Pub Date : 2024-07-02DOI: 10.1088/1361-6501/ad5de8
Jingxin Xiao, Haojun Li, Yafeng Sun, Xiaolu Liu
Aiming to address poor self-consistency of the satellite clock and orbit interpolations at the day boundary, which is caused by the discontinuities of their International GNSS Service (IGS) products for two consecutive days, an effective method is proposed to improve the precise point positioning (PPP) performances at the day boundary. According to different orders of Lagrange interpolator and different IGS Analysis Centers (ACs) products of Center for Orbit Determination in Europe (CODE), GeoForschungsZentrum (GFZ) and Wuhan University (WUH), biases at the day boundaries are estimated and analyzed using a 4-day (DOY 94-97, 2022) data set of GPS, BDS-3 and Galileo from 123 IGS stations. These estimated biases show the time-varying characteristics. The differences in biases across 9th-11th orders of Lagrange interpolator are minimal, and these variances have a negligible impact on positioning. The results show that this poor self-consistency at the day boundary has an obvious influence on the kinematic PPP positioning, especially there is a centimeter-level variation at time of 24:00:00/00:00:00. This influence on the Up direction of kinematic PPP positioning is more serious than other directions. When the bias is estimated and corrected, the kinematic PPP positioning accuracies at the day boundary have a mean improvement of 0.043, 0.064 and 0.027m for WUH, GFZ and CODE, respectively. The mean improvements for GPS, BDS-3 and Galileo are 0.021, 0.062 and 0.051m. Additionally, the static PPP performances at the day boundary show the convergence times are shortened by 3.2, 6.2, and 2.5 minutes for WUH, GFZ and CODE, respectively, when the poor self-consistency of the satellite clock and orbit interpolations is estimated and corrected. Meanwhile, its 0.5 and 1 hour positioning accuracies are improved.
{"title":"An effective method for improving GNSS precise point positioning performance at the day boundary","authors":"Jingxin Xiao, Haojun Li, Yafeng Sun, Xiaolu Liu","doi":"10.1088/1361-6501/ad5de8","DOIUrl":"https://doi.org/10.1088/1361-6501/ad5de8","url":null,"abstract":"\u0000 Aiming to address poor self-consistency of the satellite clock and orbit interpolations at the day boundary, which is caused by the discontinuities of their International GNSS Service (IGS) products for two consecutive days, an effective method is proposed to improve the precise point positioning (PPP) performances at the day boundary. According to different orders of Lagrange interpolator and different IGS Analysis Centers (ACs) products of Center for Orbit Determination in Europe (CODE), GeoForschungsZentrum (GFZ) and Wuhan University (WUH), biases at the day boundaries are estimated and analyzed using a 4-day (DOY 94-97, 2022) data set of GPS, BDS-3 and Galileo from 123 IGS stations. These estimated biases show the time-varying characteristics. The differences in biases across 9th-11th orders of Lagrange interpolator are minimal, and these variances have a negligible impact on positioning. The results show that this poor self-consistency at the day boundary has an obvious influence on the kinematic PPP positioning, especially there is a centimeter-level variation at time of 24:00:00/00:00:00. This influence on the Up direction of kinematic PPP positioning is more serious than other directions. When the bias is estimated and corrected, the kinematic PPP positioning accuracies at the day boundary have a mean improvement of 0.043, 0.064 and 0.027m for WUH, GFZ and CODE, respectively. The mean improvements for GPS, BDS-3 and Galileo are 0.021, 0.062 and 0.051m. Additionally, the static PPP performances at the day boundary show the convergence times are shortened by 3.2, 6.2, and 2.5 minutes for WUH, GFZ and CODE, respectively, when the poor self-consistency of the satellite clock and orbit interpolations is estimated and corrected. Meanwhile, its 0.5 and 1 hour positioning accuracies are improved.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141685178","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 : 2024-07-02DOI: 10.1088/1361-6501/ad5ddc
Lie Guo, Pengyuan Guo, Longxin Guan, Hui Ma
Parameter fluctuations, unmodeled dynamics, speed variation, steering actuator faults, and other multi-channel uncertain disturbances are the key challenges faced by the path tracking control of intelligent vehicles, which will affect the accuracy and stability of the path tracking. Therefore, a model predictive control (MPC) method based on a dual-stage disturbance observer (DDOB) is proposed in this paper. First, a tracking error dynamics model considering multi-channel uncertain disturbances is constructed, based on which a model predictive controller is designed to obtain the nominal front wheel steering angle by the Karush-Kuhn-Tucker (KKT) condition. Furthermore, the dual-stage disturbance observer is designed to enable real-time estimation of the system disturbances, and then the estimated disturbances are used as the compensation for the nominal front wheel steering angle, which establishes the MPC control law with parallel compensation of the dual-stage disturbance observer. Finally, the error boundedness of the dual-stage disturbance observer and the global stability of the model predictive controller are analyzed. The effectiveness and superiority of the proposed algorithm are verified through Carsim-Simulink simulation and hardware-in-the-loop (HiL) experiments.
