889results about "Detection using electromagnetic waves" patented technology

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 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 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 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.

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.

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 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.

The invention provides an electromagnetic detection system based on a sea-bottom crawler, belonging to the field of geophysical exploration technology, comprising: a survey vessel, a sea-bottom crawler, a transmitting antenna, a receiving node array, a control chip, and a power supply; the survey vessel is connected to the sea-bottom crawler through a traction rope, and the tail of the sea-bottom crawler is provided with a drag cable, on which the transmitting antenna and the receiving node array are mounted, and both the control chip and the power supply are configured in the integrated electronic cabin of the sea-bottom crawler; the power supply provides electrical energy to the sea-bottom crawler, transmitting antenna, receiving node array, and control chip, and the control chip is electrically connected to the transmitting antenna, the receiving node array, and the power system of the sea-bottom crawler; the control chip is configured to have an electromagnetic detection interference compensation module for performing interference elimination and compensation on reflected waves received by the receiving node array. It solves the technical problem of insufficient detection accuracy in existing technologies.

The invention discloses a radar and deep learning-based road surface internal disease three-dimensional morphology identification method, which integrates a novel technical path of qualitative identification and quantitative reconstruction, provides a high-precision and quantifiable reference for subsequent non-damage assessment by constructing a disease three-dimensional geometric model and reversely calibrating radar map characteristic parameters, and improves the accuracy and the accuracy of the three-dimensional morphology identification of a road surface internal disease. The problem that the three-dimensional morphology characteristics of the internal diseases of the asphalt pavement are difficult to accurately obtain at present is solved, and a calibration method is provided for obtaining the three-dimensional morphology characteristics of the internal diseases of the pavement based on a ground penetrating radar technology. And meanwhile, geometric data support is provided for mechanical response analysis and performance attenuation law research of the existing asphalt pavement structure containing internal diseases.

The invention relates to a geological radar advanced forecasting system for TBM shield construction and a detection method, which are characterized in that a transmitting antenna and a receiving antenna are arranged in a tool bit gap of a TBM shield machine, rotation of a tool bit is not affected, measurement can be carried out when the tool bit rotates, and a three-dimensional structure section right in front of the tool bit is further acquired; a method of forming obvious reflection based on geological body physical property dielectric constant difference is adopted, the TBM shield tunneling advancing direction is detected and imaged, a geological structure image is obtained, then geological information such as faults, rich water, cavities and boulders is provided, the influence of geological difference is small, and testing is more accurate compared with a seismic wave method; the receiving antenna and the transmitting antenna are arranged in the tool bit gap of the TBM, the receiving antenna and the transmitting antenna are not affected by the blade, rotation of the tool bit is not affected, and stability and accuracy of rotation measurement of the whole set of forecasting system can be guaranteed.

The invention discloses a shield tunnel ground penetrating radar one-transmitting-multi-receiving antenna array advanced detection system, which comprises a terminal processor and a one-transmitting-multi-receiving antenna array, the terminal processor is connected with the one-transmitting-multi-receiving antenna array through a coaxial cable, the one-transmitting-multi-receiving antenna array comprises a transmitting antenna and a plurality of receiving antennas, and the transmitting antenna is connected with the receiving antennas. The shield cutter heads are arranged in the radial direction of the shield cutter head, are fixed on the same radius of the shield cutter head and cover the radius of the whole shield cutter head; the shield cutterhead rotates to cut a front soil body, the terminal processor controls the one-transmitting-multiple-receiving antenna array to synchronously carry out advanced detection, the one-transmitting-multiple-receiving antenna array rotates along with the shield cutterhead to detect a circle, the transmitting antennas radiate electromagnetic waves once at fixed angle intervals, and the multiple receiving antennas record reflected electromagnetic echo signals of a front stratum once at the same time. And the one-transmitting multi-receiving antenna array follows the shield tunneling machine to gradually tunnel so as to detect obstacles in the whole tunnel excavation section. The method has the advantages of large detection range, high detection efficiency and clear detection result.

