A composting process ammonia real-time monitoring system

Abstract

The application discloses a kind of composting process ammonia real-time monitoring system, it is related to gas measurement monitoring technical field, including information acquisition module, for obtaining data information in ammonia ion concentration measurement process, including electrochemical characteristic information and dynamic response characteristic information, and obtain the microorganism activity coefficient when microorganism decomposes fertilizer and produces ammonia in composting process;Comprehensive analysis module is used to combine the electrochemical characteristic information and dynamic response characteristic information with the microorganism activity coefficient based on machine learning algorithm to establish monitoring evaluation model, generates monitoring evaluation value;Hidden danger early warning module is used to compare and analyze monitoring evaluation value with preset monitoring evaluation threshold value, judge ammonia measurement accuracy, and according to the comparison and analysis result, the hidden danger that exists anomaly issues early warning prompt;Solve the problem that composting process ammonia is not accurately monitored, improve the ammonia real-time monitoring efficiency and ammonia measurement accuracy in composting process.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of gas measurement monitoring, more specifically, the present application relates to a real-time monitoring system for ammonia gas in composting process. BACKGROUND

[0002] Ammonia monitoring system in composting process is an important tool to ensure compost quality and optimize compost management. In recent years, the technology and application in this field have been developing, and various high-sensitivity ammonia sensors have been developed, including electrochemical sensors, optical sensors and metal oxide semiconductor sensors, etc. These sensors can realize real-time monitoring and have high accuracy and response speed. Advanced technologies such as gas chromatography (GC) and mass spectrometry (MS) can be used to accurately analyze the concentration and changes of ammonia in the composting process. These technologies are usually used for laboratory research, but gradually transform to field application. Many ammonia monitoring systems connect sensors with cloud platform to realize real-time uploading and remote monitoring of data. Users can check monitoring data at any time through mobile phones or computers. Through machine learning and data analysis, the collected ammonia data can be deeply analyzed to predict the gas release trend in the composting process and optimize the compost management.

[0003] The deficiencies of the prior art are as follows:

[0004] Inaccurate measurement may lead to ammonia emission exceeding the standard, causing pollution to the surrounding environment and affecting air quality. Excessive ammonia can have a negative impact on plant growth, leading to soil acidification and reduction of biodiversity. Excessive ammonia concentration may pose a threat to human health, and long-term exposure may cause respiratory problems, eye irritation and other health problems. In agriculture, ammonia emission is closely related to the use of nitrogen fertilizer, and insufficient measurement accuracy may lead to improper fertilization, affecting crop growth and yield. Excessive use of fertilizer may increase agricultural costs due to the inability to accurately assess ammonia release. Therefore, the present application relates to a real-time monitoring system for ammonia gas in composting process to monitor and analyze the measurement accuracy of ammonia, solving the problem of inaccurate ammonia monitoring in composting process.

[0005] To solve the above problems, the present application provides a solution. SUMMARY

[0006] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present application provide a real-time monitoring system for ammonia gas in composting process, which monitors and analyzes the measurement accuracy of ammonia to solve the problems raised in the background art.

[0007] To achieve the above-mentioned purpose, the present application provides the following technical solutions:

[0008] The application discloses a composting process ammonia real-time monitoring system, comprising the following steps: a concentration measurement module is used for obtaining an ammonia solution after ammonia is introduced into water, and an ion selective electrode method is used to measure the ammonia ion concentration in the solution; an information acquisition module is used for acquiring data information in the ammonia ion concentration measurement process, including electrochemical characteristic information and dynamic response characteristic information, and acquiring a microbial activity coefficient when microorganisms decompose fertilizer to produce ammonia in the composting process; a comprehensive analysis module is used for combining the electrochemical characteristic information and the dynamic response characteristic information with the microbial activity coefficient to establish a monitoring evaluation model based on a machine learning algorithm, and generating a monitoring evaluation value; a hidden danger early warning module is used for comparing and analyzing the monitoring evaluation value with a preset monitoring evaluation threshold value, judging the ammonia measurement accuracy, and issuing a warning prompt according to the comparison and analysis result when there is an abnormal hidden danger; and a feedback analysis module is used for maintaining and managing the accuracy abnormality in the ammonia measurement, and performing comprehensive standard deviation and mean value analysis on the monitoring evaluation value output in real time after the maintenance and management, and judging the maintenance and management result.

