Aeration device operation and maintenance system and method

Abstract

Embodiments of this specification provide an aeration device operation and maintenance system and method. The system includes multiple aeration process modules, a gas detection module, an aeration control module, a blower, multiple monitoring devices, at least one aeration pipeline, at least one connecting pipeline, at least one backup aeration device, and at least one backup aeration pipeline. The method comprises obtaining first monitoring data, estimating the cleaning and maintenance requirements of the aeration process modules based on the first monitoring data and the estimated blockage probability of the aeration process modules; identifying aeration process modules whose cleaning and maintenance requirements meet preset cleaning conditions as target cleaning objects; and performing cleaning and maintenance on the target cleaning objects. This system and method can reduce system operating costs and improve system maintenance efficiency.

Description

[0001] Description of the case

[0002] This application is a divisional application filed for the Chinese application with application date of May 9, 2024, application number 202410567082.1, and invention name “A maintenance system, method, device and storage medium for an aeration device”. Technical Field

[0003] This specification relates to the field of aeration, and in particular to an aeration device operation and maintenance system and method. Background Art

[0004] Aeration devices can be used to aerate polluted water bodies. The energy consumption of the aeration device mainly comes from the energy loss of the blower, the resistance loss of the piping system, and the local resistance loss of the aerator. The energy loss of the blower and piping system generally changes according to the adjustment of the process. When maintaining the aeration device, it can be adjusted through process optimization. The local resistance loss of the aerator is mainly affected by aerator blockage, pipeline blockage, aerator damage, surface contamination, etc., and often increases with time. When maintaining the aeration device, it is generally controlled by cleaning or replacing the aerator. Common causes of aerator blockage include salt crystal precipitation, biofilm attachment and growth, pipeline condensation or sludge blockage, etc.

[0005] Currently, when aeration systems require repair, upgrades, or modifications, they typically require a temporary shutdown of the entire system and a large-scale replacement of aerators. For example, when a possible maintenance cleaning condition (e.g., a clogged aerator) is detected, scheduled cleaning or a centralized cleaning of the entire system is often performed. This can lead to unnecessary maintenance costs and low cleaning efficiency, and the system takes a long time to restart and resume normal operation, resulting in additional time costs.

[0006] Therefore, it is hoped to provide an aeration device operation and maintenance system and method, by implementing modular management of different aeration treatment modules on the aeration device maintenance system, so as to implement different update and maintenance cycles for different aeration treatment modules respectively, so that maintenance can be achieved without stopping the machine, reducing operating costs and improving maintenance efficiency. Summary of the Invention

[0007] One embodiment of the present specification provides an aeration device operation and maintenance system, including multiple aeration treatment modules, a gas detection module, an aeration control module, a blower device, multiple monitoring devices, at least one aeration pipe, at least one connecting pipe, at least one backup aeration equipment and at least one backup aeration pipe, the aeration control module includes a communication component; the at least one connecting pipe and the at least one aeration pipe are both provided with an electric blocking valve, and the aeration pipe is installed with the monitoring device; the aeration treatment module is connected to the blower device through the aeration pipe; the aeration treatment modules are connected to each other through the connecting pipe; the gas detection module is communicatively connected to the monitoring device; the backup aeration equipment is mechanically connected to the aeration treatment module through the backup aeration pipe; the aeration treatment module, the gas detection module, the aeration control module, the blower device and the electric blocking valve are connected to each other through the monitoring device. The partition valves are all communicatively connected to the aeration control module through the communication component; the gas detection module is configured to obtain first monitoring data from the monitoring device and transmit it to the aeration control module, the first monitoring data including the air pressure at multiple points in the air supply duct of the aeration tank and / or the dust content at multiple points in the aeration tank, the air pressure and the dust content being collected and obtained by the monitoring devices at multiple points; the aeration control module is configured to: estimate the cleaning and maintenance requirement value of the aeration treatment module based on the first monitoring data and the estimated blockage probability of the aeration treatment module, the cleaning and maintenance requirement value reflecting the urgency of the cleaning and maintenance of the aeration treatment module; determine the aeration treatment module whose cleaning and maintenance requirement value meets the preset cleaning conditions as the target cleaning object; the preset cleaning conditions include a first preset threshold; and perform cleaning and maintenance processing on the target cleaning object.

[0008] One embodiment of the present specification provides an aeration device operation and maintenance method, characterized in that it is executed based on the above-mentioned aeration device operation and maintenance system, and the method includes: obtaining first monitoring data, the first monitoring data including the air pressure at multiple points in the air supply duct of the aeration tank and / or the dust content at the multiple points in the aeration tank; estimating the cleaning and maintenance requirement value of the aeration treatment module based on the first monitoring data and the estimated blockage probability of the aeration treatment module, the cleaning and maintenance requirement value reflecting the urgency of cleaning and maintenance of the aeration treatment module; determining the aeration treatment module whose cleaning and maintenance requirement value meets a preset cleaning condition as a target cleaning object; the preset cleaning condition includes a first preset threshold; and performing cleaning and maintenance processing on the target cleaning object. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] This specification will be further described in the form of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting, and in these embodiments, like numbers represent like structures, wherein:

[0010] Figure 1 is a schematic structural diagram of an aeration device maintenance system according to some embodiments of this specification;

[0011] Figure 2 is a flow chart of a method for maintaining an aeration device according to some embodiments of this specification;

[0012] Figure 3 is a flow chart for generating control instructions for multiple aeration treatment modules according to some embodiments of this specification;

[0013] Figure 4 This is another flow chart for generating control instructions for multiple aeration treatment modules according to some embodiments of this specification. DETAILED DESCRIPTION

[0014] To more clearly illustrate the technical solutions of the embodiments of this specification, the following briefly describes the drawings required for describing the embodiments. Obviously, the drawings described below are merely examples or embodiments of this specification. Those skilled in the art can apply this specification to other similar scenarios based on these drawings without inventive effort. Unless otherwise apparent from the context or otherwise noted, the same reference numerals in the figures represent the same structure or operation.

[0015] It should be understood that the terms "system," "device," "unit," and / or "module" used herein are a method for distinguishing different components, elements, parts, portions, or assemblies at different levels. However, if other terms can achieve the same purpose, the terms may be replaced by other expressions.

[0016] As used in this specification and claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" do not refer to the singular but also include the plural. Generally speaking, the terms "comprises" and "include" only indicate the inclusion of the steps and elements specifically identified, and these steps and elements do not constitute an exclusive list. A method or apparatus may also include other steps or elements.

[0017] Flowcharts are used throughout this specification to illustrate the operations performed by systems according to embodiments of this specification. It should be understood that preceding or following operations do not necessarily need to be performed in exact order. Instead, the steps may be processed in reverse order or simultaneously. Furthermore, other operations may be added to these processes, or one or more operations may be removed from these processes.

[0018] Figure 1 It is a structural schematic diagram of an aeration device maintenance system according to some embodiments of this specification.

[0019] In some embodiments, the aeration device maintenance system may include multiple aeration treatment modules 2, a gas detection module 9, an aeration control module 6, a blowing device 7, multiple monitoring devices 8, at least one aeration pipe 4, at least one connecting pipe 3, at least one backup aeration equipment 10 and at least one backup aeration pipe 5.

[0020] In some embodiments, the aeration process module 2 is connected to the blower device 7 via an aeration pipe 4, and the aeration process modules 2 are connected to each other via a communication pipe 3. Each of the at least one communication pipe 3 and the at least one aeration pipe 4 is equipped with an electric isolation valve. A monitoring device 8 is installed on the aeration pipe 4, and the gas detection module 9 is in communication with the monitoring device 8. A backup aeration device 10 is mechanically connected to the aeration process module 2 via the backup aeration pipe 5. The aeration process module 2, the gas detection module 9, the blower device 7, and the electric isolation valve are all in communication with the aeration control module 6 via a communication component.

