4002 results about "Electromagnetic interference" patented technology

The invention discloses a power transmission line connection fitting fault detection method based on acoustics and electromagnetic induction, and belongs to the technical field of intelligent inspection and nondestructive detection of power transmission lines. A multi-mode sensor is carried by an unmanned aerial vehicle, ultrasonic wave, vibration, images and power frequency electromagnetic field data are synchronously collected, and a multi-dimensional original data set is constructed. Signal quality is improved by adopting wavelet noise reduction, beam forming and sound image fusion technologies, and flight vibration and electromagnetic interference are effectively suppressed by combining an adaptive filtering algorithm and a physical shielding structure. And acoustic, image and electromagnetic characteristics are extracted and normalized and fused, a dynamic threshold reference library is established, and intelligent grading discrimination of abnormity, defects and faults is realized through multi-stage early warning logic. A detection result automatically generates a report and is mapped to a three-dimensional line model, and operation and maintenance system linkage is supported. According to the method, synchronous identification of surface and internal defects is realized, the anti-interference capability is high, the detection accuracy is high, the inspection efficiency and safety are remarkably improved, and the method is suitable for intelligent operation and maintenance of the high-voltage transmission line.

The invention discloses an intelligent cable fault accurate positioning and early warning method and system, and the method comprises the steps: collecting the temperature gradient, strain distribution and partial discharge signals of the whole length of a cable in real time through a distributed optical fiber sensing network, and generating a multi-dimensional feature matrix of the operation state of the cable; based on the multi-dimensional feature matrix, outputting a preliminary fault positioning coordinate; generating corrected fault coordinates according to the topological structure data of the cable laying environment and the electromagnetic interference distribution diagram; historical fault data, real-time operation parameters and the corrected fault coordinates are fused, and a fault risk thermodynamic diagram in a future preset duration is output; and based on the fault risk thermodynamic diagram and real-time monitoring data, generating fault first-aid repair information by using a dynamic priority algorithm, synchronously triggering an early warning signal, and visually displaying a fault positioning result and a risk area in a three-dimensional geographic information system. According to the embodiment of the invention, rapid positioning, accurate early warning and intelligent disposal of the cable fault can be realized.

The invention relates to the technical field of anti-electromagnetic interference, in particular to an anti-electromagnetic interference method for a flywheel energy storage system of a data center, which comprises the following steps: acquiring change rate data of the rotating speed and the angular speed of a flywheel, judging the attribution of a disturbance interval, recording change characteristics, extracting an interference identifier, comparing the interference identifier with impedance change, and generating a switching node. Frequency response and reflection coefficient characteristics of the filtering unit are detected, a coupling channel generation label is identified, and output fluctuation is evaluated to generate an anti-interference capability state label. According to the method, the surface resistivity of the shielding layer is dynamically switched according to the comparison result of the specific interference triggering identification bit and the signal link impedance change state in each disturbance stage through classification judgment and correlation marking of inertial disturbance, so that the effect of suppressing electromagnetic interference in real time is optimized; the influence degree of electromagnetic interference can be dynamically evaluated in the system operation process, and the adaptability of the energy storage system to the electromagnetic interference is judged and adjusted in real time.

The invention provides an unmanned aerial vehicle high-precision autonomous navigation method and system based on GNSS and IMU deep fusion, and aims to solve the problems of insufficient navigation precision and poor robustness in a complex electromagnetic environment. Through a tight coupling architecture, GNSS original observed quantity and IMU pre-integration results are jointly modeled in an observation layer, and multi-source constraints are introduced in combination with factor graph optimization, so that the positioning precision and consistency in weak signal and shielding scenes are remarkably improved. For abnormal observation, a robust kernel function is adopted to dynamically adjust the weight, and the influence of electromagnetic interference and a multipath effect is effectively inhibited. Meanwhile, navigation calculation and model prediction control MPC are combined, and sub-meter hovering and high-precision trajectory tracking are achieved. According to the method, in high-voltage transmission line inspection, dependence on a high-cost sensor is reduced, the engineering application value is high, the method can be widely applied to the fields of electric power inspection, disaster emergency, infrastructure monitoring and the like, and reliable technical support is provided for high-precision autonomous navigation of the unmanned aerial vehicle in a complex environment.

