35results about How to "Data deviation is small" patented technology

The invention discloses a cooling water system flow switch verification method and system, and relates to the technical field of flow switch verification, and the method comprises the steps: detecting the current flow in real time through a flow adjusting device, comparing the current flow with a preset standard flow value, and adjusting the current flow to a preset reference state; according to the working condition of a cooling water system and the characteristics of a flow switch, the cooling water flow is adjusted through a self-adaptive flow adjusting algorithm, and data collection is conducted at multiple flow points; monitoring the triggering time and the response state of the flow switch at each flow point; analyzing historical response data of the flow switch through a machine learning algorithm, and identifying a potential fault trend of the flow switch; a report is generated based on the collected data and analysis results. According to the cooling water system flow switch calibration method provided by the invention, the downtime of the cooling water system is reduced, the operation efficiency of the system is improved, and the requirement for real-time calibration in an industrial process is met. And data deviation caused by temperature and pressure fluctuation is reduced.

The invention relates to the technical field of artificial intelligence, and discloses an AI-assisted data quality intelligent monitoring and analysis method. According to the AI-assisted data quality intelligent monitoring and analysis method, through a multi-step processing flow, multi-dimensional power data can be acquired in real time, timestamp marking can be performed, missing values and abnormal values can be effectively identified, missing value complementation is performed by adopting an interpolation method, so that data deviation is reduced, and in the feature extraction stage, the data quality is improved. The average power and the standard deviation of the power data are calculated, the volatility of the data is quantified, the data features are richer and more comprehensive, the power data quality prediction model generated through training of the support vector machine can comprehensively consider multiple dimensions such as the integrity, the accuracy, the consistency and the timeliness of the data for evaluation, and the evaluation efficiency is improved. Excessive dependence of a traditional method on a single index is avoided, and the real situation of power data quality is comprehensively reflected.

The invention provides an annotation data generation method and system based on a large language model, and the method comprises the steps: S1, obtaining a structured text of a representative contract of the same category, and generating a corresponding information extraction template based on the obtained structured text of the representative contract; s2, generating annotation data in batches based on the information extraction template and all contract texts in the same category; s3, summarizing different types of annotation data and corresponding contract texts, generating an annotation data set, and performing fine adjustment on the large language model by utilizing the annotation data set to obtain a fine-adjusted large language model; and S4, marking the contract text based on the fine-tuned large language model.

The invention discloses a method for predicting the performance of a carbon nano tube film based on WGAN-GP and Super Learner ensemble learning. According to the method, the high-quality synthetic data is generated through the WGAN-GP, so that the training data set is expanded. And then, a Super Learner ensemble learning model is utilized to combine a plurality of regression models, so that the precision and generalization ability of performance prediction are improved. According to the model, through a multi-level learning structure, the problems of data scarcity and noise are effectively solved while efficient training is kept. The method not only can accurately predict the performance of the carbon nanotube film, but also has high expandability, and is suitable for predicting and analyzing the performance of other materials. According to the invention, the limitation of processing small sample and high noise data in the prior art is overcome, and an efficient and reliable performance prediction tool is provided for the fields of material science and engineering.

The invention provides a complex industrial contract information extraction method and system based on a large language model, and the method comprises the steps: S1, carrying out the clustering analysis of different obtained industrial contract texts, and determining a cluster where each contract text is located; s2, stratified sampling is carried out on each cluster, and representative samples are obtained; s3, carrying out key content extraction meeting a preset requirement on the representative sample corresponding to each cluster; obtaining a corresponding structured text based on the extracted key content meeting the preset requirement; s4, labeling the structured text to obtain labeled data; step S5, acquiring annotation data of all clusters to generate an annotation data set, and performing fine tuning on the large language model by using the annotation data set to obtain a fine-tuned large language model; and S6, deploying the fine-tuned large language model into a production environment, and extracting key information, meeting a preset requirement, of the unlabeled contract text.

The invention relates to the field of sensor data processing, and discloses a sensor response time synchronous matching method in UCTD in a complex turbulence environment, which comprises the following steps: generating different flow rates and turbulence intensities by using a temperature control water flow tank, and placing a UCTD probe in the temperature control water flow tank to measure temperatures and conductivities under different flow rates and turbulence intensities; recording the response time of the temperature and conductivity sensor in the UCTD under different flow velocities and turbulence intensities; performing polynomial regression analysis on the recorded experimental data, and establishing a temperature and conductivity sensor response time model; minimizing an error between a predicted value and an actual value of the model by using a gradient descent method, and optimizing parameters in the model; and establishing a synchronous response time model by using the optimized model, and performing synchronous matching on the response time difference of the temperature sensor and the conductivity sensor. According to the method disclosed by the invention, the data accuracy and reliability of the UCTD in marine environment monitoring are greatly improved.

