Automatic cleaning system and method for inclined tube filler of high-density sedimentation tank

Abstract

The application provides an automatic cleaning system and method for the inclined tube filler of a high-density sedimentation tank, and relates to the technical field of intelligent operation and maintenance of sedimentation tanks, comprising a distributed modular cleaning unit group, an online visual diagnosis module, a sedimentation sensing array module, a time sequence cooperative control module and a modular operation and maintenance control hub, wherein the distributed modular cleaning unit group is arranged in the sedimentation tank and comprises a plurality of standardized independent cleaning modules; the application adopts a modular independent cleaning unit group network architecture to construct a distributed point-to-point cleaning hardware system, the standardized independent cleaning modules can be individually disassembled, expanded and replaced, and can be deployed through plug-and-play by relying on a fast plug-in interface and a CAN bus network, so that equipment maintenance and upgrading can be completed without stopping the whole sedimentation tank, and the disadvantages of traditional equipment maintenance that requires stopping production throughout the whole process can be effectively avoided; the point-to-point precise impact cleaning mode completely eliminates water flow short circuit and cleaning blind area, and has strong universality and adaptability.

Description

Technical Field

[0001] This invention relates to the field of intelligent operation and maintenance technology for sedimentation tanks, and in particular to an automatic flushing system and method for inclined tube packing in high-density sedimentation tanks. Background Technology

[0002] Existing high-density sedimentation tank inclined tube packing flushing technology mostly adopts an integrated truss-type fixed flushing structure, equipped with a timed unified flushing control mode. The equipment has a high degree of overall integration, with flushing nozzles, detection components, and control components integrated into one unit. It drives the entire area to perform synchronous flushing operations through a fixed timing program. Conventional equipment is equipped with a fixed-point pressure flushing component, combined with regular manual inspections to check for inclined tube blockage. It is widely used in various wastewater sedimentation treatment projects and can meet the basic needs of inclined tube packing sludge cleaning and anti-clogging maintenance.

[0003] However, in existing technologies, the overall fixed truss flushing structure suffers from flushing blind spots and water flow short-circuiting problems, resulting in low flushing coverage. Furthermore, the equipment cannot be modularly disassembled and expanded, requiring complete tank shutdown for maintenance, leading to prolonged downtime and low operational efficiency. It also relies on manual periodic inspections to check for blockages, resulting in high labor costs, significant inspection delays, poor blockage identification accuracy, and a high false alarm rate, failing to achieve precise online sensing. Simultaneously, the fixed-cycle timed flushing mode, without considering the actual sludge deposition state, leads to frequent ineffective flushing during low-load periods, resulting in severe waste of water and energy resources and accelerating the aging and wear of the packing material. Additionally, synchronous flushing across the entire area easily causes severe hydraulic disturbances within the tank, leading to large fluctuations in effluent turbidity and secondary sludge runoff problems, lacking a refined timing control mechanism. Finally, existing equipment has a single control protocol and a closed operation and maintenance system, supporting only simple local control and failing to achieve remote intelligent operation and maintenance, automatic fault handling, and full-process closed-loop management, resulting in insufficient intelligence and automation. Therefore, this invention proposes an automatic flushing system and method for inclined tube packing in high-density sedimentation tanks to solve the problems existing in the prior art. Summary of the Invention

[0004] To address the aforementioned issues, this invention proposes an automatic flushing system and method for inclined tube packing in high-density sedimentation tanks. It employs a modular, independent flushing unit network architecture to construct a distributed point-to-point flushing hardware system. Standardized, independent flushing modules can be individually disassembled, expanded, and replaced. Utilizing quick-connect interfaces and CAN bus networking, it achieves plug-and-play deployment, enabling equipment maintenance and upgrades without requiring a complete shutdown of the sedimentation tank, effectively avoiding the drawbacks of traditional equipment maintenance requiring total downtime. The point-to-point precise impact flushing mode completely eliminates water flow short-circuiting and flushing blind spots, stably increasing the flushing coverage of the inclined tube packing to over 98%, reducing equipment maintenance downtime, significantly improving the continuity of sedimentation tank operation and ease of maintenance. It is adaptable to both newly built tanks and the renovation of existing old tanks, demonstrating strong versatility and adaptability.

[0005] To achieve the objectives of this invention, the invention is implemented through the following technical solution: an automatic flushing system for inclined tube packing in a high-density sedimentation tank, comprising a distributed modular flushing unit group, a visual online diagnostic module, a sedimentation sensing array module, a time-series collaborative control module, and a modular operation and maintenance control center. The distributed modular flushing unit group is deployed within the sedimentation tank and includes several standardized independent flushing modules. Each standardized independent flushing module integrates a dual air-water nozzle, a pressure sensor, a flow control valve, and a micro electromagnetic actuator. It connects to the main air and water supply pipes via a quick-connect interface. Each module covers 1-2 standard 500mm×500mm inclined tube cells, and the modules communicate with each other via a CAN bus network.

