Self-detection maintenance system and method for aeration device

Abstract

The embodiment of the invention provides a self-detection maintenance system and method for an aeration device. The system comprises an aeration treatment module, a gas detection module, an aeration control module, a blower device, a monitoring device, an aeration pipeline, a communication pipeline, standby aeration equipment and a standby aeration pipeline, the method comprises the steps of obtaining first monitoring data, determining a preset test area based on the stability of the first monitoring data, controlling at least one electric blocking valve to be closed based on the preset test area, and obtaining second monitoring data; determining an estimated blockage probability of the aeration processing module based on the second monitoring data; and controlling the standby aeration equipment to perform cleaning and maintenance treatment on the aeration treatment module based on the estimated blockage probability. According to the system and the method, the maintenance efficiency of the aeration device can be improved.

Description

Description of the case

[0001] This application is for the application date of May 9, 2024, and the application number is 202410567082.1 , a divisional application filed by a Chinese application entitled “A maintenance system, method, device and storage medium for an aeration device”. Technical Field

[0002] The present invention relates to the field of aeration, and in particular to a self-detection and maintenance system and method for an aeration device. Background Art

[0003] Aeration devices can be used to aerate polluted water bodies. The energy consumption of aeration devices mainly comes from the energy loss of the air blower, the resistance loss of the pipeline system and the local resistance loss of the aerator. The energy loss of the air blower and the pipeline system generally changes according to the process adjustment. When the aeration device is maintained, 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 the aeration device is maintained, 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 water or sludge blockage, etc.

[0004] At present, when the aeration device needs to be repaired, upgraded or modified, it is usually necessary to temporarily stop the operation of the entire aeration device and then replace the aerators on a large scale. For example, when it is detected that there may be a situation that requires maintenance and cleaning (for example, the aerator is blocked), the entire aeration device is usually cleaned regularly or cleaned uniformly, which may lead to unnecessary maintenance costs, and the cleaning and maintenance efficiency is low. It takes a long time for the aeration device to restart to normal operation, resulting in additional time costs.

[0005] Therefore, it is hoped to provide an aeration device self-detection 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, maintenance can be achieved without stopping the machine, thereby reducing operating costs and improving maintenance efficiency. Summary of the invention

[0006] An embodiment of the present specification provides an aeration device self-detection and maintenance system, including an aeration treatment module, a gas detection module, an aeration control module, a blower, a monitoring device, an aeration pipe, a connecting pipe, a standby aeration device and a standby aeration pipe; the aeration control module includes a communication component, the connecting pipe and the 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 through the aeration pipe; the aeration treatment modules are connected through the connecting pipe; the gas detection module is communicatively connected to the monitoring device; the standby aeration device is mechanically connected to the aeration treatment module through the standby aeration pipe; the aeration treatment module, the gas detection module, the aeration control module, the blower and the electric blocking valve are all communicatively connected to the aeration control module through the communication component; the gas detection module is configured to receive information from the monitoring device; The aeration control module is configured to obtain first monitoring data from a monitoring device and transmit the first monitoring data to the aeration control module, wherein the first monitoring data includes air pressure at multiple points in an air supply duct of an aeration tank and / or dust content at the multiple points in the aeration tank, and the air pressure and the dust content are collected and obtained by the monitoring device; the aeration control module is configured to: determine a preset test area based on the smoothness of the first monitoring data, wherein the preset test area is an area where potential blockage exists; control at least one of the electric blocking valves to be closed based on the preset test area, and obtain second monitoring data from the monitoring device; the second monitoring data refers to data collected by the monitoring device after the electric blocking valve is closed by each of a plurality of closing strategies; determine an estimated blockage probability of the aeration treatment module based on the second monitoring data; and control the standby aeration equipment to perform cleaning and maintenance on the aeration treatment module based on the estimated blockage probability.

[0007] An embodiment of the present specification provides an aeration device maintenance method, the method comprising: obtaining first monitoring data, the first monitoring data comprising air pressure at multiple points in an air supply duct of an aeration tank and / or dust content at the multiple points in the aeration tank; determining a preset test area based on the smoothness of the first monitoring data, the preset test area being an area where potential blockage exists; controlling at least one electric barrier valve to close based on the preset test area, and obtaining second monitoring data; the second monitoring data refers to monitoring data collected after the electric barrier valve is closed using each of a plurality of closing strategies; determining an estimated blockage probability of an aeration treatment module based on the second monitoring data; and controlling a standby aeration device to perform cleaning and maintenance on the aeration treatment module based on the estimated blockage probability. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] This specification will be further described in the form of exemplary embodiments, which will be described in detail by the accompanying drawings. These embodiments are not restrictive, and in these embodiments, the same number represents the same structure, wherein:

[0009] Figure 1 is a schematic diagram of the structure of an aeration device maintenance system according to some embodiments of this specification;

[0010] Figure 2 is a flow chart of an aeration device maintenance method according to some embodiments of the present specification;

[0011] Figure 3 is a flow chart for generating control instructions for multiple aeration treatment modules according to some embodiments of this specification;

[0012] Figure 4 This is another flow chart for generating control instructions for multiple aeration treatment modules according to some embodiments of the present specification. DETAILED DESCRIPTION

[0013] In order to more clearly illustrate the technical solutions of the embodiments of this specification, the following is a brief introduction to the drawings required for the description of the embodiments. Obviously, the drawings described below are only some examples or embodiments of this specification. For ordinary technicians in this field, this specification can also be applied to other similar scenarios based on these drawings without creative work. Unless it is obvious from the language environment or otherwise explained, the same reference numerals in the figures represent the same structure or operation.

