Using digital seismic waveform recorded by the Inner Mongolia seismic network from January 2008 to December 2017, the focal mechanisms of 138 ML≥2.5 earthquakes in eastern Inner Mongolia are calculated by P-wave initial motion and amplitude ratio (FOCMEC) method. The analysis of focal mechanism solution shows that the main source types in the study area are strike-slip with a certain proportion of thrust, while normal faults types are relatively few. The advantageous directions of P-axis and T-axis are NEE-SWW and NNW-SSE directions, respectively. The study area is divided into 1°×1°. The stress tensor and stress field images of the study area are obtained by damped stress inversion (MSATSI) method. The inversion results of stress field show that the stress state in eastern Inner Mongolia is mainly strike-slip, but shear and compression exist in some areas. The maximum principal stress square mainly distributes in NEE-SWW direction and rotates clockwise from north to south.

 The focal mechanism solutions of 19 ML≥2.5 earthquakes in Xunwu and its adjacent areas are inversed using the Snoke method and seismic waveform data since 2009, and the apparent stress of 89 ML≥2.5 earthquakes are calculated. The results show that strike-slip earthquakes are dominant in Xunwu and its adjacent areas, the dominant directions of P axis of focal mechanism solution are 310°~320°, 110°~130°, and the dip angles are mostly within 40°, which is consistent with the regional NWW-SEE horizontal compressional tectonic stress field. The focal mechanism solution of 8 ML≥2.5 earthquakes in Xunwu earthquake cluster area are in good agreement. The apparent stress is positively correlated with magnitude, and there is a high value fluctuation of apparent stress before the Xunwu ML3.8 earthquake group event on November 6, 2017.

We use the co-seismic rupture data for geological surveys of the 1923 MS7.3 Renda earthquake and the 1973 MS7.4 Luhuo earthquake to invert the historical earthquake rupture models based on elastic half-space dislocation model and least squares method. The co-seismic slip distribution of the Renda earthquake is considered as the disturbance source, and we calculate the co-seismic and post-seismic Coulomb stress changes on the fault plane using the PSGRN/PSCMP program. The results show that the maximum slip of the Renda earthquake is about 3.3 m, and the moment magnitude of the Renda earthquake is MW7.0. The maximum slip of the Luhuo earthquake is about 3.7 m, and the moment magnitude is MW7.3. The maximum slip of the two earthquakes are located at the shallow of 0~5 km, and the focal mechanisms are similar which are mainly left-lateral strike-slip. The Coulomb stress change at the epicenter of the Luhuo earthquake is about 29.79 kPa due to the co-seismic and post-seismic effect of the Renda earthquake, which reaches the triggering threshold of 10 kPa.

Based on the mobile gravity monitoring data of Shanxi region, we analyze multiple time-scale gravity time-variances caused by two Yuanping earthquakes(2009 and 2016). The results indicate that the evolution process of the gravity field variation(0.5 a time scale) of these two earthquakes is“minor change before earthquake → reverse change → earthquake occurred near zero isoline and high-gradient belts →post-earthquake adjustment.” Multiple time-scale gravity field variations show that the earthquakes occurred near 0 isoline and the magnitude of gravity change before the earthquakes is approximately 40 to 50 μGal.

In this study, we construct the correction model of OTL gravity in coastal area and islands based on the NAO99b global ocean tide model, NAO99Jb regional ocean tide model, data record in tide gauge, as well as the high spatial resolution land-sea boundary extracted from the SRTM digital terrain model. As an example, the correction model for Matzu island is introduced and validated by the absolute gravity observations. The results show that the correction model would be more accurate than before.

We use the ionospheric total electric content(TEC), geomagnetic activity index, day of year and other parameters of mid-and low-latitude in 2017 to establish an ionospheric TEC prediction model based on Elman neural network with the Bayesian regularization(BR-Elman). According to the variation characteristics of the geomagnetic activity index, we construct the ionosphere model under quiescent ionospheric conditions and disturbed ionospheric conditions, respectively. The experimental results show that root mean square error, residual error and correlation coefficient of the predicted value of 5 d using the proposed method in the quiet period are 1.19 TECu, 1.03 TECu, and 0.93, respectively. The root mean square error, the residual error and the correlation coefficient of predicted value of 5 d using the proposed method in the disturbed period are 1.34 TECu, 1.01 TECu, and 0.91, respectively. The minimum root mean square error is 1.87 TECu, the minimum residual is 1.50 TECu, and the optimal correlation coefficient is 0.87 by the BP neural network model with Bayesian regularization(BR-BP) and the traditional BP neural network model. The results show that predicted accuracy of the proposed method has improved significantly compared with the prediction effects of the other two models.

