1931 results about "Power frequency" 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 a multi-parameter measurement system and method for a power frequency non-partial discharge test transformer, and relates to the technical field of state monitoring of high-voltage test equipment and power equipment, and the system comprises a synchronous trigger unit which is connected to a power frequency voltage signal collection end and is used for detecting a zero crossing point of a power frequency voltage signal and generating a synchronous trigger signal, a power frequency period is divided into a plurality of sub-windows with equal phase angles. According to the multi-parameter measurement system and method for the power frequency non-partial discharge test transformer, the problem of phase mismatch of a power frequency signal and a high-frequency partial discharge signal in traditional multi-parameter measurement is effectively solved through a power frequency phase locked synchronous trigger mechanism and a dynamic noise suppression technology; and the positioning precision of the partial discharge source and the insulation defect diagnosis reliability are improved. The nanosecond-level time sequence error control is realized, and the power frequency coupling interference is inhibited while the details of the high-frequency pulse are kept by combining a phase correlation dynamic filtering strategy, so that the signal-to-noise ratio of the weak discharge signal is improved.

The invention discloses a distribution network cable traveling wave fault early warning and positioning method and system, and the method comprises the steps: installing a device in a ring main unit, collecting a high-frequency traveling wave current and a power frequency current, and recognizing a grounding fault through a transient zero sequence comparison method and a high-frequency traveling wave polarity algorithm; weak traveling wave signals generated by insulation defects are monitored to carry out hidden danger early warning; traveling wave arrival time difference is measured through double-end distance measurement, and the position of a fault point is calculated in combination with line parameters; and early warning and positioning results are transmitted to a master station through 4G / 5G and 101 / 104 protocols. The system comprises a data acquisition module, a signal processing module, a fault positioning module, a hidden danger early warning module, a master station communication module and a master station module which work cooperatively. The method and the system are high in positioning precision, can realize accurate fault positioning and hidden danger early warning, support live-line installation, are suitable for various scenes, effectively solve the operation and maintenance problem of the distribution network cable, and improve the power supply reliability.

The invention relates to the technical field of electrical performance testing, in particular to a water supply equipment electrical performance detection system based on artificial intelligence, which comprises an electrical parameter acquisition module, an energy efficiency analysis module, an insulation performance evaluation module and a comprehensive diagnosis module. According to the invention, a three-phase voltage and current root-mean-square value is dynamically calculated through a broadband current transformer and a sliding window integration method, a 50Hz fundamental component amplitude is extracted to separate power frequency and high frequency harmonic waves, a continuous period energy efficiency ratio standard deviation triggers an insulation detection threshold value, and a parameter fluctuation and insulation degradation response mechanism is established. Harmonic interference correction synchronous processing energy efficiency ratio and leakage current integration, the detection error being lower than 5%, temperature rise rate linear regression and bearing current threshold value cooperative determination, winding aging cross validation, fault misjudgment rate reduction to 26%, closed-loop detection fusion transient capture, dynamic threshold value triggering and multi-parameter diagnosis, early warning success rate reaching 92%, and positioning response being reduced to 3 seconds.

The invention provides a multi-dimensional electrical equipment insulation analysis and evaluation method, and relates to the technical field of electrical equipment insulation online detection and intelligent diagnosis. According to the method, an electrically isolated direct current detection channel is constructed in a neutral point small resistance grounding system, controllable direct current detection signals are injected, micro direct current leakage response signals are collected, and after zero drift correction, temperature compensation and power frequency ripple suppression are carried out, layered attribution is carried out in combination with primary system topology and an equipment ledger, and a multi-dimensional response matrix is formed. According to the method, environment and working condition normalization is realized through factor rejection and robust pull-back, a mechanism model containing leakage channel equivalent parameters and path constraints is established, multi-working-condition data is fused to calculate equivalent insulation parameters and credibility indication quantity, and a multi-dimensional insulation representation vector is generated. And performing time sequence analysis on the representation vector, extracting degradation and abrupt change characteristics, outputting a health index and a risk level, and realizing quantitative evaluation and intelligent early warning of the insulation state.

