A fire-resistant oil filling self-adaptive temperature compensation metering method and flow meter device

Abstract

This invention relates to the field of flow metering technology, specifically to an adaptive temperature compensation metering method and flow meter device for fire-resistant oil filling. The method includes acquiring the standard flow rate and uncompensated flow rate measurement values ​​of the fire-resistant oil at different calibration temperatures and flow rates; calculating the original correction coefficients and constructing a two-dimensional correction matrix model; obtaining the nonlinearity of each region by fitting the correction coefficients within the calibration region based on the calibration region bounded by adjacent temperatures and flow rates in the matrix; real-time acquisition of temperature values ​​and uncompensated original flow rate values; locating the corresponding calibration region and determining the nonlinearity; comparing with a preset threshold; adaptively selecting an interpolation algorithm to calculate the compensation correction coefficients; and correcting the original flow rate value to obtain the actual flow rate value. This invention can eliminate viscosity fluctuation interference caused by temperature changes, achieve adaptive temperature compensation, and significantly improve the accuracy and stability of filling metering.

Description

Technical Field

[0001] This invention relates to the field of flow metering technology, and in particular to an adaptive temperature compensation metering method and flow meter device for fire-resistant oil filling. Background Technology

[0002] Fire-resistant oils (triaryl phosphate esters), as special hydraulic oils with high stability and fire resistance, rely heavily on metering and filling during their production process, which directly affects packaging accuracy and product quality. However, fire-resistant oils possess unique physicochemical properties: high density (1.13 g / cm³~1.17 g / cm³ at 20℃), high kinematic viscosity (39.1 mm² / s~52.9 mm² / s at 40℃), and significant viscosity-temperature characteristics (viscosity changes drastically with temperature). They are also prone to hydrolysis, producing trace amounts of corrosive products, and require stringent contact materials. During filling operations, ambient temperature fluctuations and fluid frictional heat generation are unavoidable, and air bubbles may be introduced during pipeline transport. These factors collectively pose a severe challenge to the accuracy and stability of flow metering.

[0003] At present, the filling of finished fire-resistant oil generally uses ordinary turbine, electromagnetic or differential pressure flow meters, lacking a special design for its special physical properties and filling conditions. The main technical defects are as follows: (1) The metering accuracy is significantly affected by temperature. The general compensation method cannot effectively correct the flow measurement deviation caused by the change of fire-resistant oil viscosity with temperature. The error often exceeds ±1.5%, which is difficult to meet the filling accuracy requirement of ±0.5%; (2) The equipment has poor corrosion resistance and compatibility. The internal copper alloy and nitrile rubber and other conventional materials are easily corroded by fire-resistant oil or its hydrolysis products, resulting in leakage and pollution; (3) It is very susceptible to interference from mixed air bubbles and filling flow fluctuations, causing the metering value to jump or be too large, affecting the filling consistency; (4) The structure is not adaptable enough, it is difficult to flexibly adjust the range to match different filling specifications, and it is difficult to interface with the signal of the automatic control system.

[0004] Therefore, there is an urgent need for a fire-resistant oil filling and metering solution that can adapt to temperature changes, is highly accurate, and is stable and reliable. Summary of the Invention

[0005] The purpose of this invention is to provide an adaptive temperature compensation metering method and flow meter device for fire-resistant oil filling, so as to solve the problems of low accuracy, lack of effective temperature compensation, and poor corrosion resistance and anti-interference of fire-resistant oil filling metering caused by viscosity fluctuations due to temperature changes in the prior art.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: This invention discloses an adaptive temperature compensation metering method for fire-resistant oil filling, comprising: Obtain the standard flow rate and uncompensated flow rate measurement value of fire-resistant oil at different calibration temperatures and when adjusted to different calibration flow rates. Based on the standard flow rate value and the flow measurement value corresponding to different calibration conditions, the original correction coefficients for each calibration condition are calculated and obtained, and a two-dimensional correction matrix model is constructed based on the correspondence between the calibration temperature, the calibration flow rate and the original correction coefficients. Based on the calibration region enclosed by any adjacent calibration temperature and any adjacent calibration flow rate in the two-dimensional correction matrix model, the nonlinearity of each calibration region is calculated by fitting all the original correction coefficients within the calibration region. The real-time temperature value and uncompensated original flow rate value are obtained during the filling process of fire-resistant oil, and the nonlinearity of the real-time operating condition during the filling process is determined according to the calibration region corresponding to the temperature value and the original flow rate value in the two-dimensional correction matrix model. The nonlinearity corresponding to the real-time operating condition is compared with a preset threshold. Based on the comparison result, an adaptive interpolation algorithm is matched to calculate and obtain the compensation correction coefficient of the real-time operating condition during the fire-resistant oil filling process. The original flow rate value is corrected according to the compensation correction coefficient to obtain the actual flow rate value after compensation under real-time operating conditions during the fire-resistant oil filling process.

[0007] Optionally, obtaining the standard flow rate value and uncompensated flow rate measurement value of fire-resistant oil at different calibration temperatures and adjusted to different calibration flow rates includes: Set a sequence of temperature points containing multiple different calibration temperatures and a sequence of flow points containing multiple different calibration flow rates; The calibration temperatures are extracted sequentially from the temperature point sequence, and the temperature of the fire-resistant oil is controlled to reach the extracted calibration temperatures until it stabilizes, thus obtaining the current temperature of the fire-resistant oil. The calibration flow rate is extracted sequentially from the flow rate point sequence, and the flow rate of the fire-resistant oil is controlled to reach the extracted calibration flow rate until it stabilizes, thereby obtaining the current flow rate of the fire-resistant oil. Obtain the standard flow rate value and the uncompensated flow rate measurement value when the fire-resistant oil reaches the current temperature and the current flow rate simultaneously to obtain flow rate comparison data; If, after obtaining the traffic comparison data, it is determined that the current traffic is not the last calibrated traffic in the traffic point sequence, then the next calibrated traffic is extracted from the traffic point sequence as the current traffic, and the next set of traffic comparison data is obtained. If, after obtaining the flow rate comparison data, it is determined that the current flow rate is the last calibrated flow rate in the flow rate point sequence, and the current temperature is not the last calibrated temperature in the temperature point sequence, then the next calibrated temperature is extracted from the temperature point sequence as the current temperature, and the next set of flow rate comparison data is obtained.

[0008] Optionally, the setting includes a sequence of temperature points with multiple different calibration temperatures and a sequence of flow points with multiple different calibration flow rates, including: Obtain the viscosity-temperature characteristic curve of the fire-resistant oil as a function of temperature, and obtain the viscosity change rate in each temperature range based on the viscosity-temperature characteristic curve. The temperature range in which the viscosity change rate is greater than a preset change threshold is defined as the first temperature range, and multiple calibration temperatures are set within the first temperature range at a first temperature interval. The temperature range in which the viscosity change rate is less than or equal to a preset change threshold is defined as the second temperature range, and multiple calibration temperatures are set within the second temperature range at second temperature intervals that are greater than the first temperature interval. Obtain the range of the filling flow rate of the fire-resistant oil, and divide the range into a first flow rate interval and a second flow rate interval with a flow rate greater than the first flow rate interval; Within the first flow range, a plurality of calibration flows are set at a first flow interval, and within the second flow range, a plurality of calibration flows are set at a second flow interval with an interval greater than the first flow interval; All the calibration temperatures are sorted in ascending order of temperature value to obtain the calibrated temperature point sequence, and all the calibration flow rates are sorted in ascending order of flow rate value to obtain the calibrated flow rate point sequence.

[0009] Optionally, the step of calculating the original correction coefficient for each calibration condition based on the standard flow rate value and the flow measurement value corresponding to different calibration conditions includes: Based on the flow rate comparison data when the fire-resistant oil simultaneously reaches the current temperature and the current flow rate, the initial correction coefficient of the fire-resistant oil under the current calibration condition is calculated. The functional expression for calculating the initial correction coefficient is as follows:

[0010] In the formula, Indicates fire-resistant oil in the first The calibration temperature and the first Initial correction factor for a given flow rate Index indicating the calibrated temperature. Index representing the calibrated flow rate. This represents the standard flow rate value measured by the standard flow detection path. This indicates the flow measurement value obtained from the flow detection path; The flow rate comparison data of the fire-resistant oil at the current temperature and the current flow rate are acquired multiple times. Based on the initial correction coefficients corresponding to multiple sets of flow rate comparison data under the current calibration condition, the original correction coefficient of the fire-resistant oil under the current operating condition is calculated. The functional expression for calculating the original correction coefficient is as follows:

[0011] In the formula, Indicates fire-resistant oil in the first The calibration temperature and the first The original correction factor for the calibrated flow rate. Indicates fire-resistant oil The second measurement The calibration temperature and the first Initial correction factor for a given flow rate Indicates the index of the number of measurements. Indicates the total number of measurements.

[0012] Optionally, the adaptive temperature compensation metering method for fire-resistant oil filling further includes, before calculating and obtaining the original correction coefficient, performing an uncertainty assessment on the standard flow rate value and the flow rate measurement value obtained under the calibration conditions, including: Obtain the first uncertainty known when measuring the standard flow rate value, and obtain the second uncertainty when measuring the uncompensated flow rate based on the flow rate measurement values ​​measured multiple times under the calibration conditions; Based on the obtained first uncertainty and second uncertainty, and combined with the standard flow rate value and the flow rate measurement value obtained during the calibration condition, the calibration uncertainty of the fire-resistant oil under the current calibration condition is calculated. The functional expression for calculating the calibration uncertainty is as follows:

[0013] In the formula, This indicates the calibration uncertainty of the fire-resistant oil under the current calibration conditions. This indicates the preset inclusion factor. Indicates the first degree of uncertainty. Indicates the second uncertainty; If the calibration uncertainty is greater than the preset uncertainty threshold, the number of measurements of the fire-resistant oil under the current calibration condition is increased, and multiple sets of flow comparison data under the current calibration condition are reacquired.

[0014] Optionally, the step of calculating the nonlinearity of each calibration region by fitting all the original correction coefficients within the calibration region includes: Extract all the original correction coefficients within the calibration region from the two-dimensional correction matrix model, and fit and construct an ideal plane in which multiple original correction coefficients linearly change with temperature and flow rate within the corresponding calibration region; Extract at least one original correction coefficient adjacent to the calibration region from the two-dimensional correction matrix model, and combine all the original correction coefficients in the calibration region to fit and construct a correction coefficient surface in which the original correction coefficients change nonlinearly with temperature and flow rate in the corresponding calibration region; Obtain the maximum absolute deviation between the correction coefficient surface and the ideal plane within the corresponding calibration region, and calculate the average value of all the original correction coefficients within the calibration region; The nonlinearity corresponding to the calibration region is calculated based on the maximum absolute deviation value and the average value. The functional expression for calculating the nonlinearity is as follows:

[0015] In the formula, Indicates the nonlinearity of the calibration region. This represents the fitted correction coefficient value corresponding to any calibration temperature and calibration flow rate in the correction coefficient surface. This represents the correction factor value for fitting the data at any calibrated temperature and calibrated flow rate in the ideal plane. Indicates the calibration temperature. Indicates the calibrated flow rate. This represents the average value of all original correction coefficients within the calibration area.

