A planting substrate composting device and a composting method

Abstract

This invention discloses a composting device and method for planting substrates, comprising a shell and a turning mechanism for turning the compost, disposed within and movable within the shell. The turning mechanism includes a movable frame that moves within the shell and a turning roller disposed within and rotating within the movable frame. The outer cylindrical surface of the turning roller has several turning teeth. During composting within the shell, the turning roller rotates, and as the movable frame moves, the compost material is exchanged between the upper and lower layers, and between the inner and outer layers, achieving automatic turning of the compost, improving efficiency, and reducing labor intensity. Furthermore, it enables precise control of the internal environment of the compost, improving fermentation efficiency and product quality stability.

Description

Technical Field

[0001] This invention relates to the field of forest seedling cultivation, specifically to a planting substrate composting device and composting method. Background Technology

[0002] Plant substrate composting is the process of transforming organic waste into a suitable cultivation substrate through controlled fermentation. It not only achieves resource recycling but also replaces non-renewable resources such as peat, and is widely used in horticulture, seedling cultivation, and greenhouse agriculture.

[0003] However, current methods of composting planting substrates still have many shortcomings in practice. First, many traditional methods often neglect the dynamic balance of various factors during fermentation, leading to unstable quality of the final product and difficulty in meeting the needs of different crops. Especially when facing complex and changing raw material sources and environmental conditions, existing methods lack precise control over key conditions, particularly in the regulation of moisture content and pH, often resulting in incomplete fermentation or nutrient loss, affecting the actual application effect of the substrate. Second, the composting process requires regular exchange of compost materials between layers to maintain an aerobic fermentation environment and accelerate the decomposition and maturation of organic matter. However, existing methods rely on manual shoveling and turning of the soil, which is labor-intensive and inefficient. Summary of the Invention

[0004] The purpose of this invention is to solve the above-mentioned problems and provide a composting device and method for planting substrate, which can improve the composting turning efficiency and ensure that the composting process is efficient and the final substrate quality meets the standards.

[0005] The technical solution adopted by this invention to solve its technical problem is: A composting device for planting substrate includes a housing and a turning mechanism disposed within the housing and movable within the housing for turning the compost. The flipping mechanism includes a movable frame that moves within the housing and a flipping roller that is disposed within the movable frame and rotates within the movable frame. The outer cylindrical surface of the flipping roller is provided with a plurality of flipping teeth. The mobile frame is also equipped with a water spraying mechanism for adding water to the compost and a regulator adding mechanism for adding raw materials to the compost. Several fans are provided on the side of the outer casing.

[0006] Furthermore, both ends of the mobile frame are equipped with lifting legs, and the lower ends of the lifting legs are equipped with wheels.

[0007] Furthermore, the lifting outrigger includes a fixed housing and a telescopic housing whose upper end extends into and slides within the fixed housing. Both ends of the movable frame are provided with support plates, and the lower end of the fixed housing is fixed to the support plates.

[0008] Furthermore, the water spraying mechanism includes a water tank disposed at the upper end of the movable frame and a nozzle disposed at the lower end of the water tank.

[0009] Furthermore, the regulator addition mechanism includes a material trough located at the upper end of the movable frame and a material discharge pipe located at the lower end of the material trough, wherein a solenoid valve is provided on the material discharge pipe.

[0010] Furthermore, a method for composting planting substrate, applied to the aforementioned apparatus, includes the following steps: S101 Acquire moisture content data during fermentation, monitor the internal humidity level of the compost in real time using sensors, and obtain an initial moisture distribution map; S102 Based on the initial moisture distribution map, use the k-means clustering algorithm to divide the humidity areas and determine the location coordinates of high humidity and low humidity areas; S103 Determine whether the high humidity area exceeds a preset threshold. If it does, adjust the oxygen flow rate through ventilation equipment to obtain updated oxygen distribution data; S104 Extract microbial activity indicators from the updated oxygen distribution data, use the support vector machine algorithm to predict the activity change trend, and determine the potential pH offset value; S105 For the potential pH offset value, acquire environmental condition variables such as temperature and raw material composition, determine whether the offset value is within a suitable range, and if not, simulate the stable path by adding regulators to obtain an optimized pH curve; S106 Based on the optimized pH curve, integrate fermentation efficiency indicators, use the random forest algorithm to evaluate substrate quality parameters, and determine the final quality stability level; S107 Based on the final quality stability level, generate adjustment instructions for regulatory factors to obtain an application effect report that meets crop requirements.

