Method for improving operation efficiency of filter tank

Abstract

The invention discloses a method for improving the operation efficiency of a filter tank, and belongs to the technical field of water treatment.The method includes the steps that the situation change rule of a filter material of the filter tank in the backwashing process is observed, the optimal backwashing state is found, and the internal mechanism relation of the porosity of the filter material, the expansion rate of the filter material, backwashing parameters and the like is established; the overall operation effect of the filter tank is judged, the health degree of the filter tank is evaluated, the manual inspection intensity is reduced, management personnel are assisted in decision analysis, early warning is facilitated, and the operation efficiency of the filter tank is improved while the water quality safety of effluent of the filter tank is guaranteed. The whole operation is more reasonable and intelligent, water resources are saved, the burden of a water treatment process is reduced, management is carried out in units, monitoring of daily operation is met, the opportunity of supplementing or updating of the filter material is guided through evaluation of the health degree of the filter material, and scientific early warning and refined operation and maintenance are met.

Description

Technical Field

[0001] The invention belongs to the technical field of water treatment, and in particular relates to a method for improving the operating efficiency of a filter tank. Background Art

[0002] In water treatment technology, filtration is generally used as a follow-up process of sedimentation process. Suspended matter in water is intercepted and separated by filter media. Filter media generally use quartz sand, anthracite, ceramsite, etc. Taking drinking water purification process as an example, after filtering through the filter tank, the turbidity of water can reach below 1NTU. When the turbidity of raw water is low all year round, sometimes the sedimentation or clarification structure is omitted and the direct filtration process is adopted. In tap water treatment, filtration is the main measure to ensure the sanitation and safety of water quality and is an indispensable treatment unit. Similarly, in the treatment of recycled water, rainwater and sewage, the filtration process is also widely used.

[0003] As a key structure in the water treatment process, when the "pollution load" of a filter cell reaches a critical value, the filter media of the filter cell needs to be backwashed to restore the water production capacity. At the same time, when the filtering and intercepting capacity cannot be restored by backwashing or the service life has reached a certain period of time, the filter media needs to be supplemented or replaced.

[0004] As a key link in the process of water plant, the filter tank's operation stability has always been the focus of water plant managers. It is particularly important to ensure the safety of the filter tank and improve its operation efficiency.

[0005] The filtering effect of the filter directly affects the effluent quality. At present, the main method to judge the effect of the filter is to detect the effluent quality of the filter, such as measuring water quality indicators such as turbidity or suspended solids through instruments; the filtering capacity recovery (backwashing) of the filter is mainly triggered by different means such as periodic backwashing, head loss monitoring, and liquid level monitoring.

[0006] However, the current design concept of the filter technology only monitors the inlet and outlet water quality, liquid level, head loss, etc., which brings the following problems:

[0007] 1. At present, in addition to setting up conventional turbidity meters, liquid level meters, water loss differential pressure meters and other instrument monitoring, the backwashing of the filter pool mainly relies on manual judgment or regular periodicity. Regular periodic backwashing is a relatively rough management method. Due to the limitations of the fluctuation of filter water inflow, the different degrees of attenuation of filter media filtration capacity and the different recovery effects of previous backwashing, regular periodic flushing does not capture the best flushing time point, which causes a certain degree of waste of water resources. At the same time, as the filtration capacity of the filter media gradually decreases, the regular periodic method will be difficult to meet the needs of filter media capacity recovery.

[0008] 2. The filter backwash recovery effect can be comprehensively judged by backwash resource consumption (water consumption, power consumption, etc.), backwash cycle, flushing duration and filtered water quality after backwashing. This judgment method is a "post-analysis" of process operation and it is difficult to form "pre-guidance". The inherent connection and control feedback between operation parameters and operation results have not been established, so the overall filter operation efficiency is low.

[0009] 3. The combination of preset control programs (such as backwash water pumps and fans) often ignores the influence of micro factors. For example, the temperature is lower in winter, so less flushing water is needed to achieve the same effect. There is a lack of relevant evaluation on flushing uniformity. For example, the flushing degree of filter materials close to and far from the backwash water and air inlet is not consistent. The current situation is only macro effect control. Summary of the invention

[0010] In order to solve the problems raised in the above background technology, the present invention provides a method for improving the operating efficiency of the filter bed, so as to solve the problems in the prior art that the fixed-period method will be difficult to meet the demand for filter material capacity recovery, the overall filter bed operating efficiency is low, and the preset control program combination often ignores the influence of microscopic factors.

