1416 results about "Transformer windings" patented technology

The invention relates to the technical field of power transformer state monitoring, and discloses a main transformer winding temperature rise on-line monitoring method and system, and the method comprises the steps: obtaining the calibration flight time of ultrasonic waves through an acoustic sensor array disposed on the outer wall of an oil tank in a quasi-isothermal state of a transformer; calculating a structure additional time delay which is caused by an internal fixed structure and does not change along with the temperature, and establishing an acoustic fingerprint for the transformer; during on-line monitoring, oil way net propagation time reflecting temperature change of the insulating oil is obtained from on-line flight time measured in real time; and then, based on the net propagation time of the oil way, an acoustic tomography algorithm is adopted to reconstruct internal two-dimensional or three-dimensional temperature field distribution, and the winding hot-spot temperature is finally and accurately calculated in combination with the real-time load current. According to the invention, through the acoustic fingerprint correction technology, the measurement interference of an internal fixed structure is eliminated, and non-intrusive, high-precision and visual online monitoring of the winding hot-spot temperature is realized.

The invention provides a 110V transformer winding insulation resistance absorption ratio detection method, which belongs to the technical field of transformer windings, and is characterized in that transformer operation state parameters and environmental influence factors are acquired through a multi-channel synchronous acquisition system, and thermodynamic and electrical models are established. The research adopts methods of principal component analysis, numerical integration and the like, an insulation resistance change rule is analyzed under a standard test voltage, a weight coefficient matrix is constructed in combination with an operation state and an environmental factor, a measured value is corrected through multiple linear regression and a correction coefficient method, and finally, the insulation resistance is obtained through statistical average and standard deviation analysis. The accurate evaluation of the insulation resistance absorption ratio of the transformer winding is realized; according to the method, the influence of the complex working environment and the operation state of the transformer on the insulation performance is fully considered, and the problem that various complex factors in the operation process of the transformer cannot be comprehensively considered and compensated in the prior art is solved by adopting the means of mathematical modeling, data correction, statistical analysis and the like; therefore, the technical problem of large deviation of the measurement result is solved.

The invention provides a forward-flyback full-circulation path high-capacity efficient equalization topology and a control method, and relates to the technical field of battery equalization management, and the method comprises the steps that only one multi-winding transformer is needed, and each battery pack corresponds to one transformer winding; the number of primary windings of the transformers is not increased along with the increase of the number of the batteries, and the number of the transformers is not increased along with the increase of the number of the battery packs; adjacent batteries share one pair of MOSFETs, so that nearly 50% of MOSFETs can be reduced; in addition, the equalizer provided by the invention can realize total energy flow paths between any batteries, between any battery monomer and a battery pack, between any battery packs and between any battery pack and the whole energy storage system, and can be flexibly applied to various conditions. Compared with an existing equalization topology, the equalizer provided by the invention is smaller in size and lower in cost, can select and match an equalization mode, and can be applied to a large-scale energy storage system.

The invention relates to the technical field of power equipment simulation analysis, and particularly provides a transformer winding temperature field determination method and device, and the method comprises the steps: obtaining the perception data of a transformer; taking the sensing data of the transformer as input of a pre-trained neural network model to obtain a transformer winding temperature field output by the pre-trained neural network model; wherein the sensing data comprises load current, environment temperature, temperature of the oil flow inlet and flow velocity of the oil flow inlet. According to the technical scheme provided by the invention, rapid calculation of the transformer winding temperature field considering real-time sensing data access can be realized.

