A calibration system and method for an on-line monitoring device for dissolved gases in transformer oil

Abstract

The application discloses a kind of transformer oil dissolved gas on-line monitoring device's calibration system and method, wherein, control module controls oil sample preparation unit and piston oil cylinder to complete oil sample preparation, determine the theoretical concentration of prepared oil sample and multiple indexes of oil sample preparation process, and multiple indexes are uploaded to cloud server, while generating calibration analysis report for on-line monitoring device, verifying the detection capability of on-line monitoring device;Cloud server stores multiple indexes into historical record database, and calculates the preparation efficiency coefficient of each oil sample preparation process, and average oil pump output power and average cycle preparation number, for optimizing subsequent oil sample preparation process.The application can realize the real-time monitoring and control of oil sample preparation state, improve the controllability and reliability of oil sample preparation process, and the calibration system has continuous optimization capability, reduces the dependence on operator experience.

Description

Technical Field

[0001] This invention relates to the field of electrical testing and oil sample analysis, specifically to a calibration system and method for an online monitoring device for dissolved gases in transformer oil. Background Technology

[0002] Transformer oil, as a crucial insulating medium in power equipment, directly impacts the safety and reliability of transformers. The types and concentrations of dissolved gases in transformer oil are essential for diagnosing internal transformer faults. Accurate calibration of the online dissolved gas monitoring device in transformer oil is a prerequisite for ensuring accurate and reliable on-site transformer operation monitoring in substations. The calibration system for the online dissolved gas monitoring device in transformer oil includes an oil storage module, an oil sample preparation module, and a calibration module. The oil sample preparation and analysis process includes steps such as oil sample collection, standard gas addition, mixing and dissolution, and concentration determination.

[0003] There are many existing calibration systems for online monitoring devices for dissolved gases in transformer oil and their standard oil sample preparation techniques, which often have the following technical problems:

[0004] First, in the existing technology, it is difficult to monitor and control the state and related parameters of the standard oil sample in a timely manner during the preparation of the standard oil sample. The efficiency judgment mostly relies on the experience of the operator, resulting in low operating efficiency and frequent repetitive operations.

[0005] Second, in the existing technology, it is difficult to accurately control the amount of standard gas added to the oil sample during the oil sample preparation process, especially for low-concentration oil samples, which causes the oil sample concentration to deviate from the target value, resulting in low preparation accuracy and poor operational controllability.

[0006] Third, in the existing technology, the preparation of standard oil samples of dissolved gases in transformer oil usually relies on fixed parameters or personnel experience. The oil sample concentration is prone to deviating from the target, the number of cycles is large and the efficiency is low. The influence of different operating parameters on the preparation results is unclear, and there is a lack of predictability and controllability.

[0007] In addition, existing technologies rarely address the error identification of the calibration system itself for online monitoring devices for dissolved gases in transformer oil, such as CN112461978A, CN107085088A, and CN106501425A, indicating room for improvement. Summary of the Invention

[0008] The summary section of this invention provides a brief overview of the concepts, which will be described in detail in the detailed description section below. This summary section is not intended to identify key or essential features of the claimed technical solutions, nor is it intended to limit the scope of the claimed technical solutions.

[0009] This invention proposes a calibration system and method for an online monitoring device for dissolved gases in transformer oil, in order to solve one or more of the technical problems mentioned in the background section above.

[0010] A first aspect of the present invention provides a calibration system for an online monitoring device for dissolved gases in transformer oil, comprising:

[0011] An oil sample preparation unit including an oil pump;

[0012] A piston-type hydraulic cylinder, one of its oil ports is connected to the oil pump outlet and sampling verification port of the oil sample preparation unit;

[0013] The control module is used to control the oil sample preparation unit and the piston cylinder to complete the oil sample preparation, determine the theoretical concentration of the prepared oil sample and multiple indicators of the oil sample preparation process, and upload the multiple indicators to the cloud server; at the same time, the control module obtains the oil sample concentration results detected by the online monitoring device through the verification function, compares them with the theoretical concentration of the verification system and the detection results of the laboratory chromatograph, generates a verification analysis for the online monitoring device, and verifies the detection capability of the online monitoring device;

[0014] A cloud server is used to store the aforementioned multiple indicators into a historical record database and calculate the preparation efficiency coefficient for each oil sample preparation process. The preparation efficiency coefficient comprehensively considers the oil pump output power and the number of preparation cycles. The cloud server also determines the corresponding average oil pump output power and average number of preparation cycles for each oil sample concentration range to optimize the subsequent oil sample preparation process.

[0015] A second aspect of the present invention provides a calibration method for an online monitoring device for dissolved gases in transformer oil, applied to the calibration system of the aforementioned online monitoring device for dissolved gases in transformer oil, comprising:

[0016] The target oil sample concentration is obtained. The control module controls the oil sample preparation unit and piston cylinder to complete the oil sample preparation. Based on the real-time monitoring of the gas addition and oil sample weight during the preparation process, the theoretical concentration of the prepared oil sample is calculated.

[0017] The online monitoring device is connected to the calibration port to detect oil samples, and at the same time, samples are taken through the sampling port to the laboratory chromatograph for analysis. The oil sample concentration results detected by the online monitoring device are obtained and compared with the theoretical concentration of the calibration system and the detection results of the laboratory chromatograph to generate a calibration analysis for the online monitoring device and verify the detection capability of the online monitoring device.

[0018] Multiple indicators during the oil sample preparation process are obtained and stored in a historical record database. The preparation efficiency coefficient for each oil sample preparation process is calculated, taking into account both the oil pump output power and the number of preparation cycles. For each set oil sample concentration range, the corresponding average oil pump output power and average number of preparation cycles are determined to optimize subsequent oil sample preparation processes.

[0019] Compared with existing technologies, the calibration system and method for the online monitoring device of dissolved gases in transformer oil provided by this invention uses a control module to control the oil sample preparation process, unifies management and data acquisition, and enables real-time monitoring and adjustment of parameters, making the oil sample concentration closer to the target value, improving operational efficiency, and enhancing the reliability and stability of oil sample preparation. Simultaneously, the cloud server stores and analyzes historical data for multiple monitoring indicators, calculating the oil sample preparation efficiency coefficient to evaluate each preparation, thus improving the controllability and real-time monitoring capability of the oil sample preparation process, ensuring the efficiency of oil sample preparation and the calibration performance of the system.

[0020] The calibration system and method for the online monitoring device of dissolved gases in transformer oil provided by this invention establishes an intuitive evaluation system for the preparation efficiency system and mines the optimal operating parameters under different concentration ranges based on historical data to guide the preparation of new oil samples, reduce the dependence on the operator's experience, and improve the predictability and automation level of the preparation process. Attached Figure Description

[0021] The above and other features, advantages, and aspects of the various embodiments of the present invention will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and elements are not necessarily drawn to scale.

[0022] Figure 1 This is a schematic diagram of the calibration system of the online monitoring device for dissolved gases in transformer oil according to one embodiment of the present invention;

[0023] Figure 2 This is a structural diagram of the calibration system of the online monitoring device for dissolved gases in transformer oil according to an embodiment of the present invention;

[0024] Figure 3 This is a flowchart of a calibration method for an online monitoring device for dissolved gases in transformer oil, according to one embodiment of the present invention.

