An online detection method for alcohol concentration and sugar content of fruit wine brewing production line

Abstract

This invention discloses an online detection method for alcohol concentration and sugar content in a fruit wine brewing production line. The method involves controlling a peristaltic pump and a solenoid valve to extract and filter fermentation broth from the fermentation tank via a sampling pipeline, then introducing it into a vertically arranged detection flow cell. The peristaltic pump is stopped, and the buoyancy of the fermentation broth causes bubbles to rise and dissipate, maintaining a preset settling time. A linear laser light source and a linear CCD sensor are driven to collect refractive index light signals, an ultrasonic transducer is driven to collect ultrasonic time-of-flight signals, and a temperature sensor is used to collect temperature signals. The signals are amplified and filtered. The original sugar content value is calculated based on the refractive index, and a corrected sugar content value is obtained through temperature compensation. The sound velocity of the fermentation broth is calculated based on the ultrasonic time-of-flight signal and temperature signal. Finally, the alcohol concentration value is calculated based on the corrected sugar content value, the sound velocity of the fermentation broth, and the temperature signal. The results are then sent to a display terminal.

Description

Technical Field

[0001] This invention relates to an online detection method for alcohol concentration and sugar content in a fruit wine brewing production line. Background Technology

[0002] In recent years, with the increasing demand for healthy beverages, the fruit wine industry has developed rapidly. During fruit wine brewing, sugar content and alcohol concentration are core indicators for judging the fermentation process, determining the termination time of fermentation, and ensuring the taste of the finished product. Currently, most small and medium-sized fruit wine production lines still use manual sampling, combined with handheld refractometers and hydrometers for offline testing. This testing method has the following drawbacks:

[0003] (1) The operation is complicated and human factors have a great influence. The data collected manually may not be very accurate, and it requires workers to have a certain level of work experience.

[0004] (2) Contamination may occur during the testing process. Manual sampling requires frequent opening of the tank, which may cause the fermentation liquid to be contaminated by bacteria, oxygen or other substances in the outside air, oxidizing the fermentation liquid and thus affecting the final quality of the fruit wine.

[0005] (3) The production status of fruit wine cannot be reported in a timely manner. When abnormal data is generated during the fermentation process of fruit wine, it often takes until the next test by the workers to be reported. This may reduce the quality of fruit wine or even cause the entire batch of fruit wine to spoil. Summary of the Invention

[0006] This invention provides an online method for detecting alcohol concentration and sugar content in a fruit wine brewing production line to address the problems existing in the prior art. This invention automates the entire process of fruit wine fermentation broth sampling, filtration, defoaming, detection, and cleaning, eliminating the need for manual intervention and effectively avoiding contamination problems caused by manual sampling. Simultaneously, it enables real-time online detection of sugar and alcohol concentrations, providing timely data feedback and accurately reflecting the state changes during the fruit wine fermentation process. During the detection process, various methods such as bubble settling and removal, temperature compensation, sound path correction, and multidimensional nonlinear fitting effectively eliminate the influence of various interference factors on the detection results, significantly improving detection accuracy. Furthermore, the fully automated cleaning process effectively prevents scale buildup or biofilm growth in pipelines, ensuring the long-term stable operation of the detection system and reducing equipment maintenance costs. This invention has significant practical application value for improving the automation level of fruit wine production and stabilizing the quality of fruit wine products.

[0007] The technical solutions adopted in this invention are as follows:

[0008] An online detection method for alcohol concentration and sugar content in a fruit wine brewing production line includes the following steps:

[0009] S1: Control the peristaltic pump and solenoid valve to extract and filter the fermentation liquid in the fermenter through the sampling pipeline, and then introduce it into the vertically arranged detection flow cell.

[0010] S2: Stop the peristaltic pump, allow the bubbles in the fermentation liquid to rise and be discharged under the action of buoyancy, and maintain the preset settling time;

[0011] S3: Drive a linear laser light source to irradiate the fermentation broth in the detection flow cell, and collect the refractive index light signal through a linear CCD sensor; drive an ultrasonic transducer to emit and receive ultrasonic waves into the detection flow cell, and output the original electrical signal by the ultrasonic transducer; collect the temperature signal of the fermentation broth in the detection flow cell through a temperature sensor.

