Water purification method and device

Abstract

The invention relates to a water purification method, which comprises the following steps: by taking a time-passing rate curve of a sample filter membrane as a reference, updating water quality data of two sides of the sample filter membrane corresponding to the time-passing rate curve of the sample filter membrane into the time-passing rate curve of the sample filter membrane under the condition of time dimension synchronization; the updated time-passing rate curve of the sample filtering membrane is obtained, the updated time-passing rate curve of the sample filtering membrane is marked according to the specification of the sample filtering membrane, and the marked time-passing rate curve of the sample filtering membrane is obtained; and calculating the time-passing rate curves of the plurality of sample filtering membranes in the specification of each sample filtering membrane after marking to obtain a predicted time-passing rate curve and a predicted time-passing water quality data curve of the specification of each sample filtering membrane.

Description

Technical Field

[0001] The present application relates to the field of water purification technology, and in particular to a water purification method and device. Background Art

[0002] Membrane separation technology is a process of separating components by using the difference in the permeation rate of each component in the fluid to the membrane. Relying on the selective permeability of the membrane, small molecules can freely pass through the semipermeable membrane, while large molecules are not permeable to the selective membrane and are intercepted, thereby achieving the purpose of separating, purifying and concentrating substances in multiple components.

[0003] In the existing water treatment process, filter membranes of different specifications are often used to remove suspended matter, bacteria, viruses and other harmful substances in the water to ensure that the effluent water quality meets the relevant national standards. However, the existing filter membranes are often cleaned or replaced after a fixed period of use. This method cannot efficiently utilize the performance of the filter membrane, and may result in premature replacement or late replacement, and the stability of the effluent water quality cannot be guaranteed. Summary of the invention

[0004] Based on this, it is necessary to provide a water purification method and device in view of the fact that traditional filter membranes are often cleaned or replaced after a fixed period of use. This method cannot efficiently utilize the filter membrane, and may result in premature replacement or late replacement, and cannot ensure the stability of the effluent water quality.

[0005] The present application provides a water purification method, comprising: Acquire a plurality of sample filter membrane operation data, wherein the sample filter membrane operation data includes a time-pass rate curve of the sample filter membrane, water quality data on both sides of the sample filter membrane, and specifications of the sample filter membrane; Based on the water quality data on both sides of each sample filter membrane, the time-pass rate curve of the sample filter membrane is updated to obtain the updated time-pass rate curve of each sample filter membrane; Marking the updated time-pass rate curve of each sample filter membrane based on the specification of the sample filter membrane to obtain the marked time-pass rate curve of each sample filter membrane; Based on the time-pass rate curves of multiple sample filter membranes marked corresponding to the specifications of each sample filter membrane, the predicted time-pass rate curve of the specifications of each sample filter membrane and the predicted time-water quality data curve after passing are calculated; A filter membrane prediction model is created based on each time-pass rate curve, water quality data on both sides of each sample filter membrane, specifications of each sample filter membrane, time-pass rate curve of each sample filter membrane after being marked, target time-pass rate curve of each sample filter membrane, and predicted time-pass rate curve of the specifications of each sample filter membrane and predicted time-pass water quality data curve; Obtaining operating data of a filter membrane to be tested; The specification of the filter membrane to be tested and the water quality data before the filter membrane to be tested passes through are input into the filter membrane prediction model, the filter membrane prediction model is started, and the predicted time-pass rate curve and the predicted time-water quality data curve after passing through of the filter membrane to be tested are obtained as output by the filter membrane prediction model.