[0006] The visual online diagnostic module is deployed at the observation window at the top of the sedimentation tank to collect images of the inclined tube and identify the blockage status; the sedimentation sensing array module is deployed in layers along the height of the inclined tube to collect sludge sedimentation gradient data; the time-series collaborative control module is used for zoned flushing timing regulation; the modular operation and maintenance control center integrates multiple protocol stacks, multi-level response mechanisms and remote operation and maintenance interfaces to link various modules to achieve intelligent flushing control throughout the entire process.

[0007] Further improvements include: the standardized independent flushing module is an independently packaged and detachable structure, which has the functions of plug-and-play deployment, individual disassembly and replacement, and capacity expansion and upgrade; each standardized independent flushing module realizes low-latency distributed networking communication through CAN bus, adopts point-to-point precise impact flushing mode, and each module is independently controlled and executes flushing actions independently, realizing the zoned rotation flushing operation of the sedimentation tank.

[0008] Further improvements are made in that: the deposition sensing array module is a multi-layer distributed combined sensing structure, composed of ultrasonic sensors and optical reflection sensors, which are arranged at equal intervals along the vertical height of the inclined tube packing, fully covering the inclined tube monitoring area corresponding to each standardized independent flushing module; the deposition sensing array module collects multi-dimensional data on the sludge deposition thickness, deposition density and spatial density gradient on the surface of the inclined tube packing in each zone in real time, and reconstructs a three-dimensional thermal map of sludge deposition in the inclined tube packing based on the global sensing data.

[0009] Further improvements include: the visual online diagnostic module is a standardized perception module with IP68 waterproof protection, integrating an underwater high-definition industrial camera and an AI image analysis unit, equipped with a YOLOv8 lightweight recognition model, used to identify four types of oblique tube blockage: thin-film, blocky, honeycomb, and mixed, and outputting real-time blockage type, blockage area percentage, and blockage location coordinates; the visual online diagnostic module has the function of adding or removing deployment points, and the collected image data and blockage feature data are synchronized to the cloud operation and maintenance platform in real time, supporting remote online diagnosis and historical analysis of blockage trends; wherein, the YOLOv8 lightweight recognition model uses a lightweight loss function formula to complete model iterative training and accurate recognition, the specific formula being:

[0010] ;

[0011] In the formula, Ltotal is the total loss value of the YOLOv8 model, used to characterize the overall recognition error of the model. The smaller the value, the higher the recognition accuracy of the model. Lcls is the classification loss function, used to calculate the error between the predicted values ​​of the four blockage patterns and the real labels, so as to achieve accurate determination of the blockage type. Lbox is the bounding box regression loss function, used to calculate the position and size deviation between the predicted box and the real box of the blockage area, and accurately output the blockage location coordinates and blockage area. Lobj is the target confidence loss function, used to determine whether there is a blockage target in the image area, filter water impurities and light and shadow interference, and reduce the probability of false recognition and missed recognition. The model relies on this lightweight loss formula to achieve high-precision recognition of small targets and weak blockage features in complex underwater scenes, and is suitable for underwater turbidity imaging conditions with inclined tube packing.

[0012] Further improvements are made in the following aspects: The time-series collaborative control module is the core unit for refined time-series regulation in different zones, and it has built-in multi-segment time-series optimization function, dynamic duration calculation function and sludge-water linkage control function; The time-series collaborative control module completes the division of multiple independent flushing zones according to the water flow pattern of the sedimentation tank, realizes countercurrent priority staggered flushing by relying on the gradient delay time-series algorithm, and dynamically adjusts the flushing duration of a single zone by combining the sludge load data of each zone, and realizes the matching of flushing and sludge pumping time sequences by linking with the plant's sludge pumping system.

[0013] Further improvements include: the modular operation and maintenance control center serves as the core of the system's overall management and control, adopting an integrated modular architecture combining an MCU and an edge computing board. It incorporates a multi-protocol communication stack, a five-level operation response mechanism, and an intelligent operation and maintenance management unit. The modular operation and maintenance control center is compatible with three mainstream industrial protocols: Modbus TCP, MQTT, and OPC UA. It seamlessly integrates with various factory SCADA systems, possessing full-link functions such as equipment status monitoring, data processing and analysis, fault isolation and protection, remote policy distribution, health scoring, and automatic generation of operation and maintenance work orders. This constructs an integrated closed-loop management and control system encompassing perception, decision-making, execution, and operation and maintenance, enabling unmanned intelligent operation and maintenance of equipment.

[0014] An automatic flushing method for inclined tube packing in a high-density sedimentation tank includes the following steps:

[0015] S1. Real-time data on sludge deposition thickness and density gradient in each region of the inclined tube are collected using the deposition sensing array module to construct a three-dimensional deposition thermogram.

[0016] S2. Train the flushing-deposition response curve based on the LSTM machine learning model, calculate the dynamic critical blockage threshold, and generate an adaptive flushing cycle using the dual criteria of threshold triggering and time window constraint.

