Improved spatio-temporal alignment measurement method for hull deformation

In this paper,an improved spatio-temporal alignment measurement method is presented to address the inertial matching measurement of hull deformation under the coexistence of time delay and large misalignment angle.Large misalignment angle and time delay often occur simultaneously and bring great challenges to the accurate measurement of hull deformation in space and time.The proposed method utilizes coarse alignment with large misalignment angle and time delay estimation of inertial measurement unit modeling to establish a brand-new spatiotemporal aligned hull deformation measurement model.In addition,two-step loop control is designed to ensure the accurate description of dynamic deformation angle and static deformation angle by the time-space alignment method of hull deformation.The experiments illustrate that the proposed method can effectively measure the hull deformation angle when time delay and large misalignment angle coexist.

Tracking Galloping Profile of Transmission Lines Using Wireless Inertial Measurement Units

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.

Digital image stabilization system based on inertial measurement module

In order to stabilize the video module to build digital image stabilization image sequence, a method of using inertial measurement system is proposed. Through applying real-time attitude in- formation of the camera that obtained by high-precision attitude sensor to estimate the image motion vector and then to compensate for image, the purpose of stabilizing the image sequence can be a- chieved. Experiments demonstrate that this method has a high image stabilization precision, and the up to 16 frame/s video output rate completely meets the real-time requirements.

Inertial measurement using atom interferometry

The recent advances of atom interferometer and its application in precision inertial measurement are review ed. The principle,characteristics and implementation of atom interferometer are introduced and it can be used to measure gravitational acceleration,gravity gradient and rotation for its high sensitivity. We also present the principle,structure and new progress of gravimeter,gravity gradiometer and gyroscope based on atom interferometer.

Research on Test Data Distribution of Strapdown Inertial Measurement Unit Based on Bayesian Method

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.

A Fast Small-Sample Modeling Method for Precision Inertial Systems Fault Prediction and Quantitative Anomaly Measurement

Inertial system platforms are a kind of important precision devices,which have the characteristics of difficult acquisition for state data and small sample scale.Focusing on the model optimization for data-driven fault state prediction and quantitative degreemeasurement,a fast small-sample supersphere one-class SVMmodelingmethod using support vectors pre-selection is systematically studied in this paper.By theorem-proving the irrelevance between themodel’s learning result and the non-support vectors(NSVs),the distribution characters of the support vectors are analyzed.On this basis,a modeling method with selected samples having specific geometry character fromthe training sets is also proposed.The method can remarkably eliminate theNSVs and improve the algorithm’s efficiency.The experimental results testify that the scale of training samples and the modeling time consumption both give a sharply decrease using the support vectors pre-selection method.The experimental results on inertial devices also show good fault prediction capability and effectiveness of quantitative anomaly measurement.

A New Inertial Sensing System for Dynamic Measurement of Parallel Machines

One way to solve the problem of measurement precision caused by deformity for thermal expansion, friction and load etc is to use an inertial sensor to measure a change in the length of the rod on a parallel machine. However, the characteristic of dynamic measurement in the inertial sensing system and the effects of the machine＇s working environment, bias error, misalignment and wide band random noise in inertial measurement data results in the in-accuracy of system measurement. Therefore, on the basis of the measurement system a new inertial sensing system is proposed; the drifting of error is restrained with a method of inertial error correction and the system＇s position and the velocity state variables are predicted by the data fusion. After measuring the whole 300mm movement in an experiment, the analyses of the experimental result showed that the application of the new inertial sensing system can improve the positional accuracy about 61% and the movement precision more than 20%. Measurement results also showed that the application of the new inertial sensing system for dynamic measurement was a feasible method to improve the machine＇s dynamic positioning precision. And with the further improvement of the low-cost solid-stateacceleramenter technology, the application of the machine can take a higher position and make the speed dynamic accuracy possible.

A Measure System of Zero Moment Point Using Wearable Inertial Sensors

Keeping balance is the premise of human walking. ZMP(zero moment point) is a point where total torque achieves balance. It is an important evaluation parameter of balance ability in walking, since it can be used to better reflect the dynamic balance during walking. ZMP can be used in many applications, such as medical rehabilitation, disease diagnosis, treatment and etc. In this paper, wearable inertial sensors system based on MEMS is used to measure ZMP(zero moment point) during walking, which is cheap, convenient, and free from the restriction of lab. Our wearable ZMP measurement system consists of inertial measurement subsystem and PC real-time monitoring station. Inertial measurement subsystem includes 9-axis inertial sensing nodes, the body communication network and the central node. Inertial sensing nodes are mounted on different parts of the body to collect body posture information in real-time, and then the best estimation of current posture are obtained by Kalman filter. The data from sensors is aggregated to the central node through the CAN bus, and then ZMP is calculated. Finally, it can be showed in the PC monitoring station. Experiments prove the system can achieve real-time ZMP detection during walking.