[0009] In a preferred embodiment, the specific process of measuring the ammonia ion concentration in the solution by using the ion selective electrode method is as follows: standard solutions with different known concentrations are obtained, and an electrode is immersed in the standard solutions; when the electrode potential is stable, the electrode potential value is recorded; the potential measurement process is repeated for each standard solution, and the corresponding potential value is recorded; the standard solution concentration and the potential value are fitted based on linear regression to draw a standard curve; the ion selective electrode is immersed in the to-be-measured solution; when the electrode potential is stable, the electrode potential value is recorded; and the concentration of the to-be-measured ammonia ion is obtained based on the drawn standard curve according to the electrode potential value.

[0010] In a preferred embodiment, the electrochemical characteristic information includes a dissolved concentration variation coefficient; and the dynamic response characteristic information includes an ammonia ion activity coefficient.

[0011] In a preferred embodiment, the specific acquisition step of the dissolved concentration variation coefficient is as follows: the electrode potential of the to-be-measured solution is measured multiple times by using the ion selective electrode method, and the corresponding ammonia ion concentration is found out according to the drawn standard curve; the ammonia ion concentration values measured each time are recorded to obtain a data set, and the average value and the standard deviation of the data set are calculated; and the dissolved concentration variation coefficient is calculated based on a preset variation coefficient formula according to the average value and the standard deviation.

[0012] In a preferred embodiment, the specific acquisition step of the ammonia ion activity coefficient is as follows: the conductivity of the to-be-measured solution is measured, the concentrations of various ions in the solution are calculated according to the measured conductivity, the ionic strength of the solution is calculated according to the concentrations of the various ions and the charge numbers of the various ions, and the ammonia ion activity coefficient is calculated based on the Debye-Hückel formula according to the ionic strength of the solution, the charge of the ammonia ion and the radius of the ammonia ion.

[0013] In a preferred embodiment, the specific acquisition method of the microbial activity coefficient is as follows: collect the compost solution, dilute the solution and inoculate into the culture medium, cultivate at a suitable temperature and time; obtain the initial cell concentration and the cell concentration at time t, calculate the growth rate based on the growth curve according to the initial cell concentration and the cell concentration at time t, and take the ratio of the growth rate to the concentration of available nutrients in the known substrate as the microbial activity coefficient.

[0014] In a preferred embodiment, the specific implementation process of the hidden danger early warning module is as follows: the monitoring evaluation value is compared and analyzed with the preset monitoring evaluation threshold value, and it is judged whether the ammonia gas measurement accuracy is abnormal according to the comparison and analysis result; if the monitoring evaluation value is greater than the preset monitoring evaluation threshold value, the ammonia gas measurement accuracy is normal, and no early warning prompt is needed; if the monitoring evaluation value is less than the preset monitoring evaluation threshold value, the ammonia gas measurement accuracy is abnormal, an early warning prompt is needed, and maintenance management is needed.

[0015] In a preferred embodiment, the specific implementation process of the feedback analysis module is as follows: after the system with abnormal measurement accuracy is maintained and managed, a plurality of monitoring evaluation values during ammonia gas measurement are obtained in real time, and form an analysis set, the average value and the standard deviation of the monitoring evaluation values in the analysis set are calculated; the average value and the standard deviation of the monitoring evaluation values in the analysis set are compared and analyzed with the preset evaluation threshold value and the standard deviation reference threshold value; if the average value of the monitoring evaluation values in the set is less than the preset evaluation threshold value, the maintenance and management fails, the ammonia gas measurement accuracy is abnormal, and further maintenance and management is needed; if the average value of the monitoring evaluation values in the set is greater than the preset evaluation threshold value, and the standard deviation of the monitoring evaluation values in the set is greater than the standard deviation reference threshold value, the maintenance and management effect fluctuates, the average value and the standard deviation of the monitoring evaluation values are calculated again, and compared and analyzed with the preset evaluation threshold value and the standard deviation reference threshold value; if the average value of the monitoring evaluation values in the set is greater than the preset evaluation threshold value, and the standard deviation of the monitoring evaluation values in the set is less than the standard deviation reference threshold value, the maintenance and management is successful, the ammonia gas measurement accuracy is normal.

