Efficient seismic response data storage and transmission using ARX model‐based sensor data compression algorithm

This paper presents a linear predictor (LP)‐based lossless sensor data compression algorithm for efficient transmission, storage and retrieval of seismic data. Auto‐Regressive with eXogenous input (ARX) model is selected as the model structure of LP. Since earthquake ground motion is typically measured at the base of monitored structures, the ARX model parameters are calculated in a system identification framework using sensor network data and measured input signals. In this way, sensor data compression takes advantage of structural system information to maximize the sensor data compression performance. Numerical simulation results show that several factors including LP order, measurement noise, input and limited sensor number affect the performance of the proposed lossless sensor data compression algorithm concerned. Generally, the lossless data compression algorithm is capable of reducing the size of raw sensor data while causing no information loss in the sensor data. Copyright © 2005 John Wiley & Sons, Ltd.     

传感器布设中有效独立法的简捷快速算法

本文提出一个通过正交三角分解快速计算有效独立法系数的方法。有效独立法是传感器布设中影响最广泛的一种方法,它使目标模态尽可能线性独立。传统的有效独立法计算需要对信息阵进行特征值分解或者计算矩阵逆,计算量较大。本文在笔者以前得出的有效独立法与模态动能法关系的基础上,提出先通过对模态矩阵进行正交三角分解（QR）,然后比较其行范数即可得到有效独立法的系数,进而对各待选传感器位置进行排序并迭代依次删除。在待选传感器位置比感兴趣的模态数较多时,该法的计算效率明显提高。同时,采用正交三角分解删除一行后的更新算法,进一步提高了迭代计算的效率。最后通过I-40桥的算例表明该法的有效性。     

四种新型土壤墒情传感器的对比分析

土壤墒情监测工作日益得到重视。在北京上庄试验站选择四种不同工作原理和型号的土壤墒情传感器进行了为期半年的对比分析测试,利用监测数据对土壤墒情传感器的稳定性、灵敏性、准确率三个指标进行了分析,结果表明各类传感器在监测效果方面表现各有优缺点,均表现出了较好的稳定性,对降水反应也良好,准确率略有差别,监测数据基本在烘干法值附近上下波动。通过对比分析研究,对了解土壤墒情传感器性能和大范围推广应用具有一定的参考意义。     

Efficient Bayesian sensor placement algorithm for structural identification: a general approach for multi‐type sensory systems

In this paper, a Bayesian sequential sensor placement algorithm, based on the robust information entropy, is proposed for multi‐type of sensors. The presented methodology has two salient features. It is a holistic approach such that the overall performance of various types of sensors at different locations is assessed. Therefore, it provides a rational and effective strategy to design the sensor configuration, which optimizes the use of various available resources. This sequential algorithm is very efficient due to its Bayesian nature, in which prior distribution can be incorporated. Therefore, it avoids the possible unidentifiability problem encountered in a sequential process, which starts with small number of sensors. The proposed algorithm is demonstrated using a shear building and a lattice tower with consideration of up to four types of sensors. Copyright © 2014 John Wiley & Sons, Ltd.     

轨道扣件病害自动化检测研究及应用

传统扣件检查基本采用人工检查方式,不仅工作效率低、劳动强度大,而且人为干扰因素多、检查采样率低.针对以上问题,本文提出了一种基于线结构光传感器的轨道扣件损伤和松动检测方法,并开发了轨道扣件智能监测系统以实现扣件病害自动检测.最终将研究成果应用于徐州市某地铁区间轨道扣件检测,验证了该方法的可行性和准确率,为地铁轨道扣件检...     

航向测量仪在车载三维信息采集系统中的应用

航向测量仪(Vector Sensor)的作用就是为车载惯导系统初始化提供所必须的航向角;根据不同的应用环境和特性,用航向测量仪获取在各种条件下的航向角数据,通过对这些数据在精度、稳定性以及解算时间等性能上的对比分析,得到该仪器的最佳工作状态,进而获取该状态下的航向数据;通过实际的实验测试,此状态下的数据在精度和稳定性方面都能满足惯导系统的需求。     

Calibrating the GOCE accelerations with star sensor data and a global gravity field model

A reliable and accurate gradiometer calibration is essential for the scientific return of the gravity field and steady-state ocean circulation explorer (GOCE) mission. This paper describes a new method for external calibration of the GOCE gradiometer accelerations. A global gravity field model in combination with star sensor quaternions is used to compute reference differential accelerations, which may be used to estimate various combinations of gradiometer scale factors, internal gradiometer misalignments and misalignments between star sensor and gradiometer. In many aspects, the new method is complementary to the GOCE in-flight calibration. In contrast to the in-flight calibration, which requires a satellite-shaking phase, the new method uses data from the nominal measurement phases. The results of a simulation study show that gradiometer scale factors can be estimated on a weekly basis with accuracies better than 2 × 10⁻³ for the ultrasensitive and 10⁻² for the less sensitive axes, which is compatible with the requirements of the gravity gradient error. Based on a 58-day data set, scale factors are found that can reduce the errors of the in-flight-calibrated measurements. The elements of the complete inverse calibration matrix, representing both the internal gradiometer misalignments and scale factors, can be estimated with accuracies in general better than 10⁻³.     

具有国际先进水平的CTD定标检测设备

在国家863计划的支持下，海洋技术研究成功研制了一套CTD仪器的校准设备，本文介绍了设备的组成，性能，设计经过与SBE设备进行了比较，表明该设备达到了EOCECTD设备的校准要求，同时，该设备是海洋技术研究所开发自有的高度CTD剖面仪的有力工具。     

PARASOL/POLDER3卫星数据的海洋上空云检测

在卫星海洋遥感中,云作为海气耦合系统最重要的调节器之一,其检测结果对海洋上空云微物理特性的反演精度有较大影响。因此,快速而准确识别海洋上空的云像元是卫星遥感数据处理过程中首要解决的关键问题。以PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar)卫星搭载的POLDER3载荷遥感数据为研究对象,提出一种改进的海洋上空云检测方法。首先剔除海洋耀光;接着利用有云与晴空区近红外反射率差异检验识别有云像元,并利用偏振反射率检验进一步识别低反射率的云像元;然后利用近红外与可见光反射率比值检验识别晴空像元;最后建立多角度云检测结果空间融合规则,重新标记有云、晴空和未定像元。以印度洋海区为例进行实验分析,将云检测结果与Buriez方法进行对比,发现检测精度基本相当,而有云像元的识别速度却平均提高约3倍。结果表明:该方法能有效的检测出海洋上空的云像元,满足业务化数据处理的高精度及时效性要求,为后续云微物理特性反演提供可靠的数据源。     

FDR土壤水分传感器原状土壤标定方法研究

为获得测站准确的土壤水分传感器标定参数,利用自动土壤水分站点的大型原状土壤为样本,在实验室同时进行人工称重观测和仪器自动对比观测,得到一系列的人工自动测量数据,以人工称重数据为准对自动土壤水分传感器进行订正。由于采用原状土壤,样本土壤的质地、密度、土壤颗粒和结合紧密度基本没有受到破坏,订正后的自动土壤体积含水量值能更加真实反映台站实际土壤墒情,能够修订人工对比观测期间由于样本空间不足导致的不合理的田间标定方程。