The invention discloses a method for detecting the short-circuit resistance of a power transformer based on a digital twinning technology, and the method comprises the steps: building a three-dimensional transformer vibration simulation model, and carrying out the coupling calculation of a circuit, a magnetic field, a structural force field and a flow field. Calculating current and voltage curves of the winding and magnetic field distribution of the transformer in electromagnetic field simulation; solving a deformation trend and a fault type of the winding in a structural force field; the vibration characteristics of the measuring points on the surface of the oil tank are calculated in the flow field, so that the relationship between transformer winding deformation and vibration and reactance characteristics is obtained, the short-circuit damage process of the transformer can be analyzed, the method is of great significance in mastering the damage mechanism of the transformer, the anti-short-circuit capability of the power transformer is detected from multiple aspects, the detection accuracy is improved, and the detection cost is reduced. Related tests can be carried out when transformer equipment factories or related scientific research institutions are combined with transformer short-circuit tests, transformer short-circuit laws are mastered, and the anti-short-circuit capacity of the transformer is optimized and improved.

The embodiment of the invention discloses a transformer winding short circuit fault detection method. The method comprises the following steps: acquiring magnetic flux leakage data between transformer windings; determining a short-circuit fault area according to the magnetic flux leakage data; constructing a finite element model of the transformer; simulating the finite element model of the transformer based on the short-circuit fault area to obtain a short-circuit database; and acquiring magnetic flux leakage data between the transformer windings in real time, and determining the short-circuit fault position of the transformer windings according to the short-circuit database. According to the method, accurate detection of the short-circuit fault of the transformer winding is achieved by obtaining the magnetic flux leakage data, determining the short-circuit fault area, constructing the finite element model, obtaining the short-circuit database through simulation and locating the fault in real time, the accuracy and efficiency of fault detection are improved, and powerful guarantee is provided for safe operation of the transformer.

The invention discloses a transformer winding monitoring and diagnosis data acquisition method, system and device and a medium, and belongs to the technical field of power equipment state monitoring, and the method comprises the steps: constructing a multi-scale wavelet transform and improved adaptive Kalman filtering fusion architecture, the multi-scale wavelet transform and improved adaptive Kalman filtering fusion architecture is used for acquiring a monitoring signal of a transformer winding; performing frequency division processing on the monitoring signal by using the multi-scale wavelet transform, and determining each scale coefficient; adjusting a noise covariance matrix based on improved adaptive Kalman filtering, and carrying out filtering processing on each scale coefficient to determine a filtering result; and reconstructing the filtering result into a reconstructed signal, and performing signal quality evaluation on the reconstructed signal to determine the signal quality of the transformer winding. Through multi-scale decomposition and adaptive filtering, the limitation of a traditional method under non-stationary signal processing and strong noise interference is solved, and the retention degree and the signal-to-noise ratio of signal features are improved.

The invention belongs to the technical field of power equipment maintenance, and particularly relates to a transformer winding fault diagnosis method, a terminal and a storage medium, and the method comprises the steps: obtaining frequency response curves of a transformer winding in a normal state and an abnormal state through a frequency sweep test, the head end of the primary side winding is connected with a sweep frequency signal and the tail end is suspended; determining the number of units of an equivalent network according to the number of the frequency response curve characteristic frequencies of the windings in the normal state, and reconstructing a normal winding equivalent network composed of a plurality of RLC units; according to the method, the high-precision equivalent network is constructed, the frequency response residual error analysis is performed, and the Pearson's correlation coefficient is combined to screen the high-correlation element, so that the specific position of the winding deformation or fault can be accurately positioned, the fault type is distinguished, and the limitation that the traditional frequency response method can only judge the overall deformation degree is thoroughly solved.

The invention provides a transformer winding state detection method based on temperature characteristics. The method comprises the following steps: (1) collecting operation data; (2) preprocessing the operation data; (3) taking the normalized transformer load current, the normalized active power, the normalized top oil temperature, the normalized ambient temperature and the normalized oil flow speed as input data, taking the normalized winding hot-spot temperature as output data, and constructing a data set; (4) establishing a VSN-TKAN-GRN deep learning network parallel computing model of the transformer winding hot-spot temperature considering the multi-head attention mechanism; (5) predicting the hot-spot temperature of the transformer winding based on a VSN-TKAN-GRN deep learning network parallel computing model; and (6) calculating the average relative error percentage of the transformer winding hot-spot temperature prediction result and the actual measurement result, and judging the winding state according to the change of the average relative error percentage. According to the method, the state of the transformer winding in operation can be efficiently and accurately judged, so that effective transformer operation and maintenance measures can be taken in time, and large faults are avoided.