[0006] The present application also provides a water purification device, comprising: A first detection member is provided in plurality, and a first detection member is provided on one side before each filter membrane passes through, and the first detection member is used to detect water quality data before the water passes through the filter membrane; The second detection element is provided in plurality, and a second detection element is provided on the side after each filter membrane passes through, and the second detection element is used to detect the water quality data after the water passes through the filter membrane; A plurality of pass rate detection components are provided, one pass rate detection component is provided on each filter membrane, and the pass rate detection component is used to detect the pass rate data of the filter membrane; A processing device is connected to the first detection element in communication, the processing device is connected to the second detection element in communication, and the processing device is also connected to the pass rate detection element in communication, and the processing device is used to perform the water purification method as described above The present application relates to a water purification method, which first takes the time-pass rate curve of a sample filter membrane as a benchmark, then updates the water quality data on both sides of the sample filter membrane corresponding to the time-pass rate curve of the sample filter membrane into the time-pass rate curve of the sample filter membrane under the condition of synchronization in the time dimension, thereby obtaining the updated time-pass rate curve of the sample filter membrane, and marks the updated time-pass rate curve of the sample filter membrane with the specification of the sample filter membrane to obtain the marked time-pass rate curve of the sample filter membrane; then calculates multiple marked time-pass rate curves of each sample filter membrane in the specification of each sample filter membrane to obtain a predicted time-pass rate curve of the specification of each sample filter membrane and a predicted time-pass water quality data curve. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] Figure 1 A schematic diagram of a process for purifying water provided in accordance with an embodiment of the present application.

[0008] Figure 2A schematic diagram of the structure of a water purification device provided in one embodiment of the present application.

[0009] Reference numerals: 11. First detection member; 12. Second detection member; 13. Pass rate detection member; 14. Processing device; 15. Filter membrane. DETAILED DESCRIPTION

[0010] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0011] like Figure 1 As shown, in one embodiment of the present application, the water purification method includes the following S100 to S600: S100, obtaining a plurality of sample filter membrane operation data, wherein the sample filter membrane operation data includes a time-pass rate curve of the sample filter membrane, water quality data on both sides of the sample filter membrane, and specifications of the sample filter membrane.

[0012] Specifically, the pass rate of the sample filter membrane refers to the pass rate of the liquid filtered through the sample filter membrane. The liquid here generally refers to water from underground or rivers; the water quality data on both sides of the sample filter membrane refers to the side of the sample filter membrane that is not filtered and the side after filtration, and the water quality data may refer to the particulate matter content, bacterial content, etc. in the liquid; the specifications of the sample filter membrane refer to the filtration characteristics of the sample filter membrane itself, such as the pore size of the filter membrane is 0.001-0.02 microns, etc.

[0013] S200, based on the water quality data on both sides of each sample filter membrane, the time-pass rate curve of the sample filter membrane is updated to obtain the updated time-pass rate curve of each sample filter membrane.

[0014] Specifically, updating the time-pass rate curve of the sample filter membrane based on the water quality data on both sides of the sample filter membrane means presenting the water quality data on both sides of the sample filter membrane in the time-pass rate curve, thereby obtaining an updated time-pass rate curve.

[0015] S300, marking the updated time-pass rate curve of each sample filter membrane based on the specification of the sample filter membrane, to obtain the marked time-pass rate curve of each sample filter membrane.

[0016] Specifically, the updated time-pass rate curve of each sample filter membrane is marked based on the specifications of each sample filter membrane, thereby obtaining a plurality of marked time-pass rate curves; further, a plurality of specification databases are created, and the updated time-pass rate curves of the sample filter membranes of the corresponding specifications are stored in the corresponding specification databases.

[0017] S400, based on the time-pass rate curves of multiple sample filter membranes marked corresponding to the specifications of each sample filter membrane, calculate the predicted time-pass rate curve of the specifications of each sample filter membrane and the predicted time-after-pass water quality data curve.

[0018] S500, creates a filter membrane prediction model based on each sample filtration, each time-pass rate curve, water quality data on both sides of each sample filter membrane, specifications of each sample filter membrane, time-pass rate curve of each sample filter membrane after being marked, and target time-pass rate curve of each sample filter membrane.

[0019] S600, obtaining operation data of a filter membrane to be tested.