[0012] S4: Amplify and filter the refractive index optical signal to obtain the original sugar content signal; amplify and filter the original electrical signal output by the ultrasonic transducer to convert it into an ultrasonic time-of-flight signal;

[0013] S5: Calculate the refractive index of the fermentation broth based on the original sugar content signal, convert the refractive index of the fermentation broth into the original sugar content value, and perform temperature compensation on the original sugar content value according to the temperature signal to obtain the corrected sugar content value;

[0014] S6: Calculate the sound velocity of the fermentation broth based on the ultrasonic time-of-flight signal and temperature signal, and calculate the alcohol concentration value based on the corrected sugar content value, the sound velocity of the fermentation broth and temperature signal;

[0015] S7: Send the corrected sugar content value and the alcohol concentration value to the display terminal for display.

[0016] Furthermore, the filtration is achieved through a microporous filter with a pore size of 0.45μm to 1μm.

[0017] Furthermore, the preset settling time is 3 to 5 seconds, and the detection flow cell has a straight cylindrical vertical structure with liquid entering from the bottom and exiting from the top, and an expansion and exhaust chamber at the top.

[0018] Furthermore, the linear laser source has a wavelength of 650nm, and the linear CCD sensor is a TCD1304; the laser emitted by the linear laser source forms a total internal reflection interface with the fermentation broth in the detection flow cell through an optical prism, and the linear CCD sensor obtains the refractive index light signal by detecting the position of the reflected light spot; the temperature sensor is a DS18B20 digital temperature sensor, and the temperature sensor is in direct contact with the fermentation broth in the detection flow cell.

[0019] Furthermore, the ultrasonic transducer is a piezoelectric ceramic transducer and is arranged in pairs on both sides of the detection flow cell to form a through-beam structure; the ultrasonic transducer is driven by a TDC1000 ultrasonic analog front-end chip, and the original electrical signal output by the ultrasonic transducer is processed by the ultrasonic analog front-end chip to obtain a time-of-flight pulse signal.

[0020] Furthermore, the amplification and filtering of the refractive index optical signal includes: pre-amplification using an AD620 instrumentation amplifier, followed by filtering out signal components higher than the upper limit of the readout frequency of the linear CCD sensor using a second-order active low-pass filter, wherein the cutoff frequency of the second-order active low-pass filter matches the upper limit of the readout frequency of the linear CCD sensor.

[0021] Furthermore, in S5, a second-order temperature compensation formula is used to compensate for the temperature of the original sugar content value. The second-order temperature compensation formula is as follows:

[0022] ,

[0023] in, This refers to the real-time temperature of the fermentation broth. The linear deviation rate, This represents the nonlinear deviation rate.

[0024] Furthermore, in S6, when calculating the sound velocity of the fermentation broth based on the ultrasonic time-of-flight signal and temperature signal, the ultrasonic propagation path is first corrected for temperature based on the temperature signal, and then the sound velocity is calculated using the formula:

[0025] ,

[0026] in, This is the temperature-corrected ultrasonic propagation path. For ultrasonic flight time, The velocity of sound in the fermentation broth;

[0027] ,

[0028] As the reference distance, Let be the coefficient of linear expansion of the detection flow cell. This refers to the real-time temperature of the fermentation broth.

[0029] Furthermore, in S6, when calculating the alcohol concentration based on the corrected sugar content, the sound velocity of the fermentation broth, and the temperature signal, a multidimensional nonlinear fitting model is used for calculation. The model is as follows:

[0030] ,

[0031] in, This represents the alcohol concentration value. To correct the sugar content, These are the model fitting coefficients. The velocity of sound in the fermentation broth. This refers to the real-time temperature of the fermentation broth.

[0032] Furthermore, before S1, there is a pre-cleaning step: controlling the peristaltic pump and solenoid valve to draw pure water to flush the sampling pipeline and the detection flow cell;

[0033] S7 is followed by a post-cleaning step: controlling pure water to backwash the sampling pipeline and the detection flow cell, and detecting the refractive index of the liquid in the detection flow cell in real time. When the deviation between the refractive index and the pure water reference refractive index is less than or equal to a preset threshold and maintained for a preset time, the cleaning is determined to be complete.

