996 results about "Multi band" patented technology

The invention discloses an unmanned aerial vehicle detection method based on multi-band radio spectrum analysis, and the method can recognize the flight control behaviors of a target, such as hovering, cruising or hovering, through the extraction of a signal track and the introduction of a behavior modeling mechanism, and effectively overcomes the defect that the prior art lacks the dynamic behavior analysis capability. A multi-node synchronization mechanism and a TDOA positioning method are combined, so that high-precision traceability of a target space position is realized; meanwhile, risk level assessment is carried out based on signal features, a track mode and a space region, so that the system has intelligent early warning capability. According to the whole scheme, a full-link unmanned aerial vehicle detection method from multi-frequency receiving, frequency spectrum identification, behavior judgment, target positioning to risk output is constructed, and the problems of single frequency band, rough identification means, lack of tracking and evaluation capability and the like in the prior art are effectively solved; and the practicability and the accuracy of the unmanned aerial vehicle detection system in a complex airspace environment are remarkably improved.

The invention discloses an open pit coal mine slope monitoring and early warning method and system based on multi-modal satellite fusion AI, and belongs to the technical field of geological disaster monitoring. The method comprises the following steps: S1, collecting multi-source data; s2, transmitting data in real time; s3, data preprocessing and space-time registration; s4, multi-band InSAR phase reconstruction and deformation field extraction are carried out; s5, deeply fusing the multi-source data; and S6, AI intelligent prediction and grading early warning. According to the open pit coal mine slope monitoring and early warning method and system based on multi-modal satellite fusion AI, slope global millimeter-level precision continuous deformation field monitoring is achieved, vegetation terrain shielding interference is reduced, the monitoring range is expanded, meanwhile, monitoring blind areas are eliminated, data processing efficiency is improved, a high-reliability deformation field is constructed, and the early warning error and missing report rate is reduced.

The invention discloses a broadband oscillation identification method and system based on a multi-band Nyquist criterion, and the method comprises the steps: dividing the frequency of broadband oscillation into a low frequency band, a middle frequency band and a high frequency band with overlapped frequency bands, and obtaining the oscillation signals of a monitoring node in a power grid in different frequency bands; respectively calculating the equivalent impedance of the non-overlapped frequency band of each frequency band and the equivalent impedance of the overlapped frequency band in the two adjacent frequency bands so as to construct the equivalent impedance of the low frequency band, the middle frequency band and the high frequency band with the overlapped frequency bands; establishing a Nyquist criterion of each frequency band based on a transfer function of dynamic characteristics of each frequency band in an open-loop state of the system; a generalized Nyquist criterion of the overlapped frequency bands is constructed by using the multi-frequency-band coupling matrix; constructing a comprehensive decision function according to the recognition result of the generalized Nyquist criterion on the system stability, the broadband oscillation comprehensive characteristic quantity and the change rate of the high-frequency-band impedance module value along with the frequency; and according to the value of the comprehensive decision function and a threshold value, a broadband oscillation identification result is determined, and the broadband oscillation identification capability is improved.

The invention relates to the technical field of vehicle-mounted communication, and provides a 5G network optimization method and system based on an intelligent dynamic multi-band adaptive switching system, and the method comprises the steps: obtaining network signal quality data, environment perception data and a communication task demand set; dynamic obstacle features are extracted based on environmental perception data, and signal occlusion prediction is output through a double-branch mixed deep learning model; screening qualified candidate links to construct a candidate set, generating a dynamic weight by using a deep Q network, calculating a comprehensive score of the candidate links, determining a main communication link under a hard constraint condition, and generating a communication strategy instruction; and according to the instruction type of the communication strategy instruction, performing dynamic fragmentation and multi-path distribution on the data stream, performing verification, recombination and intelligent delivery by a receiving end, and collecting a feedback data packet for network closed-loop feedback. According to the method, multi-mode sensing and signal shielding prediction are fused, and a self-adaptive switching and cooperative transmission mechanism of multi-band communication is constructed.