[0020] S700, input the specification of the filter membrane to be tested and the water quality data before the filter membrane to be tested passes into the filter membrane prediction model, start the filter membrane prediction model, and obtain the predicted time-pass rate curve and the predicted time-water quality data curve after the filter membrane to be tested output by the filter membrane prediction model.

[0021] In this embodiment, the time-pass rate curve of the sample filter membrane is first used as a benchmark, and then the water quality data on both sides of the sample filter membrane corresponding to the time-pass rate curve of the sample filter membrane is updated into the time-pass rate curve of the sample filter membrane under the condition of synchronization in the time dimension to obtain the updated time-pass rate curve of the sample filter membrane, and the updated time-pass rate curve of the sample filter membrane is marked with the specification of the sample filter membrane to obtain the marked time-pass rate curve of the sample filter membrane; then, multiple marked time-pass rate curves of the sample filter membranes in the specification of each sample filter membrane are calculated to obtain the predicted time-pass rate curve of each sample filter membrane specification and the predicted time-pass water quality data curve.

[0022] In one embodiment of the present application, the time-pass rate curve of each sample filter membrane is updated based on the water quality data on both sides of the sample filter membrane to obtain the updated time-pass rate curve of each sample filter membrane, including the following S201 to S204: S201, selecting a sample filter membrane operation data.

[0023] S202, obtaining water quality data on both sides of the sample filter membrane in the sample filter membrane operation data and a time-pass rate curve of the sample filter membrane, wherein the water quality data on both sides of the sample filter membrane include water quality data before passing through and water quality data after passing through.

[0024] S203, updating the time-pass rate curve of the sample filter membrane based on the water quality data before and after the sample filter membrane passes through, to obtain an updated time-pass rate curve of the sample filter membrane.

[0025] S204, returning to the step of selecting a sample filter membrane operation data until each sample filter membrane operation data has been selected once.

[0026] In this embodiment, the water quality data before and after the sample passes through the filter membrane are updated into the time-pass rate curve of the sample filter membrane and the time dimension is updated synchronously, so that the updated time-pass rate curve of the sample filter membrane can intuitively obtain the water quality data before the sample passes through the filter membrane, the water quality data after the sample passes through the filter membrane and the pass rate value of the sample filter membrane at a time node, and further, the influence on the passability of the sample filter membrane can be judged by the water quality before and after the sample filter membrane, and it can also help judge whether the sample filter membrane has reached its service life and whether it is time to clean it.

[0027] In one embodiment of the present application, the time-pass rate curve of the sample filter membrane is updated based on the water quality data before and after the sample filter membrane passes through to obtain the updated time-pass rate curve of the sample filter membrane, including the following S203a to S203d: S203a, based on the water quality data before the sample passes through the filtration membrane, create a time-before-passing water quality data curve.

[0028] S203b, merging the time-pre-passage water quality data curve into the time-passage rate curve of the sample filtration membrane to obtain a first fusion curve.

[0029] S203c, based on the water quality data after the sample passes through the filtration membrane, create a time-post-passage water quality data curve.

[0030] S203d, merging the time-passed water quality data curve into the first fused curve to obtain a second fused curve.

[0031] In this embodiment, the water quality data before the sample passes through the filter membrane is first established into a corresponding time-before-passage water quality data curve, and then the time-before-passage water quality data curve of the sample filter membrane is merged into the time-pass rate curve of the sample filter membrane based on a one-to-one correspondence of time points to obtain the first fusion curve.

[0032] The water quality data after the sample passes through the filter membrane is then established into a corresponding time-water quality data curve after passing through. Next, based on the one-to-one correspondence of time points, the time-water quality data curve after the sample passes through the filter membrane is merged into the first fusion curve to obtain the second fusion curve.

[0033] In one embodiment of the present application, the updated time-pass rate curve of each sample filter membrane is marked based on the specification of the sample filter membrane to obtain the marked time-pass rate curve of each sample filter membrane, including the following S301 to S304: S301, selecting an updated time-throughput rate curve.