A Combined Alignment Method for Strapdown Inertial Navigation System on Stationary Base

Owing to the weak observability of the azimuth misalignment angle,alignment accuracy and time are always the contradictory issues in the initial alignment process of Strapdown Inertial Navigation System(SINS),which requires a compromise between them.In this paper,a combined alignment mechanism is proposed to construct an observable and controllable system model,which can effectively achieve higher azimuth alignment accuracy during the fixed time period.First,the Reduced Order Kalman Filter(ROKF)alignment algorithm was utilized to calculate the misalignment angles in parallel with the classical gyrocompass alignment algorithm.Then,the misalignment angles calculated by the gyrocompass alignment method were used to formulate the augmented measurement model with zero velocity models.Finally,the zero velocity model of the ROKF method was switched into the augmented measurement model when the azimuth misalignment angle of the gyrocompass alignment method was close to steady situation.The combined alignment method was analyzed reasonably by the observability and the mathematical deduction.The comparison results of the numerical simulation and the experimental data test showed that the combined method had good performance in terms of estimation accuracy and consistency of the alignment results.

DVL/RPM Based Velocity Filter Aiding in the Underwater Vehicle Integrated Inertial Navigation System

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.

Monocular Visual-Inertial and Robotic-Arm Calibration in a Unifying Framework

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.

Implementation and Validation of a Stride Length Estimation Algorithm,Using a Single Basic Inertial Sensor on Healthy Subjects and Patients Suffering from Parkinson’s Disease

As low cost and highly portable sensors, inertial measurements units (IMU) have become increas-ingly used in gait analysis, embodying an efficient alternative to motion capture systems. Mean-while, being able to compute reliably accurate spatial gait parameters using few sensors remains a relatively complex problematic. Providing a clinical oriented solution, our study presents a gy-rometer and accelerometer based algorithm for stride length estimation. Compared to most of the numerous existing works where only an averaged stride length is computed from several IMU, or where the use of the magnetometer is incompatible with everyday use, our challenge here has been to extract each individual stride length in an easy-to-use algorithm requiring only one inertial sensor attached to the subject shank. Our results were validated on healthy subjects and patients suffering from Parkinson’s disease (PD). Estimated stride lengths were compared to GAITRite? walkway system data: the mean error over all the strides was less than 6% for healthy group and 10.3% for PD group. This method provides a reliable portable solution for monitoring the in-stantaneous stride length and opens the way to promising applications.

融合表面肌电和姿势信息的轮椅绩效评价方法

目的为客观评价轮椅的使用效益,使用表面肌电设备测试轮椅使用过程中的肌电信号,并融合姿势信号IMU来构建人机评价模型。方法分别对轮椅的折叠、刹车方式及行驶坡度进行试验来评估轮椅的使用绩效,通过对比用力肌群间的疲劳状况来判定较为舒适的轮椅折叠及刹车方式。实验要求被试者在执行轮椅任务时,分别使用两种折叠方式和三种刹车方式不同的轮椅进行实验,并在操作动作任务过程中采集sEMG和IMU信号,在实验任务结束后填写NASA-TLX量表。结果根据模型的评价指标对实验数据进行了比较与分析,横向收折式折叠和凹口式刹车(手刹位于前方)的轮椅疲劳度低,在3~4°坡度范围下轮椅使用者的受力最小,较为舒适,从而验证了模型在轮椅人机评价上的可行性,为优化轮椅设计提供参考。结论人机评价模型适用于评估产品绩效,同时提出的融合表面肌电和姿势信息的轮椅绩效评价方法具有较高的精度和准确性,能够有效地评估轮椅使用者的绩效水平。

基于PE-ANGO的MIMU现场标定方法

针对当前微惯性测量单元(MIMU)的现场标定方法存在标定步骤复杂、不利于非专业人员操作等问题,提出了一种基于先验知识增强的自适应北苍鹰优化(PE-ANGO)算法的MIMU现场标定方法。首先分析了MIMU涉及的误差并建立了加速度计和陀螺仪的目标函数,然后使用PE-ANGO算法求解目标函数并得到最优参数。为了使得标定工作易于现场操作,引入了一种用于传感器数据采集的手持MIMU来验证所提算法。仿真结果表明:PE-ANGO算法的标定精度相较于北苍鹰优化算法提高了一个数量级。实测实验表明:标定前后对俯仰角和横滚角累积误差的抑制效果分别提高了约89%和87%;与传统标定方法相比,对俯仰角和横滚角累积误差的抑制效果分别提高了71%和68%,验证了所提方法的有效性。

舰载飞机着舰撞击载荷实测技术研究

针对国内飞机起落架载荷测量中普遍存在的静标动测问题,从理论和机理上分析了静标定的应变法实测动态载荷存在问题的原因。同时,考虑到舰载飞机因定点着舰方式遭受严重的动态载荷,重点研究了舰载飞机着舰撞击载荷的静标动测问题。通过动态落震试验模拟飞机着舰过程,根据测力平台的实测载荷分析,获取了应变法实测载荷精度受动态影响的程度,提出一种改进的惯性修正方法,即:通过落震试验数据辨识质量矩阵,通过辨识的质量矩阵和实测加速度修正应变法的实测载荷。试验结果表明,改进的惯性修正方法进一步提高了垂向载荷的测量精度,显著提高了航向和侧向载荷的实测精度。

