Magnetic field measurement has a wide range of applications in many fields such as safety production, disaster prevention and mitigation, and geological exploration. Aiming at the problems of low sensitivity and temperature cross-sensitivity of fiber optic magnetic field sensors, a magnetic field sensor based on flaky Terfenol-D material and dual fiber Bragg grating is proposed. First, the sensor model is established using SolidWorks, and the strain transfer theory is analyzed. Second, the flaky Terfenol-D material is prestressed to optimize the performance of the sensor. Finally, the sensor is developed, and a magnetic field test system is built for performance testing. Experiments show that the magnetic field sensitivity of the sensor is 53.44 pm/mT, the resolution is 37.4 μT, and the temperature sensitivity is 0.23 pm/°C under an optimal prestress condition of 3.5 MPa, and the directivity is in line with the cosine law. The temperature decoupling method of dual fiber differential is used to compensate the temperature of the sensor and correct the magnetic field measurement results, which effectively suppresses the temperature interference and improves the accuracy of the magnetic field measurement. The research results are expected to be applied to magnetic field measurements in harsh environments such as complex electromagnetic interference.

Reliably determining the burial depth of the upper breakpoint is a critical challenge in detecting buried faults. Currently, reflection seismic surveys are the primary method employed for buried fault detection in Quaternary-covered areas. However, buried faults in such regions are typically shallow and small-scale. Conventional surface reflection seismic exploration is often severely affected by strong surface waves and the influence of loose Quaternary sediments near shot points, resulting in weak effective wave signals and making it difficult to extract reflection information from shallow blind zones. This ultimately leads to unreliable determination of the upper breakpoint position. The mainstream method currently used to determine this location relies on drilling cross-fault profiles. However, even when drilling profiles are conducted across seismically identified breakpoints, horizon calibration of reflection events in time sections still involves considerable uncertainty, which can potentially lead to erroneous judgments regarding the fault’s most recent period of activity. Therefore, improving the accuracy of upper breakpoint depth determination and horizon calibration is an urgent issue that needs to be addressed. To tackle these two key technical challenges, this study utilizes shallow-hole Vertical Seismic Profiling (VSP) technology closely integrated with shallow reflection seismic surveys. By refining the data acquisition methods for shallow-hole VSP, improving data processing techniques, and combining surface seismic data processing methods with VSP data processing methods, we propose a fundamental workflow for integrated surface-borehole VSP data processing. The shallow-hole VSP technique achieved excellent detection results in three aspects at the Yinchuan Xinqushao and Shizuishan Luhuatai buried faults: high-precision velocity measurement, time-section calibration, and VSP-CDP stacked imaging. The combined use of shallow-hole VSP and shallow reflection seismic surveys for detecting the burial depth of the upper breakpoint of buried faults yielded very good results at the Shizuishan Luhuatai buried fault. In addition to reliably determining the upper breakpoint depth, the detailed shallow structure near the fault zone was also clearly visible. The integration of shallow-hole VSP technology and surface reflection seismic technology promises to become a new technical method for determining the burial depth of the upper breakpoint and imaging the fine structure of buried faults.

The Shandong Seismic Network is a key component of the China Earthquake Networks Center and one of the most advanced regional seismic monitoring systems in the country. It comprises four complementary observational subnetworks: (1) a traditional broadband seismic network consisting of 124 stations installed on bedrock or in deep boreholes; (2) an earthquake early warning (EEW) strong-motion network with 238 strong-motion sensors deployed on bedrock or shallow soil; (3) an EEW micro-electro-mechanical systems (MEMS) network comprising approximately 1230 low-cost sensors mounted on building floors or walls; and (4) a seismic array of 77 broadband seismometers installed in shallow boreholes on stable ground. Together, these four subnetworks operate a total of 1669 instruments, providing multi-scale observational data that are critical for detailed characterization of source rupture processes during moderate-to-strong earthquakes. In this study, we analyze the MW 5.5 Pingyuan earthquake that struck Shandong Province on August 6, 2023 (Beijing Time, UTC+8) using data from this integrated network. Our results show that: the high-density MEMS network is sufficient for rapid post-event inversion of the rupture process, yet its inversion accuracy is somewhat limited; the strong-motion network enables stable and efficient rapid finite-fault inversion; and multi-source data fusion yields the most reliable post-earthquake source rupture model. These capabilities support quasi-real-time (within 30 min of the origin time), rapid, and refined imaging of earthquake rupture processes, offering critical guidance for emergency response and optimization of regional seismic networks.

