A membrane separation component intelligent maintenance system and method

Abstract

The embodiment of the present specification provides a membrane separation component intelligent maintenance system and method, the method is executed based on the membrane separation component intelligent maintenance system, the system comprises a membrane separation component and a remote server, the membrane separation component comprises a membrane, a shell, an automatic cleaning module, an automatic replacement module, a chemical property sensor, a physical property sensor and a microprocessor. The method comprises: based on the microprocessor, acquiring chemical property parameters and physical property parameters through the chemical property sensor and the physical property sensor respectively, and sending the parameters to the remote server; based on the chemical property parameters and the physical property parameters, determining a membrane cleaning cycle generation instruction or a replacement cycle generation instruction through the remote server; and based on the microprocessor, controlling the automatic cleaning module or the automatic replacement module to execute membrane cleaning or membrane replacement according to the membrane cleaning cycle generation instruction or the replacement cycle generation instruction.

Description

Technical Field

[0001] This specification relates to the field of wastewater treatment equipment technology, and in particular to an intelligent maintenance system and method for membrane separation components. Background Technology

[0002] Wastewater treatment is an important project for sustainable development. Membrane separation technology can effectively remove organic matter, color, hardness, and most ions from wastewater, enabling the reuse of industrial water. This not only reduces wastewater discharge but also conserves water resources. However, with repeated use, membrane separation components accumulate a large amount of fouling. This fouling not only affects the efficiency of membrane separation but also shortens the lifespan of the membrane separation components.

[0003] Therefore, it is necessary to provide an intelligent maintenance system and method for membrane separation components, which can ensure the separation performance of the filter membrane and reduce the probability of membrane separation component failure by regularly cleaning or replacing the filter membrane in the membrane separation component. Summary of the Invention

[0004] This specification provides one or more embodiments of an intelligent maintenance system for a membrane separation component. The system includes a membrane separation component and a remote server. The membrane separation component includes a membrane, a housing, an automatic cleaning module, an automatic replacement module, a chemical property sensor, a physical property sensor, and a microprocessor. The membrane is disposed within the housing. The automatic cleaning module, the automatic replacement module, and the microprocessor are all mounted on the housing. The chemical property sensor and the physical property sensor are respectively located on opposite sides of the membrane. The automatic cleaning module is configured to clean the membrane separation component; the automatic replacement module is configured to replace the membrane separation component; the chemical property sensor is configured to detect chemical property parameters of the solutions on both sides of the membrane; the physical property sensor is configured to detect physical property parameters of the solutions on both sides of the membrane; the microprocessor is configured to: record the operating parameters of the membrane separation component; acquire the chemical property parameters and the physical property parameters based on the chemical property sensor and the physical property sensor, respectively; and acquire a membrane cleaning cycle generation command or a replacement cycle generation command from the remote server, and control the automatic cleaning module or the automatic replacement module to perform membrane cleaning or membrane replacement.

[0005] This specification provides one or more embodiments of an intelligent maintenance method for a membrane separation component. The method is executed based on an intelligent maintenance system for the membrane separation component. The system includes a membrane separation component and a remote server. The membrane separation component includes a membrane, a housing, an automatic cleaning module, an automatic replacement module, a chemical property sensor, a physical property sensor, and a microprocessor. The method includes: acquiring chemical characteristic parameters and physical characteristic parameters respectively through the chemical characteristic sensor and the physical characteristic sensor, based on the microprocessor, and sending them to the remote server; determining a membrane cleaning cycle generation instruction or a membrane replacement cycle generation instruction through the remote server based on the chemical characteristic parameters and the physical characteristic parameters, including: acquiring membrane characteristic parameters and expected filtration effect; determining filtration quality based on the chemical characteristic parameters, the physical characteristic parameters, the membrane characteristic parameters, and the historical operating parameter sequence of the membrane separation component; determining the membrane cleaning cycle or replacement cycle based on the chemical characteristic parameters, the physical characteristic parameters, the filtration quality, and the expected filtration effect, and generating the membrane cleaning cycle generation instruction or the membrane replacement cycle generation instruction; and controlling the automatic cleaning module or the automatic replacement module to perform membrane cleaning or membrane replacement based on the microprocessor and the membrane cleaning cycle generation instruction or the membrane replacement cycle generation instruction. Attached Figure Description

[0006] This specification will be further described by way of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting; in these embodiments, the same reference numerals denote the same structures, wherein:

[0007] Figure 1 This is a schematic diagram of the structure of an intelligent maintenance system for membrane separation components according to some embodiments of this specification;

[0008] Figure 2 This is an exemplary flowchart of an intelligent maintenance method for membrane separation components according to some embodiments of this specification;

[0009] Figure 3 This is an exemplary schematic diagram illustrating the determination of filtration quality according to some embodiments of this specification;

[0010] Figure 4 This is an exemplary schematic diagram illustrating the determination of filtration quality according to other embodiments of this specification;

[0011] Figure 5 This is an exemplary schematic diagram illustrating the determination of cleaning or replacement cycles according to some embodiments of this specification. Detailed Implementation

[0012] The accompanying drawings used in the description of the embodiments will be briefly introduced below. The drawings do not represent all embodiments.

[0013] The terms “system,” “device,” “unit,” and / or “module” as used herein are one method of distinguishing different components, elements, parts, sections, or assemblies at different levels. However, if other terms can achieve the same purpose, they may be replaced by other expressions.

[0014] As indicated in this specification and claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" do not specifically refer to the singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of expressly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0015] Flowcharts are used in this specification to illustrate the operations performed by the system according to embodiments of this specification. It should be understood that the preceding or following operations are not necessarily performed in exact order. Instead, the steps can be processed in reverse order or simultaneously. Furthermore, other operations can be added to these processes, or one or more steps can be removed from them.

[0016] Figure 1 This is a structural schematic diagram of an intelligent maintenance system for membrane separation components according to some embodiments of this specification.

[0017] In some embodiments, the intelligent maintenance system 100 for membrane separation components includes a membrane separation component and a remote server. For example... Figure 1 As shown, the membrane separation component may include a membrane (not shown), a housing 110, an automatic cleaning module 120, an automatic replacement module 130, a chemical property sensor 140, a physical property sensor 150, and a microprocessor (not shown).

[0018] In some embodiments, the membrane is inserted into the housing 110, the automatic cleaning module 120, the automatic replacement module 130 and the microprocessor are all disposed on the housing 110, and the chemical property sensor 140 and the physical property sensor 150 are respectively disposed on both sides of the membrane.

[0019] A membrane is a medium that has separation properties. For example, membranes can include ultrafiltration membranes, microfiltration membranes, reverse osmosis membranes, etc. In some embodiments, membranes can be used to separate solutions (such as wastewater) to obtain filtered filtrate.

[0020] In some embodiments, the membrane is inserted into the housing 110 for separating solutions. As an example only, the housing 110 may have openings on its front and rear sides, through which the membrane can be inserted into the housing 110. Both ends of the membrane are connected to the automatic replacement module 130. When the automatic replacement module 130 is operating, the membrane can, under the action of the automatic replacement module 130, move along a path perpendicular to the... Figure 1 The membrane is moved in the X direction to replace it.

[0021] In some embodiments, a seal may be provided between the membrane and the housing 110 to prevent leakage of the solution inside the housing 110, thereby ensuring the reliability of the membrane separation process. In some embodiments, the seal may be made of a corrosion-resistant material, such as rubber, polytetrafluoroethylene, etc. In some embodiments, the shape of the seal may match the shape of the openings on the front and rear sides of the housing 110 to ensure effective sealing performance.

[0022] Housing 110 refers to the structure used for mounting and securing other modules or devices for the membrane separation component. In some embodiments, housing 110 may be made of engineered materials, such as stainless steel, plastic, etc.