An aeroelectromagnetic data inversion method and a system based on an approximate Jacobian matrix are provided. The method includes following steps: dividing an inversion target area into grids, and setting an initial underground space model based on divided grids; constructing an aerial transient electromagnetic three-dimensional inversion target function based on the initial underground space model, and calculating a weighting term of the model based on observation data and the inversion target function; constructing the approximate Jacobian matrix, calculating an iterative equation set based on the approximate Jacobian matrix, and updating the inversion target function based on the iterative equation set to obtain an inversion model; and inputting aerial transient electromagnetic observation data into the inversion model for inversion to obtain inversion results of each induced polarization parameter.

The invention discloses a railway communication cable inspection robot dog which comprises a machine body and four active driving legs installed on the machine body, rolling driving mechanisms are installed on the lower portions of the two active driving legs located at the front end respectively, and driven rolling wheels are installed on the lower portions of the two active driving legs located at the rear end respectively. An adjustable image direct acquisition mechanism, a universal supporting mechanism, a sensing module, a decision module, an execution module and a data module are mounted on the machine body. The method can effectively improve all-terrain adaptability and high-precision detection, has the efficient and autonomous capability, is safe and reliable in operation, intelligent in decision making, economical and efficient, and realizes the crossing from'manual patrol 'to'intelligent patrol'. The method is suitable for the technical field of railway communication cable inspection.

The invention provides a tunnel hidden defect simulation detection system, and relates to the technical field of tunnel detection. The method comprises a lining structure, a hidden defect simulation assembly, a radar assembly and a signal processing assembly. The lining structure comprises reinforcing meshes with different mesh sizes and internal defect simulation components; the reinforcing meshes with different mesh sizes are used for simulating the reinforcing meshes under different conditions, and the internal defect simulation component is used for simulating a lining structure under different internal defects; the hidden defect simulation assembly comprises a frame, a hidden defect simulation component and surrounding rock; the radar assembly is used for transmitting and receiving electromagnetic waves in a preset frequency range. The signal processing assembly is used for processing radar echo signals received by the radar, determining radar signal characteristics under the conditions of internal defects of different lining structures and tunnel hidden defects according to the radar echo signals, and constructing a hidden defect simulation detection database. According to the invention, tunnel simulation detection under different working conditions can be realized.

An assembly and method are disclosed for generating and detecting a modulated pressure signature in a fluid transported to a subsurface injection zone. The assembly includes a pump, a pulsation dampener, and a pressure modulation device that oscillates pressure to produce a frequency-modulated signature in the fluid, resulting in an alternating current streaming potential (AC-SP) at the injection zone. The method includes recording modulated electromagnetic signals at an array of electromagnetic field receivers on a surface above the subsurface injection zone, processing the data to identify source frequency signals, and correlating these signals to image subsurface fluid or pressure distribution, enabling three-dimensional mapping of subsurface structures.

The invention belongs to the technical field of civil engineering, and particularly relates to a shield tunnel structure abnormity identification method based on muon imaging and geological radar. According to the method, for a target detection section selected in a shield tunnel, a muon imaging device and a geological radar scanning device are arranged in the section, and muon flux data and geological radar reflection data in the same detection window are obtained. The method comprises the steps of target area determination and equipment layout, muon data acquisition and density imaging, geological radar data acquisition and reflector construction, space coordinate unification and image registration, fusion identification and abnormal area extraction. According to the method, the problem of false alarm of a single detection means is effectively solved, and through a multi-source data fusion method and double coupling verification of low density and strong reflection, high-efficiency and accurate positioning of hidden dangers such as cavities, voids and water erosion areas behind the shield lining can be realized, so that the false alarm rate is greatly reduced, and the decision-making efficiency of tunnel operation and maintenance is improved.

