1455results about "Detection using electromagnetic waves" patented technology

The invention relates to the field of measurement while drilling in drilling operation, in particular to a small-diameter resistivity while drilling measuring device which comprises a drill bit installed at the bottom of a drill rod, a main shaft rotationally arranged in the drill rod, hinged plates symmetrically arranged at the upper end of the drill rod, and an annular cavity formed in the drill rod. Annular frames with U-shaped sections are symmetrically arranged in the annular cavity in a sliding manner, a receiving end and a transmitting end are respectively mounted in the annular frames which correspond to each other up and down, and mounting units for limiting the transmitting end and the receiving end are arranged in the annular frames. The high-efficiency detection of measured objects with different depths and angles in a complex geological environment is realized, the vibration generated in the drilling process of the drill bit is effectively absorbed, the transmitting end and the receiving end are ensured to work in a stable environment, the measurement error caused by the vibration is avoided, and the detection precision and reliability are greatly improved.

The invention provides a deep high-precision underground disease detection method based on GPR, and relates to the technical field of geophysical exploration. Establishing a road disease forward model, and initializing the road disease forward model; obtaining an initialized road disease forward model and adding preset noise information into a result to generate fused echo data; preprocessing the fused echo data to generate target echo data; constructing a road disease data set according to the target echo data, and performing multi-frequency data fusion in the road disease data set to generate multi-frequency data; constructing a super-resolution convolutional neural network according to the multi-frequency data, and training the super-resolution convolutional neural network; inputting detection data into the trained super-resolution convolutional neural network model, and obtaining a detection report; and the road disease radar detection performance is improved.

The invention belongs to the technical field of data acquisition, and provides an underground pipeline detection data acquisition method and system, and the method comprises the following steps: collecting underground pipeline drawing data of a target region, and determining the information parameters of underground pipelines; performing field exploration, marking a ground outcrop point of the underground pipeline, and preliminarily judging the trend of the pipeline; detecting the underground pipeline through an electromagnetic method or a ground penetrating radar, and determining the position and the burial depth of the underground pipeline; reflected and scattered sound wave signals propagated through the internal fluid of the underground pipeline are collected through sound wave detection, and the state of the internal fluid is evaluated; fusing different detection data to generate an underground pipeline space model; by comprehensively using the electromagnetic method, the ground penetrating radar and the sound wave detection technology, the position, the burial depth and the internal fluid state information of the underground pipeline can be comprehensively collected, the physical position of the pipeline is determined, the state of the internal fluid of the pipeline is evaluated, and the accuracy and the reliability of the detection result are effectively improved.

The invention belongs to the technical field of liquid level monitoring, and relates to a liquid level monitoring method and system based on a radar liquid level meter. The current temperature of the stored substance in the target storage tank is matched with the dielectric constant, whether the dielectric constant is abnormal or not is judged accordingly, the influence of the temperature on the dielectric constant of the stored substance is considered, and errors caused by temperature changes when the radar liquid level meter monitors the liquid level are avoided; whether abnormal influence is generated on the monitoring process of the radar liquid level meter or not is evaluated from multiple dimensions through the key obstacles in the target storage tank, the limitation of single parameter analysis is broken through, measurement errors caused by obstacle abnormity can be reduced, and the stability of liquid level monitoring is ensured; whether foam interference or steam interference occurs or not when the radar liquid level meter monitors the liquid level is recognized through multiple verification modes, the accuracy of interference reason recognition is improved, the pertinence of maintenance measures is guaranteed, and the situation that the measurement precision of the radar liquid level meter is reduced due to abnormal medium characteristics is avoided.

The invention discloses a soil pollution accurate positioning method based on a geophysical exploration technology. The method comprises the following steps: S1, analyzing geologic features of a research area: analyzing the geologic features of the research area; s2, constructing a geological model; s3, measuring line arrangement and data acquisition; s4, data processing: obtaining a two-dimensional resistivity and polarizability image and an internal structure image of ground penetrating radar data by adopting least square inversion, training an anomalous body recognition model by utilizing a convolutional neural network, automatically recognizing anomalous body features in ERT and GPR data, and automatically screening out potential pollution areas; s5, data explanation: performing comprehensive analysis on inversion results of ERT and GPR, constructing an intelligent explanation model, automatically adjusting explanation parameters by the intelligent explanation model according to data features, and providing a plurality of explanation schemes; and S6, establishing a three-dimensional electrical structure model: establishing the three-dimensional electrical structure model of the research area by adopting a Kriging interpolation method according to the ERT inversion result and the earth surface coordinate data.