[0023] In some embodiments, the housing 110 can be a cavity structure, with an inlet and an outlet respectively provided on the left and right sides of the housing 110, and a membrane passing through the interior of the housing 110. For example... Figure 1 As shown, the solution (such as sewage) enters the housing 110 from the inlet and flows along... Figure 1 As shown, the solution flows in the X direction and passes through the membrane before exiting from the outlet. During this process, the membrane can separate the solution to obtain the filtered filtrate. Understandably, both the inlet and outlet of the housing 110 are equipped with seals to ensure the sealing requirements during the membrane separation process.

[0024] In some embodiments, the automatic cleaning module 120, the automatic replacement module 130, and the microprocessor are all disposed on the housing 110, and the chemical property sensor 140 and the physical property sensor 150 are respectively disposed on both sides of the membrane. As an example only, the automatic cleaning module 120 can be disposed at the outlet of the housing 110, and the automatic replacement module 130 can be disposed on the front and rear sides of the housing 110. The sensitive element of the chemical property sensor 140 can be disposed inside the housing 110 to facilitate a chemical reaction between the sensitive element and the solution inside the housing 110; the remaining structure of the chemical property sensor 140 is disposed on the surface of the housing 110. The sensitive element of the physical property sensor 150 can be disposed inside the housing 110 to detect changes in physical property parameters inside the housing 110; a portion of the structure of the physical property sensor 150 is disposed on the surface of the housing 110. Understandably, sealing elements are provided between the chemical property sensor 140, the physical property sensor 150, and the housing 110 to ensure the sealing of the membrane separation components.

[0025] The automatic cleaning module 120 refers to a module used for cleaning the membrane separation components. In some embodiments, the automatic cleaning module 120 may include an ultrasonic cleaning device and a chemical cleaning device.

[0026] An ultrasonic cleaning device is a device or apparatus that uses microbubbles generated by high-frequency sound waves to clean membranes. In some embodiments, an ultrasonic cleaning device may include an ultrasonic generator, a quartz transducer, a reactor, etc. By way of example only, an ultrasonic cleaning device may use an ultrasonic generator to generate mechanical vibrations, use a quartz transducer to convert the mechanical vibrations into ultrasonic waves, and use a reactor to bring the membrane into full contact with the cleaning solution, thereby forming microbubbles to remove dirt from the membrane surface.

[0027] A chemical cleaning apparatus refers to a device or apparatus that uses chemical agents to clean membranes. In some embodiments, the chemical cleaning apparatus may use chemical agents to react chemically with dirt on the membrane surface, thereby dissolving or decomposing the dirt to further clean the membrane.

[0028] like Figure 1 As shown, the automatic cleaning module 120 can be disposed on the right side of the housing 110. In some embodiments, the automatic cleaning module 120 and the housing 110 are provided with infusion pipes and drainage pipes.

[0029] In some embodiments, the automatic cleaning module 120 may, in response to relevant instructions from the microprocessor (such as instructions for generating membrane cleaning cycles), first deliver cleaning fluid (such as water) to the interior of the housing 110 through an infusion pipeline, and then invoke the ultrasonic cleaning device to perform membrane cleaning operations. In some embodiments, the automatic cleaning module 120 may, in response to instructions from the microprocessor, first deliver chemical agents to the interior of the housing 110 through an infusion pipeline, and then invoke the chemical cleaning device to perform membrane cleaning operations. It is understood that the ultrasonic cleaning device and the chemical cleaning device may also perform membrane cleaning operations simultaneously. In some embodiments, after cleaning is completed, the automatic cleaning module 120 may discharge wastewater through a drain pipeline to maintain the cleanliness of the interior of the housing 110.

[0030] The automatic replacement module 130 refers to a module used for replacing membrane separation components. In some embodiments, the automatic replacement module 130 may include a left winding reel, a left drive unit, a right winding reel, a right drive unit, and a support.

[0031] In some embodiments, the support can be used to support other devices or structures. The left winding reel can be used to wind the old film, while the right winding reel is wound with the new film. The left drive unit can drive the left winding reel to rotate, and the right drive unit can drive the right winding reel to rotate in the same direction. Understandably, the automatic changing module 130 may also include only the left drive unit, with the right winding reel rotating to move the film via the rotation of the left drive unit, thereby generating a following motion (i.e., rotating in the same direction as the left drive unit).

[0032] In some embodiments, the microprocessor can control the automatic replacement module 130 to replace the membrane in the membrane separation component. As an example only, when membrane replacement is required, the left drive unit rotates the left winding disc to wind the old membrane into the left winding disc, while the right drive unit rotates the right winding disc in the same direction to release the new membrane. Once the old membrane is completely pulled out of the housing 110 (i.e., after membrane replacement is complete), both the left and right drive units stop operating simultaneously.

[0033] In some embodiments, the microprocessor can determine whether membrane replacement is complete based on the rotational speeds of the left and right drive units and the inner diameter of the housing 110 (i.e., the length of the inner membrane). For example, the microprocessor can achieve precise control of the membrane replacement operation performed by the automatic replacement module 130 by controlling the rotational speeds and rotation times of the left and right drive units. Understandably, the automatic replacement module 130 may also include a speed sensor to detect and provide feedback on the rotational speeds of the left and right drive units in real time, thereby enabling the microprocessor to achieve closed-loop control of the automatic replacement module 130, further improving control accuracy and effectiveness.

[0034] The chemical property sensor 140 refers to a sensing device or apparatus used to detect the chemical property parameters of the solutions on both sides of a membrane. The chemical property parameters are parameters describing the chemical properties or concentration of a substance. In some embodiments, the chemical property parameters may include pH value, concentration, conductivity, dissolved oxygen, acidity / alkalinity, etc.

[0035] In some embodiments, the chemical property sensor 140 includes a plurality of chemical property sensing units, which are distributed at a first distance on both sides of the membrane.

[0036] The chemical property sensing unit is a component of the chemical property sensor 140. In some embodiments, the multiple chemical property sensing units may include various types of sensors, such as pH sensors, concentration sensors, conductivity sensors, dissolved oxygen sensors, and acid-base sensors. Understandably, various types of chemical property parameters can be obtained through multiple types of sensors.

[0037] The first distance distribution refers to the vector / matrix formed by the distances between two chemical property sensing units among multiple chemical property sensing units. In some embodiments, the first distance distribution can be represented by an adjacency matrix. For an explanation of how to determine the first distance distribution, please refer to [link to documentation]. Figure 2 And its related descriptions.

[0038] In some embodiments of this specification, a chemical characteristic sensor is used to detect the chemical characteristic parameters of the solutions on both sides of the membrane during membrane separation, providing a data basis for subsequently determining the membrane cleaning or replacement cycle. Furthermore, the chemical characteristic sensor includes multiple chemical characteristic sensing units, ensuring the richness and accuracy of the detected chemical characteristic parameters. The multiple chemical characteristic sensing units are distributed at a first distance on both sides of the membrane, enabling the acquisition of data over a wider area on both sides of the membrane, thereby making the chemical characteristic parameters more representative.

[0039] The physical property sensor 150 refers to a sensing device or equipment for the physical property parameters of the solutions on both sides of a membrane. Here, physical property parameters refer to parameters related to the physical properties of a substance. In some embodiments, physical property parameters may include temperature, pressure, flow rate, etc.

[0040] In some embodiments, the physical property sensor 150 includes a plurality of physical property sensing units, which are distributed at a second distance on both sides of the membrane.

[0041] The physical characteristic sensing unit is a component of the physical characteristic sensor 150. In some embodiments, the multiple physical characteristic sensing units may include various different types of sensors for detecting different types of physical characteristic parameters. For example, pressure sensors, temperature sensors, flow sensors, etc.

[0042] The second distance distribution refers to the vector / matrix formed by the distances between two physical characteristic sensing units among multiple physical characteristic sensing units. In some embodiments, the second distance distribution can be represented by an adjacency matrix. For an explanation of how to determine the second distance distribution, please refer to [link to documentation]. Figure 2 And its related descriptions.