[0021] The aeration pipe 4 is a hollow pipe connected between the air blowing device 7 and the aeration treatment module 2. The aeration pipe 4 can be used to transport the air generated by the air blowing device 7 to the aeration treatment module 2.

[0022] The communication pipe 3 refers to a hollow pipe connecting the aeration treatment modules 2 .

[0023] The standby aeration device 10 is a device used to perform cleaning and maintenance operations on a clogged aeration treatment module 2 .

[0024] Through the setting of the backup aeration equipment 10, when it is necessary to perform cleaning and maintenance operations on the blocked aeration treatment module 2, the aeration control module 6 can control the backup aeration equipment 10 corresponding to the blocked aeration treatment module 2 to perform aeration operations instead of the blocked aeration treatment module 2, so as to ensure that the aeration device maintenance system remains in normal operation during the maintenance period.

[0025] The standby aeration pipe 5 refers to a hollow pipe connected between the standby aeration equipment 10 and the aeration treatment module 2 .

[0026] By setting up the spare aeration pipe 5, when it is found that a certain aeration treatment module is blocked and needs cleaning and maintenance, the spare aeration pipe corresponding to the blocked aeration treatment module can be opened, and the aeration pipe corresponding to the blocked aeration treatment module can be closed. Then, gas or cleaning liquid can be supplied to the blocked aeration treatment module through the spare aeration pipe, thereby achieving cleaning and maintenance of the blocked aeration treatment module alone, without the need to clean all aeration treatment modules uniformly through the aeration pipe connected to all aeration treatment modules on the aeration device maintenance system.

[0027] An electric valve is a device that uses a motor or electromagnet to control the opening and closing of a valve. Electric barrier valves can be used to control the opening and closing of aeration modules connected to the valve, thereby adjusting the number of aeration modules that need to be open as needed.

[0028] The aeration treatment module 2 can be configured to perform aeration treatment on the water body based on the control instructions. In some embodiments, the aeration treatment module 2 can include a plurality of interconnected aerators. An aerator is a gas dispersion device.

[0029] Aeration refers to the process in which the aeration module 2 disperses the air injected by the blowing device 7 into tiny bubbles and injects them into the water body.

[0030] In some embodiments, the gas detection module 9 may be configured to obtain first monitoring data from the monitoring device 8 and transmit the first monitoring data to the aeration control module 6 .

[0031] Monitoring device 8 is used to monitor data from aeration tank 1. Aeration tank 1 is a water treatment facility that improves water quality through oxygenation. In some embodiments, monitoring device 8 may include a pressure sensor, a dust monitor, and other components. The dust monitor can utilize laser or ultrasonic technology to monitor dust levels at multiple locations within the aeration tank.

[0032] In some embodiments, the first monitoring data may include air pressure at multiple points in the air supply duct of the aeration tank 1 and / or dust content at multiple points within the aeration tank. The air pressure at multiple points is collected by monitoring devices at multiple points. The air supply duct may include an aeration duct 4, a connecting duct 3, and a backup aeration duct 5.

[0033] In some embodiments, the aeration control module 6 may be configured to generate control instructions for the plurality of aeration treatment modules 2 based on the first monitoring data; and control the aeration treatment modules 2 to perform aeration treatment on the water body based on the control instructions.

[0034] In some embodiments, the control instructions may include: controlling at least one electric blocking valve to close or open at least one aeration process module, and / or controlling at least one set of standby aeration equipment to perform cleaning and maintenance on at least one aeration process module.

[0035] In some embodiments, the blowing device 7 may be configured to inject filtered air into at least one aeration treatment module 2 that is in an open state at a preset pressure.

[0036] The preset pressure refers to the pressure at which the preset blower injects air into the aeration treatment module.

[0037] In some embodiments, the preset pressure can be preset by those skilled in the art based on experience.

[0038] In some embodiments, the preset pressure may be positively correlated with water quality parameters in the water body. Water quality parameters may include COD concentration, BOD concentration, SS concentration, etc. For example, the higher the COD concentration, BOD concentration, or SS concentration in the water body, the higher the preset pressure may be set. The higher the COD concentration, BOD concentration, or SS concentration in the water body, the higher the preset pressure the air blower needs to generate to ensure adequate oxygen transfer and organic matter degradation.

[0039] For more information about the aeration processing module 2, gas detection module 9, aeration control module 6, air blowing device 7, multiple monitoring devices 8, at least one aeration pipeline 4, at least one connecting pipeline 3, at least one backup aeration device 10 and at least one backup aeration pipeline 5, please refer to Figure 2-Figure 4 Instructions in .

[0040] It should be noted that the above description of the aeration device maintenance system and its modules is for convenience only and does not limit this specification to the scope of the embodiments. It is understood that after understanding the principles of the system, those skilled in the art may arbitrarily combine the modules or form subsystems connected to other modules without departing from the principles. In some embodiments, Figure 1 The gas detection module and aeration control module disclosed herein can be separate modules within a system, or a single module can implement the functions of two or more of these modules. For example, the modules can share a storage module, or each module can have its own storage module. Such variations are within the scope of this specification.

[0041] Figure 2 is an exemplary flow chart of an aeration device maintenance method according to some embodiments of this specification. In some embodiments, process 200 can be executed by an aeration control module of an aeration device maintenance system. Figure 2 As shown, the process 200 includes the following steps 210 to 230.

[0042] Step 210: Acquire first monitoring data through a gas detection module.

[0043] For gas detection module instructions, see Figure 1 Instructions in .

[0044] The first monitoring data refers to the data collected by the monitoring device in the aeration tank when the aeration device maintenance system 100 is operating normally. For a description of the aeration tank and the monitoring device, please refer to Figure 1 See the relevant instructions in .

[0045] Air pressure refers to the force exerted by gas on the inner wall of the air supply duct per unit area within the aeration tank. The air pressure at multiple points within the aeration tank's air supply duct can reflect the gas flow rate within the aeration system. For example, if the air pressure fluctuates significantly at multiple points within the aeration tank's air supply duct, it may indicate a blockage in the aeration process module, requiring prompt cleaning and maintenance.

[0046] Dust content refers to the concentration of suspended particulate matter in the aeration tank water during the aeration process. Dust content helps assess the efficiency of the aeration system maintenance system and the effectiveness of water quality treatment. For example, changes in dust content can reflect the degradation of organic matter in the water. For example, excessive dust content can easily cause blockage in the aeration treatment module, necessitating timely cleaning and maintenance.

[0047] In some embodiments, the aeration control module can obtain the air pressure at multiple points in the air supply duct of the aeration tank and / or the dust content at multiple points in the aeration tank through a monitoring device. For a description of the monitoring device, please refer to Figure 1 Instructions in .

[0048] For example, the aeration control module may obtain the air pressure at multiple points in the air supply duct of the aeration tank through a pressure sensor.

[0049] For another example, the aeration control module may obtain the dust content at multiple points in the air supply duct of the aeration tank through a dust monitor.

[0050] Step 220: Generate control instructions for multiple aeration treatment modules based on the first monitoring data.

[0051] For instructions on the aeration treatment module, see Figure 1 See the relevant instructions in .

[0052] Control instructions are instructions for operating and managing multiple aeration treatment modules. They ensure the normal operation and maintenance of the aeration device maintenance system.

[0053] In some embodiments, the control instructions may include controlling at least one electric blocking valve to close or open at least one aeration process module, and / or controlling at least one set of standby aeration equipment to perform cleaning and maintenance on at least one aeration process module.

[0054] For instructions on electric isolation valves and backup aeration equipment, see Figure 1 See the relevant instructions in .

[0055] Cleaning and maintenance treatment refers to the process of cleaning and maintaining the aeration treatment module by ventilating the aeration treatment module or introducing other cleaning fluids into the aeration treatment module through spare aeration equipment.

[0056] In some embodiments, the aeration control module may use Figure 3 The method shown generates control instructions for multiple aeration treatment modules. For details, see Figure 3 Instructions in .