[0011] To achieve the above object, the present invention provides the following technical solutions:

[0012] A method for improving the operating efficiency of a filter tank comprises the following steps:

[0013] S1: A camera device is arranged at regular intervals along the filter tank wall, and the camera device is used to continuously monitor the status data of the filter material in the filter tank;

[0014] S2: Analyze the situation data to form a filter material expansion curve, and analyze the filter material expansion rate by combining the filter material expansion curve with the filter material porosity;

[0015] S3: Correlate the expansion rate of the filter media with the corresponding backwashing process parameters and the water quality recovery effect after backwashing to find the optimal expansion rate that adapts to the characteristics of the filter bed;

[0016] S4: Find the optimal backwashing process parameters corresponding to the optimal expansion ratio and use them as the optimization support for the backwashing instruction.

[0017] Preferably, S1 is specifically as follows: a unit is divided at regular intervals along the filter tank wall, for a total of n units, and n camera devices are respectively responsible for image acquisition of the n units, n>0, and when the filter tank is in the filtering state and the backwashing state, each camera device collects the filter material status data of the unit corresponding to itself.

[0018] Preferably, the specific calculation method of the filter material expansion curve is:

[0019] The equivalent position of the filter material of the nth unit when the filter tank is in the filtering state is Ln , the equivalent position of the filter material in the backwash state is L n1 , then the equivalent expansion rate of the nth unit is e n =(L n1 -L n )÷L n ×100%, the equivalent expansion rates of each unit are processed together and spliced ​​to form a filter material expansion curve;

[0020] At the same time, there are the following relationships:

[0021] L n1 (1-m n )=L n (1-m 0n );

[0022] In the formula, m 0n represents the porosity of the filter material before unit expansion, m n It represents the porosity of the filter material after the expansion of n units. Combining the above two equations, we can get the relationship between the expansion rate of the filter material and the porosity of the filter material:

[0023] e n =(m n -m 0n )÷(1-m n ).

[0024] Preferably, in S3, the Mintz-Schubert formula is used to establish a correlation formula between the filter material expansion rate, the backwashing process parameters and the water quality recovery effect after backwashing:

[0025] ;

[0026] In the formula, q is the backwash intensity, d0 is the diameter of a sphere with the same volume as the filter media particles, μ is the dynamic viscosity of water, and m0 is the porosity of the filter media before unit expansion;

[0027] In the above formula, d0, μ, and m0 are all initial parameters. The water quality changes corresponding to different backwashing parameters in each backwashing are assigned and sorted, and the optimal expansion rate is found in combination with the expansion rate corresponding to the backwashing parameters.

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] This application observes the changing patterns of the filter media in the filter bed during the backwashing process, finds the optimal backwashing state, establishes the internal mechanism relationship between the filter media porosity-filter media expansion rate-backwashing parameters, and judges the overall operation effect of the filter bed. It evaluates the health of the filter bed, reduces the intensity of manual inspections and assists management personnel in decision-making and analysis, which is conducive to early warning, ensuring the safety of the water quality of the filter bed effluent while improving the operation efficiency of the filter bed. This application can replace the original periodic flushing method, making the overall operation more reasonable and intelligent, saving water resources and reducing the burden on the water treatment process. This application is managed in units to meet the monitoring of daily operations. The evaluation of the health of the filter media guides the timing of filter media replenishment or renewal, meets scientific warning, and refined operation and maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 This is a flowchart of the application;

[0031] Figure 2 A schematic diagram of the installation position of the camera device;

[0032] Figure 3 It is a schematic diagram of the calculation method of the filter material expansion curve;

[0033] Figure 4 Schematic diagram of filter material distribution. DETAILED DESCRIPTION

[0034] In order to facilitate those skilled in the art to understand the technical content of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific examples. It should be understood that the specific examples described herein are only used to explain the present invention and are not used to limit the present invention.