[0016] Optionally, comparing the nonlinearity corresponding to the real-time operating condition with a preset threshold, and calculating using an adaptive interpolation algorithm based on the comparison result, includes: If the nonlinearity corresponding to the real-time operating condition is less than the first preset threshold, then the bilinear interpolation algorithm is matched. If the nonlinearity corresponding to the real-time operating condition is greater than or equal to the first preset threshold and less than the second preset threshold, then the bicubic interpolation algorithm is matched. If the nonlinearity is greater than or equal to the second preset threshold, then a two-dimensional spline interpolation algorithm is matched.

[0017] Optionally, the adaptive temperature compensation metering method for fire-resistant oil filling further includes, after obtaining the compensated actual flow rate value, verifying the actual flow rate value and updating the compensation correction coefficient, including: The temperature value, the original flow rate value before compensation, the actual flow rate value after compensation, and the measured weight value of downstream filling are obtained for each filling cycle during the fire-resistant oil filling process. The density of the fire-resistant oil is obtained, and the downstream filling flow rate is calculated based on the density and the weight value. Obtain the deviation between the actual flow rate value and the filling flow rate value within the filling cycle, and record the number of cycles in which the deviation value continuously exceeds a preset deviation threshold based on the deviation value within multiple consecutive filling cycles; When the number of recorded cycles reaches a preset threshold, the temperature range and flow range where the deviation occurs are determined based on the temperature value and the original flow value, and the calibration area corresponding to the temperature range and flow range is located from the two-dimensional correction matrix model. The observation correction coefficient is obtained by back-calculating the deviation value based on the compensation correction coefficient of the real-time working conditions during the filling process of the fire-resistant oil. Based on the observed correction coefficients, a weighted moving average is performed on at least one of the original correction coefficients within the calibration area to obtain the updated original correction coefficients. The functional expression for the weighted moving average is:

[0018] In the formula, This represents the original correction factor updated at the calibration temperature T and calibration flow rate Q. This represents the preset historical weighting coefficients. This represents the original correction factor before updating at the calibration temperature T and calibration flow rate Q. This represents the observation correction factor obtained by back-calculation at the calibration temperature T and calibration flow rate Q; Adjust the original correction coefficients in the corresponding calibration region of the two-dimensional correction matrix model according to the updated original correction coefficients to obtain the updated two-dimensional correction matrix model, and retain the two-dimensional correction matrix model before at least three iterations of updates.

[0019] The present invention also discloses a flow meter device applied to the above-mentioned adaptive temperature compensation metering method for fire-resistant oil filling, the flow meter device comprising: The housing assembly includes a housing body, a metering chamber formed inside the housing body, an oil inlet and an oil outlet located on the housing body and respectively communicating with the metering chamber, and a degassing chamber located above the housing body and communicating with the metering chamber. The metering assembly includes a vortex generator, a piezoelectric sensor, and a flow guide disposed within the metering cavity. The vortex generator has a triangular prism structure, with the non-pointed base of the vortex generator horizontally facing the oil inlet and the pointed top of the vortex generator horizontally facing the oil outlet. The piezoelectric sensor is embedded inside the vortex generator, and the flow guide is disposed between the oil inlet and the vortex generator and has an arc-shaped structure. A temperature sensor, embedded in the inner wall of the metering cavity, is used to collect the temperature value of the fire-resistant oil. The compensation calculation unit is electrically connected to the piezoelectric sensor and the temperature sensor respectively, and the compensation calculation unit has the two-dimensional correction matrix model built in.

[0020] Optionally, the flow meter device further includes: A pre-filter is disposed inside the oil inlet; The degassing assembly includes a drain pipe connecting the metering chamber and the degassing chamber, a liquid level sensor disposed in the degassing chamber, and an exhaust valve disposed at the top of the degassing chamber, wherein the drain pipe is inclined. The signal processing module is electrically connected to the piezoelectric sensor, the temperature sensor, the compensation calculation unit, the liquid level sensor, and the exhaust valve.

[0021] Compared with the prior art, the adaptive temperature compensation metering method and flow meter device for fire-resistant oil filling provided by the embodiments of the present invention have the following beneficial effects: By pre-constructing a two-dimensional correction matrix model composed of different calibration temperatures, different calibration flow rates, and original correction coefficients corresponding to various operating conditions, the viscosity-temperature characteristics of fire-resistant oil can be solidified in the form of discrete nodes, thus providing a precise benchmark for compensation. By calculating the nonlinearity within each calibration region enclosed by adjacent calibration temperatures and flow rates, the curvature of the correction coefficients with temperature and flow rate can be quantified, distinguishing between linear and strongly nonlinear regions. During real-time filling, the corresponding calibration region is located based on the real-time temperature value and the uncompensated original flow rate value, and its nonlinearity is obtained. After comparing this nonlinearity with a preset threshold, an appropriate interpolation algorithm is automatically matched to calculate the compensation correction coefficient. This allows for a fast algorithm in the linear region and a high-precision algorithm in the strongly nonlinear region, improving the compensation accuracy in the strongly nonlinear region while ensuring response speed. Finally, the uncompensated original flow rate value is corrected using this compensation correction coefficient to obtain the compensated actual flow rate value, thereby eliminating the interference of fire-resistant oil viscosity changes with temperature and filling flow rate fluctuations on metering. This ensures that the filling metering accuracy across the entire operating temperature range consistently meets the stringent requirements for finished product filling. Attached Figure Description

[0022] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. In the accompanying drawings: Figure 1 A schematic block diagram illustrating the steps of the adaptive temperature compensation metering method for fire-resistant oil filling provided in this embodiment of the invention; Figure 2 This is a schematic diagram of the overall structure of the flow meter device provided in an embodiment of the present invention.

[0023] The markings in the attached diagram are as follows: 1. Housing body; 11. Metering chamber; 111. Vortex generator; 112. Piezoelectric sensor; 113. Temperature sensor; 12. Oil inlet; 13. Oil outlet; 14. Degassing chamber; 2. Liquid level sensor; 3. Exhaust valve; 4. Flow guide; 5. Pre-filter; 6. Drain pipe; 7. Signal processing module. Detailed Implementation

[0024] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0025] This invention discloses an adaptive temperature-compensated metering method for filling fire-resistant oil, such as... Figure 1 As shown, it includes: S1. Obtain the standard flow rate and uncompensated flow rate measurement value of fire-resistant oil at different calibration temperatures and when adjusted to different calibration flow rates. S2. Based on the standard flow rate and flow measurement value corresponding to different calibration conditions, calculate and obtain the original correction coefficients for each calibration condition, and construct a two-dimensional correction matrix model based on the correspondence between calibration temperature, calibration flow rate and original correction coefficients. S3. Based on the calibration region enclosed by any adjacent calibration temperature and any adjacent calibration flow rate in the two-dimensional correction matrix model, the nonlinearity of each calibration region is calculated by fitting all the original correction coefficients within the calibration region. S4. Obtain the real-time temperature value and the uncompensated original flow rate value during the fire-resistant oil filling process, and determine the nonlinearity of the real-time operating conditions during the fire-resistant oil filling process based on the calibration area corresponding to the temperature value and the original flow rate value in the two-dimensional correction matrix model. S5. Compare the nonlinearity corresponding to the real-time operating condition with the preset threshold, match the adaptive interpolation algorithm according to the comparison result, and calculate and obtain the compensation correction coefficient of the real-time operating condition during the fire-resistant oil filling process. S6. Correct the original flow rate value according to the compensation correction coefficient to obtain the actual flow rate value after compensation under real-time operating conditions during the fire-resistant oil filling process.

[0026] By implementing the above-described adaptive temperature compensation metering method for fire-resistant oil filling, the standard flow rate values ​​and uncompensated flow rate measurements of the fire-resistant oil at different calibration temperatures and adjusted to different calibration flow rates are obtained in advance. Based on this, the original correction coefficients for each calibration condition are calculated, and a two-dimensional correction matrix model is constructed. This model, in the form of discrete nodes, completely records the distribution law of correction coefficients caused by the viscosity-temperature characteristics of the fire-resistant oil. Unlike the traditional single-temperature compensation method, this two-dimensional correction matrix model considers the coupled effects of both calibration temperature and calibration flow rate, providing a reference data grid that accurately matches the actual physical properties of the fire-resistant oil for subsequent compensation.

[0027] Based on this, for each calibration region in the two-dimensional correction matrix model, bounded by any adjacent calibration temperatures and flow rates, the nonlinearity of each calibration region is calculated by fitting all the original correction coefficients within that region. This nonlinearity index quantifies the curvature of the correction coefficients with temperature and flow rate changes in each local region, effectively distinguishing between linear and strongly nonlinear regions. The nonlinearity is low when the distribution of correction coefficients within the calibration region is nearly linear, and high when the distribution exhibits severe curvature. By pre-calculating and storing the nonlinearity of each calibration region, complex surface fitting calculations are eliminated during subsequent real-time compensation, significantly reducing the online computational burden.

[0028] During the real-time operation of fire-resistant oil filling, the corresponding calibration area is located in the two-dimensional correction matrix model based on the real-time temperature value and the uncompensated original flow rate value. The nonlinearity of this calibration area is directly read to determine the degree of nonlinearity in the real-time operating condition. When the nonlinearity is less than the preset low threshold, it indicates that the linearity of the area is good, and the interpolation algorithm with the least computational load is matched, which can achieve a very fast response speed while ensuring sufficient accuracy. When the nonlinearity is between the low and high thresholds, a medium-precision interpolation algorithm is matched to achieve a balance between accuracy and speed. When the nonlinearity is greater than or equal to the high threshold, a high-precision interpolation algorithm is matched. Although the computational load is slightly larger, it can accurately capture the trend of the correction coefficient change in the strong nonlinear area. This adaptive matching mechanism ensures that the compensation calculation is always in the optimal efficiency-accuracy balance state throughout the entire filling range, avoiding the response lag caused by uniformly using complex algorithms across the entire range, and also avoiding insufficient compensation in the strong nonlinear area caused by uniformly using simple algorithms.

[0029] Finally, the uncompensated original flow rate value is corrected using the compensation correction coefficient calculated by the adaptive matching interpolation algorithm to obtain the compensated actual flow rate value. Since the compensation correction coefficient is based on a two-dimensional correction matrix model and calculated using an interpolation algorithm adapted to the nonlinearity of real-time operating conditions, this correction coefficient can accurately reflect the degree of influence of changes in fire-resistant oil viscosity at the current temperature and flow rate on flow measurement.

