A new intelligent water purification plant system

Abstract

This invention belongs to the field of wastewater purification technology, specifically a novel intelligent water purification plant system. It includes a fully enclosed plant building constructed with a light steel structure and prefabricated components. Within the plant building, a wastewater pretreatment module, a multi-stage biochemical module, a deep treatment module, a multi-energy complementary power supply module, an AI collaborative monitoring module, a biochemical early warning module, and a microbial environment monitoring module are arranged sequentially. One side of the wastewater pretreatment module is an inlet, and the other side connects to the multi-stage biochemical module. The other side of the multi-stage biochemical module connects to the deep treatment module, and the other side of the deep treatment module has an outlet. Wastewater passes through the pretreatment module, multi-stage biochemical module, and deep treatment module before being discharged as treated water. This invention achieves high water purification efficiency, intelligent operation and maintenance, low-carbon environmental protection capabilities, and ecological compatibility through an integrated design of modular treatment, intelligent control, green energy, and ecological collaboration.

Description

Technical Field

[0001] This invention relates to the field of wastewater purification technology, specifically a novel intelligent water purification plant system. Background Technology

[0002] Conventional wastewater treatment plants typically employ activated sludge or biofilm processes, with system equipment usually arranged in a modular layout and connected by pipelines.

[0003] With the acceleration of urbanization, the construction of large and medium-sized wastewater treatment plants has basically reached saturation, while the market prospects for decentralized small-scale wastewater treatment plants are broad. The original design concept of wastewater treatment plants is difficult to adapt to the development of the times and technological iteration. The effective wastewater filtration within a unit area is limited, and they occupy a large area, with high investment and operating costs and insufficient automation control. Therefore, we propose a new type of intelligent water purification plant system. Summary of the Invention

[0004] The purpose of this invention is to provide a novel intelligent water purification plant system to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: A novel intelligent water purification plant system includes a fully enclosed plant building. The fully enclosed plant building adopts a light steel structure and prefabricated components. Inside the fully enclosed plant building, a wastewater pretreatment module, a multi-stage biochemical module, an advanced treatment module, a multi-energy complementary power supply module, an AI collaborative monitoring module, a biochemical early warning module, and a microbial environment monitoring module are arranged sequentially. The wastewater pretreatment module, the multi-stage biochemical module, and the advanced treatment module form a combined process unit. The wastewater pretreatment module has an inlet on one side and a multi-stage biochemical module on the other side. The multi-stage biochemical module is connected to a deep treatment module on the other side, and an outlet is set on the other side of the deep treatment module. After passing through the wastewater pretreatment module, the multi-stage biochemical module, and the deep treatment module, the treated water is discharged, thus completing the wastewater purification. The biochemical early warning module monitors various indicators in the pool to provide data support for control; the microbial monitoring module is equipped with biosensors to monitor the microbial content in the pool and monitor the microbial population and activity in real time; the sensor data acquisition frequency is once per minute; the wastewater quality evaluation threshold for early warning / alarm is obtained by converting the measured values ​​detected by the sensor through a dynamic correction method of AI model that learns from historical data and real-time operating conditions. It also includes a smart operation and maintenance cloud platform and an ecological collaborative governance module. The smart operation and maintenance cloud platform serves as the system brain, integrating the entire process of data collection, analysis, control, and operation and maintenance. The ecological collaborative governance module enables the integration of the factory with the surrounding environment and resolves the NIMBY (Not In My Backyard) effect.

[0006] Preferably, the intelligent operation and maintenance cloud platform includes: Visualized management and control: The factory area is presented through 3D modeling, and the operating status and key indicators of each unit are displayed in real time. It supports access from multiple terminals such as PC and mobile devices. Remote operation and maintenance: Supports remote control of equipment and remote calibration of sensors, reducing the need for on-site operation and maintenance personnel, and enabling one person to manage 3-5 sewage treatment plants; Data analysis reports: Automatically generate daily / weekly / monthly operation reports, including water quality compliance rate, energy consumption statistics, carbon emission calculation, and operation and maintenance cost analysis, providing data support for operation optimization; Compliance Management: Automatically stores water quality and energy consumption data, with a data retention period of ≥5 years. It can export monitoring reports that meet the requirements of environmental protection departments with one click, avoiding the risk of data falsification.

[0007] Preferably, the ecological collaborative governance module includes: Noise reduction and odor removal: The plant adopts a double-layer sound insulation board and sound-absorbing cotton structure to control the noise of equipment operation below 55 decibels; a biological filter deodorization device is installed above the pretreatment unit and the biological tank to degrade malodorous gases through microorganisms; Landscape integration: An ecological buffer zone is built around the factory, planted with aquatic plants such as reeds and calamus, which can further purify the wastewater; a photovoltaic landscape garden is set up on the roof of the factory, planted with drought-resistant flowers, which is both ornamental and heat-insulating, so that the factory can be integrated into the surrounding environment. Community interaction: An environmental science education area is set up at the entrance of the factory, and the sewage treatment process, effluent quality and carbon reduction results are displayed in real time on the screen.

[0008] Preferably, the wastewater pretreatment module includes coarse / fine screens, a filtration device, and an equalization tank; the deep treatment module includes a high-density sedimentation filtration tank and an ultraviolet disinfection device; the multi-energy complementary power supply module includes rooftop photovoltaic panels, energy storage batteries, and an energy control box; and the AI ​​collaborative monitoring module is a monitoring robot responsible for unmanned inspection.

[0009] Preferably, the multi-stage biochemical module consists of an anaerobic tank and an aerobic tank, and the anaerobic tank and the aerobic tank are composed of several small tanks that are built together, with the tanks supported by an integrated steel structure frame. Both the anaerobic and aerobic tanks are equipped with microporous aeration devices and biological filter membranes. The microporous aeration devices are located at the bottom of the tanks, while the biological filter membranes are spaced at equal intervals within the tanks.

