Acidity adjusting method and system for reducing depression of soft sweets

Abstract

The invention discloses an acidity adjusting method and system for reducing depression of soft sweets, and relates to the technical field of acidity adjusting.The acidity adjusting method comprises the steps that target parameter data in the soft sweets to be detected are obtained, and the target parameter data are preprocessed; based on the preprocessed target parameter data, constructing an acidity response model and acquiring the injection amount of an acidity regulator; injecting the acidity regulator into the soft sweet slurry according to the injection amount of the acidity regulator; and dynamically adjusting parameters of the acidity response model according to real-time monitoring data. The acidity response model is constructed, the injection amount of the current acidity regulator can be accurately calculated, the method adapts to dynamic changes in the soft sweet production process, accurate control over the acidity of the soft sweet is achieved, the graded dynamic regulation strategy is implemented in combination with the target pH deviation value and recession rate feedback, accurate control over the acidity in the soft sweet production is achieved, and the soft sweet production efficiency is improved. And a data-driven, intelligent and efficient quality control solution is provided for production of soft sweets and sugar-containing colloid foods.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of acidity adjustment, and particularly relates to an acidity adjustment method and system for reducing gummy candy concave. BACKGROUND

[0002] In the field of gummy candy production, the quality and appearance of gummy candy have always been the focus of production enterprises. As a type of candy that is deeply loved by consumers, the taste, texture and appearance of gummy candy directly affect the purchasing willingness of consumers and the market competitiveness of the product. In the production process of gummy candy, gummy candy concave is a common and intractable problem. Gummy candy concave not only affects the appearance integrity of gummy candy, making it prone to appearance defects in the packaging and sales process and reducing the attractiveness of the product, but also may imply that the structure and quality of gummy candy inside have problems, thereby affecting the taste and shelf life. Gummy candy with concave is more likely to be contaminated by microorganisms during storage, leading to accelerated deterioration. The traditional gummy candy production process has many limitations in controlling gummy candy concave. Many production enterprises mainly rely on experience and simple detection means when adjusting the acidity of gummy candy. Commonly, the amount of acidity regulator is roughly determined in the early production stage. This method lacks consideration of real-time changes in the production process of gummy candy. The pH value and temperature inside gummy candy change constantly during the making, cooling and storage process, and these changes have a significant impact on the acidity balance of gummy candy. If the acidity cannot be accurately controlled, the texture of gummy candy will be difficult to guarantee uniformity, and gummy candy concave is prone to occur. In the prior art, the monitoring of the pH value and temperature inside gummy candy is often not accurate and real-time. Some simple detection equipment cannot quickly and accurately obtain key data at different positions inside gummy candy, leading to the inability to adjust production parameters in a timely manner according to data changes. In the addition of acidity regulator, there is a lack of accurate control technology. The conventional addition method cannot accurately add acidity regulator according to the real-time state of gummy candy. Either the amount is insufficient, which cannot effectively adjust the acidity, or the amount is excessive, which leads to over-acidification of gummy candy or other quality problems.

[0003] However, the common solutions at present have many shortcomings, including: the existing method lacks an acidity response model constructed based on real-time data, it is difficult to accurately calculate the injection amount of acidity regulator, and it usually adopts empirical value or simple fixed proportion addition, which cannot adapt to changes in various factors in the production process of gummy candy, leading to poor acidity adjustment effect. When adding acidity regulator, there is a lack of precise control technology, and ordinary injection methods cannot achieve precise control of small flow, making it difficult to ensure uniform distribution of the regulator in gummy candy slurry, and local acidity unevenness is prone to occur, affecting the quality of gummy candy. SUMMARY

[0004] This section is intended to summarize some aspects of the embodiments of the present application and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the abstract and title of the specification of the present application in order to avoid obscuring the purpose of this section, the abstract and the title of the specification, and such simplifications or omissions are not used to limit the scope of the present application.

[0005] In view of the above problems existing in the prior art of the acidity adjustment method and system for reducing the sag of soft candy, the present application is proposed.

[0006] Therefore, the purpose of the present application is to provide an acidity adjustment method and system for reducing the sag of soft candy, which is suitable for solving the problem that the prior art lacks an acidity response model constructed based on real-time data, it is difficult to accurately calculate the injection amount of acidity regulator, and empirical values or simple fixed proportions are usually used for addition, which cannot adapt to changes in various factors in the production process of soft candy, resulting in poor acidity adjustment effect.

[0007] To solve the above technical problems, the present application provides the following technical solutions:

[0008] In a first aspect, the embodiments of the present application provide an acidity adjustment method for reducing the sag of soft candy, which comprises obtaining target parameter data in the soft candy to be tested and preprocessing the target parameter data; based on the preprocessed target parameter data, constructing an acidity response model and obtaining the injection amount of acidity regulator; injecting the acidity regulator into the soft candy slurry according to the injection amount of the acidity regulator; and dynamically adjusting the parameters of the acidity response model according to real-time monitoring data.

