A smart monitoring method and system for the resource utilization of livestock and poultry manure

Abstract

This application discloses an intelligent monitoring method and system for the resource utilization of livestock and poultry manure, relating to the field of data monitoring technology. The method includes the following steps: acquiring manure testing data for the current batch; calculating the organic matter content coefficient in the manure testing data based on organic loss; determining a manure microbial quantity adjustment coefficient for resource utilization of the current batch of manure based on the degree of change between the organic matter content coefficient and the organic matter content coefficient in historical batches of manure testing data; and adjusting the amount of biological bacteria used in the current batch of manure based on the manure microbial quantity adjustment coefficient to facilitate resource conversion of the current batch of manure. This application improves the resource utilization efficiency of manure.

Description

Technical Field

[0001] This application relates to the field of data supervision technology, and in particular to an intelligent supervision method and system for the resource utilization of livestock and poultry manure. Background Technology

[0002] Currently, in order to reduce pollution and promote resource recycling, manure resource utilization and treatment facilities are being built in breeding areas to transform waste into resources, thereby significantly improving resource utilization efficiency while reducing environmental pollution.

[0003] In the process of treating manure, fixed process parameters are often used to utilize livestock and poultry manure for resource recovery. However, the concentration or state of manure varies between different batches, which leads to differences in the resource recovery effect under this method, resulting in poor resource recovery. Summary of the Invention

[0004] The main purpose of this application is to provide an intelligent monitoring method and system for the resource utilization of livestock and poultry manure, aiming to solve the technical problem that the resource utilization effect is poor when using fixed process parameters to utilize livestock and poultry manure.

[0005] To achieve the above objectives, embodiments of this application provide an intelligent monitoring method for the resource utilization of livestock and poultry manure, comprising:

[0006] Obtain the fecal waste test data for the current batch;

[0007] Based on the organic loss in the fecal waste detection data, the organic matter occupancy coefficient in the fecal waste detection data is calculated;

[0008] Based on the degree of change between the organic matter occupancy coefficient and the organic matter coefficient in historical batches of fecal waste detection data, the fecal waste bacterial quantity adjustment coefficient is determined when the current batch of fecal waste is used for resource utilization.

[0009] Based on the fecal microbial content adjustment coefficient, the amount of biological bacteria used in the current batch of fecal waste is adjusted to facilitate resource conversion of the current batch of fecal waste.

[0010] In one possible implementation of this application, the organic matter occupancy coefficient in the fecal waste detection data is calculated based on the organic loss in the fecal waste detection data, including:

[0011] Based on the manure testing data, the feed-to-manure conversion rate of the current batch of livestock and poultry is calculated;

[0012] To obtain the content of harmful gases generated at different times during the sewage collection process;

[0013] Based on the content of harmful gases and the feed-manure conversion rate at each time point, the material content loss coefficient of livestock and poultry manure is calculated.

[0014] Based on the material content loss coefficient, the organic matter content coefficient in the fecal waste detection data is calculated.

[0015] In one possible implementation of this application, the manure conversion rate of the current batch of livestock and poultry is calculated based on manure detection data, including:

[0016] Obtain the current batch feed usage, livestock digestion time, and manure collection volume from the manure testing data;

[0017] The feed-to-manure conversion rate of livestock and poultry is calculated based on the current batch feed usage, livestock and poultry digestion time, and manure collection volume.

[0018] In one possible embodiment of this application, the material content loss coefficient of livestock and poultry manure is calculated based on the content of harmful gases and the feed-manure conversion rate at each time point, including:

[0019] Based on the content of harmful gases at each time point and the slope of change of harmful gas content, the coefficient of variation of harmful gas content is calculated.

[0020] Extract the humidity changes at various times from the fecal waste detection data;

[0021] Determine the first ratio between the coefficient of variation of harmful gas content and the change in humidity;

[0022] Based on the first ratio and the feed-to-manure conversion rate, the material content loss coefficient of livestock and poultry manure is calculated.

[0023] In one possible implementation of this application, a coefficient of variation of harmful gas content is calculated based on the content of harmful gas at each time point and the slope of change of harmful gas content, including:

[0024] Calculate the maximum and average concentrations of harmful gases at each time point;

[0025] Determine the difference in the slope of the change in the content of harmful gases at different adjacent time points;

[0026] The coefficient of variation of harmful gas content is calculated based on the average value of the difference in slope, the maximum content value, and the average content value.

[0027] In one possible embodiment of this application, the organic matter content coefficient in the fecal waste detection data is calculated based on the material content loss coefficient, including:

[0028] Solid-liquid separation was performed on the fecal waste collection data from the fecal waste detection data, and the solid-liquid ratio of the collected fecal waste after solid-liquid separation was calculated.

[0029] The organic matter content coefficient in the fecal waste test data is calculated based on the product between the solid-liquid ratio of fecal waste and the material content loss coefficient.