The invention discloses a power grid equipment state sensing driving dynamic response method based on the Internet of Things technology, and relates to the technical field of power system automation and informatization, and the method comprises the following steps: S001, collecting original multi-dimensional state signals of a plurality of sensors deployed in a power grid equipment state sensing channel, constructing an electromagnetic disturbance recognition model, and carrying out the recognition of the original multi-dimensional state signals; frequency domain and time domain feature extraction is carried out on the signals, and a feature comparison parameter set used for distinguishing electromagnetic interference and real faults is generated. Frequency domain and time domain features are extracted through an electromagnetic disturbance recognition model, dynamic threshold judgment and response strategy adjustment are achieved in combination with multi-source sensing data, interference and faults can be accurately distinguished, early warning and protection logic can be corrected in real time, protection actions can be accurately triggered, closed-loop control is achieved, the delayed fault tolerance and multi-source verification capacity is achieved, and the method is suitable for large-scale popularization and application. The false operation rate and the false stop risk are effectively reduced, and the intelligence, the safety and the stability of power grid operation are improved.

The invention discloses an information acquisition and transmission system of track control equipment, which relates to the technical field of track traffic intelligent monitoring and comprises an intelligent sensing terminal, an edge intelligent analysis node, a safety communication module, a central control platform, a digital twin diagnosis center and a predictive maintenance engine. According to the invention, the intelligent sensing terminal integrates various sensors, adopts a permalloy shielding cavity to isolate external electromagnetic interference, is equipped with a three-stage lightning protection circuit to realize microsecond-stage lightning surge protection, can stably collect parameters of track control equipment in a severe environment, is internally provided with a lightweight LSTM model, carries out preliminary filtering analysis on original data, and is used for monitoring the parameters of the track control equipment. The device operation state can be dynamically identified, the sampling strategy can be adjusted, the basic sampling frequency is maintained in the stable state to reduce power consumption, the sampling frequency is improved by 10 times and the sensor gain is enhanced in the early warning or emergency state, all analysis decisions are completed at the local millisecond level without depending on the cloud, and the real-time performance and accuracy of data processing are effectively improved.

The invention relates to the technical field of unmanned aerial vehicle positioning, in particular to an unmanned aerial vehicle positioning method and system combining environment characteristics. According to the technical scheme, the method comprises the steps that multi-modal data of the environment where the unmanned aerial vehicle is located are collected through a multi-source heterogeneous sensor, and the multi-modal data comprise GNSS signal data, visual image data, laser radar point cloud data, inertia measurement data and electromagnetic interference monitoring data; and carrying out cooperative processing on the multi-modal data by utilizing the fusion deep learning model. A comprehensive basis is provided for subsequent processing through multi-source data collection, data quality and feature matching reliability are improved through fusion processing, timely and accurate positioning is guaranteed through real-time calculation, safe and efficient flight is achieved through a decision-making model based on accurate positioning, and the flight speed is high. The method not only solves the traditional technical problems of signal shielding, interference, dynamic interferent influence and contradiction between real-time performance and precision in a complex environment, but also shows excellent positioning stability and adaptability in various complex scenes.

The invention relates to the technical field of electrical equipment detection, and discloses an electrical equipment real-time state live detection method and system, and the system comprises a non-contact multi-source sensing array, an edge calculation unit, a high-frequency pulse excitation module, a self-adaptive installation structure, an intelligent diagnosis platform, and a self-energy-taking power supply unit. When electrical equipment state live-line detection is carried out, infrared thermodynamic characteristics, ultraviolet corona intensity and ultrasonic discharge signals are fused and collected through a non-contact multi-source sensing array, multi-parameter real-time sensing under the live-line condition is achieved, the problem of signal distortion caused by electromagnetic interference in traditional detection is solved, and the accuracy of state parameter extraction is improved; and meanwhile, the multi-dimensional feature data is subjected to standardization processing in combination with an edge calculation unit, so that the system can eliminate interference of environmental factors on detection results, the consistency of evaluation results under different working conditions is guaranteed, and state diagnosis errors are reduced.