[0011] Further, step S103 includes: The high humidity area is monitored in real time by a sensor network to obtain humidity data in the environment and obtain the humidity status value of the area. If the humidity status value exceeds a preset threshold, the threshold judgment logic is triggered to generate a control signal to start the ventilation equipment and determine the initial operation command of the equipment. The ventilation equipment is activated according to the control signal, the oxygen flow rate is adjusted, the rate parameters of the equipment during operation are recorded, and real-time rate adjustment data is obtained. The oxygen distribution status is updated by adjusting the rate data, and the changes in oxygen concentration in the region are calculated to obtain the adjusted oxygen distribution information.

[0012] Further, step S104 includes: Raw records were obtained from the stored oxygen distribution data, and preliminary screening was performed based on changes in environmental parameters to obtain the core dataset related to microbial activity. Based on the core dataset, microbial activity indicators are extracted, and the support vector machine algorithm is used to model the trend of activity change to determine the prediction result of the activity change. Based on the prediction results, the correlation between activity changes and pH values ​​is analyzed to obtain the potential range of offset values ​​and determine the interval of pH offset.

[0013] Further, step S105 includes: The system acquires environmental variable data and pH offset data, records real-time environmental variable values ​​through the data acquisition module, and obtains a preliminary environmental variable dataset. For the preliminary environmental variable dataset, a preset suitable range of values ​​is used for comparison. If a pH deviation is detected to exceed the preset suitable range, a deviation judgment method is triggered to determine the direction and magnitude of the deviation. Based on the offset direction and amplitude, the regulator type information is obtained, and a suitable regulator type and dosage value are matched with the database to generate a preliminary regulator addition plan; For the aforementioned preliminary regulator addition scheme, the pH change was predicted by simulation calculation, and the stability path diagram was calculated by numerical simulation tools to obtain the simulated pH change trend. From the simulated pH change trend, key node data of the stability path graph are extracted, and an optimization curve is generated through an optimization algorithm to determine the final pH adjustment path. Further, step S107 includes: The stable state information is obtained by using quality grade data to determine whether the current quality meets the preset standard. If the quality meets the standard, the adjustment instruction content is generated based on the analysis of control factors, and it is determined whether the instruction conforms to the preset logic rules. If the instruction conforms to the rules, the application effect data is extracted from the execution plan, analyzed using a preset evaluation model, and the effect evaluation result is obtained. Based on the evaluation results, a report is generated using the final data to complete the processing flow.

[0014] The beneficial effects of this invention are: 1. The turning mechanism in this invention includes a movable frame that moves within the outer shell and a turning roller disposed within the movable frame and rotating within the frame. The outer cylindrical surface of the turning roller is provided with several turning teeth. The planting substrate composts within the outer shell. During compost turning, the turning roller rotates, and as the movable frame moves, the compost material is exchanged between its upper and lower, inner and outer layers. This forces the introduction of air, releases waste gas, and regulates moisture and temperature, thereby maintaining an aerobic fermentation environment and accelerating the decomposition and maturation of organic matter. This achieves automatic compost turning, improving efficiency and reducing labor intensity.