The dispersion analysis of surface waves serves as an established methodology for deriving subsurface shear-wave velocity profiles. Surface waves, generated through the interaction of elastic body waves with free-surface boundaries, are conventionally excited by controlled impulsive sources yet also persistently exist within ambient vibration wavefields. This study presents a comparative analysis of Rayleigh-wave dispersion characteristics derived from ambient vibration sources using both cross-correlation techniques and conventional surface-wave methodologies. The pivotal phase in both approaches involves the precision of dispersion-image computation, which fundamentally governs the reliability of extracted dispersion curves and consequently influences the accuracy of subsequent inversion outcomes. Our findings demonstrate that the cross-correlation method yields enhanced resolution in characterizing Rayleigh-wave dispersion patterns, attributable to its inherent reduced dependence on source-function characteristics.

Cross-like Hall devices are widely used in high precision Hall sensors because of their good symmetry， high sensitivity and low offset voltage. To optimize the performance parameters of Hall sensors， the influence of the aspect ratio （L/W） in interdigital area of the cross-like Hall device operating in voltage mode on device performance was investigated. The L/W range that can achieve optimal current-related sensitivity and signal-to-noise ratio （SNR） was determined by theoretical modeling calculation and three-dimensional TCAD simulation of the device. Based on the standard 0.18 μm CMOS technology， the device was fabricated and tested.The test results show that the current-related sensitivity of Hall devices in voltage mode improves rapidly with the increase of L/W， and the increase trend becomes slow and tends to saturation when L/W≥1.0， while the best SNR can be obtained when L/W is in the range of 0.5-1.0. It is found that the Hall device performs optimally when L/W is 1.0， with a current-related sensitivity of 47.60 V/（A·T） and an output thermal noise voltage of only 5.02 μV， achieving high sensitivity and high SNR simultaneously.

The measurement of low frequency vibration signals is of great significance in seismic monitoring, health monitoring of large and medium-sized engineering structures, resource exploration, etc. A cross spring leaf-based novel FBG accelerometer was designed against the problem that it's hard for FBG acceleration sensors to effectively pick up low frequency vibration signals. Firstly, the vibration model of acceleration sensor was built and its operating principle was analyzed; secondly, the effect of structural parameters of sensor on their sensitivity and natural frequency was analyzed, and the sensor was subjected to static stress analysis and dynamic characteristics analysis through the ANSYS simulation software; finally, the sensors were subjected to performance tests with a low frequency vibration test system. Experimental results suggested that the natural frequency of FBG acceleration sensor was 63.65 Hz, it gives a flat sensitivity response in the low frequency band of 0.1-40 Hz; its sensitivity was not lower than 2000 pm/g, and the transverse interference was not higher than 1.99%; moreover, it offered favorable self-temperature compensation. Such FBG acceleration sensors with high sensitivity response at low frequencies provide important reference for the design of like sensors.

High-precision and high-sensitivity vibration acceleration sensors have been a research hotspot in engineering technology, which play an important role in engineering structural health monitoring, earthquakes, tsunamis, and geological exploration. A novel, to the best of our knowledge, fiber Bragg grating (FBG) acceleration sensor incorporating a mass block and flexible hinge was proposed against the low sensitivity and poor transverse interference resistance of existing FBG acceleration sensors. The FBG accelerometer with the multi-stage flexible hinge was modeled and theoretically analyzed, the structural parameters of the sensor were optimized and actual sensors were developed, and a sensor performance test experiment was carried out in the end. The result suggested that the sensor's natural frequency was as high as 1400 Hz, and its response was flat in the frequency range of 50-800 Hz; its sensitivity was 18.4 pm/g, linearity R 2 was 0.9983, and transverse interference immunity was below 3.2%. The research findings offered a new way of thinking about high-precision and high-sensitivity vibration measurement in engineering technology.