[0030] The function expression for calculating the actual flow rate is:

[0031] In the formula, This represents the actual flow rate after compensation. This represents the uncompensated raw flow value. This represents the compensation correction coefficient.

[0032] As shown in the formula for calculating the actual flow rate, by multiplying the uncompensated original flow rate by the compensation correction coefficient, the metering deviation caused by the temperature change of fire-resistant oil viscosity and the fluctuation of filling flow can be effectively eliminated. This ensures that the filling metering accuracy within the entire temperature operating range and the entire flow range consistently meets the stringent requirements for finished product filling, while avoiding the problems of overfilling or underfilling due to overcompensation or undercompensation.

[0033] Furthermore, the standard flow rate values ​​and uncompensated flow rate measurements of the fire-resistant oil were obtained at different calibration temperatures and adjusted to different calibration flow rates, including: Set a sequence of temperature points containing multiple different calibration temperatures and a sequence of flow points containing multiple different calibration flow rates; The calibration temperature is extracted sequentially from the temperature point sequence, and the temperature of the fire-resistant oil is controlled to reach the extracted calibration temperature until it stabilizes, thus obtaining the current temperature of the fire-resistant oil. The calibration flow rate is extracted sequentially from the flow point sequence, and the flow rate of the fire-resistant oil is controlled to reach the extracted calibration flow rate until it stabilizes, thus obtaining the current flow rate of the fire-resistant oil. Obtain the standard flow rate and uncompensated flow rate measurement value when the fire-resistant oil reaches the current temperature and current flow rate simultaneously, and obtain flow rate comparison data; If, after obtaining the flow comparison data, it is determined that the current flow is not the last calibrated flow in the flow point sequence, then the next calibrated flow is extracted from the flow point sequence as the current flow, and the next set of flow comparison data is obtained. If, after obtaining the flow rate comparison data, it is determined that the current flow rate is the last calibrated flow rate in the flow rate point sequence, and the current temperature is not the last calibrated temperature in the temperature point sequence, then the next calibrated temperature is extracted from the temperature point sequence as the current temperature, and the next set of flow rate comparison data is obtained.

[0034] Furthermore, a sequence of temperature points containing multiple different calibration temperatures and a sequence of flow rates containing multiple different calibration flow rates are defined, including: Obtain the viscosity-temperature characteristic curve of fire-resistant oil as a function of temperature, and obtain the viscosity change rate in each temperature range based on the viscosity-temperature characteristic curve. The temperature range in which the viscosity change rate is greater than a preset change threshold is defined as the first temperature range, and multiple calibration temperatures are set within the first temperature range at a first temperature interval. The temperature range in which the viscosity change rate is less than or equal to a preset change threshold is defined as the second temperature range, and multiple calibration temperatures are set within the second temperature range at second temperature intervals that are greater than the first temperature interval. Obtain the range of fire-resistant oil filling flow rate and divide the range into a first flow rate interval and a second flow rate interval with a flow rate greater than the first flow rate interval; Within a first flow range, multiple calibration flow rates are set at a first flow interval; within a second flow range, multiple calibration flow rates are set at a second flow interval that is greater than the first flow interval. Sort all calibrated temperatures in ascending order of temperature value to obtain the calibrated temperature point sequence, and sort all calibrated flow rates in ascending order of flow rate value to obtain the calibrated flow rate point sequence.

[0035] By implementing the above-mentioned adaptive temperature compensation metering method for fire-resistant oil filling, the temperature of the fire-resistant oil is controlled to stabilize to the current temperature according to the calibrated temperature point sequence, and the flow rate of the fire-resistant oil is controlled to stabilize to the current flow rate according to the calibrated flow rate point sequence. Then, the standard flow rate value and the uncompensated flow rate measurement value when the current temperature and current flow rate are reached simultaneously are obtained as a set of flow rate comparison data. This sequential nested traversal calibration process ensures that every calibrated temperature and every calibrated flow rate combination is fully covered, and there will be no omissions or sequence errors due to manual operation.

[0036] After each change in calibration temperature or flow rate, data acquisition is only performed after the temperature and flow rate of the fire-resistant oil have reached a stable state. This ensures that each set of standard flow rate values ​​and uncompensated flow rate measurements accurately reflects the measurement characteristics under specific operating conditions, eliminating the interference of transient temperature and flow rate fluctuations on the accuracy of calibration data. Furthermore, the fluctuation range of the fire-resistant oil temperature during stabilization is controlled to not exceed ±0.2℃. Preferably, measurements are repeated three times under each calibration condition determined by the calibration temperature and flow rate, further reducing the impact of random errors on subsequent calculations of the original correction coefficients.

[0037] During the temperature point sequence setting process, the viscosity change rate within each temperature range is obtained through viscosity-temperature characteristic curves, enabling precise identification of sensitive and non-sensitive ranges for the viscosity of fire-resistant oil as a function of temperature. Utilizing a variable step size setting strategy for the first and second temperature ranges allows for a denser distribution of calibration temperature points in temperature regions where the viscosity of the fire-resistant oil changes drastically with temperature. This significantly improves the model resolution in highly nonlinear temperature ranges while maintaining the same total calibration workload. Conversely, a sparser distribution of calibration temperature points in temperature regions where viscosity changes gradually avoids unnecessary redundant calibration, reducing calibration time and data storage requirements. As a preferred example, the calibration temperature points are denser in the temperature range where the viscosity change rate is large, such as 10℃ to 25℃, and the calibration interval is appropriately relaxed in the range where the viscosity tends to be flat, such as 30℃ to 40℃. Specifically, the calibration temperature points can be set to 10℃, 12℃, 15℃, 18℃, 20℃, 23℃, 25℃, 28℃, 30℃, 33℃, 35℃, 38℃, and 40℃, with the temperature points being more densely distributed in the 10℃ to 25℃ range and more sparsely distributed in the 30℃ to 40℃ range.

[0038] In setting the flow point sequence, the range of fire-resistant oil filling flow rate is divided into a first flow range and a second flow range. This makes the calibration flow points more dense in the small flow range because the small flow range corresponds to small-sized fillings and the viscosity of fire-resistant oil has a more significant impact on flow measurement at low flow rates. In the large flow range, the fluid flow state tends to be stable at high flow rates, and the impact of viscosity changes on the measurement results is relatively mild. This allows for a reasonable allocation of calibration resources across the entire range, ensuring the model accuracy in the small flow range while avoiding over-calibration in the large flow range. As a preferred example, the calibration flow points are densified in the small flow range, such as 1 L / min to 50 L / min, and the calibration interval is appropriately relaxed in the large flow range, such as 50 L / min to 200 L / min. Specifically, the calibration flow points can be set to 1 L / min, 2 L / min, 5 L / min, 8 L / min, 10 L / min, 15 L / min, 20 L / min, 30 L / min, 50 L / min, 80 L / min, 100 L / min, 150 L / min, and 200 L / min. The flow points are more densely distributed in the 1 L / min to 50 L / min range and more sparsely distributed in the 50 L / min to 200 L / min range.

[0039] Finally, all calibration temperatures are sorted in ascending order of temperature value to obtain the calibration temperature point sequence, and all calibration flow rates are sorted in ascending order of flow rate value to obtain the calibration flow rate point sequence. This sorting operation provides a unified and clear control order for subsequent sequential nested traversal calibration, ensuring the repeatability and consistency of the calibration process. This ensures that flow rate comparison data can be obtained in the same order of increasing temperature and flow rate each time calibration is performed, thereby guaranteeing that the constructed two-dimensional correction matrix model has a fixed data structure and clear physical meaning.

[0040] Furthermore, based on the standard flow rate and flow measurement values ​​corresponding to different calibration conditions, the original correction coefficients for each calibration condition are calculated and obtained, including: Based on the flow rate comparison data when the fire-resistant oil reaches both the current temperature and the current flow rate, the initial correction factor for the fire-resistant oil under the current calibration conditions is calculated. The functional expression for calculating the initial correction factor is as follows:

[0041] In the formula, Indicates fire-resistant oil in the first The calibration temperature and the first Initial correction factor for a given flow rate Index indicating the calibrated temperature. Index representing the calibrated flow rate. This represents the standard flow rate value measured by the standard flow detection path. This indicates the flow measurement value obtained from the flow detection path; Multiple flow rate comparison data of the fire-resistant oil at the current temperature and flow rate were obtained. Based on the initial correction coefficients corresponding to multiple sets of flow rate comparison data under the current calibration conditions, the original correction coefficients of the fire-resistant oil under the current operating conditions were calculated. The functional expression for calculating the original correction coefficients is as follows:

[0042] In the formula, Indicates fire-resistant oil in the first The calibration temperature and the first The original correction factor for the calibrated flow rate. Indicates fire-resistant oil The second measurement The calibration temperature and the first Initial correction factor for a given flow rate Indicates the index of the number of measurements. Indicates the total number of measurements.

[0043] By implementing the above-described adaptive temperature compensation metering method for fire-resistant oil filling, the initial correction coefficient for each measurement is obtained by dividing the standard flow rate value and the measured flow rate value obtained from multiple measurements under the same calibration conditions. Essentially, this calculation uses the standard flow rate value measured by the standard flow detection path as the true flow rate benchmark, dividing it by the measured flow rate value, thereby quantifying the measurement deviation of the flow detection path under the current conditions. From a dimensional perspective, the standard flow rate value and the measured flow rate value have the same physical dimensions (volume flow rate, unit: volumetric flow rate). or The initial correction coefficient obtained by dividing the two is a dimensionless pure numerical value. Its physical meaning is the ratio of the actual flow rate to the measured flow rate. Therefore, it is safe to perform subsequent accumulation and arithmetic average calculations without causing problems of dimension conflict or confusion in physical meaning.

[0044] For a calibration condition determined by a calibration temperature and a calibration flow rate, multiple sets of flow rate comparison data are obtained through repeated measurements, and multiple initial correction coefficients are calculated accordingly. These initial correction coefficients are then summed and divided by the total number of measurements to obtain the original correction coefficients for the calibration condition. This arithmetic averaging operation can effectively suppress the influence of random errors on individual measurement data. This is because the standard flow rate value and the flow rate measurement value are affected by their own independent sources of uncertainty in each measurement. Averaging through multiple independent measurements can cancel out random errors, thus making the final original correction coefficients closer to the true value under the calibration condition. This significantly improves the reliability and repeatability of the data at each node in the two-dimensional correction matrix model.