[0030] In one possible implementation of this application, based on the degree of change in the coefficient between the organic matter occupancy coefficient and the organic matter in historical batches of fecal waste detection data, an adjustment coefficient for the amount of fecal bacteria in the current batch of fecal waste is determined for resource utilization, including:

[0031] Based on the feed-manure conversion rate, the difference coefficient between the feed-manure conversion rate of the current batch and the historical batches is calculated;

[0032] Based on the feed-to-manure conversion rate from historical batches of manure and sewage testing data, the organic matter baseline value corresponding to the organic matter occupancy coefficient is calculated.

[0033] Based on the organic matter baseline value, the difference coefficient, and the organic matter occupancy coefficient, the adjustment coefficient of fecal bacteria quantity when the current batch of fecal waste is used for resource utilization is calculated.

[0034] In one possible implementation of this application, a difference coefficient for the feed-manure conversion rate between the current batch and historical batches is calculated based on the feed-manure conversion rate, including:

[0035] Obtain the average of a preset number of feed-to-manure conversion rates from multiple historical batches before sorting by mode. The multiple feed-to-manure conversion rates from the historical batches are sorted in ascending order.

[0036] The mean value is used as the standard parameter for feed-manure conversion rate. Based on the standard parameter and the feed-manure conversion rate of the current batch, the difference coefficient between the feed-manure conversion rate of the current batch and the historical batches is calculated.

[0037] In one possible implementation of this application, the dosage of biological agents for the current batch of fecal waste is adjusted based on a fecal bacteria quantity adjustment coefficient, including:

[0038] Determine the standard dosage of beneficial bacteria corresponding to the baseline value of organic matter;

[0039] The dosage of biological bacteria for the current batch of fecal waste is adjusted based on the product between the fecal bacteria quantity adjustment coefficient and the standard dosage of biological bacteria.

[0040] This application also provides an intelligent monitoring system for the resource utilization of livestock and poultry manure. The intelligent monitoring system for the resource utilization of livestock and poultry manure includes a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any intelligent monitoring method for the resource utilization of livestock and poultry manure.

[0041] This application provides an intelligent monitoring method and system for the resource utilization of livestock and poultry manure. Compared with related technologies that use fixed process parameters for the resource utilization of livestock and poultry manure, the latter suffers from varying concentrations or states between different batches of manure, leading to inconsistent resource utilization results and ultimately poor utilization. However, in this application, by acquiring the manure detection data of the current batch, and based on the organic loss in the manure detection data, the organic matter content coefficient in the manure detection data is calculated. The method then analyzes the changes in the organic matter content coefficient between this coefficient and the organic matter content coefficients of historical batches of manure detection data. The degree of adjustment coefficient for the amount of bacteria in the fecal waste is determined when the current batch of fecal waste is used for resource utilization. Then, based on the adjustment coefficient, the amount of biological bacteria used in the current batch of fecal waste is adjusted to facilitate resource conversion. The adjustment coefficient for the amount of bacteria in the fecal waste is determined by considering the proportion of organic matter in different batches of fecal waste and the degree of change between the organic matter content coefficient of the current batch of fecal waste and the organic matter coefficient in the historical batches of fecal waste detection data. This avoids the situation where the resource utilization effect is poor due to the different concentrations or states of fecal waste between different batches, and improves the resource conversion / utilization effect of fecal waste. Attached Figure Description

[0042] Figure 1 This is a flowchart illustrating the first embodiment of the intelligent monitoring method for the resource utilization of livestock and poultry manure in this application.

[0043] Figure 2 This is a flowchart illustrating the second embodiment of the intelligent monitoring method for the resource utilization of livestock and poultry manure in this application.

[0044] Figure 3 This is a schematic diagram of the device structure of the hardware operating environment involved in the embodiments of this application. Detailed Implementation

[0045] It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit this application.

[0046] This application provides an intelligent monitoring method for the resource utilization of livestock and poultry manure. In the first embodiment of this intelligent monitoring method for the resource utilization of livestock and poultry manure, refer to... Figure 1 ,include:

[0047] Step S10: Obtain the fecal waste test data for the current batch;

[0048] Step S20: Based on the organic loss in the fecal waste detection data, calculate the organic matter occupancy coefficient in the fecal waste detection data;

[0049] Step S30: Based on the degree of change between the organic matter occupancy coefficient and the organic matter coefficient in the historical batch of fecal waste detection data, determine the fecal waste bacterial quantity adjustment coefficient when the current batch of fecal waste is used for resource utilization.

[0050] Step S40: Based on the fecal bacteria quantity adjustment coefficient, adjust the amount of biological bacteria used in the current batch of fecal waste to carry out resource conversion of the current batch of fecal waste.

[0051] This embodiment aims to determine the fecal microbial content adjustment coefficient based on the organic matter content of different batches of fecal waste and the degree of change between the organic matter content coefficient of the current batch of fecal waste and the organic matter content coefficient of historical batches of fecal waste detection data. This will help avoid poor resource utilization due to differences in concentration or state between different batches of fecal waste and improve the resource conversion / utilization effect of fecal waste.