An automobile transmission shaft precision detection device belongs to the technical field of automobile transmission shaft detection and comprises a base, a side plate A and a side plate B are fixedly mounted on the upper surface of the base, a threaded rod is rotatably mounted between the side plate A and the side plate B, the outer surface of the threaded rod is in threaded connection with a sliding table, and a supporting plate is fixedly mounted on the upper surface of the sliding table. A rotating rod is rotatably installed in the supporting plate in a penetrating mode, a motor is fixedly installed on the left surface of the supporting plate, an abutting block is fixedly installed at the right end of the rotating rod, an I-shaped clamping plate is rotatably installed in the side plate B in a penetrating mode, a plurality of axis positioning grooves are formed in the left surface of the I-shaped clamping plate, and the circle centers of the axis positioning grooves and the circle center of the abutting block are located at the same transverse horizontal position. According to the utility model, the whole process of determining the axis position of the automobile transmission shaft is simple and rapid to operate, the data deviation of subsequent detection can be effectively reduced, and the accuracy of a detection result is ensured.

The invention belongs to the technical field of federated learning and software defect prediction, and particularly relates to a high-robustness heterogeneous software defect prediction algorithm based on federated learning. According to the algorithm, firstly, local data of a participant is preprocessed by utilizing Tomek links and an One-Site Selection (OSS) algorithm, and the problem of class imbalance is relieved; a representative feature subset is selected through chi-square test, and the number of features of data of each participant is unified. A local convolutional neural network is constructed by each participant, and data is divided into a training set and a test set. According to the method, the robustness of the model under the tag noise condition is enhanced by introducing Client Confidence Reweighted (CCR) and an improved Bootstrap Loss loss function, knowledge exchange is carried out through KL divergence, the communication overhead is reduced, and the model performance is improved. Finally, the model is trained and verified, efficient and accurate software defect prediction is achieved, the problems of data isomerism and label noise are effectively solved, and prediction precision and efficiency are improved.

The invention relates to the technical field of artificial intelligence questions, in particular to an analysis report generation method based on a question result of a large language model, which comprises a question system for obtaining the question result according to a question input by a user, and further comprises the step of constructing a report template database. The method comprises the following steps: S1, vectorizing a natural language; s2, in the Weaviate vector database, selecting a cue word with the maximum similarity value to match a cue word template; and S3, if the matching is successful, performing secondary calculation on the question number result according to the cue word template, combining the question number result and the secondary calculation result to form report data, filling the report data into a report template associated with the current cue word template, and generating a complete analysis report. According to the method, the data processing efficiency and reliability are greatly improved, meanwhile, the labor cost is reduced, and optimization and innovation of a data analysis process are promoted.

The invention relates to the technical field of desert environment monitoring, and discloses a desert ecological environment monitoring and early warning method and system, and the method comprises the steps: determining the vegetation index and soil spectrum characteristics of a monitored region according to an aerial image of the monitored region, and evaluating the monitoring score of the monitored region; and according to a relationship between the monitoring score and a historical monitoring score, determining to carry out environment monitoring on the monitored area, and when the monitoring score is smaller than the historical monitoring score, carrying out environment monitoring on the monitored area. And according to the soil data and the environment data of the monitored area, determining a soil score and an environment score of the monitored area, and evaluating a quarantine score of the monitored area. And obtaining a historical quarantine score of the monitoring area in adjacent time periods, and determining an early warning level of the monitoring area according to a quarantine score difference value between the quarantine score and the historical quarantine score. According to the method, the ecological state is evaluated in time by comprehensively analyzing the data of the monitored area, so that early warning and effective management of desertification are realized.

The utility model discloses a kind of automobile stabilizer bar detection tool, it is related to automobile detection technical field, including box, two motors are installed in the inside of box, the one end of each motor is connected with screw rod, the outer wall of screw rod is connected with support with thread, the top end side of support is equipped with hydraulic cylinder, the telescopic end of hydraulic cylinder is connected with push rod, the outer wall of push rod is slidably connected with two push blocks, the inner wall of each push block is equipped with sliding slot, each push block is slidably connected with push rod by sliding slot;In the utility model, balanced force of stabilizer bar is realized by three-point positioning using fixing assembly, actual installation working condition is simulated, local stress concentration problem caused by traditional single-point, two-point clamping is avoided, ensure that stabilizer bar is evenly stressed during detection process, avoid deformation or damage caused by improper clamping, reduce the data deviation generated by clamping problem, improve detection accuracy.