{"title":"Model predictive path tracking control of intelligent vehicle based on dual-stage disturbance observer under multi-channel disturbances","authors":"Lie Guo, Pengyuan Guo, Longxin Guan, Hui Ma","doi":"10.1088/1361-6501/ad5ddc","DOIUrl":"https://doi.org/10.1088/1361-6501/ad5ddc","url":null,"abstract":"\u0000 Parameter fluctuations, unmodeled dynamics, speed variation, steering actuator faults, and other multi-channel uncertain disturbances are the key challenges faced by the path tracking control of intelligent vehicles, which will affect the accuracy and stability of the path tracking. Therefore, a model predictive control (MPC) method based on a dual-stage disturbance observer (DDOB) is proposed in this paper. First, a tracking error dynamics model considering multi-channel uncertain disturbances is constructed, based on which a model predictive controller is designed to obtain the nominal front wheel steering angle by the Karush-Kuhn-Tucker (KKT) condition. Furthermore, the dual-stage disturbance observer is designed to enable real-time estimation of the system disturbances, and then the estimated disturbances are used as the compensation for the nominal front wheel steering angle, which establishes the MPC control law with parallel compensation of the dual-stage disturbance observer. Finally, the error boundedness of the dual-stage disturbance observer and the global stability of the model predictive controller are analyzed. The effectiveness and superiority of the proposed algorithm are verified through Carsim-Simulink simulation and hardware-in-the-loop (HiL) experiments.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141684941","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 : 2024-07-02DOI: 10.1088/1361-6501/ad5de2
Wenqing Su, Ji Tan, Zhaoshui He, Zhijie Lin, Chang Liu
The measurement of complete 3D topography in mesoscale plays a vital role in high-precision reverse engineering, oral medical modeling, circuit detection, etc. Traditional structured light systems are limited to measuring 3D shapes from a single perspective. How to achieve high-quality mesoscopic panoramic 3D measurement remains challenging, especially in complex measured scenarios such as dynamic measurement, scattering medium, and high reflectance. To overcome these problems, we develop a handheld mesoscopic panoramic 3D measurement system for such complex scenes together with the fast point-cloud-registration and accurate 3D-reconstruction, where a motion discrimination mechanism is designed to ensure that the captured fringe is in a quasi-stationary case by avoiding the motion errors caused during fringe scanning; a deep neural network is utilized to suppressing the fringe-degradation caused by scattering mediums resulting to significantly improves the quality of the 3D point cloud; a strategy based on phase averaging is additionally proposed to simultaneously correct the saturation-induced errors and gamma nonlinear errors. Finally, the proposed system with a multi-threaded data processing framework is further developed to verify the proposed method and the corresponding experiments verify its feasibility.