[0034] The present invention has the following beneficial effects:

[0035] (1) Automatic sampling and cleaning are achieved by peristaltic pump and solenoid valve, eliminating the need for manual opening of fermentation tank and reducing the risk of external bacteria and oxygen intrusion; at the same time, it replaces the offline manual detection method of handheld refractometer, realizing continuous online monitoring of sugar and alcohol concentration during fermentation, enabling more timely detection of fermentation abnormalities and reducing manual labor intensity.

[0036] (2) By using a microporous filter to pre-filter out solid impurities such as fruit pomace, and combining it with the gravity defoaming mechanism of the vertical DC flow tank, the interference of bubbles and suspended matter on optical refractive index detection and ultrasonic velocity detection is effectively avoided; the sugar content value is corrected by a second-order temperature compensation algorithm, and the ultrasonic path is temperature-corrected based on the thermal expansion coefficient of the detection flow tank material, which reduces the influence of fermentation broth temperature fluctuation on the measurement results; furthermore, the alcohol concentration is calculated based on a multidimensional fitting model of sugar content, sound velocity and temperature, which reduces the cross-sensitivity error caused by changes in associated components such as glycerol and organic acids in the fermentation broth when detecting a single parameter, so that the detection results more accurately reflect the real process state.

[0037] (3) Through the optical closed-loop cleaning verification mechanism (using the refractive index of pure water as a reference to determine the cleaning endpoint), the residual fermentation liquid in the detection flow cell and pipeline is effectively removed, avoiding cross-contamination between samples and scaling in the pipeline, and ensuring the repeatability and accuracy of continuous multiple detections; the dual-core architecture design (the main controller is responsible for high-speed signal acquisition and calculation, and the auxiliary controller is responsible for low-power display management) achieves a balance between detection real-time performance and system stability. Attached Figure Description

[0038] Figure 1 This is the overall system structure diagram.

[0039] Figure 2 This is a schematic diagram of the fluid pipeline and the detection flow cell.

[0040] Figure 3 It is a flowchart of the overall software design.

[0041] Figure 4 This is a schematic diagram of the photoelectric refractive index detection principle.

[0042] Figure 5 This is a schematic diagram of a signal amplification and filtering circuit.

[0043] Figure 6 This is the flowchart of the main control program.

[0044] Figure 7 This is the flowchart of the ADC acquisition module program.

[0045] Figure 8 This is a flowchart of the data processing procedure. Detailed Implementation

[0046] The invention will now be further described with reference to the accompanying drawings.

[0047] like Figure 1 As shown, this invention provides an online detection method for alcohol concentration and sugar content in a fruit wine brewing production line. It is implemented using a hardware system based on a dual-core control architecture and multi-sensor collaborative detection. The overall system structure is as follows: Figure 1 As shown, the system uses an STM32 microcontroller as the core to complete signal acquisition, data processing, and logic control, while an MSP430 auxiliary microcontroller completes data reception, display driving, and alarm control. The two communicate via a USART serial port. The system is also equipped with an automatic sampling and cleaning circulation system, a photoelectric refractive sugar content detection module, an ultrasonic alcohol concentration detection module, a temperature detection module, a signal conditioning module, a solenoid valve and pump control module, and a display terminal. All modules work together to achieve online, accurate, and non-destructive detection of alcohol concentration and sugar content in fruit wine fermentation liquid, effectively solving the problems of low efficiency, easy contamination, and delayed data feedback in traditional manual detection.

[0048] Before the test begins, the system performs a pre-cleaning step. The STM32 microcontroller issues control commands to drive the solenoid valve and pump control module to open the corresponding solenoid valve. At the same time, it controls the peristaltic pump to draw pure water from the pure water tank. The pure water flows through the sampling pipeline and the test flow cell to thoroughly flush the sampling pipeline and the inside of the test flow cell, so as to avoid the interference of impurities and residual liquid in the pipeline with the subsequent test results. After the pre-cleaning is completed, the peristaltic pump stops working and the corresponding solenoid valve closes.