The invention provides a line arrester operation monitoring method and device based on bimodal synchronous analysis, and the method is applied to an operation monitoring device comprising a lightning stroke recognition module, a signal collection module and an operation diagnosis module, and specifically comprises the steps: recognizing a lightning stroke event; bimodal current waveform signal acquisition for synchronously triggering an impact current signal and a power frequency follow current signal; dynamically associating the bimodal current waveform signal based on the time dimension and the amplitude dimension; and establishing a correlation diagnosis model, and outputting an abnormality diagnosis result according to the correlated bimodal current waveform signal. According to the method, the dual-mode current waveform is synchronously collected and the dual-mode current waveform signal is dynamically associated, so that the recovery state of the line arrester after action is comprehensively and accurately mastered, the abnormal state of the line arrester is more accurately identified, the identification accuracy of potential fault hidden dangers is improved, the occurrence probability of misjudgment and missed judgment is reduced, and the reliability of the line arrester is improved. And the effectiveness and reliability of line lightning arrester monitoring are ensured.

The invention discloses a multichannel electrophysiological signal acquisition system and an acquisition method thereof, and the multichannel electrophysiological signal acquisition system comprises a power supply module electrically connected with a controller, an analog front-end chipset, a filter module and an analog-to-digital conversion module; the analog front-end chip set is used for acquiring an analog signal and preprocessing the analog signal; the pre-processed analog signal is converted into a digital signal through a filter module and an analog-to-digital conversion module, and the digital signal is transmitted to a controller; the filter module is used for filtering and denoising; the timer module connected with the controller generates a sampling frequency, transmits the sampling frequency to the analog-to-digital conversion module, and provides a time sequence signal for the analog-to-digital conversion module. The invention discloses a multi-channel electrophysiological signal acquisition system, which solves the problem of synchronous sampling time sequence control of a high-density electrode array and eliminates signal phase deviation caused by clock jitter among multiple channels under the constraint of maintaining the total power consumption of the system. And real-time power frequency interference suppression is realized.

The invention is suitable for the technical field of fault diagnosis, and provides a distributed power transmission line fault diagnosis method based on ground potential end transient information perception, and the method comprises the steps: collecting a broadband transient signal of each node ground potential end of a power transmission line; synchronously acquiring an electromagnetic transient signal and an environmental parameter through the composite sensing unit; performing dynamic filtering correction on the broadband transient signal according to a preset transmission line impedance matching model; a deep learning model is adopted to perform hybrid processing on the corrected broadband transient signals and electromagnetic transient signals, traveling wave head time-frequency features and power frequency abrupt change features are extracted, and fault probability and type classification results are output; verifying a fault positioning result through a multi-stage verification mechanism; the extracted characteristic quantity is preprocessed at the edge side of the detection terminal, and the processed data is transmitted to a master station system through an encryption protocol, so that the fault diagnosis accuracy of the distributed power transmission line is effectively improved.

The invention relates to the technical field of magnetic bias monitoring, in particular to a real-time monitoring method and system for direct-current magnetic bias of a transformer. The method comprises the following steps: acquiring a primary side current signal and an iron core vibration signal of the transformer; analyzing the zero-flux closed-loop characteristic of the primary side current signal of the transformer and performing temperature drift elimination on the primary side current signal of the transformer to generate a primary side optimization signal of the transformer; performing magnetostrictive vibration noise separation on the iron core vibration signal to generate an iron core vibration separation signal; dynamically filtering a power frequency fundamental wave of the primary side optimization signal of the transformer to extract a pure direct current component; and performing wavelet packet decomposition on the iron core vibration separation signal, and performing magnetostriction characteristic spectrum extraction on the decomposed iron core vibration separation signal to obtain an iron core magnetostriction characteristic spectrum. According to the invention, through multi-source signal fusion and material characteristic modeling, the accuracy, real-time performance and graded protection response capability of transformer DC magnetic bias monitoring are improved.

