Pub Date : 2024-01-12DOI: 10.1088/1361-6501/ad1e1d
Luiza Felippi de Lima, Roberta Dutra, Diego González, Rubem Luis Sommer, C A Perottoni, C. Aguzzoli, Mariana Roesch-Ely
Magnetoelastic resonance devices are attractive for application as biosensors in health-related areas as they allow contactless detection of pathogenic agents with high sensitivity. After functionalization, they offer valuable diagnostic options that promote efficient capture of mass on the sensor surface through biological interactions. Magnetoelastic sensors are also sensitive to external factors such as temperature, magnetic fields, and variations in mass that can arise from processes unrelated to biological interactions, including corrosion and salt crystallization. This article evaluates extrinsic factors that affect the response of magnetoelastic resonance sensors for diagnostic applications. In particular, the influence of heat treatments, operation temperature, applied DC magnetic field bias, and corrosive environment were studied. The control of all these factors is crucial for the design, fabrication, and functionalization of magnetoelastic resonance biosensors and for the development of measuring instrumentation and effective measurement protocols. This work established maximum operating temperature and bias field variations to keep the sensor sensitivity. Heat treatment of the sensors before and after coating improved the signal-to-noise ratio and corrosion resistance. Further improvement in corrosion resistance was provided by cathodic protection, which has been proven beneficial for applications of magnetoelastic resonance sensors in aqueous fluids.
{"title":"Role of extrinsic factors on magnetoelastic resonance biosensors sensitivity","authors":"Luiza Felippi de Lima, Roberta Dutra, Diego González, Rubem Luis Sommer, C A Perottoni, C. Aguzzoli, Mariana Roesch-Ely","doi":"10.1088/1361-6501/ad1e1d","DOIUrl":"https://doi.org/10.1088/1361-6501/ad1e1d","url":null,"abstract":"\u0000 Magnetoelastic resonance devices are attractive for application as biosensors in health-related areas as they allow contactless detection of pathogenic agents with high sensitivity. After functionalization, they offer valuable diagnostic options that promote efficient capture of mass on the sensor surface through biological interactions. Magnetoelastic sensors are also sensitive to external factors such as temperature, magnetic fields, and variations in mass that can arise from processes unrelated to biological interactions, including corrosion and salt crystallization. This article evaluates extrinsic factors that affect the response of magnetoelastic resonance sensors for diagnostic applications. In particular, the influence of heat treatments, operation temperature, applied DC magnetic field bias, and corrosive environment were studied. The control of all these factors is crucial for the design, fabrication, and functionalization of magnetoelastic resonance biosensors and for the development of measuring instrumentation and effective measurement protocols. This work established maximum operating temperature and bias field variations to keep the sensor sensitivity. Heat treatment of the sensors before and after coating improved the signal-to-noise ratio and corrosion resistance. Further improvement in corrosion resistance was provided by cathodic protection, which has been proven beneficial for applications of magnetoelastic resonance sensors in aqueous fluids.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":"15 9","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139437304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2024-01-11DOI: 10.1088/1361-6501/ad1db1
Pengfei Zhang, Yuanxi Yang, R. Tu, Yuping Gao, Bing Wang
The carrier-phase (CP) technique based on the BeiDou global satellite navigation system (BDS-3) has proven to be an important spatial tool for remote time and frequency transfer. The current CP technique models the receiver clock offset as a white noise stochastic process, and easily absorbs some unmodeled errors, which compromises time and frequency transfer performance. To further improve the performance of time and frequency transfer, a new BDS-3 receiver clock estimation algorithm based on the epoch-difference (ED) model is presented, and the mathematical principle and applied mode are discussed. The algorithm makes full use of both observation of current epoch and practical variation of receiver clock offset, further improving the performance of time and frequency transfer. Five MGEX network stations equipped with various types of receivers and antennas with dual-frequency BDS-3 signals were used to establish four time transfer links (i.e., AMC4–PTBB, BRUX–PTBB, OP71–PTBB, and WTZS–PTBB) to evaluate their effectiveness. The ED model improved all four time links in terms of noise level, with improvements of 17.0%, 18.3%, 20.3%, and 5.9% for AMC4–PTBB, BRUX–PTBB, OP71–PTBB, and WTZS–PTBB, respectively, when compared with the results from a non-ED model. ED model outputs were better than raw solutions in terms of frequency stability at all time links, particularly for average time intervals (tau) < 1,000 s. The mean improvement was 8.1% for AMC4–PTBB, 16.1% for BRUX–PTBB, 10.0% for OP71–PTBB, and 18.6% for WTZS–PTBB when the average time (tau) was less than 1,000 s.
