Method for optimizing water distribution of multi-series parallel secondary sedimentation tank

Abstract

The application provides a multi-series parallel secondary sedimentation tank water inflow distribution optimization method, aiming at the analysis of daily water inflow, mixed liquid sludge concentration, and backflow sludge concentration and other data of actual treatment conditions, the backflow of each series is calculated through material balance back calculation, the concentration ratio is calculated as a sedimentation performance evaluation index, the actual solid load of each series of secondary sedimentation tanks is calculated, and the water inflow of each series is redistributed. The method can greatly eliminate the mud running phenomenon caused by overloading water inflow in the biological treatment series, reduce the filter clogging frequency, reduce the backwashing water, electricity consumption and coagulant dosage, prolong the service life of the filter material, and improve the stability and operation economy of the sewage treatment system.

Description

Technical Field

[0001] This invention belongs to the field of water treatment technology, and in particular relates to an optimized method for the influent distribution of multiple parallel secondary sedimentation tanks. Background Technology

[0002] Secondary sedimentation tanks are the core unit of wastewater biological treatment processes, responsible for solid-liquid separation of the effluent from the biological treatment tank. Their operational performance decisively impacts the energy consumption, chemical consumption, and lifespan of subsequent advanced treatment units. The existing design uses multiple parallel radial flow secondary sedimentation tanks, which suffer from uneven distribution of return flow rates among the different series. The return pump stations are affected by factors such as differences in pipeline friction resistance, local resistance of valves and fittings, and inconsistent performance degradation of the return pumps, resulting in significant deviations in the actual return flow rates of each series. This deviation cannot be self-balanced during operation, leading to a difference in the total treatment flow rate of different secondary sedimentation tanks that can reach thousands to tens of thousands of cubic meters per day, resulting in a severely unbalanced solid load distribution. Under the current conventional operating mode, operators can only visually inspect the floating sludge on the tank surface and the turbidity of the effluent to determine if there is sludge leakage. However, the gradual rise of the sludge layer and the exceeding of solid load limits occur entirely below the liquid surface, making early detection difficult. After a malfunction occurs, suspended solids (SS), COD, and total phosphorus in the effluent often exceed standards simultaneously. This leads to rapid clogging of subsequent filters, doubling of backwashing frequency, and a significant increase in chemical and power consumption. In severe cases, it can even cause sludge loss and operational instability throughout the entire system. Current industry-standard optimization solutions generally rely on hardware modifications such as installing online flow meters, modifying return pipelines, and adding regulating valves. These modifications are not only costly but also require shutdowns for construction, making them unsuitable for the low-cost optimization needs of existing wastewater treatment plants. Furthermore, existing technologies directly calculate return flow rate using the rated flow rate of the return pump and on-site instantaneous sampling to determine the return sludge concentration. This method is susceptible to sampling point deviations and fluctuations in operating conditions, resulting in highly discrete calculation results. It often leads to distortions where the return ratio exceeds the reasonable range for the project, making it completely unsuitable for accurate load calculation. Summary of the Invention

[0003] In view of this, the present invention aims to propose an optimized method for the influent distribution of multiple series of parallel secondary sedimentation tanks, which achieves the balancing of solid load across the entire series by redistributing the influent flow rate, thereby reducing the risk of sludge runoff from the secondary sedimentation tank at its source.

