395 results about "Electric field sensor" patented technology

The invention discloses a cable life dynamic evaluation system based on multi-physics field coupling, and particularly relates to the field of industrial automation and control systems, which comprises a multi-physics field sensing module, a coupling analysis engine module, a dynamic life evaluation module, a digital twin interaction module and an environmental interference suppression module, through a distributed optical fiber temperature sensor, a capacitive electric field sensor and a magnetostrictive stress sensor, temperature, electric field, magnetic field and mechanical stress data of a cable are collected in real time, multi-physical field characteristics and a cable defect database are matched in real time by using a cross-scale dynamic association algorithm, a damage state is evaluated, and the cable defect detection accuracy is improved. A time sequence neural network architecture is adopted to predict the remaining life, model self-correction is achieved through digital twin comparison, interference is suppressed in combination with an environment-physical field coupling compensation matrix, sensing and evaluation of the health state of the cable, life prediction and continuous optimization of the model are achieved, and the efficiency of cable life evaluation is improved.

The invention discloses a thunder and lightning early warning method based on atmospheric electric field networking monitoring. The method comprises the following steps: collecting multi-point electric field intensity data in a region in real time through a high-density electric field sensor network, and constructing an electric field intensity distribution matrix; for the constructed electric field intensity distribution matrix, space-time evolution characteristics of lightning activities are extracted, and lightning occurrence probability distribution is generated; acquiring temperature, humidity and air pressure parameters from multi-source meteorological data, performing data fusion with the generated thunder and lightning occurrence probability distribution, and constructing a comprehensive environment characteristic data set; and for the constructed comprehensive environment characteristic data set, calculating a comprehensive risk index, and if the index exceeds a preset thunder and lightning triggering threshold, etc. According to the lightning early warning method, the distribution matrix is constructed through the high-density electric field network, the spatial-temporal characteristics are extracted to generate the initial probability, and the physical rationality and the environment false alarm resistance of early risk identification are remarkably improved through fusion with the multi-source meteorological data.

The application discloses a thunderstorm monitoring device and path planning method of unmanned aerial vehicle based on electric field and magnetic field detection. The device comprises a quadrature magnetic antenna array, a vertical differential electric field sensor, a signal processing module, a positioning algorithm module, a distance estimation module, an autonomous decision module, a GNSS module and an inertial measurement module. The quadrature magnetic antenna array is composed of two orthogonally arranged magnetic antennas, which are at a 45° angle with the flight direction of the unmanned aerial vehicle, and is used for receiving the horizontal magnetic field signal of lightning radiation. The vertical differential electric field sensor comprises two groups of upper and lower electrode plates and measures the differential value of the vertical electric field intensity. Through the cooperative measurement of the magnetic antenna array and the electric field sensor, the lightning azimuth (θ) is calculated by combining the magnetic field intensity ratio, and the quadrant is corrected by using the electric field polarity. Based on the magnetic field amplitude attenuation model and the waveform rise time correction factor, a distance estimation model is constructed. The autonomous decision module generates an approach path or an obstacle avoidance path according to the lightning azimuth and distance, and drives the flight control system to adjust the heading.

The invention discloses an electric field sensor-carrying unmanned aerial vehicle electricity testing platform and an electricity testing method, and relates to the technical field related to electricity testing, and the platform comprises an initialization unit which is used for calling electricity testing scene data and weather environment data according to an electricity testing task instruction to carry out the flight path planning of a multi-rotor unmanned aerial vehicle; the linkage acquisition unit is used for executing electric field signal acquisition; the alignment return unit is used for returning the mapped position attitude data and the electric field signal set to the edge calculation layer; a suppression unit for performing environmental interference suppression; and the discrimination unit is used for executing electricity verification correction discrimination of the electric field signal set and the mapped position attitude data and generating an electricity verification correction discrimination result. The technical problems that in the prior art, flight path planning is not scientific, electric field signal collection is prone to being interfered, data processing and judging efficiency is low, accuracy is poor, and electricity testing work efficiency and safety are poor are solved, and the technical effects of improving electric field signal processing accuracy, electricity testing work efficiency and safety are achieved.