The invention discloses a low ionosphere intelligent inversion method based on VLF radio wave detection, and the method comprises the steps: collecting ground-based very-low-frequency wave amplitude data, defining a gated cycle unit network objective function as an optimized performance index, and employing a mean square error as the objective function; and carrying out dynamic position updating by adopting a whale optimization algorithm, setting a double-stop criterion, and stopping iterative training to obtain an optimal model when the maximum number of iterations or a verification error convergence threshold value is reached. The calculation result of the LWPC model is used as a training set, the GRU network is used as an objective function estimator from foundation very low frequency data to low ionosphere parameters, the inversion method can accurately approach a real model, and the algorithm performance is effective and feasible and is remarkably improved compared with an existing model.

The invention discloses a while-drilling electromagnetic wave advanced detection sensitivity analysis method, and belongs to the field of oil-gas exploration and development. The method comprises the following steps: constructing a while-drilling electromagnetic wave advanced detection model, quantifying the influence of different measurement parameters on advanced detection signals, then analyzing the response characteristics of the advanced detection signals, extracting key sensitivity factors, and defining a single-parameter sensitivity function and a multi-parameter coupling sensitivity function; the sensitivity of advanced detection signals is qualitatively and quantitatively analyzed from the four angles of the distance to the interface, the formation resistivity, the interlayer and the stratigraphic dip angle, so that the while-drilling electromagnetic wave advanced detection range is optimized, and the adaptability in the well logging process is enhanced. And meanwhile, the advanced detection second-order sensitivity is approximately solved by adopting a central difference formula, influence factors suffered by advanced detection signals are analyzed from a numerical angle, the interaction of multi-parameter coupling is analyzed, and a scientific basis is provided for electromagnetic wave logging while drilling accurate inversion and instrument design.

The cloth bag pile construction method comprises the following steps that S1, a circle of positioning ribs are welded to a reinforcement cage every several meters, and a circle of positioning ferrule is installed on the basis of the welded positioning ribs; s2, geotechnical cloth is adopted for first-layer wrapping from bottom to top, the bottom is fixed to a positioning ferrule in a winding and wrapping mode, and iron wires are used for binding every designated interval; s3, a PE plastic film is adopted for second-layer wrapping from bottom to top, and adhesive tape is used for fixing every specified interval; and S4, geotextile is adopted for second-layer wrapping from bottom to top, the bottom is fixed to the positioning ferrule in a winding wrapping mode, iron wires are used for binding every specified interval, the geotextile is longitudinally connected in a lap joint mode, longitudinal joints of the geotextile and longitudinal joints of the first-layer geotextile are staggered, and installation of the geomembrane bag is completed. According to the construction method, loss of slurry can be effectively reduced, the bearing capacity and stability of the cast-in-place pile are guaranteed, and the construction method can be well applied to construction of the cast-in-place pile containing the karst cave or the soil cave.

The invention provides a drill hole joint detection method and system capable of reducing the number of advance drill holes in a tunnel roadway, and relates to the field of roadway engineering detection, and the method comprises the steps: obtaining the depth of a measurement point and the radar data and transient electromagnetic data of a target region, and enabling the radar data and the transient electromagnetic data to be collected through an integrated detection device in a drill hole; performing feature extraction on the radar data and the transient electromagnetic data, and fusing the extracted features based on contribution weights of the radar and the transient electromagnetism to obtain a fused feature vector; based on the depth of the measuring point and the fused feature vector, utilizing the trained physical information neural network to invert the dielectric constant and the resistivity; according to the dielectric constant and the resistivity, the geological anomalous body of the target area is identified; according to the invention, the drilling radar and the drilling transient electromagnetism are combined, so that the number of advanced drilling holes is reduced, the detection cost is reduced, and the full-area coverage of the forepoling of the roadway is ensured.

