CN101786721B - Random process predicting method for outlet water organic substance concentration of municipal sewage treatment plant - Google Patents

Abstract

The invention discloses a random process predicting method for outlet water organic substance concentration of a municipal sewage treatment plant, which comprises the following steps of: by using an outlet water organic substance of the sewage treatment plant as a research object, establishing a mass conservation differential equation of inlet and outlet water organic substances, introducing a random process and deducing to obtain a predicted result of the outlet water organic substance concentration of the municipal sewage treatment plant. The invention needs to measure the yield coefficient, the maximum ratio growth rate and the saturation constant of heterotrophic bacteria and can predict the dynamic change process of the outlet water organic substance concentration when the water quality, the water quantity and the like of actual inlet water are fluctuated by simultaneously utilizing the aeration tank mixed liquid volatile suspended solid concentration of the sewage treatment plant, the hydraulic detention time, the actual inlet and outlet water total BOD5 (Biochemical Oxygen Demand) and the daily measured data. The novel activated sludge dynamic model method of the invention has the advantages of simple and feasible operation, fewer measured parameters, better fitting of a predicted value and a measured value and the like.

Description

The stochastic process Forecasting Methodology of effluent of municipal sewage plant organic concentration

Technical field

The present invention relates to the biological sewage treatment field, be specifically related to a kind of stochastic process Forecasting Methodology of effluent of municipal sewage plant organic concentration.

Background technology

In urban sewage treatment process, Sludge System is occupied an leading position.(Wastewater Treatment Plant, WWTP) the organic concentration model mainly contains static model and dynamicmodel two big classes in the municipal sewage plant.Five sixties of 20th century, more external scholars introduce the reactor theory and the germ theory of chemical field, set up classical activated sludge process mathematical model separately by the relation between substrate degradation, microorganism growth and each parameter, wherein most representative is Eckenfedlder, Lawrence-McCarty and Mckinney activated sludge kinetics model, they are all based on the Monod equation, and the development of activated sludge process is had great pushing effect.Wherein the Lawrence-McCarty model combines the Monod equation and has released sludge age θ about organic concentration with sludge age _cDesign formula still worldwide is extensive use of so far, is the main method in China and other numerous national design specificationss.It thinks the outlet water organic substance concentration S of system _eOnly with sludge age θ _cRelevant, and irrelevant with entering organic matter of water concentration etc., its expression formula is

$S_e=\frac{K_S(1+K_d{\mathrm{\θ}}_c)}{Y_H{v}_{\max }{\mathrm{\θ}}_c-(1+K_d{\mathrm{\θ}}_c)}$

In the formula, K _SBe semi-saturation constant, K _dBe microorganism diminution factor, Y _HBe heterotrophic bacterium yield coefficient, v _MaxBe maximum organic matter degradation rate.It is generally acknowledged that above-mentioned four sewage kinetic parameters are constant.

Classical static model are described organic matter biodegradation process qualitative features really, the deterministic model of organic concentration have been set up, though model is under the enough big situation of design safety factor, can satisfy designing requirement to a certain extent, but can't reflect the uncertainty that exists in the organic matter degradation process truly, be difficult to instruct the municipal sewage plant faced in actual moving process because of water quality and quantity change cause effluent quality can not stably reaching standard etc. problem.In view of these practical problemss, the present research focus of activated sludge model focuses mostly at dynamicmodel just, especially ASM series deterministic model.

International water quality association (IWA) is on the basis of summing up existing various biological sewage treatment mathematical models, in the ASM series model that releases one after another the 80s and 90s in 20th century, its common feature is that activated sludge process is studied as a complex system, integral body is divided into the part, set up each partial model, set up the relation between each part again, attempt to study the behavioral characteristics of activated sludge process complex system from local and whole relation.Because the ASM series model is to describe the Sludge System complex dynamic process with differential equation group, so model is more paid attention to the reaction mechanism of microorganism, therefore the ASM model is also extensively thought white-box model by the experts and scholars of western developed country, also claims deterministic model.But ASM series model complex structure, sewage kinetic parameter are too much, cause model uncertainty to increase, and are not easy to practical application.

