1932results about "Detection using electromagnetic waves" patented technology

Provided herein is a tunnel electromagnetic joint scanning detection method and a system thereof. It introduces a new tunnel electromagnetic detection system called TEJS, realizes three-dimensional joint inversion of multi-component, time domain and frequency domain signals, and forms tunnel joint scanning imaging. This method adopts the mode of surface transmission, underground reception, multi-source transmission and multi-component reception. Based on an observation system, a large number of stochastic models are constructed and numerically simulated, and a large number of training data sets are constructed by using the simulated data to complete the training of UNet model. This model can realize real-time and fast imaging of the position of the low-resistance anomalous body in three-dimensional space. An algorithm forms a dual checking mechanism through surface imaging and underground imaging, which constrains the three-dimensional spatial position of anomalous body together to prevent misjudgment.

The present disclosure discloses a three-dimensional inversion method of airborne transient electromagnetics based on deep learning. The method of the present disclosure proposes two strategies that focus on training datasets, to improve the performance of deep learning models, including divide and conquer strategy and random models generating. Through a large of reasonable structural models, appropriate network setups, a more generalized result can be obtained through our proposed U-Net framework, which has been demonstrated to be effective on both synthetic and field data. This scheme can realize the rapid prospecting of three-dimensional resistivity structure in large-area target region, and solve the problem of low efficiency of traditional three-dimensional inversion calculation of ATEM and poor migration ability of three-dimensional inversion based on deep learning developed by predecessors.

The invention provides a multi-parameter MIMO (Multiple Input Multiple Output) aviation time-frequency detection system and method, which can be applied to the technical field of underground medium detection. The system comprises a flying platform, a transmitting subsystem, a receiving subsystem and a measurement and control subsystem, and the transmitting subsystem is configured to load a first current pulse into a transmitting coil through a first current transmitter to achieve primary electromagnetic field excitation and load a second current pulse into a compensation coil through a second current transmitter to achieve secondary electromagnetic field excitation. Compensation electromagnetic field excitation is realized; the receiving subsystem is configured to be used for sampling the first current pulse and the second current pulse and collecting secondary electromagnetic field response to obtain underground medium electrical information of the target detection area; and the measurement and control subsystem is configured to send a control instruction to the transmitting subsystem and the receiving subsystem according to a sampling result and set detection parameters and monitor the working state of the detection system, and the measurement and control subsystem adjusts the first current pulse and the second current pulse in real time.

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 discloses an ultra-deep underground pipeline detection method and device, a storage medium and a program product, and the method comprises the steps: transmitting a multi-frequency electromagnetic wave signal, receiving an acoustic response generated by the multi-frequency electromagnetic wave signal, and determining an underground geological structure in combination with a preset geological material frequency spectrum database. A composite detection signal is generated by simulating an underground propagation path of a multi-frequency electromagnetic wave signal and performing phase adjustment and power adjustment. And finally determining position information and depth information of the pipeline in the generated underground structure image by transmitting a composite detection signal and processing a return signal by using a time reversal mirror technology. According to the method, multi-frequency electromagnetic wave signals, acoustic response analysis, geological material characteristics and signal processing technologies are comprehensively utilized, and the precision and reliability of ultra-deep underground pipeline detection can be effectively improved.

The invention relates to a method and a device for probing a subsurface structure. The method comprises the steps of (a) sending a probe signal as an electromagnetic wave into the structure. (b) receiving an echo signal of the electromagnetic wave from the structure, and (c) processing the echo signal for deriving information about the structure. The step (c) of processing the echo signal comprises sampling the echo signal at a sampling frequency fs. The probe signal comprises multiple discrete frequency components fn,k, wherein at least two of the multiple frequency components fn,k are located in different Nyquist zones. An n-th Nyquist zone covers a frequency range from (n−1)*Tfs / 2 to n*fs / 2 with fs being the sampling frequency and n=1, 2 . . . . Further, k=1 . . . K and K is the number of frequency components fn,k in the n-th Nyquist zone. The method and device facilitate an increase in data acquisition speed without losing information on any of the frequency components.

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 discloses a dam leakage detection method based on combination of a circuit and an electromagnetic field. The method comprises the following steps: step 1, placing an emission electrode at a certain depth in a water area on one side of an upstream face of a dam; 2, a loop electrode is placed at the position 3 meters away from one side of the downstream face of the dam; step 3, connecting the emission electrode and the loop electrode by using a power supply to form a planar array; 4, detecting a voltage signal of the electromagnetic wave by the collecting electrode; step 5, placing a horizontally polarized loop antenna on one side for transmitting, and symmetrically placing a vertically polarized loop antenna and a line antenna on the other side for receiving; and 6, detecting the vertical position of the leakage path by using a common depth method. According to the detection method disclosed by the invention, the detection efficiency and precision can be improved, weak leakage can be accurately positioned, the operation is simple, operation by using a ship in water is not needed, and a dam structure does not need to be damaged by drilling.