{"title":"Handheld structured light system for panoramic 3D measurement in mesoscale","authors":"Wenqing Su, Ji Tan, Zhaoshui He, Zhijie Lin, Chang Liu","doi":"10.1088/1361-6501/ad5de2","DOIUrl":"https://doi.org/10.1088/1361-6501/ad5de2","url":null,"abstract":"\u0000 The measurement of complete 3D topography in mesoscale plays a vital role in high-precision reverse engineering, oral medical modeling, circuit detection, etc. Traditional structured light systems are limited to measuring 3D shapes from a single perspective. How to achieve high-quality mesoscopic panoramic 3D measurement remains challenging, especially in complex measured scenarios such as dynamic measurement, scattering medium, and high reflectance. To overcome these problems, we develop a handheld mesoscopic panoramic 3D measurement system for such complex scenes together with the fast point-cloud-registration and accurate 3D-reconstruction, where a motion discrimination mechanism is designed to ensure that the captured fringe is in a quasi-stationary case by avoiding the motion errors caused during fringe scanning; a deep neural network is utilized to suppressing the fringe-degradation caused by scattering mediums resulting to significantly improves the quality of the 3D point cloud; a strategy based on phase averaging is additionally proposed to simultaneously correct the saturation-induced errors and gamma nonlinear errors. Finally, the proposed system with a multi-threaded data processing framework is further developed to verify the proposed method and the corresponding experiments verify its feasibility.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141687641","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 method based on broad spectrum interference using femtosecond pulses is an important ranging method. In this paper, we experimentally evaluate the effect of interferometric spectral bandwidth used for calculation on the ranging results, and precision can be improved by choosing the optimal spectral bandwidth. In addition, in order to eliminate the influence of interferometric spectral fluctuations on the measurement results, we introduce the detrend algorithm into the processing algorithm and compare the measurement results before and after the algorithm improvement. Then, four kinds of nominal distance were measured and the contribution of the relevant factors to the measurement uncertainty is evaluated. Finally, the synthetic standard uncertainty of measurement results was 0.02 μm, 0.10 μm, 1.05 μm and 2.78 μm for nominal distance of ~0 m, ~1.5 m, ~16.5 m and ~43.5 m respectively.
基于飞秒脉冲宽光谱干涉的方法是一种重要的测距方法。本文通过实验评估了用于计算的干涉光谱带宽对测距结果的影响，并通过选择最佳光谱带宽来提高精度。此外，为了消除干涉光谱波动对测量结果的影响，我们在处理算法中引入了去趋势算法，并比较了算法改进前后的测量结果。然后，测量了四种标称距离，评估了相关因素对测量不确定度的贡献。最后，对于 ~0 m、 ~1.5 m、 ~16.5 m 和 ~43.5 m 的标称距离，测量结果的合成标准不确定度分别为 0.02 μm、0.10 μm、1.05 μm 和 2.78 μm。
{"title":"High-precision long distance measurement based on broad spectrum interferometry using a femtosecond laser","authors":"Haoran Gao, Lei Huang, Xin Xu, Dagui Wang, Pengxiang Ge, Huining Zhao","doi":"10.1088/1361-6501/ad5ddb","DOIUrl":"https://doi.org/10.1088/1361-6501/ad5ddb","url":null,"abstract":"\u0000 The method based on broad spectrum interference using femtosecond pulses is an important ranging method. In this paper, we experimentally evaluate the effect of interferometric spectral bandwidth used for calculation on the ranging results, and precision can be improved by choosing the optimal spectral bandwidth. In addition, in order to eliminate the influence of interferometric spectral fluctuations on the measurement results, we introduce the detrend algorithm into the processing algorithm and compare the measurement results before and after the algorithm improvement. Then, four kinds of nominal distance were measured and the contribution of the relevant factors to the measurement uncertainty is evaluated. Finally, the synthetic standard uncertainty of measurement results was 0.02 μm, 0.10 μm, 1.05 μm and 2.78 μm for nominal distance of ~0 m, ~1.5 m, ~16.5 m and ~43.5 m respectively.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141687967","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 : 2024-07-02DOI: 10.1088/1361-6501/ad5ddd
Ou Pu, Boqiu Yuan, Zhengnong Li, Zheng Chen, Yong Liang, Xiqiao Lin, Jihui Tan, Zhen Li
Utilizing Pb(ZrTi)O3-5A piezoelectric ceramic (hereafter referred to as PZT-5A) as sensors, we studied the movement speed of sand particles in multiphase wind-sand flows. We developed a mathematical model that effectively links the impact force of sand grains with the output voltage of PZT-5A, incorporating factors such as the piezoelectric coefficient and sand particle characteristics. Additionally, we proposed a new method to accurately determine the elastic recovery coefficient of sand particles using PZT-5A sensor measurements and experimental setups, which is significant for the field of material science. Wind tunnel experiments revealed that at heights ranging from 0.1 to 1.0m, sand particle speeds range from 52.8% to 91.4% of wind speeds. As wind speed increases to 15m/s, sand particle speed nears 91.4% of wind speed. Yet, at a constant wind speed, sand speed drops as sediment discharge rises. This research offers fresh insights into sand particle dynamics in wind-sand contexts.
