Intelligent fermentation monitoring method and system for low-sugar and low-fat bread

Abstract

The invention relates to the technical field of fermentation gas monitoring, in particular to an intelligent fermentation monitoring method and system for low-sugar and low-fat bread. The method comprises the following steps: firstly, acquiring carbon dioxide fermentation measurement at the current moment according to the change condition of a local carbon dioxide concentration value along with time at the current moment; according to the gas saturation amount of the by-product in the preset reference range at the current moment, obtaining the local negative influence measurement of the by-product at the current moment; integrating the local negative influence measurement of all byproducts at the current moment to obtain the overall negative influence measurement at the current moment; and further obtaining the overall fermentation effect measurement at the current moment. And controlling the fermentation equipment based on the overall fermentation effect measurement at the current moment. According to the method, the fermentation effect at the current moment is analyzed more accurately by fully considering the expression condition of the fermentation gas, so that the fermentation stopping process of the fermentation equipment is reasonably controlled, and the quality of the low-sugar and low-fat bread is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of fermentation gas monitoring, and in particular to an intelligent fermentation monitoring method and system for low-sugar and low-fat bread. Background Art

[0002] Low-sugar and low-fat bread is a type of bread that focuses on healthy eating. It is characterized by significantly reduced sugar and fat content to meet consumers' demand for healthy food. Fermentation is a key step in the production process of low-sugar and low-fat bread. During the bread fermentation process, yeast will decompose the limited sugar in the dough to produce carbon dioxide and other by-products. The appropriate fermentation time can make the dough fully expand and form a soft and porous structure, thereby improving the taste and texture of the bread. If the fermentation time is too short, the dough often cannot fully expand, resulting in a tight taste of the bread; if the fermentation time is too long, the dough will often over-ferment, resulting in a sour taste of the bread.

[0003] In order to ensure that low-sugar and low-fat bread achieves the ideal fermentation effect, it is particularly important to control the fermentation equipment to stop fermentation in time. The existing technology compares the carbon dioxide concentration value obtained by real-time monitoring with the preset threshold value to evaluate the fermentation effect and decide whether to control the fermentation equipment to stop fermentation. However, when using the existing technology for fermentation control, due to the low sugar content of low-sugar and low-fat bread, the amount of carbon dioxide produced by yeast when decomposing sugar may be relatively small. Therefore, relying solely on carbon dioxide concentration as the basis for evaluating the fermentation effect ignores the by-products produced during the fermentation process and the dynamic change characteristics of carbon dioxide concentration, making the evaluation of the fermentation effect inaccurate, and it is difficult to ensure the rationality of controlling the fermentation equipment to stop fermentation, resulting in poor quality of low-sugar and low-fat bread. Summary of the invention

[0004] In order to solve the technical problem that it is difficult to reasonably control the fermentation equipment to stop fermentation in the prior art, the purpose of the present invention is to provide an intelligent fermentation monitoring method and system for low-sugar and low-fat bread. The technical solution adopted is as follows: A fermentation intelligent monitoring method for low-sugar and low-fat bread, the method comprising: Acquire a fermentation gas data set of a bread fermentation monitoring process; the fermentation gas data set includes a carbon dioxide concentration value at each sampling time and a gas concentration value of each byproduct; According to the change of the local carbon dioxide concentration value at the current moment with time, the carbon dioxide fermentation measurement at the current moment is obtained; according to the numerical value and numerical change of the gas concentration value of the by-product at the sampling moment, the gas saturation measurement of the by-product at the sampling moment is obtained; according to the gas saturation measurement of the by-product within the preset reference range at the current moment, the local negative impact measurement of the by-product at the current moment is obtained; the overall negative impact measurement at the current moment is obtained by combining the local negative impact measurements of all the by-products at the current moment; based on the carbon dioxide fermentation measurement at the current moment and the overall negative impact measurement, the overall fermentation effect measurement at the current moment is obtained; Based on the overall fermentation effect measurement at the current moment, the fermentation equipment is controlled.

[0005] Furthermore, the method for obtaining the carbon dioxide fermentation measurement includes: According to the numerical value of the carbon dioxide concentration value at the current moment and its numerical change, obtaining the carbon dioxide saturation state indicator at the current moment; According to the change stability of the carbon dioxide saturation state indicator in the preset local range at the current moment, obtaining the carbon dioxide saturation real indicator at the current moment; The carbon dioxide saturation state indicator and the carbon dioxide saturation real indicator are forwardly integrated to obtain the carbon dioxide fermentation measurement at the current moment.

[0006] Furthermore, the method for obtaining the carbon dioxide saturation state index includes: The absolute value of the second-order difference value of the carbon dioxide concentration value at the current moment is calculated to obtain the carbon dioxide rate change value at the current moment; the sum of the carbon dioxide rate change value at the current moment and the preset denominator adjustment value is calculated, and the ratio of the carbon dioxide concentration value at the current moment to the sum is calculated to obtain the carbon dioxide saturation state index at the current moment.

