Farm manure treatment system based on solid-liquid separation

Abstract

The present invention relates to the technical field of sewage treatment, and in particular to a farm manure treatment system based on solid-liquid separation, comprising: a plurality of collectors, a plurality of adjustment modules and a processor, which utilizes monitoring of the water state and the solid state to determine the corresponding solid living environment, and determines whether the adjustment of the treatment pool is completed based on the adjusted solid development and water flow. While effectively avoiding the problem of decreased solid activity due to low temperature, it also avoids malfunction of the treatment pool due to the low temperature environment, effectively improves the stability of the treatment pool operation, and thus effectively improves the treatment efficiency of the manure treatment system.

Description

Technical Field

[0001] The present invention relates to the technical field of sewage treatment, and in particular to a farm manure treatment system based on solid-liquid separation. Background Art

[0002] With the development of breeding technology, the scale of breeding enterprises is getting larger and larger, and the pretreatment of farm waste is becoming more and more important. Untreated manure will pollute water, soil and air, spread pathogens, and endanger the ecology and human health. After scientific treatment, it can be made into organic fertilizer, produce biogas or recycle water resources, promoting the development of green agriculture.

[0003] Currently, the main methods for separating and treating farm manure and sewage include: biofloc separation, mechanical separation, flocculation and sedimentation, micro-sand assisted separation, biogas engineering combination and "three separations and one purification" mode. Among them, biofloc requires strict control of environmental conditions, mechanical separation equipment has high energy consumption or maintenance costs, flocculants may introduce secondary pollution, micro-sand technology is complex to operate, biogas engineering requires large investment and liquid manure treatment still requires follow-up measures, and "three separations and one purification" has poor adaptability to water quality fluctuations.

[0004] Chinese Patent Authorization Publication No. CN113149213B discloses a device for rapidly cultivating aerobic granular solids and treating low-C / N ratio municipal sewage. The device comprises a domestic sewage inlet bucket, an inlet peristaltic pump, an AGSBR reactor for simultaneous nitrification and endogenous denitrification and phosphorus removal, an online automatic control system, and an outlet bucket. The device is based on the startup of aerobic granular solids in high C / N ratio sewage based on metabolic and hydraulic selective pressure combined with high hydraulic shear force. The simultaneous nitrification and endogenous denitrification process ensures stable operation of low C / N ratio sewage treatment. By coordinating the operation of key functional bacteria (PAOs, GAOs, DNPAOs, DNGAOs, AOB, NOB, OHOs) in the anaerobic, aerobic, and anoxic phases, simultaneous nitrogen and phosphorus removal from sewage is achieved without the need for an external carbon source. This method shortens the startup period for the granular solids, and the resulting granular solids are smaller, more stable, and less prone to swelling and disintegration.

[0005] Among the above-mentioned technologies, the treatment methods for urban sewage are difficult to be miniaturized and applied to additional equipment in farms. Moreover, for farm manure with a high organic matter content, the above-mentioned types of treatment costs are high, and it is difficult to effectively control the breakage of solid particles after separation, which ultimately leads to a decrease in treatment effect or sewage leakage. Summary of the Invention

[0006] To this end, the present invention provides a farm manure treatment system based on solid-liquid separation, which is used to overcome the problem in the prior art that solid particles after effective control separation are damaged, ultimately leading to a decrease in treatment effect or sewage leakage, thereby causing a decrease in the treatment efficiency of the manure treatment system.

[0007] To achieve the above objectives, the present invention provides a farm manure treatment system based on solid-liquid separation, comprising:

[0008] Several collectors for collecting image parameters and environmental parameters of the processing pool;

[0009] Several adjustment modules are used to generate corresponding solid state parameters and corresponding water state parameters according to the image parameters, and adjust the states of the solid and water according to the environmental parameters, including:

[0010] a solid regulator, responsive to generation of solid state parameters, to adjust solid motion according to environmental parameters;

[0011] a water regulator, responsive to the generation of the water state parameter, to adjust the water movement according to the environmental parameter;

[0012] The processor is used to control the actions of each collector and adjustment module, including:

[0013] an adjustment console for determining expected image parameters of the treatment tank based on the solid body movement and the water body movement;

[0014] An image analysis station, which collects real-time image parameters of the treatment pool at preset maintenance intervals;

[0015] and, comparing the expected image parameters with the real-time image parameters to determine the solid motion and / or water motion for the next preset maintenance time;

[0016] Wherein, the solid state parameters include at least the particle size and integrity of the solid;

[0017] The water state parameters include at least aeration volume and flow rate.

