Pub Date : 2024-11-16DOI: 10.1016/j.measurement.2024.116241
Ze Chen, Yingjie Mei, Chuanzhi Sun, Yongmeng Liu, Jiubin Tan
The length of aero-engine fan blades usually exceeds 1 m, making contact-based coordinate measuring machines (CMM) costly and time-consuming. To enhance measurement efficiency and accuracy, we developed a large-field flexible measurement system. We propose the system calibration method using a standard sphere as the reference and taking the turntable axis into account. A model-driven path planning and multi-view data fusion (MVDF) strategy was introduced to enhance efficiency and reduce misalignment due to the robotic arm’s lower positioning accuracy. To improve cross-sectional data sorting and thinning, we proposed an adaptive threshold synchronous sorting and noise suppression method. Additionally, we developed algorithms for chord length and maximum thickness extraction to streamline the process. Experiments show improved accuracy for blade thickness (0.092 mm) and chord length (0.096 mm).
{"title":"An efficient automated measurement method for aero-engine fan blade geometric parameters","authors":"Ze Chen, Yingjie Mei, Chuanzhi Sun, Yongmeng Liu, Jiubin Tan","doi":"10.1016/j.measurement.2024.116241","DOIUrl":"10.1016/j.measurement.2024.116241","url":null,"abstract":"<div><div>The length of aero-engine fan blades usually exceeds 1 m, making contact-based coordinate measuring machines (CMM) costly and time-consuming. To enhance measurement efficiency and accuracy, we developed a large-field flexible measurement system. We propose the system calibration method using a standard sphere as the reference and taking the turntable axis into account. A model-driven path planning and multi-view data fusion (MVDF) strategy was introduced to enhance efficiency and reduce misalignment due to the robotic arm’s lower positioning accuracy. To improve cross-sectional data sorting and thinning, we proposed an adaptive threshold synchronous sorting and noise suppression method. Additionally, we developed algorithms for chord length and maximum thickness extraction to streamline the process. Experiments show improved accuracy for blade thickness (0.092 mm) and chord length (0.096 mm).</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"242 ","pages":"Article 116241"},"PeriodicalIF":5.2,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142701696","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 : 2024-11-16DOI: 10.1016/j.measurement.2024.116256
Yanjuan Hu, Qingling Liu, You Zhou, Changhua Yin
In automotive manufacturing, brake disc balance accuracy is critical for braking system reliability. The tracking accuracy of the balancing machine’s turntable servo system directly influences production efficiency and disc balance. To enhance turntable servo control in position and velocity tracking, this paper proposes a fractional order proportional integral derivative (FOPID) controller using a deep deterministic policy gradient (DDPG) algorithm inspired by deep reinforcement learning (DRL). A dynamic model of the servo system is developed to support the design of the DDPG FOPID control strategy. Anti-interference and anti-noise experiments are conducted to compare control strategies including fuzzy logic (Fuzzy), genetic algorithm (GA) PID, particle swarm optimization (PSO) PID, Q-learning PID, DDPG PID and DDPG FOPID through the physical experimental platform of the turntable servo system. Experimental results demonstrate that the DDPG FOPID strategy offers superior robustness and tracking performance, suggesting its potential to advance intelligent control methods in automotive manufacturing.
