A method for calculating alcohol concentration based on secondary compensation

Abstract

The application discloses a method for calculating alcohol concentration based on secondary compensation, and relates to the technical field of alcohol concentration detection. The application innovatively introduces fluid viscous damping characteristics as a third measurement dimension, uses the driving gain parameter of the Coriolis force mass flowmeter to inversely calculate the actual viscosity of the fluid in real time, and breaks the single measurement limitation of the traditional density and temperature. Meanwhile, the physical characteristics of the solid in the brewed wine are extremely sensitive to the viscosity, the dry extract content in the wine is accurately inversely estimated based on the viscosity deviation, the density virtual high value caused by the solid is further quantitatively calculated, and the measured density is subtractively corrected. Through the secondary compensation mechanism, the interference of the solid is effectively removed, and the real density of the pure base liquor is restored.

Description

Technical Field

[0001] This invention belongs to the field of alcohol concentration detection technology, and specifically relates to a method for calculating alcohol concentration based on secondary compensation. Background Technology

[0002] Coriolis mass flow meters, due to their ability to simultaneously and directly measure fluid mass flow rate, density, and temperature, along with their absence of moving parts and high measurement accuracy, have been widely used in the online monitoring of wineries. Based on the traditional measurement principle of Coriolis mass flow meters, the liquid being measured is typically considered an ideal binary mixture of ethanol and water. Since ethanol and water have definite density differences at different temperatures, the measurement system only needs to collect the current density and temperature of the liquid in real time, and then, by referring to an internationally recognized alcohol density-concentration conversion table, can reverse-calculate the current volumetric or mass concentration. However, actual brewed wines are not ideal binary mixtures, but rather complex multi-component systems containing non-alcoholic dry extracts such as sugars, phenols, and amino acids. Existing general detection models ignore the physical influence of these solid components. Furthermore, the presence of these dissolved solids significantly increases the physical density of the fluid, resulting in measured density values ​​that are consistently higher than the theoretical density of pure base wine at the same alcohol content. Because the original algorithm of the Coriolis mass flow meter cannot distinguish whether the increase in density is caused by a decrease in alcohol concentration or an increase in solid content, the instrument often mistakenly interprets the density increase caused by solids as an increase in water content, resulting in the final output alcohol concentration reading being generally lower than the true value. Summary of the Invention

[0003] To address the shortcomings of existing technologies, this invention provides a method for calculating alcohol concentration based on secondary compensation, thereby solving the aforementioned technical problems.

[0004] A method for calculating alcohol concentration based on quadratic compensation includes the following steps:

[0005] S1: Real-time acquisition of the current temperature, current density measurement, and driving gain parameters reflecting the viscosity and damping characteristics of the liquid being measured as it flows through the Coriolis mass flow meter.

[0006] S2: Calculate the current actual viscosity value of the tested wine based on the driving gain parameters;

[0007] S3: Based on the preset standard model of the mixing system, calculate the theoretical reference viscosity value when assuming the tested wine is a pure binary mixture, according to the current temperature value and the current density measurement value;

[0008] S4: Obtain the difference between the current actual viscosity value and the theoretical reference viscosity value, as the viscosity deviation;

[0009] S5: Using a preset masking correlation model, calculate the density increment correction value caused by non-alcoholic solids based on the viscosity deviation.

[0010] S6: Based on the density increment correction value, the current density measurement value is compensated and corrected to obtain the pure base wine density;

[0011] S7: Calculate the true alcohol concentration of the tested liquor based on the current temperature value and the density of the pure base liquor.

[0012] Preferably, the method for constructing the standard model of the hybrid system in step S3 is as follows:

[0013] In a laboratory setting, pure ethanol aqueous solutions with different concentration gradients were prepared, and their standard density and standard viscosity values ​​were measured at different temperature points. A fitting function was established with temperature and density as independent variables and viscosity as dependent variable.

[0014] By substituting the real-time measured current temperature and density values ​​into the fitting function, the theoretical reference viscosity value that should exist under the current measurement conditions can be derived.

[0015] Preferably, the formula for calculating the current actual viscosity value based on the driving gain parameter in step S2 is as follows:

[0016] ;

[0017] in, For the intercept term, The coefficient of the linear term, The coefficient of the quadratic term, The density term coefficients, the driving gain parameters The driving current or driving voltage value required to maintain constant amplitude vibration of the measuring tube, This is the current density measurement value. This is the current actual viscosity value.

