21 results about "Seismometer" patented technology

The present disclosure relates to a seismograph, which includes: a crystal oscillator for generating a local clock signal; a data acquisition unit, coupled to the crystal oscillator and configured to acquire sampled data based on the local clock signal, and the data acquisition unit is further configured to acquire a fixed amount of sampled data within each period of the clock signal; a reference clock receiver for receiving a reference clock signal; and a controller, which is coupled to the data acquisition unit and the reference clock receiver and processes the sampled data. In addition, the present disclosure also relates to a method for managing sampled data of a seismograph, a controller, a non-transitory machine-readable storage medium, and a program product.

An earthquake detection method is disclosed. The method comprises the following steps: receiving a first signal and at least a second signal, wherein the first signal is triggered in response to a first vibration state of a main detection site, and the at least a second signal is triggered in response to at least a second vibration state of at least a backup detection site; determining whether a quantity of those being enabled among the at least a second signal satisfies a quantity ratio condition, and determining whether the first signal and the quantity of the at least a second signal are both enabled at a specific time point, wherein the first and the quantity of the at least a second signals respectively have a first and at least a second initial enabled time points; and determining there is a real earthquake event when an interval between the first and the at least a second signal satisfies a time relationship.

This application provides a seismic data acquisition method and apparatus. The method includes: acquiring and storing raw seismic data of a selected area in the field using pre-deployed nodal seismometers; transmitting the raw seismic data to an indoor private cloud platform at preset sampling intervals using the nodal seismometers until sampling is complete; after the nodal seismometers are retrieved, retrieving the raw seismic data stored in the nodal seismometers via a 5G private network; sorting the raw seismic data in the nodal seismometers and the raw seismic data in the private cloud platform to obtain target seismic data, and removing all the raw seismic data; and saving the target seismic data in the private cloud platform. This enables remote operation and automation of the nodal seismometers, thereby improving the efficiency of parameter configuration and data copying and retrieval, reducing the degree of manual intervention, and enhancing the level of automation.

The present disclosure relates to the field of geophysical exploration technology, and discloses a quality control method and system for shotpoint excitation. The method is applied to a quality control analysis module and comprises: for each target shotpoint in a to-be-tested region, in response to an excitation module of an excitation assembly being excited at the target shotpoint position, real-time receiving optical fiber seismic data from a seismic data processing module, wherein the to-be-tested region has at least one target shotpoint, and the to-be-tested region has seismic instruments being collected; comparing whether the quality control result of the optical fiber seismic data meets the expected requirement to determine whether the excitation quality of the shotpoint meets the requirement; and in response to the excitation quality of the shotpoint meeting the requirement, determining that the excitation of the target shotpoint is effective. The method can solve the problem that the current seismic instruments cannot perform real-time quality control on the excitation state of the shotpoint, and improve the excitation production efficiency and quality of geophysical exploration.

This invention provides a method, device, and medium for automatic identification and detection of extended power supplies for nodal seismographs, belonging to the field of seismic exploration. The method includes: confirming good contact at the extended power supply interface; obtaining the remaining capacity of the extended power supply; using a step-up / step-down DC-DC circuit to boost the output voltage of the extended power supply; and judging the connection status of the extended power supply in real time. This invention can quickly complete the automatic identification and detection of extended power supplies, effectively improve the success rate of assembly, ensure the reliability of the extended power supply, reduce the risk of rework due to operational errors, and improve construction efficiency.

The application discloses a seismic exploration data collection method for a power system, comprising the following steps: acquiring data information of a target power system; determining a survey line direction and arranging a seismic source; arranging two same geophones in a set range on both sides of the seismic source along the survey line direction; connecting a geophone signal output end to a seismic instrument input end; performing a seismic exploration operation; and completing collection of seismic exploration data of a target power system. The application further discloses a system for implementing the seismic exploration data collection method for the power system. The application not only realizes collection of seismic exploration data for the power system, but also has higher reliability and better accuracy in the data collection process.