[0057] In some embodiments, the first monitoring data also includes vibration data collected by vibration sensors at multiple points in the aeration tank and its corresponding air supply duct; the aeration control module can also use Figure 4 The method shown generates control instructions for multiple aeration treatment modules. For details, see Figure 4 Instructions in .

[0058] Step 230: Based on the control instruction, control the aeration treatment module to perform aeration treatment on the water body.

[0059] In some embodiments, the aeration control module can control the aeration treatment module to perform aeration treatment on the water body based on the control instructions. For example, if the aeration treatment modules currently operating in the aeration tank include aeration treatment module A, aeration treatment module B, and aeration treatment module C, and the control instructions are to control only standby aeration equipment A to perform cleaning and maintenance on aeration treatment module A, the aeration control module can open standby aeration pipeline A corresponding to aeration treatment module A, close aeration pipeline A corresponding to aeration treatment module A, and then pass gas or cleaning fluid into aeration treatment module A through standby aeration pipeline A, thereby performing cleaning and maintenance on aeration treatment module A alone, while keeping aeration treatment modules B and aeration treatment modules C open for aeration treatment.

[0060] For another example, if the aeration treatment modules working in the aeration tank in the current state include aeration treatment module A, aeration treatment module B and aeration treatment module C, and the control instruction is to only control the electric barrier valve D to open aeration treatment module D and control the electric barrier valve E to open to open aeration treatment module E; then the aeration control module can control the electric barrier valve D corresponding to aeration treatment module D and the electric barrier valve E corresponding to aeration treatment module E to open, so as to open aeration treatment module D and aeration treatment module E for aeration treatment, while keeping aeration treatment module A, aeration treatment module B and aeration treatment module C in the open state for aeration treatment.

[0061] In some embodiments of the present specification, the aeration control module generates control instructions for multiple aeration treatment modules based on the first monitoring data; and based on the control instructions, controls the corresponding aeration treatment modules to perform aeration treatment on the water body, thereby controlling at least one electric blocking valve to close or open at least one of the aeration treatment modules according to the control instructions, and / or controlling the standby aeration equipment to perform cleaning and maintenance on the aeration treatment modules that are clogged in a certain period of time, while the aeration treatment modules that are not clogged perform aeration treatment normally. By implementing modular management for different aeration treatment modules on the aeration device maintenance system, different update and maintenance cycles are implemented for different aeration treatment modules respectively, and maintenance can be achieved without shutting down the machine, thereby reducing operating costs and improving maintenance efficiency.

[0062] Figure 3 This is an exemplary flow chart for generating control instructions for multiple aeration processing modules according to some embodiments of this specification. In some embodiments, process 300 can be executed by an aeration control module of an aeration device maintenance system. Figure 3 As shown, the process 300 includes the following steps 310 to 340.

[0063] Step 310: Determine a preset test area based on the smoothness of the first monitoring data.

[0064] The stability of the first monitoring data refers to the stability of the air pressure at multiple points in the air supply duct of the aeration tank in the first monitoring data.

[0065] In some embodiments, the aeration control module can calculate the variance of the air pressure at multiple points in the air supply duct of the aeration tank based on the first monitoring data, and use the variance of the air pressure as the stability of the first monitoring data. The air pressure at each point is the average of the air pressures collected at multiple preset time points corresponding to each point. The preset time points can be preset by those skilled in the art based on experience.

[0066] In some embodiments, the smaller the variance value of the air pressure is, the better the smoothness of the first monitoring data may be.

[0067] The preset test area may be an area in the aeration tank where there is a potential blockage, for example, an area where there is a potentially blocked air supply duct or an area where there is a potentially blocked aeration treatment module.

[0068] In some embodiments, the aeration control module may determine a grid area where the air pressure sensor points that meet a specific condition are located as a preset test area. The specific condition may be that the stability of the first monitoring data is less than a stability threshold corresponding to the corresponding air pressure sensor point.

[0069] In some embodiments, those skilled in the art may divide the entire aeration tank into grids according to a preset length and width to obtain multiple grid areas. Each air pressure sensor point may be located in a divided grid area.

[0070] The stability threshold refers to a critical value of stability and can be preset by those skilled in the art based on experience.

[0071] In some embodiments, each grid area may have a different stability threshold. The aeration treatment module may determine the stability threshold of the corresponding grid area based on the historical blockage times and historical cleaning frequencies of each grid area. For example, the greater the historical blockage times and the higher the historical cleaning frequency of a grid area, the larger the stability threshold corresponding to the grid area.

[0072] The number of historical blockages refers to the total number of blockages that occurred in each aeration treatment module in the grid area in history.

[0073] The historical cleaning frequency refers to the average value of the historical cleaning frequencies of each aeration treatment module in the grid area.

[0074] In some embodiments, the aeration control module may determine the historical blockage times and historical cleaning frequencies of each grid area based on historical data.

[0075] In some embodiments, a greater number of historical blockages indicates that the aeration treatment module and the air supply duct in the grid area are more likely to be blocked. Therefore, a larger stability threshold can be preset for the grid area to relax the judgment conditions and prevent missed judgments.

[0076] In some embodiments, a higher historical cleaning frequency indicates that the grid area accumulates blockage faster and is more likely to affect aeration operations, requiring frequent cleaning. Therefore, a larger stability threshold can be preset for the grid area to relax the judgment conditions and more strictly eliminate these hidden dangers.

[0077] In some embodiments described herein, by determining the smoothness threshold of each grid area based on the historical blockage times and historical cleaning frequencies of each grid area, the rationality and accuracy of the ultimately determined smoothness threshold can be improved.

[0078] Step 320: Based on the preset test area, control at least one electric blocking valve to close, and obtain multiple sets of second monitoring data from the monitoring device.

[0079] For instructions on electric isolation valves, see Figure 1 See the relevant instructions in .

[0080] Secondary monitoring data refers to data collected by the monitoring device after closing the electric isolation valve using each of multiple closing strategies. A closing strategy refers to the method used to close the electric isolation valve within a predefined test area. By using multiple closing strategies, secondary monitoring data can be obtained under multiple closing strategies, enriching the data. The format of the secondary monitoring data can be similar to that of the primary monitoring data.

[0081] In some embodiments, the second monitoring data may include all data types involved in the first monitoring data, water temperature, dissolved oxygen content, etc.

[0082] In some embodiments, the aeration control module controls the closing of at least one electric barrier valve based on a preset test area and obtains multiple sets of second monitoring data from the monitoring device. The specific implementation method can be implemented by the following steps 321 and 322:

[0083] Step 321: Based on the preset test area, control at least one electric blocking valve to close and generate a complete closing strategy.

[0084] In some embodiments, the aeration control module may permutate and combine all aeration treatment modules in a preset test area to obtain all combinations of aeration treatment modules; and obtain all shutdown strategies based on all combinations of aeration treatment modules.

[0085] The arrangement and combination can be a single aeration treatment module as a group, a combination of two aeration treatment modules as a group, any combination of three aeration treatment modules as a group, and so on, until all possible aeration treatment module combinations are traversed.

[0086] For example, assuming that there are aeration treatment module x, aeration treatment module y, and aeration treatment module z in a preset test area, the aeration control module can arrange and combine aeration treatment module x, aeration treatment module y, and aeration treatment module z (e.g., single arrangement and combination, two-by-two arrangement and combination, three-way arrangement and combination, etc.) to obtain the following combination of all aeration treatment modules: ① aeration treatment module x; ② aeration treatment module y; ③ aeration treatment module z; ④ aeration treatment module x+y; ⑤ aeration treatment module x+z; ⑥ aeration treatment module y+z; ⑦ aeration treatment module x+y+z.

[0087] In some embodiments, the aeration control module may use the closing mode of the electric barrier valve corresponding to the aeration treatment module in each group of all the combinations of aeration treatment modules as a corresponding set of closing strategies, thereby obtaining all the closing strategies.