[0025] Figure 4 This is a flowchart of a calibration method for an online monitoring device for dissolved gases in transformer oil, according to one embodiment of the present invention. Detailed Implementation

[0026] The invention will now be described in more detail with reference to the accompanying drawings. While some embodiments of the invention are shown in the drawings, it should be understood that the invention can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the invention. It should be understood that the drawings and embodiments of the invention are for illustrative purposes only and are not intended to limit the scope of protection of the invention.

[0027] It should also be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings. Unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0028] It should be noted that the concepts of "first" and "second" mentioned in this invention are only used to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0029] It should be noted that the terms "a" and "a plurality of" used in this invention are illustrative rather than restrictive. Those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0030] The names of messages or information exchanged between the various devices of this invention are for illustrative purposes only and are not intended to limit the scope of these messages or information.

[0031] The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0032] In existing standard oil sample preparation processes, the state and related parameters of the standard oil sample are difficult to monitor and control in a timely manner. Efficiency judgments largely rely on human experience, resulting in low operational efficiency and frequent repetitive operations. To address this problem, some embodiments of this invention employ a control module to control the oil sample preparation process, unifying management and data acquisition, enabling real-time monitoring and adjustment of parameters, and setting an efficiency coefficient from an efficient configuration perspective as a direct evaluation of efficiency.

[0033] like Figure 1 and Figure 2 The diagram shown is a system schematic of a calibration system for an online monitoring device for dissolved gases in transformer oil according to the present invention. Specifically, it includes an oil sample preparation unit, a piston cylinder 1, a control module 7, and a cloud server.

[0034] The oil sample preparation unit is used to prepare oil samples. The piston cylinder 1 is connected to the oil sample preparation unit. The oil sample preparation unit and the piston cylinder 1 work together to complete the oil sample preparation under the control of the control module 7.

[0035] In some embodiments, the piston cylinder 1 has an oil port on its lower side, which is connected to the oil outlet 11 of the oil sample preparation unit and the sampling and verification port 12, so that the oil sample can be smoothly transferred from the piston cylinder 1 to the online monitoring device for processing or sampling and verification. Specifically, the piston cylinder 1 is used to hold blank oil or oil sample and serves as an oil storage and distribution unit in the oil sample preparation and transportation process.

[0036] Blank oil refers to transformer insulating oil without any added standard gas, used as the base carrier for oil samples. An oil sample is oil prepared by dissolving standard gas at a predetermined concentration and type in the blank oil, used for calibration or testing of online monitoring devices. Standard gas refers to a gas of known type and concentration stored in a gas cylinder, used to dissolve in the transformer oil at a predetermined ratio to form a standard oil sample for use in the calibration or testing of online monitoring devices.

[0037] The control module is used to control the oil sample preparation unit and the piston cylinder to complete the oil sample preparation, determine the theoretical concentration of the prepared oil sample and multiple indicators of the oil sample preparation process, and upload the multiple indicators to the cloud server.

[0038] In some embodiments, the control module 7 serves as the core control and data processing unit of the calibration system, used to uniformly manage various operations and monitoring tasks during the oil sample preparation process. Specifically, the control module 7 can logically control the opening and closing of multiple valves, and can also calculate the theoretical concentration of the prepared oil sample and multiple indicators of the oil sample preparation process by collecting detection values ​​from multiple sensors, and transmit these multiple indicators to the cloud server.

[0039] The system includes multiple sensors, such as pressure sensors, temperature sensors, and a weight monitoring module. The pressure sensor reads the pressure of the gas in the standard gas volumetric container 2. The temperature sensor monitors the temperature of the oil sample in the piston cylinder 1. The weight monitoring module monitors the remaining oil sample in the piston cylinder 1 and the amount of oil entering the piston cylinder 1 each time during oil sample preparation. The theoretical concentration can be used for real-time evaluation of the oil sample preparation quality. Multiple indicators, such as the oil pump output power and the number of preparation cycles, can be used to optimize subsequent oil sample preparation processes.

[0040] The control module 7 is also used to analyze the calibration results of the online monitoring device. It detects the oil sample prepared by the calibration system through the online monitoring device, obtains the oil sample concentration result detected by the online monitoring device, and compares it with the theoretical concentration of the calibration system and the detection results of the laboratory chromatograph. It generates a calibration analysis report for the online monitoring device to verify the detection capability of the online monitoring device.

[0041] The cloud server is used to store multiple indicators into a historical database and calculate the preparation efficiency coefficient of each oil sample preparation process. For each oil sample concentration range, the corresponding average oil pump output power and average number of preparation cycles are determined. The obtained average oil pump output power and average number of preparation cycles are used to optimize the subsequent oil sample preparation process.

[0042] In some embodiments, the cloud server can establish a communication connection with the control module 7 to receive multiple indicators from the control module 7, and these indicators will be stored in a historical record database for subsequent data analysis. The cloud server can also calculate the preparation efficiency coefficient for each oil sample preparation process based on historical data in the historical record database, and calculate the corresponding average oil pump output power and average number of preparation cycles for each oil sample concentration range. These data indicators can be used to optimize the subsequent oil sample preparation process.

[0043] The preparation efficiency coefficient can be understood as a quantitative indicator of the overall efficiency of the oil sample preparation process. Its calculation comprehensively considers factors such as the oil pump output power and the number of preparation cycles, reflecting the oil sample preparation efficiency level at the target concentration, while completing the preparation of the target concentration oil sample with the lowest possible energy consumption and the shortest possible time. Among the selected factors:

[0044] The output power (P) of the oil pump directly reflects the energy consumption level of the preparation process. The higher the pump power, the higher the oil sample circulation flow rate per unit time, but the higher the energy consumption. If the power is too low, the circulation speed is slow, prolonging the preparation time. The average oil pump output power refers to the average value of the pump output power in multiple preparation processes within a corresponding concentration range. It can be used to measure the energy consumption and stability of the oil pump in the oil sample preparation process.

[0045] The number of cycles (N) directly reflects time efficiency. Based on the target air intake requirement, the air intake steps are repeated until the requirement is met. A higher number of cycles indicates a longer overall preparation time and higher time cost. The average number of cycles refers to the average number of cycles required to achieve the target oil sample concentration within a given concentration range; it can be used to reflect the operational complexity of the preparation process.

[0046] The above embodiments of the present invention, by setting a preparation efficiency coefficient, integrate the dispersed parameters in the preparation process into a single quantitative index, enabling horizontal comparison of efficiency under different preparation conditions, such as the efficiency difference between batch A and batch B. At the same time, it can also achieve optimization direction positioning, solving the drawback of relying on human experience to judge efficiency.

[0047] Specifically, in some embodiments, the calculation of the preparation efficiency coefficient can be performed in the following order: parameter standardization, weighted calculation, and result normalization, wherein:

[0048] (1) Parameter standardization is used to eliminate differences in magnitude. It converts each original parameter into a standardized value (dimensionless) that is greater than or equal to 0 and less than or equal to 1, ensuring that parameters of different dimensions can be directly used in the calculation.