[0018] Preferably, the formula for the masking correlation model in step S5 is as follows:

[0019]

[0020]

[0021] in, It is the viscosity sensitivity coefficient. These are density influence coefficients; both coefficients are constants obtained by calibration for specific types of wine. This is the density increment correction value;

[0022] This is a theoretical reference viscosity value. This is the viscosity deviation. This refers to the content of dry extract.

[0023] Preferably, the steps for obtaining the viscosity sensitivity coefficient and density influence coefficient are as follows:

[0024] Select at least one type of wine sample and determine its dry extract content and true alcohol concentration in the laboratory.

[0025] The original measured density and original measured viscosity of the wine sample were determined using a Coriolis mass flow meter at a standard reference temperature.

[0026] The viscosity sensitivity coefficient is calculated by using the deviation between the original measured viscosity and the theoretical reference viscosity value as the independent variable and the dry extract content as the dependent variable through data fitting.

[0027] The density influence coefficient is obtained by using the dry extract content as the independent variable and the difference between the original measured density and the theoretical density corresponding to the actual alcohol content as the dependent variable, and by data fitting calculation.

[0028] Preferably, the compensation and correction step in step S6 is as follows:

[0029] When the calculated density increment correction value exceeds the preset dead zone threshold, the density of the pure base wine is calculated based on the following formula:

[0030]

[0031] in, For the density of pure base wine, This is the density increment correction value. This is the current density measurement value;

[0032] If the calculated density increment correction value does not exceed the preset dead zone threshold, no correction is made, and the density of the pure base wine is directly set to equal the current density measurement value.

[0033] Preferably, the current temperature value collected in step S1 is preprocessed using the following thermal hysteresis compensation formula:

[0034]

[0035] in, For sensor readings, The time constant of the instrument. This represents the actual temperature of the fluid. This represents the rate of temperature change.

[0036] Preferably, step S7 specifically includes the following steps:

[0037] Convert the density of pure base liquor to the standard density at the standard reference temperature;

[0038] Refer to the corresponding alcohol concentration table based on the OIMLR22 international recommendations.

[0039] Preferably, the method further includes an adaptive filtering step on the output of step S7:

[0040] Monitor the volatility of the output results in real time;

[0041] When the volatility exceeds the set threshold, the filter time constant is reduced to improve the response speed.

[0042] When volatility is less than a set threshold, the filter time constant is increased to improve stability.

[0043] Preferably, the following steps are also included:

[0044] When the calculated viscosity deviation or dry extract content exceeds the preset alarm threshold, the instrument outputs an abnormal alarm signal.

[0045] The beneficial effects of this invention are as follows: It innovatively introduces fluid viscosity damping characteristics as a third measurement dimension, utilizing the driving gain parameter of the Coriolis mass flow meter to invert the actual viscosity of the fluid in real time, breaking the limitations of traditional single-measurement methods that rely solely on density and temperature. Simultaneously, leveraging the physical characteristic that solids in brewed wine are extremely sensitive to viscosity, it accurately estimates the dry extract content in the wine based on viscosity deviation, further quantitatively calculating the inflated density value caused by solids, and subtracting to correct the measured density. Through this secondary compensation mechanism, the interference of solids is effectively eliminated, restoring the true density of the pure base wine. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 The present invention provides a flowchart of a method for calculating alcohol concentration based on secondary compensation. Detailed Implementation

[0048] The following disclosure provides many different embodiments or examples for implementing different structures of the present invention. To simplify the disclosure of the present invention, the components and arrangements of specific examples are described below. Of course, these are merely examples and are not intended to limit the present invention.

[0049] The embodiments of the invention will now be described in detail with reference to the accompanying drawings.

[0050] like Figure 1 As shown, a method for calculating alcohol concentration based on secondary compensation includes the following steps:

[0051] S1: Real-time acquisition of the current temperature, current density measurement, and driving gain parameters reflecting the viscosity and damping characteristics of the liquid being measured as it flows through the Coriolis mass flow meter.

[0052] S2: Calculate the current actual viscosity value of the tested wine based on the driving gain parameters;

[0053] S3: Based on the preset standard model of the mixing system, calculate the theoretical reference viscosity value when assuming the tested wine is a pure binary mixture, according to the current temperature value and the current density measurement value;

[0054] S4: Obtain the difference between the current actual viscosity value and the theoretical reference viscosity value, as the viscosity deviation;

[0055] S5: Using a preset masking correlation model, calculate the density increment correction value caused by non-alcoholic solids based on the viscosity deviation.