{"title":"Tracking performance optimization of balancing machine turntable servo system based on deep deterministic policy gradient fractional order proportional integral derivative control strategy","authors":"Yanjuan Hu, Qingling Liu, You Zhou, Changhua Yin","doi":"10.1016/j.measurement.2024.116256","DOIUrl":"10.1016/j.measurement.2024.116256","url":null,"abstract":"<div><div>In automotive manufacturing, brake disc balance accuracy is critical for braking system reliability. The tracking accuracy of the balancing machine’s turntable servo system directly influences production efficiency and disc balance. To enhance turntable servo control in position and velocity tracking, this paper proposes a fractional order proportional integral derivative (FOPID) controller using a deep deterministic policy gradient (DDPG) algorithm inspired by deep reinforcement learning (DRL). A dynamic model of the servo system is developed to support the design of the DDPG FOPID control strategy. Anti-interference and anti-noise experiments are conducted to compare control strategies including fuzzy logic (Fuzzy), genetic algorithm (GA) PID, particle swarm optimization (PSO) PID, Q-learning PID, DDPG PID and DDPG FOPID through the physical experimental platform of the turntable servo system. Experimental results demonstrate that the DDPG FOPID strategy offers superior robustness and tracking performance, suggesting its potential to advance intelligent control methods in automotive manufacturing.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"242 ","pages":"Article 116256"},"PeriodicalIF":5.2,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142701707","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 : 2024-11-15DOI: 10.1016/j.measurement.2024.116245
Hongwei Xu , Pengcheng Li , Jing Wang , Wenkai Liang
The intricacies surrounding the induction of black screen faults in smart watt-hour meters pose a significant challenge, particularly given the vast amount of data training samples and the absence of a robust decision correlation process. To address this, a real-time detection method for black screen faults in single-phase intelligent watt-hour meters is proposed, utilizing a random forest two-classifier approach. This method identifies the black screen fault feature by calculating the entropy value of the relevant attributes and selecting those with higher entropy. The attribute data is then discretized using an equidistant division method. A training sample set for black screen fault detection is constructed based on the bagging method, and decision trees are subsequently built and tailored to the identified fault characteristics. Each tree selects the optimal attribute for branching, which ultimately leads to the development of a second random forest classifier. This classifier employs a majority voting method as its decision rule, effectively delivering black screen fault detection results for single-phase smart meters. Notably, the experimental outcomes demonstrate the accuracy of this approach, as it achieved a remarkably low error rate of only 15 out of 1800 black screen fault test samples.
{"title":"A study on black screen fault detection of single-phase smart energy meter based on random forest binary classifier","authors":"Hongwei Xu , Pengcheng Li , Jing Wang , Wenkai Liang","doi":"10.1016/j.measurement.2024.116245","DOIUrl":"10.1016/j.measurement.2024.116245","url":null,"abstract":"<div><div>The intricacies surrounding the induction of black screen faults in smart watt-hour meters pose a significant challenge, particularly given the vast amount of data training samples and the absence of a robust decision correlation process. To address this, a real-time detection method for black screen faults in single-phase intelligent watt-hour meters is proposed, utilizing a random forest two-classifier approach. This method identifies the black screen fault feature by calculating the entropy value of the relevant attributes and selecting those with higher entropy. The attribute data is then discretized using an equidistant division method. A training sample set for black screen fault detection is constructed based on the bagging method, and decision trees are subsequently built and tailored to the identified fault characteristics. Each tree selects the optimal attribute for branching, which ultimately leads to the development of a second random forest classifier. This classifier employs a majority voting method as its decision rule, effectively delivering black screen fault detection results for single-phase smart meters. Notably, the experimental outcomes demonstrate the accuracy of this approach, as it achieved a remarkably low error rate of only 15 out of 1800 black screen fault test samples.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"242 ","pages":"Article 116245"},"PeriodicalIF":5.2,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142701791","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 : 2024-11-15DOI: 10.1016/j.measurement.2024.116214
Azubuike H. Amadi , Joseph A. Ajienka , Onyewuchi Akaranta , Pwafureino Reuel Moses , Nnaemeka U. Achara , Victor Damilare Ola , Robinson David Udo
Soil resistivity testing has emerged as a crucial tool for assessing soil corrosivity and informing corrosion control strategies. This review paper aims to explore the limitations of soil resistivity testing and provide insights into alternative methods for accurate measurements and assessment. The paper reveals the challenges associated with surface electrode placement, depth limitations, soil heterogeneity, and the influence of surrounding structures and vegetation. It also discusses potential interference and error sources in soil resistivity testing. To overcome these limitations, alternative electrode configurations, advanced placement techniques, and integrated geophysical approaches were explored. The paper revealed the importance of addressing electrical interference and noise, electrode contact resistance, and equipment limitations in resistivity testing. Additionally, it compared pH testing, corrosion coupons, corrosion inhibitors, and cathodic protection. While these techniques offer advantages, they also have limitations, and the limitations presented in this correspondence are argued to exist provided the soil resistivity displays using present techniques.
