1886 results about "Transformer oil" patented technology

The invention discloses an on-line detection method for gas in transformer oil based on photoacoustic spectrum self-correction, and relates to the technical field of spectrum detection and power equipment state monitoring, and the method comprises the following steps: S1, emitting modulation laser with a specific wavelength to a gas sample released by the transformer oil through a laser, and exciting gas molecules to generate photoacoustic signals; and S2, detecting the photoacoustic signal by using a photoacoustic sensor, converting the signal into an electric signal, and outputting the electric signal. According to the online detection method for the gas in the transformer oil, the correction coefficient is adjusted in real time through a self-correction algorithm, errors caused by light path changes and sensor aging are effectively compensated, the precision and stability of long-term detection are remarkably improved, and the detection accuracy is improved by combining a gas spectrum database and a mode recognition algorithm. According to the method, accurate qualitative and quantitative analysis of various gases is realized, the problem of cross sensitivity of multiple components is solved, and the method also has temperature and pressure compensation functions and can automatically adapt to environmental changes.

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 relates to a transformer multi-physics field coupling numerical simulation method and device and a storage medium. The method comprises the following steps: performing coupling calculation on a target working condition by using an electromagnetic, heat, flow and force coupling calculation model of a transformer to obtain transformer loss data and temperature rise data; mapping the temperature rise data to a transformer electromagnetic and force coupling calculation model by using a grid node data mapping method to serve as an initial value, and performing coupling calculation on a target working condition to obtain dynamic data of an internal structural member of the transformer; performing fast Fourier transform on the dynamic data in a preset frequency range to obtain dynamic data under each frequency; and mapping the temperature rise data and the dynamic data under each frequency to a transformer sound and force coupling calculation model as initial values, and carrying out coupling calculation on a target working condition to obtain transformer oil tank vibration and external noise data. Compared with the prior art, the method has the advantages that the calculation amount is effectively reduced, and the accuracy of predicting the internal state of the transformer is improved.

The invention discloses a fault detonation simulation test method and platform for an extra-high voltage converter transformer network side bushing, and the method comprises the steps: providing a critical value calculation method for primary physical explosion and secondary chemical explosion of the extra-high voltage converter transformer network side bushing under different arc fault energy conditions; and the critical conditions of primary physical explosion and secondary chemical explosion can be accurately judged. According to the invention, the whole dynamic evolution process from rapid cracking of transformer oil and sudden pressure increase caused by converter transformer fault arc to superposition of physical explosion and explosion chemistry can be truly simulated, a grid-side bushing fault detonation critical discrimination method is provided, and technical parameters and theoretical support are provided for the explosion-proof and pressure-relief design of the converter transformer.

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 oil temperature monitoring system and method for an oil-immersed transformer, and relates to the technical power equipment state monitoring field, and the system comprises a temperature sensor module, a data acquisition module, a data processing and analysis module, an early warning module and a fault diagnosis module; the temperature sensor module comprises a plurality of temperature sensors distributed at different positions of the oil-immersed transformer and is used for acquiring oil temperature data in the transformer in real time; the data acquisition module is connected with the temperature sensor module and is used for collecting oil temperature data acquired by a temperature sensor and transmitting the data to the data processing and analyzing module; the data processing and analyzing module is used for processing and analyzing the collected oil temperature data; the early warning module is used for sending out an early warning signal when the data processing and analyzing module detects that the oil temperature is abnormal or predicts that the hot spot temperature exceeds a safety threshold value; according to the invention, the problem that the fault of the transformer cannot be accurately monitored and intelligently diagnosed is solved.

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 fault detection method based on gas in oil and related equipment, relates to the technical field of power equipment monitoring, and effectively solves the problem that the content difference of characteristic gas of the same fault type is large under different transformer oil temperatures due to the fluctuation of the transformer oil temperature in the traditional method by adopting the technical scheme. The detection system eliminates the influence of the oil temperature change on the gas content through oil temperature correction and standardization processing, so that the fault judgment of the transformer is more accurate and reliable. And meanwhile, the detection system adopts the characteristic gas ratio matrix to judge the fault type, so that misjudgment possibly caused by pure dependence on a content absolute value is avoided, and the accuracy and reliability of transformer fault diagnosis are improved.

