Temperature control method and system for organic fertilizer fermentation bin and medium

Abstract

The invention provides a temperature control method and system for an organic fertilizer fermentation bin and a medium, and relates to the technical field of temperature control, and the method specifically comprises the steps: obtaining the environmental parameters and corresponding control parameters of the fermentation bin at a plurality of historical moments, obtaining the environmental parameters of the fermentation bin at the current moment, and calculating the comprehensive gas concentration and environmental state index; setting a target temperature, calculating the deviation between the current temperature and the target temperature, analyzing the correlation among a temperature deviation value, an environment state index and a control parameter by using a Pearson's correlation coefficient, and calculating the control parameter; and adjusting the heater and the ventilation equipment according to the control parameters. By obtaining and analyzing various key parameters in the fermentation bin in real time, comprehensive evaluation of the environment state is achieved, the accuracy of temperature control is improved, correlation analysis among temperature deviation, environment state indexes and control parameters is effectively integrated, operation of heating and ventilation equipment is dynamically adjusted in combination with a phase change material, and the temperature control accuracy is improved. The stability of the fermentation process is improved.

Description

Technical Field

[0001] The invention relates to the technical field of temperature control, and in particular to a temperature control method, system and medium for an organic fertilizer fermentation bin. Background Art

[0002] In the production process of organic fertilizer, fermentation is a key link, and environmental parameters such as temperature, humidity, carbon dioxide concentration and oxygen concentration have a significant impact on the fermentation effect. Traditional temperature control methods in fermentation chambers often rely on temperature sensors for single parameter monitoring. This method lacks a comprehensive assessment of the environment, resulting in insufficient accuracy and flexibility in temperature control. Especially when environmental conditions change greatly, a single temperature control strategy may not be able to adapt to the rapidly changing fermentation environment, resulting in large temperature fluctuations, affecting the activity of microorganisms and the effective decomposition of organic matter. In addition, traditional methods often ignore the impact of other environmental factors such as humidity and gas concentration on the fermentation process, which can easily lead to a delay in the control system's response to various environmental conditions, thereby reducing the overall fermentation efficiency and the quality of the final product.

[0003] The shortcomings of the prior art in temperature control are also reflected in the insufficient use of historical data. Many traditional control systems rely mainly on real-time data when adjusting temperature, and lack systematic analysis and learning of historical environmental parameters. This single reliance on real-time data makes it difficult for the control model to adapt to the complex and changeable fermentation environment, and it is also impossible to effectively identify the key parameters related to temperature changes. Therefore, in a multivariable environment, the stability and reliability of the control system are limited, and usually require high human intervention for manual adjustment and optimization. Furthermore, traditional control models often lack dynamics and cannot respond to changes in environmental conditions in real time, resulting in difficulty in quickly adjusting control strategies when faced with emergencies, causing the fermentation process to be at risk. These shortcomings significantly restrict the efficiency of organic fertilizer production and the quality of products, and there is an urgent need for a more intelligent, comprehensive and dynamic temperature control method to meet the needs of modern agricultural production.

[0004] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0005] The object of the present invention is to provide a temperature control method, system and medium for an organic fertilizer fermentation bin to solve the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A temperature control method for an organic fertilizer fermentation bin, comprising the following specific steps:

[0008] Step 1: Obtain the environmental parameters and corresponding control parameters of the fermentation bin at multiple historical moments, and obtain the environmental parameters of the fermentation bin at the current moment. There are five environmental parameters, including temperature, humidity, carbon dioxide concentration, oxygen concentration and comprehensive gas concentration, and the comprehensive gas concentration is the ratio of carbon dioxide concentration to oxygen concentration in the fermentation bin;

[0009] Step 2: Combine the comprehensive gas concentration, temperature and humidity to generate an environmental status index that reflects the environmental conditions in the fermentation chamber, set the target temperature, and calculate the temperature deviation from the target temperature;

[0010] Step 3: Calculate the Pearson correlation coefficients between various environmental parameters and control parameters, and use them to screen out key parameters that are strongly correlated with control parameters. Construct a control model whose inputs are key parameters, temperature deviation, and environmental status index, and whose outputs are control parameters. Use historical data to train the control model.