{"title":"Measurement of sand particle motion speed in multiphase wind-sand flow based on piezoelectric ceramic sensors","authors":"Ou Pu, Boqiu Yuan, Zhengnong Li, Zheng Chen, Yong Liang, Xiqiao Lin, Jihui Tan, Zhen Li","doi":"10.1088/1361-6501/ad5ddd","DOIUrl":"https://doi.org/10.1088/1361-6501/ad5ddd","url":null,"abstract":"\u0000 Utilizing Pb(ZrTi)O3-5A piezoelectric ceramic (hereafter referred to as PZT-5A) as sensors, we studied the movement speed of sand particles in multiphase wind-sand flows. We developed a mathematical model that effectively links the impact force of sand grains with the output voltage of PZT-5A, incorporating factors such as the piezoelectric coefficient and sand particle characteristics. Additionally, we proposed a new method to accurately determine the elastic recovery coefficient of sand particles using PZT-5A sensor measurements and experimental setups, which is significant for the field of material science. Wind tunnel experiments revealed that at heights ranging from 0.1 to 1.0m, sand particle speeds range from 52.8% to 91.4% of wind speeds. As wind speed increases to 15m/s, sand particle speed nears 91.4% of wind speed. Yet, at a constant wind speed, sand speed drops as sediment discharge rises. This research offers fresh insights into sand particle dynamics in wind-sand contexts.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141684128","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 : 2024-07-02DOI: 10.1088/1361-6501/ad5dd7
Chenyan Tan, Zijun Chen, Ailin Liao, Xintian Zeng, Jinchao Cao
The optimization of an unmanned aerial vehicle (UAV) aerial photogrammetry scheme is crucial for achieving higher precision mapping results. Three representative factors, namely the real-time kinematic (RTK) mode, flight altitude, and the number of ground control points (GCPs) were selected to analyze their impact on UAV aerial photogrammetry accuracy. Four flight altitude tests were conducted separately in two RTK modes, and five GCP layout schemes were designed. Based on this, the root mean square error (RMSE) values of 40 aerial photogrammetric results were analyzed. The results showed a significant correlation between flight altitude and resolution of the UAV aerial photogrammetric results. Further, conversion formulas between actual image resolution and flight altitude for different GCP values were also derived in RTK and non-RTK modes. In the case of precise positioning, the horizontal and vertical accuracy of the aerial photogrammetric image decreased with increasing flight altitude. Under the same flight altitude, the addition or no addition of GCPs, including changes in GCP numbers, had no significant effect on improving the accuracy of aerial photogrammetry in RTK mode. However, in non-RTK mode, the number of GCPs significantly affected accuracy. The horizontal and vertical RMSE values decreased rapidly with the increase in GCP numbers and then stabilized. However, regardless of whether RTK was activated, an excessive number of GCPs was not conducive to improving the accuracy of aerial photogrammetric results. The mapping accuracy of UAVs in RTK mode without GCPs was equivalent to that in non-RTK mode with GCPs. Therefore, when using RTK-UAVs, deploying GCPs is unnecessary under suitable circumstances. Finally, practical suggestions for optimizing the UAV aerial photogrammetry scheme are provided as a reference for related applications.
