Anti-burn oil flow compensation method and flowmeter based on viscosity-temperature mode decomposition double filtering

Abstract

The present application relates to the technical field of flow measurement, in particular to a kind of anti-burning oil flow compensation method and flowmeter based on viscosity-temperature modal decomposition double filtering, method includes obtaining the measured temperature value and measured viscosity value of anti-burning oil temperature stable to target constant temperature fluctuation range, and carry out synchronous viscosity-temperature characteristic modal decomposition, obtain fast variable viscosity component and slow variable viscosity component, construct the state observation model of double time scale respectively and carry out filtering estimation, obtain the standard viscosity value under target constant temperature, with two filtering estimation values fusion calculation actual total viscosity, obtain basic compensation coefficient by piecewise linear reference function, superimpose the aging offset correction amount based on slow variable viscosity estimation value, obtain dynamic compensation coefficient, utilize dynamic compensation coefficient to the original flow measurement value is revised, obtain the actual flow value after compensation.The present application can eliminate the double influence of temperature disturbance and oil deterioration on measurement, make full-condition flow measurement precision significantly improve.

Description

Technical Field

[0001] This invention relates to the field of flow metering technology, and in particular to a fire-resistant oil flow compensation method and flow meter based on viscosity-temperature mode decomposition dual filtering. Background Technology

[0002] The kinematic viscosity of fire-resistant oil (mainly phosphate ester fire-resistant oil) is highly sensitive to temperature, and its viscosity can vary by several times within the common ambient temperature range of 5℃ to 35℃. During flow measurement, significant changes in viscosity can directly cause the instrument coefficient of volumetric flow meters (such as oval gear flow meters) to drift, leading to excessive measurement errors. In existing technologies, some solutions use temperature compensation algorithms to correct errors, but these algorithms are only effective within small temperature fluctuations and cannot fundamentally eliminate the impact of viscosity changes on measurement. Other solutions use external heating devices for simple pipeline heating, but these are not integrated with the flow meter body, making it difficult to accurately control the temperature of the oil entering the flow meter, and they suffer from drawbacks such as uneven heating, overheating of empty pipes, and significant interference from ambient temperature.

[0003] In recent years, some improvement solutions have proposed an integrated structure of "pre-heating constant temperature heating + flow meter", which attempts to heat fire-resistant oil with different inlet temperatures to a constant temperature state, so that the viscosity of the oil entering the flow meter is stable within the allowable range. However, the following technical problems remain unresolved in practical applications: (1) Due to factors such as instantaneous flow fluctuations, lag in heating power response, and ambient temperature interference, the actual oil temperature entering the flow meter is difficult to be strictly stabilized at the target value, and the corresponding viscosity still fluctuates within a small range, causing the volumetric flow meter's instrument coefficient to deviate, and the final measurement error may still exceed ±0.5%; (2) Existing solutions all implicitly assume "constant temperature equals constant viscosity", but the viscosity of fire-resistant oil depends not only on temperature, but also on various factors such as the degree of oil aging, water content, and additive consumption. Even if the temperature is strictly constant, the viscosity of fire-resistant oil that has been running for a long time may still rise slowly. Constant temperature heating cannot compensate for the measurement deviation caused by this, and frequent offline calibration is required, resulting in high maintenance costs; (3) The gear clearance and flow channel geometry of traditional volumetric flow meters are fixed values, and they have no passive adjustment capability for temperature changes. They cannot offset the volume measurement deviation caused by viscosity fluctuations from a mechanistic perspective, and rely entirely on external temperature control and algorithm correction, which is not robust enough.

[0004] Therefore, there is an urgent need for an integrated intelligent metering solution that can simultaneously achieve active constant temperature heating, online viscosity sensing, dynamic instrument coefficient correction, and passive structural compensation. Summary of the Invention

[0005] The purpose of this invention is to provide a fire-resistant oil flow compensation method and flow meter based on viscosity-temperature mode decomposition dual filtering, so as to solve the problems in the prior art of fire-resistant oil flow measurement caused by viscosity changes due to temperature fluctuations and oil aging, the inability of constant temperature scheme to eliminate residual errors, and the lack of real-time viscosity feedback and passive compensation capabilities.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: This invention discloses a fire-resistant oil flow compensation method based on viscosity-temperature mode decomposition dual filtering, comprising: The temperature of the fire-resistant oil is controlled to be stable within a preset target constant temperature range, and the measured temperature and viscosity values ​​of the fire-resistant oil are obtained when it is stable within the temperature fluctuation range. Synchronous viscosity-temperature characteristic mode decomposition was performed on the measured viscosity value and the measured temperature value to obtain the fast viscosity component caused by residual temperature disturbance and the slow viscosity component caused by oil deterioration. An adaptive state observation model with dual time scales is constructed to filter and estimate the fast-varying viscosity component and the slow-varying viscosity component respectively, so as to obtain the filtered fast-varying viscosity estimate and the slow-varying viscosity estimate. Obtain the standard viscosity value of the fire-resistant oil at the target constant temperature, and calculate the current actual total viscosity of the fire-resistant oil based on the standard viscosity value, the fast-changing viscosity estimate, and the slow-changing viscosity estimate. Based on the actual total viscosity, the basic compensation coefficient is obtained through a piecewise linear reference function calibrated in advance, and the dynamic compensation coefficient is obtained by superimposing the aging offset correction amount on the slowly varying viscosity estimate. The original flow measurement value of the fire-resistant oil during the flow metering process is obtained, and the original flow measurement value is corrected according to the dynamic compensation coefficient to obtain the compensated actual flow value.

[0007] Optionally, the step of performing simultaneous viscosity-temperature characteristic mode decomposition on the measured viscosity value and the measured temperature value to obtain the fast viscosity component caused by residual temperature perturbation and the slow viscosity component caused by oil degradation includes: A first time series consisting of the measured viscosity values ​​at multiple times and a second time series consisting of the measured temperature values ​​at multiple times are obtained; Using the frequency distribution characteristics of the second time series as a frequency domain reference, the first time series is decomposed into multiple modal components based on adaptive variational mode decomposition; The center frequency of each modal component is obtained, and the modal components with a center frequency greater than a preset frequency threshold are classified as fast viscosity components, while the modal components with a center frequency less than or equal to the preset frequency threshold are classified as slow viscosity components.

[0008] Optionally, the construction of the dual-time-scale adaptive state observation model filters and estimates the rapidly varying viscosity component and the slowly varying viscosity component respectively, to obtain filtered rapidly varying viscosity estimates and slowly varying viscosity estimates, including: Construct fast-scale state-space models and slow-scale state-space models; The instantaneous value of the rapidly varying viscosity component at the current moment is used as the observation input of the fast-scale state-space model. The estimated value of the rapidly varying viscosity at the current moment is output by performing prediction-update recursive calculation, and the residuals in the update process are recorded. Obtain the window average value of the slow-varying viscosity component at the current time, and use the window average value as the observation input of the slow-scale state-space model. Output the estimated value of the slow-varying viscosity at the current time by performing prediction-update recursive calculation. The model parameters of the slow-scale state-space model are corrected based on the residuals, and the baseline reference for state prediction of the fast-scale state-space model is updated based on the slow viscosity estimate. Based on the modified slow-scale state-space model and the updated fast-scale state-space model, the prediction-update recursive calculation is performed again, and the filtered fast-variable viscosity estimate and slow-variable viscosity estimate at the current time are output respectively.

[0009] Optionally, the construction of the fast-scale state-space model and the slow-scale state-space model includes: Based on the dynamic characteristics of the rapidly varying viscosity components, a fast-scale state-space model is constructed, comprising a first state equation and a first observation equation. The functional expressions of the first state equation and the first observation equation are as follows:

[0010]

[0011] In the formula, Indicates the rapid viscosity component in the th... The state variable at time t, Indicates the rapid viscosity component in the th... The state variable at time t, This represents noise in fast-scale processes. Indicates the rapid viscosity component in the th... The observed value at time, Indicates the rapid viscosity component in the th... The instantaneous value at a given moment. This indicates fast-scale observation noise. Indicates a fast-scale time index; Based on the dynamic characteristics of the slowly varying viscosity component, a slow-scale state-space model is constructed, comprising a second state equation and a second observation equation. The functional expressions of the second state equation and the second observation equation are as follows:

[0012]

[0013] In the formula, Indicates the slow viscosity component in the th... The state variable at time t, Indicates the slow viscosity component in the th... The state variable at time t, This represents noise in slow-scale processes. Indicates the slow viscosity component in the th... The observed value at time, Indicates the slow viscosity component in the th... The average value of the window at time points. This indicates slow-scale observation noise. This indicates a slow-scale time index.

[0014] Optionally, the fire-resistant oil flow compensation method further includes obtaining the window average value of the slowly varying viscosity component when constructing the slow-scale state-space model, including: Obtain a pre-calibrated standard viscosity-temperature curve function, and determine the standard viscosity value at the target isothermal temperature from the standard viscosity-temperature curve function; Based on the measured viscosity value and the standard viscosity value at the current moment, the viscosity difference at the current moment is calculated, and the viscosity difference at multiple moments is obtained to obtain a time series of the difference. The time series difference is averaged using a preset window length to obtain the window average of the slowly varying viscosity component. The function expression for the sliding window averaging is:

[0015] In the formula, This represents the measured viscosity value. Indicates the standard viscosity value. This represents the measured temperature value. This means summing all values ​​within the current window and then averaging them. Indicates the time index.

[0016] Optionally, obtaining the basic compensation coefficient through a pre-experimentally calibrated piecewise linear reference function and superimposing the aging offset correction amount based on the slowly varying viscosity estimate includes: Query the pre-calibrated piecewise linear reference function, and obtain the basic compensation coefficient corresponding to the viscosity range of the actual total viscosity from the piecewise linear reference function; Based on the estimated slow viscosity and the preset aging sensitivity coefficient, the aging offset correction is calculated. The functional expression for calculating the aging offset correction is as follows:

[0017] In the formula, This indicates the amount of aging offset correction. Indicates the aging sensitivity coefficient. This represents an estimate of the slowly changing viscosity. Based on the aging offset correction amount and the basic compensation coefficient, the dynamic compensation coefficient is calculated, and the functional expression for calculating the dynamic compensation coefficient is as follows:

[0018] In the formula, Indicates the dynamic compensation coefficient. Indicates the basic compensation coefficient. This indicates the actual total viscosity.