[0011] Step 4: Input the key parameters, temperature deviation and environmental status index at the current moment into the control model to obtain the control parameters at the current moment, and perform temperature control based on the control parameters.

[0012] Furthermore, the top, bottom and middle positions of the fermentation bin are set as key positions, and sensors are used to obtain the temperature, humidity, carbon dioxide concentration and oxygen concentration at each key position in the fermentation bin, and the average thereof is used as the temperature, humidity, carbon dioxide concentration and oxygen concentration of the fermentation bin.

[0013] Furthermore, the data obtained in step 1 is preprocessed as raw data, and then the preprocessed data is used to perform subsequent steps. The preprocessing is to convert the raw data into corresponding standard scores. The formula for converting the standard scores is as follows:

[0014]

[0015] Among them, Z is the standard score, R is the original data, μ is the average value of the same type of original data, and σ is the standard deviation of the same type of original data;

[0016] The target temperature is preprocessed in the same way to obtain a standard score corresponding to the target temperature, and in the standard score calculation formula corresponding to the target temperature, the mean value and standard deviation adopt the mean value and standard deviation of the temperature respectively.

[0017] Furthermore, the comprehensive gas concentration in the fermentation chamber is calculated based on the formula:

[0018]

[0019] Among them, GAS is the comprehensive gas concentration in the fermentation chamber, is the carbon dioxide concentration, is the oxygen concentration;

[0020] The environmental status index of the fermentation warehouse is calculated according to the following formula:

[0021]

[0022] Among them, ENV is the environmental status index of the fermentation chamber, T is the current temperature of the fermentation chamber, and T y is the temperature threshold, S is the humidity, S y is the optimal humidity value of the fermentation chamber, GAS is the comprehensive gas concentration, GAS y is the optimal comprehensive gas concentration, ω1 and ω2 are preset proportional coefficients, and ω1>ω2>0.

[0023] Furthermore, the target temperature is set to T set , the formula for calculating temperature deviation is as follows:

[0024] ΔT=T set -T

[0025] Where ΔT is the temperature deviation from the target temperature, T set is the target temperature, and T is the current temperature of the fermentation chamber.

[0026] Furthermore, the logic for determining the key parameters is:

[0027] The Pearson correlation coefficient between temperature and control parameters is calculated according to the following formula:

[0028]

[0029] Among them, r(T) is the Pearson correlation coefficient between temperature and control parameters, T j represents the temperature obtained at the jth historical moment, U j represents the control parameters obtained at the jth historical moment, is the average temperature obtained for all historical moments, The mean value of the control parameters obtained for all historical moments;

[0030] Similarly, the Pearson correlation coefficient between humidity and control parameters, the Pearson correlation coefficient between carbon dioxide concentration and control parameters, the Pearson correlation coefficient between oxygen concentration and control parameters, and the Pearson correlation coefficient between comprehensive gas concentration and control parameters are obtained;

[0031] Sort the environmental parameters from large to small according to the absolute value of the Pearson correlation coefficient, and select at least the top two environmental parameters as key parameters.

[0032] Furthermore, the expression of the control model is as follows:

[0033]

[0034] Among them, U is the control parameter, ΔT is the temperature deviation, ENV is the environmental status index, A k is the kth key parameter, α is the weight coefficient of temperature deviation, β is the weight coefficient of environmental state index, γ k is the weight coefficient of the kth key parameter, k is the type index of the key parameter, and k∈[1,K], K is the total number of key parameter types, and |α|>|β|>|γ k |, and the weight coefficient relationship of each key parameter is set according to the absolute value of its Pearson correlation coefficient, and C1 is the first constant correction index.

[0035] Furthermore, the method for temperature control based on the control parameters is: adjusting the heater and ventilation equipment according to the control parameters, and arranging phase change materials in the fermentation bin to adjust the temperature in the fermentation bin.