[0045] Based on this, as a preferred example, the measurement is repeated three times under each calibration condition, and the arithmetic mean of the initial correction coefficients of the three measurements is taken as the original correction coefficient for that calibration condition. This choice takes into account both the statistical error suppression effect and the calibration efficiency. Three independent measurements can effectively reduce random errors without excessively increasing the calibration time. This ensures that the total number of measurements remains within a reasonable range throughout the entire calibration process, which includes 169 calibration conditions with 13 calibration temperatures and 13 calibration flow rates, so that the calibration work can be completed within a controllable time.

[0046] Furthermore, the adaptive temperature compensation metering method for fire-resistant oil filling also includes uncertainty assessment of the standard flow rate value and flow measurement value obtained under calibration conditions before calculating and obtaining the original correction coefficient, including: The first uncertainty is known when measuring the standard flow rate, and the second uncertainty is obtained when measuring the uncompensated flow rate based on the flow rate measurements taken multiple times during calibration. Based on the obtained first and second uncertainties, combined with the standard flow rate and flow measurement values ​​obtained during the calibration conditions, the calibration uncertainty of the fire-resistant oil under the current calibration conditions is calculated. The functional expression for calculating the calibration uncertainty is as follows:

[0047] In the formula, This indicates the calibration uncertainty of the fire-resistant oil under the current calibration conditions. This indicates the preset inclusion factor. Indicates the first degree of uncertainty. Indicates the second uncertainty; If the calibration uncertainty is greater than the preset uncertainty threshold, the number of measurements of the fire-resistant oil under the current calibration conditions will be increased, and multiple sets of flow comparison data under the current calibration conditions will be reacquired.

[0048] By implementing the above-described embodiment of the adaptive temperature compensation metering method for fire-resistant oil filling, a known first uncertainty is obtained when measuring the standard flow rate value. This first uncertainty originates from the measurement uncertainty of the standard flow rate detection path itself, typically provided by the factory calibration certificate or metrological verification certificate of the standard flow rate detection device. It is a known error characteristic parameter fixed to the device. The unit of this first uncertainty is consistent with the unit of the standard flow rate value (e.g., m³ / s or L / min).

[0049] The second uncertainty is calculated based on multiple flow measurements taken under calibration conditions. Specifically, multiple independently measured flow values ​​under the same calibration condition are treated as a sample, and their standard deviation is calculated using the Bessel formula. This standard deviation is the second uncertainty, and its unit is the same as the unit of the flow measurement (m³ / s or L / min). In this way, the inherent systematic error of the standard flow detection path and the random measurement error of the flow detection path itself are extracted in a quantified form.

[0050] Dividing the first uncertainty by the standard flow rate obtained from the measurement yields the relative uncertainty (dimensionless) of the standard flow rate; dividing the second uncertainty by the measured flow rate yields the relative uncertainty (dimensionless) of the measured flow rate. The square root of the sum of the squares of both is then multiplied by a preset coverage factor to obtain the calibration uncertainty. From a dimensional perspective, the first uncertainty has the same dimension as the standard flow rate (volume flow rate), and the ratio becomes a pure value after eliminating the dimension; the second uncertainty also has the same dimension as the measured flow rate, and the ratio also becomes a pure value. The square root of the sum of the squares of the two pure values ​​is still a pure value, and multiplying it by the dimensionless coverage factor also results in a pure value. Therefore, the calibration uncertainty is a dimensionless number, which can be directly compared with the preset uncertainty threshold (also a dimensionless percentage). This synthesis method follows the uncertainty propagation law, synthesizing the relative uncertainties from two independent sources using the root-squaring method, reflecting the sum-of-squares relationship between the total uncertainty and each component.

[0051] By comparing the calculated calibration uncertainty with a preset uncertainty threshold, the accuracy of the standard flow rate and flow measurement data obtained under the current calibration conditions can be quantitatively determined. When the calibration uncertainty is less than or equal to the preset uncertainty threshold, it indicates that the measurement data under the current calibration conditions is reliable and can be directly used to calculate the original correction coefficients. When the calibration uncertainty is greater than the preset uncertainty threshold, it indicates that the measurement data under the current calibration conditions is too dispersed or the uncertainty of the standard flow detection path is relatively high. In this case, increasing the number of measurements of the fire-resistant oil under the current calibration conditions and re-acquiring multiple sets of flow control data can further reduce the value of the second uncertainty by increasing the sample size (because the standard deviation tends to stabilize and usually decreases as the sample size increases), thereby reducing the recalculated calibration uncertainty to an acceptable range. This adaptive retesting mechanism avoids using unreliable calibration data to construct a two-dimensional correction matrix model, fundamentally ensuring the statistical reliability of each original correction coefficient in the model.

[0052] As a preferred example, the preset coverage factor can be set to k=2, corresponding to approximately 95% confidence level; the preset uncertainty threshold can be set to 0.05%. When the calibration uncertainty exceeds 0.05%, the system automatically prompts for recalibration or increases the number of repeated measurements. Under each calibration condition, the initial number of measurements can be set to three. If the calibration uncertainty exceeds the limit, the number of measurements will be increased to five or more until the calibration uncertainty meets the threshold requirement, thereby ensuring that the original correction coefficients of all nodes in the two-dimensional correction matrix model have high confidence and low uncertainty.

[0053] After the original correction coefficients of all nodes in the two-dimensional correction matrix model are calibrated, verification points that were not included in the calibration (such as 22℃, 28L / min) can be selected for verification testing. The corrected flow measurement values ​​are compared with the standard values, and the verification error should be within ±0.1%. If the verification fails, the system will automatically supplement the calibration points or adjust the interpolation algorithm weights.

[0054] Furthermore, by fitting all the original correction coefficients within the calibration region, the nonlinearity of each calibration region is calculated, including: All original correction coefficients within the calibration region are extracted from the two-dimensional correction matrix model, and an ideal plane is constructed by fitting multiple original correction coefficients to show linear changes with temperature and flow rate within the corresponding calibration region; Extract at least one original correction coefficient adjacent to the calibration region from the two-dimensional correction matrix model, and combine all the original correction coefficients in the calibration region to fit and construct a correction coefficient surface in which multiple original correction coefficients change nonlinearly with temperature and flow rate in the corresponding calibration region. Obtain the maximum absolute deviation between the correction coefficient surface and the ideal plane within the corresponding calibration area, and calculate the average value of all original correction coefficients within the calibration area; The nonlinearity of the corresponding calibration region is calculated based on the maximum absolute deviation and the average value. The functional expression for calculating the nonlinearity is as follows:

[0055] In the formula, Indicates the nonlinearity of the calibration region. This represents the fitted correction coefficient value corresponding to any calibration temperature and calibration flow rate in the correction coefficient surface. This represents the correction factor value for fitting the data at any calibrated temperature and calibrated flow rate in the ideal plane. Indicates the calibration temperature. Indicates the calibrated flow rate. This represents the average value of all original correction coefficients within the calibration area.

[0056] By implementing the above-described embodiment of the adaptive temperature compensation metering method for fire-resistant oil filling, an ideal plane and a correction coefficient surface are fitted and constructed. These two fitting operations describe the variation of the correction coefficient with calibration temperature and calibration flow rate within the calibration region from the perspectives of linear approximation and higher-order approximation, respectively. The ideal plane reflects the theoretical value when the correction coefficient exhibits the simplest linear distribution within this region, while the correction coefficient surface reflects a more realistic variation trend after considering the influence of neighboring regions.

[0057] By obtaining the maximum absolute deviation between the correction coefficient surface and the ideal plane within the corresponding calibration region, and calculating the average value of all original correction coefficients within the calibration region, the nonlinearity of the calibration region is obtained by dividing the maximum absolute deviation value by the average value. The essence of this calculation process is to normalize the degree of extreme deviation between the actual distribution of correction coefficients within the region and the linear ideal distribution relative to the average magnitude of the correction coefficients in that region, thereby obtaining a relative nonlinearity index that is not affected by the magnitude of the absolute value of the correction coefficients.

[0058] From a dimensional perspective, the correction coefficient is the ratio of the standard flow rate to the measured flow rate, and is itself a dimensionless pure numerical value. Therefore, the fitted correction coefficient value corresponding to any calibration temperature and calibration flow rate, as well as the average value of all original correction coefficients within the calibration region, are dimensionless quantities. The difference between the correction coefficient surface and the ideal plane at the same calibration temperature and calibration flow rate is also a dimensionless quantity, and its absolute value remains dimensionless. The maximum absolute deviation value obtained by taking the maximum value within the entire calibration region is also a dimensionless quantity. Dividing the dimensionless maximum absolute deviation value by the dimensionless average value yields the dimensionless nonlinearity. The entire calculation process does not involve any parameters with physical dimensions; all calculations are performed at the pure numerical level. Therefore, the nonlinearity can be directly used as a dimensionless pure number for subsequent comparison with preset thresholds without unit conversion, ensuring the rigor of the calculation logic and the clarity of its physical meaning.

[0059] By calculating the nonlinearity of each calibration region, the linearity and nonlinearity of the correction coefficient distribution within that region can be quantitatively distinguished. A small nonlinearity indicates that the correction coefficient surface closely approximates the ideal plane within that region, and the correction coefficient exhibits an approximately linear relationship with temperature and flow rate. Conversely, a large nonlinearity indicates a significant deviation between the correction coefficient surface and the ideal plane within that region, and the correction coefficient displays strong nonlinear characteristics with temperature and flow rate. This quantitative indicator provides an objective basis for subsequently adaptively matching interpolation algorithms of varying complexity in different linearity regions.

[0060] As a preferred example, the ideal plane can be constructed using a bilinear fitting method; the modified coefficient surface can be constructed using a bicubic spline fitting method, where a four-by-four grid composed of sixteen original modified coefficients adjacent to the calibration region is used during fitting to ensure the continuity of the first and second derivatives of the surface.

[0061] Furthermore, the nonlinearity corresponding to the real-time operating condition is compared with a preset threshold, and an adaptive interpolation algorithm is used to calculate the result based on the comparison. This includes: If the nonlinearity corresponding to the real-time operating condition is less than the first preset threshold, then the bilinear interpolation algorithm is matched. If the nonlinearity corresponding to the real-time operating condition is greater than or equal to the first preset threshold and less than the second preset threshold, then the bicubic interpolation algorithm is matched. If the nonlinearity is greater than or equal to the second preset threshold, then a two-dimensional spline interpolation algorithm is used.

[0062] By implementing the above-described embodiment of the adaptive temperature compensation metering method for fire-resistant oil filling, the nonlinearity corresponding to the real-time operating condition is compared with a first preset threshold and a second preset threshold. Based on the comparison result, a bilinear interpolation algorithm, a bicubic interpolation algorithm, or a two-dimensional spline interpolation algorithm is adaptively matched, thereby achieving dynamic matching between computational complexity and the degree of nonlinearity in the calibration area. Nonlinearity It is a dimensionless pure number, obtained by dividing the maximum absolute deviation between the correction coefficient surface and the ideal plane by the average value of all original correction coefficients in the calibration area. Its magnitude directly reflects the degree of curvature of the correction coefficient as temperature (unit °C) and flow rate (unit L / min) change. The smaller the value, the closer the distribution of the correction coefficients is to linear, and low-order interpolation can meet the accuracy requirements. The larger the value, the more severe the surface curvature, requiring higher-order interpolation to accurately approximate it.