[0088] For example, based on the combination of all aeration treatment modules obtained in the above embodiment, the corresponding all-shutdown strategy is:

[0089] ① Close aeration treatment module x; ② Close aeration treatment module y; ③ Close aeration treatment module z; ④ Close aeration treatment modules x+y; ⑤ Close aeration treatment modules x+z; ⑥ Close aeration treatment modules y+z; ⑦ Close aeration treatment modules x+y+z.

[0090] Step 322 , sequentially executing each group of closing strategies in all closing strategies, and obtaining a group of second monitoring data obtained from the monitoring device under each group of closing strategies, so as to obtain multiple groups of second monitoring data.

[0091] Step 330 : Determine an estimated clogging probability of each aeration treatment module based on the multiple sets of second monitoring data.

[0092] The estimated clogging probability can be used to indicate the possibility of clogging of the aeration treatment module. In some embodiments, the estimated clogging probability can be represented by a value ranging from 0 to 100%, where a larger value indicates a greater clogging probability.

[0093] In some embodiments, the aeration control module determines the estimated blockage probability of each aeration treatment module based on multiple sets of second monitoring data, which can be implemented by the following steps 331 to 336:

[0094] Step 331: Calculate the increment of the smoothness of each set of second monitoring data based on the multiple sets of second monitoring data.

[0095] The stability of the second monitoring data refers to the stability of the air pressure at multiple points in the air supply duct of the aeration tank in the second monitoring data.

[0096] The increment of the smoothness of the second monitoring data refers to the increase in the smoothness of the air pressure corresponding to the second monitoring data compared to the smoothness of the air pressure corresponding to the first monitoring data.

[0097] In some embodiments, the aeration control module may calculate the stability of each set of second monitoring data based on multiple sets of second monitoring data; and use the difference between the stability of each set of second monitoring data and the stability of the first monitoring data as the increment of the stability of the corresponding set of second monitoring data.

[0098] Step 332 : Filter out the second monitoring data whose increment of the smoothness is negative, and use the at least one set of second monitoring data remaining after the filtering as at least one set of target monitoring data.

[0099] The target monitoring data refers to the second detection data whose increment of smoothness is not negative.

[0100] Step 333 : according to the aeration processing module that is shut down in the shutdown strategy corresponding to each set of target monitoring data in at least one set of target monitoring data, count the number of times each aeration processing module is shut down in multiple sets of target monitoring data.

[0101] In step 334 , the aeration treatment module whose number of shutdown times is greater than a preset shutdown threshold is determined as a potential blockage module.

[0102] The preset shutdown threshold refers to a critical value of the number of times the aeration treatment module is shut down. In some embodiments, the preset shutdown threshold can be preset by those skilled in the art based on experience.

[0103] In some embodiments, the predetermined shut-off threshold may be related to a rate of change of a pressure difference across a filter assembly of the blower device.

[0104] A filter assembly is a filter element or filter assembly used to filter air in a blower unit. When air passes through the filter assembly, it encounters resistance, resulting in a pressure difference between the front and rear sides of the filter assembly.

[0105] The pressure difference of the filter assembly refers to the pressure difference between the front and rear sides of the filter assembly used to filter air in the blower device.

[0106] The pressure difference change rate of the filter assembly refers to the rate of change of the pressure difference between the front and rear sides of the filter assembly within a preset time period.

[0107] In some embodiments, the aeration control module may calculate the pressure differential change rate of the filter assembly by calculating the difference in pressure differentials between the front and rear sides of the filter assembly at different time points and dividing the difference by the corresponding time interval. In some embodiments, if the pressure differential change rate of the filter assembly calculated by the aeration control module is greater, the aeration control module may determine that the resistance of the filter assembly is changing rapidly per unit time, indicating that the filter assembly is severely clogged or has dust accumulation.

[0108] In some embodiments, the greater the pressure difference change rate of the filter assembly of the blowing device, the greater the value of the preset closing threshold.

[0109] In some embodiments of the present specification, if the filter assembly has not been replaced for a long time, resulting in excessive accumulation of dust, the pressure difference change rate of the filter assembly will be greater than that of the filter assembly without dust accumulation. Therefore, if the pressure difference change rate of the filter assembly of the blower device increases, there is a certain probability that it is caused by the condition of the filter assembly itself, rather than by the blockage of the aeration treatment module. At this time, by making the preset closing threshold positively correlated with the pressure difference change rate of the filter assembly of the blower device, the preset closing threshold is increased to set the judgment condition of the potential blockage module more stringent, thereby reducing misjudgment.

[0110] Step 335 : For each potential congestion module, determine the estimated congestion probability of the potential congestion module according to the number of times the potential congestion module is closed in the closing strategy corresponding to each target monitoring data.

[0111] The estimated congestion probability refers to the estimated probability of congestion in the potential congestion module.

[0112] In some embodiments, the estimated jam probability may be positively correlated to the number of times the potential jam module is disabled. For example, the more times the potential jam module is disabled, the greater the estimated jam probability.

[0113] In some embodiments, the aeration control module can determine an estimated blockage probability based on the number of times the potential blockage module has been shut down, using a preset comparison table. The preset comparison table contains a correspondence between the number of times the potential blockage module has been shut down and a reference estimated blockage probability. The preset comparison table can be constructed based on prior knowledge or historical data.

[0114] In step 336 , after removing the potential blockage modules in the aeration tank, the estimated blockage probabilities of the remaining aeration treatment modules are all assigned to 0 or a lower preset value.

[0115] In some embodiments, after removing the potential blocking modules from the aeration tank, the remaining aeration treatment modules may be aeration treatment modules within the preset test area or may be aeration treatment modules outside the preset test area.

[0116] In some embodiments, after removing the potentially blocked modules from the aeration tank, the aeration control module may assign an estimated blockage probability of 0 to the remaining aeration treatment modules that are not within a preset test area, and assign an estimated blockage probability of aeration treatment modules within the preset test area to a lower preset value. The preset value may be preset by a person skilled in the art based on experience.

[0117] Step 340 : Based on the estimated blockage probability, control at least one group of standby aeration equipment to perform cleaning and maintenance on at least one aeration process module.

[0118] For instructions on alternate aeration equipment, see Figure 1 See the relevant instructions in .

[0119] For instructions on cleaning and maintenance, see Figure 2 Relevant instructions in step 220.

[0120] In some embodiments, the aeration control module may perform cleaning maintenance operations using spare aeration equipment on aeration processing modules whose estimated blockage probability is greater than a preset blockage threshold. The preset blockage threshold may be determined by those skilled in the art based on historical data or experience.

[0121] In some embodiments, the aeration control module may further generate and send an early warning message to the aeration processing module that is performing the cleaning and maintenance operation.

[0122] The warning information can be one or more of sound, text, video, etc.

[0123] It can be understood that when all the air supply ducts in the entire aeration tank are completely unblocked, the air pressure in each air supply duct is relatively stable; when the air supply duct is partially blocked, the blockage may disturb the airflow, and the blockage may not be completely fixed, that is, it may be in a semi-active state under the action of the airflow, which further strengthens the disturbance of the airflow, resulting in unstable pressure in some ducts; if the blocked air supply duct / aeration treatment module is closed by an electric blocking valve, then the remaining air supply ducts will form a steady state due to the absence of disturbances caused by the blockage, and the air pressure can return to stability.

[0124] In some embodiments of the present specification, by determining a preset test area based on the smoothness of the pressure data in the first monitoring data, controlling at least one electric blocking valve to close, and then determining the estimated blockage probability of each aeration treatment module through multiple sets of second monitoring data obtained by the monitoring device, the accuracy of the ultimately determined estimated blockage probability can be improved, thereby improving the accuracy of controlling at least one set of standby aeration equipment to perform cleaning and maintenance on at least one aeration treatment module.