{"title":"Improved performance of BDS-3 time and frequency transfer based on an epoch differenced model with receiver clock estimation","authors":"Pengfei Zhang, Yuanxi Yang, R. Tu, Yuping Gao, Bing Wang","doi":"10.1088/1361-6501/ad1db1","DOIUrl":"https://doi.org/10.1088/1361-6501/ad1db1","url":null,"abstract":"\u0000 The carrier-phase (CP) technique based on the BeiDou global satellite navigation system (BDS-3) has proven to be an important spatial tool for remote time and frequency transfer. The current CP technique models the receiver clock offset as a white noise stochastic process, and easily absorbs some unmodeled errors, which compromises time and frequency transfer performance. To further improve the performance of time and frequency transfer, a new BDS-3 receiver clock estimation algorithm based on the epoch-difference (ED) model is presented, and the mathematical principle and applied mode are discussed. The algorithm makes full use of both observation of current epoch and practical variation of receiver clock offset, further improving the performance of time and frequency transfer. Five MGEX network stations equipped with various types of receivers and antennas with dual-frequency BDS-3 signals were used to establish four time transfer links (i.e., AMC4–PTBB, BRUX–PTBB, OP71–PTBB, and WTZS–PTBB) to evaluate their effectiveness. The ED model improved all four time links in terms of noise level, with improvements of 17.0%, 18.3%, 20.3%, and 5.9% for AMC4–PTBB, BRUX–PTBB, OP71–PTBB, and WTZS–PTBB, respectively, when compared with the results from a non-ED model. ED model outputs were better than raw solutions in terms of frequency stability at all time links, particularly for average time intervals (tau) < 1,000 s. The mean improvement was 8.1% for AMC4–PTBB, 16.1% for BRUX–PTBB, 10.0% for OP71–PTBB, and 18.6% for WTZS–PTBB when the average time (tau) was less than 1,000 s.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":"10 3","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139438883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The free calcium oxide (f-CaO) content in cement clinker serves as a critical quality indicator for cement production. However, many soft sensor models employed for predicting f-CaO content utilize a limited amount of labeled data, leading to the underutilization of a substantial volume of unlabeled data and its associated information. To tackle these challenges, this study introduces soft sensor methodology based on improved semi-supervised Attention Stacked Autoencoders (ASS-SAE). We propose an enhanced confidence-generating pseudo-labeling technique to identify high-confidence pseudo-labeled samples from pseudo-labels within a subset of correlated samples, addressing the issue of inadequate labeled data. To fully utilize the information hidden in the unlabeled data, the proposed method incorporating the confidence attention mechanism then assigns weights to the high-confidence pseudo-labeled data and inputs them into the SAE along with labeled data from a subset of similar samples for re-fine-tuning. By conducting an illustrative analysis using authentic cement data proposed for this study, the effectiveness of the approaches employed in this research is substantiated.substantiated.
{"title":"A soft sensor model based on an improved semi-supervised stacked autoencoder for just-in-time updating of cement clinker production process data f-CaO","authors":"wei zheng, Hui Liu, XiaoYu Zhou, XiaoJun Xue, Heng Li, JianXun Liu","doi":"10.1088/1361-6501/ad1d30","DOIUrl":"https://doi.org/10.1088/1361-6501/ad1d30","url":null,"abstract":"\u0000 The free calcium oxide (f-CaO) content in cement clinker serves as a critical quality indicator for cement production. However, many soft sensor models employed for predicting f-CaO content utilize a limited amount of labeled data, leading to the underutilization of a substantial volume of unlabeled data and its associated information. To tackle these challenges, this study introduces soft sensor methodology based on improved semi-supervised Attention Stacked Autoencoders (ASS-SAE). We propose an enhanced confidence-generating pseudo-labeling technique to identify high-confidence pseudo-labeled samples from pseudo-labels within a subset of correlated samples, addressing the issue of inadequate labeled data. To fully utilize the information hidden in the unlabeled data, the proposed method incorporating the confidence attention mechanism then assigns weights to the high-confidence pseudo-labeled data and inputs them into the SAE along with labeled data from a subset of similar samples for re-fine-tuning. By conducting an illustrative analysis using authentic cement data proposed for this study, the effectiveness of the approaches employed in this research is substantiated.substantiated.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":"6 9","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139439527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2024-01-10DOI: 10.1088/1361-6501/ad1d48
Xinyue Zhao, Tiancheng Yu, Lianpeng Kang, Huarong Shen, Zaixing He
Shiny surface is challenging for the structured light fringe projection three-dimensional (3D) measurement technique, since the image saturation caused by highlight results in incorrect intensities in captured images of fringe patterns, and leads to serious phase errors and measurement errors. To address the issue, an adaptive chessboard-like high-frequency projection (ACHP) intensity adjustment technique is proposed. The proposed method alleviates image saturation by adaptively adjusting the intensity of the high-frequency chessboard-like projection pattern (CHP). And the complementary patterns are projected to suppress reflections and enhance the robustness of decoding. The experimental results demonstrate that the proposed method achieve high measurement accuracy for shiny surfaces.