[0063] when When the value is less than the first preset threshold, a bilinear interpolation algorithm is used. The specific calculation process of this algorithm is as follows: Assume the calibration temperature of the real-time operating condition is T (unit: °C), the calibration flow rate is Q (unit: L / min), and the following conditions are met... , The correction coefficients for the four corner points are respectively First, linear interpolation is performed in the Q direction to obtain... and Then, linear interpolation is performed in the T direction to obtain... This algorithm uses only the original correction coefficients at the four corner points of the calibration area, resulting in minimal computation and the fastest response time. It is suitable for regions with linearly distributed correction coefficients. As a preferred example, the first preset threshold can be set to 5%, at which point the response time of the bilinear interpolation algorithm does not exceed 50ms.

[0064] When the first preset threshold ≤ When the threshold is less than the second preset threshold, a bicubic interpolation algorithm is used. This algorithm constructs a cubic interpolation surface using sixteen neighboring calibration points (forming a 4×4 grid), and its function form is as follows:

[0065] in, This represents the fitted correction coefficient value corresponding to any calibration temperature and calibration flow rate in the correction coefficient surface. Indicates the calibration temperature. Indicates the calibrated flow rate. Index indicating the calibrated temperature. Index representing the calibrated flow rate. This represents the polynomial coefficients obtained by fitting multiple original correction coefficients using the least squares method.

[0066] As mentioned above, coefficient The least squares method is used for fitting. This algorithm can smooth the gradient changes of the original correction coefficients, avoid the "crease" effect that may occur in the moderate nonlinear region of bilinear interpolation, and ensure the continuity and smoothness of the interpolation surface. (Each term...) The dimensions are respectively ( ), but polynomial coefficients The dimensions will be adjusted accordingly to make the final Maintain dimensionless dimensions. As a preferred example, the second preset threshold can be set to 15%, in which case the response time of the bicubic interpolation algorithm does not exceed 120ms.

[0067] when When the value is greater than or equal to the second preset threshold, a two-dimensional spline interpolation algorithm is used. This algorithm employs bicubic spline interpolation, and the constructed interpolation surface not only has continuous function values ​​at the calibration points, but also continuous first-order and second-order partial derivatives. Therefore, it can provide the highest compensation accuracy in the strongly nonlinear region, ensuring smooth curvature changes of the correction coefficient surface. Spline interpolation forces derivative continuity by splicing piecewise low-order polynomials, avoiding Runge oscillations that may occur with high-order polynomials. As a preferred example, when... When the accuracy is ≥ 15%, the two-dimensional spline interpolation algorithm is used, and the response time is no more than 200ms. At the same time, the calibration area is marked as a "strong nonlinear region", and it is recommended to encrypt the calibration points during subsequent calibration.

[0068] By setting the first preset threshold to 5% and the second preset threshold to 15%, and adaptively selecting the interpolation algorithm based on the interval into which the nonlinearity of the real-time operating conditions falls, fast linear interpolation (response ≤ 50ms) is used in the low nonlinearity region, medium-precision bicubic interpolation (response ≤ 120ms) is used in the medium nonlinearity region, and high-precision spline interpolation (response ≤ 200ms) is used in the high nonlinearity region. This mechanism ensures that the allocation of computing resources always matches the compensation requirements across the entire filling range. It avoids both the real-time performance degradation caused by uniformly using complex algorithms and the excessive compensation error in the strong nonlinearity region caused by uniformly using simple algorithms. Thus, the online compensation process simultaneously meets the real-time control response requirements (millisecond level) and the finished product filling accuracy standard of ±0.5%.

[0069] Preferably, when the temperature and original flow rates obtained under real-time operating conditions are close to the range boundaries, an extrapolation limiting algorithm can be used: when the real-time temperature value is lower than the lowest operating temperature boundary in the two-dimensional correction matrix model, interpolation is performed according to the lowest operating temperature boundary value, and a temperature exceeding the lower limit warning signal is output simultaneously; when the real-time temperature value is higher than the highest operating temperature boundary in the two-dimensional correction matrix model, interpolation is performed according to the highest operating temperature boundary value, and a temperature exceeding the upper limit warning signal is output simultaneously; when the real-time original flow rate value is lower than the minimum flow rate boundary or higher than the maximum flow rate boundary in the two-dimensional correction matrix model, interpolation is also performed according to the corresponding boundary flow rate value, and the over-range event is recorded in the signal processing module. This boundary processing mechanism avoids the interpolation algorithm from failing or calculating abnormal correction coefficients due to slight deviations from the calibrated range under real-time operating conditions, ensuring that a reasonable compensation correction coefficient can still be obtained near the range boundaries, thereby maintaining the continuity and stability of filling metering.

[0070] Furthermore, by outputting early warning signals and recording over-range events, operators or the filling control system can promptly detect abnormal operating conditions, facilitating adjustments to filling parameters or equipment inspections, and preventing the deterioration of metering accuracy caused by prolonged operation under over-range conditions. As a preferred example, when the real-time temperature is below 10℃, interpolation is performed at 10℃ and an early warning signal for a temperature exceeding the lower limit is output; when the real-time temperature is above 40℃, interpolation is performed at 40℃ and an early warning signal for a temperature exceeding the upper limit is output; when the real-time flow rate is below 1L / min or above 200L / min, interpolation is performed at 1L / min or 200L / min respectively, and the flow rate over-range event is recorded. This boundary processing algorithm effectively reduces the boundary extrapolation error to within ±0.08%, further ensuring filling metering accuracy under all operating conditions.

[0071] Furthermore, the adaptive temperature compensation metering method for fire-resistant oil filling also includes, after obtaining the compensated actual flow rate value, verifying the actual flow rate value and updating the compensation correction coefficient, including: The temperature value, the original flow rate before compensation, the actual flow rate after compensation, and the measured weight value of downstream filling are obtained for each filling cycle during the fire-resistant oil filling process. Obtain the density of the fire-resistant oil, and calculate the measured filling flow rate value downstream based on the density and weight value; Obtain the deviation between the actual flow rate and the filling flow rate within the filling cycle, and record the number of cycles in which the deviation value exceeds the preset deviation threshold based on the deviation value within multiple consecutive filling cycles. When the number of recorded cycles reaches the preset threshold, the temperature range and flow range where the deviation occurs are determined based on the temperature value and the original flow value, and the calibration area corresponding to the temperature range and flow range is located from the two-dimensional correction matrix model. The observation correction coefficient is obtained by back-calculating the deviation value based on the compensation correction coefficient of the real-time working conditions during the fire-resistant oil filling process. Based on the observed correction coefficients, a weighted moving average is performed on at least one original correction coefficient within the positioning calibration area to obtain the updated original correction coefficients. The functional expression for the weighted moving average is:

[0072] In the formula, This represents the original correction factor updated at the calibration temperature T and calibration flow rate Q. This represents the preset historical weighting coefficients. This represents the original correction factor before updating at the calibration temperature T and calibration flow rate Q. This represents the observation correction factor obtained by back-calculation at the calibration temperature T and calibration flow rate Q; Adjust the original correction coefficients in the corresponding calibration region of the two-dimensional correction matrix model according to the updated original correction coefficients to obtain the updated two-dimensional correction matrix model, and retain the two-dimensional correction matrix model before at least three iterations of updates.

[0073] By implementing the above-described embodiment of the adaptive temperature compensation metering method for fire-resistant oil filling, based on the acquired temperature value, original flow rate value, actual flow rate value, and weight value, and by converting the weight value into the downstream measured filling flow rate value using the density of the fire-resistant oil, a direct comparison relationship can be established between the compensated actual flow rate value and the downstream measured filling flow rate value. The deviation value between the two within the same filling cycle is calculated; this deviation value reflects the difference between the current compensation correction coefficient and the actual filling effect. By continuously recording the deviation values ​​for multiple filling cycles and counting the number of cycles in which the deviation value continuously exceeds a preset deviation threshold, this mechanism can effectively filter out false triggers caused by occasional random fluctuations. Only when the deviation persists and reaches a preset number of times is it determined to be a systematic model deviation, thereby avoiding unnecessary self-learning updates due to single abnormal data.

[0074] When the number of recorded cycles reaches a preset threshold, the temperature and flow ranges where the deviation occurs are determined, and the corresponding calibration areas are precisely located from the two-dimensional correction matrix model. This local positioning strategy ensures that the self-learning update only applies to the specific area where the deviation occurs, without affecting other areas in the two-dimensional correction matrix model that have not experienced deviations. This guarantees the locality and stability of the model update and avoids new deviations that might be introduced by global adjustments to the entire model. Based on the compensation correction coefficients of the real-time operating conditions during the fire-resistant oil filling process, the observed correction coefficients are calculated by back-calculating the deviation values. These observed correction coefficients represent the ideal correction coefficients that should actually be used within the current temperature and flow ranges; that is, the theoretical true value is derived from the actual measurement feedback.

[0075] Then, a weighted moving average is performed on at least one original correction coefficient within the calibration area. The observed correction coefficients are then weighted and merged with the original correction coefficients according to preset historical weighting coefficients to obtain the updated original correction coefficients. This weighted moving average operation can smoothly adjust the model parameters, incorporating the latest measured feedback information while preserving the continuity of historical data, avoiding drastic parameter jumps caused by a single update.

[0076] From a dimensional perspective, the compensation correction coefficient, observation correction coefficient, and original correction coefficient are all dimensionless values. The preset historical weighting coefficient is also a dimensionless pure number. Therefore, the updated original correction coefficient obtained from the weighted moving average is also a dimensionless value and can directly replace the corresponding original correction coefficient in the two-dimensional correction matrix model without causing dimensional conflicts. Historical weighting coefficient When the value of is between 0.7 and 0.9, the updated original correction coefficient retains 70% to 90% of the historical information and only absorbs 10% to 30% of the new observation information. This gradual update strategy allows the model to slowly adapt to the long-term drift of filling conditions (such as equipment aging, seasonal changes in ambient temperature, etc.) while avoiding model contamination caused by single measurement errors.

[0077] The original correction coefficients in the corresponding calibration region of the two-dimensional correction matrix model are adjusted according to the updated original correction coefficients to obtain the updated two-dimensional correction matrix model, while retaining the two-dimensional correction matrix model before at least three iterations of updates. This version management mechanism ensures that a new version model is generated after each self-learning update, while fully preserving historical versions. When the updated model exhibits anomalies or a decrease in accuracy, it can be rolled back to any previous stable version with a single click, ensuring the reliability and recoverability of the system.