[0010] Preferably, the biochemical early warning module includes, but is not limited to, water temperature sensors, pH sensors, dissolved oxygen sensors, turbidity sensors, ammonia nitrogen sensors, residual chlorine sensors, and COD sensors, which monitor various indicators in the influent in real time and provide data for intelligent closed-loop control; the sensor data is linked with the AI ​​big model, and when a certain indicator approaches the warning threshold, the system automatically adjusts the parameters of the associated equipment.

[0011] Preferably, the factory system includes a control platform, a data acquisition / transmission module, and a data processing / analysis module. The data acquisition / transmission module comprises a data acquisition module and a data transmission module. The data acquisition module is connected to sensors, responsible for receiving analog signals output by the sensors, converting them into digital signals, and adding time watermarks to the acquired data to ensure timeliness and traceability. The data transmission module uses wired or wireless transmission methods. Wired transmission uses, but is not limited to, RS-485 bus or Ethernet, while wireless transmission uses, but is not limited to, GPRS, 4G / 5G, LoRa, and NB-IoT technologies to send the acquired data to the control platform and the smart operation and maintenance cloud platform. The data processing / analysis module includes a data receiving / storage module and a data analysis module. It receives, parses, and stores the transmitted data within the control platform and the smart operation and maintenance cloud platform. The storage database includes, but is not limited to, relational database MySQL or non-relational database MongoDB, storing real-time and historical data collected by sensors.

[0012] Preferably, the data analysis module employs one or more of the following: statistical analysis model, trend analysis model, and correlation analysis model. The statistical analysis model calculates the average, maximum, minimum, and standard deviation of the data parameters. The trend analysis model analyzes the changing trend of the data parameters over time through time series analysis. The correlation analysis model studies the interrelationships between data parameters at different collection points to obtain the changes in data parameters within the relevant region.

[0013] Preferably, the control system is equipped with a warning / alarm module, with thresholds set for both warning and alarm. Typically, the alarm threshold is higher than the warning threshold. When the monitored data parameters exceed the predetermined threshold, a warning or alarm is activated. When the data threshold reaches the warning threshold, the abnormal data collection point is alerted by flashing or increasing the font thickness of the data display. When the data threshold reaches the alarm threshold, the system triggers an alarm. Alarm methods include on-site and remote alarms. On-site alarms use, but are not limited to, buzzers, sirens, and warning lights. Remote alarms connect the control system to the Internet and notify relevant personnel via, but are not limited to, SMS, email, and APP push notifications to complete the warning task.

[0014] Compared with the prior art, the beneficial effects of the present invention are: This solution integrates modular treatment, intelligent management and control, green energy supply, and ecological collaborative governance, achieving a comprehensive improvement in water purification efficiency, intelligent operation and maintenance, low-carbon environmental protection capabilities, and ecological compatibility. It also significantly reduces the amount of treated sludge, resulting in less sludge and a marked increase in the compliance rate of effluent. Furthermore, the rational distribution of aerobic and anaerobic tanks, combined with anoxic tanks, forms a highly efficient and synergistic multi-level biochemical reaction system, further enhancing the degradation of organic pollutants and the removal of nitrogen and phosphorus.

[0015] The system achieves dual improvements in sludge reduction and water quality compliance. It reduces sludge production by using a biofiltration membrane to retain highly efficient microorganisms and optimizes aeration parameters and hydraulic retention time. At the same time, the system undergoes deep treatment through high-density sedimentation filtration and ultraviolet disinfection, ensuring that the effluent quality consistently meets standards. Some of the effluent can be directly reused for purposes such as greening irrigation and equipment cleaning.

[0016] Enhanced Tank Layout: Anaerobic, anoxic, and aerobic tanks are scientifically zoned and constructed according to wastewater treatment logic, supported by an integrated steel structure frame. Each tank is divided into several smaller tanks with independent influent and connected effluent. This rational tank distribution extends the wastewater reaction path, strengthens the synergistic effect of denitrification and nitrification, and improves total nitrogen removal rate and organic pollutant degradation efficiency.

[0017] Intelligent regulation of sludge and water quality: The biochemical early warning module collects data every minute through multiple sensors, which are linked with the AI ​​big data model to adjust parameters such as aeration rate and acid / alkali dosage in real time to maintain stable microbial activity and reduce the risk of sludge bulking; the microbial environment monitoring module predicts reaction efficiency through biosensors and adds nutrients in advance to ensure sludge settling performance and further reduce sludge discharge.

[0018] Modular process synergy: The double-layer filtration structure of the wastewater pretreatment module effectively removes suspended impurities, reduces the load on the subsequent biological module, and reduces the source of sludge generation; the combination of microporous aeration device and biological filter membrane in the multi-stage biological module improves the efficiency of pollutant degradation while reducing sludge production; the deep treatment module thoroughly purifies the water quality and ensures the compliance rate of effluent.

[0019] Full-process automated control: The system achieves unmanned operation throughout the entire wastewater purification cycle through the coordinated control of the wastewater pretreatment module, multi-stage biochemical module, and advanced treatment module, resulting in stable effluent quality that meets the requirements for reuse of reclaimed water.