{"title":"Adaptive chessboard-like high-frequency projection method for three-dimensional measurement of shiny surfaces","authors":"Xinyue Zhao, Tiancheng Yu, Lianpeng Kang, Huarong Shen, Zaixing He","doi":"10.1088/1361-6501/ad1d48","DOIUrl":"https://doi.org/10.1088/1361-6501/ad1d48","url":null,"abstract":"\u0000 Shiny surface is challenging for the structured light fringe projection three-dimensional (3D) measurement technique, since the image saturation caused by highlight results in incorrect intensities in captured images of fringe patterns, and leads to serious phase errors and measurement errors. To address the issue, an adaptive chessboard-like high-frequency projection (ACHP) intensity adjustment technique is proposed. The proposed method alleviates image saturation by adaptively adjusting the intensity of the high-frequency chessboard-like projection pattern (CHP). And the complementary patterns are projected to suppress reflections and enhance the robustness of decoding. The experimental results demonstrate that the proposed method achieve high measurement accuracy for shiny surfaces.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":"12 10","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139439746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2024-01-10DOI: 10.1088/1361-6501/ad1d49
Vinicius Morgan, Amadeu Sum, Ning Wu, A. Dante, Ângelo Marcio de Souza Gomes, Luciana Spinelli, Fernando Gomes de Souza Jr, R. Allil, M. M. Werneck
Abstract Inductive heating using magnetic nanoparticles (MNPs) is a critical process extensively investigated for cancer treatment. However, the high cost of commercially available equipment hinders its accessibility for many research groups. In response, this paper introduces a simple electronic circuit with low-cost components, making it easy to construct even for non-electronic experts. Operating within the 50 – 200 kHz range, the circuit employs a parallel inductor-capacitor configuration, providing a maximum induction magnetic field of 23.6 mT. Ltspice software simulations align well with oscilloscope measurements. Using commercial iron oxide nanoparticles (~16 nm) in water suspensions (1-10 mg/mL), the device exhibited a concentration-dependent reduction in Specific Absorption Rate (SAR) values, consistent with literature findings. Hyperthermia temperatures were achieved in a few minutes at 52.5 kHz and 23.6 mT in the highest concentration. At 81.9 kHz and 21.5 mT, a temperature of 93°C was achieved after 22 minutes at 10 mg/mL. Additionally, the device demonstrated stable and safe operation over a 100-minute period, as validated by an ice-melting experiment. These results highlight the device's efficacy for hyperthermia experiments in both biological and non-biological systems, particularly advantageous for larger nanoparticles in a blocked state. The proposed device holds significant potential for contributing to hyperthermia studies across diverse research groups. Future development will focus on frequency adjustment without reducing the alternating magnetic field amplitude and a thorough investigation of field homogeneity inside the coils.