The invention relates to the technical field of ground resistance detection, in particular to a single-core cable ground resistance detection method capable of resisting strong power frequency interference. High-frequency signals are injected in a non-contact mode through a coupling type capacitor clamp, background voltage and current signals are collected firstly, and injection frequency far away from power frequency and harmonic waves is selected through Fourier analysis; cancelling background noise by adopting a normalized least mean square adaptive filter to generate an enhanced signal; the signal is down-converted to a base band through digital quadrature demodulation, a Kalman filter estimates the amplitude and the phase in real time, and the state and noise parameters are periodically calibrated through a compressed sensing algorithm; and finally, loop impedance is calculated according to the voltage and current amplitudes and the phase difference to obtain grounding resistance. The method has the advantages of being non-contact, high in safety, strong in anti-interference capability, high in measurement precision and the like, and is suitable for monitoring the grounding state of the cable in a complex electromagnetic environment.

The invention discloses a high-voltage cable operation state on-line monitoring, intelligent early warning and fault positioning system, particularly relates to the technical field of power equipment insulation monitoring, and is used for solving the problems that transient discharge signals generated in the cable insulation degradation process are difficult to effectively capture and accurate fault positioning cannot be realized in the prior art. The method comprises the following steps: collecting transient leakage current signals and traveling wave propagation characteristic parameters, performing phase correlation analysis on leakage current pulses and power frequency voltage to identify discharge types, and performing variational mode decomposition and Hilbert-Huang transform on the signals to respectively extract complexity characteristics and energy distribution characteristics; signal logic conflicts are judged by analyzing similarity and statistical distance among characteristics of a plurality of monitoring points, and collaborative diagnosis is started or traveling wave distance measurement is directly utilized to carry out insulation state evaluation and fault location. And finally, differential early warning levels are generated according to the diagnosis result, and fault line selection and positioning information is output to realize real-time monitoring, intelligent early warning and accurate positioning of the operation state of the high-voltage cable.

The invention discloses an intelligent electromagnetic induction heating method and system for multi-parameter collaborative frequency domain separation, and provides a synchronous parameter acquisition and frequency domain separation processing scheme for solving the problems of temperature detection lag, insufficient frequency domain interference processing and weak dynamic adaptation capability in the prior art. Transient current, voltage and change rate (a first parameter group) of an electromagnetic coil are synchronously acquired, and high-frequency fluctuation (greater than or equal to 10kHz) and low-frequency disturbance (1t, 1t) are converted into low-frequency fluctuation (greater than or equal to 10kHz) by combining environment temperature, cookware materials and user preferences (a second parameter group); 10kHz) is used for frequency spectrum separation. Phase difference features are extracted through band elimination filtering and FFT, heating priorities are corrected in combination with dynamic compensation factors, and a segmented heating curve is generated through time-frequency domain weighted fusion. And the system adjusts PWM parameters in real time, and triggers adaptive protection when detecting that the phase is abnormal or the power frequency exceeds the limit. According to the method, the limitation of single-frequency-band detection is broken through, high-frequency noise suppression and low-frequency disturbance compensation are realized, and accurate temperature control of ferromagnetic / non-ferromagnetic cookware is supported.

The invention relates to the technical field of variable frequency speed regulation, in particular to an automatic water pump control strategy and energy efficiency optimization method and system.The method comprises the following steps of obtaining water pump outlet flow data, calculating flow acceleration, determining the pressure gradient direction, matching the hydraulic power trend, calculating frequency instruction deviation and setting the adjustable range; lagging and current rising mark inertia disturbance, power frequency limitation is set, a compensation value is generated, the frequency rate is dynamically adjusted in combination with all factors, and the frequency conversion adjusting priority is generated. According to the method, through matching of the flow acceleration and the pressure gradient, the sensing capacity for dynamic changes of fluid is improved, frequency adjustment of a frequency converter is optimized in combination with frequency deviation calculation, energy consumption increase caused by lag is reduced, and based on correlation analysis of the motor rotating speed change rate and current fluctuation, inertia disturbance accurate recognition is achieved; the voltage compensation timeliness is improved by combining bus voltage dynamic monitoring and a reverse compression strategy, the frequency of the frequency converter is dynamically adjusted by combining multiple parameters, and the response speed and the energy efficiency are improved.

