Filter element replacement monitoring method for ozone ceramic composite filter system

Abstract

The invention relates to the technical field of water treatment, in particular to a filter element replacement monitoring method for an ozone ceramic composite filter system. Comprising the following steps: acquiring basic use parameters of a to-be-monitored composite filtering system and water quality parameters of to-be-treated water; inputting various difference values of the basic use parameters and the full-load use parameters into a use state correction model, and outputting use state correction parameters; calculating water quality correction parameters according to the water quality parameters of the to-be-treated water; and multiplying the reference filter element replacement time by the use state correction parameter and the water quality correction parameter in sequence to calculate the filter element replacement time. According to the method, the use state of the ozone ceramic composite filter system and the water quality of the water to be treated are evaluated respectively, the accuracy of predicting the replacement time can be effectively improved, and the maintenance cost is remarkably reduced on the premise of ensuring the safety of the water quality.

Description

Technical Field

[0001] The invention relates to the technical field of water treatment, and in particular to a filter element replacement monitoring method for an ozone ceramic composite filtration system. Background Art

[0002] Ozone is a strong oxidant. Its strong oxidizing property can quickly react with organic matter in water, destroying bacterial and viral cell walls, nucleic acids and protein structures, thereby achieving the purpose of purifying water quality and sterilizing. However, ozone disinfection itself does not have the effect of filtering and purifying water. Therefore, in the process of direct drinking water treatment, it can only be used as one of the filtering methods. The common usage is ozone disinfection combined with ceramic filtration.

[0003] The basic principle of ceramic filters is to purify fluids through the combination of a porous body and a filter membrane. The fluid passes through the porous body and the filter membrane, and after being purified, it flows out from the openings on the outer peripheral surface or the end surface.

[0004] The composite filtration system of ozone combined with ceramic filtration has good disinfection and filtration water treatment capabilities. Its disadvantage is that with long-term use, the ceramic filter membrane will absorb a large amount of dirt and the water quality of the outlet will decrease over time.

[0005] The common solution is to replace or clean the ceramic filter membrane regularly. However, the timing of replacing the ceramic filter membrane is not only related to the intensity and time of use of the ozone ceramic composite filter system, but also to the water quality of the water to be filtered. In this case, how to determine the maintenance time of the ozone ceramic composite filter system under different working environments is a technical problem that needs to be solved urgently. Summary of the invention

[0006] The present invention discloses a filter element replacement monitoring method for an ozone ceramic composite filtration system, wherein the ozone ceramic composite filtration system comprises an ozone disinfection subsystem and a ceramic filtration subsystem. After the water to be treated is disinfected by the ozone disinfection subsystem, it is filtered by the ceramic filtration subsystem. The specific method is as follows:

[0007] Obtain the basic usage parameters of the composite filtration system to be monitored and the water quality parameters of the water to be treated;

[0008] Calculate the differences between basic usage parameters and full load usage parameters;

[0009] Input each difference into the usage state correction model and output the usage state correction parameters;

[0010] Calculate water quality correction parameters according to water quality parameters of the water to be treated;

[0011] The filter element replacement time of the ceramic filter subsystem of the composite filter system to be monitored is calculated by multiplying the reference filter element replacement time by the usage status correction parameter and the water quality correction parameter in sequence.

[0012] The advantage of this embodiment is that the use status of the ozone ceramic composite filtration system and the water quality of the water to be treated are evaluated separately, which can effectively improve the accuracy of predicting the replacement time and significantly reduce maintenance costs while ensuring water quality safety.

[0013] Furthermore, the basic usage parameters include:

[0014] The operating time of the ozone disinfection subsystem per unit cycle time;

[0015] Average load of ozone disinfection subsystem per unit cycle time;

[0016] The operation time of the ceramic filtration subsystem per unit cycle time;

[0017] The average load of the ceramic filtration subsystem per unit cycle time.