[0014] It should be understood that the "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 words can achieve the same purpose, the words can be replaced by other expressions.

[0015] As shown in this specification and claims, unless the context clearly indicates an exception, the words "a", "an", "an" and / or "the" do not refer to the singular and may also include the plural. Generally speaking, the terms "comprise" and "include" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0016] Flowcharts are used in this specification to illustrate the operations performed by the system according to the embodiments of this specification. It should be understood that the preceding or following operations are not necessarily performed precisely in order. Instead, the steps may be processed in reverse order or simultaneously. At the same time, other operations may also be added to these processes, or one or more operations may be removed from these processes.

[0017] Figure 1 It is a schematic diagram of the structure of the aeration device maintenance system shown in some embodiments of this specification.

[0018] 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.

[0019] In some embodiments, the aeration treatment module 2 is connected to the blower 7 through the aeration pipe 4, and the aeration treatment modules 2 are connected through the connecting pipe 3. Each of at least one connecting pipe 3 and at least one aeration pipe 4 is provided with an electric blocking valve, a monitoring device 8 is installed on the aeration pipe 4, and the gas detection module 9 is connected in communication with the monitoring device 8. The standby aeration device 10 is mechanically connected to the aeration treatment module 2 through the standby aeration pipe 5. The aeration treatment module 2, the gas detection module 9, the blower 7 and the electric blocking valve are all connected in communication with the aeration control module 6 through the communication component.

[0020] The aeration pipe 4 refers to 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.

[0021] The communication pipe 3 refers to a hollow pipe connecting the aeration treatment modules 2 .

[0022] The standby aeration device 10 is a device used to perform cleaning and maintenance operations on a blocked aeration treatment module 2 .

[0023] Through the setting of the backup aeration equipment 10, when the blocked aeration treatment module 2 needs to be cleaned and maintained, 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 maintenance.

[0024] The standby aeration pipeline 5 refers to a hollow pipeline connected between the standby aeration equipment 10 and the aeration treatment module 2 .

[0025] By setting 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, and then the blocked aeration treatment module can be ventilated with gas or cleaning liquid through the spare aeration pipe, so as to achieve 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 with all aeration treatment modules on the aeration device maintenance system.

[0026] An electric valve is a device that controls the opening and closing of a valve through an electric motor or an electromagnet. An electric barrier valve can be used to control the opening or closing of an aeration treatment module connected to the electric barrier valve, thereby adjusting the number of aeration treatment modules that need to be opened and working as needed.

[0027] The aeration treatment module 2 may be configured to perform aeration treatment on the water body based on the control instructions. In some embodiments, the aeration treatment module 2 may include a plurality of interconnected aerators. An aerator is a gas dispersion device.

[0028] Aeration treatment refers to the process in which the aeration treatment module 2 disperses the air injected by the blowing device 7 into tiny bubbles and injects them into the water body.

[0029] 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 .

[0030] The monitoring device 8 is a device for monitoring the data of the aeration tank 1. The aeration tank 1 is a water treatment device that improves water quality by increasing oxygen. In some embodiments, the monitoring device 8 may include a pressure sensor, a dust monitor, etc. The dust monitor can monitor the dust content at multiple points in the aeration tank based on technologies such as laser and ultrasonic waves.

[0031] In some embodiments, the first monitoring data may include the air pressure at multiple points in the air supply pipe of the aeration tank 1 and / or the dust content at multiple points in the aeration tank, and the air pressure at multiple points is collected and obtained by monitoring devices at multiple points. The air supply pipe may include an aeration pipe 4, a connecting pipe 3, and a spare aeration pipe 5, etc.

[0032] 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.

[0033] 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.

[0034] In some embodiments, the blowing device 7 can be configured to inject filtered air into at least one aeration treatment module 2 in an open state at a preset pressure.

[0035] The preset pressure refers to the pressure at which the preset blowing device injects air into the aeration treatment module.

[0036] In some embodiments, the preset pressure may be preset by a person skilled in the art based on experience.

[0037] In some embodiments, the preset pressure may be positively correlated with water quality parameters in the water body. The water quality parameters may include COD concentration, BOD concentration, SS concentration, etc. in the water body. For example, the greater the COD concentration, BOD concentration, and SS concentration in the water body, the greater the preset pressure may be set. The greater the COD concentration, BOD concentration, and SS concentration in the water body, the higher the preset pressure that the blower needs to generate to ensure sufficient oxygen transfer and organic matter degradation.

[0038] For more information about the aeration treatment module 2, the gas detection module 9, the aeration control module 6, the blowing device 7, the plurality of monitoring devices 8, the at least one aeration pipeline 4, the at least one connecting pipeline 3, the at least one spare aeration device 10 and the at least one spare aeration pipeline 5, please refer to Figure 2-Figure 4 Instructions in .

[0039] It should be noted that the above description of the aeration device maintenance system and its modules is only for the convenience of description and does not limit the present specification to the scope of the embodiments. It is understandable that, after understanding the principle of the system, those skilled in the art may arbitrarily combine the modules or form a subsystem to connect with other modules without deviating from the principle. In some embodiments, Figure 1 The gas detection module and aeration control module disclosed in the specification can be different modules in a system, or one module can realize the functions of two or more modules. For example, each module can share a storage module, or each module can have its own storage module. Such variations are within the scope of protection of this specification.