[0049] Among them, the normalized value of the oil pump output power P_std:

[0050] ;

[0051] In the above formula, Pmax is the maximum allowable oil pump power of the system (e.g., 5kW), Pmin is the minimum effective power (e.g., 0.5kW), and Pactual is the actual power of this formulation. During the formulation process, the higher the oil pump output power, the higher the energy consumption cost and the worse the efficiency contribution. Therefore, the above standardized formula adopts inverse standardization.

[0052] For example, if Pactual = 2kW, Pmax = 5kW, and Pmin = 0.5kW, then The higher the standardization value, the better the energy efficiency.

[0053] The fewer the number of cycles in the preparation process, the higher the time efficiency. Therefore, the standardized value of the number of cycles (N_std) is inversely standardized.

[0054] ;

[0055] Where Nmax is the maximum number of cycles allowed by the system, exceeding which is considered an abnormal formulation; Nmin is the minimum effective number of cycles to ensure that the intake air volume is close to the target value; Nactual is the number of cycles for this formulation.

[0056] For example: if Nmax is 20 times and Nmin is 3 times, then if Nactual = 5 times, then... The higher the standardization value, the better the time efficiency.

[0057] (2) Weighted calculation: different weights can be set to adapt to different application scenarios.

[0058] After standardizing the above parameters, weights wP and wN are assigned to these standardized parameters according to actual needs, with wP + wN = 1. By selecting the weights wP and wN, priorities for different dimensions and scenarios can be adapted. The specific weights for configuring the efficiency coefficients can be determined based on historical data regression analysis or multi-objective optimization algorithms, or user-defined weights are also supported.

[0059] For example, if rapid verification is required for troubleshooting, the time efficiency weight can be increased to wN=0.4, and the power weight can be decreased to wP=0.6, i.e., wN=0.4, wP=0.6.

[0060] For example, if energy saving and consumption reduction are prioritized, such as during batch verification, the power weight can be increased (wP=0.8) and the cycle number weight can be decreased (wN=0.2), i.e., wN=0.2 and wP=0.8.

[0061] After selecting the above weights according to different dimensions and scenario requirements, the weighted calculation yields the basic efficiency value E_base:

[0062] E_base = wP × P_std + wN × N_std.

[0063] (3) Result normalization is used to present the results intuitively.

[0064] Convert E_base to a final preparation efficiency coefficient E that is greater than or equal to 0 and less than or equal to 100 for quick determination:

[0065] E = E_base × 100.

[0066] The preparation efficiency coefficient of the above embodiments of the present invention provides a correlation model between accuracy and efficiency; a higher preparation efficiency coefficient indicates that the preparation is more in line with expectations. Based on the influence of various factors in each preparation process within the preparation efficiency coefficient, subsequent optimization directions or fault locations can be identified. Furthermore, by obtaining the average oil pump output power and average number of preparation cycles for a particular batch, and referring to the above formula, the total preparation efficiency coefficient in the verification of different batches can be obtained. By comparing the total preparation efficiency coefficients of different batches, the influence of various factors in the preparation process of the corresponding batch can be accurately located, providing a precise optimization reference for subsequent oil sample preparation processes. Simultaneously, compared to the prior art where preparation evaluation relies on operator experience, is highly subjective, and lacks standardized criteria, the preparation efficiency coefficient of the embodiments of the present invention digitizes and standardizes the evaluation process. Different operators can directly judge the preparation effect through the coefficient value, greatly reducing operational difficulty and the skill requirements for personnel.

[0067] In the embodiments described above, the controllability and real-time monitoring capabilities of the oil sample preparation process are improved. Specifically, through the centralized storage and transportation of oil samples and blank oil using a piston-type cylinder, the connection between the standard gas volumetric tank and multiple standard gas cylinders, and the unified management and data acquisition of valves and sensors by the control module, real-time monitoring and adjustment of state parameters such as oil sample pressure, weight, and temperature are achieved. This makes the oil sample concentration closer to the target value, increases operational efficiency, reduces repetitive operations, and improves the reliability and stability of oil sample preparation. Simultaneously, the cloud server stores and analyzes historical data of multiple monitoring indicators, calculates the oil sample preparation efficiency coefficient, analyzes cyclical patterns, and provides optimization references for subsequent oil sample preparation, thereby further improving the accuracy and efficiency of oil sample preparation and the calibration performance of the online monitoring device.

[0068] In existing technologies, the amount of standard gas added to the oil sample during oil sample preparation is difficult to control precisely, especially for low-concentration oil samples. This leads to deviations from the target concentration, resulting in low preparation accuracy and poor operational controllability. To address this issue, in some embodiments of the present invention, the oil sample preparation unit consists of a standard gas volumetric tank 2, multiple valves, multiple sensors, a vacuum pump 4, and an oil pump 5. The vacuum pump 4 is connected to the standard gas volumetric tank 2, and the outlet of the oil pump 5 is connected to an oil port on one side of the lower part of the piston cylinder 1. The standard gas volumetric tank 2 is connected to multiple standard gas cylinders and the piston cylinder 1. The valves are standard gas valves. The sensors can be pressure sensors, temperature sensors, and weight monitoring modules. The volumetric tank can have various adjustable volumes to accommodate different gas addition requirements.

[0069] Vacuum pump 4 can be connected to standard gas volumetric container 2 to perform vacuum treatment inside standard gas volumetric container 2 before oil sample preparation, thereby removing residual gas and impurities and ensuring the accurate and reliable concentration of standard gas subsequently entering standard gas volumetric container 2. Specifically, vacuum pump 4 can periodically perform evacuation operation on standard gas volumetric container 2 to ensure the stability of oil sample preparation process and the repeatability of experimental results.

[0070] The outlet of oil pump 5 can be connected to an oil port on one side of the lower part of piston cylinder 1, used to pump blank oil or oil sample to piston cylinder 1, so as to realize the circulation, injection or discharge of oil sample during the preparation process. Specifically, oil pump 5 can adjust the flow rate and opening timing according to the instructions of control module 7, thereby ensuring that the speed and quantity of oil sample entering piston cylinder 1 meet the predetermined requirements, and ensuring the accuracy and stability of oil sample preparation.

[0071] Based on the above embodiments, the calibration system of the online dissolved gas monitoring device in transformer oil also includes a flexible hose 6. The flexible hose 6 can connect the oil pump 5 to the upper oil port of the piston cylinder 1, providing a flexible oil circuit connection during oil sample preparation and transportation. Specifically, the flexible hose 6 can adapt to changes in the oil volume in the piston cylinder 1 and the height difference of the upper oil port of the cylinder, ensuring smooth flow of the oil sample during circulation, injection, or discharge, avoiding leakage or blockage, thereby improving the stability and safety of oil sample preparation.

[0072] The standard gas volumetric container 2 can be connected to multiple standard gas cylinders 3 and piston cylinder 1. The standard gas volumetric container 2 is used to receive the standard gas released from the standard gas cylinders 3 and to transport the standard gas to the piston cylinder 1 through pipelines to achieve mixing of gas and oil sample.

[0073] In some embodiments, the calibration system of the online dissolved gas monitoring device in transformer oil further includes a heating belt wrapped around the outside of the piston cylinder 1. Specifically, the heating belt is used to heat the oil sample in the piston cylinder 1 to increase the dissolution rate of the standard gas in the oil sample, reduce potential problems of insufficient or uneven dissolution, thereby accelerating the oil sample dissolution process, reducing concentration measurement deviations caused by insufficient or uneven dissolution, and ensuring uniform gas dissolution and concentration accuracy. Furthermore, the heating temperature of the heating belt can be adjusted by the control module 7 to adapt to the needs of different oil sample preparation conditions. An upper limit protection for the heating temperature can be set to prevent the heating belt from being too hot for extended periods, leading to oil aging or gas escape due to cylinder seal aging.