[0018] The advantage of this embodiment is that, for the composite system, the working conditions of the two series subsystems are taken into consideration. Compared with considering the working conditions of the composite system alone, the replacement time prediction accuracy of the ozone ceramic filter system can be significantly improved.

[0019] Furthermore, the average load of the ozone disinfection subsystem per unit cycle time is calculated as follows:

[0020] Obtain the maximum amount of water filtered by the ozone disinfection subsystem within a unit cycle time;

[0021] Record the average amount of water filtered by the ozone disinfection subsystem per unit cycle time;

[0022] The average load of the ozone disinfection subsystem in a unit cycle is calculated by dividing the average filtered water volume of the ozone disinfection subsystem in a unit cycle by the maximum filtered water volume;

[0023] The average load of the ceramic filtration subsystem per unit cycle time is calculated as follows:

[0024] Obtain the maximum filtered water volume of the ceramic filtration subsystem within a unit cycle time;

[0025] Record the average filtered water volume of the ceramic filtration subsystem per unit cycle time;

[0026] The average load of the ceramic filtration subsystem per unit cycle is calculated by dividing the average filtered water volume of the ceramic filtration subsystem per unit cycle by the maximum filtered water volume.

[0027] The advantage of this embodiment is that, when testing the load, normalization processing is adopted to unify the working time of different subsystems into a ratio, which is convenient for later model training.

[0028] Furthermore, the differences between the basic usage parameters and the full load usage parameters are calculated as follows:

[0029] The unit cycle time minus the running time of the ozone disinfection subsystem within the unit cycle time, and then divided by the unit cycle time, the running difference of the ozone disinfection subsystem is calculated;

[0030] 1 minus the average load of the ceramic filtration subsystem in the unit cycle time to calculate the load difference of the ozone disinfection subsystem;

[0031] The unit cycle time minus the operation time of the ceramic filtration subsystem within the unit cycle time, and then divided by the unit cycle time, the operation difference of the ceramic filtration subsystem is calculated;

[0032] 1 minus the average load of the ceramic filtration subsystem in unit cycle time to calculate the load difference of the ceramic filtration subsystem.

[0033] The advantage of this embodiment is that it uses the difference between the composite filtering system and the benchmark usage as the data input, which can highlight the characteristic differences between the data to be predicted and the benchmark data, and has a higher accuracy in subsequent prediction analysis.

[0034] Furthermore, a usage status correction model is constructed, and the specific method is as follows:

[0035] The same ozone ceramic composite filtration system was selected as the benchmark composite filtration system;

[0036] The benchmark composite filtration system processes benchmark water at the maximum water output efficiency and records the output water quality information. When the output water quality is lower than expected, the working time of the benchmark composite filtration system is recorded as the benchmark filter element replacement time;

[0037] Replace the ceramic filter subsystem filter element of the benchmark composite filter system, conduct several filtration tests with different ozone disinfection subsystem operating time, different ozone disinfection subsystem average load, different ceramic filter subsystem operating time and different ceramic filter subsystem average load, and record the test filter element replacement time for each filtration test;

[0038] Divide the test filter element replacement time by the reference filter element replacement time and record it as the usage status correction parameter for each filtration test;

[0039] The training samples are constructed based on the difference between the running time of the ozone disinfection subsystem and the full-load usage parameters, the difference between the average load of the ozone disinfection subsystem and the full-load usage parameters, the difference between the running time of the ceramic filtration subsystem and the full-load usage parameters, the difference between the average load of the ceramic filtration subsystem and the full-load usage parameters, and the corresponding usage status correction parameters of each filtration test;

[0040] The BP neural network model is trained with training samples until the model converges.

[0041] The advantage of this embodiment is that the BP neural network model is used to fit the functional relationship between input and output data, and the prediction accuracy and operability are higher for the multi-data nonlinear data prediction of the composite filtering system. When constructing the training samples, the actual conditions of the two subsystems are taken into consideration to ensure that key data will not be missed.

