DPCM-based vibration sensor data compression and its effect on structural system identification

Due to the large scale and complexity of civil infrastructures, structural health monitoring typically requires a substantial number of sensors, which consequently generate huge volumes of sensor data. Innovative sensor data compression techniques are highly desired to facilitate efficient data storage and remote retrieval of sensor data. This paper presents a vibration sensor data compression algorithm based on the Differential Pulse Code Modulation (DPCM) method and the consideration of effects of signal distortion due to lossy data compression on structural system identification. The DPCM system concerned consists of two primary components: linear predictor and quantizer. For the DPCM system considered in this study, the Least Square method is used to derive the linear predictor coefficients and Jayant quantizer is used for scalar quantization. A 5-DOF model structure is used as the prototype structure in numerical study. Numerical simulation was carried out to study the performance of the proposed DPCM-based data compression algorithm as well as its effect on the accuracy of structural identification including modal parameters and second order structural parameters such as stiffness and damping coefficients. It is found that the DPCM-based sensor data compression method is capable of reducing the raw sensor data size to a significant extent while having a minor effect on the modal parameters as well as second order structural parameters identified from reconstructed sensor data.     

Tracking modal parameters from building seismic response data using recursive subspace identification algorithm

Tracking modal parameters and estimating the current structural state of a building from seismic response measurements, particularly during strong earthquake excitations, can provide useful information for building safety assessment and the adaptive control of a structure. Therefore, online or recursive identification techniques need to be developed and implemented for building seismic response monitoring. This paper develops and examines different methods to track modal parameters from building seismic response data. The methods include recursive data‐driven subspace identification (RSI‐DATA) using Givens rotation algorithm, and RSI‐DATA using Bona fide algorithm. The question on how well the results of RSI‐DATA reflect the real condition is investigated and verified with a bilinear SDOF simulation study. Time‐varying modal parameters of a four‐story reinforced concrete school building are identified based on a series of earthquake excitations, including several seismic events, large and small. Discussions on the different methods' ability to track the time‐varying modal parameters are presented. The variation of the identified building modal frequencies and damping ratios from a series of event‐by‐event seismic responses, particularly before and after retrofitting of the building is also discussed. Copyright © 2017 John Wiley & Sons, Ltd.     

High‐resolution seismic monitoring of instrumented buildings using a model‐based state observer

This paper proposes a model‐based state observer to perform high‐definition response estimation in partially instrumented building structures. The proposed estimator is verified in a simulated five‐story shear‐building structure and validated using measurements from a seven‐story reinforced concrete building slice tested at the NEES‐University of California at San Diego shake table. In both cases the proposed estimator yielded satisfactory results by estimating the time history of shear forces, bending moments, displacements, and strains at various points/sections of interest. The proposed algorithm can be used in instrumented buildings for various practical applications such as post‐earthquake damage assessment, structural control, and building code calibration. Copyright © 2016 John Wiley & Sons, Ltd.     

A real-time algorithm for broadband high-dynamic seismic data compression

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地震数据IP传输及存储技术应用

介绍一种IP传输方案。该方案通过地震数据IP传输及存储单元(ITU)、IP流多串口服务器完成，能实现单个台站与多个台网中心的Internet传输、单个台站与多个台网中心的专线传输、地震台网中心之间的Internet连接、远程数据下载及参数设置等多种传输方式，该传输方案具备实时性、可压缩性、多路服务、安全性、数据在线保存、传输费用低、操作简单等特点。     

Dynamic model updating using a combined genetic‐eigensensitivity algorithm and application in seismic response prediction

A reliable computational model is necessary for evaluating the state and predicting the future performance of existing structures, especially after exposure to damaging effects such as an earthquake. A major problem with the existing iterative‐based model updating methods is that the search might be trapped in local optima. The genetic algorithms (GAs) offer a desirable alternative because of their ability in performing a robust search for the global optimal solution. This paper presents a GA‐based model updating approach using a real‐coding scheme for global model updating based on dynamic measurement data. An eigensensitivity method is employed to further fine‐tune the GA updated results in case the sensitivity problem arises due to restricted measurement information. The application on shear‐type frames reveals that with a limited amount of modal data, namely the lowest three natural frequencies and the first mode shape, it is possible to achieve satisfactory updating by the GA alone for cases involving a limited number of parameters (storey stiffness herein). With the incorporation of the eigensensitivity algorithm, the updating capability is extended to a sufficiently large number of parameters. In case the modal data contain errors, the GA is also shown to be able to update the model to a satisfactory accuracy, provided the required amount of modal data is available. An example is given in which a 6‐DOF stick model for an actual six‐storey RC frame is updated using the measured dynamic properties. The effectiveness of the updating is evaluated by comparing the measured and predicted seismic response using the updated model. Copyright © 2005 John Wiley & Sons, Ltd.     