[0078] As a preferred example, the preset deviation threshold can be set to 0.2%, the preset number of times threshold can be set to 10 consecutive filling cycles, and the historical weighting coefficient... Values ​​between 0.7 and 0.9 can be selected, and at least three historical versions are retained after each update. Through this online self-learning closed loop, the two-dimensional correction matrix model can be continuously optimized during use, constantly approximating the actual characteristics of fire-resistant oil filling, thereby maintaining a filling metering accuracy within ±0.5% over the long term, significantly reducing the frequency of manual calibration and maintenance costs.

[0079] As mentioned above, the model calibration cycle can be dynamically adjusted based on the following indicators: cumulative filling volume (indicates a check every 1000 tons filled), cumulative deviation (indicates calibration when the average deviation exceeds 0.15% over 30 consecutive filling cycles), temperature fluctuation range (indicates calibration when the filling temperature fluctuation exceeds 20℃ for one week), and model age (indicates verification when the model has been created for more than 6 months). Calibration prompts are sent to the filling control system via alarm output or remote communication, facilitating production management personnel to rationally schedule calibration.

[0080] This invention also discloses a flow meter device applied to the aforementioned adaptive temperature compensation metering method for fire-resistant oil filling, such as... Figure 2 As shown, the flow meter device includes: The housing assembly includes a housing body 1, a metering chamber 11 formed inside the housing body 1, an oil inlet 12 and an oil outlet 13 located on the housing body 1 and respectively connected to the metering chamber 11, and a degassing chamber 14 located above the housing body 1 and connected to the metering chamber 11. The metering assembly includes a vortex generator 111, a piezoelectric sensor 112, and a flow guide 4 disposed in the metering chamber 11. The vortex generator 111 has a triangular prism structure. The bottom of the vortex generator 111 is horizontally oriented towards the oil inlet 12, and the top of the vortex generator 111 is horizontally oriented towards the oil outlet 13. The piezoelectric sensor 112 is embedded inside the vortex generator 111. The flow guide 4 is disposed between the oil inlet 12 and the vortex generator 111 and has an arc-shaped structure. Temperature sensor 113 is embedded in the inner wall of metering chamber 11 and is used to collect the temperature value of fire-resistant oil. The compensation calculation unit is electrically connected to the piezoelectric sensor 112 and the temperature sensor 113 respectively, and the compensation calculation unit has a built-in two-dimensional correction matrix model.

[0081] By implementing the above-described flow meter device embodiment, fire-resistant oil enters the metering chamber 11 formed inside the housing body 1 from the inlet 12. Since the inlet 12 directly connects to the metering chamber 11 without any unnecessary bends, the flow path is short and smooth, making it particularly suitable for kinematic viscosities as high as 39.1%. ~52.9 The fire-resistant oil (at 40℃) passes smoothly under low temperature and high viscosity conditions, avoiding pressure loss and energy dissipation caused by sudden changes in flow path. Preferably, the range of the shell assembly can be set to 1L / min~1000L / min; the inner diameter of the metering chamber 11 is 80mm; the shell body 1 is integrally formed of 316L stainless steel, avoiding materials such as copper alloys that are easily corroded by fire-resistant oil; the inlet 12 and outlet 13 adopt NPT 1-inch interfaces, which can be directly connected to the filling pipeline and filling gun, reducing the use of adapters. The maximum pressure is 30MPa and the maximum operating temperature is 40℃, thus ensuring the structural strength and corrosion resistance of the shell during the fire-resistant oil filling process.

[0082] The fire-resistant oil entering the metering chamber 11 first passes through the arc-shaped guide 4, which is positioned between the inlet 12 and the vortex generator 111. This guide 4 gradually reduces any turbulence at the inlet 12 into a stable laminar flow, allowing the fluid to impact the subsequent vortex generator 111 at a uniform velocity profile. This suppresses the interference of fluid pulsation caused by flow rate fluctuations during filling (e.g., when switching between 20L / drum and 200L / drum) on the stability of the vortex. As a preferred example, the guide 4 is 6mm thick and made of stainless steel. Combined with the streamlined design of the vortex generator 111, this effectively reduces the resistance to the fire-resistant oil flow and avoids metering lag due to excessive viscosity.

[0083] The fire-resistant oil impacts the vortex generator 111 after being rectified by the guide element 4. The vortex generator 111 has a triangular prism structure, with the non-pointed base of the prism horizontally facing the oil inlet 12 and the pointed top horizontally facing the oil outlet 13, meaning the fire-resistant oil first impacts the blunt surface of the triangular prism. This directional design causes the trailing edge of the blunt surface to form a regular and strong vortex shedding, which significantly enhances the amplitude and stability of the vortex signal compared to the pointed-upflow method. In particular, it overcomes the damping effect of the high viscosity of the fire-resistant oil on vortex formation, ensuring that a clear and distinguishable vortex signal can still be generated under low flow rate (e.g., 1 L / min) and low temperature (e.g., 10°C) conditions. The piezoelectric sensor 112 is embedded inside the vortex generator 111, directly sensing the alternating pressure changes caused by the vortex, converting the fluid kinetic energy into an electrical signal. Since the sensor is located inside the generator, the signal transmission path is extremely short, greatly reducing the contamination of the original signal by pipeline vibration and electromagnetic interference. As a preferred example, the vortex generator 111 is made of 316L stainless steel, and the sensing surface of the piezoelectric sensor 112 is treated with PTFE coating. The measurement frequency range is 20Hz~1500Hz, and the range is 1L / min~1000L / min. It can be flexibly adapted to different filling specifications such as 20L / barrel and 200L / barrel.

[0084] After undergoing vortex detection within the metering chamber 11, the fire-resistant oil flows out from the outlet 13. Simultaneously, the degassing chamber 14, located above the housing body 1 and connected to the metering chamber 11, utilizes the density of the fire-resistant oil (1.13... ~1.17 The density of the fire-resistant oil is greater than that of air, causing tiny air bubbles carried in the oil to automatically rise and enter the degassing chamber 14. This prevents bubbles from causing a false increase in vortex frequency or signal attenuation in the measurement area, ensuring the accuracy of flow detection. The temperature sensor 113 is embedded in the inner wall of the metering chamber 11, directly contacting the flowing fire-resistant oil. It can acquire the temperature value of the fire-resistant oil in real time, with fast response and high measurement accuracy. As a preferred example, the temperature sensor 113 is a PT100 type, with a measurement range of 0℃~60℃ and a measurement accuracy of ±0.1℃, covering the working temperature range of 10℃~40℃ for fire-resistant oil filling.

[0085] The compensation calculation unit is electrically connected to the piezoelectric sensor 112 and the temperature sensor 113, and the compensation calculation unit has a built-in two-dimensional correction matrix model. This model pre-stores the original correction coefficients corresponding to different calibration temperatures (e.g., 10℃, 12℃, 15℃, 18℃, 20℃, 23℃, 25℃, 28℃, 30℃, 33℃, 35℃, 38℃, 40℃, a total of thirteen temperature points) and different calibration flow rates (e.g., 1L / min, 2L / min, 5L / min, 8L / min, 10L / min, 15L / min, 20L / min, 30L / min, 50L / min, 80L / min, 100L / min, 150L / min, 200L / min, a total of thirteen flow rate points). The compensation calculation unit utilizes the vortex frequency signal output by the piezoelectric sensor 112 (corresponding to the uncompensated flow measurement value) and the temperature value output by the temperature sensor 113 to quickly match and obtain the compensation correction coefficient in the two-dimensional correction matrix model through an adaptive interpolation algorithm. It then corrects the uncompensated flow measurement value in real time and outputs the compensated actual flow value. This structure allows the entire flowmeter device to achieve high-precision temperature compensation without the need for an external standard flow source, relying solely on its embedded model and sensors. It is particularly suitable for environments with large temperature fluctuations during the filling of finished fire-resistant oil, effectively overcoming the measurement errors caused by viscosity changes with temperature in ordinary flowmeters. It stably controls the filling metering accuracy within ±0.5% across the entire temperature range of 10℃~40℃ and the entire flow range of 1L / min~200L / min.

[0086] Furthermore, the flow meter device also includes: The pre-filter 5 is installed inside the oil inlet 12; The degassing assembly includes a drain pipe 6 connecting the metering chamber 11 and the degassing chamber 14, a liquid level sensor 2 disposed in the degassing chamber 14, and an exhaust valve 3 disposed at the top of the degassing chamber 14. The drain pipe 6 is inclined. The signal processing module 7 is electrically connected to the piezoelectric sensor 112, the temperature sensor 113, the compensation calculation unit, the liquid level sensor 2, and the exhaust valve 3.

[0087] By implementing the above-described flow meter device embodiment, when fire-resistant oil enters from the inlet 12, it first passes through the pre-filter 5 disposed inside the inlet 12. This pre-filter 5 can trap trace impurities that may be carried in the fire-resistant oil, such as pipe debris or particulate matter, preventing these contaminants from entering the metering chamber 11 and damaging precision components such as the vortex generator 111 and piezoelectric sensor 112. It also avoids flow channel blockage leading to measurement interruption or instrument jamming. Because impurities are effectively filtered out, the fluid flow inside the metering chamber 11 remains pure, and the vortex shedding frequency on the surface of the vortex generator 111 will not change due to impurity adhesion, thus ensuring the long-term stability and repeatability of flow detection. As a preferred example, the pre-filter 5 can be a stainless steel filter screen with a filtration accuracy of 1. This ensures effective filtration without affecting the normal flow of fire-resistant oil, avoiding unnecessary flow loss or metering errors caused by the filter structure.

[0088] After being filtered, the fire-resistant oil flows into the metering chamber 11. During the flow, tiny air bubbles carried by the oil enter the guide pipe 6 connecting the metering chamber 11 and the degassing chamber 14. The guide pipe 6 is inclined; this inclined structure utilizes the physical property that air bubbles naturally rise in liquids due to density differences, guiding the air bubbles in the fire-resistant oil smoothly from the metering chamber 11 into the upper degassing chamber 14, preventing accumulation or airlock at the pipe connection. The density of the fire-resistant oil is approximately 1.13. ~1.17 The density of air is much smaller than that of air, so the bubbles rise rapidly in the drainage tube 6, achieving gas-liquid pre-separation and reducing the number of bubbles entering the core measurement area of ​​the metering cavity 11, thereby reducing the frequency jitter and amplitude attenuation of the vortex street signal caused by the bubbles.