[0034] S302, obtaining the specification of the sample filter membrane of the updated time-pass rate curve.

[0035] S303, marking the updated time-pass rate curve with the obtained specification of the sample filter membrane to obtain a marked updated time-pass rate curve.

[0036] S304, returning to the step of selecting an updated time-throughput rate curve, until each updated time-throughput rate curve has been selected once.

[0037] In this embodiment, a specification database can be established to store the sample filter membrane operation data of each sample filter membrane in the corresponding specification database, so as to provide convenience and save time when acquiring data for sample filter membranes of different specifications.

[0038] In one embodiment of the present application, the time-pass rate curves after marking the multiple sample filter membranes corresponding to the specifications of each sample filter membrane are calculated to obtain the predicted time-pass rate curve and the predicted time-water quality data curve after passing the specification of each sample filter membrane, including the following S401 to S403: S401, selecting an updated time-pass rate curve in the specification of a sample filter membrane.

[0039] S402, dividing the updated time-pass rate curve based on the water quality data before the sample passes through the filtration membrane to obtain a plurality of segmented curves.

[0040] S403, returning an updated time-pass rate curve in the specification of the selected sample filter membrane, until each updated time-pass rate curve in the specification of each sample filter membrane is returned.

[0041] In this embodiment, the filtration efficiency of sample filter membranes of different specifications in different filtration environments is somewhat different. Therefore, based on the water quality data before the sample filter membrane passes through, multiple data are acquired and analyzed to obtain the pass rate working curves of sample filter membranes of different specifications in different filtration environments.

[0042] In one embodiment of the present application, the updated time-pass rate curve is divided based on the water quality data before the sample passes through the filter membrane to obtain a plurality of segmented curves, including the following S402a to S402b: S402a, analyzing the water quality data curve before passing through time to obtain water quality data of at least one concentration.

[0043] S402b, dividing the updated time-pass rate curve based on the water quality data of all concentrations to obtain a plurality of segmented curves.

[0044] In this embodiment, the updated time-throughput rate curve is cut based on the water quality data of each concentration to obtain multiple partially updated time-throughput rate curves, and the water quality data in each partially updated time-throughput rate curve is a fixed value or the water quality data fluctuates within a certain range.

[0045] In one embodiment of the present application, the time-pass rate curves after marking the multiple sample filter membranes corresponding to the specifications of each sample filter membrane are calculated to obtain the predicted time-pass rate curve and the predicted time-water quality data curve after passing the specification of each sample filter membrane, and further include the following S404 to S412: S404, selecting water quality data of a concentration in the specification of a sample filter membrane.

[0046] S405, analyzing the water quality data of the concentration to obtain a plurality of segmented curves of the water quality data of the concentration.

[0047] S406, merging the multiple segmented curves into the same coordinate system based on the time dimension to obtain a target curve.

[0048] S407, selecting a time node of the target curve.

[0049] S408, analyzing the time node to obtain the filter membrane pass rate values ​​of all samples at the time node.

[0050] S409, calculating the average value of all sample filter membrane pass rates, and using the average value as the predicted sample filter membrane pass rate value at the time node.

[0051] S410, returning to a time node of the selected target curve until each time node of the target curve has been selected once.

[0052] S411, based on the time sequence, all predicted sample filter membrane pass rate values ​​are included in the same coordinate system to obtain a predicted time-pass rate curve of the specification of the sample filter membrane.

[0053] S412, returning the water quality data of a concentration in the specification of the selected sample filter membrane, until the water quality data of each concentration in the specification of each sample filter membrane has been selected once.

[0054] Specifically, the corresponding prediction time-pass rate curve is generated with the specifications of the sample filter membrane and the concentration of the water quality data as limiting conditions. Furthermore, multiple prediction time-pass rate curves for different sample filter membrane specifications and different water quality data concentrations can be obtained, thereby forming a prediction capability with a wider coverage.