[0019] Optionally, the step of correcting the original flow measurement value according to the dynamic compensation coefficient to obtain the compensated actual flow value includes: The actual flow rate is calculated based on the dynamic compensation coefficient and the original flow rate measurement. The functional expression for calculating the actual flow rate is as follows:

[0020] In the formula, This represents the actual flow rate. This represents the original flow measurement value. Indicates the time index.

[0021] Optionally, stabilizing the temperature of the fire-resistant oil within a preset target constant temperature range includes: Obtain the physical properties of the fire-resistant oil, as well as the measured inlet temperature and instantaneous volumetric flow rate of the fire-resistant oil before preheating; Based on the difference between the measured inlet temperature and the preset target constant temperature, and combined with the physical property parameters, the feedforward heating power of the fire-resistant oil is calculated. The functional expression for calculating the feedforward heating power is as follows:

[0022] In the formula, This represents the feedforward heating power of the fire-resistant oil at time t. This indicates the specific heat capacity of fire-resistant oil. Indicates the density of fire-resistant oil. This represents the instantaneous volumetric flow rate of fire-resistant oil at time t. This indicates the preset target constant temperature. This represents the measured inlet temperature of the fire-resistant oil at time t. Obtain the measured outlet temperature of the fire-resistant oil after preheating and before flow compensation, and calculate the feedback heating power based on the difference between the measured outlet temperature and the preset target constant temperature. The functional expression for calculating the feedback heating power is as follows:

[0023]

[0024] In the formula, This represents the feedback heating power of the fire-resistant oil at time t. This represents the preset scaling factor. This represents the difference between the fire-resistant oil at time t and the target isothermal temperature. This represents the preset integral coefficient. This represents the preset differential coefficient. Indicates the difference versus time The points, Indicates the difference versus time The derivative, This represents the measured outlet temperature of the fire-resistant oil at time t. The feedforward heating power and the feedback heating power are superimposed to obtain the total heating power, and a heating power allocation command is generated. The fire-resistant oil is preheated in stages according to the heating power allocation command until the temperature stabilizes within the temperature fluctuation range of the target constant temperature.

[0025] The present invention also discloses a flow meter applied to the above-mentioned fire-resistant oil flow compensation method, wherein the flow meter includes a pre-heating constant temperature unit, a metering body and a sensing control unit; The pre-heating constant temperature unit includes a straight pipe section and a heating assembly disposed on the outer wall of the straight pipe section. The straight pipe section is divided into an inlet section rapid preheating zone and an outlet section constant temperature zone along the axial direction. The heating assembly includes a first heating element corresponding to the inlet section rapid preheating zone and a second heating element corresponding to the outlet section constant temperature zone. A heat homogenizing layer is provided between the first heating element and the second heating element and the outer wall of the straight pipe section, respectively. The metering body includes a housing, a volumetric metering rotor, and a pulse generating device. A metering chamber communicating with the oil outlet of the straight pipe section is formed inside the housing. The volumetric metering rotor is rotatably disposed in the metering chamber. The pulse generating device is fixedly disposed in the metering chamber. The pulse generating device and the volumetric metering rotor are non-contact magnetic coupling induction. The sensing and control unit includes a controller, an inlet temperature sensor, an outlet temperature sensor, and a viscosity sensor. The controller has an embedded calculation module for executing the fire-resistant oil flow compensation method. The controller is electrically connected to the first heating element, the second heating element, the pulse generator, the inlet temperature sensor, the outlet temperature sensor, and the viscosity sensor. The inlet temperature sensor is fixed in the oil inlet of the straight pipe section, and the outlet temperature sensor and the viscosity sensor are both fixed in the oil outlet of the straight pipe section.

[0026] Optionally, the flow meter further includes a passive thermal compensation component, a thermal insulation layer, a flow switch, and a seal. A fitting clearance is formed between the outer peripheral surface of the volumetric metering rotor and the inner wall of the metering chamber. The passive thermal compensation component is fixed on the inner wall of the metering chamber and located within the fitting clearance, and is used to expand to reduce the fitting clearance when the temperature rises. The thermal insulation layer is wrapped around the front constant temperature heating unit and the metering body. The flow switch is located at the oil inlet of the metering body and is electrically connected to the controller for linkage with the heating component. The two ends of the metering body are respectively formed with assembly interfaces that communicate with the metering chamber, and the sealing element is respectively fixed in the two assembly interfaces.

[0027] Compared with the prior art, the beneficial effects of the fire-resistant oil flow compensation method and flow meter based on viscosity-temperature mode decomposition dual filtering provided by the embodiments of the present invention are as follows: By stabilizing the fire-resistant oil temperature within the target isothermal temperature range, a stable prerequisite is provided for subsequent viscosity compensation. The measured viscosity and temperature values ​​are simultaneously decomposed to obtain the fast-changing component caused by residual temperature disturbances and the slow-changing component caused by oil degradation. A dual-time-scale adaptive state observation model is used to filter and estimate both components, yielding high-confidence estimates for both fast and slow viscosity. The standard viscosity value at the target isothermal temperature is then fused with the two estimates to calculate the actual total viscosity, ensuring that the total viscosity simultaneously includes information from three time scales: the baseline value, the second-level disturbance value, and the long-term drift value. A piecewise linear baseline function is used to process the actual total viscosity to obtain the basic compensation coefficient, which is then superimposed with an aging offset correction based on the slow-changing estimate, forming a dynamic compensation coefficient that compensates for both baseline changes and long-term drift. This coefficient is applied to the original flow measurement value, enabling the compensated actual flow value to simultaneously track the dual effects of fast-changing temperature disturbances and slow-changing oil degradation. Attached Figure Description

[0028] 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 1A schematic block diagram illustrating the steps of the fire-resistant oil flow compensation method provided in this embodiment of the invention; Figure 2 This is a schematic diagram of the overall structure of the flow meter provided in an embodiment of the present invention; Figure 3 This is a schematic flowchart illustrating the closed-loop control of fire-resistant oil temperature using a flow meter provided in an embodiment of the present invention.

[0029] The markings in the attached diagram are as follows: 1. Pre-heating constant temperature unit; 11. Straight pipe section; 12. Heating assembly; 2. Metering body; 21. Housing; 22. Volumetric metering rotor; 23. Pulse generator; 3. Sensor control unit; 31. Controller; 32. Inlet temperature sensor; 33. Outlet temperature sensor; 34. Viscosity sensor; 4. Thermal insulation layer; 5. Flow switch; 6. Sealing components; Detailed Implementation 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.

[0030] This invention discloses a fire-resistant oil flow compensation method based on viscosity-temperature mode decomposition dual filtering, such as... Figure 1 As shown, it includes: S1. Control the temperature of the fire-resistant oil to stabilize within the preset target constant temperature range, and obtain the measured temperature and viscosity values ​​of the fire-resistant oil when it stabilizes within the temperature fluctuation range; S2. Perform synchronous viscosity-temperature characteristic mode decomposition on the measured viscosity value and measured temperature value to obtain the fast viscosity component caused by residual temperature disturbance and the slow viscosity component caused by oil deterioration. S3. Construct an adaptive state observation model with dual time scales to filter and estimate the fast-varying viscosity component and the slow-varying viscosity component respectively, and obtain the filtered fast-varying viscosity estimate and the slow-varying viscosity estimate. S4. Obtain the standard viscosity value of the fire-resistant oil at the target constant temperature, and calculate the current actual total viscosity of the fire-resistant oil based on the standard viscosity value, the estimated value of the fast-changing viscosity, and the estimated value of the slow-changing viscosity. S5. Based on the actual total viscosity, obtain the basic compensation coefficient through the piecewise linear reference function calibrated in the pre-experiment, and obtain the dynamic compensation coefficient by superimposing the aging offset correction amount on the slowly varying viscosity estimate. S6. Obtain the original flow measurement value of the fire-resistant oil during the flow metering process, and correct the original flow measurement value according to the dynamic compensation coefficient to obtain the compensated actual flow value.

[0031] By implementing the above-described embodiment of the fire-resistant oil flow compensation method, firstly, the temperature of the fire-resistant oil is stabilized to the target constant temperature range, ensuring that the oil temperature entering the subsequent compensation stage is within a known and controllable narrow range. The introduction of this fluctuation range clarifies the practical engineering boundary of the temperature closed-loop control, namely, stabilizing the temperature of the fire-resistant oil to a temperature range that allows for small fluctuations. In engineering practice, due to factors such as instantaneous flow fluctuations, lag in heating power response, and ambient temperature interference, the measured outlet temperature value inevitably exhibits residual small fluctuations, which are the main physical source of the rapid viscosity component. Therefore, using "stabilizing to the preset target constant temperature range" as a prerequisite makes the rapid viscosity component physically explainable—it is a second-level viscosity fluctuation caused by residual temperature disturbances, assuming that large-scale temperature changes have been eliminated by the temperature closed-loop control. At this point, the measured viscosity value no longer contains the dominant evolution caused by large-scale temperature changes, but is mainly composed of two sources: one is the rapid fluctuations caused by residual temperature disturbances, and the other is the slow drift caused by long-term oil deterioration. These two sources are fundamentally different in both physical origin and time scale. The measured temperature value and the measured viscosity value were obtained synchronously in time and space, providing a frequency domain reference for subsequent synchronous decomposition.

