1493 results about "Transformer oil" patented technology

The invention relates to the technical field of charging pile group load intelligent regulation and control, and particularly discloses a charging pile group load intelligent regulation and control method and system based on dynamic power equalization, and the method comprises the steps: collecting the oil temperature of a transformer in real time, calculating a total output power threshold value, and correcting the actual output power of a charging pile through combining the line loss and the equipment aging degree; a multi-dimensional load regulation and control decision matrix including user priority, equipment health degree and power regulation sensitivity is established, a dynamic power strategy is allocated through matrix weight, power allocation is inclined to high-priority users and health equipment, emergency power allocation and progressive readjustment during newly-added demands are supported, and the power regulation and control efficiency is improved. Impact of sudden power change on a power grid is avoided, system stability is ensured when newly added loads are accessed, refined intelligent regulation and control of loads of the charging pile group are finally realized, transformer safety, charging efficiency and user experience are improved, and power grid stability and resource optimization configuration are ensured.

The invention provides an intelligent analysis method for the oil temperature and the oil level of a transformer. The method comprises the following steps: S1, acquiring oil temperature and oil level data of a transformer, generating displacement diagrams of two data in a coordinate system, drawing an actual oil temperature and oil level curve, and comparing the actual oil temperature and oil level curve with a standard oil temperature and oil level curve given by a manufacturer; s2, generating a relation function between the oil level and the oil temperature by using the transformer oil temperature and oil level monitoring, checking and analyzing device, and performing data comparison with a standard oil temperature and oil level curve given by a manufacturer; s3, analyzing whether the deviation between the oil temperature and oil level curve and a standard oil temperature and oil level curve given by a manufacturer exceeds an allowable value or not under the high-temperature and low-temperature operation conditions; according to the invention, quantitative data analysis can be carried out on the oil temperature and the oil quantity of the oil-immersed transformer.

The invention discloses an environment-adaptive transformer oil sample Raman spectrum detection method and related equipment, and relates to the field of optical sensing systems. The method comprises the following steps: collecting oil sample Raman spectrums and environmental parameters in multiple operation scenes, and constructing a multi-scene spectrum characteristic model and a standard fingerprint database; pre-processing and denoising parameters are adaptively set based on the environmental perception vector, and baseline correction and joint denoising are carried out on the original spectrum; scene discrimination is carried out by fusing the characteristics of peak position, peak height, peak width, integral area and the like, a scene-related component standard spectrum dictionary is generated, and the concentration and confidence of each target component are obtained by adopting constrained spectral line unmixing and quantitative calibration; and driving the fingerprint database and the model to update in combination with quality control indexes such as spectral shape relevancy and residual errors and a drift detection result. The system is composed of a Raman spectrum acquisition module, an environment monitoring module and a data processing module, and can improve the robustness and quantitative precision of Raman detection of transformer oil in a complex environment.

The invention discloses a transformer oil leakage detection method and device based on polarization-ultraviolet fusion imaging, and the device comprises a housing, a support, a camera, an environment induction device, an overall controller, a power supply, a polaroid rotating wheel assembly, a lens seat assembly, and an image processor. And the motor driver, the illumination intensity sensor, the ultraviolet irradiance sensor, the image processor and the power supply are electrically connected with the integral controller respectively. According to the invention, a multi-angle polarization image and a non-polarization image in the same field of view can be acquired, and then polarization characteristics contained in an oil stain fluorescence signal are extracted and effectively distinguished from non-polarization characteristics of background light; in the daytime mode, the transformer oil leakage detection device can identify a target area with relatively high polarization intensity, and through image fusion enhancement processing, non-target background signals are significantly suppressed, and the fluorescence significance of an oil leakage characteristic area is improved.

The invention discloses a method and a system for identifying mixed gas in transformer oil, a product and a medium, and relates to the technical field of testing or analyzing materials by means of measuring chemical or physical properties of the materials, and the method comprises the following steps: acquiring an internal structure diagram of a transformer, determining spatial position relations of parts and corresponding temperature distribution characteristics, and obtaining solubility differences of different spatial positions according to the spatial position relations and the corresponding temperature distribution characteristics. During operation, mixed gas concentration data of a plurality of detection points are collected, initial gas concentration data are recorded when an operation threshold range is deviated, and gas concentration change data are corrected according to solubility differences of different temperature zones. Calculating gas concentration space-time distribution characteristics, and determining a gas accumulation area according to the gas concentration space-time distribution characteristics and a space position relation. And separating the mixed gas components by using a gas chromatographic method, comparing preset gas types with the content of each component, and determining the corresponding gas type of each internal region. By implementing the method, the accuracy of identifying the types of the mixed gas in the transformer oil can be improved.