The invention belongs to the field of data processing, and particularly relates to a high-voltage direct-current electric field intensity measuring method and a related device. In the device, an optical fiber direct-current electric field sensor at least comprises a signal processing unit, an optical fiber voltage sensing head, a fixed electrode and a rotating electrode. The method comprises the following steps: deploying a measuring device in a space to be measured; the rotating electrode is controlled to rotate at a constant speed, so that the center distance between the fixed electrode and the rotating electrode is periodically changed along with the rotating track; collecting an alternating current signal voltage generated by an alternating potential difference between the fixed electrode and the rotating electrode in a constant-speed rotating process through an optical fiber voltage sensing head; and performing numerical processing on the alternating current signal voltage through a signal processing unit to obtain a measured value of the high-voltage direct current electric field intensity, and optimizing the measured value in combination with a physical compensation model and a data driving compensation model. The method can realize the measurement of the high-voltage direct-current space electric field intensity, improve the measurement accuracy and expand the measurement range.

The invention discloses an error correction method and device for non-intrusive voltage differential measurement, a medium and a product, and relates to the technical field of voltage measurement, and the method is applied to a scene in which a differential electric field sensor array is arranged in a set range with a measured conductor as the center. Comprising the following steps: constructing an initial correction model based on a sensor distance and a measured conductor voltage; under the actual working condition, the initial correction model is processed through a least square method, and a correction model is obtained; when non-intrusive voltage differential measurement is carried out, the current measured conductor voltage and the sensor distance are obtained, and a correction coefficient is determined by adopting the correction model; and completing error correction of non-intrusive voltage differential measurement based on the correction coefficient. According to the invention, the complexity of an inversion algorithm and the special requirement on the spatial position of the sensor can be reduced.

The invention discloses an electricity testing measuring device for power equipment. The invention relates to the field of space electric field measurement, and solves the problems of unsafety and low anti-interference capability of an existing electricity testing scheme. The electric field sensor collects the electric field intensity in a non-contact manner, and the distance sensor synchronously collects the detection distance, so that a conventional contact type electroscope does not need to contact equipment through a telescopic insulating rod. The signal processing circuit preprocesses electric field intensity information and distance information respectively to obtain effective analog signals representing the electric field to be measured, and the defect that a traditional non-contact plate electrode sensor induces stray electric fields indifferentially is overcome. Besides, the judgment control circuit judges the electrification state according to the preset electric field threshold value corresponding to the current distance analog signal instead of a single fixed threshold value of a traditional device instead of adopting a fixed threshold value, the electric field distribution characteristics of equipment with different voltage grades are adapted, manual intervention is not needed, and personal safety is guaranteed. And the occurrence rate of production accidents caused by abnormal electrification of equipment is reduced.

The invention discloses an MEMS and TMR fused overhead line lightweight monitoring device, and the device comprises an annular shielding cover which sleeves a to-be-detected overhead conductor and is coaxial with the to-be-detected overhead conductor, and the side wall of the annular shielding cover is provided with a through hole; the sensing unit comprises at least two MEMS electric field sensors and at least two TMR magnetic field sensors and is used for detecting an electric field and a magnetic field generated by the overhead conductor to be detected; the analysis processing unit is used for receiving, processing and transmitting the signal generated by the sensing unit; and the power supply unit is arranged in the annular shielding cover and is electrically connected with the sensing unit and the analysis processing unit. The beneficial effect of the invention is that the coupling crosstalk phenomenon generated by an external electromagnetic field can be effectively suppressed. Moreover, the monitoring device is small in size, is convenient to install and deploy in a complex line environment, provides a stable hardware basis for precise inversion of voltage and current through structural cooperation, and provides reliable support for intelligent monitoring of an overhead line.