[0015] 2. This invention integrates real-time sensor monitoring of initial moisture distribution maps and uses k-means clustering to divide humidity zones. After determining the threshold of high humidity zones, it adjusts ventilation equipment to update oxygen distribution. Microbial activity indicators are extracted, and support vector machine algorithms are used to predict activity trends and pH shifts. Environmental variables are combined to simulate regulator addition paths and optimize pH curves. Finally, fermentation efficiency indicators are integrated, and a random forest algorithm is used to evaluate the final quality level and generate control instructions. This solves the logical correlation problem of dynamic imbalance of fermentation process parameters. It achieves precise control of the composting internal environment, improves fermentation efficiency and product quality stability, generates application effect reports that meet crop requirements, and ultimately enhances the economic and environmental benefits of agricultural waste resource utilization. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the structure of the present invention; Figure 2 This is a schematic diagram of the flipping mechanism structure of the present invention. Figure 1 ; Figure 3 This is a schematic diagram of the flipping mechanism structure of the present invention. Figure 2 ; Figure 4 This is a flowchart of the present invention; Figure 5 The flowchart for adjusting the instruction judgment is provided for this invention.

[0017] In the diagram: 1. Outer shell; 2. Moving frame; 3. Tilting roller; 4. Tilting tooth; 5. Fan; 6. Walking wheel; 7. Fixed shell; 8. Telescopic shell; 9. Support plate; 10. Water tank; 11. Nozzle; 12. Material trough; 13. Material drop pipe; 14. Solenoid valve. Detailed Implementation

[0018] like Figure 1 As shown, a planting substrate composting device includes a housing 1 and a turning mechanism for turning the compost, which is disposed inside the housing 1 and moves within the housing 1.

[0019] like Figure 2 and Figure 3As shown, the turning mechanism includes a movable frame 2 that moves within the outer casing 1, and a turning roller 3 that is disposed within and rotates within the movable frame 2. The outer cylindrical surface of the turning roller 3 is provided with several turning teeth 4. The two ends of the rotating shaft of the turning roller 3 are rotatably connected to both sides of the movable frame 2. A motor that drives the turning roller 3 to rotate is mounted on the movable frame 2. The planting substrate composts within the outer casing 1. During compost turning, the turning roller 3 rotates, and as the movable frame 2 moves, the compost material is exchanged between the upper and lower layers and between the inner and outer layers. This forces the introduction of air, releases waste gas, and regulates moisture and temperature, thereby maintaining an aerobic fermentation environment and accelerating the decomposition and maturation of organic matter. This achieves automatic compost turning, improving efficiency and reducing labor intensity.

[0020] The mobile frame 2 is also equipped with a water spraying mechanism for adding water to the compost and a regulator adding mechanism for adding regulators to the compost.

[0021] like Figure 1 As shown, a plurality of fans 5 are provided on the side of the outer casing 1.

[0022] like Figure 2 As shown, the mobile frame 2 is provided with lifting legs at both ends, and the lower end of the lifting legs is provided with a traveling wheel 6. Each side of the mobile frame 2 is provided with two lifting legs to ensure the stability of the mobile frame 2. The traveling wheel 6 is a set of active wheels, thereby enabling the mobile frame 2 to move along the length of the outer shell 1 inside the outer shell 1.

[0023] like Figure 2 As shown, the lifting outrigger includes a fixed housing 7 and a telescopic housing 8 whose upper end extends into and slides within the fixed housing 7. Both ends of the movable frame 2 are provided with support plates 9. The lower end of the fixed housing 7 is fixed to the support plate 9. A hydraulic cylinder is provided inside the fixed housing 7. The cylinder body end of the hydraulic cylinder is fixed inside the fixed housing 7. The piston rod end of the hydraulic cylinder is connected to the telescopic housing 8. The movable frame 2 is driven to rise and fall by extending and retracting the piston rod of the hydraulic cylinder. When it is necessary to turn the compost, the movable frame 2 first descends, so that the turning roller 3 comes into contact with the compost. After the turning is completed, the turning roller 3 rises and separates from the compost.