[0043] In some embodiments of this specification, by setting up physical property sensors to detect the physical property parameters of the solutions on both sides of the membrane during membrane separation, a data basis can be provided for subsequently determining the membrane cleaning cycle or replacement cycle. Furthermore, the physical property sensors include multiple physical property sensing units, ensuring the richness and accuracy of the detected physical property parameters. The multiple physical property sensing units are distributed at a second distance on both sides of the membrane, enabling the collection of data over a wider area on both sides of the membrane, thereby making the physical property parameters more representative.

[0044] A microprocessor can process data and / or information obtained from system components or other devices. Based on this data, information, and / or processing results, the processor can execute program instructions to perform one or more functions described in this application. In some embodiments, a microprocessor may include one or more sub-processing devices (e.g., a single-core processing device or a multi-core multi-chip processing device). By way of example only, a microprocessor may include a central processing unit (CPU), a programmable logic device (PLD), a controller, a microprocessor unit, or any combination thereof.

[0045] In some embodiments, the microprocessor may be configured to: record the operating parameters of the membrane separation component; acquire chemical characteristic parameters and physical characteristic parameters based on the chemical characteristic sensor 140 and the physical characteristic sensor 150, respectively; and acquire membrane cleaning cycle generation instructions or replacement cycle generation instructions from a remote server, and control the automatic cleaning module 120 or the automatic replacement module 130 to perform membrane cleaning or membrane replacement.

[0046] The operating parameters of a membrane separation unit refer to the parameters related to its operation. For example, the operating parameters of a membrane separation unit may include the membrane's operating mode (such as full-process filtration or cross-flow filtration) and the unit's operating parameters (such as the solution flow rate, solute concentration and type, suspended solids concentration, etc.).

[0047] In some embodiments, the operating parameters of the membrane separation component can be obtained based on user input. In some embodiments, the microprocessor may include a memory capable of recording and storing the operating parameters, chemical property parameters, physical property parameters, and instructions derived from a remote processor of the membrane separation component.

[0048] In some embodiments, after the chemical property sensor 140 and the physical property sensor 150 respectively collect chemical property parameters and physical property parameters, they can be transmitted to the microprocessor via the communication device 160, thereby enabling the microprocessor to acquire the chemical property parameters and physical property parameters. For a detailed description of the communication device 160, please refer to [link to relevant documentation]. Figure 1 The relevant descriptions will follow later.

[0049] In some embodiments, the microprocessor can receive membrane cleaning cycle generation instructions or replacement cycle generation instructions sent by a remote server via the communication device 160. After receiving the membrane cleaning cycle generation instructions or replacement cycle generation instructions, the microprocessor can send them to the automatic cleaning module 120 or the automatic replacement module 130 via the communication device 160, so that the automatic cleaning module 120 periodically performs membrane cleaning operations or the automatic replacement module 130 periodically performs membrane replacement operations.

[0050] In some embodiments, such as Figure 1 As shown, the membrane separation component may further include a communication device 160. The communication device 160 is disposed on the housing 110. In some embodiments, the communication device 160 is configured to communicate with a microprocessor, an automatic cleaning module 120, an automatic replacement module 130, a chemical property sensor 140, a physical property sensor 150, and a remote server.

[0051] The communication device 160 can connect to the various components of the intelligent maintenance system for membrane separation components to enable data and / or information transmission between these components. For example, the communication device 160 can send chemical characteristic parameters detected by the chemical characteristic sensor 140 to the microprocessor. As another example, the communication device 160 can transmit membrane cleaning cycle generation instructions or replacement cycle generation instructions generated by a remote server to the microprocessor.

[0052] In some embodiments, the communication device 160 can be any one or more of a wired network or a wireless network. For example, the communication device 160 may include a cable network, a fiber optic network, a local area network (LAN), a wireless local area network (WLAN), a Bluetooth network, an internal device bus, internal device wiring, cable connections, etc., or any combination thereof. The network connection between the various components of the system can be achieved using one or more of the above methods.

[0053] A remote server is a server capable of remotely managing resources and processing data and / or information from at least one component of the system or an external data source (such as a user terminal). In some embodiments, a remote server may be a single server or a group of servers. The server group may be centralized or distributed (e.g., the remote server may be a distributed system), and may be dedicated or simultaneously provided by other devices or systems. In some embodiments, the remote server may be implemented on a cloud platform or provided virtually. As an example only, the cloud platform may include private cloud, public cloud, hybrid cloud, community cloud, distributed cloud, internal cloud, multi-tiered cloud, etc., or any combination thereof.

[0054] In some embodiments, the remote server can determine the filtration quality based on chemical characteristic parameters, physical characteristic parameters, membrane characteristic parameters, and the historical operating parameter sequence of the membrane separation component; and determine the membrane cleaning cycle or replacement cycle based on chemical characteristic parameters, physical characteristic parameters, filtration quality, and expected filtration effect, and generate a membrane cleaning cycle generation instruction or a replacement cycle generation instruction. For detailed explanations of the above, please refer to relevant content in other parts of this specification (such as...). Figures 2-5 (and related descriptions).

[0055] In some embodiments, the intelligent maintenance system for membrane separation components further includes a user terminal (not shown in the figures). A user terminal refers to one or more terminal devices or software used by a user. For example, a user terminal can be one or any combination of mobile devices, tablet computers, laptop computers, desktop computers, and other devices with input and / or output functions.

[0056] In some embodiments, the user terminal can transmit data and / or information with other components of the membrane separation unit intelligent maintenance via the communication device 160. For example, the user can input data and / or information through the user terminal. Alternatively, the user terminal can display relevant instructions output by a remote server (such as instructions for generating membrane cleaning cycles), or display the filtration effect after membrane cleaning or replacement.

[0057] In some embodiments of this specification, by setting chemical and physical characteristic sensors to collect chemical and physical characteristic parameters respectively, it is helpful to observe the state changes of the membrane separation process. Both chemical and physical characteristic parameters can provide data support for determining the membrane cleaning or replacement cycle. By setting automatic cleaning and automatic replacement modules to periodically clean or replace the membrane separation components, separation efficiency can be improved, energy consumption reduced, and the service life of the membrane separation components extended. By setting a microprocessor to acquire and store relevant parameters and sending them to a remote server via a communication device, the remote server can adjust the maintenance cycle of the membrane separation components in a timely and effective manner. Furthermore, by fixing each module or device to the housing, and by providing multiple seals in the housing, the stability and reliability of the membrane separation process can be ensured.

[0058] Figure 2 This is an exemplary flowchart of an intelligent maintenance method for membrane separation components according to some embodiments of this specification. In some embodiments, process 200 may be executed by an intelligent maintenance system 100 for membrane separation components. Figure 2 As shown, process 200 includes the following steps:

[0059] Step 210: Based on the microprocessor, chemical property parameters and physical property parameters are acquired through chemical property sensors and physical property sensors, respectively, and sent to a remote server.

[0060] As mentioned above, the chemical property sensor includes multiple chemical property sensing units, which are distributed at a first distance on both sides of the membrane. In some embodiments, chemical property parameters can be obtained based on the multiple chemical property sensing units.

[0061] For more information on chemical property parameters, chemical property sensors, chemical property sensing units, and the first distance distribution, please refer to [link to relevant documentation]. Figure 1 And its related descriptions.

[0062] In some embodiments, the remote server may determine the first distance distribution in various ways. For example, the remote server may determine the first distance distribution based on preset rules, manual settings, or other methods.

[0063] In some embodiments, the remote server can generate multiple first candidate distance distributions; calculate the degree of dispersion of the chemical characteristic parameters corresponding to each first candidate distance distribution at different points on both sides of the membrane; and determine the first candidate distance distribution corresponding to the degree of dispersion that meets a first preset requirement as the first distance distribution.