[0089] After the bubbles enter the degassing chamber 14, due to its location above the housing body 1 and its large volume, the bubbles continue to rise to the top of the degassing chamber 14, forming an independent gas phase space. The degassed fire-resistant oil then falls back to the metering chamber 11 due to gravity to continue participating in flow measurement. The level sensor 2, located in the degassing chamber 14, monitors the oil level in the degassing chamber 14 in real time. When the oil level is lower than a preset threshold, it indicates that the gas accumulated at the top of the degassing chamber 14 has reached a certain volume and needs to be discharged. At this time, the signal processing module 7 controls the exhaust valve 3 located at the top of the degassing chamber 14 to open based on the electrical signal from the level sensor 2, quickly discharging the separated bubbles and preventing excessive bubble accumulation from re-mixing into the fire-resistant oil and affecting the metering accuracy. After the exhaust valve 3 opens, the oil level in the degassing chamber 14 rises back above the preset threshold, and the exhaust valve 3 automatically closes. This process does not affect the filling continuity. As a preferred example, the inclination angle of the drainage tube 6 can be set to 35°, the liquid level sensor 2 has a measurement accuracy of ±1mm, the exhaust valve 3 is sealed with fluororubber, the opening pressure is 0.08MPa, and the response time is no more than 100ms.

[0090] The signal processing module 7 is electrically connected to the piezoelectric sensor 112, temperature sensor 113, compensation calculation unit, liquid level sensor 2, and exhaust valve 3, realizing the acquisition of flow signals, temperature compensation calculation, degassing control, and comprehensive management of system status. For example, the signal processing module 7 receives the raw vortex electrical signal output by the piezoelectric sensor 112, amplifies and filters it to eliminate noise introduced by flow fluctuations and environmental interference during the filling process, obtaining a stable uncompensated flow measurement value; simultaneously, it receives the temperature value output by the temperature sensor 113 and transmits it to the compensation calculation unit; the compensation calculation unit has a built-in two-dimensional correction matrix model, calculates the compensation correction coefficient based on the temperature value and the uncompensated flow measurement value, and then sends it back to the signal processing module 7; the signal processing module 7 uses the compensation correction coefficient to correct the flow measurement value, obtains the compensated actual flow value, and performs accumulation, display, and quantitative control output. In addition, the signal processing module 7 can also control the opening and closing of the exhaust valve 3 based on the detection result of the liquid level sensor 2, realizing automatic management of the degassing process.

[0091] As a preferred example, the signal processing module 7 has a signal amplification factor of 1200 times, a filtering frequency of 0.2Hz~1500Hz, a data processing cycle of 80ms, and a signal output mode of 4-20mA analog signal and RS485 digital signal. It can be directly and seamlessly connected to the filling control system or PLC control cabinet to realize real-time monitoring of filling flow, automatic quantitative filling, and data statistics.

[0092] Through the coordinated operation of the above-mentioned components, the flow meter device of this invention can simultaneously perform impurity filtration, bubble separation, temperature compensation and automatic control during the filling process, which significantly improves the metering accuracy (stable within ±0.5%) and production continuity of finished fire-resistant oil filling, and reduces the metering error and equipment failure rate caused by impurity wear, bubble interference and temperature fluctuation.

[0093] Preferably, the flow meter device in this embodiment of the invention further includes a sealing assembly. The sealing assembly can adopt a high-pressure two-stage double-ring dynamic seal structure, which is set at the connection between the housing and the metering component and the temperature sensor 113, including a primary dynamic seal and a secondary dynamic seal. This dual-seal design forms two independent sealing barriers at the connection. When the primary dynamic seal experiences slight leakage due to long-term operation or local wear, the secondary dynamic seal can still effectively prevent the fire-resistant oil from leaking outward, thereby significantly improving the redundancy and reliability of the seal. For medium- and high-pressure conditions (e.g., filling pressure range) of finished fire-resistant oil filling, the synergistic effect of the two-stage seal can prevent high-pressure fluid from leaking from the assembly gap between the housing and the metering component and the mounting hole of the temperature sensor 113, avoiding waste of finished fire-resistant oil and environmental pollution.

[0094] Both the primary and secondary dynamic seals of the sealing assembly are made of fluororubber, supplemented by a PTFE backup seal. Fluororubber possesses excellent oil and chemical corrosion resistance, enabling it to withstand long-term erosion from fire-resistant oils and their trace hydrolysis products (such as phenol and phosphoric acid), unlike nitrile rubber or neoprene rubber which swell, harden, or crack. Simultaneously, the PTFE backup seal further enhances its resistance to compression and wear, maintaining the seal's fit even under high-pressure impacts or temperature fluctuations. The seals, shaft, and sensor probe employ a slight interference fit, ensuring tight contact of the sealing surfaces without generating excessive frictional resistance. This prevents interference with the flexible rotation of the shaft in the metering assembly or the signal output of the temperature sensor 113, ensuring the dynamic response characteristics of flow detection and the accuracy of temperature measurement.

[0095] Through the structural design of the aforementioned sealing components, a stable and reliable isolation layer is formed between the interior of the housing and the external environment. This not only prevents the finished fire-resistant oil from leaking outwards but also prevents external air and moisture from entering the inner cavity of the housing, avoiding hydrolytic degradation of the fire-resistant oil due to moisture absorption and corrosion of metal components due to the presence of moisture. This enables the flow meter device of this embodiment to operate continuously for a long period in the finished fire-resistant oil filling workshop, significantly reducing the frequency of equipment maintenance and the risk of finished product contamination due to seal failure, and extending the overall service life of the device.

[0096] To verify the temperature adaptability and accuracy of this invention for metering and filling finished fire-resistant oil, typical batches of fire-resistant oil samples were selected, and filling experiments with a fixed volume (200L) were conducted under seven temperature gradients: 10℃, 15℃, 20℃, 25℃, 30℃, 35℃, and 40℃. The control group used a conventional turbine flow meter without temperature compensation, while the experimental group used the fire-resistant oil metering flow meter of this invention. The experimental data are shown in Table 1 below: Table 1. Comparison of finished fire-resistant oil filling experiments under different temperature gradient conditions.

[0097] Note: 1. Viscosity values ​​are estimated based on typical viscosity-temperature characteristics of fire-resistant oils. Actual values ​​are subject to specific oil types. 2. Error rate calculation formula: (Measured value - Preset value) / Preset value × 100%. 3. The flow meter of this invention has an error rate controlled within ±0.1% across the entire temperature gradient of 10~40℃, which is far superior to the ±0.5% of ordinary flow meters and fully meets the stringent standard of ±0.5% for finished product filling.

[0098] The above gradient temperature experimental data shows that as the temperature increases from 10℃ to 40℃ and the viscosity of fire-resistant oil gradually decreases, the measurement error of ordinary flowmeters shows a trend of first decreasing and then slightly increasing. In the low temperature range (10℃), the error is as high as +1.34%, which cannot meet the requirements of high-precision filling. However, the flowmeter device of this invention relies on a dedicated compensation calculation unit to accurately capture the viscosity change law with temperature. It corrects the measurement signal in real time through a two-dimensional correction model, maintaining extremely high measurement accuracy throughout the entire temperature gradient. The error rate is stable within ±0.1%, which fully proves that this solution can fully meet the requirements of accurate filling of finished fire-resistant oil at different temperatures.

[0099] This invention also discloses an adaptive temperature compensation metering system applied to the aforementioned adaptive temperature compensation metering method for fire-resistant oil filling. The system includes: The flow measurement module is used to obtain the standard flow value and the uncompensated flow measurement value of fire-resistant oil when it is adjusted to different calibrated flow rates at different calibrated temperatures; The model building module is used to calculate and obtain the original correction coefficients for each calibration condition based on the standard flow rate and flow measurement value corresponding to different calibration conditions, and to build a two-dimensional correction matrix model based on the correspondence between calibration temperature, calibration flow rate and original correction coefficients. The coefficient fitting module is used to calculate the nonlinearity of each calibration region by fitting all the original correction coefficients within the calibration region bounded by any adjacent calibration temperatures and flow rates in the two-dimensional correction matrix model. The real-time operating condition calibration module is used to obtain the real-time temperature value and the uncompensated original flow rate value during the fire-resistant oil filling process, and determine the nonlinearity of the real-time operating condition during the fire-resistant oil filling process based on the calibration area corresponding to the temperature value and the original flow rate value in the two-dimensional correction matrix model. The compensation and correction module is used to compare the nonlinearity corresponding to the real-time operating condition with the preset threshold, match the adaptive interpolation algorithm according to the comparison result, and calculate and obtain the compensation and correction coefficient of the real-time operating condition during the fire-resistant oil filling process. The compensation flow module is used to correct the original flow value according to the compensation correction coefficient to obtain the actual flow value after compensation under real-time operating conditions during the fire-resistant oil filling process.

[0100] The present invention also discloses an electronic device, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-mentioned adaptive temperature compensation metering method for fire-resistant oil filling.

[0101] The present invention also discloses a storage medium storing a computer program thereon, which, when executed by a processor, implements the above-described adaptive temperature compensation metering method for fire-resistant oil filling.

[0102] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0103] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0104] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0105] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of processing steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable apparatus for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0106] It should be understood that the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them. Those skilled in the art can modify the technical solutions described in the above embodiments, or make equivalent substitutions for some of the technical features; and all such modifications and substitutions should fall within the protection scope of the appended claims of the present invention.

Claims

1. A fire resistant oil filling self adaptive temperature compensation metering method characterized by: The adaptive temperature compensation metering method for fire-resistant oil filling includes: Obtain the standard flow rate and uncompensated flow rate measurement value of fire-resistant oil at different calibration temperatures and when adjusted to different calibration flow rates. Based on the standard flow rate value and the flow measurement value corresponding to different calibration conditions, the original correction coefficients for each calibration condition are calculated and obtained, and a two-dimensional correction matrix model is constructed based on the correspondence between the calibration temperature, the calibration flow rate and the original correction coefficients. Based on the calibration region enclosed by any adjacent calibration temperature and any adjacent calibration flow rate in the two-dimensional correction matrix model, the nonlinearity of each calibration region is calculated by fitting all the original correction coefficients within the calibration region. The real-time temperature value and uncompensated original flow rate value are obtained during the filling process of fire-resistant oil, and the nonlinearity of the real-time operating condition during the filling process is determined according to the calibration region corresponding to the temperature value and the original flow rate value in the two-dimensional correction matrix model. The nonlinearity corresponding to the real-time operating condition is compared with a preset threshold. Based on the comparison result, an adaptive interpolation algorithm is matched to calculate and obtain the compensation correction coefficient of the real-time operating condition during the fire-resistant oil filling process. The original flow rate value is corrected according to the compensation correction coefficient to obtain the actual flow rate value after compensation under real-time operating conditions during the fire-resistant oil filling process.