[0004] To achieve the above objectives, the technical solution of the present invention is implemented as follows: A method for optimizing the influent distribution of multiple parallel secondary sedimentation tanks, comprising the following steps: S1. Collect routine operation and monitoring data for each secondary sedimentation tank for 7 consecutive days, including influent flow rate Q. in The mixed liquor sludge concentration (MLSS) and sludge volume index (SVI) were calculated, and outlier data were removed. The influent flow rate (Q) for each secondary sedimentation tank was also calculated. inThe average values ​​of mixed liquor sludge concentration (MLSS) and sludge volume index (SVI); then, according to formula X... r = (1.2 × 10 6 The return sludge concentration X is calculated using the SVI / SVI method. r X r Substitute into the material balance formula The amount of returned sludge in each secondary sedimentation tank was obtained. S2, Introducing the concentration ratio R c As a core evaluation parameter for the sedimentation and concentration capacity of a secondary sedimentation tank, R c =X r / MLSS, concentration ratio R c A higher R value indicates a stronger ability of the secondary sedimentation tank to concentrate sludge from the biological treatment tank, and the ability to withstand higher solids loads. c The theoretical settling performance is ranked based on the size of the sedimentation tanks; then, the performance is re-ranked by combining the average SVI value and the actual solid load tolerance. S3. Under the premise that the total influent volume remains unchanged, the secondary sedimentation tank with the first performance ranking in S2 is selected as the benchmark unit and its weight coefficient is set to 1.00. The influent volume allocation weight of the other secondary sedimentation tanks is the ratio of their own concentration ratio to the concentration ratio of the benchmark unit. All secondary sedimentation tanks are redistributed with the total influent volume according to the new weight ratio. S4. The exponential smoothing formula is used to predict the MLSS of each secondary sedimentation tank for the next 3 days, and then the trend of solid load change is estimated. The formula for exponential smoothing is: X t+1 =0.3X t +0.7 ; Among them, X t Let be the measured MLSS value on day t. Let X be the MLSS prediction value for day t. t+1 is the MLSS prediction value for day t+1, and 0.3 is the smoothing parameter.

[0005] The concentration ratio reflects the secondary settling tank's ability to concentrate dilute mixed liquor into return sludge. The higher the concentration ratio, the stronger the concentration capacity of the secondary settling tank theoretically. The SVI reflects the settling velocity and compressibility of the activated sludge. A lower SVI indicates faster sludge settling, denser flocs, and better compressibility. A high SVI indicates relatively loose sludge flocs and a relatively slow settling velocity; even with a high calculated concentration ratio, the actual sedimentation effect may be poor. Therefore, the final ranking of settling performance is based on solid load tolerance. Based on the initial screening using the concentration ratio, the SVI is introduced to correct the ranking, and the actual stable solid load that each series can withstand is used as the final confirmation criterion.

[0006] Furthermore, in S1, the rules for removing outlier data are as follows: For SVI, the value range is 50-150 mL / g, and values ​​with SVI < 50 mL / g or SVI > 150 mL / g are discarded. For MLSS, it will conform to |X r Samples with MLSS∣<0.5g / L were removed to avoid drastic fluctuations in reflux flow rate calculation caused by minor measurement errors.

[0007] Furthermore, the exclusion ratio does not exceed 5% of the total sample size, and the effective sample size of each series is sufficient after exclusion, so as not to affect the statistical representativeness.

[0008] Furthermore, in S2, the correction method combining the average SVI and the actual solid load tolerance is as follows: the solid load is calculated based on the actual test data to obtain the actual solid load value. A larger value indicates higher tolerance, and a smaller value indicates lower tolerance. When the SVI is too high, the actual solid load tolerance is low, so the ranking positions are swapped. When the SVI is the highest, the concentration ratio is the lowest, and the actual tolerance is the worst, it remains at the bottom.

[0009] Furthermore, in S4, early warnings can be set based on the estimated trend of solid load changes: When the estimated solid load increases for three consecutive days, and reaches 240 kg / (m²), 2 •d)≤ Load on day 3 < 260 kg / (m 2 •d) indicates a yellow alert, and the high-load series of inflows should be gradually relocated within 1-2 days; When the estimated solid load increases for three consecutive days, and the load on the third day is ≥260 kg / (m³) 2 •d) Immediately initiate water intake distribution adjustment to avoid sudden mud spillage.

[0010] Furthermore, when a yellow alert is issued, the method for relocating those affected by flooding is as follows: Using the solid load formula for inverse calculation, taking the target solid load as the control target, the target transfer amount is calculated, that is, reducing the target solid load to 240 kg / (m³). 2 •d) The following water transfer volume is required: First, transfer 20%~30% of the total target water volume. After operation, collect the latest data and recalculate the predicted solid load; if the predicted solid load is still 240 kg / (m³), then... 2 •d) If the load is above 240 kg / (m³) and still rising, continue to increase the amount of water transferred; if the predicted load has dropped to 240 kg / (m³) 2 •d) If the rise has stopped or has fallen below the threshold, the adjustment should be terminated. Each adjustment should be spaced out, and the patient should be observed for 3-4 hours after each adjustment to avoid over-adjustment that could cause new imbalances.

[0011] Furthermore, the formula for calculating solid load is: Solid load = ((Q) in +Qr ()×MLSS) / A, where A is the surface area of ​​the secondary sedimentation tank, m 2 .