The present application relates to the technical field of underground structure detection, and discloses a background noise empirical Green function interpolation method based on a conditional diffusion model, which comprises the following steps: collecting empirical Green function signals between station pairs formed by all seismographs in a target area and position coordinates of all seismographs as a training data set; inputting the empirical Green function signal containing noise, position coordinates of two seismographs in a station and a current denoising step number into a denoising neural network; taking the original empirical Green function signal in the training data set as a training target, inputting corresponding position coordinates of any two target points without seismographs into the trained denoising neural network, and generating an interpolated empirical Green function signal between the two target points. The method is more accurate than a traditional empirical Green function signal interpolation algorithm, can replace real observation data to a certain extent in a scenario where the number of seismographs is insufficient, and improves the underground structure detection capability.

This application provides a data acquisition method, a self-contained seismograph, equipment, and medium for a self-contained seismograph, relating to the field of earthquake monitoring technology. The method, by integrating a low-energy-consumption first sensor and a high-precision second sensor into the self-contained seismograph, employs a method where the first sensor continuously acquires initial vibration signals and compares them with a preset vibration signal threshold to determine the presence of abnormal events. Only when an abnormal event is detected is the power module activated to supply power to the second sensor to acquire target earthquake data. Power is then deactivated after acquisition. This approach ensures continuous data acquisition using the low-energy-consumption first sensor when no abnormal events are detected, reducing overall energy consumption, extending equipment runtime, and lowering monitoring costs and maintenance workload. Simultaneously, it enables timely activation of the high-precision second sensor to acquire accurate target earthquake data when an abnormal event is detected, providing a reliable basis for subsequent earthquake analysis and improving the accuracy and effectiveness of earthquake monitoring.

This invention belongs to the field of vibration testing and isolation technology, and relates to a non-contact seismograph-based active-passive combined vibration isolation testing system and method. The system includes active and passive isolation platforms, connecting brackets mounted on the active and passive combined isolation platforms, a laser Doppler vibrometer, and multiple vibration acceleration sensors and acquisition systems mounted on the isolation platforms and the laser Doppler vibrometer. This invention combines the laser Doppler vibrometer with the active-passive combined isolation platform to ensure high-precision acquisition of target vibration signals even in environments with external interference. By synchronously acquiring vibration data from the laser Doppler vibrometer and acceleration sensor signals, and performing comparative analysis, the performance of the isolation system can be accurately verified and evaluated. This invention also incorporates various flexibly combinable and controllable excitation devices to simulate the actual working state of the isolation system under different external loads and excitation positions, thereby comprehensively evaluating the performance of the isolation system under different operating conditions.

This invention belongs to the field of seismic image signal processing, and provides a method and related apparatus for digitizing short-period seismograph observation maps. The method includes: removing noise from scanned short-period seismograph observation map images to obtain denoised images; using a correction formula based on the length of the recording pen, correcting for arc distortion in the denoised images to obtain arc-distortion-corrected images; since the images also have tilt distortion, based on the working principle of short-period seismographs, deriving an inherent displacement formula for the recording pen, and using this formula to correct for tilt distortion in the arc-distortion-corrected images to obtain distortion-free seismic waveform images; and digitizing the distortion-free seismic waveform images. This application solves the problem mentioned in the background art that previous solutions only completed the electronic scanning and storage of simulated seismic observation maps, without realizing the digitization of the electronic image waveforms, by performing image preprocessing and digitization processing on simulated seismic observation maps.

The application provides a seismic visual early warning method combining monocular depth estimation and an optical flow method. The method realizes inversion of ground acceleration at a base of a street lamp type device by fusing monocular depth estimation and a robust optical flow algorithm suitable for a traffic scene, and can construct a distributed seismic monitoring network based on inversion data, solves the industry pain points of high deployment cost and insufficient coverage density of a traditional seismograph, and provides a high cost-effective solution for city-level earthquake early warning.