[0052] The specific steps are as follows:

[0053] Step S10: Obtain the fecal waste test data for the current batch.

[0054] As an example, the intelligent monitoring method for the resource utilization of livestock and poultry manure can be applied to an intelligent monitoring device for the resource utilization of livestock and poultry manure, which belongs to the category of intelligent monitoring equipment for the resource utilization of livestock and poultry manure.

[0055] As an example, manure testing data can be obtained through multi-device testing during livestock and poultry farming, and the data can be uploaded to a regulatory system platform. Methods for obtaining manure testing data include, but are not limited to, the following:

[0056] 1. Use temperature and humidity sensors to detect air temperature and humidity during livestock and poultry farming, and use gas detectors to obtain information on the volatilization of manure in livestock and poultry farms.

[0057] 2. The timing and weight of manure collection are obtained by using the scraper to start the timer and the weighbridge, and the viscosity of the manure is obtained by using a solid-liquid separation device.

[0058] 3. The amount added is analyzed based on the total amount of feed added. The amount used can be analyzed by observing the amount of feed remaining when adding the feed.

[0059] Furthermore, data is sampled at regular intervals, such as 1 minute or 10 minutes. For real-time detection data, the data is numbered according to the detection time. For detection data at a single moment, such as the time of fecal collection, the start time of the scraper is recorded as the time of fecal collection.

[0060] As an example, the cleaning of livestock and poultry manure is done in different batches, with intervals of one week or ten days between each batch, without any specific time limit.

[0061] Step S20: Based on the organic loss in the fecal waste detection data, calculate the organic matter occupancy coefficient in the fecal waste detection data.

[0062] As an example, the differences in the content of substances in manure can affect the efficiency of manure resource utilization and conversion. If fixed process parameters are used for resource utilization, the best treatment effect cannot be obtained. Therefore, in order to improve the efficiency of livestock and poultry manure resource utilization, it is necessary to analyze the detection data of manure collection during the generation process, and then analyze the quality differences or organic matter differences of manure from the manure generation process, so as to adjust the process parameters in the manure resource utilization process.

[0063] As an example, in the process of livestock and poultry farming, the quality of manure in the manure testing data is similar. However, when the health status of livestock and poultry is abnormal or the livestock and poultry farming environment is abnormal, the amount of feed consumed or digested by livestock and poultry may be abnormal. This leads to differences in the parameters of the produced manure compared with historical manure parameters, and there will be losses in the manure. In this case, the organic matter content of each batch of manure will be different. Therefore, it is necessary to calculate the organic matter content coefficient in the manure testing data.

[0064] As an example, the organic matter content coefficient represents the proportion of organic matter in the amount of livestock and poultry manure collected. The amount of organic matter directly affects the resource utilization effect in this embodiment.

[0065] The step S20, which calculates the organic matter content coefficient in the fecal waste detection data based on the organic loss in the fecal waste detection data, includes steps S21 to S24:

[0066] Step S21: Based on the manure detection data, calculate the feed-to-manure conversion rate of the current batch of livestock and poultry.

[0067] As an example, feed-to-manure conversion ratio represents the ratio of feed mass to manure mass produced by livestock and poultry, indicating the conversion efficiency of feed and manure. The higher the value, the slower the digestion of livestock and poultry in the farm.

[0068] The step S21, which calculates the manure conversion rate of the current batch of livestock and poultry based on manure detection data, includes:

[0069] Obtain the current batch feed usage, livestock digestion time, and manure collection volume from the manure testing data.

[0070] The feed-to-manure conversion rate of livestock and poultry is calculated based on the current batch feed usage, livestock and poultry digestion time, and manure collection volume.

[0071] As an example, the current batch feed usage is the amount of feed consumed by livestock and poultry within the corresponding time period of the current batch. The digestion time of livestock and poultry can be the time period between the feed addition time and the operation time of the manure scraper. This time period is considered as the digestion time of livestock and poultry. The amount of manure collected is the amount of manure collected by the manure scraper.

[0072] As an example, the feed-to-manure conversion rate L can be calculated as follows:

[0073]

[0074] In the formula, This represents the amount of feed used within the current batch and time period. For the amount of feces and sewage collected, The feed-to-manure ratio, This refers to the manure conversion time, i.e., the digestion time of livestock and poultry. This is an inverse proportionality coefficient for digestion time, used as a unit of time. The feed-to-manure ratio per unit time represents the feed-to-manure conversion efficiency.

[0075] Step S22: Obtain the content of harmful gases generated at different times during the fecal collection process.

[0076] As an example, the content of harmful gases can be the content of nitrogen and ammonia. During the livestock and poultry breeding period, the manure produced is not cleaned up immediately after it is produced, but is cleaned up uniformly with a manure scraper after a period of time. If it is not cleaned up in time, the accumulated manure will be continuously decomposed by microorganisms in the farm. In this process, harmful gases such as ammonia will be produced, thereby reducing the nitrogen element in the livestock and poultry manure and reducing the substance content of the manure.