The invention relates to the technical field of electric field measurement, in particular to a non-contact electric field sensor design method and system, and the method comprises the steps: carrying out the electromagnetic analysis and shielding structure topological optimization based on the environment characteristics of a transformer substation, and generating mechanical design parameters; shielding structure parameters are formed through material selection and electrode optimization, a three-dimensional electromagnetic field simulation model is established, and multi-scene interference simulation and sensitivity verification are carried out; and configuring a temperature compensation circuit and optimizing circuit parameters, performing dynamic response analysis and material matching degree evaluation through a high-frequency material test platform, and finally generating sensor specification parameters. According to the method, the anti-interference performance, the measurement precision and the stability of the sensor are remarkably improved, and the method is suitable for high-precision electric field measurement in a complex electromagnetic environment.

The invention discloses a power frequency phase adaptive acquisition device, and relates to the technical field of electric power signal measurement, the device acquires electric field data at a gap through an electric field sensor integrated on an edge shell, calculates electric field intensity fluctuation, and generates interference diagnosis information in combination with a preset interference determination threshold value; when the interference diagnosis information shows that effective interference exists, the electric field intensity variable quantity is calculated, a mapping model is established based on a proportionality coefficient obtained through an experiment so as to obtain zero crossing point offset, and the sampling trigger moment of a zero crossing point detection module is corrected; the clock synchronization module calculates a phase difference by taking the corrected trigger moment as a reference, dynamically adjusts a calibration frequency by combining a phase difference threshold value, and outputs a synchronized system clock signal; and the control system takes the synchronized system clock signal as a trigger signal, collects power frequency phase data according to a power frequency period, and stores the power frequency phase data to a database through a transmission unit, thereby realizing high-precision power frequency phase collection.

The invention belongs to the technical field of high-power microwave effect tests in laboratories, and relates to a built-in conformal optical fiber electric field sensor array test system and method, and the method comprises the following steps: S1, preparing before implementation; s2, quick assembly and disassembly are carried out; s3, real-time measurement and closed loop are carried out; s4, a step of result confirmation and log uploading; s5, a step of preparing a next round of experiment; the technical scheme of the invention is mainly used for carrying out internal electric field distributed measurement on a fixed test body or a slide rail supported test body in a shielding cabin, a compact range or a GTEM room and other experimental environments; the system is composed of a conformal optical fiber electric field sensor array, an optical fiber link unit, a photoelectric integration module, a self-calibration unit, an energy source and an interface, can be assembled and disassembled within 5 min, can be repeatedly used for more than 100 times, remarkably reduces the operation cost of a laboratory, and provides a core test means for a high-precision, high-efficiency and low-cost anti-missile weapon HPM effect test.

The invention provides an electric field variation measuring method and system. The method comprises the following steps: installing a differential electric field sensor in an electric field variation to-be-measured area; collecting and preprocessing electric field change data of the electric field change quantity to-be-measured area based on a differential electric field sensor; based on the preprocessed electric field change data, an electric field change quantity distribution model is established, and a data analysis result is obtained; and generating an electric field variation monitoring report based on a data analysis result. The system comprises a differential electric field sensing module which is used for capturing an electric field change signal in an electric field change quantity to-be-measured area by adopting a differential electric field sensor; the high-precision data processing unit is used for receiving and preprocessing the electric field change signal to obtain electric field change data; the remote communication module is used for realizing real-time remote transmission of electric field change data by adopting a low-power wide area network technology or a wired communication mode; and the intelligent analysis platform is used for receiving the electric field change data, performing comprehensive analysis and generating an electric field change quantity monitoring report.

A system and method for characterizing matter, for example, soil organic content is disclosed. A radiation and electric field sensor measure sample properties before, during and after irradiation. Calibrations are developed relating those measurements to useful properties of matter, for example, soil density and organic content. As an example of an embodiment of the disclosed invention an instrument attachment for portable X-ray fluorescence instrumentation was prototyped enabling concurrent volumetric soil organic matter quantification. This primary prototype outperformed more expensive emerging visible-near infrared multivariate instrumentation using parsimonious soil specific simple linear regression (R2 ranged 0.85-0.97) enabling rapid, parallel, nondestructive, cost-effective acquisition of soil elemental concentrations together with organic content data.

