529results about "Frequency analysis" patented technology

The invention discloses a distribution line fault intelligent diagnosis method based on multi-source information fusion, and belongs to the technical field of power system fault detection and diagnosis, and the method comprises the steps: obtaining distribution line data and meteorological data; superposing the distribution line data with the meteorological data to generate a space-time fusion feature matrix based on the wire space displacement; dynamically adjusting a preset initial threshold value by using the space-time fusion feature matrix; and performing multi-round verification on the abnormal fluctuation of the electrical parameters of the line according to the fault judgment threshold, generating a fault positioning instruction, performing real-time matching with the topological structure of the line, correcting the priority queue of the fault section based on the switching action feedback data of the feeder terminal, and triggering the fault removal action matched with the priority. According to the method, spatial-temporal feature fusion of current, voltage, weather and spatial displacement data and a dynamic threshold adjustment mechanism are adopted, the fault type can be accurately identified, the fault section can be positioned in real time, and the diagnosis precision and the response speed in a complex environment are remarkably improved.

The invention provides a mining circuit fault self-diagnosis method and system. According to the method, current and voltage waveforms and three-dimensional vibration signals of a cable are collected, and anti-interference data are generated through self-adaptive noise reduction and time sequence synchronization; a waveform interception window is dynamically adjusted based on the correlation between the mechanical vibration intensity and the current transient rate, the wave crest slope variable quantity is extracted from the current transient segment, high-frequency harmonic energy is separated from the voltage transient segment, time-frequency analysis is carried out on the vibration signal to extract an energy sudden increase frequency point, and a mechanical damage spectrum feature set is constructed; inputting the features into a space-time correlation model, and verifying space-time consistency of current distortion and voltage abnormity to generate composite features; dynamically correcting a fault threshold based on the environmental interference factor; and finally, a short-circuit peak or open-circuit oscillation diagnosis result is output according to the association strength of the electrical and mechanical characteristics. According to the invention, accurate fault self-diagnosis of the mining cable under a complex working condition is realized.

The invention discloses an automatic anchor point searching and processing method for grid-connected test data of a photovoltaic inverter, and belongs to the technical field of automatic test of a power system. According to the method, a three-phase voltage and current signal output by a power grid simulator and an inverter power instruction signal are aligned through a high-precision time synchronization device; wavelet transform multi-scale noise reduction and moving average filtering combined preprocessing is adopted to improve the signal-to-noise ratio; identifying a voltage zero crossing point candidate set, a drop starting point candidate set and a recovery termination point candidate set based on a self-adaptive dynamic threshold value; transient energy characteristic verification is introduced for a voltage drop starting point; effective anchor points are confirmed through time window association of power instruction step changes. According to the method, the problems of low efficiency of manual key event point identification, misjudgment caused by noise interference, grid event and inverter response time sequence correlation missing and the like are solved, and the automation degree of test data analysis, anchor point positioning precision and control response time sequence analysis reliability are remarkably improved.

The invention relates to the technical field of cable partial discharge detection and diagnosis, provides a high-voltage cable multi-parameter intelligent diagnosis method, system and equipment and a storage medium, and aims to solve the problems of low accuracy and poor reliability of high-voltage cable multi-parameter diagnosis caused by multiple factors. The method comprises the following steps: decomposing a partial discharge signal after interference filtering, extracting a time domain amplitude change rate and an energy distribution parameter, and generating a multi-dimensional time-frequency domain feature vector; calibrating a multi-dimensional time-frequency domain feature vector, carrying out nonlinear manifold mapping, generating a low-dimensional feature vector matched with dielectric spectrum characteristics, matching a partial discharge type with the highest similarity with an identification result, judging an insulation degradation level in combination with a final loss threshold interval, and generating a comprehensive diagnosis report. According to the invention, the ultrahigh-frequency sensor array captures the partial discharge signal matched with the dielectric spectrum, precise identification of the discharge type and dynamic evaluation of the insulation degradation level are realized through multi-scale analysis and deep learning fusion, and the reliability of high-voltage cable diagnosis is improved.