[0074] Based on the above embodiments, the calibration system of the online monitoring device for dissolved gases in transformer oil also includes: a standard gas external interface 14, which is connected to the standard gas constant volume tank 2.

[0075] In some embodiments, the standard gas external interface 14 can be connected to the standard gas volumetric container 2 to access an external standard gas cylinder, thereby expanding the range of gas types and concentrations required for oil sample preparation. Operators can connect additional external standard gas cylinders through the standard gas external interface 14 to introduce the required gas into the standard gas volumetric container 2, meeting the needs of different oil sample preparation tasks and ensuring the flexibility and accuracy of the online monitoring device calibration or testing process. Here, the external standard gas cylinder refers to a gas cylinder not permanently installed inside the instrument, which can be temporarily accessed by the operator to provide additional standard gas to meet more diverse oil sample preparation needs.

[0076] In some embodiments, the oil sample preparation unit includes multiple valves, wherein a first valve 15 is provided between the standard gas volumetric vessel 2 and the standard gas cylinder 3; a second valve 16 is provided between the standard gas volumetric vessel 2 and the vacuum pump 4; a third valve 17 is provided between the left oil outlet of the lower part of the piston cylinder 1 and the standard gas volumetric vessel 2; a fourth valve 18 is provided between the upper oil port of the piston cylinder 1 and the left oil outlet of the lower part of the piston cylinder 1; and a fifth valve 19 is provided between the left oil outlet of the lower part of the piston cylinder 1 and the oil sample inlet 13. These valves can be solenoid valves, and their opening or closing during the oil sample preparation process is controlled by a control module.

[0077] Specifically, these valves are used to control the flow direction and flow rate of oil samples and standard gases in the system. For example, the first valve 15 can be a switch that controls the release of gas from the standard gas cylinder 3 to the standard gas volumetric container 2. Through the coordinated control of these valves, flexible switching of the oil sample preparation process, accurate control of gas feed rate, and safety of oil sample flow can be achieved, thereby ensuring the stability and reliability of the oil sample preparation and calibration processes of the online monitoring device's calibration system.

[0078] Based on the above embodiments, the calibration system of the online dissolved gas monitoring device in transformer oil further includes: a power supply module 8. The power supply module 8 is connected to the input power through the power port 21 and provides different levels of voltage and current to components such as the control module 7, piston cylinder 1, heating belt 10, vacuum pump 4, oil pump 5, weight monitoring module 9, temperature sensor, pressure sensor, and valves to ensure the normal operation of each component during oil sample preparation and monitoring. The power supply module 8 can provide different levels of voltage according to the power and operating status of each component, ensuring the system is safe, stable, and efficient, and also supports the automated operation of the online monitoring device.

[0079] In addition, the verification system may also include a display screen 20 for displaying a human-machine interface; furthermore, it may include a housing 22 for housing and protecting the internal components of the verification system; and it may also include casters 23 for improving the mobility and convenience of the verification system.

[0080] In another embodiment of the present invention, a calibration method for an online monitoring device for dissolved gases in transformer oil is also provided, applied to the calibration system of the above-mentioned online monitoring device for dissolved gases in transformer oil, the calibration method comprising:

[0081] M100: Obtain the target oil sample concentration. The control module controls the oil sample preparation unit and piston cylinder to complete the oil sample preparation. Based on the real-time monitoring of the gas addition and oil sample weight during the preparation process, the theoretical concentration of the prepared oil sample is calculated.

[0082] M200, the online monitoring device is connected to the calibration port to detect oil samples, and at the same time, samples are taken through the sampling port to the laboratory chromatograph for analysis. The oil sample concentration results detected by the online monitoring device are obtained and compared with the theoretical concentration of the calibration system and the detection results of the laboratory chromatograph to generate a calibration analysis for the online monitoring device and verify the detection capability of the online monitoring device.

[0083] The M300 acquires multiple indicators during the oil sample preparation process, stores these indicators in a historical record database, and calculates the preparation efficiency coefficient for each oil sample preparation process. The preparation efficiency coefficient comprehensively considers the oil pump output power and the number of preparation cycles. For each set oil sample concentration range, the corresponding average oil pump output power and average number of preparation cycles are determined to optimize subsequent oil sample preparation processes.

[0084] In the above embodiments of the present invention, the historical record database is updated after each operation is completed, that is, the historical record database contains the record of the latest configuration data.

[0085] In some embodiments, step M100 of the above verification method, which involves obtaining the target oil sample concentration, the control module controlling the oil sample preparation unit and the piston cylinder to complete the oil sample preparation, and calculating the theoretical concentration of the prepared oil sample based on the real-time monitored gas addition and oil sample weight during the preparation process, may include the following operations:

[0086] S101 connects the blank oil to the oil mixing inlet and obtains the target oil sample concentration input by the user through the human-machine interface.

[0087] In some embodiments, such as Figure 3 As shown, blank oil can be connected to the oil mixing inlet, and the target oil sample concentration input by the user can be obtained through the human-machine interface. Specifically, the user can input the target oil sample concentration through the human-machine interface, so that the subsequent control module 7 can automatically select a suitable standard gas and preparation scheme based on the concentration to achieve accurate oil sample preparation. The oil mixing inlet is used to safely and controllably inject blank oil into the piston cylinder 1.

[0088] S102, Based on the target oil sample concentration, select a standard gas bottle that matches the target oil sample concentration from multiple standard gas bottles and use it as the target standard gas bottle.

[0089] In some embodiments, based on the target oil sample concentration set by the user, the control module 7 can select a standard gas cylinder from a plurality of standard gas cylinders 3 that matches the target oil sample concentration and use it as the target standard gas cylinder. Specifically, the target standard gas cylinder refers to the selected cylinder that will release standard gas into the piston cylinder 1, and its gas type and concentration can meet the preparation requirements of the target oil sample, thereby ensuring that the concentration of each gas component in the oil sample is accurate and meets the set standard.

[0090] S103, control the valve connected to the target standard gas cylinder and the first valve to open, so that the standard gas in the target standard gas cylinder enters the standard gas volumetric container, and close the valve of the target standard gas cylinder and the first valve after the standard gas enters the standard gas volumetric container.

[0091] In some embodiments, the control module 7 can perform automated logic control to ensure that the input process of the standard gas is controlled and stable. Specifically, the control module 7 can issue an opening command to the target standard gas cylinder according to the predetermined target oil sample concentration, and simultaneously open the first valve 15 to allow the standard gas to flow into the standard gas volumetric tank 2. When the gas volume reaches the set value, the control module 7 then sequentially closes the valve of the target standard gas cylinder and the first valve 15 to avoid overfilling or residual leakage, ensuring that the gas volume in the standard gas volumetric tank 2 matches the set target.

[0092] S104, the pressure of the standard gas before transfer is detected by a pressure sensor installed in the standard gas volumetric container.