Up to now, at the activated sludge process of municipal sewage plant, it is still rare to consider the influence of uncertain factor and set up the research report of uncertainty models.In recent years, the international research focus mainly carries out uncertainty analysis around the WWTP model, parameter that wherein is primarily aimed at the ASM series model etc. is carried out uncertainty analysis (Sin et al., 2009), mainly uses methods such as Monte Carlo (MC) method and single factor sensitivity analysis.Rousseau (2001), Bixio (2002), Benedetti (2008) and McCormick (2008) etc. have mainly proved the importance of uncertainty analysis in the WWTP model to be designed to purpose; Flores-Alsina utilization Uncertainty Analysis Method such as (2008) has compared the selection of the different control strategies of WWTP model, shows that uncertainty analysis determines that to WWTP the optimum control scheme is significant; Abusam (2001～2003) utilizes single factor Sensitivity Analysis Method to investigate the influence of the variation of stoichiometric coefficient, kinetic parameter and operating parameter to the oxidation ditch mathematical model, by ASM1 and utilize MC method respectively independent quantitative analysis influent load and probabilistic influences such as parameter value, starting condition, model structure and water temperature, net result provides with represented as histograms, they also analyze the uncertainty of oxidation ditch modeling, point out that reverse uncertainty analysis method is more effective; Digiano FA (2004) also utilizes the MC method that the uncertainty of bacterial multiplication in the mechanism model is analyzed.Up to now, great majority research still rests on the theoretical analysis stage, owing to fail to break through the expression of math equation and find the solution, therefore still fails so far to combine with the actual motion system.

In view of urban sewage treatment system has highly non-linear, time variation, uncertain stickiness in time, the present invention thinks after deliberation, setting up structure is simple relatively, parameter is less stochastic model general trend and the dynamic changing process with the reflection system, is another important development direction of activated sludge dynamic model.This class model is not obtained substantive breakthroughs at present in the world as yet, does not domesticly appear in the newspapers as yet.

Summary of the invention

Deficiency at existing sludge age method and ASM series model, the object of the present invention is to provide a kind of stochastic process Forecasting Methodology of effluent of municipal sewage plant organic concentration, for theory of random processes is provided fundamental basis in the application in biological sewage treatment field, technical support and modelling verification, for the venture analysis of municipal sewage plant's operational management provides the quantification reference frame.

In view of urban sewage treatment system has highly non-linear, time variation, uncertain stickiness in time, the present invention is according to the dynamic mass conservation equation, consider that the actual influent quality and the water yield change, utilize stochastic process to set up the stochastic model of municipal sewage plant's organic concentration, obtain analytic solution and the expectation function and the variance function of this model, but quantitative analysis influences the key factor of its effluent quality and steady running.With respect to static activated sludge model analogy method, method of the present invention can be predicted the respective change of outlet water organic substance concentration (is index with total BOD5) when the actual influent quality water yield fluctuates; With respect to ASM series dynamicmodel, the present invention have easy and simple to handle feasible, actual measurement parameter outlet water organic substance concentration and measured value match few, that find the solution is better, and can take into full account the influence to effluent quality such as actual influent quality water yield variation and various kinetic parameter fluctuations.

The present invention seeks to realize like this: the stochastic process Forecasting Methodology of effluent of municipal sewage plant organic concentration comprises the steps:

1) utilize the existing installation of municipal sewage plant to survey heterotrophic bacterium yield coefficient Y _H, the heterotrophic bacterium maximum specific growth rate With the semi-saturation constant K _S, aeration tank mixed liquor volatile suspended solid, MLVSS concentration X _V, hydraulic detention time HRT and actual entering organic matter of water concentration S ₀Wherein, $\mathrm{HRT}=\frac{V}{Q},$ Q is a flooding velocity, and V is biological treatment structures volume.