[0012] Compared with existing technologies, the optimized influent distribution method for multiple parallel secondary sedimentation tanks described in this invention has the following advantages: 1. Significantly improved accuracy in sludge return flow measurement: The SVI empirical formula is adopted to replace on-site instantaneous sampling measurement for X. r This eliminates calculation distortions caused by sampling points, mud layer fluctuations, and pump parallel operation conditions, ensuring that the calculation results for return flow and solid load closely match the actual on-site conditions.

[0013] 2. Quantitative settling performance and more scientific water distribution: The first-ever combination of concentration ratio index and SVI correction grading no longer relies solely on SVI to judge sludge status, but uses the actual concentration carrying capacity as the water distribution weight to balance the solid load of each tank.

[0014] 3. Achieve proactive risk control: The exponential smoothing model can theoretically predict changes in MLSS and solid load 3 days in advance. Two-level early warning rules guide maintenance personnel to adjust water supply in advance, avoid sludge leakage, and control excessive SS in effluent from the source.

[0015] 4. Reduce overall plant operation and maintenance costs: Eliminate local overload sludge leakage, reduce the frequency of filter clogging, reduce the amount of backwash water, electricity and coagulant added, extend the service life of filter media, and improve the stability and economic efficiency of the sewage treatment system. Attached Figure Description

[0016] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings: Figure 1 A comparison chart of the load range changes before and after optimization for five secondary sedimentation tank series. Detailed Implementation

[0017] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other.

[0018] In this document, unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0019] In this document, when values ​​are described as ranges, it should be understood that such disclosure includes disclosure of all possible subranges within that range, as well as the specific numerical values ​​that fall within that range, regardless of whether the specific numerical value or specific subrange is explicitly specified.

[0020] In this article, the terms "multiple" or "more than" are used unless otherwise specified, referring to a quantity greater than or equal to 2. For example, "one or more" means one or more types.

[0021] In this document, the terms "preferred" and "more preferred" are used only to describe implementation methods or embodiments with better effects, and should be understood as not constituting a limitation on the scope of protection of this invention.

[0022] In this document, terms such as "further" are used for descriptive purposes to indicate differences in content, but should not be construed as limiting the scope of protection of this invention.

[0023] In this article, the term "and / or" describes an association between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or A and B.

[0024] In this document, the term "about" means a specified value of + / - 10%, preferably + / - 5%, and more preferably + / - 1%.

[0025] In this article, the terms “include,” “including,” “have,” “contain,” etc., are all open-ended terms, meaning that they include but are not limited to.

[0026] Unless otherwise stated, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art. While only preferred methods and materials have been described herein, any methods and materials similar to or equivalent to those described herein may be used in the implementation or testing of this invention.

[0027] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0028] This invention is based on the following research: (1) The absolute value of SS in the effluent is not used for quantitative calculation, but only as a reference in trend judgment or in the analysis of whether it exceeds the standard.

[0029] (2) The original parallel return pump nameplate rating is not used as the actual operating flow rate. The material balance formula provided in the design standard is used to calculate the replacement in the study.

[0030] (3) The amount of residual sludge discharged in this study accounts for a very low proportion of the total sludge discharge, and it is taken from the bottom sludge of the secondary sedimentation tank. The deviation of the back calculation of the total bottom sludge discharge can be ignored, so it is simplified and not considered.

[0031] (4) In the material balance calculation, the amount of solids carried by the effluent suspended solids and residual sludge is relatively small, so the effluent SS and residual sludge mass are ignored.

[0032] (5) The temperature variation range in this study is relatively small. It is assumed that temperature only affects the sludge settling characteristics by changing the dynamic viscosity of water. The indirect effects of small temperature fluctuations on sludge floc structure, microbial activity and settling performance are ignored.

[0033] (6) It is assumed that the surface areas of the secondary sedimentation tanks studied are completely equal, and that there are no differences in tank depth, inlet and outlet water methods, sludge scraper type, etc. The wastewater quality (COD, BOD, SS, etc.) of each secondary sedimentation tank series is the same.

[0034] This embodiment uses a series of five secondary sedimentation tanks for research. Without increasing equipment investment, it precisely adjusts the long-standing problem of uneven solid load distribution in multiple secondary sedimentation tanks, significantly reduces the risk of sudden sludge leakage under high load operation, and fully utilizes the idle sedimentation treatment capacity of existing tanks.