The invention provides a power transformer free gas detection method and system for material screening based on machine learning, and the method comprises the steps: carrying out the sampling of a compound space, and calculating a material characteristic data set of different doping configurations for the adsorption performance of a target gas through a high-throughput first principle; based on the material characteristic data set, a CGCNN convolution kernel is fused through a GNN framework, and a pre-trained material screening model is obtained and used for predicting the adsorption performance of different doping configurations to target gas; screening by utilizing a pre-trained material screening model to obtain an optimal doping configuration meeting a preset performance threshold value; screening based on the optimal doping configuration to obtain an optimal gas sensitive material; acquiring a response signal of the sensor array to the dissolved gas removed from the transformer oil, identifying the type of the target gas, and estimating the corresponding gas concentration; wherein the sensor array is prepared from an optimal gas sensitive material. According to the invention, rapid, accurate and on-line detection of various key free gases in transformer oil can be realized.

The invention discloses a transformer fault diagnosis method, system and equipment and a medium, and the method comprises the steps: through the linkage design of an oil pumping sampling module and a transparent sampling channel, combining high-speed camera shooting collection and synchronous light source illumination, and obtaining the image of particles in a transformer oil sample in real time; secondary pollution and personal errors possibly caused by traditional off-line sampling are avoided, and the detection efficiency and the objectivity of data are improved; the ResNet neural network is introduced to carry out feature extraction on the oil sample image, the particle number and particle size distribution information are automatically identified, the complex process of manually designing features in a traditional image processing method is avoided, and the accuracy and robustness of diagnosis are greatly improved; by setting judgment threshold values for indexes such as the particle number, the average particle size and the large particle size proportion, logic judgment is conducted in combination with the actual operation state, potential abrasion, pollution and other abnormalities can be recognized in the early stage, the capacity of quick response and advanced intervention is achieved, and the operation safety and the intelligent operation and maintenance level of the transformer are remarkably improved.

The invention relates to the technical field of transformers, in particular to an oil-immersed power transformer which comprises a hollow rod, a first round rod, a first piston, a first spring, a cylinder, a second round rod, a second piston, a limiting block and a ventilation assembly. A hollow rod is fixedly connected to the diaphragm; a first round rod is slidably connected to the hollow rod. A first piston is fixedly connected to the first round rod and makes contact with the lower end of the hollow rod. A cylinder is fixedly connected to the box body; through cooperation of the hollow rod, the first round rod, the first piston, the first spring, the cylinder, the second round rod, the second piston, the second spring and the limiting block, pressure relief operation can be automatically completed when pressure in the transformer body is increased abnormally, and therefore the transformer body can be protected; and the transformer oil sprayed out at a high speed can be intercepted and prevented from being sprayed to the outside to pollute the environment, the intercepted transformer oil is gathered on the upper side of the diaphragm, manual collection of the transformer oil can be facilitated, and waste is avoided.

The invention relates to the technical field of researching or analyzing materials by testing chemical or physical properties of materials, in particular to an intelligent analysis method for corrosivity of sulfide molecules in transformer oil. The influence of the oil environment on the adsorption energy is simulated and corrected in combination with molecular dynamics, a microscopic parameter database is constructed, and a corrosion risk grade classification rule and a generation rate prediction model are established. Oil data are collected in real time and input into the model to output a dynamic risk level, and a circulation rate adjusting or corrosion inhibitor adding instruction is triggered. Model parameters are regularly corrected by combining a closed-loop feedback mechanism, and a microscopic database is expanded, so that transfer learning prediction of unknown sulfide corrosion behaviors is realized. According to the method, the limitation of an existing single experiment condition is broken through, the relevance between a microcosmic molecular mechanism and a macroscopic corrosion behavior is dynamically analyzed, and the prediction precision under the multi-factor coupling effect is improved.