[0040] Figure 2 is an exemplary flow chart of an aeration device maintenance method according to some embodiments of the present specification. In some embodiments, process 200 may be executed by an aeration control module of an aeration device maintenance system. Figure 2As shown, the process 200 includes the following steps 210 to 230.

[0041] Step 210: Acquire first monitoring data through a gas detection module.

[0042] For a description of the gas detection module, see Figure 1 Instructions in .

[0043] 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, see Figure 1 See the relevant instructions in .

[0044] Air pressure refers to the pressure of gas on the inner wall of the air supply duct per unit area in the aeration tank. The air pressure at multiple points in the air supply duct of the aeration tank can reflect the gas flow in the aeration device system. For example, if the air pressure at multiple points in the air supply duct of the aeration tank fluctuates greatly, it may be that the aeration treatment module is blocked and needs to be cleaned and maintained in time.

[0045] Dust content refers to the content of suspended particles in the water of the aeration tank during the aeration process. Dust content helps to evaluate the working efficiency of the aeration device maintenance system and the water quality treatment effect. For example, the change in dust content can reflect the degradation of organic matter in the water body. For example, excessive dust content is more likely to cause clogging of the aeration treatment module, so it also needs to be cleaned and maintained in time.

[0046] 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 .

[0047] 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.

[0048] 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.

[0049] Step 220: Generate control instructions for multiple aeration treatment modules based on the first monitoring data.

[0050] For a description of the aeration treatment module, see Figure 1 See the relevant instructions in .

[0051] Control instructions are instructions for operating and managing multiple aeration treatment modules. Control instructions can ensure the normal operation and maintenance of the aeration device maintenance system.

[0052] 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.

[0053] For instructions on electric isolation valves and backup aeration equipment, see Figure 1 See the relevant instructions in .

[0054] 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.

[0055] 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 .

[0056] 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 may also use Figure 4 The method shown generates control instructions for multiple aeration treatment modules. For details, see Figure 4 Instructions in .

[0057] Step 230: Based on the control instruction, control the aeration treatment module to perform aeration treatment on the water body.

[0058] 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 instruction. For 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 control only the standby aeration device A to perform cleaning and maintenance on aeration treatment module A; then the aeration control module can open the standby aeration pipeline A corresponding to aeration treatment module A, close the aeration pipeline A corresponding to aeration treatment module A, and then pass gas or cleaning liquid into aeration treatment module A through the standby aeration pipeline A, so as to achieve cleaning and maintenance of aeration treatment module A alone, while keeping aeration treatment module B and aeration treatment module C in the open state for aeration treatment.

[0059] 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 the aeration treatment module D and control the electric barrier valve E to open, so as to open the aeration treatment module E; then the aeration control module can control the electric barrier valve D corresponding to the aeration treatment module D and the electric barrier valve E corresponding to the aeration treatment module E to open, so as to open the aeration treatment module D and the aeration treatment module E for aeration treatment, while keeping the aeration treatment module A, the aeration treatment module B and the aeration treatment module C in the open state for aeration treatment.

[0060] 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 barrier 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 blocked in a certain period of time, while the aeration treatment modules that are not blocked 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, and maintenance can be achieved without stopping the machine, thereby reducing operating costs and improving maintenance efficiency.

[0061] Figure 3 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.

[0062] Step 310: Determine a preset test area based on the stability of the first monitoring data.

[0063] 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.

[0064] 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 refers to the average value of the air pressure collected at multiple preset time points corresponding to each point. The preset time point can be preset by a technician in this field based on experience.

[0065] In some embodiments, the smaller the variance value of the air pressure is, the better the smoothness of the first monitoring data may be.

[0066] 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 a potentially blocked aeration treatment module in the aeration tank.

[0067] In some embodiments, the aeration control module may determine the grid area where the air pressure sensor points that meet a specific condition are located as the preset test area. The specific condition may be that the stability of the first monitoring data is less than the stability threshold corresponding to the corresponding air pressure sensor point.

[0068] 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 a plurality of grid areas. The point of each air pressure sensor may be located in a certain divided grid area.

[0069] The stability threshold refers to the critical value of stability, and can be preset by those skilled in the art based on experience.

[0070] In some embodiments, each grid area may have a different smoothness threshold, and the aeration treatment module may determine the smoothness threshold of the corresponding grid area based on the historical blockage times and historical cleaning frequencies of each grid area. For example, the more historical blockage times and the higher the historical cleaning frequency of a grid area, the larger the smoothness threshold corresponding to the grid area.

[0071] The historical blockage times refer to the sum of the historical blockage times of each aeration treatment module in the grid area.

[0072] The historical cleaning frequency refers to the average value of the historical cleaning frequencies of each aeration treatment module in the grid area.

[0073] 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.

[0074] In some embodiments, a greater number of historical blockages means 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.

[0075] In some embodiments, a higher historical cleaning frequency means 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.

[0076] In some embodiments of the present specification, by determining the smoothness threshold of the corresponding grid area based on the historical blockage times and historical cleaning frequencies of each grid area, the rationality and accuracy of the finally determined smoothness threshold can be improved.

[0077] 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.

[0078] For instructions on electric isolation valves, see Figure 1 See the relevant instructions in .

[0079] The second monitoring data refers to the data collected by the monitoring device after the electric blocking valve is closed using each of the multiple closing strategies. The closing strategy refers to the way to close the electric blocking valve in a preset test area. Through multiple closing strategies, the second monitoring data under multiple closing strategies can be obtained, thereby enriching the data. The data format of the second monitoring data can be similar to the first monitoring data.