[0009] As a preferred scheme of the acidity adjustment method for reducing the sag of soft candy, the target parameter data comprises pH value and temperature data in the soft candy to be tested; and the acidity regulator is a composite regulator composed of organic acid, inorganic acid, composite acidity regulator, pH responsive acidity regulator and natural acidity regulator.

[0010] As a preferred scheme of the acidity adjustment method for reducing the sag of soft candy, the construction of the acidity response model based on the pH value and temperature data comprises the following steps:

[0011] The measured pH value is corrected by a temperature compensation function to eliminate the influence of temperature on ion activity, and the specific formula is as follows:

[0012] pH a =pH r +α·(T-T s );

[0013] Wherein, pH a is the corrected pH value after temperature compensation; pH r is the measured pH value of the sensor; T is the real-time temperature; Ts T is the reference temperature; and a is a temperature compensation coefficient for reflecting the influence of temperature on ion activity;

[0014] The pH deviation value reflects the difference between the current acidity and the target, and the specific formula is as follows:

[0015] ΔpH = pH t -pH a ;

[0016] Wherein, ΔpH is the target pH deviation value, and the ideal pH value is preset according to the soft candy formula; pH t is the target pH value; pH a is the corrected pH value after temperature compensation;

[0017] The basic amount of the acidity regulator is calculated by considering the quality of the soft candy syrup, the effective concentration of the acid, and the deviation sensitivity, and the specific formula is as follows:

[0018] Q0 = k·m·ΔpH;

[0019] Wherein, Q0 is the basic amount of the acidity regulator; k is the acidity regulator dosage proportionality constant; m is the mass of the syrup to be adjusted; and ΔpH is the target pH deviation value;

[0020] The pH value measured at different temperatures is corrected by introducing a temperature correction factor, and the specific formula is as follows:

[0021] f(T) = 1 + β(T-T o );

[0022] Wherein, f(T) is the temperature correction factor for the effect of the acidity regulator; β is a temperature sensitivity coefficient for reflecting the influence of temperature on the effect of the acidity regulator; T is the real-time temperature; and T o is the optimal temperature for the effect of the acidity regulator; the acidity response model is constructed by combining the basic amount of the acidity regulator and the temperature correction factor.

[0023] As a preferred scheme of the acidity adjustment method for reducing the soft candy depression, the specific formula of the acidity response model is as follows:

[0024] Q = k·m·(pH t -(pH r + a(T-T s ))·(1 + β(T-T o ));

[0025] Wherein, Q is the injection amount of the acidity regulator; k is the acidity regulator dosage proportionality constant; m is the mass of the syrup to be adjusted; pH t is the target pH value; pH rpH is the measured pH value of the sensor; α is the temperature compensation coefficient; T is the real-time temperature; T s pH is the reference temperature; β is the temperature sensitivity coefficient; T o is the optimal temperature for the action of the acidity regulator.

[0026] As a preferred solution of the acidity adjustment method for reducing the soft candy concave of the present application, wherein: the specific case of the target pH deviation value is as follows: when the target pH deviation value is less than the first threshold value, it indicates that the current acidity is close to the target value, which belongs to slight fluctuation, and the calculated basic amount of acidity according to the acidity response model generates the acidity adjustment strategy and injects the acidity regulator; when the target pH deviation value is greater than the first threshold value and less than the second threshold value, it indicates that the acidity deviates from the target value, which will cause the abnormal setting speed of the syrup and the risk of slight concave, and 50% of the calculated amount is injected first, and the remaining amount is added after 10 seconds according to the real-time feedback; when the target pH deviation value is greater than the second threshold value, it indicates that the acidity deviates from the target value seriously, and the gel structure of the syrup is destroyed, which will cause the large-area concave, deformation or adhesion of the soft candy, and the current batch of syrup production is immediately stopped, the prepared syrup is detected offline, the acidity regulator is added to the target range, and the sensor failure, injection pipeline blockage or temperature control system abnormality is checked.

[0027] As a preferred solution of the acidity adjustment method for reducing the soft candy concave of the present application, wherein: the dynamic adjustment of the injection strategy of the acidity regulator according to the real-time monitoring data includes the following steps: injecting the acidity regulator according to the model calculation result according to the current model parameter; detecting the concave rate of the soft candy after forming by the visual detection equipment in real time; calculating the target concave rate deviation value, and the specific formula is as follows:

[0028] ΔR=R r -R t ;

[0029] Wherein, ΔR is the target concave rate deviation value; R r is the actual concave rate; R t is the target concave rate.