[0018] Furthermore, the collector collects the water image of the treatment pool at a preset resolution, and determines the condensation state of the solid according to the shadow range of the water image.

[0019] and determining the operating state of the solid according to the bubble range of the water body image,

[0020] and, determining the floating state of the solid according to the grayscale of the water body image;

[0021] The condensation state, the running state, and the floating state are output as image parameters.

[0022] Furthermore, the collector collects the adhesion image of the water body and the temperature data of the water body at a preset resolution, and determines the flow characteristics of the treatment pool according to the adhesion image of the water body.

[0023] and, determining the water flow impact force of the treatment pool according to the water body temperature and the flow characteristics;

[0024] outputting the flow characteristics and the water flow impact force as the environmental parameters;

[0025] The flow characteristics include the flow velocity and flow direction of the water in the treatment pool.

[0026] Furthermore, the adjustment module determines the particle size and aggregation of the solid according to the image parameters, determines the stability of the solid according to the environmental parameters, and outputs the particle size, aggregation and stability as the solid features.

[0027] Furthermore, the solid regulator determines the target particle size of the solid according to the water temperature, determines the real-time particle size of the solid, and compares the real-time particle size with the target particle size, wherein,

[0028] The solids conditioner agitates the solids in response to the real-time particle size being larger than the target particle size.

[0029] Furthermore, the water body regulator determines the target water surface flow rate and the solid target flow rate of the solid according to the water body temperature, and adjusts the real-time water surface flow rate to be the same as the target water surface flow rate, wherein,

[0030] In response to the real-time flow rate of the solids being no less than the target flow rate of the solids, the water regulator reduces the real-time flow rate of the water surface;

[0031] In response to the real-time flow rate of solids being less than the target flow rate of solids, the water body regulator increases the real-time flow rate of the water surface.

[0032] Furthermore, the image analysis station constructs a database using solid motion images and water motion images of at least two previous preset maintenance periods as historical data.

[0033] Determine a solid body movement development image and a water body movement development image based on the historical data,

[0034] and determining corresponding expected solid images and expected water images according to adjustment time nodes for completing the solid motion and the water motion;

[0035] comparing the real-time solid image with the expected solid image and generating a corresponding solid development state;

[0036] and, comparing the actual water body image with the expected water body image, and generating a corresponding water body development state;

[0037] The solid development state and the water development state are output as the expected image parameters.

[0038] Furthermore, the image analysis station determines the expected image parameters at the solid time nodes of the solid motion development image,

[0039] and, the expected image parameters at the water body time node corresponding to the water body movement development image;

[0040] In response to the synchronization of the solid body time node and the water body time node, the image analysis station issues a synchronization comparison instruction;

[0041] In response to the solid body time node being out of sync with the water body time node, the image analysis station issues an asynchronous comparison instruction.

[0042] Further, if the solid body time node and the water body time node are consistent with the expected image parameters, the image analysis station determines that the maintenance is completed;

[0043] If the solid time node and the water time node are inconsistent with the expected image parameters, the image analysis station determines to adjust the expected image parameters and outputs them as new environmental parameters, and determines that maintenance is completed after the output.

[0044] Further, in response to the asynchronous comparison instruction,

[0045] If the solid body time node is earlier than the water body time node, the image analysis station determines that the maintenance is completed;

[0046] If the solid time node is later than the water time node, the image analysis station determines that maintenance has failed and resets the database constructed with the historical data.

[0047] Compared with the existing technology, the beneficial effect of the present invention is that it utilizes the monitoring of water state and solid state to determine the corresponding solid living environment, and determines whether the adjustment of the treatment pool is completed based on the adjusted solid development and water flow. While effectively avoiding the problem of decreased solid activity due to low temperature, it also avoids the malfunction of the treatment pool caused by the low temperature environment, effectively improving the stability of the treatment pool operation, and thus effectively improving the treatment efficiency of the manure treatment system.

[0048] Furthermore, by observing the water body, the fluidity of the treatment pool is determined, and whether the various components in the treatment pool can fully contact the air is determined. This effectively avoids the problem of microorganisms in the treatment pool dying or losing their activity due to insufficient access to oxygen, and effectively improves the treatment efficiency of the manure treatment system.