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 discloses a reclosing locking method and system based on winding hot-spot temperature fitting, and relates to the technical field of power transformer dynamic stability assessment, and the method comprises the steps: determining a target transformer, collecting parameters, building a winding current calculation model, calculating steady-state and short-circuit current waveforms, and carrying out the winding temperature rise test of the transformer, the method comprises the following steps: measuring a steady-state temperature rise value, constructing and correcting an electromagnetic heat flow coupling model, generating steady-state and transient-state temperature field data of a winding, constructing a target function of a winding hot-spot temperature, fitting simulation data by utilizing an optimization algorithm, obtaining a fitting function, calculating a winding stress value under a short-circuit working condition in real time, and comparing the winding stress value with a dynamically adjusted stress limit value, so as to obtain a winding stress value. Alarm and locking reclosing are triggered according to the result, and intelligent protection of the transformer is achieved. According to the invention, through accurate parameter acquisition, model establishment, temperature field simulation, hot-spot temperature fitting and stress calculation, real-time monitoring and intelligent protection of the transformer winding under the short-circuit working condition are realized.

The invention belongs to the technical field of winding insulation monitoring, and discloses a transformer winding insulation monitoring system which comprises the following steps: acquiring transformer winding data and an aging degree label; performing image enhancement processing, temperature correction, hot spot detection and temperature marking on the transformer winding data to generate a hot spot temperature distribution diagram; constructing a winding insulation aging prediction model for predicting the insulation aging degree of the winding based on the hot-spot temperature distribution diagram and the aging degree label; real-time transformer winding data are collected, prediction is carried out through the winding insulation aging prediction model based on the real-time transformer winding data, the winding insulation aging degree is obtained, and early warning judgment is carried out according to the winding insulation aging degree; the initiative of transformer maintenance is greatly improved, a user is helped to take necessary measures before a fault occurs, the risks of power failure accidents and equipment damage are reduced, and the service life of equipment is prolonged.

The invention belongs to the technical field of rapid calculation of a temperature field of a transformer winding, and particularly relates to a method for extracting a transient temperature rise main mode of the transformer winding by using a mixed norm. Comprising the following steps: S1, setting simulation step length and time, and determining a winding temperature rise sampling analysis point; s2, acquiring temperature rise distribution of a winding temperature field from the first sampling moment to the + 1th sampling moment, and constructing matrixes Tk and Tk + 1; s3, calculating D according to dynamic modal decomposition; s4, calculating an infinity-norm and a 2-norm of the matrix row vector, and defining a convex combination of the infinity-norm and the 2-norm as a norm of the matrix row vector; s5, simplifying a calculation formula of Tk; s6, calculating to obtain an instantaneous value of Tk, setting the instantaneous value to be equal to + 1, returning to the step S3, and carrying out winding temperature rise prediction at the next moment; according to the method, the overall and local characteristics of the modes are considered, the accuracy of main mode selection is improved, and the prediction precision of the instantaneous temperature rise of the winding temperature field is improved.

The present invention relates to the technical field of transformer fault detection. Disclosed is a transformer early fault diagnosis method based on the difference between virtual and actual winding leakage magnetic field waveforms, comprising: collecting leakage magnetic field information of a non-ideal winding structure transformer by means of fiber-optic magnetic field sensors; decomposing a winding of the non-ideal winding structure transformer into a plurality of regular windings; superposing leakage magnetic fields at the ends of a plurality of regular windings to obtain a non-ideal winding end leakage magnetic field; calculating a leakage flux matrix leakage inductance parameter and a leakage magnetic field output matrix parameter on the basis of the non-ideal winding end leakage magnetic field; establishing a circuit-leakage magnetic field multi-state digital model corresponding to the transformer; and using the difference between an actual transformer leakage magnetic field waveform and a digital transformer model virtual leakage magnetic field waveform as a fault characteristic quantity, completing threshold calculation and early fault sensitivity verification, forming a waveform difference-based early fault diagnosis criterion, and determining a fault position. The present invention can achieve quick and sensitive diagnosis of early faults of transformer windings and improves device operating reliability.