[0125] For example, assume that the entire aeration tank has 100 air pressure sensors, which are placed at 100 points respectively; 100 pressure sequences are obtained as the first monitoring data, wherein each pressure sequence corresponds to a point, and each pressure sequence includes the air pressure collected at each point at multiple preset time points, and the multiple preset time points can be preset by technical personnel in this field based on experience; according to the first monitoring data, a preset test area is determined; a closing test (partial / full closing) is performed in the preset test area, and each test corresponds to a group of pressure sequences, and this group of pressure sequences contains 100 pressure sequences, and each group of pressure sequences is the second monitoring data corresponding to each test; based on the multiple second monitoring data obtained from the test, the estimated blockage probability is determined to improve the accuracy of the estimated blockage probability finally determined, thereby improving the accuracy of controlling at least one group of standby aeration equipment to perform cleaning and maintenance processing on at least one aeration treatment module.

[0126] It should be noted that the above description of process 300 is for illustration and purpose only and does not limit the scope of application of this specification. Those skilled in the art may make various modifications and alterations to process 300 under the guidance of this specification. However, such modifications and alterations are still within the scope of this specification.

[0127] Figure 4 This is another exemplary flow chart for generating control instructions for multiple aeration processing modules according to some embodiments of this specification. In some embodiments, process 400 can be executed by an aeration control module of an aeration device maintenance system. Figure 4 As shown, the process 400 includes the following steps 410 to 460.

[0128] Step 410 : Estimate the cleaning and maintenance requirement value of each aeration treatment module based on the first monitoring data and the estimated blockage probability of each aeration treatment module.

[0129] In some embodiments, the first monitoring data may further include vibration data collected by vibration sensors at multiple points in the aeration tank and the air supply duct of the aeration tank.

[0130] Vibration data refers to data collected by vibration sensors installed at preset positions in the aeration tank and its air supply duct, such as vibration frequency, etc. The preset positions can be preset by those skilled in the art based on experience.

[0131] In some embodiments, the vibration data may reflect the vibrations generated when mechanical equipment such as standby aeration equipment and blower devices are in operation and when gas flows in the air supply duct.

[0132] For more information about the first monitoring data, see Figure 2 Description of step 210.

[0133] For a description of the estimated clogging probability and how to determine it for each aeration treatment module, see Figure 3 Instructions in .

[0134] The cleaning and maintenance demand value refers to a value of the urgency of cleaning and maintenance of the aeration treatment module estimated based on the first monitoring data.

[0135] In some embodiments, the cleaning and maintenance requirement value may reflect the urgency of cleaning and maintenance of the aeration treatment module. For example, the greater the cleaning and maintenance requirement value, the higher the urgency.

[0136] In some embodiments, the aeration control module can determine a first target characteristic vector based on the first monitoring data and the estimated blockage probability of each of the aeration treatment modules; determine a first associated characteristic vector through a vector database based on the first target characteristic vector; and determine the reference cleaning and maintenance requirement value of the reference aeration treatment module corresponding to the first associated characteristic vector as the cleaning and maintenance requirement value of the aeration treatment module.

[0137] In some embodiments, the first monitoring data may include vibration data collected by vibration sensors at multiple points in the aeration tank and the air supply duct of the aeration tank, air pressure at multiple points in the air supply duct of the aeration tank, and dust content at multiple points in the aeration tank.

[0138] The vector database contains multiple first reference feature vectors, each of which corresponds to a reference cleaning and maintenance requirement value for a reference aeration treatment module. The first reference feature vectors are constructed based on historical first monitoring data and the historically estimated blockage probability of each aeration treatment module. The reference cleaning and maintenance requirement values ​​for the reference aeration treatment modules are determined using the same method as the labels in the estimation model. For details, see the description of the labels below.

[0139] In some embodiments, the aeration control module may determine, based on the first target feature vector, a first reference feature vector in a vector database that meets a target preset condition, and determine the first reference feature vector that meets the target preset condition as the first associated feature vector. In some embodiments, the target preset condition may include a minimum vector distance from the first target feature vector.

[0140] In some embodiments, the aeration control module may determine the cleaning and maintenance requirement value of the aeration treatment module based on the reference cleaning and maintenance requirement value of the reference aeration treatment module corresponding to the determined first correlation feature vector.

[0141] In some embodiments, the aeration control module may further construct an aeration working structure diagram based on the first monitoring data; and based on the aeration working structure diagram, predict the cleaning and maintenance requirement value of the aeration treatment module corresponding to each node in the aeration working structure diagram through an estimation model.

[0142] The aeration working structure diagram refers to a data structure diagram constructed by the aeration processing modules in the aeration tank and their corresponding air supply ducts.

[0143] In some embodiments, the aeration work structure graph is a data structure consisting of nodes and edges, where the edges connect the nodes, and the nodes and edges may have attributes.

[0144] In some embodiments, a node in the aeration operation structure diagram may correspond to an aeration process module in the aeration tank. The node's attributes may reflect the characteristics of the corresponding aeration process module. For example, the node's attributes may include: first monitoring data collected by a monitoring device on the aeration pipeline directly connected to the aeration process module; an estimated blockage probability of the aeration process module; and the like.

[0145] In some embodiments, the node attributes in the aeration work structure diagram may further include a water quality parameter change rate of a water quality parameter at a point where an aeration treatment module corresponding to the node is located.

[0146] Water quality parameters refer to various parameters related to the water quality of a body of water. For example, water quality parameters can include indicators such as Chemical Oxygen Demand (COD), Biochemical Oxygen Demand (BOD), Suspended Solids (SS), and nitrogen and phosphorus removal rates.

[0147] In some embodiments, the aeration control module can determine COD by high-temperature digestion method, oxidant titration method, etc., determine BOD by dilution inoculation method, and determine SS by membrane filter method, laser particle size analyzer, etc.

[0148] The water quality parameter change rate refers to the change in water quality parameters within a preset time period (for example, the last week).

[0149] In some embodiments, the aeration control module may use the following first formula to determine the rate of change of the water quality parameter:

[0150] Water quality parameter change rate = (mean change of COD concentration + mean change of BOD concentration + mean change of SS concentration + mean change of nitrogen and phosphorus removal rate) / 4;

[0151] In some embodiments, the aeration control module may count the COD concentration differences at multiple adjacent consecutive moments and then calculate the average of the multiple COD concentration differences to obtain the COD concentration variation mean. The multiple adjacent consecutive moments may be preset by those skilled in the art based on experience.

[0152] The calculation methods for the mean change of BOD concentration, the mean change of SS concentration, and the mean change of nitrogen and phosphorus removal rate are similar to those for the mean change of COD concentration. Please refer to the above description for details.

[0153] In some embodiments of the present specification, since the more frequent the rate of change of the water quality parameters, the more fluctuating the water quality parameters, and the more complex the water quality, it may mean that the aeration treatment module is working poorly in this area and needs to be maintained and cleaned as a priority, by including the water quality parameter change rate at the point where the aeration treatment module is located in the node attributes of the aeration work structure diagram, and combining the water quality parameter change rate to determine the maintenance order for maintenance, it is possible to prioritize the maintenance and cleaning of aeration treatment modules with complex water quality.

[0154] In some embodiments, the node attributes in the aeration work structure diagram may also include the bubble diameter distribution at multiple preset moments in the grid area where the aeration treatment module corresponding to the node is located. The multiple preset moments can be preset by those skilled in the art based on experience. For a description of the grid area, see Figure 3 Description of step 310.

[0155] Bubbles refer to the bubbles generated in the grid area where the aeration treatment module corresponding to the node is located.

[0156] Bubble diameter refers to the diameter of the bubble.

[0157] The bubble diameter distribution refers to the number of bubbles of various bubble diameters at a preset time within the grid area where the aeration treatment module corresponding to the node is located. For example, the statistical results of the bubble diameter distribution within a grid area at a preset time t1 can be expressed as the following table:

[0158]

[0159] In some embodiments, the aeration control module can capture images of the aeration tank using a camera device, and through image recognition, identify bubbles in the images captured at multiple consecutive preset moments. Based on the bubbles, the module can determine the number of pixels occupied by each bubble (e.g., 100 pixels = 0.33 inches) to calculate the diameter of each bubble. Finally, based on the bubble diameter of each bubble, the module can statistically determine the distribution of bubble diameters at multiple consecutive preset moments. Image recognition methods can include neural network algorithms, decision tree algorithms, and the like.