[0049] After pre-cleaning is completed, the formal testing process begins, starting with step S1.

[0050] like Figure 2As shown, the STM32 microcontroller controls the peristaltic pump and the sampling solenoid valve to open. Under the power of the peristaltic pump, the fermentation broth in the fermenter is drawn through the sampling pipeline and first filtered through a microporous filter. The pore size of the microporous filter is 0.45μm~1μm, which can effectively filter out large particles of fruit residue in the fermentation broth and prevent fruit residue from clogging the pipeline or adhering to the surface of the detection sensor and affecting the detection accuracy. The filtered fermentation broth is introduced into the vertically arranged detection flow cell. The detection flow cell has a straight cylindrical vertical structure and adopts a bottom inlet and top outlet design. The top has an expansion and exhaust chamber to provide space for subsequent bubble discharge.

[0051] The structural design of the flow cell allows for the natural bubbling of bubbles based on Stokes' law, with the bubble rising velocity satisfying the formula... The system sets the settling and defoaming time reference accordingly.

[0052] After the fermentation broth is introduced into the flow-through test tank, step S2 is performed.

[0053] The STM32 microcontroller controls the peristaltic pump to stop working. At this time, the fermentation broth is in a static state in the detection flow cell. Under the action of buoyancy, the air bubbles contained in the fermentation broth naturally float upward and are discharged from the top expansion and exhaust chamber. In order to ensure that the air bubbles are completely discharged and to avoid the air bubbles interfering with the propagation of light and ultrasonic signals, the preset static time of the fermentation broth is controlled to be 3 to 5 seconds. After the static time is completed, the fermentation broth in the detection flow cell is in a stable detection state without air bubbles.

[0054] Then proceed with step S3.

[0055] Simultaneously, multiple sensors are activated to complete signal acquisition. First, the linear laser source in the photoelectric refractive sugar content detection module is driven. This linear laser source emits a wavelength of 650nm. The emitted laser beam, after being refracted by an optical prism group, forms a total internal reflection interface with the fermentation broth in the detection flow cell. Figure 4 As shown, the laser undergoes total internal reflection at the interface to form a reflected light spot. The position signal of the reflected light spot, i.e. the refractive index light signal, is collected by a linear CCD sensor (TCD1304). The change of this signal corresponds to the refractive index of the fermentation broth.

[0056] Meanwhile, the STM32 microcontroller drives the ultrasonic transducer of the ultrasonic alcohol concentration detection module through the TDC1000 ultrasonic analog front-end chip. The ultrasonic transducer is a piezoelectric ceramic transducer, and they are arranged in pairs on both sides of the detection flow cell to form a through-beam structure. One ultrasonic transducer emits ultrasonic waves into the fermentation liquid in the detection flow cell, and the other ultrasonic transducer receives the ultrasonic waves after they are propagated through the fermentation liquid. The ultrasonic transducer converts the received ultrasonic signal into a raw electrical signal and outputs it.

[0057] While acquiring optical and ultrasonic signals, the DS18B20 digital temperature sensor, which is in direct contact with the fermentation broth in the detection flow tank, acquires the temperature signal of the fermentation broth in real time. This temperature signal provides data support for subsequent temperature compensation and sound path correction.

[0058] All acquired signals are transmitted to the signal conditioning module, where step S4 is executed to amplify and filter the signals.

[0059] For the refractive index light signal acquired by the linear CCD sensor, an AD620 instrumentation amplifier is first used for pre-amplification to amplify the weak light signal to a range recognizable by the STM32 microcontroller. The amplified signal is then input to a second-order active low-pass filter (OPO7). The cutoff frequency of this filter matches the upper limit of the readout frequency of the linear CCD sensor, effectively filtering out high-frequency interference components above the upper limit of the readout frequency. After amplification and filtering, the original sugar content signal is obtained. For the original electrical signal output from the ultrasonic transducer, the same amplification and filtering process is used: first amplified by the AD620 instrumentation amplifier, then filtered by a second-order active low-pass filter to remove interference. The original electrical signal is then processed by the TDC1000 ultrasonic analog front-end chip and converted into an ultrasonic time-of-flight signal, such as... Figure 5 The circuit principle for signal amplification and filtering is as follows: the processed raw sugar content signal, ultrasonic time-of-flight signal, and temperature signal collected by the temperature sensor are all transmitted to the STM32 microcontroller for data processing. The ADC acquisition process is as follows: Figure 7 As shown, this ensures the accuracy of signal acquisition.

