Ground Motion Signals Research Articles

Recognition and prediction of ground vibration signal based on machine learning algorithm

Accurate recognition of the type of ground motion is a basic task in the field of seismic engineering. In this paper, the key technologies of detection and recognition of underground seismic signal are studied. The target recognition algorithm is designed to realize the target recognition through denoising the collected target signal and extracting the characteristic quantity. Considering that ground motion signals generated by moving targets on the ground are susceptible to environmental noise, this paper introduces the working principle of wavelet packet denoising and its support vector machine classification model. Wavelet packet was used to transform the signal to denoise first, then zero-crossing rate analysis of the denoised signal was carried out after wavelet packet denoising and extracts the parameters, and the energy of cross-correlation criteria was selected finally. Quantitative indices are combined to construct multi-feature vectors, which are used as input of multi-class support vector machine for training and prediction. In this model, the optimal parameters of support vector machine model are found by genetic algorithm parameter optimization. The experimental results show that the improved model can recognize and classify the ground motion signals caused by people and vehicles correctly and can improve the performance of the classifier.

Exploiting both output channels of seismically decoupled infrasound sensors for enhanced transient detection and direction-of-arrival estimation

Some infrasound sensors have internal sensing capabilities that remove or permit subsequent removal of much of the effect of ground motion on the measured pressure fluctuations. This presentation explores possible enhancements to transient acoustic signal detection and direction-of-arrival estimation when data corresponding to the ground motion and pressure fluctuation signals are analyzed simultaneously using statistical array signal processing techniques. Data from three 4-element infrasound sensor arrays that were deployed to detect explosive events occurring from 10 km to 20 km distant are used as the basis for the study.

Empirical recurrence rates for ground motion signals on planetary surfaces

We determine the recurrence rates of ground motion events as a function of sensed velocity amplitude at several terrestrial locations, and make a first interplanetary comparison with measurements on the Moon, Mars, Venus and Titan. This empirical approach gives an intuitive order-of-magnitude guide to the observed ground motion (including both tectonic and ocean- and atmosphere-forced signals) of these locations as a guide to instrument expectations on future missions, without invoking interior models and specific sources: for example a Venera-14 observation of possible ground motion indicates a microseismic environment mid-way between noisy and quiet terrestrial locations. Quiet terrestrial regions see a peak velocity amplitude in mm/s roughly equal to 0.3*N(-0.7), where N is the number of “events” (half-hour intervals in which a given peak ground motion is exceeded) observed per year. The Apollo data show endogenous seismic signals for a given recurrence rate that are typically about 10,000 times smaller in amplitude than a quiet site on Earth, although local thermally-induced moonquakes are much more common. Viking data masked for low-wind periods appear comparable with a quiet terrestrial site, whereas a Venera observation of microseisms suggests ground motion more similar to a more active terrestrial location. Recurrence rate plots from in-situ measurements provide a context for seismic instrumentation on future planetary missions, e.g. to guide formulation of data compression schemes. While even small geophones can discriminate terrestrial activity rates, observations with guidance accelerometers are typically too insensitive to provide meaningful constraints (i.e. a non-zero number of “events”) on actual ground motion observations unless operated for very long periods.

Influence of wind turbines on seismic stations in the upper rhine graben, SW Germany