{"title":"A review of soil resistivity testing for enhanced corrosion Control: Overcoming limitations through integrated geophysical approaches and alternative methodologies","authors":"Azubuike H. Amadi , Joseph A. Ajienka , Onyewuchi Akaranta , Pwafureino Reuel Moses , Nnaemeka U. Achara , Victor Damilare Ola , Robinson David Udo","doi":"10.1016/j.measurement.2024.116214","DOIUrl":"10.1016/j.measurement.2024.116214","url":null,"abstract":"<div><div>Soil resistivity testing has emerged as a crucial tool for assessing soil corrosivity and informing corrosion control strategies. This review paper aims to explore the limitations of soil resistivity testing and provide insights into alternative methods for accurate measurements and assessment. The paper reveals the challenges associated with surface electrode placement, depth limitations, soil heterogeneity, and the<!--> <!-->influence of surrounding structures and vegetation. It also discusses potential interference and error sources in soil resistivity testing. To overcome these limitations, alternative electrode configurations, advanced placement techniques, and integrated geophysical approaches were explored. The paper revealed the importance of addressing electrical interference and noise, electrode contact resistance, and equipment limitations in resistivity testing. Additionally, it compared pH testing, corrosion coupons, corrosion inhibitors, and cathodic protection. While these techniques offer advantages, they also have limitations, and the limitations presented in this correspondence are argued to exist provided the soil resistivity displays using present techniques.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"242 ","pages":"Article 116214"},"PeriodicalIF":5.2,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142705344","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 : 2024-11-15DOI: 10.1016/j.measurement.2024.116172
Jacob Wekalao , Abdullah Baz , Shobhit K. Patel
This study presents an advanced sensor system integrating gold metasurfaces with graphene for the detection of reproductive hormones via refractive index variations. The proposed design operates under terahertz (THz) excitation to exploit the unique molecular signatures of hormones and minimize potential interferences. Comprehensive numerical analysis and finite element method (FEM) simulations were conducted to optimize the sensor’s design parameters and evaluate its efficacy. The optimized sensor exhibits exceptional performance metrics, including a peak sensitivity of 375 GHzRIU−1, a figure of merit (FOM) of 7.693 RIU−1, a quality factor (Q) of 2.381, and a limit of detection (LOD) of 0.556 RIU. Furthermore, the sensor demonstrates two-bit encoding capabilities through modulation of graphene’s chemical potential. Integration of a K-Nearest Neighbors (KNN) Regressor model enhances the sensor’s accuracy while reducing required resources and simulation time by approximately 85 %. These findings demonstrate the sensor’s potential for diverse applications, particularly in the biomedical field.
{"title":"Design and analysis of high-sensitivity hormone sensor with KNN behavior prediction for healthcare and biomedical applications","authors":"Jacob Wekalao , Abdullah Baz , Shobhit K. Patel","doi":"10.1016/j.measurement.2024.116172","DOIUrl":"10.1016/j.measurement.2024.116172","url":null,"abstract":"<div><div>This study presents an advanced sensor system integrating gold metasurfaces with graphene for the detection of reproductive hormones via refractive index variations. The proposed design operates under terahertz (THz) excitation to exploit the unique molecular signatures of hormones and minimize potential interferences. Comprehensive numerical analysis and finite element method (FEM) simulations were conducted to optimize the sensor’s design parameters and evaluate its efficacy. The optimized sensor exhibits exceptional performance metrics, including a peak sensitivity of 375 GHzRIU<sup>−</sup>1, a figure of merit (FOM) of 7.693 RIU<sup>−</sup>1, a quality factor (Q) of 2.381, and a limit of detection (LOD) of 0.556 RIU. Furthermore, the sensor demonstrates two-bit encoding capabilities through modulation of graphene’s chemical potential. Integration of a K-Nearest Neighbors (KNN) Regressor model enhances the sensor’s accuracy while reducing required resources and simulation time by approximately 85 %. These findings demonstrate the sensor’s potential for diverse applications, particularly in the biomedical field.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"242 ","pages":"Article 116172"},"PeriodicalIF":5.2,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142651557","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 : 2024-11-15DOI: 10.1016/j.measurement.2024.116226