[0016] The technical effects and advantages of the compost process ammonia gas real-time monitoring system are as follows:

[0017] 1. The present application can monitor the concentration change of ammonia gas in the composting process in real time, feedback the gas condition of the composting environment in time, help the operator to quickly identify potential problems, optimize the ventilation and moisture management of composting through monitoring the ammonia gas concentration, thereby improving the fermentation efficiency of composting and the quality of the final product, the excessive emission of ammonia gas will pollute the environment, real-time monitoring can effectively control the release of ammonia gas, reduce the impact on the surrounding environment, and meet the requirements of sustainable development.

[0018] 2.The present application is combined with other composting equipment to realize automatic management, reduce manual intervention, improve operation efficiency, record ammonia concentration data, facilitate subsequent analysis and research, help improve composting process and management strategy, usually equipped with a friendly user interface to enable operators to easily view monitoring data and trends, enhance the operability of the system, optimize the composting process, reduce unnecessary resource waste, reduce operating costs, and thus improve economic benefits. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 A composting process ammonia real-time monitoring system structure diagram is provided. DETAILED DESCRIPTION

[0020] The technical solutions in the embodiments of the present application will be described clearly and completely below in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0021] Embodiment 1, Figure 1 A composting process ammonia real-time monitoring system is provided.

[0022] The concentration measurement module is used to obtain the solution after ammonia gas is introduced into water, and the ion selective electrode method is used to measure the ammonia ion concentration in the solution.

[0023] The ion selective electrode method is an electrochemical analysis technique for measuring the concentration of specific ions. Its main principle is to use the sensitivity of the selective electrode to the target ion to determine the concentration of the ion in the solution by measuring the potential difference between the electrode and the reference electrode.

[0024] The specific process of measuring the ammonia ion concentration in the solution by using the ion selective electrode method is as follows:

[0025] A series of standard solutions with known concentrations are selected to cover the target concentration range. For ammonia ion selective electrodes, different concentrations of ammonium chloride solution can be used.

[0026] The ion selective electrode and the reference electrode are respectively immersed in the first standard solution, and gently stirred to ensure uniformity.

[0027] After the electrode potential stabilizes, the electrode potential value is recorded.

[0028] Repeat the above process for each standard solution, measure and record the corresponding potential value.

[0029] The logarithm of the measured standard solution concentration is taken as the abscissa, and the potential value is taken as the ordinate to draw a standard curve. The data points are fitted using a linear regression method to obtain a linear equation, which describes the relationship between ion concentration and electrode potential. The linear equation is based on the specific formula of the Nernst equation as follows: In the formula, E is the electrode potential, E 0 is the standard electrode potential, R is the gas constant, T is the absolute temperature, n is the ion charge, F is the Faraday constant, [A n ] is the concentration of ammonia ions;

[0030] The solution after passing ammonia gas into water is referred to as the test solution. The ion-selective electrode is immersed in the test solution, and the electrode potential is allowed to stabilize.

[0031] The electrode potential value is recorded, and the concentration of the test ammonia ions is calculated using the calibration curve.

[0032] The information acquisition module acquires data information during the ammonia ion concentration measurement process, including electrochemical characteristic information and dynamic response characteristic information, and acquires the microbial activity coefficient when microorganisms decompose fertilizers to produce ammonia gas during the composting process;

[0033] The electrochemical characteristic information includes the dissolved concentration variation coefficient;

[0034] The specific acquisition steps of the dissolved concentration variation coefficient are as follows:

[0035] The electrode potential of the test solution is measured multiple times using the ion-selective electrode method. According to the drawn standard curve, the corresponding ammonia ion concentration is found, and the solution is measured under the same conditions (such as temperature, pH, etc.);

[0036] The ammonia ion concentration value of each measurement is recorded to obtain a set of data, and the mean and standard deviation of the data set are calculated;

[0037] The dissolved concentration variation coefficient is calculated based on the preset variation coefficient formula according to the mean and standard deviation;

[0038] The dynamic response characteristic information includes the ammonia ion activity coefficient;

[0039] The specific acquisition steps of the ammonia ion activity coefficient are as follows:

[0040] The conductivity of the test solution is measured using a conductivity meter. Conductivity is related to ion concentration in the solution and can reflect ion activity. The concentrations of various ions in the solution are calculated based on the measured conductivity. The ionic strength of the solution is calculated based on the concentrations of various ions and the number of charges of each ion. The ammonia ion activity coefficient is calculated based on the Debye-Hückel formula combining the charge and radius of the ammonia ion.