[0035] The optimized influent distribution method for multiple parallel secondary sedimentation tanks described in this embodiment includes the following steps: S1. Collect routine operation monitoring data from 5 secondary sedimentation tanks for 7 consecutive days, including influent flow rate Q. in The mixed liquor sludge concentration (MLSS) and sludge volume index (SVI) were calculated, and outliers were removed to obtain the influent flow rate Q for each secondary sedimentation tank. in The average values ​​of mixed liquor sludge concentration (MLSS) and sludge volume index (SVI) are then calculated using formula X. r = (1.2 × 10 6 The return sludge concentration X is calculated using the SVI / SVI method. r .

[0036] The rules for removing outlier data are set as follows: (1) SVI is an indicator reflecting the flocculation and settling performance of activated sludge. The SVI value range is 50-150 mL / g. SVI < 50 mL / g indicates sludge aging, and SVI > 150 mL / g indicates sludge bulking. The estimated X values ​​for these two types of samples are... r The deviation from the normal value caused the denominator X to... r -If the MLSS value is negative or too small, a reasonable return flow cannot be obtained, and it will be rejected.

[0037] (2) During routine MLSS sampling, abnormal values ​​may occur due to improper sampling location, drying and weighing errors, etc. When the MLSS value differs from the calculated return sludge concentration X... r When the values ​​are close, a small measurement error can cause Q to... rDrastic fluctuations render the calculation results unreliable, thus eliminating them and avoiding drastic fluctuations in the calculation of return flow caused by minor measurement errors.

[0038] S2, X r Substitute into the material balance formula The amount of returned sludge in each secondary sedimentation tank was obtained.

[0039] When calculating the return sludge flow rate using the material balance formula, the actual measured return sludge concentration is affected by multiple factors, including sampling location, sampling frequency, fluctuations in the sludge layer height in the secondary sedimentation tank, unstable sludge settling state, and disturbances in on-site operating conditions. Empirical calculations yield the actual measured X... r The large dispersion leads to a significant overestimation of the calculated return sludge flow rate and return ratio, exceeding the reasonable range for conventional water supply and drainage engineering. This results in distorted calculations that lack design value.

[0040] Therefore, the empirical formula X is adopted. r = (1.2 × 10 6 The SVI (Self-Volume Index) is used to estimate the concentration of returned sludge, avoiding the randomness of on-site instantaneous sampling and the interference of operating condition fluctuations. X is obtained using this method. r Substituting the values ​​into the material balance formula to calculate the amount of sludge to be returned, the return flow rate and return ratio parameters are found to be reasonable and in line with the traditional design and verification methods for water supply and drainage engineering.

[0041] The average values ​​of the test data and calculation results for the five secondary sedimentation tanks are shown in Table 1-2 below.

[0042] The formula for calculating solid load is: Solid load = ((Q) in +Q r ()×MLSS) / A, where A is the surface area of ​​the secondary sedimentation tank, m 2 .

[0043] Table 1. Test data for each secondary sedimentation tank As can be seen from Table 1, the solid load of secondary sedimentation tank No. 1 far exceeds the conventional design limit (the "Outdoor Drainage Design Standard" (GB50014-2021) stipulates that the solid load of a radial flow secondary sedimentation tank with peripheral inlet and peripheral outlet should not exceed 200 kg / (m³). 2 •d)), it has been in a state of high risk of sludge runoff for a long time. The solid load of No. 2 series is only slightly higher than the design value, and the sedimentation capacity of the pool is largely idle.

[0044] S3, Introducing the concentration ratio R c As a core evaluation parameter for the sedimentation and concentration capacity of a secondary sedimentation tank, R c =X r / MLSS, concentration ratio R cA higher R value indicates a stronger ability of the secondary sedimentation tank to concentrate sludge from the biological treatment tank, and the ability to withstand higher solids loads. c The theoretical settling performance is ranked by the magnitude of the solid load (SVI). Then, the performance of the secondary settling tank is re-ranked by combining the average SVI value and the actual solid load tolerance.

[0045] In operation and management, sludge settling performance is usually evaluated using the SVI (Sludge Volume Index). A lower SVI value indicates better settling performance. However, it cannot measure the sludge thickening efficiency of the secondary settling tank under actual operating conditions. Therefore, the return sludge concentration X... r The concentration ratio, which is the ratio of mixed liquor sludge concentration (MLSS), was used to compare the concentration capacity of various series of secondary sedimentation tanks.