Lakshmanaprakash S , Abirami A , Madanachitran R , Mekala R , Vaibhav Hirlekar Vaishali
The major challenges faced in the modern era involve fulfilling urgent needs for multi-access health-tracking systems and reliable identification of diseases. Recent advancements in IoMT and technological innovations are shaping the adoption of smart healthcare systems widely across the world. A sophisticated, round-the-clock health monitoring system is required for the efficient tracking of patients, together with timely medical interventions. State-of-the-art computing and cloud infrastructures shall be demanded from smart medical facilities. This work presents the development of a Deep Optimized Network model: IoMT-enabled intelligent, automated edge computing environment for healthcare monitoring in disease diagnosis. In this regard, we have utilized the technique of feature selection, called Coot Optimized Feature Selection, for choosing only the relevant features from preprocessed medical data so that the performance of the classifier improves both at the time of training and at testing. Further, we propose a novel deep learning-based algorithm called the Convoluted Recurrent Attention Network, CRAN, which can identify and classify various diseases related to genetic disorder, chronic disease, or heart-related disorder while maintaining low time complexity with high efficiency. In this respect, the hyper-parameters of the CRAN model are fine-tuned using the Cray Fish Optimization technique, allowing optimal classification learning. Extensive performance evaluations using the widely recognized open-source medical datasets validate the effectiveness of the proposed DON model. The results identify the outcomes of the model with high accuracy in the classification of diseases, establishing it as a reliable solution for effective health monitoring. From these findings, one may infer that the integration of IoMT with advanced computational techniques would definitely enhance the healthcare delivery systems. With the DON model, high accuracy in disease identification and efficient monitoring lead to better patient outcomes by ensuring streamlined healthcare processes.
现代社会面临的主要挑战包括满足对多入口健康跟踪系统和可靠疾病识别的迫切需求。物联网医疗技术的最新进展和技术创新正在推动智能医疗系统在全球的广泛应用。为了有效追踪病人并及时采取医疗干预措施，需要一个先进的全天候健康监测系统。智能医疗设施需要最先进的计算和云基础设施。这项工作介绍了深度优化网络模型的开发情况：IoMT 支持的智能、自动化边缘计算环境，用于疾病诊断中的医疗监控。在这方面，我们利用了名为 "Coot 优化特征选择 "的特征选择技术，只从预处理的医疗数据中选择相关特征，从而提高分类器在训练和测试时的性能。此外，我们还提出了一种新颖的基于深度学习的算法--卷积递归注意网络（CRAN），它可以识别和分类与遗传疾病、慢性疾病或心脏相关疾病有关的各种疾病，同时保持较低的时间复杂度和较高的效率。在这方面，CRAN 模型的超参数通过 Cray Fish 优化技术进行了微调，从而实现了最佳的分类学习。使用广泛认可的开源医疗数据集进行的广泛性能评估验证了所提出的 DON 模型的有效性。结果表明，该模型在疾病分类方面具有很高的准确性，是有效监测健康状况的可靠解决方案。从这些发现中，我们可以推断出，将 IoMT 与先进的计算技术相融合必将增强医疗保健服务系统。有了 DON 模型，疾病识别的高准确性和有效的监测可确保简化医疗保健流程，从而改善患者的治疗效果。
{"title":"DON: Deep Optimized Network model based on Coot and Convoluted Recurrent learning algorithms for healthcare monitoring in IoMT systems","authors":"Lakshmanaprakash S , Abirami A , Madanachitran R , Mekala R , Vaibhav Hirlekar Vaishali","doi":"10.1016/j.measurement.2024.116226","DOIUrl":"10.1016/j.measurement.2024.116226","url":null,"abstract":"<div><div>The major challenges faced in the modern era involve fulfilling urgent needs for multi-access health-tracking systems and reliable identification of diseases. Recent advancements in IoMT and technological innovations are shaping the adoption of smart healthcare systems widely across the world. A sophisticated, round-the-clock health monitoring system is required for the efficient tracking of patients, together with timely medical interventions. State-of-the-art computing and cloud infrastructures shall be demanded from smart medical facilities. This work presents the development of a Deep Optimized Network model: IoMT-enabled intelligent, automated edge computing environment for healthcare monitoring in disease diagnosis. In this regard, we have utilized the technique of feature selection, called Coot Optimized Feature Selection, for choosing only the relevant features from preprocessed medical data so that the performance of the classifier improves both at the time of training and at testing. Further, we propose a novel deep learning-based algorithm called the Convoluted Recurrent Attention Network, CRAN, which can identify and classify various diseases related to genetic disorder, chronic disease, or heart-related disorder while maintaining low time complexity with high efficiency. In this respect, the hyper-parameters of the CRAN model are fine-tuned