[0064] The first candidate distance distribution refers to a plurality of alternative distance distributions used to determine the first distance distribution. In some embodiments, the first candidate distance distribution may be determined based on historical data.

[0065] The degree of dispersion of chemical property parameters at different points on both sides of the membrane can reflect the difference in chemical property parameters detected at different points when multiple chemical property sensing units are distributed at a first candidate distance on both sides of the membrane.

[0066] In some embodiments, the dispersion of chemical characteristic parameters at different points on both sides of the membrane can be represented as the variance or standard deviation of the chemical characteristic parameters detected at different points when multiple chemical characteristic sensing units are arranged at a first candidate distance distribution on both sides of the membrane. It can be understood that the dispersion of chemical characteristic parameters corresponding to each first candidate distance distribution at different points on both sides of the membrane can be obtained by calculating the variance or standard deviation of the chemical characteristic parameters detected at different points when multiple chemical characteristic sensing units are arranged at a first candidate distance distribution on both sides of the membrane.

[0067] In some embodiments, the remote server can determine the dispersion of the chemical characteristic parameter at different points on one side of the membrane (e.g., the left or right side) corresponding to each of a plurality of first candidate distance distributions. That is, the dispersion of the chemical characteristic parameter at different points on one side of the membrane can include the dispersion of the chemical characteristic parameter at different points on the left side of the membrane and the dispersion of the chemical characteristic parameter at different points on the right side of the membrane.

[0068] The first preset requirement refers to a pre-defined requirement for determining a first distance distribution. For example, the first preset requirement may include maximizing the dispersion of chemical characteristic parameters at different points on both sides of the membrane. In some embodiments, the remote server may determine the first candidate distance distribution corresponding to the maximization of dispersion of chemical characteristic parameters at different points on both sides of the membrane as the first distance distribution.

[0069] In some embodiments of this specification, by calculating the degree of dispersion of chemical characteristic parameters corresponding to each of the multiple first candidate distance distributions at different points on both sides of the membrane, and determining the first candidate distance distribution corresponding to the degree of dispersion that meets the first preset requirement as the first distance distribution, the placement positions of multiple chemical characteristic sensing units can be more dispersed, so as to obtain the chemical characteristic parameters of the solution on both sides of the membrane over the widest possible range, thereby improving the rationality and representativeness of the chemical characteristic parameters.

[0070] As mentioned above, the physical property sensor includes multiple physical property sensing units, which are distributed at a second distance on both sides of the membrane. In some embodiments, physical property parameters can be obtained based on the multiple physical property sensing units.

[0071] For more information on physical characteristic parameters, physical characteristic sensors, physical characteristic sensing units, and the second distance distribution, please refer to [link to relevant documentation]. Figure 1 And its related descriptions.

[0072] In some embodiments, the remote server can determine the second distance distribution in various ways. For example, the remote server can determine the second distance distribution based on preset rules, manual settings, or other methods.

[0073] In some embodiments, the remote server may generate a plurality of second candidate distance distributions; calculate the degree of dispersion of the physical characteristic parameters corresponding to each of the plurality of second candidate distance distributions at different points on both sides of the membrane; and determine the second candidate distance distribution whose dispersion degree meets a second preset requirement as the second distance distribution.

[0074] The second candidate distance distribution refers to a plurality of alternative distance distributions used to determine the second distance distribution. In some embodiments, the second candidate distance distribution may be determined based on historical data.

[0075] The degree of dispersion of physical property parameters at different points on both sides of the membrane can reflect the difference in physical property parameters detected at different points when multiple physical property sensing units are distributed at a second candidate distance on both sides of the membrane.

[0076] In some embodiments, the dispersion of physical property parameters at different points on both sides of the membrane can be represented as the variance or standard deviation of the physical property parameters detected at different points when multiple physical property sensing units are distributed at a second candidate distance on both sides of the membrane. It should be noted that the method for calculating the dispersion of physical property parameters at different points on both sides of the membrane is similar to the method for calculating the dispersion of chemical property parameters at different points on both sides of the membrane, and will not be repeated here.

[0077] The second preset requirement refers to a pre-defined requirement for determining a second distance distribution. For example, the second preset requirement may include maximizing the dispersion of physical property parameters at different points on both sides of the membrane. In some embodiments, the remote server may determine the second candidate distance distribution corresponding to the maximization of dispersion of physical property parameters at different points on both sides of the membrane as the second distance distribution.

[0078] In some embodiments of this specification, by calculating the dispersion degree of physical characteristic parameters corresponding to each of the multiple second candidate distance distributions at different points on both sides of the membrane, and determining the second candidate distance distribution corresponding to the dispersion degree meeting the second preset requirement as the second distance distribution, the placement positions of multiple physical characteristic sensing units can be more dispersed, so as to obtain the physical characteristic parameters of the solution on both sides of the membrane over the widest possible range, thereby improving the rationality and representativeness of the physical characteristic parameters.

[0079] In some embodiments, after obtaining the chemical and physical property parameters, the microprocessor can send them to a remote server via a communication device.

[0080] Step 220: Based on chemical and physical property parameters, determine the membrane cleaning cycle generation instruction or replacement cycle generation instruction via a remote server.

[0081] Cleaning cycle generation instructions are instructions generated by a remote server to control the automatic cleaning module to perform membrane cleaning operations. Replacement cycle generation instructions are instructions generated by a remote server to control the automatic replacement module to perform membrane replacement operations.

[0082] In some embodiments, determining the membrane cleaning cycle generation instruction or replacement cycle generation instruction via a remote server based on chemical and physical property parameters includes the following steps:

[0083] S1, obtain membrane characteristic parameters and expected filtration effect.

[0084] Membrane characteristic parameters refer to parameters related to the properties of a membrane. For example, membrane characteristic parameters may include membrane properties (such as membrane thickness, membrane flux, membrane selectivity, etc.), porosity, type, and membrane module, etc.

[0085] The expected filtration effect refers to the pre-set, desired wastewater filtration effect. In some embodiments, the expected filtration effect can be reflected in the requirements for various parameters or indicators. For example, the required pH value after filtration, the required temperature, and the required filtration quality (such as the purity of the filtrate).

[0086] In some embodiments, both membrane characteristic parameters and expected filtration effect can be obtained based on user input. As an example only, the user can pre-input the membrane characteristic parameters and expected filtration effect through a user terminal.

[0087] S2 determines the filtration quality based on chemical characteristic parameters, physical characteristic parameters, membrane characteristic parameters, and the historical operating parameter sequence of the membrane separation component.

[0088] The historical operating parameter sequence of the membrane separation unit refers to the sequence of historical operating parameters of the membrane separation unit within a preset time period. The preset time period can be set manually.

[0089] In some embodiments, the historical operating parameter sequence of the membrane separation component can be obtained based on historical data. Understandably, the historical operating parameter sequence of the membrane separation component can be obtained by arranging the historical operating parameters of the membrane separation component within a preset time period in chronological order.

[0090] Filtration quality refers to a parameter used to evaluate the filtration effectiveness of a membrane. In some embodiments, filtration quality can be expressed as the purity of the filtrate, i.e., the purity of the filtered solution.

[0091] In some embodiments, a remote server can determine filtration quality in various ways based on chemical characteristic parameters, physical characteristic parameters, membrane characteristic parameters, and historical operating parameter sequences of the membrane separation component. For example, the remote server can determine filtration quality from a database using vector matching.

[0092] As an example only, the database may include multiple first reference vectors and the filtration quality corresponding to each of the multiple first reference vectors. The first reference vectors are constructed based on a sequence of historical chemical characteristic parameters, historical physical characteristic parameters, historical membrane characteristic parameters, and historical operating parameters of historical membrane separation components.

[0093] The remote server constructs a first matching vector based on current chemical, physical, and membrane characteristic parameters, as well as the historical operating parameter sequence of the membrane separation component. It then calculates the distance between each first reference vector and the first matching vector. The first reference vector whose distance to the first matching vector meets a preset distance condition is determined as the target vector, and the filtration quality corresponding to the target vector is determined as the filtration quality corresponding to the first matching vector. The preset distance condition can be set based on actual conditions. For example, the preset distance condition could be the minimum vector distance or the vector distance being less than a distance threshold.

