Evaluation system based on sewage treatment capacity

Abstract

The invention discloses an evaluation system based on sewage treatment capacity, and relates to the technical field of sewage treatment capacity evaluation, and the system comprises a sewage component treatment unit, a treatment effect sub-evaluation unit, a first to-be-evaluated sewage quantity obtaining unit, a first to-be-evaluated sewage quantity obtaining unit, a second to-be-evaluated sewage quantity obtaining unit, a first to-be-evaluated sewage quantity obtaining unit, a second to-be-evaluated sewage quantity obtaining unit and a second to-be-evaluated sewage quantity obtaining unit, the processing effect prediction unit is used for predicting a first actual effect prediction value according to first to-be-detected sewage data to which the first to-be-evaluated sewage amount belongs, and performing compensation synthesis on the first actual effect prediction value to obtain a first evaluation effect value; dividing the current sewage quantity into a plurality of unequal sub sewage quantities twice to obtain a second to-be-evaluated sewage quantity and a third to-be-evaluated sewage quantity, dividing the previous sewage quantity in an ascending order and dividing the latter sewage quantity in a descending order to predict a second evaluation effect value and a third evaluation effect value, and averaging the three evaluation effect values to obtain a sewage treatment capacity evaluation value. The evaluation system based on the sewage treatment capacity provided by the invention can improve the accuracy of an evaluation result.

Description

Technical Field

[0001] The present application relates to the technical field of sewage treatment capacity assessment, and in particular to an assessment system based on sewage treatment capacity. Background Art

[0002] With the rapid development of industrialization and urbanization, wastewater discharge has increased dramatically, posing a serious threat to the natural environment and ecosystems. Assessing wastewater purification and treatment capacity is crucial for effectively controlling pollutant emissions, protecting water resources, and maintaining ecological balance.

[0003] In traditional technologies, the assessment of sewage treatment capacity is often based on the simultaneous purification treatment of the entire sewage volume, and the sewage treatment capacity is assessed based on the final purification efficiency. This results in large assessment errors, and a single sewage purification assessment is conducted in a unified manner. The assessment error occurs when a large amount of sewage is simultaneously discharged, resulting in insufficient response, which leads to large errors in the final assessment results and reduces the efficiency and cost of the entire assessment and treatment work. Summary of the Invention

[0004] In order to overcome the above-mentioned deficiencies of the prior art, the present application provides an evaluation system based on sewage treatment capacity.

[0005] This application provides an evaluation system based on sewage treatment capacity, which adopts the following technical solutions:

[0006] a sewage component processing unit, configured to obtain historical sewage treatment data, establish a simulation prediction model based on the historical sewage treatment data, obtain a current sewage volume, divide the current sewage volume into a number of unequal sub-sewage volume sets, and screen a target sub-sewage volume from the sub-sewage volume sets through sewage treatment effect prediction using the simulation prediction model, so as to divide the current sewage volume into a number of sub-sewage volumes that are equal to the target sub-sewage volume to obtain a first sewage volume to be evaluated;

[0007] a treatment effect sub-evaluation unit, configured to predict a first actual effect prediction value based on first test sewage data belonging to the first sewage volume to be evaluated and a simulation prediction model, calculate a difference between the actual and theoretical effects based on the first actual effect prediction value, calculate a first effect compensation coefficient, and compensate the first actual effect prediction value based on the first effect compensation coefficient to comprehensively obtain a first evaluation effect value;

[0008] The overall treatment effect evaluation unit is used to divide the current sewage volume into several unequal sub-sewage volumes according to the target sub-sewage volume to obtain a second sewage volume to be evaluated, and the sub-sewage volumes in the second sewage volume to be evaluated are in ascending order; divide the current sewage volume into several unequal sub-sewage volumes to obtain a third sewage volume to be evaluated, and the sub-sewage volumes in the third sewage volume to be evaluated are in descending order; based on the second sewage volume to be evaluated and the third sewage volume to be evaluated, the second effect compensation coefficient and the third effect compensation coefficient are calculated to predict the second evaluation effect value and the third evaluation effect value; the first evaluation effect value, the second evaluation effect value and the third evaluation effect value are averaged to obtain the sewage treatment capacity evaluation value.