[0077] Specifically, during the decomposition of manure by microorganisms, the more suitable the temperature, the more active the microorganisms, the faster the decomposition rate, leading to an increase in the concentration of nitrogen and ammonia in the air, which in turn reduces the carbon-nitrogen ratio of the collected manure and ultimately affects the quality of the resource utilization products. Conversely, in low-temperature or dry environments, the activity of microorganisms is inhibited, the decomposition rate slows down, and the negative impact of manure accumulation on the farm environment is also reduced. Furthermore, without changing the feed, the content of substances in livestock and poultry manure is affected by the temperature and humidity of the environment.

[0078] Step S23: Based on the content of harmful gases and the feed-manure conversion rate at each time point, calculate the material content loss coefficient of livestock and poultry manure.

[0079] As an example, the process of collecting feces and sewage corresponds to a collection period. This period can be divided into multiple moments, and the time interval between two adjacent moments can be 10 seconds, 30 seconds, etc., without any specific limitation.

[0080] As an example, the content of harmful gases can affect the consumption of manure produced by livestock and poultry. The difference coefficient indicates the absorption of feed by livestock and poultry. Therefore, the loss coefficient of the material content of manure produced by livestock and poultry is considered from two aspects.

[0081] As an example, the material content loss coefficient represents the material loss of manure produced by livestock and poultry. The larger the material content loss coefficient, the greater the material loss.

[0082] Step S23, which calculates the material content loss coefficient of livestock and poultry manure based on the content of harmful gases and the feed-manure conversion rate at each time point, includes:

[0083] Based on the content of harmful gases at each time point and the slope of change of the content of harmful gases, the coefficient of variation of the content of harmful gases is calculated.

[0084] As an example, the coefficient of variation of harmful gas content is used to represent the change in the content of harmful gases. The content of harmful gases is constantly changing at different times during the collection of feces and sewage. The coefficient of variation of harmful gas content during the collection process can be determined based on the content of harmful gases at different times and the slope of the change in the content of harmful gases.

[0085] The step of calculating the coefficient of variation of harmful gas content based on the content of harmful gases at each time point and the slope of change of harmful gas content includes:

[0086] Calculate the maximum and average content of harmful gases at each time point.

[0087] As an example, the maximum content is the maximum value of the harmful gas content at each detected time, while the average content is the average value of the harmful gas content at each time.

[0088] Determine the difference in the slope of the change in the content of harmful gases at different adjacent time points.

[0089] As an example, the content of harmful gases at each time point corresponds to a slope of change, and the difference in slope is the difference obtained by subtracting the slopes of change of harmful gas content at adjacent time points.

[0090] The coefficient of variation of harmful gas content is calculated based on the average value of the difference in slope, the maximum content value, and the average content value.

[0091] As an example, the coefficient of variation B for harmful gas content can be calculated as follows:

[0092]

[0093] In the formula, This represents the maximum concentration of harmful gases. The average content is measured, where the subscript N indicates a harmful gas, such as nitrogen and ammonia. Let be the slope of the change in the content of harmful gases at time i+1. This represents the difference in the slope of the change in harmful gas content between adjacent time points (time point i+1 and time point i). The mean value of the slope difference of gas content change is used to represent the incremental change of harmful gas content. Here, I represents the total number of times harmful gases are detected during the manure collection process. When the slope difference value is positive, the detected gas content in the farm increases, microorganisms are active, and the content of substances present in the manure decreases.

[0094] As an example, based on the changes in the content of harmful gases in the air, the amount of fecal waste degraded during that period was analyzed. The greater the amount of degradation, the faster the degradation rate and the faster the loss of organic matter. At this time, the content of substances that are conducive to resource utilization is lower, which reduces the resource utilization effect.

[0095] Extract the humidity changes at various times from the fecal waste detection data.

[0096] As an example, during the manure collection process, changes in temperature and humidity also affect the degradation rate of microorganisms. In order to ensure the stable health status in the farm, the temperature fluctuation is small. However, with the decomposition of microorganisms, the humidity in the farm increases, an anaerobic environment is formed, volatile fatty acids accumulate, leading to a decrease in the pH value of the manure and an increase in the conversion rate of ammonium nitrogen to ammonia. This results in a decrease in the content of resource substances in the manure. Therefore, based on the humidity change at each time point and the coefficient of variation of harmful gas content, the material content loss coefficient of livestock and poultry manure is determined.

[0097] Determine the first ratio between the coefficient of variation of harmful gas content and the change in humidity.

[0098] As an example, the first ratio is the ratio between the coefficient of variation of harmful gas content and the amount of humidity change, which represents the resource material loss coefficient under the influence of humidity change on harmful gas content variation.

[0099] Based on the first ratio and the feed-to-manure conversion rate, the material content loss coefficient of livestock and poultry manure is calculated.