[0094] For detailed descriptions of other embodiments regarding determining filtration quality based on chemical characteristic parameters, physical characteristic parameters, membrane characteristic parameters, and historical operating parameter sequences of the membrane separation component, please refer to [link to relevant documentation]. Figures 3-4 And its related descriptions.

[0095] S3, based on chemical characteristic parameters, physical characteristic parameters, filtration quality and expected filtration effect, determines the membrane cleaning cycle or replacement cycle, and generates a membrane cleaning cycle generation instruction or a replacement cycle generation instruction.

[0096] The cleaning cycle refers to the time interval between two consecutive membrane cleaning cycles. For example, the cleaning cycle could be 6 hours.

[0097] The replacement cycle refers to the time interval between two consecutive membrane replacements. For example, the replacement cycle can be 10 days, half a month, etc.

[0098] In some embodiments, based on chemical characteristic parameters, physical characteristic parameters, filtration quality, and expected filtration effect, a remote server can determine the membrane cleaning cycle or replacement cycle from a database using vector matching.

[0099] As an example only, the database may include multiple second reference vectors and the membrane cleaning cycle or replacement cycle corresponding to each of the multiple second reference vectors. The second reference vectors are constructed based on historical chemical characteristic parameters, historical physical characteristic parameters, historical filtration quality, and historical expected filtration effect.

[0100] The remote server constructs a second matching vector based on the current chemical and physical properties, filtration quality, and expected filtration effect. It should be noted that since the method for determining the membrane cleaning or replacement cycle based on the second matching vector and the second reference vector is similar to the method for determining the filtration quality based on the first matching vector and the first reference vector, it will not be elaborated further here.

[0101] For detailed descriptions of other embodiments regarding determining the membrane cleaning or replacement cycle based on chemical property parameters, physical property parameters, filtration quality, and expected filtration effect, please refer to [link to relevant documentation]. Figure 5 And its related descriptions.

[0102] In some embodiments, once the membrane cleaning cycle or replacement cycle is determined, the remote server can automatically generate a membrane cleaning cycle generation instruction or a replacement cycle generation instruction. For example, once the membrane cleaning cycle is determined, the remote server can automatically generate a membrane cleaning cycle generation instruction.

[0103] Step 230: Based on the microprocessor, generate instructions according to the membrane cleaning cycle or replacement cycle, and control the automatic cleaning module or automatic replacement module to perform membrane cleaning or membrane replacement.

[0104] Membrane cleaning refers to operations performed to clean membranes. Examples include ultrasonic cleaning and chemical cleaning. Membrane replacement refers to operations performed to replace membranes. Examples include stretch wrapping.

[0105] In some embodiments, upon receiving a membrane cleaning cycle generation command or a membrane replacement cycle generation command, the microprocessor can correspondingly control the automatic cleaning module or the automatic replacement module to perform membrane cleaning or membrane replacement. As an example only, upon receiving a membrane cleaning cycle generation command, the microprocessor can control the automatic cleaning module to periodically perform membrane cleaning operations. Upon receiving a membrane replacement cycle generation command, the microprocessor can control the automatic replacement module to periodically perform membrane replacement operations.

[0106] Understandably, membrane cleaning and membrane replacement operations cannot be performed simultaneously. That is, when the automatic cleaning module performs membrane cleaning, the automatic replacement module stops working; conversely, when the automatic replacement module performs membrane replacement, the automatic cleaning module stops working.

[0107] Some embodiments in this specification determine membrane cleaning cycle generation instructions or replacement cycle generation instructions based on chemical and physical characteristic parameters. Based on the membrane cleaning cycle generation instructions or replacement cycle generation instructions, the automatic cleaning module or automatic replacement module is controlled to perform membrane cleaning or membrane replacement. This allows for timely cleaning or replacement of the membrane, thereby effectively ensuring the membrane separation performance and also helping to improve the service life of the membrane separation components.

[0108] It should be noted that the above description of process 200 is for illustrative purposes only and does not limit the scope of this specification. Those skilled in the art can make various modifications and changes to process 200 under the guidance of this specification. However, these modifications and changes remain within the scope of this specification.

[0109] Figure 3 This is an exemplary schematic diagram illustrating the determination of filtration quality according to some embodiments of this specification.

[0110] In some embodiments, such as Figure 3 As shown, the remote server can determine the operating parameters 330 based on the historical operating parameter sequence 310 and membrane characteristic parameters 320 of the membrane separation component; and determine the filtration quality 360 based on the chemical characteristic parameters 340, physical characteristic parameters 350 and operating parameters 330.

[0111] Operating parameter 330 refers to parameters used to measure the operating rate of the membrane. For example, operating parameter 330 may include the membrane's water flux, desalination rate, etc.

[0112] In some embodiments, based on the historical operating parameter sequence 310 and membrane characteristic parameters 320 of the membrane separation component, the remote server can determine the operating parameters 330 by vector matching.

[0113] As an example only, the remote server can cluster the historical operating parameter sequences, membrane characteristic parameters, and operating parameters of the membrane separation components in the historical data to generate multiple first cluster centers. Based on the historical operating parameter sequences and membrane characteristic parameters of the membrane separation components corresponding to the multiple first cluster centers, a first standard vector is constructed. Based on the historical operating parameter sequences and membrane characteristic parameters of the current membrane separation components, a third matching vector is constructed. Then, by calculating the first similarity between the third matching vector and the first standard vector, the operating parameter corresponding to the first standard vector with the highest first similarity is determined as the current operating parameter.

[0114] In some embodiments, based on chemical characteristic parameters 340, physical characteristic parameters 350, and operating parameters 330, the remote server can also determine the filtration quality 360 through vector matching. Understandably, since the method for determining the filtration quality is similar to the method for determining the operating parameters described above, it will not be repeated here.

[0115] In some embodiments, the remote server can determine estimated operating parameters based on chemical characteristic parameters, physical characteristic parameters, and operating parameters; and determine filtration quality based on chemical characteristic parameters, physical characteristic parameters, and estimated operating parameters. For detailed explanations of the above, please refer to [link to relevant documentation]. Figure 4 And its related descriptions.

[0116] For more information on the historical operating parameter sequence, membrane characteristic parameters, chemical characteristic parameters, physical characteristic parameters, and filtration quality of the membrane separation unit, please refer to the relevant descriptions in other parts of this manual (such as...). Figure 2 (and related descriptions).

[0117] In some embodiments of this specification, operating parameters are determined based on the historical operating parameter sequence of the membrane separation component and membrane characteristic parameters, enabling real-time determination of the membrane's filtration status. Simultaneously, by combining chemical and physical characteristic parameters to determine filtration quality, the filtration quality can more closely reflect actual conditions. Furthermore, since the chemical and physical characteristic parameters are collected by multiple sensing units distributed on both sides of the membrane, the filtration quality can reflect the condition of different locations or regions of the membrane, making the filtration quality more targeted.

[0118] Figure 4 This is an exemplary schematic diagram illustrating the determination of filtration quality according to other embodiments of this specification.

[0119] In some embodiments, such as Figure 4 As shown, the remote server can determine the estimated operating parameter 410 based on the chemical characteristic parameter 340, the physical characteristic parameter 350, and the operating parameter 330; and determine the filtration quality 360 based on the chemical characteristic parameter 340, the physical characteristic parameter 350, and the estimated operating parameter 410.

[0120] The estimated working parameter 410 refers to the working parameters within a future time period. The future time period can be a preset value, an empirical value, etc.