[0009] Preferably, historical sewage treatment data is obtained, and historical amounts of sewage to be treated and sewage characteristic parameters are extracted from the historical sewage treatment data. Based on the historical amounts of sewage to be treated and the sewage characteristic parameters, historical purification usage data required for the historical amounts of sewage to be treated are extracted from the historical sewage treatment data. Based on the historical amounts of sewage to be treated, the sewage characteristic parameters and the historical purification usage data, the historical actual effect values ​​after sewage treatment are calculated. Based on the historical amounts of sewage to be treated, the sewage characteristic parameters, the historical purification usage data and the historical actual effect values, a simulation prediction model is established.

[0010] Preferably, the current sewage volume that needs to be treated is obtained, the current sewage volume is divided into several unequal sub-sewage volume sets, the sub-sewage volume sets and the sewage characteristic data belonging to the sub-sewage volumes are input into a simulation prediction model for testing to obtain a data set to be purified, the sub-sewage volume sets, the data set to be purified, and the effect value set belonging to the sub-sewage volume set and the data set to be purified are numerically integrated in a unified manner to obtain an integrated evaluation value set to be judged, and according to the maximum value in the integrated evaluation value set to be judged, the corresponding sub-sewage volume is screened out from the sub-sewage volume set to obtain a target sub-sewage volume;

[0011] According to the target sub-wastewater volume, the current sewage volume is divided into a number of sub-wastewater volumes that are equal to the target sub-wastewater volume to obtain a first sewage volume to be evaluated.

[0012] Preferably, current purification demand data required for the current sewage volume is obtained, sewage parameters contained in each equal amount of sewage in the first sewage volume to be evaluated are detected to obtain first sewage data to be tested, and according to the first sewage data to be tested, the current purification demand data is divided according to theoretical data matching to obtain first purification data to be tested;

[0013] Inputting the first sewage volume to be evaluated, the first sewage data to be tested, and the first purification data to be tested into a simulation prediction model to obtain a first actual effect prediction value;

[0014] According to the first sewage volume to be evaluated, the first sewage data to be tested and the first purification data to be tested, a first theoretical effect value is obtained, and the difference between the first theoretical effect value and the first actual effect prediction value is calculated to obtain a first effect difference value.

[0015] Preferably, the first effect difference value and the first theoretical effect value are compared to obtain a first effect compensation coefficient, wherein when the first actual effect prediction value is greater than the first theoretical effect value, the first effect compensation coefficient is an incremental compensation, when the first actual effect prediction value is equal to the first theoretical effect value, the first effect compensation coefficient is a zero compensation, and when the first actual effect prediction value is less than the first theoretical effect value, the first effect compensation coefficient is a depreciation compensation;

[0016] According to the first effect compensation coefficient, the first actual effect prediction value is compensated and synthesized to obtain a first evaluation effect value.

[0017] Preferably, according to the target sub-wastewater volume, the current sewage volume is divided into several unequal sub-wastewater volumes to obtain a second sewage volume to be evaluated, the sub-wastewater volumes in the second sewage volume to be evaluated are in ascending order, the volume differences between adjacent sub-wastewater volumes are equal, and the median sub-wastewater volume in the second sewage volume to be evaluated is the target sub-wastewater volume;

[0018] According to the second sewage volume to be evaluated, the first actual effect prediction value and the first effect compensation coefficient, the second actual effect prediction value and the second effect compensation coefficient are predicted. According to the second effect compensation coefficient, the second actual effect prediction value is compensated and comprehensively obtained to obtain the second evaluation effect value.

[0019] Preferably, according to the target sub-wastewater volume, the current sewage volume is divided into several unequal sub-wastewater volumes to obtain a third sewage volume to be evaluated, the sub-wastewater volumes in the third sewage volume to be evaluated are in descending order, the volume differences between adjacent sub-wastewater volumes are equal, and the median sub-wastewater volume in the third sewage volume to be evaluated is the target sub-wastewater volume;

[0020] According to the third sewage volume to be evaluated, the first actual effect predicted value and the first effect compensation coefficient, a third actual effect predicted value and a third effect compensation coefficient are predicted; and according to the third effect compensation coefficient, the third actual effect predicted value is compensated to obtain a third evaluation effect value;

[0021] The sewage treatment capacity evaluation value is obtained by averaging the first evaluation effect value, the second evaluation effect value and the third evaluation effect value.