[0080] In some embodiments, the second monitoring data may include all data types involved in the first monitoring data, water body temperature, dissolved oxygen content, etc.

[0081] In some embodiments, the aeration control module controls at least one electric barrier valve to close based on the preset test area, and obtains multiple sets of second monitoring data from the monitoring device in a specific implementation manner, which can be implemented by the following steps 321-322:

[0082] Step 321, based on the preset test area, control at least one electric blocking valve to close and generate a complete closing strategy.

[0083] In some embodiments, the aeration control module may use permutations and combinations of all aeration treatment modules in a preset test area to obtain combinations of all aeration treatment modules; and obtain all shutdown strategies based on the combinations of all aeration treatment modules.

[0084] 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.

[0085] For example, assuming that there are aeration treatment module x, aeration treatment module y and aeration treatment module z in the preset test area, the aeration control module can arrange and combine the aeration treatment module x, aeration treatment module y and aeration treatment module z (such as a single arrangement and combination, two-by-two arrangement and combination, three 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.

[0086] 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 the combination mode of all the aeration treatment modules as a corresponding set of closing strategies, thereby obtaining all the closing strategies.

[0087] For example, based on the combination of all aeration treatment modules obtained in the above embodiment, the corresponding all-shutdown strategy is:

[0088] ① Close aeration treatment module x; ② Close aeration treatment module y; ③ Close aeration treatment module z; ④ Close aeration treatment module x+y; ⑤ Close aeration treatment module x+z; ⑥ Close aeration treatment module y+z; ⑦ Close aeration treatment module x+y+z.

[0089] 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.

[0090] Step 330 : determining an estimated clogging probability of each aeration treatment module based on the multiple sets of second monitoring data.

[0091] The estimated blockage probability can be used to characterize the possibility of blockage in the aeration treatment module. In some embodiments, the estimated blockage probability can be represented by a value of 0 to 100%, and a larger value indicates a greater blockage probability.

[0092] In some embodiments, the specific implementation method of the aeration control module determining the estimated blockage probability of each aeration treatment module based on multiple sets of second monitoring data can be implemented by the following steps 331 to 336:

[0093] Step 331, based on multiple groups of second monitoring data, calculate the increment of the smoothness of each group of second monitoring data.

[0094] 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.

[0095] 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 with the smoothness of the air pressure corresponding to the first monitoring data.

[0096] In some embodiments, the aeration control module may calculate the stability of each group of second monitoring data based on multiple groups of second monitoring data; and use the difference between the stability of each group of second monitoring data and the stability of the first monitoring data as the increment of the stability of the corresponding group of second monitoring data.

[0097] Step 332: filter out the second monitoring data whose increment of the smoothness is negative, and use at least one group of second monitoring data remaining after the filter out as at least one group of target monitoring data.

[0098] The target monitoring data refers to the second detection data whose increment of smoothness is not negative.

[0099] Step 333 , according to the aeration processing module that is turned off 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 turned off in multiple sets of target monitoring data.

[0100] Step 334: determine the aeration processing module whose number of shutdowns is greater than a preset shutdown threshold as a potential blockage module.

[0101] The preset closing threshold refers to the critical value of the number of times the aeration treatment module is closed. In some embodiments, the preset closing threshold can be preset by those skilled in the art based on experience.

[0102] In some embodiments, the preset closing threshold may be related to a rate of change of a pressure difference across a filter assembly of the blower device.

[0103] The filter assembly refers to the filter element or filter assembly used to filter air in the blower. When air passes through the filter assembly, it will encounter resistance from the filter assembly, resulting in a pressure difference between the front and rear sides of the filter assembly.

[0104] 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.

[0105] 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.

[0106] In some embodiments, the aeration control module can obtain the pressure difference change rate of the filter assembly by calculating the difference between the pressure difference between the front and rear sides of the filter assembly at different time points and dividing it by the corresponding time interval. In some embodiments, if the pressure difference change rate of the filter assembly calculated by the aeration control module is larger, the aeration control module can determine that the resistance of the filter assembly changes faster per unit time, indicating that the blockage degree or dust accumulation of the filter assembly is more serious.

[0107] 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.

[0108] In some embodiments of the present specification, if the filter assembly has not been replaced for a long time, resulting in excessive dust accumulation, 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.

[0109] 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.

[0110] The estimated congestion probability refers to the estimated probability of congestion in a potential congestion module.

[0111] In some embodiments, the estimated jam probability may be positively correlated to the number of times the potential jam module is turned off. For example, the more times the potential jam module is turned off, the greater the estimated jam probability.

[0112] In some embodiments, the aeration control module can determine the estimated blockage probability based on the number of times the potential blockage module is closed through a preset comparison table. The preset comparison table contains a corresponding relationship between the number of times the reference potential blockage module is closed and the reference estimated blockage probability. The preset comparison can be constructed based on prior knowledge or historical data.

[0113] Step 336: After removing the potential blocking modules from the aeration tank, the estimated blocking probabilities of the remaining aeration treatment modules are all assigned to 0 or a lower preset value.

[0114] In some embodiments, after the potential blocking modules are removed 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.

[0115] In some embodiments, the aeration control module may assign an estimated blockage probability of 0 to the aeration treatment modules that are not in the preset test area among the remaining aeration treatment modules after removing the potential blockage modules in the aeration tank, and assign an estimated blockage probability of aeration treatment modules in the preset test area to a lower preset value. The preset value may be preset by those skilled in the art based on experience.

