Galloping of power transmission lines might bring about huge damage such as massive power outage and collapse of the transmission towers. To realize forecast of the galloping and provide data for study on the gallopin...Galloping of power transmission lines might bring about huge damage such as massive power outage and collapse of the transmission towers. To realize forecast of the galloping and provide data for study on the galloping mechanism, this paper proposes an online monitoring system for tracking galloping profile of power transmission lines based on wireless inertial measurement units (WIMUs). The system is composed of three modules: wireless inertial measurement nodes, monitoring base station, and remote monitoring station. After detailing the hardware system, the corresponding software which positions and displays galloping profile of the transmission line in real-time is outlined. The feasibility of the proposed on-line monitoring system is demonstrated through a series of experiments at the State Grid Key Laboratory of Power Overhead Transmission Line Galloping (Zhengzhou, China) by taking into account different vibration patterns.展开更多
Aiming at that the successive test data set of the strapdown inertial measurement unit is always small,a Bayesian method is used to study its statistical characteristics.Its prior and posterior distributions are set u...Aiming at that the successive test data set of the strapdown inertial measurement unit is always small,a Bayesian method is used to study its statistical characteristics.Its prior and posterior distributions are set up by the method and the pretest,sample and population information.Some statistical inferences can be made based on the posterior distribution.It can reduce the statistical analysis error in the case of small sample set.展开更多
Pavement horizontal curve is designed to serve as a transition between straight segments, and its presence may cause a series of driving-related safety issues to motorists and drivers. As is recognized that traditiona...Pavement horizontal curve is designed to serve as a transition between straight segments, and its presence may cause a series of driving-related safety issues to motorists and drivers. As is recognized that traditional methods for curve geometry investigation are time consuming, labor intensive, and inaccurate, this study attempts to develop a method that can automatically conduct horizontal curve identification and measurement at network level. The digital highway data vehicle （DHDV） was utilized for data collection, in which three Euler angles, driving speed, and acceleration of survey vehicle were measured with an inertial measurement unit （IMU）. The 3D profiling data used for cross slope calibration was obtained with PaveVision3D Ultra technology at 1 mm resolution. In this study, the curve identification was based on the variation of heading angle, and the curve radius was calculated with ki- nematic method, geometry method, and lateral acceleration method. In order to verify the accuracy of the three methods, the analysis of variance （ANOVA） test was applied by using the control variable of curve radius measured by field test. Based on the measured curve radius, a curve safety analysis model was used to predict the crash rates and safe driving speeds at horizontal curves. Finally, a case study on 4.35 km road segment demonstrated that the proposed method could efficiently conduct network level analysis.展开更多
High-precision localization technology is attracting widespread attention in harsh indoor environments.In this paper,we present a fingerprint localization and tracking system to estimate the locations of the tag based...High-precision localization technology is attracting widespread attention in harsh indoor environments.In this paper,we present a fingerprint localization and tracking system to estimate the locations of the tag based on a deep belief network(DBN).In this system,we propose using coefficients as fingerprints to combine the ultra-wideband(UWB)and inertial measurement unit(IMU)estimation linearly,termed as a HUID system.In particular,the fingerprints are trained by a DBN and estimated by a radial basis function(RBF).However,UWB-based estimation via a trilateral method is severely affected by the non-line-of-sight(NLoS)problem,which limits the localization precision.To tackle this problem,we adopt the random forest classifier to identify line-of-sight(LoS)and NLoS conditions.Then,we adopt the random forest regressor to mitigate ranging errors based on the identification results for improving UWB localization precision.The experimental results show that the mean square error(MSE)of the localization error for the proposed HUID system reduces by 12.96%,50.16%,and 64.92%compared with that of the existing extended Kalman filter(EKF),single UWB,and single IMU estimation methods,respectively.展开更多