[0041] The specific calculation formula of the ammonia ion activity coefficient is as follows: In the formula, r is the ammonia ion activity coefficient, A and B are constants related to the characteristics of the solution, z is the charge of the ammonia ion, a is the radius of the ammonia ion, and I is the ionic strength of the solution.

[0042] The specific method for obtaining the microbial activity coefficient is as follows:

[0043] Collect the compost solution to ensure representativeness for analyzing the activity of microorganisms;

[0044] Determine the nitrogen content, carbon content and other nutrients in the solution to understand the growth basis of microorganisms;

[0045] Select a culture medium suitable for the target microorganism to provide the necessary nutrients for growth;

[0046] Dilute the solution and inoculate it into the culture medium, and incubate it at the appropriate temperature and time;

[0047] Use a spectrophotometer to monitor the turbidity of the culture solution to determine the growth of microorganisms;

[0048] Calculate the growth rate according to the growth curve, and take the ratio of the growth rate to the concentration of available nutrients in the known substrate as the microbial activity coefficient, with the specific calculation formula as follows: In the formula, k is the microbial activity coefficient, N t is the cell concentration at time t, N0 is the initial cell concentration, and C is the concentration of available nutrients in the substrate.

[0049] The comprehensive analysis module is used to combine the electrochemical characteristic information and dynamic response characteristic information with the microbial activity coefficient to establish a monitoring evaluation model based on a machine learning algorithm, and generate a monitoring evaluation value.

[0050] The specific calculation formula of the monitoring evaluation value is as follows: In the formula, P is the monitoring evaluation value, b is the dissolved concentration variation coefficient, r is the ammonia ion activity coefficient, k is the microbial activity coefficient, μ1 is the dissolved concentration variation coefficient weight, μ2 is the ammonia ion activity coefficient weight, and μ3 is the microbial activity coefficient weight.

[0051] The coefficient of variation of the dissolved concentration reflects the degree of dispersion of the concentration measurement. A higher coefficient of variation indicates greater volatility in the concentration measurement, meaning that the measurement result is unstable, thereby reducing the measurement accuracy; the ammonia ion activity coefficient is used to correct the relationship between the actual activity and the concentration of ions in the solution, and a higher activity coefficient indicates that the ammonia ion is more active in the solution, meaning that its actual reaction participation ability is stronger, thereby improving the accuracy and reliability of the measurement; the microbial activity coefficient reflects the conversion ability of microorganisms to ammonia gas, and a higher microbial activity means that microorganisms can effectively utilize ammonia gas, which may make the measurement result more representative, therefore, when the microbial activity coefficient is higher, the measurement accuracy is usually improved.

[0052] The hidden danger early warning module compares and analyzes the monitoring evaluation value with the preset monitoring evaluation threshold, judges the ammonia gas measurement accuracy, and according to the comparison and analysis result, issues a warning prompt for the hidden danger existing abnormity;

[0053] The monitoring evaluation value is compared and analyzed with the preset monitoring evaluation threshold, whether the ammonia gas measurement accuracy is abnormal is judged according to the comparison and analysis result, if the monitoring evaluation value is greater than the preset monitoring evaluation threshold, the ammonia gas measurement accuracy is normal, and no warning prompt is needed;

[0054] If the monitoring evaluation value is less than the preset monitoring evaluation threshold, the ammonia gas measurement accuracy is abnormal, a warning prompt needs to be issued, and maintenance management needs to be performed.

[0055] The hidden danger early warning module compares and analyzes the real-time monitoring evaluation value with the preset threshold, judges the ammonia gas measurement accuracy, and issues a warning prompt for the abnormal situation, the advantages of this system mainly lie in the following aspects:

[0056] 1. Improve safety

[0057] Timely warning: when the ammonia gas concentration exceeds the safety threshold, the system can quickly issue an alarm to help take timely measures to avoid potential safety hazards;

[0058] Prevent accidents: through early detection and warning, the risk of accidents such as fire or explosion caused by ammonia gas leakage or high concentration can be effectively reduced;

[0059] 2. Optimize management

[0060] Real-time monitoring and feedback: provide real-time data analysis to help managers understand the ammonia gas level at any time and adjust the operation strategy in a timely manner;

[0061] Data-driven decision making: based on the analysis results provided by the system, the management can make more scientific decisions based on data, thereby improving management efficiency;

[0062] 3. Environmental protection

[0063] Emission Reduction: By monitoring and early warning, timely measures can be taken to reduce ammonia emissions, reduce the impact on the environment, and meet environmental regulations;