The invention relates to the technical field of meteorological monitoring, in particular to a ring main unit lightning micrometeorological online monitoring system and method, and the system comprises a feature extraction module, a frequency spectrum detection module, a frequency band pool screening module, a path adjustment module and an interference avoidance module. The method comprises the following steps: collecting an electric field intensity extreme value sequence, calculating a change rate difference ratio, identifying thunder and lightning precursor characteristics, combining a frequency spectrum energy density map, analyzing an energy peak frequency band and a drop point of a frequency hopping signal, judging a thunder and lightning frequency signal concentration area, performing frequency spectrum interference filtering, and combining a dynamic time warping algorithm. The time deviation between a lightning stroke time point and frequency hopping scheduling is analyzed; a frequency hopping path is adjusted in real time; the response timeliness is improved; the difference value before and after electric field disturbance is monitored; and support is provided for monitoring stability and response adaptability of the thunder and lightning risk environment.

The invention relates to the technical field of prediction algorithms, and discloses a high-precision active power filtering and prediction algorithm for a three-phase ammeter, which comprises the following steps: acquiring original signals of three-phase voltage and current for baseline correction, performing time-frequency analysis on non-stationary harmonic waves and noise of the original signals, and dynamically adjusting filtering parameters; voltage and current phase alignment is carried out through FIR phase shift and zero crossing point detection, a phase-locked loop is constructed by using GRU to track the frequency of a power grid, the sampling frequency is dynamically adjusted, and frequency mutation is detected; iapFFT transformation is optimized to suppress spectrum leakage, a phase error is corrected through a deep learning network, and weak harmonic detection is enhanced by using an attention mechanism; classifying harmonic waves, and adaptively calculating total active power; dimensionality reduction is carried out on historical power and environmental parameters through an auto-encoder, and future active power is predicted; low-power-consumption hardware is adapted, and training efficiency and data security are optimized; three-phase signals are processed in parallel, and FPGA storage and FFT / FIR cores are optimized for filtering processing; and dynamically adjusting parameters of the phase-locked loop.

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 technical field of electric energy measurement, and provides a power grid side electric energy metering method and device considering inter-harmonic components, and the method comprises the following steps: obtaining voltage data and current data of a power grid side, and extracting a voltage waveform signal and a current waveform signal through constructing a steady-state signal model; based on the obtained waveform signals, fundamental component extraction is carried out, based on a unary linear regression method, the amplitudes and phases of harmonic signals and inter-harmonic signals are compensated, and harmonic components and inter-harmonic components are extracted; based on the obtained fundamental component, each harmonic component and inter-harmonic component of each signal, calculating to obtain fundamental electric energy, harmonic electric energy and inter-harmonic electric energy; and based on the fundamental wave electric energy, the harmonic electric energy and the inter-harmonic electric energy, correcting the measured electric energy of the power grid side. And through steady-state model fitting and a unary linear regression compensation mechanism, the response and adaptability to high-frequency disturbance components are improved.

The invention relates to the technical field of power systems, in particular to a power system broadband oscillation disturbance source grading positioning method and system, and the method comprises the steps: calculating the compression ratio of a measurement signal according to the sampling resolution of an original measurement signal and a real-time transmission interval, and obtaining an initial compression coefficient; performing frequency domain decomposition on the original measurement signal to obtain frequency spectrum characteristic data, and compressing the original measurement signal based on the frequency spectrum characteristic data and the initial compression coefficient to obtain a measurement compression signal; embedding a time sequence position code in the measurement compression signal to generate time sequence input data; analyzing the time sequence input data by using a multi-head attention mechanism to obtain an attention weighted signal; and generating a reconstruction signal according to the attention weighted signal, and obtaining a broadband oscillation disturbance source grading positioning result based on the reconstruction signal and the disturbance propagation path. According to the method, rapid and accurate grading and positioning of the broadband oscillation disturbance source are realized through technologies of self-adaptive compression, broadband oscillation characteristic reservation, topology propagation path analysis and the like.

The invention discloses a high-voltage direct-current cable state online monitoring method and system based on MMC low-frequency injection. The method comprises the steps that an MMC controller injects a low-frequency three-phase alternating-current signal into a direct-current cable based on an MMC low-frequency injection control strategy; the MMC low-frequency injection control strategy comprises the steps that an MMC controller adopts a double-closed-loop control mode composed of an outer voltage loop and an inner current loop; a voltage error is calculated through an outer voltage loop, and a differential-mode voltage Udiffdq * and a common-mode voltage Ucomdq * are calculated through an inner current loop, so that the MMC outputs a target voltage Ugoal signal to a direct-current cable; according to the method, active injection of the low-frequency alternating-current signal with the specific frequency and amplitude is achieved by setting the specific MMC control strategy, a hardware structure of a main loop of an MMC system does not need to be modified, and implementation is safe, easy, convenient and flexible; and meanwhile, online quantitative evaluation of the insulation state of the direct-current cable is realized, and the monitoring process is high in precision, simple, convenient and efficient.