[0017] S3. Identify the blockage pattern through the visual online diagnostic module and match the corresponding flushing strategy;

[0018] S4. Divide the sedimentation tank into multiple sections and use the countercurrent priority gradient delay time sequence algorithm to complete the zone flushing;

[0019] S5. Achieve closed-loop operation and maintenance management throughout the entire process through a modular operation and maintenance control center.

[0020] A further improvement is made in S2, where the adaptive rinsing cycle is calculated using the following formula:

[0021] ;

[0022] Wherein, Ttrigger is the real-time trigger flushing cycle of the module, in hours; Tmin is the minimum forced flushing interval, fixed at 6 hours, used to ensure the basic flushing frequency under extreme conditions; Tmax is the maximum limit flushing interval, fixed at 72 hours, used to avoid severe packing blockage caused by long-term lack of flushing; D is the real-time sludge deposition density in the local area of ​​the inclined tube, in kg / m³; Dcrit is the dynamic critical blockage threshold output by the LSTM model in real time, in kg / m³; and t is the interval between the current module and the last flush, in hours.

[0023] A further improvement is made in S4, where the reverse-current priority gradient delay timing algorithm uses the following formula:

[0024] ;

[0025] in, The gradient delay flushing time of the nth flushing section relative to the first inlet flushing section is expressed in seconds (s); n is the sequence number of the flushing sections divided along the water flow direction of the sedimentation tank, with values ​​of 2, 3, 4, and 5. The preset unit base delay time is fixed at 15s; this formula is used to achieve a step-by-step gradient delay start-up flushing at the inlet, front middle section, rear middle section, and outlet.

[0026] A further improvement is made in S4, where the dynamic flushing duration for a single section during zone flushing is calculated using the following formula:

[0027] ;

[0028] Wherein, Trun is the real-time flushing duration of a single section, in min; Tbase is the basic flushing duration, fixed at 5 min; k is the sludge load correction coefficient, with a value of 0.25 m³ / (kg·min); Davg is the average deposition density of the inclined tube in this section, in kg / m³; the dynamic range of flushing duration is 5-12 min, adapting to different sludge load conditions; the average deposition density Davg of the section is obtained by collecting the sludge gradient data of the partition by the deposition sensing array module and calculating the mean, and the dynamic flushing duration is generated in real time by the time-series collaborative control module to achieve adaptive matching between sludge load and flushing duration.

[0029] The beneficial effects of this invention are as follows:

[0030] 1. This invention adopts a modular independent flushing unit networking architecture to build a distributed point-to-point flushing hardware system. The standardized independent flushing modules can be disassembled, expanded, and replaced individually. Relying on quick-connect interfaces and CAN bus networking, it achieves plug-and-play deployment. Equipment maintenance and upgrades can be completed without shutting down the entire sedimentation tank, effectively avoiding the drawbacks of traditional equipment maintenance that requires a complete shutdown. The point-to-point precise impact flushing mode completely eliminates water flow short circuits and flushing blind spots, stably increasing the flushing coverage of inclined tube packing to over 98%, reducing equipment maintenance downtime, and significantly improving the continuity of sedimentation tank operation and ease of maintenance. It is suitable for newly built tanks and the renovation of existing old tanks, with strong versatility and adaptability.

[0031] 2. This invention employs a visual recognition-based online diagnostic module for obstructed pipe conditions, establishing a modular AI intelligent perception system. Relying on IP68 high-protection underwater visual acquisition components and the YOLOv8 lightweight recognition model, it accurately distinguishes four types of blockage and precisely outputs multi-dimensional data on blockage location, area, and type. It abandons the traditional, extensive maintenance model of periodic manual inspections. The system can perform real-time online monitoring, remote diagnosis, and trend analysis, reducing the frequency of manual inspections from once a week to once a month, significantly reducing the workload of manual maintenance. Simultaneously, it controls the false trigger rate of blockages to within 3%, solving the problems of delayed manual inspections, large judgment errors, and frequent missed and false detections, providing reliable data perception support for precise adaptive flushing.

[0032] 3. This invention adopts an adaptive flushing cycle generation method based on sludge deposition gradient, breaking through the technical bottleneck of traditional fixed-sequence flushing. It relies on a multi-layer ultrasonic + optical deposition sensor array to construct a three-dimensional sludge deposition thermogram, and combines an LSTM machine learning model to iteratively optimize the critical clogging threshold. It uses a threshold trigger + time window constraint dual criterion to replace the traditional fixed-cycle flushing logic. Through a dedicated adaptive algorithm, it dynamically matches the flushing timing of each module, eliminating the problems of ineffective flushing under low sludge load and incomplete flushing under high load, and achieving precise flushing on demand. Ultimately, it reduces the overall flushing frequency of the system by 40% and the backwash water consumption by 35%, effectively reducing the wear and tear of the packing material due to long-term frequent flushing, extending the service life of the inclined tube packing to more than 5 years, and significantly improving the economic efficiency of equipment operation.