[0116] Step 340: Based on the estimated blockage probability, control at least one group of standby aeration equipment to perform cleaning and maintenance processing on at least one aeration processing module.

[0117] For instructions on alternate aeration equipment, see Figure 1 See the relevant instructions in .

[0118] For instructions on cleaning and maintenance, see Figure 2 Relevant instructions in step 220.

[0119] In some embodiments, the aeration control module can perform cleaning maintenance operations on aeration processing modules whose estimated blockage probability is greater than a preset blockage threshold through spare aeration equipment. The preset blockage threshold can be determined by those skilled in the art based on historical data or experience.

[0120] In some embodiments, the aeration control module may also generate and send an early warning message to the aeration processing module that performs the cleaning and maintenance operation.

[0121] The warning information can be one or more of sound, text, video, etc.

[0122] 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, thereby causing unstable pressure in some pipes; 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.

[0123] 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 barrier valve to close, and then determining the estimated blockage probability of each aeration treatment module through multiple groups 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 group of standby aeration equipment to perform cleaning and maintenance on at least one aeration treatment module.

[0124] 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 pressures 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; according to the multiple second monitoring data obtained from the test, an 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.

[0125] It should be noted that the above description of process 300 is only for example and illustration, and does not limit the scope of application of this specification. For those skilled in the art, various modifications and changes can be made to process 300 under the guidance of this specification. However, these modifications and changes are still within the scope of this specification.

[0126] Figure 4 is another exemplary flow chart for generating control instructions for multiple aeration processing modules according to some embodiments of the present specification. In some embodiments, process 400 may be executed by an aeration control module of an aeration device maintenance system. Figure 4 As shown, process 400 includes the following steps 410 to 460.

[0127] Step 410 : estimating 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.

[0128] In some embodiments, the first monitoring data may also include vibration data collected by vibration sensors at multiple points in the aeration tank and the air supply duct of the aeration tank.

[0129] Vibration data refers to data collected by a vibration sensor installed at a preset position in the aeration tank and its air supply duct, such as vibration frequency, etc. The preset position can be preset by those skilled in the art based on experience.

[0130] 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.

[0131] For more information about the first monitoring data, see Figure 2 Description of step 210.

[0132] For a description of the estimated probability of clogging and how to determine the estimated probability of clogging for each aeration treatment module, see Figure 3 Instructions in .

[0133] The cleaning and maintenance requirement value refers to a value of the urgency of cleaning and maintenance of the aeration treatment module estimated based on the first monitoring data.

[0134] 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.

[0135] 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.

[0136] 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.

[0137] The vector database includes a plurality of first reference feature vectors, wherein each first reference feature vector has a corresponding reference cleaning and maintenance requirement value of a reference aeration treatment module. The first reference feature vector is a feature vector constructed based on the historical first monitoring data and the historical estimated blockage probability of each historical aeration treatment module. The method for determining the reference cleaning and maintenance requirement value of the reference aeration treatment module is the same as the method for determining the label in the estimation model, and specifically see the description of the label below.

[0138] In some embodiments, the aeration control module may determine, based on the first target feature vector, a first reference feature vector that meets the target preset condition in the vector database, 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 with the first target feature vector.

[0139] In some embodiments, the aeration control module may determine the cleaning maintenance requirement value of the aeration treatment module based on the reference cleaning maintenance requirement value of the reference aeration treatment module corresponding to the determined first correlation feature vector.

[0140] In some embodiments, the aeration control module may also 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.

[0141] 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.

[0142] 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.

[0143] In some embodiments, a node of the aeration work structure diagram may correspond to an aeration processing module in the aeration tank. The attributes of the node may reflect the characteristics of the corresponding aeration processing module. For example, the attributes of the node may include: first monitoring data collected by a monitoring device on an aeration pipeline directly connected to the aeration processing module, an estimated blockage probability of the aeration processing module, etc.

[0144] In some embodiments, the node attributes in the aeration work structure diagram may also 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.

[0145] Water quality parameters refer to various parameter data related to the water quality in the water body. For example, water quality parameters may include indicators such as Chemical Oxygen Demand (COD), Biochemical Oxygen Demand (BOD), Suspended Solids (SS), and nitrogen and phosphorus removal rates.

[0146] 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, determine SS by membrane filter method, laser particle size analyzer, etc.

[0147] The water quality parameter change rate refers to the change in water quality parameters within a preset time period (for example, the last week).

[0148] In some embodiments, the aeration control module may use the following first formula to determine the rate of change of the water quality parameter:

[0149] 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;

[0150] In some embodiments, the aeration control module can count the COD concentration differences at multiple adjacent continuous moments, and then calculate the average of the multiple COD concentration differences to obtain the mean change of COD concentration. The multiple adjacent continuous moments can be preset by those skilled in the art based on experience.

[0151] The calculation methods of 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 the mean change of COD concentration. Please refer to the above description for details.

[0152] In some embodiments of the present specification, since the more frequent the change rate of water quality parameters is, the more volatile the water quality parameters are, the more complex the water quality is, which may mean that the aeration treatment module is performing poorly in this area and requires priority maintenance and cleaning. 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 determining the maintenance order in combination with the water quality parameter change rate, it is possible to prioritize the maintenance and cleaning of aeration treatment modules with complex water quality.

[0153] In some embodiments, the node attributes in the aeration work structure diagram may also include the bubble diameter distribution at multiple preset times in the grid area where the aeration treatment module corresponding to the node is located. The multiple preset times 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.