[0049] Furthermore, by observing the size and flow pattern of the solid matter in the treatment pool, the flow and shape of the solid matter in the treatment pool are determined. While effectively improving the flow monitoring of manure and other solid components, it effectively avoids the problem of solid matter being broken up by excessive water flow and invading other equipment with the water flow, thereby effectively improving the stability of the manure treatment system.

[0050] Furthermore, by observing the flow and separation of solids and liquids, it is possible to determine whether the treatment pool maintenance is completed during treatment, and whether the solid matter and microorganisms including sludge in the pool are alive when completed. This effectively avoids the problem of inactivation of microorganisms in the treatment pool due to lack of oxygen, excessive water flow rate or abnormal temperature, which in turn leads to reduced treatment effect, and at the same time effectively improves the stability of the manure treatment system. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 This is a schematic structural diagram of a farm manure treatment system based on solid-liquid separation according to the present invention;

[0052] Figure 2 This is a schematic diagram of the layout of the collector and adjustment module according to an embodiment of the present invention. DETAILED DESCRIPTION

[0053] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are merely used to explain the present invention and are not intended to limit the present invention.

[0054] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0055] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside", and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0056] Furthermore, it should be noted that, in the description of the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0057] See also Figure 1 As shown in FIG, it is a structural schematic diagram of the farm manure treatment system based on solid-liquid separation of the present invention, comprising:

[0058] Several collectors for collecting image parameters and environmental parameters of the processing pool;

[0059] Several adjustment modules are used to generate corresponding solid state parameters and corresponding water state parameters according to image parameters, and adjust the states of solid and water according to environmental parameters, including:

[0060] a solid regulator, responsive to generation of solid state parameters, to adjust solid motion according to environmental parameters;

[0061] A water regulator responds to the generation of water state parameters and adjusts water movement according to environmental parameters;

[0062] The processor is used to control the actions of each collector and adjustment module, including:

[0063] Adjusting the control console to determine the expected image parameters of the treatment tank based on the movement of solids and water;

[0064] Image analysis station, with preset maintenance intervals, to collect real-time image parameters of the processing pool;

[0065] and, comparing expected image parameters with real-time image parameters to determine solid motion and / or water motion for the next predetermined maintenance duration;

[0066] Wherein, the solid state parameters include at least the particle size and integrity of the solid;

[0067] Water state parameters include at least aeration volume and flow rate.

[0068] Compared with the existing technology, the beneficial effect of the present invention is that it utilizes the monitoring of water state and solid state to determine the corresponding solid living environment, and determines whether the adjustment of the treatment pool is completed based on the adjusted solid development and water flow. While effectively avoiding the problem of decreased solid activity due to low temperature, it also avoids the malfunction of the treatment pool caused by the low temperature environment, effectively improving the stability of the treatment pool operation, and thus effectively improving the treatment efficiency of the manure treatment system.

[0069] Example 1: The manure treatment pool of a pig farm uses this system for solid-liquid separation.

[0070] Collector: The camera captures images in the pool and detects the coagulation state of solid feces (such as whether it is clumping), while the temperature sensor monitors the water temperature (which affects the decomposition rate of feces).

[0071] Adjustment module:

[0072] Solids Regulator: If the solid particle size is found to be too large (caking affects separation), the stirring device is started to break up the feces lumps and make them easier to settle.

[0073] Water regulator: Based on the detection result of insufficient aeration, increase the aeration intensity to promote the decomposition of organic matter.

[0074] processor:

[0075] Image analysis station: Compare the expected (evenly suspended fine particles) with the actual image (large precipitates) and adjust the stirring frequency for the next cycle.

[0076] Results: After optimization, the solid separation efficiency was improved and the water turbidity was reduced.

[0077] Example 2: The dairy farm manure treatment pool needs to balance solid precipitation and water flow.

[0078] Collector: Image analysis shows that there are too many floating solids (affecting sedimentation), and the flow rate sensor detects that the water flow is too slow (causing siltation).

[0079] Adjustment module:

[0080] Solids regulator: Reduce the stirring speed to avoid excessive crushing that makes it difficult for microparticles to settle.

[0081] Water regulator: Increases water pump power, increases flow rate and prevents solid sedimentation from clogging pipes.

[0082] processor:

[0083] Adjustment console: Based on historical data, it is predicted that the aeration volume will need to be reduced due to low temperatures in winter (to avoid heat loss).

[0084] Results: Solid precipitation efficiency was stable and water circulation rate adapted to seasonal changes.