By analysing long- and short-term seismological measurements at wind farms close to the town of Landau, SW Germany, we present new insights into ground motion signals from wind turbines (WTs) at local seismic stations. Because of their need to be located in similar regions with sparsely anthropogenic activities, wind turbines impact seismic stations and their recordings in a way that is not yet fully understood by researchers. To ensure the undisturbed recording tasks of a regional seismic array or a single station by a protected area around those endangered stations, it is very important to investigate the behavior of WTs as a seismic source. For that reason, we calculate averaged one-hour long spectra of the power spectral density (PSD) before and after the installation of a new wind farm within the investigated area. These PSD are ordered according to the rotation speed. We observe a clear increase of the PSD level after the WT installation in a frequency range of 0.5 to 10 Hz up to a distance of 5.5 km away from the WT. By analysing seismic borehole data, we also observe a decrease of the PSD of wind dependent signals with depth. The impact of wind-dependent signals is found to be much more pronounced for the shallower station (150 m depth) than for the deeper one (305 m depth). Using short-term profile measurements, we fit a power-law decay proportional to 1/r b to the main WT-induced PSD peaks and differentiate between near-field and far-field effects of ground motions. For low frequencies in the range from 1 to 4 Hz, we determine a b value of 0.78 to 0.85 for the far field, which is consistent with surface waves. The b value increases (up to 1.59) with increasing frequencies (up to 5.5 Hz), which is obviously due to attenuating effects like scattering or anelasticity. These results give a better understanding of the seismic wavefield interactions between wind turbines (or wind farms) with nearby seismic stations, including borehole installations, in a sedimentary setting.

The Ruin of the Roman Temple of Kedesh, Israel; Example of a Precariously Balanced Archaeological Structure Used as a Seismoscope

In certain regions and under favorable geologic conditions, precariously balanced rocks may form. These types of unusual formations have been used to estimate yield ground motions. Because such balanced rocks have not been ‘unbalanced’, they can be used as a rough estimate for ground motions which have not been reached or exceeded since the balanced formation achieved its contemporary state. We hypothesize that other ancient manmade structures, delicate in terms of stability and particularly those that have survived earthquake ground motions intact, can be used in the same manner. We therefore suggest that these structures act as a highly local seismoscope for determining maximum upper ground motion bounds. We apply the concept of the study of precariously balanced rocks to the ruin of the Roman temple of Kedesh, located in close proximity to a branch of the Dead Sea Transform Fault. The delicate-looking ruin was surveyed with a 3D laser scanner. Based on the point cloud from that survey, a discrete element model of the remaining temple wall was constructed. To test the stability of the model we used 54 analytical ground motion signals with frequencies ranging from 0.3 to 2 Hz and PGAs between 1 and 9 m/s 2 and simulated and measured strong ground motions of eight earthquakes. Two hypothetical local earthquake scenarios, five of which are historical earthquakes of the region and one is a strong motion record of the 1999 Taiwan Chi Chi earthquake were also used to test the hypothesis. None of the simulated earthquakes (historical or assumed) toppled the ruin; only the strong motion record collapsed the structure. The simulations reveal a surprisingly high stability of the ruin of the Roman temple of Kedesh mainly due to the small height to width ratio of the remaining walls. However, ground motion with large PGAs at a low frequency range in EW direction does collapse the remains of the temple.

The acceleration response spectra for legnica-glogow

Czasopismo Techniczne » 2017 » Volume 9 » The acceleration response spectra for Legnica-Glogow copper district A A A

A Novel Multitemporal InSAR Model for Joint Estimation of Deformation Rates and Orbital Errors

Orbital errors, characterized typically as longwavelength artifacts, commonly exist in interferometric synthetic aperture radar (InSAR) imagery as a result of inaccurate determination of the sensor state vector. Orbital errors degrade the precision of multitemporal InSAR products (i.e., ground deformation). Although research on orbital error reduction has been ongoing for nearly two decades and several algorithms for reducing the effect of the errors are already in existence, the errors cannot always be corrected efficiently and reliably. We propose a novel model that is able to jointly estimate deformation rates and orbital errors based on the different spatial-temporal characteristics of the two types of signals. The proposed model is able to isolate a long-wavelength ground motion signal from the orbital error even when the two types of signals exhibit similar spatial patterns. The proposed algorithm is efficient and requires no ground control points. In addition, the method is built upon wrapped phases of interferograms, eliminating the need of phase unwrapping. The performance of the proposed model is validated using both simulated and real data sets. The demo codes of the proposed model are also provided for reference.