[0154] Bubbles refer to the bubbles generated in the grid area where the aeration treatment module corresponding to the node is located.

[0155] The bubble diameter refers to the diameter of the bubble.

[0156] The bubble diameter distribution refers to the number of bubbles under each bubble diameter obtained by statistics at a preset time in the grid area where the aeration treatment module corresponding to the node is located. For example, the statistical results of the bubble diameter distribution in a grid area at a preset time t1 can be expressed as the following table:

[0157] In some embodiments, the aeration control module can obtain images of the aeration tank based on a camera device, obtain bubbles in the images taken at multiple consecutive preset moments through image recognition, determine the number of pixels occupied by each bubble based on the bubble (e.g., 100 pixels = 0.33 inches, etc.), and calculate the bubble diameter of each bubble, and obtain the distribution of bubble diameters at multiple consecutive preset moments based on the bubble diameter of each bubble. The image recognition method can include a neural network algorithm, a decision tree algorithm, etc.

[0158] 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 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 requirement value.

[0159] In some embodiments, an edge of the aeration work structure diagram may correspond to an air supply duct actually connected between aeration processing modules. The attributes of the edge may reflect the characteristics of the air supply duct actually connected between the corresponding aeration processing modules. For example, the attributes of the edge may include: the length of the air supply duct, etc.

[0160] 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.

[0161] In some embodiments, the estimation model can be obtained through training based on a plurality of labeled training samples.

[0162] 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 an aeration processing module in a historical sample aeration tank and its corresponding air supply duct.

[0163] In some embodiments, the aeration control module may construct a historical sample aeration working 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 working structure diagram may be determined based on historical data.

[0164] In some embodiments, the label may be an actual cleaning and maintenance demand value corresponding to the aeration processing module of each node in the historical sample aeration work structure diagram.

[0165] Labels can be determined through manual annotation.

[0166] In some embodiments, the aeration control module can obtain the actual historical moment when each aeration treatment module actually failed or was blocked in the history of the aeration device maintenance system and the historical moment when the historical sample aeration work structure diagram was constructed according to the historical sample aeration work structure diagram; calculate the difference between the actual historical moment when the failure or blockage actually occurred in the history and the historical moment when the historical sample was constructed; determine the cleaning and maintenance requirement value of the aeration treatment module based on the difference; and use the cleaning and maintenance requirement value of the aeration treatment module as the label value. In some implementations, the smaller the difference, the larger the label value can be preset.

[0167] For example, a historical sample aeration working structure diagram is constructed by data at historical time t1, and the historical sample aeration working structure diagram includes an aeration treatment module A. The label value of the aeration treatment module A in the historical sample aeration working structure diagram may be negatively correlated to the difference between historical time t2 and historical time t1 when the aeration treatment module A fails or is actually blocked.

[0168] In some embodiments of the present specification, by constructing an aeration working structure diagram based on the first monitoring data, inputting an estimation model, and determining the cleaning and maintenance requirement value of the aeration treatment module, the cleaning and maintenance requirement value can be determined quickly and accurately.

[0169] Step 420: determine the aeration treatment modules whose cleaning maintenance requirement values ​​are greater than a first preset threshold as target cleaning objects.

[0170] The first preset threshold refers to a critical value of the cleaning maintenance requirement value.

[0171] 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.

[0172] In some embodiments, the aeration control module can calculate, based on historical data, when the cleaning and maintenance demand value is large enough, the aeration treatment module needs to be cleaned immediately, otherwise, the normal operation of the aeration treatment module will be affected, and the cleaning and maintenance demand value at this time is the historical preset threshold. In some embodiments, the aeration control module may have multiple situations in the historical data where the aeration treatment module needs to be cleaned immediately, and the aeration control module may have multiple historical preset thresholds.

[0173] In some embodiments, the weighted weight may 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 sequence according to each group of closing strategies in all closing strategies, 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 a description of the closing strategy, please refer to Figure 3 Description of step 320.

[0174] 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.

[0175] As an example only, the first preset threshold may be calculated using the following second formula:

[0176] The first preset threshold value = k1*mean of multiple historical preset threshold values+k2*standard deviation of multiple historical preset threshold values, wherein 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 greater k1 (the maximum value of k1 is 1) and the smaller k2 (the minimum value of k2 is 0).

[0177] 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 group 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 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 Pearson coefficient P(x) as a number between [-1,1]; the closer the absolute value of Pearson coefficient P(x) is to 1, the more relevant it is, the greater the consistency of 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).

[0178] 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 weights with the degree of consistency of the water quality parameters measured before and after closing the electric barrier valve, the corresponding weights are adjusted to reflect the importance of the water quality parameters 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.

[0179] The target cleaning object refers to the aeration treatment module that needs to perform cleaning and maintenance treatment.

[0180] In some embodiments, the aeration control module may directly determine the aeration treatment modules whose cleaning maintenance requirement values ​​are greater than a first preset threshold as target cleaning objects.

[0181] Step 430, performing cleaning and maintenance processing on the target cleaning object.

[0182] In some embodiments, the aeration control module can control the standby aeration equipment corresponding to the target cleaning object to perform cleaning maintenance processing on the target cleaning object. For a description of the cleaning maintenance processing, see Figure 2 Description of step 220.

[0183] In some embodiments, the method for generating control instructions for a plurality of aeration treatment modules may further include the following steps 440 to 460 .

[0184] Step 440: determine the aeration treatment modules whose cleaning maintenance requirement values ​​are greater than the second preset threshold and less than the first preset threshold as queued cleaning objects.