[0085] Specifically, the collector collects water images of the treatment pool at a preset resolution and determines the condensation state of the solid according to the shadow range of the water image.

[0086] And, determine the running state of the solid according to the bubble range of the water image,

[0087] and, determining the floating state of the solid according to the grayscale of the water body image;

[0088] The condensation state, running state and floating state are output as image parameters.

[0089] See also Figure 2As shown in FIG, it is a schematic diagram of the layout of the collector and the adjustment module of an embodiment of the present invention. The collector collects the adhesion image of the water body and the temperature data of the water body at a preset resolution, and determines the flow characteristics of the treatment pool based on the adhesion image of the water body.

[0090] and, determining the water flow impact force in the treatment pool based on the water temperature and flow characteristics;

[0091] Output flow characteristics and water flow impact force as environmental parameters;

[0092] Among them, flow characteristics include the flow velocity and direction of water in the treatment pool.

[0093] By observing the water body, the fluidity of the treatment pool is determined, and whether the components in the treatment pool can fully contact the air is determined. This effectively avoids the problem of microorganisms in the treatment pool dying or losing their activity due to insufficient oxygen, and effectively improves the treatment efficiency of the manure treatment system.

[0094] Example 3: Based on Example 1, the system was used to optimize solid-liquid separation in a manure treatment pool (size: 10m×5m×2m) at a pig farm.

[0095] Image acquisition and analysis

[0096] Collector:

[0097] Use a 20-megapixel camera (preset resolution) to capture water images and detect the following parameters:

[0098] Shadow range: Image analysis shows that the shadow area accounts for 35% (threshold: <30%), and the solid coagulation state is judged to be "moderately agglomerated".

[0099] Bubble coverage: Bubbles cover 15% of the area (normal range: 5%~10%), indicating that solids are decomposing too quickly and the operating state is "overactive".

[0100] Grayscale value: The average grayscale value of the water surface is 120 (standard: 80~100), there are too many floating solids, and the state is "lightly suspended".

[0101] Output image parameters: condensed state = 35%, running state = 15%, floating state = 120 grayscale.

[0102] Environmental parameter collection:

[0103] Measured by adhesion image analysis (resolution: 0.1mm / pixel):

[0104] Flow velocity: 0.3m / s (target: 0.5m / s), flow direction southeast (needs correction).

[0105] Temperature: 25°C (optimal: 20-22°C), combined with the flow rate, the water impact force is calculated to be 12N / m² (lower than the target value of 15N / m²).

[0106] Output environmental parameters: flow velocity = 0.3 m / s, flow direction = southeast, impact force = 12 N / m².

[0107] Adjusting module response

[0108] Solid Regulator:

[0109] The target particle size was 5 mm, and the real-time detection was 8 mm (60% over the standard). The agitator (power 1.5 kW) was started and run for 10 minutes to reduce the particle size to 6 mm.

[0110] Water regulator:

[0111] The target aeration volume is 20L / min, but it is currently only 15L / min. Increase the aeration pump power to 120%;

[0112] Adjust the water flow direction to due south and increase the flow rate to 0.45m / s (impact force reaches 14N / m²).

[0113] Processor Feedback

[0114] Image analysis station:

[0115] After 2 hours of maintenance, retest:

[0116] The shadow range is reduced to 28% (meeting the standard), the bubble range is 9% (normal), and the grayscale value is 95 (optimization successful).

[0117] Instructions for the next cycle: shorten the stirring time to 8 minutes and maintain the aeration volume at 20 L / min.

[0118] Example 4: Based on Example 2, the dairy farm treatment pool (capacity 50m³) needs to solve the solid deposition problem in winter.

[0119] Image acquisition and analysis

[0120] Collector:

[0121] HD camera (resolution 4K) analysis:

[0122] Shading range: 50% (severe agglomeration, threshold <20%), condensation state "severely compacted".

[0123] Bubble range: 3% (low temperature leads to insufficient decomposition), operating state is "stagnant".

[0124] Gray value: 150 (excessive suspended solids).

[0125] Output image parameters: condensed state = 50%, running state = 3%, floating state = 150 grayscale.

[0126] Environmental parameter collection:

[0127] Adhesive images show:

[0128] The flow rate is only 0.1m / s (target: 0.3m / s), and the flow direction is chaotic.

[0129] At a water temperature of 8°C (lower than the optimal 15°C), the impact force is only 5N / m².