[0056] S6: Based on the density increment correction value, the current density measurement value is compensated and corrected to obtain the pure base wine density;

[0057] S7: Calculate the true alcohol concentration of the tested liquor based on the current temperature value and the density of the pure base liquor.

[0058] In specific implementation, steps S1 to S2 first utilize the instrument characteristic polynomial coefficients calibrated at the factory to map the dimensionless drive gain signal into a physically meaningful current actual viscosity value in real time. In one embodiment, for the low-viscosity fluid in the aged whisky production line, based on the viscosity sensitivity coefficient and density influence coefficient obtained by least squares calibration, when the liquid containing oak barrel extract flows through the instrument, step S3 calls the stored standard model of the mixing system to calculate the theoretical reference viscosity that the liquid should possess if it were a pure liquid of the same temperature and density. Since the macromolecular characteristics of dry extract contribute much more to viscosity than to density, the viscosity deviation detected in step S4 will show a significantly positive value. Steps S5 to S6 use this deviation to back-calculate the dry extract content using a linear regression model, then calculate the density increment correction value, subtract this value from the measured density to restore the pure base liquor density, and finally, in step S7, output the corrected true alcohol concentration in conjunction with the OIML R22 standard table. The final calculation process is as follows: The fluid temperature is 20℃, and the current density measured by the Coriolis mass flow meter is 0.9480 g / cm³, corresponding to an apparent alcohol content of approximately 40% vol. Simultaneously, the actual viscosity value obtained after converting the acquired driving gain parameters is 2.5 mPa·s. The system calls the preset standard model for the mixing system and calculates that under the conditions of 20℃ and 0.9480 g / cm³, the theoretical reference viscosity value for a pure ethanol-water solution should be 1.8 mPa·s. At this point, step S4 calculates a significant viscosity deviation of 0.7 mPa·s. Based on the masking correlation model, this deviation indicates that the fluid contains a large amount of high-viscosity solids, such as polyphenols and sugars from oak barrel aging. Based on this, the system calculates a density increment correction value of 0.0020 g / cm³. In step S6, the measured density is corrected to 0.9460 g / cm³, and the actual alcohol concentration is calculated using this corrected density. The results show that the actual alcohol content should be 41.2% vol instead of 40% vol, effectively eliminating the error of low reading caused by solids.

[0059] In another implementation, for high-sugar blended wines or wines fermenting midway through fermentation, these fluids are non-Newtonian or high-viscosity fluids, with viscosity sensitivity coefficients significantly higher than those of distilled spirits. In this scenario, the system automatically switches to the correction model parameters in the high-viscosity range by identifying the magnitude of the viscosity deviation. This prevents over- or under-correction of density due to excessive solids content, ensuring that the physical properties of ethanol are locked in even under a wide range of solids interference. Compared to existing technologies that rely solely on density measurement, the advantage of this solution lies in creatively introducing viscosity as a third-dimensional fingerprint for identifying fluid components. By utilizing the high sensitivity of solids to viscosity, the aliasing signals of ethanol concentration and solids content in density measurement are decoupled. This not only eliminates the systematic error of lower alcohol content measurements caused by the solids masking effect in traditional methods, achieving accurate online measurement without laboratory distillation sampling, but also significantly reduces manual verification costs and production delays. The final calculation process is as follows: At the same temperature of 20℃, the measured density is still 0.9480 g / cm³, but the acquired driving gain parameter is low, resulting in a calculated actual viscosity value of only 1.82 mPa·s. Compared to the theoretical reference viscosity of 1.8 mPa·s, the viscosity deviation is only 0.02 mPa·s, which is within the preset error dead zone. The system determines that the fluid is approximately a pure binary mixture, and the density increment correction value approaches zero. Therefore, no density correction is performed, and the alcohol concentration is directly output based on the original density. This adaptive mechanism ensures that the algorithm does not overcompensate when processing pure liquids, guaranteeing universality across the entire range.