The invention discloses a single image super-resolution reconstruction method and system based on wavelet transform and cross-domain feature fusion. According to the method, firstly, a low-resolution RGB image is mapped to a high-dimensional feature space through a shallow feature extraction module; performing up-sampling and discrete wavelet decomposition on the features by using a wavelet feature mixing module to obtain multi-band features; low-frequency and high-frequency depth features are respectively extracted through a double-branch structure, cross-domain fusion is realized by means of a deformable cross attention mechanism, and the feature expression ability is enhanced in combination with residual connection; and finally, reconstructing a high-resolution image through convolution, up-sampling and regularization processing. In the training process, a pixel-level loss function is adopted to optimize network parameters, the multi-frequency-domain feature sensitivity is effectively improved, texture and structure information is balanced, the image contrast, definition and structural integrity are improved, and high-quality real-time super-resolution reconstruction can be achieved.

The invention relates to a hydrogen storage station safety monitoring method and system based on a wireless passive three-signal sensor, and belongs to the technical field of safety monitoring. Wireless passive three-signal sensor nodes are deployed in a hydrogen storage station to form a three-dimensional monitoring network; the temperature, strain and hydrogen detection units of the sensor are simultaneously excited through the multi-frequency-band signal transceiver, so that parallel acquisition of three-parameter signals is realized; performing signal decoupling, temperature compensation and primary risk assessment by using an edge computing gateway; deep data mining and risk assessment are carried out through a cloud early warning platform in combination with a digital twinborn model; wherein multi-parameter signal decoupling is realized by adopting a frequency division multiplexing and wavelet denoising algorithm, and safety early warning is carried out in combination with a three-level early warning decision tree. The hydrogen storage station electric spark risk can be eliminated, high-precision synchronous monitoring of temperature, strain and hydrogen concentration is achieved, and the hydrogen leakage early warning time is shortened.

The invention relates to a six-eye camera panoramic video real-time splicing method and system and computer equipment, and the method comprises the steps: synchronously carrying out the image collection through a six-eye camera array, and adding a timestamp to each video frame image; performing real-time feature extraction on the video frame image, and establishing a feature matching relationship in a view field overlapping region of adjacent cameras; based on the feature matching relationship, mapping each video frame image to a unified splicing coordinate system through projection transformation; performing splicing processing on the video frame images after projection transformation through multi-band fusion, and eliminating splicing traces at the boundary of the field of view; and reconstructing the panoramic frame images obtained after splicing processing according to a time sequence, and outputting a continuous panoramic video stream so as to realize real-time and seamless splicing and correction of six paths of high-definition video streams and finally output a global panoramic video stream with no visual fracture and consistent time and space.

The invention relates to the technical field of sealing performance testing, in particular to a breather valve performance online testing method for oil and gas storage and transportation, which comprises the following steps: acquiring a vibration signal of a breather valve body, a multi-band acoustic signal of a valve port and a total pressure signal in a storage tank; performing multi-scale complex wavelet decomposition, and constructing a time frequency-energy correlation feature tensor; the total pressure signal and the time frequency-energy correlation characteristic tensor serve as a combined observation value and are input into a preset continuous Gaussian mixture hidden Markov model containing four hidden states of sealing, transient micro-leakage, continuous leakage and full-amount opening, and the posterior probability is calculated; and calculating to obtain a real-time leakage rate. According to the method, the opening pressure can be accurately determined, the real-time leakage rate can be quantitatively calculated after the leakage state is recognized, comprehensive and accurate quantitative online evaluation of core performance parameters of the breather valve is achieved, and the multi-source information fusion degree and the anti-interference capacity are improved.

The invention discloses a duct grouting fullness detection method and device, and relates to the technical field of duct grouting fullness detection.The duct grouting fullness detection method comprises the following steps that an ultrasonic probe is arranged at an inlet of a duct and transmits an ultrasonic signal, and a receiver is arranged at an outlet of the duct and used for receiving reflection and transmission signals and collecting ultrasonic propagation data in the duct; and performing frequency decomposition on the acquired signals, and analyzing energy attenuation conditions of the signals in different frequency bands by using penetration characteristics of ultrasonic waves with different frequencies. According to the method, multi-band ultrasonic detection, self-adaptive signal compensation and machine learning technologies are combined, so that the accuracy and robustness of duct grouting fullness detection are remarkably improved. Multi-band detection covers different depths, and an adaptive compensation algorithm maintains signal stability and reduces misjudgment. The machine learning optimizes data fusion, ensures that the system adapts to different construction conditions and outputs stable results, and the generated grouting map provides clear visualization to help engineers to quickly identify and maintain defect areas.