Geomagnetism, similar to other areas of geophysics, is an observation-based science. Data agreement between comparative geomagnetic vector observations is one of the most important evaluation criteria for high-quality geomagnetic data. The main influencing factors affecting the agreement between comparative observational data are the attitude angle, scale factor, long-term time drift, and temperature. In this paper, we propose a method based on a genetic algorithm and linear regression to correct for these effects and use the distribution pattern of points in Bland–Altman plots with a 95% confidence interval length to qualitatively and quantitatively evaluate the agreement between the comparative observational data. In Bland–Altman plots with better agreement, that is, with the corrected data, more than 95% of the points are distributed within the 95% confidence interval and there is no obvious pattern in the distribution of the points. Meanwhile, the length of 95% confidence interval decreased significantly after the correction. The method presented here has positive effects on the vector instrumentation detection and would enhance the robustness of geomagnetic observatory by bringing the data quality of the backup variometer data in line with the primary variometer. Graphical Abstract

A monolithic integrated front-end CMOS Hall sensor microsystem working at the current mode is presented for linear magnetic field measurement. The geometry of the cross-shaped Hall plates is optimized to enable the best tradeoff between current sensitivity and signal-to-noise ratio (SNR) by theoretical modeling. Furthermore, a novel current-mode four-phase spinning current method combined with the correlated double sampling demodulation technique is proposed to amplify the weak Hall current signals and to cancel the high offset and noise. Fabricated using a standard 0.18- $\mu \text{m}$ low-voltage CMOS technology, it is experimentally demonstrated that a maximum current sensitivity of 6.86%/T and an optimal SNR are achieved when the cross length-to-width ( $L/W)$ ratio of the Hall plate is about 0.4. At a supply voltage of 3.3 V, the linearity of the Hall sensor microsystem is up to 99.9% in the magnetic field range within ±200 mT. The magnetic field resolution is as low as 100 $\mu \text{T}$ , the residual offset is less than $52~\mu \text{T}$ , and the power consumption is about 15.4 mW.

An integrated front-end vertical CMOS Hall magnetic sensor is proposed for the in-plane magnetic field measurement. To improve the magnetic sensitivity and to obtain low offset, a fully symmetric vertical Hall device (FSVHD) has been optimized with a minimum size design. A new four-phase spinning current modulation associated with a correlated double sampling (CDS) demodulation technique has been further applied to compensate for the offset and also to provide a linear Hall output voltage. The vertical Hall sensor chip has been manufactured in a 0.18 μm low-voltage CMOS technology and it occupies an area of 1.54 mm2. The experimental results show in the magnetic field range from –200 to 200 mT, the entire vertical Hall sensor performs with the linearity of 99.9% and the system magnetic sensitivity of 1.22 V/T and the residual offset of 60 μT. Meanwhile, it consumes 4.5 mW at a 3.3 V supply voltage. The proposed vertical Hall sensor is very suitable for the low-cost system-on-chip (SOC) implementation of 2D or 3D magnetic microsystems.

In order to minimize interruptions to recording, geomagnetic observatories usually use a back-up instrument operating simultaneously with the primary instrument in order to obtain comparative observations. Based on the correction parameter calculation method established in the previous work, we focused on the effects of temperature and instrument drift on the comparative geomagnetic vector observations. The linear influence of temperature on the comparative data was shown to be variable. The relative temperature coefficient changed around the temperature inflection point and showed a V-type distribution in a scatter plot. This conclusion was verified in laboratory experiments. The long-term time drift between the comparative instruments exhibits a linear pattern, and the fitness of the correction model can be evaluated by the degree to which the residual distribution of the fitted straight line conforms to the normal distribution. However, the absolute value of the long-term time drift between variometers with the same type of probe is very small. Therefore, long-term time drift correction should be carried out with care. The associated analysis and conclusions have the potential to benefit data agreement correction of long-term comparative geomagnetic vector observations and comparative testing of the performance of vector instruments.