[0020] The intelligent operation and maintenance cloud platform supports remote control of equipment and sensor calibration, combined with automated inspection by monitoring robots, enabling one operation and maintenance personnel to manage 3-5 factories of similar size, reducing labor costs. Furthermore, it improves the monitoring and early warning system, strengthens risk management, optimizes ecosystem compatibility, and eliminates the NIMBY (Not In My Backyard) effect. Attached Figure Description

[0021] Figure 1 This is a logic block diagram of the present invention. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] In the description of this invention, it should be understood that the terms "upper", "lower", "front", "rear", "left", "right", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0024] Example: Please see Figure 1 The present invention provides the following technical solution: A novel intelligent water purification plant system includes a fully enclosed plant building. The plant building utilizes a light steel structure and prefabricated components, with key connecting parts custom-produced via 3D printing. This allows for rapid assembly of the main plant structure within 15 days. Inside the fully enclosed plant building, sequentially arranged modules include wastewater pretreatment, multi-stage biochemical treatment, advanced treatment, multi-energy complementary power supply, AI collaborative monitoring, biochemical early warning, and microbial environmental monitoring. These modules, along with the wastewater pretreatment module, multi-stage biochemical treatment module, and advanced treatment module, form a combined process unit, enabling rapid installation and deployment. The wastewater pretreatment module has an inlet on one side and a multi-stage biological treatment module on the other side. The multi-stage biological treatment module is connected to the advanced treatment module on the other side, and the advanced treatment module has an outlet on the other side. After passing through the wastewater pretreatment module, the multi-stage biological treatment module, and the advanced treatment module, the treated water is discharged, thus completing the wastewater purification process. The biochemical early warning module monitors various indicators in the pool to provide data support for control; the microbial monitoring module is equipped with biosensors to monitor the microbial content in the pool and monitor the microbial population and activity in real time; the sensor data acquisition frequency is once per minute, and the wastewater quality evaluation threshold for early warning / alarm is obtained by converting the measured values ​​detected by the sensors through a dynamic correction method of AI model that learns from historical data and real-time operating conditions. It also includes a smart operation and maintenance cloud platform and an ecological collaborative governance module. The smart operation and maintenance cloud platform serves as the system's brain, integrating the entire process of data collection, analysis, control, and operation and maintenance. The ecological collaborative governance module enables the integration of the factory with its surrounding environment, resolving the NIMBY (Not In My Backyard) effect.

[0025] The wastewater pretreatment module includes coarse / fine screens, filtration devices, and equalization tanks.

[0026] The multi-stage biochemical module consists of anaerobic and aerobic tanks, which are constructed from several smaller tanks, supported by an integrated steel frame.

[0027] Both the anaerobic and aerobic tanks are equipped with microporous aeration devices and biological filter membranes. The microporous aeration devices are located at the bottom of the tank, while the biological filter membranes are spaced at equal intervals within the tank.

[0028] The advanced treatment module includes a high-density sedimentation filtration tank and an ultraviolet disinfection device.

[0029] The multi-energy complementary power supply module includes rooftop photovoltaic panels, energy storage batteries, and power control boxes.

[0030] The AI ​​collaborative monitoring module is a monitoring robot equipped with AI visual recognition. It is responsible for unmanned inspections and can automatically identify abnormal noises, leaks, and instrument malfunctions in equipment. The collaborative robot can perform simple maintenance tasks such as filter replacement and reagent replenishment.

[0031] The biochemical early warning module includes, but is not limited to, water temperature sensors, pH sensors, dissolved oxygen sensors, turbidity sensors, ammonia nitrogen sensors, residual chlorine sensors, and COD sensors. It monitors various indicators in the influent in real time, providing data for intelligent closed-loop control. The sensor data is linked with the AI ​​big model. When a certain indicator approaches the warning threshold, the system automatically adjusts the parameters of related equipment (such as increasing the aeration rate when dissolved oxygen is low) to achieve intelligent closed-loop control.

[0032] The factory system includes a control platform, a data acquisition / transmission module, and a data processing / analysis module. The data acquisition / transmission module comprises a data acquisition module and a data transmission module. The data acquisition module is connected to sensors, responsible for receiving analog signals output by the sensors, converting them into digital signals, and adding time watermarks to the acquired data to ensure timeliness and traceability. The data transmission module uses wired or wireless transmission methods. Wired transmission uses, but is not limited to, RS-485 bus or Ethernet, while wireless transmission uses, but is not limited to, GPRS, 4G / 5G, LoRa, and NB-IoT technologies to send the acquired data to the control platform and the smart operation and maintenance cloud platform.

[0033] The data processing / analysis module includes a data receiving / storage module and a data analysis module. It receives, parses, and stores the transmitted data within the control platform and the smart operation and maintenance cloud platform. The storage database includes, but is not limited to, relational database MySQL or non-relational database MongoDB, storing real-time and historical data collected by sensors.

[0034] The data analysis module employs one or more of the following models: statistical analysis, trend analysis, and correlation analysis. The statistical analysis model calculates the mean, maximum, minimum, and standard deviation of the data parameters. The trend analysis model analyzes the changing trends of the data parameters over time through time series analysis. The correlation analysis model studies the interrelationships between data parameters at different collection points to obtain the changes in data parameters within a relevant region. The control system is equipped with a warning / alarm module. Warning and alarm thresholds are set for each, with the alarm threshold typically higher than the warning threshold. When the monitored data parameters exceed the predetermined threshold, a warning or alarm is activated. When the data threshold reaches the warning threshold, the abnormal data collection point is alerted by flashing or increasing the font thickness. When the data threshold reaches the alarm threshold, the system triggers an alarm. Alarm methods include on-site and remote alarms. On-site alarms use, but are not limited to, buzzers, sirens, and warning lights. Remote alarms connect the control system to the internet and notify relevant personnel via, but are not limited to, SMS, email, and app push notifications, thus completing the warning task.

[0035] The intelligent operation and maintenance cloud platform includes the following functions: Visualized management and control: The system presents the actual scene of the plant through 3D modeling, and displays the real-time operating status of each unit [such as influent flow rate, dissolved oxygen in the biological treatment tank, and photovoltaic power generation] and key indicators [such as effluent COD and carbon emissions], supporting access from multiple terminals such as PC and mobile devices; Remote operation and maintenance: Supports remote control of equipment [such as starting standby pumps, adjusting photovoltaic energy storage strategies], and remote calibration of sensors, reducing the need for on-site operation and maintenance personnel, and enabling one person to manage 3-5 wastewater treatment plants; Data analysis reports: Automatically generate daily / weekly / monthly operation reports, including water quality compliance rate, energy consumption statistics, carbon emission calculation, and operation and maintenance cost analysis, providing data support for operation optimization; Compliance Management: Automatically stores water quality and energy consumption data, with a data retention period of ≥5 years. It can export monitoring reports that meet the requirements of environmental protection departments with one click, avoiding the risk of data falsification.