[0032] Based on this, simultaneous viscosity-temperature characteristic mode decomposition is performed on the measured viscosity and temperature values. This separates the two physical quantities modally at the same frequency scale, allowing the fluctuations caused by residual temperature disturbances and the drift caused by long-term oil degradation in the measured viscosity value to be extracted as fast-changing viscosity components and slow-changing viscosity components, respectively. This simultaneous decomposition strategy utilizes the frequency distribution characteristics in the temperature signal as a frequency domain reference, accurately defining the frequency boundary between fast and slow changes. This avoids the mode aliasing problem caused by the lack of a frequency domain reference when decomposing based solely on a single viscosity signal, ensuring that the fast-changing and slow-changing viscosity components have a clear basis for distinguishing their physical origins.

[0033] An adaptive state observation model with two time scales is constructed. By matching the dynamic characteristics of the second-level fluctuations of the fast-changing component and the day-to-month drift of the slow-changing component with two observation models at different time scales, the measurement noise in their respective frequency bands can be effectively suppressed. Both the fast-changing viscosity estimate and the slow-changing viscosity estimate are filtered, which have higher confidence and smoother time-series characteristics compared with the original decomposed components, eliminating the interference of spurious fluctuations caused by sensor noise or instantaneous disturbances on the subsequent calculation of compensation coefficients.

[0034] The standard viscosity value is the theoretical viscosity of new oil at the target constant temperature, determined by factory calibration and unchanged over time. The actual total viscosity is calculated by fusing the standard viscosity value at the target constant temperature with the estimated rapid and slow viscosity changes. This fusion process ensures that the actual total viscosity simultaneously includes the reference viscosity at the factory calibration state, the instantaneous viscosity shift caused by residual temperature disturbances, and the slow viscosity drift caused by long-term oil degradation, achieving a coordinated expression of viscosity information at three different time scales. Subsequently, a pre-calibrated piecewise linear reference function is used to process the actual total viscosity to obtain the basic compensation coefficient. This function has its own linear mapping relationship in different viscosity ranges, accurately reflecting the fundamental law of viscosity variation in the volumetric flowmeter's coefficient. Based on this, an aging offset correction is separately superimposed on the slow viscosity estimate, decoupling the long-term degradation compensation part and the rapid temperature disturbance compensation part in the dynamic compensation coefficient, allowing them to adjust independently without interference.

[0035] After obtaining the original flow measurement value, a dynamic compensation coefficient is used to correct it, so that the compensated actual flow value simultaneously eliminates the influence of residual temperature disturbance represented by the fast viscosity component and the influence of oil degradation represented by the slow viscosity component, thereby achieving compensation for the dual sources of viscosity change under the target isothermal conditions.

[0036] Furthermore, simultaneous viscosity-temperature characteristic mode decomposition was performed on the measured viscosity and temperature values ​​to obtain the fast viscosity component caused by residual temperature disturbance and the slow viscosity component caused by oil degradation, including: A first time series consisting of measured viscosity values ​​at multiple times and a second time series consisting of measured temperature values ​​at multiple times are obtained. Using the frequency distribution characteristics of the second time series as a frequency domain reference, the first time series is decomposed into multiple modal components based on adaptive variational mode decomposition. The center frequency of each modal component is obtained. Modal components with a center frequency greater than a preset frequency threshold are classified as fast viscosity components, and modal components with a center frequency less than or equal to the preset frequency threshold are classified as slow viscosity components.

[0037] By implementing the above-described embodiment of the fire-resistant oil flow compensation method, a first time series and a second time series were obtained, establishing a synchronous correspondence between viscosity and temperature in the time dimension. This allows subsequent decomposition to process both signals under the same time reference, providing a data foundation for mode separation based on frequency characteristics. Using the frequency distribution characteristics of the second time series as a frequency domain reference, the naturally occurring frequency components in the temperature signal are used to guide the decomposition process of the first time series. The high-frequency components in the temperature signal reflect the frequency characteristics of residual temperature perturbations, while the low-frequency components reflect the frequency characteristics of slow temperature changes. By using this frequency distribution characteristic as a reference, the decomposition of the viscosity signal at the same frequency scale has a clear physical reference, avoiding mode aliasing.

[0038] Adaptive variational mode decomposition (ADD) decomposes the first time series into multiple modal components. This method iteratively solves the variational model to adaptively classify the signal into several modal components with different center frequencies. Each component represents the fluctuation characteristics of the viscosity signal in different frequency bands. Since the decomposition process uses the frequency distribution characteristics of the temperature signal as a reference, the center frequency of each modal component naturally corresponds to the frequency distribution of the temperature signal. Modal components with a center frequency greater than a preset frequency threshold are classified as fast-changing viscosity components, and those with a center frequency less than or equal to the preset frequency threshold are classified as slow-changing viscosity components. This classification method uses the frequency boundary between residual temperature disturbances and slow temperature changes in the temperature signal as the threshold basis, ensuring that the fast-changing viscosity components are physically related to residual temperature disturbances, and the slow-changing viscosity components are physically related to oil degradation. The two components do not overlap in the frequency domain and each has a clear physical meaning, providing a physically meaningful input signal for subsequent filtering estimation.

[0039] As an example, adaptive variational mode decomposition can employ a variational mode decomposition algorithm with a decomposition level of 2 (fast or slow only), a penalty factor of 1500, and a preset frequency threshold that can be determined based on the temperature signal spectrum analysis.

[0040] Furthermore, an adaptive state observation model with dual time scales is constructed to filter and estimate the rapidly varying viscosity component and the slowly varying viscosity component, respectively, to obtain the filtered rapidly varying viscosity estimate and the slowly varying viscosity estimate, including: Construct fast-scale state-space models and slow-scale state-space models; Using the instantaneous value of the rapidly varying viscosity component at the current moment as the observation input of the fast-scale state-space model, the estimated value of the rapidly varying viscosity at the current moment is output by performing prediction-update recursive calculation, and the residuals in the update process are recorded. Obtain the window average value of the slow-variable viscosity component at the current time, and use the window average value as the observation input of the slow-scale state-space model. Output the estimated value of the slow-variable viscosity at the current time by performing prediction-update recursive calculation. The model parameters of the slow-scale state-space model are corrected based on the residuals, and the baseline reference for state prediction of the fast-scale state-space model is updated based on the slow viscosity estimate. Based on the corrected slow-scale state-space model and the updated fast-scale state-space model, the prediction-update recursive calculation is performed again, and the filtered fast-variable viscosity estimate and slow-variable viscosity estimate at the current time are output respectively.

[0041] By implementing the above-described fire-resistant oil flow compensation method, fast-scale and slow-scale state-space models are constructed respectively. Independent processing channels are established for the different time-scale characteristics of the fast and slow viscosity components, enabling second-level fluctuations and day-to-month drifts to be recursively processed according to their respective suitable time scales. This avoids the problem of over-filtering of one component and under-filtering of another due to time-scale mismatch in a single observation model. As a preferred example, both the fast-scale and slow-scale state-space models can employ a Kalman filter structure to implement prediction-update recursive calculations.

[0042] Using the instantaneous value of the rapidly varying viscosity component at the current moment as the observation input, the estimated value of the rapidly varying viscosity at the current moment is output by performing a prediction-update recursive calculation. This process separates the noise component and the real fluctuation component in the rapidly varying component, so that the estimated value of the rapidly varying viscosity retains the rapid change characteristics of the rapidly varying component while eliminating random spikes caused by observation noise. The recorded residual contains information that was not interpreted by the model during the fast-scale filtering process, providing a usable basis for correction of the slow-scale model.

[0043] Using the window average value of the slow viscosity component at the current moment as the observation input, the slow viscosity estimate at the current moment is output by performing prediction-update recursion. The window averaging process suppresses the high-frequency residual components that may be mixed in the slow component, so that the data input to the slow-scale observation model has good smoothness. The prediction-update recursion further filters out the residual fluctuations that the window averaging cannot completely eliminate, so that the slow viscosity estimate can truly reflect the slow drift trend of oil deterioration without being disturbed by short-term disturbances.

[0044] The model parameters of the slow-scale state-space model are corrected based on the residuals, and the slowly varying viscosity estimate is updated as the baseline reference for the fast-scale state-space model when making state predictions, forming a two-way cascaded coupling mechanism. The residuals generated in the fast-scale filtering reflect systematic bias information in the fast-variable components that are not fully captured by the fast-scale model. This residual is passed to the slow-scale model and used to correct its parameters, enabling the slow-scale model to adjust its estimation benchmark for the slowly varying trend based on the feedback information from the fast-variable channel. At the same time, the slowly varying viscosity estimate is used as the baseline reference for the fast-scale model, allowing the fast-scale model to adjust its prediction benchmark based on the long-term trend information output by the slow-variable channel when making state predictions, thus achieving two-way information fusion between the fast and slow filters. In subsequent recursive calculations, the corrected slow-scale state-space model and the updated fast-scale state-space model are used for recursive calculations. This process ensures that after the fast and slow filter channels exchange information and mutually correct their parameters, the estimated values ​​output by each channel contain the information contribution of the other channel, resulting in higher estimation accuracy and stronger consistency compared to independent filtering.

[0045] Furthermore, fast-scale state-space models and slow-scale state-space models are constructed, including: Based on the dynamic characteristics of the rapidly varying viscosity components, a fast-scale state-space model is constructed, comprising a first state equation and a first observation equation. The functional expressions of the first state equation and the first observation equation are as follows:

[0046]

[0047] In the formula, Indicates the rapid viscosity component in the th... The state variable at time t, Indicates the rapid viscosity component in the th... The state variable at time t, This represents noise in fast-scale processes. Indicates the rapid viscosity component in the th... The observed value at time, Indicates the rapid viscosity component in the th... The instantaneous value at a given moment. This indicates fast-scale observation noise. Indicates a fast-scale time index; Based on the dynamic characteristics of the slowly varying viscosity component, a slow-scale state-space model is constructed, which includes a second state equation and a second observation equation. The functional expressions of the second state equation and the second observation equation are as follows:

[0048]

[0049] In the formula, Indicates the slow viscosity component in the th... The state variable at time t, Indicates the slow viscosity component in the th... The state variable at time t, This represents noise in slow-scale processes. Indicates the slow viscosity component in the th... The observed value at time, Indicates the slow viscosity component in the th... The average value of the window at time points. This indicates slow-scale observation noise. This indicates a slow-scale time index.