[0055] In this embodiment, the specification of a sample filter membrane is first limited as the primary condition, and then a random concentration of water quality data is used as the second limit adjustment to obtain a segmented curve, and all the obtained segmented curves are merged into the same coordinate system based on the chronological order, and then all the sample filter membrane pass rate values ​​of each time node are obtained, and the sample filter membrane pass rate values ​​of each time node are screened and cleaned, and invalid data or more extreme data are deleted, and then the average of all the remaining sample filter membrane pass rate values ​​is calculated, and the average value is used as the predicted sample filter membrane pass rate value of each corresponding time node.

[0056] In one embodiment of the present application, the time-pass rate curves after marking the multiple sample filter membranes corresponding to the specifications of each sample filter membrane are calculated to obtain the predicted time-pass rate curve and the predicted time-water quality data curve after passing the specification of each sample filter membrane, and further include the following S413 to S420: S413, selecting water quality data of a concentration in the specification of a sample filter membrane.

[0057] S414, obtaining a target curve of the water quality data of the concentration.

[0058] S415, selecting a time node of the target curve.

[0059] S416, analyzing the time node to obtain water quality data of all samples after passing through the filter membrane at the time node.

[0060] S417, calculating the average value of the water quality data of all samples after passing through the filter membrane, and using the obtained average value as the average value of the water quality data of the predicted samples after passing through the filter membrane at the time node.

[0061] S418, returning to a time node of the selected target curve until each time node of the target curve has been selected once.

[0062] S419, based on the time sequence, the average values ​​of all the predicted water quality data after the sample filter membrane passes through are included in the same coordinate system to obtain a predicted sample filter membrane time-water quality data curve after passing through the sample filter membrane specification.

[0063] S420, returning the water quality data of a concentration in the specification of the selected sample filter membrane, until the water quality data of each concentration in the specification of each sample filter membrane has been selected once.

[0064] Specifically, the corresponding prediction time-water quality data curve after passage is generated based on the specifications of the sample filter membrane and the concentration of the water quality data. Furthermore, multiple prediction time-water quality data curves after passage for different sample filter membrane specifications and different water quality data concentrations can be obtained, thereby forming a prediction capability with a wider coverage.

[0065] In this embodiment, the specification of a sample filter membrane is first limited as the primary condition, and then a water quality data of a random concentration is used as the second limit adjustment to obtain a segmented curve, and all the obtained segmented curves are merged into the same coordinate system based on the chronological order, and then the water quality data after all the sample filters pass through each time node are obtained, and the water quality data after the sample filters pass through each time node are screened and cleaned, and invalid data or more extreme data are deleted, and then the remaining water quality data after all the sample filters pass through the membrane are averaged, and the average value is used as the predicted water quality data after the sample filters pass through each time node.

[0066] In one embodiment of the present application, after the specification of the filter membrane to be tested and the water quality data before the filter membrane to be tested passes through are input into the filter membrane prediction model, the filter membrane prediction model is started, and the predicted time-pass rate curve and the predicted time-water quality data curve after the filter membrane to be tested output by the filter membrane prediction model are obtained, the water purification method further includes the following S710 to S750: S710, obtaining a preset pass rate value.

[0067] S720, based on the intersection of the preset pass rate value and the predicted time-pass rate curve of the filter membrane to be tested, obtain a first time coordinate parameter of the intersection.

[0068] S730, obtaining water quality data after the preset is passed.

[0069] S740, based on the intersection of the preset water quality data after passing through and the predicted time of the filter membrane to be tested-the water quality data after passing through, obtain a second time coordinate parameter of the intersection.

[0070] S750, based on the time sequence, compare the first time coordinate parameter and the second time coordinate parameter, and output the one with the earlier time as the target time node.

[0071] Specifically, the preset pass rate value and the preset water quality data after passing are set based on the properties of the filter membrane to be tested or the production requirements.