[0030] As a preferred solution of the acidity adjustment method for reducing the soft candy depression, the specific cases of the target depression rate deviation value are as follows: if the target depression rate deviation value is less than the depression threshold value, it indicates that the current acidity adjustment strategy is effective, and further analysis is performed; if the target depression rate deviation value is close to the depression threshold value, the model parameters are locally fine-tuned, the temperature compensation coefficient is adjusted, and the influence of temperature on the effect of the acidity regulator is corrected according to the difference between the current temperature and the optimal action temperature; if the target depression rate deviation value is stable and close to 0, no parameter adjustment is performed, and real-time monitoring is maintained; if the target depression rate deviation value is greater than the depression threshold value, it indicates that the current acidity adjustment strategy is abnormal, the automatic adjustment is suspended, the global optimization of the model parameters is started, the temperature compensation coefficient is recalculated, the proportion constant of the dosage is corrected, the sensor accuracy is checked, the effectiveness of the acidity regulator is verified, the injection equipment is checked, and after calibration, the automatic adjustment is restored, and whether the depression rate converges to within the threshold value is detected.

[0031] In a second aspect, to further solve the above technical problems, the embodiments of the present application provide an acidity adjustment system for reducing soft candy depression, comprising: a data acquisition module for acquiring target parameter data in a soft candy to be tested and performing preprocessing; a model construction module for constructing an acidity response model and acquiring an injection amount of a current acidity regulator; a slurry injection module for injecting the acidity regulator into soft candy slurry; and a dynamic adjustment module for dynamically adjusting acidity response model parameters.

[0032] In a third aspect, the embodiments of the present application provide a computer device, comprising a memory and a processor, and the memory stores a computer program, wherein the computer program is executed by the processor to implement any step of the acidity adjustment method for reducing soft candy depression according to the first aspect of the present application.

[0033] In a fourth aspect, the embodiments of the present application provide a computer readable storage medium, which stores a computer program, wherein the computer program is executed by a processor to implement any step of the acidity adjustment method for reducing soft candy depression according to the first aspect of the present application.

[0034] The beneficial effects of the present application are: the present application constructs an acidity response model based on the obtained pH value and temperature data, changes the previous way of adding acidity regulator by experience or simple fixed proportion, the model can accurately calculate the current injection amount of acidity regulator, adapts to the dynamic changes in soft candy production process, realizes the precise control of the acidity of soft candy, greatly improves the effect of acidity adjustment, uses sensors to collect data in real time and carries out temperature compensation correction, combines the target pH deviation value with the concave rate feedback to implement the hierarchical dynamic adjustment strategy, realizes the precise control of the acidity in the production of soft candy, the differentiated injection strategy based on three levels of threshold controls the concave risk caused by slight, moderate and severe acidity deviation at a low level, dynamically adjusts the model parameters through visual detection feedback, realizes the adaptive calibration of long-term interference such as raw material fluctuation and equipment aging, provides a data-driven, intelligent and efficient quality control solution for soft candy and sugar-containing gel food production, and significantly improves the production stability and economic benefits. BRIEF DESCRIPTION OF DRAWINGS

[0035] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creating labor. Among them:

[0036] Figure 1 The implementation flowchart of the present application in embodiment 1.

[0037] Figure 2 The dynamic adjustment diagram of the acidity response model in embodiment 1. DETAILED DESCRIPTION

[0038] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application will be described in detail in conjunction with the drawings of the specification.

[0039] In the following description, many specific details are set forth in order to provide a thorough understanding of the present application, but the present application can also be implemented in other ways different from those described herein, and those skilled in the art can make similar generalizations without departing from the connotation of the present application, therefore the present application is not limited to the specific embodiments disclosed below.

[0040] Secondly, the "one embodiment" or "embodiment" referred to herein means that the specific features, structures or characteristics can be included in at least one implementation of the present application. "In one embodiment" appearing in different places in the specification does not mean the same embodiment, nor is it an independent or alternative embodiment that excludes other embodiments.

[0041] Embodiment 1

[0042] Referring to Figure 1 and Figure 2 For the first embodiment of the present application, the embodiment provides an acidity adjustment method for reducing gummy concave, comprising the following steps:

[0043] S1: obtaining target parameter data in the gummy to be measured, and preprocessing the target parameter data.

[0044] Further, the target parameter data includes pH value and temperature data in the gummy to be measured.

[0045] Specifically, the pH value in the gummy to be measured is obtained by a pH sensor, and the temperature data is obtained by a temperature sensor.

[0046] It should be noted that the pH value directly determines the core chemical parameter of the gummy gel structure, and the temperature data is a key environmental parameter for correcting measurement error and reaction conditions.

[0047] In the embodiment of the present application, the preprocessing of the pH value is temperature compensation correction, and the preprocessing of the temperature data is noise filtering, validity verification, range check, unified data format and normalization.

[0048] Preferably, in the gummy production process, the accurate pH value is directly related to the formation of the gummy gel structure, the preprocessed pH data makes the injection amount calculation of the acidity regulator more accurate, avoids abnormal colloid coagulation caused by acidity deviation, and the accurate processing of the temperature data corrects the action efficiency of the regulator, ensures optimal adjustment under different environmental temperatures, and effectively reduces quality defects such as gummy concave and deformation.