[0035] Example 1

[0036] like Figure 1 As shown, a method for improving the operating efficiency of a filter tank comprises the following steps:

[0037] S1: Figure 2 As shown, a unit is divided at regular intervals along the filter tank wall, for a total of n units. N cameras are responsible for image acquisition of n units, where n>0. When the filter tank is in the filtering state and the backwashing state, each camera collects the filter material status data of its corresponding unit at intervals of △t (△t≥0). In the filtering state, the filter material status data can be used to calculate the amount of filter material, judge the uniformity and health, and issue an early warning for supplementation and replacement of filter material based on the above data.

[0038] S2: Analyze the situation data to form a filter material expansion curve. The filter material expansion curve is combined with the filter material porosity to analyze the filter material expansion rate. The specific calculation method of the filter material expansion curve is:

[0039] like Figure 3 and Figure 4 As shown, the equivalent position of the filter material of the nth unit when the filter tank is in the filtering state is L n , the equivalent position of the filter material in the backwash state is L n1 , then the equivalent expansion rate of the nth unit is e n =(L n1 -L n )÷L n ×100%, the equivalent expansion rates of each unit are processed together and spliced ​​to form a filter material expansion curve;

[0040] At the same time, since the volume of filter media in the filter tank does not change in theory before and after expansion, but the pore volume of the filter media increases, the following relationship exists:

[0041] L n1 (1-m n )=L n (1-m 0n );

[0042] In the formula, m 0n represents the porosity of the filter material before unit expansion, m n It represents the porosity of the filter material after the expansion of n units. Combining the above two equations, we can get the relationship between the expansion rate of the filter material and the porosity of the filter material:

[0043] e n =(m n -m 0n )÷(1-m n ).

[0044] S3: Correlate the filter media expansion rate with the corresponding backwashing process parameters and the water quality recovery effect after backwashing to find the optimal expansion rate that adapts to the filter characteristics; use the Mintz-Schubert formula to establish the correlation formula between the filter media expansion rate, backwashing process parameters and the water quality recovery effect after backwashing:

[0045] ;

[0046] In the formula, q is the backwash intensity, d0 is the diameter of a sphere with the same volume as the filter media particles, μ is the dynamic viscosity of water, and m0 is the porosity of the filter media before unit expansion;

[0047] In the above formula, d0, μ, and m0 are all initial parameters. The corresponding parameters of each backwashing, the expansion rate of the filter material, and the changes in water quality before and after backwashing are associated. The changes in water quality corresponding to different backwashing parameters in each time are assigned and sorted, and the optimal expansion rate is found in combination with the expansion rate corresponding to the backwashing parameters;

[0048] S4: Find the best backwashing process parameters corresponding to the best expansion rate, use them as the optimization support for the backwashing instructions, and store the best results as historical working condition samples in the experience library. The next time you seek the optimal solution, you can refer to the historical working condition samples and influencing factors (weather, temperature, etc.) in the experience library.

[0049] In this embodiment, when a filter tank is backwashed, each camera device collects images of the filter material distribution position in its own coverage area in real time. After being processed by the image recognition algorithm, the filter material expansion curve at the corresponding moment and the filter material porosity of each unit are quantified. Since the flushing intensity of each unit will be different in actual situations, the flushing intensity of each unit is uneven. Generally, the closer the unit is to the flushing air pipe or water pipe, the greater the flushing intensity is, and the filter material may be lost. The farther the unit is from the flushing air pipe or water pipe, the smaller the flushing intensity is, and the filter material's ability to intercept pollution may be insufficiently restored. The flushing intensity mentioned in the design and operation process is the average value obtained by dividing the flushing flow of the fan or water pump by the filter material area. This is still a gap for refined management and achieving the global optimal goal. It is expected that through this unit-based management, attention will be paid to the changes in the filter material from a micro level, and the internal connection between the flushing parameters and the filter material characteristics will be established to form an "optimal instruction" and continue to pay attention.

[0050] Because the performance of the filter material tends to gradually decrease during operation, the camera device continuously monitors and updates with use, provides early warning information and makes overall judgments in the case of insufficient filter material thickness and loss. In addition to providing the best backwashing time and backwashing parameters, it also provides the best time to update the filter material. After image recognition algorithm processing, it quantifies the health of the regional filter material and hierarchically distinguishes the real-time filter material characteristics of different positions in the filter tank, replacing the original rough management mode of fixed-period flushing. At the same time, it makes up for the deficiency of manual inspections in judging the health of the filter material, avoids the waste of water resources, and makes the operation and management of the water plant more intelligent.