[0130] Output environmental parameters: flow velocity = 0.1m / s, flow direction = disordered, impact force = 5N / m².

[0131] Adjusting module response

[0132] Solid Regulator:

[0133] The target particle size was 10 mm (larger particles were allowed in winter), and the real-time detection was 20 mm. The heating stirrer was started (power 2 kW, temperature raised to 12 °C), and the particle size dropped to 15 mm.

[0134] Water regulator:

[0135] Adjust the water pump frequency to 40Hz (originally 30Hz), and increase the flow rate to 0.25m / s;

[0136] Close some aeration holes (reduce the aeration rate from 10L / min to 5L / min) to reduce heat loss.

[0137] Processor Feedback

[0138] Image analysis station:

[0139] Recheck after 6 hours:

[0140] Shadow range 22% (still slightly high), Bubble range 6% (improved), Grayscale value 110.

[0141] Next cycle instructions: Heating and stirring are extended to 15 minutes, and the flow rate is maintained at 0.25 m / s.

[0142] Specifically, the adjustment module determines the particle size and aggregation of the solid according to the image parameters, determines the stability of the solid according to the environmental parameters, and outputs the particle size, aggregation and stability as solid features.

[0143] Specifically, the solid regulator determines the target particle size of the solid according to the water temperature, determines the real-time particle size of the solid, and compares the real-time particle size with the target particle size, wherein,

[0144] The solids conditioner agitates the solids in response to the actual particle size being larger than the target particle size.

[0145] Specifically, the water regulator determines the target flow rate of the water surface and the target flow rate of the solid according to the water temperature, and adjusts the real-time flow rate of the water surface to make it the same as the target flow rate of the water surface, wherein,

[0146] The real-time flow rate of the response solid is not less than the target flow rate of the solid, and the water regulator reduces the real-time flow rate of the water surface;

[0147] In response to the real-time flow rate of the solid being less than the target flow rate of the solid, the water regulator increases the real-time flow rate of the water surface.

[0148] It is easy to understand that the solid regulator can be set as a stirring device or a nozzle using water flow / air flow, and the water regulator can be a water pump or a nozzle using water flow / air flow.

[0149] Specifically, the image analysis station uses the solid motion images and water motion images of at least two preset maintenance periods as historical data to build a database.

[0150] Determine the solid motion development image and the water motion development image based on historical data,

[0151] and, determining corresponding expected solid images and expected water images according to adjustment time nodes for completing solid motion and water motion;

[0152] Compare the real-time solid image with the expected solid image and generate the corresponding solid development state;

[0153] and, comparing the actual water body image with the expected water body image, and generating the corresponding water body development status;

[0154] The solid development state and the water development state are output as expected image parameters.

[0155] By observing the size and flow pattern of solid matter in the treatment pool, the flow and shape of solid matter in the treatment pool are determined. While effectively improving the flow monitoring of manure and other solid components, it effectively avoids the problem of solid matter being broken up by excessive water flow and invading other equipment with the water flow, thereby effectively improving the stability of the manure treatment system.

[0156] Example 5: Based on Example 1:

[0157] 1. Solid Characterization Analysis

[0158] Image parameter analysis:

[0159] Real-time particle size: The average diameter of solid particles measured by image analysis is 8 mm (target particle size: 5 mm).

[0160] Aggregation: If the image shows that the solid aggregate area accounts for 40% (threshold: <30%), it is judged as "high aggregation".

[0161] Environmental parameter analysis:

[0162] Water temperature: 25℃ (optimal range: 20~22℃).

[0163] Water impact force: 12N / m² (target: 15N / m²).

[0164] Stability calculation: Due to the high temperature (25°C) and low impact force (12N / m²), the solid decomposes easily but settles poorly, resulting in a "medium to low" stability.

[0165] Output solid characteristics: particle size = 8mm, aggregation = 40%, stability = medium to low.

[0166] 2. Solid state regulator response

[0167] Target particle size: Based on a water temperature of 25°C, set the target particle size to 5mm (high temperatures require smaller particles to avoid corruption).

[0168] Real-time particle size: 8mm (exceeding the standard by 60%).

[0169] Adjustment action:

[0170] The 1.5 kW agitator was started and run for 10 minutes to reduce the particle size to 6 mm (still slightly high, but improved).

[0171] Because the degree of aggregation was still high (35%), the stirring time was increased to 12 minutes in the next cycle.