[0007] Furthermore, the method for obtaining the true carbon dioxide saturation index includes: Each sampling moment in the preset local range of the current moment is taken as each local moment of the current moment; the differential value of the carbon dioxide saturation state index at each local moment is calculated to obtain the saturation state change index at each local moment; the variance of the saturation state change index at all the local moments is calculated and negative correlation mapping is performed to obtain the true carbon dioxide saturation index at the current moment.

[0008] Furthermore, the method for obtaining the gas saturation measurement includes: For any by-product, the absolute value of the second-order difference value corresponding to the gas concentration value of the by-product at the sampling time is calculated and negative correlation mapping is performed to obtain the negative correlation mapping result; the product of the negative correlation mapping result and the gas concentration value of the by-product at the sampling time is calculated and normalized to obtain the gas saturation measurement of the by-product at the sampling time.

[0009] Furthermore, the method for obtaining the local negative impact metric includes: For any by-product, within the preset reference range at the current moment, each sampling moment at which the gas saturation value is greater than the preset saturation threshold is taken as the saturation moment; and the saturation moments exceeding the preset number of consecutive moments are taken as the saturation time period; According to the length of the saturation time period and the corresponding gas saturation measurement, obtaining a first negative impact indicator of the byproduct in the saturation time period; According to the time interval between the adjacent saturation time periods in time sequence and the time interval between the saturation time period and the current moment, obtaining a second negative impact indicator of the byproduct in the saturation time period; The first negative impact indicator and the second negative impact indicator of the by-product in all saturation time periods are forwardly integrated to obtain a local negative impact measure of the by-product at the current moment.

[0010] Furthermore, the method for obtaining the first negative impact indicator includes: The length of the saturation time period is used as the first saturation parameter of the saturation time period; the maximum gas saturation measurement corresponding to all gas saturation measurements at all sampling moments in the saturation time period is used as the second saturation parameter of the saturation time period; the product of the first saturation parameter and the second saturation parameter is calculated as the first negative impact indicator of the by-product in the saturation time period.

[0011] Furthermore, the method for obtaining the second negative impact indicator includes: The time interval between each saturation time period and the previous saturation time period in the time series dimension is taken as the first interval of the saturation time; the time interval between the last sampling moment of the saturation time period and the current moment is taken as the second interval; the product of the first interval and the second interval is calculated and negative correlation mapping is performed as the second negative impact indicator of the by-product in the saturation time period.

[0012] Furthermore, the method for obtaining the overall fermentation effect measurement includes: The difference between the carbon dioxide fermentation metric at the current moment and the overall negative impact metric is calculated and normalized to obtain the overall fermentation effect metric at the current moment.

[0013] The present invention proposes an intelligent fermentation monitoring system for low-sugar and low-fat bread, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the intelligent fermentation monitoring method for low-sugar and low-fat bread are implemented.

[0014] The present invention has the following beneficial effects: In order to evaluate the fermentation effect at the current moment, a carbon dioxide fermentation metric is constructed to accurately reflect the saturation degree of carbon dioxide; the gas saturation metric is used to reflect the saturation degree of the by-products at the current moment, and then the local negative impact metric of the by-products is constructed to reflect the negative impact of the by-products on the current fermentation. During the fermentation process, multiple by-products are produced at the same time and have a negative impact on the current fermentation. The local negative impact metrics of all by-products at the current moment are combined to obtain an overall negative impact metric. The overall negative impact metric reflects the comprehensive negative impact of all by-products on fermentation at the current moment. The carbon dioxide fermentation metric at the current moment and the overall negative impact metric are combined to obtain the overall fermentation effect metric at the current moment. The overall fermentation effect metric can more accurately reflect the fermentation effect at the current moment, thereby realizing the reasonable control of the fermentation equipment to stop fermentation and ensuring the fermentation effect of low-sugar and low-fat bread. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 A flow chart of an intelligent fermentation monitoring method for low-sugar and low-fat bread provided by one embodiment of the present invention; Figure 2 A flow chart of a method for obtaining carbon dioxide fermentation metrics provided by one embodiment of the present invention; Figure 3 A flow chart of a method for obtaining a local negative impact metric provided by an embodiment of the present invention; Figure 4 A structural diagram of an intelligent fermentation monitoring system for low-sugar and low-fat bread provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation method, structure, characteristics and effects of the intelligent fermentation monitoring method and system for low-sugar and low-fat bread proposed by the present invention are described in detail below in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0018] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0019] The specific scheme of the intelligent fermentation monitoring method and system for low-sugar and low-fat bread provided by the present invention is described in detail below with reference to the accompanying drawings.

[0020] The embodiment of the present invention provides a fermentation intelligent monitoring method and system for low-sugar and low-fat bread. Figure 1 , which shows a flow chart of an intelligent fermentation monitoring method for low-sugar and low-fat bread provided by an embodiment of the present invention, the method comprising the following steps: Step S1: Acquire a fermentation gas data set of a bread fermentation monitoring process; the fermentation gas data set includes a carbon dioxide concentration value at each sampling moment and a gas concentration value of each by-product.