The invention relates to an unmanned aerial vehicle target detection method based on a space-time synchronization association mechanism, and relates to the technical field of wireless detection, and the method comprises the following steps: S1, building a unified time reference system, and ensuring that precise timestamp alignment is carried out on IQ data streams collected by two technologies, and the precision reaches a microsecond level; s2, acquiring unmanned aerial vehicle signal data obtained by protocol reverse analysis and a radio frequency fingerprint identification technology; s3, constructing a three-dimensional incidence matrix containing a time window, a frequency domain position and a space arrival angle, and performing space-time matching on the detection events in the synchronous window; and S4, analyzing a matching result to identify a real unmanned aerial vehicle target. According to the method, the unmanned aerial vehicle signal can be effectively and accurately analyzed, the accuracy and reliability of unmanned aerial vehicle target detection are improved, and the possibility of multi-target false alarm is reduced.

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 relates to the technical field of geophysical exploration, in particular to a complete polarization borehole radar detection device and a detection method thereof, and the device comprises a transmitting antenna unit which is used for transmitting horizontal polarization and vertical polarization radar signals; the receiving antenna unit is used for receiving horizontal polarization and vertical polarization radar signals; the directional positioning unit is used for measuring the real-time directions and positions of the transmitting and receiving antenna units so as to judge whether the direction and the position are target directions and target positions or not; the radar transmitting and receiving control unit is used for activating different horizontal polarization and vertical polarization antennas to construct a plurality of polarization modes, and switching to any polarization mode according to a target detection requirement so as to acquire multi-polarization radar data; and the host control unit is used for carrying out image reconstruction on the multi-polarization radar data so as to obtain a three-dimensional underground structure image. Therefore, the problems that a traditional wellhole radar cannot achieve three-dimensional imaging, and a single-hole wellhole detection radar cannot achieve positioning and orientation are solved.

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 an ionospheric scintillation phenomenon monitoring method and system, terminal equipment and a storage medium, and the method comprises the steps: controlling a receiver end to carry out the data processing of a received satellite signal, and generating a dual-frequency carrier phase observation value of the satellite signal; calculating the total electron content of an ionized layer on an inclined path in each observation epoch based on the double-frequency carrier phase observation value; acquiring the total electron content of the ionized layer on an inclined path in each observation epoch in the current detection period, generating a change rate index of the total electron content of the ionized layer in the current detection period based on the total electron content of the ionized layer, and when the change rate index of the total electron content of the ionized layer is greater than a preset change rate index, detecting the total electron content of the ionized layer in the current detection period. And judging that the ionospheric scintillation phenomenon occurs in the current detection period. The reliability and economical efficiency of ionospheric scintillation monitoring can be improved.

The invention discloses a periodogram and incoming wave direction finding fused multi-unmanned aerial vehicle signal identification method and system, and relates to a signal processing technology, and the method comprises the steps: obtaining to-be-identified signals with time domain aliasing and frequency domain non-aliasing; suppressing the noise of the to-be-identified signal by using an average periodogram method and smooth filtering, and calculating a bottom noise value; according to the calculated bottom noise value, setting a judgment threshold to detect a target unmanned aerial vehicle signal; estimating the start-stop frequency and bandwidth of the detected target unmanned aerial vehicle signal; performing signal separation by using an FIR filter according to the estimated starting and ending frequency and bandwidth; and executing incoming wave lateral direction based on the separated target unmanned aerial vehicle signal so as to complete signal identification. According to the method, unmanned aerial vehicle signal detection is completed through an average periodogram method, unmanned aerial vehicle weak signals which are sparsely distributed in space are further obtained through a direction finding method, and weak signal unmanned aerial vehicles which are far in distance are detected.

The invention provides a power transmission project karst geology detection method and system based on a ground penetrating radar, and relates to the technical field of geophysical ground penetrating radar detection, and the method comprises the steps: building a target body model of karst geology based on an autocorrelation random medium, carrying out the forward modeling to generate ground penetrating radar data, carrying out the inversion to generate a dielectric constant diagram, and constructing a karst disaster data set; constructing an inversion network taking the ground penetrating radar data as input and the dielectric constant diagram as output, and performing wavelet-independent ground penetrating radar source-independent deep learning on the inversion network by using the karst disaster data set; through the trained inversion network, inversion is carried out on the obtained actually-measured ground penetrating radar data, and a dielectric constant diagram of the karst geology is obtained through prediction; through preparation of the ground penetrating radar karst disaster data set based on the self-correlation random medium and ground penetrating radar source-independent deep learning inversion independent of wavelets, rapid inversion and attribute imaging of karst underground disasters of a power transmission line are realized, and the accuracy of karst geological detection of a power transmission project is improved.