针对井下弱磁观测环境狭小,测量精度要求高,但方便实时上传数据,可实现自动测量等特点,设计并制作了一种适用于井下绝对观测的氦光泵磁力仪单片机的频率计。频率计基于Cortex-M3内核的ARM芯片,通过定时器的外部时钟模式进行定时计数,在中断函数中进行计算,得到信号频率。多次实验后,为进一步提高测量精度,使用32 MHz有源温补晶振为芯片提供主频信号,提高了主频精度,减少程序对CPU的资源占用率。实验结果表明:频率计精度较高,满足项目需求。系统误差稳定,在840.70 kHz—1.96 MHz的弱磁测量范围内,误差均为1 Hz,易结合误差原因通过软件补偿实现高精度测量。

Traditional fluxgate sensors used in geomagnetic field observations are large, costly, power-consuming and often limited in their use. Although the size of the micro-fluxgate sensors has been significantly reduced, their performance, including indicators such as accuracy and signal-to-noise, does not meet observational requirements. To address these problems, a new race-track type probe is designed based on a magnetic core made of a Co-based amorphous ribbon. The size of this single-component probe is only Φ10 mm × 30 mm. The signal processing circuit is also optimized. The whole size of the sensor integrated with probes and data acquisition module is Φ70 mm × 100 mm. Compared with traditional fluxgate and micro-fluxgate sensors, the designed sensor is compact and provides excellent performance equal to traditional fluxgate sensors with good linearity and RMS noise of less than 0.1 nT. From operational tests, the results are in good agreement with those from a standard fluxgate magnetometer. Being more suitable for modern dense deployment of geomagnetic observations, this small-size fluxgate sensor offers promising research applications at lower costs.

Suffering from structural deterioration and natural disasters, the resilience of civil structures in the face of extreme loadings inevitably drops, which may lead to catastrophic structural failure and presents great threats to public safety. Earthquake-induced extreme loading is one of the major reasons behind the structural failure of buildings. However, many buildings in earthquake-prone areas of China lack safety monitoring, and prevalent structural health monitoring systems are generally very expensive and complicated for extensive applications. To facilitate cost-effective building-safety monitoring, this study investigates a method using cost-effective MEMS accelerometers for buildings’ rapid after-earthquake assessment. First, a parameter analysis of a cost-effective MEMS sensor is conducted to confirm its suitability for building-safety monitoring. Second, different from the existing investigations that tend to use a simplified building model or small-scaled frame structure excited by strong motions in laboratories, this study selects an in-service public building located in a typical earthquake-prone area after an analysis of earthquake risk in China. The building is instrumented with the selected cost-effective MEMS accelerometers, characterized by a low noise level and the capability to capture low-frequency small-amplitude dynamic responses. Furthermore, a rapid after-earthquake assessment scheme is proposed, which systematically includes fast missing data reconstruction, displacement response estimation based on an acceleration response integral, and safety assessment based on the maximum displacement and maximum inter-story drift ratio. Finally, the proposed method is successfully applied to a building-safety assessment by using earthquake-induced building responses suffering from missing data. This study is conducive to the extensive engineering application of MEMS-based cost-effective building monitoring and rapid after-earthquake assessment.

In earthquake monitoring, an important aspect of the operational effect of earthquake intensity rapid reporting and earthquake early warning networks depends on the density and performance of the deployed seismic sensors. To improve the resolution of seismic sensors as much as possible while keeping costs low, in this article the use of multiple low-cost and low-resolution digital MEMS accelerometers is proposed to increase the resolution through the correlation average method. In addition, a cost-effective MEMS seismic sensor is developed. With ARM and Linux embedded computer technology, this instrument can cyclically store the continuous collected data on a built-in large-capacity SD card for approximately 12 months. With its real-time seismic data processing algorithm, this instrument is able to automatically identify seismic events and calculate ground motion parameters. Moreover, the instrument is easy to install in a variety of ground or building conditions. The results show that the RMS noise of the instrument is reduced from 0.096 cm/s2 with a single MEMS accelerometer to 0.034 cm/s2 in a bandwidth of 0.1–20 Hz by using the correlation average method of eight low-cost MEMS accelerometers. The dynamic range reaches more than 90 dB, the amplitude–frequency response of its input and output within −3 dB is DC −80 Hz, and the linearity is better than 0.47%. In the records from our instrument, earthquakes with magnitudes between M2.2 and M5.1 and distances from the epicenter shorter than 200 km have a relatively high SNR, and are more visible than they were prior to the joint averaging.