[0021] In order to reasonably control the fermentation equipment to stop fermentation, the fermentation gas data set of the bread fermentation monitoring process is first obtained to provide data support for the subsequent analysis of the real-time fermentation effect.

[0022] From the bread fermentation monitoring equipment, the carbon dioxide concentration value and the gas concentration value of each by-product at each sampling time are obtained. The specific acquisition process includes: The materials for fermenting low-sugar and low-fat bread are fully prepared and placed in a closed fermentation device for fermentation. A gas sampling device is reasonably set in the fermentation device to collect fermentation gas to monitor the fermentation status in real time. During the bread fermentation monitoring process, according to the preset sampling frequency, the gas sampling device is started to continuously collect gas in the preset sampling time period to obtain the sampled gas samples corresponding to each sampling time. The sampled gas samples at each sampling time are sent to the infrared spectrometer for detection. The infrared spectrometer identifies and measures the content of various gases in the sampled gas sample by detecting the characteristic absorption bands of different chemical bonds and functional groups in the gas in the infrared spectrum, and the gas concentration value of each fermentation gas can be obtained. Among them, carbon dioxide is the direct product of yeast activity during bread fermentation, and its concentration change can reflect the activity of yeast and fermentation rate. The gas concentration value corresponding to carbon dioxide is used as the carbon dioxide concentration value; in addition to carbon dioxide, other gas byproducts may be produced during the fermentation process, that is, the sampled gas sample may include byproducts, such as ethanol byproducts and acetic acid byproducts, etc. The concentration of the byproducts can also provide information about the fermentation state. The gas concentration value of each byproduct can be obtained by detection by the infrared spectrometer. The carbon dioxide concentration value and the gas concentration value of each by-product at each sampling time are taken as the fermentation gas data set.

[0023] It should be noted that, in order to facilitate calculations, all indicator data involved in the calculations in the embodiments of the present invention are subjected to data preprocessing to eliminate the dimension effect. The specific means of removing the dimension effect are technical means well known to those skilled in the art and are not limited here. In one embodiment of the present invention, the preset sampling frequency is 30 seconds / time, and the preset sampling time period is 10 seconds. The implementer can set it according to the implementation scenario. The last sampling moment in the present invention is the current moment.

[0024] In order to ensure that low-sugar and low-fat bread achieves the ideal fermentation effect, it is particularly important to reasonably control the fermentation equipment to stop fermentation. The present invention combines the dynamic change characteristics of carbon dioxide concentration and the gas concentration value of the byproducts produced during the fermentation process to more accurately analyze the fermentation effect at the current moment, thereby reasonably controlling the fermentation equipment to stop fermentation and ensuring the quality of low-sugar and low-fat bread.

[0025] Step S2: Obtain the carbon dioxide fermentation measurement at the current moment according to the change of the local carbon dioxide concentration value at the current moment with time; obtain the gas saturation measurement of the by-product at the sampling moment according to the numerical size and numerical change of the gas concentration value of the by-product at the sampling moment; obtain the local negative impact measurement of the by-product at the current moment according to the gas saturation measurement of the by-product within the preset reference range at the current moment; obtain the overall negative impact measurement at the current moment by combining the local negative impact measurements of all by-products at the current moment; obtain the overall fermentation effect measurement at the current moment based on the carbon dioxide fermentation measurement and the overall negative impact measurement at the current moment.

[0026] In order to evaluate the fermentation effect at the current moment, a carbon dioxide fermentation metric is constructed to accurately reflect the saturation degree of carbon dioxide; the gas saturation metric is used to reflect the saturation degree of the by-products at the current moment, and then the local negative impact metric of the by-products is constructed to reflect the negative impact of the by-products on the current fermentation. During the fermentation process, multiple by-products are produced simultaneously and have a negative impact on the current fermentation. The local negative impact metrics of all by-products at the current moment are combined to obtain an overall negative impact metric. The overall negative impact metric reflects the comprehensive negative impact of all by-products on fermentation at the current moment. The carbon dioxide fermentation metric and the overall negative impact metric are combined to obtain the overall fermentation effect metric at the current moment. The overall fermentation effect metric can more accurately reflect the fermentation effect at the current moment.