This application relates to the field of geophysical exploration technology, and in particular to a method and device for zero-time correction of air gun excitation based on underwater vibration recording. The method includes: real-time measurement of the geodetic coordinates of the floating platform and the underwater seismometer at the moment of air gun excitation, and calculation of the distance between the air gun and the reservoir bottom; determining the propagation path of the air gun excitation sound wave based on the sound wave velocity in the reservoir bottom medium and water, the distance between the air gun and the reservoir bottom, the geodetic coordinates of the floating platform and the underwater seismometer at the moment of air gun excitation; obtaining the initial vibration time of the reservoir bottom at the geodetic coordinates of the underwater seismometer location based on the recorded near-field vibration waveform; and calculating the initial vibration time of the reservoir bottom vertically below the air gun based on the distance between the air gun and the reservoir bottom, the propagation path of the air gun excitation sound wave, the sound wave velocity, and the initial vibration time of the reservoir bottom. This application helps to achieve high-precision zero-time correction of air gun excitation.

The present disclosure relates to an earthquake prediction network design that is formed by the coordinated operation of an IoT (I)-based radon measurement / prediction network, in which the radon concentrations in outdoor environments and / or in soil gas near active fault lines are continuously monitored from a central location and in which the next radon level can be automatically predicted before measurement by means of the prediction algorithms used, together with seismographs that measure ground movements, and that comprises an early warning system in which the authorities (Y) are automatically informed in cases where earthquake risk is detected.

1. Name of the product in this design: Integrated seismograph. 2. Purpose of this design: For earthquake sensing. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.

This invention discloses a fiber optic seismic record reconstruction method based on CVAE and detector constraints, belonging to the field of geophysical exploration and signal processing technology. It utilizes discretely distributed high-precision seismometers as anchor points to segment distributed acoustic wave sensing fiber optic acquisition data. A pre-trained reconstruction model, centered on a conditional variational autoencoder (CVAE), is constructed to obtain general mapping characteristics for converting fiber optic acquisition data to high-fidelity seismic detector acquisition data. The fiber optic acquisition data is preprocessed to align its modes with those of the seismic detector acquisition data. Each data segment and the seismic detector acquisition data at its two end anchor points are used as input constraints. Leveraging the continuous evolution characteristics of the CVAE latent space and combining real-time double-ended strong boundary constraints, a high-fidelity seismic record with high sampling density is output. This effectively solves the technical challenge of integrating high-density observation with high-quality processing systems, thereby improving exploration accuracy.

The utility model discloses a detection device of seismic instrument normal operation relates to seismic instrument detection technical field. The utility model discloses a rack and swing subassembly loaded on the rack, the rack includes the bottom plate, the guide rail board fixed in the bottom plate upper portion and the load plate through the sliding block assembly on the guide rail board upper edge, the swing subassembly includes the connecting rod fixed in the load plate edge intermediate position, swing arm fixed through the connecting piece and the connecting rod, the transmission disc of swing arm end portion rotation cooperation through the shaft piece and is used for the motor of transmission disc rotary drive. The utility model drives transmission disc swing arm and connecting rod interlock through the motor, makes the load plate produce periodic swing to simulate the vibration condition when the earthquake occurs, and this movement mode can be more real to restore the motion form of seismic wave, provides the test environment of close actual working condition for seismic instrument, and it is helpful to improve the accuracy and reliability of detection result.

This application relates to a method and system for monitoring unmanned aerial vehicles (UAVs) based on the Doppler effect of a seismograph. The method includes: acquiring ground vibration signals of the monitoring area collected by a seismograph, segmenting them, and then performing detrending, denoising, and filtering processing; performing time-frequency analysis on the processed vibration signals to obtain the corresponding time spectrum; extracting UAV signals from the time spectrum using an artificial intelligence algorithm and inputting them into a pre-trained deep learning model to output the time-frequency trajectory region of the UAV signals and their corresponding time range; performing dominant frequency tracking within the time-frequency trajectory region to obtain the instantaneous frequency sequence that changes with time, and extracting frequency offset information representing the Doppler effect of relative motion; constructing Doppler inversion constraints based on the frequency offset information, and obtaining estimation results of the UAV excitation frequency, flight speed, flight altitude, and spatial position through optimization; performing trajectory consistency constraints and anomaly removal on the estimation results, outputting the UAV monitoring results, and generating a monitoring report.