[0050] Furthermore, the fire-resistant oil flow compensation method also includes obtaining the window average value of the slowly varying viscosity components when constructing the slow-scale state-space model, including: Obtain the pre-calibrated standard viscosity-temperature curve function, and determine the standard viscosity value at the target isothermal temperature from the standard viscosity-temperature curve function; Based on the measured viscosity value and the standard viscosity value at the current moment, the viscosity difference at the current moment is calculated, and the viscosity difference values ​​at multiple moments are obtained to obtain a time series of the difference. A sliding window averaging process is applied to the difference time series with a preset window length to obtain the window average value of the slowly varying viscosity component. The functional expression for the sliding window averaging process is as follows:

[0051] In the formula, This represents the measured viscosity value. Indicates the standard viscosity value. This represents the measured temperature value. This means summing all values ​​within the current window and then averaging them. Indicates the time index.

[0052] By implementing the above-described embodiment of the fire-resistant oil flow compensation method, fast-scale state-space models and slow-scale state-space models were constructed respectively, achieving independent mathematical descriptions of the dynamic characteristics of the fast-varying viscosity components and the slow-varying viscosity components. The first state equation adopts a random walk model to describe the transition process of the fast-varying viscosity state variable between adjacent time steps. This equation reflects the transmission of the fast-varying viscosity component from the current time step to the next time step after adding process noise to the current time step. This characterizes the unpredictable fluctuations of the rapidly varying viscosity component caused by residual temperature perturbations within an extremely short timescale. The first observation equation then represents the instantaneous value of the rapidly varying viscosity component at the current moment. As a source of observation, and related to fast-scale observation noise. Together they constitute fast-scale observations .

[0053] As a preferred example, the fast-scale state-space model can use a fast-scale Kalman filter to achieve state estimation. Its process noise covariance and observation noise covariance can be set according to the fluctuation amplitude of the fast-varying components and the sensor noise level, for example, the process noise covariance is 0.0001, the observation noise covariance is 0.01, and the sampling period is 0.1s.

[0054] The second state equation employs a random walk model to describe the transition process of the slowly varying viscosity state variable between adjacent time steps, with process noise... This characterizes the slow and unpredictable drift trend of the slowly varying viscosity component caused by oil degradation over time scales ranging from days to months. The second observation equation uses the window average of the slowly varying viscosity component at the current moment as the observation source, and combines it with slow-scale observation noise. Together they constitute slow-scale observations .

[0055] The fast-scale and slow-scale state-space models maintain a consistent structure, differing only in the magnitudes of the process noise covariance and observation noise covariance, as well as their respective time index scales. This structural consistency allows both filters to share the same algorithmic framework when performing prediction-update recursive calculations, facilitating information exchange and parameter passing between them, and simplifying the algorithm's code implementation in embedded controllers. As an example, the slow-scale state-space model can employ a slow-scale Kalman filter for state estimation, with its sampling period set much larger than that of the fast-scale filter to match the rate of change of the slowly varying components. For instance, the process noise covariance could be 0.000001, the observation noise covariance 0.001, and the update period 600 seconds.

[0056] Since the slowly varying viscosity component reflects the oil degradation trend over days to months, directly using the instantaneous values ​​sampled at high frequencies as the observation input would result in a large amount of high-frequency residual noise and rapid disturbances masking the slowly varying trend signal, leading to a slower convergence speed for the slow-scale state estimation. Therefore, before inputting the slowly varying viscosity component into the second observation equation, it is pre-processed using a sliding window averaging. The standard viscosity value at the target isothermal temperature can be obtained through a pre-calibrated standard viscosity-temperature curve function. Based on the viscosity difference between the measured viscosity value and the standard viscosity value at the current moment, the viscosity change contributed by the temperature deviation from the target isothermal temperature is removed, so that the viscosity difference mainly reflects the viscosity change caused by non-temperature factors such as oil degradation. After obtaining the viscosity difference values ​​at multiple moments to form a difference time series, a sliding window averaging process is performed with a preset window length to obtain the window average value of the slowly varying viscosity component.

[0057] From a dimensional perspective, the measured viscosity value The unit is kinematic viscosity (e.g., unit of viscosity). Standard viscosity value The units of both are kinematic viscosity units, and the viscosity difference obtained by subtracting the two is also in kinematic viscosity units. The sliding window averaging operation sums all viscosity differences within the current window and divides by the window length. Summation and division operations do not change the dimensions of the physical quantity; therefore, the dimension of the output slowly varying viscosity component window average remains in kinematic viscosity units. The entire calculation process involves the same physical quantity (kinematic viscosity), requiring no normalization.

[0058] As a preferred example, the standard viscosity-temperature curve function can be pre-obtained from the measured viscosity-temperature data of fire-resistant oil through exponential or polynomial fitting, for example... The preset window length can be set to match the sampling period of the slow-scale state space model to ensure that complete window data is available for each slow-scale state update. At the same time, the window length should not be too short to avoid insufficient suppression of high-frequency residual noise, nor should it be too long to preserve the response speed of the slow variable component in tracking the oil deterioration trend.

[0059] Furthermore, the basic compensation coefficients are obtained through a piecewise linear benchmark function calibrated in advance, and aging offset corrections are superimposed based on the slowly varying viscosity estimate, including: Query the pre-calibrated piecewise linear reference function and obtain the basic compensation coefficient corresponding to the viscosity range of the actual total viscosity from the piecewise linear reference function; Based on the estimated slow viscosity and the preset aging sensitivity coefficient, the aging offset correction is calculated. The functional expression for calculating the aging offset correction is as follows:

[0060] In the formula, This indicates the amount of aging offset correction. Indicates the aging sensitivity coefficient. This represents an estimate of the slowly changing viscosity. Based on the aging offset correction and the basic compensation coefficient, the dynamic compensation coefficient is calculated. The functional expression for calculating the dynamic compensation coefficient is as follows:

[0061] In the formula, Indicates the dynamic compensation coefficient. Indicates the basic compensation coefficient. This indicates the actual total viscosity.

[0062] By implementing the above-described embodiment of the fire-resistant oil flow compensation method, the piecewise linear reference function can divide the viscosity variation range of the fire-resistant oil into multiple continuous intervals. Within each interval, the basic compensation coefficient has a linear mapping relationship with the actual total viscosity. This allows for simple linear calculations to obtain the corresponding basic compensation coefficient by determining which viscosity interval the actual total viscosity falls into, avoiding complex calculations involving higher-order polynomials or exponential functions. This piecewise linearization method results in extremely low computational complexity in obtaining the basic compensation coefficient, making it suitable for real-time operation in embedded controllers. Furthermore, pre-calibration experiments ensure that the mapping relationship within each interval is consistent with the actual flow meter coefficient's variation with viscosity.

[0063] As a preferred example, the piecewise linear reference function can be pre-constructed by measuring the flowmeter's instrument coefficient at multiple standard viscosity points and then using piecewise linear interpolation. The number of viscosity intervals can be determined based on the degree of nonlinearity of the flowmeter's instrument coefficient as a function of viscosity; the stronger the nonlinearity, the denser the interval divisions. For example, it can be calculated as follows: ≤20 hour, ;20 <ν≤35 hour, ν>35 hour, (Divided into three sections), reflecting the basic change of the flow meter coefficient with viscosity.

[0064] The slow viscosity estimate characterizes the slow viscosity drift of fire-resistant oil over days to months caused by factors such as oil aging, additive consumption, and water contamination, while the preset aging sensitivity coefficient... This reflects the compensation correction ratio corresponding to a unit change in slowly varying viscosity. The aging offset correction obtained by multiplying the two is specifically used to compensate for the viscosity shift caused by long-term degradation, forming an independent correction channel with the basic compensation coefficient. From a dimensional perspective, the dimension of the slowly varying viscosity estimate is in kinematic viscosity units, while the dimension of the preset aging sensitivity coefficient is the reciprocal of the kinematic viscosity units. Multiplying the two yields a dimensionless aging offset correction, consistent with the dimensionless property of the basic compensation coefficient. Therefore, the two can be directly added without additional dimensional conversion or normalization. This dimensional consistency ensures that the physical meaning of the dynamic compensation coefficient is clear—it is a dimensionless multiplicative correction factor that directly affects the original flow measurement value.

[0065] Because the base compensation coefficient and the aging offset correction amount correspond to different physical sources—the former is used to compensate for the baseline change in the flow meter coefficient under the actual total viscosity, and the latter is specifically used to compensate for the additional offset caused by long-term degradation—the two are independent and additive, allowing the dynamic compensation coefficient to simultaneously cover both the basic change and long-term drift of viscosity. The base compensation coefficient portion of the dynamic compensation coefficient adjusts in real time with changes in the actual total viscosity, enabling rapid response to instantaneous viscosity fluctuations caused by residual temperature disturbances; while the aging offset correction amount adjusts gradually with the slow change in the estimated viscosity, automatically tracking the oil degradation process without frequent offline calibration. This dual-channel independent correction mechanism ensures that the dynamic compensation coefficient has corresponding compensation components for viscosity change sources at different time scales, avoiding over-reliance on a single compensation channel and thus reducing the risk of overall compensation failure due to estimation errors in a single channel.

[0066] As a preferred example, the piecewise linear reference function can be calibrated by dividing the instrument coefficient of the elliptical gear flowmeter into three viscosity intervals based on experimental data of the change in viscosity with the elliptical gear flowmeter. The preset aging sensitivity coefficient can be determined by measuring the proportional relationship between the viscosity shift at different aging stages and the corresponding compensation correction amount in the accelerated aging test of the oil before leaving the factory. It is used to characterize the correction range of the dynamic compensation coefficient corresponding to each unit change in the estimated value of slow viscosity. Its physical meaning is the instrument coefficient compensation correction amount caused by a unit slow viscosity drift.