[0060] After receiving various signals, the STM32 microcontroller first executes step S5 to calculate the sugar content.

[0061] Based on the original sugar content signal, the light-dark boundary points of the linear CCD sensor's acquired signal are extracted using a sub-pixel gray-level centroid method combined with a first-order differential operator. This yields the pixel position index P of the light-dark boundary line with a decimal value. Then, the original refractive index of the fermentation broth is calculated by substituting the structural parameters of the optical system into the geometric optics conversion formula. This geometric optics conversion formula is as follows:

[0062] ,

[0063] in, The refractive index of the optical prism. Let be the structural constant of the combination of the prism's mounting tilt angle and base angle. The focal length of the imaging lens. For a single physical pixel size of a linear CCD sensor, This is the reference pixel position index on the CCD corresponding to the system's light center.

[0064] To reduce the floating-point computational load on the main control microcontroller, the system, during the initialization phase, combines the aforementioned geometric optics theoretical model with Taylor expansion and standard liquid calibration points to reduce its dimension and convert it into a quadratic polynomial fitting curve formula. In actual calculations, this fitting formula is directly used to calculate the original refractive index. The formula is as follows: Where a, b, and c are equipment-specific coefficients, calculated and saved by matrix inversion during system initialization calibration. After obtaining the original refractive index of the fermentation broth, it is substituted into the preset calibration formula to convert it into the original sugar content value of the fermentation broth.

[0065] Since temperature affects the refractive index of the fermentation broth, thus impacting the accuracy of sugar content detection, a second-order temperature compensation formula is used to compensate for the original sugar content value based on the real-time temperature signal acquired by the temperature sensor, resulting in a corrected sugar content value. The second-order temperature compensation formula is as follows:

[0066] ,

[0067] Where T is the real-time temperature of the fermentation broth. The temperature linearity deviation rate is 0.068. The temperature nonlinearity deviation rate is set to 0.00015. The corrected sugar content value after temperature compensation accurately reflects the actual sugar content of the fermentation broth. The entire data processing flow is as follows: Figure 8 As shown.

[0068] After calculating the sugar content, proceed to step S6 to calculate the alcohol concentration.

[0069] First, the sound velocity of the fermentation broth is calculated based on the ultrasonic time-of-flight signal and temperature signal. Since the material of the flow cell expands and contracts with temperature changes, thus altering the ultrasonic propagation path, a temperature correction is first applied to the ultrasonic propagation path based on the temperature signal. The correction formula is as follows:

[0070] ,

[0071] in, The reference distance for ultrasonic propagation is given by γ, the coefficient of linear expansion of the flow cell is given by γ, and T is the real-time temperature of the fermentation broth. The temperature-corrected ultrasonic propagation path is then obtained. Then, through the formula Calculate the actual sound velocity of the fermentation broth, where ν is the ultrasonic flight time, and v is the sound velocity in the fermentation broth.

[0072] The propagation speed of ultrasound in the fermentation broth is affected by multiple factors, including alcohol concentration, sugar content, and temperature. Therefore, after obtaining the sound velocity in the fermentation broth, the corrected sugar content value and real-time temperature signal obtained in step S5 are combined and substituted into a preset multidimensional nonlinear fitting model to calculate the alcohol concentration value of the fermentation broth. The multidimensional nonlinear fitting model is as follows:

[0073] ,

[0074] in This represents the alcohol concentration value. To correct the sugar content, These are the model fitting coefficients obtained by training with the standard sample pool. The velocity of sound in the fermentation broth. The model provides the real-time temperature of the fermentation broth and enables accurate calculation of alcohol concentration under the coupling of multiple factors.

[0075] After the STM32 microcontroller completes the calculation of the corrected sugar content and alcohol concentration, it executes step S7.