[0022] Compared with the prior art, the present invention has the following characteristics and beneficial effects:

[0023] By establishing a correlation between actual sewage treatment effects on sewage volume input, sewage characteristic data and purification demand data based on historical sewage treatment data, a simulation prediction model is established to facilitate the subsequent prediction of sewage treatment effects based on current sewage volume, sewage characteristic data and purification demand data, so as to make full use of historical characteristic data for information development research analysis, improve the reliability of prediction results, increase the utilization rate of data resources, and avoid the traditional technology of evaluating sewage treatment capacity by only conducting a one-time single overall sewage volume for unified purification treatment, which leads to insufficient sewage in the purification process and affects the accuracy of the final evaluation results. By dividing the current sewage volume into several sub-sewage volumes, the sewage treatment capacity can be evaluated to the maximum extent, that is, the conditions for sewage to undergo sufficient purification reaction are provided to reduce the error of the evaluation results. The divided sub-sewage volumes are not divided arbitrarily, but are divided using the original First, a predictive analysis is performed based on the simulation prediction model to screen out the target sub-wastewater volume that can be optimally purified. In order to further reduce the evaluation error, evaluation predictions are performed under three different sub-wastewater volume divisions. One is to divide the current sewage volume into several sub-wastewater volumes that are equal to the target sub-wastewater volume to obtain a first sewage volume to be evaluated; one is to divide the current sewage volume into several unequal sub-wastewater volumes to obtain a second sewage volume to be evaluated, and the sub-wastewater volumes in the second sewage volume to be evaluated are in ascending order, and the quantity differences between adjacent sub-wastewater volumes are equal, and the median sub-wastewater volume in the second sewage volume to be evaluated is the target sub-wastewater volume; and another is to divide the current sewage volume into several unequal sub-wastewater volumes to obtain a third sewage volume to be evaluated, and the sub-wastewater volumes in the third sewage volume to be evaluated are in descending order, and the quantity differences between adjacent sub-wastewater volumes are equal, and the median sub-wastewater volume in the third sewage volume to be evaluated is the target sub-wastewater volume. The purification treatment of the component sewage in these three cases is carried out respectively, and the evaluation effect values ​​obtained from the final evaluation are comprehensively statistically analyzed to obtain the final sewage treatment capacity evaluation value, thereby reducing the large error caused by taking only one evaluation treatment method, and further playing a verification role. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 This is a structural block diagram of an evaluation system based on sewage treatment capacity mainly embodied in this embodiment. DETAILED DESCRIPTION

[0025] The present invention is further described in detail below with reference to the following examples.

[0026] Reference Figure 1 , an evaluation system based on sewage treatment capacity, including a sewage component treatment unit, a treatment effect sub-evaluation unit and a treatment effect overall evaluation unit:

[0027] The sewage component processing unit is used to obtain historical sewage treatment data, establish a simulation prediction model based on the historical sewage treatment data, obtain the current sewage volume, divide the current sewage volume into several unequal sub-sewage volume sets, and predict the sewage treatment effect through the simulation prediction model. The target sub-sewage volume is screened out from the sub-sewage volume set, and the current sewage volume is divided into several sub-sewage volumes that are equal to the target sub-sewage volume to obtain the first sewage volume to be evaluated.

[0028] The specific implementation method of the sewage component treatment unit is as follows:

[0029] Obtain historical sewage treatment data, extract historical volumes of sewage to be treated and sewage characteristic parameters from the historical sewage treatment data, extract historical purification usage data required for the historical volumes of sewage to be treated from the historical sewage treatment data based on the historical volumes of sewage to be treated and the sewage characteristic parameters, calculate historical actual effect values ​​after sewage treatment based on the historical volumes of sewage to be treated, sewage characteristic parameters and historical purification usage data, and establish a simulation prediction model based on the historical volumes of sewage to be treated, sewage characteristic parameters, historical purification usage data and historical actual effect values.