[0033] 4. This invention employs a multi-segment collaborative flushing timing optimization algorithm to achieve refined timing control of modular and zoned flushing. The sedimentation tank is divided into multiple independent flushing segments along the water flow direction. A counter-current priority and gradient delay control strategy is adopted, coupled with a dynamic duration flushing and flushing sludge removal linkage mechanism. This effectively avoids the problem of excessive hydraulic disturbance in the tank caused by simultaneous flushing of multiple segments. The flushing duration of each segment is adaptively adjusted according to the sludge load. Local sludge removal is quickly started after flushing to prevent secondary sedimentation and sludge run-off of flushed sludge. This reduces the fluctuation range of turbidity in the sedimentation tank effluent by 60%, significantly improves the stability of effluent water quality, ensures the continuous and stable water purification effect of the high-density sedimentation tank, and achieves continuous and safe operation without production interruption.

[0034] 5. This invention integrates a modular control center with a remote operation and maintenance protocol stack to construct a closed-loop intelligent system covering the entire chain of perception, decision-making, execution, and operation and maintenance. The modular control center is compatible with three mainstream industrial protocols and can seamlessly connect to existing SCADA control systems. It has a built-in five-level equipment operation response mechanism to adapt to various working conditions and fault scenarios. With dual operation and maintenance interfaces on both web and mobile terminals, it enables unmanned operation and maintenance modes such as remote distribution of flushing strategies, automatic assessment of equipment health, and automatic generation of operation and maintenance work orders. This changes the traditional local manual on-site operation and maintenance mode, reduces the labor costs of operation and maintenance, and comprehensively improves the intelligent, automated, and standardized operation and maintenance level of the inclined tube packing flushing system. Attached Figure Description

[0035] Figure 1 This is a schematic diagram of the system of the present invention;

[0036] Figure 2 This is a flowchart of the method of the present invention. Detailed Implementation

[0037] To enhance understanding of the present invention, the present invention will be further described in detail below with reference to embodiments. These embodiments are only used to explain the present invention and do not constitute a limitation on the scope of protection of the present invention.

[0038] Example 1

[0039] according to Figure 1 , 2 As shown, this embodiment proposes an automatic flushing system and method for inclined tube packing in a high-density sedimentation tank. A standard high-density sedimentation tank is used, and the inclined tube packing area is divided into 48 standard 500mm×500mm cells. Each cell is equipped with 48 standardized independent flushing modules, with each module covering one standard cell. The modules connect to the main air and water supply lines of the plant via quick-connect interfaces, and a distributed flushing network is established between the modules via a CAN bus. During system operation, point-to-point precise flushing is achieved through the modular independent architecture, eliminating blind spots and water flow short-circuiting problems inherent in traditional truss-based full-area flushing systems.

[0040] This embodiment employs an adaptive flushing cycle formula, combining real-time data on sludge deposition density to regulate the flushing timing. Initial values ​​are set to Tmin=6h and Tmax=72h, and the dynamic threshold Dcrit is iteratively optimized using an LSTM model. When the local deposition density D exceeds the dynamic threshold Dcrit, the module immediately initiates forced flushing at the shortest interval; when the deposition density is low but the interval reaches its upper limit, preventative flushing is automatically triggered.

[0041] This embodiment supports independent disassembly and maintenance of each module without the need for a complete shutdown of the pool. The results show that the flushing coverage of this architecture reaches 98.6%, and the maintenance downtime is reduced by 72% compared to traditional equipment, perfectly adapting to the needs of continuous production operation.

[0042] Example 2

[0043] according to Figure 1 , 2 As shown in the figure, this embodiment proposes an automatic flushing system and method for inclined tube packing in a high-density sedimentation tank. Six sets of IP68-level visual online diagnostic modules are evenly deployed on the top of the sedimentation tank to fully cover the inclined tube packing area. The modules are equipped with a YOLOv8 lightweight recognition model. The model parameters are optimized based on the accuracy calculation formula. After debugging, the model recognition accuracy is stable at ≥97.2%.

[0044] The system acquires real-time images of the inclined tube packing surface, automatically distinguishes between four types of blockage faults: film-type, block-type, honeycomb-type, and mixed-type. It accurately outputs the coordinates and area percentage of each blockage area and simultaneously uploads them to the cloud-based operation and maintenance platform to generate a blockage trend curve. Based on the identification results, the system automatically matches corresponding flushing water pressure, duration, and timing strategies. For large-area block-type blockages, the flushing time is extended, while for film-type mild blockages, a low-pressure rapid flushing mode is used.

[0045] This embodiment eliminates the original weekly manual inspection system and replaces it with a monthly review inspection. After 30 days of equipment operation, the blockage false trigger rate was only 2.1%, with no missed or incorrect inspections, which greatly reduces the intensity of manual maintenance and provides stable sensing support for precise flushing.

[0046] Example 3

[0047] according to Figure 1 , 2 As shown in the figure, this embodiment proposes an automatic flushing system and method for inclined tube packing in a high-density sedimentation tank. A three-layer ultrasonic + optical combined deposition sensor array is arranged in layers along the vertical height of the inclined tube to collect sludge deposition thickness and density data at different heights and in different areas in real time, and to construct a high-precision three-dimensional deposition thermal map.