Application of wavelet theory to identify yielding in seismic response of bi‐linear structures

The time–frequency and the time‐scale analysis methods are used in this paper to identify the dynamic characteristics of non‐linear seismic response of structural systems with single degree of freedom (SDOF) and multiple degrees of freedom (MDOF). Based on the floor acceleration response time histories of bi‐linear SDOF and MDOF structures, the current study compares the results of system identification using the short‐time Fourier transform (STFT), continuous wavelet transform (CWT) and discrete wavelet transform (DWT) methods. The aim is to identify the frequency variations and the time at on‐set of yielding and unloading of a bi‐linear structural system during seismic response. The results demonstrate that the CWT method is better than the STFT method in both time and frequency resolutions, and that the DWT method is the best at detecting the time at on‐set of yielding and unloading. Combining the results of CWT and DWT methods therefore provides accurate information of both frequency variations and yielding time in non‐linear seismic response. To alleviate the problems associated with noise‐contaminated signals, e.g. seismic response data recorded on site, the study suggests that low‐pass filtering be carried out before applying the DWT method to decompose the signals into multiple levels of details. Copyright © 2001 John Wiley & Sons, Ltd.     

Identification of model structure parameters via combination of AFMM and ARX from seismic response data

To identify the model structure parameters in shaking table tests from seismic response, especially from timevarying response records, this paper presents a new methodology by combining the online recursive Adaptive Forgetting through Multiple Models(AFMM) and offline Auto-Regression with eXogenous variables(ARX) model. First, the AFMM is employed to detect whether the response of model structure is time-invariant or time-varying when subjected to strong motions. Second, if the response is time-invariant, the modal parameters are identifi ed from the entire response record, such as the acceleration time-history using the ARX model. If the response is time-varying, the acceleration record is divided into three segments according to the accurate time-varying points detected by AFMM, and parameters are identifi ed by only using the tail segment data, which is time-invariant and suited for analysis by the ARX model. Finally, the changes in dynamic properties due to various strong motions are obtained using the presented methodology. The feasibility and advantages of the method are demonstrated by identifying the modal parameters of a 12-story reinforced concrete(RC) frame structure in a shaking table test.     

ARX结构模态参数识别方法对比(I)——基于理论地震反应时程的对比

结构参数识别是结构抗震安全性能鉴定和健康诊断的基础。利用地震观测记录来识别结构模态参数,是地震工程领域备受关注的研究课题之一。本文利用三层平面框架结构的理论地震反应时程,对一维、多维和整体ARX模型三种模态参数识别方法进行了对比分析。结果表明：整体ARX模型的识别结果较为稳定且精度较高,更适合于进行多自由度结构参数识别。     

Mallat算法在数字地震信号压缩中的应用

地震台站多、数据采集量大,日产出数据量庞大,研究数字地震信号的压缩方法成为行业热门课题。尝试将Mallat算法应用于数字地震波形数据压缩。选取不同的小波分解函数,对不同类型的数字地震信号进行3—5层的小波分解,将得到的小波系数进行分层硬阈值重构运算,对原始信号和处理信号进行压缩。分析可知,Mallat算法压缩比更高,与原始信号相比,重构信号不失真、能量保留系数高。     

地震数据无线传输技术的新进展

24bit数字地震观测系统的应用对无线数传设备提出了许多新的要求。不断恶化的外部电磁环境亦要求无线数传设备具有更强的抗干扰能力，在研制新一代异步无线数传调制解调板时，自主开发或引用了几项新技术并取得了很的实用效果。异步数据复用是无线阻网实现各种容量等级汇集中继的关键技术，在提高复用效率，完善容量等级，增加设备功能等方面有新的产品推出，这些新技术的应用和新成果的取得，不仅大大扩展了无线数传在地震遥测中的应用范围，亦大大提高了无线数传在强干扰中的生存能力。     

地震数据存储交换中的压缩技术

通过对全球地震专家系统所使用的地震数据传输过程的解析，介绍一种行之有效的数字地震数据压缩编码及使用的原理和方法。     

测震台网数据传输补数技术

针对测震台网波形数据传输中断导致丢数现象,开发测震台网自动补数系统SDARS,自动检测数据丢失现象,并从地震台数据采集器下载缺失数据;设计手动辅助补数工具软件SeisDataUtil,提供不同格式的地震数据文件的手动补数功能。通过此套补数系统,有效提高测震台网波形数据完整率,最小化减少波形数据丢失。     

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.     

