Biscuit dough processing information monitoring management system

Abstract

The invention relates to the technical field of dough processing quality monitoring, in particular to a biscuit dough processing information monitoring management system.According to the biscuit dough processing information monitoring management system, the quality of dough is preliminarily estimated according to corresponding parameters in the dough preparation process in big data, then the shelf life of the current batch of dough is predicted, and the more the water content of the dough is, the more likely the dough goes bad; the better the elasticity, the better the quality and the longer the shelf life of the dough are, the actual quality of the dough is analyzed by periodically detecting the moisture content of the prepared dough and the elasticity of the dough, the control precision aiming at the actual situation of the dough is improved, the longer the storage time of the prepared dough is, the more variables in the storage process are, and the better the quality is. For example, the environment temperature changes in the dough taking process, so that the dough is more prone to deterioration, secondary analysis is conducted on the pre-estimation condition of the quality guarantee duration of the dough according to the storage duration of the dough, and misjudgment caused by the environment changes in the dough storage process is avoided.

Description

Technical Field

[0001] The invention relates to the technical field of dough processing quality monitoring, and in particular to a biscuit dough processing information monitoring and management system. Background Art

[0002] Dough is an important part of preparing biscuits, and the quality of dough has a great influence on the quality of the biscuits. In actual use, the prepared dough is generally more than the number of biscuits prepared, and the excess dough will be stored first. The existing technology collects the spectral information of the dough during the fermentation process through a near-infrared spectrometer, and establishes a monitoring model for the dough based on the spectral information, thereby realizing online real-time monitoring of dough fermentation. However, it does not take into account the influence of different flours, the storage environment of flour, and the storage environment of the prepared dough on the quality of the dough, thereby affecting the quality of the biscuits.

[0003] Chinese patent publication number: CN111259970A discloses an intelligent monitoring method for dough fermentation status during steamed bread processing, the steps are: using a near-infrared spectrometer to collect spectral information of the dough during fermentation, Qavizky-Golay convolution smoothing method to reduce noise on the collected spectral information, and then using the CARQ-Qi-PLQ algorithm to screen all collected spectral variables, and after 50 times of five-fold interactive optimization model, the optimal characteristic variables that can reflect the changes in dough characteristics during fermentation are screened out, and finally, these variables are used to establish a QVM monitoring model for dough fermentation status. This method can realize online monitoring, and is fast and accurate, which is conducive to the online real-time monitoring of dough fermentation in the industrial production of steamed bread. It can be widely used in steamed bread and bread production lines.

[0004] However, the prior art still has the following problems:

[0005] The effects of different flours, the storage environment of the flour, and the storage environment of the dough on the quality of the dough, which in turn affects the quality of the biscuits, are not considered. Summary of the invention

[0006] To this end, the present invention provides a biscuit dough processing information monitoring and management system to overcome the problem in the prior art that different flours, the storage environment of the flour, and the storage environment of the prepared dough have no consideration of the impact on the quality of the dough, thereby affecting the quality of the prepared biscuits.

[0007] To achieve the above-mentioned purpose, the present invention provides a biscuit dough processing information monitoring and management system. It includes:

[0008] A dough preparation module is used to mix the flour raw materials in a predetermined ratio to prepare dough;

[0009] A data acquisition module connected to the dough preparation module for acquiring parameters in the dough preparation process, the parameters including raw material storage time, raw material storage environment parameters, raw material mixing time and dough preparation environment parameters;

[0010] An estimation module, which is connected to the data acquisition module and is used to acquire parameters in the dough preparation process from the big data, and determine the estimated shelf life of the dough prepared in the current batch according to the acquired parameters;

[0011] A monitoring module, which is connected to the dough preparation module and is used to obtain a dough sample of the current batch and monitor various parameters of the dough sample to determine the actual shelf life of the dough batch;

[0012] A data analysis module is connected to the dough preparation module, the data acquisition module, the estimation module and the monitoring module, and is used to analyze whether the estimated shelf life is qualified based on the estimated shelf life and the actual shelf life, to make a secondary judgment on whether the estimated shelf life of the current batch of dough is qualified based on the storage time of the dough, to calculate dough quality characterization parameters based on various parameters of the dough sample, and to analyze the reasons for unqualified estimation based on the dough quality characterization parameters.