[0024] like Figure 3 As shown, the water spraying mechanism includes a water tank 10 located at the upper end of the movable frame 2 and a nozzle 11 located at the lower end of the water tank 10. A water pipe is provided at the lower end of the water tank 10, and the nozzle 11 is installed at the lower end of the water pipe. A water pump and a solenoid valve are provided on the water pipe, thereby realizing the spraying of water into the compost fertilizer and replenishing water as needed.

[0025] like Figure 2 and Figure 3As shown, the regulator addition mechanism includes a material trough 12 located at the upper end of the movable frame 2 and a material drop pipe 13 located at the lower end of the material trough 12. The material drop pipe 13 is equipped with a solenoid valve 14, and the addition of regulator to the compost fertilizer is achieved by opening and closing the solenoid valve 14.

[0026] like Figure 4 As shown, a method for composting planting substrate, applied to the aforementioned apparatus, includes the following steps: S101 Acquire moisture content data during fermentation, monitor the internal humidity level of the compost in real time using sensors, and estimate the humidity distribution in unmonitored areas using data interpolation to obtain an initial moisture distribution map; S102 Based on the initial moisture distribution map, use the k-means clustering algorithm to divide the humidity areas and determine the location coordinates of high-humidity and low-humidity areas; S103 Determine whether the high-humidity area exceeds a preset threshold. If it does, adjust the oxygen flow rate through ventilation equipment to obtain updated oxygen distribution data; S104 Extract microbial activity indicators from the updated oxygen distribution data, use the support vector machine algorithm to predict the trend of activity changes, and determine the potential pH offset; S105 For the potential pH offset, acquire environmental condition variables such as temperature and raw material composition, determine whether the offset is within a suitable range, and if not, simulate the stable path by adding regulators to obtain an optimized pH curve; S106 Based on the optimized pH curve, integrate fermentation efficiency indicators, use the random forest algorithm to evaluate substrate quality parameters, and determine the final quality stability level; S107 Based on the final quality stability level, generate adjustment instructions for regulatory factors to obtain an application effect report that meets crop requirements.

[0027] In step S101, sensors are typically placed at different depths and locations within the compost pile to cover the main areas. Since data is missing for unmonitored areas, data interpolation is used to estimate the overall moisture distribution. Data interpolation can be based on the principle of spatial distance-weighted averaging, assigning different weights to data from known points according to their distance, thereby calculating the moisture values ​​for unmonitored areas and forming an initial moisture distribution map.

[0028] In step S102, k-means clustering is used to classify the moisture distribution and obtain preliminary division results of the humidity regions. If the boundary regions of high-humidity and low-humidity areas overlap in the preliminary division results, the specific affiliation of the boundary regions is determined by comparing the humidity values ​​at the pixel level. For the region affiliation data, spatial interpolation is used to smooth the humidity values ​​of the boundary regions to obtain more accurate region division boundaries. Based on the region division boundaries, the final distribution data of the humidity regions is generated.

[0029] k-means clustering is a method for grouping data, the core of which is to cluster humidity data into several categories based on similarity. For example, in a compost pile, assuming the humidity data ranges from 20% to 80%, the system can divide the data into three categories: high humidity, medium humidity, and low humidity. Initially, areas with humidity values ​​above 60% are classified as high humidity areas, those below 30% as low humidity areas, and the rest as medium humidity areas.

[0030] If the boundaries between high-humidity and low-humidity areas overlap, pixel-level humidity value comparisons can be performed point-by-point to determine their affiliation. For example, if a point has a humidity value of 45%, while the average humidity in the surrounding high-humidity area is 60% and the average humidity in the low-humidity area is 30%, this comparison indicates that the point is closer to the low-humidity area. This refined processing effectively reduces classification errors, ensures the accuracy of region division, and provides more reliable data support for humidity control during subsequent fermentation processes.