The present invention relates to the field of vehicle-mounted intelligent interaction technology, and in particular to a method and system for enhancing tactile feedback of a vehicle-mounted intelligent surface, comprising the following steps: S1: collecting multi-touch input data on the vehicle-mounted intelligent surface and driving status data of the vehicle; S2: correcting the touch point positions in the multi-touch input data using a dynamic weighting algorithm; S3: identifying and eliminating false touch data that does not meet preset conditions; S4: calculating the true position of each touch point and generating a touch point position mapping table; S5: configuring parameters of a tactile feedback system; S6: optimizing the intensity and frequency of tactile feedback in real time to meet the needs under different driving conditions; the present invention optimizes the accuracy and adaptability of tactile feedback of the vehicle-mounted intelligent surface through dynamic weighting and adaptive regression algorithms, effectively reduces data deviations caused by dynamic changes of the vehicle, ensures the real-time and accuracy of tactile feedback, and thus improves the intuitiveness and safety of driving experience.

The invention discloses a multi-modal physiological signal dynamic impedance adaptation and synchronous acquisition system, which belongs to the technical field of multi-modal data acquisition, and comprises a plurality of multi-modal data acquisition terminals, a relay gateway and an upper computer, the multi-modal data acquisition terminals are connected with the relay gateway, and the upper computer is connected with the relay gateway; each multi-modal data acquisition terminal comprises a multi-modal data acquisition end, a control module, a wireless communication module and a storage module, the multi-modal data acquisition end is used for acquiring multi-modal data, the control module receives data transmitted by the multi-modal data acquisition end and transmits the received data to the storage module and the relay gateway, and meanwhile, the wireless communication module transmits the received data to the relay gateway. The impedance is dynamically adapted to improve the input signal quality of the multi-modal data acquisition end; the storage module is used for storing data transmitted by the control module, and the wireless communication module is used for transmitting signals. By adopting the system, the portability of equipment and the wearing comfort of a user are improved, and the synchronization precision is high.

The invention provides a threshold self-adaptive noise reduction gesture recognition method and system based on surface electromyography in the technical field of gesture recognition, and the method comprises the following steps: S1, obtaining a large number of historical surface electromyography signals for recognizing gestures, preprocessing the historical surface electromyography signals, and constructing a data set; s2, creating a gesture recognition model based on a feature extraction module, a self-adaptive noise reduction module and a gesture classification module; the feature extraction module, the adaptive noise reduction module and the gesture classification module are connected in sequence; s3, training a gesture recognition model through the data set, and continuously optimizing hyper-parameters of the gesture recognition model in the training process; and S4, deploying the trained gesture recognition model, and performing gesture recognition by using the deployed gesture recognition model. The method has the advantage that the gesture recognition precision is greatly improved.

The application relates to a multi-parameter water quality monitoring device which comprises a turbidity sensor, a flow cell, a residual chlorine sensor, a PH sensor and a conductivity sensor; the turbidity sensor is suitable for being connected to a water inlet; the flow cell is internally provided with a residual chlorine sensor bin, a PH sensor bin, a conductivity sensor bin and a connecting channel; the residual chlorine sensor bin, the PH sensor bin and the conductivity sensor bin are vertically arranged; the connecting channel is horizontally arranged and is in communication with the bottoms of the residual chlorine sensor bin, the PH sensor bin and the conductivity sensor bin; the residual chlorine sensor is arranged at the internal top end of the residual chlorine sensor bin; the PH sensor is arranged at the internal top end of the PH sensor bin; and the conductivity sensor is arranged at the internal top end of the conductivity sensor bin; the flow cell is further internally provided with a pressure stabilizing bin; the pressure stabilizing bin is vertically arranged, the bottom of the pressure stabilizing bin is connected with the end of the connecting channel, the top of the pressure stabilizing bin is connected with the turbidity sensor, and the end of the connecting channel, which is away from the pressure stabilizing bin, is provided with a water outlet.