[0093] In some embodiments, a pressure sensor installed on the standard gas volumetric tank 2 can collect the gas pressure data inside the tank in real time, and transmit the detected value to the control module 7 for recording and processing. Specifically, the gas pressure detection result before transfer can serve as important reference data for subsequent calculation of the gas volume and concentration entering the oil sample. It can also be used to determine whether there is a leak or abnormal filling in the standard gas volumetric tank 2, thereby improving the accuracy and reliability of the oil sample preparation process. Here, the gas pressure before transfer refers to the gas pressure value inside the standard gas volumetric tank 2 before the standard gas enters the piston cylinder.

[0094] S105 controls the opening of the third valve. After the standard gas is transferred from the standard gas constant volume tank to the piston cylinder, the third valve is closed.

[0095] In some embodiments, the control module 7 can logically control the third valve 17 to transfer standard gas from the standard gas volumetric tank 2 to the piston cylinder 1. Specifically, by controlling the opening and closing of the third valve 17, standard gas can be transferred from the standard gas volumetric tank to the piston cylinder 1, thereby quantitatively controlling the amount of gas added and ensuring the accuracy of oil sample preparation.

[0096] S106, open the fifth valve and oil pump to transfer blank oil from the oil mixing inlet to the piston cylinder, and close the fifth valve and oil pump.

[0097] In some embodiments, the control module 7 can control the opening of the fifth valve 19 and the oil pump 5, allowing blank oil to enter the piston cylinder 1 from the oil sample inlet. Specifically, the weight monitoring module 9 and the pressure sensor monitor the amount of oil and gas entering the piston cylinder 1 in real time, thereby ensuring that the oil sample concentration meets the predetermined requirements.

[0098] S107, measure the gas pressure after the transfer of the standard gas constant volume container, calculate the pressure difference before and after the transfer, and determine the volume of standard gas entering the piston cylinder through the pressure difference.

[0099] In some embodiments, the pressure data of the standard gas constant volume tank 2 after transfer can be collected in real time by a pressure sensor, and the change in pressure before and after transfer can be calculated by the control module 7. In practice, the pressure difference is directly proportional to the gas volume. Through this calculation, the volume of standard gas entering the piston cylinder 1 can be accurately estimated, thereby ensuring that the gas concentration of the oil sample meets the predetermined requirements and improving the accuracy and reliability of oil sample preparation.

[0100] Of course, in some preferred embodiments, based on the set temperature sensor, corresponding temperature compensation can be further performed when calculating the gas volume to make the calculation results more accurate.

[0101] S108, determine whether the standard gas volume has reached the target intake volume. If the target intake volume has not been reached, continue to execute S103 to S107.

[0102] In some embodiments, after calculating the pressure difference between the gas pressure before and after the transfer, the control module 7 can further determine whether the standard gas volume calculated from the pressure difference meets the preset target intake volume. When the standard gas volume is detected to be less than the target intake volume, the control module 7 will execute the aforementioned intake and detection process again, that is, sequentially control the opening and closing of the valve of the target standard gas bottle and the first valve until the standard gas volume entering the piston cylinder 1 reaches the required target intake volume. Through this cyclic judgment and replenishment mechanism, it can be ensured that the final standard gas volume entering the piston cylinder 1 meets the set requirements, thereby improving the accuracy and stability of gas mixing during oil sample preparation. The target intake volume can be calculated from the target oil sample concentration input by the human-machine interface corresponding to the display screen 20 and the weight of the blank oil in the piston cylinder 1.

[0103] S109, if the target intake volume is reached, the weight of the blank oil in the piston cylinder is measured by the weight monitoring module located below the piston cylinder, and the theoretical concentration of the prepared oil sample is calculated by the standard gas volume and the weight of the blank oil.

[0104] In some embodiments, when the cumulative volume of standard gas entering the piston cylinder 1 reaches the target intake volume, the control module 7 can measure the weight of the blank oil in the piston cylinder in real time through a weight monitoring module located below the piston cylinder. Subsequently, the theoretical concentration corresponding to the prepared oil sample is further calculated using the target intake volume in the piston cylinder 1 and the measured weight of the blank oil. The theoretical concentration reflects the expected concentration level after the standard gas is mixed with the oil sample during the current oil sample preparation process, thus providing a reference for subsequent actual measurements and verification.

[0105] In some embodiments, the amount of gas added and the mass of the oil sample can be directly calculated by combining pressure difference gas measurement and gravimetric oil measurement, which in principle ensures the accuracy of the theoretical concentration calculation and guarantees the accuracy of the entire system.

[0106] Following S109 above, step M200 is performed, in which the oil sample prepared by the calibration system is detected by the online monitoring device, the oil sample concentration result detected by the online monitoring device is obtained, and compared with the theoretical concentration of the calibration system and the detection result of the laboratory chromatograph, generating a calibration analysis report for the online monitoring device to verify the detection capability of the online monitoring device.

[0107] In some embodiments, the control module 7 can measure the prepared oil sample using a laboratory chromatograph to obtain the actual oil sample concentration, which reflects the true concentration level of the standard gas after mixing in the oil sample. Subsequently, the control module 7 can compare the actual oil sample concentration with the theoretical concentration calculated in S109, and generate the oil mixing balance effect and ratio of the calibration system based on the difference between the two.

[0108] The comparison results are used to evaluate the accuracy of the oil sample preparation process, provide reference data for subsequent oil sample preparation and monitoring, and can be used to optimize the operation logic of the control module 7 for the oil sample preparation process, thereby improving the accuracy of oil sample preparation and the overall reliability of the system.

[0109] In the above embodiments of the present invention, the precise timing control of the start-up and shutdown of multiple valves, oil pumps, and vacuum pumps can be achieved using a multi-threaded design, which can be implemented using existing technologies.

[0110] In some embodiments, the calibration method for the online monitoring device for dissolved gases in transformer oil further includes: if an accelerated dissolution command is received through the human-machine interface, controlling the heating belt wrapped around the outside of the piston cylinder to open, so as to heat the piston cylinder and thereby accelerate the dissolution of the oil sample.

[0111] Specifically, the control module 7 can receive the accelerated dissolution task command issued by the human-machine interface and control the heating belt 10 to be energized to heat the piston cylinder 1. Heating the oil sample can increase the dissolution rate of the standard gas in the oil, shorten the oil sample dissolution time, and at the same time ensure the uniformity of oil sample concentration and dissolution accuracy, thereby improving the calibration or testing efficiency of the online monitoring device.

[0112] In some embodiments, the calibration method for the online monitoring device for dissolved gases in transformer oil further includes: acquiring the detection values ​​of a pressure sensor, a temperature sensor, and a weight monitoring module 9, wherein the pressure sensor acquires the pressure of the gas in the standard gas constant volume tank 2, the temperature sensor monitors the temperature of the oil sample in the piston cylinder 1, and the weight monitoring module 9 monitors the remaining amount of oil sample in the piston cylinder 1 and the amount of oil entering the piston cylinder 1 each time during the oil sample preparation process.

[0113] Specifically, the control module 7 can collect the detection values ​​from the pressure sensor, temperature sensor, and weight monitoring module 9, calculate the theoretical concentration of the prepared oil sample and multiple indicators of the oil sample preparation process based on the detection values, and transmit these multiple indicators to the cloud server.