The invention discloses a micro-nano electric field sensor, which comprises three electrodes including a cathode, an extraction electrode and a collector, the three electrodes are connected with an external control circuit through leads, and an insulating layer is arranged among the cathode, the extraction electrode and the collector and is used for separating the three electrodes so as to ensure the independence of an electric field and the accuracy of a signal. By means of the advanced nanometer manufacturing technology, the problems that in the traditional electric field sensor manufacturing process, cost is high, the period is long, and doping is prone to occurring can be solved, the performance of the electric field sensor can be effectively improved, the reliability and stability of the electric field sensor are improved, and the device meets the increasing technical requirements for miniaturization and integration.

The invention relates to the technical field of power equipment monitoring, and discloses an abnormal discharge electric field feature extraction method. The method comprises the following steps: standardizing and normalizing data acquired from a multi-channel electric field sensor array of a transformer substation to generate a standardized data stream; performing wavelet decomposition, adaptive threshold noise reduction and reconstruction on the basis of the stream to obtain a denoised signal; time domain statistics and frequency domain energy spectrum analysis are carried out on the signals, features are fused, and a joint feature vector is constructed; training a convolutional neural network classifier based on the vector; and updating a dynamic threshold rule according to the classifier output probability, and finally realizing real-time early warning and model feedback through GPU parallel computing. According to the method, the signal-to-noise ratio and the feature expression capability of the abnormal discharge signal can be effectively improved, and the detection accuracy, the real-time performance and the self-adaptive capability of the system are enhanced.

The invention relates to the technical field of power grid measurement, in particular to a miniaturized wireless self-powered alternating current electric field measurement method and system. Comprising the following steps: acquiring radio frequency energy in an electric field environment, and converting the radio frequency energy into direct current electric energy through a radio frequency energy acquisition system consisting of a microstrip antenna, a voltage doubling rectifying circuit and an energy management circuit; an alternating current electric field signal is collected through a differential dual-electrode sensor structure, and an electric field voltage signal is generated; amplifying the voltage signal through an instrument amplifier, and obtaining a digital signal of the electric field signal through an analog-to-digital conversion circuit; and processing and analyzing the alternating current electric field information according to the digital signal. By combining a radio frequency energy acquisition technology with a differential dual-electrode sensing structure, the electric field sensor has the performance characteristics of self energy supply, miniaturization, high precision, wide frequency response and low power consumption. The system can measure various types of electric field signals, including sine wave, triangular wave and square wave electric field signals, has a wide frequency range and a wide measuring range, and is excellent in linearity.

The invention provides a fracturing crack real-time monitoring method and system based on time-varying electric field dynamic data, and the method specifically comprises the steps: obtaining an electric field data sequence which changes with time and is collected by an electric field sensor disposed in a fracturing work area; for each monitoring time step k in the electric field data sequence, executing the following sequential Bayesian inversion: a, constructing state parameter prior distribution of the time step k by adopting kernel density estimation based on a sample of crack state parameter posteriori distribution of the time step k-1; b, establishing a target posterior probability density function composed of prior distribution, a likelihood function and a physical regularization item; c, in Markov chain Monte Carlo iteration, sampling is carried out on the target posterior probability density function; and d, after iteration is finished, taking a sample set output by the Markov chain as crack state parameter posteriori distribution of the time step k, and extracting crack three-dimensional geometrical morphology and distribution information from the sample set.

The invention belongs to the technical field of power equipment monitoring, and discloses a quantum sensing and MEMS sensing integrated partial discharge detection device and method. Partial discharge signals are collected through the quantum sensor and the electric field sensor; the data acquisition card transmits data to the microprocessor, the microprocessor judges the discharge type by using a wavelet transform method, extracts characteristic parameters, transmits the data to the computer, analyzes and determines calculation weights of different sensors according to the characteristic parameters to perform data fusion, and calculates and displays the partial discharge electric field intensity. According to the method, data fusion of the quantum sensor and the MEMS sensor is realized, more comprehensive and accurate information is provided, the source and characteristics of partial discharge can be better identified, the diagnosis accuracy and the reliability of a detection system are improved, false alarm and missing alarm are reduced, and reliable data are provided for the operation state, fault diagnosis and maintenance of power equipment.