[0030] The current sewage volume that needs to be treated is obtained, and the current sewage volume is divided into several unequal sub-sewage volume sets. The sub-sewage volume sets and the sewage characteristic data to which the sub-sewage volumes belong are input into the simulation prediction model for testing to obtain the data set to be purified. The sub-sewage volume sets, the data set to be purified, and the effect value set to which the sub-sewage volume sets and the data set to be purified belong are numerically integrated in a unified manner to obtain the integrated evaluation value set to be judged. According to the maximum value in the integrated evaluation value set to be judged, the corresponding sub-sewage volume is screened out from the sub-sewage volume set to obtain the target sub-sewage volume.

[0031] According to the target sub-wastewater volume, the current sewage volume is divided into a number of sub-wastewater volumes that are equal to the target sub-wastewater volume to obtain a first sewage volume to be evaluated.

[0032] Specifically, such as historical sewage treatment data (referring to the amount of sewage discharged for sewage purification treatment in historical periods, sewage characteristic data to which the discharged sewage belongs (such as water quality-related characteristics: conventional water quality indicators (chemical oxygen demand (COD), biochemical oxygen demand (BOD), total suspended solids (TSS), ammonia nitrogen (NH3-N), total nitrogen (TN), total phosphorus (TP), etc., these indicators can reflect the content of pollutants in sewage); heavy metal content: such as lead, mercury, cadmium, arsenic, etc., which can be detected by atomic absorption spectroscopy, etc. to evaluate whether the sewage contains toxic and harmful heavy metal elements), purification data required for sewage purification (referring to the amount of chemical dosage: in the sewage treatment process, various chemicals are often added, such as flocculants, coagulants, disinfectants, etc. The amount of chemical dosage directly affects the treatment effect and operating costs, so it is necessary to accurately record the amount of chemical dosage and adjust and optimize it according to the treatment effect), and also includes the actual effect of sewage purification treatment. The actual effect value of the sewage treatment process is calculated based on the historical sewage volume, sewage characteristic parameters and historical purification usage data (e.g. the historical sewage volume, sewage characteristic parameters and historical purification usage data of the historical period q1, and the corresponding historical sewage treatment data in the historical period q1, and the degree of compliance of the water quality index data after sewage treatment corresponding to the historical sewage volume, sewage characteristic parameters and historical purification usage data, is the historical actual effect value). A simulation prediction model is established (e.g. if the historical sewage volume is L1, and the sewage characteristic parameters of L1 are S1 If the historical purification usage data is J1, then (L1, S1) is used as the x-axis and J1 is used as the y-axis. According to the data of L, S, and J in multiple historical periods, a sewage treatment effect characteristic curve is constructed. The slope of the curve of the constructed sewage treatment effect characteristic curve is the sewage treatment effect. In order to reduce the influence of the error of the theoretical sewage treatment effect, the actual effect value is verified. If the historical actual effect value is G1, for example, the ratio between J1 and (L1, S1) is adjusted to G1 to realize the correction of the constructed sewage treatment effect characteristic curve. And according to the trend trend characteristics of the sewage treatment effect characteristic curve, Carry out subsequent trend extension prediction (such as based on the statistics of the slope change amplitude characteristics, because the information has the characteristics of development), if the ductility prediction sewage treatment effect characteristic curve is T1, that is, the simulation prediction model), the current sewage volume (if it is L2), the sub-sewage volume set (at this time, random division is performed (the divided sub-sewage volumes are all different), if it is divided into l1, l2, l3, l4, l5, it should be noted that the divided sub-sewage volumes can detect the sewage characteristic data to which they belong, if they are s1, s2, s3, s4, s5 respectively), the data set needs to be purified (then predictive matching is performed based on the sub-sewage volume set and the data information in T1, and in order to improve the matching accuracy,Then combine s1, s2, s3, s4, and s5 for matching, so that the corresponding purification demand data can be matched from T1. If they are x1, x2, x3, x4, and x5 respectively, the integrated evaluation value set is to be judged (according to the obtained sub-sewage volume set, the data set to be purified, and the sub-sewage volume set, the predictive sewage treatment effect can be obtained from T1 accordingly. If they are g1, g2, g3, g4, and g5 respectively, these four types of data are unified and integrated. For example, the ratio between the data to be purified and the sub-sewage volume is first calculated (here the data to be purified is the total data statistics: such as The sum of the total amount of various reagents added), and then superimpose the obtained ratio and the corresponding sewage treatment effect value. If the integrated data obtained are N1, N2, N3, N4, and N5 respectively), the target sub-sewage volume (if N3 is the maximum value, then select l3 corresponding to N3 as the target sub-sewage volume for subsequent division of the current sewage volume. The larger the N value, the better the purification effect in the l3 sub-pollution volume, and the better the required purification data), the first sewage volume to be evaluated (then divide L2 into l3 sub-sewage volumes, if i equal parts are obtained).