[0042] Furthermore, the water quality correction parameters are calculated as follows:

[0043] Select the water to be treated whose water quality parameters are at the average value as the treatment benchmark water;

[0044] Obtaining a number of untreated waters of different water qualities as a number of test waters;

[0045] The benchmark composite filtration system uses the maximum water effluent efficiency to filter and treat the benchmark water and several test waters respectively until the effluent water quality is lower than the design value, and the working time of the benchmark composite filtration system filtering and treating the benchmark water and several test waters is recorded;

[0046] The working time of filtering different test water is divided by the working time of filtering the reference water to calculate the water quality correction parameters of different test water;

[0047] Linear fitting of the functional relationship between water quality parameters and water quality correction parameters for different water quality tests;

[0048] The water quality parameters of the water to be treated are input into the combined function to calculate the water quality correction parameters.

[0049] The advantage of this embodiment is that the water quality is an important parameter that affects the replacement time of the filter membrane, and a separate analysis of the water quality can improve the final prediction result.

[0050] Other advantages, objectives and features of the present invention will be described in the following description to some extent, and to some extent, will be obvious to those skilled in the art based on the following examination and study, or can be taught from the practice of the present invention. The objectives and other advantages of the present invention can be achieved and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The accompanying drawings of the present invention are as follows.

[0052] Figure 1 It is a schematic diagram of the overall process of the present invention.

[0053] Figure 2 This is a schematic diagram of the subsystem average load calculation process.

[0054] Figure 3 Schematic diagram of the process of constructing a usage status correction model. DETAILED DESCRIPTION

[0055] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0056] A filter element replacement monitoring method for an ozone ceramic composite filter system, such as Figure 1 As shown, the specific steps are as follows:

[0057] S1. Obtain basic usage parameters of the composite filtration system to be monitored and water quality parameters of the water to be treated.

[0058] The basic usage parameters include: the operating time Ot of the ozone disinfection subsystem per unit cycle time, the average load Op of the ozone disinfection subsystem per unit cycle time, the operating time Ct of the ceramic filtration subsystem per unit cycle time, and the average load Cp of the ceramic filtration subsystem per unit cycle time.

[0059] The water quality parameters of the water to be treated include organic matter content a, inorganic salt content b, microbial content c, heavy metal content d, and turbidity e.

[0060] S2. Calculate the differences between basic usage parameters and full load usage parameters.

[0061] S21. The difference between the running time Ot of the ozone disinfection subsystem in unit cycle time and the full load usage parameter D Ot , the calculation method is as follows:

[0062]

[0063] Where T is the unit cycle length.

[0064] S22, the difference between the average load Op of the ozone disinfection subsystem in the unit cycle time and the full load usage parameter D Op ,like Figure 2 As shown, the calculation method is as follows:

[0065] Get the maximum filtered water volume Ov of the ozone disinfection subsystem in unit cycle time max ;

[0066] Record the average filtered water volume OV of the monitored ozone disinfection subsystem in the current unit cycle time average ;

[0067] Calculate the average load Op of the ozone disinfection subsystem per unit cycle time:

[0068]

[0069] D Op =1-Op

[0070] S23. The difference between the operation time Ct of the ceramic filter subsystem in unit cycle time and the full load usage parameter D Ct , the calculation method is as follows:

[0071]

[0072] S24. The difference between the average load Cp of the ceramic filter subsystem and the full load usage parameter within a unit cycle time D Cp ,like Figure 2 As shown, the calculation method is as follows:

[0073] Get the maximum filtered water volume Cv of the ceramic filtration subsystem per unit cycle time max ;

[0074] Record the average filtered water volume Cv of the ceramic filter subsystem to be monitored in the current unit cycle time average ;

[0075] Calculate the average load Op of the ozone disinfection subsystem per unit cycle time:

[0076]

[0077] D Cp =1-Cp.

[0079] S3, the difference of each item, that is, D Ot , D Op , D Ct and D Cp , input the usage state correction model, and output the usage state correction parameter w1.