[0048] Based on the LSTM threshold iteration formula, with an iteration smoothing coefficient α=0.85, the model is trained using a historical 3-month flushing-deposition dataset, and the dynamic critical clogging threshold Dcrit is continuously iteratively optimized. A dual-criteria flushing trigger formula combining threshold triggering and time window constraints (the core adaptive control method of this invention, generated by the modular operation and maintenance control center reading real-time sludge deposition data from the deposition sensing array and calculating the LSTM dynamic threshold) is adopted, abandoning the traditional fixed 24-hour flushing cycle and achieving on-demand adaptive flushing. For low influent load and low deposition density conditions, the system automatically extends the flushing interval to the upper limit of 72 hours; for heavy rain and high turbidity influent conditions, it automatically shortens the flushing interval to the minimum limit of 6 hours.

[0049] After 60 days of continuous operation and testing, this embodiment, compared with the traditional fixed flushing mode, reduced the overall flushing frequency by 42%, reduced the backflushing water consumption by 36%, significantly reduced the wear rate of the packing, and effectively extended the service life of the equipment.

[0050] Example 4

[0051] according to Figure 1 , 2 As shown in the figure, this embodiment proposes an automatic flushing system and method for inclined tube packing in a high-density sedimentation tank. The high-density sedimentation tank is divided into four independent flushing sections along the water flow direction: inlet, front middle section, rear middle section, and outlet. A counter-current priority and gradient delay timing control strategy is adopted, and a basic delay time is set based on the gradient delay formula. =15s, and the delay time of each section is calculated sequentially to achieve segmented and staggered start flushing. At the same time, a dynamic duration calculation formula is adopted, with the base flushing duration Tbase=5min and the load correction coefficient k=0.25. The flushing duration is dynamically adjusted according to the real-time average deposition density of each section, and the duration range is stably controlled within 5-12min.

[0052] The system strictly adheres to the linkage logic of initiating local sludge removal 5 seconds after flushing is completed, quickly removing detached sludge. Operational monitoring data shows that in this embodiment, the range of hydraulic disturbance within the tank is significantly reduced, the fluctuation range of effluent turbidity is reduced by 63%, there is no sludge runoff or secondary sedimentation throughout the process, and the stability of effluent water quality is significantly improved.

[0053] Example 5

[0054] according to Figure 1 , 2 As shown in the figure, this embodiment proposes an automatic flushing system and method for inclined tube packing in a high-density sedimentation tank. It is equipped with a modular integrated control center, which integrates three industrial protocol stacks: Modbus TCP, MQTT, and OPC UA. It seamlessly connects to the existing SCADA operation and maintenance system in the plant and has a built-in five-level operation response mechanism: normal, early warning, load limit, forced flushing, and fault isolation.

[0055] This embodiment features a core flushing trigger formula based on a threshold trigger and a time window constraint. This formula is constructed using the LSTM adaptive control core method of this invention. It relies on real-time sludge deposition data collected by the deposition sensing array module and the model's dynamic critical threshold. The modular operation and maintenance control center performs real-time calculations and adaptively generates flushing trigger times for each module, achieving intelligent on-demand flushing under all operating conditions. The system integrates the aforementioned sensing, decision-making, and execution technologies. Through an edge computing unit, it aggregates real-time operating data, visual diagnostic data, and deposition sensing data from each flushing module, automatically completes module health scoring, automatically triggers isolation protection for faulty modules, generates maintenance work orders, and simultaneously pushes them to the web and mobile app. Maintenance personnel can remotely issue flushing strategies, adjust algorithm parameters, and view equipment operating trends and fault records, achieving unmanned operation and maintenance.

[0056] After long-term operation and verification, this embodiment can realize closed-loop intelligent management and control of the entire chain, without the need for on-site personnel, reducing maintenance manpower costs by 52% and improving equipment fault handling and response efficiency by more than 80%.

[0057] Comparative Example: Traditional Fixed Truss Timed Flushing System

[0058] The existing system employs a traditional, fixed truss-type flushing device with a 24-hour fixed-time flushing program. It lacks a modular distributed control structure, AI-powered online visual perception, and adaptive cycle and timing optimization algorithms. It relies solely on weekly manual inspections to troubleshoot blockages. Equipment failure maintenance requires complete system shutdown, and the system lacks zoned timing control for synchronous flushing and a remote intelligent operation and maintenance system. Under the same influent water quality, treatment capacity, and operating environment, the system operated continuously for 60 days. Key parameters such as equipment flushing coverage, downtime, frequency of manual inspections, water and energy consumption, effluent turbidity fluctuations, and maintenance costs were statistically analyzed and compared with the five embodiments of this invention to verify the advanced nature and practicality of the technical solution.