[0036] The present invention also provides a temperature control system for an organic fertilizer fermentation bin, which is used to implement the temperature control method for an organic fertilizer fermentation bin, comprising:

[0037] The data acquisition module is used to obtain the environmental parameters of the fermentation bin and the corresponding control parameters at multiple historical moments, and obtain the environmental parameters of the fermentation bin at the current moment. There are five environmental parameters, including temperature, humidity, carbon dioxide concentration, oxygen concentration and comprehensive gas concentration, and the comprehensive gas concentration is the ratio of carbon dioxide concentration to oxygen concentration in the fermentation bin;

[0038] The data processing module is used to combine the comprehensive gas concentration, temperature and humidity to generate an environmental status index reflecting the environmental conditions in the fermentation chamber, set the target temperature, and calculate the temperature deviation from the target temperature;

[0039] The correlation analysis module is used to calculate the Pearson correlation coefficients between various environmental parameters and control parameters, and to screen out key parameters that are strongly correlated with the control parameters, build a control model with key parameters, temperature deviation and environmental status index as input, and control parameters as output, and use historical data to train the control model;

[0040] The regulating module is used to input the key parameters, temperature deviation and environmental status index at the current moment into the control model to obtain the control parameters at the current moment and perform temperature control based on the control parameters.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] The present invention realizes a comprehensive evaluation of environmental status by real-time acquisition and analysis of standard scores of multiple key parameters in the fermentation bin. This method not only improves the accuracy of temperature control, but also effectively integrates the correlation analysis between temperature deviation, environmental status index and control parameters, dynamically adjusts the operation of heating and ventilation equipment, and improves the stability and efficiency of the fermentation process. In addition, in combination with the use of phase change materials, the temperature regulation mechanism is further optimized, so that the fermentation bin can maintain a suitable microbial growth temperature when the temperature fluctuates, thereby improving the fermentation quality and production efficiency of organic fertilizer. This intelligent temperature control strategy provides a practical solution for the efficient production of organic fertilizer. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a schematic diagram of the overall method flow of the present invention;

[0044] Figure 2 It is a schematic diagram of the overall system module of the present invention. DETAILED DESCRIPTION

[0045] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0046] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0047] Example:

[0048] See also Figure 1 , the present invention provides a technical solution:

[0049] A temperature control method for an organic fertilizer fermentation bin, comprising the following specific steps:

[0050] Step 1: Obtain the environmental parameters and corresponding control parameters of the fermentation bin at multiple historical moments, and obtain the environmental parameters of the fermentation bin at the current moment. There are five environmental parameters, including temperature, humidity, carbon dioxide concentration, oxygen concentration and comprehensive gas concentration, and the comprehensive gas concentration is the ratio of carbon dioxide concentration to oxygen concentration in the fermentation bin;

[0051] In this embodiment, the top, bottom and middle positions of the fermentation bin are set as key positions, and sensors are used to obtain the temperature, humidity, carbon dioxide concentration and oxygen concentration at each key position in the fermentation bin, and the average thereof is used as the temperature, humidity, carbon dioxide concentration and oxygen concentration of the fermentation bin.

[0052] The data obtained in step 1 is preprocessed as raw data, and then the preprocessed data is used for subsequent steps. The preprocessing is to convert the raw data into corresponding standard scores. The formula for converting the standard scores is as follows:

[0053]

[0054] Among them, Z is the standard score, R is the original data, μ is the average value of the same type of original data, and σ is the standard deviation of the same type of original data;

[0055] Standard scores convert data of different dimensions into dimensionless values, so that various environmental parameters can be compared on the same scale, avoiding confusion and bias caused by different dimensions; through standardization, the data is converted to the same standard distribution, usually a normal distribution with a mean of 0 and a standard deviation of 1. This makes the model more consistent in processing and analysis, avoiding instability in model training due to differences in the range of the original data.

[0056] The target temperature is preprocessed in the same way to obtain a standard score corresponding to the target temperature, and in the standard score calculation formula corresponding to the target temperature, the mean value and standard deviation adopt the mean value and standard deviation of the temperature respectively.

[0057] The comprehensive gas concentration in the fermentation chamber is calculated based on the formula:

[0058]

[0059] Among them, GAS is the comprehensive gas concentration in the fermentation chamber, is the carbon dioxide concentration, is the oxygen concentration;

[0060] The main advantage of step 1 is to fully obtain the historical environmental parameters and corresponding control parameters of the fermentation chamber, and analyze them in combination with the current environmental data. This method not only covers a variety of environmental parameters such as temperature, humidity, carbon dioxide concentration, oxygen concentration, etc., but also introduces comprehensive gas concentration to provide a more comprehensive environmental assessment. This multi-dimensional data collection method can effectively capture the changing trends in the fermentation process, enabling the control system to make decisions based on more accurate data, enhancing the ability to adapt to dynamic changes in the fermentation environment, and thus optimizing the temperature control effect.