[0172] 3. Water Regulator Response

[0173] Target flow rate:

[0174] Target flow rate on water surface: 0.5m / s (higher flow rate is required to prevent sedimentation at high temperature).

[0175] Target flow rate for solids: 0.3 m / s (to avoid particles being dispersed).

[0176] Real-time flow rate: 0.3m / s (water surface), 0.2m / s (solid).

[0177] Adjustment action:

[0178] Solid flow rate (0.2 m / s) < target (0.3 m / s) → Increase water surface velocity to 0.4 m / s.

[0179] The solid flow rate is detected to rise to 0.28m / s (close to the target), and the current flow rate is maintained.

[0180] 4. Image Analysis Station Feedback

[0181] Historical data comparison:

[0182] Data of the first two maintenance cycles:

[0183] Cycle 1: Particle size from 10mm to 7mm, taking 15 minutes.

[0184] Cycle 2: Particle size from 9mm to 6mm, taking 12 minutes.

[0185] Prediction: This time: the particle size will change from 8mm to 5mm in 14 minutes (actual time is 15 minutes, error + 1 minute).

[0186] Development status:

[0187] Solids: Actual particle size 6mm vs expected 5mm → “Progress is lagging behind”.

[0188] Water body: Actual flow rate 0.4m / s vs. expected flow rate 0.5m / s → “Close to target”.

[0189] Adjustment for the next cycle:

[0190] Due to solid lag, the stirring power was increased to 2kW and the maintenance cycle was shortened to every 1.5 hours.

[0191] Example 6: Based on Example 2:

[0192] 1. Solid Characterization Analysis

[0193] Image parameter analysis:

[0194] Real-time particle size: The image shows an average diameter of 20 mm (target: 10 mm, larger particles are allowed in winter).

[0195] Aggregation degree: Aggregation area accounts for 60% (severe agglomeration).

[0196] Environmental parameter analysis:

[0197] Water temperature: 8°C (low temperature leads to slow decomposition).

[0198] Water impact force: 5N / m² (target: 10N / m²).

[0199] Stability calculation: solid sedimentation is stable at low temperatures but easy to harden, and the stability is "high but hardening should be prevented".

[0200] Output solid characteristics: particle size = 20mm, aggregation = 60%, stability = high but need to prevent compaction.

[0201] 2. Solid state regulator response

[0202] Target particle size: Based on the water temperature of 8°C, the target particle size is set to 10mm.

[0203] Real-time particle size: 20mm (exceeding the standard by 100%).

[0204] Adjustment action:

[0205] The heating stirrer (2 kW) was started, the water temperature was raised to 12°C, and the particle size was reduced to 15 mm after stirring for 15 minutes.

[0206] Due to the limited effect of low temperature, the heating time was extended to 20 minutes in the next cycle.

[0207] 3. Water Regulator Response

[0208] Target flow rate:

[0209] Target flow rate on the water surface: 0.3m / s (lower flow rate is required at low temperatures to reduce heat loss).

[0210] Target flow rate for solids: 0.15 m / s (to avoid deposition of large particles).

[0211] Real-time flow rate: 0.1m / s (water surface), 0.05m / s (solid).

[0212] Adjustment action:

[0213] Solid flow rate (0.05 m / s) < target (0.15 m / s) → Increase water surface velocity to 0.2 m / s.

[0214] The solid flow rate was detected to rise to 0.12m / s, which was still insufficient, so it was further increased to 0.25m / s (finally meeting the standard).

[0215] 4. Image Analysis Station Feedback

[0216] Historical data comparison:

[0217] Data of the first two maintenance cycles:

[0218] Cycle 1: Particle size from 25 mm to 18 mm, 30 minutes (no heating).

[0219] Cycle 2: Particle size from 22mm to 16mm, 25 minutes (heating for 10 minutes).

[0220] Prediction for this time: It will take 40 minutes for the particle size to change from 20mm to 10mm (in reality it only dropped to 15mm, which did not meet the standard).

[0221] Development status:

[0222] Solid: Actual 15mm vs expected 10mm → “serious lag”.

[0223] Water body: Actual flow rate 0.25m / s vs. expected flow rate 0.3m / s → “80% of target achieved”.

[0224] Adjustment for the next cycle:

[0225] Due to severe solid lag, the heating power was increased to 3 kW and the stirring time was extended to 25 min.