{"title":"Development of Experimental Device for Inductive Heating of Magnetic Nanoparticles","authors":"Vinicius Morgan, Amadeu Sum, Ning Wu, A. Dante, Ângelo Marcio de Souza Gomes, Luciana Spinelli, Fernando Gomes de Souza Jr, R. Allil, M. M. Werneck","doi":"10.1088/1361-6501/ad1d49","DOIUrl":"https://doi.org/10.1088/1361-6501/ad1d49","url":null,"abstract":"\u0000 Abstract Inductive heating using magnetic nanoparticles (MNPs) is a critical process extensively investigated for cancer treatment. However, the high cost of commercially available equipment hinders its accessibility for many research groups. In response, this paper introduces a simple electronic circuit with low-cost components, making it easy to construct even for non-electronic experts. Operating within the 50 – 200 kHz range, the circuit employs a parallel inductor-capacitor configuration, providing a maximum induction magnetic field of 23.6 mT. Ltspice software simulations align well with oscilloscope measurements. Using commercial iron oxide nanoparticles (~16 nm) in water suspensions (1-10 mg/mL), the device exhibited a concentration-dependent reduction in Specific Absorption Rate (SAR) values, consistent with literature findings. Hyperthermia temperatures were achieved in a few minutes at 52.5 kHz and 23.6 mT in the highest concentration. At 81.9 kHz and 21.5 mT, a temperature of 93°C was achieved after 22 minutes at 10 mg/mL. Additionally, the device demonstrated stable and safe operation over a 100-minute period, as validated by an ice-melting experiment. These results highlight the device's efficacy for hyperthermia experiments in both biological and non-biological systems, particularly advantageous for larger nanoparticles in a blocked state. The proposed device holds significant potential for contributing to hyperthermia studies across diverse research groups. Future development will focus on frequency adjustment without reducing the alternating magnetic field amplitude and a thorough investigation of field homogeneity inside the coils.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":"5 11","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139439140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2024-01-10DOI: 10.1088/1361-6501/ad1d2d
Weipeng Liu, Ziwen Ren, Xu Li
In recent years, the registration method based on deep learning has received extensive attention from scholars due to its superiority in real-time performance. Most of the work directly use convolutional neural networks to map the image to be registered into the transform space. However, the receptive field of convolutional neural networks is limited, and multi-layer convolution superposition is needed to obtain a relatively large receptive field. Transformer-based methods can better express spatial relationships through attention mechanisms. However, the self-attention and the multi-head mechanisms make each small block calculate the relationship with other small blocks regardless of distance. Due to the limited moving range of corresponding voxel points in the medical images, this long-distance dependence may cause the model to be interfered by long-distance voxels. In this paper, we convert the spatial transformation of the corresponding voxel points into the calculation of the basic vector basis to propose the SV-basis module and design a two-stage multi-scale registration model. Experiments are carried out on brain and lung datasets to prove the effectiveness and universality of the proposed registration method. According to the anatomical characteristics of medical images, the corresponding loss function is designed to introduce mask information into the registration task. The experimental results show that the proposed method can accurately register brain and lung images.
{"title":"Weakly supervised medical image registration with multi-information guidance","authors":"Weipeng Liu, Ziwen Ren, Xu Li","doi":"10.1088/1361-6501/ad1d2d","DOIUrl":"https://doi.org/10.1088/1361-6501/ad1d2d","url":null,"abstract":"\u0000 In recent years, the registration method based on deep learning has received extensive attention from scholars due to its superiority in real-time performance. Most of the work directly use convolutional neural networks to map the image to be registered into the transform space. However, the receptive field of convolutional neural networks is limited, and multi-layer convolution superposition is needed to obtain a relatively large receptive field. Transformer-based methods can better express spatial relationships through attention mechanisms. However, the self-attention and the multi-head mechanisms make each small block calculate the relationship with other small blocks regardless of distance. Due to the limited moving range of corresponding voxel points in the medical images, this long-distance dependence may cause the model to be interfered by long-distance voxels. In this paper, we convert the spatial transformation of the corresponding voxel points into the calculation of the basic vector basis to propose the SV-basis module and design a two-stage multi-scale registration model. Experiments are carried out on brain and lung datasets to prove the effectiveness and universality of the proposed registration method. According to the anatomical characteristics of medical images, the corresponding loss function is designed to introduce mask information into the registration task. The experimental results show that the proposed method can accurately register brain and lung images.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":"8 6","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139439303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2024-01-10DOI: 10.1088/1361-6501/ad1d2c
Ana Gleice Silva Santos, Luiz Fernado Rust Carmo, Charles Bezerra do Prado
Metrological control of breathalyzers used at sobriety checkpoints is done by metrological institutes or police departments to ensure the accuracy of the results. Periodic checks carried out to ensure accurate measurements are not enough, as instruments can have errors between verifications that are not detected by traffic agents. In this article, we present a new proposal to evaluate instruments using machine learning algorithms capable of detecting failures before they occur. Historical instrument measurement data is used, with the application of classification techniques and thus labeling the instruments in order to indicate those that may previously fail before the next verification. Experiments are performed with fuel cells to identify which instruments have cells that can compromise measurement results during inspections. The study ends with the simulation of using the instrument to trace the wear curve over time. The results show that it is possible to apply machine learning to assist in the metrological control of breathalyzers and thus provide more security when these instruments are used in traffic inspections.