[0049] S2: based on the preprocessed target parameter data, constructing an acidity response model and obtaining the injection amount of the acidity regulator.

[0050] It should be noted that the acidity influence model is used to obtain the injection amount of the acidity regulator.

[0051] Preferably, the acidity regulator is a composite regulator composed of organic acid, inorganic acid, composite acidity regulator, pH responsive acidity regulator and natural acidity regulator.

[0052] Specifically, constructing the acidity response model based on the pH value and the temperature data includes the following steps: correcting the measured pH value by a temperature compensation function to eliminate the influence of temperature on ion activity, and the specific formula is as follows:

[0053] pH a =pH r +α·(T-T s );

[0054] Wherein, pHa pH is the corrected pH value after temperature compensation; pH r pH is the measured pH value of the sensor; T is the real-time temperature collected by the temperature sensor; T s T is the reference temperature determined according to the requirements of the soft candy production process; a is the temperature compensation coefficient, which is determined by measuring the measurement error of the pH sensor at different temperatures, analyzing the relationship between temperature and measurement deviation, and fitting to obtain the temperature compensation coefficient, which is used to eliminate the influence of temperature on pH measurement and to reflect the influence of temperature on ion activity.

[0055] The pH deviation value reflects the difference between the current acidity and the target, and the specific formula is as follows:

[0056] ΔpH = pH t -pH a ;

[0057] Where ΔpH is the target pH deviation value; pH t is the target pH value, usually set to 4.5-5.0, determined by the research and development personnel according to the characteristics of the soft candy gel and the taste requirements; pH a is the corrected pH value after temperature compensation.

[0058] The basic amount of acidity regulator is calculated by considering the quality of the soft candy syrup, the effective concentration of the acid, and the deviation sensitivity, and the specific formula is as follows:

[0059] Q0 = k·m·ΔpH;

[0060] Where Q0 is the basic amount of acidity regulator; k is the proportion constant of the amount of acidity regulator; m is the mass of the syrup to be adjusted, accurately measured by weighing equipment; ΔpH is the target pH deviation value.

[0061] The pH value measured at different temperatures is corrected by introducing a temperature correction factor, and the specific formula is as follows:

[0062] f(T) = 1 + β(T-T opt );

[0063] Where f(T) is the temperature correction factor for the effect of the acidity regulator; β is the temperature sensitivity coefficient, which is used to reflect the influence of temperature on the effect of the acidity regulator; T is the real-time temperature; T o is the optimal temperature for the effect of the acidity regulator, determined by the research and development personnel through experiments and process optimization, used to improve the adaptability and adjustment accuracy of the model.

[0064] The acidity response model is constructed according to the basic amount of acidity regulator and the temperature correction factor.

[0065] Specifically, the specific formula of the acidity response model is as follows:

[0066] w=k*m*(pH t -(pH r +α(T-T s )))·(1+β(T-T o ));

[0067] Wherein, Q is the injection amount of the acidity regulator; k is the acidity regulator dosage proportionality constant; m is the mass of the syrup to be adjusted; pH t is the target pH value; pH r is the measured pH value of the sensor; a is the temperature compensation coefficient; T is the real-time temperature; T s is the reference temperature; β is the temperature sensitivity coefficient; T o is the optimal temperature of the acidity regulator.

[0068] Preferably, the specific conditions of injecting the acidity regulator into the soft syrup according to the calculation results are as follows:

[0069] When the target pH deviation value ΔpH is less than the first threshold value, it indicates that the current acidity is close to the target value, which belongs to slight fluctuation, and the acidity adjustment strategy is generated based on the basic amount calculated according to the acidity response model and the acidity regulator is injected.

[0070] When the target pH deviation value ΔpH is greater than the first threshold value and less than the second threshold value, it indicates that the acidity deviates from the target value, which will cause abnormal setting speed of the syrup and risk of slight concave, 50% of the calculated amount is injected first, and the remaining amount is added after 10 seconds according to the real-time feedback.

[0071] When the target pH deviation value ΔpH is greater than the second threshold value, it indicates that the acidity deviates from the target value seriously, the gel structure of the syrup is destroyed, which will cause large-area concave, deformation or adhesion of the soft candy, the current batch of syrup production is immediately stopped, the prepared syrup is detected offline, the acidity regulator is added to the target range, and the sensor failure, injection pipeline blockage or temperature control system abnormality is checked.

[0072] It should be noted that when the syrup pH value has hysteresis characteristics, full amount input is easy to cause reverse fluctuation after the pH value exceeds the target range, and staged injection through "half amount trial + feedback correction" limits single adjustment within a safe range and reduces the risk of overshoot.