The invention discloses a transformer fault diagnosis method based on a time-frequency domain feature interactive fusion network. The method comprises the following steps: data collection: collecting a data set of dissolved characteristic gas in transformer oil with a marked type; data preprocessing: removing obvious error data through data cleaning, and then processing unbalanced data by using oversampling and downsampling; fault type judgment is carried out based on three pairs of ratio coding combinations of gas; network construction: constructing an interactive fusion network based on time-frequency domain features; network training: inputting the training data set into the constructed network for network training; and fault classification: inputting the test data set into the trained time-frequency domain feature-based interactive fusion network to obtain a classification result. The method improves the feature expression capability, reduces the overfitting risk, improves the accuracy and efficiency of fault diagnosis, and can be used in the field of transformer operation and maintenance.

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 discloses vacuum degassing and automatic oiling equipment for a transformer, and relates to the technical field of transformer oiling. Comprising an oil injection device, the bottom of the oil injection device is provided with an anti-bubble suction part, and the anti-bubble suction part is used for preventing bubbles; a mistaken suction prevention part is mounted on the bubble prevention suction part; the mistaken suction prevention part is used for preventing transformer oil from being sucked mistakenly; a floating lifting adapter is mounted on the oil injection device; a film spacer is mounted on the floating lifting adapter; the film spacer is used for spacing new oil and old oil; the thin film spacer can be matched with the floating lifting adapter, so that new oil and old oil are isolated during oil change, mixing of the new oil and the old oil can be reduced, oil change quality is improved, and waste of the new oil is reduced; the problems that an existing transformer vacuum degassing automatic oiling device can only conduct small-amount oiling generally when a transformer does not stop working, and new and old oil isolation replacement oiling is not convenient to conduct are solved.

The invention relates to the technical field of transformer oil level detection, and discloses an oil level detection system for a liquid-immersed transformer, and the system comprises a detection module which is disposed in an oil cavity of the transformer, and the detection module is configured to obtain temperature data, oil level data and vibration data in the oil cavity of the transformer; the central control module is electrically connected with the detection module, and the central control module is configured to correct the oil level data according to the temperature data and the vibration data; and the early warning module is electrically connected with the central control module, and the early warning module is configured to determine whether to send early warning information or not according to the corrected oil level data. Intelligent correction and risk judgment can be carried out on the oil level information based on the multi-source sensing data, and the accuracy of transformer oil level monitoring and the reliability of early warning response are remarkably improved.

The invention discloses a method, device and system for classifying and recognizing impurity particles in transformer oil and a medium, and the method comprises the steps: obtaining an image of the impurity particles in the transformer oil in real time, taking the image as an original image, and forming a data set based on the original image; preprocessing the original image in the data set to obtain a preprocessed image; a K-means + + algorithm is adopted to generate a new prior frame; according to the new prior frame, training a YOLO target detection algorithm to obtain a trained YOLO target detection model; and performing target detection on the preprocessed images based on the trained YOLO target detection model, automatically identifying different types of impurity particles, automatically counting the number of prediction frames on all the images, and outputting the number of different types of particles. According to the invention, the accuracy and efficiency of monitoring the particle impurities in the transformer oil can be effectively improved, and important reference is provided for state evaluation and fault detection of the transformer.

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 discloses a low-loss double-reverse-star rectifier transformer for a hydrogen production system, and relates to the technical field of double-reverse-star rectifier transformers, the low-loss double-reverse-star rectifier transformer comprises a box body, cooling fins, a coil, a connector lug, a supporting box and a cooling module, the cooling fins are installed on the outer wall of the box body, the coil is installed on the inner wall of the box body, the connector lug penetrates through the top of the box body, and the supporting box is arranged in the box body. One end of the connector lug is connected with the outer wall of the coil, and a supporting box is installed on the outer wall of the box body. The oil pump is started to suck transformer oil in the box body into the continuous bow-shaped pipe, at the moment, the first fan is started to generate wind power to blow to the surface of the continuous bow-shaped pipe, so that the transformer oil in the continuous bow-shaped pipe is cooled, and the cooled transformer oil enters the box body again through the discharge head; at the moment, a first motor rotates to drive a first beating head to rotate, the first beating head rotates to drive a T-shaped frame to move, the T-shaped frame moves to drive a first spring to move, and the first spring moves to enable the T-shaped frame to drive a ram to move.