Reliable and accurate calibration for camera,inertial measurement unit(IMU)and robot is a critical prerequisite for visual-inertial based robot pose estimation and surrounding environment perception.However,traditiona...Reliable and accurate calibration for camera,inertial measurement unit(IMU)and robot is a critical prerequisite for visual-inertial based robot pose estimation and surrounding environment perception.However,traditional calibrations suffer inaccuracy and inconsistency.To address these problems,this paper proposes a monocular visual-inertial and robotic-arm calibration in a unifying framework.In our method,the spatial relationship is geometrically correlated between the sensing units and robotic arm.The decoupled estimations on rotation and translation could reduce the coupled errors during the optimization.Additionally,the robotic calibration moving trajectory has been designed in a spiral pattern that enables full excitations on 6 DOF motions repeatably and consistently.The calibration has been evaluated on our developed platform.In the experiments,the calibration achieves the accuracy with rotation and translation RMSEs less than 0.7°and 0.01 m,respectively.The comparisons with state-of-the-art results prove our calibration consistency,accuracy and effectiveness.展开更多
The purpose of this paper is to design a DVL-RPM based VKF (Velocity Kalman Filter) design for a performance improvement underwater integrated navigation system. The integrated navigation sensor using DVL (Doppler Vel...The purpose of this paper is to design a DVL-RPM based VKF (Velocity Kalman Filter) design for a performance improvement underwater integrated navigation system. The integrated navigation sensor using DVL (Doppler Velocity Log) is widely used to improve the underwater navigation performance. However, the DVL’s range of measuring varied depending on the characteristics of sensor. So, if the sea gets too deep suddenly, it cannot measure the velocity. To complement such a weak point, the VKF was additionally designed, which was made of DVL, RPM (Revolve Per Minutes) of motor, and ES (Echo Sounder). The proposed approach relies on a VKF, augmented by an altitude from ES based switching architecture to yield robust performance, even when DVL exceeds the measurement range and the measured value is unable to be valid. The proposed approach relies on two parts: 1) indirect feedback navigation Kalman filter design, 2) VKF design. To evaluate the proposed method, we compare the VKF aided navigation system with PINS (Pure Inertial Navigation System) and conventional INS-DVL navigation system through simulation results. Simulations illustrate the effectiveness of the underwater navigation system assisted by the additional DVL-RPM based VKF in underwater environment.展开更多
文摘Galloping of power transmission lines might bring about huge damage such as massive power outage and collapse of the transmission towers. To realize forecast of the galloping and provide data for study on the galloping mechanism, this paper proposes an online monitoring system for tracking galloping profile of power transmission lines based on wireless inertial measurement units (WIMUs). The system is composed of three modules: wireless inertial measurement nodes, monitoring base station, and remote monitoring station. After detailing the hardware system, the corresponding software which positions and displays galloping profile of the transmission line in real-time is outlined. The feasibility of the proposed on-line monitoring system is demonstrated through a series of experiments at the State Grid Key Laboratory of Power Overhead Transmission Line Galloping (Zhengzhou, China) by taking into account different vibration patterns.
文摘Aiming at that the successive test data set of the strapdown inertial measurement unit is always small,a Bayesian method is used to study its statistical characteristics.Its prior and posterior distributions are set up by the method and the pretest,sample and population information.Some statistical inferences can be made based on the posterior distribution.It can reduce the statistical analysis error in the case of small sample set.
文摘为了提高表面肌电信号(surface electromyography,sEMG)的手势分类准确率,通过惯性测量单元(inertial measurement unit,IMU)与采集姿态信号与sEMG的混合信号,提出了GRUBiLSTM双层网络的实时手势分类算法。第1层门控循环单元(gated recurrent unit,GRU)利用能量组合算子特征对混合信号进行突变点检测,定位运动态数据起始点;第2层双向长短时记忆循环神经网络(Bi-directional long short term memory,BiLSTM)使用能量核相图特征对运动态混合信号进行2个方向10种手势的分类。通过离线模型优化,分类算法识别时间低于40 ms,突变点检测精度88.7%以上,手势分类准确率为85%,信息传输率(informationtranslaterate, ITR)达到89.9 bits/min,与基于机器学习的分类算法相比,在准确率与计算效率上具有优势。
文摘Pavement horizontal curve is designed to serve as a transition between straight segments, and its presence may cause a series of driving-related safety issues to motorists and drivers. As is recognized that traditional methods for curve geometry investigation are time consuming, labor intensive, and inaccurate, this study attempts to develop a method that can automatically conduct horizontal curve identification and measurement at network level. The digital highway data vehicle （DHDV） was utilized for data collection, in which three Euler angles, driving speed, and acceleration of survey vehicle were measured with an inertial measurement unit （IMU）. The 3D profiling data used for cross slope calibration was obtained with PaveVision3D Ultra technology at 1 mm resolution. In this study, the curve identification was based on the variation of heading angle, and the curve radius was calculated with ki- nematic method, geometry method, and lateral acceleration method. In order to verify the accuracy of the three methods, the analysis of variance （ANOVA） test was applied by using the control variable of curve radius measured by field test. Based on the measured curve radius, a curve safety analysis model was used to predict the crash rates and safe driving speeds at horizontal curves. Finally, a case study on 4.35 km road segment demonstrated that the proposed method could efficiently conduct network level analysis.