[0121] In some embodiments, based on chemical characteristic parameters 340, physical characteristic parameters 350, and operating parameters 330, the remote server can determine the estimated operating parameters 410 in various ways. For example, the remote server can determine the estimated operating parameters 410 based on a first preset table. The first preset table is a lookup table relating the chemical characteristic parameters 340, physical characteristic parameters 350, and operating parameters 330 to the estimated operating parameters 410. The first preset table may include multiple sets of correspondences, and each set of chemical characteristic parameters 340, physical characteristic parameters 350, and operating parameters 330 corresponds to its own estimated operating parameters 410. In some embodiments, the first preset table may be constructed based on historical data.

[0122] In some embodiments, the remote server may determine the estimated chemical characteristic parameters and the estimated physical characteristic parameters based on the chemical characteristic parameters 340 and the physical characteristic parameters 350; and determine the estimated operating parameters 410 based on the estimated chemical characteristic parameters, the estimated physical characteristic parameters and the operating parameters 330.

[0123] Predicted chemical property parameters refer to chemical property parameters within a future time period. Predicted physical property parameters refer to physical property parameters within a future time period. It can be understood that both predicted chemical and physical property parameters are data sequences, meaning that each point in time within the future time period corresponds to both predicted chemical and physical property parameters. In some embodiments, the time points can be obtained by dividing the future time period into preset time intervals. These preset time intervals are set manually.

[0124] In some embodiments, based on chemical property parameters 340 and physical property parameters 350, the remote server can obtain the chemical property parameter change curve and the physical property parameter change curve by fitting the chemical property parameters and physical property parameters within a preset time period in historical data, and then determine the estimated chemical property parameters and the estimated physical property parameters.

[0125] In some embodiments, the estimated chemical and physical property parameters are also related to the current operating parameters of the membrane separation component. In some embodiments, the remote server can determine the estimated chemical and physical property parameters based on the chemical property parameter 340, the physical property parameter 350, and the current operating parameters of the membrane separation component using a first parameter prediction model.

[0126] The current operating parameters of the membrane separation unit refer to its operating parameters at the current moment. Examples include the current operating mode of the membrane and the current operating parameters of the membrane separation unit. In some embodiments, the current operating parameters of the membrane separation unit can be obtained based on user input. For more information on membrane operating modes and the operating parameters of the membrane separation unit, please refer to [link to relevant documentation]. Figure 1 And its related descriptions.

[0127] The first parameter prediction model refers to the model used to determine the predicted chemical property parameters and the predicted physical property parameters. In some embodiments, the first parameter prediction model may include a machine learning model. For example, the first parameter prediction model may include one or more combinations of models such as Recurrent Neural Networks (RNN) models, Long Short-Term Memory (LSTM) models, or other custom models.

[0128] In some embodiments, the input to the first parameter prediction model may include chemical property parameters 340, physical property parameters 350, and the current operating parameters of the membrane separation component, and the output of the first parameter prediction model may include estimated chemical property parameters and estimated physical property parameters.

[0129] In some embodiments, the first parameter prediction model can be trained based on a large number of first training samples with first labels. The first training samples may include at least the chemical and physical property parameters of the samples at a first historical time point obtained from historical data, as well as the current operating parameters of the sample membrane separation component. A remote server can calculate the average value of the chemical and physical property parameters of the first training samples over the time period from the first historical time point to a second historical time point, and use these average values ​​as the first label of the first training samples. The first historical time point is before the second historical time point. The time period from the first historical time point to the second historical time point can be preset by the user terminal. For example, from the beginning of one cycle to the beginning of the next cycle.

[0130] In some embodiments, a first training sample can be input into an initial first parameter prediction model. The initial first parameter prediction model is updated iteratively through training until the trained model meets preset training conditions, thus obtaining a trained first parameter prediction model. The preset training conditions can be a loss function less than a threshold, convergence, or the training period reaching a threshold. In some embodiments, the method for iteratively updating the model parameters can include conventional model training methods such as stochastic gradient descent.

[0131] In some embodiments of this specification, a trained first parameter prediction model is used to process chemical characteristic parameters, physical characteristic parameters, and the current operating parameters of the membrane separation component to determine the estimated chemical characteristic parameters and estimated physical characteristic parameters, which can effectively improve the accuracy of the estimated chemical characteristic parameters and estimated physical characteristic parameters.

[0132] In some embodiments, based on the estimated chemical characteristic parameters, estimated physical characteristic parameters, and operating parameters 330, the remote server can determine the estimated operating parameters 410 based on a second preset table. The second preset table is a lookup table relating the estimated chemical characteristic parameters, estimated physical characteristic parameters, and operating parameters 330 to the estimated operating parameters 410. The second preset table may include multiple sets of correspondences, with each set of estimated chemical characteristic parameters, physical characteristic parameters, and operating parameters 330 corresponding to its own estimated operating parameters 410. The second preset table can be constructed based on historical data.

[0133] In some embodiments, the remote server can determine the estimated operating parameters 410 based on the estimated chemical property parameters, the estimated physical property parameters, and the operating parameters 330 using a second parameter prediction model.

[0134] The second-parameter prediction model refers to a model used to determine the estimated working parameters. In some embodiments, the second-parameter prediction model may include a machine learning model. For example, the second-parameter prediction model may include one or more combinations of models such as RNN models, LSTM models, or other custom models.

[0135] In some embodiments, the input to the second parameter prediction model may include estimated chemical property parameters, estimated physical property parameters, and operating parameters 330, and the output of the second parameter prediction model may include estimated operating parameters 410.

[0136] In some embodiments, the second parameter prediction model can be trained based on a large number of second training samples with second labels. The second training samples may include at least the estimated chemical property parameters, estimated physical property parameters, and working parameters of samples at a first historical time point obtained from historical data. A remote server can calculate the average value of the working parameters of the second training samples over the time period from the first historical time point to the second historical time point, and use this average value as the second label of the second training samples. The first historical time point is prior to the second historical time point. The time period from the first historical time point to the second historical time point can be preset by the user terminal. For example, from the beginning of one cycle to the beginning of the next cycle.

[0137] It should be noted that the training method for the second parameter prediction model is similar to that for the first parameter prediction model, and will not be repeated here.

[0138] In some embodiments of this specification, the predicted chemical property parameters, predicted physical property parameters, and operating parameters are processed by a trained second parameter prediction model to determine the predicted operating parameters, which can effectively improve the accuracy of the predicted operating parameters.

[0139] In some embodiments, the remote server can determine the filtration quality 360 based on chemical characteristic parameters 340, physical characteristic parameters 350, estimated chemical characteristic parameters, estimated physical characteristic parameters, and estimated operating parameters using a preset method.

[0140] A preset method refers to a method that is pre-defined and used to determine the quality of filtration. For example, preset methods may include, but are not limited to, machine learning models and calculation formulas.

[0141] In some embodiments, a preset method can be used to characterize the correlation between chemical characteristic parameters 340, physical characteristic parameters 350, estimated chemical characteristic parameters, estimated physical characteristic parameters, and estimated operating parameters and the filtration quality 360. That is, a remote server can calculate the filtration quality 360 based on the chemical characteristic parameters 340, physical characteristic parameters 350, estimated chemical characteristic parameters, estimated physical characteristic parameters, and estimated operating parameters using a calculation formula.

[0142] Understandably, the chemical characteristic parameter 340, physical characteristic parameter 350, estimated chemical characteristic parameter, estimated physical characteristic parameter, and estimated operating parameter can all be represented based on vectors. In some embodiments, the filtration quality 360 is positively correlated with the cosine of the angle between the chemical characteristic parameter vector and the standard chemical characteristic parameter vector, the cosine of the angle between the physical characteristic parameter vector and the standard physical characteristic parameter vector, the cosine of the angle between the estimated chemical characteristic parameter vector and the standard chemical characteristic parameter vector, the cosine of the angle between the estimated physical characteristic parameter vector and the standard physical characteristic parameter vector, and the cosine of the angle between the estimated operating parameter vector and the standard operating parameter vector.