The invention provides an underground ore body positioning identification method and system based on a ground penetrating radar, and relates to the technical field of ore body detection, and the method comprises the steps: inputting a corrected multi-dimensional point cloud feature set into a pre-trained closed-loop convolutional neural network, optimizing the network parameters through transfer learning, and obtaining a multi-dimensional point cloud feature set; outputting the category confidence and the spatial position probability distribution point cloud of the ore body target; on the basis of the spatial position probability distribution point cloud, generating ore body depth and horizontal positioning point cloud through a reverse projection algorithm in combination with an electromagnetic wave two-way travel time calculation rule and a Kanay resistivity measurement result; and performing multi-scale two-dimensional empirical mode decomposition on the reverse projection positioning point cloud, and filtering noise components to extract a high-confidence target point cloud. According to the invention, the accuracy and stability of ore body identification are improved.

To monitor the state of a vehicle without being affected by the ambient environment such as in the nighttime.SOLUTION: A detector comprises: an acquisition unit that, on the basis of a reflected wave that is reflected on an object moving in the cabin from a transmitted wave transmitted toward the inside of a cabin of a vehicle, acquires time-series data of a point group indicating one or more detection points representing the position of the object moving in the cabin; an operation unit that analyzes the behavior of the point group moving with the lapse of time on the basis of the time-series data of the point group; and a determination unit that determines whether the object enters or exits from the cabin on the basis of the behavior of the point group.SELECTED DRAWING: Figure 5

The invention provides an advanced geological forecasting method and system, and the method comprises the steps: arranging a plurality of radar measurement points on the ground surface of a to-be-constructed region according to the operation plan of tunneling equipment, so as to install a radar; before the tunneling equipment executes the tunneling operation, a radar is used for detecting whether a geological abnormal body exists under the earth surface of the to-be-constructed area or not. According to the scheme, the radar is arranged on the ground surface for detection, the problem that in a traditional method, the radar is difficult to arrange between a cutterhead and a tunnel face of tunneling equipment is solved, and therefore effective monitoring on poor excavation construction conditions is achieved; the influence of electromagnetic interference generated by underground tunneling equipment on radar signals is remarkably reduced, and the accuracy of advanced geological forecast is improved.

The invention relates to the field of image processing, and discloses a transformer-based GPR image clutter removal method, which comprises the following steps of: constructing a deep learning algorithm model of a transformer; the model comprises a feature extraction layer, a feature fusion layer and a feature output layer, and the feature extraction layer comprises a convolution layer, three continuous axis-based transformer modules and a cross-layer attention fusion module which are connected in sequence; the feature fusion layer adopts an encoder-decoder layered structure, an encoder comprises four stages, a decoder comprises three stages, and weighted jump connection is carried out between the encoder and the decoder; the feature output layer comprises three continuous axis-based transformer modules, a cross-layer attention fusion module and a convolution layer which are connected in sequence; and after the model is trained, clutters are removed by using the trained model. According to the method disclosed by the invention, effective signals can be reserved while clutters are removed, and the processing precision is improved.

The invention provides a high-frequency electromagnetic excitation cable detection image reconstruction method and system, and belongs to the technical field of underground facility multi-field coupling detection and imaging, and the method comprises the steps: applying high-frequency electromagnetic excitation to an underground medium; receiving an electromagnetic signal transmitted through an underground medium, synchronously collecting a sound signal generated by electromagnetic excitation, and preprocessing the electromagnetic signal and the sound signal; performing structure imaging on the electromagnetic signal by adopting a frequency wave number migration imaging algorithm to obtain medium structure distribution; performing electrical parameter imaging on the electromagnetic signal by adopting a Born approximate inverse scattering imaging algorithm to obtain medium electromagnetic characteristic parameter distribution; sound source distribution reconstruction is carried out on the sound signals through a time reversal algorithm, and medium sound source response characteristic distribution is obtained; and inputting imaging results of the three algorithms into a pre-constructed deep reinforcement learning model for dynamic fusion to generate an underground medium comprehensive parameter reconstruction image.

The present invention discloses a low-frequency large-span electromagnetic wave CT data correction method, which comprises the following steps: Step 1, obtaining the initial emission field strength, the ground surface absorption coefficient and the absorption coefficient in the borehole: using the initial emission field strength obtained in Step 1, the distance from the emission antenna in the borehole to the hole mouth, and the distance from the receiving antenna in the borehole to the hole mouth, to obtain the field strength propagating along the borehole and the field strength propagating along the borehole, and the field strength of the corrected low-frequency electromagnetic wave propagating in a straight line at the shortest distance in the medium. The correction method disclosed by the present invention solves the problem of poor inversion effect of the measured data of the low-frequency cross-hole electromagnetic wave CT, realizes the application of the low-frequency cross-hole electromagnetic wave CT technology in a large hole distance of 20-40 m, improves the detection efficiency and reduces the detection cost.