[0036] The intelligent operation and maintenance cloud platform serves as the system's brain, integrating data collection, AI analysis, intelligent control, and unmanned operation and maintenance throughout the entire process, enabling 24 / 7 operation of the water plant in complete darkness. The multi-energy complementary power supply module, with photovoltaic power as its core, is combined with wind power generation and energy storage systems to achieve energy self-balancing and self-circulation, thus achieving the goal of a carbon-neutral water plant. The ecological collaborative governance module integrates the plant with its surrounding environment, resolving the NIMBY (Not In My Backyard) effect.

[0037] The rooftop photovoltaic panels cover 90% of the factory rooftop, and are paired with flexible photovoltaic modules (suitable for curved roofs). The photovoltaic installed capacity is designed to meet 120% of the factory's total energy consumption. Small wind turbine generator, with a size suitable for open areas around the factory; The energy storage battery capacity is designed based on the factory's maximum 8-hour load. Equipped with an AI energy dispatch module, it prioritizes the use of photovoltaic and wind power generation, activating energy storage when insufficient, and connecting to the grid in extreme cases to ensure an energy self-balancing rate of ≥90% and reduce annual carbon emissions to 0.1 tCO2 / m³. 3 The following describes a carbon-neutral water plant.

[0038] The ecological collaborative governance module includes the following functions: Noise reduction and deodorization: The factory adopts a double-layer sound insulation board and sound-absorbing cotton structure to control the noise of equipment operation below 55 decibels, which complies with the "Emission Standard for Environmental Noise at the Boundary of Industrial Enterprises"; a biological filter deodorization device is installed above the pretreatment unit and the biochemical pool, which degrades malodorous gases through microorganisms, with a deodorization efficiency of over 90%; Landscape integration: An ecological buffer zone is built around the factory, planted with aquatic plants such as reeds and calamus, which can further purify the wastewater; a photovoltaic landscape garden is set up on the roof of the factory, planted with drought-resistant flowers, which is both ornamental and heat-insulating, so that the factory can be integrated into the surrounding environment. Community interaction: An environmental science education area is set up at the entrance of the factory, with real-time displays showing the wastewater treatment process, effluent quality, and carbon reduction results; it is also open to nearby residents on a regular basis to raise public awareness of environmental protection.

[0039] Working principle: After entering the plant area through the inlet, wastewater successively passes through the wastewater pretreatment module to remove coarse impurities and suspended solids, the multi-stage biological module to degrade organic pollutants, and the deep treatment module to achieve water quality standards before being discharged or reused through the outlet. At the same time, the multi-energy complementary power supply module provides green energy for the entire system, the AI ​​collaborative monitoring module and various sensor monitoring modules collect operational data in real time, and the data is processed and uploaded to the smart operation and maintenance cloud platform to achieve full-process visualized control and intelligent decision-making. The ecological collaborative governance module ensures the harmonious coexistence of the factory and the surrounding environment.

[0040] Wastewater pretreatment module: Coarse / fine screens: Mechanical automatic screens are used, with bar spacing of 20mm [coarse screen] and 5mm [fine screen]. They are controlled by PLC to start and stop on a timer [default operation once every 30 minutes, which can be automatically adjusted according to the turbidity of the influent]. They effectively intercept large suspended solids such as tree branches, plastic bags, and sand in the sewage. The screenings are transported to a sealed screening box by a screw conveyor and regularly cleaned and disposed of by a professional organization.

[0041] Filtration device: It adopts a quartz sand-activated carbon double-layer filtration structure, with filter media particle sizes of 0.8-1.2mm [quartz sand] and 1.5-2.0mm [activated carbon], and the filtration speed is controlled at 8-10m / h. It can further remove fine suspended solids [particle size ≥10μm], some colloids and odor substances from the water.

[0042] Equalization tank: The effective volume is designed according to the plant's maximum treatment capacity of 2 hours. A submersible agitator [stirring rate 500r / min] is installed in the tank to ensure that the wastewater quality and quantity are uniform and stable, and to avoid the subsequent biological module from being impacted by the influent fluctuations. At the same time, a liquid level sensor is installed in the tank to monitor the water level in real time. When the water level is lower than the warning value [20% of the design volume] or higher than the upper limit value [90% of the design volume], an early warning is triggered and the influent valve is linked to adjust the flow rate.

[0043] Multi-level biochemical module: The anaerobic and aerobic tanks are supported by an integrated steel structure frame. The effective volume of each tank is designed according to the treatment scale of the plant and is divided into multiple small tanks with independent inlet and series outlet, which facilitates flexible adjustment of the operating load and reduces the impact of single tank failure on the overall system.

[0044] The microporous aeration device is only installed at the bottom of the aerobic tank. It adopts a liftable tubular aerator with an aeration orifice diameter of 2-3μm and an oxygen utilization rate of over 35%. The aeration rate is controlled by a variable frequency blower [aeration rate range: 1.5-3m³]. 3 / (m 2 •h)], to match the dissolved oxygen demand of the aerobic tank in real time.

[0045] Biological filter membranes are arranged at equal intervals in both the anaerobic and aerobic tanks. The membranes are made of PVDF hollow fiber and are fixed by a support. They can trap activated sludge and microorganisms in the water, increase the biomass in the tanks, and enhance the degradation efficiency of pollutants.

[0046] The anaerobic tank achieves denitrification by mixing the influent with the return liquid from the aerobic tank, with a total nitrogen removal rate of over 70%. The aerobic tank provides oxygen to microorganisms through aeration, enabling the oxidation and decomposition of organic pollutants and the nitrification of ammonia nitrogen.