The invention relates to the technical field of narrow-band filters, and discloses an ultra-low power consumption narrow-band filter implementation method based on a digital phased array system, and the method comprises the following steps: S1, collecting input signal data, carrying out the adaptive preprocessing, and generating preprocessed signal data; s2, performing digital beam forming processing based on the preprocessed signal data to generate digital beam forming data; s3, performing narrowband filtering parameter matching processing according to the digital beam forming data to generate narrowband filtering parameter data; in the narrowband filtering processing process, disturbance of environmental electromagnetic interference to a target signal is identified and eliminated in real time through adaptive noise suppression and a multi-dimensional signal preprocessing mechanism, so that the system can guarantee the pointing precision of digital beam forming, the pointing offset problem in the space signal capturing process is avoided, the accuracy of narrowband signal extraction is improved, and the accuracy of narrowband signal extraction is improved. And the reliability of filtering output and the signal fidelity are enhanced.

The invention discloses an unmanned aerial vehicle intrusion real-time alarm and countering guidance system based on RID information. The system comprises a multi-source information acquisition and fusion module, an intrusion detection and threat evaluation module, a real-time alarm and countering strategy generation module, a feedback evaluation and strategy iteration module, a signal loss prediction and compensation module, a comprehensive processing terminal module and the like. The system establishes a three-dimensional geofence model by analyzing remote identification information of the unmanned aerial vehicle and fusing radar, photoelectric, electromagnetic and other multi-source data, and performs dynamic judgment and multi-factor threat grading on a target intrusion state. Multi-mode alarm is automatically triggered according to the threat level, and a hierarchical countering scheme from broadcast alarm and electromagnetic interference to physical capture is generated; and when the RID signal is lost, the system realizes continuous tracking and state recovery of the target by using a motion prediction and probability association algorithm.

The invention discloses a high-voltage circuit breaker arcing monitoring system and method, and relates to the technical field of power equipment operation state detection, and the method comprises the following steps: S1, synchronously collecting arcing spectral signals and electromagnetic interference vector data under a unified time reference, and carrying out primary differential processing to generate stable base plane signals; s2, inputting the stable base plane signal into the interference identification model, generating a multi-dimensional spectrogram through time-frequency mapping, extracting an interference time sequence boundary, and outputting an interference weight matrix; the arcing monitoring method based on spectrum and electromagnetic signal synchronous acquisition is constructed, interference identification, signal purification, energy analysis and control instruction generation are fused, parameter self-optimization is realized through closed-loop feedback, the arcing identification accuracy and the arc quenching response efficiency are effectively improved, and the arcing monitoring method is suitable for large-scale popularization and application. And the operation safety and the intelligent level of the circuit breaker in a strong interference environment are enhanced.

The invention provides an electrical equipment remote maintenance guidance method and system. The method comprises the following steps: capturing an aperiodic torque waveform and a magnetic field gradient abnormal signal by deploying a torque fluctuation sensor and a magnetoresistive sensor; performing multi-scale frequency band division on the non-periodic torque waveform, screening out a transient high-frequency component in a start-stop stage of equipment, and separating out a magnetic field polarity reversal characteristic from a magnetic field gradient abnormal signal; performing cross-domain matching on the occurrence time of the transient high-frequency component and the spatial orientation of the magnetic field polarity reversal feature to generate a mixed feature mark; calculating a frequency band overlapping degree based on the time-frequency energy distribution marked by the mixed features and generating a coherence map; and matching a fault historical case library according to the coherence map, and outputting a maintenance strategy set aiming at the rotating shaft dynamic unbalance and electromagnetic interference superposition fault. According to the invention, through fusion of torque fluctuation and magnetic field distortion collaborative analysis, the precision of mechanical and electromagnetic composite fault diagnosis of the rotating shaft is improved.

The invention belongs to the technical field of geophysical monitoring, and relates to an electromagnetic interference detection method for earthquake monitoring, which comprises the following steps: deploying a multi-dimensional electromagnetic field sensing unit and an earthquake signal acquisition unit and realizing high-precision synchronization; synchronously acquiring multi-dimensional electromagnetic field and seismic physical signal data; performing multi-feature and noise feature extraction on the two; inputting the features into a pre-trained machine learning / deep learning model for identification, and outputting information such as interference type, intensity and azimuth angle; and carrying out influence evaluation and quality marking on the seismic data according to the output, and selectively inhibiting or compensating. Through the above scheme, multi-dimensional perception and characterization, high-precision synchronization and correlation analysis, intelligent identification and spatial positioning are realized, and the reliability and accuracy of earthquake monitoring data are significantly improved.