The invention relates to the technical field of heat exchange equipment, and provides a tube bundle type heat exchanger, a heat exchange performance calibration method thereof and a thermo-acoustic engine. The tube bundle type heat exchanger comprises a shell, a heating piece and a tube bundle, the shell comprises a heat exchange cavity and a working cavity, the heat exchange cavity and the working cavity are arranged at an interval, and liquid metal is arranged in the heat exchange cavity; the heating piece penetrates through the heat exchange cavity and is used for heating the liquid metal; the tube bundle penetrates through the heat exchange cavity and is spaced from the heating piece, openings in the two ends of the tube bundle communicate with the working cavity, and the tube bundle is used for conveying working gas. According to the tube bundle type heat exchanger, a uniform temperature field is formed through the combination of the heating piece and the liquid metal, the power of the heating piece can be directly used as reference data for measuring the heat exchange performance of the tube bundle type heat exchanger, and heat sources such as high-temperature flames and high-temperature flue gas do not participate in the heat exchange process of the tube bundle type heat exchanger; in other words, complex radiation and convective heat exchange modes do not exist, and the difficulty of accurate evaluation of the performance of the heat exchanger is effectively reduced.

The invention discloses an acoustic radar near-surface wind speed inversion method and system based on entropy weight feature fusion, and the method specifically comprises the steps: carrying out the preprocessing of acoustic radar frequency spectrum data, and obtaining the preprocessed frequency spectrum data; based on the preprocessed spectrum data, constructing a Doppler window dynamic migration model based on turbulence dynamics power law distribution; on the basis of a Doppler window dynamic migration model, candidate spectrum peaks are selected at each height layer, a feature space is constructed, feature weights are dynamically distributed by using an information entropy theory, and an optimal spectrum peak is selected; introducing a symmetry constraint optimization strategy to the optimal spectrum peak, detecting the profile symmetry of the wind spectrum in the symmetric direction, and calibrating an asymmetric result to obtain a target wind speed inversion result; and comparing and evaluating the target wind speed inversion result and the wind speed of the anemometer tower as a reference to complete inversion result verification. According to the method, the wind speed inversion precision of the acoustic radar in a complex environment is effectively improved, and better evaluation and efficient utilization of wind energy resources are promoted.

The invention belongs to the field of circuit detection, and provides a real-time detonation signal generation circuit and a detection method, and the method comprises the steps: transmitting a low-voltage instruction, carrying out the networking of an electronic delay module, and charging to enter a to-be-detonated state; the ignition high voltage generating circuit generates ignition high voltage, and load current caused by M6 conduction is generated on a gun line; starting exploder current detection, completing gun line current detection within a set time, analyzing and processing the change of gun line current to obtain a continuous characteristic value and an initiation current ratio, calculating, analyzing and processing the obtained continuous characteristic value and initiation current ratio to obtain a gun line current stable value, and dividing the gun line current stable value; the detonation current is compared with the reference current to obtain the starting moment, the delayed ignition time is the detonation moment, a real-time detonation signal is immediately sent to a detonation system after delay, abnormal problems possibly occurring in a circuit are detected and fed back in time, and the precision and reliability of detonation operation are improved.

This application discloses a method, system, equipment, medium, and product for calculating the carbon footprint of recycled building materials, relating to the fields of product life cycle assessment and carbon footprint accounting technology. The method includes: establishing a life cycle inventory of the source processes corresponding to inorganic solid waste based on the quality allocation method and / or economic value-added allocation method, and constructing a regionalized carbon emission factor database; introducing actual production line operation data as a calibration benchmark, verifying, correcting, and supplementing the activity level data of each unit process node, and constructing an activity level dataset; standardizing the emission factors and activity level data according to standardized accounting rules, constructing a general framework model for calculating the carbon footprint of recycled building materials, and calculating the stage emissions and the carbon footprint accounting results of recycled building materials based on the processed emission factors and activity level data. This application unifies the methodology, improves data quality and availability, and constructs a general and flexible accounting model.

The utility model relates to the field of auxiliary frock provides a kind of anti-roll bar link assembly device. Anti-roll bar link assembly device includes base;First clamping component, setting in base, first clamping component includes the clamping groove of being set in pair, clamping groove is used to place the node mandrel of anti-roll bar link, first clamping piece is arranged in clamping groove for the node mandrel clamped in clamping groove;Second clamping component, setting in base, second clamping component includes clamping rod, clamping rod is used to the bearing of the rod end of anti-roll bar link clamped between clamping rod and base. The anti-roll bar link assembly device can firmly fix node mandrel, avoid the positioning deviation caused by the thickness change of mandrel;Can eliminate the wobble clearance of rod end bearing;Reduce the data deviation after assembly;Adjustable first clamping piece can be adapted to node mandrel of different thickness without replacing parts, save the changeover adjustment time of traditional frock.