[0031] Spatial interpolation provides a reasonable estimate of humidity values ​​in areas not directly measured. For example, assuming two known points within a boundary region have humidity values ​​of 50% and 40%, interpolation can extrapolate the humidity value at the unmeasured intermediate point to be approximately 45%, thus ensuring a continuous humidity distribution across the entire region. This smoothing process helps eliminate abrupt changes in the data, resulting in more natural boundary divisions between regions.

[0032] On the topic of generating the final humidity distribution data, based on the aforementioned classification, boundary assignment, and smoothing processes, a complete humidity distribution map can be formed.

[0033] Step S103 includes: real-time monitoring of the high humidity area through a sensor network to obtain humidity data in the environment and obtain the humidity status value of the area; if the humidity status value exceeds a preset threshold, triggering threshold judgment logic to generate a control signal to start the ventilation equipment and determine the initial operation command of the equipment; activating the ventilation equipment according to the control signal, adjusting the oxygen flow rate, recording the rate parameters during the operation of the equipment, and obtaining real-time rate adjustment data; updating the oxygen distribution status through the rate adjustment data, calculating the change in oxygen concentration in the area, and obtaining the adjusted oxygen distribution information; using a support vector machine algorithm to evaluate the uniformity of oxygen distribution in the area based on the adjusted oxygen distribution information, and determining whether it meets the expected standard; if the uniformity does not meet the expected standard, generating a secondary adjustment command based on the evaluation result, adjusting the operating parameters of the ventilation equipment, and obtaining the updated oxygen distribution data.

[0034] The composting system is equipped with multiple humidity sensors to collect humidity data for specific areas. If the humidity level in a certain area reaches 85%, while the preset threshold is 80%, the system will trigger threshold judgment logic, generating a control signal to activate the ventilation equipment. The sensors collect data every 5 minutes and transmit the data to the central control system, which determines whether to activate the equipment based on the humidity value. This real-time monitoring method can promptly capture environmental changes and ensure that humidity is controlled within a suitable range.

[0035] The initial operating commands and oxygen flow rate adjustments for ventilation equipment can be achieved through a preset rate parameter table. Assuming the initial operating command sets the ventilation equipment's airflow speed to 3 m / s, the system will record the rate parameters during equipment operation and adjust it to 4 m / s based on real-time data to increase oxygen flow. The system will record rate data every 10 minutes during equipment operation, forming a dynamic adjustment database.

[0036] When using the support vector machine algorithm to assess oxygen distribution uniformity, the distribution of oxygen concentration in different locations within the greenhouse can be analyzed to determine whether the expected standard has been met. If the oxygen concentration in a certain area of ​​the greenhouse is between 18% and 22%, while the standard requirement is 20% ± 1%, the system will generate secondary adjustment instructions based on the assessment results, adjusting the operating parameters of the ventilation equipment, such as increasing the wind speed to 5 m / s. By comparing and analyzing historical and real-time data, the system can determine whether the uniformity meets the requirements. This assessment method can effectively identify problem areas with uneven distribution, providing a basis for subsequent adjustments.

[0037] Step S104 includes: obtaining raw records from stored oxygen distribution data, performing preliminary screening based on changes in environmental parameters to obtain a core dataset related to microbial activity; extracting microbial activity indicators based on the core dataset, modeling the activity change trend using a support vector machine algorithm, and determining the predicted results of the activity change; analyzing the correlation between activity change and pH value through the predicted results, obtaining the potential offset value range, and determining the interval of the pH offset.

[0038] When conducting initial screening based on changes in environmental parameters, noise data irrelevant to these parameters is eliminated, resulting in datasets related to microbial activity. For example, a focus can be placed on oxygen distribution when humidity exceeds 80%. This screening method helps to focus on core issues and avoid data redundancy.

[0039] To extract indicators of microbial activity, the relationship between oxygen concentration and microbial metabolic rate can be analyzed. For example, when the oxygen concentration is below 19%, microbial activity decreases significantly. When using the support vector machine algorithm for modeling, the trend of activity changes can be correlated with variables such as time and humidity to predict activity fluctuations over the next 12 hours.