[0013] Furthermore, the data analysis module analyzes whether the estimated shelf life is qualified based on the estimated shelf life and the actual shelf life, including:

[0014] Calculate the difference between the estimated shelf life and the actual shelf life.

[0015] Based on the time difference analysis, the estimated shelf life of the current batch of dough is determined to be qualified.

[0016] Furthermore, the data analysis module analyzes whether the estimated shelf life of the dough of the current batch is qualified based on the time difference, including:

[0017] If the time difference is less than or equal to a first preset time difference standard threshold, the data analysis module determines that the estimated shelf life of the current batch of dough is qualified;

[0018] If the time difference is greater than the first preset time difference standard threshold and less than or equal to the second preset time difference standard threshold, the data analysis module determines whether the estimated shelf life of the current batch of dough based on the storage time of the dough is qualified for secondary determination;

[0019] If the time difference is greater than the second preset time difference standard threshold, the data analysis module determines that the estimated shelf life of the current batch of dough is unqualified, and analyzes the reasons for the unqualified estimate based on the dough quality characterization parameters.

[0020] Furthermore, the data analysis module performs a secondary determination on whether the estimated shelf life of the current batch of dough is qualified based on the storage time of the dough, including:

[0021] If the storage time is less than a preset storage time standard threshold, the data analysis module determines that the estimated shelf life of the current batch of dough is unqualified, and analyzes the reasons for the unqualified estimation based on the dough quality characterization parameters;

[0022] If the storage time is greater than or equal to the preset storage time standard threshold, the data analysis module determines to correct the detection cycle of the monitoring module for the dough based on the shelf life.

[0023] Further, the data analysis module modifies the detection cycle of the monitoring module, wherein:

[0024] The reduction amount of the detection period is proportional to the storage time.

[0025] Furthermore, the data analysis module calculates dough quality characterization parameters, including:

[0026] The monitoring module periodically detects the moisture content and elasticity of the dough sample.

[0027] Calculate the ratio of the preset moisture content standard threshold to the moisture content to obtain the first moisture content feature,

[0028] Calculate the ratio of elasticity to the preset elasticity standard threshold to obtain the second elasticity feature,

[0029] The dough quality characterization parameter is obtained by weighted summing the first moisture content characteristic and the second elasticity characteristic.

[0030] Furthermore, the data analysis module estimates the reasons for failure based on dough quality characterization parameter analysis, including:

[0031] Draw the time domain curve of dough quality characterization parameters based on the calculated dough quality characterization parameters.

[0032] Calculate the variance of dough quality characterization parameters at each time point,

[0033] If the variance is greater than or equal to a preset variance standard threshold, the data analysis module determines that the reason for the estimated failure is that the storage environment is unqualified;

[0034] If the variance is less than the preset variance standard threshold, the data analysis module determines that the reason for the unqualified estimate is that the prediction model used to predict the shelf life of the dough is unqualified.

[0035] Further, the data analysis module increases the ambient temperature of dough storage based on the variance when the storage environment is unqualified, wherein:

[0036] The increase in the ambient temperature during dough storage is positively correlated with the variance.

[0037] Furthermore, the data analysis module determines the prediction result based on the variance reduction prediction model when the prediction model is unqualified, wherein:

[0038] The amount of reduction in the prediction results of the prediction model is positively correlated with the variance.

[0039] Furthermore, the shelf life of the dough is the time period from when the dough is prepared to when the dough data is monitored.