The invention discloses a transformer winding drying constant pressure device, which relates to the field of transformer production, including a base and a hydraulic lifting device, wherein the top of the base is rotatably connected to a cross rotating frame, and a third motor driving the cross rotating frame to rotate is installed on the top of the base, and the four arms of the cross rotating frame are all slidably connected to a bottom block, and the bottom of the bottom block is rotatably connected to a bottom roller, and the bottom roller protrudes from the top of the bottom block. In the process of pressing the transformer winding up and down, the present invention can drive the bottom roller and the top roller to rotate and roll the top and bottom of the winding back and forth through the rotating frame and the top frame, so that the top and bottom stress points of the winding can be changed back and forth as much as possible, so that the winding is more evenly stressed, and when pressing down, the side rollers are also linked to approach the side of the extruded winding, and when the bottom roller and the top roller roll the top and bottom of the winding, the side rollers also roll the side of the winding, so as to ensure the flatness of the side of the winding, so that the winding is pressed more compactly.

The invention discloses a transformer noise suppression method, system, equipment and medium, and the method comprises the steps: collecting the winding temperature, iron core temperature, cooling system working condition, load current and other operation parameters of a transformer in real time, constructing a multi-physical field coupling model covering electromagnetic, thermal and mechanical characteristics, and providing basic data for noise analysis; based on a heat conduction equation and a vibration acoustics theory, a mapping relation between a heat dissipation state and a transformer noise source is established, and dynamic influences of heat dissipation on noise amplitude and frequency are quantified; through combination of finite element simulation and a thermal network model, winding / iron core deformation caused by temperature change is analyzed, then a modulation rule of deformation on noise radiation characteristics is derived, and a heat dissipation state-physical deformation-noise characteristic transfer function is constructed; and based on the transfer function, dynamically adjusting operation parameters of the transformer by adopting a model predictive control and adaptive filtering technology, and minimizing noise output on the premise of ensuring heat dissipation efficiency.

The invention discloses a transformer winding fault simulation device and a transformer winding fault simulation method. A firm basic platform is provided for subsequent fault simulation operation. The annular lifting platform can drive the mechanical arm system to move in the radial direction and the axial direction, and accurate positioning of the mechanical arm system in the circumferential direction and the height direction of the transformer winding is achieved. A clamping mechanical arm in the mechanical arm system is used for clamping and extracting a transformer coil pressing piece, a block placing mechanical arm is used for inserting and withdrawing a wedge block, the clamping mechanical arm and the block placing mechanical arm cooperate with each other, the axial loosening fault of the transformer winding can be accurately simulated at different positions, and the accuracy and repeatability of fault simulation are improved. Besides, the transformer winding fault simulation method provided by the invention not only can be used for quantitatively judging the axial loosening degree of the winding, but also can be used for accurately positioning a specific area where the fault occurs according to the comparison of the energy module values of the partitions, thereby providing a reliable diagnosis basis for the preventive maintenance of the transformer.