[0073] In the embodiments of the present application, temperature not only affects the measurement accuracy of the pH sensor, but also changes the effect of the full degree regulator, at the same time, the dissociation speed of the acidity regulator and the reaction rate with the colloid also change with temperature, the present model corrects the pH measurement error and the adjustment regulator action efficiency through the temperature compensation function and the temperature correction factor, respectively, to ensure the accuracy of the model under different temperature conditions.

[0074] For example, a food factory produces lemon-flavored gelatin soft candy, sets the target pH value of 4.8, the reference temperature of 25℃, the acidity regulator dosage proportionality constant k = 0.1 mL / (g pH), the temperature sensitivity coefficient β = 0.02, the optimal temperature T s of the acidity regulator is 25℃, and the mass of the syrup to be adjusted m = 1000g.

[0075] At t1, the pH sensor measures the pH value of 4.60, and the temperature sensor displays the real-time temperature of 30.0℃. First, according to the temperature compensation formula, the measured pH value is corrected using the temperature compensation coefficient α = 0.01, and the pH a = 4.60 + 0.01 × (30-25) = 4.55; then the pH deviation ΔpH = 4.8-4.55 = 0.25 is calculated, and thus the basic dosage of the acidity regulator Q0 = 0.1 × 1000 × 0.25 = 25mL is obtained; then the temperature correction factor formula is calculated f(T) = 1 + 0.02 × (25-30) = 0.9, and finally the regulator injection amount Q = 25 × 0.9 = 22.5mL is determined. Since the target pH deviation value is small at this time, it belongs to slight fluctuation, and the direct injection adjustment strategy is adopted, and the soft candy forming has a concave rate of 1.8%, which meets the quality standard.

[0076] At t2, the measured pH value is reduced to 4.20, and the real-time temperature is 35.0℃. Similarly, the temperature compensation is first performed, and the pH a = 4.20 + 0.01 × (25-35) = 4.10, and the pH deviation ΔpH = 4.8-4.10 = 0.7 is calculated, and the basic dosage Q0 = 0.1 × 1000 × 0.7 = 70mL is obtained. The temperature correction factor f(T) = 1 + 0.02 × (25-35) = 0.8, and finally the dosage Q = 70 × 0.8 = 56mL is obtained. In view of the fact that the pH deviation value indicates that the acidity deviates from the target value, there is a risk of slight concave, so 50% of the calculated amount, i.e. 28mL, is first injected, and the remaining amount is added after 10 seconds according to the real-time feedback. This way effectively avoids the pH value overshoot caused by full injection, and ensures the stability of the soft candy quality.

[0077] At t3, the measured pH value is 3.80, and the real-time temperature is 32.0℃. After calculation, the temperature-compensated pH a= 3.80 + 0.01 x (25 - 32) = 3.73, pH deviation value ΔpH = 4.8 - 3.73 = 1.07, base dosage Q0 = 0.1 x 1000 x 1.07 = 107 mL, temperature correction factor f(T) = 1 + 0.02 x (25 - 32) = 0.86, final dosage Q = 107 x 0.86 = 92.02 mL, at this time the pH deviation value shows that the acidity deviates from the target value seriously, the gel structure of the syrup is at risk of being destroyed, so the current batch of syrup production is immediately stopped, the prepared syrup is detected offline, and the adjusting agent is added to the target range, thereby preventing the soft candy from being severely deformed and avoiding production loss.

[0078] Preferably, the model can combine real-time measurement data, accurately calculate the dosage of the acidity adjusting agent, and take reasonable adjustment strategies according to the deviation degree, thereby effectively ensuring the production quality of the soft candy, which has significant advantages compared with the traditional method.

[0079] S3: injecting the acidity adjusting agent into the soft candy syrup according to the injection amount of the acidity adjusting agent.

[0080] Specifically, the specific steps of injecting the acidity adjusting agent into the soft candy syrup according to the injection amount of the acidity adjusting agent are as follows:

[0081] A metering pump is connected to a liquid storage tank, and an atomizing nozzle or a flow guide pipe is arranged at the end of the pipeline to uniformly disperse the adjusting agent into the syrup.

[0082] The injection is performed when the syrup is cooked and cooled to a specific interval to avoid volatilization of acid components or premature denaturation of the colloid caused by high temperature.

[0083] The syrup stirring device is turned on during the injection to ensure that the adjusting agent and the syrup are fully mixed to prevent the formation of lumps due to excessive local acidity.

[0084] After the injection is completed, the stirring is maintained for 1-3 minutes, and the syrup viscosity sensor or manual sampling is observed to confirm that there is no stratification or local coagulation.

[0085] Within 5 minutes after the injection, the pH value and temperature data are continuously collected for 3 times, and the fluctuation range is required to be ≤±0.05 pH, and the temperature change is required to be ≤±1°C, otherwise the secondary adjustment is triggered.

[0086] If the metering pump stops during the injection, the standby pump is immediately switched to, the remaining amount is calibrated by manual addition, and the batch of syrup is marked as a “special treatment batch”, and the sampling detection frequency is increased subsequently.