[0040] Compared with the prior art, the beneficial effect of the present invention lies in that the quality of the dough is preliminarily estimated according to the corresponding parameters in the dough preparation process in the big data, and then the shelf life of the dough of the current batch is predicted. The more water content of the dough, the easier it is to deteriorate. The better the elasticity of the dough, the better the quality and the longer the shelf life. The actual quality of the dough is analyzed by periodically detecting the water content of the prepared dough and the elasticity of the dough, thereby improving the control accuracy for the actual situation of the dough. The longer the storage time of the dough after preparation, the more variables there are in the storage process. For example, the ambient temperature will change during the dough taking process, so the dough is more likely to deteriorate. The estimated shelf life of the dough is secondary analyzed according to the storage time of the dough to avoid misjudgment due to environmental changes during the storage of the dough.

[0041] Furthermore, in the present invention, the better the elasticity of the dough, the better the strength of the network structure inside the dough, and the less likely the dough is to deteriorate. The present invention comprehensively analyzes the quality of the dough based on the moisture content of the dough and the elasticity of the dough, thereby improving the accuracy of analyzing the quality of the dough. During the storage of the dough, the moisture will gradually evaporate. The faster the moisture content of the dough changes, the faster the temperature in the storage environment changes, and the more likely the dough is to deteriorate. The present invention analyzes the problems in the dough storage process based on the variance of the moisture content in the dough, thereby improving the control accuracy of the dough storage process, and adjusts the dough storage environment temperature according to the analysis results to extend the shelf life of the dough, and corrects the estimated time of the estimation model, thereby improving the estimation accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a structural block diagram of the biscuit dough processing information monitoring and management system of the present invention;

[0043] Figure 2 A flow chart for analyzing whether the estimated shelf life of the current batch of dough is qualified;

[0044] Figure 3 A flow chart for estimating whether the secondary determination is qualified;

[0045] Figure 4 This is a decision flow chart for analyzing the causes of estimated non-conformance. DETAILED DESCRIPTION

[0046] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0047] It should be pointed out that the data in this embodiment are obtained by comprehensive analysis and evaluation of the historical data of the system of the present invention in the six months before this determination and the corresponding historical determination results. Before this detection, the system of the present invention comprehensively determines the values ​​of the preset parameter standards for this determination based on the evaluation values ​​of the 37,383 retrieval results detected cumulatively in the first three months. It can be understood by those skilled in the art that the system of the present invention can determine the single parameter mentioned above by selecting the value with the highest proportion as the preset standard parameter according to the data distribution, using weighted summation to use the obtained value as the preset standard parameter, substituting each historical data into a specific formula and using the value obtained by the formula as the preset standard parameter or other selection methods, as long as the system of the present invention can clearly define the different specific situations in the single determination process through the obtained values.

[0048] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0049] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0050] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0051] See also Figure 1 As shown, it is a structural block diagram of the biscuit dough processing information monitoring and management system of the present invention.

[0052] The embodiment of the present invention provides a biscuit dough processing information monitoring and management system, comprising:

[0053] A dough preparation module is used to mix the flour raw materials in a predetermined ratio to prepare dough;

[0054] A data acquisition module connected to the dough preparation module for acquiring parameters in the dough preparation process, the parameters including raw material storage time, raw material storage environment parameters, raw material mixing time and dough preparation environment parameters;

[0055] An estimation module, which is connected to the data acquisition module and is used to acquire parameters in the dough preparation process from the big data, and determine the estimated shelf life of the dough prepared in the current batch according to the acquired parameters;

[0056] A monitoring module, which is connected to the dough preparation module and is used to obtain a dough sample of the current batch and monitor various parameters of the dough sample to determine the actual shelf life of the dough batch;

[0057] A data analysis module is connected to the dough preparation module, the data acquisition module, the estimation module and the monitoring module, and is used to analyze whether the estimated shelf life is qualified based on the estimated shelf life and the actual shelf life, to make a secondary judgment on whether the estimated shelf life of the current batch of dough is qualified based on the storage time of the dough, to calculate dough quality characterization parameters based on various parameters of the dough sample, and to analyze the reasons for unqualified estimation based on the dough quality characterization parameters.