[0226] Specifically, the image analysis station determines the expected image parameters at solid time nodes of the solid motion development image,

[0227] and, the expected image parameters at the water body time nodes corresponding to the water body motion development image;

[0228] In response to the synchronization of the solid body time node and the water body time node, the image analysis station issues a synchronization comparison instruction;

[0229] In response to the fact that the solid time node is not synchronized with the water time node, the image analysis station issues an asynchronous comparison instruction.

[0230] Specifically, if the solid body time node and the water body time node are consistent with the expected image parameters, the image analysis station determines that maintenance is complete;

[0231] If the solid time node and the water time node are inconsistent with the expected image parameters, the image analysis station determines to adjust the expected image parameters and outputs them as new environmental parameters, and determines that the maintenance is completed after the output.

[0232] Specifically, in response to the asynchronous comparison instruction,

[0233] If the solid body time node is earlier than the water body time node, the image analysis station determines that the maintenance is complete;

[0234] If the solid time node is later than the water time node, the image analysis station determines that the maintenance has failed and resets the database constructed with historical data.

[0235] Example 7: Based on Example 3:

[0236] 1. Time node analysis

[0237] Solid motion development image:

[0238] Goal: Reduce solid particle size from 8mm to 5mm

[0239] Historical data shows that it takes 15 minutes (solid time node)

[0240] Image of water movement development:

[0241] Goal: Increase flow rate from 0.3m / s to 0.5m / s

[0242] Historical data shows that it takes 10 minutes (water body time node)

[0243] 2. Synchronicity Judgment

[0244] Solid time node (15 minutes) ≠ water time node (10 minutes) → asynchronous comparison command

[0245] Solid time node (15 minutes) > Water time node (10 minutes) → Maintenance failure

[0246] 3. System Response

[0247] Reason for determination:

[0248] Insufficient solid regulation efficiency (stirring power 1.5kW is too low)

[0249] Water regulation is completed too early, resulting in unstable flow patterns.

[0250] Perform the operation:

[0251] Reset the history database (clear unmatched optimization records)

[0252] Adjust the new parameters:

[0253] Increase stirring power to 2kW (shorten solids processing time to 12 minutes)

[0254] Reduce the initial flow rate target to 0.4m / s (extend water conditioning to 12 minutes)

[0255] Revalidation:

[0256] In the new cycle, solid 12 minutes / water 12 minutes → synchronous completion

[0257] Example 8: Based on Example 4:

[0258] 1. Time node analysis

[0259] Solid motion development image:

[0260] Goal: Reduce particle size from 20mm to 10mm

[0261] Historical data shows that it takes 40 minutes (solid time node)

[0262] Image of water movement development:

[0263] Goal: Increase flow rate from 0.1m / s to 0.3m / s

[0264] Historical data shows that it takes 30 minutes (water body time node)

[0265] 2. Synchronicity Judgment

[0266] Solid time node (40 minutes) ≠ water time node (30 minutes) → asynchronous comparison command

[0267] Solid time node (40 minutes) > Water time node (30 minutes) → Maintenance failure

[0268] 3. System Response

[0269] Reason for determination:

[0270] Low temperature causes insufficient heating (2kW heater power is insufficient)

[0271] Premature completion of flow rate adjustment leads to particle deposition

[0272] Perform the operation:

[0273] Reset the historical database (winter data needs to be remodeled)

[0274] Adjust the new parameters:

[0275] Heating power increased to 3kW (shortening solids processing time to 35 minutes)

[0276] Set step flow rate adjustment: 0.1→0.2m / s (20min), 0.2→0.3m / s (15min)

[0277] Revalidation:

[0278] In the new cycle, solid 35 minutes / water 35 minutes → completed simultaneously

[0279] By observing the flow and separation of solids and liquids, it is determined whether the treatment pool maintenance is completed during treatment, and whether the solid matter and microorganisms including sludge in the pool are alive when completed. This effectively avoids the problem of microbial inactivation in the treatment pool due to lack of oxygen, excessive water flow rate or abnormal temperature, which in turn leads to reduced treatment effect, and effectively improves the stability of the manure treatment system.

[0280] Thus far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art may make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present invention.