[0087] It should be noted that the specific interval is determined according to the colloid characteristics.

[0088] S4: dynamically adjusting the acidity response model parameters according to the real-time monitoring data.

[0089] Preferably, according to the real-time monitoring data, the acidity response model parameters are dynamically adjusted, including the following steps:

[0090] According to the model calculation results according to the current model parameters, the acidity regulator is injected.

[0091] The indentation rate of the formed soft candy is detected in real time by a visual detection device.

[0092] The target indentation rate deviation value is calculated, and the specific formula is as follows:

[0093] ΔR = R r -R t ;

[0094] Where, ΔR is the target indentation rate deviation value; R r is the actual indentation rate, which is detected in real time by a visual detection device; R t is the target indentation rate, which is the ideal indentation rate preset according to the product quality standard.

[0095] Specifically, the specific situation of the target indentation rate deviation value is as follows: if the target indentation rate deviation value is less than the indentation threshold, it indicates that the current acidity adjustment strategy is effective, and further analysis is performed:

[0096] If the target indentation rate deviation value is close to the indentation threshold, the model parameters are locally fine-tuned: the temperature compensation coefficient is adjusted, and the influence of temperature on the effect of the acidity regulator is corrected according to the difference between the current temperature and the optimal action temperature.

[0097] If the target indentation rate deviation value is stable and close to 0, no parameter adjustment is performed, and real-time monitoring is maintained.

[0098] If the target indentation rate deviation value is greater than the indentation threshold, it indicates that the current acidity adjustment strategy is abnormal, the automatic adjustment is suspended, the global optimization of the model parameters is started, the temperature compensation coefficient is recalculated, the dosage proportion constant is corrected, the sensor accuracy is checked, the effectiveness of the acidity regulator is verified, the injection equipment is checked, and the automatic adjustment is restored after calibration. The indentation rate is detected whether it converges to the indentation threshold.

[0099] It should be noted that the dynamic adjustment of the indentation threshold is as follows:

[0100] If the actual indentation rate continues to approach the current indentation threshold, the threshold is tightened to promote quality improvement, and the adjustment steps are as follows:

[0101] The last 10 batches of data are retrieved to confirm whether the indentation rate is showing a sustained upward trend, the upper threshold is reduced from 1.5% to 1.4%, and the lower threshold remains unchanged at 0.5% to avoid excessive tightening leading to misjudgment. The temperature compensation coefficient is fine-tuned simultaneously to enhance the correction of temperature on pH measurement and prevent the indentation rate from rising due to temperature fluctuations.

[0102] Produce 2 batches according to the new threshold value. If the concave rate is stable at 0.6%-1.3%, confirm the threshold value adjustment; if it is out of range, roll back the threshold value and analyze whether it is a setting precision problem.

[0103] If the actual concave rate frequently breaks through the threshold value, relax the threshold value, investigate the systematic deviation, and adjust the steps:

[0104] Identify and exclude occasional abnormal batches caused by equipment failure, sensor drift, etc. Temporarily increase the upper threshold value from 1.5% to 2.0% to leave buffer space for process adjustment, avoid frequent triggering of global optimization leading to production interruption, check the error of acidity regulator injection amount, whether the stirring speed of syrup is stable, and prioritize repair of equipment problems. When the equipment failure is repaired and the concave rate of the last 5 batches is ≤1.5%, roll back the threshold value to the initial setting value and continue to monitor stability.

[0105] Continuous feedback loop: after each threshold value adjustment, record the adjustment reason, concave rate data before and after adjustment, and model parameter changes involved, form a "threshold value adjustment log", and provide reference for subsequent optimization.

[0106] It should be noted that when the following situations occur, skip the threshold value adjustment and directly trigger the emergency measures:

[0107] Sudden equipment failure: if the visual detection equipment misjudges the concave rate for 5 consecutive times, leading to threshold value calculation error, immediately switch to manual detection mode and recalibrate the equipment after repair.

[0108] Raw material batch abnormality: the viscosity of a batch of gelatin fluctuates more than 20%, causing abnormal increase of concave rate, so the raw material batch is isolated first instead of adjusting the threshold value.

[0109] Extreme environmental impact: the temperature in the production workshop rises by 10°C, exceeding the sensor's applicable range, triggering a temperature sensor failure alarm, suspending production and calibrating the environment, instead of modifying the threshold value.

[0110] For example, on a certain gummy production line, the intelligent monitoring system detects that the pH value of the gummy syrup shows a slow but continuous deviation trend after the equipment has been running for several hours; when the deviation duration reaches 3 hours and the change rate accelerates, the system automatically sends a secondary warning to the operator, prompting that the acidity adjustment may be abnormal. After receiving the alarm, the operator quickly checks the equipment and finds that the acidity regulator injection pump has a slight jam due to long-term operation, causing a decrease in injection accuracy. After timely repairing the pump body and recalibrating it, the injection amount is adjusted according to the acidity response model to avoid the quality accident of gummy gel structure failure and large-area concave caused by continuous acidity deviation, ensuring the forming quality and production stability of gummy products.