using the Cray Fish Optimization technique, allowing optimal classification learning. Extensive performance evaluations using the widely recognized open-source medical datasets validate the effectiveness of the proposed DON model. The results identify the outcomes of the model with high accuracy in the classification of diseases, establishing it as a reliable solution for effective health monitoring. From these findings, one may infer that the integration of IoMT with advanced computational techniques would definitely enhance the healthcare delivery systems. With the DON model, high accuracy in disease identification and efficient monitoring lead to better patient outcomes by ensuring streamlined healthcare processes.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"242 ","pages":"Article 116226"},"PeriodicalIF":5.2,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142701695","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 : 2024-11-15DOI: 10.1016/j.measurement.2024.116224
Jin Huang , Haoda Li , Zichen Liu , Zhikun Wang , Yingqiang Wang , Ying Chen
The integrated navigation system (INS), which integrates the strap-down inertial navigation system (SINS) and the Doppler velocity log (DVL), is widely used in the application of autonomous underwater vehicle (AUV) navigation and positioning. However, due to the constraints imposed by the AUV’s size and system design, a coordinate system mismatch occurs between the DVL and SINS, which can be modeled as installation error (IE), including installation error angles and lever arm errors that significantly impact the system’s accuracy. To address these issues, we introduce an INS based on feedback error-state Kalman filter (ESKF) that accounts for DVL installation error (IE) and propose a DVL IE compensation method. This paper details the system design of the ESKF-based INS, including the coarse initial alignment of the moving base, fine alignment, mechanization, and data fusion. The proposed IE compensation method is designed to successively estimate and correct the DVL IE, utilizing the global navigation satellite system (GNSS) for observations, minimizing the error model output to estimate the IE value. Simulations and field experiments indicate that the cumulative accuracy has been improved by 50.3% after compensation. Finally, carried by a disc-shaped AUV, the ESKF-based INS with DVL IE compensation performs well in practical AUV navigation applications.
综合导航系统（INS）集成了带式惯性导航系统（SINS）和多普勒速度记录仪（DVL），广泛应用于自主潜水器（AUV）的导航和定位。然而，由于 AUV 的尺寸和系统设计的限制，DVL 和 SINS 之间会出现坐标系不匹配的情况，这种不匹配可模拟为安装误差 (IE)，包括安装误差角和杠杆臂误差，对系统的精度造成严重影响。为解决这些问题，我们引入了一种基于反馈误差状态卡尔曼滤波器（ESKF）的 INS，该 INS 考虑了 DVL 安装误差（IE），并提出了一种 DVL IE 补偿方法。本文详细介绍了基于 ESKF 的 INS 的系统设计，包括移动基座的粗初始对准、精细对准、机械化和数据融合。所提出的 IE 补偿方法旨在利用全球导航卫星系统（GNSS）进行观测，通过最小化误差模型输出来估算 IE 值，从而连续估算和修正 DVL IE。模拟和现场实验表明，补偿后的累积精度提高了 50.3%。最后，基于 ESKF 和 DVL IE 补偿的 INS 由圆盘形 AUV 搭载，在实际 AUV 导航应用中表现良好。
{"title":"GNSS-aided installation error compensation for DVL/INS integrated navigation system using error-state Kalman filter","authors":"Jin Huang , Haoda Li , Zichen Liu , Zhikun Wang , Yingqiang Wang , Ying Chen","doi":"10.1016/j.measurement.2024.116224","DOIUrl":"10.1016/j.measurement.2024.116224","url":null,"abstract":"<div><div>The integrated navigation system (INS), which integrates the strap-down inertial navigation system (SINS) and the Doppler velocity log (DVL), is widely used in the application of autonomous underwater vehicle (AUV) navigation and positioning. However, due to the constraints imposed by the AUV’s size and system design, a coordinate system mismatch occurs between the DVL and SINS, which can be modeled as installation error (IE), including installation error angles and lever arm errors that significantly impact the system’s accuracy. To address these issues, we introduce an INS based on feedback error-state Kalman filter (ESKF) that accounts for DVL installation error (IE) and propose a DVL IE compensation method. This paper details the system design of the ESKF-based INS, including the coarse initial alignment of the moving base, fine alignment, mechanization, and data fusion. The proposed IE compensation method is designed to successively estimate and correct the DVL IE, utilizing the global navigation satellite system (GNSS) for observations, minimizing the error model output to estimate the IE value. Simulations and field experiments indicate that the cumulative accuracy has been improved by 50.3% after compensation. Finally, carried by a disc-shaped AUV, the ESKF-based INS with DVL IE compensation performs well in practical AUV navigation applications.