The invention discloses an anti-corrosion treatment process for a transformer oil tank. The anti-corrosion treatment process comprises the following steps that S1, the surface of the oil tank is pretreated; step S2, coating a primer; s3, intermediate paint is coated; step S4, coating a finishing coat; and S5, coating post-treatment is carried out. By selecting high-performance anti-corrosion paint and a reasonable coating process, the anti-corrosion performance of the surface of the transformer oil tank is remarkably improved, erosion of various corrosion factors can be resisted for a long time, and the anti-corrosion performance is excellent; an air spraying method is adopted, so that uniform distribution of a coating on the surface of the transformer oil tank is ensured, and the problem that the anti-corrosion effect is reduced due to non-uniform coating is avoided; through surface pretreatment and selection of a high-adhesive-force coating, the binding force of the coating and a transformer oil tank base material is enhanced, and the durability and reliability of the coating are improved; the process adopts a mechanical coating method, so that the construction efficiency is improved, the labor intensity is reduced, and the construction efficiency is high.

The invention relates to the technical field of oil-immersed power transformers, in particular to an oil-immersed power transformer which comprises an oil-immersed power transformer body, a transformer oil conservator is fixedly mounted on the oil-immersed power transformer body, and a fixing frame is fixedly connected to the transformer oil conservator. The sunshade curtains are fixedly connected to the two sides of one end of the fixing frame, the transmission mechanism is fixedly connected to the fixing frame, the curtain pulling frame is arranged on the fixing frame in a sliding fit mode, the oil conservator cleaning mechanism is arranged at the bottom end of the middle of the curtain pulling frame in a sliding fit mode, and the air guide mechanisms are fixedly connected to the fixing frame. The curtain pulling frame is driven by the transmission mechanism to move, so that the sunshade curtain can be unfolded to block above the transformer oil conservator, and sunshade protection is performed on the transformer oil conservator. Direct irradiation of the sun to the oil conservator can be effectively shielded, sunlight radiation heat transfer is reduced, the temperature of the oil conservator is prevented from being too high, and then the temperature of oil in the transformer is effectively reduced.

The invention belongs to the technical field of transformer equipment, and particularly relates to an automatic sampling device and method for transformer oil and gas. The device comprises a control box and a sampling sealing box, wherein a display screen, a keyboard and a code scanning module are arranged at the front part of a box body of the control box; the sampling sealing box comprises a sampling sealing box cover and a sampling sealing box body, a sampling bag support is arranged in the sampling sealing box body, the sampling bag is arranged on the sampling bag support, and a two-way valve is arranged at the top of the sampling bag; a sampling chamber air outlet pipeline, a sampling chamber air inlet pipeline, a third pipeline and a fourth pipeline are arranged on one side, connected with the sealing box, of the control box; the third pipeline and the fourth pipeline are respectively connected with the two-way valve; a first vacuum pump gas inlet pipeline, a second vacuum pump gas outlet pipeline, a waste liquid tank pipeline, a transformer oil sample pipeline and a transformer gas sample pipeline are arranged at the rear part of the control box. According to the invention, the convenience, safety and reliability of transformer oil and gas sampling are comprehensively improved, and powerful technical support is provided for safe and stable operation of a power system.

The invention belongs to the technical field of transformer decontamination, and particularly relates to a cleaning and decontamination structure suitable for oil change of an oil-immersed transformer. Comprising a shell, the shell is provided with an oil conservator, the lower side of the shell is fixedly connected and communicated with an oil discharge pipe, fixing plates distributed in a rectangular shape are arranged in the shell, the fixing plates are fixedly connected with scrapers, the two symmetrically-distributed fixing plates are fixedly connected with sliding rods, the fixing plates are fixedly connected with fixing blocks, and the sliding rods are fixedly connected with the fixing blocks. The fixing block is in spline connection with a driving rod, the driving rod is fixedly connected with pressing rods distributed at equal intervals, and the scraping plate is fixedly connected with guide blocks distributed at equal intervals. The extrusion rods are driven by the driving rods to extrude the adjacent guide blocks, so that the scraping plates are gradually close to the inner wall of the shell, oil dirt on the inner wall of the shell is scraped layer by layer, the oil dirt scraping effect is improved, and the situation that a large amount of oil dirt is accumulated below the scraping plates and is difficult to scour subsequently is avoided in the layer-by-layer scraping mode.