[0080] Construct a usage status correction model, such as Figure 3 As shown, the specific method is as follows:

[0081] S31. Select the same ozone ceramic composite filtration system as the benchmark composite filtration system;

[0082] S32, the benchmark composite filtration system processes the benchmark water with the maximum water output efficiency, records the water quality information of the output water, and when the output water quality is lower than expected, records the working time of the benchmark composite filtration system as the benchmark filter element replacement time Rt;

[0083] The effluent water quality information includes organic matter content a, inorganic salt content b, microbial content c, heavy metal content d, and turbidity e.

[0084] S33. Replace the filter element of the ceramic filter subsystem of the benchmark composite filter system, and conduct several filtration tests with different ozone disinfection subsystem operation time, different ozone disinfection subsystem average load, different ceramic filter subsystem operation time and different ceramic filter subsystem average load, and record the test filter element replacement time Et for each filtration test i , i is the filtration test number;

[0085] S34, dividing the test filter element replacement time by the reference filter element replacement time, and recording it as the usage status correction parameter for each filtration test, that is,

[0086] S35. Construct training samples based on the difference between the running time of the ozone disinfection subsystem and the full load usage parameters of each filtration test, the difference between the average load of the ozone disinfection subsystem and the full load usage parameters, the difference between the running time of the ceramic filtration subsystem and the full load usage parameters, the difference between the average load of the ceramic filtration subsystem and the full load usage parameters, and the corresponding usage status correction parameters.

[0087] S36, training the BP neural network model with the training samples until the model converges.

[0088] S4. Calculate water quality correction parameters based on the water quality parameters of the water to be treated.

[0089] Calculate the water quality correction parameters as follows:

[0090] S41. Select the water to be treated whose water quality parameters are at the average value as the treatment reference water 0 ;

[0091] S42. Obtain some untreated water of different water quality as some test water j ;

[0092] S43, the benchmark composite filtration system processes at the maximum water output efficiency, and filters and processes the benchmark water and some test water respectively, until the water quality of the effluent is lower than the design value, and records the working time wt of the benchmark composite filtration system filtering and processing the benchmark water 0 And the working time of several test water wt j ;

[0093] S44. Divide the working time of filtering different test water by the working time of filtering the reference water to calculate the water quality correction parameters of different test water, that is,

[0094] S45, linear fitting of the functional relationship between water quality parameters and water quality correction parameters of water used for different water quality tests;

[0095] S46. The function obtained by combining the water quality parameters of the water to be treated is used to calculate the water quality correction parameter w2.

[0096] S5. Multiply the reference filter element replacement time by the usage status correction parameter and the water quality correction parameter in sequence to calculate the filter element replacement time of the ceramic filter subsystem of the composite filter system to be monitored. The calculation formula is as follows:

[0097] Rt×w1×w2.

[0099] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A filter element replacement monitoring method for an ozone ceramic composite filtration system, wherein the ozone ceramic composite filtration system comprises an ozone disinfection subsystem and a ceramic filtration subsystem, wherein the water to be treated is disinfected by the ozone disinfection subsystem and then filtered by the ceramic filtration subsystem, wherein: The specific method is as follows: Obtain the basic usage parameters of the composite filtration system to be monitored and the water quality parameters of the water to be treated; Calculate the differences between basic usage parameters and full load usage parameters; Input each difference into the usage state correction model and output the usage state correction parameters; Calculate water quality correction parameters according to water quality parameters of the water to be treated; The filter element replacement time of the ceramic filter subsystem of the composite filter system to be monitored is calculated by multiplying the reference filter element replacement time by the usage status correction parameter and the water quality correction parameter in sequence.

2. The filter element replacement monitoring method for an ozone ceramic composite filtration system according to claim 1, characterized in that: The basic usage parameters include: The operating time of the ozone disinfection subsystem per unit cycle time; Average load of ozone disinfection subsystem per unit cycle time; The operation time of the ceramic filtration subsystem per unit cycle time; The average load of the ceramic filtration subsystem per unit cycle time.