The invention relates to a safety collision avoidance risk assessment method for a crane jib and electrified equipment, and belongs to the technical field of power construction. The method comprises the following steps: measuring electric field intensity by using an electric field sensor, and measuring and calculating a distance L1 from high-voltage live equipment to a test point; measuring and calculating the radial length L2 of the crane jib by using a pulse laser flight time measurement method; comparing the distance L1 from the electrified high-voltage equipment to the test point with the safety distance Ls1, and calculating a risk coefficient K1; comparing the radial length L2 of the crane jib with a safety threshold value Ls2, and calculating a risk coefficient K2; calculating a comprehensive risk coefficient Kave; and then the risk level is judged, and corresponding early warning is carried out. According to the invention, the problems of complex installation, high cost, poor compatibility and the like of a traditional anti-collision system are solved, the safety distance between the suspension arm and the electrified equipment in the hoisting operation can be evaluated in real time, the occurrence of collision accidents is effectively avoided, and the operation safety of an electric power construction site is guaranteed.

The invention discloses a self-excited AGC closed-loop detection system of an MEMS electric field sensor, and the system comprises an MEMS sensitive structure which comprises a shielding electrode, an induction electrode and a driving structure, the driving structure receives a voltage driving signal, generates mechanical deformation, drives the shielding electrode to generate displacement, couples a to-be-detected electric field signal with a displacement signal of the shielding electrode, and outputs a to-be-detected electric field signal and a to-be-detected electric field signal; outputting a differential mode current signal; the driving circuit is connected with the excitation end and the output end of the MEMS sensitive structure and is used for adjusting gain according to the displacement signal and adjusting a voltage driving signal according to the gain so as to form AGC closed-loop feedback and maintain stable resonance of the MEMS sensitive structure; and the signal demodulation circuit is connected with the output end of the MEMS sensitive structure and is used for receiving and demodulating the differential mode current signal. The beneficial effects of the invention are that the stability of the vibration amplitude of the sensor is guaranteed, the anti-interference capability and the electric field induction sensitivity of the sensor are improved, and the high-precision detection of the to-be-detected electric field signal is realized.

The invention relates to the technical field of electric field detection and early warning. The invention aims to overcome the defect of lack of an electric field detection device under the hot-line working condition of an ultra-high-voltage line in the prior art, and relates to an electric field detection device under the hot-line working condition of the ultra-high-voltage line, which is a non-contact electric field detection device and is used for detecting the electric field under the hot-line working condition of the ultra-high-voltage line in the hot-line working condition of the ultra-high-voltage line. The non-contact electric field detection device takes a microprocessor as a core control unit, and is composed of a double-spherical-shell type electric field sensor, a differential amplifier, a filter circuit, a true RMS conversion circuit, a power supply module and a man-machine interaction circuit. And deep association of data support, function collaboration and scene adaptation is carried out through the structure. The problem that traditional equipment is insufficient in stability in a severe environment is solved, continuous and stable operation of the electric field detection equipment under complex working conditions is achieved, it is ensured that reliable electric field intensity data can be continuously output, and a basic guarantee is provided for operation safety evaluation.

The invention discloses a reflective lithium niobate crystal alternating current or direct current integrated strong electric field sensor. Light transmission paths of the input polarization-maintaining optical fiber collimator, the polarizer, the quarter-wave plate, the electro-optical crystal, the hollow roof reflector, the polarization splitting prism, the total reflection mirror, the first polarization analyzer, the second polarization analyzer, the first output single-mode optical fiber collimator and the second output single-mode optical fiber collimator are coaxially arranged in parallel; and the LED light source is coupled in the packaging shell through insulating glue. The invention develops a reflective lithium niobate crystal alternating current or direct current integrated strong electric field sensor for measurement of an alternating current / direct current electric field in a mode of combining a polarization splitting prism and a lithium niobate crystal to rotate a shielding electrode.