The invention discloses an automatic welding device for producing a transformer oil tank, which comprises a supporting and fixing device, a mechanical arm, a transformer oil tank shell and cooling fins, the mechanical arm is arranged on one side of the supporting and fixing device, and a welding gun is arranged on the mechanical arm; the supporting and fixing device comprises a positioning and fixing mechanism, a fixing mechanism and a bottom supporting frame, the positioning and fixing mechanism and the fixing mechanism are symmetrically arranged above the bottom supporting frame, one end of the top end of the bottom supporting frame is fixedly connected with an installation support, and a servo motor is fixedly installed at the top end of the installation support. The transformer oil tank shell is positioned and fixed in the horizontal direction and the vertical direction, the overturning face of the transformer oil tank shell is adjusted through the servo motor, time and labor are greatly saved, the overall welding progress is accelerated, and the transformer oil tank shell is more convenient to disassemble through the movable design of the sliding supporting plate.

The invention provides a degassing-free transformer oil monitoring device and method. A transparent accommodating pipe is used for being communicated with an external transformer oil supply device; the laser detection assembly is arranged on one side of the transparent accommodating tube; the voltage regulation and control unit is connected with the transparent accommodating tube; the imaging assembly is arranged on one side of the transparent accommodating tube and is used for acquiring optical image data of the Tyndall phenomenon in the transformer oil sample under different voltage conditions; the data processing unit is used for setting a segmentation point in the middle position of a Tyndall light pillar based on the Tyndall light pillar in the image data collected by the imaging assembly, determining a standard deviation according to the ratio of the total number of gray pixels on the left side and the right side of the Tyndall light pillar, and determining a threshold value of the Tyndall light pillar according to the relation between the standard deviation and a preset threshold value range. And judging the existence state and distribution characteristics of the gas in the transformer oil sample. Degassing treatment is not needed, the process is simplified, sample pollution is avoided, and the monitoring accuracy and stability of the gas in the transformer oil are remarkably improved.

The invention belongs to the technical field of transformer monitoring, discloses a method, a system and equipment for cleaning and checking transformer oil chromatography online monitoring data and a medium, and aims to solve the problem of recognition accuracy. The method comprises the following steps: acquiring the concentration of the dissolved gas in the transformer oil to construct gas concentration time sequence data, identifying and eliminating missing values and / or zero values in the gas concentration time sequence data, filling by using a linear interpolation method, detecting other values by using a Z-Score method to determine an obviously abnormal value E1, and calculating the concentration of the dissolved gas in the transformer oil. Preprocessed gas concentration data are obtained from E1 data in gas concentration time sequence data, specific value characteristic data are constructed according to an IEC three-specific-value method and added, then points which do not belong to data clusters obtained through clustering are determined as outliers by applying a DBSCAN clustering algorithm, and the outliers are determined as outliers. And identifying the clustered data clusters with fuzzy boundaries, finding out points near the boundaries, marking the points as boundary points, summarizing to form an abnormal data set E < total > to be checked, approving the abnormal data set E < total > by adopting a Rogers ratio method, and judging whether the abnormal data set E < total > is abnormal or not.

According to the transformer oil level monitoring method and system based on temperature compensation, the medium, the program product and the terminal, through combination of multi-sensor fusion and an intelligent algorithm, full-dimension sensing of the running state of the transformer is achieved. Compared with a traditional single-function monitoring device, the traditional device usually only monitors single parameters such as oil level or oil temperature and cannot comprehensively consider the incidence relation among the parameters, so that the recognition accuracy of oil level monitoring is low. According to the method, through fusion analysis of the multi-source data and in combination with learning and analysis capabilities of a machine learning algorithm, potential relationships and fault features behind the data can be mined, and the oil level monitoring and recognition accuracy is remarkably improved. According to the invention, fault hidden dangers can be found more timely and accurately, measures can be taken in a targeted manner for maintenance, and unnecessary inspection and maintenance are reduced, so that the operation and maintenance cost of the whole life cycle of the transformer is effectively reduced.