[0046] Concentration R c Function: (1) Used to quantify and rank the sedimentation and concentration performance of each secondary sedimentation tank. Calculate the concentration ratio of each series to clearly determine the superiority or inferiority of the sedimentation performance of each series.

[0047] (2) Used to diagnose problems of load and capacity mismatch. By comparing the correspondence between the concentration ratio and the current solid load, the risk series of "small horse pulling a big cart" and the series of idle treatment capacity are identified, providing a basis for subsequent water distribution adjustments.

[0048] (3) Under the condition that the total influent volume remains unchanged, the influent volume is allocated according to the concentration ratio: the series with good settling performance is allocated a higher influent volume, and the series with poor performance is appropriately reduced. This helps to balance the solid load of each series and avoid some series from operating under overload.

[0049] Table 2. Ranking of Concentration Ratio and Sedimentation Performance of Each Secondary Sedimentation Tank As shown in Table 2, according to R c The theoretical settlement performance is ranked by the size of R. c2 >R c3 >R c4 >R c1 >R c5 However, the concentration ratio only reflects the "theoretical concentration capacity" and cannot be directly equated to the "actual sludge-water separation capacity." For example, a small MLSS in the denominator can "artificially inflate" the concentration ratio value, so a high value does not necessarily indicate excellent actual settling performance. This is because a high SVI in a certain series might indicate slower sludge settling and looser flocs. In actual operation, this might be close to its tolerance limit. Therefore, it is necessary to adjust the value based on both SVI and actual solids load tolerance. The ranking is based on the following principle: under the premise of ensuring effluent quality, the higher the solids load that the series can withstand, the better the settling performance. The final ranking is shown in Table 2.

[0050] The concentration ratio is used only as an initial weighting reference, not the sole criterion: First, a preliminary screening is conducted based on the concentration ratio values ​​to obtain a theoretical ranking. Then, the Solids Index (SVI) and actual solids load tolerance are introduced to correct the preliminary screening results: if the SVI is too high and the actual tolerance is low, the positions are swapped; if the SVI is the highest, the concentration ratio is the lowest, and the actual tolerance is the worst, then it remains at the bottom. This ranking method, combining quantitative indicators with practical engineering considerations, is more reliable than simply relying on the concentration ratio value.

[0051] S4. Under the premise that the total influent volume remains unchanged, select the second sedimentation tank ranked first as the benchmark unit and set its weight coefficient to 1.00. The influent volume allocation weight of the other second sedimentation tanks is the ratio of their own concentration ratio to the concentration ratio of the benchmark unit. All second sedimentation tanks redistribute the total influent volume according to the weight ratio.

[0052] The total weights are: 2.03 / 2.27+2.28 / 2.27+1.00+2.19 / 2.27+2.02 / 2.27=0.89+1.00+1.00+0.96+0.89=4.74.

[0053] Based on this, the new water inflow and predicted solid load were calculated, and the results are shown in Table 3.

[0054] Table 3 Water redistribution scheme and predicted solid load Comparison of solid loads before and after adjustment Figure 1 As shown, the range of solid loads for each series has increased from the original 83 kg / (m²) 2 •d) Reduced to 30 kg / (m 2 •d) The balance was significantly improved. The loads of series 1 and 5 decreased significantly, the loads of series 2 and 4 increased moderately, and the loads of series 3 remained basically the same. This scheme made full use of the differences in settlement performance among the series to optimize the target.

[0055] S5. In order to identify the risk of sludge overflow in advance, the exponential smoothing method is used to predict the MLSS of each secondary sedimentation tank for the next 3 days, and then estimate the trend of solid load change. The formula for exponential smoothing is: X t+1 =0.3X t +0.7 ; Among them, X t Let be the measured MLSS value on day t. Let X be the MLSS prediction value for day t. t+1 is the MLSS prediction value for day t+1, and 0.3 is the smoothing parameter.

[0056] Taking Series 3 as an example, we use one week's data to predict the next three days. The comparison between the predicted results and the actual values ​​is shown in Table 4.

[0057] Table 4 Extended Prediction Validation The average absolute error is approximately 3.7 kg / (m²). 2 •d) The relative error is less than 2%, indicating that the prediction model has high reliability.