[0027] In the initial stage of fermentation, yeasts reproduce rapidly mainly through aerobic respiration, and the rate of carbon dioxide production is relatively low at this time. As the oxygen in the environment is gradually consumed, yeasts begin to turn to anaerobic fermentation. In the early stage of anaerobic fermentation, yeast metabolism is extremely active, resulting in a sharp increase in the rate of carbon dioxide production; as time goes on, the activity of yeasts may gradually weaken, thereby causing the rate of carbon dioxide production to slow down accordingly, and may produce too many by-products that are not conducive to the quality of bread. In the process of bread fermentation monitoring, timely analysis of fermentation status feedback is crucial. Carbon dioxide is the core product in the fermentation process and has a very high reference value for evaluating the fermentation state of bread. The ideal fermentation state is to ensure that carbon dioxide can reach a saturation level while reducing the saturation level of by-products that have an adverse effect on the quality of bread. In order to achieve a significant distinction between carbon dioxide and by-products in saturation state, thereby ensuring the fermentation effect and final quality of the bread. For in-depth analysis and accurate evaluation of the saturation state of carbon dioxide, please refer to Figure 2 , which shows a flow chart of a method for obtaining carbon dioxide fermentation metrics in one embodiment of the present invention. Preferably, in one embodiment of the present invention, the method for obtaining carbon dioxide fermentation metrics includes: Step S201: obtaining a carbon dioxide saturation state indicator at the current moment according to the value of the carbon dioxide concentration value at the current moment and its value change.

[0028] Firstly, a carbon dioxide saturation status index at the current moment is constructed to preliminarily reflect the carbon dioxide saturation status at the current moment.

[0029] Preferably, in one embodiment of the present invention, the absolute value of the second-order difference value of the carbon dioxide concentration value at the current moment is calculated to obtain the carbon dioxide rate change value at the current moment; the sum of the carbon dioxide rate change value at the current moment and the preset denominator adjustment value is calculated, and the ratio of the carbon dioxide concentration value at the current moment to the sum value is calculated to obtain the carbon dioxide saturation state index at the current moment. In one embodiment of the present invention, the preset denominator adjustment value is 0.1 to prevent the denominator from being 0. It should be noted that the second-order difference value is a technical means well known to those skilled in the art, and is only briefly described here. All carbon dioxide concentration values ​​are sorted according to the sampling time sequence. First, the difference between the carbon dioxide concentration value at the current moment and the previous moment is calculated to obtain the first-order difference value. Next, the difference between the first-order difference value at the current moment and the first-order difference value at the previous moment is calculated, that is, the second-order difference value of the carbon dioxide concentration value at the current moment is obtained.

[0030] According to the above steps, during the bread fermentation process, the rate of carbon dioxide production has undergone a significant change process from the initial stage of anaerobic fermentation of yeast to the saturation stage when its activity gradually weakens. In the early stage of fermentation, yeast metabolism is active and the rate of carbon dioxide production rises rapidly; as time goes by, yeast activity may gradually weaken, resulting in a slowdown in the rate of carbon dioxide production. Two core parameters, carbon dioxide rate change value and carbon dioxide concentration value, are introduced. Among them, the carbon dioxide rate change value can sensitively reflect the strength changes of yeast metabolic activity, while the carbon dioxide concentration value intuitively reflects the accumulation of gas in the fermentation system. The smaller the carbon dioxide rate change value, the more stable the metabolic activity of yeast is, and the slower the change in the rate of carbon dioxide production is, indicating that the fermentation system is gradually approaching a saturated state. The larger the carbon dioxide concentration value, the more carbon dioxide accumulates in the fermentation system, and the closer it is to a saturated state. The sum of the carbon dioxide rate change value at the current moment and the preset denominator adjustment value is calculated, and the ratio of the carbon dioxide concentration value at the current moment to the sum value is calculated to obtain the carbon dioxide saturation state index at the current moment. The carbon dioxide saturation state index can more preliminarily reflect the saturation level of carbon dioxide.

[0031] Step S202: obtaining the carbon dioxide saturation real index at the current moment according to the change stability of the carbon dioxide saturation state index in the preset local range at the current moment.

[0032] Due to the continuous changes in the internal structure of bread and the overflow of gas, the carbon dioxide saturation state indicator may be affected by fluctuations, leading to misjudgment of the carbon dioxide saturation state. In order to more accurately evaluate the carbon dioxide saturation state, it is considered that the carbon dioxide saturation state means that the concentration of carbon dioxide in the fermentation system reaches a relatively stable equilibrium point, because the fermentation system has a certain self-regulation ability and can maintain the relative stability of the carbon dioxide concentration. In the saturated state, even if the external conditions change slightly, the carbon dioxide concentration will not fluctuate significantly. Construct a true carbon dioxide saturation indicator to reflect the stability of the carbon dioxide saturation state at the current moment, so as to accurately analyze the authenticity of the carbon dioxide saturation state in the fermentation system.

[0033] Preferably, in one embodiment of the present invention, each sampling moment in the preset local range of the current moment is used as each local moment of the current moment; the difference value of the carbon dioxide saturation state index at each local moment is calculated to obtain the saturation state change index at each local moment; the variance of the saturation state change index at all local moments is calculated and negative correlation mapping is performed to obtain the real carbon dioxide saturation index at the current moment. It should be noted that negative correlation mapping is a technical means well known to those skilled in the art, and negative correlation mapping can be in the form of inverse proportion or negative exponential power, which is not limited. In one embodiment of the present invention, the range of the sampling moments including the preset number before the current moment is used as the preset local range of the current moment. In one embodiment of the present invention, the preset number is 6, and the implementer can set it according to the implementation scenario. It should be noted that the present invention uses forward difference to calculate the difference value, that is, the current data minus the previous data in the time series dimension.