The present invention provides a pipe pile offset data collection auxiliary device, including a top plate, a rectangular frame fixedly installed at the bottom of the top plate, two arc-shaped clamping plates symmetrically arranged on the inner side of the rectangular frame, a clamping and positioning mechanism for controlling the relative movement of the two arc-shaped clamping plates arranged in the rectangular frame, a lifting bracket arranged at the bottom of the rectangular frame, a rectangular frame arranged above the top plate, four support rods symmetrically fixedly installed on the lower side of the rectangular frame, and a clamping and supporting mechanism for fixing and supporting the RTK carbon fiber rod arranged in the rectangular frame. The height of the present invention is adjustable, and the clamping and positioning mechanism is used to control the two groups of arc-shaped clamping plates and arc-shaped clamping pads to symmetrically clamp the two sides of the pipe pile, and the top plate is adjusted to be concentric with the pipe pile, so as to facilitate the rapid identification of the center of the pipe pile for measurement using the RTK instrument, and the RTK instrument can be supported, so as to facilitate the user to record data, and the work can be completed by one person, saving time and effort, and the components are easy to disassemble and assemble, and easy to carry and use.

The disclosed embodiment provides a method, device, electronic device and computer-readable storage medium for predicting the number of infectious diseases, belonging to the field of medical data technology. The method for predicting the number of infectious diseases includes: correcting the original medical data related to the target disease, obtaining the corrected data corresponding to the original medical data; determining multidimensional feature data in combination with the corrected data and the associated data corresponding to the target disease; predicting according to the multidimensional feature data corresponding to the reference time before the target time, so as to determine the number of cases belonging to the target disease for the target time. The disclosed embodiment can improve the accuracy of case number prediction.

This invention relates to the field of wastewater treatment technology, and discloses a method and system for processing water treatment efficiency data in recirculating aquaculture systems (RAS). The method includes: assessing the influence of trace element parameters in standard water quality data of the RAS area on the RAS area, and converting them into influence weights corresponding to the trace element parameters; adjusting the influence weights based on the synergistic and antagonistic reactions between trace elements in the standard water quality data to obtain optimized influence weights; merging the trace element parameters and optimized influence weights into a comprehensive water treatment efficiency index for the RAS area; determining that the RAS area is in an inefficient operating state when the comprehensive water treatment efficiency index is lower than the lower limit of the historical threshold range; and selecting water quality adjustment strategies corresponding to the inefficient operating state from a preset water quality adjustment strategy library. This invention can improve the efficiency of RAS water treatment efficiency data processing.

This invention proposes an apparatus and method for evaluating the thermal oxidative stability of liquid compounds based on pressure measurement, belonging to the technical field of chemical analysis experimental apparatus. The apparatus includes an oxygen supply unit, a reaction unit, a cooling unit, and a pressure measurement unit. The oxygen supply unit controls the vacuuming and oxygenation of the apparatus. The reaction unit achieves precise temperature control and homogenization of the reaction liquid through a high-temperature heating circulating bath and a magnetic stirrer. The cooling unit eliminates interference from volatile products on pressure measurement through a cryogenic trap. The pressure measurement unit collects system pressure data in real time using a high-sensitivity pressure transmitter and transmits it to a computer. The method involves evacuating the apparatus and then oxygenating it to a set pressure, heating and maintaining the reaction temperature, monitoring system pressure changes through the pressure transmitter, and recording data and calculating oxygen consumption on the computer. This invention can track the oxygen consumption rate in real time, reveal the oxidation pattern, and is suitable for rapid and accurate evaluation of the thermal oxidative stability of various liquid compounds.

According to the microfluidic system capable of improving the cell recovery rate, provided by the invention, after liquid drops are generated, the liquid drops which are not wrapped by DNA tags are separated from the liquid drops which are successfully wrapped by the DNA tags through the high-precision liquid drop sorting module, and the sorting aims at ensuring that the unmarked liquid drops can be effectively reused in subsequent steps. And fusing the sorted liquid drops which are not coated with the DNA labels and the liquid drops coated with the DNA labels again under the action of a liquid drop fusion module, so as to complete the re-labeling of the cells. According to the innovative step, the cells which are not effectively marked in the primary droplet generation process are reused, so that the recovery rate and the utilization rate of the cells are greatly improved, the initial quantity of the cells required by an experiment is reduced, the waste of cell samples, especially precious cell samples, is avoided, and the cost is reduced. The material consumption of samples and the cost of repeated experiments are reduced.