[0100] As an example, the material content loss coefficient R can be calculated as follows:

[0101]

[0102] In the formula, This is the ratio of the coefficient of variation in harmful gas content to the change in humidity when fecal waste is not collected; it is also known as the first ratio, representing the resource loss coefficient under the influence of humidity changes on harmful gas content. The absolute value of the product of the loss coefficient and the feed-manure conversion rate is the material loss coefficient of manure during the non-collection period under the current feed-manure conversion rate. The result is normalized using the tanh() function. The greater the material loss, the greater the normalized material content loss coefficient.

[0103] Step S24: Based on the material content loss coefficient, calculate the organic matter content coefficient in the fecal waste detection data.

[0104] As an example, the organic matter content coefficient of the collected fecal waste is calculated based on the amount of material loss in the collected fecal waste.

[0105] The step of calculating the organic matter content coefficient in fecal waste testing data based on the material content loss coefficient includes:

[0106] Solid-liquid separation was performed on the fecal waste collection data from the fecal waste detection data, and the solid-liquid ratio of the collected fecal waste after solid-liquid separation was calculated.

[0107] As an example, after the collection of livestock and poultry manure, the manure contains a large amount of liquid, which causes the gaps in the manure to be filled with liquid, thus affecting the diffusion of oxygen in the gaps. Therefore, when the collected livestock and poultry manure is processed for resource utilization, it is necessary to perform solid-liquid separation treatment (after solid-liquid separation treatment, the solid part still contains a small amount of liquid). This is beneficial to the resource utilization of livestock and poultry manure, while also obtaining information on the digestion of feed by livestock.

[0108] As an example, the solid-liquid ratio of fecal waste It can be represented as:

[0109]

[0110] in, This represents the weight of the solid after solid-liquid separation. The amount of manure collected is the amount of feed. The higher the GY value, the better the digestion of feed by livestock and poultry, and the less organic matter content in the manure. In this embodiment, the calculation is performed under the scenario of complete digestion, without considering the case of direct discharge of feed residue. The better the digestion of feed by livestock and poultry, the less organic matter content in the manure.

[0111] The organic matter content coefficient in the fecal waste test data is calculated based on the product between the solid-liquid ratio of fecal waste and the material content loss coefficient.

[0112] As an example, the organic matter occupancy factor Z can be calculated as follows:

[0113]

[0114] In the formula, This is the product of the material loss coefficient of manure and the solid-liquid ratio of manure. It reflects the relationship between the solid-liquid ratio and the material loss in feed. The lower the solid-liquid ratio, the worse the digestibility, indicating a greater loss of substances from manure relative to feed. The function performs inverse proportional normalization on the results. A higher proportion of solid mass in the feces indicates less organic matter, and a larger material loss coefficient also indicates a higher organic matter content coefficient in the feces. The smaller the value, the lower the proportion of organic matter in the sewage.

[0115] Step S30: Based on the degree of change between the organic matter occupancy coefficient and the organic matter coefficient in the historical batch of fecal waste detection data, determine the fecal waste bacterial quantity adjustment coefficient for the current batch of fecal waste when it is used for resource utilization.

[0116] As an example, based on the difference in organic matter between the current batch and historical batches, an adjustment coefficient for the amount of bacteria in the fecal waste is determined. This adjustment coefficient is then used to adjust the process parameters / bacterial dosage when utilizing the current batch of fecal waste for resource recovery, thereby maximizing the resource recovery effect.

[0117] Step S40: Based on the fecal bacteria quantity adjustment coefficient, adjust the amount of biological bacteria used in the current batch of fecal waste to carry out resource conversion of the current batch of fecal waste.

[0118] As an example, after calculating the adjustment coefficient for the amount of bacteria in the fecal waste, the standard dosage of biological bacteria is adaptively adjusted based on the adjustment coefficient for the current batch of fecal waste, so as to transform the current batch of fecal waste into resources and improve resource utilization efficiency.

[0119] This application provides an intelligent monitoring method for the resource utilization of livestock and poultry manure. Compared to related technologies that utilize livestock and poultry manure with fixed process parameters, where differences in concentration or state between batches lead to varying resource utilization effects and poor overall efficiency, this application obtains manure testing data for the current batch. Based on the organic loss in the manure testing data, it calculates the organic matter content coefficient. Based on the degree of change between the organic matter content coefficient and the organic matter coefficient in historical batches, it determines the manure microbial quantity adjustment coefficient for resource utilization. Furthermore, based on this adjustment coefficient, it adjusts the amount of biological bacteria used in the current batch of manure to facilitate resource conversion. By determining the organic matter content coefficient of the current batch and the degree of change between the organic matter content coefficient and the organic matter coefficient in historical batches, the microbial quantity adjustment coefficient is determined. This avoids the poor resource utilization effect caused by differences in concentration or state between different batches of manure, thus improving the resource conversion / utilization efficiency of manure.

[0120] Furthermore, referring to Figure 2 Based on the first embodiment of this application, another embodiment of this application is provided. In this embodiment, step S30, which determines the fecal microbial quantity adjustment coefficient for the current batch of fecal waste for resource utilization based on the degree of change between the organic matter occupancy coefficient and the organic matter coefficient in historical batch fecal waste detection data, includes:

[0121] Step S31: Based on the feed-to-manure conversion rate, calculate the difference coefficient of the feed-to-manure conversion rate between the current batch and historical batches.