{"title":"Accuracy analysis of UAV aerial photogrammetry based on RTK mode, flight altitude, and number of GCPs","authors":"Chenyan Tan, Zijun Chen, Ailin Liao, Xintian Zeng, Jinchao Cao","doi":"10.1088/1361-6501/ad5dd7","DOIUrl":"https://doi.org/10.1088/1361-6501/ad5dd7","url":null,"abstract":"\u0000 The optimization of an unmanned aerial vehicle (UAV) aerial photogrammetry scheme is crucial for achieving higher precision mapping results. Three representative factors, namely the real-time kinematic (RTK) mode, flight altitude, and the number of ground control points (GCPs) were selected to analyze their impact on UAV aerial photogrammetry accuracy. Four flight altitude tests were conducted separately in two RTK modes, and five GCP layout schemes were designed. Based on this, the root mean square error (RMSE) values of 40 aerial photogrammetric results were analyzed. The results showed a significant correlation between flight altitude and resolution of the UAV aerial photogrammetric results. Further, conversion formulas between actual image resolution and flight altitude for different GCP values were also derived in RTK and non-RTK modes. In the case of precise positioning, the horizontal and vertical accuracy of the aerial photogrammetric image decreased with increasing flight altitude. Under the same flight altitude, the addition or no addition of GCPs, including changes in GCP numbers, had no significant effect on improving the accuracy of aerial photogrammetry in RTK mode. However, in non-RTK mode, the number of GCPs significantly affected accuracy. The horizontal and vertical RMSE values decreased rapidly with the increase in GCP numbers and then stabilized. However, regardless of whether RTK was activated, an excessive number of GCPs was not conducive to improving the accuracy of aerial photogrammetric results. The mapping accuracy of UAVs in RTK mode without GCPs was equivalent to that in non-RTK mode with GCPs. Therefore, when using RTK-UAVs, deploying GCPs is unnecessary under suitable circumstances. Finally, practical suggestions for optimizing the UAV aerial photogrammetry scheme are provided as a reference for related applications.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141685310","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 : 2024-07-02DOI: 10.1088/1361-6501/ad5dec
Guiling Zhao, Jinbao Wang, Shuai Gao, Zihao Jiang
The Global Navigation Satellite System/Strapdown Inertial Navigation System (GNSS/SINS) integrated navigation system is an important technology for UAV measurement and vehicle movement measurement. But in the operational process of the GNSS/SINS integrated navigation system, the Global Navigation Satellite System (GNSS) signal is vulnerable to external interference, resulting in abnormal system measurement data, and system faults. These faults will reduce the navigation and positioning performance of the system and reduce the measurement accuracy of the system. Aiming at this problem, a GNSS/SINS fault detection and robust adaptive algorithm based on sliding average smooth bounded layer width is proposed. The algorithm evaluates the system measurement data based on the innovation residual and incorporates the sliding average filter to design the fault detection function based on the smooth bounded width layer. Accurate detection of system faults using fault detection function. The fault detection function value is used to construct the robust cofactor matrix to correct the measurement error in real-time, to improve the accuracy and robustness of the state estimation. The experimental results show that: The proposed algorithm in the paper compares with two traditional robust adaptive algorithms based on smooth bounded layer fault detection and residual chi-square fault detection. The fault detection rates for small step faults show an increase of more than 44.26% and 9.54%, respectively. Similarly, for slowly varying faults, the fault detection rates exhibit an increase of more than 29.32% and 13.56%, respectively. Throughout the fault, the filtering accuracy demonstrates an increase of more than 16.52% and 15.47%, respectively. The algorithm effectively improves the measurement accuracy of the GNSS/SINS integrated navigation system.