A terahertz signal-based image collection method and system. The image collection method includes: providing two terahertz devices respectively on two sides of an inspection region; adjusting a posture of a swinging reflection plate of each terahertz device to reflect terahertz wave signals emitted by a target to be inspected in the inspection region, and preventing the terahertz wave signals of the target to be inspected reflected by the swinging reflection plate of one of the two terahertz devices from being incident on the swinging reflection plate of the other one of the two terahertz devices; and generating terahertz images of different sides of the target to be inspected based on terahertz signals reflected from the swinging reflection plates of the two terahertz devices.

The invention belongs to the technical field of geophysical exploration, and particularly relates to a method and a system for quantitatively measuring intrinsic parameters of bedrock fractures based on all-angle domain amplitude and phase joint inversion. The method comprises the following steps: acquiring geological radar reflection data of a target fracture at a plurality of incident angles; synchronously extracting data sequences of amplitude change along with angles and phase change along with angles; establishing a fracture reflection theoretical model; constructing a target function jointly constrained by the amplitude residual and the phase residual; and adopting a global optimization algorithm to minimize the target function, and synchronously inverting to obtain the fracture opening, the filler dielectric constant and the occurrence parameter. According to the invention, through the combined constraint of the amplitude and the phase, the inversion multiplicity is effectively inhibited; accurate system effect correction is adopted, so that the reliability of large-angle data is ensured; according to the method, multi-parameter synchronous inversion without prior hypothesis is realized, the inversion precision is small in relative error, the method is obviously superior to a traditional method, and the method has important engineering application value.

The invention discloses a three-dimensional transient electromagnetic detection method for tunnel advanced geological forecast. The transient electromagnetic exploration method has the advantages of low construction cost, high safety coefficient, reliable detection result and the like. The method comprises the following steps: installing a plurality of loop sources in an area nearby a tunnel face in a set mode, and obtaining stratum information data of the area nearby the tunnel face; and analyzing the data by adopting a three-dimensional transient electromagnetic forward and reverse modeling method to obtain related information of the unfavorable geologic body in front of the tunnel face. According to the method, the efficiency and the accuracy of transient electromagnetic tunnel advanced prediction are improved.

A road disease identification method and system based on geological radar data relates to the field of electrical digital data processing, and the method comprises the steps: transmitting electromagnetic waves to the interior of a target detection road through a geological radar transmitting antenna along a preset detection route, and receiving electromagnetic wave signals reflected by different media in the target detection road through a receiving antenna, obtaining original reflected wave data; after preprocessing the original reflected wave data, aligning ground reflected waves of each signal channel of the original reflected wave data through zero point adjustment to obtain reference data; extracting signals in an effective frequency range in the reference data, and averaging by adopting a sliding time window to obtain a wave group morphological feature, an amplitude feature and a phase spectrum feature of the target area; and matching with a preset feature threshold according to a combination relationship of the wave group morphological features, the amplitude features and the phase spectrum features to obtain a disease type of each target area in the target detection road. By implementing the method, the accuracy of road disease identification can be improved.

Imaging systems and associated methods are described. According to one aspect, an imaging system includes an antenna array having transmit and receive antennas, the transmit antennas emit electromagnetic energy from a plurality of different positions about a target imaging volume and the receive antennas receive reflections of the electromagnetic energy at the different positions, a transceiver configured to control the emission of the electromagnetic energy and to generate radar data that is indicative of the reflections of the electromagnetic energy received via the receive antennas; and processing circuitry configured to focus the radar data to provide first focused data in a first dimension, to focus the radar data in a second dimension to provide second focused data, and use the second focused data to focus the radar data in a third dimension to provide third focused data comprising an image of the target imaging volume.