[0061] Compared with the prior art, step 1 introduces historical data, so that the control system not only relies on real-time data, but also can be combined with historical trends for more accurate prediction and control. This method significantly improves the intelligent level of temperature control, and can better identify the relationship between control parameters, thereby improving the stability and efficiency of the overall fermentation process. In addition, this step provides a solid data foundation for subsequent model construction and optimization, so that the control model can more accurately adjust the control strategy in a dynamic environment, reduce human intervention, and improve the degree of automation. In this patent scheme, step 1 is used to provide important basic support for the implementation of the overall scheme. By accurately obtaining and analyzing historical and current environmental parameters, it can ensure that the control model construction of subsequent steps is more scientific and effective. In this way, not only the scientificity and accuracy of the temperature control of the fermentation bin are improved, but also a solid data foundation is laid for realizing an efficient and stable fermentation process, which promotes the improvement of the production efficiency and product quality of organic fertilizers.

[0062] Step 2: Combine the comprehensive gas concentration, temperature and humidity to generate an environmental status index that reflects the environmental conditions in the fermentation chamber, set the target temperature, and calculate the temperature deviation from the target temperature;

[0063] In this embodiment, the environmental status index of the fermentation bin is calculated according to the following formula:

[0064]

[0065] Among them, ENV is the environmental status index of the fermentation chamber, which reflects the promotion of the current environment to microbial fermentation. The larger the ENV, the more suitable it is for microbial fermentation and reproduction. T is the temperature, T y is the temperature threshold, S is the humidity, S y is the optimal humidity value of the fermentation chamber, GAS is the comprehensive gas concentration, GAS yis the optimal comprehensive gas concentration, ω1 and ω2 are preset proportional coefficients, and ω1>ω2>0. This is because temperature and humidity are two key factors in the fermentation process, which directly affect the metabolic activity and growth rate of microorganisms. Appropriate temperature and humidity conditions can promote the reproduction and activity of microorganisms, thereby improving the efficiency of fermentation and product quality. Therefore, ω1, as the composite influence coefficient of temperature and humidity, will be given a larger weight.

[0066] When |TT y When | increases, it means that the difference between the current temperature and the temperature threshold increases, the metabolic activity of microorganisms will be inhibited, and the environmental status index ENV decreases; when |SS y |When it increases, it means that the deviation between the current humidity and the optimal humidity value increases, which is usually not conducive to the growth of microorganisms, slowing down the fermentation process and ultimately affecting the quality and yield of organic fertilizers. Therefore, the environmental status index ENV decreases; |GAS-GAS y The larger the value of |, the greater the deviation between the comprehensive gas concentration and the optimal comprehensive gas concentration, which has an inhibitory effect on the production of microorganisms, so the environmental status index ENV will decrease accordingly; that is, |TT y |、|SS y |、|GAS-GAS y |Negatively correlated with ENV.

[0067] Set the target temperature to T set , the formula for calculating temperature deviation is as follows:

[0068] ΔT=T set -T

[0069] Where ΔT is the temperature deviation from the target temperature, T set is the target temperature, and T is the current temperature of the fermentation chamber.

[0070] The main advantage of step 2 is that it generates an environmental status index that reflects the environmental conditions in the fermentation chamber by integrating gas concentration, temperature and humidity. This index can integrate the influence of multiple environmental parameters to provide a more comprehensive and intuitive environmental assessment. This method not only simplifies the analysis process of multiple parameters, but also better captures the relationship between various variables in the fermentation process, providing a solid basis for subsequent temperature control strategies. At the same time, setting the target temperature and calculating the temperature deviation enables the control system to clearly understand the gap between the current temperature condition and the ideal state, and then formulate a scientific adjustment plan.