[0122] As an example, by calculating the feed-to-manure conversion rate of the current batch and the corresponding feed-to-manure conversion rate of historical batches, and then determining the difference between the two, the difference in feed-to-manure conversion between the current batch and historical batches can be determined.

[0123] The step S31, which calculates the difference coefficient of feed-manure conversion rate between the current batch and historical batches based on the feed-manure conversion rate, includes:

[0124] Obtain the average of a preset number of feed-to-manure conversion rates from multiple historical batches before sorting by mode. The feed-to-manure conversion rates from multiple historical batches are sorted in ascending order.

[0125] As an example, the preset quantity can be 3 or 4, and there is no specific limit.

[0126] As an example, taking pigs as an example, the feed-to-manure conversion rate is different for different types of pigs. For example, the modes of feed-to-manure conversion rates for growing pigs, adult pigs, and meat pigs are 15%, 25%, and 30%, respectively. Arranged in ascending order, the mean of this value is...

[0127] (15% + 25% + 30%) / 3 = 23.3%.

[0128] The mean value is used as the standard parameter for feed-manure conversion rate. Based on the standard parameter and the feed-manure conversion rate of the current batch, the difference coefficient between the feed-manure conversion rate of the current batch and the historical batches is calculated.

[0129] As an example, the standard parameter for feed-to-manure conversion rate Represented as:

[0130]

[0131] Where m1, m2, and m3 represent the modes of the top three feed-to-manure conversion rates. This is the mean of the modes of the top 3 feed-to-manure conversion rates.

[0132] As an example, the difference coefficient H can be calculated as follows:

[0133]

[0134] In the formula, L represents the feed-to-manure conversion rate of the current batch. This indicates the standard parameter for feed-to-manure conversion rate. The difference between the current feed conversion rate and the standard parameter for feed-to-manure conversion rate is used. The function normalizes the results and obtains the difference coefficient of feed conversion rate between the current batch and historical batches.

[0135] As an example, if the current feed-to-manure conversion rate difference coefficient If the current rate of manure conversion is high, it indicates that the livestock and poultry may have digestive abnormalities, resulting in a high carbon content in the manure. When manure is not cleaned using a scraper, the manure accumulates, the composting temperature rises, the microbial activity in the manure is high, and the microbial conversion efficiency is high, which increases the nitrogen and ammonia content in the air.

[0136] Conversely, when H < 0, livestock and poultry absorb feed better, organic matter in manure is reduced, and microbial activity is lower.

[0137] Step S32: Based on the feed-to-manure conversion rate of manure detection data in historical batches, calculate the organic matter baseline value corresponding to the organic matter occupancy coefficient.

[0138] As an example, when treating manure, biological bacteria or enzymes are added to improve the resource utilization rate of manure. Each time, a standard amount is added as the baseline, which is the amount of livestock and poultry manure generated under normal conditions. However, the amount of manure generated each time is uncertain. Therefore, the baseline value of organic matter is calculated based on the feed-to-manure conversion rate of manure detection data in historical batches.

[0139] As an example, the organic matter benchmark is based on the feed-to-manure conversion rate standard parameter. The calculated result is obtained by using the standard parameter of feed-to-manure conversion rate. Substitute these values ​​into the formula for calculating the substance content loss coefficient R, and then calculate the organic matter baseline value based on the obtained substance content loss coefficient.

[0140] Step S33: Based on the organic matter baseline value, the difference coefficient, and the organic matter occupancy coefficient, calculate the fecal microbial quantity adjustment coefficient for the current batch of fecal waste when it is used for resource utilization.

[0141] As an example, the adjustment coefficient for fecal microbial count The calculation method can be:

[0142]

[0143] In the formula, The ratio of the current organic matter content coefficient in fecal waste to the baseline organic matter value is used as an adjustment parameter, where H represents the difference coefficient. Obtain the sign value as the adjustment direction. The parentheses represent the sign function, where positive values ​​are set to 1, negative values ​​to -1, and negative values ​​to 0. tanh() is the normalization function.

[0144] Among them, through The symbolic function obtains the symbol of the current manure-feed conversion rate bias coefficient, which is used to analyze the digestive state of livestock and poultry when manure is generated, thereby obtaining the increase or decrease of organic matter and other substances in the manure.

[0145] The step S40, which adjusts the dosage of biological agents for the current batch of fecal waste based on the fecal bacteria quantity adjustment coefficient, includes:

[0146] Determine the standard dosage of beneficial bacteria corresponding to the organic matter baseline value.

[0147] The dosage of biological bacteria for the current batch of fecal waste is adjusted based on the product between the fecal bacteria quantity adjustment coefficient and the standard dosage of biological bacteria.