The invention relates to the technical field of water treatment equipment, in particular to an ultrasonic water treatment equipment control method and system based on variable-frequency vibration waves. According to the method, based on preset fluid working condition parameters, ultrasonic frequency conversion vibration wave signals covering multiple frequency bands are dynamically generated, and a vibrator array is driven to generate a composite sound field; a cavitation effect and an activation effect are synchronously excited in a fluid medium through variable-frequency vibration wave signals, so that physical form depolymerization and surface charge distribution change of scale forming substances occur; a shearing effect is formed on a fluid-pipe wall boundary layer, an attached state biological membrane structure is stripped, and the microscopic binding force of a crystallized scale body is loosened; monitoring the dispersion degree of scale-forming substances in the fluid and the state of a boundary layer, and adjusting the frequency band combination and energy distribution of variable-frequency vibration waves to maintain scale inhibition; and continuously optimizing the frequency conversion strategy and the sound field intensity according to the feedback data of the scale inhibition maintenance state. Through intelligent multi-band frequency conversion control of the ultrasonic water treatment equipment, efficient and environment-friendly water treatment and scale prevention effects are realized.

The invention relates to the technical field of unmanned aerial vehicle signal processing, and discloses an unmanned aerial vehicle countering multiband radar early warning system, which comprises a multiband radar detection module, an echo data processing module, a target identification and positioning module and an early warning information generation module. The multi-band radar detection module emits radar waves of different frequency bands to obtain echo data, the echo data processing module calculates the difference degree and the comprehensive difference coefficient for target identification, the target identification and positioning module determines the position of the unmanned aerial vehicle, and the early warning information generation module issues early warning. The method has the advantages that accuracy and reliability are improved through multi-frequency-band detection, targets are accurately recognized and positioned, threat levels can be evaluated, interference resistance, clutter suppression and environment self-adaption capacity are achieved, multiple targets can be distinguished and tracked, the defects of an existing unmanned aerial vehicle monitoring technology are effectively overcome, powerful support is provided for unmanned aerial vehicle countering, and the method is worthy of popularization and application. And public safety and key area stability are ensured.

The invention relates to a detection-interference integrated unmanned aerial vehicle electromagnetic interference device, which belongs to the technical field of electronic countermeasure, and comprises an integrated design of an antenna module, a radio frequency front end module, a digital signal processing module and a main control module, the radio frequency front-end module comprises a detection receiving channel and an interference transmitting channel to process signal conversion, the digital signal processing module executes signal detection and analysis, intelligent interference decision and anti-self-interference signal processing based on a self-adaptive filtering algorithm, and the main control module is responsible for overall control and power supply. According to the invention, the technical problems of large response delay, complex system cooperation and incapability of continuous reconnaissance in the interference process of traditional anti-unmanned aerial vehicle equipment are solved. Real-time signal cancellation is achieved through the normalized least mean square algorithm, the reconnaissance capability is kept while interference is applied, the method has the advantages of being rapid in response, accurate in interference, low in power consumption and the like, and the countering efficiency is remarkably improved.

The invention relates to the technical field of unmanned aerial vehicle supervision, and discloses a multi-band multi-channel unmanned aerial vehicle RID signal analysis system. According to the system, RID signals of 2.4 GHz, 5.2 GHz and 5.8 GHz frequency bands are collected in parallel through a multi-frequency-band antenna group and a multi-channel radio frequency receiving module, and real-time analysis and algorithm scheduling of the RID signals are achieved through an FPGA + ARM heterogeneous processing unit. Four modules of multi-sensor space-time alignment and cross validation, lightweight national secret encryption and data integrity verification, self-adaptive scheduling based on reinforcement learning and unmanned aerial vehicle behavior digital twinning and intrusion early warning are integrated in algorithm, and a closed-loop processing flow from RID signal receiving, data calibration and secure transmission to intelligent research and judgment is formed. The method effectively solves the problems of incomplete RID signal coverage, low data reliability, weak safety protection, insufficient early warning capability and the like in the prior art, has the advantages of high analysis precision, good safety, high resource utilization rate, accurate early warning and the like, and is suitable for low-altitude supervision scenes such as urban security and protection, border management and control and the like.