[0064] Ecosystem Protection: Effective management of ammonia levels helps protect the surrounding ecosystem and maintain biodiversity;

[0065] 4. Improve Compliance

[0066] Ensure regulatory compliance: The system can help enterprises monitor ammonia emissions to ensure compliance with relevant environmental regulations, avoiding fines or legal liability due to violations;

[0067] Documented Records: Automatically generated monitoring data and alarm records can serve as important evidence for compliance audits;

[0068] 5. Reduce Operating Costs

[0069] Loss Reduction: Through timely warnings and interventions, equipment damage and downtime caused by excessive ammonia can be reduced, thereby reducing operating costs;

[0070] Resource Conservation: Optimizing ammonia management and improving fertilizer utilization efficiency can help save costs and improve economic efficiency;

[0071] 6. Enhance Public Trust

[0072] Improved Transparency: Through effective ammonia monitoring and early warning, enterprises can demonstrate their environmental commitment to the public, enhancing corporate image and social responsibility;

[0073] Enhance employee safety: Provide a safe working environment, enhance employee trust and satisfaction with the company, and promote employee enthusiasm;

[0074] 7. Technological Progress and Innovation

[0075] Promote technological development: The implementation of the hazard early warning module can promote the progress of related technologies, encourage enterprises to invest in new technologies and methods, and improve overall monitoring capabilities;

[0076] Promote data sharing: Through integration with other systems, promote data sharing and collaboration between different departments and agencies;

[0077] The hazard early warning module not only improves the accuracy and real-time nature of ammonia monitoring, but also brings significant benefits to enterprises in safety management, environmental protection, and compliance operations. The implementation of such a system can effectively reduce risks, optimize resource allocation, and promote sustainable development of enterprises.

[0078] The feedback analysis module maintains and manages the precision abnormalities existing in ammonia measurement, and performs comprehensive standard deviation and mean analysis on the real-time output monitoring evaluation values after maintenance management to determine the maintenance management results.

[0079] When maintaining and managing the precision abnormalities existing in ammonia measurement, a number of monitoring evaluation values during ammonia measurement are acquired in real time, and form an analysis set;

[0080] The mean and standard deviation of the monitoring evaluation values in the analysis set are calculated, and the mean and standard deviation of the monitoring evaluation values in the analysis set are compared with the pre-set evaluation threshold and standard deviation reference threshold;

[0081] If the mean of the monitoring evaluation values in the set is less than the pre-set evaluation threshold, the maintenance management fails, the ammonia measurement precision is abnormal, and further maintenance management is required;

[0082] If the mean of the monitoring evaluation values in the set is greater than the pre-set evaluation threshold, and the standard deviation of the monitoring evaluation values in the set is greater than the standard deviation reference threshold, the maintenance management effect fluctuates, and the mean and standard deviation of the monitoring evaluation values in the analysis set are calculated again and compared with the pre-set evaluation threshold and standard deviation reference threshold;

[0083] If the mean of the monitoring evaluation values in the set is greater than the pre-set evaluation threshold, and the standard deviation of the monitoring evaluation values in the set is less than the standard deviation reference threshold, the maintenance management is successful, and the ammonia measurement precision is normal.

[0084] The feedback analysis module plays an important role in the maintenance management of ammonia measurement precision abnormalities, and its main benefits include:

[0085] 1. Precision improvement

[0086] Continuous optimization of monitoring: through standard deviation and mean analysis of the monitoring evaluation values output after maintenance, the fluctuation of measurement data can be identified, helping to further optimize the calibration of sensors and measurement equipment;

[0087] Accurate data feedback: quantitative analysis of maintenance results helps to ensure the reliability of monitoring data and improve overall measurement precision;

[0088] 2. Real-time monitoring and response

[0089] Dynamic adjustment: real-time output of monitoring evaluation values can quickly reflect the maintenance effect, and management personnel can adjust operations in real time according to the analysis results to ensure that the ammonia concentration remains at a safe level;

[0090] Quick identification of problems: through standard deviation and mean monitoring, potential problems can be quickly identified and necessary measures can be taken to reduce risks;

[0091] 3. Data-driven decision support

[0092] Scientific decision-making: Compare real-time monitoring data with historical data to help management make data-based scientific decisions;

[0093] Preventive maintenance: Identify potential weaknesses or failures in the system and perform maintenance in advance to reduce unexpected problems;

[0094] 4. Enhance compliance and reporting capabilities

[0095] Compliance proof: By recording and analyzing monitoring data after maintenance management, enterprises can provide compliance reports to prove their compliance in ammonia management;

[0096] Transparent record: The record of maintenance and analysis results provides detailed basis for future audits and inspections, enhancing transparency;

[0097] 5. Reduce costs

[0098] Reduce downtime: By identifying and addressing precision anomalies in a timely manner, avoid equipment failure or production stoppage due to measurement errors, thereby reducing operating costs;

[0099] Optimize resource allocation: After understanding the maintenance effect, allocate maintenance resources and funds more reasonably to avoid unnecessary expenses.