The invention discloses a transformer winding deformation on-line monitoring method based on impedance characteristic identification, and relates to the technical field of transformer winding parameter monitoring method.The transformer winding deformation on-line monitoring method comprises the steps that a T-shaped equivalent circuit of a transformer and the relation between input signals of the transformer and winding parameters are established; the method comprises the following steps: assuming that voltage excitation remains unchanged during normal operation of a transformer, when the temperature of a winding changes along with the change of a load connected to a secondary side and the environment temperature, other electrical quantities of the transformer all change, and acquiring the temperature change of the winding and real-time waveform data of voltages and currents at two ends of the transformer at corresponding moments; a winding resistance value and real-time waveform data of a sampling period are calculated according to winding temperature change, a phasor value is calculated, and parameters of a T-type equivalent circuit of the transformer are identified by using a recursive least square method based on a forgetting factor. On-line monitoring of the operation state of the transformer winding can be realized, the fault of the transformer winding can be found in time, the fault rate of the transformer is effectively reduced, and the service life is prolonged.

The embodiment of the invention discloses an off-line monitoring method and device for the state of a transformer winding, equipment and a storage medium. The method comprises the steps of obtaining off-line frequency response test data, at least comprising a smooth frequency response curve, of a transformer; obtaining a resonance frequency and a resonance peak value according to the smooth frequency response curve, and calculating a first transformer capacity, a first no-load loss and a first short-circuit loss under the resonance frequency; utilizing the first transformer capacity, the first no-load loss, the first short-circuit loss and a preset multi-dimensional inferior fusion model to obtain a first comprehensive index used for reflecting the performance change of the transformer winding under the resonant frequency; and determining the current winding state of the transformer according to the first comprehensive index and a predetermined second comprehensive index. By means of the mode, higher sensitivity and reliability can be displayed in diagnosis of winding states such as winding deformation faults, and the method has important significance in prolonging the service life of a transformer and improving the operation reliability and economical efficiency of a power grid.

The invention provides a transformer winding anti-short circuit checking capability evaluation method, which belongs to the technical field of transformer winding anti-short circuit, and comprises the following steps: firstly, establishing an electromagnetic force thermal calculation model, inputting related material characteristic data, and obtaining stress and temperature distribution data through electromagnetic force thermal coupling calculation; establishing an anti-short-circuit capability key factor influence database; then short-circuit working condition data are collected in real time, and weights and correlation coefficients of all factors are obtained through analysis in combination with a database; and verifying the accuracy of the calculation model through a short-circuit stress test of the transformer winding, finally establishing an anti-short-circuit capability evaluation model, and calculating to obtain an evaluation vector containing various evaluation coefficients as an evaluation result of the anti-short-circuit checking capability of the transformer winding. According to the transformer winding anti-short-circuit checking capability evaluation method provided by the invention, the problems that key physical factors influencing the winding strength are not comprehensively considered and the evaluation precision needs to be improved in the existing transformer winding anti-short-circuit checking capability evaluation method are solved.

The invention discloses a method for evaluating deformation of a transformer winding based on a frequency response-impedance-capacitance comprehensive model. Characteristic indexes are obtained through loss testing, direct measurement and a low-voltage impedance method, collaborative diagnosis is conducted through a frequency response method, an impedance method and a capacitance method, a diagnosis model is established, and therefore the specific position and type of a fault are obtained. According to the method, three methods are comprehensively utilized to evaluate the transformer winding, and the problems that an existing transformer winding deformation state evaluation method is single, limited in data and inaccurate in evaluation result are solved.

The invention provides a wire pressing auxiliary device and method for a transformer winding machine, and relates to the technical field of winding machines, comprising a winding machine body and a rotating shaft, wherein a rotating shaft is rotatably provided at the lower part of one side of the winding machine body, and a winding piece is connected to one side of the rotating shaft, a sliding rod is slidably provided at the upper part of one side of the winding machine body, and a shaft plate is provided on one side of the upper and lower ends of the sliding rod; the invention drives the winding piece to rotate by the rotating shaft to wind the copper wire, and presses the clamping arm by pressing the elastic piece so that the two groups of clamping arms rotate inwardly and are clamped on the outer side of the winding piece, so that the wire pressing roller presses the winding part of the copper wire for regular winding, and presses and regularizes from two points, and before that, the copper wire passes between two groups of cleaning rollers and then between two groups of clamping rollers, and the T-shaped square column is pushed by the first spring to move the mounting plate inward, and the two groups of cleaning rollers and two groups of clamping rollers clamp the copper wire for cleaning and regularization, thereby improving the quality of the copper wire and having diversified functions.