[0059] Validation data:

[0060] Inclined tube flushing coverage 82.3% 98.5% An increase of 16.2%. Annual maintenance downtime 128h 38.4h Reduce by 70% Frequency of manual inspection Once a week Once a month Inspection workload reduced by 75% Blocking false trigger rate 11.6% 2.8% Decrease by 8.8% Daily flushing frequency 1 time / day 0.6 times / day Reduced by 40% Backwash water volume 100% 65% Reduce by 35% Fluctuation range of effluent turbidity ±3.2 NTU ±1.28NTU Reduce by 60% Operation and maintenance labor costs 100% 50% Reduce by 50% Service life of inclined tube packing 2-3 years 5 years or more Service life greatly extended

[0061] This data, using a traditional truss-type timed flushing system as a comparison, quantitatively verifies the technological superiority of the five core innovations of this invention—modular hardware architecture, AI visual perception, adaptive cycle control, time-series collaborative optimization, and remote closed-loop operation and maintenance—under the same influent water quality, treatment load, and operating environment conditions. First, this invention, relying on a distributed modular independent flushing unit architecture, eliminates flushing blind spots and water flow short-circuiting problems, increasing flushing coverage from 82.3% to 98.5%. Simultaneously, the modular online operation and maintenance feature reduces annual maintenance downtime by 70%, significantly improving equipment continuous operation rate. Second, the intelligent perception system based on the YOLOv8 visual online diagnostic module replaces the traditional manual inspection mode, reducing inspection frequency by 75% and the blockage false trigger rate from 11.6% to 2.8%, effectively solving the shortcomings of slow manual operation and maintenance and low identification accuracy. Furthermore, the dual-criteria adaptive flushing method based on LSTM dynamic thresholds abandons the traditional fixed-time flushing mode, precisely starting and stopping flushing as needed. This reduces the daily flushing frequency by 40% and backwash water consumption by 35%, resulting in significant water and energy savings. It also effectively slows down packing wear and extends the service life from 2-3 years to over 5 years. Simultaneously, the multi-segment gradient delay time-series optimization algorithm effectively suppresses hydraulic disturbances within the tank, reducing effluent turbidity fluctuations by 60%, eliminating sludge runoff and secondary sedimentation, and significantly improving effluent water quality stability. Finally, the modular control center's full-link closed-loop operation and maintenance system achieves unmanned intelligent management and control, reducing maintenance labor costs by 50%. This comprehensively improves the automation and intelligent operation level of the high-density sedimentation tank inclined tube flushing system, with all indicators significantly outperforming traditional technical solutions.

[0062] This invention adopts a modular independent flushing unit networking architecture to build a distributed point-to-point flushing hardware system. The standardized independent flushing modules can be disassembled, expanded, and replaced individually. Relying on quick-connect interfaces and CAN bus networking, it achieves plug-and-play deployment. Equipment maintenance and upgrades can be completed without shutting down the entire sedimentation tank, effectively avoiding the drawbacks of traditional equipment maintenance that requires complete downtime. The point-to-point precise impact flushing mode completely eliminates water flow short circuits and flushing blind spots, stably increasing the flushing coverage of inclined tube packing to over 98%, reducing equipment maintenance downtime, and significantly improving the continuity of sedimentation tank operation and ease of maintenance. It is suitable for both newly built tanks and the renovation of existing old tanks, with strong versatility and adaptability. This invention employs a vision-based online diagnostic module for obstructed pipe conditions, establishing a modular AI intelligent perception system. Leveraging an IP68 high-protection underwater visual acquisition component and the YOLOv8 lightweight recognition model, it accurately distinguishes four types of blockage and precisely outputs multi-dimensional data on blockage location, area, and type. It abandons the traditional, extensive maintenance model of periodic manual inspections. The system can perform real-time online monitoring, remote diagnosis, and trend analysis, reducing the frequency of manual inspections from once a week to once a month, significantly decreasing the workload of manual maintenance. Simultaneously, it controls the false trigger rate of blockages to within 3%, solving the problems of delayed manual inspections, large judgment errors, and frequent missed and false detections, providing reliable data perception support for precise adaptive flushing. This invention employs an adaptive flushing cycle generation method based on sludge deposition gradient, breaking through the technical bottleneck of traditional fixed-sequence flushing. It relies on a multi-layer ultrasonic + optical deposition sensor array to construct a three-dimensional sludge deposition thermogram, and combines an LSTM machine learning model to iteratively optimize the critical clogging threshold. It replaces the traditional fixed-cycle flushing logic with a dual criterion of threshold triggering + time window constraint, and dynamically matches the flushing timing of each module through a dedicated adaptive algorithm. This eliminates the problems of ineffective flushing under low sludge load and incomplete flushing under high load, achieving precise flushing on demand. Ultimately, it reduces the overall flushing frequency of the system by 40%, reduces backwash water consumption by 35%, effectively reduces the wear and tear of the packing material due to long-term frequent flushing, extends the service life of the inclined tube packing to more than 5 years, and significantly improves the economic efficiency of equipment operation. This invention employs a multi-segment collaborative flushing timing optimization algorithm to achieve refined timing control of modular and zoned flushing. The sedimentation tank is divided into multiple independent flushing segments along the water flow direction. A counter-current priority and gradient delay control strategy is adopted, coupled with a dynamic duration flushing and flushing sludge removal linkage mechanism. This effectively avoids the problem of excessive hydraulic disturbance in the tank caused by simultaneous flushing of multiple segments. The flushing duration of each segment is adaptively adjusted according to the sludge load. Local sludge removal is quickly started after flushing to prevent secondary sedimentation and sludge runoff. The turbidity fluctuation of the sedimentation tank effluent is reduced by 60%, which greatly improves the stability of the effluent water quality, ensures the continuous and stable water purification effect of the high-density sedimentation tank, and achieves continuous and safe operation without production interruption.This invention integrates a modular control center with a remote operation and maintenance protocol stack to construct a closed-loop intelligent system covering the entire chain of perception, decision-making, execution, and operation and maintenance. The modular control center is compatible with three mainstream industrial protocols and can seamlessly connect to existing SCADA control systems. It has a built-in five-level equipment operation response mechanism to adapt to various working conditions and fault scenarios. With dual operation and maintenance interfaces on both web and mobile terminals, it enables unmanned operation and maintenance modes such as remote distribution of flushing strategies, automatic assessment of equipment health, and automatic generation of operation and maintenance work orders. This changes the traditional local manual on-site operation and maintenance mode, reduces operation and maintenance labor costs, and comprehensively improves the intelligent, automated, and standardized operation and maintenance level of the inclined tube packing flushing system.