{"title":"MACHINE LEARNING IN LEGAL METROLOGY – DETECTING BREATHALYZERS’ FAILURES","authors":"Ana Gleice Silva Santos, Luiz Fernado Rust Carmo, Charles Bezerra do Prado","doi":"10.1088/1361-6501/ad1d2c","DOIUrl":"https://doi.org/10.1088/1361-6501/ad1d2c","url":null,"abstract":"\u0000 Metrological control of breathalyzers used at sobriety checkpoints is done by metrological institutes or police departments to ensure the accuracy of the results. Periodic checks carried out to ensure accurate measurements are not enough, as instruments can have errors between verifications that are not detected by traffic agents. In this article, we present a new proposal to evaluate instruments using machine learning algorithms capable of detecting failures before they occur. Historical instrument measurement data is used, with the application of classification techniques and thus labeling the instruments in order to indicate those that may previously fail before the next verification. Experiments are performed with fuel cells to identify which instruments have cells that can compromise measurement results during inspections. The study ends with the simulation of using the instrument to trace the wear curve over time. The results show that it is possible to apply machine learning to assist in the metrological control of breathalyzers and thus provide more security when these instruments are used in traffic inspections. ","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":"5 35","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139439756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
For the issue of significant noise in the collected bearing fault signals, a new bearing fault diagnosis model based on mutual mapping of signals and images (MMSI) and sparse representation (SR) denoising is proposed. Firstly, the fault signal is divided into several segments with the same number of sampling points, and then arrange these segments in ascending order of rows. Secondly, convert the arranged signals into grayscale image and use dictionary learning for block denoising. Then, the de-noised grayscale image is restored to a signal in line order. Finally, k-nearest neighbor (KNN) is used for fault classification. To verify the performance of the proposed model, experiments are tested on 12 single working conditions and 30 multi working conditions on the Case Western Reserve University (CWRU) dataset and the Paderborn dataset. The experimental results indicate that compared with some existing models, the MMSI-SR-KNN model can not only accurately diagnose bearing faults in artificial damage experiments, but also performs better in real damage faults. This indicates that the model has good generalization ability between different datasets and working conditions.
{"title":"A new model for bearing fault diagnosis based on mutual mapping of signals and images and sparse representation","authors":"Jing Yang, Yanping Bai, Xiuhui Tan, Rong Cheng, Hongping Hu, Peng Wang, Wendong Zhang","doi":"10.1088/1361-6501/ad1d4a","DOIUrl":"https://doi.org/10.1088/1361-6501/ad1d4a","url":null,"abstract":"\u0000 For the issue of significant noise in the collected bearing fault signals, a new bearing fault diagnosis model based on mutual mapping of signals and images (MMSI) and sparse representation (SR) denoising is proposed. Firstly, the fault signal is divided into several segments with the same number of sampling points, and then arrange these segments in ascending order of rows. Secondly, convert the arranged signals into grayscale image and use dictionary learning for block denoising. Then, the de-noised grayscale image is restored to a signal in line order. Finally, k-nearest neighbor (KNN) is used for fault classification. To verify the performance of the proposed model, experiments are tested on 12 single working conditions and 30 multi working conditions on the Case Western Reserve University (CWRU) dataset and the Paderborn dataset. The experimental results indicate that compared with some existing models, the MMSI-SR-KNN model can not only accurately diagnose bearing faults in artificial damage experiments, but also performs better in real damage faults. This indicates that the model has good generalization ability between different datasets and working conditions.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":"69 20","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139440790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The aviation community is actively pursuing advanced receiver autonomous integrity monitoring (ARAIM) to enhance the safety of aircraft navigation services. Protection level calculation is a crucial task in the solution separation-based ARAIM as it determines the availability of the ARAIM. Accurately determining the worst-case fault bias (WCFB) is beneficial in improving the bounding tightness of protection level on positioning error. Unfortunately, the WCFB determination is a challenging task that requires a time-consuming searching procedure, especially when dealing with the multi-satellite faults. The traditional ARAIM protection level is achieved by constructing an over-conservative worst-case positioning error bound to avoid the unacceptable time-consumption of the brute-force searching for multi-satellite WCFBs. However, this approach comes at the cost of losing the tightness of the protection level and the availability of the ARAIM. The ARAIM milestone reports have pointed out that the availability of the baseline ARAIM needs to be continuously improved in order to satisfy the worldwide localizer precision vertical 200 (LPV-200) requirements. In response, this paper proposes a novel multi-satellite WCFBs searching method for the ARAIM to improve the tightness of protection level. The method consists of determining the worst-case fault direction and constructing an efficient WCFBs searching procedure. GPS/Galileo dual-constellation simulation result demonstrates that the proposed method not only can improve the availability of the ARAIM up to 9.33% when compared with the traditional method, but also achieves comparable computation efficiency.