Outlet water organic substance with the municipal sewage plant is a research object, is system boundary with the biological processing unit, according to mass conservation equation, can list the organic mass conservation differential equation of Inlet and outlet water:

$V\frac{\mathrm{dS}\left(t\right)}{\mathrm{dt}}={\mathrm{QS}}_0-\mathrm{QS}\left(t\right)+\mathrm{Vr}$

Promptly

$\frac{\mathrm{dS}\left(t\right)}{\mathrm{dt}}=\frac{Q}{V}{S}_0-\frac{Q}{V}S\left(t\right)+r---\left(1\right)$

Wherein, S (t) is an outlet water organic substance concentration, and t is the time,

Be derivative about the time; S ₀Be entering organic matter of water concentration, r is an organic matter degradation rate.

In municipal effluent, utilize the Monod equation to express organic matter degradation rate with heterotrophic bacterium, be

$r=-\frac{\mathrm{dS}\left(t\right)}{\mathrm{dt}}=-\frac{1}{Y_H}\·X_V\·{\widehat{\mathrm{\μ}}}_H\·\frac{S\left(t\right)}{K_S+S\left(t\right)}$

Low concentration of substrate (S (t)＜＜K _S) time, organic matter degradation can be considered first order reaction, and therefore, organic matter degradation rate is $r\≈-\frac{{\widehat{\mathrm{\μ}}}_H}{K_S}\·\frac{X_V}{Y_H}S\left(t\right).$ Carry it into formula (1), can obtain the determinacy equation of outlet water organic substance concentration:

$\frac{\mathrm{dS}\left(t\right)}{\mathrm{dt}}=\frac{Q}{V}{S}_0-(\frac{Q}{V}+\frac{{\widehat{\mathrm{\μ}}}_H}{K_S}\·\frac{X_V}{Y_H})S\left(t\right)---\left(2\right)$

2) utilize entering organic matter of water concentration, feedwater quality and the sewage kinetic parameter of the daily actual measurement in municipal sewage plant to carry out mathematical statistics, can distinguish the standard deviation of entering organic matter of water concentration

The standard deviation sigma of amount of inlet water _{Q (t)}And the standard deviation sigma of sewage kinetic parameter _P

The height of considering the actual cities Sewage treatment systems is non-linear, time variation, uncertain stickiness in time, need increase a Disturbance on organic concentration determinacy equations based.This Disturbance is mainly considered following four prediction reference factors: the 1. variation of influent quality; 2. the variation of amount of inlet water; 3. the non-constant of kinetic parameter; 4. the error of bringing because of the one-level reduced equation that uses the Monod pattern.

At first obtain first three reference factor, utilize entering organic matter of water concentration, feedwater quality and the sewage kinetic parameter of the daily actual measurement in municipal sewage plant to carry out mathematical statistics, can obtain the standard deviation of influent quality, amount of inlet water and sewage kinetic parameter respectively σ _{Q (t)}And σ _PAbove-mentioned three kinds of uncertain factors are taken all factors into consideration be disturbance factor σ _{S (t)}, in order to represent the strength of turbulence of this stochastic process, that is: ${\mathrm{\σ}}_{S\left(t\right)}=\sqrt{w_1{\mathrm{\σ}}_{S_0\left(t\right)}^2+w_2{\mathrm{\σ}}_{Q\left(t\right)}^2+w_3{\mathrm{\σ}}_P^2},$ W in the formula ₁, w ₂, w ₃Expression respectively

σ _{Q (t)}, σ _PWeight, each weight can be carried out assignment to the influence degree of sewage work's actual motion according to its corresponding parameters, and w ₁+ w ₂+ w ₃=1.In sewage work, since water collecting basin with promote the homogenizing of pumping plant to the water yield, the amount of inlet water fluctuation to effluent quality to influence meeting weakened, and the fluctuation range of kinetic parameter generally can be very not big, therefore, the weight maximum of influent quality influence of fluctuations in this model.