The invention provides an asphalt thickness intelligent detection method, device and system based on a ground penetrating radar, and relates to the technical field of asphalt thickness detection, and the method comprises the steps: enabling a multi-channel ground penetrating radar detection module to carry out the periodic lifting motion, obtaining calibration data, and building a noise signal model; single-point measurement is carried out, and the relative dielectric constant of the to-be-measured asphalt pavement is measured by adopting a common center method; adjusting the height of a ground penetrating radar antenna of the multi-channel ground penetrating radar detection module, and continuously measuring radar data of the asphalt road section; and based on the calibration data and the noise signal model, carrying out calibration, de-noising and smoothing processing on the radar data of the asphalt road section, tracking and generating an optimal boundary position through a dynamic programming algorithm, and calculating to obtain the pavement asphalt thickness distribution condition. The multi-channel ground penetrating radar and the lifting device work cooperatively, the relative dielectric constant is measured through the common midpoint method, the optimal height of the ground penetrating radar antenna is calculated, and the dynamic planning algorithm tracks and generates the optimal boundary for automatic processing.

The invention discloses a hydraulic ring geologic structure detection method and system based on a geological radar, and belongs to the technical field of hydraulic ring geologic structure detection. Based on a geologic structure of a detection area and a detection target, obtained geological radar image data and seismic wave data are subjected to joint inversion; and comparing a joint inversion result with an actual condition, obtaining a geological radar and seismic wave joint inversion result by determining a stratigraphic interface, lithology change and anomalous body position in a geological radar image and setting an initial velocity model, a density model and parameters of inversion, and establishing a finite element model of a hydraulic ring geological structure. The method comprises the following steps: performing grid division on a hydraulic ring geologic structure, setting constraint conditions of the hydraulic ring geologic structure, simulating a load effect under an actual working condition, obtaining stress distribution, a displacement field and bearing capacity key indexes of the hydraulic ring geologic structure, and monitoring the change condition of the hydraulic ring geologic structure in real time. The method can improve the accuracy and reliability of the detection result.

A method may include acquiring data from a wellbore imaging tool disposed in a wellbore in a subterranean formation, wherein the wellbore includes an electrically insulating oil-based fluid introduced into the wellbore as a drilling lubricant; determining an electrically insulating oil-based fluid resistance and a reference formation resistance based on the data via a circuit model comprising a series term and a parallel term; and detecting a location of a fracture in the formation based on a change in current from the tool through the electrically insulating oil-based fluid and into the formation, the change in current is obtained by determining an effective formation resistance based on at least a portion of the data of the location and by comparing the effective formation resistance to the reference formation resistance.

The invention relates to a tunnel lining quality detection method, which comprises the following steps of: acquiring tunnel lining ground penetrating radar data, and preprocessing the tunnel lining ground penetrating radar data; carrying out image segmentation on the preprocessed radar image, and dividing the preprocessed radar image into a lining thickness region, a steel bar distribution region and other background regions; counting the number of reinforcing steel bars in the reinforcing steel bar distribution area through a polymorphic detection method; on the basis of the segmented lining thickness area, the actual lining thickness is calculated in combination with the dielectric constant difference; inputting actually measured radar data into the cavity recognition model, and outputting a cavity recognition result; and generating a tunnel lining quality evaluation report by integrating the number of the reinforcing steel bars, the actual lining thickness and the cavity identification result. According to the prediction method provided by the invention, integrated operation of lining thickness measurement, steel bar statistics and defect detection is realized through multi-task collaborative optimization, the detection efficiency and precision are improved, and a reliable technical scheme is provided for tunnel lining quality evaluation.

The utility model discloses a shield tunneling machine excavating device adopting a telescopic movable cutterhead, and relates to the technical field of shield tunneling machine excavating, in particular to the shield tunneling machine excavating device adopting the telescopic movable cutterhead. Comprising a main body, a shield tunneling machine digger, a sliding rail, a range finder, a cutterhead, an angle sensor, a hydraulic cylinder, a controller, a geological radar, a GPS module, a WiFi module and a wear monitoring device. In the utility model, the hydraulic cylinder, the sliding rail, the controller and the angle sensor are integrated, so that the cutterhead can be telescopically and flexibly adjusted to adapt to different geological conditions. The GPS module, the range finder and the geological radar are combined, so that the navigation precision and the real-time geological information acquisition capability are improved, and the accuracy and the safety of a tunneling path are ensured. And due to the application of the wear monitoring device and the WiFi module, real-time monitoring and data transmission of the wear of the cutterhead are realized, and the equipment fault and maintenance cost are reduced.