[0058] The following early warning rules are set to guide operational adjustments: Yellow alert: Solid load is predicted to rise for three consecutive days, and reach 240 kg / (m³). 2 •d)≤ Load on day 3 < 260 kg / (m 2 •d) Gradually transfer part of the influent from the high-load series within 1-2 days; The specific method for transferring the incoming water is as follows: The solid load is calculated using the solid load formula, and the target solid load (e.g., 235 kg / (m²)) is taken. 2 ·d)) is used as the control target, and the target transfer amount is calculated, that is, the target solid load is reduced to 240 kg / (m³). 2 •d) The following water transfer volume is required: First, transfer 20%~30% of the total target water volume. After operation, collect the latest data and recalculate the predicted solid load; if the predicted solid load is still 240 kg / (m³), then... 2 •d) If the load is above 240 kg / (m³) and still rising, continue to increase the amount of water transferred; if the predicted load has dropped to 240 kg / (m³) 2 •d) If the rise has stopped or has ceased, the adjustment ends; each adjustment is spaced out, and sufficient observation time is allowed after each adjustment to avoid over-adjustment causing new imbalances.

[0059] The observation interval after each adjustment is mainly based on the theoretical hydraulic retention time (HRT) of the secondary sedimentation tank, as shown in Table 5. The HRT corresponding to the influent flow rate of each series of secondary sedimentation tanks in this invention is approximately 3.1-3.7h, and the adjustment interval is determined to be 4 hours after rounding.

[0060] The choice of this duration is based on the following three considerations: Firstly, it covers the hydraulic replacement cycle. After adjusting the valve, the flow distribution entering the secondary sedimentation tank changes, but the original water volume and sludge layer state in the tank will not change instantaneously. It requires at least one hydraulic retention time (3.1-3.7h) to complete the basic replacement of the water volume in the tank and allow the sludge layer to begin transitioning to a new equilibrium state. The 4-hour interval is slightly longer than the maximum HRT, providing ample observation window for the hydraulic response.

[0061] Secondly, in actual operation, operators need to complete the entire process of "sampling → testing → data processing → calculation and verification → decision-making". From sampling to obtaining MLSS and SVI data, and then combining the flow data to complete the solid load verification calculation, plus the time for previous adjustment operations and recording, the 4-hour cycle accommodates the process of "adjustment → response → detection → judgment", avoiding data loss or hasty decision-making due to insufficient time.

[0062] Third, avoid over-adjustment. Secondary sedimentation tank systems have significant inertia, and changes in the sediment layer lag considerably behind hydraulic adjustments. If the observation interval is too short (e.g., less than 2 hours), the system may not have fully responded before the next round of adjustments, easily leading to cumulative adjustments and overcompensation, which can trigger new imbalances. A 4-hour interval allows the system sufficient time to complete its initial response, enabling operators to judge trends based on relatively stable data and make more accurate decisions.

[0063] If manual sampling and testing are the primary method, it is recommended to maintain a standard interval of 4 hours. The principle is that the adjustment interval should not be less than the theoretical HRT and should match the on-site data acquisition cycle.

[0064] Table 5. Hydraulic residence time for each series (effective water depth 4.0m) Red Alert: Solid load is predicted to increase for three consecutive days, with the solid load on the third day ≥260 kg / (m³). 2 •d) Immediately initiate water intake distribution adjustment to avoid sudden mud spillage.

[0065] When it is predicted that a certain series is about to trigger a red alert, it is recommended to transfer part of its influent to other series with better performance 1-2 days in advance to reduce the solids flux of the high-load series and avoid sludge runoff.

[0066] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for optimizing the influent distribution of multiple parallel secondary sedimentation tanks, characterized in that: The method includes the following steps: S1. Collect routine operation and monitoring data for each secondary sedimentation tank for 7 consecutive days, including influent flow rate Q. in The mixed liquor sludge concentration (MLSS) and sludge volume index (SVI) were calculated, and outlier data were removed. The influent flow rate (Q) for each secondary sedimentation tank was also calculated. in The average values ​​of mixed liquor sludge concentration (MLSS) and sludge volume index (SVI); then, according to formula X... r = (1.2 × 10 6 The return sludge concentration X is calculated using the SVI / SVI method. r X r Substitute into the material balance formula The amount of returned sludge in each secondary sedimentation tank was obtained. S2, Introducing the concentration ratio R c As a core evaluation parameter for the sedimentation and concentration capacity of a secondary sedimentation tank, R c =X r / MLSS, concentration ratio R c A higher R value indicates a stronger ability of the secondary sedimentation tank to concentrate sludge from the biological treatment tank, and the ability to withstand higher solids loads. c The theoretical settling performance is ranked based on the size of the sedimentation tanks; then, the performance is re-ranked by combining the average SVI value and the actual solid load tolerance. S3. Under the premise that the total influent volume remains unchanged, the secondary sedimentation tank with the first performance ranking in S2 is selected as the benchmark unit and its weight coefficient is set to 1.