[0114] In these embodiments, the accuracy and controllability of oil sample concentration preparation are improved. Specifically, by using components such as vacuum pumps, oil pumps, and flexible hoses in combination, the standard gas is accurately transported and circulated from the gas cylinder to the oil sample. Combined with the pressure sensor inside the standard gas volume control tank and the weight monitoring module below the piston cylinder for real-time measurement of gas volume and oil sample weight, the amount of standard gas entering the oil sample can be accurately calculated and controlled. Especially in the preparation of low-concentration oil samples, this ensures that the oil sample concentration is close to the preset target, improving the controllability and preparation accuracy of the operation.

[0115] In existing technologies, the preparation of dissolved gas standard oil samples in transformer oil typically relies on fixed parameters or human experience. This leads to sample concentrations that easily deviate from the target, requires numerous cycles with low efficiency, and lacks clear understanding of the influence of different operating parameters on the preparation results, resulting in a lack of predictability, controllability, and self-optimization capabilities. To better address these issues, in some embodiments of this invention, step M300 can utilize a cloud server for data processing. The cloud server can establish a communication connection with control module 7 to receive multiple indicators from control module 7. These indicators can be stored in a historical data database for subsequent data analysis, further enhancing the predictability, controllability, and self-optimization capabilities of the verification system.

[0116] Based on the aforementioned objectives of predictability and controllability, the calibration method for the online monitoring device for dissolved gases in transformer oil in the embodiments of the present invention includes the following steps in step M300:

[0117] S11, Obtain the historical configuration dataset within the historical time period;

[0118] Each historical preparation dataset corresponds to one oil sample preparation and dissolution process, including timestamp, target oil sample concentration, standard gas bottle number, standard gas concentration corresponding to the standard gas bottle number, number of preparation cycles, oil pump output power, and heating belt on / off status.

[0119] In some embodiments, such as Figure 4As shown, the execution entity can be a cloud server. The cloud server can retrieve historical preparation datasets from a historical record database and record the entire process of each oil sample preparation. The historical preparation dataset can include information about the transformer oil, timestamps, target oil sample concentration, standard gas cylinder number, the standard gas concentration corresponding to the standard gas cylinder number, the number of preparation cycles, oil pump output power, heating belt on / off status, and other parameter data during the preparation process. This historical preparation data is used to analyze the impact of different operating parameters on the achievement of oil sample concentration targets and dissolution efficiency, providing a basis for optimizing oil sample preparation strategies, predicting oil sample dissolution time, and improving the automation control accuracy of the calibration system for online monitoring devices.

[0120] S12: Select historical preparation data from the historical preparation dataset where the number of cyclic preparations is less than a preset threshold to obtain a filtered subset of historical preparation data.

[0121] In some embodiments, the cloud server can filter historical preparation data based on a preset cycle number threshold, removing records with excessive cycle numbers, inaccurate oil sample concentration, or low dissolution efficiency, thereby obtaining a reliable subset of historical preparation data.

[0122] S13. Based on the above-mentioned selection of a subset of historical preparation data, calculate the preparation efficiency coefficient corresponding to each historical preparation data. The higher the preparation efficiency coefficient, the better the preparation meets expectations and the better the preparation can be completed.

[0123] In some embodiments, the cloud server can obtain the preparation efficiency coefficient by filtering a subset of historical preparation data and referring to the formula described above. The preparation efficiency coefficient is used to evaluate the impact of different operating parameters on the speed at which the oil sample concentration reaches the target. Data with a higher preparation efficiency coefficient indicates that the oil sample can reach the target concentration with fewer cycles, which can provide an optimization reference for current oil sample preparation, thereby improving the efficiency of oil sample preparation and the level of automation in laboratory or field operations.

[0124] S14. According to multiple preset oil sample concentration ranges, the selected historical formulation data subsets are grouped to obtain multiple historical formulation data groups, each historical formulation data group corresponding to an oil sample concentration range.

[0125] In some embodiments, the cloud server can group a subset of historical preparation data according to a pre-defined concentration range, grouping historical preparation data with similar concentrations into the same historical preparation data group. Each historical preparation data group can be used to analyze the preparation efficiency and cyclical patterns within the same concentration range, thereby providing targeted reference data for the concentration control of the current oil sample, optimizing the oil sample preparation process, and improving the speed and accuracy of achieving the concentration target.

[0126] S15. For each historical formulation data group, sort them according to the formulation efficiency coefficient to obtain the historical formulation data sequence corresponding to each historical formulation data group. It can be seen that each oil sample concentration range corresponds to a historical formulation data sequence.

[0127] In some embodiments, the cloud server can sort the historical preparation data within each historical preparation data group according to the preparation efficiency coefficient from high to low, forming a historical preparation data sequence. This sequence can intuitively reflect the efficiency differences of oil sample preparation under different historical operating parameters within the same oil sample concentration range, thereby providing an optimization reference for the preparation of the current oil sample, enabling the oil sample to reach the target concentration with less energy consumption, fewer cycles, and a shorter time, thus improving the efficiency and accuracy of oil sample preparation.

[0128] S16, for each historical preparation data sequence, select several historical preparation data whose preparation efficiency coefficient falls within the preset preparation efficiency coefficient range.

[0129] In some embodiments, the cloud server can select historical preparation data with efficiency coefficients falling within a preset range from each historical preparation data sequence as a reference. These selected historical preparation data represent optimal preparation methods with similar oil sample concentrations, thus providing a reliable operational reference for the current oil sample preparation and improving the success rate and efficiency of oil sample preparation. This embodiment of the invention aims to use the lowest possible energy consumption and the shortest possible time as a preparation reference, therefore employing a preparation efficiency coefficient threshold to select historical preparation data with high efficiency. In other embodiments, such as those for broader applicability, historical data can be stratified, setting multiple efficiencies (high, medium, low, etc.), retaining a certain number of top-ranked samples in each category, thereby adapting to different needs.

[0130] S17. For each oil sample concentration range, based on several historical preparation data, determine the corresponding average oil pump output power, standard gas cylinder number distribution, and the scores and average number of preparation cycles for each standard gas cylinder number in the preparation process.

[0131] In some embodiments, the cloud server can perform statistical analysis on several historical preparation data selected within each oil sample concentration range, calculate the average oil pump output power, the average number of preparation cycles, and statistically analyze various scores for each standard gas cylinder number corresponding to the preparation process, such as preparation time score, result accuracy score, etc., as well as the distribution of standard gas cylinder numbers. These statistical results can reflect the typical operating parameters and efficiency levels of oil sample preparation within a specific concentration range, providing data reference for current oil sample preparation. The preparation time score measures the efficiency of completing oil sample preparation within a specific concentration range; the shorter the time, the higher the score. The result accuracy score measures the degree of agreement between the final preparation result and the target concentration; the smaller the error, the higher the score. The distribution of standard gas cylinder numbers refers to the frequency of occurrence of standard gas cylinders from different batches (gas characteristics) used in a specific historical preparation data set. The same batch refers to gases of the same properties, such as the same gas type and concentration.

[0132] S18. When a new oil sample needs to be prepared, first determine the oil sample concentration range corresponding to the user's expected oil sample, and determine a batch of standard gas cylinders according to the user's synchronous input priority options. During the preparation process, monitor various indicators and compare them with the average number of preparation cycles and the average oil pump output power. If the deviation value is too large, a prompt will be issued.