{"title":"A GNSS/SINS fault detection and robust adaptive algorithm based on sliding average smooth bounded layer width","authors":"Guiling Zhao, Jinbao Wang, Shuai Gao, Zihao Jiang","doi":"10.1088/1361-6501/ad5dec","DOIUrl":"https://doi.org/10.1088/1361-6501/ad5dec","url":null,"abstract":"\u0000 The Global Navigation Satellite System/Strapdown Inertial Navigation System (GNSS/SINS) integrated navigation system is an important technology for UAV measurement and vehicle movement measurement. But in the operational process of the GNSS/SINS integrated navigation system, the Global Navigation Satellite System (GNSS) signal is vulnerable to external interference, resulting in abnormal system measurement data, and system faults. These faults will reduce the navigation and positioning performance of the system and reduce the measurement accuracy of the system. Aiming at this problem, a GNSS/SINS fault detection and robust adaptive algorithm based on sliding average smooth bounded layer width is proposed. The algorithm evaluates the system measurement data based on the innovation residual and incorporates the sliding average filter to design the fault detection function based on the smooth bounded width layer. Accurate detection of system faults using fault detection function. The fault detection function value is used to construct the robust cofactor matrix to correct the measurement error in real-time, to improve the accuracy and robustness of the state estimation. The experimental results show that: The proposed algorithm in the paper compares with two traditional robust adaptive algorithms based on smooth bounded layer fault detection and residual chi-square fault detection. The fault detection rates for small step faults show an increase of more than 44.26% and 9.54%, respectively. Similarly, for slowly varying faults, the fault detection rates exhibit an increase of more than 29.32% and 13.56%, respectively. Throughout the fault, the filtering accuracy demonstrates an increase of more than 16.52% and 15.47%, respectively. The algorithm effectively improves the measurement accuracy of the GNSS/SINS integrated navigation system.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141688323","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 : 2024-07-02DOI: 10.1088/1361-6501/ad5de0
Kai Zhang, lei Yu Su, yi Jia Zhou, dong Dong Wang, kuang Huai Ding, biao Hua Zhang
Internal stresses play a crucial part in determining a material's properties, which emphasizes the significance of accurate stress measurement and analysis. Neutron diffraction technology is a very promising approach to studying the complex microstructural properties of many materials, especially with the growing demand for cryogenic studies. This new device has a robust load capacity of 50 kN and works smoothly in a wide temperature range of 6 K to 473 K. Furthermore, the diffraction angle is 47 degrees broader. Regardless of the samples, we observed that a thermal balance point existed close to 180 K. Importantly, thermal resistance (TR) was eliminated by the use of an analytical method, which has an extraordinarily small error of 2%. Using this exact calibration methodology ensures that the sample temperature is accurate during the experiments. This work presents a crucial apparatus for investigating the complexity of internal stresses in materials and offers an effective method for estimating and managing sample temperatures while doing research.
内应力在决定材料性能方面起着至关重要的作用，这就强调了精确应力测量和分析的重要性。中子衍射技术是研究许多材料复杂微观结构特性的一种非常有前途的方法，尤其是随着低温研究需求的不断增长。这一新设备具有 50 kN 的强大负载能力，可在 6 K 至 473 K 的宽温度范围内平稳工作。重要的是，通过使用误差极小的 2% 分析方法，消除了热阻 (TR)。使用这种精确的校准方法确保了实验过程中样品温度的准确性。这项工作为研究材料内应力的复杂性提供了一种重要的仪器，并为在研究过程中估算和管理样品温度提供了一种有效的方法。
{"title":"Temperature Calibration of Sample Rods for Neutron Diffraction Apparatus in the Range of 6-473K","authors":"Kai Zhang, lei Yu Su, yi Jia Zhou, dong Dong Wang, kuang Huai Ding, biao Hua Zhang","doi":"10.1088/1361-6501/ad5de0","DOIUrl":"https://doi.org/10.1088/1361-6501/ad5de0","url":null,"abstract":"\u0000 Internal stresses play a crucial part in determining a material's properties, which emphasizes the significance of accurate stress measurement and analysis. Neutron diffraction technology is a very promising approach to studying the complex microstructural properties of many materials, especially with the growing demand for cryogenic studies. This new device has a robust load capacity of 50 kN and works smoothly in a wide temperature range of 6 K to 473 K. Furthermore, the diffraction angle is 47 degrees broader. Regardless of the samples, we observed that a thermal balance point existed close to 180 K. Importantly, thermal resistance (TR) was eliminated by the use of an analytical method, which has an extraordinarily small error of 2%. Using this exact calibration methodology ensures that the sample temperature is accurate during the experiments. This work presents a crucial apparatus for investigating the complexity of internal stresses in materials and offers an effective method for estimating and managing sample temperatures while doing research.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141687224","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}
SLAM technology is crucial to robot navigation. Despite the good performance of traditional SLAM algorithms in static environments, dynamic objects typically exist in realistic operating environments. These objects can lead to misassociated features, which in turn considerably impact the system’s localization accuracy and robustness. To better address this challenge, we have proposed the OMS-SLAM. In OMS-SLAM, we adopted the YOLOv8 target detection network to extract object information from environment and designed a dynamic probability propagation model that is coupled with target detection and multiple geometric constrains to determine the dynamic objects in the environment. For the identified dynamic objects, we have designed a foreground image segmentation algorithm based on depth image histogram statistics to extract the object contours and eliminate the feature points within these contours. We then use the GMS (Grid-based Motion Statistics) matching pair as the filtering strategy to enhance the quality of the feature points and use the enhanced feature points for tracking. This combined method can accurately identify dynamic objects and extract related feature points, significantly reducing its interference and consequently enhancing the system's robustness and localization accuracy. We also built static dense point cloud maps to support advanced tasks of robots. Finally, through testing on the high-speed dataset of TUM RGB-D, it was found that the root mean square error of the Absolute Trajectory Error (ATE) in this study decreased by an average of 97.10%, compared to ORB-SLAM2. Moreover, tests in real-world scenarios also confirmed the effectiveness of the OMS-SLAM algorithm in dynamic environments.