[0072] In this embodiment, the time coordinate parameter of the intersection of a preset pass rate value and a predicted time-pass rate curve of the filter membrane to be tested is calculated to obtain a first time coordinate parameter as the predicted time point for cleaning or maintenance of the filter membrane to be tested; then, the time coordinate parameter of the intersection of a preset water quality data after passing and a predicted time-water quality data curve after passing of the filter membrane to be tested is calculated to obtain a second time coordinate parameter as the predicted time point for cleaning or maintenance of the filter membrane to be tested; the first time coordinate parameter and the second time coordinate parameter are compared to take the earlier time node as the time point for cleaning or maintenance of the filter membrane to be tested.

[0073] During actual use, the predicted time-pass rate curve and the predicted time-water quality data curve after the filter membrane to be tested will be updated in real time as the water quality data before the filter membrane to be tested passes through changes. Furthermore, the first time coordinate parameter and the second time parameter are dynamic data, and therefore are more in line with the actual working process of the filter membrane.

[0074] As the operating time of each filter membrane increases, more historical operating data of the filter membrane can be updated to the operating data of the sample filter membrane, and then the predicted time-pass rate curve and predicted time-water quality data curve corresponding to the filter membrane of the corresponding specifications can be further adjusted to increase the accuracy of the prediction.

[0075] Furthermore, by combining and analyzing the time-pass rate curve of the filter membrane when a failure occurs and the water quality data on both sides of the filter membrane, data change characteristics corresponding to different failures can be generated, thereby facilitating the characteristic analysis and judgment of the filter membrane.

[0076] like Figure 2 As shown, in one embodiment of the present application, the water purification device includes a plurality of first detection elements 11 , a plurality of second detection elements 12 , a plurality of pass rate detection elements 13 , a processing device 14 and a plurality of filter membranes 15 .

[0077] The first detection member 11 is provided in plurality, and a first detection member 11 is provided on one side before each filter membrane 15 passes through, and the first detection member 11 is used to detect water quality data before the filter membrane 15 passes through.

[0078] The second detection element 12 is provided in plurality, and a second detection element 12 is provided on the side after each filter membrane 15 passes through. The second detection element 12 is used to detect the water quality data after the water passes through the filter membrane 15 .

[0079] The pass rate detection element 13 is provided in plurality, and one pass rate detection element 13 is provided on each filter membrane 15 . The pass rate detection element 13 is used to detect the pass rate data of the filter membrane 15 .

[0080] The processing device 14 is communicatively connected to the first detection component 11 , the processing device 14 is communicatively connected to the second detection component 12 , and the processing device 14 is also communicatively connected to the pass rate detection component 13 . The processing device 14 is used to execute the water purification method as described above.

[0081] In this embodiment, the first detection component 11 detects water quality data on one side of the filter membrane 15 before it passes through, and sends the detected data to the processing device 14; the second detection component 12 detects water quality data on one side of the filter membrane 15 after it passes through, and sends the detected data to the processing device 14; the pass rate detection component 13 is used to detect the passability of the filter membrane 15 in real time, and send the detected data to the processing device 14. When the passability of the filter membrane 15 is low, it is time to clean or maintain it.