Resource-efficient wireless sensor network architecture based on bio-mimicry of the mammalian auditory system

While wireless sensor networks have been successfully deployed on a variety of civil infrastructure systems for structural monitoring, past studies have shown that there is room for improvement in terms of network robustness and overall resource consumption efficiency. The mechanisms employed by biological nervous systems (e.g. signal modulation, communication, and integration) can be used as inspiration for overcoming the performance bottlenecks seen in existing wireless sensor nodes and networks. The mammalian auditory system is of particular interest due to its unique signal decomposition techniques (performed by the cochlea) that enable real-time processing of complex sound signals. In this article, a novel wireless sensor architecture based on the operational principles of cochlea is described. The performance of the proposed sensor is validated on a single-degree-of-freedom structure that is excited by seismic ground motion signals, thus demonstrating its real-time monitoring capabilities while maintaining high data compression rates.

Extraction of forward-directivity velocity pulses using S-Transform-based signal decomposition technique

Robust methods for time-frequency analysis of time series, which provide local information of signals, allow earthquake engineers to study both the input and output of dynamic time history analysis with more reliability. Moreover, time-frequency representations (TFRs) have a major role in the analysis of non-stationary seismic signals exhibiting significant time variation of frequency content. S-Transform (ST) is a modern TFR, which can measure local characteristics of a signal such as amplitude, frequency, and phase at any time instant. This paper presents a new method for decomposition of ground motion signals. A modified version of ST-based technique, originally employed to decompose signals of gearbox vibration, is introduced and applied to the extraction and characterization of pulse-like part of near-fault velocity records, which is contributed to the directivity effects. In addition, a new definition based on ST analysis is used to identify pulse period. The results of implementation of proposed procedure on a database of pulse-like ground motion recordings belonging to the different ranges of magnitude demonstrate the efficiency of proposed method compared with other available approaches. The results, also, indicate that simple approximation of distinct pulses using single-period waveforms, unlike the extracted pulses, cannot represent the impulsive nature of real records adequately.

Ground motion simulations for İzmir, Turkey: parameter uncertainty

In ground motion simulation studies based on earthquake rupture scenarios, the absolute ground motion level, frequency content, signal duration and distribution of simulated ground motion is highly dependent on the input parameters used in the calculations. We conduct a predictive study assessing the potential ground motions for Izmir, Turkey based on earthquake scenarios. We calculate ground motions from a reference scenario (Mw6.8) and compare it to 25 test scenarios for the Izmir fault in order to investigate the effect of input parameter uncertainty on the simulated ground motion. In this study, we use a hybrid broadband frequency (0.1–10 Hz) ground motion simulation technique. We find average ground motion levels in the central area of Izmir of more than 600 cm/s2 and 60 cm/s for peak ground acceleration and velocity, respectively, while the standard deviation is found to exceed 200 cm/s2 and 20 cm/s, respectively. The tested parameters identified to have the largest influence on the absolute ground motion level are seismic moment, average stress-drop, rise time and rupture velocity. Parameters identified to have the least effect on ground motion level are rake and ratio of stress-drop on asperities to background stress-drop. The low-frequency ground motion, critical in terms of damage to the building stock in Izmir, is mostly affected by the location of nucleation point, seismic moment, depth of the rupture area, rise time and the velocity model. It is, therefore, highly recommended that future studies focus on reducing the uncertainties in these input parameters.

Cost‐effective monitoring of ground motion related to earthquakes, landslides, or volcanic activity by joint use of a single‐frequency GPS and a MEMS accelerometer

AbstractReal‐time detection and precise estimation of strong ground motion are crucial for rapid assessment and early warning of geohazards such as earthquakes, landslides, and volcanic activity. This challenging task can be accomplished by combining GPS and accelerometer measurements because of their complementary capabilities to resolve broadband ground motion signals. However, for implementing an operational monitoring network of such joint measurement systems, cost‐effective techniques need to be developed and rigorously tested. We propose a new approach for joint processing of single‐frequency GPS and MEMS (microelectromechanical systems) accelerometer data in real time. To demonstrate the performance of our method, we describe results from outdoor experiments under controlled conditions. For validation, we analyzed dual‐frequency GPS data and images recorded by a video camera. The results of the different sensors agree very well, suggesting that real‐time broadband information of ground motion can be provided by using single‐frequency GPS and MEMS accelerometers.