[0071] Compared with the prior art, step 2 can effectively improve the flexibility and intelligence level of temperature control by introducing the concept of environmental status index. Traditional control methods are often based on a single or a few parameters for regulation, lacking consideration of the combined effects of multiple environmental factors. This may lead to lags and inaccuracies in temperature control strategies. The implementation of step 2 can realize real-time analysis of multi-dimensional environmental information, thereby identifying the needs and adjustment directions of temperature control more quickly, improving response speed and control accuracy. In this patent scheme, step 2 is used to provide an important dynamic analysis tool for the execution of the overall scheme. By generating an environmental status index, the control system can monitor and evaluate the environmental conditions of the fermentation bin in real time to ensure that temperature control is more accurate and effective. In this way, not only can energy consumption be reduced and fermentation efficiency be improved, but also the quality of the produced organic fertilizer can be ensured to be more stable, promoting the successful implementation of the overall scheme and enhancing its sustainability.

[0072] Step 3: Calculate the Pearson correlation coefficients between various environmental parameters and control parameters, and use them to screen out key parameters that are strongly correlated with control parameters. Construct a control model whose inputs are key parameters, temperature deviation, and environmental status index, and whose outputs are control parameters. Use historical data to train the control model.

[0073] In this embodiment, the historical control parameter obtained refers to the temperature adjustment amount set by the expert group according to the environmental data at that time; the specific logic for obtaining the control parameter is: the expert group determines the optimal temperature value according to the environmental parameters of the fermentation bin at the historical moment, and then uses the difference between the optimal temperature value and the temperature at the historical moment as the temperature adjustment amount;

[0074] The logic behind determining key parameters is:

[0075] The Pearson correlation coefficient between temperature and control parameters is calculated according to the following formula:

[0076]

[0077] Among them, r(T) is the Pearson correlation coefficient between temperature and control parameters, T j represents the temperature obtained at the jth historical moment, U j represents the control parameters obtained at the jth historical moment, is the average temperature obtained at all historical moments, The mean value of the control parameters obtained for all historical moments;

[0078] Similarly, the Pearson correlation coefficient between humidity and control parameters, the Pearson correlation coefficient between carbon dioxide concentration and control parameters, the Pearson correlation coefficient between oxygen concentration and control parameters, and the Pearson correlation coefficient between comprehensive gas concentration and control parameters are obtained;

[0079] Sort the environmental parameters from large to small according to the absolute value of the Pearson correlation coefficient, and select at least the top two environmental parameters as key parameters.

[0080] The main advantage of step 3 is that by calculating the Pearson correlation coefficient between various environmental parameters and control parameters, the key parameters that have a significant impact on the control parameters can be systematically identified. This process enables the temperature control model to be constructed based on a data-driven approach, ensuring that the input selection of the model is scientific and meaningful. By screening out strongly correlated key parameters, temperature deviations, and environmental state indices, the control model can more accurately reflect the dynamic changes of the actual fermentation environment, thereby improving the response speed and accuracy of temperature control.

[0081] Compared with the prior art, step 3 introduces statistical methods of data analysis to make the construction of the control model more scientific and rigorous. Traditional control methods often rely on experience or simple linear relationships and lack an in-depth understanding of the interaction of complex environmental factors. The implementation of step 3 enables the control model to be trained based on historical data, making full use of past experience, reducing the subjectivity of human intervention, and improving the reliability and adaptability of the model. In this patent scheme, the use of step 3 provides a solid theoretical basis and data support for the overall scheme. By scientifically identifying key parameters, the control model can be continuously optimized and adjusted to achieve precise control of the temperature of the fermentation bin. This not only improves the stability and efficiency of the fermentation process, but also provides a guarantee for the high-quality production of organic fertilizers, and promotes the successful implementation of the overall scheme and its universality and sustainability in practical applications.

[0082] Step 4: Input the key parameters, temperature deviation and environmental state index at the current moment into the control model to obtain the control parameters at the current moment, and perform temperature control based on the control parameters;

[0083] In this embodiment, the control model is a neural network model, and its expression is as follows:

[0084]