The invention relates to the technical field of laser spectrum gas detection, and particularly discloses a TDLAS (tunable diode laser absorption spectroscopy) double-gas concentration synchronous calibration and decoupling method in the presence of spectrum aliasing interference, and the method comprises the following steps: acquiring a multi-band harmonic signal subjected to adaptive optimization while acquiring environmental parameters; an optimal frequency band signal is determined based on the signal quality index; and calculating a spectral aliasing coefficient according to the characteristics of the optimal frequency band signal, dynamically adjusting operation parameters of a search algorithm based on a numerical value interval in which the spectral aliasing coefficient is located, and determining an initial range of dual-gas concentration in a search space. According to the method, the improved genetic algorithm based on the spectral aliasing coefficient dynamic adjustment search strategy is combined with the incremental support vector regression model, stage processing from coarse calibration to fine decoupling is achieved, and the calculation efficiency and the search precision can be automatically balanced when the spectral aliasing degree changes; and online correction is carried out on the model in combination with aging characteristics.

The invention relates to an aluminum pipe local conduction regulation and control method, system and device based on dynamic electromagnetic field modulation and a medium, and the method comprises the steps: driving an electromagnetic coupling array to scan a target conduction region of an aluminum pipe, so as to construct a three-dimensional dynamic electromagnetic model; analyzing and generating a multi-band excitation parameter combination in a bandwidth constraint range according to the target conductivity gradient parameter; the method comprises the following steps: driving an electromagnetic coupling array by a multi-band excitation parameter combination, collecting an electromagnetic response spectrum of a target conductive area in real time, extracting an eddy current characteristic component set, calculating an obtained phase compensation amount, and dynamically adjusting an excitation phase difference and a power ratio of the electromagnetic coupling array to form a controllable standing wave interference field; and solving the Lyapunov function gradient difference between the node distribution characteristics of the standing wave interference field and the predicted value of the three-dimensional dynamic electromagnetic model so as to iteratively update the multi-band excitation parameter combination. According to the invention, high-precision dynamic regulation and control of the conductivity gradient of the aluminum tube are realized, the energy consumption is effectively reduced, and the stability of a standing wave interference field is enhanced.

The invention relates to the technical field of radio frequency power matching, and discloses a direct-current radio frequency hybrid high-power network matching optimization method. The method comprises the following steps: collecting current fluctuation data of a direct-current power supply module and power reflection data of a radio-frequency emission module, and generating a hybrid network impedance characteristic set; calling a power grid topology analysis engine to analyze the set to obtain an impedance track characteristic matrix; performing dynamic trajectory optimization on the matrix based on a preset frequency domain stability constraint rule to generate corrected impedance trajectory distribution; fusing the corrected track distribution and the radio frequency load dynamic response data, and constructing multi-band matching topological feature representation; performing parameter decoupling on the topological feature representation through a nonlinear matching mapping engine to generate an optimal matching parameter configuration table; and finally adjusting the voltage stabilization coefficient of the DC power supply module and the tuning capacitance value of the radio frequency emission module according to the configuration table. According to the method, efficient matching optimization of the hybrid network is realized, and the stability and adaptability of system operation are improved.

The invention provides a radar signal depth feature extraction method and system based on adversarial sample defense, electronic equipment and a storage medium, and relates to the technical field of radar signal processing.The radar signal depth feature extraction method comprises the steps that a spacecraft synthetic aperture radar original echo signal is collected and converted into a time-frequency feature map, and intra-pulse and inter-pulse features are extracted in parallel to generate a combined matrix; receiving a deception jamming signal by using a polarization radar group, generating a signal data body without polarization influence through complex coherent superposition, inputting the deception jamming signal and the signal data body into a feature decoupling adversarial network, and separating bullet micro-motion target feature data by means of mutual information maximization constraint; and finally, inputting into a multi-scale local attention module to extract multi-band characteristic components, performing adaptive weight coefficient fusion according to power entropy, performing polarization channel energy correction, and outputting anti-interference fingerprint characteristics with micro-Doppler characteristic enhancement, so that anti-interference processing of the spacecraft synthetic aperture radar signals can be realized. And warhead target anti-interference fingerprint features with micro-Doppler feature enhancement characteristics are effectively extracted.