[0185] The second preset threshold refers to another critical value of the cleaning maintenance requirement value that is different from the first preset threshold. The second preset threshold may be smaller than the first preset threshold.

[0186] In some embodiments, the second preset threshold is associated with the change of 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 please refer to the description in the above step 420 for details.

[0187] The objects in the queue for cleaning refer to the aeration treatment modules in the aeration tank that need cleaning and maintenance but are not urgent. The cleaning and maintenance requirements of the objects in the queue for cleaning are lower than those of the target cleaning objects, and they can be slightly delayed, but they still need to be maintained and cleaned at the appropriate time to ensure the long-term stable operation of the aeration device maintenance system.

[0188] 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 queued cleaning object.

[0189] Step 450 : determining the cleaning and maintenance order of each of the queued cleaning objects based on the cleaning and maintenance demand values ​​and aeration importance of the queued cleaning objects.

[0190] Aeration importance refers to the degree of influence of the location of the aeration treatment module in the aeration device maintenance system on the entire aeration device maintenance system. For example, the aeration treatment module located in the center of the entire aeration tank may be more important than the aeration treatment module at the edge.

[0191] In some embodiments, the importance of aeration can be measured by a value between 0 and 100%, and the closer to 100%, the more important it is.

[0192] In some embodiments, the aeration control module can obtain the position of the queued cleaning object in the aeration tank through a sensor installed on the aeration treatment module, and determine the importance of the queued cleaning object based on the position of the queued cleaning object in the aeration tank. For example, if the queued cleaning object includes an aeration treatment module located in the central area of ​​the entire aeration tank and an aeration treatment module located in the edge area of ​​the entire aeration tank, since the aeration treatment module located in the central area of ​​the entire aeration tank may be more important than the module at the edge position, the importance of the aeration treatment module located in the central area of ​​the entire aeration tank can be preset to 100%, and the importance of the aeration treatment module located in the edge area of ​​the entire aeration tank can be preset to 10%.

[0193] In some embodiments, the aeration control module may also determine the aeration importance of each cleaning object in the queue through a preset algorithm based on the real-time value of the water quality parameter of each cleaning object in the queue before and after cleaning and maintenance, and the number of cleanings of the cleaning object in the queue.

[0194] The real-time value of a water quality parameter refers to the value of the water quality parameter obtained by real-time measurement.

[0195] The cleaning times of a queued cleaning object refers to the number of cleaning times that have been executed for the queued cleaning object.

[0196] Just as an example, the preset algorithm may be the following third formula:

[0197] 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 queued cleaning objects; 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.

[0198] In some embodiments, the selected reference water quality parameters may include BOD, COD and SS, then N=3.

[0199] In some embodiments, the weight k j It can be negatively correlated with the time of a certain cleaning object in the queue for the jth cleaning. 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.

[0200] 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, and the number of cleanings of the queued cleaning object.

[0201] The cleaning and maintenance sequence refers to the order or sequence of cleaning and maintenance treatments of the aeration treatment modules in the queue for cleaning.

[0202] In some embodiments, the aeration control module can determine the 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.

[0203] 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 can be preset.

[0204] As an example only, the aeration control module may use the following fourth formula to determine the comprehensive value of each queued cleaning object:

[0205] The comprehensive value Si of each queued cleaning object = Vi × Wi, where Wi is greater than 0 and less than 1, and Vi is the cleaning maintenance requirement value of each queued cleaning object.

[0206] In some embodiments, the aeration control module can sort the comprehensive value of each queued cleaning object from high to low, and the queued cleaning object with a higher score will be cleaned and maintained in the front. If the scores are the same, they can also be sorted or processed according to other factors (for example, if the scores are the same, the higher the importance of aeration, the earlier the cleaning and maintenance will be performed), so as to determine the cleaning and maintenance order of each queued cleaning object.

[0207] Step 460, based on the cleaning and maintenance order, cleaning and maintenance processing is performed on the queued cleaning objects.

[0208] 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.

[0209] 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.

[0210] In the process of determining the cleaning and maintenance order of each queued cleaning object, the cleaning and maintenance demand value of the queued cleaning object 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 queued cleaning object and ensure the normal operation of the aeration device maintenance system.

[0211] The basic concepts have been described above. Obviously, for those skilled in the art, the above detailed disclosure is only for example and does not constitute a limitation of this specification. Although not explicitly stated here, those skilled in the art may make various modifications, improvements and corrections to this specification. Such modifications, improvements and corrections are suggested in this specification, so such modifications, improvements and corrections still belong to the spirit and scope of the exemplary embodiments of this specification.

[0212] At the same time, this specification uses specific words to describe the embodiments of this specification. For example, "one embodiment", "an embodiment", and / or "some embodiments" refer to a certain feature, structure or characteristic related to at least one embodiment of this specification. Therefore, it should be emphasized and noted that "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more in different positions in this specification does not necessarily refer to the same embodiment. In addition, certain features, structures or characteristics in one or more embodiments of this specification can be appropriately combined.

[0213] In addition, unless explicitly stated in the claims, the order of the processing elements and sequences described in this specification, the use of alphanumeric characters, or the use of other names are not intended to limit the order of the processes and methods of this specification. Although the above disclosure discusses some invention embodiments that are currently considered useful through various examples, it should be understood that such details are only for illustrative purposes, and the attached 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 essence 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.