The invention discloses a zero-sequence pilot-frequency excitation method for a double-circuit line in an incomplete power failure environment, which comprises the following steps of: applying zero-sequence pilot-frequency signal excitation on a power failure line by using a pilot-frequency power supply as an excitation signal source of a zero-sequence network of the double-circuit line, different-frequency induced current and voltage are measured at secondary sides of a current transformer and a voltage transformer at two sides of the operation line, and different-frequency zero-sequence voltage and different-frequency zero-sequence current in the double-circuit line zero-sequence network are obtained; simultaneously solving a zero-sequence network equation, and calculating mutual impedance between double circuits; performing frequency conversion to obtain the power frequency mutual impedance of the line; and finally, carrying out simulation verification by constructing a non-full-stop double-circuit line zero-sequence mutual inductance impedance measurement system. According to the method, the multi-path coupling caused by the existing power frequency interference method and the accuracy problem caused by the signal measurement error of the zero sequence increment method are solved, the test calculation can be accurately completed under the complex interference working condition, and the safety risk caused by the single-phase reclosing operation is avoided.

The invention belongs to the field of magnetic resonance measurement signal noise filtering, and particularly relates to a ground magnetic resonance signal sparse denoising method of a combined dictionary, which comprises the following steps: reconstructing a power frequency harmonic component of a magnetic resonance signal according to frequency bands, and eliminating power frequency harmonics from the magnetic resonance signal to obtain a power frequency-removed signal; constructing a track matrix Z by adopting a Gaussian random matrix, constructing a track matrix Y by adopting a power frequency-removed signal, taking first K columns of the track matrix Z and normalizing to obtain an initial dictionary D, and using the track matrix Y as an original sample for constructing a sparse coefficient matrix X; updating the initial dictionary D and the sparse coefficient matrix X through K-SVD dictionary learning, and reconstructing a track matrix by adopting the updated dictionary # imgabs0 # and the sparse coefficient matrix # imgabs1 # to obtain a track matrix W; and obtaining a pure magnetic resonance signal by taking the first row of the track matrix W, and realizing effective removal of MRS signal noise in a complex electromagnetic interference scene under the condition of single signal acquisition.

The invention discloses an energy storage system cooperative control method and system for power grid frequency modulation, belongs to the field of power grid control, and particularly relates to power grid frequency control, and the method comprises the steps: collecting power output time sequence data of each energy storage system in a target power grid in response to a power grid frequency modulation instruction through data monitoring equipment, to identify a timing misalignment event due to communication delay or response difference; acquiring output power data of each time sequence dislocation event so as to judge whether a cooperative failure condition occurs among the energy storage systems or not; if it is determined that a cooperative failure condition occurs, generating a frequency modulation power task redistribution instruction with smooth power grid power fluctuation as a target according to the output power data, and obtaining delay data to generate a communication time sequence adjustment instruction synchronized with power distribution, so as to adjust the frequency modulation power task according to the communication time sequence adjustment instruction; and cooperative control of each energy storage system in the target power grid is realized. The stability of power frequency modulation of the power grid can be improved through cooperative control of the energy storage system in the power grid.

The invention relates to a partial discharge detection system based on Rydberg atoms in the field of partial discharge detection of electrical equipment, the system comprises an optical path frequency stabilization module, an atom probe, a photoelectric detection module, a controller module and a power frequency synchronous trigger signal circuit, the optical path frequency stabilization module locks 852.35 nm probe light and pump light frequency less than 509.53 nm through SAS and EIT technologies, and the atomic probe is used for detecting the frequency of the probe light. Inducing transition from a cesium atom ground state to a first excited state to a Rydberg state; under the effect of partial discharge pulse, the atomic probe outputs a modulated EIT transmission spectrum signal, after photoelectric conversion and filtering, the controller module analyzes the amplitude and phase information of the pulse in combination with a power frequency synchronizing signal, the upper computer generates a PRPD diagram to analyze the discharge correlation, the detection sensitivity of the system reaches-50dBm, the frequency band of 300MHz-2GHz is covered, the dynamic range is greater than or equal to 50dB, the equivalent height is greater than or equal to 20mm, and the discharge correlation is greater than or equal to 20mm. Broadband and high-resolution detection is achieved, the problem of phase synchronization is solved, and the device is suitable for high-voltage environment on-line monitoring.