The invention belongs to the technical field of power equipment state monitoring, and discloses a cable branch box operation state intelligent evaluation system based on multi-sensor fusion, which comprises a state acquisition module used for acquiring a partial discharge signal, a voltage fluctuation signal, a terminal temperature signal and a terminal contact resistance signal of a cable branch box in an operation process, constructing a multi-source operation state parameter set of the cable branch box through time synchronization and physical quantity normalization processing; the mutual coupling analysis module is used for performing transient correlation deduction on the partial discharge signal and the corresponding voltage fluctuation signal based on the multi-source operation state parameter set to obtain a partial discharge-voltage coupling amount; when the partial discharge-voltage coupling amount exceeds a preset partial discharge-voltage coupling amount threshold value, determining that partial discharge abnormity caused by insulation degradation exists in the cable branch box; comprehensive and accurate evaluation of the operation state of the cable branch box is realized, and reliable support is provided for safe operation and maintenance of equipment.

The invention relates to the technical field of transformer fault detection, in particular to a converter transformer fault diagnosis method and device based on robot return data. The method comprises the following steps: accessing an original partial discharge signal of the converter transformer acquired by an on-site inspection robot into a diagnosis platform in the form of a dynamic return data packet by adopting a target communication mode to obtain a filtered pure partial discharge signal in a time domain; obtaining a dominant mode representing the characteristics of the pure partial discharge signal; inputting the dominant mode into the trained classifier to obtain a fault defect type of the converter transformer corresponding to the pure partial discharge signal; and visualizing the fault defect position and type of the converter transformer and the original partial discharge signal on the three-dimensional model of the converter transformer. According to the embodiment of the invention, the identification precision of the defect type of the converter transformer is improved, and the fault information of the converter transformer is visually displayed.

The invention relates to the technical field of power distribution network fault detection, and discloses a power distribution network high-resistance grounding fault intelligent detection method, system and device and a medium, and the method comprises the steps: collecting a power distribution network line transient signal which comprises a transient zero-sequence voltage signal and a transient zero-sequence current signal; preprocessing the transient signal and extracting a multi-dimensional feature set for representing high-resistance grounding fault characteristics, wherein the multi-dimensional feature set comprises a transient energy feature, a wavelet entropy feature and a harmonic component feature; and inputting the extracted multi-dimensional feature set into a pre-trained machine learning model, and simultaneously outputting a judgment result of the high-resistance grounding fault and an estimated value of the grounding resistance through the machine learning model. According to the method, the transient energy, the multi-scale wavelet entropy, the odd harmonic amplitude and the phase, which are derived from different analysis domains and have complementary physical meanings, are deeply fused, so that the problem that a single feature is weak in characterization capability and easy to fail under the conditions of high noise and high resistance is effectively solved.

The invention discloses a multichannel parallel level conversion circuit test system, which relates to the technical field of circuit test and comprises a test host, a multichannel parallel level conversion circuit, a signal source module, a signal acquisition module, a control module and a display module. The test host performs test logic verification on the whole process of the circuit test, the multichannel parallel level conversion circuit serves as a target circuit to be subjected to circuit test, a test signal of the circuit test is generated according to the signal source module, and a test case of the test signal is constructed. The signal acquisition module acquires an output signal of the multichannel parallel level conversion circuit, and generates a circuit tuning output signal after signal gain, signal noise optimization and frequency band filtering, the control module performs circuit testing on a target circuit according to a test case and the circuit tuning output signal, and finally, the control module performs circuit testing on the target circuit according to the test case and the circuit tuning output signal. And the display module visually displays the test result.