基于足间距信息辅助的行人三维惯性定位算法

针对行人惯性导航系统误差随时间累积致使定位精度严重下降的问题,提出了一种基于足间距信息辅助的行人三维惯性定位算法。该算法在零速修正算法的基础上,利用足部安装的超声波测距模块实时测量行人双足相对距离,构建了基于超声测距的足间距约束模型,通过随机森林算法实现行人运动模式识别,并针对上下楼梯场景,利用台阶高度和足间距信息进行高度解算,最终实现行人三维惯性定位。在实际路线上开展了三维定位实验,数据显示,所提算法平面闭环误差为总路程的0.64%,与零速修正算法相比下降了55.56%,高度误差为0.06 m,与零速修正和气压计联合算法相比下降了64.70%,能够实现导航误差在总路程的0.50%以内的三维定位。实验结果表明,所提算法具有良好的工程应用价值。

基于改进LSTM网络的无人机MEMS-IMU零偏在线标定方法

针对在卫星信号拒止、视觉系统退化场景中无人机MEMS-IMU零偏无法准确估计并补偿导致导航误差迅速发散的问题,提出一种基于改进长短时记忆(LSTM)网络的零偏在线标定方法。首先,为解决MEMS-IMU零偏数据非线性强、传统循环时间网络训练效果差的问题,设计序列到序列的LSTM神经网络结构,引入教师强迫机制,提高了网络特征学习能力。然后,在导航过程中使用训练后的网络对MEMS-IMU零偏在线标定,补偿后的IMU量测与视觉信息联合优化,保证了导航定位精度。实验结果表明,在纯惯性导航实验中,所提方法的绝对位置误差比传统LSTM方法减小了6.5%;在EUROC数据集下进行的视觉惯性组合导航实验中,所提方法的平均绝对位置误差比传统LSTM方法减小了15%。

基于激光诱导石墨烯的木制惯性测量单元

针对商用低精度惯性测量单元具有高成本、制造工艺复杂、废弃后污染环境、不能生物降解等缺点,提出一种低成本、可生物降解的木制惯性测量单元。该设计包含平衡振子和非平衡振子单元,分别用于测量3轴加速度和3轴角加速度。采用激光诱导石墨烯的工艺在木梁上制备应变传感器阵列,并形成多组惠斯顿电桥测量电路。结果表明:加速度方面,X轴灵敏度为0.006 m V/g,Y轴灵敏度为8.695×10^(-4)m V/g,Z轴灵敏度为0.200 m V/g;角加速度方面,X轴灵敏度为0.285 m V/(rad/s^(2)),绕Y轴旋转的灵敏度为0.305 m V/(rad/s^(2)),绕Z轴旋转的灵敏度为0.765 m V/(rad/s^(2))。与有限单元法仿真结果对比,实验测量误差在10%以内,且具有良好的重复测量精度。该惯性测量单元在木制船舶、木制载具、木制家具等方面具有潜在的应用前景。

基于局部摄影的单目视觉输电线路弧垂测量

定期监测输电线路中导线弧垂的大小对输电线路的稳定运行有重要意义。传统的弧垂测量方法操作复杂且耗时较长,应用单目视觉获取完整导线图像是一种便捷的弧垂测量方法,但是当输电线路的档距过大时,相机受视场角和分辨率的限制,无法拍摄完整的导线,难以测量弧垂。针对上述问题,设计了一种便捷可用的局部摄影测量方法,将IMU中的加速度计传感器与高分辨率工业单目相机结合,在已知少量输电线路参数的条件下,只需拍摄待测导线的左侧部分即可。获得单幅导线图像后,引入语义分割技术提取图像中的导线,以摄影测量模型为基础将导线的实际点与对应成像点建立联系,以此建立非线性方程组,经非线性求解恢复导线的三维形状,进而计算导线弧垂。弧垂的测量相对误差可以控制在5%以内,满足实际应用需求。

一种双路并行的大规模手势识别模型

文章以大规模手势为研究对象,提出一种基于肌电信号(electromyography,EMG)分支和惯性测量单元(inertial measurement unit,IMU)分支的双路并行手势识别模型。首先,设计双路并行模型来充分提取数据特征,EMG分支利用二维卷积神经网络设计双流结构,分别关注EMG信号的空间和通道变化,IMU分支在卷积长短时记忆(convolutional long short-term memory,ConvLSTM)网络基础上引入时间机制,将空间信息与时间信息融合;其次,对模型预训练并根据预训练模型进行参数微调,提高模型泛化性;最后,在500个常用的中国手语手势上进行测试,结果表明,该模型平均识别率为82.1%,与SignSpeaker和CG-Recognizer相比分别提高了21.0%和6.8%。