[0133] In some embodiments, the cloud server can determine the oil sample concentration range to which the user belongs based on the desired oil sample concentration input. Simultaneously, based on the user's synchronously input priority options, such as time priority or accuracy priority, and using the scores calculated in S17 and the distribution of standard gas cylinder numbers, it selects the most suitable batch of standard gas cylinders (gas characteristics) for the current task, and then determines the standard gas cylinder number for this preparation. During the preparation process, the control module 7 can monitor various key indicators in real time, such as the oil pump output power and the number of preparation cycles. The cloud server can compare the real-time monitored oil pump output power and the number of preparation cycles with the average oil pump output power and the average number of preparation cycles calculated in S17 to obtain the corresponding comparison results. If the comparison results indicate that the deviation between the real-time monitored indicators and the historical average is too large, the cloud server will issue a prompt message to remind the operator to take measures. This helps to promptly detect abnormalities in the preparation process and improves the controllability and reliability of the system.

[0134] In these embodiments, historical preparation data is acquired and the preparation efficiency coefficient is calculated. This historical data is then filtered, grouped, and sorted. The average oil pump output power and average number of preparation cycles are used as reference parameters to guide the preparation process of new oil samples. As a result, the current oil sample can reach the target concentration with less energy consumption, fewer cycles, and in a shorter time, improving the efficiency, accuracy, and automation level of oil sample preparation, while also enhancing the predictability and operational controllability of oil sample preparation.

[0135] Of course, in other embodiments, closed-loop control can be further introduced for each verification result obtained above. That is, the detection result of the laboratory chromatograph is used as the reference data to obtain the error between the theoretical preparation result of the current verification system and the reference data. This error is sent as a feedback signal to the control module or cloud server to correct the next preparation process. This can overcome the errors that exist in the verification system itself, such as systematic measurement offsets, including but not limited to the offsets caused by minor leaks in the gas injection valve and volume measurement errors in the gas mixing device. This enables the identification and compensation of the systematic errors of the verification system itself, so that the verification system has self-optimization capabilities.

[0136] In some embodiments, after calibration, the laboratory chromatograph detection result C_actual is obtained. C_actual is compared with the theoretical concentration C_theoretical of the calibration system, and the absolute error ΔC = C_actual - C_theoretical is calculated. Simultaneously, the relative error δ = ΔC / C_actual can also be calculated. Then, the absolute error ΔC and relative error δ are fed back to the control module or cloud server. The relative error δ can visually display the reliability, stability, and credibility of the calibration system itself, while the absolute error ΔC can be used to correct the preparation process, such as correcting the target inlet gas volume or the theoretical concentration model.

[0137] For example, to correct the target intake air volume, if the current preparation aims to achieve a target concentration C_target, but the actual concentration is C_actual (as determined by laboratory chromatography), a correction factor η = C_target / C_actual can be calculated. The next time an oil sample of the same concentration is prepared, the system can multiply the calculated target intake air volume V_gas by this correction factor η, i.e., V_gas_new = V_gas η. This correction targets the systematic fixed errors introduced by hardware such as volume measurement and valve control in the calibration system, reducing or eliminating systematic deviations in the gas distribution process. Even better, multiple correction coefficients η are calculated from the results of multiple calibrations, and the average of these multiple η values ​​is used as the final correction coefficient. This avoids the instability of individual data points and excessively frequent system adjustments.

[0138] Furthermore, the above verification results can be used to further refine the theoretical concentration model. For example, the absolute error ΔC can be used as a systematic deviation value and directly compensated in subsequent theoretical concentration calculations. For instance, C_theoretical_new = C_theoretical + k ΔC, where k is a gain factor less than 1 to prevent over-adjustment. In practice, k can be obtained by analyzing historical verification data using regression analysis. This correction can overcome systematic errors introduced by software or physical balancing processes. Similarly, multiple absolute errors ΔC can be calculated from the results of multiple verifications, and the average of these multiple ΔC values ​​can be used as the final systematic deviation value for compensation.

[0139] The above method is simple to implement. By employing the closed-loop control described in the embodiments, the calibration process verifies not only the online device but also the preparation accuracy of the calibration system itself. The difference data between the two is uploaded to the cloud server for continuous optimization, thereby reducing system errors with each calibration / batch, making the system increasingly accurate over use. Of course, ensuring the accuracy of the laboratory chromatograph is crucial in this method. Different high-precision chromatographs can be used for verification, and the average value obtained can be used as a benchmark to eliminate the relative deviation of any single instrument, ensuring the reliability of the entire verification and optimization process.

[0140] The above description is merely a selection of preferred embodiments of the present invention and an explanation of the technical principles employed. Parts not described in detail can be implemented with reference to existing technologies. Those skilled in the art should understand that the scope of the invention is not limited to specific combinations of the above-described technical features, but also includes other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions disclosed in this invention.

Claims

1. A calibration system for an online monitoring device for dissolved gases in transformer oil, characterized in that, include: An oil sample preparation unit including an oil pump; A piston-type hydraulic cylinder, one of its oil ports is connected to the oil pump outlet and sampling verification port of the oil sample preparation unit; The control module is used to control the oil sample preparation unit and the piston cylinder to complete the oil sample preparation, determine the theoretical concentration of the prepared oil sample and multiple indicators of the oil sample preparation process, and upload the multiple indicators to the cloud server; at the same time, the control module obtains the oil sample concentration results detected by the online monitoring device through the verification function, compares them with the theoretical concentration of the verification system and the detection results of the laboratory chromatograph, generates a verification analysis for the online monitoring device, and verifies the detection capability of the online monitoring device; A cloud server is used to store the aforementioned multiple indicators into a historical record database and calculate the preparation efficiency coefficient for each oil sample preparation process. The preparation efficiency coefficient comprehensively considers the oil pump output power and the number of preparation cycles. The cloud server also determines the corresponding average oil pump output power and average number of preparation cycles for each oil sample concentration range to optimize the subsequent oil sample preparation process. The cloud server calculates the preparation efficiency coefficient for each oil sample preparation process, including: Parameter standardization: The original parameters are converted into standardized values ​​greater than or equal to 0 and less than or equal to 1, resulting in the standardized value of pump output power P_std and the standardized value of cycle number N_std; where: The normalized value of the oil pump output power P_std: ； In the above formula, Pmax is the maximum allowable oil pump power of the system, Pmin is the minimum effective power, and Pactual is the actual power of this formulation. During the formulation process, the higher the oil pump output power, the higher the energy consumption cost and the worse the efficiency contribution. The above oil pump output power standardized value P_std adopts inverse standardization. The standardized value of the number of iterations, N_std: ； In the above formula, Nmax is the maximum number of cycles allowed by the system; exceeding this number indicates an abnormal formulation. Nmin is the minimum effective number of cycles to ensure that the intake air volume is close to the target value. Nactual is the number of cycles for this formulation. The fewer the number of cycles during the formulation process, the higher the time efficiency. Therefore, the standardized value of the number of cycles N_std is back-standardized. Weighted calculation: Assign corresponding weights wP and wN to the standardized parameters P_std and N_std, respectively, with wP + wN = 1. The weighted calculation yields the baseline efficiency value E_base. E_base=wP×P_std+wN×N_std Result normalization: Convert E_base to a final preparation efficiency coefficient E that is greater than or equal to 0 and less than or equal to 100. E = E_base × 100.

