ultrasonic-assisted grinding experiments were carried out to verify the validity of the new model. The comparison between the BP neural network and the statistical correlation neural network shows a reduction in the mean absolute percentage error of maximum Mises stress from 6.36 % to 2.97 %, and the mean absolute error of Kendall’staucorrelationcoefficient was reduced from 0.25 to 0.11. The results show that the statistical correlation neural network constructs a more effective agent model based on the small sample data by characterizing the statistical correlation between the input and the output variables. It reduces the manufacturing cost and provides a theoretical basis for subsequent machining parameter optimization.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"253 ","pages":"Article 117823"},"PeriodicalIF":5.2,"publicationDate":"2025-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143947182","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

Measurement and analysis of dynamic load sharing in planetary gear trains considering high power operations and system errors 考虑大功率运行和系统误差的行星轮系动负载分担测量与分析

IF 5.2 2区工程技术

Measurement Pub Date : 2025-05-11 DOI: 10.1016/j.measurement.2025.117828

Cheng Wang

{"title":"Measurement and analysis of dynamic load sharing in planetary gear trains considering high power operations and system errors","authors":"Cheng Wang","doi":"10.1016/j.measurement.2025.117828","DOIUrl":"10.1016/j.measurement.2025.117828","url":null,"abstract":"<div><div>Studying load sharing in planetary gear trains (PGTs) is crucial for enhancing their load capacity and minimizing vibration and noise. One of the primary factors influencing load sharing is the presence of various types of errors within the system. PGTs are inherently complex mechanical systems that involve numerous types of errors, making it impossible for theoretical models to comprehensively capture all of these errors. Therefore, research often necessitates focusing on certain errors, inevitably leading to limited outcomes. Current research has also emphasized this point. Experimentation is the most effective methodology; however, current experiments have not fully accounted for high-power operating conditions due to experimental costs and methodologies. High power is another important factor affecting load sharing. The load sharing coefficient is used to quantify the degree of load distribution among its components. In response to the aforementioned challenges, this paper proposes a precise measurement methodology for the dynamic load sharing coefficient of PGTs under high-power conditions, taking into account integrated errors within the system. Based on the processing and analysis of a large amount of collected data, the influence of high power (including rotational speed and torque) and the number of planetary gears on the dynamic load sharing coefficient is investigated. This work provides guidance for improving the load-bearing capacity and reducing vibration and noise in PGTs.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"253 ","pages":"Article 117828"},"PeriodicalIF":5.2,"publicationDate":"2025-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143947183","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

Sensor reduction of batch-produced satellites based on prediction of machine learning model 基于机器学习模型预测的批量生产卫星传感器缩减

IF 5.2 2区工程技术

Measurement Pub Date : 2025-05-11 DOI: 10.1016/j.measurement.2025.117829

Jie Zhang , Sang Ye , Hao Sun , Pu Yang , Jiachong Yin

{"title":"Sensor reduction of batch-produced satellites based on prediction of machine learning model","authors":"Jie Zhang , Sang Ye , Hao Sun , Pu Yang , Jiachong Yin","doi":"10.1016/j.measurement.2025.117829","DOIUrl":"10.1016/j.measurement.2025.117829","url":null,"abstract":"<div><div>The extensive use of sensors conflicts with the tight schedules and rapid data-processing needs of batch-produced satellites. Existing sensor reduction methods cannot fit the engineering realities of batch-produced satellites, where some locations are unsuitable for sensors, data reduction overlooks key inter-satellite differences, and precise sensor positioning is difficult. In this paper, a combined method of K-means clustering for sensor reduction and fully neural network (FCNN) for response prediction was proposed. This approach constructs candidate sensors and adjusts data structures to suit batch-satellite engineering realities. Additionally, the effects of model algorithms and training-set data were studied. The main findings are as follows: (1) The proposed combined method of K – means clustering and FCNN is effective and robust for sensor reduction of batch-produced satellites. (2) The numbers of hidden layers and neurons in FCNN as well as the number of retained sensors in K – means clustering have little effect on the results. (3) The training set is preferred to encompass data of every vibration direction and amplitude to ensure robust generalization capacities.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"253 ","pages":"Article 117829"},"PeriodicalIF":5.2,"publicationDate":"2025-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143947146","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

Detection of total bilirubin based on multi-wavelength excitation fluorescence spectroscopy 基于多波长激发荧光光谱法检测总胆红素

IF 5.2 2区工程技术

Measurement Pub Date : 2025-05-10 DOI: 10.1016/j.measurement.2025.117807

Kang Wang , Shuo Wang , Ling Lin , Zhe Zhao , Gang Li

{"title":"Detection of total bilirubin based on multi-wavelength excitation fluorescence spectroscopy","authors":"Kang Wang , Shuo Wang , Ling Lin , Zhe Zhao , Gang Li","doi":"10.1016/j.measurement.2025.117807","DOIUrl":"10.1016/j.measurement.2025.117807","url":null,"abstract":"<div><div>Due to the overlapping absorption lines of all components in the blood, the spectrum of total bilirubin is largely obscured by strongly absorbing components, making it difficult to obtain high-precision detection results. Therefore, this article proposes a detection method for multi wavelength excitation fluorescence spectroscopy. The experiment collected fluorescence spectra of 325 samples at four wavelengths and established a total bilirubin model. In the experimental results, compared with the single wavelength method, the multi wavelength method reduced the root mean square error of the modeling set and prediction set by 50.5 % and 55.7 %, respectively, and reduced the mean absolute error of the sample prediction results to 2.121 <span><math><mrow><mi>μ</mi><mi>m</mi><mi>o</mi><mi>l</mi><mo>/</mo><mi>L</mi></mrow></math></span>. The experimental results show that this article improves the spectral line difference coefficient between target and non-target components by increasing the information carried by the spectrum and the constraint equation of data analysis, while providing a complete research idea and method for the detection of other blood components with fluorescence effects.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"253 ","pages":"Article 117807"},"PeriodicalIF":5.2,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143947184","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