The invention relates to a neural network-based high-voltage live-line work safety early warning method. The method comprises the following steps of 1, establishing a high-voltage transmission line electric field calculation model by using a surface charge method; 2, establishing an overall three-dimensional model of the transformer substation; 3, constructing a signal processing circuit of the power frequency electric field sensor, capturing electric field information in real time through the power frequency electric field sensor, and converting the electric field information into a processable electric signal; 4, real-time data from the power frequency electric field sensor are received, feature extraction and classification are carried out by adopting an early warning method based on a convolutional neural network, and potential safety hazards are identified; 5, establishing a neural network-based high-voltage live working safety early warning comprehensive platform integrating data acquisition, processing, analysis and early warning; the method has the advantages that the neural network algorithm is adopted, the distance and the azimuth angle are accurately judged, live-line work is early warned, and the accident rate is greatly reduced.

The invention discloses a non-equilibrium Michelson interferometer electric field sensor capable of automatically calibrating temperature influence, which has the characteristics of wide bandwidth, high measurement precision and small interference of distribution of an electric field to be measured, and can also automatically calibrate temperature influence and prevent a working point of the non-equilibrium Michelson interferometer electric field sensor from deviating. The electric field sensor comprises a lithium niobate substrate, the lithium niobate substrate is provided with a non-equilibrium Michelson interferometer, the non-equilibrium Michelson interferometer comprises an input and output waveguide, the input and output waveguide is connected with a first waveguide arm and a second waveguide arm which are different in length, two sides of the first waveguide arm are provided with electrodes, and the second waveguide arm is provided with electrodes. An antenna is arranged on the electrode, a first metal reflecting mirror is arranged at the tail end of the first waveguide arm, a second metal reflecting mirror is arranged at the tail end of the second waveguide arm, the first metal reflecting mirror and the second metal reflecting mirror are both arranged on the lithium niobate substrate, and the thermal expansion coefficients of the first metal reflecting mirror and the second metal reflecting mirror are different.

The invention relates to the technical field of electromagnetic interference suppression, and discloses an intelligent control method for electromagnetic interference suppression in a photovoltaic energy storage system, and the method comprises the steps: obtaining an electromagnetic transient pulse flow signal of an electric field sensor in the photovoltaic energy storage system; carrying out electromagnetic transient pulse interference signal suppression by adopting a self-adaptive time-varying filter and recording suppression time; performing electric field change detection on the distribution transformer by adopting an electric field sensor to judge whether the electric field change is detected or not; if yes, performing steady-state electromagnetic interference suppression on the distribution transformer; and if not, performing cyclic detection according to the time length from the current time to the suppression time. According to the method, a transient pulse interference signal automatic suppression mode based on the adaptive time-varying filter is adopted, the measurement precision of the electric field around the distribution transformer is improved, steady-state electromagnetic interference suppression is performed on the distribution transformer, the influence of electromagnetic interference on the electric field sensor and the distribution transformer can be effectively suppressed, and the measurement accuracy is improved. And the operation stability of the photovoltaic energy storage system is improved.

The invention discloses a piezoelectric film based on an MEMS electric field sensor and a manufacturing method of the piezoelectric film. The piezoelectric film comprises a substrate layer, an electrode layer and a PZT layer. The manufacturing method comprises the following steps: preparing PZT sol, forming an amorphous form, and then forming the crystalline PZT piezoelectric film. PZT is adopted as a piezoelectric material, large driving force can be obtained, the degree of converting electric energy into mechanical energy is high, reliability is good, and compatibility with the technology is good. The PZT piezoelectric film is prepared through a sol-gel method, good controllability is achieved, operation is easy and convenient, it is ensured that the structure of the piezoelectric film is more stable through multiple times of coating and high-temperature annealing treatment, the crystalline PZT piezoelectric film can be formed easily, and therefore the piezoelectric performance and stability of the piezoelectric film are remarkably improved, and the piezoelectric film can be applied to the field of piezoelectric devices. The method is suitable for large-scale production and application of various high-performance piezoelectric devices.