[0160] In some embodiments of the present specification, if there is a large change in the bubble diameter distribution between each preset moment in a plurality of consecutive preset moments, it can be seen from the generation of bubbles that at this time there is a relatively unstable air pressure and gas flow in the grid area, and this may be caused by the aeration treatment of the grid area. Therefore, introducing the bubble diameter distribution characteristics of the bubbles in the aeration working structure diagram can enable the prediction model to learn more information and improve the accuracy of the final predicted cleaning and maintenance demand value.

[0161] In some embodiments, an edge of the aeration operation structure diagram may correspond to an air supply duct actually connected between aeration process modules. The attributes of the edge may reflect the characteristics of the air supply duct actually connected between the aeration process modules. For example, the edge attributes may include the length of the air supply duct.

[0162] In some embodiments, the estimation model may be a machine learning model. In some embodiments, the estimation model may be a graph neural network (GNN) model. The output of the estimation model may be a cleaning and maintenance requirement value corresponding to each node.

[0163] In some embodiments, the estimation model can be obtained through training based on a plurality of labeled training samples.

[0164] In some embodiments, each group of training samples in the training samples may include a historical sample aeration working structure diagram. The historical sample aeration working structure diagram refers to a data structure diagram constructed by the aeration processing modules in the historical sample aeration tank and their corresponding air supply pipes.

[0165] In some embodiments, the aeration control module may construct a historical sample aeration work structure diagram through the aeration processing modules in the historical sample aeration tank and their corresponding air supply ducts, wherein the attributes of the nodes and edges of the historical sample aeration work structure diagram may be determined based on historical data.

[0166] In some embodiments, the label may be an actual cleaning and maintenance requirement value corresponding to the aeration processing module of each node in the historical sample aeration work structure diagram.

[0167] Labels can be determined through manual annotation.

[0168] In some embodiments, the aeration control module can obtain, based on the historical sample aeration operation structure diagram, the actual historical time when each aeration process module actually experienced a failure or blockage during the historical actual operation of the aeration device maintenance system and the historical time when the historical sample aeration operation structure diagram was constructed; calculate the difference between the actual historical time when the failure or blockage actually occurred and the historical time when the historical sample was constructed; determine the cleaning and maintenance requirement value of the aeration process module based on the difference; and use the cleaning and maintenance requirement value of the aeration process module as a tag value. In some implementations, the smaller the difference, the larger the tag value can be preset.

[0169] For example, a historical sample aeration working structure diagram is constructed based on data at historical time t1, and the historical sample aeration working structure diagram includes aeration treatment module A. Then, the label value of aeration treatment module A in the historical sample aeration working structure diagram may be negatively correlated with the difference between historical time t2 and historical time t1 when aeration treatment module A fails or is actually blocked.

[0170] In some embodiments of the present specification, by constructing an aeration working structure diagram based on the first monitoring data and inputting an estimation model to determine the cleaning and maintenance requirement value of the aeration treatment module, the cleaning and maintenance requirement value can be determined quickly and accurately.

[0171] Step 420 : Determine the aeration treatment modules whose cleaning maintenance requirement values ​​are greater than a first preset threshold as target cleaning objects.

[0172] The first preset threshold refers to a critical value of the cleaning and maintenance requirement value.

[0173] In some embodiments, the aeration control module may determine the first preset threshold at the current moment based on a weighted sum of the means and standard deviations of multiple historical preset thresholds.

[0174] In some embodiments, the aeration control module can determine, based on historical data, when a cleaning and maintenance requirement reaches a certain level, necessitating immediate cleaning of the aeration process module. Otherwise, normal operation of the aeration process module will be impacted. The cleaning and maintenance requirement at that time serves as a historical preset threshold. In some embodiments, the aeration control module may have historical data indicating multiple instances where immediate cleaning of the aeration process module was required. Consequently, the aeration control module may have multiple historical preset thresholds.

[0175] In some embodiments, the weighted weight can be related to the consistency of the water quality parameters measured before and after the electric barrier valve is closed, wherein the electric barrier valve is closed in accordance with each group of closing strategies in sequence, and each group of closing strategies corresponds to a water quality parameter measured before and after the electric barrier valve is closed. For example, the greater the consistency of the water quality parameters measured before and after the electric barrier valve is closed, the greater the weight corresponding to the mean of multiple historical preset thresholds (the maximum is 1), and the smaller the weight corresponding to the standard deviation of multiple historical preset thresholds (the minimum is 0). For an explanation of the closing strategy, please refer to Figure 3 Description in step 320.

[0176] In some embodiments, the aeration control module can determine the consistency of the water quality parameters measured before and after closing the electric barrier valve based on the absolute value of the difference between the water quality parameters measured before and after closing the electric barrier valve. For example, the larger the absolute value, the worse the consistency of the water quality parameters measured before and after closing the electric barrier valve.

[0177] For example only, the first preset threshold may be calculated using the following second formula:

[0178] The first preset threshold value = k1 * the mean of the multiple historical preset threshold values ​​+ k2 * the standard deviation of the multiple historical preset threshold values, where k1 and k2 are numbers greater than 0 and less than 1. k1 and k2 can be preset by those skilled in the art based on experience. For example, the greater the consistency of the water quality parameters measured before and after closing the electric barrier valve, the larger k1 (the maximum value of k1 is 1) and the smaller k2 (the minimum value of k2 is 0).

[0179] In some embodiments, the aeration control module can count the water quality parameter x1 before closing the electric barrier valve and the water quality parameter x2 after closing the electric barrier valve corresponding to each set of closing strategies; calculate the mean of the water quality parameter x1 before closing the electric barrier valve corresponding to all closing strategies, and the mean of the water quality parameter x2 after closing the electric barrier valve corresponding to all closing strategies; calculate the covariance cov(water quality parameter x1, water quality parameter x2) based on the mean of the water quality parameter x1 and the mean of the water quality parameter x2; calculate the standard deviation of the water quality parameter x1 based on the mean of the water quality parameter x1 and the mean of the water quality parameter x2. and the standard deviation of water quality parameter x2; calculate the Pearson coefficient P(x) = [cov(water quality parameter x1, water quality parameter x2)] / [standard deviation of water quality parameter x1 * standard deviation of water quality parameter x2], and obtain the Pearson coefficient P(x) as a number between [-1,1]; the closer the absolute value of the Pearson coefficient P(x) is to 1, the more relevant it is, the greater the consistency of the water quality parameters measured before and after closing the electric barrier valve, the greater the weight corresponding to the mean of multiple historical preset thresholds (the maximum is 1), and the smaller the weight corresponding to the standard deviation of multiple historical preset thresholds (the minimum is 0).

[0180] It is understandable that closing the electric barrier valve may affect the water quality parameters. If the water quality parameters show abnormal changes after closing the electric barrier valve, such as a decrease in dissolved oxygen or an increase in ammonia nitrogen concentration, it may mean that the aeration treatment module is clogged or has other problems and needs to be cleaned and maintained. By associating the weighted weight with the degree of consistency of the water quality parameters measured before and after closing the electric barrier valve, the corresponding weight is adjusted to reflect the importance of the water quality parameter in determining the first preset threshold value. This can more directly take into account the actual operation of the aeration treatment module and more accurately evaluate the cleaning and maintenance needs of the aeration treatment module.

[0181] The target cleaning object refers to the aeration treatment module that needs to be cleaned and maintained.

[0182] In some embodiments, the aeration control module may directly determine an aeration treatment module having a cleaning maintenance requirement value greater than a first preset threshold as a target cleaning object.

[0183] Step 430: Perform cleaning and maintenance processing on the target cleaning object.

[0184] In some embodiments, the aeration control module can control the standby aeration equipment corresponding to the target cleaning object to perform cleaning and maintenance processing on the target cleaning object. For a description of the cleaning and maintenance processing, please refer to Figure 2 Description of step 220.