[0111] In the embodiments of the present application, the first threshold value and the second threshold value are determined through experimental tests: according to the corresponding relationship between the pH deviation and the gummy quality: when the pH deviation is small, the gummy quality has no obvious influence, and the first threshold value is determined; when the pH deviation further increases, the syrup solidification speed is abnormal, and slight concave is generated, and the second threshold value is determined; the concave threshold value is determined based on the product quality standard and statistical analysis, according to the quality requirement of the gummy, the maximum concave rate that can be accepted is determined, the concave rate data of a large number of qualified products in normal production is counted, and the distribution range and the fluctuation mean value are calculated.

[0112] In summary, the present application constructs an acidity response model based on the acquired pH value and temperature data, changes the previous way of adding acidity regulator by experience or simple fixed proportion, the model can accurately calculate the injection amount of the current acidity regulator, adapt to the dynamic changes in the gummy production process, realize the precise control of the gummy acidity, greatly improve the effect of acidity adjustment, use the sensor to collect data in real time and perform temperature compensation correction, implement the hierarchical dynamic adjustment strategy combined with the target pH deviation value and the concave rate feedback, realize the precise control of the acidity in the gummy production, based on the difference of the three threshold values, the concave risk caused by slight, moderate and severe acidity deviation is respectively controlled at a low level, the model parameters are dynamically adjusted through visual detection feedback, the adaptive calibration of long-term interference such as raw material fluctuation and equipment aging is realized, a data-driven, intelligent and efficient quality control solution for gummy and sugar-containing colloid food production is provided, and the production stability and economic benefit are significantly improved.

[0113] In embodiment 2, the present embodiment also provides an acidity adjustment system for reducing gummy concave, comprising: a data acquisition module for acquiring target parameter data in the gummy to be tested and performing preprocessing; a model construction module for constructing an acidity response model and acquiring the injection amount of the current acidity regulator; a slurry injection module for injecting the acidity regulator into the gummy slurry; and a dynamic adjustment module for dynamically adjusting the parameters of the acidity response model.

[0114] In embodiment 3, the present embodiment provides a computer device suitable for the case of the acidity adjustment method for reducing gummy concave, comprising: a memory and a processor; the memory is used for storing computer executable instructions, and the processor is used for executing the computer executable instructions to realize the acidity adjustment method for reducing gummy concave as proposed in the above embodiments.

[0115] The computer device can be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected by a system bus. The processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for running the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is configured to perform wired or wireless communication with an external terminal. The wireless communication can be achieved by WIFI, a carrier network, NFC (Near Field Communication) or other technologies. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer overlaid on the display screen, or a key, trackball or touchpad arranged on the shell of the computer device, or an external keyboard, touchpad or mouse, etc.

[0116] The embodiment also provides a storage medium having a computer program stored thereon, the program being executed by a processor to implement the method for reducing the acidity of gummy concave parts as described in the above embodiment. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as a static random access memory (SRAM), an electrically erasable programmable read-only memory (EEPROM), an erasable programmable read-only memory (EPROM), a programmable read-only memory (PROM), a read-only memory (ROM), a magnetic storage device, a flash memory, a magnetic disk or an optical disk.

[0117] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present application but not limit the present application. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced equivalently without departing from the spirit and scope of the technical solutions of the present application, and all of them should be covered in the scope of the claims of the present application.

Claims

1. A method for adjusting the acidity of soft candies to reduce concavity, characterized by: include: Obtaining target parameter data in the soft candy to be tested, and preprocessing the target parameter data; Based on the pre-processed target parameter data, an acidity response model is constructed and the injection amount of the acidity regulator is obtained; injecting the acidity regulator into the soft candy slurry according to the injection amount of the acidity regulator; Dynamically adjust the acidity response model parameters based on real-time monitoring data.

2. The method for adjusting the acidity of soft candies to reduce concavity according to claim 1, wherein: The target parameter data include pH value and temperature data in the soft candy to be tested; The acidity regulator is a composite regulator composed of an organic acid, an inorganic acid, a composite acidity regulator, a pH-responsive acidity regulator and a natural acidity regulator.