[0033] The treatment effect sub-evaluation unit is used to predict a first actual effect prediction value based on the first sewage data to be tested and the simulation prediction model belonging to the first sewage volume to be evaluated, calculate the effect difference between the actual and theoretical values ​​based on the first actual effect prediction value, calculate the first effect compensation coefficient, and compensate the first actual effect prediction value based on the first effect compensation coefficient to obtain the first evaluation effect value.

[0034] The specific implementation of the processing effect sub-evaluation unit is as follows:

[0035] The current purification demand data required for the current sewage volume is obtained, and the sewage parameters contained in each molecular sewage volume in the first sewage volume to be evaluated are detected to obtain the first sewage data to be tested. According to the first sewage data to be tested, the current purification demand data is divided into theoretical data matching to obtain the first purification data to be tested.

[0036] The first sewage volume to be evaluated, the first sewage data to be tested, and the first purification data to be tested are input into a simulation prediction model for testing to obtain a first actual effect prediction value.

[0037] A first theoretical effect value is obtained according to the first sewage volume to be evaluated, the first sewage data to be tested and the first purification data to be tested, and a first effect difference value is obtained by calculating the difference between the first theoretical effect value and the first actual effect prediction value.

[0038] The first effect difference and the first theoretical effect value are compared to obtain the first effect compensation coefficient, wherein, when the first actual effect prediction value is greater than the first theoretical effect value, the first effect compensation coefficient is value-added compensation, when the first actual effect prediction value is equal to the first theoretical effect value, the first effect compensation coefficient is zero compensation, and when the first actual effect prediction value is less than the first theoretical effect value, the first effect compensation coefficient is value-reduced compensation.

[0039] According to the first effect compensation coefficient, the first actual effect prediction value is compensated and synthesized to obtain a first evaluation effect value.

[0040] Specifically, such as the current purification demand data (if it is S2), the first sewage data to be tested (the sewage characteristic data of each sub-sewage volume l3 of i equal parts are the same if it is m1), the first purification data to be tested (then S2 is divided into corresponding matching groups according to the m1 of each sub-sewage volume l3 of i equal parts, if they are b1, b2, b3, b4, b5, then the i equal parts of sub-sewage volume l3 are released at different time points in turn (for example, the first part of sub-sewage volume l3 is released first, and the second part of sub-sewage volume l3 is released after the preset time point. The preset time point here is set by the management personnel, and so on)), the first actual effect prediction value (if they are G2, G3, G4, G5, G6, which correspond to the sewage treatment effect values ​​of each sub-sewage volume l3 of i equal parts respectively), the first theoretical effect value (refers to the theoretical sewage treatment before sewage treatment). Estimation of water treatment effect, such as the ideal purification effect value after purification treatment required by the sewage characteristic data of the theoretical sewage volume, which can be judged empirically based on the sewage treatment data in the historical period, with the maximum value tending to 100%, but not equal to 100%), first effect difference (when the first actual effect prediction value is greater than the first theoretical effect value, the first effect compensation coefficient is value-added compensation, then G2-G0 is greater than 0, and the value-added symbol is "+"; when the first actual effect prediction value is equal to the first theoretical effect value, the first effect compensation coefficient is zero compensation, G2-G0 is 0; when the first actual effect prediction value is less than the first theoretical effect value, the first effect compensation coefficient is value-reduced compensation, then G2-G3 is less than 0, and the value-added symbol is "-"), first effect compensation coefficient (for example, after the first portion of sewage volume l3 is released: the first effect difference is value-added compensation g1, then g1 / G0,The value-added symbol is "+"), the first evaluation effect value (for example, the comprehensive evaluation effect value after the first portion of sewage volume l3 is released is: Z1=G1+G1*(g1 / G0), if the effect compensation coefficient after the second portion of sewage volume l3 is g11, and the value-added symbol is "+", and if the theoretical effect value is G01, then the comprehensive evaluation effect value after the second portion of sewage volume l3 is: Z2=Z1+G2+G2*(g11 / G01), if the effect compensation coefficient after the third portion of sewage volume l3 is 0, then the comprehensive evaluation effect value after the third portion of sewage volume l3 is: Z 3=Z2+G3, if the effect compensation coefficient after the fourth sewage volume l3 is released is g13, and the value-added symbol is "-", and the theoretical effect value is G02, then the comprehensive evaluation effect value after the fourth sewage volume l3 is released is: Z4=Z3-G4*(g13 / G02), if the effect compensation coefficient after the fifth sewage volume l3 is released is g14, and the value-added symbol is "-", and the theoretical effect value is G03, then the comprehensive evaluation effect value after the fifth sewage volume l3 is released is: Z5=Z4-G5*(g13 / G03), then Z5 is the first evaluation effect value).