The invention discloses an electric power centralized control system transformer state acquisition system and method based on edge analysis, and belongs to the field of enterprise substation operation and maintenance technology management.The system comprises an intelligent gateway machine, an edge analysis device, a camera and a transformer winding temperature measuring device; the edge analysis device is connected with the intelligent gateway machine, the camera and the transformer winding temperature measurement device, and the camera and the transformer winding temperature measurement device are arranged on a transformer site and used for collecting transformer oil liquid level video information and transformer winding temperature information respectively and transmitting the information to the edge analysis device. The intelligent gateway machine is deployed in a substation secondary room and is used for acquiring power load information of a transformer and transmitting the power load information to the edge analysis device; and the edge analysis device is deployed in a transformer substation secondary room, analyzes the transformer oil liquid level video information, the transformer winding temperature information and the transformer power load information through an edge analysis algorithm to obtain a transformer health state value, and transmits the transformer health state value to the electric power centralized control system after conversion.

The invention discloses a simple winding mold for an oil-immersed power transformer, and particularly relates to the technical field of transformer winding, the simple winding mold comprises a center ring, a supporting assembly is arranged on the center ring, the supporting assembly comprises a supporting cylinder arranged at the top end of a dislocation cavity, and a plurality of base plates are distributed on the outer side of the supporting cylinder. Through corresponding cooperative use of the structures, radial inward pressure during wire winding can be resisted, the collapse or bulging phenomenon caused by tension compression of the inner layer of the coil can be avoided, more uniform outer side support can be provided, and the circular retentivity of the section of the coil can be remarkably improved; and segmented and layered support of the coil is realized. According to the structure, the supporting range can be flexibly adjusted according to the thickness of the coil, a datum plate is matched for positioning the position of the wire, the phenomenon that the wire slides off and is not evenly stacked when the wide coil or multiple layers are wound is effectively avoided, and the overall compactness and the radial mechanical strength of the coil can be greatly improved by combining the winding tension and the pre-pressing technology.

The invention discloses a distributed wireless control system and method for transformer winding deformation detection. The distributed wireless control system comprises a plurality of transformers, a first deformation detection device, a second deformation detection device, an edge computing server and a cloud platform, wherein the first deformation detection device and the second deformation detection device are electrically connected with windings of the transformers; the first deformation detection device is used for generating a first fault signal when a winding deformation fault is detected; the edge computing server is used for analyzing according to the type of the fault winding and the short-circuit impedance variable quantity to obtain a first fault credibility level; and the cloud platform is used for obtaining the second fault credibility according to the historical data of the transformer winding, and determining a fault secondary judgment strategy according to the first fault credibility level and the second fault credibility. According to the invention, two different types of winding deformation detection devices are arranged to work cooperatively, and a secondary judgment strategy is executed based on judgment of the fault credibility level and the fault credibility, so that the problem of deformation fault false alarm in actual work is reduced, and the accuracy and reliability of deformation fault detection are improved.

The utility model relates to the technical field of biomedical engineering bionics, and discloses a miniature annular transformer winding jig which comprises a base assembly, a sliding rail assembly, a sliding block assembly, a winding adjusting assembly and a follow-up assembly, the sliding rail assembly is arranged on the base assembly in a sliding mode, the sliding block assembly is connected to the sliding rail assembly in a sliding mode, and the winding adjusting assembly is arranged on the follow-up assembly. The winding adjusting assembly is arranged on the sliding block assembly, the follow-up assembly is arranged on the sliding rail assembly, a containing opening for containing a magnetic ring is formed between the winding adjusting assembly and the follow-up assembly, and the device achieves the purposes that winding pressure can be adjusted, the winding visual angle can be adjusted, the winding angle can be adjusted, the lengths of primary and secondary reserved wires can be adjusted, and enameled wires can be wound in a lossless mode. And winding of the miniature ring transformers of different specifications can be achieved by replacing the winding adjusting assembly, meanwhile, one-time fixing and one-time winding are achieved, the winding time and cost are saved, the winding difficulty is reduced, and the winding success rate is increased.