[0047] Deep processing module: Wastewater that has undergone biochemical treatment still contains a small amount of suspended solids and pathogens, and needs to be further purified through a deep treatment module to ensure that the effluent meets the discharge standards.

[0048] The high-density sedimentation filtration tank adopts an integrated design of inclined tube sedimentation and filtration, with honeycomb inclined tubes installed inside the tank, and the surface load controlled at 2.5m². 3 / (m 2 •h) can quickly intercept fine suspended solids in the water. After sedimentation, the water enters the filter tank to further remove residual suspended solids and colloids. The turbidity of the filtered water is ≤1 NTU.

[0049] The ultraviolet disinfection device uses low-pressure, high-intensity ultraviolet lamps, with the disinfection dosage controlled at 40 mJ / cm². 2 The PLC controls the start / stop and cleaning of the lamps, which can effectively kill pathogens such as E. coli and fecal streptococci in the water, and there are no disinfection byproducts, thus avoiding secondary pollution.

[0050] AI Collaborative Monitoring Module: The robot is a wheeled mobile robot equipped with a high-definition camera with 4K resolution, 360° rotation, 10x optical zoom, infrared thermal imager, and sound sensor. The monitoring robot is equipped with a laser navigation system, which can automatically inspect according to a preset route. The inspection cycle can be set, and manual inspection can also be remotely controlled through the smart operation and maintenance platform.

[0051] During the robot's inspection, it captures videos and images in real time, collects equipment temperature and operating sound data, and uploads them to the smart operation and maintenance cloud platform via the network. When an abnormality is detected, it automatically marks the abnormal location and triggers an alarm, while simultaneously uploading on-site footage to facilitate remote fault assessment by maintenance personnel.

[0052] Biochemical early warning module: Includes a water temperature sensor [measurement range 0-50℃, accuracy ±0.5℃], a pH sensor [measurement range 0-14, accuracy ±0.1], a dissolved oxygen sensor [measurement range 0-20mg / L, accuracy ±0.2mg / L], a turbidity sensor [measurement range 0-1000NTU, accuracy ±2%], an ammonia nitrogen sensor [measurement range 0-50mg / L, accuracy ±5%], a residual chlorine sensor [measurement range 0-10mg / L, accuracy ±0.1mg / L], and a COD sensor [measurement range 0-1000mg / L, accuracy ±10%].

[0053] Sensors collect water quality indicators from key points such as influent, biological treatment tank, and effluent in real time, with a data collection frequency of once per minute. After collection, the data is converted into digital signals by the data acquisition module and a time watermark is added to ensure the timeliness and traceability of the data. After the data is uploaded to the intelligent operation and maintenance platform, it is used to adjust the operating parameters of the biological treatment module. For example, when the dissolved oxygen in the biological treatment tank is lower than 2 mg / L, the aeration rate is automatically increased; when the pH of the influent is lower than 6.5 or higher than 8.5, acid-base regulators are automatically added.

[0054] Microbial environmental monitoring module: Biosensors are used to monitor the quantity and activity of microorganisms in the biological treatment tank in real time. By understanding the structure and activity of the microbial community in real time, the efficiency of the biochemical reaction can be predicted in advance, avoiding water quality exceeding standards due to insufficient microbial activity. For example, when the number of nitrifying bacteria is below 10... 5 When the concentration of CFU / mL is low, the ammonia nitrogen removal rate may decrease, triggering an early warning and adding microbial nutrients.

[0055] Intelligent Operation and Maintenance Cloud Platform: By integrating the entire process of data collection, analysis, control, and operation and maintenance, the factory can achieve unmanned operation and maintenance with fewer personnel, thereby improving operational efficiency and management level.

[0056] Based on the factory's CAD drawings and on-site scanning data, a 1:1 scale 3D real scene model was constructed. The model includes all processing units, equipment, and pipelines, and can be freely scaled, rotated, and roamed. Key monitoring points (such as inlet, biological treatment tank, and outlet) are marked on the 3D model. Clicking on a monitoring point allows you to view real-time data (such as inlet flow rate, dissolved oxygen, and effluent COD). At the same time, a dashboard of key indicators (such as water quality compliance rate, photovoltaic self-sufficiency rate, and equipment integrity rate) is displayed on the right side of the model. The data is updated every 10 seconds. It supports access via PC (via browser login) and mobile devices (APP, mini-program). Mobile devices support offline viewing of cached data (automatically synchronized after network recovery), meeting the management needs of operations and maintenance personnel anytime, anywhere.

[0057] The cloud platform allows for remote control of equipment such as fans, water pumps, valves, and photovoltaic inverters. After control commands are issued, the system provides real-time feedback on the equipment's execution status, preventing misoperation.

[0058] For sensors with remote calibration capabilities, calibration commands can be sent via a cloud platform, and the sensor will automatically complete the calibration without on-site operation. Remote operation and maintenance can enable one maintenance personnel to manage 3-5 wastewater treatment plants of the same size, reducing labor costs by more than 70% compared to the traditional operation and maintenance model. The system automatically generates operation reports daily [24:00], weekly [Sunday 24:00], and monthly [end of month 24:00]. The reports include: Water quality data: average, maximum, minimum, and compliance rates of each indicator for influent / effluent [compared with GB18918-2002 Class A standard]; Energy consumption data: Total electricity consumption, photovoltaic power generation, grid electricity consumption, energy consumption per unit of water treatment [kWh / m³] 3 ]; Carbon emission data: fossil fuel carbon emissions [calculated based on grid electricity consumption], photovoltaic carbon reduction, net carbon emissions; Operation and maintenance data: equipment runtime, number of failures, maintenance costs, and chemical consumption; Report Applications: The report supports export in PDF and Excel formats and can be directly used for internal operational analysis (such as optimizing reagent dosage and adjusting photovoltaic energy storage strategies) and external regulatory reporting (such as submitting monthly water quality reports to environmental protection departments).