The invention discloses a carrier communication system power frequency band adjusting method and device, a carrier communication system comprises a plurality of preset frequency bands, and the adjusting method comprises the following steps: respectively obtaining channel noise data of the plurality of preset frequency bands in a current detection period; based on a frequency band quality relevance model, the communication quality evaluation value of the corresponding preset frequency band is calculated in combination with the channel noise data, and the frequency band quality relevance model is trained based on the noise historical data of the preset frequency band and the corresponding link quality historical data; and selecting a corresponding preset frequency band as a selected frequency band of the next detection period according to the communication quality evaluation value, and synchronously optimizing the power configuration of the carrier communication system according to the selected frequency band. Through a frequency band quality evaluation model fusing multi-dimensional noise feature analysis and historical data driving, the defects of traditional fixed frequency band allocation and linear power adjustment are effectively overcome, and prospective accurate prediction and adjustment of frequency band communication quality are realized based on noise history and link quality relevance modeling.

The invention relates to the technical field of power frequency resistance real-time monitoring, and provides a traction power supply 27.5 kV cable interval grounding grid power frequency resistance real-time monitoring method and system, and the method comprises the steps: obtaining the temperature distribution data of the surface of a conductor of a grounding grid; acquiring voltage and current response of the grounding grid when the local temperature rise value exceeds a preset reference value to perform frequency domain conversion, and generating a broadband impedance spectroscopy analysis result; aligning earth surface coordinates corresponding to the temperature measurement nodes with underground coordinates corresponding to the impedance measurement points, generating a space correlation grid, generating a temperature rise phase deviation coupling relation matrix, and generating a real-time monitoring result of the power frequency resistance of the grounding grid according to a power frequency impedance correction value in the space correlation grid and the temperature rise phase deviation coupling relation matrix; according to the invention, accurate space matching between the abnormal temperature rise area and the impedance change of the corresponding conductor is realized, the adaptability of a monitoring network to the extension direction and the burial depth change of the conductor is enhanced, and feature signal omission caused by fixed measurement point deployment is avoided.

The invention relates to the field of power distribution network ground fault accurate judgment, and discloses a power distribution network ground fault accurate positioning method based on traveling wave detection and artificial intelligence, which comprises the following steps: (a) collecting a power distribution network traveling wave voltage signal through a multi-node synchronous sensor array, and generating a preprocessing signal through baseline correction and wavelet threshold denoising; (b) constructing a Gaussian random field model of line resistance, inductance and capacitance, and simulating a traveling wave propagation process in combination with a nonlinear wave equation; and (c) defining Finsler measurement on the traveling wave signal manifold, and separating the aliasing mode by minimizing path integration. According to the invention, the technical scheme of multi-node synchronous signal acquisition and self-adaptive preprocessing is adopted, so that the effect of eliminating coupling of power frequency interference and high-frequency noise is achieved. Compared with a scheme depending on a single sensor and a fixed filtering threshold in the prior art, the method solves the defect that the wave head time difference extraction is not accurate due to asynchronous sampling.

The invention discloses an ultrasonic-assisted broaching machine tool based on a resonance broach and a design method. The machine tool comprises a broaching machine structure; a groove of the ultrasonic broaching tool is located in the position corresponding to the vibration mode wave crest of the broaching tool; the main piezoelectric actuator device is arranged in the groove; the compensation piezoelectric actuator device is arranged at the position, corresponding to the radial vibration mode, of the ultrasonic broach; the frequency of the ultrasonic power supply and the main power supply is the corresponding frequency when the axial ultrasonic vibration amplitude is maximum and the radial ultrasonic vibration amplitude is minimum under different power supply frequencies, the main driving voltage is determined according to the frequency of the main power supply, the preset broaching maximum speed of the broach and an ultrasonic auxiliary broaching effectiveness coefficient, and the frequency of the compensation power supply is the same as the frequency of the main power supply; the phase difference is 180 degrees, and the compensation driving voltage is the corresponding driving voltage when the ratio of the radial ultrasonic vibration amplitude to the axial ultrasonic vibration amplitude in different driving voltages is smaller than or equal to a preset threshold value. The ultrasonic assistance of the broach which needs to be frequently clamped can be realized.