[0085] Among them, U is the control parameter, ΔT is the temperature deviation, ENV is the environmental status index, A k is the kth key parameter, α is the weight coefficient of temperature deviation, β is the weight coefficient of environmental state index, γ k is the weight coefficient of the kth key parameter, k is the type index of the key parameter, and k∈[1,K], K is the total number of key parameter types, and |α|>|β|>|γ k|, this is because temperature is one of the most critical parameters in the fermentation process, which directly affects the metabolic activity and fermentation efficiency of microorganisms. The environmental state index ENV combines multiple factors such as temperature, humidity and comprehensive gas concentration, and is a comprehensive reflection of the environmental state of the fermentation chamber. The reason why its weight is second only to temperature deviation is that although it also has an important impact on the fermentation process, its change is slower than the direct impact of temperature deviation. Key parameters are usually responses to specific environmental conditions. Their changes may have a certain impact on temperature control, but not as direct as temperature deviation and environmental state index. Therefore, their weight settings are smaller than the first two. And the size relationship of the weight coefficient of each key parameter is set according to the absolute value of its Pearson correlation coefficient. The Pearson correlation coefficient is a statistical method used to quantify the linear relationship between two variables. By calculating the Pearson correlation coefficient between each key parameter and the control parameter, it is possible to clearly identify which key parameters have a more significant impact on the control parameter. The larger the absolute value of the correlation coefficient, the stronger the relationship between the variables, so it can reasonably reflect the importance of each key parameter in the control model; C1 is the first constant correction index.

[0086] The existing technology only considers temperature to determine the temperature adjustment amount. Introducing other factors such as humidity and comprehensive gas concentration for comprehensive consideration can reduce the impact of single variable fluctuations on temperature adjustment, thereby making the temperature control process more stable and robust. The environmental system is a complex multi-factor system. Considering temperature alone may not reflect the actual fermentation status. By comprehensively considering multiple environmental factors, we can have a more comprehensive understanding of the actual environmental conditions of the fermentation warehouse, thereby making more accurate temperature adjustment decisions.

[0087] The method of temperature control based on control parameters is: adjusting the heater and ventilation equipment according to the control parameters, and arranging phase change materials in the fermentation bin to adjust the temperature in the fermentation bin:

[0088] The control parameter U is compared with the preset threshold U pre For comparison:

[0089] If U>U pre , then increase the heater power to raise the temperature of the fermentation chamber to the target temperature;

[0090] If U pre , then increase the ventilation rate and lower the temperature of the fermentation bin to the target temperature;

[0091] If U=U pre , indicating that the current control parameters are just at the preset values, maintaining the settings of the existing heating and ventilation equipment;

[0092] Regulate heaters and ventilators by controlling parameters;

[0093] ​Take a certain mass of phase change material and place it in the fermentation chamber, record the state change of the phase change material, if the phase change material changes from solid to liquid, use the following formula to calculate the heat absorbed by the phase change material:

[0094] Q pcm =-M pcm *L f

[0095] If the phase change material changes from liquid to solid, the heat released by the phase change material is calculated using the following formula:

[0096] Q pcm =M pcm *L f

[0097] Among them, Q pcm is the heat absorbed or released by the phase change material, M_pcm is the mass of the phase change material, and L_f is the latent heat of phase change;

[0098] According to the calculated Q pcm , evaluate the effect of phase change materials on the fermentation chamber temperature at different time periods:

[0099] If Q pcm If it is a negative value, it means that the phase change material is absorbing heat, indicating that the external temperature is decreasing and the heating equipment needs to be adjusted to maintain the temperature;

[0100] If Q pcm If it is a positive value, it means that the phase change material is releasing heat. If the temperature of the fermentation bin is between 25℃-35℃ at this time, it means that the temperature of the fermentation bin has reached the ideal state. If the temperature is greater than 35℃, it is necessary to increase the ventilation rate and reduce the temperature in the fermentation bin.

[0101] The main advantage of step 4 is that the key parameters, temperature deviation and environmental status index at the current moment are input into the control model, so as to calculate the optimal control parameters in real time for temperature regulation. This method ensures the dynamic and real-time nature of temperature control, enabling the system to respond quickly to changes in the fermentation environment and maintain the stability of the fermentation process. This real-time feedback mechanism can significantly improve the accuracy of temperature control and reduce the negative impact of temperature fluctuations on the fermentation effect, thereby effectively improving the production efficiency and quality of organic fertilizers.