[0059] Ecological collaborative governance module: The fully enclosed factory building adopts a double-layer color steel plate structure with sound-absorbing cotton in the middle. The outer layer of color steel plate is 0.8mm thick, the inner layer of color steel plate is 0.6mm thick, and the middle is filled with 50mm thick centrifugal glass wool [sound absorption coefficient ≥0.8]. At the same time, the factory doors and windows are designed with sound insulation to control the noise of equipment operation below 55 decibels at the factory boundary.

[0060] Deodorization via biological filter: A sealed cover is installed above the pretreatment unit [coarse / fine screen, equalization tank] and the biochemical tank. A gas collection pipe is installed inside the cover to collect odorous gases and introduce them into the biological filter. The biological filter adopts a packing material and microbial structure. The packing material is volcanic rock with deodorizing microorganisms attached to its surface. When odorous gases pass through the packing material layer, they are degraded into harmless carbon dioxide, water, and nitrogen by the microorganisms, achieving a deodorization efficiency of over 90%.

[0061] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or basic characteristics. Therefore, the embodiments should be considered exemplary and non-limiting in all respects. The scope of the invention is defined by the appended claims rather than the foregoing description. Therefore, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention, and no reference numerals in the claims should be construed as limiting the scope of the claims.

[0062] This solution integrates modular treatment, intelligent management and control, green energy supply, and ecological collaborative governance, achieving a comprehensive improvement in water purification efficiency, intelligent operation and maintenance, low-carbon environmental protection capabilities, and ecological compatibility. It also significantly reduces the amount of treated sludge, resulting in less sludge and a marked increase in the compliance rate of effluent. Furthermore, the rational distribution of aerobic and anaerobic tanks, combined with anoxic tanks, forms a highly efficient and synergistic multi-level biochemical reaction system, further enhancing the degradation of organic pollutants and the removal of nitrogen and phosphorus.

[0063] The system achieves dual improvements in sludge reduction and water quality compliance. It reduces sludge production by using a biofiltration membrane to retain highly efficient microorganisms and optimizes aeration parameters and hydraulic retention time. At the same time, the system undergoes deep treatment through high-density sedimentation filtration and ultraviolet disinfection, ensuring that the effluent quality consistently meets standards. Some of the effluent can be directly reused for purposes such as greening irrigation and equipment cleaning.

[0064] Enhanced Tank Layout: Anaerobic, anoxic, and aerobic tanks are scientifically zoned and constructed according to wastewater treatment logic, supported by an integrated steel structure frame. Each tank is divided into several smaller tanks with independent influent and connected effluent. This rational tank distribution extends the wastewater reaction path, strengthens the synergistic effect of denitrification and nitrification, and improves total nitrogen removal rate and organic pollutant degradation efficiency.

[0065] Intelligent regulation of sludge and water quality: The biochemical early warning module collects data every minute through multiple sensors, which are linked with the AI ​​big data model to adjust parameters such as aeration rate and acid / alkali dosage in real time to maintain stable microbial activity and reduce the risk of sludge bulking; the microbial environment monitoring module predicts reaction efficiency through biosensors and adds nutrients in advance to ensure sludge settling performance and further reduce sludge discharge.

[0066] Modular process synergy: The double-layer filtration structure of the wastewater pretreatment module effectively removes suspended impurities, reduces the load on the subsequent biological module, and reduces the source of sludge generation; the combination of microporous aeration device and biological filter membrane in the multi-stage biological module improves the efficiency of pollutant degradation while reducing sludge production; the deep treatment module thoroughly purifies the water quality and ensures the compliance rate of effluent.

[0067] Example 1:

[0068] A wastewater treatment plant in a certain area requires a treatment capacity of 20,000 tons per day, serving three surrounding industrial parks and two residential communities. The plant utilizes a fully enclosed light steel structure with prefabricated components. Key connection nodes were custom-produced using 3D printing, and the main structure was assembled in just 14 days. The plant covers a total area of ​​8,000 square meters, with the treatment unit area accounting for 70% and supporting facilities and ecological areas accounting for 30%. The overall layout is compact and efficient, optimizing the use of land resources.

[0069] Two hundred thousand tons of wastewater per day enter the pretreatment module through the inlet. First, it passes through a coarse screen (20mm spacing) to intercept large floating debris (such as plastic bags and branches). The intercepted screenings are collected by an automatic cleaning machine and transported to the solid waste treatment center. The wastewater then flows into a fine screen (5mm spacing) to further remove fine impurities. Next, it enters a filtration device to remove suspended particles, reducing the load on subsequent treatment processes. Finally, the wastewater flows into a 5000-cubic-meter equalization tank, where a stirring device balances the water quality and quantity to ensure stable operation of subsequent treatment units. This module employs a modular process design, and installation and deployment took only 3 days.

[0070] The pretreated wastewater enters a multi-stage biological treatment module, which consists of two anaerobic tanks, six aerobic tanks, and fourteen aerobic tanks, with a total effective volume of 16,000 cubic meters, supported by an integrated steel frame structure. In the anaerobic tanks, denitrification removes nitrate nitrogen from the water, while the aerobic tanks utilize microorganisms to degrade organic pollutants. Microporous aeration devices are installed at the bottom of each tank to provide sufficient oxygen for microbial growth. Biological filter membranes are installed at equal intervals within the tanks to enhance pollutant interception and microbial attachment. During operation, the system automatically adjusts the hydraulic retention time of the anaerobic and aerobic tanks according to changes in the influent water quality to ensure treatment effectiveness.