SLAM 技术对机器人导航至关重要。尽管传统的 SLAM 算法在静态环境中性能良好，但在现实操作环境中通常存在动态物体。这些物体可能会导致误关联特征，进而严重影响系统的定位精度和鲁棒性。为了更好地应对这一挑战，我们提出了 OMS-SLAM。在 OMS-SLAM 中，我们采用 YOLOv8 目标检测网络从环境中提取物体信息，并设计了一个动态概率传播模型，该模型与目标检测和多重几何约束相结合，以确定环境中的动态物体。对于识别出的动态物体，我们设计了一种基于深度图像直方图统计的前景图像分割算法，以提取物体轮廓并消除轮廓内的特征点。然后，我们使用 GMS（基于网格的运动统计）匹配对作为过滤策略来增强特征点的质量，并使用增强后的特征点进行跟踪。这种组合方法能准确识别动态物体并提取相关特征点，大大减少了干扰，从而提高了系统的鲁棒性和定位精度。我们还建立了静态密集点云图，以支持机器人的高级任务。最后，通过对 TUM RGB-D 高速数据集的测试发现，与 ORB-SLAM2 相比，本研究中的绝对轨迹误差（ATE）的均方根误差平均降低了 97.10%。此外，实际场景中的测试也证实了 OMS-SLAM 算法在动态环境中的有效性。
{"title":"OMS-SLAM: Dynamic Scene Visual SLAM Based on Object Detection with Multiple Geometric Feature Constraints and Statistical Threshold Segmentation","authors":"Jialiang Tang, Zhengyong Feng, Peng Liao, Liheng Chen, Xiaomei Xiao","doi":"10.1088/1361-6501/ad5de5","DOIUrl":"https://doi.org/10.1088/1361-6501/ad5de5","url":null,"abstract":"\u0000 SLAM technology is crucial to robot navigation. Despite the good performance of traditional SLAM algorithms in static environments, dynamic objects typically exist in realistic operating environments. These objects can lead to misassociated features, which in turn considerably impact the system’s localization accuracy and robustness. To better address this challenge, we have proposed the OMS-SLAM. In OMS-SLAM, we adopted the YOLOv8 target detection network to extract object information from environment and designed a dynamic probability propagation model that is coupled with target detection and multiple geometric constrains to determine the dynamic objects in the environment. For the identified dynamic objects, we have designed a foreground image segmentation algorithm based on depth image histogram statistics to extract the object contours and eliminate the feature points within these contours. We then use the GMS (Grid-based Motion Statistics) matching pair as the filtering strategy to enhance the quality of the feature points and use the enhanced feature points for tracking. This combined method can accurately identify dynamic objects and extract related feature points, significantly reducing its interference and consequently enhancing the system's robustness and localization accuracy. We also built static dense point cloud maps to support advanced tasks of robots. Finally, through testing on the high-speed dataset of TUM RGB-D, it was found that the root mean square error of the Absolute Trajectory Error (ATE) in this study decreased by an average of 97.10%, compared to ORB-SLAM2. Moreover, tests in real-world scenarios also confirmed the effectiveness of the OMS-SLAM algorithm in dynamic environments.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141685688","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}
Accurate location of unknown radio transmitter (URT) is the key to secure wireless communication. Since the fingerprint positioning methods based on received signal strength difference (RSSD) can adapt to the diversity of transmitting power and frequency, RSSD has become a popular scheme for locating the unknown radio transmitter. However, the RSSD is obtained by subtracting the RSS from two different access points (APs), so the interference of noise on the RSS is inherited and amplified by the RSSD. Besides, the need for more APs to ensure positioning accuracy leads to an increase in hardware costs. In this paper, a RSSD-based fuzzy weight grey correlation degree positioning algorithm, called FUZZY-GREY, is proposed to reduce the interference of noise, save AP hardware cost and improve the positioning accuracy. Firstly, online RSSD vector is improved by using fuzzy weight to reduce the noise interference. Secondly, the RSSD-based grey correlation coefficient is designed to calculate the correlation degree of the corresponding RSSD and ensure data integrity. Finally, a RSSD-based grey correlation degree scheme combining with fuzzy weight is proposed to select optimal reference points (RPs). Simulation and experimental results show that the proposed algorithm has better positioning performance than weighted k-nearest neighbor (WKNN), maximum correlation coefficient estimation (MCORE), Naive Bayes and support vector machine (SVM) in the case of different selected K numbers, grid distances, noise levels and AP numbers.