The invention relates to the technical field of power system court management, and particularly discloses a court identification and user binding method based on a special transformer acquisition terminal, which comprises the following steps: separating harmonic interference generated by start and stop of an electric welding machine through a kurtosis index and time-frequency energy entropy fusion detection method, and extracting a fundamental voltage and a pure power signal; constructing a dynamic time bending model containing phase consistency and gradient feature constraint based on the fundamental wave voltage, and calculating voltage track similarity to judge electrical coupling; for the users with electrical coupling, dynamic weight power cross-correlation analysis is fused to generate a comprehensive decision value, and a space-time diagram neural network is utilized to update a transformer area topology structure online in combination with a historical topology change event, so that the dynamic determination of the transformer area to which the users belong is realized; through multi-dimensional feature fusion and anti-interference algorithm design, the problems of phase deviation and waveform distortion caused by electric welding machine harmonic waves are reduced, and the transformer area identification accuracy and real-time performance are improved.

A multi-channel analog-digital converter (ADC) subsystem for test device such as a spectrum analyzer may include multiple multi-channel ADCs to receive down-converted signals and convert the received signals to digital output signals, a field programmable gate array (FPGA) to select one or more ADCs based on a frequency, a bandwidth, and / or a signal type of each received signal and a characteristic of each ADC, and an ADC sample clock to provide a clock signal to the selected ADCs. Characteristics of the ADCs may include a resolution, a signal-to-noise-and-distortion ratio (SINAD), an effective number of bits (ENOB), a signal-to-noise ratio (SNR), a total harmonic distortion (THD), a total harmonic distortion plus noise (THD+N), and / or a spurious free dynamic range (SFDR).

The invention relates to the technical field of line fault detection, in particular to an automatic alarm method and system based on distribution line online fault detection, and the method comprises the steps: detecting a current environment, obtaining current wind speed data, if a current wind speed value greater than a preset standard wind speed threshold exists in the current wind speed data, obtaining a repair line set based on a plurality of distribution lines, if the current wind speed value larger than the preset standard wind speed threshold value does not exist in the current wind speed data, statistical characteristics of the distribution line are obtained, a physical construction model is obtained, the statistical characteristics are input into the physical construction model, a model prediction value is obtained, fault point positioning operation is executed on a fault electric line, the position of a fault point is obtained, and an automatic alarm mechanism is triggered. And performing fault repair on the fault electric line to obtain a normal electric line set, and completing automatic alarm based on distribution line online fault detection based on the normal electric line set and the repair line set. The reliability and the operation efficiency of the power system can be improved.

The application discloses a kind of non-contact track frequency shift signal online monitoring method and system, applied to intelligent monitoring technical field, method includes: receiving first measured voltage and second measured voltage;First measured voltage and second measured voltage are input first conditioning circuit by first transmission line, receive the first output voltage output by first conditioning circuit, and the parallel transmission line formed after first measured voltage and second measured voltage are connected in parallel by second transmission line and third transmission line are input second conditioning circuit, receive the second output voltage output by second conditioning circuit;According to first output voltage and second output voltage, calculate first measured voltage.The application is realized by the way of double-path simultaneous monitoring, reduces the influence of the related capacitance value change caused by environmental conditions on monitoring result, to effectively improve monitoring precision, and then provides solid foundation for non-contact frequency shift signal back-end processing.

The invention relates to the technical field of air door motor control, and discloses an air door motor control method and system based on current detection, and the method comprises the steps: carrying out the single-phase current signal collection of an air door motor system, and obtaining a current change signal in the opening and closing process of an air door; carrying out FFT (Fast Fourier Transform) and wavelet decomposition processing on the current change signal to obtain a current characteristic spectrum component and a time domain characteristic; processing the current characteristic frequency spectrum component and the time domain characteristic to obtain an air door load current characteristic; iterative learning control is executed, and air door rotating speed control parameters are generated; the PWM duty ratio is calculated, and air door motor driving pulses are generated; according to the air door motor control method, a complete air door motor control protection mechanism is established, abnormal conditions such as stalling can be detected and coped with in time, the safety of an air door motor system is improved, and the service life of the air door motor system is prolonged.

The invention discloses a GIS ultrahigh frequency sensor ultrasonic cooperative detection system based on piezoelectric energization, and relates to the field of electric power detection, and the system comprises an excitation module which is used for transmitting a piezoelectric excitation signal with a specific frequency to a preset detection region in GIS equipment, so as to trigger the potential partial discharge acoustoelectric signal radiation of the region; the sensing module is used for receiving ultrahigh-frequency electromagnetic signals and ultrasonic vibration signals radiated by partial discharge in the GIS equipment; the excitation frequency, the filtering bandwidth and the sampling rate are dynamically optimized according to the detection result, the detection accuracy and efficiency are continuously improved, and reliable and effective guarantee is provided for safe operation and defect early warning of GIS equipment.