The invention discloses an automatic control method and system for transformer substation maintenance, operation and maintenance supervision based on data analysis, and belongs to the technical field of transformer substation maintenance, and the method comprises the steps: collecting multi-source monitoring data of a transformer substation, including voltage, current, transformer oil temperature, partial discharge signals, GIS equipment vibration frequency and insulating oil chromatographic data; performing time sequence processing on the multi-source monitoring data to generate time sequence monitoring data, performing filtering processing on power frequency noise in the time sequence monitoring data by adopting a Daubechies wavelet basis function, and performing feature extraction to obtain time sequence processing data; inputting the time sequence processing data into a pre-constructed long short-term memory network model for fault prediction to obtain an equipment fault probability prediction value; when the equipment fault probability prediction value exceeds a preset threshold value, triggering a multi-stage early warning signal and executing an automatic control operation; and according to the maintenance record data, calculating a fault recovery rate and an operation stability index, and generating a maintenance evaluation report.

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 provides a system and method for detecting free carbon particles in transformer oil based on a microelectrode array, and the system comprises a sampling module which comprises an oil inlet pipeline and a filtering device, an oil sample is conveyed to a microelectrode array sensor module from a transformer oil tank through the oil inlet pipeline, and the filtering device is located in the oil inlet pipeline; a filter membrane is arranged in the filter device to remove impurities in the oil sample; the microelectrode array sensor module comprises a microelectrode array sensor, the microelectrode array sensor is nanoelectrodes arranged on a silicon substrate, the surface of the microelectrode array sensor is coated with graphene oxide to adsorb free carbon particles in an oil sample, and when the free carbon particles are adsorbed to the surface of the microelectrode array sensor, an adsorption signal is generated; and the signal processing unit is used for extracting the characteristic frequency and intensity of the vibration of the carbon particles in the adsorption signal, and classifying the carbon particles according to the characteristic frequency and intensity of the carbon particles. The device is compact in structure, the maintenance cost is reduced, and the operation process is simplified.

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 discloses a multi-mode online detection method and system for transformer oil, and relates to the technical field of online monitoring of transformer oil, and the method comprises the steps: deducing a dielectric constant based on a Maxwell equation and an electric displacement invariant principle in combination with a real-time voltage; segmenting, marking and sharpening a real-time visual image by combining a curvature prior smoothing approximation algorithm with a segmentation mark sharpening method; performing denoising enhancement on the real-time thermodynamic image by adopting a filtering mapping enhancement method to generate a real-time enhanced thermodynamic image, and deducing the temperature based on region screening and colorimetric mapping; deriving an acid value based on the gray value of the second target visual image in combination with a fluorescence standard curve, obtaining the actual height of an oil column in a third target visual image through an improved edge detection and scale scaling method, and calculating the change height of the oil column to reflect the viscosity; an aging index is generated through analysis of a logic regression device, and whether to adjust a monitoring interval or send an early warning prompt is dynamically decided based on an early warning decision mechanism, so that online self-adaptive detection and early warning of the transformer oil are realized.

The invention provides a transformer fault diagnosis method, system and device and a medium, and belongs to the technical field of power equipment fault diagnosis, and the method comprises the following steps: obtaining sample data of dissolved gas in transformer oil; carrying out weight calculation on the features of the sample data by using a Relief-F algorithm, and sorting and screening out an optimal feature set for transformer fault diagnosis according to the weights of the features; inputting features in the optimal feature set into a deep neural network model, training the deep neural network model, and in the training process, optimizing parameters of the deep neural network model by using a Tianying algorithm to obtain a transformer fault diagnosis model; and obtaining a to-be-tested sample of the transformer, and inputting the to-be-tested sample of the transformer into the transformer fault diagnosis model to obtain a transformer fault diagnosis type. According to the invention, the accuracy of fault diagnosis can be improved.

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 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 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.