[0034] For the above steps, each sampling moment in the preset local range of the current moment is taken as the local moment of the current moment. The differential value of the carbon dioxide saturation state index at the local moment is calculated, and the differential value reflects the change in the carbon dioxide saturation state index between adjacent time points. The variance of all saturation state change indicators is calculated, and the variance reflects the discrete degree of the change. The larger the variance, the more unstable the change; the smaller the variance, the more stable the change. Calculate the variance of all saturation state change indicators and perform negative correlation mapping to obtain the true carbon dioxide saturation index at the current moment. The larger the true carbon dioxide saturation index, the more stable the change, which means that the authenticity of the carbon dioxide saturation state in the fermentation system at the current moment is higher.

[0035] Step S203: forwardly fuse the carbon dioxide saturation state indicator and the carbon dioxide saturation real indicator to obtain the carbon dioxide fermentation measurement at the current moment.

[0036] The carbon dioxide saturation state index can preliminarily reflect the carbon dioxide saturation state in the fermentation system at the current moment. The carbon dioxide saturation true index can further illustrate the authenticity of the carbon dioxide saturation state in the fermentation system at the current moment. The carbon dioxide saturation state index and the carbon dioxide saturation true index are integrated to obtain the carbon dioxide fermentation measurement at the current moment. The carbon dioxide fermentation measurement can more accurately reflect the saturation state of carbon dioxide in the fermentation process.

[0037] It should be noted that forward fusion is an existing technology well known to those skilled in the art, and forward fusion can adopt simple product, arithmetic mean or other suitable fusion methods. In one embodiment of the present invention, the product of the carbon dioxide saturation state index and the carbon dioxide saturation real index is calculated to obtain the carbon dioxide fermentation measurement at the current moment.

[0038] Considering that in addition to carbon dioxide, some by-products are also produced during the fermentation process, such as alcohol by-products and lactic acid by-products. Excessive accumulation of by-products will have an adverse effect on the quality of the bread, such as sour taste and hard texture. The ideal fermentation state is to ensure that carbon dioxide can reach a saturation level, while reducing the saturation level of by-products that have an adverse effect on the quality of the bread. The significant distinction between carbon dioxide and by-products in saturation state ensures the flavor and quality of low-sugar and low-fat bread. In order to deeply analyze the saturation state of the by-products, preferably, in one embodiment of the present invention, the method for obtaining the gas saturation measurement includes: For any by-product, the absolute value of the second-order difference value corresponding to the gas concentration value of the by-product at the sampling time is calculated and negative correlation mapping is performed to obtain the negative correlation mapping result; the product of the negative correlation mapping result and the gas concentration value of the by-product at the sampling time is calculated and normalized to obtain the gas saturation measurement of the by-product at the sampling time. It should be noted that negative correlation mapping and normalization processing are both technical means well known to those skilled in the art. Negative correlation mapping can be in the form of inverse proportion or negative exponential power, and normalization processing can be linear normalization, etc., which are not limited here.

[0039] For the above steps, for any by-product, calculate the absolute value of the second-order difference value of the by-product gas concentration value to reflect the trend of its concentration change. Considering that when the by-product concentration changes rapidly, it means that the by-product is accumulating rapidly, and its saturation measure should be low; when the concentration changes slowly, the by-product is close to the saturation state, and its saturation measure should be high. Perform negative correlation mapping on the absolute value of the second-order difference value to obtain the negative correlation mapping result; multiply the negative correlation mapping result by the gas concentration value of the by-product at the sampling time to obtain the gas saturation measure of the by-product at the sampling time. By combining the concentration change rate of the by-product and the actual concentration value, the gas saturation measure is finally obtained, and the gas saturation measure can more accurately reflect the saturation state of the by-product at the current moment.

[0040] To analyze the negative impact of any byproduct on the current fermentation, see Figure 3 , which shows a flow chart of a method for obtaining a local negative impact metric in one embodiment of the present invention. Preferably, in one embodiment of the present invention, the method for obtaining a local negative impact metric includes: Step S211: For any by-product, within the preset reference range at the current moment, each sampling moment at which the gas saturation value is greater than the preset saturation threshold is taken as the saturation moment; and the saturation moments exceeding the preset number of consecutive moments are taken as the saturation time period.

[0041] To identify the point in time during the fermentation process when byproducts reach gas saturation conditions and further determine the time period over which these saturation conditions persist.

[0042] In one embodiment of the present invention, the preset saturation threshold is set to 0.67, which is used to determine the saturation state of the by-product gas. The implementer can set it according to the experience value. The present invention takes the range including the current moment and all previous sampling moments as the preset reference range of the current moment, and sets the number of preset moments to 1. The implementer can set it according to the implementation requirements.

[0043] Step S212: acquiring a first negative impact indicator of the byproduct in the saturation time period according to the length of the saturation time period and the corresponding gas saturation measurement.