The invention discloses an atmosphere and ocean integrated atmosphere temperature and humidity profile inversion method based on multiple sources and multiple frequency bands. The method comprises the following steps: S1, acquiring multi-source collaborative observation data, and preprocessing the acquired data; s2, constructing an integrated state vector and coupling forward model, and obtaining an integrated state vector X; s3, performing optimal estimation based on the preprocessed data and the integrated state vector X, and performing joint inversion to realize integrated inversion solution; and S4, outputting an inversion result and theoretical uncertainty output. According to the method, integrated cooperative inversion is carried out through a physical model and an optimal estimation theory, and the inversion precision of the atmosphere temperature and humidity profile in the clear sky and in the presence of clouds, especially in the air above the ocean, is remarkably improved.

The invention relates to the technical field of fan early warning, in particular to a fan intelligent early warning method and system based on a self-adaptive scheme and computer equipment. Multi-frequency-band heterogeneous data are collected in real time through multiple sensors, and four-dimensional tensor data are constructed. And carrying out single-factor evaluation on the environmental risk and the fan state risk. And fusing the two types of risks by using a double-layer fusion mechanism to obtain a fusion risk value. And setting different risk probability early warning thresholds according to fan operation requirements, comparing the fused risk value with the different risk probability early warning thresholds, and judging the state of the fan. And once the risk value exceeds the threshold value, identifying the high-risk data cluster, associating the fault mode library to determine a potential risk mode, and triggering a corresponding early warning signal so as to timely process and ensure the safe operation of the fan. The real-time and accurate early warning of the potential risk of the fan is realized, and the safety and reliability of the operation of the fan are improved.

Radiating elements comprise a first dipole radiator that includes a first dipole arm and a second dipole arm, a second dipole radiator that includes a third dipole arm and a fourth dipole arm and first through fourth electromagnetic bandgap structures that are coupled to distal end portions of the respective first through fourth dipole arms.

The invention provides an acoustic emission ore pulp granularity online detection system and method based on a Hertz collision mode, and belongs to the technical field of ore dressing process monitoring and control. The system comprises an ore pulp bypass circulation module, a particle size calculation module and a particle size measurement control module. A built-in acoustic emission sensor is used for collecting acoustic emission signals generated by Hertz elastic collision between signal ore pulp particles and a probe; multi-band energy features and time domain features are extracted in combination with wavelet packet decomposition, and a fusion feature vector is constructed by fusing ore pulp flow velocity and density information; the fusion feature vector is input into a BP neural network model after dimension reduction processing, and the proportion of particles with the particle size smaller than a set threshold value in the ore pulp is predicted online. Full-process management of sampling, preparing, measuring and liquid discharging is achieved through automatic control, and the system has the advantages of being high in measuring precision and automation degree, low in cost, high in anti-interference capacity and the like, is suitable for continuous online monitoring of the ore pulp granularity on the ore dressing site and provides data support for flotation process optimization.

The invention discloses a millimeter wave electrocardiogram reconstruction system and method based on adaptive MODWT and CNN-BiLSTM-CA, and the method comprises the steps: collecting a tiny phase displacement signal of a target thoracic cavity region, and carrying out the multi-band decomposition and key component adaptive screening of an original signal through combining with a multi-scale stationary wavelet decomposition algorithm; and introducing a channel attention mechanism to enhance key information representation, inputting a reconstruction signal into a deep learning model combining a convolutional neural network and a bidirectional long-short term memory network, completing time sequence modeling and nonlinear mapping, and outputting a reconstruction waveform highly consistent with a standard electrocardiogram. According to the method, the signal reduction capacity under the complex interference condition is remarkably improved, high-precision and privacy-friendly remote physiological signal monitoring can be achieved under the condition of not depending on a lead electrode, and the method is superior to a traditional baseline model in the aspects of waveform reduction precision, signal time sequence consistency, model generalization capacity and the like; the method is suitable for various application scenes such as intelligent medical treatment.