3. The filter element replacement monitoring method for an ozone ceramic composite filtration system according to claim 2, characterized in that: The average load of the ozone disinfection subsystem per unit cycle time is calculated as follows: Obtain the maximum amount of water filtered by the ozone disinfection subsystem within a unit cycle time; Record the average amount of water filtered by the ozone disinfection subsystem per unit cycle time; The average load of the ozone disinfection subsystem in a unit cycle is calculated by dividing the average filtered water volume of the ozone disinfection subsystem in a unit cycle by the maximum filtered water volume; The average load of the ceramic filtration subsystem per unit cycle time is calculated as follows: Obtain the maximum filtered water volume of the ceramic filtration subsystem within a unit cycle time; Record the average filtered water volume of the ceramic filtration subsystem per unit cycle time; The average load of the ceramic filtration subsystem per unit cycle is calculated by dividing the average filtered water volume of the ceramic filtration subsystem per unit cycle by the maximum filtered water volume.

4. The filter element replacement monitoring method for an ozone ceramic composite filtration system according to claim 3, characterized in that: Calculate the differences between basic usage parameters and full load usage parameters as follows: The unit cycle time minus the running time of the ozone disinfection subsystem within the unit cycle time, and then divided by the unit cycle time, the running difference of the ozone disinfection subsystem is calculated; 1 minus the average load of the ceramic filtration subsystem in the unit cycle time to calculate the load difference of the ozone disinfection subsystem; The unit cycle time minus the operation time of the ceramic filtration subsystem within the unit cycle time, and then divided by the unit cycle time, the operation difference of the ceramic filtration subsystem is calculated; 1 minus the average load of the ceramic filtration subsystem in unit cycle time to calculate the load difference of the ceramic filtration subsystem.

5. The filter element replacement monitoring method for an ozone ceramic composite filtration system according to claim 1, characterized in that: Construct a usage status correction model. The specific method is as follows: The same ozone ceramic composite filtration system was selected as the benchmark composite filtration system; The benchmark composite filtration system processes benchmark water at the maximum water output efficiency and records the output water quality information. When the output water quality is lower than expected, the working time of the benchmark composite filtration system is recorded as the benchmark filter element replacement time; Replace the ceramic filter subsystem filter element of the benchmark composite filter system, conduct several filtration tests with different ozone disinfection subsystem operating time, different ozone disinfection subsystem average load, different ceramic filter subsystem operating time and different ceramic filter subsystem average load, and record the test filter element replacement time for each filtration test; Divide the test filter element replacement time by the reference filter element replacement time and record it as the usage status correction parameter for each filtration test; The training samples are constructed based on the difference between the running time of the ozone disinfection subsystem and the full-load usage parameters, the difference between the average load of the ozone disinfection subsystem and the full-load usage parameters, the difference between the running time of the ceramic filtration subsystem and the full-load usage parameters, the difference between the average load of the ceramic filtration subsystem and the full-load usage parameters, and the corresponding usage status correction parameters of each filtration test; The BP neural network model is trained with training samples until the model converges.

6. The filter element replacement monitoring method for an ozone ceramic composite filtration system according to claim 1, characterized in that: Calculate the water quality correction parameters as follows: Select the water to be treated whose water quality parameters are at the average value as the treatment benchmark water; Obtaining a number of untreated waters of different water qualities as a number of test waters; The benchmark composite filtration system uses the maximum water effluent efficiency to filter and treat the benchmark water and several test waters respectively until the effluent water quality is lower than the design value, and the working time of the benchmark composite filtration system filtering and treating the benchmark water and several test waters is recorded; The working time of filtering different test water is divided by the working time of filtering the reference water to calculate the water quality correction parameters of different test water; Linear fitting of the functional relationship between water quality parameters and water quality correction parameters for different water quality tests; The water quality parameters of the water to be treated are input into the combined function to calculate the water quality correction parameters.

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