3) error that is caused by simplification merges processing, and it is treated to a Wiener-Hopf equation W (t); As the forecasting techniques means, this Wiener-Hopf equation is carried out match by the Random function among the Matlab, and then the stochastic equation of outlet water organic substance concentration is:

$\frac{\mathrm{dS}\left(t\right)}{\mathrm{dt}}=\frac{Q}{V}{S}_0-(\frac{Q}{V}+\frac{{\widehat{\mathrm{\μ}}}_H}{K_S}\·\frac{X_V}{Y_H})S\left(t\right)+{\mathrm{\σ}}_{S\left(t\right)}W\left(t\right)---\left(3\right)$

Order $\mathrm{\&alpha;}=\frac{Q}{V}+\frac{{\widehat{\mathrm{\&mu;}}}_H}{K_S}\&CenterDot;\frac{X_V}{Y_H},$ $\mathrm{\&beta;}=\frac{\mathrm{<figure-callout\; id="0"\; label="Q\; V\; S"\; filenames="HSA00000024924900012.png"\; state="\{\{state\}\}">Q</figure-callout>}}{V}{S}_{}{}_0,$ Then formula (3) is expressed as:

dS(t)＝(β-αS(t))dt+σ _S(t)dB(t) (4)

B in the formula (t) is pedesis, dB (t)=W (t) dt.

Utilize

Formula is found the solution formula (4), can obtain the anticipation function of outlet water organic substance concentration S (t):

$S\left(t\right)=e^{-\mathrm{\&alpha;}(t-t_0)}S\left(t_0\right)+\frac{\mathrm{\&beta;}}{\mathrm{\&alpha;}}-\frac{\mathrm{\&beta;}}{\mathrm{\&alpha;}}{e}^{-\mathrm{\&alpha;}(t-t_0)}+{\mathrm{\&sigma;}}_{S\left(t\right)}{\&Integral;}_{t_0}^t{e}^{\mathrm{\&alpha;}(x-t)}\mathrm{dB}\left(x\right)---\left(5\right)$

In the formula, t ₀Expression prediction time of origin, e is a natural constant.Be about to described measured value input computer, utilize Matlab to pass through functional relation (5) again and can predict and obtain the municipal sewage plant in the outlet water organic substance concentration S of random time t (t).

Further, the expectation function E[S of outlet water organic substance concentration (t)] with variance function D[S (t)] be calculated as follows by computer and obtain:

$E\left[S\left(t\right)\right]=e^{-\mathrm{\&alpha;}(t-t_0)}E\left[S\left(t_0\right)\right]+\frac{\mathrm{\&beta;}}{\mathrm{\&alpha;}}-\frac{\mathrm{\&beta;}}{\mathrm{\&alpha;}}{e}^{-\mathrm{\&alpha;}(t-t_0)}---\left(6\right)$

$D\left[S\left(t\right)\right]=e^{-2\mathrm{\&alpha;}(t-t_0)}D\left[S\left(t_0\right)\right]-{\mathrm{\&sigma;}}_{S\left(t\right)}^2\frac{e^{-2\mathrm{\&alpha;}(t-t_0)}-1}{2\mathrm{\&alpha;}}---\left(7\right)$

S (t in the formula ₀) outlet water organic substance concentration of expression prediction time of origin.

Utilize expectation function E[S (t)] and variance function D[S (t)] can understand the overall variation tendency of effluent of municipal sewage plant organic concentration, be convenient to carry out venture analysis, help adjusting flexibly the actual motion control scheme of Sewage Plant the sewage disposal plant effluent organic concentration is whether up to standard.

Main innovate point of the present invention is that stochastic process is introduced the Sludge System modeling, has set up the random process model of outlet water organic substance concentration, and the multinomial uncertain factor that influences the sewage disposal plant effluent organic concentration is quantized.Present method is brand-new dynamic activity mud model, the present international and domestic this model that still do not have.

With respect to prior art, the present invention has following advantage:

1) with respect to the activated sludge model of static state, the dynamic changing process that the present invention can simulation and forecast outlet water organic substance concentration when fluctuations such as the actual influent quality water yield; With respect to the ASM series model, the present invention's parameter to be measured is few, only needs to survey the yield coefficient Y of heterotrophic bacterium _H, maximum specific growth rate

And semi-saturation constant K _S, can carry out the stochastic simulation prediction, easy and simple to handle feasible, precision of prediction is higher, and can take into full account the influence to effluent quality such as actual influent quality water yield variation and various kinetic parameter fluctuations.