The invention discloses an anti-unmanned aerial vehicle monitoring and scheduling method with adaptive frequency band identification, relates to the technical field of anti-unmanned aerial vehicle monitoring and scheduling, and is used for solving the problem of poor frequency band identification and interference optimization. According to the method, a closed-loop mechanism with linkage of radar echo analysis, frequency band efficiency evaluation and monitoring scheduling is constructed, frequency band efficiency characteristics of an unmanned aerial vehicle target are extracted through multi-frequency-band monitoring data, a recommended tracking frequency band and a candidate countering frequency band are dynamically identified, and a scheduling reference scheme is generated in combination with frequency spectrum occupation and protected frequency band information. A quantitative basis is provided for frequency band selection and power configuration of the interference equipment; meanwhile, the frequency band weight and the recognition rule are continuously optimized based on monitoring operation feedback, fine judgment of the unmanned aerial vehicle signal and the external electromagnetic interference source is achieved, and the unmanned aerial vehicle wave band recognition accuracy, the scheduling reference reliability and the operation stability of the system in the complex electromagnetic environment are improved.

The invention relates to the technical field of aero-engine nondestructive testing, and discloses a method for detecting defects and thickness of a surface coating of an aero-engine blade. The invention designs a novel acoustic impedance sensor special for a blade coating, the novel acoustic impedance sensor comprises a plurality of independently controlled transduction units, each transduction unit has multi-band detection capability, main resonant frequencies of different transduction units are configured in a differentiated manner, and during detection, the novel acoustic impedance sensor is coupled to the surface of a blade; the material state is reversely deduced by measuring the energy absorption spectrum of broadband sound waves in the coating, and the blade surface coating defect and thickness detection is achieved.

The invention relates to the technical field of target detection and identification, and discloses a low-altitude target identification system and method combined with multi-band signal processing. Comprising the steps of establishing a cross-frequency implicit vector model and constraining a geometric scale, a scattering center and rotor harmonic waves through synchronous acquisition of an L-band radar, a Ku-band radar and a millimeter-wave radar, and realizing unified characterization of multi-frequency signals; receiving a global satellite navigation system reflection signal, communication channel state information or a very high frequency / ultrahigh frequency passive radar signal to form prior discrimination, and triggering high-frequency radar short-time imaging; carrying out propagation correction on millimeter wave, terahertz and infrared signals in combination with a meteorological profile and generating an environment label; determining a sampling window by using the region of interest and rotor phase prediction, and optimizing a residence strategy; harmonic waves are extracted from radar and acoustic signals, robust pairing is carried out, and a cross-domain consistency score output category is calculated. The method realizes multi-frequency multi-source cooperative processing, has environment self-adaption and closed-loop feedback capabilities, and can improve the precision and stability of low-altitude target identification.

The invention provides a broadband carrier multi-band interference suppression system and method, and relates to the technical field of interference suppression, and the method comprises the steps: carrying out the frequency domain analysis of a received broadband carrier signal when receiving a 5G new carrier signal; determining an interference dominant frequency band and an interference hybrid frequency band at the frequency point position, and determining a multi-domain control instruction when the inter-frequency interference of the broadband carrier multi-band interference is suppressed according to the interference dominant frequency band and the interference hybrid frequency band; obtaining a frequency band interference-to-signal ratio between a target signal component and an interference signal component of a 5G new carrier signal in the broadband carrier signal, and carrying out fusion alignment on the frequency band interference-to-signal ratio and the multi-domain control instruction to obtain a co-location interference path when the broadband carrier signal is propagated in a receiving channel; determining an interference amplitude limiting value when interference exists in the receiving channel according to the co-location interference path; and cancelling the interference amplitude limiting value from the received signal. According to the method and the device, the broadband carrier multi-band interference can be dynamically suppressed in a complex multi-band interference scene, so that the signal transmission reliability of broadband carrier communication is improved.