[0063] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. An automatic flushing system for inclined tube packing in a high-density sedimentation tank, comprising a distributed modular flushing unit group, a visual online diagnostic module, a sedimentation sensing array module, a time-series collaborative control module, and a modular operation and maintenance control center, characterized in that: The distributed modular flushing unit group is deployed in the sedimentation tank and includes several standardized independent flushing modules. Each standardized independent flushing module integrates air and water dual nozzles, pressure sensors, flow control valves and micro electromagnetic actuators. It is connected to the main air supply and water supply mains through quick-connect interfaces. Each module covers 1-2 standard 500mm×500mm inclined tube cells. The modules communicate with each other through a CAN bus network. The visual online diagnostic module is deployed in the observation window at the top of the sedimentation tank to acquire images of the inclined tube and identify the blockage status; The deposition sensing array module is deployed in layers along the height of the inclined tube to collect sludge deposition gradient data; the time-series collaborative control module is used for zoned flushing timing regulation; the modular operation and maintenance control center integrates multiple protocol stacks, multi-level response mechanisms and remote operation and maintenance interfaces, and links various modules to achieve intelligent flushing control throughout the entire process.

2. The automatic flushing system for inclined tube packing in a high-density sedimentation tank according to claim 1, characterized in that: The standardized independent flushing module is an independently packaged and detachable structure, which has the functions of plug-and-play deployment, individual disassembly and replacement, and capacity expansion and upgrade. Each standardized independent flushing module realizes low-latency distributed networking communication through CAN bus, adopts point-to-point precision impact flushing mode, and each module is independently controlled and executes flushing actions independently, realizing the zonal rotation flushing operation of sedimentation tank.

3. The automatic flushing system for inclined tube packing in a high-density sedimentation tank according to claim 1, characterized in that: The deposition sensing array module is a multi-layered distributed combined sensing structure, composed of ultrasonic sensors and optical reflection sensors, and is arranged in layers at equal intervals along the vertical height of the inclined tube packing, fully covering the inclined tube monitoring area corresponding to each standardized independent flushing module; the deposition sensing array module collects multi-dimensional data on the sludge deposition thickness, deposition density and spatial density gradient on the surface of the inclined tube packing in each zone in real time, and reconstructs a three-dimensional thermal map of sludge deposition in the inclined tube packing based on the global sensing data.

4. The automatic flushing system for inclined tube packing in a high-density sedimentation tank according to claim 1, characterized in that: The visual online diagnostic module is a standardized perception module with IP68 waterproof protection, integrating an underwater high-definition industrial camera and an AI image analysis unit. It is equipped with a lightweight YOLOv8 recognition model to identify four types of oblique tube blockage: thin-film, blocky, honeycomb, and mixed. It outputs real-time blockage type, blockage area percentage, and blockage location coordinates. The module allows for adding or removing deployment points, and the collected image data and blockage feature data are synchronized to the cloud-based operation and maintenance platform in real time, supporting remote online diagnosis and historical analysis of blockage trends. The lightweight YOLOv8 recognition model uses a lightweight loss function formula for iterative model training and accurate recognition. The specific formula is as follows: ； In the formula, Ltotal is the total loss value of the YOLOv8 model, used to characterize the overall recognition error of the model. The smaller the value, the higher the recognition accuracy of the model. Lcls is the classification loss function, used to calculate the error between the predicted values ​​of the four blockage patterns and the real labels, so as to achieve accurate determination of the blockage type. Lbox is the bounding box regression loss function, used to calculate the position and size deviation between the predicted box and the real box of the blockage area, and accurately output the blockage location coordinates and blockage area. Lobj is the target confidence loss function, used to determine whether there is a blockage target in the image area, filter water impurities and light and shadow interference, and reduce the probability of false recognition and missed recognition. The model relies on this lightweight loss formula to achieve high-precision recognition of small targets and weak blockage features in complex underwater scenes, and is suitable for underwater turbidity imaging conditions with inclined tube packing.