The invention discloses a method for suppressing magnetotelluric mixed noise in a shallow water area. The method comprises the following steps: reading a noisy ocean MT time sequence; setting phase space reconstruction parameters; constructing a phase-space vector to obtain a noisy data matrix; noise priori information is obtained through noise pre-estimation; constructing an original noisy data matrix after noise whitening; performing singular value decomposition to obtain a feature vector and a feature value matrix of a data covariance matrix after noise whitening; selecting a low-order principal component after noise adjustment principal component transformation to reconstruct a denoised data matrix; recovering the denoised data matrix into a time sequence; carrying out Fourier transform to obtain an ocean MT magnetic field component amplitude spectrum, and combining to obtain an ocean MT four-component amplitude spectrum; detecting the frequency point of the pulse in the four-component amplitude spectrum; and setting all amplitudes corresponding to pulse frequency points in the four-component amplitude spectrum to be 0, and performing inverse Fourier transform to obtain a processed four-component time sequence. According to the invention, the ocean magnetotelluric signals can be better processed, and the data quality is improved.

A barrier component, a metal detector component; and a base structure that physically connects to the barrier component and connects to the metal detector component, wherein the base structure distances the barrier component from the metal detector component a distance that prevents electromagnetic interference between the barrier component and the metal detector component. A monitoring component monitors at least one gate system parameter of the gate system and stores the at least one gate system parameter or transmits the at least one gate system parameter to a monitoring service over a network.

The invention provides a tunnel detection vehicle based on a geological radar and a tunnel lining quality detection system and method.The tunnel detection vehicle is characterized by comprising a plurality of detection arms used for clamping the geological radar to move on the surface of a tunnel lining; the carrying engineering vehicle is used for carrying the mechanical arm to move on the road surface; the plurality of geological radars are used for detecting the tunnel lining quality based on radar signals; the tunnel lining quality detection system is used for acquiring lining surface data and track data of the carrying engineering vehicle in real time, and based on the lining surface data and the track data, the telescopic parameters of the detection arm and the clamping angle of the geological radar are adaptively regulated and controlled. According to the invention, through the cooperation of all the components and the system, stable fitting of the geological radar antenna and the tunnel lining curved surface under various road conditions is realized, the efficiency, the accuracy and the safety of tunnel lining quality detection are improved, and meanwhile, the detection requirements of different scenes of tunnels under construction and operation are met.

A geophysical or space-based detection, interrogation, or exploration system includes a compact electric dipole driven transmitter for producing a primary electromagnetic field, and a very sensitive electromagnetic sensing receiver for detecting a secondary electromagnetic field produced by electromagnetic induction in a target responsive to the primary electromagnetic. The electromagnetic sensing receiver is configured to employ computer-controlled software that operates an inverse algorithm that processes receiver data resulting from detection by the electromagnetic sensing receiver of the secondary electromagnetic field, and that performs analysis on results of the inverse algorithm to classify the target in a manner that distinguishes material, shape, or location of the target, and that displays results of the analysis. The compact electric dipole driven transmitter can be a compact transmitting antenna according to the present invention that includes a vacuum tube, a charged particle beam gun, a beam timing controller, and a beam speed controller.

The embodiment of the invention discloses a quality control method and device for logging-while-drilling data and computing equipment. The method comprises the following steps: acquiring actually measured signal values of different sampling orientations acquired by the electromagnetic wave logging-while-drilling instrument at a target depth; performing waveform fitting on the actually measured signal values of different sampling orientations to generate a waveform coefficient corresponding to the target depth; fitting signal values of different sampling directions are generated based on the waveform coefficients; extracting a waveform baseline from the waveform coefficient, processing the measured signal value by using the waveform baseline to obtain a corrected measured signal value, and processing the fitted signal value by using the waveform baseline to obtain a corrected fitted signal value; calculating a data error of the sampling orientation according to the corrected actual measurement signal value and the corrected fitting signal value of the sampling orientation; and generating a quality index value of the target depth according to the data errors of different sampling orientations at the target depth. According to the scheme, accurate quality detection and accurate control of the logging-while-drilling data can be achieved, and the subsequent logging data analysis accuracy is improved.