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"242 ","pages":"Article 116224"},"PeriodicalIF":5.2,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142701709","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 ultrasound wireless power transmission (UWPT) technology often faces challenges such as low power transmission efficiency and safety concerns. This paper proposes a highly reliable α–alumina integrated ultrasound transducer–based ultrasound wireless power transmission (IUT–UWPT) system designed for metallic medium. The proposed system is capable of powering and communicating with embedded sensors inside metal–sealed tanks. An acoustic wave transmission model for the IUT–UWPT system is developed based on acoustic theory to optimize the thickness of the matching layer and bonding layers between piezoelectric ceramics and metallic medium. The effect of the α–alumina integrated ultrasound transducer on the input–output characteristics of the system is analyzed using the mason equivalent circuit method considering acoustic attenuation and finite element simulation. Experimental results show that, compared to traditional UWPT systems without α–alumina integrated ultrasound transducer, the IUT–UWPT system exhibits a broader frequency response range from 0.8 MHz to 1.2 MHz and achieves a 13.19 % increase in maximum output power. Notably, the insulating properties of the α–alumina integrated ultrasound transducer prevent electrical generation on the surface of the metal–sealed tank. This system is well–suited for health monitoring in storage facilities such as gas pipelines, liquid nitrogen tanks and nuclear waste containers.
{"title":"Design of α–alumina integrated ultrasound transducer for wireless power transmission system","authors":"Bingrui Zhang, Juan Cui, Zheng Wang, Mingzheng Zhang, Yongqiu Zheng, Chenyang Xue","doi":"10.1016/j.measurement.2024.116221","DOIUrl":"10.1016/j.measurement.2024.116221","url":null,"abstract":"<div><div>Traditional ultrasound wireless power transmission (UWPT) technology often faces challenges such as low power transmission efficiency and safety concerns. This paper proposes a highly reliable α–alumina integrated ultrasound transducer–based ultrasound wireless power transmission (IUT–UWPT) system designed for metallic medium. The proposed system is capable of powering and communicating with embedded sensors inside metal–sealed tanks. An acoustic wave transmission model for the IUT–UWPT system is developed based on acoustic theory to optimize the thickness of the matching layer and bonding layers between piezoelectric ceramics and metallic medium. The effect of the α–alumina integrated ultrasound transducer on the input–output characteristics of the system is analyzed using the mason equivalent circuit method considering acoustic attenuation and finite element simulation. Experimental results show that, compared to traditional UWPT systems without α–alumina integrated ultrasound transducer, the IUT–UWPT system exhibits a broader frequency response range from 0.8 MHz to 1.2 MHz and achieves a 13.19 % increase in maximum output power. Notably, the insulating properties of the α–alumina integrated ultrasound transducer prevent electrical generation on the surface of the metal–sealed tank. This system is well–suited for health monitoring in storage facilities such as gas pipelines, liquid nitrogen tanks and nuclear waste containers.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"242 ","pages":"Article 116221"},"PeriodicalIF":5.2,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142701794","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 : 2024-11-15DOI: 10.1016/j.measurement.2024.116217
Zefeng Li , Yuwei Qu , Xin Wang , Yuheng Wang , Danian Wang , Xiaoyue Guo , Changhua Xin , Qian Qiu , Lan Rao , Jinhui Yuan
In this paper, a water-filled D-shaped photonic crystal fiber (WFDSPCF) sensor based on the birefringence response for simultaneously measuring the liquid refractive index (LRI) and liquid temperature (LT) is proposed. We undertake theoretical and simulation calculations, and the results show that the proposed WFDSPCF can achieve ultrahigh LRI and LT sensitivities when operating around the group birefringence turning point. By optimizing the structural parameters, the proposed WFDSPCF sensor can achieve LRI and LT sensitivities of -25642.86 nm/RIU and 12.8 nm/°C, respectively. In addition, in order to eliminate the sensing crosstalk between the LRI and LT, a parallel Lyot interferometer structure is also proposed. The proposed WFDSPCF sensor is expected to have potential use in biochemical sensing, measurement science, and environmental monitoring.