[0041] The overall treatment effect evaluation unit is used to divide the current sewage volume into several unequal sub-sewage volumes according to the target sub-sewage volume to obtain a second sewage volume to be evaluated, and the sub-sewage volumes in the second sewage volume to be evaluated are in ascending order; divide the current sewage volume into several unequal sub-sewage volumes to obtain a third sewage volume to be evaluated, and the sub-sewage volumes in the third sewage volume to be evaluated are in descending order; based on the second sewage volume to be evaluated and the third sewage volume to be evaluated, the second effect compensation coefficient and the third effect compensation coefficient are calculated to predict the second evaluation effect value and the third evaluation effect value; the first evaluation effect value, the second evaluation effect value and the third evaluation effect value are averaged to obtain the sewage treatment capacity evaluation value.

[0042] The specific implementation method of the overall treatment effect evaluation unit is as follows:

[0043] According to the target sub-wastewater volume, the current sewage volume is divided into several unequal sub-wastewater volumes to obtain the second sewage volume to be evaluated. The sub-wastewater volumes in the second sewage volume to be evaluated are in ascending order, and the volume differences between adjacent sub-wastewater volumes are equal. The median sub-wastewater volume in the second sewage volume to be evaluated is the target sub-wastewater volume.

[0044] According to the second sewage volume to be evaluated, the first actual effect prediction value and the first effect compensation coefficient, the second actual effect prediction value and the second effect compensation coefficient are predicted. According to the second effect compensation coefficient, the second actual effect prediction value is compensated and comprehensively obtained to obtain the second evaluation effect value.

[0045] According to the target sub-wastewater volume, the current sewage volume is divided into several unequal sub-wastewater volumes to obtain the third sewage volume to be evaluated. The sub-wastewater volumes in the third sewage volume to be evaluated are in descending order, and the volume differences between adjacent sub-wastewater volumes are equal. The median sub-wastewater volume in the third sewage volume to be evaluated is the target sub-wastewater volume.

[0046] According to the third sewage volume to be evaluated, the first actual effect prediction value and the first effect compensation coefficient, the third actual effect prediction value and the third effect compensation coefficient are predicted. According to the third effect compensation coefficient, the third actual effect prediction value is compensated and comprehensively obtained to obtain the third evaluation effect value.

[0047] The sewage treatment capacity evaluation value is obtained by averaging the first evaluation effect value, the second evaluation effect value and the third evaluation effect value.