[0058] Specifically, the present invention does not limit the specific structure of the dough preparation module, and a dough mixer or a blender may be used, which belongs to the prior art and will not be described in detail here.

[0059] Specifically, there is no limitation on the specific structure of the estimation module and the data analysis module, which may be composed of logic components, including a field programmable processor, a computer, and a microprocessor in the computer.

[0060] Specifically, the data analysis module analyzes whether the estimated shelf life is qualified according to the estimated shelf life and the actual shelf life, including:

[0061] Calculate the difference between the estimated shelf life and the actual shelf life.

[0062] Based on the time difference analysis, the estimated shelf life of the current batch of dough is determined to be qualified.

[0063] See also Figure 2As shown, it is a flow chart for analyzing whether the estimated shelf life of the current batch of dough is qualified.

[0064] Specifically, the data analysis module analyzes whether the estimated shelf life of the dough of the current batch is qualified based on the time difference, including:

[0065] If the time difference is less than or equal to a first preset time difference standard threshold, the data analysis module determines that the estimated shelf life of the current batch of dough is qualified;

[0066] If the time difference is greater than the first preset time difference standard threshold and less than or equal to the second preset time difference standard threshold, the data analysis module determines whether the estimated shelf life of the current batch of dough based on the storage time of the dough is qualified for secondary determination;

[0067] If the time difference is greater than the second preset time difference standard threshold, the data analysis module determines that the estimated shelf life of the current batch of dough is unqualified, and analyzes the reasons for the unqualified estimate based on the dough quality characterization parameters.

[0068] Specifically, in this embodiment, the first preset duration difference standard threshold is selected in the interval [24h, 48h], and the second preset duration difference standard threshold is selected in the interval [72h, 96h].

[0069] See also Figure 3 As shown, it is a flow chart for determining whether the secondary estimation is qualified.

[0070] Specifically, the data analysis module performs a secondary determination on whether the estimated shelf life of the current batch of dough is qualified based on the storage time of the dough, including:

[0071] If the storage time is less than a preset storage time standard threshold, the data analysis module determines that the estimated shelf life of the current batch of dough is unqualified, and analyzes the reasons for the unqualified estimation based on the dough quality characterization parameters;

[0072] If the storage time is greater than or equal to the preset storage time standard threshold, the data analysis module determines to correct the detection cycle of the monitoring module for the dough based on the shelf life.

[0073] Specifically, in this embodiment, the preset storage time standard threshold value Q0 is obtained in advance, and the storage time of several different doughs from preparation to spoilage is recorded, and the average storage time △Q is solved, and Q0=α×△Q is set, α represents the first accuracy coefficient, 0.7<α<0.85.

[0074] Specifically, the data analysis module modifies the detection cycle of the monitoring module, wherein:

[0075] The reduction amount of the detection period is proportional to the storage time.

[0076] In this embodiment, optionally,

[0077] The storage time Q is compared with a preset first storage time comparison threshold △Q1 and a second preset storage time comparison threshold Q2,

[0078] If Q≤△Q1, reduce the first detection time T1 and set T1=0.2×T0;

[0079] If △Q1<Q≤△Q2, then reduce the second detection time T2 and set T2=0.25×T0;

[0080] If △Q2<Q, then reduce the third detection time T3, and set T3=0.3×T0;

[0081] Wherein T0 is the initial detection interval duration, △Q1=1.1×Q0, △Q2=1.3×Q0, and Q0 represents the preset storage duration standard threshold.

[0082] Specifically, the data analysis module calculates dough quality characterization parameters, including:

[0083] The monitoring module periodically detects the moisture content and elasticity of the dough sample.

[0084] Calculate the ratio of the preset moisture content standard threshold to the moisture content to obtain the first moisture content feature,

[0085] Calculate the ratio of elasticity to the preset elasticity standard threshold to obtain the second elasticity feature,

[0086] The dough quality characterization parameter is obtained by weighted summing the first moisture content characteristic and the second elasticity characteristic.