[0100] 6. Improve employee safety awareness

[0101] Safety training: Through analysis results, provide employees with training and knowledge sharing on ammonia management to enhance their safety awareness;

[0102] Improve working environment: More accurate ammonia monitoring helps improve the working environment and enhance employees' sense of security and job satisfaction;

[0103] 7. Promote technological progress

[0104] Promote technology update: Feedback from the analysis module can provide basis for equipment upgrade and technology improvement, promoting the application of new technology;

[0105] Enhance innovation capability: Through continuous feedback and improvement, enterprises can maintain technological leadership in ammonia monitoring and management;

[0106] 8. Support environmental protection

[0107] Reduce emission risk: Through accurate monitoring and timely response, reduce the risk of ammonia emissions and protect the surrounding environment;

[0108] Improve sustainability: Scientific management measures help achieve the company's sustainable development goals and comply with environmental protection policies;

[0109] The application of the feedback analysis module in ammonia measurement not only improves measurement accuracy and data reliability, but also provides strong support for enterprise safety management, decision support and environmental protection. The implementation of such a system not only reduces risks and costs, but also improves overall operational efficiency and promotes sustainable development.

[0110] The above formulas are dimensionless values calculated, and the formulas are obtained by collecting a large amount of data to simulate a formula of the most recent real situation. The preset parameters in the formula are set by a person skilled in the art according to the actual situation.

[0111] The above embodiments can be realized wholly or partially by software, hardware, firmware or any combination thereof. When realized by software, the above embodiments can be realized wholly or partially in the form of a computer program product.

[0112] Those skilled in the art can realize that the modules and algorithm steps of the examples described in combination with the embodiments disclosed herein can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solution. A person skilled in the art can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0113] In addition, the functional modules in each embodiment of the present application can be integrated in one processing module, or each module can exist physically independently, or two or more modules can be integrated in one module.

[0114] The above is merely a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0115] Finally, the above is only the preferred embodiment of the present application and is not intended to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A real-time ammonia monitoring system for composting processes, characterized in that, Includes the following steps: The concentration measurement module is used to obtain the test solution after ammonia gas is introduced into water, and the concentration of ammonia ions in the solution is measured by ion-selective electrode method. The information acquisition module is used to acquire data information during the ammonia ion concentration measurement process, including electrochemical characteristic information and dynamic response characteristic information, and to acquire the microbial activity coefficient when microorganisms decompose fertilizer to produce ammonia gas during composting. The comprehensive analysis module is used to combine electrochemical characteristic information and dynamic response characteristic information with microbial activity coefficients to establish a monitoring and evaluation model based on machine learning algorithms, and generate monitoring and evaluation values. The hazard warning module is used to compare and analyze the monitoring and assessment values ​​with the preset monitoring and assessment thresholds to determine the accuracy of ammonia measurement, and to issue warnings for any abnormal hazards based on the comparison and analysis results. The feedback analysis module is used to maintain and manage the accuracy anomalies that exist during ammonia measurement, and to perform comprehensive standard deviation and mean analysis on the real-time output monitoring and evaluation values ​​after maintenance and management to judge the maintenance and management results. Electrochemical characteristic information includes the coefficient of variation of solubility concentration, and dynamic response characteristic information includes the ammonia ion activity coefficient; The specific steps for obtaining the coefficient of variation of the solubility concentration are as follows: The electrode potential of the test solution was measured multiple times using the ion-selective electrode method, and the corresponding ammonia ion concentration was determined based on the plotted standard curve. Record the ammonia ion concentration values ​​measured each time to obtain a data set, and calculate the mean and standard deviation of this data set; The coefficient of variation of the dissolved concentration is calculated based on the mean and standard deviation using a pre-defined formula. The specific steps for obtaining the ammonia ion activity coefficient are as follows: Measure the conductivity of the solution to be tested, and calculate the concentration of each ion in the solution based on the measured conductivity. The ionic strength of the solution is calculated based on the concentration and charge of each ion. The ammonia ion activity coefficient is calculated based on the Debye-Hückel formula, which combines the ionic strength of the solution with the charge and radius of the ammonia ions. The specific formula for calculating the ammonia ion activity coefficient is as follows: In the formula, r is the ammonia ion activity coefficient, A and B are constants related to solution properties, z is the ammonia ion charge, a is the ammonia ion radius, and I is the ionic strength of the solution. The specific method for obtaining the microbial activity coefficient is as follows: Collect the compost solution, dilute it, and inoculate it into the culture medium. Cultivate it at a suitable temperature and time. Obtain the initial cell concentration and the cell concentration at time t. Calculate the growth rate based on the growth curve using the initial cell concentration and the cell concentration at time t. Use the ratio of the growth rate to the concentration of available nutrients in the known substrate as the microbial activity coefficient. The specific formula for calculating the microbial activity coefficient is as follows: In the formula, k is the microbial activity coefficient. It is the cell concentration at time t. C is the initial cell concentration, and C is the concentration of available nutrients in the matrix.