[0185] In some embodiments, the method for generating control instructions for multiple aeration treatment modules may further include the following steps 440 to 460 .

[0186] In step 440 , the aeration treatment modules whose cleaning maintenance requirement values ​​are greater than the second preset threshold and less than the first preset threshold are determined as objects to be queued for cleaning.

[0187] The second preset threshold refers to another critical value of the cleaning and maintenance requirement value that is different from the first preset threshold. The second preset threshold may be smaller than the first preset threshold.

[0188] In some embodiments, the second preset threshold is associated with a change in the water quality parameter before and after the target cleaning object is cleaned and maintained. The method for determining the second preset threshold is similar to the method for determining the first preset threshold, and for details, refer to the description in the aforementioned step 420.

[0189] Cleaning queues are aeration treatment modules in the aeration tank that require less urgent cleaning and maintenance. These cleaning queues require less maintenance than target cleanings and can be delayed slightly, but they still require maintenance and cleaning at the appropriate time to ensure the long-term stability of the aeration system.

[0190] In some embodiments, the aeration control module may determine an aeration treatment module whose cleaning maintenance requirement value is greater than a second preset threshold and less than a first preset threshold as a cleaning queue object.

[0191] Step 450 : Determine the cleaning and maintenance order of each cleaning object in the queue based on the cleaning and maintenance demand value and aeration importance of the cleaning object in the queue.

[0192] Aeration importance refers to the degree to which the location of an aeration treatment module in the aeration device maintenance system affects the entire aeration device maintenance system. For example, an aeration treatment module located in the center of the aeration tank may be more important than an aeration treatment module located at the edge.

[0193] In some embodiments, the importance of aeration can be measured by a value between 0 and 100%, where the closer to 100%, the more important it is.

[0194] In some embodiments, the aeration control module may obtain the locations of the queued cleaning objects in the aeration tank via sensors installed on the aeration treatment modules, and determine the importance of the queued cleaning objects based on the locations of the queued cleaning objects in the aeration tank. For example, if the queued cleaning objects include aeration treatment modules located in the central region of the entire aeration tank and aeration treatment modules located in the edge regions of the entire aeration tank, since the aeration treatment modules located in the central region of the entire aeration tank are likely more important than the modules located in the edge regions, the importance of the aeration treatment modules located in the central region of the entire aeration tank may be preset to 100%, and the importance of the aeration treatment modules located in the edge regions of the entire aeration tank may be preset to 10%.

[0195] In some embodiments, the aeration control module may further determine the aeration importance of each cleaning object in the queue through a preset algorithm based on the real-time values ​​of water quality parameters of each cleaning object before and after cleaning and maintenance, and the number of cleaning times of the cleaning object in the queue.

[0196] The real-time value of a water quality parameter refers to the value of the water quality parameter obtained by real-time measurement.

[0197] The number of cleaning times for a queued cleaning object refers to the number of cleaning times that have been executed for the queued cleaning object.

[0198] Just as an example, the preset algorithm may be the following third formula:

[0199] The aeration importance of each cleaning object in the queue Among them, N refers to the number of types of reference water quality parameters selected; M refers to the number of cleaning times of the objects in the queue; i is the standard value of the water quality parameter, which is the preset value; weight k j Greater than 0 and less than 1; The absolute value of the difference between the real-time value of water quality parameter i after cleaning and the standard value of water quality parameter i during a certain historical cleaning j of a certain queued cleaning object; It is the absolute value of the difference between the real-time value of water quality parameter i before cleaning and the standard value of water quality parameter i during a historical cleaning j of a certain queued cleaning object.

[0200] In some embodiments, the selected reference water quality parameters may include BOD, COD, and SS, and then N=3.

[0201] In some embodiments, the weight k j It can be negatively correlated with the time of the jth cleaning of a certain cleaning object in the queue. It can be understood that the shorter the cleaning time, the higher the cleaning efficiency, and the better the cleaning object in the queue performs in this cleaning maintenance, and the more significant the improvement effect on water quality parameters. Therefore, the shorter the cleaning time, the greater the weight k. j The bigger.

[0202] In some embodiments of the present specification, the aeration importance of each queued cleaning object is determined with higher accuracy through a preset algorithm based on the real-time values ​​of water quality parameters of each queued cleaning object before and after cleaning and maintenance, as well as the number of cleaning times of the queued cleaning object.

[0203] The cleaning and maintenance sequence refers to the order or sequence of cleaning and maintenance of each aeration treatment module in the cleaning queue.

[0204] In some embodiments, the aeration control module can determine a weight coefficient corresponding to the cleaning and maintenance requirement value of each queued cleaning object based on the aeration importance of each queued cleaning object; multiply the cleaning and maintenance requirement value of each queued cleaning object by the corresponding weight coefficient to obtain a comprehensive value of each queued cleaning object; and determine the cleaning and maintenance order of each queued cleaning object based on the comprehensive value of each queued cleaning object.

[0205] In some embodiments, the weight coefficient Wi of each queued cleaning object is related to the aeration importance of each queued cleaning object. For example, the higher the aeration importance of the queued cleaning object, the higher the weight coefficient Wi may be preset.

[0206] For example only, the aeration control module may use the following fourth formula to determine the comprehensive value of each queued cleaning object:

[0207] The comprehensive value Si of each cleaning object in the queue is equal to Vi×Wi, where Wi is greater than 0 and less than 1, and Vi is the cleaning maintenance demand value of each cleaning object in the queue.

[0208] In some embodiments, the aeration control module may sort the comprehensive value of each queued cleaning object from high to low, with the queued cleaning object having a higher score being placed first for cleaning and maintenance. If the scores are the same, the objects may be sorted or processed according to other factors (e.g., if the scores are the same, the higher the importance of aeration, the earlier the cleaning and maintenance will be performed), thereby determining the cleaning and maintenance order of each queued cleaning object.

[0209] Step 460: Perform cleaning and maintenance processing on the queued cleaning objects based on the cleaning and maintenance order.

[0210] In some embodiments, the aeration control module may perform cleaning and maintenance processing on the queued cleaning objects in sequence based on the cleaning and maintenance order.

[0211] In some embodiments of the present specification, in the process of estimating the cleaning and maintenance requirement value of each aeration treatment module, the vibration data collected by vibration sensors at multiple points in the aeration tank and the air supply duct of the aeration tank, the air pressure at multiple points in the air supply duct of the aeration tank and the dust content at multiple points in the aeration tank, and the estimated blockage probability of each aeration treatment module are taken into consideration at the same time, thereby improving the accuracy of the final determined cleaning and maintenance requirement value, and thereby improving the accuracy of the final determined target cleaning object.

[0212] In the process of determining the cleaning and maintenance order of each cleaning object in the queue, the cleaning and maintenance demand value of the cleaning object in the queue and the aeration importance are taken into consideration at the same time, which can further ensure the rationality and accuracy of the cleaning and maintenance order of each cleaning object in the queue and ensure the normal operation of the aeration device maintenance system.

[0213] While the basic concepts have been described above, it will be apparent to those skilled in the art that the detailed disclosure is merely illustrative and does not limit this specification. Although not explicitly stated herein, various modifications, improvements, and revisions to this specification may be made by those skilled in the art. Such modifications, improvements, and revisions are suggested in this specification and remain within the spirit and scope of the exemplary embodiments of this specification.

[0214] This specification also uses specific terms to describe the embodiments of this specification. For example, "one embodiment," "an embodiment," and / or "some embodiments" refer to a feature, structure, or characteristic associated with at least one embodiment of this specification. Therefore, it should be emphasized and noted that references to "one embodiment," "an embodiment," or "an alternative embodiment" two or more times in different locations in this specification do not necessarily refer to the same embodiment. Furthermore, certain features, structures, or characteristics of one or more embodiments of this specification may be appropriately combined.