[0076] The two sets of data are sent to the MSP430 auxiliary microcontroller via the USART serial port. After receiving the data, the MSP430 auxiliary microcontroller drives the display terminal to display the data. The display terminal can simultaneously display the real-time values ​​and historical trend curves of sugar content and alcohol concentration. If the detected data exceeds the preset process threshold, the system will automatically trigger an alarm prompt, so that the staff can keep abreast of the status of the fermentation liquid.

[0077] After the data is displayed, the testing process is not yet complete. The system will then perform a post-cleaning step. The STM32 microcontroller will control the peristaltic pump and cleaning solenoid valve to open, drawing pure water to backwash the sampling pipeline and the flow cell. The amount of cleaning fluid used is calculated based on the pipeline dead volume formula, which is: Ensure that the amount of cleaning fluid used meets the process requirements for pipeline cleaning.

[0078] During the cleaning process, the photoelectric refractive sugar content detection module will detect the refractive index of the rinsing liquid in the flow tank in real time. When the detected refractive index is compared with the refractive index of 20℃ pure water, the refractive index will be determined. The absolute value of the deviation satisfies: If this stable state is maintained for 3 seconds, it is determined that the residual liquid in the pipeline and the detection flow cell has been completely cleaned. The STM32 microcontroller will then issue a control command to stop the peristaltic pump and close the corresponding solenoid valve, while simultaneously opening the waste discharge solenoid valve to drain the pure water from the pipeline and the detection flow cell, completing the entire post-cleaning process. The system will then return to standby mode, awaiting the next detection command. Figure 3 The overall design flow of the system software is as follows: the execution of each step is implemented by the software program with timing control and logic drive. The flow of the main control program is as follows: Figure 6 As shown, this ensures that the testing process is automated and continuous.

[0079] To verify the accuracy and practicality of this detection method, comparative tests were conducted on sugar content and alcohol concentration. For the sugar content test, sucrose solutions of different concentrations were prepared to simulate fruit wine fermentation liquid, and the method was used for detection at a constant temperature of 20℃. The results were compared with those obtained using a standard Abbe refractometer. Specific test results are shown in Table 1 below.

[0080] Table 1. Results of Sugar Content Test

[0081]

[0082] The alcohol concentration test used finished fruit wines with different alcohol concentrations as test samples, and this method was used for detection. The test results were compared with the laboratory values ​​determined by distillation. The specific test results are shown in Table 2 below:

[0083] Table 2. Results of alcohol concentration test

[0084]

[0085] The test results above show that the absolute error of this method in sugar content measurement can be controlled within ±0.2 Brix, and the error in alcohol concentration can be controlled within ±0.5% vol, which fully meets the process monitoring requirements of fruit wine fermentation.

[0086] The above description is only a preferred embodiment of the present invention. It should be noted that those skilled in the art can make several improvements without departing from the principle of the present invention, and these improvements should also be considered within the scope of protection of the present invention.

Claims

1. A method for online detection of alcohol concentration and sugar content in a fruit wine brewing production line, characterized in that: Includes the following steps: S1: Control the peristaltic pump and solenoid valve to extract and filter the fermentation liquid in the fermenter through the sampling pipeline, and then introduce it into the vertically arranged detection flow cell. S2: Stop the peristaltic pump, allow the bubbles in the fermentation liquid to rise and be discharged naturally under the action of buoyancy, and maintain the preset settling time; S3: Drive a linear laser light source to irradiate the fermentation broth in the detection flow cell, and collect the refractive index light signal through a linear CCD sensor; drive an ultrasonic transducer to emit and receive ultrasonic waves into the detection flow cell, and output the original electrical signal by the ultrasonic transducer; collect the temperature signal of the fermentation broth in the detection flow cell through a temperature sensor. S4: Amplify and filter the refractive index optical signal to obtain the original sugar content signal; amplify and filter the original electrical signal output by the ultrasonic transducer to convert it into an ultrasonic time-of-flight signal; S5: Calculate the refractive index of the fermentation broth based on the original sugar content signal, convert the refractive index of the fermentation broth into the original sugar content value, and perform temperature compensation on the original sugar content value according to the temperature signal to obtain the corrected sugar content value; S6: Calculate the sound velocity of the fermentation broth based on the ultrasonic time-of-flight signal and temperature signal, and calculate the alcohol concentration value based on the corrected sugar content value, the sound velocity of the fermentation broth and temperature signal; S7: Send the corrected sugar content value and the alcohol concentration value to the display terminal for display.