{"title":"Improved protection level for the solution-separation ARAIM based on worst-case fault bias searching","authors":"Ruijie Li, Liang Li, jiachang jiang, Fengze Du, Zhibo Na, Xin Xu","doi":"10.1088/1361-6501/ad1d2b","DOIUrl":"https://doi.org/10.1088/1361-6501/ad1d2b","url":null,"abstract":"\u0000 The aviation community is actively pursuing advanced receiver autonomous integrity monitoring (ARAIM) to enhance the safety of aircraft navigation services. Protection level calculation is a crucial task in the solution separation-based ARAIM as it determines the availability of the ARAIM. Accurately determining the worst-case fault bias (WCFB) is beneficial in improving the bounding tightness of protection level on positioning error. Unfortunately, the WCFB determination is a challenging task that requires a time-consuming searching procedure, especially when dealing with the multi-satellite faults. The traditional ARAIM protection level is achieved by constructing an over-conservative worst-case positioning error bound to avoid the unacceptable time-consumption of the brute-force searching for multi-satellite WCFBs. However, this approach comes at the cost of losing the tightness of the protection level and the availability of the ARAIM. The ARAIM milestone reports have pointed out that the availability of the baseline ARAIM needs to be continuously improved in order to satisfy the worldwide localizer precision vertical 200 (LPV-200) requirements. In response, this paper proposes a novel multi-satellite WCFBs searching method for the ARAIM to improve the tightness of protection level. The method consists of determining the worst-case fault direction and constructing an efficient WCFBs searching procedure. GPS/Galileo dual-constellation simulation result demonstrates that the proposed method not only can improve the availability of the ARAIM up to 9.33% when compared with the traditional method, but also achieves comparable computation efficiency.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":"2 12","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139440247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2024-01-10DOI: 10.1088/1361-6501/ad1d2f
Mingyue Liu, R. Tu, Fangxin Li, Qiushi Chen, Qi Li, Junmei Chen, Pengfei Zhang, Xiaochun Lu
With the continuous development and increasing popularity of the fifth generation (5G) of mobile communications technology, its fusion with the Global Navigation Satellite System (GNSS) data can effectively improve problems with service interruptions or poor satellite signal reception. In this study, GPS and 5G data were fused, and the resulting experimental algorithm showed that it effective improves time transfer’s frequency stability and reliability. Moreover, this technique reduced the noise level of time-transmitted clock offset sequences, while suppressing short-term mutations. By simulating different degrees of satellite signal occlusion, it was further verified that the GPS+5G fusion method can provide stable, high-precision, and real-time delivery services under insufficient satellite signal reception. This provides a reference for high-precision time transfer technology in complex environments and further improves the reliability of GNSS high-precision time transfer.
{"title":"GPS + 5G fusion for high-precision time transfer","authors":"Mingyue Liu, R. Tu, Fangxin Li, Qiushi Chen, Qi Li, Junmei Chen, Pengfei Zhang, Xiaochun Lu","doi":"10.1088/1361-6501/ad1d2f","DOIUrl":"https://doi.org/10.1088/1361-6501/ad1d2f","url":null,"abstract":"\u0000 With the continuous development and increasing popularity of the fifth generation (5G) of mobile communications technology, its fusion with the Global Navigation Satellite System (GNSS) data can effectively improve problems with service interruptions or poor satellite signal reception. In this study, GPS and 5G data were fused, and the resulting experimental algorithm showed that it effective improves time transfer’s frequency stability and reliability. Moreover, this technique reduced the noise level of time-transmitted clock offset sequences, while suppressing short-term mutations. By simulating different degrees of satellite signal occlusion, it was further verified that the GPS+5G fusion method can provide stable, high-precision, and real-time delivery services under insufficient satellite signal reception. This provides a reference for high-precision time transfer technology in complex environments and further improves the reliability of GNSS high-precision time transfer.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":"82 6","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139440445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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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