2) the present invention adopts total BOD ₅Index as organic concentration, biological significance is clear and definite, and the existing Inlet and outlet water index in municipal sewage plant just has this, and needn't require the sewage quality feature is carried out complexity, detail analysis as the ASM series model, therefore is convenient to very much practicality.

3) the present invention can not only provide the stochastic prediction value of effluent of municipal sewage plant organic concentration, simultaneously can also further provide its expectation function and variance function, that is to say, can not only provide the dynamic change predictor S (t) of this plant effluent organic concentration, and can provide its overall variation tendency and promptly expect function E[S (t)] and variance function D[S (t)], be convenient to carry out venture analysis, help adjusting flexibly the actual motion control scheme of Sewage Plant the sewage disposal plant effluent organic concentration is whether up to standard.

Description of drawings

Fig. 1 is the schema of the stochastic process Forecasting Methodology of effluent of municipal sewage plant organic concentration of the present invention;

The correlation curve figure of Fig. 2 for predicting the outcome in the embodiment of the invention with actual outlet water organic substance concentration.

Embodiment

Below in conjunction with embodiment the present invention is done to describe in further detail.

Referring to Fig. 1, the invention provides a kind of stochastic process Forecasting Methodology of effluent of municipal sewage plant organic concentration, comprise the steps:

1) utilize the existing installation of municipal sewage plant to survey heterotrophic bacterium yield coefficient Y _H, the heterotrophic bacterium maximum specific growth rate

With the semi-saturation constant K _S, aeration tank mixed liquor volatile suspended solid, MLVSS concentration X _V, hydraulic detention time HRT and actual entering organic matter of water concentration S ₀Wherein, $\mathrm{HRT}=\frac{Q}{V},$ Q is a flooding velocity, and V is the reactor volume of Treating Municipal Sewage.

(1) actual measurement heterotrophic bacterium yield coefficient Y _H

Y _HStrict difinition be: when all available energy all are used for removing the microbial biomass that unit matrix is generated when synthetic.Y _HCan estimate by in dissolved organic matter removal process, measuring the cellular material growing amount.Sewage at first should precipitate and the elimination particulate matter, only contains dissolved organic matter in the filtrate, takes out on a small quantity acclimated microorganism inoculation from complete.Regularly take out mixed solution, measure solvability BOD ₅With mixed liquor volatile suspended solid, MLVSS concentration MLVSS.The productive rate of heterotrophic bacterium can by

Obtain.Repeat several times, just can obtain Y _HValue.To municipal effluent, general Y _H=0.6～0.7mg MLVSS/mg BOD ₅

(2) actual measurement heterotrophic bacterium maximum specific growth rate

And semi-saturation constant K _S

The heterotrophic bacterium maximum specific growth rate

And semi-saturation constant K _SBeing subjected to the influence of influent quality, microbial population and the concrete pattern of biological treatment structures, is not constant value usually,

Measured value concentrate (municipal effluent μ relatively _H=3～13.2d ^-1), and K _SBe worth then widely different (municipal effluent K _S=17～310mg BOD ₅/ L), must field measurement.

In the ASM series model, generally adopt the respiration monitoring method to estimate

And K _SThe most of municipal sewage plants of China may temporarily not possess such condition determination at present, and therefore, the present invention advises adopting chemostat to carry out test determination, and this is practicable.Promptly utilize the formula after the linearizing $\frac{1}{S\left(t\right)}=\frac{{\widehat{\mathrm{\&mu;}}}_H}{K_S}{\mathrm{\&theta;}}_c-\frac{1}{K_S},$ Measure different sludge age θ _cThe time organic concentration S (t), utilize 1/S (t) to θ _CBe figure and can obtain straight line, just can try to achieve according to intercept and slope

And K _SShould note avoiding the oxygen restriction in the mensuration process, to municipal effluent (20 ℃), general dissolved oxygen concentration must be greater than 2mg/L.

(3) collect daily measured data X _V, HRT and the total BOD of actual Inlet and outlet water ₅Data

The total BOD of actual Inlet and outlet water ₅Value and feed water flow value can be thought normal distribution, also show the reasonableness of this hypothesis from the real data in 4～8 years in several municipal sewage plants that we collect.