The invention belongs to the technical field of power equipment state monitoring, and discloses a transformer oil dissolved gas surface enhanced Raman spectrum in-situ monitoring method and a transformer oil dissolved gas surface enhanced Raman spectrum in-situ monitoring system. The system comprises a membrane degassing unit, a Raman sensing unit, a light path unit, a data processing unit and a calibration early warning unit, the method comprises the following steps: firstly preparing a gold nanostar array sensing substrate with bifunctional groups to realize selective adsorption and signal enhancement of characteristic gas, then completing in-situ oil-gas separation through the membrane degassing unit, collecting a Raman spectrum through the light path unit, and calculating the Raman spectrum of the gold nanostar array sensing substrate according to the Raman spectrum. Spectral analysis and quantification are completed based on multiple algorithms, and fault early warning is achieved in combination with temperature and pressure compensation and an industrial standard threshold value. According to the scheme, the problems of lagging, weak interference resistance and the like of traditional monitoring are solved, high sensitivity and high specificity are achieved, full-process automatic closed-loop monitoring can be achieved, and accurate data support is provided for operation and maintenance of the transformer.

The invention relates to the technical field of transformers, and particularly discloses a transformer fault diagnosis method and system.The transformer fault diagnosis method comprises the steps that firstly, concentration data of gas dissolved in transformer oil is collected, the potential fault type of a transformer is preliminarily determined based on a three-ratio method, and a diagnosis result confidence evaluation mechanism is introduced; a confidence score for the potential fault type is calculated. And when the confidence coefficient is lower than a preset threshold value, further combining the potential fault type and the confidence coefficient thereof with basic attribute data of the transformer to form fault diagnosis priori data. And then, deep conjoint analysis is performed on the concentration data of the gas dissolved in the oil and the fault diagnosis prior data by using the trained fault diagnosis model, so that more comprehensive fault features can be captured, and an accurate transformer fault diagnosis result can be obtained. According to the method, a deep learning algorithm is introduced during low-confidence diagnosis of a traditional three-ratio method, so that the accuracy and reliability of transformer fault diagnosis can be remarkably improved.

The invention provides an oil taking port positioning method and system based on monocular vision and laser positioning. The method comprises the steps that laser point cloud data and a monocular image near an oil taking port are acquired; constructing a three-dimensional model of the oil taking port based on the laser point cloud data, and projecting the three-dimensional model of the oil taking port into a two-dimensional slice image according to an acquisition position label of the monocular camera; matching the two-dimensional slice image with the monocular image to determine the two-dimensional feature position of the oil extraction port; calculating the feature distance between the oil taking port and the camera based on the matched two-dimensional feature position of the oil taking port and the focal length label and the size label of the monocular image; on the basis of the position parameters of the oil taking port in the laser point cloud data, the feature distance is combined, and initial three-dimensional coordinates of the oil taking port are generated; and unifying the pixel coordinates of the monocular vision and the laser point cloud coordinates into the same coordinate system, and carrying out preliminary three-dimensional coordinate data fusion to obtain the final three-dimensional coordinates of the oil extraction port. The positioning precision of the transformer oil taking robot on the oil taking port is improved.

The invention relates to the technical field of transformers, and discloses a noise reduction type finned radiator for a transformer, which comprises a transformer body, and the transformer body comprises a transformer box, an oil outlet pipe, an oil inlet pipe and a radiator; a variable section unit is arranged on the oil outlet pipe and used for making memory metal contract or stretch to drive a movable shaft to move when the environment temperature or the oil temperature changes according to the characteristic that the memory metal is sensitive to the temperature, and a section adjusting block moves in an adjusting cavity through a first connecting rod and an adjusting column. And the section of an internal flow channel of the oil outlet pipe is adjusted. Through the variable section unit, the internal flow channel section of the oil outlet pipe can be automatically adjusted according to the environment temperature by means of the characteristic that memory metal is sensitive to the temperature. And in a low-temperature environment, the memory metal shrinks to drive related parts to move the section adjusting block and reduce the section of the flow channel, so that the flow velocity of the transformer oil is accelerated, and the problem of excessive heat dissipation or insufficient heat dissipation is avoided.