2. The online detection method for alcohol concentration and sugar content in a fruit wine brewing production line as described in claim 1, characterized in that: The filtration is achieved through a microporous filter with a pore size of 0.45 μm to 1 μm.

3. The online detection method for alcohol concentration and sugar content in a fruit wine brewing production line as described in claim 1, characterized in that: The preset settling time is 3 to 5 seconds. The detection flow cell has a vertical cylindrical structure with liquid entering from the bottom and exiting from the top. An expansion and exhaust chamber is provided at the top.

4. The online detection method for alcohol concentration and sugar content in a fruit wine brewing production line as described in claim 1, characterized in that: The linear laser source has a wavelength of 650 nm; the laser emitted by the linear laser source forms a total internal reflection interface with the fermentation broth in the detection flow cell through an optical prism, and the linear CCD sensor obtains the refractive index light signal by detecting the position of the reflected light spot.

5. The online detection method for alcohol concentration and sugar content in a fruit wine brewing production line as described in claim 1, characterized in that: The ultrasonic transducer is a piezoelectric ceramic transducer and is arranged in pairs on both sides of the detection flow cell to form a through-beam structure; the ultrasonic transducer is driven by an ultrasonic analog front-end chip, and the original electrical signal output by the ultrasonic transducer is processed by the ultrasonic analog front-end chip to obtain a time-of-flight pulse signal.

6. The online detection method for alcohol concentration and sugar content in a fruit wine brewing production line as described in claim 1, characterized in that: The amplification and filtering of the refractive index optical signal includes: pre-amplification using an instrumentation amplifier, followed by filtering out signal components higher than the upper limit of the readout frequency of the linear CCD sensor using a second-order active low-pass filter. The cutoff frequency of the second-order active low-pass filter matches the upper limit of the readout frequency of the linear CCD sensor.

7. The online detection method for alcohol concentration and sugar content in a fruit wine brewing production line as described in claim 1, characterized in that: In S5, a second-order temperature compensation formula is used to compensate for the temperature of the original sugar content value. The second-order temperature compensation formula is as follows: ， in, This refers to the real-time temperature of the fermentation broth. The linear deviation rate, This represents the nonlinear deviation rate.

8. The online detection method for alcohol concentration and sugar content in a fruit wine brewing production line as described in claim 1, characterized in that: In S6, when calculating the sound velocity of the fermentation broth based on the ultrasonic time-of-flight signal and temperature signal, the ultrasonic propagation path is first corrected for temperature based on the temperature signal, and then the sound velocity is calculated using the formula: ， in, This is the temperature-corrected ultrasonic propagation path. For ultrasonic flight time, The velocity of sound in the fermentation broth; ， As the reference distance, Let be the coefficient of linear expansion of the detection flow cell. This refers to the real-time temperature of the fermentation broth.

9. The online detection method for alcohol concentration and sugar content in a fruit wine brewing production line as described in claim 1, characterized in that: In S6, when calculating the alcohol concentration based on the corrected sugar content, fermentation broth sound velocity, and temperature signal, a multidimensional nonlinear fitting model is used. The model is as follows: ， in, This represents the alcohol concentration value. To correct the sugar content, These are the model fitting coefficients. The velocity of sound in the fermentation broth. This refers to the real-time temperature of the fermentation broth.

10. The online detection method for alcohol concentration and sugar content in a fruit wine brewing production line as described in claim 1, characterized in that: Before S1, there is also a pre-cleaning step: controlling the peristaltic pump and solenoid valve to draw pure water to flush the sampling pipeline and the detection flow cell; S7 is followed by a post-cleaning step: controlling pure water to backwash the sampling pipeline and the detection flow cell, and detecting the refractive index of the liquid in the detection flow cell in real time. When the deviation between the refractive index and the pure water reference refractive index is less than or equal to a preset threshold and maintained for a preset time, the cleaning is determined to be complete.

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