[0060] The acquisition and processing of the drive gain parameter is the physical basis of this scheme. In this embodiment, the drive gain parameter is explicitly defined as the magnitude of the excitation current output by the Coriolis mass flow meter transmitter to maintain the constant amplitude vibration of the measuring tube at its natural frequency. The physical principle is as follows: the viscosity of the fluid inside the measuring tube directly determines the damping characteristics of the mechanical vibration; high-viscosity fluids generate greater internal friction during vibration, leading to faster energy dissipation; to counteract this damping and maintain the vibration amplitude of the measuring tube without attenuation, the transmitter's closed-loop control circuit must output greater drive energy. Therefore, there is a monotonically increasing physical mapping relationship between the drive gain parameter and the actual viscosity of the fluid. This allows the current actual viscosity value of the measured liquid to be obtained by simply calculating the drive signal inside the instrument without adding additional viscometer hardware.

[0061] More specifically, the method for constructing the standard model of the hybrid system in step S3 is as follows:

[0062] In a laboratory setting, pure ethanol aqueous solutions with different concentration gradients were prepared, and their standard density and standard viscosity values ​​were measured at different temperature points. A fitting function was established with temperature and density as independent variables and viscosity as dependent variable.

[0063] By substituting the real-time measured current temperature and density values ​​into the fitting function, the theoretical reference viscosity value that should exist under the current measurement conditions can be derived.

[0064] In practice, technicians must prepare gradient pure ethanol-water solutions covering the entire range under the stringent constant temperature environment of a laboratory. They then systematically measure standard density and viscosity data at different temperature points, constructing a standard fingerprint library containing three-dimensional data of temperature, density, and viscosity. A multivariate nonlinear regression algorithm is then used to generate a mapping function with high fitting accuracy, which is then embedded into the instrument's processor. When the instrument is running online, the real-time collected temperature and the current measured density (including solid interference) are substituted into this function. The resulting theoretical reference viscosity represents the ideal rheological state assuming the liquid is completely free of solids. This design is based on the thermodynamic determinism of pure binary mixtures, meaning that at a specific temperature and concentration, the viscosity of a pure ethanol-water solution is the only definite physical quantity. Any measured viscosity fluctuations deviating from this theoretical value can be attributed to the presence of non-alcoholic substances. Compared to existing technologies that rely solely on static density tables and cannot detect changes in fluid rheological properties, this solution constructs a dynamic viscosity benchmark, providing an indispensable differential zero point for subsequent calculation of solid content. This effectively avoids interference from natural viscosity drift caused by fluctuations in ambient temperature or changes in base alcohol content on the compensation algorithm, ensuring the specificity and signal-to-noise ratio of solid identification.

[0065] More specifically, the formula for calculating the current actual viscosity value based on the driving gain parameter in step S2 is as follows:

[0066]

[0067] in, For the intercept term, The coefficient of the linear term, The coefficient of the quadratic term, The density term coefficients, the driving gain parameters The driving current or driving voltage value required to maintain constant amplitude vibration of the measuring tube, This is the current density measurement value. This is the current actual viscosity value.

[0068] The coefficients described in this invention , , , These are instrument constants that describe the mapping relationship between the vibration damping characteristics of the measuring tube of a Coriolis mass flow meter and the fluid viscosity. To ensure measurement accuracy, these coefficients need to be obtained through standard fluid calibration experiments before the instrument leaves the factory or during maintenance.

[0069] The specific calibration and calculation steps are as follows:

[0070] Several standard viscosity fluids covering the instrument's measurement range were selected. These fluids included air, pure water, aqueous solutions of glycerol at different concentrations, or standard silicone oil. The standard fluids were sequentially flowed through or filled the Coriolis mass flow meter, controlled at different temperature points. For each measurement point, the standard viscosity value, drive gain parameter, and current density measurement value were recorded simultaneously. The standard viscosity value was measured using a high-precision laboratory viscometer or obtained from a table; the drive gain value was obtained by acquiring the drive current or percentage output by the instrument to maintain the vibration of the measuring tube; and the measured density value was obtained by acquiring the fluid density measured by the instrument in real time.

[0071] Substitute the collected data points into the formula for calculating the current actual viscosity value, and construct and solve a system of equations using a multiple linear regression algorithm or the least squares method. Retain the set of equations that minimizes the sum of squared residuals between the calculated viscosity and the standard viscosity for all test points. , , , As an instrument coefficient.

[0072] More specifically, the formula for the masking correlation model in step S5 is shown below:

[0073]

[0074] in, It is the viscosity sensitivity coefficient. These are density influence coefficients; both coefficients are constants obtained by calibration for specific types of wine. This is the density increment correction value;

[0075] This is a theoretical reference viscosity value. This is the viscosity deviation. This refers to the content of dry extract.