[0087] Specifically, the elasticity of the dough is the rebound distance of the dough sample after the dough sample is pressed with a predetermined pressure.

[0088] See also Figure 4 As shown, it is a decision flow chart for analyzing and estimating the reasons for non-conformity.

[0089] Specifically, the data analysis module estimates the reasons for failure based on dough quality characterization parameters, including:

[0090] Draw the time domain curve of dough quality characterization parameters based on the calculated dough quality characterization parameters.

[0091] Calculate the variance of dough quality characterization parameters at each time point,

[0092] If the variance is greater than or equal to a preset variance standard threshold, the data analysis module determines that the reason for the estimated failure is that the storage environment is unqualified;

[0093] If the variance is less than the preset variance standard threshold, the data analysis module determines that the reason for the unqualified estimate is that the prediction model used to predict the shelf life of the dough is unqualified.

[0094] Specifically, in this embodiment, the preset variance standard threshold D0 is obtained by pre-measurement, and the quality characterization parameters of several doughs in a predetermined period are calculated and recorded respectively, and the variance of the quality characterization parameters of each dough is calculated respectively, and the variance mean △D is solved, and D0=β×△D is set, where β represents the second precision coefficient, 0.68<β<0.82.

[0095] Specifically, the data analysis module increases the ambient temperature of dough storage based on the variance when the storage environment is unqualified, wherein:

[0096] The increase in the ambient temperature during dough storage is positively correlated with the variance.

[0097] In this embodiment, optionally,

[0098] The variance D is compared with the first preset variance comparison threshold △D1 and the second preset variance comparison threshold D2,

[0099] If D≤△D1, increase the first ambient temperature A1 and set A1=0.2×A0;

[0100] If △D1<D≤△D2, then increase the second ambient temperature A2 and set A2=0.25×A0;

[0101] If △D2<D, then increase the third ambient temperature A3 and set A3=0.3×A0;

[0102] Where T0 is the initial detection interval duration, △D1=1.2×D0, △D2=1.3×D0, and D0 represents the preset variance standard threshold.

[0103] Specifically, the data analysis module determines the prediction result based on the variance reduction prediction model when the prediction model is unqualified, wherein:

[0104] The amount of reduction in the prediction results of the prediction model is positively correlated with the variance.

[0105] In this embodiment, optionally,

[0106] The variance D is compared with the first preset variance comparison threshold △D1 and the second preset variance comparison threshold D2,

[0107] If D≤△D1, then reduce the first prediction result C1 and set C1=0.2×C0;

[0108] If △D1<D≤△D2, then reduce the second prediction result C2 and set C2=0.3×C0;

[0109] If △D2<D, then reduce the third prediction result C3, and set C3=0.35×C0;

[0110] Where C0 is the initial prediction result.

[0111] Specifically, the shelf life of the dough is the time period from when the dough is prepared to when the dough data is monitored.

[0112] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0113] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A biscuit dough processing information monitoring and management system, characterized in that: include: A dough preparation module is used to mix the flour raw materials in a predetermined ratio to prepare dough; A data acquisition module connected to the dough preparation module for acquiring parameters in the dough preparation process, the parameters including raw material storage time, raw material storage environment parameters, raw material mixing time and dough preparation environment parameters; An estimation module, which is connected to the data acquisition module and is used to acquire parameters in the dough preparation process from the big data, and determine the estimated shelf life of the dough prepared in the current batch according to the acquired parameters; A monitoring module, which is connected to the dough preparation module and is used to obtain a dough sample of the current batch and monitor various parameters of the dough sample to determine the actual shelf life of the dough batch; A data analysis module is connected to the dough preparation module, the data acquisition module, the estimation module and the monitoring module, and is used to analyze whether the estimated shelf life is qualified based on the estimated shelf life and the actual shelf life, to make a secondary judgment on whether the estimated shelf life of the current batch of dough is qualified based on the storage time of the dough, to calculate dough quality characterization parameters based on various parameters of the dough sample, and to analyze the reasons for unqualified estimation based on the dough quality characterization parameters.