[0040] When analyzing the correlation between activity changes and pH values, it is assumed that the prediction results show that the decrease in activity is highly correlated with pH shifts below 5.5, with the shift value ranging from 5.0 to 5.5.

[0041] Step S105 includes: acquiring environmental variable data and pH offset data from the system, recording real-time environmental variable values ​​through a data acquisition module to obtain a preliminary environmental variable dataset; comparing the preliminary environmental variable dataset with a preset suitable range value, and if the pH offset is detected to exceed the preset suitable range value, triggering an offset judgment method to determine the offset direction and magnitude; acquiring regulator type information based on the offset direction and magnitude, matching suitable regulator types and dosage values ​​through a database to generate a preliminary regulator addition plan; predicting pH changes using a simulation calculation method for the preliminary regulator addition plan, calculating a stable path diagram using a numerical simulation tool to obtain the simulated pH change trend; extracting key node data from the simulated pH change trend, generating an optimized curve diagram through an optimization algorithm, and determining the final pH adjustment path.

[0042] To determine pH deviation, a preset suitable range of values ​​can be used for comparison. If a pH value of 6.2 is detected, which is lower than the target lower limit of 6.5, the system will trigger the deviation judgment method, determining that the deviation direction is acidic, with an amplitude of 0.3 units.

[0043] When generating a regulator addition plan, the system matches suitable regulator types from the database based on the offset direction and magnitude. If the pH is acidic, the system may select sodium hydroxide as the regulator and recommend an addition dose of 0.1 grams per liter of solution based on an offset magnitude of 0.3.

[0044] Simulation calculations for the regulator addition scheme can predict the pH change trend using numerical simulation tools. Assuming the addition of 0.1 g of sodium hydroxide, simulation results show that the pH gradually increases from 6.2 to 6.6 within 2 hours, forming a stable path.

[0045] When optimizing the pH adjustment pathway, key node data can be extracted from the stability graph, such as the two time points when the pH reaches 6.4 and 6.6. An optimization algorithm can then be used to generate a smooth adjustment curve. The final determined pathway may involve gradually adding the regulator in stages to avoid drastic environmental fluctuations caused by a single excessive addition. This optimization method can improve the stability of the regulation and protect microbial activity from shocks. Step S107 includes: acquiring pH curve data, smoothing the pH curve data using a pre-established processing model to obtain optimized pH trend data. Based on the optimized pH trend data, combined with fermentation efficiency data, historical records are extracted from the database for matching analysis to determine the correspondence pattern between fermentation efficiency and the pH trend data. For the correspondence pattern, key parameters related to substrate quality are extracted, and the key parameters are ranked by importance using a random forest algorithm to determine key influencing factors. If a parameter among the key influencing factors exceeds a preset threshold, the parameter is weighted to obtain a weighted substrate quality parameter set. Based on the weighted substrate quality parameter set, combined with quality stability standards, a stratified comparison method is used to determine the preliminary stability level of substrate quality. For the preliminary stability level, a multi-dimensional comparison is performed using a historical data verification module to obtain the final quality stability level determination result.

[0046] Smoothing can be achieved through pre-established processing models, such as using time series smoothing methods to remove noise interference from the data and ensure the continuity of the curve and the readability of the trend.

[0047] When extracting key parameters related to substrate quality, attention can be paid to indicators such as organic matter content and moisture content. Analysis using the random forest algorithm revealed that organic matter content accounts for 40% of the importance, significantly higher than other parameters. If its value exceeds a preset threshold, for example, a standard value of 60% while the actual value is 75%, it needs to be weighted, and the weighting coefficients adjusted to balance the impact.