The invention relates to the field of sensors, and discloses an anti-electromagnetic interference dynamic compensation method for a gas sensor of power equipment, which comprises the following steps: monitoring and collecting sensor data, uploading the sensor data to a central processing unit for data fusion, and carrying out volatility analysis on the fused sensor data, so as to obtain an anti-electromagnetic interference dynamic compensation result. The change relation of the fluctuation of the sensor data along with time is monitored in real time, and the fluctuation abnormal state of the sensor data is analyzed and detected by combining a fluctuation analysis result with real-time environmental parameters, so that the monitoring duration and the monitoring frequency of the sensor data are dynamically adjusted; analyzing the contribution degree of the electromagnetic interference to the error generated by the gas sensor, detecting whether the error interferes with the measurement state of the gas sensor, and correcting the gas concentration measurement value by using a temperature and humidity-gas response coupling correction algorithm of Kalman filtering to realize the dynamic compensation of the gas concentration measurement value. And the accuracy of the corrected gas concentration estimated value is improved.

The invention relates to the technical field of power converters, in particular to a power converter real-time fault diagnosis method and system based on edge calculation. According to the method, operation data, including electrical parameters, thermal parameters and the like, of the power converter are obtained firstly, aging and quality are ensured through synchronous filtering, limitation of a traditional single parameter is broken through, tiny abnormity and instantaneous fluctuation can be captured, and redundancy is avoided; according to the equipment structure, edge computing nodes are deployed near a data source, the transmission distance is shortened, delay is reduced, electromagnetic interference is avoided, accuracy is improved, resources with excellent computing power are matched, and local real-time monitoring is supported. Next, an edge computing node lightweight algorithm is used for localization analysis, normal data and abnormal data are quickly distinguished, identification time consumption does not need to be reduced by transmitting to a cloud end, it is ensured that abnormality is found immediately according to misjudgment and sensitivity improvement of a dynamic baseline, and finally, thermal radiation information is obtained in combination with abnormal data, and a fault is accurately positioned by associating a device structure and parameters. And refining to an element level to shorten the troubleshooting time, and analyzing the trend to realize predictive maintenance.

The invention relates to the technical field of electrical measurement, and discloses an electrical measurement instrument dynamic calibration error compensation method, which comprises the following steps: S1, multi-source data real-time acquisition: integrating a temperature sensor, a humidity sensor and an electromagnetic interference detection module in a measurement instrument, configuring voltage, current, frequency and other measurement channels, and carrying out multi-source data real-time acquisition at the frequency of not less than 100HZ; environmental parameters (temperature T, humidity H and electromagnetic interference intensity E) and measurement data (model characteristic parameters X1, X2,..., Xn such as voltage, current and frequency) are synchronously acquired. According to the electrical measuring instrument dynamic calibration error compensation method, through multi-source data real-time acquisition and composite error model construction, in combination with multiple linear regression and an improved BP neural network, environment and measurement signal changes are comprehensively captured, an error compensation value is accurately calculated, a measurement error can be effectively controlled within an extremely small range, and the error compensation accuracy is improved. Compared with a traditional method, the measurement precision is greatly improved.

The invention discloses a transformer substation intelligent patrol recognition algorithm optimization method based on multi-modal fusion, and belongs to the technical field of transformer substation patrol, and the method comprises the following steps: synchronously obtaining a visible light image, an infrared thermal imaging spectrum, an ultrasonic partial discharge signal and environmental parameters, and building a four-dimensional space-time calibration matrix; a dual-channel attention mechanism is adopted to realize multi-source data fusion, a spatial alignment channel and a feature enhancement channel are included, the spatial alignment channel realizes pixel-level registration of visible light and infrared images through affine transformation, and the feature enhancement channel utilizes a graph neural network to construct topological correlation mapping of acoustic, thermal and optical features; constructing a three-stage training architecture containing noise injection; and adding an adversarial generative network in a preprocessing layer to simulate rain fog and electromagnetic interference environments. According to the method, the identification threshold is updated online by deploying a sliding time window mechanism in an output layer, and the problems of poor feature extraction robustness and high false alarm rate of a traditional algorithm in complex environments such as strong electromagnetic fields and rain and fog are solved.