The invention discloses a column type distribution transformer winding abnormity detection system and detection method. The detection system comprises a frequency response detection instrument, a signal coupling assembly, an impedance matching module and a data processing module. The frequency response detection instrument is used for outputting a frequency sweep excitation signal and collecting a winding response signal; the signal coupling assembly is used for isolating power frequency voltage and filtering low-frequency interference; the impedance matching module is used for adjusting output impedance and input impedance to realize matching with electrical characteristics of different windings; and the data processing module is used for constructing an equivalent detection loop model, completing frequency response simulation calculation and carrying out frequency domain analysis and anomaly identification on an actually measured response curve. According to the invention, electrified state diagnosis of distribution transformer winding structure abnormity (such as deformation and loosening) can be realized.

The invention belongs to the field of overvoltage protection, and relates to an overvoltage stabilizing and protecting device which comprises a data acquisition operation module, a control logic module, a display module, an overvoltage protecting assembly and a high-voltage vacuum circuit breaker or an electric isolation handcart structure. The real-time monitoring and protection of the working state of the overvoltage protection assembly are realized; through the arrangement of the high-voltage circuit breaker or the electric isolation handcart, when the overvoltage protection assembly is detected to be abnormal, the connection between the overvoltage protection assembly and the high-voltage bus can be rapidly cut off, so that the system safety is ensured; the device integrates a transient fault recording function and can capture wave map data before and after a power frequency overvoltage fault of the system; the overvoltage protection assembly in the device adopts a geometric center air cooling heat dissipation mode, the fan is quick in starting response, the operating temperature of the overvoltage protection assembly is greatly reduced, the operating time of the overvoltage protection assembly can be effectively prolonged, and the device adopts an integrated modular structural design, so that the operation safety, the maintenance and the management are greatly facilitated.

The invention discloses a communication data transmission method and system for an intelligent charging pile, and relates to the technical field of intelligent charging pile communication, and the method comprises the steps: constructing a reverse power line transmission channel model based on an equivalent channel response matrix, extracting channel frequency response, generating a channel equalization configuration parameter set through a joint optimization equalization algorithm, and transmitting the channel equalization configuration parameter set to a communication module. Subcarrier modulation orders are dynamically allocated according to the signal-to-noise ratio parameter, and a pre-balanced OFDM time domain signal is generated; on the basis of the channel equalization configuration parameter set and the pre-equalization OFDM time domain signal, dynamically monitoring power frequency harmonic noise of the cable, and inhibiting interference through a filtering algorithm to generate a clean power line carrier signal; and generating a verified V2G communication control instruction through a cyclic redundancy check method based on the clean power line carrier signal in combination with the main polarization direction feature vector. According to the method, an accurate channel model is constructed by combining an equivalent channel response matrix and cable characteristics, and dynamic subcarrier distribution is realized based on signal-to-noise ratio parameters.

The invention belongs to the technical field of hydraulic engineering, and relates to a dam safety monitoring system and method based on the Internet of Things, and the system comprises a vibration energy supply module, a cylindrical bluff body structure and a piezoelectric ceramic sensor are arranged on the upstream face of a dam, the bluff body structure is used for guiding water flow to form a Karman vortex street, and the water flow speed of the dam is monitored in real time; analyzing a Karman vortex shedding frequency based on an FFT spectrum, and matching the Karman vortex shedding frequency with the resonant frequency of the piezoelectric ceramic sensor to obtain dual-frequency matching data; the multi-dimensional observation acquisition module is used for converting kinetic energy of dam water flow into electric energy by using the generated Karman vortex shedding frequency, supplying power to a preset multi-dimensional sensor through the converted electric energy, and acquiring dam multi-dimensional observation data based on the multi-dimensional sensor; the three-dimensional hopping communication module is used for sensing and identifying power frequency and harmonic components of the surrounding environment in real time based on the dual-frequency matching data, and generating a dynamic avoidance frequency point table to complete frequency hopping switching; and the reliability and foresight of dam safety monitoring are enhanced.