[0067] Furthermore, the original flow measurement value is corrected according to the dynamic compensation coefficient to obtain the compensated actual flow value, including: The actual flow rate is calculated based on the dynamic compensation coefficient and the original flow measurement value. The functional expression for calculating the actual flow rate is as follows:

[0068] In the formula, This represents the actual flow rate. This represents the original flow measurement value. Indicates the time index.

[0069] By implementing the above-described embodiment of the fire-resistant oil flow compensation method, the dynamic compensation coefficient is directly applied to the original flow measurement value, completing the entire chain from viscosity signal acquisition, mode decomposition, filtering estimation, total viscosity calculation, compensation coefficient generation to final flow correction. The dynamic compensation coefficient is a dimensionless multiplicative correction factor, while the original flow measurement value is in volumetric flow rate units. The actual flow value obtained by multiplying the two maintains the same volumetric flow rate dimension as the original flow measurement value, and the entire correction process does not involve dimension conversion or normalization. The original flow measurement value is the uncompensated flow value obtained by converting the original pulse signal output by the pulse generator of the flow meter. The dynamic compensation coefficient combines information from two independent channels: the basic compensation coefficient and the aging offset correction amount, which correspond to the instrument coefficient reference change under the actual total viscosity and the additional offset caused by long-term deterioration, respectively. After multiplying the two, the instantaneous viscosity fluctuation caused by residual temperature disturbance in the actual flow value is eliminated by the basic channel, and the slow viscosity drift caused by oil deterioration is eliminated by the aging channel, so that the corrected actual flow value is compensated on both the fast-changing disturbance and the slow-changing drift time scales.

[0070] As a preferred example, the original flow measurement value can be obtained from the volumetric flow rate value after pulse equivalent conversion of the original pulse signal output by the elliptical gear flow meter, and the dynamic compensation coefficient is directly multiplicatively corrected on the original flow measurement value.

[0071] As mentioned above, after correcting the actual flow rate, a residual-based mismatch detection and sensorless self-calibration process can be further performed: Calculate the squared difference between the current compensated actual flow rate and the reference flow rate, and then perform window averaging on the squared difference using a preset sliding window length to obtain the error energy at the current moment. The functional expression for calculating the error energy is as follows:

[0072] In the formula, Represents error energy. Indicates fire-resistant oil in The actual flow rate after time-compensation Indicates fire-resistant oil in The reference flow rate at any given time, where t represents the time index; The error energy is compared with a preset mismatch threshold. When the error energy exceeds the mismatch threshold for a duration that reaches a preset time threshold, the current compensation mismatch is determined. After determining the compensation mismatch, a recalibration process is triggered to continuously update the piecewise coefficients of the pre-calibrated piecewise linear benchmark function until the error energy is less than or equal to the mismatch threshold and the update stops.

[0073] Specifically, when a mismatch is detected in the current compensation, meaning that the piecewise coefficients of the pre-calibrated piecewise linear reference function can no longer accurately reflect the actual viscosity-instrument coefficient mapping relationship of the current fire-resistant oil, a background recalibration process is automatically triggered. This process updates the piecewise coefficients of the piecewise linear reference function, restoring the recalculated basic compensation coefficients to match the actual operating conditions. The entire recalibration process is executed in the background, without affecting the continuity and real-time performance of the metering output, thus achieving adaptive model maintenance without manual intervention.

[0074] As a preferred example, the window length of the sliding window error energy can be set to 600 seconds, the mismatch threshold can be set to 0.01%, and the duration threshold can be set to 10 minutes.

[0075] Furthermore, controlling the temperature of the fire-resistant oil to stabilize within a preset target constant temperature range includes: Obtain the physical properties of the fire-resistant oil, as well as the measured inlet temperature and instantaneous volumetric flow rate of the fire-resistant oil before preheating; Based on the difference between the measured inlet temperature and the preset target constant temperature, the feedforward heating power of the fire-resistant oil is calculated using physical property parameters. The functional expression for calculating the feedforward heating power is as follows:

[0076] In the formula, This represents the feedforward heating power of the fire-resistant oil at time t. This indicates the specific heat capacity of fire-resistant oil. Indicates the density of fire-resistant oil. This represents the instantaneous volumetric flow rate of fire-resistant oil at time t. This indicates the preset target constant temperature. This represents the measured inlet temperature of the fire-resistant oil at time t. Obtain the measured outlet temperature of the fire-resistant oil after preheating and before flow compensation. Calculate the feedback heating power based on the difference between the measured outlet temperature and the preset target constant temperature. The functional expression for calculating the feedback heating power is as follows:

[0077]

[0078] In the formula, This represents the feedback heating power of the fire-resistant oil at time t. This represents the preset scaling factor. This represents the difference between the fire-resistant oil at time t and the target isothermal temperature. This represents the preset integral coefficient. This represents the preset differential coefficient. Indicates the difference versus time The points, Indicates the difference versus time The derivative, This represents the measured outlet temperature of the fire-resistant oil at time t. The feedforward heating power and the feedback heating power are superimposed to obtain the total heating power, and a heating power allocation command is generated. The fire-resistant oil is preheated in stages according to the heating power allocation command until the temperature stabilizes within the temperature fluctuation range of the target constant temperature.

[0079] By implementing the above-described embodiment of the fire-resistant oil flow compensation method, the feedforward channel pre-calculates the required heating power based on the difference between the measured inlet temperature and the preset target constant temperature, as well as the instantaneous volumetric flow rate, before temperature disturbances occur. This allows for early response to changes in heat load, avoiding the inherent lag in traditional pure feedback control, which requires waiting for the measured outlet temperature to deviate from the target before starting adjustment. From a dimensional perspective, specific heat capacity... The unit is J / (kg) K), density The unit is Instantaneous volumetric flow rate The unit is Multiplying the three together gives J / (s) The value of feedforward heating power is W, which is calculated by multiplying the measured inlet temperature value by the difference between the measured inlet temperature value and the preset target constant temperature value (in K). The units of the feedforward heating power are W. The dimensions of each parameter are coordinated in the whole calculation process, and no additional normalization processing is required.

[0080] The feedback heating power is based on the deviation between the measured outlet temperature and the preset target constant temperature. It is calculated in parallel using proportional, integral, and derivative terms, and then superimposed to output the final power. The proportional term adjusts the power proportionally to the current deviation, ensuring a rapid increase in heating power as the deviation increases. The integral term integrates the accumulated historical deviations to eliminate steady-state residual deviations caused by system thermal inertia. The derivative term predicts the temperature change trend based on the rate of change of the deviation and applies reverse regulation in advance to suppress temperature overshoot and undershoot. The feedback channel performs temperature correction after the fire-resistant oil has been preheated and before entering the flow compensation stage, forming a time-based relay with the feedforward channel.

[0081] The feedforward channel pre-configures the initial power based on inlet conditions before the fire-resistant oil enters the heating section, gaining an advantage in active control. The feedback channel performs fine corrections just before the fire-resistant oil leaves the heating section and enters the metering stage, compensating for residual errors in the feedforward channel caused by model parameter deviations or unmodeled interference. The two complement each other in terms of time and function, forming a closed loop for temperature control from the heating inlet to the metering inlet, stabilizing the measured outlet temperature value within the preset target constant temperature fluctuation range.

[0082] After generating the total heating power, it is further distributed to the segmented preheating stage, allowing the fire-resistant oil to gradually heat up as it passes through different heating sections. The rapid preheating zone at the inlet handles most of the temperature rise, quickly raising the low-temperature inlet oil to near the target temperature. The fine constant-temperature zone at the outlet handles the remaining minor fine-tuning, compensating for residual deviations caused by sudden flow changes or inlet temperature fluctuations. Compared to a single heating zone with concentrated full-power heating, segmented preheating effectively avoids localized overheating caused by power concentration in a single section, reducing the risk of coking or deterioration of the fire-resistant oil due to localized high temperatures. Furthermore, the combination of rapid preheating at the front end and fine-tuning at the back end makes the heating process smooth and efficient, contributing to the stable maintenance of the preset target constant temperature. Through the synergy of feedforward and feedback, the temperature fluctuation range of the fire-resistant oil entering the metering system is controlled within ±0.5℃.

[0083] As a preferred example, the physical properties involved in the feedforward heating power calculation can be obtained by consulting the physical property handbook of fire-resistant oil or by experimental measurement and pre-stored in the controller 31. The proportional coefficient, integral coefficient, and derivative coefficient can be pre-determined using the Ziegler-Nichols critical proportionality method. Segmented preheating can be achieved by configuring independent heating sources in the rapid preheating zone at the inlet and the fine constant temperature zone at the outlet. Both heating sources are controlled separately by the controller 31 according to the heating power distribution command.

[0084] Among them, the Ziegler-Nichols critical proportional gain method is a commonly used method for determining PID parameters. The specific steps are as follows: First, determine the integral coefficients... and differential coefficients Set the control to zero, retaining only proportional control; gradually increase the proportional coefficient starting from a small value until the measured outlet temperature exhibits a continuous oscillation with constant amplitude. Record the critical proportional gain and critical oscillation period at this point. Calculate the proportional coefficient, integral coefficient, and derivative coefficient using the Ziegler-Nichols empirical formula based on the critical proportional gain and critical oscillation period. Write the calculated parameters as initial values ​​into the controller and fine-tune them during actual operation based on the control effect.

[0085] As a preferred example, the scaling factor It can be set to 0.6 times the critical proportional gain, and the integral coefficient is... It can be set to 1.2 times the critical proportional gain divided by the critical oscillation period, with the differential coefficient... This can be set to 0.075 times the critical proportional gain multiplied by the critical oscillation period. Those skilled in the art can fine-tune the above coefficients according to the actual system response characteristics.