The invention relates to the technical field of wireless communication, in particular to a production line wireless communication system and method. The system comprises a multi-dimensional feature sensing module, an interference intelligent cognition and decision-making module, a communication opportunity decision-making module and a channel resource arrangement module. An expected action sequence, transient current features and spatial position topology of an interference source are collected through a multi-dimensional feature sensing module, and an interference source multi-dimensional feature set is generated through fusion; the interference intelligent cognition and decision-making module performs space-time spectrum joint modeling of an interference field based on the feature set, generates a workshop electromagnetic environment situation map, constructs a whole network link toughness map in parallel, and generates a conflict-free communication scheduling table through fusion analysis and multi-dimensional cost optimization; the communication opportunity decision module converts the dispatch table into an executable instruction; and the channel resource arrangement module executes the instruction and realizes closed-loop feedback. According to the method, the problem of communication uncertainty caused by industrial electromagnetic interference is solved, and reliable transmission of key services such as automatic guided vehicle scheduling and man-machine interaction is ensured.

The invention discloses an electrostatic induction and optical imaging principle-fused online monitoring device and method for wear particles of a water-lubricated bearing, and belongs to the field of state monitoring of mechanical equipment. The device comprises a square insulation detection cavity, a detection electrode array, an electromagnetic shielding shell, a high-speed optical imaging module and a signal processing unit, the square insulation detection cavity is installed in a bearing lubrication water loop. The detection electrode array is fixed to the outer wall of the cavity and used for capturing electrostatic signals generated when the abrasion particles pass through. The electromagnetic shielding shell wraps the detection cavity and is grounded through a wire to eliminate environmental electromagnetic interference. The high-speed optical imaging module integrates a high-magnification microscope lens and a CMOS sensor, is coaxially mounted with the detection cavity, and obtains the morphology characteristics of the wear particles in real time; and the signal processing unit performs multi-modal data fusion analysis on the electrostatic signal and the optical image. Through cooperative detection of electrostatic induction and optical imaging, the monitoring precision and reliability of the wear particles of the water-lubricated bearing are remarkably improved.

The invention provides a transformer substation unmanned aerial vehicle three-dimensional route real-time planning and autonomous obstacle avoidance system, and relates to the technical field of non-electrical variable control or adjustment systems. Through cooperative work of a navigation mode switching module and a near-field navigation control module, an electric field of equipment is used as a natural navigation beacon; and high-precision autonomous flight is realized in a strong electromagnetic interference area with RTK signal failure, and the dependence on external positioning is eliminated, so that the inspection blind area is eliminated. Meanwhile, a fusion environment map containing multi-physics field information is constructed, the value of observation points is scientifically quantified according to waypoint inspection efficiency indexes, and a path planning algorithm aims at optimizing a comprehensive target fusing energy consumption, risks and inspection efficiency. The design not only ensures that the unmanned aerial vehicle can safely get close to the core equipment, but also enables the planned route to be the most valuable path rather than the shortest path, and finally fundamentally improves the safety, the operation efficiency and the data validity of substation inspection.

The invention provides an anti-interference sound and vibration detection method and device, and relates to the field of sound and vibration detection. The method comprises the following steps: acquiring target special equipment and an equipment type corresponding to the target special equipment; according to the equipment type, acquiring a multi-channel high-sensitivity sensing array combination corresponding to the equipment type from a preset inspection method database; acquiring sound vibration signal data corresponding to the target special equipment based on the multi-channel high-sensitivity sensing array combination; performing modal decomposition on the sound vibration signal data by applying an improved empirical mode decomposition algorithm, eliminating pseudo-modal components and reconstructing effective modal signal data; and inputting the reconstructed effective modal signal data into a sound-vibration collaborative recognition model, and outputting a structural state recognition result of the target special equipment through the sound-vibration collaborative recognition model. According to the method and the device, the problem of low sound vibration detection accuracy of a traditional sound vibration detection technology when mechanical impact, fluid disturbance, electromagnetic interference or multi-source background noise is accompanied in the environment where the detected equipment is located is solved.