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A comprehensive evaluation of surface topography can contribute to many appropriate responses on the properties of manufactured products. Precise measurement and data processing may allow for improvement in the control quality. Many advantages were achieved in the increasing accuracy of the surface topography measuring devices and whole control systems. Since contactless measuring equipment is much faster than tactile, analysis of surface topography for industrial applications was encouraged under the non-contact systems. However, those rapidly evolving measuring techniques are fraught with many external disturbances which can radically affect the final surface topography measurement results. One of the often considered errors is those strictly related to the vibrations. As the effect of this type of external disturbance, the surface topography measurement results are burdened with the occurrence of high-frequency noise. A standardised and often proposed method for the compensation of this type of measurement error is to repeat the measurement process and average the received results. It seems to be the most encouraging proposal, however, the time-reducing requirements from the industry performance do not pose this solution as optimal. Therefore, a well-known and often used in surface metrology is an S-filter, data processing algorithm based on the Gaussian weighting function. From many intensive studies, it was concluded that this filtering approach may increase errors in the calculation of ISO 25178 surface texture parameters. Some of the ISO 25178 surface texture parameters were distorted by more than 100%, especially those sensitive to the occurrence of high-frequency measurement noise. Therefore, alternatively, to the general Gaussian filter, many other filtering methods were applied in surface metrology. However, the process of selection of a vibrational noise reduction filter must be validated before any proposals. One of the main objectives of the present work is to guide the regular user on how to select an appropriate filtering method for many types of etched surface topographies measured with a contactless white light interference method considering the reduction of both high-frequency noise and its impact on the variations of surface texture parameters. From the studied filtering methods, the spline filter gave the most encouraging results. As the final, the proposed methodology was validated in terms of ISO 25178 surface texture parameters evaluation comparing them to the results obtained by an international procedure based on the measurement repetitions.
对表面形貌的全面评估有助于对制成品的特性做出许多适当的反应。精确的测量和数据处理可以提高控制质量。在提高表面形貌测量设备和整个控制系统的精度方面取得了许多优势。由于非接触式测量设备比接触式测量设备速度更快，因此在非接触式系统下鼓励对工业应用中的表面形貌进行分析。然而，这些快速发展的测量技术充满了许多外部干扰，会从根本上影响最终的表面形貌测量结果。其中一个经常被考虑的误差就是与振动严格相关的误差。由于这类外部干扰的影响，表面形貌测量结果会受到高频噪声的影响。为补偿这类测量误差，经常提出的一种标准化方法是重复测量过程并将所得结果平均化。这似乎是最令人鼓舞的建议，然而，工业性能对缩短时间的要求并没有使这一解决方案成为最佳方案。因此，表面计量学中常用的一种著名算法是基于高斯加权函数的数据处理算法 S-滤波器。许多深入研究得出结论，这种滤波方法可能会增加 ISO 25178 表面纹理参数计算的误差。一些 ISO 25178 表面纹理参数的失真度超过 100%，尤其是那些对高频测量噪声敏感的参数。因此，除了一般的高斯滤波器，表面计量学中还应用了许多其他滤波方法。然而，在提出任何建议之前，都必须对振动降噪滤波器的选择过程进行验证。本研究的主要目的之一是指导普通用户如何为使用非接触式白光干涉测量法测量的多种类型蚀刻表面形貌选择合适的滤波方法，同时考虑降低高频噪声及其对表面纹理参数变化的影响。在所研究的滤波方法中，样条线滤波器的结果最令人鼓舞。最后，在 ISO 25178 表面纹理参数评估方面，对所提出的方法进行了验证，并将其与基于重复测量的国际程序所获得的结果进行了比较。
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