[0143] An example calculation formula includes: Filtration mass = w1×cos(chemical characteristic parameter, standard chemical characteristic parameter) + w2×cos(physical characteristic parameter, standard physical characteristic parameter) + w3×cos(estimated chemical characteristic parameter, standard chemical characteristic parameter) + w4×cos(estimated physical characteristic parameter, standard physical characteristic parameter) + w5×cos(estimated operating parameter, standard operating parameter).

[0144] Among them, w1 to w5 are order-of-magnitude balance parameters, which can be manually set based on past experience or actual conditions. Standard chemical characteristic parameters are the standard values ​​corresponding to the chemical characteristic parameters and the estimated chemical characteristic parameters; that is, the chemical characteristic parameters and the estimated chemical characteristic parameters both correspond to a single standard value. Standard physical characteristic parameters are the standard values ​​corresponding to the physical characteristic parameters and the estimated physical characteristic parameters; that is, the physical characteristic parameters and the estimated physical characteristic parameters both correspond to a single standard value. Standard working parameters are the standard values ​​corresponding to the estimated working parameters. These standard values ​​can be pre-set target parameter values, which can be manually set based on past experience or actual conditions. In other words, standard chemical characteristic parameters, standard physical characteristic parameters, and standard working parameters can all be manually set based on past experience or actual conditions.

[0145] For more information on filtration quality, please refer to the relevant descriptions in other parts of this manual (such as...). Figures 2-3 (and related descriptions).

[0146] Some embodiments in this specification, based on chemical characteristic parameters, physical characteristic parameters, estimated chemical characteristic parameters, estimated physical characteristic parameters, and estimated operating parameters, comprehensively consider the differences between each parameter and its standard value, and determine their corresponding weights according to past experience or actual conditions to comprehensively determine the filtration quality, making the filtration quality closer to the actual situation, thereby enabling a more accurate determination of the membrane cleaning cycle or replacement cycle.

[0147] Figure 5 This is an exemplary schematic diagram illustrating the determination of cleaning or replacement cycles according to some embodiments of this specification.

[0148] In some embodiments, such as Figure 5 As shown, the remote server can predict the quality parameter 510 based on the chemical characteristic parameter 340 and the physical characteristic parameter 350; and determine the membrane cleaning cycle or replacement cycle 530 based on the quality parameter 510, the filtration quality 360 and the expected filtration effect 520.

[0149] Quality parameter 510 refers to a parameter used to assess the working quality of the membrane over a future period. In some embodiments, quality parameter 510 may include the membrane's lifespan 510-1 and the membrane's working quality 510-2. The membrane's working quality 510-2 refers to the filtration quality of the filtrate over the membrane's lifespan.

[0150] In some embodiments, the remote server can determine the mass parameter 510 in various ways based on the chemical property parameter 340 and the physical property parameter 350. For example, the remote server can determine the mass parameter 510 from a database based on vector matching.

[0151] As an example only, the database may include multiple third reference vectors and a corresponding mass parameter 510 for each of the multiple third reference vectors. The third reference vectors are constructed based on historical chemical and physical property parameters.

[0152] The remote server constructs a fourth matching vector based on the current chemical and physical property parameters. It should be noted that the method for determining mass parameters based on the fourth matching vector and the third reference vector differs from... Figure 2 The method for determining the filtering quality based on the first vector to be matched and the first reference vector is similar and will not be described in detail here.

[0153] In some embodiments, the remote server can determine the quality parameter 510 based on the chemical property parameter 340, physical property parameter 350, estimated chemical property parameter, estimated physical property parameter, and estimated working parameter 410 through a quality parameter prediction model.

[0154] A quality parameter prediction model refers to a model used to determine quality parameter 510. In some embodiments, the quality parameter prediction model may include a machine learning model. For example, the quality parameter prediction model may include one or more combinations of models such as Deep Neural Networks (DNN) models, Convolutional Neural Networks (CNN) models, or other custom models.

[0155] In some embodiments, the inputs to the quality parameter prediction model may include chemical property parameters 340, physical property parameters 350, estimated chemical property parameters, estimated physical property parameters, and estimated working parameters 410, and the output of the quality parameter prediction model may include quality parameters 510.

[0156] In some embodiments, the quality parameter prediction model can be trained based on a large number of third training samples with third labels. These third training samples may include at least the chemical and physical property parameters of samples at a first historical time point obtained from historical data, the estimated chemical and physical property parameters of samples, and the estimated working parameters of samples. A remote server can calculate the average value of the quality parameters of the third training samples over the time period from the first historical time point to the second historical time point, and determine this average value as the third label. The first historical time point is prior to the second historical time point. The time period from the first historical time point to the second historical time point can be preset by the user terminal. For example, from the beginning of one cycle to the beginning of the next cycle.

[0157] It should be noted that the training method for the quality parameter prediction model is similar to that for the first parameter prediction model, and will not be repeated here.

[0158] For more information on chemical property parameters, physical property parameters, estimated chemical property parameters, estimated physical property parameters, and estimated operating parameters, please refer to the relevant descriptions in other parts of this manual (such as...). Figure 4 (and related descriptions).

[0159] Some embodiments in this specification use a trained quality parameter prediction model to process chemical property parameters, physical property parameters, estimated chemical property parameters, estimated physical property parameters, and estimated working parameters to determine quality parameters, which can effectively improve the accuracy of quality parameters.

[0160] In some embodiments, the remote server can determine the membrane cleaning cycle or replacement cycle 530 based on the quality parameter 510, filtration quality 360, and expected filtration effect 520 using a third preset table. The third preset table is a lookup table relating the quality parameter 510, filtration quality 360, and expected filtration effect 520 to the membrane cleaning cycle and replacement cycle. The third preset table may include multiple sets of correspondences, with each set of quality parameter 510, filtration quality 360, and expected filtration effect 520 corresponding to its own membrane cleaning cycle and replacement cycle. The third preset table can be constructed based on historical data.

[0161] In some embodiments, the remote server may determine a candidate cleaning cycle or a candidate replacement cycle based on the quality parameter 510 and the expected filtration effect 520; determine the filtration effect after membrane cleaning or membrane replacement based on the candidate cleaning cycle or candidate replacement cycle and the filtration quality 360; and determine the membrane cleaning cycle or replacement cycle 530 based on the filtration effect.

[0162] A candidate cleaning cycle refers to a plurality of alternative times for determining the cleaning cycle of the membrane. A candidate replacement cycle refers to a plurality of alternative times for determining the replacement cycle of the membrane. In some embodiments, the candidate cleaning cycle or candidate replacement cycle may be obtained based on user input. In some embodiments, the candidate cleaning cycle or candidate replacement cycle may be determined based on historical data.

[0163] The filtration effect after membrane cleaning or replacement refers to the filtration effect of the membrane after cleaning or replacement. In some embodiments, the filtration effect after membrane cleaning or replacement can be reflected as a comprehensive measure of the filtration quality and economic benefits of the cleaned or replaced membrane.

[0164] In some embodiments, based on candidate cleaning cycles or candidate replacement cycles and filtration quality 360, a remote server can determine the filtration effect after membrane cleaning or replacement using various methods. Exemplary methods include, but are not limited to, machine learning models.

[0165] In some embodiments, the remote server can calculate the filtration effect after membrane cleaning or replacement by weighting the candidate cleaning cycle or candidate replacement cycle with the filtration quality 360. For a detailed explanation of the filtration quality 360, please refer to [link to relevant documentation]. Figures 2-4 And its related descriptions.

[0166] For example only, the filtration effect after membrane cleaning or replacement = n1 × (cleaning cost ÷ candidate cleaning cycle) + n2 × (replacement cost ÷ candidate replacement cycle) + n3 × filtration quality. Where n1 to n3 are the corresponding weight values ​​for each parameter, n1 = 0 or n2 = 0, and n3 ≠ 0. In some embodiments, the specific values ​​of n1 to n3 can be set based on actual needs. For example only, when higher economic efficiency is required, n1 or n2 can be increased and n3 decreased accordingly; when higher filtration quality is required, n3 can be increased and n1 or n2 decreased accordingly.