[0086] Preferably, to prevent the measured outlet temperature from exceeding the set temperature due to extreme operating conditions, an over-temperature safety protection mechanism can be set based on the feedback of the measured outlet temperature. For example, under normal operating conditions, the temperature closed-loop control has stabilized the measured outlet temperature near the preset target constant temperature, and the measured outlet temperature will not exceed the set temperature. However, in extreme cases such as instantaneous flow interruption, failure of heating component 12, or abnormality of controller 31, the measured outlet temperature may temporarily deviate from the preset target constant temperature. At this time, the measured outlet temperature is compared with a preset first safety threshold. When the measured outlet temperature is greater than the first safety threshold, the total heating power is directly reduced to quickly reduce the heating power and prevent the temperature from rising further. At the same time, the measured outlet temperature is compared with a preset second safety threshold. The second safety threshold is higher than the first safety threshold. When the measured outlet temperature is greater than the second safety threshold, the power supply to the first and second heating components is forcibly cut off until the measured outlet temperature falls back to the safe range before heating is resumed. In this tiered safety protection mechanism, the power reduction or cutoff action triggered by the first safety threshold does not rely on the integral adjustment process of the PID controller, but directly acts on the power supply circuit of the heating component. Its response speed is much faster than PID feedback regulation, allowing intervention at the initial stage of temperature overshoot. The second safety threshold acts as the final protective barrier, completely cutting off the heating source in extreme fault conditions to prevent the fire-resistant oil from deteriorating or coking due to continuous overheating, thus ensuring the safety of the equipment and the oil. As a preferred example, the first safety threshold can be set to a preset target constant temperature plus a first offset, and the second safety threshold can be set to a preset target constant temperature plus a second offset, where the second offset is greater than the first offset.

[0087] This invention also discloses a flow meter applied to the aforementioned fire-resistant oil flow compensation method, such as... Figure 2 As shown, the flow meter includes a pre-heating constant temperature unit 1, a metering body 2, and a sensing control unit 3; The pre-heating constant temperature unit 1 includes a straight pipe section 11 and a heating component 12 disposed on the outer wall of the straight pipe section 11. The straight pipe section 11 is divided into an inlet section rapid preheating zone and an outlet section constant temperature zone along the axial direction. The heating component 12 includes a first heating element corresponding to the inlet section rapid preheating zone and a second heating element corresponding to the outlet section constant temperature zone. The first heating element and the second heating element are respectively provided with a heat homogenizing layer between them and the outer wall of the straight pipe section 11. The metering body 2 includes a housing 21, a volumetric metering rotor 22, and a pulse generator 23. A metering chamber is formed inside the housing 21, which is connected to the oil outlet of the straight pipe section 11. The volumetric metering rotor 22 is rotatably installed inside the metering chamber. The pulse generator 23 is fixed inside the metering chamber. The pulse generator 23 and the volumetric metering rotor 22 are non-contact magnetic coupling induction. The sensing and control unit 3 includes a controller 31, an inlet temperature sensor 32, an outlet temperature sensor 33, and a viscosity sensor 34. The controller 31 has an embedded calculation module for performing the fire-resistant oil flow compensation method. The controller 31 is electrically connected to the first heating element, the second heating element, the pulse generator 23, the inlet temperature sensor 32, the outlet temperature sensor 33, and the viscosity sensor 34. The inlet temperature sensor 32 is fixed in the oil inlet of the straight pipe section 11, and the outlet temperature sensor 33 and the viscosity sensor 34 are both fixed in the oil outlet of the straight pipe section 11.

[0088] By implementing the above-described flowmeter embodiment, the straight pipe section 11 is sequentially divided axially into an inlet rapid preheating zone and an outlet constant temperature zone, with corresponding first and second heating elements installed. This allows the fire-resistant oil to pass through two independently controlled heating zones as it flows through the straight pipe section 11. The inlet rapid preheating zone handles the main temperature rise of the fire-resistant oil from the measured inlet temperature to near the target constant temperature. The outlet constant temperature zone is responsible for finely correcting the temperature of the preheated fire-resistant oil, ensuring that its temperature gradually approaches the target constant temperature before leaving the straight pipe section 11 and entering the metering body 2. This segmented heating structure avoids local overheating and thermal stress concentration that may occur when a single heating element is heated at full power, resulting in a smooth and continuous temperature rise of the fire-resistant oil within the straight pipe section 11. Simultaneously, the heat homogenizing layer evenly transfers the heat generated by the heating element to the pipe wall and the internal oil, preventing localized high-temperature points on the pipe wall caused by poor contact between the heating element and the pipe wall or uneven heating power distribution, thus reducing the risk of coking or deterioration of the fire-resistant oil due to contact with locally overheated surfaces.

[0089] As a preferred example, the straight pipe section 11 is preferably a 316L stainless steel straight pipe section 11 with a length of 650mm. The first and second heating elements can be electric heating wires or heating tapes, and the heat spreader can be a thermally conductive silicone pad or an aluminum foil wrapping layer. Segmented heating: the inlet section rapid preheating zone is 250mm long and has a power of 200W; the outlet section constant temperature zone is 400mm long and has a power of 150W.

[0090] A metering chamber is formed within the housing 21 of the metering body 2. Heated fire-resistant oil flows directly into the metering chamber through the outlet of the straight pipe section 11, shortening the pipeline distance between the heating section outlet and the metering inlet, reducing heat loss during transmission, and ensuring that the temperature of the fire-resistant oil entering the metering chamber matches the measured outlet temperature at the outlet of the straight pipe section 11. A volumetric metering rotor 22 is rotatably mounted within the metering chamber. After the fire-resistant oil enters the metering chamber, it drives the volumetric metering rotor 22 to rotate. The pulse generator 23 detects the rotational motion of the volumetric metering rotor 22 through magnetic field induction and outputs a raw pulse signal corresponding to the displacement. This non-contact magnetic coupling induction method eliminates mechanical contact and friction between the pulse generator 23 and the volumetric metering rotor 22, avoiding wear and accuracy degradation caused by long-term mechanical contact and reducing the maintenance frequency of the metering body 2.

[0091] As a preferred example, the metering body 2 is preferably a 0.5-class elliptical gear flow meter, that is, the volumetric metering rotor 22 can be an elliptical gear rotor, the pulse generating device 23 can be a Hall sensor, the elliptical gear rotor has a permanent magnet embedded in it, and the Hall sensor outputs a pulse signal by detecting the alternating magnetic field generated by the permanent magnet when the elliptical gear rotor rotates.

[0092] The inlet temperature sensor 32 acquires the measured inlet temperature value in real time before the fire-resistant oil enters the straight pipe section 11, providing real-time temperature input for calculating the feedforward heating power. The outlet temperature sensor 33 acquires the measured outlet temperature value in real time before the fire-resistant oil leaves the heating section and enters the metering body 2, providing real-time temperature feedback for calculating the feedback heating power. The viscosity sensor 34 measures within a range of 1. ~500 With an accuracy of ±1%, it is fixed inside the oil outlet of the straight pipe section 11. It acquires the measured viscosity value in real time before the fire-resistant oil leaves the heating section and enters the metering body 2, so that the measured viscosity value and the measured outlet temperature value are consistent in spatial position. The synchronous acquisition of the two provides a position matching signal input for subsequent synchronous decomposition.

[0093] The controller 31 has an embedded calculation module for executing the fire-resistant oil flow compensation method, and temperature acquisition, viscosity acquisition, heating control, and flow pulse acquisition are all integrated into the same controller 31, enabling a complete closed loop from temperature sensing, heating control, viscosity acquisition to flow pulse reading. As a preferred example, the inlet temperature sensor 32 and the outlet temperature sensor 33 can be platinum resistance thermometers, the viscosity sensor 34 can be a vibration type or a capillary differential pressure type viscosity sensor, and the controller 31 can be an embedded microcontroller 31 based on an STM32F407.

[0094] Furthermore, the flow meter also includes a passive thermal compensation component, a thermal insulation layer 4, a flow switch 5, and a sealing component 6; A fitting clearance is formed between the outer peripheral surface of the volumetric metering rotor 22 and the inner wall of the metering chamber. A passive thermal compensation component is fixed on the inner wall of the metering chamber and located within the fitting clearance, and is used to expand to reduce the fitting clearance when the temperature rises. The heat insulation and protective layer 4 is wrapped around the front constant temperature heating unit 1 and the metering body 2. The flow switch 5 is set at the oil inlet of the metering body 2 and electrically connected to the controller 31 for linkage with the heating component 12. The two ends of the measuring body 2 are respectively formed with assembly interfaces that communicate with the measuring chamber, and the sealing element 6 is respectively fixed in the two assembly interfaces.

[0095] By implementing the above-described flowmeter embodiment, the passive thermal compensation component is preferably made of a material with a high coefficient of thermal expansion. This allows the dimensional changes that occur when the material with a high coefficient of thermal expansion changes with temperature, enabling the clearance between the outer circumference of the volumetric metering rotor 22 and the inner wall of the metering chamber to automatically shrink as the temperature increases. The temperature-clearance response has a functional relationship:

[0096] In the formula, Indicates temperature The following fit clearance, Indicates reference temperature The following fit clearance, Indicates the effective radial expansion coefficient of the passive thermal compensation component. Indicates the current temperature of the fire-resistant oil. Indicates the reference temperature.

[0097] When the temperature of fire-resistant oil unexpectedly rises, its viscosity decreases accordingly, increasing the leakage between the volumetric metering rotor 22 and the metering chamber. This increased leakage leads to a negative metering deviation. In this case, the passive thermal compensation component automatically expands and contracts the gap, causing the leakage to rapidly decrease according to the cubic relationship of the gap, thus partially or completely offsetting the negative metering deviation caused by the decrease in viscosity. Conversely, when the temperature unexpectedly drops, the increased viscosity leads to a decrease in leakage, causing a positive shift in the metering error. In this case, the passive thermal compensation structure contracts, increasing the mating gap, and the leakage increases according to the cubic ratio, partially offsetting the positive deviation.