[0044] The first negative impact indicator quantifies the negative impact of the by-products on the current fermentation during the saturation period by analyzing the accumulation degree of the by-products during the saturation period.

[0045] In one embodiment of the present invention, the length of the saturation time period is used as the first saturation parameter of the saturation time period; the maximum gas saturation measurement among the gas saturation measurements corresponding to all sampling moments in the saturation time period is used as the second saturation parameter of the saturation time period; and the product of the first saturation parameter and the second saturation parameter is calculated as the first negative impact indicator of the by-product in the saturation time period.

[0046] For the above steps, the first saturation parameter reflects the duration of the byproduct in the saturated state. The longer the time, the more serious the accumulation of the byproduct. The second saturation parameter represents the highest level of byproduct gas saturation in the saturated time period, reflecting the peak value of byproduct accumulation. The first negative impact refers to the comprehensive consideration of the duration of the saturated time period and the peak value of saturation, which can more comprehensively reflect the negative impact of the byproduct on the current fermentation in the saturated time period.

[0047] Step S213: acquiring a second negative impact indicator of the by-product in the saturation time period according to the time interval between adjacent saturation time periods in time sequence and the time interval between the saturation time period and the current moment.

[0048] The second negative impact indicator quantifies the negative impact of the byproducts on the current fermentation during the saturation time period through the time interval between the saturation time periods and the relationship between the saturation time periods and the current moment.

[0049] In one embodiment of the present invention, the time interval between each saturation time period and the previous saturation time period in the time series dimension is taken as the first interval of the saturation time; the time interval between the last sampling moment of the saturation time period and the current moment is taken as the second interval; the product of the first interval and the second interval is calculated and negative correlation mapping is performed as the second negative impact indicator of the byproduct in the saturation time period. In the present invention, the negative correlation mapping can be in the form of inverse proportion or negative exponential power, which is not limited here.

[0050] For the above steps, the first interval reflects the time required for the byproduct to go from one saturation state to the next saturation state, and the interval between adjacent saturation states. The larger the first interval, the less frequent the saturation state of the byproduct occurs, and the smaller the negative impact of the byproduct on the current fermentation in the saturation time period; the second interval reflects the time from the end of the saturation state to the current time, and the impact of the saturation state of the byproduct on the current time. The larger the second interval, the smaller the negative impact of the byproduct on the current fermentation in the saturation time period; the product of the first interval and the second interval is calculated and negatively correlated, as the second negative impact indicator of the byproduct in the saturation time period. The second negative impact indicator quantifies the negative impact of byproduct accumulation on the current fermentation by considering the time interval between saturation time periods and the relationship between the saturation time period and the current moment.

[0051] Step S214: forwardly integrate the first negative impact indicator and the second negative impact indicator of the by-product in all saturation time periods to obtain the local negative impact measure of the by-product at the current moment.

[0052] The first negative impact index and the second negative impact index of all saturation time periods are comprehensively considered to obtain the local negative impact metric of the byproduct on the fermentation at the current moment. The local negative impact metric more comprehensively evaluates the negative impact of the byproduct on the current fermentation.

[0053] It should be noted that forward fusion is an existing technology well known to those skilled in the art, and forward fusion can adopt simple product, arithmetic mean or other suitable fusion methods. In one embodiment of the present invention, the sum of the first negative impact index and the second negative impact index of the by-product in the saturated time period is calculated to obtain the negative comprehensive impact index of the by-product in the saturated time period; the cumulative value of the negative comprehensive impact index of the by-product in all saturated time periods is calculated to obtain the local negative impact measure of the by-product at the current moment.

[0054] It should be noted that the process of obtaining the local negative impact measurement of any by-product at the current moment is illustrated here by way of example, and the process of obtaining the local negative impact measurement of all by-products at the current moment is the same and will not be described in detail here.

[0055] In order to analyze the negative impact of all by-products on the current fermentation, preferably, in one embodiment of the present invention, the method for obtaining the overall negative impact metric includes: The cumulative value of the local negative impact metrics of all byproducts at the current moment is calculated to obtain the overall negative impact metric at the current moment.

[0056] In order to measure the overall fermentation effect of the fermentation process at the current moment, preferably, in one embodiment of the present invention, the method for obtaining the overall fermentation effect measurement includes: The difference between the carbon dioxide fermentation metric at the current moment and the overall negative impact metric is calculated and normalized to obtain the overall fermentation effect metric at the current moment. In the present invention, a linear normalization method can be used for normalization.

[0057] For the above steps, considering that the ideal fermentation state is to ensure that carbon dioxide can reach a saturation level, while reducing the saturation of byproducts that have an adverse effect on bread quality. The carbon dioxide fermentation metric can accurately reflect the saturation state of carbon dioxide during the fermentation process; the local negative impact metric more comprehensively evaluates the negative impact of byproducts on the current fermentation. By calculating the difference between the carbon dioxide fermentation metric at the current moment and the overall negative impact metric, the overall fermentation effect metric at the current moment is obtained. The overall fermentation effect metric can accurately reflect the fermentation effect at the current moment.