[0082] The technical features of the above-described embodiments may be arbitrarily combined, and the execution order of the method steps is not limited. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0083] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A water purification method, characterized in that: The water purification method comprises: Acquire a plurality of sample filter membrane operation data, wherein the sample filter membrane operation data includes a time-pass rate curve of the sample filter membrane, water quality data on both sides of the sample filter membrane, and specifications of the sample filter membrane; Based on the water quality data on both sides of each sample filter membrane, the time-pass rate curve of the sample filter membrane is updated to obtain the updated time-pass rate curve of each sample filter membrane; Marking the updated time-pass rate curve of each sample filter membrane based on the specification of the sample filter membrane to obtain the marked time-pass rate curve of each sample filter membrane; Based on the time-pass rate curves of multiple sample filter membranes marked corresponding to the specifications of each sample filter membrane, the predicted time-pass rate curve of the specifications of each sample filter membrane and the predicted time-water quality data curve after passing are calculated; A filter membrane prediction model is created based on each time-pass rate curve, water quality data on both sides of each sample filter membrane, specifications of each sample filter membrane, time-pass rate curve of each sample filter membrane after being marked, target time-pass rate curve of each sample filter membrane, and predicted time-pass rate curve of the specifications of each sample filter membrane and predicted time-pass water quality data curve; Obtaining operating data of a filter membrane to be tested; The specification of the filter membrane to be tested and the water quality data before the filter membrane to be tested passes through are input into the filter membrane prediction model, the filter membrane prediction model is started, and the predicted time-pass rate curve and the predicted time-water quality data curve after passing through of the filter membrane to be tested are obtained as output by the filter membrane prediction model.

2. The water purification method according to claim 1, characterized in that: The time-pass rate curve of each sample filter membrane is updated based on the water quality data on both sides of the sample filter membrane to obtain the updated time-pass rate curve of each sample filter membrane, including: Select a sample filter membrane operation data; Obtaining water quality data on both sides of the sample filter membrane and a time-pass rate curve of the sample filter membrane in the sample filter membrane operation data, wherein the water quality data on both sides of the sample filter membrane include water quality data before passing through and water quality data after passing through; Based on the water quality data before and after the sample filter membrane passes through the water quality membrane, the time-pass rate curve of the sample filter membrane is updated to obtain an updated time-pass rate curve of the sample filter membrane; Return to the step of selecting a sample filter membrane operation data until each sample filter membrane operation data has been selected once.

3. The water purification method according to claim 2, characterized in that: The method of updating the time-pass rate curve of the sample filter membrane based on the water quality data before and after the sample filter membrane passes through the sample filter membrane to obtain the updated time-pass rate curve of the sample filter membrane includes: Based on the water quality data before the sample passes through the filter membrane, a time-water quality data curve before passing through is created; The time-pre-passage water quality data curve is merged into the time-passage rate curve of the sample filtration membrane to obtain the first fusion curve; Based on the water quality data after the sample passes through the filter membrane, a time-water quality data curve after passing through is created; The time-passed water quality data curve is merged into the first fusion curve to obtain the second fusion curve.

4. The water purification method according to claim 3, characterized in that: The method of marking the updated time-pass rate curve of each sample filter membrane based on the specification of the sample filter membrane to obtain the marked time-pass rate curve of each sample filter membrane includes: Select an updated time-throughput rate curve; obtaining specifications of the sample filter membrane of the updated time-passage rate curve; Marking the updated time-pass rate curve with the obtained specification of the sample filter membrane to obtain a marked updated time-pass rate curve; Return to selecting an updated time-throughput rate curve until each updated time-throughput rate curve has been selected once.

5. The water purification method according to claim 4, characterized in that: The time-pass rate curves after marking of multiple sample filter membranes corresponding to the specifications of each sample filter membrane are calculated to obtain the predicted time-pass rate curve of the specifications of each sample filter membrane and the predicted time-water quality data curve after passing, including: Select an updated time-passage rate curve in the specification of a sample filter membrane; The updated time-pass rate curve is divided based on the water quality data before the sample passes through the filter membrane to obtain a plurality of segmented curves; Return an updated time-pass rate curve in the specification of the selected sample filter membrane, until each updated time-pass rate curve in the specification of each sample filter membrane is returned.

6. The water purification method according to claim 5, characterized in that: The updated time-pass rate curve is divided based on the water quality data before the sample passes through the filter membrane to obtain multiple segmented curves, including: Analysis time - through the previous water quality data curve, obtain at least one concentration of water quality data; The updated time-passage rate curve is divided based on the water quality data of all concentrations to obtain a plurality of segmented curves.