A weighted mean temperature model is established using the ERA-Interim data from 2014 to 2018 for the Japanese region. We analyze the errors of the Tm model and carry out seasonal corrections. The results show that: 1) A linear weighted mean temperature model suitable for the Japanese region is established, and accuracy is improved by about 16% compared with the Bevis model; 2) It is found that the residual time series of the linear model shows seasonal variations, so seasonal correction of the linear model is implemented.  The accuracy of the corrected model is improved by about 37% and 25% compared with the Bevis model and the linear model; 3) Comparing the three models with the integral Tm of sounding stations, the superiority of the seasonal corrected model is further illustrated.

This paper analyzes the application of the classical correction method and the least squares correction method in tidal monitoring from aspects of station environment and monitoring requirements. The results show that both methods can correct the error and improve the inversion precision, and that the two methods have different applicability. When the weather conditions are normal, the correction effect of the classic correction method is better, and the time resolution of the result is not changed substantially. The least square method is more suitable for special situations such as storm surge or tsunami. It is considered that when the effective azimuth of the sea area is small, the correction effect of both methods is reduced and the classical correction method is more affected.

 In this paper, empirical mode decomposition(EMD), ensemble empirical mode decomposition(EEMD) and complete ensemble empirical mode decomposition(CEEMD) are used to decompose the original baseline time series. The corresponding time series intrinsic mode function(IMF), correlation coefficients and periodic intensity are obtained, and the season components are determined. The decomposition method is optimized by comparing the superposition power spectrum of the season item with the original baseline time series. The results show that CEEMD method has the best effect on extracting and reconstructing season item of baseline time series.

In order to weaken the kinetic model anomaly when using Kalman filtering for PPP parameter estimation, we propose adaptively filtering with classified adaptive factors. According to the different reliability of PPP parameters to be evaluated, the state parameter vector is divided into two groups, namely position and others. Through three days observations from six IGS stations, the solutions of different Kalman filtering are obtained. The results show that the adaptive Kalman filter can accelerate the PPP convergence by adjusting the state prediction covariance by the adaptive factor. In the static modes, the average convergence time is reduced from 28.2 min to 19.4 min, the average accuracies are notably improved by 7%, 14% and 19%, which are 1.50 cm, 3.34 cm and 5.55 cm in the N,E and U directions. In the kinematic mode, the average accuracies are notably improved by 13%, 28%, and 43%, which are 2.7 cm, 3.6 cm, and 6.3 cm in the N, E and U directions.

Based on the integer property of double-difference ambiguity, we prove that the integer property of between-satellite single-difference(BSSD) ambiguities would be invoked once the basis ambiguities are successfully fixed. In order to select a group of independent BSSD ambiguities as a “complete” datum, the concept of ambiguity-continuity-arc is proposed, along with a strategy for selecting basis ambiguities. An experiment is carried out to validate the novel approach. The total number of basis ambiguities is about 2 times that achieved by the old method, resulting in the percentage of fixed BSSD ambiguities improved from about 60% to about 90%, after the basis ambiguities are fixed. The clock products obtained with the proposed approach are validated with rapid static precise point positioning. We show that the percentage of ambiguity-fixed solution is 96.00%, and the RMS in north, east and up directions are 7.3 mm, 9.8 mm and 23.3 mm, respectively.

We propose an integrated self-adaptive parameter selection scheme. Our method takes advantage of the fact that the kernel function order and the smoothing factor are in an optimal range, and the distribution of kernel function nodes should be in accordance with terrain characteristics. By combining the orthogonalization algorithm to select the nodes and the two-dimensional particle swarm algorithm to determine the optimal order and smoothing factor, we realize the fully self-adaptive selection of multiquadric function parameters. Two areas with different topographic relief are selected for GPS elevation fitting; the results show that accuracy and reliability of our method are both better than the traditional empirical parameter selection and partially self-adaptive parameter selection method.