The invention discloses a power distribution network high-resistance fault positioning method and positioning system based on multistage joint filtering, and the method comprises the steps: collecting the power data of a power distribution network in real time, including a zero-sequence voltage signal and a zero-sequence current signal; constructing a signal flow graph strategy to process the power data by using a multi-stage joint filtering technology, and generating output data; the extraction of fault features is completed while the signal descrambling is carried out; establishing a dynamic threshold value, and performing comparative analysis based on the output data and the dynamic threshold value to determine a fault occurrence moment; based on a fault occurrence moment, generating a fault measure by using a heuristic method and feature polarity accumulation; based on two-dimensional characteristics of fault measurement amplitude and polarity and according to distribution characteristics of fault measurement of each measurement point relative to a fault point, a fault section is positioned through a recursion positioning algorithm containing an adaptive threshold value, a fault feeder line is quickly positioned, recursion positioning is carried out by using the adaptive threshold value, abnormal values caused by interference are eliminated, and the fault feeder line is quickly positioned. Therefore, accurate positioning under complex working conditions is realized.

The invention relates to a current-to-voltage acquisition circuit for suppressing common-mode interference. The current-to-voltage acquisition circuit comprises a current amplification module, a current transformer, a high-pass filter, an interference acquisition module, an interference analysis module and a suppression execution module, by means of the design, the common-mode interference suppression effect is better than that of a traditional sampling circuit, errors caused by sampling signal deviation generated by interference are avoided to the maximum degree, the common-mode interference suppression circuit is particularly suitable for interference scenes or occasions where interference sources change, the changed interference sources can be calculated in a sampling statistics mode, and the interference source suppression effect is improved. Therefore, the suppression ratio of common-mode suppression is adjusted, and the environment condition is dynamically tracked to obtain an accurate sampling effect.

The invention belongs to the technical field of gap measurement, and particularly relates to a high-temperature-resistant transparent shell type eddy current tip gap measuring device and method, and the device comprises a sensor probe module, a signal conditioning module, a data collection module and a data processing module. The sensor probe module is mounted on the outer wall of the casing; the sensor probe module comprises a permanent magnet excitation source, a soft magnet magnetic core and a receiving coil; the signal conditioning module is electrically connected with the receiving coil and is used for amplifying, filtering and integrating the weak induction signal; the data acquisition module is electrically connected with the signal conditioning module and converts an analog signal into a digital signal; the data processing module is used for processing the acquired digital signals and extracting blade tip clearance information.

The invention relates to the technical field of radio frequency measurement, and discloses a method for measuring the high-frequency characteristic of a radio frequency coaxial probe. The method comprises the following steps: acquiring high-frequency response data of a radio frequency coaxial probe, segmenting a full frequency band based on a predefined frequency band division strategy, and identifying a key frequency band region; according to the response amplitude and phase distribution of the key frequency band region, screening a reference frequency band and extracting an impedance reference value, optimizing impedance matching parameters of a non-reference frequency band based on the reference value, and generating a frequency band impedance optimization parameter set; recombining a full-band impedance distribution sequence according to the parameter set to generate an initial impedance matching scheme; and finally, monitoring the high-frequency transmission deviation under the initial scheme in real time, counting the impedance fluctuation quantity and the phase offset, and generating an impedance correction instruction. The method effectively improves the stability and reliability of the measurement of the high-frequency characteristic of the radio frequency coaxial probe by accurately identifying the key frequency band in a segmented manner, guiding the impedance parameter optimization by the reference value and combining a dynamic correction mechanism.

Provided are a method and apparatus for detecting a failure of a solar module. The method includes obtaining real-time power generation data of each of a plurality of solar modules included in at least one solar array, setting a reference value using at least one of past power generation data of the plurality of solar modules and specifications of the plurality of solar modules, determining each of the plurality of solar modules to be either a normal solar module or an abnormal solar module by comparing the reference value with a power generation amount of each of the plurality of solar modules, which is calculated using the real-time power generation data, and providing an interface displaying a solar module determined to be the abnormal solar module.