Observation of Core Phase ScS from the Mw 9.0 Tohoku-Oki Earthquake with High-Rate GPS

High-rate Global Positioning Systems (GPS) observations can record ground motions from moderate to strong earthquakes at distances of a few kilometers up to thousands of kilometers (Larson et al., 2003; Bock et al., 2004; Ohta et al., 2006;Wang et al., 2007; Davis and Smalley, 2009; Delouis et al., 2010; Shi et al., 2010; Yue and Lay, 2011). These observations detect strong signals such as S wave and surface waves (Kouba, 2003; Larson et al., 2003; Irwan et al., 2004; Ohta et al., 2006;Wang et al., 2007; Davis and Smalley, 2009; Shi et al., 2010), as well as relatively weaker seismic phases such as P waves (Avallone et al., 2011). Seismic phases arriving later than surface waves have been rarely reported. Although it has been confirmed that arbitrarily large seismic signals are recorded with high-rate GPS (Bock et al., 2004), we assess here the lower limit of signals from earthquakes that can be recovered from high-rate GPS records. Benefits of exploiting high-rate GPS in earthquake source studies include the ability to detect arbitrarily large dynamic ground motions that do not clip in the presence of strong ground motion and accurate recording of ground displacements without needing to doubly integrate acceleration records of strong-motion seismometers (Graizer, 2010). As a result, high-rate GPS records are now routinely used in studies of earthquake source parameters and rupture process independently of, or jointly with, seismological observations (Miyazaki et al., 2003; Ji et al., 2004; Bilich et al., 2008; Yokota et al., 2009; Avallone et al., 2011; Yue and Lay, 2011; Bock et al., 2011; Crowell et al., 2012). Though whole waveforms of high-rate GPS records have been employed in modeling earthquake source processes, it is not certain whether the wiggles following surface waves are true ground-motion signals or contamination from GPS signal propagation effects such as multipath or ionospheric distortion. Accordingly, very few phases following the arrival time of surface waves have been confirmed on high-rate GPS records, primarily because of the inherently lower signal-to-noise ratio (SNR). Identification and retrieval of the weaker secondary arrivals from high-rate GPS records would further confirm capability of GPS in recording ground motions, and thus lead to improved broadband seismograms via collated GPS and seismometers (Bock et al., 2011). Among the later arrivals, the seismic phase ScS is expected to be strong due to the complete reflection at the core–mantle boundary between the solid mantle and the liquid outer core where shear waves disappear. Moreover, ScS is far behind surface waves at close distances (less than 20°) where contamination of the surface-wave coda is weak. Here, we present a record section of seismograms retrieved from high-rate GPS from the 2011 Tohoku earthquake wherein we observe a weak but coherent seismic phase that we associate with ScS. This inference is supported by comparison of the high-rate GPS records with seismic records and synthetic seismograms.

A distributed mass structural system for soil-structure-interaction and base isolation studies

A base isolation system placed within a structure for seismic protection will perform differently in the presence of soil-structure-interaction phenomena, as compared to the case where the structure is founded on competent soil and/or rock. This is so for two basic reasons: (a) there is filtering affecting the input ground motion signal at the base of the structure, and (b) the overall mechanical characteristics of the combined soil-structure system have changed as compared to the original structure resting on firm ground. Thus, a base isolation design has to account for soil-structure-interaction in order to have the system fine-tuned to the particular geological conditions and seismicity of the construction site in question. In this work, we introduce a distributed mass representation of the superstructure that has four possible dynamic response modes, namely flexure, shearing, torsion and axial vibrations. The foundation is treated as a rigid block, and the soil is represented by the equivalent spring-damper-virtual mass system, whereby these mechanical parameters may be frequency dependent. Typical base isolation systems used nowadays are lead rubber bearing designs whose mechanical behavior comprises a spring element, a damper and a hysteretic component. In terms of analysis, a substructuring methodology is employed that is cast in the frequency domain, with conditions of equilibrium and compatibility enforced at the common structure-foundation-soil boundaries. This approach is both efficient and adequate for investigating soil-structure-interaction effects, but cannot handle the hysteretic behavior of the base isolator, which is better captured by using time-stepping algorithms. In closing, some comments are made regarding possible ways for incorporating the base isolator in the present soil-structural system analysis, along with some preliminary results.