2. The real-time ammonia monitoring system for composting process according to claim 1, characterized in that, The specific process for measuring the concentration of ammonia ions in solution using the ion-selective electrode method is as follows: Obtain standard solutions of known different concentrations, and immerse the electrode in the standard solutions; Record the electrode potential value when the electrode potential stabilizes; Repeat the potential measurement process for each standard solution and record the corresponding potential value; A standard curve was plotted based on linear regression fitting of the standard solution concentration and potential value. Obtain the test solution and immerse the ion-selective electrode in the test solution; Record the electrode potential value when the electrode potential is stable; The concentration of ammonia ions to be measured is obtained based on the electrode potential values ​​and a standard curve plotted.

3. The real-time ammonia monitoring system for composting process according to claim 1, characterized in that, The specific implementation process of the hidden danger early warning module is as follows: The monitoring and evaluation values ​​are compared and analyzed with the preset monitoring and evaluation thresholds, and the results of the comparison and analysis are used to determine whether the ammonia measurement accuracy is abnormal. If the monitored value is greater than the preset monitoring threshold, the ammonia measurement accuracy is normal and no warning is required. If the monitored and evaluated value is less than the preset monitoring and evaluated threshold, the ammonia measurement accuracy is abnormal, and an early warning should be issued and maintenance management should be carried out.

4. The real-time ammonia monitoring system for composting process according to claim 3, characterized in that, The specific implementation process of the feedback analysis module is as follows: After maintaining and managing the system with abnormal measurement accuracy, several monitoring and evaluation values ​​of ammonia gas measurement are acquired in real time and formed into an analysis set. The average value and standard deviation of the monitoring and evaluation values ​​in the analysis set are calculated. The average and standard deviation of the monitoring and evaluation values ​​within the analysis set are compared and analyzed with the pre-set evaluation threshold and standard deviation reference threshold; If the average value of the monitored and evaluated values ​​within the set is less than the preset evaluation threshold, then maintenance and management will fail, the ammonia measurement accuracy will be abnormal, and further maintenance and management will be required. If the average value of the monitoring and evaluation values ​​within the set is greater than the preset evaluation threshold, and the standard deviation of the monitoring and evaluation values ​​within the set is greater than the standard deviation reference threshold, then the maintenance and management effect fluctuates. In this case, it is necessary to recalculate the average value and standard deviation of the monitoring and evaluation values ​​and compare them with the preset evaluation threshold and standard deviation reference threshold. If the average value of the monitoring and evaluation values ​​within the set is greater than the preset evaluation threshold, and the standard deviation of the monitoring and evaluation values ​​within the set is less than the standard deviation reference threshold, then the maintenance and management are successful, and the ammonia measurement accuracy is normal.

5. The real-time ammonia monitoring system for composting process according to claim 1, characterized in that, The specific formula for calculating the monitoring and evaluation value is as follows: In the formula, These are monitoring and assessment values; b is the coefficient of variation of solubility concentration; r is the ammonia ion activity coefficient; and k is the microbial activity coefficient. It is the weight of the coefficient of variation of the solubility concentration. It is the weight of the ammonia ion activity coefficient. It is the weight of the microbial activity coefficient.

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