2. The calibration system for the online monitoring device for dissolved gases in transformer oil according to claim 1, characterized in that, The oil sample preparation unit also includes a standard gas volume-dilution vessel and a vacuum pump. The vacuum pump is connected to the standard gas volume-dilution vessel, and the standard gas volume-dilution vessel is connected to multiple standard gas cylinders and the piston-type oil cylinder. The oil sample preparation unit also includes multiple sensors, including a weight monitoring module, a temperature sensor, and a pressure sensor. The pressure sensor reads the pressure of the gas in the standard gas volumetric container, the temperature sensor monitors the temperature of the oil sample in the piston cylinder, and the weight monitoring module monitors the remaining oil sample in the piston cylinder and the amount of oil entering the piston cylinder each time during the oil sample preparation process. The control module reads the detection values ​​from the multiple sensors and uses these values ​​to determine the theoretical concentration of the prepared oil sample and various indicators of the oil sample preparation process.

3. The calibration system for the online monitoring device for dissolved gases in transformer oil according to claim 2, characterized in that: The oil sample preparation unit also includes multiple valves, the opening and closing of which are controlled by the control module during the oil sample preparation process. The system includes a first valve between the standard gas volumetric container and the standard gas cylinder, a second valve between the standard gas volumetric container and the vacuum pump, a third valve between the left oil outlet at the lower part of the piston cylinder and the standard gas volumetric container, a fourth valve between the upper oil port of the piston cylinder and the left oil outlet at the lower part of the piston cylinder, and a fifth valve between the left oil outlet at the lower part of the piston cylinder and the oil sample inlet.

4. The calibration system for the online monitoring device for dissolved gases in transformer oil according to claim 3, characterized in that, Also includes: A heating belt wrapped around the outside of the piston cylinder is used to heat the piston cylinder.

5. A calibration method for an online monitoring device for dissolved gases in transformer oil, applied to the calibration system of the online monitoring device for dissolved gases in transformer oil as described in any one of claims 3 or 4, characterized in that, include: The target oil sample concentration is obtained. The control module controls the oil sample preparation unit and piston cylinder to complete the oil sample preparation. Based on the real-time monitoring of the gas addition and oil sample weight during the preparation process, the theoretical concentration of the prepared oil sample is calculated. The online monitoring device is connected to the calibration port to detect oil samples, and at the same time, samples are taken through the sampling port to the laboratory chromatograph for analysis. The oil sample concentration results detected by the online monitoring device are obtained and compared with the theoretical concentration of the calibration system and the detection results of the laboratory chromatograph to generate a calibration analysis for the online monitoring device and verify the detection capability of the online monitoring device. Multiple indicators during the oil sample preparation process are obtained and stored in a historical record database. The preparation efficiency coefficient for each oil sample preparation process is calculated, taking into account both the oil pump output power and the number of preparation cycles. For each set oil sample concentration range, the corresponding average oil pump output power and average number of preparation cycles are determined to optimize subsequent oil sample preparation processes.

6. The calibration method for the online monitoring device for dissolved gases in transformer oil according to claim 5, characterized in that, The target oil sample concentration is obtained, and the oil sample preparation unit and piston cylinder are controlled to complete the oil sample preparation. Based on the real-time monitoring of the gas addition and oil sample weight during the preparation process, the theoretical concentration of the prepared oil sample is calculated, including: S101, connect the blank oil to the oil mixing inlet and obtain the target oil sample concentration input by the user through the human-machine interface; S102, based on the target oil sample concentration, select a standard gas bottle that matches the target oil sample concentration from a plurality of standard gas bottles and use it as the target standard gas bottle; S103, control the valve connected to the target standard gas cylinder and the first valve to open, so that the standard gas in the target standard gas cylinder enters the standard gas volumetric container, and close the valve of the target standard gas cylinder and the first valve after the standard gas enters the standard gas volumetric container; S104, The pressure of the standard gas before transfer is detected by a pressure sensor installed in the standard gas volumetric container; S105, control the third valve to open, and after the gas is transferred from the standard gas constant volume tank to the piston cylinder, close the third valve; S106, open the fifth valve and oil pump to transfer blank oil from the oil mixing inlet to the piston cylinder, and close the fifth valve and oil pump; S107, Measure the gas pressure after the transfer of the standard gas constant volume container, calculate the pressure difference before and after the transfer, and determine the volume of standard gas entering the piston cylinder through the pressure difference; S108, determine whether the standard gas volume has reached the target intake volume. If the target intake volume has not been reached, continue to execute S103 to S107. S109, if the target intake volume is reached, the weight of the blank oil in the piston cylinder is measured by the weight monitoring module located below the piston cylinder, and the theoretical concentration of the prepared oil sample is calculated by the standard gas volume and the weight of the blank oil.

7. The calibration method for the online monitoring device for dissolved gases in transformer oil according to claim 6, characterized in that, Also includes: The pressure of the gas in the standard gas constant volume tank is obtained by a pressure sensor, the temperature of the oil sample in the piston cylinder is obtained by a temperature sensor, and the remaining amount of oil sample in the piston cylinder and the amount of oil entering the piston cylinder each time during the oil sample preparation process are obtained by a weight monitoring module. The control module determines the theoretical concentration of the prepared oil sample and multiple indicators of the oil sample preparation process through the detection values ​​of the pressure sensor, the temperature sensor and the weight monitoring module, and uploads the multiple indicators to the cloud server.

8. The calibration method for the online monitoring device for dissolved gases in transformer oil according to claim 7, characterized in that, Perform the following operations on the cloud server: Obtain historical preparation datasets within a historical time period. Each historical preparation dataset corresponds to one oil sample preparation and dissolution process, specifically including timestamp, target oil sample concentration, standard gas bottle number, standard gas concentration corresponding to the standard gas bottle number, number of preparation cycles, oil pump output power, and heating belt on / off status. Select historical recipe data from the historical recipe dataset whose number of cyclic recipes is less than a preset threshold to obtain a filtered subset of historical recipe data; Based on the selected subset of historical preparation data, calculate the preparation efficiency coefficient corresponding to each historical preparation data. According to multiple preset oil sample concentration ranges and target oil sample concentrations, the selected historical formulation data subsets are grouped to obtain multiple historical formulation data groups, each historical formulation data group corresponding to an oil sample concentration range. For each historical preparation data group, sort them according to the preparation efficiency coefficient to obtain the historical preparation data sequence corresponding to each historical preparation data group; For each historical preparation data group, select multiple historical preparation data sets whose preparation efficiency coefficients fall within a preset preparation efficiency coefficient range. For each oil sample concentration range, the corresponding average oil pump output power and average number of cycle preparations are determined based on multiple historical preparation data.

9. The calibration method for the online monitoring device for dissolved gases in transformer oil according to claim 5, characterized in that, Also includes: The detection results of the laboratory chromatograph are used as reference data to obtain the error between the theoretical preparation result of this calibration system and the reference data. This error is then sent as a feedback signal to the control module or cloud server to correct the next preparation process.

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