The embodiment of the invention discloses a waveform identification and correction method and system for winding deformation diagnosis, and relates to the technical field of transformer winding monitoring, and the method comprises the steps: synchronously collecting voltage and current signals, and carrying out the preprocessing; performing waveform disturbance type identification on the preprocessed signal, and dividing the disturbance type into harmonic dominant disturbance, voltage sag disturbance or compound disturbance, and harmonic dominant disturbance, voltage sag disturbance or compound disturbance; dynamically selecting a corresponding waveform processing path according to a waveform disturbance type identification result; processing the signal by adopting the selected waveform processing path so as to correct and reconstruct the signal and obtain compensated voltage and current waveform data; by constructing a disturbance identification and path adaptive processing mechanism, the problems of processing lag and compensation distortion of a general algorithm during dynamic signal disturbance are solved, the identification precision is improved, and real-time error correction is realized.

The invention provides a rapid detection and diagnosis method and system for a short-circuit fault of a transformer winding, and relates to the technical field of transformers, and the method comprises the steps: collecting the electrical parameters of the transformer winding, calculating equivalent impedance, building a transfer function model and an equivalent impedance model, and extracting a frequency domain fault characteristic quantity and a short-circuit force characteristic; and constructing a characteristic quantity judgment matrix to obtain a weight coefficient, carrying out multi-source information fusion by utilizing a D-S evidence theory, and realizing fault diagnosis by combining fuzzy comprehensive evaluation. The method can accurately identify the short-circuit fault type of the transformer winding, and improves the reliability and accuracy of fault diagnosis.

The invention provides an alternating current withstand voltage characteristic detection method of a 110KV grounding transformer winding, and belongs to the technical field of grounding transformer windings, and the method comprises the steps: building a scaling type grounding transformer winding physical model, carrying out the power frequency alternating current voltage test under different voltage levels, employing the orthogonal decomposition to analyze the voltage and current waveforms, building a multi-dimensional characteristic correlation matrix, and carrying out the detection of the alternating current withstand voltage characteristic of the 110KV grounding transformer winding. And calculating power frequency and harmonic impedance coefficients. According to the method, the alternating-current voltage withstanding capability of the actual grounding transformer winding is accurately evaluated on the basis of the proportional relation between the model and the actual 110KV grounding transformer winding, and an innovative research method is provided for diagnosis of the insulating performance of the transformer. According to the detection method provided by the invention, the defects in the prior art are overcome, comprehensive and deep analysis of the AC voltage withstanding characteristic of the grounding transformer winding is realized, and the technical problem that the AC voltage withstanding characteristic of the grounding transformer winding is difficult to comprehensively evaluate by an existing single detection means is solved.

The invention discloses a transformer hollow winding model building method and system based on a multi-function PEEC method. The method comprises the steps that discretization processing is conducted on a target transformer winding, and the target transformer winding is divided into a plurality of volume units and area units; according to geometric parameters of the volume units and the area units, partial inductance matrixes, potential coefficient matrixes and resistance matrixes among all the grids are calculated; according to geometric characteristics of a target transformer winding, different improved approximation methods are adopted to calculate specific numerical values of the partial inductance matrix and the potential coefficient matrix; and establishing a target transformer winding equivalent circuit model according to the partial inductance matrix, the potential coefficient matrix and the resistance matrix of which the specific numerical values are calculated. The method not only improves the accuracy and calculation efficiency of the model, but also simplifies the model building process, improves the performance prediction capability of the transformer, and has high adaptability.