[0281] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that the present invention is susceptible to various modifications and variations. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A farm manure treatment system based on solid-liquid separation, characterized in that: include: Several collectors for collecting image parameters and environmental parameters of the processing pool; Several adjustment modules are used to generate corresponding solid state parameters and corresponding water state parameters according to the image parameters, and adjust the states of the solid and water according to the environmental parameters, including: a solid regulator, responsive to generation of solid state parameters, to adjust solid motion according to environmental parameters; a water regulator, responsive to the generation of the water state parameter, to adjust the water movement according to the environmental parameter; The processor is used to control the actions of each collector and adjustment module, including: an adjustment console for determining expected image parameters of the treatment tank based on the solid body movement and the water body movement; An image analysis station, which collects real-time image parameters of the treatment pool at preset maintenance intervals; and, comparing the expected image parameters with the real-time image parameters to determine the solid motion and / or water motion for the next preset maintenance time; Wherein, the solid state parameters include at least the particle size and integrity of the solid; The water state parameters include at least aeration volume and flow rate.

2. The farm manure treatment system based on solid-liquid separation according to claim 1 is characterized in that: The collector collects the water image of the treatment pool at a preset resolution, and determines the condensation state of the solid according to the shadow range of the water image. and determining the operating state of the solid according to the bubble range of the water body image, and, determining the floating state of the solid according to the grayscale of the water body image; The condensation state, the running state, and the floating state are output as image parameters.

3. The farm manure treatment system based on solid-liquid separation according to claim 1 is characterized in that: The collector collects the adhesion image of the water body and the temperature data of the water body at a preset resolution, and determines the flow characteristics of the treatment pool based on the adhesion image of the water body. and, determining the water flow impact force of the treatment pool according to the water body temperature and the flow characteristics; outputting the flow characteristics and the water flow impact force as the environmental parameters; The flow characteristics include the flow velocity and flow direction of the water in the treatment pool.

4. The farm manure treatment system based on solid-liquid separation according to claim 2 or 3, characterized in that: The adjustment module determines the particle size and aggregation of the solid according to the image parameters, determines the stability of the solid according to the environmental parameters, and outputs the particle size, aggregation and stability as the solid features.

5. The farm manure treatment system based on solid-liquid separation according to claim 4 is characterized in that: The solid regulator determines the target particle size of the solid according to the water temperature, determines the real-time particle size of the solid, and compares the real-time particle size with the target particle size, wherein, The solids conditioner agitates the solids in response to the real-time particle size being larger than the target particle size.

6. The farm manure treatment system based on solid-liquid separation according to claim 4 is characterized in that: The water body regulator determines the water surface target flow rate and the solid target flow rate of the solid according to the water body temperature, and adjusts the real-time water surface flow rate to be the same as the water surface target flow rate, wherein, In response to the real-time flow rate of the solids being no less than the target flow rate of the solids, the water regulator reduces the real-time flow rate of the water surface; In response to the real-time flow rate of solids being less than the target flow rate of solids, the water body regulator increases the real-time flow rate of the water surface.

7. The farm manure treatment system based on solid-liquid separation according to claim 5 or 6, characterized in that: The image analysis station uses the solid motion images and water motion images of at least two preset maintenance periods as historical data to build a database. Determine a solid body movement development image and a water body movement development image based on the historical data, and determining corresponding expected solid images and expected water images according to adjustment time nodes for completing the solid motion and the water motion; comparing the real-time solid image with the expected solid image and generating a corresponding solid development state; and, comparing the actual water body image with the expected water body image, and generating a corresponding water body development state; The solid development state and the water development state are output as the expected image parameters.

8. The farm manure treatment system based on solid-liquid separation according to claim 7 is characterized in that: The image analysis station determines the expected image parameters at the solid time nodes of the solid motion development image, and, the expected image parameters at the water body time node corresponding to the water body movement development image; In response to the synchronization of the solid body time node and the water body time node, the image analysis station issues a synchronization comparison instruction; In response to the solid body time node being out of sync with the water body time node, the image analysis station issues an asynchronous comparison instruction.

9. The farm manure treatment system based on solid-liquid separation according to claim 8 is characterized in that: If the solid body time node and the water body time node are consistent with the expected image parameters, the image analysis station determines that the maintenance is completed; If the solid time node and the water time node are inconsistent with the expected image parameters, the image analysis station determines to adjust the expected image parameters and outputs them as new environmental parameters, and determines that maintenance is completed after the output.

10. The farm manure treatment system based on solid-liquid separation according to claim 9 is characterized in that: In response to the asynchronous comparison instruction, If the solid body time node is earlier than the water body time node, the image analysis station determines that the maintenance is completed; If the solid time node is later than the water time node, the image analysis station determines that maintenance has failed and resets the database constructed with the historical data.

Images