[0098] This passive thermal compensation component automatically responds to temperature changes without external power supply, control signals, or algorithmic intervention. It operates on an open-loop physical compensation basis, with its response speed depending solely on the material's thermal conductivity, significantly faster than closed-loop temperature control. The passive thermal compensation structure is independent of and does not interfere with the active viscosity-temperature characteristic mode decomposition and dual-filter compensation algorithms. Even when the active algorithm experiences estimation errors due to extreme conditions, the passive thermal compensation structure can still independently provide physical compensation, further enhancing the flowmeter's robustness under abnormal temperature fluctuations from a hardware perspective.

[0099] As a preferred example, the passive thermal compensation component can be made of a thin layer of alloy with a high coefficient of thermal expansion (such as Mn-Cu alloy, with a linear expansion coefficient ≥25×). / K) or shape memory alloy ring. The thickness is 0.3mm, and the designed fit clearance is 0.15mm at 20℃, which decreases to 0.08mm at 60℃.

[0100] The thermal insulation layer 4 isolates the heating section and metering section from the external environment, which can reduce the interference of ambient temperature changes and airflow on the oil temperature in the straight pipe section 11. This makes it less likely for the oil temperature, which has already stabilized at the outlet of the heating section, to drop due to external heat dissipation before entering the metering body 2. This reduces the external heat load that the temperature closed-loop control unit needs to resist in order to maintain the target constant temperature. At the same time, it makes the ambient temperature of the passive thermal compensation component more stable, avoiding the frequent expansion or contraction of the passive thermal compensation component due to drastic fluctuations in external temperature, which would affect its compensation accuracy.

[0101] As a preferred example, the thermal insulation layer 4 can be a composite structure with an inner layer of 25mm high-temperature resistant rock wool insulation and an outer layer of aluminum foil cover. In low-temperature or outdoor conditions, an additional stainless steel explosion-proof protective shell can be installed.

[0102] The flow switch 5 is linked to the heating component 12. When there is flow in the fire-resistant oil pipeline, the flow switch 5 remains in normal condition and the heating component 12 operates normally. When there is no flow in the pipeline, the flow switch 5 is triggered and sends a signal to the controller 31. The controller 31 cuts off the power supply to the heating component 12, causing the first and second heating elements to stop heating. This prevents the heating component 12 from working continuously when there is no oil flow in the straight pipe section 11, which would cause the pipe wall temperature to rise continuously. This prevents the fire-resistant oil from aging or coking due to overheating of the empty pipe and eliminates the safety hazards caused by dry burning of the empty pipe.

[0103] As a preferred example, the flow switch 5 may be a mechanical target flow switch 5 or an electronic thermal flow switch 5.

[0104] The assembly interfaces at both ends of the metering body 2 are used to connect the oil outlet of the upstream straight pipe section 11 and the downstream pipeline, respectively. The seal 6 forms a sealing barrier at the two connection positions to prevent fire-resistant oil from leaking out from the assembly interface, while also preventing external air and moisture from entering the metering chamber from the interface. The fixed setting of the seal 6 within the assembly interface ensures that the sealing position does not shift during long-term operation, avoiding sealing failure caused by the displacement of the seal 6.

[0105] As a preferred example, seal 6 may be an O-ring or gasket made of fluororubber or polytetrafluoroethylene to suit the chemical properties of fire-resistant oil.

[0106] As mentioned above, all components that come into contact with fire-resistant oil (including seal 6 and sensors) are made of materials compatible with phosphate ester fire-resistant oil, such as 316L stainless steel, fluororubber, and polytetrafluoroethylene, to ensure long-term operation without corrosion or leakage.

[0107] In summary, regarding the fire-resistant oil flow compensation method and flow meter based on viscosity-temperature mode decomposition dual filtering provided by this invention, temperature closed-loop control is as follows: Figure 3 As shown, the working process is verified: When the inlet oil temperature is 5℃, the heating element 12 operates at full power, the outlet oil temperature is 39.8℃, and the measured viscosity is 28.5%. (Base viscosity 27 at 40℃) After modal decomposition, the fast-varying components are extremely small, while the slow-varying components are identified as 1.5. Offset, output compensation coefficient 0.998, final error -0.06%; When the inlet oil temperature is 35℃, the heating element 12 maintains low power for heat preservation, the outlet oil temperature is 40.2℃, and the measured viscosity is 26.2. The compensation coefficient is 1.003, and the final error is +0.06%. When the viscosity of the aged oil rises to 35 At 40°C, the slow-varying filter automatically updates the baseline viscosity to 35 after several cycles. The compensation coefficient adaptively changes to 1.011, and after 300 hours of continuous operation without human intervention, the maximum error is ≤ ±0.12%. When the traffic jumps from 5 The number of cases suddenly increased to 10 At that time, the fast-changing filter completes the compensation coefficient update within 2 seconds, with overshoot ≤0.08% and no oscillation; When different batches of fire-resistant oil are manually replaced (the reference viscosity becomes 30) If the error energy exceeds the threshold for 10 minutes, the system automatically triggers background recalibration, and resumes high-precision measurement after 2 seconds without interrupting the output. When the outlet temperature unexpectedly rises to 60℃ (simulating temperature control failure), the passive thermal compensation structure automatically reduces the tooth tip clearance from 0.15mm to 0.08mm, reducing leakage by approximately 40% and improving the metering error from -1.2% without compensation to -0.3%. When there is no flow in the pipeline, flow switch 5 is triggered, immediately cutting off the power supply to the heating tape to prevent the empty pipeline from overheating.

[0108] Further experimental testing was conducted using phosphate ester fire-resistant oil as the medium, with a flow rate of 10. Each temperature point was measured 10 times to determine the error range, as shown in Table 1. Table 1. Comparison of metering errors for different schemes at different inlet oil temperatures.

[0109] Table 1 shows that the unheated conventional flowmeter exhibits significant errors at different inlet oil temperatures. In the low-temperature zone (5℃), the error is negatively negative by -3.6%, while in the high-temperature zone (35℃), it is positively negative by +2.2%. The error increases sharply as the temperature deviates from the reference value (approximately 20℃), and the absolute error is far higher than the usable standard of ±0.5%. This indicates that relying solely on the flowmeter's original measurement cannot meet the accuracy requirements for fire-resistant oil over a wide temperature range. The pure isothermal (uncompensated) solution narrows the error to around ±0.5%, specifically -0.45% at 5℃ and +0.49% at 35℃. While still on the edge of usability, it is close to exceeding the standard, and the error still shows a significant drift trend with temperature. This indicates that a simple isothermal solution cannot completely eliminate the influence of viscosity changes on the instrument coefficient of the volumetric flowmeter.

[0110] The fire-resistant oil flow compensation method of this invention maintains an error within ±0.1% across the entire temperature range of 5℃ to 35℃, with a maximum absolute value of only 0.06%, and exhibits extremely narrow error fluctuations (±0.03%), representing a reduction of approximately one order of magnitude compared to the pure isothermal solution. This verifies that the fire-resistant oil flow compensation method based on viscosity-temperature mode decomposition and dual filtering can effectively eliminate the influence of residual viscosity fluctuations after isothermal treatment on metering, while the passive thermal compensation component further enhances stability at high temperatures.

[0111] This invention also discloses a fire-resistant oil flow compensation system applied to the above-mentioned fire-resistant oil flow compensation method, the system comprising: The viscosity-temperature data acquisition module is used to control the temperature of fire-resistant oil to stabilize within a preset target constant temperature fluctuation range, and to acquire the measured temperature and viscosity values ​​of the fire-resistant oil at the target constant temperature. The data decomposition module is used to perform synchronous viscosity-temperature characteristic mode decomposition on the measured viscosity value and the measured temperature value to obtain the fast viscosity component caused by residual temperature disturbance and the slow viscosity component caused by oil deterioration. The dual-scale observation module is used to construct an adaptive state observation model with dual time scales to filter and estimate the fast-varying viscosity component and the slow-varying viscosity component respectively, so as to obtain the filtered fast-varying viscosity estimate and the slow-varying viscosity estimate. The total viscosity calculation module is used to obtain the standard viscosity value of the fire-resistant oil at the target constant temperature, and calculate the current actual total viscosity of the fire-resistant oil based on the standard viscosity value, the fast-changing viscosity estimate, and the slow-changing viscosity estimate. The dynamic compensation module is used to obtain the basic compensation coefficient based on the actual total viscosity through a pre-experimentally calibrated piecewise linear reference function, and to obtain the dynamic compensation coefficient by superimposing the aging offset correction amount on the slowly varying viscosity estimate. The flow correction module is used to obtain the original flow measurement value of fire-resistant oil during the flow metering process, and correct the original flow measurement value according to the dynamic compensation coefficient to obtain the compensated actual flow value.

[0112] The present invention also discloses an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-described fire-resistant oil flow compensation method.

[0113] The present invention also discloses a storage medium on which a computer program is stored, which, when executed by a processor, implements the above-described fire-resistant oil flow compensation method.

[0114] 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.

[0115] 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.

[0116] 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.

[0117] 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 1One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0118] 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 flow compensation method based on viscosity-temperature mode decomposition dual filtering, characterized in that: The fire-resistant oil flow compensation method includes: The temperature of the fire-resistant oil is controlled to be stable within a preset target constant temperature range, and the measured temperature and viscosity values ​​of the fire-resistant oil are obtained when it is stable within the temperature fluctuation range. Synchronous viscosity-temperature characteristic mode decomposition was performed on the measured viscosity value and the measured temperature value to obtain the fast viscosity component caused by residual temperature disturbance and the slow viscosity component caused by oil deterioration. An adaptive state observation model with dual time scales is constructed to filter and estimate the fast-varying viscosity component and the slow-varying viscosity component respectively, so as to obtain the filtered fast-varying viscosity estimate and the slow-varying viscosity estimate. Obtain the standard viscosity value of the fire-resistant oil at the target constant temperature, and calculate the current actual total viscosity of the fire-resistant oil based on the standard viscosity value, the fast-changing viscosity estimate, and the slow-changing viscosity estimate. Based on the actual total viscosity, the basic compensation coefficient is obtained through a piecewise linear reference function calibrated in advance, and the dynamic compensation coefficient is obtained by superimposing the aging offset correction amount on the slowly varying viscosity estimate. The original flow measurement value of the fire-resistant oil during the flow metering process is obtained, and the original flow measurement value is corrected according to the dynamic compensation coefficient to obtain the compensated actual flow value.