The invention discloses a litchi preservation control method and system based on adjustment of a low-frequency electric field. The method relates to the technical field of power supply control, and comprises the following steps: collecting and processing litchi fresh-keeping parameters, analyzing the parameters to obtain a quantitative evaluation value, and further optimizing and adjusting the litchi fresh-keeping control method. According to the method, litchis are pre-cooled and then stacked into a litchis stacked body, a low-frequency electric field is applied through a power supply device, and a capacitive electric field sensor array is used for monitoring and collecting original litchis fresh-keeping parameters in real time and pre-treating the original litchis fresh-keeping parameters to obtain the litchis fresh-keeping parameters; according to the method, the litchi preservation control electric field uniformity and the control reliability are quantitatively evaluated, the obtained electric field data uniformity quantized value and the obtained control reliability quantized value are compared with judgment values in a database for analysis, and therefore the method for optimizing the litchi preservation control is obtained, the reliability of the litchi preservation control method is improved, and the reliability of the litchi preservation control method is improved. The problem that in the prior art, a litchi preservation control method is insufficient in reliability is solved.

The invention discloses a substation danger area judgment method and system based on electric field gradient perception, and relates to the field of safety monitoring, and the method comprises the steps: arranging an electric field sensor array in a key equipment area of a substation; performing noise reduction processing on the data of each sensor node to obtain an electric field vector set; obtaining the electric field intensity change rate of each monitoring point through a space vector differential algorithm, and generating an electric field gradient tensor; dividing the electric field gradient value, and constructing a dynamic danger level mapping rule; performing spatial interpolation through a Delaunay triangulation algorithm to generate an electric field gradient equipotential surface; constructing an electric field gradient space distribution model, and generating a dynamic danger boundary envelope body in real time; and correcting the boundary of the dangerous area through the pre-trained gradient compensation coefficient matrix and triggering a graded early warning signal. The method has the advantages that the electric field gradient change of the transformer substation is monitored in real time through the electric field sensor array and the wavelet denoising technology, the dangerous area is dynamically evaluated, and the accuracy and real-time performance of dangerous area judgment are effectively improved.

The invention relates to the technical field of overvoltage monitoring, in particular to a wide-frequency-domain overvoltage online monitoring system and method for electric power high-voltage equipment. Comprising an electric field sensor array, an acquisition unit, a calculation unit and an output unit, the electric field sensor array comprises a plurality of sensors which are radially distributed on the same circumferential plane and have different measuring ranges and sensitivities, and sensors which are axially distributed; the electric field sensor comprises a sensing unit and a fiber bragg grating temperature measuring unit; the fiber bragg grating temperature measuring unit is suitable for measuring the temperature of the sensing unit; the acquisition unit is suitable for synchronously acquiring the emergent light intensity of the sensing unit and the temperature data of the fiber grating temperature measurement unit. The multi-range sensors distributed in the radial direction achieve wide-range and high-sensitivity voltage sensing through differential design, the intrusion direction of overvoltage can be determined through cooperation of the axial sensors and the radial sensors, and the problem that the range and sensitivity of a single electric field sensor are mutually restricted is solved.

The invention relates to an electric field visualization real-time monitoring system and method, belongs to the technical field of electric field visualization, and is used for solving the problems of insufficient real-time performance, large measurement interference, incomplete imaging, weak multi-user cooperation and lack of unified time reference in the prior art. The method comprises the following steps: acquiring electric field scattering data of a test body by a conformal optical fiber electric field sensor array, transmitting the electric field scattering data to an edge GPU node through a plastic optical fiber-CAN-FD link, and converting the electric field scattering data into electric field amplitude data; the edge GPU node is combined with WebGL3D texture mapping and a volume ray casting algorithm to complete volume rendering, and multi-user concurrent interaction is realized through a Web server and a browser client; and a White-Rabbit clock architecture is adopted to provide a unified time reference for the whole process. According to the method, dynamic and accurate capturing of the electric field is achieved, and the multi-user concurrent access requirement is effectively met.