3. The method for adjusting the acidity of soft candies to reduce concavity according to claim 2, wherein: Constructing an acidity response model based on the pH and temperature data comprises the following steps: The measured pH value is corrected by the temperature compensation function to eliminate the influence of temperature on ion activity. The specific formula is as follows: pH a pH r +α·(TT s ); Among them, pH a is the corrected pH value after temperature compensation; pH r is the pH value measured by the sensor; T is the real-time temperature; T s is the reference temperature; α is the temperature compensation coefficient; The pH deviation value reflects the gap between the current acidity and the target. The specific formula is as follows: ΔpH=pH t -pH a ; Among them, ΔpH is the target pH deviation value, which is the ideal pH value preset according to the soft candy formula; pH t is the target pH value; pH a is the corrected pH value after temperature compensation; The basic dosage of acidity regulator is calculated by considering the quality of soft candy slurry, effective acid concentration and deviation sensitivity. The specific formula is as follows: Q0=k·m·ΔpH; Where Q0 is the basic dosage of acidity regulator; k is the proportional constant of acidity regulator dosage; m is the mass of syrup to be adjusted; ΔpH is the target pH deviation value; By introducing the temperature correction factor, the pH value measured at different temperatures is corrected. The specific formula is as follows: f(T)=1+β(T-T o ); Where f(T) is the correction factor of temperature on the effect of acidity regulator; β is the temperature sensitivity coefficient; T is the real-time temperature; T o The optimal temperature for the acidity regulator to work; An acidity response model was constructed based on the basic dosage of acidity regulator and the temperature correction factor.

4. The method for adjusting the acidity of soft candies to reduce concavity according to claim 3, wherein: The specific formula of the acidity response model is as follows: Q=k·m·(pH t -(pH r +α(T-T s )))·(1+β(T-T o )); Where Q is the injection amount of acidity regulator; k is the proportional constant of acidity regulator dosage; m is the mass of syrup to be adjusted; pH t is the target pH value; pH r is the pH value measured by the sensor; α is the temperature compensation coefficient; T is the real-time temperature; T s is the reference temperature; β is the temperature sensitivity coefficient; T o This is the optimal temperature for the acidity regulator to work.

5. The method for adjusting the acidity of soft candies to reduce concavity according to claim 4, wherein: The specific conditions of the target pH deviation value are as follows: When the target pH deviation value is less than the first-level threshold, it indicates that the current acidity is close to the target value and is a slight fluctuation. The acidity adjustment strategy is generated according to the basic dosage calculated by the acidity response model and the acidity regulator is injected; When the target pH deviation value is greater than the first threshold and less than the second threshold, it indicates that the acidity deviates from the target value, which will cause abnormal syrup solidification speed and the risk of slight concavity. First, inject 50% of the calculated amount, and then add the remaining amount after an interval of 10 seconds based on real-time feedback; When the target pH deviation value is greater than the secondary threshold, it indicates that the acidity deviates seriously from the target value and the syrup gel structure is destroyed, which will cause large-scale depression, deformation or adhesion of the soft candy. Immediately stop the production of the current batch of syrup, conduct offline testing on the prepared syrup, add acidity regulator to the target range, and check for sensor failure, injection pipeline blockage or temperature control system abnormality.

6. The method for adjusting the acidity of soft candies to reduce concavity according to claim 1, wherein: The method of dynamically adjusting the acidity response model parameters according to the real-time monitoring data comprises the following steps: Inject acidity regulator according to current model parameters and model calculation results; Use visual inspection equipment to detect the concavity rate of soft candies in real time after molding; Calculate the target sag rate deviation value. The specific formula is as follows: ΔR=R r -R t ; Among them, ΔR is the target sag rate deviation value; R r is the actual concavity rate; R t is the target sag rate.

7. The method for adjusting the acidity of soft candies to reduce concavity according to claim 6, wherein: The specific situation of the target sag rate deviation value is as follows: If the target concavity rate deviation is less than the concavity threshold, it indicates that the current acidity adjustment strategy is effective and further analysis is performed: If the target depression rate deviation is close to the depression threshold, the model parameters are locally fine-tuned, the temperature compensation coefficient is adjusted, and the effect of temperature on the effect of the acidity regulator is corrected according to the difference between the current temperature and the optimal working temperature; If the target sag rate deviation value is stable and close to 0, no parameter adjustment is performed and real-time monitoring is maintained; If the target sag rate deviation is greater than the sag threshold, it indicates that the current acidity adjustment strategy is abnormal. Automatic adjustment is suspended and global optimization of model parameters is initiated: recalculating the temperature compensation coefficient, correcting the acidity regulator dosage proportional constant, checking sensor accuracy, verifying the effectiveness of the acidity regulator, checking the injection equipment, resuming automatic adjustment after calibration, and checking whether the sag rate converges to the threshold.

8. An acidity adjustment system for reducing soft candy concavity, based on the acidity adjustment method for reducing soft candy concavity according to any one of claims 1 to 7, characterized in that: include, The data acquisition module is used to obtain the target parameter data in the soft candy to be tested and perform preprocessing; A model building module is used to build an acidity response model and obtain the current injection amount of the acidity regulator; A slurry injection module is used to inject an acidity regulator into the soft candy slurry; A dynamic adjustment module is used to dynamically adjust the acidity response model parameters.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the acidity adjustment method for reducing the depression of soft candy according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the acidity adjustment method for reducing the depression of soft candy according to any one of claims 1 to 7 are implemented.

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