[0076] More specifically, the steps for obtaining the viscosity sensitivity coefficient and density influence coefficient are as follows:

[0077] Select at least one type of wine sample and determine its dry extract content and true alcohol concentration in the laboratory.

[0078] The original measured density and original measured viscosity of the wine sample were determined using a Coriolis mass flow meter at a standard reference temperature.

[0079] The viscosity sensitivity coefficient is calculated by using the deviation between the original measured viscosity and the theoretical reference viscosity value as the independent variable and the dry extract content as the dependent variable through data fitting.

[0080] The density influence coefficient is obtained by using the dry extract content as the independent variable and the difference between the original measured density and the theoretical density corresponding to the actual alcohol content as the dependent variable, and by data fitting calculation.

[0081] The data fitting calculation in the above steps specifically refers to the process of solving the coefficients of the linear equation using the least squares method or the arithmetic mean method. Specifically, since this invention presupposes a linear relationship between solid content and viscosity deviation, multiple sets of similar wine samples with different solid contents are prepared during calibration. The viscosity deviation and true solid content of each set of samples are measured, and these data points are substituted into the linear regression model to calculate the slope of the straight line. This slope is the required viscosity sensitivity coefficient. Similarly, the density influence coefficient is also obtained by establishing a linear regression model between solid content and density increment and calculating its slope.

[0082] More specifically, the compensation and correction steps in step S6 are as follows:

[0083] When the calculated density increment correction value exceeds the preset dead zone threshold, the density of the pure base wine is calculated based on the following formula:

[0084]

[0085] in, For the density of pure base wine, This is the density increment correction value. This is the current density measurement value;

[0086] If the calculated density increment correction value does not exceed the preset dead zone threshold, no correction is made, and the density of the pure base wine is directly set to equal the current density measurement value.

[0087] Highly robust signal processing is achieved by introducing conditional discrimination logic in the density correction stage: the processor monitors the absolute amplitude of the density increment correction value calculated in the preceding steps in real time and compares it with a dead-zone threshold preset in non-volatile memory. This threshold is typically set based on the noise variance statistics of the instrument under standard pure solvent conditions. When the calculated correction value exceeds this threshold, the system determines that there is indeed a significant solids content in the fluid, and then activates the compensation algorithm to perform a subtraction operation, thereby eliminating the density deviation caused by solids. Conversely, if the correction value falls within the dead-zone threshold, the system determines that the current non-zero calculated value is measurement noise or calculation truncation error, does not perform a correction operation, and directly transmits the original measured value as the pure base liquor density output. When performing pure water cleaning on the production line or measuring low-viscosity fluids in the aged whisky production line, the algorithm calculates a tiny correction value of 0.0002 g / cm³ due to the influence of weak fluid turbulence. Since this value is less than the dead-zone threshold, the system determines it as invalid noise and masks it, directly outputting the original density value, avoiding the indication jump caused by over-correction. When measuring high-sugar blended wines or wines in the middle of fermentation, the viscosity increases significantly. The density increment correction value calculated by the algorithm is 0.0042 g / cm³, which is much greater than the preset threshold of 0.0005 g / cm³. The logic threshold is broken, and the system performs a correction operation, which effectively removes the interference of sugar and ensures the measurement accuracy under high solid content conditions.

[0088] The dead-zone threshold, in a physical sense, defines an effective signal discrimination boundary to distinguish between real solid interference and random measurement noise in the instrument system. Due to the inherent background noise in Coriolis flowmeters when measuring density and drive gain, and the small floating-point truncation error generated during numerical calculations, even when measuring pure fluids, the theoretically calculated density increment correction value is rarely strictly zero, but rather exhibits a small value fluctuating around zero. The design principle of the dead-zone threshold is to forcibly ignore small calculation deviations below the threshold, preventing the algorithm from introducing artificial false corrections when measuring pure water, pure alcohol, or wines with extremely low solids content, thereby ensuring the zero-point stability of the system and the smoothness of the measurement data under ideal operating conditions. Compared to the all-through unconditional correction technique, this dual-mode switching strategy based on the dead-zone threshold eliminates algorithm jitter in the low signal-to-noise ratio range, retaining the compensation capability for high-concentration solids while preventing the introduction of additional calculation errors when processing pure fluids, significantly improving the dynamic adaptability and data reliability of the instrument when switching between different process stages.