2. The fire-resistant oil flow compensation method according to claim 1, characterized in that, The simultaneous viscosity-temperature characteristic mode decomposition of the measured viscosity value and the measured temperature value yields a fast viscosity component caused by residual temperature disturbance and a slow viscosity component caused by oil degradation, including: A first time series consisting of the measured viscosity values ​​at multiple times and a second time series consisting of the measured temperature values ​​at multiple times are obtained; Using the frequency distribution characteristics of the second time series as a frequency domain reference, the first time series is decomposed into multiple modal components based on adaptive variational mode decomposition; The center frequency of each modal component is obtained, and the modal components with a center frequency greater than a preset frequency threshold are classified as fast viscosity components, while the modal components with a center frequency less than or equal to the preset frequency threshold are classified as slow viscosity components.

3. The fire-resistant oil flow compensation method according to claim 1, characterized in that, The constructed dual-time-scale adaptive state observation model filters and estimates the rapidly varying viscosity component and the slowly varying viscosity component, respectively, to obtain filtered estimates of the rapidly varying viscosity and the slowly varying viscosity, including: Construct fast-scale state-space models and slow-scale state-space models; The instantaneous value of the rapidly varying viscosity component at the current moment is used as the observation input of the fast-scale state-space model. The estimated value of the rapidly varying viscosity at the current moment is output by performing prediction-update recursive calculation, and the residuals in the update process are recorded. Obtain the window average value of the slow-varying viscosity component at the current time, and use the window average value as the observation input of the slow-scale state-space model. Output the estimated value of the slow-varying viscosity at the current time by performing prediction-update recursive calculation. The model parameters of the slow-scale state-space model are corrected based on the residuals, and the baseline reference for state prediction of the fast-scale state-space model is updated based on the slow viscosity estimate. Based on the modified slow-scale state-space model and the updated fast-scale state-space model, the prediction-update recursive calculation is performed again, and the filtered fast-variable viscosity estimate and slow-variable viscosity estimate at the current time are output respectively.

4. The fire-resistant oil flow compensation method according to claim 3, characterized in that, The construction of the fast-scale state-space model and the slow-scale state-space model includes: Based on the dynamic characteristics of the rapidly varying viscosity components, a fast-scale state-space model is constructed, comprising a first state equation and a first observation equation. The functional expressions of the first state equation and the first observation equation are as follows: In the formula, Indicates the rapid viscosity component in the th... The state variable at time t, Indicates the rapid viscosity component in the th... The state variable at time t, This represents noise in fast-scale processes. Indicates the rapid viscosity component in the th... The observed value at time, Indicates the rapid viscosity component in the th... The instantaneous value at a given moment. This indicates fast-scale observation noise. Indicates a fast-scale time index; Based on the dynamic characteristics of the slowly varying viscosity component, a slow-scale state-space model is constructed, comprising a second state equation and a second observation equation. The functional expressions of the second state equation and the second observation equation are as follows: In the formula, Indicates the slow viscosity component in the th... The state variable at time t, Indicates the slow viscosity component in the th... The state variable at time t, This represents noise in slow-scale processes. Indicates the slow viscosity component in the th... The observed value at time, Indicates the slow viscosity component in the th... The average value of the window at time points. This indicates slow-scale observation noise. This indicates a slow-scale time index.

5. The fire-resistant oil flow compensation method according to claim 4, characterized in that, The fire-resistant oil flow compensation method further includes obtaining the window average value of the slowly varying viscosity component when constructing the slow-scale state-space model, including: Obtain a pre-calibrated standard viscosity-temperature curve function, and determine the standard viscosity value at the target isothermal temperature from the standard viscosity-temperature curve function; Based on the measured viscosity value and the standard viscosity value at the current moment, the viscosity difference at the current moment is calculated, and the viscosity difference at multiple moments is obtained to obtain a time series of the difference. The time series difference is averaged using a preset window length to obtain the window average of the slowly varying viscosity component. The function expression for the sliding window averaging is: In the formula, This represents the measured viscosity value. Indicates the standard viscosity value. This represents the measured temperature value. This means summing all values ​​within the current window and then averaging them. Indicates the time index.

6. The fire-resistant oil flow compensation method according to claim 1, characterized in that, The process of obtaining the basic compensation coefficient through a pre-calibrated piecewise linear benchmark function and then superimposing the aging offset correction amount based on the estimated slow viscosity includes: Query the pre-calibrated piecewise linear reference function, and obtain the basic compensation coefficient corresponding to the viscosity range of the actual total viscosity from the piecewise linear reference function; Based on the estimated slow viscosity and the preset aging sensitivity coefficient, the aging offset correction is calculated. The functional expression for calculating the aging offset correction is as follows: In the formula, This indicates the amount of aging offset correction. Indicates the aging sensitivity coefficient. This represents an estimate of the slowly changing viscosity. Based on the aging offset correction amount and the basic compensation coefficient, the dynamic compensation coefficient is calculated, and the functional expression for calculating the dynamic compensation coefficient is as follows: In the formula, Indicates the dynamic compensation coefficient. Indicates the basic compensation coefficient. This indicates the actual total viscosity.

7. The fire-resistant oil flow compensation method according to claim 6, characterized in that, The step of correcting the original flow measurement value according to the dynamic compensation coefficient to obtain the compensated actual flow value includes: The actual flow rate is calculated based on the dynamic compensation coefficient and the original flow rate measurement. The functional expression for calculating the actual flow rate is as follows: In the formula, This represents the actual flow rate. This represents the original flow measurement value. Indicates the time index.

8. The fire-resistant oil flow compensation method according to claim 1, characterized in that, The control of the temperature of fire-resistant oil to stabilize within a preset target constant temperature range includes: Obtain the physical properties of the fire-resistant oil, as well as the measured inlet temperature and instantaneous volumetric flow rate of the fire-resistant oil before preheating; Based on the difference between the measured inlet temperature and the preset target constant temperature, and combined with the physical property parameters, the feedforward heating power of the fire-resistant oil is calculated. The functional expression for calculating the feedforward heating power is as follows: In the formula, This represents the feedforward heating power of the fire-resistant oil at time t. This indicates the specific heat capacity of fire-resistant oil. Indicates the density of fire-resistant oil. This represents the instantaneous volumetric flow rate of fire-resistant oil at time t. This indicates the preset target constant temperature. This represents the measured inlet temperature of the fire-resistant oil at time t. Obtain the measured outlet temperature of the fire-resistant oil after preheating and before flow compensation, and calculate the feedback heating power based on the difference between the measured outlet temperature and the preset target constant temperature. The functional expression for calculating the feedback heating power is as follows: In the formula, This represents the feedback heating power of the fire-resistant oil at time t. This represents the preset scaling factor. This represents the difference between the fire-resistant oil at time t and the target isothermal temperature. This represents the preset integral coefficient. This represents the preset differential coefficient. Indicates the difference versus time The points, Indicates the difference versus time The derivative, This represents the measured outlet temperature of the fire-resistant oil at time t. The feedforward heating power and the feedback heating power are superimposed to obtain the total heating power, and a heating power allocation command is generated. The fire-resistant oil is preheated in stages according to the heating power allocation command until the temperature stabilizes within the temperature fluctuation range of the target constant temperature.

9. A flow meter, applied to the fire-resistant oil flow compensation method according to any one of claims 1-8, characterized in that: The flow meter includes a pre-heating constant temperature unit, a metering body, and a sensing control unit; The pre-heating constant temperature unit includes a straight pipe section and a heating assembly disposed on the outer wall of the straight pipe section. The straight pipe section is divided into an inlet section rapid preheating zone and an outlet section constant temperature zone along the axial direction. The heating assembly includes a first heating element corresponding to the inlet section rapid preheating zone and a second heating element corresponding to the outlet section constant temperature zone. A heat homogenizing layer is provided between the first heating element and the second heating element and the outer wall of the straight pipe section, respectively. The metering body includes a housing, a volumetric metering rotor, and a pulse generating device. A metering chamber communicating with the oil outlet of the straight pipe section is formed inside the housing. The volumetric metering rotor is rotatably disposed in the metering chamber. The pulse generating device is fixedly disposed in the metering chamber. The pulse generating device and the volumetric metering rotor are non-contact magnetic coupling induction. The sensing and control unit includes a controller, an inlet temperature sensor, an outlet temperature sensor, and a viscosity sensor. The controller has an embedded calculation module for executing the fire-resistant oil flow compensation method. The controller is electrically connected to the first heating element, the second heating element, the pulse generator, the inlet temperature sensor, the outlet temperature sensor, and the viscosity sensor. The inlet temperature sensor is fixed in the oil inlet of the straight pipe section, and the outlet temperature sensor and the viscosity sensor are both fixed in the oil outlet of the straight pipe section.

10. The flow meter according to claim 9, characterized in that: The flow meter also includes a passive thermal compensation component, a thermal insulation layer, a flow switch, and a sealing component; A fitting clearance is formed between the outer peripheral surface of the volumetric metering rotor and the inner wall of the metering chamber. The passive thermal compensation component is fixed on the inner wall of the metering chamber and located within the fitting clearance, and is used to expand to reduce the fitting clearance when the temperature rises. The thermal insulation layer is wrapped around the front constant temperature heating unit and the metering body. The flow switch is located at the oil inlet of the metering body and is electrically connected to the controller for linkage with the heating component. The two ends of the metering body are respectively formed with assembly interfaces that communicate with the metering chamber, and the sealing element is respectively fixed in the two assembly interfaces.

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