The invention discloses a driver controller detection system, which comprises an acquisition module, an acquisition module, a processing module, an identification module, a judgment module, an analysis module and a generation module, the acquisition module captures contact information and electromagnetic interference data of contacts in real time by means of a high-dynamic voltage sensor and a broadband EMC probe; the acquisition module is triggered by a locomotive signal and records dynamic working condition data; the processing module aligns the data, performs denoising and extracts fault parameters; the identification module scans the voltage waveform and judges the transient contact failure; the judgment module monitors EMC data and compares an instruction position, and judges misoperation; the analysis module analyzes fault association, judges a composite type and triggers an alarm; the generation module generates a detection report and a log. According to the system, a multi-dimensional monitoring network is constructed under a dynamic working condition, data reliability is guaranteed, faults are accurately identified, a compound fault source is positioned, and the safety and stability of locomotive operation are improved through risk grading early warning and automatic reporting.

The invention relates to a gas sensor environment anti-interference drift compensation method, system and equipment, and the method comprises the steps: collecting a mixed gas response signal in an environment, and obtaining an electromagnetic interference signal under the same timestamp; threshold truncation is carried out on spike pulses in the mixed gas response signals to obtain trend waveform signals caused by gas concentration changes, and denoising processing is carried out on the electromagnetic interference signals to obtain effective electromagnetic interference parameters; performing feature recognition on the effective electromagnetic interference parameters through a preset interference-response cooperative processing model to determine an interference mode and an interference intensity grade, synchronously analyzing the trend waveform signal to obtain a response feature curve of the target gas and the interference gas, and obtaining a drift compensation coefficient of the target gas; and carrying out collaborative optimization on the drift compensation coefficient through a preset interaction influence model to obtain a final compensation result so as to achieve the purpose of outputting a high-precision target gas concentration detection result.

The invention relates to the technical field of communication signal analysis, in particular to a communication signal analysis method and device, equipment and a storage medium. The method comprises the following steps: carrying out full-band signal continuous acquisition on a detection area, and extracting an original signal flow; performing potential electromagnetic interference detection and electromagnetic interference distribution marking on the original signal flow to obtain an interference source distribution diagram; dynamic interference suppression is carried out based on the interference source distribution map, real-time suppression parameter adjustment is carried out, and a calibration optimization signal flow is constructed; performing real-time intensity calculation on the calibration optimization signal flow, and constructing a regional signal intensity distribution model; and performing signal quality evaluation and real-time decision early warning based on the regional signal intensity distribution model. According to the method, the communication signal quality and stability of the area can be accurately and rapidly evaluated.

The invention provides a multi-source data fusion self-positioning method and system. The method comprises the following steps: acquiring GPS positioning data, visual image data and laser radar point cloud data of an unmanned aerial vehicle; carrying out noise reduction preprocessing on the GPS positioning data by adopting an unscented Kalman filtering algorithm; performing sensor joint calibration based on a visual image and a laser radar point cloud, and establishing a geometric mapping relation between a camera coordinate system and a world coordinate system by retrieving a preset high-precision tower ledger library and solving a PnP problem; inputting the image target detection data, the GPS state estimation value and the geometric mapping data into a pre-trained auto-encoder regression network; anti-interference potential features are extracted through an encoder of the network, and a target position estimation value of the target space position of the unmanned aerial vehicle is output through a regression head. According to the invention, the problem of positioning drift caused by strong electromagnetic interference and complex landform in electric power inspection is effectively solved.

The invention provides an integrated circuit chip electromagnetic interference intelligent suppression and shielding method and system, and relates to the technical field of integrated circuits, and the method comprises the steps: collecting chip electromagnetic interference data, and carrying out the time-frequency domain decomposition and feature extraction, so as to obtain an initial electromagnetic interference feature vector; calculating an electromagnetic interference threat index based on state space mapping and action space search, and further evaluating the electromagnetic interference situation and determining the minimum shielding strength; carrying out optimization design on the electromagnetic shielding structure by adopting a gradient-guided genetic algorithm to obtain an optimal shielding structure parameter; real-time electromagnetic interference data are adjusted according to the parameters, the suppression ratio is calculated, and iterative design is carried out by combining the suppression ratio optimization genetic algorithm. According to the invention, intelligent evaluation and dynamic suppression of electromagnetic interference are realized, and the accuracy and adaptability of shielding structure design are improved.