[0048] To compare the weighted set of matrix quality parameters with the quality stability standards, a stratified comparison method can be used to classify the quality into three levels: high, medium, and low. For example, in a certain test, the organic matter content and humidity parameters both meet the high-level standard, but another parameter is slightly below the medium-level requirement; in this case, the initial assessment would be medium-level. This stratified approach refines the evaluation dimensions, ensuring the comprehensiveness of the results.

[0049] When performing multi-dimensional comparisons using the historical data verification module, the past 500 fermentation records can be accessed to analyze the quality stability under similar parameter combinations. Assuming that 90% of these records show that the medium-grade substrate performs stably in subsequent fermentations, the substrate is ultimately determined to be of medium quality and usable. Throughout the process, the key focus is on the correlation between pH trends and substrate quality.

[0050] Subtle changes in pH often reflect the chemical environment within the substrate. Through the series of analyses described above, potential problems can be effectively identified, allowing for early optimization of fermentation conditions. This method not only improves the stability of the fermentation process but also provides data support for quality control, indirectly ensuring production efficiency.

[0051] like Figure 5 As shown, step S107 includes: obtaining the stable state information through quality level data, determining whether the current quality meets the preset standard; if the quality meets the standard, generating the adjustment instruction content based on the analysis of control factors, and determining whether the instruction conforms to the preset logical rules; if the instruction conforms to the rules, extracting application effect data from the execution plan, analyzing it using a preset evaluation model, and obtaining the effect evaluation result; generating report content based on the effect evaluation result and the final data, thus completing the processing flow.

[0052] When acquiring quality grade data to determine steady-state information, this can be achieved by real-time monitoring of various indicators of the substrate during fermentation. Assuming that in a certain fermentation experiment, the quality grade data includes key indicators such as pH, temperature, and humidity, preset standards can be used to determine whether the current quality meets expectations.

[0053] The analysis of control factors after quality standards are met begins with fine-tuning the fermentation environment. Assuming the analysis reveals that slightly high humidity might affect subsequent stability, the generated adjustment instruction might be to reduce humidity to 75%. When determining whether the instruction conforms to preset logical rules, it can be checked whether the instruction is consistent with historical control records. For example, in similar situations in the past, humidity adjustments did not exceed 5%, while this adjustment is within a reasonable range and therefore conforms to the rules. This analytical approach helps avoid blind adjustments and ensures the feasibility of the instructions.

Claims

1. A composting device for planting substrate, characterized in that, Includes a housing (1) and a turning mechanism for turning over compost, which is disposed within the housing (1) and moves within the housing (1); The flipping mechanism includes a movable frame (2) that moves within the outer shell (1) and a flipping roller (3) that is disposed within the movable frame (2) and rotates within the movable frame (2). The outer cylindrical surface of the flipping roller (3) is provided with a plurality of flipping teeth (4). The mobile frame (2) is also equipped with a water spraying mechanism for adding water to the compost fertilizer and a regulator adding mechanism for adding regulator to the compost fertilizer. The outer casing (1) has several fans (5) on its side.

2. The planting substrate composting device as described in claim 1, characterized in that, The mobile frame (2) is provided with lifting legs at both ends, and the lower end of the lifting legs is provided with a walking wheel (6).

3. The planting substrate composting device as described in claim 2, characterized in that, The lifting outrigger includes a fixed housing (7) and a telescopic housing (8) whose upper end extends into the fixed housing (7) and slides within the fixed housing (7). Both ends of the movable frame (2) are provided with support plates (9), and the lower end of the fixed housing (7) is fixed on the support plate (9).

4. The planting substrate composting device as described in claim 1, characterized in that, The water spraying mechanism includes a water tank (10) located at the upper end of the movable frame (2) and a nozzle (11) located at the lower end of the water tank (10).

5. The planting substrate composting device as described in claim 1, characterized in that, The regulator addition mechanism includes a material trough (12) located at the upper end of the movable frame (2) and a material drop pipe (13) located at the lower end of the material trough (12), and a solenoid valve (14) is provided on the material drop pipe (13).