The present invention discloses an aerial mixed-field source electromagnetic detection system and method. The system uses a helicopter as a carrier platform, and adopts a mode of ground electrical source and aerial magnetic source excitation, aerial high-sensitivity small-bandwidth coil and aerial low-sensitivity large-bandwidth coil reception. The high-sensitivity small-bandwidth coil can sense the weak signal generated by the high-power electrical source and the natural field source exciting the earth, and has the advantages of high-power transmission, large detection depth, light mounting, high sensitivity, etc., and is mainly used for deep earth detection; the low-sensitivity large-bandwidth coil is coplanar with the transmitting coil of the magnetic source transmitter, and has the advantages of accuracy, high signal-to-noise ratio, high resolution, etc., and is mainly used for medium and shallow earth detection. The present invention gives full play to the advantages of the helicopter's flexible maneuverability, high-power ground power supply, and rich natural field source spectrum components, and combines the advantages of magnetic source, electrical source and natural field source electromagnetic detection systems to achieve fast, large-area, and large-depth detection range of all-round refined electromagnetic exploration.

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 discloses a rapid detection method for a tunnel to pass through a large karst cave, and relates to the technical field of civil engineering, and the method comprises the following steps: S1, selecting a detection position and drilling a drill hole; s2, installing a drilling radar; s3, setting a ground radar; s4, starting radar data acquisition; s5, performing data processing and analysis to generate a tomography image; s6, karst cave identification and analysis; s7, safety measures and construction schemes are formulated; and S8, dynamically adjusting the detection parameters. According to the invention, through combined use of the drilling radar and the ground radar and combination of advanced data processing technologies and algorithms, a high-precision tomography image can be generated, the position, the shape, the size and the filling condition of the karst cave can be accurately identified, reliable geological information is provided for construction, and potential safety hazards in the construction process are effectively avoided.

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.

The invention discloses a multi-source data detection fused surface karst zone structure prediction method and device. The method comprises the steps of S1, obtaining apparent resistivity data detected by a high-density electrical method, electromagnetic wave data detected by a ground penetrating radar and remote sensing data of an overground environment; s2, extracting spatial distribution of surface environment factors based on the remote sensing image; s3, according to the apparent resistivity data, the electromagnetic wave data and the corresponding spatial distribution data, preliminarily determining soil and surface karst zone thickness data of the measured karst area; s4, the apparent resistivity data, the electromagnetic wave data, the surface environment factors and the corresponding thickness data form a training data set, and the model is trained to obtain a surface karst zone structure prediction model; and S5, inputting data obtained in real time into the surface karst zone structure prediction model to obtain a prediction result. The method has the advantages of being simple in implementation method, low in cost, high in prediction precision and efficiency and the like.

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

Disclosed are a joint landslide monitoring system and method. The system includes: a high-frequency electromagnetic wave monitoring module configured to continuously emit electromagnetic wave signals into a monitoring area, perform interference processing on signals received by a receiving antenna to obtain target signals, and obtain surface deformation information of the monitoring area according to a phase difference of the target signals; a low-frequency seismic wave monitoring module configured to propagate seismic waves downward from a ground surface in the monitoring area, receive reflected waves from a creeping medium that the seismic waves encounter, obtain frequency-domain interference characteristics of internal creeping; and determine a longitudinal force on a 3D stratigraphic landslide mass shear surface; and a cloud platform configured to determine a maximum subsidence amount and a subsidence velocity of the monitoring area, and issue alert information when the maximum subsidence amount or the subsidence velocity exceeds a preset range.

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.

A device for detecting an approach of a part of a user's body and / or of a portable user equipment, housed on board a motor vehicle, including: a near-field communication antenna configured to transmit and receive signals at a high resonant frequency between 3-30 MHz. The antenna includes at least one winding extending continuously in the form of a set of rods such that the rods have a variable capacitance connected to the antenna and the antenna is able to generate a capacitance variation in response to the approach of a part of a user's body; a measurer for measuring, through electromagnetic coupling with the antenna, an impedance variation or a frequency variation of the antenna. The measurer having a series resonant frequency at the selected high resonant frequency and able to detect the approach of a portable user equipment or the approach of a part of the user's body.

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 discloses an urban complex water supply pipe network dark leakage detection method, device, equipment, medium and product, and relates to the technical field of water supply pipe network detection.The method comprises the steps that a ground penetrating radar is used for determining the pipeline position of a to-be-detected urban water supply pipe network, and ground penetrating radar detection data are obtained along the pipeline position; preprocessing the ground penetrating radar detection data to obtain preprocessed ground penetrating radar detection data; determining a soil relative dielectric constant based on the preprocessed ground penetrating radar detection data and the reflection interface; the reflection interface is determined according to the pipe depth information; according to the method, the ground penetrating radar is used for carrying out urban complex water supply pipe network dark leakage detection, and the urban complex water supply pipe network dark leakage detection precision can be improved.