[0148] As an example, the standard dosage of biological bacteria is the organic matter content coefficient under conventional standards. The amount of biological bacteria used It was obtained by calibration based on the test data of various fecal wastes from historical batches.

[0149] As an example, the organic matter content coefficient of the current batch of fecal waste is obtained by multiplying the fecal bacteria quantity adjustment coefficient with the standard dosage of biological bacteria. The amount of biological bacteria used below :

[0150]

[0151] in, This represents the adjustment coefficient for fecal bacteria count. This indicates the standard dosage of biological bacteria; when the organic matter in feces decreases, A negative value indicates that the amount of beneficial bacteria used in the current batch is less than the standard dosage. This occurs when the amount of organic matter in the sewage increases. If the value is positive, the amount of beneficial bacteria used in the current batch is higher than the standard amount.

[0152] Subsequently, the system informs the resource utilization engineering operators of the analysis results through the terminal display device, and at the same time visualizes the data of the livestock and poultry breeding process, so as to facilitate the operators to adjust the amount of biological bacteria used according to the actual situation.

[0153] In this embodiment, the amount of biological bacteria used in each batch of feces is adaptively adjusted by calculating the fecal bacteria quantity adjustment coefficient for resource utilization of the current batch based on the fecal waste detection data obtained in real time and the organic matter content coefficient of the fecal waste detection data.

[0154] Reference Figure 3 , Figure 3 This is a schematic diagram of the device structure of the hardware operating environment involved in the embodiments of this application.

[0155] like Figure 3 As shown, the intelligent monitoring device for the resource utilization of livestock and poultry manure may include: a processor 1001, a memory 1005, and a communication bus 1002. The communication bus 1002 is used to realize the connection and communication between the processor 1001 and the memory 1005.

[0156] Optionally, the intelligent monitoring equipment for the resource utilization of livestock and poultry manure may also include a user interface, a network interface, a camera, RF (Radio Frequency) circuitry, sensors, a WiFi module, etc. The user interface may include a display screen and an input submodule such as a keyboard; optionally, the user interface may also include standard wired or wireless interfaces. The network interface may include standard wired or wireless interfaces (such as a Wi-Fi interface).

[0157] Those skilled in the art will understand that Figure 3 The structure of the intelligent monitoring equipment for the resource utilization of livestock and poultry manure shown in the figure does not constitute a limitation on the intelligent monitoring equipment for the resource utilization of livestock and poultry manure. It may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0158] like Figure 3 As shown, the memory 1005, serving as a storage medium, may include an operating system, a network communication module, and an intelligent monitoring program for the resource utilization of livestock and poultry manure. The operating system is a program that manages and controls the hardware and software resources of the intelligent monitoring equipment for the resource utilization of livestock and poultry manure, supporting the operation of the intelligent monitoring program and other software and / or programs. The network communication module is used to enable communication between the various components within the memory 1005, as well as communication with other hardware and software in the intelligent monitoring system for the resource utilization of livestock and poultry manure.

[0159] exist Figure 3 In the intelligent monitoring device for the resource utilization of livestock and poultry manure shown, the processor 1001 is used to execute the intelligent monitoring program for the resource utilization of livestock and poultry manure stored in the memory 1005 to implement the steps of the intelligent monitoring method for the resource utilization of livestock and poultry manure mentioned above.

[0160] The specific implementation method of the intelligent monitoring device for the resource utilization of livestock and poultry manure in this application is basically the same as the embodiments of the intelligent monitoring method for the resource utilization of livestock and poultry manure described above, and will not be repeated here.

[0161] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0162] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0163] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods of the various embodiments of this application.

[0164] The above are merely preferred embodiments of this application and do not limit the scope of this application. Any equivalent structural or procedural transformations made based on the description and drawings of this application, or direct or indirect applications in other related technical fields, are similarly included within the scope of protection of this application.