The invention discloses a frequency sweep measurement method and system. The method comprises the following steps: acquiring a fundamental frequency reference phase of each measured equipment access point at a measurement moment; executing rough scanning of the first-stage injection; analyzing the coarse scanning response data to identify a target frequency band which needs to be subjected to second preset resolution measurement; executing fine scanning of second-stage injection for the target frequency band; and analyzing the fine scanning response data, and obtaining a stability contribution evaluation result of each tested device to the power grid system based on an analysis result of the fine scanning response data and an analysis result of the coarse scanning response data. According to the scheme of the invention, the method can achieve the quick recognition of the potential key frequency region in a broadband range through the hierarchical rough scanning and fine scanning strategies, and avoids the time-consuming high-resolution measurement in a whole frequency band. And then, high-resolution fine scanning is performed on the identified target frequency bands in a targeted manner, so that accurate and detailed response data can be obtained in the key region.

The described technology provides a radiometer system, including an N-path transmission combiner including one or more sum-difference couplers and one or more quadrature couplers to generate N-path output signals including one or more sum output signals, difference output signals, and quadrature injected noise reference output signals; and, an N-path radio receiver array configured to couple the one or more sum output signals, the difference output signals, and the quadrature injected noise reference output signals into a complex cross-correlator, wherein the complex cross-correlator is configured to process the one or more sum output signals, the difference output signals, and the quadrature injected noise reference output signals to generate a plurality of calibration outputs to be interpreted by a computer based algorithm to determine calibration parameters of the radiometer system.

The invention discloses a transformer substation AC power supply residual current detection method and device, and the method comprises the steps: carrying out the vector synthesis of three-phase current data and zero line current data, forming a current difference sequence, exporting a residual current reference curve, and carrying out the fluctuation analysis of the residual current reference curve, and judging the leakage characteristics. After effective leakage features are formed through harmonic elimination, dominant frequency components are locked through frequency spectrum decomposition; calibrating a leakage type identifier according to the dominant frequency component and forming segmented leakage distribution; a deviation degree is formed by means of segmented leakage distribution and residual current reference curve deviation analysis, a correction deviation value is formed through load fluctuation compensation, and a standard exceeding coefficient is formed according to threshold value comparison to detect abnormal nodes to form hidden danger data; establishing a judgment rule based on the hidden danger data and the leakage type identifier to form a detection evaluation index; and executing path tracking on the detection evaluation indexes to form leakage position information, forming a disposal priority through intensity analysis to generate a residual current detection report, and realizing leakage current classification identification and self-adaptive evaluation.

The invention discloses a fault monitoring and positioning method for a high-voltage drop-out fuse, and relates to the technical field of power equipment fault monitoring, and the method comprises the steps: obtaining original monitoring sequences corresponding to current and voltage sensors disposed at upper and lower ports of a target fuse; activating a working mode recognizer to execute working mode recognition of the target fuse, establishing a global mode label, executing adaptive matching of a mode fingerprint database, and establishing a standard comparison fingerprint with a trust identifier; establishing residual spectrum characteristics; and establishing a fault discrimination vector, carrying out space fault positioning by using the fault discrimination vector, and generating a fault positioning result. According to the invention, the technical problems of insufficient fault monitoring and positioning accuracy, lack of visual presentation capability and low monitoring and positioning efficiency of the high-voltage drop-out fuse in the prior art are solved, and accurate positioning and visual presentation of the fault of the high-voltage drop-out fuse are realized. And the accuracy and efficiency of fault monitoring and positioning are improved.

The invention discloses a power distribution network reliability intelligent analysis method and analysis system, particularly relates to the technical field of power system fault detection, and is used for solving the problems of misjudgment and missed judgment caused by fault feature weakening and harmonic interference in a bidirectional power flow scene in an existing method. The method comprises the following steps: firstly, synchronously collecting fundamental wave and harmonic components of nodes of a power distribution network, extracting a current amplitude change rate and a phase offset by adopting time-frequency domain conjoint analysis, and generating dynamic distribution characteristics by combining harmonic energy clustering; identifying high-frequency interference components in a bidirectional power flow mode by quantizing a phase deviation direction and harmonic energy aggregation characteristics; based on a harmonic frequency band coupling effect and a current dynamic association relationship, an adaptive detection threshold function is constructed, and accurate separation of fault features is realized; and finally, combining a real-time fault judgment result with historical repair data to generate a reliability evaluation parameter. And the sensitivity of fault detection and the rationality of reliability evaluation in a complex operation environment are remarkably improved.