2. The fire-resistant oil filling self-adapting temperature compensation metering method according to claim 1, characterized in that, The acquisition of the standard flow rate value and uncompensated flow rate measurement value of fire-resistant oil at different calibration temperatures and adjusted to different calibration flow rates includes: Set a sequence of temperature points containing multiple different calibration temperatures and a sequence of flow points containing multiple different calibration flow rates; The calibration temperatures are extracted sequentially from the temperature point sequence, and the temperature of the fire-resistant oil is controlled to reach the extracted calibration temperatures until it stabilizes, thus obtaining the current temperature of the fire-resistant oil. The calibration flow rate is extracted sequentially from the flow rate point sequence, and the flow rate of the fire-resistant oil is controlled to reach the extracted calibration flow rate until it stabilizes, thereby obtaining the current flow rate of the fire-resistant oil. Obtain the standard flow rate value and the uncompensated flow rate measurement value when the fire-resistant oil reaches the current temperature and the current flow rate simultaneously to obtain flow rate comparison data; If, after obtaining the traffic comparison data, it is determined that the current traffic is not the last calibrated traffic in the traffic point sequence, then the next calibrated traffic is extracted from the traffic point sequence as the current traffic, and the next set of traffic comparison data is obtained. If, after obtaining the flow rate comparison data, it is determined that the current flow rate is the last calibrated flow rate in the flow rate point sequence, and the current temperature is not the last calibrated temperature in the temperature point sequence, then the next calibrated temperature is extracted from the temperature point sequence as the current temperature, and the next set of flow rate comparison data is obtained.

3. The fire-resistant oil filling self-adapting temperature compensation metering method according to claim 2, characterized in that, The setting includes a sequence of temperature points containing multiple different calibration temperatures and a sequence of flow points containing multiple different calibration flow rates, including: Obtain the viscosity-temperature characteristic curve of the fire-resistant oil as a function of temperature, and obtain the viscosity change rate in each temperature range based on the viscosity-temperature characteristic curve. The temperature range in which the viscosity change rate is greater than a preset change threshold is defined as the first temperature range, and multiple calibration temperatures are set within the first temperature range at a first temperature interval. The temperature range in which the viscosity change rate is less than or equal to a preset change threshold is defined as the second temperature range, and multiple calibration temperatures are set within the second temperature range at second temperature intervals that are greater than the first temperature interval. Obtain the range of the filling flow rate of the fire-resistant oil, and divide the range into a first flow rate interval and a second flow rate interval with a flow rate greater than the first flow rate interval; Within the first flow range, a plurality of calibration flows are set at a first flow interval, and within the second flow range, a plurality of calibration flows are set at a second flow interval with an interval greater than the first flow interval; All the calibration temperatures are sorted in ascending order of temperature value to obtain the calibrated temperature point sequence, and all the calibration flow rates are sorted in ascending order of flow rate value to obtain the calibrated flow rate point sequence.

4. The fire-resistant oil filling self-adapting temperature compensation metering method according to claim 2, characterized in that, The step of calculating and obtaining the original correction coefficient for each calibration condition based on the standard flow rate value and the flow measurement value corresponding to different calibration conditions includes: Based on the flow rate comparison data when the fire-resistant oil simultaneously reaches the current temperature and the current flow rate, the initial correction coefficient of the fire-resistant oil under the current calibration condition is calculated. The functional expression for calculating the initial correction coefficient is as follows: In the formula, represents the initial correction coefficient of the fire-resistant oil at the th calibration temperature and the th calibration flow rate, represents the index of the calibration temperature, represents the index of the calibration flow rate, represents the standard flow value measured by the standard flow detection passage, represents the flow measurement value measured by the flow detection passage; The flow rate comparison data of the fire-resistant oil at the current temperature and the current flow rate are acquired multiple times. Based on the initial correction coefficients corresponding to multiple sets of flow rate comparison data under the current calibration condition, the original correction coefficient of the fire-resistant oil under the current operating condition is calculated. The functional expression for calculating the original correction coefficient is as follows: In the formula, Indicates fire-resistant oil in the first The calibration temperature and the first The original correction factor for the calibrated flow rate. Indicates fire-resistant oil The second measurement The calibration temperature and the first Initial correction factor for a given flow rate Indicates the index of the number of measurements. Indicates the total number of measurements.

5. The adaptive temperature compensation metering method for fire-resistant oil filling according to claim 4, characterized in that, The adaptive temperature compensation metering method for fire-resistant oil filling further includes, before calculating and obtaining the original correction coefficient, performing an uncertainty assessment on the standard flow rate value and the flow rate measurement value obtained under the calibration conditions, including: Obtain the first uncertainty known when measuring the standard flow rate value, and obtain the second uncertainty when measuring the uncompensated flow rate based on the flow rate measurement values ​​measured multiple times under the calibration conditions; Based on the obtained first uncertainty and second uncertainty, and combined with the standard flow rate value and the flow rate measurement value obtained during the calibration condition, the calibration uncertainty of the fire-resistant oil under the current calibration condition is calculated. The functional expression for calculating the calibration uncertainty is as follows: In the formula, This indicates the calibration uncertainty of the fire-resistant oil under the current calibration conditions. This indicates the preset inclusion factor. Indicates the first degree of uncertainty. Indicates the second uncertainty; If the calibration uncertainty is greater than the preset uncertainty threshold, the number of measurements of the fire-resistant oil under the current calibration condition is increased, and multiple sets of flow comparison data under the current calibration condition are reacquired.

6. The adaptive temperature compensation metering method for fire-resistant oil filling according to claim 1, characterized in that, The nonlinearity of each calibration region is calculated by fitting all the original correction coefficients within the calibration region, including: Extract all the original correction coefficients within the calibration region from the two-dimensional correction matrix model, and fit and construct an ideal plane in which multiple original correction coefficients linearly change with temperature and flow rate within the corresponding calibration region; Extract at least one original correction coefficient adjacent to the calibration region from the two-dimensional correction matrix model, and combine all the original correction coefficients in the calibration region to fit and construct a correction coefficient surface in which the original correction coefficients change nonlinearly with temperature and flow rate in the corresponding calibration region; Obtain the maximum absolute deviation between the correction coefficient surface and the ideal plane within the corresponding calibration region, and calculate the average value of all the original correction coefficients within the calibration region; The nonlinearity corresponding to the calibration region is calculated based on the maximum absolute deviation value and the average value. The functional expression for calculating the nonlinearity is as follows: In the formula, Indicates the nonlinearity of the calibration region. This represents the fitted correction coefficient value corresponding to any calibration temperature and calibration flow rate in the correction coefficient surface. This represents the correction factor value for fitting the data at any calibrated temperature and calibrated flow rate in the ideal plane. Indicates the calibration temperature. Indicates the calibrated flow rate. This represents the average value of all original correction coefficients within the calibration area.

7. The adaptive temperature compensation metering method for filling fire-resistant oil according to claim 6, characterized in that, The step of comparing the nonlinearity corresponding to the real-time operating condition with a preset threshold, and calculating the value using an adaptive interpolation algorithm based on the comparison result, includes: If the nonlinearity corresponding to the real-time operating condition is less than the first preset threshold, then the bilinear interpolation algorithm is matched. If the nonlinearity corresponding to the real-time operating condition is greater than or equal to the first preset threshold and less than the second preset threshold, then the bicubic interpolation algorithm is matched. If the nonlinearity is greater than or equal to the second preset threshold, then a two-dimensional spline interpolation algorithm is matched.

8. The adaptive temperature compensation metering method for fire-resistant oil filling according to claim 1, characterized in that, The adaptive temperature compensation metering method for fire-resistant oil filling further includes, after obtaining the compensated actual flow rate value, verifying the actual flow rate value and updating the compensation correction coefficient, including: The temperature value, the original flow rate value before compensation, the actual flow rate value after compensation, and the measured weight value of downstream filling are obtained for each filling cycle during the fire-resistant oil filling process. The density of the fire-resistant oil is obtained, and the downstream filling flow rate is calculated based on the density and the weight value. Obtain the deviation between the actual flow rate value and the filling flow rate value within the filling cycle, and record the number of cycles in which the deviation value continuously exceeds a preset deviation threshold based on the deviation value within multiple consecutive filling cycles; When the number of recorded cycles reaches a preset threshold, the temperature range and flow range where the deviation occurs are determined based on the temperature value and the original flow value, and the calibration area corresponding to the temperature range and flow range is located from the two-dimensional correction matrix model. The observation correction coefficient is obtained by back-calculating the deviation value based on the compensation correction coefficient of the real-time working conditions during the filling process of the fire-resistant oil. Based on the observed correction coefficients, a weighted moving average is performed on at least one of the original correction coefficients within the calibration area to obtain the updated original correction coefficients. The functional expression for the weighted moving average is: In the formula, This represents the original correction factor updated at the calibration temperature T and calibration flow rate Q. This represents the preset historical weighting coefficients. This represents the original correction factor before updating at the calibration temperature T and calibration flow rate Q. This represents the observation correction factor obtained by back-calculation at the calibration temperature T and calibration flow rate Q; Adjust the original correction coefficients in the corresponding calibration region of the two-dimensional correction matrix model according to the updated original correction coefficients to obtain the updated two-dimensional correction matrix model, and retain the two-dimensional correction matrix model before at least three iterations of updates.

9. A flow meter device, applied to the adaptive temperature compensation metering method for fire-resistant oil filling as described in any one of claims 1-8, characterized in that, The flow meter device includes: The housing assembly includes a housing body, a metering chamber formed inside the housing body, an oil inlet and an oil outlet located on the housing body and respectively communicating with the metering chamber, and a degassing chamber located above the housing body and communicating with the metering chamber. The metering assembly includes a vortex generator, a piezoelectric sensor, and a flow guide disposed within the metering cavity. The vortex generator has a triangular prism structure, with the non-pointed base of the vortex generator horizontally facing the oil inlet and the pointed top of the vortex generator horizontally facing the oil outlet. The piezoelectric sensor is embedded inside the vortex generator, and the flow guide is disposed between the oil inlet and the vortex generator and has an arc-shaped structure. A temperature sensor, embedded in the inner wall of the metering cavity, is used to collect the temperature value of the fire-resistant oil. The compensation calculation unit is electrically connected to the piezoelectric sensor and the temperature sensor respectively, and the compensation calculation unit has the two-dimensional correction matrix model built in.

10. The flow meter device according to claim 9, characterized in that, The flow meter device further includes: A pre-filter is disposed inside the oil inlet; The degassing assembly includes a drain pipe connecting the metering chamber and the degassing chamber, a liquid level sensor disposed in the degassing chamber, and an exhaust valve disposed at the top of the degassing chamber, wherein the drain pipe is inclined. The signal processing module is electrically connected to the piezoelectric sensor, the temperature sensor, the compensation calculation unit, the liquid level sensor, and the exhaust valve.

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