地震烈度仪数据传输协议

中国地震烈度速报与预警系统建设即将全面启动,面对未来地震预警系统中大量地震烈度仪的接入,为了方便数据的传输、汇集、共享、使用和管理,设计一种地震烈度仪数据传输协议。本文介绍烈度仪数据传输协议设计思想和特点,并给出一种参考实现,重点表述各个模块的功能和逻辑关系。     

Efficient and accurate edge‐preserving smoothing for 3D hexagonally sampled seismic data

The automatic detection of geological features such as faults and channels is a challenging problem in today's seismic exploration industry. Edge detection filters are generally applied to locate features. It is desirable to reduce noise in the data before edge detection. The application of smoothing or low‐pass filters results in noise suppression, but this causes edge blurring as well. Edge‐preserving smoothing is a technique that results in simultaneous edge preservation and noise suppression. Until now, edge‐preserving smoothing has been carried out on rectangular sampled seismic data. In this paper, an attempt has been made to detect edges by applying edge‐preserving smoothing as a pre‐processing step in the hexagonally sampled seismic‐data spatial domain. A hexagonal approach is an efficient method of sampling and has greater symmetry than a rectangular approach. Here, spiral architecture has been employed to handle the hexagonally sampled seismic data. A comparison of edge‐preserving smoothing on both rectangular and hexagonally sampled seismic data is carried out. The data used were provided by Saudi Aramco. It is shown that hexagonal processing results in well‐defined edges with fewer computations.     

System identification applied to long‐span cable‐supported bridges using seismic records

This paper presents the application of system identification (SI) to long‐span cable‐supported bridges using seismic records. The SI method is based on the System Realization using Information Matrix (SRIM) that utilizes correlations between base motions and bridge accelerations to identify coefficient matrices of a state‐space model. Numerical simulations using a benchmark cable‐stayed bridge demonstrate the advantages of this method in dealing with multiple‐input multiple‐output (MIMO) data from relatively short seismic records. Important issues related to the effects of sensor arrangement, measurement noise, input inclusion, and the types of input with respect to identification results are also investigated. The method is applied to identify modal parameters of the Yokohama Bay Bridge, Rainbow Bridge, and Tsurumi Fairway Bridge using the records from the 2004 Chuetsu‐Niigata earthquake. Comparison of modal parameters with the results of ambient vibration tests, forced vibration tests, and analytical models are presented together with discussions regarding the effects of earthquake excitation amplitude on global and local structural modes. Copyright © 2007 John Wiley & Sons, Ltd.     

Sensitivity of seismic structural response to interpretation of soils data

This paper investigates the sensitivity of the predicted seismic response of buildings in a PWR nuclear power station to the potential changes in the techniques and methods of interpreting soil data that have occurred over the last decade. The investigation is based on the soil-structure interaction (SSI) response of a typical PWR reactor building on a soft site during a seismic event. The current techniques and methods of interpretation of soils data tend to lead to a stiffer site with lower soil material damping than the earlier techniques. This leads to an increase in the SSI natural frequencies of typical buildings and an increase in its seismic response. This increase in the seismic response could put into question any seismic design based on seismic loads derived using the previously accepted generic soil data. The paper concludes with a recommendation for further consideration of the proposed departure from the previously accepted soil data.     

Interbuilding interpolation of peak seismic response using spatially correlated demand parameters

Seismic structural responses recorded in instrumented buildings during an earthquake are used to provide insights into the demands placed on neighboring, noninstrumented buildings, using a framework to interpolate structural response demands across buildings. The interbuilding interpolation model relies on the spatial and structural correlations of responses in coregionally located buildings subjected to a seismic event. A dataset of response demands for a portfolio of reinforced concrete moment frame buildings is generated by performing nonlinear response history analyses on structural models using ground motions recorded from historical scenario earthquakes. The dataset is used to characterize the correlation between seismic demands across different buildings. Semivariograms are used to model spatial and structural correlations and then incorporated into a kriging algorithm, which forms the basis of the interpolation models. The effect of several model and dataset attributes and assumptions, for example, using intensity‐measure‐based versus engineering demand parameter‐based semivariograms, and size of training dataset relative to portfolio, on the overall performance are evaluated along with the limitations of the proposed model.     

SEED格式STEIM2数据压缩算法在实时地震数据传输中的应用

在一定带宽内,及时、高效、无失真地传输地震数据是地震数据传输的基本要求,SEED格式给出的数据格式在数据压缩方面有其独到之处,但SEED格式没有定义数据正确性和完整性保证机制和检验方法,因而影响实时传输中的使用。本文提出一种基于SEED格式的STEIM2数据压缩算法,同EDAS数据包形式兼容的实时压缩数据包编码方法,来实现实时压缩数据的传输。经理论评估和实际数据检验,它容易实现,效率高,安全,可靠,完全可以应用于实时数据传输。