[0048] Specifically, for example, the second sewage volume to be assessed (if they are r1, r2, l3, r4, r5), the second actual effect prediction value and the second effect compensation coefficient (the interpretation is the same as the first actual effect prediction value and the first effect compensation coefficient, if the second actual effect prediction values ​​are: G11, G21, G31, G41, G51, the second effect compensation coefficients are: g2, g21, g22, 0, g23, among which the increment symbol of g2, g21, g22 is “ +”, g23’s planting symbol is “-”, and the corresponding theoretical effect values ​​are obtained: if they are G04, G05, G06, G07, and G08 respectively, the comprehensive evaluation effect value after r1 is placed is: K1=G11+G11*(g2 / G04), the comprehensive evaluation effect value after r2 is placed is: K2=K1+G21+G21*(g21 / G05), and so on. If the second evaluation effect value is K5), the third sewage volume to be evaluated (If they are R1, R2, l3, R4, R5 respectively), the third actual effect prediction value and the third effect compensation coefficient (the interpretation is the same as the first actual effect prediction value and the first effect compensation coefficient. If the third actual effect prediction values ​​are: G111, G211, G311, G411, G511 respectively, the third effect compensation coefficients are: g3, 0, g31, g32, g33 respectively, where the planting symbol of g3 is "+", the planting symbol of g31, g32, g33 is "+". The symbol is "-", and the corresponding theoretical effect value is obtained: if they are G09, G10, G11, G12, and G13 respectively, the comprehensive evaluation effect value after the release of R1 is: W1=G111+G111*(g3 / G09), the comprehensive evaluation effect value after the release of R2 is: W2=W1+G211, and so on. If the second evaluation effect value is W5), the sewage treatment capacity evaluation value (that is, (Z5+K5+W5) / 3 if it is P).

[0049] The above are all preferred embodiments of the present application, and are not intended to limit the scope of protection of the present application. Therefore, any equivalent changes made based on the structure, shape, and principle of the present application should be included in the scope of protection of the present application.

Claims

1. A sewage treatment capacity evaluation system, characterized in that: include: a sewage component processing unit, configured to obtain historical sewage treatment data, establish a simulation prediction model based on the historical sewage treatment data, obtain a current sewage volume, divide the current sewage volume into a number of unequal sub-sewage volume sets, and screen a target sub-sewage volume from the sub-sewage volume sets through sewage treatment effect prediction using the simulation prediction model, so as to divide the current sewage volume into a number of sub-sewage volumes that are equal to the target sub-sewage volume to obtain a first sewage volume to be evaluated; a treatment effect sub-evaluation unit, configured to predict a first actual effect prediction value based on first test sewage data belonging to the first sewage volume to be evaluated and a simulation prediction model, calculate a difference between the actual and theoretical effects based on the first actual effect prediction value, calculate a first effect compensation coefficient, and compensate the first actual effect prediction value based on the first effect compensation coefficient to comprehensively obtain a first evaluation effect value; The overall treatment effect evaluation unit is used to divide the current sewage volume into several unequal sub-sewage volumes according to the target sub-sewage volume to obtain a second sewage volume to be evaluated, and the sub-sewage volumes in the second sewage volume to be evaluated are in ascending order; divide the current sewage volume into several unequal sub-sewage volumes to obtain a third sewage volume to be evaluated, and the sub-sewage volumes in the third sewage volume to be evaluated are in descending order; based on the second sewage volume to be evaluated and the third sewage volume to be evaluated, the second effect compensation coefficient and the third effect compensation coefficient are calculated to predict the second evaluation effect value and the third evaluation effect value; the first evaluation effect value, the second evaluation effect value and the third evaluation effect value are averaged to obtain the sewage treatment capacity evaluation value.

2. The sewage treatment capacity evaluation system according to claim 1, characterized in that: The specific implementation of the sewage component treatment unit includes the following: Obtain historical sewage treatment data, extract historical amounts of sewage to be treated and sewage characteristic parameters from the historical sewage treatment data, extract historical purification usage data required for the historical amounts of sewage to be treated from the historical sewage treatment data based on the historical amounts of sewage to be treated and the sewage characteristic parameters, calculate historical actual effect values ​​after sewage treatment based on the historical amounts of sewage to be treated, sewage characteristic parameters and historical purification usage data, and establish a simulation prediction model based on the historical amounts of sewage to be treated, sewage characteristic parameters, historical purification usage data and historical actual effect values.