6. A method for composting planting substrate, applied to the apparatus according to any one of claims 1 to 5, characterized in that, Includes the following steps: S101 Acquire moisture content data during fermentation, monitor the internal humidity level of the compost in real time using sensors, and obtain an initial moisture distribution map; S102 Based on the initial moisture distribution map, use the k-means clustering algorithm to divide the humidity areas and determine the location coordinates of high humidity and low humidity areas; S103 Determine whether the high humidity area exceeds a preset threshold. If it does, adjust the oxygen flow rate through ventilation equipment to obtain updated oxygen distribution data; S104 Extract microbial activity indicators from the updated oxygen distribution data, use the support vector machine algorithm to predict the activity change trend, and determine the potential pH offset value; S105 For the potential pH offset value, acquire environmental condition variables such as temperature and raw material composition, determine whether the offset value is within a suitable range, and if not, simulate the stable path by adding regulators to obtain an optimized pH curve; S106 Based on the optimized pH curve, integrate fermentation efficiency indicators, use the random forest algorithm to evaluate substrate quality parameters, and determine the final quality stability level; S107 Based on the final quality stability level, generate adjustment instructions for regulatory factors to obtain an application effect report that meets crop requirements.

7. The method for composting planting substrate as described in claim 6, characterized in that, Step S103 includes: The high humidity area is monitored in real time by a sensor network to obtain humidity data in the environment and obtain the humidity status value of the area. If the humidity status value exceeds a preset threshold, the threshold judgment logic is triggered to generate a control signal to start the ventilation equipment and determine the initial operation command of the equipment. The ventilation equipment is activated according to the control signal, the oxygen flow rate is adjusted, the rate parameters of the equipment during operation are recorded, and real-time rate adjustment data is obtained. The oxygen distribution status is updated by adjusting the rate data, and the changes in oxygen concentration in the region are calculated to obtain the adjusted oxygen distribution information.

8. The method for composting planting substrate as described in claim 6, characterized in that, Step S104 includes: Raw records were obtained from the stored oxygen distribution data, and preliminary screening was performed based on changes in environmental parameters to obtain the core dataset related to microbial activity. Based on the core dataset, microbial activity indicators are extracted, and the support vector machine algorithm is used to model the trend of activity change to determine the prediction result of the activity change. Based on the prediction results, the correlation between activity changes and pH values ​​is analyzed to obtain the potential range of offset values ​​and determine the interval of pH offset.

9. A method for composting planting substrate as described in claim 6, characterized in that, Step S105 includes: The system acquires environmental variable data and pH offset data, records real-time environmental variable values ​​through the data acquisition module, and obtains a preliminary environmental variable dataset. For the preliminary environmental variable dataset, a preset suitable range of values ​​is used for comparison. If a pH deviation is detected to exceed the preset suitable range, a deviation judgment method is triggered to determine the direction and magnitude of the deviation. Based on the offset direction and amplitude, the regulator type information is obtained, and a suitable regulator type and dosage value are matched with the database to generate a preliminary regulator addition plan; For the aforementioned preliminary regulator addition scheme, the pH change was predicted by simulation calculation, and the stability path diagram was calculated by numerical simulation tools to obtain the simulated pH change trend. From the simulated pH change trend, key node data of the stable path graph are extracted, and an optimization curve is generated through an optimization algorithm to determine the final pH adjustment path.

10. A method for composting planting substrate as described in claim 6, characterized in that, Step S107 includes: The stable state information is obtained by using quality grade data to determine whether the current quality meets the preset standard. If the quality meets the standard, an adjustment instruction is generated based on the analysis of control factors, and it is determined whether the instruction conforms to the preset logic rules. If the instruction conforms to the rules, the application effect data is extracted from the execution plan, analyzed using a preset evaluation model, and the effect evaluation result is obtained. Based on the evaluation results, a report is generated using the final data to complete the processing flow.

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