[0058] Step S3: Based on the overall fermentation effect measurement at the current moment, the fermentation equipment is controlled.

[0059] The overall fermentation effect measurement can accurately reflect the fermentation effect at the current moment, thereby realizing the reasonable control of the fermentation equipment to stop fermentation and ensuring the fermentation effect of low-sugar and low-fat bread.

[0060] Preferably, in one embodiment of the present invention, the method for controlling the fermentation equipment comprises: If the overall fermentation effect measurement at the current moment is greater than the preset fermentation threshold, the fermentation equipment is controlled to stop fermentation; if the overall fermentation effect measurement at the current moment is not greater than the preset fermentation threshold, the fermentation equipment is controlled to continue fermentation. The preset fermentation threshold in the present invention is set to 0.57, and the implementer can set it according to the implementation requirements, in order to ensure that the fermentation process can reach the ideal carbon dioxide saturation level and control the generation of adverse by-products within a reasonable range.

[0061] For the above steps, the overall fermentation effect measurement value at the current moment is compared with the preset fermentation threshold. If the overall fermentation effect measurement at the current moment is greater than the preset fermentation threshold, it means that the fermentation process is sufficient. At this time, the fermentation equipment should be controlled to stop fermentation to avoid quality degradation caused by excessive fermentation. If the overall fermentation effect measurement at the current moment is not greater than the preset fermentation threshold, it means that there is still room for further fermentation. At this time, the fermentation equipment should be controlled to continue fermentation to promote further expansion of the dough and sufficient dissolution of the gas.

[0062] The present invention also proposes an intelligent fermentation monitoring system for low-sugar and low-fat bread, please refer to Figure 4 , which shows a structural diagram of an intelligent fermentation monitoring system for low-sugar and low-fat bread provided by an embodiment of the present invention. The system includes: a data acquisition module 101, a fermentation effect analysis module 102 and a control module 103.

[0063] The data acquisition module 101 is used to acquire a fermentation gas data set of the bread fermentation monitoring process; the fermentation gas data set includes the carbon dioxide concentration value at each sampling time and the gas concentration value of each by-product.

[0064] The fermentation effect analysis module 102 is used to obtain the carbon dioxide fermentation measurement at the current moment according to the change of the local carbon dioxide concentration value at the current moment over time; to obtain the gas saturation measurement of the by-product at the sampling moment according to the numerical size and numerical change of the gas concentration value of the by-product at the sampling moment; to obtain the local negative impact measurement of the by-product at the current moment according to the gas saturation measurement of the by-product within the preset reference range at the current moment; to obtain the overall negative impact measurement at the current moment by integrating the local negative impact measurements of all by-products at the current moment; and to obtain the overall fermentation effect measurement at the current moment based on the carbon dioxide fermentation measurement and the overall negative impact measurement at the current moment.

[0065] The control module 103 is used to control the fermentation equipment based on the overall fermentation effect measurement at the current moment.

[0066] It should be noted that the system provided in the above embodiment is only illustrated by the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the computer device is divided into different functional modules to complete all or part of the functions described above. In addition, the intelligent fermentation monitoring system for low-sugar and low-fat bread provided in the above embodiment and the intelligent fermentation monitoring method embodiment for low-sugar and low-fat bread belong to the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0067] In summary, the embodiment of the present invention provides an intelligent fermentation monitoring method and system for low-sugar and low-fat bread. First, according to the change of the local carbon dioxide concentration value at the current moment with time, the carbon dioxide fermentation measurement at the current moment is obtained; according to the numerical value and numerical change of the gas concentration value of the by-product at the current moment, the gas saturation measurement of the by-product at the current moment is obtained; according to the gas saturation measurement of the by-product in the preset reference range at the current moment, the local negative impact measurement of the by-product at the current moment is obtained; the local negative impact measurement of all by-products at the current moment is combined to obtain the overall negative impact measurement at the current moment; based on the carbon dioxide fermentation measurement at the current moment and the overall negative impact measurement, the overall fermentation effect measurement at the current moment is obtained. Based on the overall fermentation effect measurement at the current moment, the fermentation equipment is controlled. In the embodiment of the present invention, the performance of the fermentation gas is fully considered to more accurately analyze the fermentation effect at the current moment, so as to reasonably control the fermentation equipment to stop fermentation and ensure the fermentation effect of low-sugar and low-fat bread.

[0068] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0069] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. An intelligent fermentation monitoring method for low-sugar and low-fat bread, characterized in that: The method comprises: Acquire a fermentation gas data set of a bread fermentation monitoring process; the fermentation gas data set includes a carbon dioxide concentration value at each sampling time and a gas concentration value of each byproduct; According to the change of the local carbon dioxide concentration value at the current moment with time, the carbon dioxide fermentation measurement at the current moment is obtained; according to the numerical value and numerical change of the gas concentration value of the by-product at the sampling moment, the gas saturation measurement of the by-product at the sampling moment is obtained; according to the gas saturation measurement of the by-product within the preset reference range at the current moment, the local negative impact measurement of the by-product at the current moment is obtained; the overall negative impact measurement at the current moment is obtained by combining the local negative impact measurements of all the by-products at the current moment; based on the carbon dioxide fermentation measurement at the current moment and the overall negative impact measurement, the overall fermentation effect measurement at the current moment is obtained; Based on the overall fermentation effect measurement at the current moment, the fermentation equipment is controlled.