[0214] Similarly, it should be noted that in order to simplify the description disclosed in this specification and thus help understand one or more embodiments of the invention, in the above description of the embodiments of this specification, multiple features are sometimes combined into one embodiment, figure or description thereof. However, this disclosure method does not mean that the features required by the subject matter of this specification are more than the features mentioned in the claims. In fact, the features of the embodiments are less than all the features of the single embodiment disclosed above.

[0215] In some embodiments, numbers describing the number of components and attributes are used. 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 specified, "about", "approximately" or "substantially" indicate that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may change according to the required features 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 setting of such numerical values ​​is as accurate as possible within the feasible range.

[0216] Each patent, patent application, patent application publication, and other materials, such as articles, books, specifications, publications, documents, etc., cited in this specification are hereby incorporated by reference in their entirety. Except for application history documents that are inconsistent with or conflicting with the contents of this specification, documents that limit the broadest scope of the claims of this specification (currently or later attached to this specification) are also excluded. It should be noted that if the descriptions, definitions, and / or use of terms in the materials attached to this specification are inconsistent or conflicting with the contents described in this specification, the descriptions, definitions, and / or use of terms in this specification shall prevail.

[0217] Finally, it should be understood that the embodiments described in this specification are only used to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, as an example and not a 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 introduced and described in this specification.

Claims

1. A self-detection and maintenance system for an aeration device, characterized in that: It includes an aeration treatment module, a gas detection module, an aeration control module, a blasting device, a monitoring device, an aeration pipeline, a connecting pipeline, a standby aeration device and a standby aeration pipeline; The aeration control module includes a communication component, the communication pipe and the aeration pipe are both provided with electric blocking valves, and the monitoring device is installed on the aeration pipe; The aeration processing module is connected to the blast device through the aeration pipeline; the aeration processing modules are connected to each other through the communication pipeline; the gas detection module is communicatively connected to the monitoring device; the standby aeration equipment is mechanically connected to the aeration processing module through the standby aeration pipeline; The aeration processing module, the gas detection module, the aeration control module, the air blowing device and the electric blocking valve are all 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 the first monitoring 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 the multiple points in the aeration tank, and the air pressure and the dust content are collected and obtained by the monitoring device; The aeration control module is configured to: Determine a preset test area based on the stability of the first monitoring data, where the preset test area is an area with potential blockage; Based on the preset test area, at least one of the electric blocking valves is controlled to be closed, and second monitoring data is obtained from the monitoring device; the second monitoring data refers to data collected by the monitoring device after the electric blocking valve is closed by each of the multiple closing strategies; determining an estimated clogging probability of the aeration treatment module based on the second monitoring data; Based on the estimated blockage probability, the standby aeration equipment is controlled to perform cleaning and maintenance processing on the aeration processing module.

2. The system according to claim 1, characterized in that The aeration control module is further configured to: Based on multiple groups of the second monitoring data, calculating an increment of the stability of each group of the second monitoring data; Screening out multiple groups of the second monitoring data based on a preset screening condition to obtain at least one group of target monitoring data, wherein the preset screening condition is related to the 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 in the at least one set of target monitoring data is shut down; Based on the preset blocking conditions, determining the potential blocking module; The preset blocking condition is related to the number of times the aeration treatment module is 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 The estimated blockage probability of the aeration treatment modules in the aeration tank, except the potential blockage modules, is assigned a preset value.

3. The system according to claim 2, characterized in that The preset blocking condition includes a number of times being closed being greater than a preset closing threshold, and the preset closing threshold is related to a pressure difference change rate of a filter assembly of the blowing device.

4. The system according to claim 1, characterized in that The aeration control module is further configured to: determine a grid area where air pressure sensor points that meet specific conditions are located as the preset test area, wherein the specific conditions include that the stability of the first monitoring data is less than a stability threshold corresponding to the corresponding air pressure sensor point.

5. The system according to claim 4, characterized in that Different grid areas have different stability thresholds; The aeration treatment module is configured to determine the stability threshold corresponding to the grid area based on the historical blockage times and historical cleaning frequency of the grid area.

6. The system according to claim 1, characterized in that The aeration control module is further configured to: Based on the control instruction, the aeration treatment module is controlled 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 aeration treatment module, and / or controlling at least one group of the standby aeration equipment to perform cleaning and maintenance treatment on the at least one aeration treatment module; The blowing device is configured to inject filtered air at a preset pressure into at least one of the aeration treatment modules that is in an open state.

7. The system according to claim 1, characterized in that 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 is further configured to: estimating a 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, wherein the cleaning and maintenance requirement value reflects the urgency of cleaning and maintenance of the aeration treatment module; Determine the aeration treatment module whose cleaning maintenance requirement value is greater than a first preset threshold as a target cleaning object; The target cleaning object is cleaned and maintained.

8. The system according to claim 7, characterized in that 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.

9. A self-detection and maintenance method for an aeration device, characterized in that: The aeration device self-detection and maintenance system according to claim 1 is performed, and the method comprises: Acquiring first monitoring data, wherein the first monitoring data includes air pressure at multiple points in an air supply duct of an aeration tank and / or dust content at the multiple points in the aeration tank; Determine a preset test area based on the stability of the first monitoring data, where the preset test area is an area with potential blockage; Based on the preset test area, at least one electric blocking valve is controlled to be closed, and second monitoring data is obtained; the second monitoring data refers to the monitoring data collected after the electric blocking valve is closed using each of the multiple closing strategies; determining an estimated clogging probability of the aeration treatment module based on the second monitoring data; Based on the estimated clogging probability, the standby aeration equipment is controlled to perform cleaning and maintenance processing on the aeration processing module.

Images