准确定位未知无线电发射机（URT）是确保无线通信安全的关键。由于基于接收信号强度差（RSSD）的指纹定位方法能适应发射功率和频率的多样性，RSSD 已成为定位未知无线电发射机的流行方案。然而，RSSD 是通过减去两个不同接入点（AP）的 RSS 得到的，因此 RSSD 会继承和放大噪声对 RSS 的干扰。此外，由于需要更多接入点来确保定位精度，导致硬件成本增加。本文提出了一种基于 RSSD 的模糊权灰色关联度定位算法 FUZZY-GREY，以减少噪声干扰，节约 AP 硬件成本，提高定位精度。首先，利用模糊权重改进在线 RSSD 向量，以减少噪声干扰。其次，设计基于 RSSD 的灰色关联系数，计算相应 RSSD 的关联度，确保数据完整性。最后，提出了基于 RSSD 的灰色关联度方案，并结合模糊权重选择最佳参考点（RP）。仿真和实验结果表明，与加权 K 近邻（WKNN）、最大相关系数估计（MCORE）、Naive Bayes 和支持向量机（SVM）相比，在选择不同的 K 数、网格距离、噪声水平和 AP 数的情况下，所提出的算法具有更好的定位性能。
{"title":"Indoor unknown radio transmitter localization using improved RSSD and grey correlation degree","authors":"Liyang Zhang, Chenyu Xu, Rui Gao, Yin Liang, Lidong Zhang, Lixia Guo","doi":"10.1088/1361-6501/ad5de6","DOIUrl":"https://doi.org/10.1088/1361-6501/ad5de6","url":null,"abstract":"\u0000 Accurate location of unknown radio transmitter (URT) is the key to secure wireless communication. Since the fingerprint positioning methods based on received signal strength difference (RSSD) can adapt to the diversity of transmitting power and frequency, RSSD has become a popular scheme for locating the unknown radio transmitter. However, the RSSD is obtained by subtracting the RSS from two different access points (APs), so the interference of noise on the RSS is inherited and amplified by the RSSD. Besides, the need for more APs to ensure positioning accuracy leads to an increase in hardware costs. In this paper, a RSSD-based fuzzy weight grey correlation degree positioning algorithm, called FUZZY-GREY, is proposed to reduce the interference of noise, save AP hardware cost and improve the positioning accuracy. Firstly, online RSSD vector is improved by using fuzzy weight to reduce the noise interference. Secondly, the RSSD-based grey correlation coefficient is designed to calculate the correlation degree of the corresponding RSSD and ensure data integrity. Finally, a RSSD-based grey correlation degree scheme combining with fuzzy weight is proposed to select optimal reference points (RPs). Simulation and experimental results show that the proposed algorithm has better positioning performance than weighted k-nearest neighbor (WKNN), maximum correlation coefficient estimation (MCORE), Naive Bayes and support vector machine (SVM) in the case of different selected K numbers, grid distances, noise levels and AP numbers.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141687458","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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