2. The biscuit dough processing information monitoring and management system according to claim 1, characterized in that: The data analysis module analyzes whether the estimated shelf life is qualified according to the estimated shelf life and the actual shelf life, including: Calculate the difference between the estimated shelf life and the actual shelf life. Based on the time difference analysis, the estimated shelf life of the current batch of dough is determined to be qualified.

3. The biscuit dough processing information monitoring and management system according to claim 2, characterized in that: The data analysis module analyzes whether the estimated shelf life of the dough of the current batch is qualified based on the time difference, including: If the time difference is less than or equal to a first preset time difference standard threshold, the data analysis module determines that the estimated shelf life of the current batch of dough is qualified; If the time difference is greater than the first preset time difference standard threshold and less than or equal to the second preset time difference standard threshold, the data analysis module determines whether the estimated shelf life of the current batch of dough based on the storage time of the dough is qualified for secondary determination; If the time difference is greater than the second preset time difference standard threshold, the data analysis module determines that the estimated shelf life of the current batch of dough is unqualified, and analyzes the reasons for the unqualified estimate based on the dough quality characterization parameters.

4. The biscuit dough processing information monitoring and management system according to claim 1, characterized in that: The data analysis module performs a secondary determination on whether the estimated shelf life of the current batch of dough is qualified based on the storage time of the dough, including: If the storage time is less than a preset storage time standard threshold, the data analysis module determines that the estimated shelf life of the current batch of dough is unqualified, and analyzes the reasons for the unqualified estimation based on the dough quality characterization parameters; If the storage time is greater than or equal to the preset storage time standard threshold, the data analysis module determines to correct the detection cycle of the monitoring module for the dough based on the shelf life.

5. The biscuit dough processing information monitoring and management system according to claim 4, characterized in that: The data analysis module modifies the detection cycle of the monitoring module, wherein: The reduction amount of the detection period is proportional to the storage time.

6. The biscuit dough processing information monitoring and management system according to claim 4, characterized in that: The data analysis module calculates dough quality characterization parameters, including: The monitoring module periodically detects the moisture content and elasticity of the dough sample. Calculate the ratio of the preset moisture content standard threshold to the moisture content to obtain the first moisture content feature, Calculate the ratio of elasticity to the preset elasticity standard threshold to obtain the second elasticity feature, The dough quality characterization parameter is obtained by weighted summing the first moisture content characteristic and the second elasticity characteristic.

7. The biscuit dough processing information monitoring and management system according to claim 1, characterized in that: The data analysis module estimates the reasons for failure based on dough quality characterization parameter analysis, including: Draw the time domain curve of dough quality characterization parameters based on the calculated dough quality characterization parameters. Calculate the variance of dough quality characterization parameters at each time point, If the variance is greater than or equal to a preset variance standard threshold, the data analysis module determines that the reason for the estimated failure is that the storage environment is unqualified; If the variance is less than the preset variance standard threshold, the data analysis module determines that the reason for the unqualified estimate is that the prediction model used to predict the shelf life of the dough is unqualified.

8. The biscuit dough processing information monitoring and management system according to claim 7, characterized in that: The data analysis module increases the ambient temperature of dough storage based on the variance when the storage environment is unqualified, wherein: The increase in the ambient temperature during dough storage is positively correlated with the variance.

9. The biscuit dough processing information monitoring and management system according to claim 1, characterized in that: The data analysis module determines the prediction result based on the variance reduction prediction model when the prediction model is unqualified, wherein: The amount of reduction in the prediction results of the prediction model is positively correlated with the variance.

10. The biscuit dough processing information monitoring and management system according to claim 1, characterized in that: The shelf life of the dough is the time period from when the dough is prepared to when the dough data is monitored.

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