The invention provides an AI-driven multi-wireless-signal candid photographing detection device which comprises a mounting shell, a hardware acquisition layer, an edge computing layer, a cloud federation layer and a man-machine interaction layer, and all the layers achieve signal interaction through PCIe4.0 and SPI hardware interface communication protocols. The broadband patch antenna, the ceramic antenna and the helical antenna are adopted to cover a full target frequency band, the millimeter wave radar chip is matched, the 16 * 16 metamaterial RIS panel is additionally configured, and the weak signal receiving power is improved by synchronously controlling a reflection phase focusing signal, so that the problem of missing detection is solved; the multi-signal tensor decomposition unit and the CNN-LSTM signal classification unit construct frequency, intensity, time and phase four-order tensors, and overlapped signals are separated through Khatri-Rao space-time coding; a three-layer CNN and a two-layer LSTM are combined, precise classification of candid photographing signals is realized, the misjudgment rate is reduced, millimeter wave assisted precise distance measurement is combined with millimeter wave flight time data and an RSSI attenuation model, a distance measurement error is controlled through a dynamic weighting algorithm, and the problem of positioning misalignment is solved.

The invention relates to the technical field of underground space detection, and discloses a high-resolution three-dimensional imaging GNSS (Global Navigation Satellite System) positioning type shallow cavity detection system which comprises a mobile carrier platform, a step frequency continuous wave radar subsystem, a high-precision positioning and attitude sensing subsystem, a central control and edge calculation subsystem and a wireless communication module. According to the system, radar acquisition and hardware-level synchronization of positioning data are realized by using GNSS pulse per second; the central control subsystem dynamically modulates the radar frequency step number and the residence time according to the instantaneous velocity of the carrier to ensure that the space sampling interval is constant; and signal enhancement is carried out in combination with geographic semantic prior, three-dimensional deduction reconstruction is carried out on sparse survey line data by using a conditional generative adversarial network, and active supplementary collection of a reverse-driven low-confidence region is evaluated through confidence. According to the method, high-precision positioning, self-adaptive efficient acquisition and full-process closed-loop detection of the underground cavity are realized, and the reliability of detection data and the engineering application value are improved.

The invention relates to the technical field of underground pipeline detection, in particular to a Hertz signal digitization method and system for underground pipeline detection. A digital detection excitation signal with stable Hertz frequency is generated by adopting a phase accumulation mechanism of a DDS (direct digital synthesis) technology and digital interpolation translation; a controllable random jitter frequency division strategy is introduced to generate multiple groups of single-frequency-point voltage signals to reduce spectrum aliasing and background noise; a response signal is sampled and filtered through a high-precision ADC and a self-adaptive FIR low-pass filter; and carrying out detection analysis and alarm on the target underground pipeline in combination with the frequency band energy normalization analysis and feature vector construction of the wavelet sub-band. According to the invention, digital improvement can be carried out on a 512 Hz analog signal detected by a traditional underground pipeline, and the sensitivity, the anti-interference capability and the signal processing precision of underground pipeline detection are greatly improved.

The invention discloses a shield front karst fissure grouting plugging method based on feedforward identification and directional regulation and control, which comprises the steps of front geological information acquisition, target area identification, grouting path planning, parameter adaptive regulation and control, directional grouting execution and plugging effect feedback. Feature fusion processing of geometric features of the cavity region from a time domain to a frequency domain is realized, geological types and features of the cavity region are analyzed in combination with data, and remarkable reduction of cavity three-dimensional coordinate positioning errors and remarkable improvement of boundary recognition precision are realized; in the drilling process, the boundary of the cavity is sensed in real time, synchronous grouting and air exhaust are achieved through automatic deviation correction of the posture adjusting mechanism and the double-through-hole design, air pressure fluctuation in the cavity is controlled within a safe and stable range, and the risk of cavity collapse caused by air pressure changes is effectively prevented.