[0089] More specifically, the current temperature value collected in step S1 is preprocessed using the following thermal hysteresis compensation formula:

[0090]

[0091] in, For sensor readings, The time constant of the instrument. This represents the actual temperature of the fluid. This represents the rate of temperature change.

[0092] More specifically, step S7 includes the following steps:

[0093] Convert the density of pure base liquor to the standard density at the standard reference temperature;

[0094] Refer to the corresponding alcohol concentration table based on the OIMLR22 international recommendations.

[0095] In practice, the density value of the pure base liquor after the solids compensation correction in the previous steps and the current fluid temperature value are used. The density value at the current non-standard temperature is equivalently converted to the standard density value at the standard reference temperature using a preset ethanol-water volume thermal expansion coefficient algorithm, which is usually 20 degrees Celsius, to eliminate the physical influence of temperature fluctuations on the expansion and contraction of liquid volume. Then, using this standard density as an index, the OIML R22 international recommended alcohol concentration reference table is searched in the storage unit. For intermediate values ​​not listed in the table, the accurate volume alcohol content is calculated using bilinear interpolation.

[0096] More specifically, it also includes the step of adaptively filtering the output of step S7:

[0097] Monitor the volatility of the output results in real time;

[0098] When the volatility exceeds the set threshold, the filter time constant is reduced to improve the response speed.

[0099] When volatility is less than a set threshold, the filter time constant is increased to improve stability.

[0100] In practical implementation, a sliding window algorithm is used to calculate in real time the sum of the statistical variance or the absolute value of the first-order difference of several consecutive alcohol concentration output values, thereby quantifying the volatility of the current measurement data. The core parameters of the first-order low-pass filter are dynamically adjusted based on this volatility. When a sharp increase in volatility is detected and exceeds the set threshold, such as during the switching between the head and tail of the liquor or the instant of valve opening and closing, it is determined to be a sudden change in the actual operating condition. The time constant is immediately shortened automatically, and the filter damping is weakened, so that the output curve can quickly track the actual concentration step. Conversely, when the volatility falls back to the low threshold range, such as during steady-state filling or static measurement in the storage tank, it is determined to be random noise interference. The time constant is automatically increased to enhance the smoothing and suppression capabilities and filter out the minor jitter caused by fluid turbulence and electromagnetic interference.

[0101] The core principle of this design lies in resolving the inherent trade-off between sensitivity and stability in traditional fixed-parameter filtering processes. It utilizes high-frequency fluctuation characteristics to identify changes in operating conditions, achieving a separation of dynamic and static control. Implementation results show that this technology reduces the instrument's stabilization time by more than 60% during wine-changing operations, while lowering the reading fluctuation amplitude by an order of magnitude during constant-current measurements, thus balancing process control agility with reading stability during trade handover.

[0102] More specifically, it also includes the following steps:

[0103] When the calculated viscosity deviation or dry extract content exceeds the preset alarm threshold, the instrument outputs an abnormal alarm signal.

[0104] While performing routine metering tasks, the system runs in parallel with process diagnostic logic, comparing the calculated viscosity deviation or dry extract content with preset process safety thresholds in real time. Once the monitored data exceeds the threshold boundary—for example, a significant dry extract reading is detected in a pure vodka production line, or the viscosity deviation shows an atypical positive abrupt change—an abnormal status flag is immediately set, and an interlock shutdown command is sent to the central control system via the fieldbus, forcibly shutting off the feed valve. The principle behind this design is to utilize the extremely high physical sensitivity of fluid viscosity to changes in composition, using it as a quality fingerprint independent of density for verification. Abnormal viscosity deviations often indicate not only potential failure in alcohol content measurement but also directly point to serious process accidents such as raw material contamination, mismixing of different types of alcohol, or incomplete pipeline cleaning. Compared to traditional instruments that passively output values ​​without being able to identify their reasonableness, this solution successfully intercepted batch quality accidents caused by residual syrup in pipelines mixing with base spirits, moving post-incident inspection to process interception and significantly reducing production risks.

[0105] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.