The disclosure provides a method for improving the efficiency of a micro-inverter, and a dual-active-bridge-type micro-inverter. The method including: performing power modulation mode switching of a dual-active-bridge-type micro-inverter, such that the power is bi-directionally transmitted from a direct-current side to an alternating-current side and from the alternating-current side to the direct-current side, thereby reducing an effective value of a secondary side current of a transformer; and according to the modulation mode switching characteristic of the dual-active-bridge-type micro-inverter within a power frequency period, performing hybrid optimization on the turn ratio of a primary side to a secondary side and a transformer leakage inductance of a high-frequency transformer of the dual-active-bridge-type micro-inverter.

The invention discloses an intelligent fault recording and traveling wave distance measurement integrated control method and device, and belongs to the technical field of fault positioning, and the method comprises the steps: collecting the power frequency electric quantity data and high-frequency traveling wave data of monitoring points at two sides of a fault line; calculating a first fault distance estimation value based on the power frequency electrical quantity data, and identifying an initial traveling wave head based on the high-frequency traveling wave data to calculate a second fault distance estimation value; defining an evaluation time period, and calculating a signal-to-noise ratio value in the evaluation time period; and according to the signal-to-noise ratio value, determining the contribution degree of the first fault distance estimation value and the second fault distance estimation value in generating final fault positioning distance calculation, and performing comprehensive processing on the first fault distance estimation value and the second fault distance estimation value in combination with the contribution degree to obtain a final fault positioning distance. According to the invention, the accuracy and reliability of fault positioning are improved, and positioning requirements under different fault conditions and signal environments are met.

The invention discloses a power equipment insulation state detection method and device, equipment and a storage medium, relates to the technical field of power equipment, and aims to solve the problem of low detection accuracy of an existing detection mode on whether the power equipment is insulated or not. The method comprises the following steps: acquiring a partial discharge signal of power equipment, dividing the partial discharge signal into a plurality of continuous discharge period segments based on power supply frequency, and carrying out dynamic identification and amplitude limitation on the partial discharge signal in each discharge period segment to obtain an effective pulse signal with reserved pulse phase information, bottom noise self-adaptive elimination processing is carried out on the effective pulse signals based on a sliding window model, noise reduction signals are generated, a phase resolution partial discharge (PRPD) matrix is constructed according to the noise reduction signals, an insulation state diagnosis result is output according to the PRPD matrix, and the PRPD matrix is a matrix of a phase-amplitude two-dimensional space.

The invention discloses a low-frequency load shedding method and system based on zero crossing point real-time frequency tracking, and the method specifically comprises the steps: setting a dynamic time window according to the power frequency characteristics of a sensing signal, and removing an abnormal zero crossing point exceeding the dynamic time window; matching a pre-stored harmonic feature library, establishing a mapping relation between a harmonic mode and a phase offset, and performing adaptive phase compensation on a pseudo zero crossing point of the sensing signal; a sensing signal, PMU phasor data and meteorological parameters are input into a three-dimensional convolutional neural network, a cross-modal incidence matrix is calculated through a self-attention mechanism, a future frequency change trajectory is predicted in combination with an LSTM unit, and an optimal load shedding strategy is output; and based on the optimal load shedding strategy, in combination with a forward acceleration criterion and reverse fault locking, executing emergency load shedding according to load importance grading. The technical bottleneck of a traditional low-frequency load shedding device is effectively solved, and the performance and reliability of frequency stability control of the power system are remarkably improved.

The invention relates to the technical field of power system relay protection, and discloses a relay protection device mutual inductor adjustment system and method, and the system comprises a system connection initialization module, a data collection reference data generation module, a power frequency background signal offset module, a pilot frequency current injection error calibration module, and a calibration result verification output module. The method comprises the following steps: initializing sampling frequency of a to-be-calibrated mutual inductor and calibration source output precision of a calibration system, collecting amplitude and phase data of real-time power frequency current of the mutual inductor, generating offset current with equal amplitude and opposite directions through power electronic compensation based on reference data, optimizing offset current parameters through a closed-loop adjustment algorithm, and adjusting the offset current parameters through a closed-loop adjustment algorithm. Power frequency background signal offset is completed, pilot frequency calibration parameters are set, a difference value between a mutual inductor pilot frequency output signal and a calibration source standard signal is extracted by adopting a zero pointing technology, an optimal calibration coefficient is automatically calculated, verification of a calibration result is completed, and accuracy and reliability of the calibration result are ensured.