The present invention relates to the technical field of sand content detection, and discloses a water conservancy and hydrology sand content detection system and method, the system comprising: a collection module divides the water area to be detected into a number of identical sampling ranges, and performs multi-point sampling in each range, and performs secondary sampling after a preset time interval, a judgment module calculates the sand content of each sample, and judges whether the sand content needs to be adjusted according to the sand particle size information, an adjustment module adjusts the sand content according to the sand particle size, and calculates the average sand content within the same sampling range at the same time, the adjustment module also collects water flow information, and adjusts the average sand content, and finally, a decision module summarizes the final sand content results within each sampling range and integrates them into a spatial sand content distribution map. The present invention can provide high-precision sand content detection results.

The invention relates to the technical field of flaw detection, in particular to an online flaw detection method and system for flaw detection by combining an image analysis and processing technology. Comprising the following steps: S1, obtaining detection image data, preprocessing the detection image data, carrying out grid division on the preprocessed image, and extracting features; s2, performing odd-even division on the gridded image, and calculating an angle according to a division result; and S3, constructing a prediction model and performing real-time prediction analysis. According to the method, the image data are collected at equal intervals and preprocessed, so that the calculation complexity is reduced, and the processing efficiency is improved; performing odd-even grid division, calculating an included angle, and refining defect types and severity; an LSTM model is constructed for real-time prediction, and the prediction precision and reliability are improved in combination with historical data; and finally, a closed-loop system is formed, real-time online monitoring is realized, the defect type and severity are accurately judged, the continuity and reliability of detection are ensured, and powerful technical support is provided for defect damage detection.

The invention discloses an LLM-based data set production method, system and device and a medium, and the method comprises the steps: carrying out the data collection, forming a data set containing diversified labels, and guaranteeing that the data in the data set has diversified sources; processing the data set by adopting a fair resampling algorithm: firstly, carrying out statistical analysis on data in the data set, and identifying a data category or attribute with deviation; according to the number and importance of the data samples of the data categories or attributes, weighting or re-sampling the data in the data set, so that the data set is more balanced on the whole; the diversity and fairness of a data set are enhanced by adopting an adversarial training technology; and evaluation and adjustment are carried out through indexes. According to the scheme, the diversity and fairness of the data set can be enhanced, and the performance of the LLM in practical application is improved.

The invention relates to the technical field of water quality monitoring, and discloses a depth-adjustable surface water quality monitoring sampling device, comprising an expansion mechanism, wherein the expansion mechanism also comprises a fixed plate, wherein a sliding rail is fixedly connected to the side wall of the fixed plate, before using the device, the fixed plate is fixed at a river bank position, and then the height of the adjustment plate at the outer wall of the sliding gear rod is set, and a buckle is used to control the extension length of the collection telescopic tube, and finally the whole device is put into water. At this time, due to the impact effect of the water flow, when the impact force acts on the inclined surface of the inclined plate, the water flow will push the mounting plate to tilt toward the center of the river, so that the collection mechanism approaches the center of the river, wherein the restricted cross is rotatably connected to the slider, and when the device is in use, an arc change will occur, and after the collection box reaches the designated position, the collection mechanism will be lowered, and the push spring will drive the collection telescopic tube to move down to a predetermined position, thereby completing the collection work of the device on surface water.

The utility model discloses high-precision transformer oil chromatography on-line monitoring equipment, which relates to the technical field of transformer oil chromatography on-line detection appliances, and comprises a cabinet body, the cabinet body is divided into two side areas, and one side area of the cabinet body is divided into an upper layer structure, a middle layer structure and a lower layer structure; a gear pump is installed on the bottom layer of an inner cavity of an area on one side of the cabinet body, an oil-gas separation box is installed at one end of the gear pump, an oil-gas permeable membrane is installed in the oil-gas separation box, and the oil-gas permeable membrane divides the oil-gas separation box into an oil cavity and a gas cavity. The effects of quick mounting and multi-tank placement are achieved, the problems that a traditional nitrogen tank is inconvenient to mount and dismount due to frequent use and the mounting number is small are solved, and the rapidness and durability of nitrogen tank replacement are improved; through cooperation between the gas analyzer and the data processing equipment, large-scale patrol of personnel is not needed, data deviation caused by human factors is reduced, and the real-time performance of monitoring is improved.