[0165] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0166] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A method for intelligent monitoring of the resource utilization of livestock and poultry manure, characterized in that, The method includes: Step S10: Obtain the fecal waste test data for the current batch; Step S20: Based on the organic loss in the fecal waste detection data, calculate the organic matter occupancy coefficient in the fecal waste detection data; Step S20 includes: Step S21: Based on the manure detection data, calculate the feed-to-manure conversion rate of the current batch of livestock and poultry; Step S21 includes: Obtain the current batch feed usage, livestock digestion time, and manure collection volume from the manure detection data; Based on the current batch feed usage, livestock digestion time, and manure collection volume, the feed-to-manure conversion rate of livestock is calculated. The calculation method for the feed-to-manure conversion rate is as follows: ； In the formula, Indicates the feed-to-manure conversion rate. This represents the amount of feed used in the current batch. The amount of feces collected corresponds to the fecal waste detection data. For the digestion time of livestock and poultry It is an inverse proportionality coefficient for the digestion time of livestock and poultry; Step S22: Obtain the content of harmful gases generated at different times during the fecal collection process; Step S23: Based on the content of harmful gases and the feed-manure conversion rate at each time point, calculate the material content loss coefficient of livestock and poultry manure, wherein the material content loss coefficient is calculated as follows: ； In the formula, Indicates the loss coefficient of material content. This represents the coefficient of variation of harmful gas content. Indicates the amount of change in humidity. The feed-to-manure conversion rate is given by the tanh function, which represents the normalization process. The coefficient of variation for harmful gas content is calculated as follows: ； In the formula, This represents the maximum value of the harmful gas content. The value represents the average content of the harmful gases, where the subscript N indicates the harmful gas content. Let be the slope of the change in the content of harmful gases at time i+1. This represents the difference in the slope of the change in harmful gas content between time i+1 and time i. Mean value of the slope difference in the change rate of harmful gas content; Step S24: Based on the substance content loss coefficient, calculate the organic matter content coefficient in the fecal waste detection data, wherein the organic matter content coefficient is calculated as follows: ； In the formula, Z represents the organic matter occupancy coefficient. This represents the solid-liquid ratio of fecal waste. The calculation method for the solid-liquid ratio of fecal waste is as follows: ； in, The solid weight after solid-liquid separation of the fecal waste collection volume in the fecal waste detection data. This refers to the amount of fecal waste collected. Step S30: Based on the degree of change between the organic matter occupancy coefficient and the organic matter coefficient in the historical batch of fecal waste detection data, determine the fecal waste bacterial quantity adjustment coefficient when the current batch of fecal waste is used for resource utilization; Step S30 includes: Step S31: Based on the feed-manure conversion rate, calculate the difference coefficient of feed-manure conversion rate between the current batch and historical batches; The difference coefficient is calculated as follows: ； In the formula, This indicates the feed-to-manure conversion rate for the current batch. This indicates the standard parameter for feed-to-manure conversion rate; Step S32: Based on the feed-to-manure conversion rate from the historical batches of manure detection data, calculate the organic matter baseline value corresponding to the organic matter occupancy coefficient; Step S33: Based on the organic matter baseline value, the difference coefficient, and the organic matter occupancy coefficient, calculate the fecal microbial quantity adjustment coefficient when the current batch of fecal waste is used for resource utilization; The calculation method for the fecal bacteria quantity adjustment coefficient is as follows: ； In the formula, This is the ratio of the current organic matter content coefficient in fecal waste to the baseline value of organic matter. Step S40: Based on the fecal bacteria quantity adjustment coefficient, adjust the amount of biological bacteria used in the current batch of fecal waste to convert the current batch of fecal waste into resources.

2. The intelligent monitoring method for the resource utilization of livestock and poultry manure as described in claim 1, characterized in that, Step S23 includes: Step S230: Based on the content of harmful gases at each time point and the slope of change of the content of harmful gases, calculate the coefficient of variation of harmful gas content; Step S231: Extract the humidity change at each time point from the fecal waste detection data; Step S232: Determine the first ratio between the coefficient of variation of the harmful gas content and the change in humidity; Step S233: Based on the first ratio and the feed-manure conversion rate, calculate the material content loss coefficient of livestock and poultry manure.

3. The intelligent monitoring method for the resource utilization of livestock and poultry manure as described in claim 2, characterized in that, Step S230 includes: Calculate the maximum and average content of the harmful gas at each time point; Determine the difference in the slope of the change in the content of harmful gases at different adjacent time points; Based on the average value of the difference in the slope of change, the maximum value of the content, and the average value of the content, the coefficient of variation of the harmful gas content is calculated.

4. The intelligent monitoring method for the resource utilization of livestock and poultry manure as described in claim 1, characterized in that, Step S24 includes: The amount of fecal waste collected in the fecal waste detection data is subjected to solid-liquid separation processing, and the solid-liquid ratio of the collected fecal waste after solid-liquid separation is calculated. The organic matter content coefficient in the fecal waste detection data is calculated based on the product of the solid-liquid ratio of the fecal waste and the loss coefficient of the substance content.

5. The intelligent monitoring method for the resource utilization of livestock and poultry manure as described in claim 1, characterized in that, Step S31 includes: Obtain the average of a preset number of feed-to-manure conversion rates from multiple historical batches before sorting by mode. The multiple feed-to-manure conversion rates from the historical batches are sorted in ascending order. The average value is used as the standard parameter for feed-manure conversion rate. Based on the standard parameter for feed-manure conversion rate and the feed-manure conversion rate of the current batch, the difference coefficient of feed-manure conversion rate between the current batch and historical batches is calculated.

6. The intelligent monitoring method for the resource utilization of livestock and poultry manure as described in claim 1, characterized in that, Step S40 includes: Determine the standard dosage of the microorganisms corresponding to the organic matter baseline value; The dosage of biological bacteria for the current batch of fecal waste is adjusted based on the product of the fecal bacteria quantity adjustment coefficient and the standard dosage of biological bacteria.

7. An intelligent monitoring system for the resource utilization of livestock and poultry manure, characterized in that, The system includes a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that the processor executes the computer program to implement the steps of the method as described in any one of claims 1 to 6.

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