Corrections of stratified tropospheric delays in SAR interferometry: Validation with global atmospheric models

The main limiting factor on the accuracy of Interferometric SAR measurements (InSAR) comes from phase propagation delays through the troposphere. The delay can be divided into a stratified component, which correlates with the topography and often dominates the tropospheric signal, and a turbulent component. We use Global Atmospheric Models (GAM) to estimate the stratified phase delay and delay-elevation ratio at epochs of SAR acquisitions, and compare them to observed phase delay derived from SAR interferograms. Three test areas are selected with different geographic and climatic environments and with large SAR archive available. The Lake Mead, Nevada, USA is covered by 79 ERS1/2 and ENVISAT acquisitions, the Haiyuan Fault area, Gansu, China, by 24 ERS1/2 acquisitions, and the Afar region, Republic of Djibouti, by 91 Radarsat acquisitions. The hydrostatic and wet stratified delays are computed from GAM as a function of atmospheric pressure P, temperature T, and water vapor partial pressure e vertical profiles. The hydrostatic delay, which depends on ratio P/ T, varies significantly at low elevation and cannot be neglected. The wet component of the delay depends mostly on the near surface specific humidity. GAM predicted delay-elevation ratios are in good agreement with the ratios derived from InSAR data away from deforming zones. Both estimations of the delay-elevation ratio can thus be used to perform a first order correction of the observed interferometric phase to retrieve a ground motion signal of low amplitude. We also demonstrate that aliasing of daily and seasonal variations in the stratified delay due to uneven sampling of SAR data significantly bias InSAR data stacks or time series produced after temporal smoothing. In all three test cases, the InSAR data stacks or smoothed time series present a residual stratified delay of the order of the expected deformation signal. In all cases, correcting interferograms from the stratified delay removes all these biases. We quantify the standard error associated with the correction of the stratified atmospheric delay. It varies from one site to another depending on the prevailing atmospheric conditions, but remains bounded by the standard deviation of the daily fluctuations of the stratified delay around the seasonal average. Finally we suggest that the phase delay correction can potentially be improved by introducing a non-linear dependence to the elevation derived from GAM.

Bayesian Learning Using Automatic Relevance Determination Prior with an Application to Earthquake Early Warning

A novel method of Bayesian learning with automatic relevance determination prior is presented that provides a powerful approach to problems of classification based on data features, for example, classifying soil liquefaction potential based on soil and seismic shaking parameters, automatically classifying the damage states of a structure after severe loading based on features of its dynamic response, and real-time classification of earthquakes based on seismic signals. After introduction of the theory, the method is illustrated by applying it to an earthquake record dataset from nine earthquakes to build an efficient real-time algorithm for near-source versus far-source classification of incoming seismic ground motion signals. This classification is needed in the development of early warning systems for large earthquakes. It is shown that the proposed methodology is promising since it provides a classifier with higher correct classification rates and better generalization performance than a previous Bayesian learning method with a fixed prior distribution that was applied to the same classification problem.