In this study, we select one superconducting gravimeter(SG) at Lhasa station, two gPhone gravimeters at Enshi and Kunming stations, and the co-located STS-1 and STS-2.5 seismometers. Noise levels at the seismic frequency band of 0.1 to 100 mHz for these instruments are estimated, and noise levels of instruments at the same site are compared. Numerical results show that the noise level of the SG at Lhasa station is slightly higher than those of the co-located seismometers at the frequency band above 1 mHz, but lower than 1 mHz. The noise levels of gPhone gravimeters at Enshi and Kunming stations are higher than those of the co-located seismometers above 0.5 mHz, and similar at the frequency band of 0.1 to 0.5 mHz. The SNM(seismic noise magnitude) values calculated by two methods with and without bandpass filtering are compared. Results show that, the SNM values calculated with bandpass filtering are smaller and smoother.

To further study the reliability of borehole strain observations in source inversion and earth structure model studies, the co-seismic signals of the 2016 M7.8 earthquake in Indonesia, recorded by borehole strainmeter, are processed and the theoretical co-seismic strain data is calculated by QSSP software. Firstly, P wave phases are identified in the effective monitoring data, and their arrival times are analyzed. Then, the correlation between the observed data and theoretical ones is analyzed and the correlation coefficient is obtained. The result shows that the observed data is in good agreement with the theoretical data in the epicentral distance of 36°~52°. Therefore, the borehole strain observation data of the stations within the range of 36°~ 52° from the epicenter can be used for the source inversion and the verification of the new earth structure model with reliable results.

To obtain the relationship between M2 apparent tide factors and mechanical properties, we first use the Venedikow analysis method to calculate apparent M2 tide factors. Then, uniaxial compression test is carried out on the core of the observation layer of the borehole, and the mechanical parameters of the sample are obtained according to the stress-strain curve. We observe the effects between M2 apparent tide factors and the uniaxial compressive strength and elastic modulus. The results show that the elastic modulus of the borehole has obvious influence on M2 apparent tide factors, and with the increase of M2 apparent tide factors, the elastic modulus of rock decreases in inverse power function, and the two have a good correlation. The main factor of the mechanical properties of borehole leads to the great difference of M2 apparent tidal factors for body strainmeter.

Through wavelet decomposition, the typical events of the fixed-point deformation instruments of Kuancheng station are analyzed by atmospheric pressure interference. We obtain the characteristics of atmospheric pressure interference on different instruments in different frequency bands. We eliminate interference and achieve better results.

In order to meet the needs of calibration and verification during the calibration period of earthquake radon observatory, a portable miniature radon chamber is developed, combining decay law and the measuring principle of radon. This instrument can effectively overcome the supervision of standard radium sources and realize the quality control of earthquake radon measuring instrument. The calibration efficiency test is carried out according to the related technical requirements. The results show that the miniature radon chamber system can be applied to the calibration and response experiment of radon measuring instrument, serving earthquake monitoring, prediction and scientific research.

In this paper, piezoelectric-concrete beam electromechanical coupling models with different crack conditions are established using finite element software ABAQUS. The excitation signal is input by the piezoelectric actuator at the set position of concrete beam and the feedback signal is collected in real time. The stress wave signal value and wavelet packet energy value are calculated, and we explore the intrinsic relationship between the value and the damage conditions. The results show that the signal value of piezoelectric stress wave decreases with the increase of crack depth, under the condition with mid-span vertical crack and oblique crack. The signal value decreases when the crack width increases to 2~3 mm, but then the influence of the width increase is not obvious. When the depth of crack reaches the height of longitudinal center of beam in its evolution direction, the stress wave receiving signal is greatly attenuated. Using the relative energy value of the signal as the damage degree factor is beneficial to analyze the propagation and attenuation mechanism of stress wave inside the damaged concrete, and it is effective for detecting the damage degree of concrete crack.

In this paper, we design a novel corrosion sensor based on fiber Bragg grating (FBG). The sensor is mainly composed of a rust body, a stainless-steel body and a fiber with two FBGs connected in series. The FBG wound around the surface of the rust body monitors the corrosion strain of the steel bar, and the FBG wound around the surface of the stainless-steel body acts as a temperature compensator to eliminate the influence of temperature changes on the swell strain monitoring. To investigate the performance of the proposed corrosion sensor, an electrochemically accelerated corrosion experiment is carried out on concrete specimens of different strength grades. The experimental results show that the sensor sensitivity of the quality corrosion rate is 0.02%, and the monitoring range is over 1%. It can be demonstrated that the proposed sensor can monitor in real time the corrosion process and detect the characteristics of steel bars in concrete. The monitoring data can be employed to indicate durability loss due to steel corrosion in reinforced concrete structures. Therefore, the proposed corrosion sensor has a wide application prospect in the field of structural health monitoring.