The invention relates to the technical field of oil level monitoring, in particular to a transformer oil level monitoring device and system based on dual-mode ultrasonic sensing. The method comprises the following steps: acquiring transformer oil level and vibration acceleration; threshold value differences are obtained through oil level comparison, and the oil levels are divided; based on different types of oil level fluctuations, quantities and intervals, oil level anomaly comprehensive indexes are obtained; after the over-limit oil level is screened, an oil level abnormal factor is determined, and an oil level abnormal value is obtained in combination with the oil level abnormal comprehensive index; determining a change moment and a reaction time range based on the vibration acceleration; an acceleration oil level influence factor is determined by analyzing correlation, and a fault characteristic value is obtained in combination with an interference factor; and monitoring the oil level through the fault characteristic value. The reliability of the whole monitoring system is improved.

The invention discloses a fireproof and explosion-proof safety type transformer, and relates to the technical field of transformers, one side of the top end of an embedded fixing box is connected with an outer row fixing pipe in a penetrating manner, the top end of the inner side of the outer row fixing pipe is fixedly provided with a pressing spring, and the bottom end of the pressing spring is fixedly provided with an I-shaped clamping frame; a clamping sealing ring is fixed to the position, corresponding to the I-shaped clamping frame, of the inner side of the outer exhaust fixing pipe, a plurality of exhaust fixing holes are formed in the outer side end of the outer exhaust fixing pipe at equal intervals, and isolation double-layer sleeves are symmetrically welded to the top end of the inner side of the embedded fixing box. The situation that the environment is polluted due to the fact that transformer oil overflows when hot steam is exhausted is avoided, meanwhile, resources are recycled, resource waste is reduced, the transformer oil is supplemented in real time, stability of internal protection is guaranteed, meanwhile, an internal fire extinguishing component is used for directly conducting fire extinguishing treatment on the interior, and the environment is protected. And the condition of high-pressure deflagration and explosion caused by internal fire is avoided.

The invention discloses a high-overload distribution transformer design method based on geometric dimension reduction and multi-objective optimization, and the method comprises the steps: simplifying the three-dimensional structure of a transformer based on the axial symmetry characteristics of the transformer, building a two-dimensional axial symmetry model, and reserving the key geometric characteristics of an iron core, a winding and transformer oil; based on the two-dimensional axisymmetric model, constructing an electromagnetic-flow-heat multi-physics field coupling simulation model, calculating electromagnetic field distribution, and simulating oil flow and temperature field distribution in the transformer; based on the finite element simulation data and an improved four-vector multi-objective optimization algorithm, establishing a multi-objective optimization model, carrying out collaborative optimization on transformer structure parameters, and outputting a Pareto optimal solution set; and determining an optimal design scheme of the electromagnetic structure of the transformer according to the Pareto optimal solution set. Through the improved four-vector multi-objective optimization algorithm, the local development and global exploration capabilities are comprehensively improved, and the accuracy and diversity of the optimization scheme are improved.

The invention provides a transformer oil aging state detection method and system, and the method comprises the steps: applying a step scanning type low-frequency sinusoidal voltage signal to a to-be-detected oil sample, detecting current response, and calculating a complex dielectric constant spectrum; carrying out coarse graining processing on the dielectric loss spectrum, calculating a sample entropy, and fitting an entropy-scale curve to obtain a multi-scale entropy attenuation rate; extracting fusion parameters including relaxation peak frequency, normalized dielectric loss increment and multi-scale entropy attenuation rate; based on the fusion parameter, generating a membership degree vector of the oil sample to be detected through a fuzzy C-means clustering algorithm; and judging the aging grade of the transformer oil according to the membership degree vector of the oil sample to be detected. According to the method, the relaxation peak frequency, the normalized dielectric loss increment and the multi-scale entropy attenuation rate of the dielectric loss spectrum are combined to construct a feature space, a fuzzy C-means clustering algorithm is adopted to generate a membership degree vector, a nonlinear mapping relation between parameters and aging levels is established, the uncertainty of the aging state is quantified, and the accuracy of the aging state is improved. And non-intrusive and high-precision transformer oil state evaluation is realized.