Processing of strong-motion accelerograms: needs, options and consequences

Recordings from strong-motion accelerographs are of fundamental importance in earthquake engineering, forming the basis for all characterizations of ground shaking employed for seismic design. The recordings, particularly those from analog instruments, invariably contain noise that can mask and distort the ground-motion signal at both high and low frequencies. For any application of recorded accelerograms in engineering seismology or earthquake engineering, it is important to identify the presence of this noise in the digitized time-history and its influence on the parameters that are to be derived from the records. If the parameters of interest are affected by noise then appropriate processing needs to be applied to the records, although it must be accepted from the outset that it is generally not possible to recover the actual ground motion over a wide range of frequencies. There are many schemes available for processing strong-motion data and it is important to be aware of the merits and pitfalls associated with each option. Equally important is to appreciate the effects of the procedures on the records in order to avoid errors in the interpretation and use of the results. Options for processing strong-motion accelerograms are presented, discussed and evaluated from the perspective of engineering application.

Application of the Empirical Mode Decomposition-Hilbert Spectrum Method to Identify Near-Fault Ground-Motion Characteristics and Structural Responses

In this article, the empirical mode decomposition method combined with the Hilbert spectrum method (EMD + HHT) is used to analyze the free-field ground motion and to estimate the global structural property of building and bridge structure through the measurement of seismic response data. The EMD + HHT method provides a powerful tool for signal processing to identify nonlinear and nonstationary data. Based on the decomposed ground-motion signal, the absolute input energy of each decomposed wave was studied (the fling step [pulselike wave] can be separated from the recorded near-fault ground motion). Through application of the EMD + HHT method to building and bridge seismic response data, the time-varying system natural frequency and damping ratio can also be estimated. Damage identification from seismic response data of buildings and bridges, particularly from the Chi-Chi earthquake data, is also described. Manuscript received 31 July 2000.

Ground-motion Response Spectra in Eastern North America for Different Critical Damping Values

National seismic hazard maps in Canada and the United States generally provide input ground motions in the form of 2%/50-year response spectra for an assumed 5% of critical damping. This paper presents a practical method to modify 5%-damped response spectra for sites in eastern North America (ENA) to provide response spectra for damping values other than 5%, based on analysis of typical ENA earthquake ground-motion signals over a range of magnitudes and distances.

Tides, earthquakes and ground noise as seen by theabsolute gravimeter FG5 and its superspring;comparison with a superconducting gravimeter and abroadband seismometer

Results are presented of a comparison between different instruments (an absolute gravimeter FG5, asuperconducting gravimeter C026 and a broadband seismometer STS-2) which have been operated in parallel at the same site in Strasbourg (France). Thanks to a fast sampling technique (20 Hz), we first present the position and coil output signals from the superspring of the FG5, which acts as a long-period seismograph, and compare it with the ground-motion signal directly observed with the seismometer STS-2. The effect on the absolute gravimeter (AG) measurements of a large earthquake (Peru, M = 8.1) in June 2001 is also shown. We finally investigate how well Earth tides are retrieved on both the absolute and the superconducting gravimeters and give a comparison in the spectral domain of their respective noise levels.

Functional series TARMA modelling and simulation of earthquake ground motion

AbstractThe non‐stationary Functional Series time‐dependent autoregressive moving average (TARMA) modelling and simulation of earthquake ground motion is considered. Full Functional Series TARMA models, capable of modelling both resonances and antiresonances, are examined for the first time via a novel mixed parametric/non‐parametric estimation scheme, and critical comparisons with pure TAR and recursive ARMA (RARMA)‐recursive maximum likelihood (RML) adaptive filtering type modelling are made. The study is based upon two California ground motion signals: a 1979 El Centro accelerogram and a 1994 Pacoima Dam accelerogram. A systematic analysis, employing various functional subspaces and model orders, leads to two Haar function based models: a TARMA(2,4)8 model for the El Centro case and a TARMA(6,2)10 model for the Pacoima Dam case. Both models are formally validated and their simulation (synthesis) capabilities are demonstrated via Monte Carlo experiments focusing on important time domain signal characteristics. The Functional Series TAR/TARMA models are shown to achieve parsimony, as well as superior accuracy and simulation capabilities, over their RARMA counterparts. Copyright © 2001 John Wiley & Sons Ltd.