The invention discloses a void disease three-dimensional reconstruction method based on a radar signal time domain peak value, and belongs to the field of pavement disease nondestructive testing. Aiming at the problems that the existing ground penetrating radar (GPR) depends on manual interpretation, the resolution of a grey-scale map is low, and the three-dimensional space form of the void disease cannot be obtained, the method comprises the following steps: firstly, processing GPR data and utilizing time domain signal characteristics: identifying zero crossing points corresponding to the first peak value and the last peak value of a single-channel A-scan signal, and accurately positioning the starting depth and the ending depth of a void interface; based on the transverse continuity of the B-scan image, the relevance of adjacent multiple channels of signals is analyzed, the transverse start-stop channel number and the vertical depth range of the void area are determined, and a horizontal plane positioning bounding box is generated; and finally, fusing coordinate information of a multi-channel B-scan positioning frame, and constructing a void disease geometric model containing three-dimensional sizes of a long (X-axis), a wide (Y-axis) and a deep (Z-axis) through space conversion and superposition. According to the method, the depth is directly positioned from the time domain peak value, complex frequency domain calculation is avoided, and the noise immunity is high; horizontal boundary automatic extraction and disease three-dimensional visualization are realized, and accurate geometric parameters are provided for structural safety assessment; the method can be extensively applied to other pavement disease detection.

The utility model relates to the technical field of detection, and discloses a detection assembly, a door plate and a pass-type detection device. The detection assembly is applied to the pass-type detection device, the pass-type detection device comprises door plates located on the two sides, a detection channel is formed between the door plates on the two sides, and the detection assembly can be installed in each door plate of the pass-type detection device. The detection assembly comprises a main frame, and a nonlinear detection module and an eddy current detection module which are arranged in the main frame; wherein the nonlinear detection module comprises an antenna assembly, the eddy current detection module comprises a coil assembly, and the coil assembly is located on the side, opposite to the detection channel, of the antenna assembly. According to the detection assembly, a nonlinear node detection technology and an eddy current detection technology are combined, and the arrangement mode is reasonably arranged, so that the reliability of matched detection of the two detection technologies can be improved.

The invention discloses a method and a system for reconstructing a cavity shielded by a shallow reinforcing mesh. The method comprises the following steps: constructing a layered medium scene containing the shallow reinforcing mesh and the cavity; acquiring image data information with different shielding states and preprocessing the image data information to construct a reconstruction data set; constructing a reconstruction initial model of the cavity shielded by the shallow reinforcing mesh, and training to obtain a reconstruction model of the cavity shielded by the shallow reinforcing mesh; and adopting the obtained reconstruction model of the cavity shielded by the shallow reinforcing mesh to reconstruct the actual cavity shielded by the shallow reinforcing mesh. According to the method, multiple types of training data are acquired through a constructed layered medium scene containing a shallow reinforcing mesh and a cavity, and a reconstruction model of the cavity shielded by the shallow reinforcing mesh, which comprises a U-shaped network, a Sobel operator, an attention mechanism, a residual structure, an average mechanism and a jump connection scheme, is trained; therefore, the reconstruction of the cavity under the shielding of the shallow reinforcing mesh can be realized, the reliability is higher, the accuracy is better, and the reconstruction efficiency is higher.

The invention discloses an underground pipeline distribution detection method and system based on a ground penetrating radar, and relates to the field of underground pipe network engineering. The method comprises the steps of performing orthogonal grid division on a to-be-detected interval based on grid preset parameters, performing GPR orthogonal scanning on a grid detection area, and determining an initial trend of an underground pipeline according to a first vertex and a second vertex; adjusting the initial trend of the underground pipeline based on the initial vertical scanning direction; on the basis of the adjusted direction of the underground pipeline, continuing to perform GPR scanning on the grid detection area until scanning of the grid detection area is completed, and inputting obtained radar original data into the image detection model to obtain a first type of parameter value corresponding to the underground pipeline; and inputting the first type parameter value and the second type parameter value into a pipe diameter prediction model to obtain a pipe diameter value. According to the invention, through linkage of the three modules, intelligent and efficient cooperative one-stop service of detection image analysis, detection path planning and detection remote control can be realized.