Claims

1. A method for calculating alcohol concentration based on quadratic compensation, characterized in that, Includes the following steps: S1: Real-time acquisition of the current temperature, current density measurement, and driving gain parameters reflecting the viscosity and damping characteristics of the liquid being measured as it flows through the Coriolis mass flow meter. S2: Calculate the current actual viscosity value of the tested wine based on the driving gain parameter; the specific formula for calculating the current actual viscosity value based on the driving gain parameter is as follows: ； in, For the intercept term, The coefficient of the linear term, The coefficient of the quadratic term, The density term coefficients, the driving gain parameters The driving current or driving voltage value required to maintain constant amplitude vibration of the measuring tube, This is the current density measurement value. This is the current actual viscosity value; S3: Based on the preset standard model of the mixing system, calculate the theoretical reference viscosity value when assuming the tested wine is a pure binary mixture, according to the current temperature value and the current density measurement value; S4: Obtain the difference between the current actual viscosity value and the theoretical reference viscosity value, as the viscosity deviation; S5: Using a preset masking correlation model, calculate the density increment correction value caused by non-alcoholic solids based on the viscosity deviation; the formula for the masking correlation model is as follows: ， ； in, It is the viscosity sensitivity coefficient. These are density influence coefficients; both coefficients are constants obtained by calibration for specific types of wine. This is the density increment correction value; This is the theoretical reference viscosity value. This is the viscosity deviation. This refers to the content of dry extract; S6: Based on the density increment correction value, the current density measurement value is compensated and corrected to obtain the pure base wine density; S7: Calculate the true alcohol concentration of the tested liquor based on the current temperature value and the density of the pure base liquor.

2. The method for calculating alcohol concentration based on secondary compensation according to claim 1, characterized in that, The method for constructing the standard model of the hybrid system in step S3 is as follows: In a laboratory setting, pure ethanol aqueous solutions with different concentration gradients were prepared, and their standard density and standard viscosity values ​​were measured at different temperature points. A fitting function was established with temperature and density as independent variables and viscosity as dependent variable. By substituting the real-time measured current temperature and density values ​​into the fitting function, the theoretical reference viscosity value that should exist under the current measurement conditions can be derived.

3. The method for calculating alcohol concentration based on secondary compensation according to claim 1, characterized in that, The specific steps for obtaining the viscosity sensitivity coefficient and density influence coefficient are as follows: Select at least one type of wine sample and determine its dry extract content and true alcohol concentration in the laboratory. The original measured density and original measured viscosity of the wine sample were determined using a Coriolis mass flow meter at a standard reference temperature. The viscosity sensitivity coefficient is calculated by using the deviation between the original measured viscosity and the theoretical reference viscosity value as the independent variable and the dry extract content as the dependent variable through data fitting. The density influence coefficient is obtained by using the dry extract content as the independent variable and the difference between the original measured density and the theoretical density corresponding to the actual alcohol content as the dependent variable, and by data fitting calculation.

4. The method for calculating alcohol concentration based on secondary compensation according to claim 1, characterized in that, The compensation and correction steps in step S6 are as follows: When the calculated density increment correction value exceeds the preset dead zone threshold, the density of the pure base wine is calculated based on the following formula: ； in, For the density of pure base wine, This is the density increment correction value. This is the current density measurement value; If the calculated density increment correction value does not exceed the preset dead zone threshold, no correction is made, and the density of the pure base wine is directly set to equal the current density measurement value.

5. The method for calculating alcohol concentration based on secondary compensation according to claim 1, characterized in that, The current temperature value collected in step S1 is preprocessed using the following thermal hysteresis compensation formula: ； in, For sensor readings, The time constant of the instrument. This represents the actual temperature of the fluid. This represents the rate of temperature change.

6. The method for calculating alcohol concentration based on secondary compensation according to claim 1, characterized in that, Step S7 specifically includes the following steps: Convert the density of pure base liquor to the standard density at the standard reference temperature; Refer to the corresponding alcohol concentration table based on the OIMLR22 international recommendations.

7. The method for calculating alcohol concentration based on secondary compensation according to claim 1, characterized in that, It also includes the step of adaptively filtering the output of step S7: Monitor the volatility of the output results in real time; When the volatility exceeds the set threshold, the filter time constant is reduced to improve the response speed. When volatility is less than a set threshold, the filter time constant is increased to improve stability.

8. The method for calculating alcohol concentration based on secondary compensation according to claim 1, characterized in that, It also includes the following steps: When the calculated viscosity deviation or dry extract content exceeds the preset alarm threshold, the instrument outputs an abnormal alarm signal.

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