2. The intelligent fermentation monitoring method for low-sugar and low-fat bread according to claim 1, characterized in that: The method for obtaining the carbon dioxide fermentation metric comprises: According to the numerical value of the carbon dioxide concentration value at the current moment and its numerical change, obtaining the carbon dioxide saturation state indicator at the current moment; According to the change stability of the carbon dioxide saturation state indicator in the preset local range at the current moment, obtaining the carbon dioxide saturation real indicator at the current moment; The carbon dioxide saturation state indicator and the carbon dioxide saturation real indicator are forwardly integrated to obtain the carbon dioxide fermentation measurement at the current moment.

3. The intelligent fermentation monitoring method for low-sugar and low-fat bread according to claim 2, characterized in that: The method for obtaining the carbon dioxide saturation state index comprises: The absolute value of the second-order difference value of the carbon dioxide concentration value at the current moment is calculated to obtain the carbon dioxide rate change value at the current moment; the sum of the carbon dioxide rate change value at the current moment and the preset denominator adjustment value is calculated, and the ratio of the carbon dioxide concentration value at the current moment to the sum is calculated to obtain the carbon dioxide saturation state index at the current moment.

4. The intelligent fermentation monitoring method for low-sugar and low-fat bread according to claim 2, characterized in that: The method for obtaining the true carbon dioxide saturation index comprises: Each sampling moment in the preset local range of the current moment is taken as each local moment of the current moment; the differential value of the carbon dioxide saturation state index at each local moment is calculated to obtain the saturation state change index at each local moment; the variance of the saturation state change index at all the local moments is calculated and negative correlation mapping is performed to obtain the true carbon dioxide saturation index at the current moment.

5. The intelligent fermentation monitoring method for low-sugar and low-fat bread according to claim 1, characterized in that: The method for obtaining the gas saturation measurement includes: For any by-product, the absolute value of the second-order difference value corresponding to the gas concentration value of the by-product at the sampling time is calculated and negative correlation mapping is performed to obtain the negative correlation mapping result; the product of the negative correlation mapping result and the gas concentration value of the by-product at the sampling time is calculated and normalized to obtain the gas saturation measurement of the by-product at the sampling time.

6. The intelligent fermentation monitoring method for low-sugar and low-fat bread according to claim 1, characterized in that: The method for obtaining the local negative impact metric includes: For any by-product, within the preset reference range at the current moment, each sampling moment at which the gas saturation value is greater than the preset saturation threshold is taken as the saturation moment; and the saturation moments exceeding the preset number of consecutive moments are taken as the saturation time period; According to the length of the saturation time period and the corresponding gas saturation measurement, obtaining a first negative impact indicator of the byproduct in the saturation time period; According to the time interval between the adjacent saturation time periods in time sequence and the time interval between the saturation time period and the current moment, obtaining a second negative impact indicator of the byproduct in the saturation time period; The first negative impact indicator and the second negative impact indicator of the by-product in all saturation time periods are forwardly integrated to obtain a local negative impact measure of the by-product at the current moment.

7. The intelligent fermentation monitoring method for low-sugar and low-fat bread according to claim 6, characterized in that: The method for obtaining the first negative impact indicator includes: The length of the saturation time period is used as the first saturation parameter of the saturation time period; the maximum gas saturation measurement corresponding to all gas saturation measurements at all sampling moments in the saturation time period is used as the second saturation parameter of the saturation time period; the product of the first saturation parameter and the second saturation parameter is calculated as the first negative impact indicator of the by-product in the saturation time period.

8. The intelligent fermentation monitoring method for low-sugar and low-fat bread according to claim 6, characterized in that: The method for obtaining the second negative impact indicator includes: The time interval between each saturation time period and the previous saturation time period in the time series dimension is taken as the first interval of the saturation time; the time interval between the last sampling moment of the saturation time period and the current moment is taken as the second interval; the product of the first interval and the second interval is calculated and negative correlation mapping is performed as the second negative impact indicator of the by-product in the saturation time period.

9. The intelligent fermentation monitoring method for low-sugar and low-fat bread according to claim 1, characterized in that: The method for obtaining the overall fermentation effect measurement includes: The difference between the carbon dioxide fermentation metric at the current moment and the overall negative impact metric is calculated and normalized to obtain the overall fermentation effect metric at the current moment.

10. An intelligent fermentation monitoring system for low-sugar and low-fat bread, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the intelligent fermentation monitoring method for low-sugar and low-fat bread as described in any one of claims 1 to 9 are implemented.

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