7. The water purification method according to claim 6, characterized in that: The method of calculating the predicted time-pass rate curve and the predicted time-pass water quality data curve of each sample filter membrane specification based on the time-pass rate curves of the multiple sample filter membranes marked corresponding to the specifications of each sample filter membrane, further includes: Select a concentration of water quality data from the specification of a sample filter membrane; Analyze the water quality data of the concentration to obtain multiple segmented curves of the water quality data of the concentration; Based on the time dimension, multiple segmented curves are merged into the same coordinate system to obtain the target curve; Select a time node of the target curve; Analyze the time node to obtain the filter membrane pass rate values ​​of all samples at the time node; The average value of all sample filter membrane pass rates is calculated, and the average value is used as the predicted sample filter membrane pass rate value at the time node; Return a time node of the selected target curve until each time node of the target curve has been selected once; Based on the time sequence, all predicted sample filter membrane pass rate values ​​are included in the same coordinate system to obtain the predicted time-pass rate curve of the sample filter membrane specification; The water quality data of a concentration in the specification of the selected sample filter membrane is returned until the water quality data of each concentration in the specification of each sample filter membrane has been selected once.

8. The water purification method according to claim 7, characterized in that: The method of calculating the predicted time-pass rate curve and the predicted time-pass water quality data curve of each sample filter membrane specification based on the time-pass rate curves of the multiple sample filter membranes marked corresponding to the specifications of each sample filter membrane, further includes: Select a concentration of water quality data from the specification of a sample filter membrane; Obtain the target curve of water quality data at this concentration; Select a time node of the target curve; Analyze the time node and obtain the water quality data of all samples after passing through the filter membrane at the time node; The average value of the water quality data of all samples after passing through the filter membrane is calculated, and the obtained average value is used as the average value of the water quality data of the predicted samples after passing through the filter membrane at that time node; Return a time node of the selected target curve until each time node of the target curve has been selected once; Based on the time sequence, the average values ​​of all the predicted water quality data after the sample filter membrane passes through are included in the same coordinate system to obtain the predicted time-water quality data curve after passing through the sample filter membrane specification; The water quality data of a concentration in the specification of the selected sample filter membrane is returned until the water quality data of each concentration in the specification of each sample filter membrane has been selected once.

9. The water purification method according to claim 8, characterized in that: After the specification of the filter membrane to be tested and the water quality data before the filter membrane to be tested passes through are input into the filter membrane prediction model, the filter membrane prediction model is started, and the predicted time-pass rate curve and the predicted time-water quality data curve after the filter membrane to be tested output by the filter membrane prediction model are obtained, the water purification method further includes: Get the preset pass rate value; Based on the intersection of the preset pass rate value and the predicted time-pass rate curve of the filter membrane to be tested, a first time coordinate parameter of the intersection is obtained; Obtain water quality data after preset passing; Based on the intersection of the preset water quality data after passing through and the predicted time of the filter membrane to be tested-the water quality data after passing through, a second time coordinate parameter of the intersection is obtained; Based on the time sequence, the first time coordinate parameter and the second time coordinate parameter are compared, and the one with the earlier time is output as the target time node.

10. A water purification device, characterized in that: The water purification device comprises: A first detection member is provided in plurality, and a first detection member is provided on a side before each filter membrane passes through, and the first detection member is used to detect water quality data before the water passes through the filter membrane; The second detection element is provided in plurality, and a second detection element is provided on the side after each filter membrane passes through, and the second detection element is used to detect the water quality data after the water passes through the filter membrane; A plurality of pass rate detection components are provided, one pass rate detection component is provided on each filter membrane, and the pass rate detection component is used to detect the pass rate data of the filter membrane; A processing device is communicatively connected to the first detection component, the processing device is communicatively connected to the second detection component, and the processing device is also communicatively connected to the pass rate detection component, and the processing device is used to execute the water purification method as described in any one of claims 1-9 above.

Images