The invention discloses a DP-MZM-based reconfigurable mixer with phase shift and image rejection functions, and belongs to the field of microwave photon signal processing. By adjusting an input radio frequency signal and a direct current bias voltage of the DP-MZM1, four different LO frequency doubling and mixing functions can be realized. By controlling the angle alpha between the polarization direction of the polarization analyzer and one axis of the modulator, the phase of the generated signal can be flexibly tuned in the range of 0-360 degrees. When combined with the optical frequency comb, the multi-channel multi-band frequency conversion system can be expanded into a multi-channel multi-band frequency conversion system with independent phase tuning capability by utilizing the channel switching and frequency slot selection functions of the wavelength selection switch, and parallel output of various frequency mixing results can be realized. By adjusting the phase difference between the two-channel output signals, I / Q mixing, double-balanced mixing and image rejection mixing can be configured. The scheme is not influenced by direct current bias drift, the system complexity is reduced, and the frequency conversion efficiency is improved.

The invention relates to the technical field of oil sludge resource regeneration, and discloses a water oil sludge resource regeneration device based on a composite ultrasonic field and application. The device comprises an oil sludge parameter acquisition module, a resonant frequency analysis module, a sound field coupling control module, a phase shift interference analysis module and a separation strengthening execution module. The oil sludge parameter acquisition module acquires a rheological characteristic data set of the oil-containing sludge in real time; the resonance frequency analysis module generates a dual-target resonance frequency parameter based on the data set; the sound field coupling control module drives the piezoelectric transducer array to generate a focused ultrasonic field, and a sound field coupling model is constructed; the phase shift interference analysis module corrects the phase offset of the model and outputs a multi-band sound energy injection sequence; and the separation strengthening execution module regulates and controls the rotating speed gradient of the mechanical centrifugal unit, triggers membrane stack pulse backwashing, and finally generates regenerated base oil and a purified water phase product. According to the device, efficient regeneration of water-oil sludge resources is realized through cooperation of multiple modules.

The invention relates to the technical field of GIS partial discharge high-precision three-dimensional positioning, and discloses a multi-stage iteration GIS partial discharge high-precision three-dimensional positioning method, and the technical scheme is characterized in that S1, an electromagnetic simulation model is constructed based on a GIS equipment structure, and the installation position of an ultrahigh frequency sensor is optimized through electromagnetic simulation; s2, performing wide-band adaptive sub-band reconstruction and multi-resolution feature enhancement processing on the acquired signals; s3, calculating three-dimensional focusing energy distribution by adopting a multi-band time inversion method, and extracting candidate discharge positions; s4, screening candidate positions; s5, performing multi-stage hybrid optimization on the screening result to obtain refined three-dimensional positioning coordinates; and S6, outputting a three-dimensional positioning result, and performing performance evaluation based on a confidence index. According to the method, a time delay consistency screening mechanism is introduced, false candidate points which do not conform to an actual signal propagation rule are effectively eliminated, and the accuracy and reliability of a positioning result are remarkably improved.

The invention discloses a cable trench fireproof cover plate performance detection device and method based on multi-band electromagnetic waves. The device comprises a microwave detection module, a terahertz imaging module, a high-precision two-dimensional mechanical scanning platform, a synchronous control and data fusion unit and a comprehensive data analysis platform. The microwave module is used for transmitting and receiving 1-10GHz electromagnetic waves to realize deep structure detection; the terahertz module works at a frequency band of 0.1-3 THz and is used for acquiring near-surface time-domain spectral information. And the scanning platform drives the modules to perform two-dimensional rasterization scanning on the surface of the cover plate. And the synchronous control and data fusion unit coordinates the time sequence action of each module to ensure the time-space consistency of data acquisition. And the comprehensive data analysis platform performs fusion processing on the multi-source data through an inversion and imaging algorithm to generate a comprehensive evaluation report covering internal macroscopic defects, near-surface microdefects and coating thickness. According to the invention, through collaborative integration of microwave and terahertz technologies, multi-scale and integrated nondestructive testing and performance evaluation of the fireproof cover plate from a deep layer to a surface layer are realized.