3. The sewage treatment capacity evaluation system according to claim 2, characterized in that: The specific implementation of the sewage component treatment unit also includes the following: Obtain a current sewage volume that needs to be treated, divide the current sewage volume into several unequal sub-sewage volume sets, input the sub-sewage volume sets and sewage characteristic data belonging to the sub-sewage volumes into a simulation prediction model for testing to obtain a data set to be purified, perform unified numerical integration on the sub-sewage volume sets, the data set to be purified, and the effect value set belonging to the sub-sewage volume set and the data set to be purified to obtain a to-be-judged integrated evaluation value set, and according to the maximum value in the to-be-judged integrated evaluation value set, screen out the corresponding sub-sewage volume from the sub-sewage volume set to obtain a target sub-sewage volume; According to the target sub-wastewater volume, the current sewage volume is divided into a number of sub-wastewater volumes that are equal to the target sub-wastewater volume to obtain a first sewage volume to be evaluated.

4. The sewage treatment capacity evaluation system according to claim 3, characterized in that: The specific implementation of the processing effect sub-evaluation unit includes the following: Obtaining current purification demand data required for the current sewage volume, detecting sewage parameters contained in each equal amount of sewage in the first sewage volume to be evaluated to obtain first sewage data to be tested, and performing theoretical data matching division on the current purification demand data based on the first sewage data to obtain first purification data to be tested; Inputting the first sewage volume to be evaluated, the first sewage data to be tested, and the first purification data to be tested into a simulation prediction model to obtain a first actual effect prediction value; According to the first sewage volume to be evaluated, the first sewage data to be tested and the first purification data to be tested, a first theoretical effect value is obtained, and the difference between the first theoretical effect value and the first actual effect prediction value is calculated to obtain a first effect difference value.

5. The sewage treatment capacity evaluation system according to claim 4, characterized in that: The specific implementation of the processing effect sub-evaluation unit also includes the following: Comparing the first effect difference value and the first theoretical effect value to obtain a first effect compensation coefficient, wherein when the first actual effect prediction value is greater than the first theoretical effect value, the first effect compensation coefficient is an incremental compensation, when the first actual effect prediction value is equal to the first theoretical effect value, the first effect compensation coefficient is a zero compensation, and when the first actual effect prediction value is less than the first theoretical effect value, the first effect compensation coefficient is a depreciation compensation; According to the first effect compensation coefficient, the first actual effect prediction value is compensated and synthesized to obtain a first evaluation effect value.

6. The sewage treatment capacity evaluation system according to claim 5, characterized in that: The specific implementation of the treatment effect overall evaluation unit includes the following: According to the target sub-wastewater volume, the current wastewater volume is divided into several unequal sub-wastewater volumes to obtain a second wastewater volume to be evaluated, wherein the sub-wastewater volumes in the second wastewater volume to be evaluated are in ascending order, the volume differences between adjacent sub-wastewater volumes are equal, and the median sub-wastewater volume in the second wastewater volume to be evaluated is the target sub-wastewater volume; According to the second sewage volume to be evaluated, the first actual effect prediction value and the first effect compensation coefficient, the second actual effect prediction value and the second effect compensation coefficient are predicted. According to the second effect compensation coefficient, the second actual effect prediction value is compensated and comprehensively obtained to obtain the second evaluation effect value.

7. The sewage treatment capacity evaluation system according to claim 6, characterized in that: The specific implementation of the processing effect overall evaluation unit also includes the following: According to the target sub-wastewater volume, the current wastewater volume is divided into several unequal sub-wastewater volumes to obtain a third wastewater volume to be evaluated. The sub-wastewater volumes in the third wastewater volume to be evaluated are in descending order, and the volume differences between adjacent sub-wastewater volumes are equal. The median sub-wastewater volume in the third wastewater volume to be evaluated is the target sub-wastewater volume. According to the third sewage volume to be evaluated, the first actual effect predicted value and the first effect compensation coefficient, a third actual effect predicted value and a third effect compensation coefficient are predicted; and according to the third effect compensation coefficient, the third actual effect predicted value is compensated to obtain a third evaluation effect value; The sewage treatment capacity evaluation value is obtained by averaging the first evaluation effect value, the second evaluation effect value and the third evaluation effect value.

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