The invention relates to the technical field of measurement and testing, in particular to a leakage detection method and system for transformer oil tank production, and the method comprises the steps: dividing a to-be-detected oil tank into a plurality of test regions; determining an ideal net pressure attenuation rate by using the average pressure drop rate, the pressure change rate corresponding to the temperature change and the volume change amount of the oil tank cavity in the target time period in the target test area; determining a pressure attenuation deviation degree by using the ideal net pressure attenuation rate and the actually measured net pressure attenuation rate; determining an acoustic activity weight by using the acoustic activity degree of the acoustic signal in the acoustic event and the background noise average energy of the plurality of test areas in the acoustic event; and determining a regional leakage comprehensive index by using the acoustic activity weight and the pressure attenuation deviation degree, and further determining the leakage detection condition of the oil tank by using the regional leakage comprehensive index. According to the technical scheme, the accuracy and reliability of leakage detection are effectively improved, environment temperature interference is effectively eliminated, and background noise changes are dynamically adapted.

The invention discloses a transformer oil tank, and relates to the technical field of power transformers, the transformer oil tank comprises an oil tank body and a plurality of groups of fin mechanisms, and each group of fin mechanism comprises radiating fins with cavities formed inside. The cooling fins with the cavities are arranged on the outer side of the oil tank body, the slidable adjusting plate and the driving assembly are matched, the effective oil storage volume of the cooling fins can be flexibly adjusted according to the environment temperature, the maximum cooling area is guaranteed in the non-low-temperature environment so that efficient cooling can be achieved, the cooling contact area is reduced in the low-temperature environment, and the service life of the oil tank is prolonged. Wax precipitation and viscosity increase caused by excessive cooling of the cooling oil are avoided, so that the insulating property and the circulating fluidity of the cooling oil are maintained, the circulating stirring mechanism can promote efficient circulation of the cooling oil between the oil tank and the fins under driving of the driving mechanism, and the heat dissipation efficiency is further improved; the problems of heat dissipation and insulation performance of the oil-immersed transformer in a low-temperature environment are effectively solved, and the operation reliability and environmental adaptability of equipment are improved.

The oil-immersed transformer oil tank sealing anti-seepage structure comprises a transformer oil tank, a fixing assembly and an end cover are arranged at the upper end of the transformer oil tank, the transformer oil tank is connected with the end cover through the fixing assembly, and a jacking mechanism, a transmission assembly and a pressing assembly are arranged at the upper end of the end cover; the jacking mechanism provides power for the pressing assembly through the transmission assembly. The lower end of the end cover is fixedly connected with a sealing ring and a sealing air bag, the side end of the sealing air bag is fixedly connected with a connecting pipe, the end, away from the sealing air bag, of the connecting pipe penetrates through the end cover and is fixedly connected with the end cover, and the connecting pipe communicates with the pressing assembly. By arranging the fixing assembly, the sealing ring and the sealing air bag, double-layer sealing can be achieved at the joint of the end cover and the transformer oil tank, and therefore leakage of transformer oil is effectively prevented.

The invention provides a transformer oil-water exchanger leakage early warning and protection method based on a cooler body. According to the leakage early warning and protection method for the oil-water exchanger of the transformer based on the cooler body, accurate early warning and positioning can be achieved in the early stage of tiny leakage of the oil-water exchanger of the cooler body, water is effectively prevented from entering a main oil way of the transformer by automatically isolating the faulty cooler, and the leakage of the oil-water exchanger of the transformer is prevented. And the system response speed and the operation reliability are obviously improved.

The invention discloses a transformer oil leakage detection algorithm based on improved YOLOv8, and the algorithm comprises the following steps: obtaining transformer data, carrying out the preprocessing of the transformer data, and obtaining the preprocessed transformer data; extracting the preprocessed transformer data by adopting a backbone network to obtain multi-scale feature data; embedding the simple parameter-free attention module into the original neck network to obtain a target neck network, and inputting the multi-scale feature data into the target neck network for multi-scale fusion to obtain fused feature data; executing a detection task on the fused feature data by adopting a head network to obtain oil leakage detection information; and removing redundant detection frames in the oil leakage detection information by using a non-maximum suppression algorithm to obtain an oil leakage detection result of the transformer. According to the method, the problems that a YOLOv8 model cannot cope with a complex environment and the detection accuracy is not high are solved.