基金supported in part by the National Natural Science Foundation of China under Grant No.61771474in part by the Postgraduate Research&Practice Innovation Program of Jiangsu Province under Grant No.KYCX212243+2 种基金in part by the Young Talents of Xuzhou Science and Technology Plan Project under Grant No.KC19051in part by the Open Research Fund of National Mobile Communications Research Laboratory,Southeast University under Grant No.2021D02in part by the Open Fund of Information Photonics and Optical Communications (IPOC) (BUPT)。
文摘High-precision localization technology is attracting widespread attention in harsh indoor environments.In this paper,we present a fingerprint localization and tracking system to estimate the locations of the tag based on a deep belief network(DBN).In this system,we propose using coefficients as fingerprints to combine the ultra-wideband(UWB)and inertial measurement unit(IMU)estimation linearly,termed as a HUID system.In particular,the fingerprints are trained by a DBN and estimated by a radial basis function(RBF).However,UWB-based estimation via a trilateral method is severely affected by the non-line-of-sight(NLoS)problem,which limits the localization precision.To tackle this problem,we adopt the random forest classifier to identify line-of-sight(LoS)and NLoS conditions.Then,we adopt the random forest regressor to mitigate ranging errors based on the identification results for improving UWB localization precision.The experimental results show that the mean square error(MSE)of the localization error for the proposed HUID system reduces by 12.96%,50.16%,and 64.92%compared with that of the existing extended Kalman filter(EKF),single UWB,and single IMU estimation methods,respectively.
基金This work was supported by the International Partnership Program of Chinese Academy of Sciences(173321KYSB20180020,173321KYSB20200002)the National Natural Science Foundation of China(61903357,62022088)+3 种基金Liaoning Provincial Natural Science Foundation of China(2020-MS-032,2019-YQ-09,2020JH2/10500002,2021JH6/10500114)LiaoNing Revitalization Talents Program(XLYC1902110)China Postdoctoral Science Foundation(2020M672600)the Swedish Foundation for Strategic Research(APR20-0023).
文摘Reliable and accurate calibration for camera,inertial measurement unit(IMU)and robot is a critical prerequisite for visual-inertial based robot pose estimation and surrounding environment perception.However,traditional calibrations suffer inaccuracy and inconsistency.To address these problems,this paper proposes a monocular visual-inertial and robotic-arm calibration in a unifying framework.In our method,the spatial relationship is geometrically correlated between the sensing units and robotic arm.The decoupled estimations on rotation and translation could reduce the coupled errors during the optimization.Additionally,the robotic calibration moving trajectory has been designed in a spiral pattern that enables full excitations on 6 DOF motions repeatably and consistently.The calibration has been evaluated on our developed platform.In the experiments,the calibration achieves the accuracy with rotation and translation RMSEs less than 0.7°and 0.01 m,respectively.The comparisons with state-of-the-art results prove our calibration consistency,accuracy and effectiveness.
文摘The purpose of this paper is to design a DVL-RPM based VKF (Velocity Kalman Filter) design for a performance improvement underwater integrated navigation system. The integrated navigation sensor using DVL (Doppler Velocity Log) is widely used to improve the underwater navigation performance. However, the DVL’s range of measuring varied depending on the characteristics of sensor. So, if the sea gets too deep suddenly, it cannot measure the velocity. To complement such a weak point, the VKF was additionally designed, which was made of DVL, RPM (Revolve Per Minutes) of motor, and ES (Echo Sounder). The proposed approach relies on a VKF, augmented by an altitude from ES based switching architecture to yield robust performance, even when DVL exceeds the measurement range and the measured value is unable to be valid. The proposed approach relies on two parts: 1) indirect feedback navigation Kalman filter design, 2) VKF design. To evaluate the proposed method, we compare the VKF aided navigation system with PINS (Pure Inertial Navigation System) and conventional INS-DVL navigation system through simulation results. Simulations illustrate the effectiveness of the underwater navigation system assisted by the additional DVL-RPM based VKF in underwater environment.