5. The automatic flushing system for inclined tube packing in a high-density sedimentation tank according to claim 1, characterized in that: The time-series collaborative control module is the core unit for refined time-series regulation in different zones. It has built-in functions for multi-segment time-series optimization, dynamic duration calculation, and sludge-water linkage control. The time-series collaborative control module divides multiple independent flushing zones according to the flow pattern of the sedimentation tank, and realizes countercurrent priority staggered flushing by relying on the gradient delay time-series algorithm. At the same time, it dynamically adjusts the flushing duration of a single zone by combining the sludge load data of each zone, and links with the plant's sludge pumping system to achieve flushing and sludge pumping time-series matching.

6. The automatic flushing system for inclined tube packing in a high-density sedimentation tank according to claim 1, characterized in that: The modular operation and maintenance control center serves as the core of the system's overall management and control. It adopts an integrated modular architecture combining an MCU and an edge computing board, and incorporates a multi-protocol communication stack, a five-level operation response mechanism, and an intelligent operation and maintenance management unit. The modular operation and maintenance control center is compatible with three mainstream industrial protocols: Modbus TCP, MQTT, and OPC UA. It seamlessly connects to various factory SCADA systems and possesses full-link functions such as equipment status monitoring, data processing and analysis, fault isolation and protection, remote policy distribution, health scoring, and automatic generation of operation and maintenance work orders. It constructs an integrated closed-loop management and control system encompassing perception, decision-making, execution, and operation and maintenance, enabling unmanned intelligent operation and maintenance of equipment.

7. An automatic flushing method for inclined tube packing in a high-density sedimentation tank, employing the automatic flushing system for inclined tube packing in a high-density sedimentation tank as described in any one of claims 1-6, characterized in that, Includes the following steps: S1. Real-time data on sludge deposition thickness and density gradient in each region of the inclined tube are collected using the deposition sensing array module to construct a three-dimensional deposition thermogram. S2. Train the flushing-deposition response curve based on the LSTM machine learning model, calculate the dynamic critical blockage threshold, and generate an adaptive flushing cycle using the dual criteria of threshold triggering and time window constraint. S3. Identify the blockage pattern through the visual online diagnostic module and match the corresponding flushing strategy; S4. Divide the sedimentation tank into multiple sections and use the countercurrent priority gradient delay time sequence algorithm to complete the zone flushing; S5. Achieve closed-loop operation and maintenance management throughout the entire process through a modular operation and maintenance control center.

8. The automatic flushing method for inclined tube packing in a high-density sedimentation tank according to claim 7, characterized in that: In S2, the adaptive rinsing cycle is calculated using the following formula: ； Wherein, Ttrigger is the real-time trigger flushing cycle of the module, in hours; Tmin is the minimum forced flushing interval, fixed at 6 hours, used to ensure the basic flushing frequency under extreme conditions; Tmax is the maximum limit flushing interval, fixed at 72 hours, used to avoid severe packing blockage caused by long-term lack of flushing; D is the real-time sludge deposition density in the local area of ​​the inclined tube, in kg / m³; Dcrit is the dynamic critical blockage threshold output by the LSTM model in real time, in kg / m³; and t is the interval between the current module and the last flush, in hours.

9. The automatic flushing method for inclined tube packing in a high-density sedimentation tank according to claim 7, characterized in that: In S4, the reverse-current priority gradient delay timing algorithm uses the following formula: ； in, The gradient delay flushing time of the nth flushing section relative to the first inlet flushing section is expressed in seconds (s); n is the sequence number of the flushing sections divided along the water flow direction of the sedimentation tank, with values ​​of 2, 3, 4, and 5. The preset unit base delay time is fixed at 15s; this formula is used to achieve a step-by-step gradient delay start-up flushing at the inlet, front middle section, rear middle section, and outlet.

10. The automatic flushing method for inclined tube packing in a high-density sedimentation tank according to claim 9, characterized in that: In step S4, during zoned flushing, the dynamic flushing duration for a single zone is determined using the following formula: ； Wherein, Trun is the real-time flushing duration of a single section, in min; Tbase is the basic flushing duration, fixed at 5 min; k is the sludge load correction coefficient, with a value of 0.25 m³ / (kg·min); Davg is the average deposition density of the inclined tube in this section, in kg / m³; the dynamic range of flushing duration is 5-12 min, adapting to different sludge load conditions; the average deposition density Davg of the section is obtained by collecting the sludge gradient data of the partition by the deposition sensing array module and calculating the mean, and the dynamic flushing duration is generated in real time by the time-series collaborative control module to achieve adaptive matching between sludge load and flushing duration.

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