[0167] Some embodiments in this specification, based on candidate cleaning cycles or candidate replacement cycles and filtration quality 360, obtain the filtration effect after membrane cleaning or replacement through weighted calculation. This comprehensively considers the impact of economic benefits and filtration quality on the filtration effect, so that the subsequently determined membrane cleaning cycle or replacement cycle can meet the actual needs of different users, thereby improving the user experience.

[0168] In some embodiments, based on the above-mentioned filtration effect, the remote server can determine the candidate cleaning cycle or candidate replacement cycle corresponding to the best filtration effect as the membrane cleaning cycle or replacement cycle 530.

[0169] Some embodiments in this specification, based on candidate cleaning cycles or candidate replacement cycles and filtration quality, can achieve filtration effects after membrane cleaning or replacement that meet the actual needs of different users through weighted calculations; at the same time, based on this filtration effect, the membrane cleaning cycle or replacement cycle can be determined quickly and accurately.

[0170] In some embodiments, the remote server may also determine the membrane cleaning cycle or replacement cycle 530 by vector matching based on quality parameters, expected filtration effect and candidate cleaning cycles or candidate replacement cycles in historical data.

[0171] As an example, the remote server can cluster the quality parameters, expected filtering effects, and candidate cleaning or replacement cycles from historical data to generate multiple second cluster centers. Based on the quality parameters, expected filtering effects, and candidate cleaning or replacement cycles corresponding to these second cluster centers, a second standard vector is constructed. A fifth matching vector is constructed based on the current quality parameters and expected filtering effects. Then, by calculating the second similarity between the fifth matching vector and the second standard vector, the candidate cleaning or replacement cycle corresponding to the second standard vector whose second similarity meets the similarity threshold is determined as the membrane's cleaning or replacement cycle 530. The similarity threshold can be manually set based on past experience or actual needs.

[0172] In some embodiments of this specification, quality parameters are predicted based on chemical and physical property parameters; and the membrane cleaning cycle or replacement cycle is determined based on the quality parameters, filtration quality, and expected filtration effect. This allows the membrane cleaning cycle or replacement cycle to meet the actual needs of different users, thereby making the intelligent maintenance system for membrane separation components more intelligent.

[0173] The basic concepts have been described above. Obviously, for those skilled in the art, the detailed disclosure above is merely illustrative and does not constitute a limitation of this specification. Although not explicitly stated herein, 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 and therefore remain within the spirit and scope of the exemplary embodiments described herein.

Claims

1. An intelligent maintenance system for membrane separation components, characterized in that, include: The membrane separation component includes a membrane, a housing, an automatic cleaning module, an automatic replacement module, a chemical property sensor, a physical property sensor, and a microprocessor. The membrane is disposed within the housing. The automatic cleaning module, the automatic replacement module, and the microprocessor are all disposed on the housing. The chemical property sensor and the physical property sensor are respectively disposed on both sides of the membrane. The automatic cleaning module is configured to clean the membrane; The automatic replacement module is configured to replace the membrane; The chemical property sensor is configured to detect chemical property parameters of the solutions on both sides of the membrane; The physical property sensor is configured to detect the physical property parameters of the solutions on both sides of the membrane; The microprocessor is configured to: Record the operating parameters of the membrane separation component; Obtain membrane characteristic parameters and expected filtration effect; The filtration quality is determined based on the chemical characteristic parameters, the physical characteristic parameters, the membrane characteristic parameters, and the historical operating parameter sequence of the membrane separation component. Based on the chemical characteristic parameters, the physical characteristic parameters, the filtration quality, and the expected filtration effect, the cleaning cycle or replacement cycle of the membrane is determined, and a cleaning cycle generation instruction or a replacement cycle generation instruction for the membrane is generated. Based on the microprocessor, instructions are generated according to the membrane cleaning cycle or replacement cycle, and the automatic cleaning module or automatic replacement module is controlled to perform membrane cleaning or membrane replacement.

2. The intelligent maintenance system for membrane separation components as described in claim 1, characterized in that, The chemical property sensor includes multiple chemical property sensing units, which are distributed at a first distance on both sides of the membrane.

3. The intelligent maintenance system for membrane separation components as described in claim 1, characterized in that, The physical property sensor includes multiple physical property sensing units, which are distributed at a second distance on both sides of the membrane.

4. The intelligent maintenance system for membrane separation components as described in claim 1, characterized in that, The membrane separation component also includes a communication device, which is disposed on the housing; The communication device is configured to communicate with the microprocessor, the automatic cleaning module, the automatic replacement module, the chemical property sensor, the physical property sensor, and the remote server.

5. A method for intelligent maintenance of membrane separation components, characterized in that, Based on the intelligent maintenance system for membrane separation components according to claim 1, the system includes a membrane separation component and a remote server, the membrane separation component includes a membrane, a housing, an automatic cleaning module, an automatic replacement module, a chemical property sensor, a physical property sensor, and a microprocessor; the method includes: Based on the microprocessor, chemical property parameters and physical property parameters are acquired by the chemical property sensor and the physical property sensor, respectively, and then sent to the remote server. Based on the chemical and physical property parameters, the remote server determines the membrane cleaning cycle generation instruction or replacement cycle generation instruction, including: Obtain membrane characteristic parameters and expected filtration effect; The filtration quality is determined based on the chemical characteristic parameters, the physical characteristic parameters, the membrane characteristic parameters, and the historical operating parameter sequence of the membrane separation component. Based on the chemical characteristic parameters, the physical characteristic parameters, the filtration quality, and the expected filtration effect, the cleaning cycle or replacement cycle of the membrane is determined, and a cleaning cycle generation instruction or a replacement cycle generation instruction for the membrane is generated. Based on the microprocessor, instructions are generated according to the membrane cleaning cycle or replacement cycle, and the automatic cleaning module or automatic replacement module is controlled to perform membrane cleaning or membrane replacement.

6. The intelligent maintenance method for membrane separation components as described in claim 5, characterized in that, The chemical property sensor includes multiple chemical property sensing units, which are distributed at a first distance on both sides of the membrane; the chemical property parameters are obtained based on the multiple chemical property sensing units.

7. The intelligent maintenance method for membrane separation components as described in claim 5, characterized in that, The physical property sensor includes multiple physical property sensing units, which are distributed at a second distance on both sides of the membrane; the physical property parameters are obtained based on the multiple physical property sensing units.

8. The intelligent maintenance method for membrane separation components as described in claim 5, characterized in that, The determination of filtration quality based on the chemical characteristic parameters, the physical characteristic parameters, the membrane characteristic parameters, and the historical operating parameter sequence of the membrane separation component includes: Based on the historical operating parameter sequence of the membrane separation component and the membrane characteristic parameters, the operating parameters are determined, including the membrane water flux and desalination rate. The filtration quality is determined based on the chemical property parameters, the physical property parameters, and the operating parameters.

9. The intelligent maintenance method for membrane separation components as described in claim 8, characterized in that, Determining the filtration quality based on the chemical characteristic parameters, the physical characteristic parameters, and the operating parameters includes: Based on the chemical property parameters, the physical property parameters, and the operating parameters, the estimated operating parameters are determined; The filtration quality is determined based on the chemical characteristic parameters, the physical characteristic parameters, and the estimated operating parameters.

10. The intelligent maintenance method for membrane separation components as described in claim 5, characterized in that, Determining the membrane's cleaning or replacement cycle based on the chemical properties, physical properties, filtration quality, and expected filtration effect includes: Based on the chemical and physical properties, quality parameters are predicted, including the membrane's lifespan and its operational quality. Based on the quality parameters, the filtration quality, and the expected filtration effect, the cleaning cycle or replacement cycle of the membrane is determined.

Images