00. The influent volume allocation weight of the other secondary sedimentation tanks is the ratio of their own concentration ratio to the concentration ratio of the benchmark unit. All secondary sedimentation tanks are redistributed with the total influent volume according to the new weight ratio. S4. The exponential smoothing formula is used to predict the MLSS of each secondary sedimentation tank for the next 3 days, and then the trend of solid load change is estimated. The formula for exponential smoothing is: X t+1 =0.3X t +0.7 ; Among them, X t Let be the measured MLSS value on day t. Let X be the MLSS prediction value for day t. t+1 is the MLSS prediction value for day t+1, and 0.3 is the smoothing parameter.

2. The method for optimizing the influent distribution of multiple parallel secondary sedimentation tanks according to claim 1, characterized in that: In S1, the rules for removing outlier data are as follows: For SVI, the value range is 50-150 mL / g, and values ​​with SVI < 50 mL / g or SVI > 150 mL / g are discarded. For MLSS, it will conform to |X r Samples with MLSS∣<0.5g / L were removed to avoid drastic fluctuations in reflux flow rate calculation caused by minor measurement errors.

3. The method for optimizing the influent distribution of multiple parallel secondary sedimentation tanks according to claim 2, characterized in that: The exclusion ratio shall not exceed 5% of the total sample size. After exclusion, the effective sample size of each series is sufficient and does not affect the statistical representativeness.

4. The method for optimizing the influent distribution of multiple parallel secondary sedimentation tanks according to claim 1, characterized in that: In S2, the correction method combining the average SVI and the actual solid load tolerance is as follows: the solid load is calculated based on the actual test data to obtain the actual solid load value. A larger value indicates higher tolerance, and a smaller value indicates lower tolerance. When the SVI is too high, the actual solid load tolerance is low, so the ranking positions are swapped. When the SVI is the highest, the concentration ratio is the lowest, and the actual tolerance is the worst, it is kept at the bottom.

5. The method for optimizing the influent distribution of multiple parallel secondary sedimentation tanks according to claim 1, characterized in that: In S4, early warnings can also be set based on the estimated trend of solid load changes: When the estimated solid load increases for three consecutive days, and reaches 240 kg / (m²), 2 •d)≤ Load on day 3 < 260 kg / (m 2 •d) indicates a yellow alert, and the high-load series of inflows should be gradually relocated within 1-2 days; When the estimated solid load increases for three consecutive days, and the load on the third day is ≥260 kg / (m³) 2 •d) Immediately initiate water intake distribution adjustment to avoid sudden mud spillage.

6. The method for optimizing the influent distribution of multiple parallel secondary sedimentation tanks according to claim 5, characterized in that: When a yellow alert is issued, the method for relocating those affected by flooding is as follows: Using the solid load formula for inverse calculation, taking the target solid load as the control target, the target transfer amount is calculated, that is, reducing the target solid load to 240 kg / (m³). 2 •d) The following water transfer volume is required: First, transfer 20%~30% of the total target water volume. After operation, collect the latest data and recalculate the predicted solid load; if the predicted solid load is still 240 kg / (m³), then... 2 •d) If the load is above 240 kg / (m³) and still rising, continue to increase the amount of water transferred; if the predicted load has dropped to 240 kg / (m³) 2 •d) If the rise has stopped or has fallen below the threshold, the adjustment should be terminated. Each adjustment should be spaced out, and the patient should be observed for 3-4 hours after each adjustment to avoid over-adjustment that could cause new imbalances.

7. The method for optimizing the influent distribution of multiple parallel secondary sedimentation tanks according to any one of claims 1-6, characterized in that: The formula for calculating solid load is: Solid load = ((Q) in +Q r ()×MLSS) / A, where A is the surface area of ​​the secondary sedimentation tank, m 2 .

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