[0215] In addition, unless expressly stated in the claims, the order of the processing elements and sequences, the use of alphanumeric characters, or the use of other names described in this specification are not intended to limit the order of the processes and methods of this specification. Although the above disclosure discusses some of the invention embodiments currently considered useful through various examples, it should be understood that such details are for illustrative purposes only, and the appended claims are not limited to the disclosed embodiments. On the contrary, the claims are intended to cover all modifications and equivalent combinations that are consistent with the spirit and scope of the embodiments of this specification. For example, although the system components described above can be implemented by hardware devices, they can also be implemented only by software solutions, such as installing the described system on an existing server or mobile device.

[0216] Similarly, it should be noted that, in order to simplify the presentation of this specification and thus facilitate understanding of one or more embodiments of the invention, the foregoing descriptions of the embodiments of this specification sometimes combine multiple features into a single embodiment, figure, or description thereof. However, this disclosure method does not imply that the subject matter of this specification requires more features than those recited in the claims. In fact, an embodiment may have fewer features than all of the features of a single disclosed embodiment.

[0217] In some embodiments, numbers are used to describe the quantity of components and attributes. It should be understood that such numbers used in the description of the embodiments are modified by the modifiers "about", "approximately" or "substantially" in some examples. Unless otherwise stated, "about", "approximately" or "substantially" indicate that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the description and claims are approximate values, which may change according to the required characteristics of individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and adopt the general method of retaining digits. Although the numerical domains and parameters used to confirm the breadth of their range in some embodiments of this specification are approximate values, in specific embodiments, the settings of such numerical values ​​are as accurate as possible within the feasible range.

[0218] Each patent, patent application, patent application publication, and other materials, such as articles, books, specifications, publications, and documents, cited in this specification is hereby incorporated by reference in its entirety. This includes application history documents that are inconsistent with or conflict with the content of this specification, as well as documents (currently or subsequently attached to this specification) that limit the broadest scope of the claims of this specification. It should be noted that if the descriptions, definitions, and / or terminology used in the accompanying materials are inconsistent or conflicting with the content of this specification, the descriptions, definitions, and / or terminology used in this specification will control.

[0219] Finally, it should be understood that the embodiments described in this specification are intended only to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, by way of example and not limitation, alternative configurations of the embodiments of this specification may be considered consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly described and illustrated in this specification.

Claims

1. An aeration device operation and maintenance system, characterized in that: The system comprises a plurality of aeration processing modules, a gas detection module, an aeration control module, a blower, a plurality of monitoring devices, at least one aeration pipe, at least one connecting pipe, at least one backup aeration device, and at least one backup aeration pipe. The aeration control module includes a communication component. The at least one connecting pipe and the at least one aeration pipe are both equipped with electric isolation valves. The monitoring device is installed on the aeration pipe. The aeration treatment module is connected to the blower device via the aeration pipe; the aeration treatment modules are connected to each other via the communication pipe; the gas detection module is in communication connection with the monitoring device; the backup aeration equipment is mechanically connected to the aeration treatment module via the backup aeration pipe; the aeration treatment module, the gas detection module, the aeration control module, the blower device, and the electric barrier valve are all in communication connection with the aeration control module via the communication component; The gas detection module is configured to obtain first monitoring data from the monitoring device and transmit the data to the aeration control module, wherein the first monitoring data includes air pressure at multiple points in the air supply duct of the aeration tank and / or dust content at multiple points in the aeration tank, the air pressure and dust content being collected and obtained by the monitoring device at multiple points; The aeration control module is configured to: estimating a cleaning and maintenance requirement value of the aeration process module based on the first monitoring data and the estimated blockage probability of the aeration process module, wherein the cleaning and maintenance requirement value reflects the urgency of cleaning and maintenance of the aeration process module; Determine the aeration treatment module whose cleaning maintenance requirement value meets a preset cleaning condition as a target cleaning object; the preset cleaning condition includes a first preset threshold; Performing cleaning and maintenance processing on the target cleaning object; The aeration control module is further configured to: generating control instructions for a plurality of the aeration treatment modules; Based on the control instruction, controlling the aeration treatment module to perform aeration treatment on the water body; the control instruction includes: controlling at least one electric blocking valve to close or open at least one of the aeration treatment modules, and / or controlling at least one group of the standby aeration equipment to perform cleaning and maintenance on the at least one aeration treatment module; The blowing device is configured to inject filtered air into at least one of the aeration treatment modules in an open state at a preset pressure; Based on the stability of the first monitoring data, a preset test area is determined, where the preset test area is an area with potential blockage; the stability of the first monitoring data refers to the stability of the air pressure at multiple points in the air supply duct of the aeration tank in the first monitoring data. Based on the preset test area, controlling at least one of the electric blocking valves to close, and acquiring multiple sets of second monitoring data from the monitoring device; determining an estimated clogging probability of each of the aeration treatment modules based on the multiple sets of second monitoring data; calculating, based on the plurality of sets of the second monitoring data, an increment of the smoothness of each set of the second monitoring data; the smoothness of the second monitoring data refers to the smoothness of the air pressure at a plurality of points in the air supply duct of the aeration tank in the second monitoring data; the increment of the smoothness of the second monitoring data refers to an increase in the smoothness of the air pressure corresponding to the second monitoring data compared to the smoothness of the air pressure corresponding to the first monitoring data; Filtering the plurality of sets of the second monitoring data based on a preset screening condition to obtain at least one set of target monitoring data, wherein the preset screening condition is related to an increment of the smoothness of the second monitoring data; According to the shutdown strategy corresponding to each set of target monitoring data in the at least one set of target monitoring data, counting the number of times each aeration treatment module is shut down in the at least one set of target monitoring data; Determining a potential blockage module based on a preset blockage condition; the preset blockage condition is related to the number of times the aeration treatment module has been shut down; For each of the potential congestion modules, determining an estimated congestion probability of the potential congestion module according to the number of times the potential congestion module is closed in the closing strategy corresponding to each set of target monitoring data; and Assigning the estimated blockage probability of the aeration treatment modules in the aeration tank, excluding the potential blockage modules, to a preset value; A grid area where the air pressure sensor points that meet specific conditions are located is determined as the preset test area, and the specific conditions include that the smoothness of the first monitoring data is less than the smoothness threshold corresponding to the corresponding air pressure sensor point.

2. The system according to claim 1, wherein: The first preset threshold is determined based on a weighted value of statistical values ​​of a plurality of historical preset thresholds, where the statistical value includes a mean and a standard deviation of the plurality of historical preset thresholds.

3. The system according to claim 1, wherein: The aeration control module is further configured to: Determine the aeration treatment modules whose cleaning maintenance demand values ​​are greater than the second preset threshold and less than the first preset threshold as queued cleaning objects; Determining a cleaning and maintenance order for each cleaning object in the queue based on the cleaning and maintenance demand value and aeration importance of the cleaning object in the queue; Based on the cleaning and maintenance order, cleaning and maintenance processing is performed on the queued cleaning objects.

4. The system according to claim 3, characterized in that The aeration control module is further configured to: The aeration importance of the queued cleaning object is determined based on the real-time values ​​of the water quality parameters of the queued cleaning object before and after the cleaning and maintenance treatment, and the number of cleaning times of the queued cleaning object.

5. An aeration device operation and maintenance method, characterized in that: The aeration device operation and maintenance system according to claim 1 is implemented, wherein the method comprises: Acquiring first monitoring data, the first monitoring data including air pressure at multiple points in an air supply duct of the aeration tank and / or dust content at the multiple points in the aeration tank; estimating a cleaning and maintenance requirement value of the aeration process module based on the first monitoring data and the estimated blockage probability of the aeration process module, wherein the cleaning and maintenance requirement value reflects the urgency of cleaning and maintenance of the aeration process module; Determine the aeration treatment module whose cleaning maintenance requirement value meets a preset cleaning condition as a target cleaning object; the preset cleaning condition includes a first preset threshold; Perform cleaning and maintenance processing on the target cleaning object.

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