[0051] It should be noted that the filtration and backwashing characteristics of the filter bed are also affected by factors such as sudden changes in water quality, water volume, dosage, water temperature and external interference. On the basis of analyzing the filter media situation to improve the overall filter bed operation efficiency, the flushing parameter planning should also be weighted according to the degree of influence. For example, in winter, the water temperature is lower and the water viscosity coefficient is higher. Under the same flushing intensity conditions, the expansion rate of the filter layer increases, and less backwashing water can be used.

[0052] The purpose of the present invention is to predict the optimal backwashing state by observing the changing rules of the state of the filter media in the backwashing process, establish the inherent mechanism relationship between the filter media porosity-filter media expansion rate-backwashing parameters, and judge the overall operation effect of the filter. Evaluating the health of the filter, reducing the intensity of manual inspections and assisting management personnel in decision-making and analysis, is conducive to early warning, ensuring the safety of the water quality of the filter effluent while improving the operation efficiency of the filter. By introducing the application method of image recognition technology, the state of the filter media is observed, and combined with the changes in the expansion of the filter media during backwashing, the relationship between the optimal expansion rate and the optimal flushing parameters is quantified through the collection and analysis of a large amount of data, and the overall optimality is achieved through effect evaluation. This kind of visual image collection and analysis introduces big data thinking, realizes truly intelligent operation, and is suitable for various new or renovation projects using filter technology.

Claims

1. A method for improving the operating efficiency of a filter tank, characterized in that: The following steps are involved: S1: A camera device is arranged at regular intervals along the filter tank wall, and the camera device is used to continuously monitor the status data of the filter material in the filter tank; S2: Analyze the situation data to form a filter material expansion curve, and analyze the filter material expansion rate by combining the filter material expansion curve with the filter material porosity; S3: Correlate the expansion rate of the filter media with the corresponding backwashing process parameters and the water quality recovery effect after backwashing to find the optimal expansion rate that adapts to the characteristics of the filter bed; S4: Find the optimal backwashing process parameters corresponding to the optimal expansion ratio and use them as the optimization support for the backwashing instruction.

2. A method for improving the operating efficiency of a filter tank according to claim 1, characterized in that: S1 is specifically as follows: a unit is divided at regular intervals along the filter tank wall, for a total of n units, and n cameras are respectively responsible for collecting images of the n units, n>0. When the filter tank is in the filtering state and the backwashing state, each camera collects the filter material status data of the unit corresponding to itself.

3. A method for improving filter bed operation efficiency according to claim 2, characterized in that: The specific calculation method of the filter material expansion curve is: The equivalent position of the filter material of the nth unit when the filter tank is in the filtering state is L n , the equivalent position of the filter material in the backwash state is L n1 , then the equivalent expansion rate of the nth unit is e n =(L n1 -L n )÷L n ×100%, the equivalent expansion rates of each unit are processed together and spliced ​​to form a filter material expansion curve; At the same time, there are the following relationships: L n1 (1-m n )=L n (1-m 0n ); In the formula, m 0n represents the porosity of the filter material before unit expansion, m n It represents the porosity of the filter material after the expansion of n units. Combining the above two equations, we can get the relationship between the expansion rate of the filter material and the porosity of the filter material: e n =(m n -m 0n )÷(1-m n )。 4. A method for improving filter bed operation efficiency according to claim 1, characterized in that: In S3, the Mintz-Schubert formula was used to establish the correlation formula between the filter media expansion rate, backwashing process parameters and the water quality recovery effect after backwashing: ； In the formula, q is the backwash intensity, d0 is the diameter of a sphere with the same volume as the filter media particles, μ is the dynamic viscosity of water, and m0 is the porosity of the filter media before unit expansion; In the above formula, d0, μ, and m0 are all initial parameters. The water quality changes corresponding to different backwashing parameters in each backwashing are assigned and sorted, and the optimal expansion rate is found in combination with the expansion rate corresponding to the backwashing parameters.

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