[0071] After biochemical treatment, the wastewater enters the advanced treatment module, first flowing into two high-density sedimentation and filtration tanks. Flocculants are added to achieve deep removal of suspended solids, and the settled sludge is pumped to the sludge treatment unit. The filtered wastewater then enters an ultraviolet disinfection device using high-intensity UV lamps to ensure the total bacterial count in the effluent meets standards. The treated clean water is discharged through the outlet, with a portion reused for irrigation of the plant's green spaces and equipment cleaning, and the remainder connected to the municipal reclaimed water network. The effluent quality from this module consistently meets the Class A standard of the "Discharge Standard of Pollutants for Municipal Wastewater Treatment Plants".

[0072] The factory building's roof is 90% covered by photovoltaic panels, with flexible photovoltaic modules adapted to the curved roof. The total installed capacity is designed to meet 120% of the factory's total energy consumption, reaching 1.2MW. Four small wind turbines are installed in the surrounding open areas to supplement power generation. The energy storage battery capacity is designed for the factory's maximum 8-hour load and is equipped with an AI energy dispatch module, prioritizing the use of photovoltaic and wind power generation, activating energy storage when insufficient, and connecting to the grid in extreme cases. Currently, the factory's energy self-balancing rate is stable at 92%, and annual carbon emissions have been reduced to 0.08 tCO2 / m³. 3 To achieve the goal of carbon neutrality.

[0073] The factory has deployed 12 monitoring robots, equipped with an AI visual recognition system, to conduct unmanned inspections of the entire factory every 2 hours along a preset route. These robots can automatically identify problems such as abnormal equipment noise, leaks, and instrument malfunctions, with an accuracy rate of 98%. Additionally, 6 collaborative robots are deployed to handle simple maintenance tasks such as filter replacement (once a week) and chemical replenishment (twice a day), reducing the need for on-site maintenance personnel.

[0074] The biochemical early warning module is equipped with multiple sensors for water temperature, pH, dissolved oxygen, turbidity, ammonia nitrogen, residual chlorine, and COD, collecting data every minute and linking with an AI model to achieve intelligent closed-loop control. For example, when the dissolved oxygen content in the aerobic tank is detected to be below 2 mg / L, the system automatically increases the aeration rate; when the pH value deviates from the suitable range of 7-8.5, the system automatically adjusts the acid and alkali dosage. The biosensors in the microbial monitoring module monitor the microbial population and activity in the tank in real time, and the data is synchronized to the intelligent operation and maintenance cloud platform to provide data support for process adjustments.

[0075] Data processing: The data acquisition module connects to each sensor, converting analog signals into digital signals and adding time watermarks. Data is transmitted to the control platform and the smart operation and maintenance cloud platform via RS-485 bus (wired) and 5G technology (wireless). Data storage employs a combination of MySQL relational database and MongoDB non-relational database to ensure secure storage of both real-time and historical data. The data analysis module uses statistical analysis, trend analysis, and correlation analysis models to calculate the average and maximum values ​​of data parameters, analyzing data trends over time and the interrelationships between data from different collection points.

[0076] The system has two threshold levels: early warning and alarm. When the alarm threshold exceeds the early warning threshold, the abnormal data collection point flashes as a notification. When the alarm threshold is reached, the on-site buzzer, alarm bell, and warning lights activate simultaneously, and relevant personnel are notified remotely via SMS, email, and app push notifications. To date, it has successfully provided early warnings for three water quality fluctuations and two equipment failures, ensuring stable system operation.

[0077] The platform uses 3D modeling to present a realistic view of the wastewater treatment plant, displaying real-time operational status such as influent flow rate, dissolved oxygen in the biological treatment tank, and photovoltaic power generation, as well as key indicators like effluent COD and carbon emissions. It supports access from multiple devices, including PCs and mobile devices. Remote operation and maintenance capabilities include enabling backup pump activation, adjusting photovoltaic energy storage strategies, and remote sensor calibration. Currently, one maintenance personnel can simultaneously manage three similar wastewater treatment plants. The platform automatically generates daily / weekly / monthly operational reports, including water quality compliance rates and energy consumption statistics. Data is retained for up to six years, and monitoring reports compliant with environmental protection department requirements can be exported with a single click. The plant operates 24 / 7 in darkness, reducing operation and maintenance costs by 30%.

[0078] The plant utilizes a double-layer sound insulation panel and sound-absorbing cotton structure, controlling equipment operating noise below 53 decibels, meeting relevant standards. A biological filter deodorization device is installed above the pretreatment unit and biological treatment tank, achieving a deodorization efficiency of 93%. A 20-meter-wide ecological buffer zone is constructed around the plant, planted with aquatic plants such as reeds and calamus to further purify the effluent; a photovoltaic landscape garden is installed on the roof, planted with drought-resistant flowers. An environmental science education area is set up at the plant entrance, displaying the wastewater treatment process, effluent quality, and carbon reduction results in real time on screens. It is open to nearby residents on the 15th of each month to raise public environmental awareness and effectively address the NIMBY (Not In My Backyard) effect.

[0079] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A novel intelligent water purification plant system, comprising a fully enclosed plant building, wherein the fully enclosed plant building adopts a light steel structure and prefabricated components, and within the fully enclosed plant building are sequentially arranged a wastewater pretreatment module, a multi-stage biochemical module, a deep treatment module, a multi-energy complementary power supply module, an AI collaborative monitoring module, a biochemical early warning module, and a microbial environment monitoring module, characterized in that, The wastewater pretreatment module, multi-stage biochemical module, and advanced treatment module form a combined process unit; The wastewater pretreatment module has an inlet on one side and a multi-stage biochemical module on the other side. The multi-stage biochemical module is connected to a deep treatment module on the other side, and an outlet is set on the other side of the deep treatment module. After passing through the wastewater pretreatment module, the multi-stage biochemical module, and the deep treatment module, the treated water is discharged, thus completing the wastewater purification. The biochemical early warning module monitors various indicators in the pool to provide data support for control; the microbial monitoring module is equipped with biosensors to monitor the microbial content in the pool and monitor the microbial population and activity in real time; the sensor data acquisition frequency is once per minute; the wastewater quality evaluation threshold for early warning / alarm is obtained by converting the measured values ​​detected by the sensor through a dynamic correction method based on historical data and real-time operating conditions through a self-learning AI model. It also includes a smart operation and maintenance cloud platform and an ecological collaborative governance module. The smart operation and maintenance cloud platform serves as the system brain, integrating the entire process of data collection, analysis, control, and operation and maintenance. The ecological collaborative governance module enables the integration of the factory with the surrounding environment and resolves the NIMBY (Not In My Backyard) effect.