为解决用于高密度布设的低成本MEMS烈度计集成软、硬件资源有限,且难以嵌入较为复杂算法的这一问题,基于Matlab的仿真计算,通过讨论在不同特征函数、时窗长度和短窗位置下STA/LTA值的变化趋势、拾取效果和运算时间,以选取能提高算法灵敏性、改善地震事件拾取效果和提高算法计算效率的参数,并将改进的STA/LTA算法应用于实际地震数据处理.结果表明:不同的特征函数对事件拾取率、拾取时间偏差和算法运算时间影响不同;长短时窗长度相差越大,STA/LTA值的变化越明显;时窗越长,算法运算时间越长;短窗置后可以增大STA/LTA值的变化幅度、减少算法计算量,改善算法拾取时间.改进的STA/LTA算法拾取效果更好,计算效率更高,占用内存资源更小,更适用于集成资源有限的MEMS烈度计.

This paper introduces a current-mode low-offset and high-sensitivity full symmetric vertical Hall device (FSVHD). The effect of device geometry structure and contact size on sensitivity and offset was studied by TCAD simulation. Based on current-mode, the structure of FSVHD was optimized to achieve both high sensitivity and low offset in 0.18-μm standard CMOS technology. TCAD simulation reveals that the sensitivity in the current-mode is twice larger than that in the voltage-mode. Further, the current-mode sensitivity is increased from 1.8% T -1 to 2.4% T -1 and the offset is reduced by an order of magnitude by optimizing the structural parameters.

Total harmonic distortion （THD） and intermodulation distortion （IMD） characteris-tics are two important nonlinear parameters of seismic data recorders. Input signal mode and peak value of sine-wave can affect the test results of these two characteristics. In order to deter-mine these effects, the basic principles on THD and IMD were introduced in this paper, and then test methods, data processing methods and effect analyses on THD and IMD were fully presented. Finally, some different kinds of sine-waves were input into the seismic data recorder to test THD and IMD. The test results show that the two signals with the same peak value but different input-mode have great impact on THD, and those with the same frequency but different peak value of sine-wave have great impact on IMD. However, signal frequency variation has no impact on THD and IMD. The research in this paper is of great value for quality test of seismic data recorder, which can be applied to test THD and IMD of seismic data recorders.

Earthquake precursor data have been used as an important basis for earthquake prediction. In this study, a recurrent neural network (RNN) architecture with long short-term memory (LSTM) units is utilized to develop a predictive model for normal data. Furthermore, the prediction errors from the predictive models are used to indicate normal or abnormal behavior. An additional advantage of using the LSTM networks is that the earthquake precursor data can be directly fed into the network without any elaborate preprocessing as required by other approaches. Furthermore, no prior information on abnormal data is needed by these networks as they are trained only using normal data. Experiments using three groups of real data were conducted to compare the anomaly detection results of the proposed method with those of manual recognition. The comparison results indicated that the proposed LSTM network achieves promising results and is viable for detecting anomalies in earthquake precursor data.

A novel Hall sensor microsystem working in the current mode is presented. The current-mode four-phase current spinning technique is applied to modulate the polarity of the Hall current and the offset current. Further, the use of a current integrating amplifier and a correlated double sampling demodulator performs twice offset-cancellation operations and then demodulates the Hall signal to the low frequency. Designed by 0.18-μm CMOS technology, the simulation results show that the Hall sensor obtains a low residual offset less than 88 μT and high linearity up to 99.9% in the magnetic fields ranging from 5 to 155 mT.