In the actual motion of municipal sewage plant, X _V, HRT and sewage kinetic parameter etc. may not be absolute constant, but we can get its mean value (municipal effluent X earlier _V=1500～2500mg/L), when prediction, consider to strengthen certain strength of turbulence then, this uncertainty is reflected.

2) utilize entering organic matter of water concentration, feedwater quality and the sewage kinetic parameter of the daily actual measurement in municipal sewage plant to carry out mathematical statistics, obtain the standard deviation of entering organic matter of water concentration respectively

The standard deviation sigma of amount of inlet water _{Q (t)}And the standard deviation sigma of sewage kinetic parameter _P

3) utilize the penalty coefficient of a Wiener-Hopf equation W of Matlab match (t), utilize formula dS=(β-α S) dt+ σ as simplification error _{S (t)}DB (t), and substitution $\mathrm{\&alpha;}=\frac{Q}{V}+\frac{{\widehat{\mathrm{\&mu;}}}_H}{K_S}\&CenterDot;\frac{X_V}{Y_H},$ $\mathrm{\&beta;}=\frac{\mathrm{<figure-callout\; id="0"\; label="Q\; V\; S"\; filenames="HSA00000024924900012.png"\; state="\{\{state\}\}">Q</figure-callout>}}{V}{S}_{}{}_0,$ Can find the solution by Matlab.

By above step, just measurable when fluctuation such as the actual influent quality water yield outlet water organic substance concentration (with total BOD ₅Be index) dynamic changing process.

The inventive method is only at the organism modeling in the biological treatment structures, and not to the second pond modeling, because organic degraded is almost all finished at the biological treatment structures, the analogue value of present method also is at the biological treatment structures.But because the municipal sewage plant is made of " biological treatment structures+second pond ", by second pond control mud-water separation effect, still, the deposition efficiency of second pond can not reach 100%, current specifications is also stipulated its water outlet SS≤20mg/L, shows that actual water outlet contains the graininess organism.For second pond is considered together also that to the influence of outlet water organic substance concentration present method finally adopts the second pond water outlet to survey total BOD through theoretical and actual analysis research ₅Mean value as the total BOD of this stochastic model mimic water outlet ₅Initial value, the influence of determining to have considered second pond of initial value itself like this.

Embodiment:

According to certain municipal sewage plant 2004～2008 48 totally months actual operating data, utilize the inventive method its outlet water organic substance concentration to be simulated by Matlab.

Model parameter value: Y _H=0.65mg MLVSS/mg BOD ₅, μ _H=3.5d ^-1, K _S=150mg/L, HRT=8h, X _V=2000mg/L, S ₀(0)=and 125mg/L, S (0)=9mg/L, σ _{S (t)}=40mg/L, α=75, β=375.Wherein organic concentration is all with BOD ₅Be index, the time is unit with the sky, and dt=1/1000.

With above-mentioned parameter value basis $S\left(t\right)=e^{-\mathrm{\&alpha;}(t-t_0)}S\left(t_0\right)+\frac{\mathrm{\&beta;}}{\mathrm{\&alpha;}}-\frac{\mathrm{\&beta;}}{\mathrm{\&alpha;}}{e}^{-\mathrm{\&alpha;}(t-t_0)}+{\mathrm{\&sigma;}}_{S\left(t\right)}{\&Integral;}_{t_0}^t{e}^{\mathrm{\&alpha;}(s-t)}\mathrm{dB}\left(s\right)$ Or dS=(β-α S) dt+ σ _{S (t)}DB (t) carries out simulation and forecast by computer with Matlab.The actual outlet water organic substance concentration of this sewage work obtains the comparative graph of outlet water organic substance concentration referring to Fig. 2 with adopting present method prediction.Can see that from figure except that the initial period of open curve causes certain deviation because of the reason of initial value setting, in other most predetermined period, predictor and actual value are all very approaching, precision of prediction is very high.