[0102] Compared with the prior art, step 4 enhances the intelligence of the control system by applying a data-driven control model to real-time environmental monitoring. Traditional temperature control methods often adopt fixed adjustment strategies and lack in-depth analysis and adaptation to real-time changes. The implementation of step 4 means that the temperature control of the fermentation bin can be dynamically adjusted based on real-time data, greatly improving the flexibility and adaptability of the system, so that it can better meet the needs of different fermentation stages. In this patent scheme, the use of step 4 provides key real-time control capabilities for the overall scheme. By combining dynamic input with a trained control model, accurate and efficient temperature control is ensured. This process not only optimizes the fermentation conditions, but also provides a sustainable solution for achieving high-quality organic fertilizer production, enhancing the practical effect and economic benefits of the entire scheme.

[0103] See also Figure 2 , a temperature control system for an organic fertilizer fermentation bin, comprising:

[0104] The data acquisition module is used to obtain the environmental parameters of the fermentation bin and the corresponding control parameters at multiple historical moments, and obtain the environmental parameters of the fermentation bin at the current moment. There are five environmental parameters, including temperature, humidity, carbon dioxide concentration, oxygen concentration and comprehensive gas concentration, and the comprehensive gas concentration is the ratio of carbon dioxide concentration to oxygen concentration in the fermentation bin;

[0105] The data processing module is used to combine the comprehensive gas concentration, temperature and humidity to generate an environmental status index reflecting the environmental conditions in the fermentation chamber, set the target temperature, and calculate the temperature deviation from the target temperature;

[0106] The correlation analysis module is used to calculate the Pearson correlation coefficients between various environmental parameters and control parameters, and to screen out key parameters that are strongly correlated with the control parameters, build a control model with key parameters, temperature deviation and environmental status index as input, and control parameters as output, and use historical data to train the control model;

[0107] The regulating module is used to input the key parameters, temperature deviation and environmental status index at the current moment into the control model to obtain the control parameters at the current moment and perform temperature control based on the control parameters.

[0108] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0109] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product. Those skilled in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0110] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0111] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A temperature control method for an organic fertilizer fermentation bin, characterized in that: The specific steps include: Step 1: Obtain environmental parameters and corresponding control parameters of the fermentation bin at multiple historical moments, and obtain environmental parameters of the fermentation bin at the current moment. There are five environmental parameters, including temperature, humidity, carbon dioxide concentration, oxygen concentration and comprehensive gas concentration. The comprehensive gas concentration is the ratio of carbon dioxide concentration to oxygen concentration in the fermentation bin. The control parameter is the temperature adjustment amount. Step 2: Combine the comprehensive gas concentration, temperature and humidity to generate an environmental status index that reflects the environmental conditions in the fermentation chamber, set the target temperature, and calculate the temperature deviation from the target temperature; Step 3: Calculate the Pearson correlation coefficients between various environmental parameters and control parameters, and use them to screen out key parameters that are strongly correlated with control parameters. Construct a control model whose inputs are key parameters, temperature deviation, and environmental status index, and whose outputs are control parameters. Use historical data to train the control model. Step 4: Input the key parameters, temperature deviation and environmental status index at the current moment into the control model to obtain the control parameters at the current moment, and perform temperature control based on the control parameters.

2. The temperature control method for an organic fertilizer fermentation warehouse according to claim 1, characterized in that: The top, bottom and middle positions of the fermentation bin are set as key positions, and sensors are used to obtain the temperature, humidity, carbon dioxide concentration and oxygen concentration at each key position in the fermentation bin, and the average value is used as the temperature, humidity, carbon dioxide concentration and oxygen concentration of the fermentation bin.

3. The temperature control method of a kind of organic fertilizer fermentation warehouse according to claim 1 is characterized in that: The data obtained in step 1 is preprocessed as raw data, and then the preprocessed data is used for subsequent steps. The preprocessing is to convert the raw data into corresponding standard scores. The formula for converting the standard scores is as follows: Among them, Z is the standard score, R is the original data, μ is the average value of the same type of original data, and σ is the standard deviation of the same type of original data; The target temperature is preprocessed in the same way to obtain a standard score corresponding to the target temperature, and in the standard score calculation formula corresponding to the target temperature, the mean value and standard deviation adopt the mean value and standard deviation of the temperature respectively.