The invention provides a rapid wire falling control method for an overhead transmission cable inspection robot, and relates to the technical field of intelligent control, and the method comprises the steps: obtaining electromagnetic field intensity data monitored by an airborne electromagnetic sensor in real time according to a corrected wire falling path; according to the electromagnetic field intensity data, counteracting pose offset of the unmanned aerial vehicle and the working platform caused by electromagnetic interference in real time to obtain a control signal after the pose offset is counteracted; and driving the unmanned aerial vehicle and the working platform to execute a wire falling control action according to the corrected wire falling path and the control signal after the offset of the pose offset until the working platform realizes stable hovering positioning at a specified position of the target ground wire. According to the invention, automation and intelligence of power transmission cable inspection are improved.

The invention discloses a multi-layer protection cable resistant to an extreme environment, and belongs to the technical field of cables. The cable is of a seven-layer composite structure design and sequentially comprises a conductor, an insulating layer, a shielding layer, a buffer layer, a waterproof layer, a heat insulation layer and a protective outer layer from inside to outside, and the conductor is made of high-purity oxygen-free copper; the insulating layer is made of a polyimide material and has high temperature resistance, low temperature resistance and excellent insulating property; the shielding layer is composed of a tinned copper wire woven mesh and a high-permeability permalloy foil, and electromagnetic interference is effectively shielded; the buffer layer is made of an elastic rubber material to relieve mechanical stress; the waterproof layer adopts a nanoscale fluorosilicone resin coating and has excellent waterproof performance; the heat insulation layer is made of ceramic fibers and aerogel, and efficient heat insulation is provided; and the protective outer layer is made of a high-strength and corrosion-resistant polyether-ether-ketone (PEEK) material. The cable has excellent high temperature resistance, low temperature resistance, corrosion resistance and electromagnetic interference resistance, is suitable for extreme environments, and ensures stable transmission of electric power and signals under extreme conditions.

The invention relates to the technical field of ecological system service function evaluation. The invention relates to a frequency offset correction algorithm in HPLC (High Performance Liquid Chromatography) + HRF (High Radio Frequency) dual-mode communication. The method comprises the following steps: S1, collecting phase sequence data from an HPLC communication link, collecting frequency offset estimation data and corresponding confidence data from an HRF communication link, and adaptively adjusting a preset detection threshold value of the phase sequence data according to the confidence data; s2, performing pulse abnormal sample point detection and elimination on the phase sequence data according to the adjusted preset detection threshold value; according to the method, the detection threshold is dynamically adjusted through the confidence data, so that the anomaly detection process can be matched with the current interference environment in real time, the integrity of the phase sequence data is maintained, and the problem of insufficient adaptability of a fixed detection threshold in an electromagnetic interference dynamic change scene is solved; and a more reliable phase data basis is provided for subsequent interpolation compensation and frequency offset estimation, so that the frequency offset correction precision of the dual-mode communication system is improved.

The invention discloses a three-dimensional integrated packaging structure and a packaging process thereof. The three-dimensional integrated packaging structure comprises a flip or normal chip with a functional surface and an opposite back surface; the rewiring layer and the chip are vertically stacked and electrically connected with each other; electrically leading the rewiring layer out of the packaging structure; the stacking direction of the inductor and the chip is parallel to the thickness direction of the chip, the inductor and the chip, the rewiring layer and the lead-out structure are physically isolated through an insulating medium layer, the inductor is of a spiral, multi-ring layer overlapping or sectional winding structure, the inductor comprises a magnetic core, a spiral coil surrounding the surface of the magnetic core is formed through etching and electroplating processes, and the lead-out structure is arranged on the surface of the spiral coil. The spiral coil comprises a circuit A, a circuit B and a circuit C, and the magnetic core and the spiral coil are encapsulated by the insulating medium layer. The inductor and the chip are stacked in an inverted or normal mode, the three-dimensional structure saves space, reduces parasitic inductance, resistance and the like, signal transmission is stable, electromagnetic interference is small, and the three-dimensional structure is suitable for the chip packaging field of miniaturization, high integration and the like.