Explanation is at last, above embodiment is only unrestricted in order to technical scheme of the present invention to be described, although the present invention is had been described in detail with reference to preferred embodiment, those of ordinary skill in the art is to be understood that, can make amendment or be equal to replacement technical scheme of the present invention, and not breaking away from the aim and the scope of technical solution of the present invention, it all should be encompassed in the middle of the claim scope of the present invention.

Claims (2)

1. the stochastic process Forecasting Methodology of effluent of municipal sewage plant organic concentration is characterized in that comprising the steps:

1) utilize the existing installation of municipal sewage plant to survey heterotrophic bacterium yield coefficient Y _H, the heterotrophic bacterium maximum specific growth rate

With the semi-saturation constant K _S, aeration tank mixed liquor volatile suspended solid, MLVSS concentration X _V, hydraulic detention time HRT and actual entering organic matter of water concentration S ₀Wherein,

Q is a flooding velocity, and V is the reactor volume of Treating Municipal Sewage;

2) utilize entering organic matter of water concentration, feedwater quality and the sewage kinetic parameter of the daily actual measurement in municipal sewage plant to carry out mathematical statistics, obtain the standard deviation of entering organic matter of water concentration respectively

The standard deviation sigma of amount of inlet water _{Q (t)}And the standard deviation sigma of sewage kinetic parameter _P

3) with described measured value input computer, utilize the penalty coefficient of a Wiener-Hopf equation W of Matlab match (t), and utilize Matlab by following function prediction outlet water organic substance concentration S (t) as simplification error:

$S\left(t\right)=e^{-\mathrm{\&alpha;}(t-t_0)}S\left(t_0\right)+\frac{\mathrm{\&beta;}}{\mathrm{\&alpha;}}-\frac{\mathrm{\&beta;}}{\mathrm{\&alpha;}}{e}^{-\mathrm{\&alpha;}(t-t_0)}+{\mathrm{\&sigma;}}_{S\left(t\right)}{\&Integral;}_{x=t_0}^{x=t}{e}^{\mathrm{\&alpha;}(x-t)}\mathrm{dB}\left(x\right);$

Wherein, t is the time, t ₀Expression prediction time of origin, e is a natural constant; $\mathrm{\&alpha;}=\frac{Q}{V}+\frac{{\widehat{\mathrm{\&mu;}}}_H}{K_S}\&CenterDot;\frac{X_V}{Y_H},$ $\mathrm{\&beta;}=\frac{Q}{V}{S}_0;$ σ _{S (t)}For disturbance factor and ${\mathrm{\&sigma;}}_{S\left(t\right)}=\sqrt{w_1{\mathrm{\&sigma;}}_{S_0\left(t\right)}^2+w_2{\mathrm{\&sigma;}}_{Q\left(t\right)}^2+w_3{\mathrm{\&sigma;}}_P^2},$ W wherein ₁, w ₂, w ₃Expression respectively

σ _{Q (t)}, σ _PWeight, and w ₁+ w ₂+ w ₃=1; B (t) represents pedesis, and dB (t)=W (t) dt.

2. the stochastic process Forecasting Methodology of effluent of municipal sewage plant organic concentration according to claim 1 is characterized in that the expectation function E[S (t) of described outlet water organic substance concentration] and variance function D[S (t)] be calculated as follows by computer and obtain:

$E\left[S\left(t\right)\right]=e^{-\mathrm{\&alpha;}(t-t_0)}E\left[S\left(t_0\right)\right]+\frac{\mathrm{\&beta;}}{\mathrm{\&alpha;}}-\frac{\mathrm{\&beta;}}{\mathrm{\&alpha;}}{e}^{-\mathrm{\&alpha;}(t-t_0)},$

$D\left[S\left(t\right)\right]=e^{-2\mathrm{\&alpha;}(t-t_0)}D\left[S\left(t_0\right)\right]-{\mathrm{\&sigma;}}_{S\left(t\right)}^2\frac{e^{-2\mathrm{\&alpha;}(t-t_0)}-1}{2\mathrm{\&alpha;}};$

In the formula, S (t ₀) outlet water organic substance concentration of expression prediction time of origin.

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