4. The temperature control method for an organic fertilizer fermentation warehouse according to claim 1, characterized in that: The comprehensive gas concentration in the fermentation chamber is calculated based on the formula: Among them, GAS is the comprehensive gas concentration in the fermentation chamber, is the carbon dioxide concentration, is the oxygen concentration; The environmental status index of the fermentation warehouse is calculated according to the following formula: Among them, ENV is the environmental status index of the fermentation chamber, T is the current temperature of the fermentation chamber, and T y is the temperature threshold, S is the humidity, S y is the optimal humidity value of the fermentation chamber, GAS is the comprehensive gas concentration, GAS y is the optimal comprehensive gas concentration, ω1 and ω2 are preset proportional coefficients, and ω1>ω2>0.

5. The temperature control method for an organic fertilizer fermentation warehouse according to claim 1, characterized in that: Set the target temperature to T set , the formula for calculating temperature deviation is as follows: ΔT=T set -T Where ΔT is the temperature deviation from the target temperature, T set is the target temperature, and T is the current temperature of the fermentation chamber.

6. The temperature control method of an organic fertilizer fermentation warehouse according to claim 1, characterized in that: The logic behind determining key parameters is: The Pearson correlation coefficient between temperature and control parameters is calculated according to the following formula: Among them, r(T) is the Pearson correlation coefficient between temperature and control parameters, T j represents the temperature obtained at the jth historical moment, U j represents the control parameters obtained at the jth historical moment, is the average temperature obtained at all historical moments, The mean value of the control parameters obtained for all historical moments; Similarly, the Pearson correlation coefficient between humidity and control parameters, the Pearson correlation coefficient between carbon dioxide concentration and control parameters, the Pearson correlation coefficient between oxygen concentration and control parameters, and the Pearson correlation coefficient between comprehensive gas concentration and control parameters are obtained; Sort the environmental parameters from large to small according to the absolute value of the Pearson correlation coefficient, and select at least the top two environmental parameters as key parameters.

7. The temperature control method of an organic fertilizer fermentation warehouse according to claim 1, characterized in that: The expression of the control model is as follows: Among them, U is the control parameter, ΔT is the temperature deviation, ENV is the environmental status index, A k is the kth key parameter, α is the weight coefficient of temperature deviation, β is the weight coefficient of environmental state index, γ k is the weight coefficient of the kth key parameter, k is the type index of the key parameter, and k∈[1,K], K is the total number of key parameter types, and |α|>|β|>|γ k |, and the weight coefficient relationship of each key parameter is set according to the absolute value of its Pearson correlation coefficient, and C1 is the first constant correction index.

8. The temperature control method for an organic fertilizer fermentation bin according to claim 1, characterized in that: The method for temperature control based on control parameters is: adjusting the heater and ventilation equipment according to the control parameters, and arranging phase change materials in the fermentation bin to adjust the temperature in the fermentation bin.

9. A temperature control system for an organic fertilizer fermentation bin, characterized in that: The temperature control system of an organic fertilizer fermentation bin is used to implement the temperature control method of an organic fertilizer fermentation bin according to any one of claims 1 to 8, comprising: The data acquisition module is used to obtain the environmental parameters of the fermentation bin and the corresponding control parameters at multiple historical moments, and obtain the environmental parameters of the fermentation bin at the current moment. There are five environmental parameters, including temperature, humidity, carbon dioxide concentration, oxygen concentration and comprehensive gas concentration, and the comprehensive gas concentration is the ratio of carbon dioxide concentration to oxygen concentration in the fermentation bin; The data processing module is used to combine the comprehensive gas concentration, temperature and humidity to generate an environmental status index reflecting the environmental conditions in the fermentation chamber, set the target temperature, and calculate the temperature deviation from the target temperature; The correlation analysis module is used to calculate the Pearson correlation coefficients between various environmental parameters and control parameters, and to screen out key parameters that are strongly correlated with the control parameters, build a control model with key parameters, temperature deviation and environmental status index as input, and control parameters as output, and use historical data to train the control model; The regulating module is used to input the key parameters, temperature deviation and environmental status index at the current moment into the control model to obtain the control parameters at the current moment and perform temperature control based on the control parameters.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the temperature control method for an organic fertilizer fermentation bin according to any one of claims 1 to 8 is implemented.

Images