2. The novel intelligent water purification plant system according to claim 1, characterized in that: The intelligent operation and maintenance cloud platform includes: Visualized management and control: The factory area is presented through 3D modeling, and the operating status and key indicators of each unit are displayed in real time. It supports access from multiple terminals such as PC and mobile devices. Remote operation and maintenance: Supports remote control of equipment and remote calibration of sensors, reducing the need for on-site operation and maintenance personnel, and enabling one person to manage 3-5 sewage treatment plants; Data analysis reports: Automatically generate daily / weekly / monthly operation reports, including water quality compliance rate, energy consumption statistics, carbon emission calculation, and operation and maintenance cost analysis, providing data support for operation optimization; Compliance Management: Automatically stores water quality and energy consumption data, with a data retention period of ≥5 years. It can export monitoring reports that meet the requirements of environmental protection departments with one click, avoiding the risk of data falsification.

3. The novel intelligent water purification plant system according to claim 1, characterized in that: The ecological collaborative governance module includes: Noise reduction and odor removal: The plant adopts a double-layer sound insulation board and sound-absorbing cotton structure to control the noise of equipment operation below 55 decibels; a biological filter deodorization device is installed above the pretreatment unit and the biological tank to degrade malodorous gases through microorganisms; Landscape integration: An ecological buffer zone is built around the factory, planted with aquatic plants such as reeds and calamus, which can further purify the wastewater; a photovoltaic landscape garden is set up on the roof of the factory, planted with drought-resistant flowers, which is both ornamental and heat-insulating, so that the factory can be integrated into the surrounding environment. Community interaction: An environmental science education area is set up at the entrance of the factory, and the sewage treatment process, effluent quality and carbon reduction results are displayed in real time on the screen.

4. The novel intelligent water purification plant system according to claim 1, characterized in that: The wastewater pretreatment module includes coarse / fine screens, a filtration device, and an equalization tank; the deep treatment module includes a high-density sedimentation filtration tank and an ultraviolet disinfection device; the multi-energy complementary power supply module includes rooftop photovoltaic panels, energy storage batteries, and an energy control box; and the AI ​​collaborative monitoring module is a monitoring robot responsible for unmanned inspections.

5. The novel intelligent water purification plant system according to claim 1, characterized in that: The multi-stage biochemical module consists of anaerobic tanks and aerobic tanks, which are composed of several small tanks. The tanks are supported by an integrated steel structure frame. Both the anaerobic and aerobic tanks are equipped with microporous aeration devices and biological filter membranes. The microporous aeration devices are located at the bottom of the tanks, while the biological filter membranes are spaced at equal intervals within the tanks.

6. The novel intelligent water purification plant system according to claim 1, characterized in that: The biochemical early warning module includes, but is not limited to, water temperature sensors, pH sensors, dissolved oxygen sensors, turbidity sensors, ammonia nitrogen sensors, residual chlorine sensors, and COD sensors, which monitor various indicators in the influent in real time and provide data for intelligent closed-loop control; the sensor data is linked with the AI ​​big model, and when a certain indicator approaches the warning threshold, the system automatically adjusts the parameters of the associated equipment.

7. The novel intelligent water purification plant system according to claim 1, characterized in that: The factory system includes a control platform, a data acquisition / transmission module, and a data processing / analysis module. The data acquisition / transmission module comprises a data acquisition module and a data transmission module. The data acquisition module is connected to sensors, responsible for receiving analog signals output by the sensors, converting them into digital signals, and adding time watermarks to the acquired data to ensure timeliness and traceability. The data transmission module uses wired or wireless transmission methods. Wired transmission uses, but is not limited to, RS-485 bus or Ethernet, while wireless transmission uses, but is not limited to, GPRS, 4G / 5G, LoRa, and NB-IoT technologies to send the acquired data to the control platform and the smart operation and maintenance cloud platform. The data processing / analysis module includes a data receiving / storage module and a data analysis module. It receives, parses, and stores the transmitted data within the control platform and the smart operation and maintenance cloud platform. The storage database includes, but is not limited to, relational database MySQL or non-relational database MongoDB, storing real-time and historical data collected by sensors.

8. A novel intelligent water purification plant system according to claim 7, characterized in that: The data analysis module employs one or more of the following models: statistical analysis model, trend analysis model, and correlation analysis model. The statistical analysis model calculates the mean, maximum, minimum, and standard deviation of the data parameters. Trend analysis models use time series analysis to determine the changing trends of data parameters over time. Correlation analysis models study the interrelationships between data parameters at different collection points to obtain the changes in data parameters within a relevant region.

9. A novel intelligent water purification plant system according to claim 8, characterized in that: The control system is equipped with a warning / alarm module. Warning and alarm thresholds are set for each, with the alarm threshold typically higher than the warning threshold. When the monitored data parameters exceed the predetermined threshold, a warning or alarm is activated. When the data threshold reaches the warning threshold, the abnormal data collection point is alerted by flashing or increasing the font thickness. When the data threshold reaches the alarm threshold, the system triggers an alarm. Alarm methods include on-site and remote alarms. On-site alarms use, but are not limited to, buzzers, sirens, and warning lights. Remote alarms connect the control system to the internet and notify relevant personnel via, but are not limited to, SMS, email, and app push notifications, thus completing the warning task.

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