JPH07275882A - Sewage treatment control apparatus - Google Patents

Abstract

PURPOSE:To enable control not bringing about the lowering of the quality of treated water during a period forming a self-regression model and to stabilize a system by providing an MLSS objective value adder, a total sludge amt. objective value adder and a dissolved oxygen objective value adder. CONSTITUTION:In this sewage treatment control apparatus equipped with an upper control system using a linear model including even the lower control system related to an activated sludge treatment control apparatus as a part of a treatment apparatus, an MLSS objective adder 45 inputting an MLSS objective value calculated from manual analytical data and the output of the optimizing device 31 of the operation device 27 of the upper control system to output them to an excessive sludge amt. operation device 39 is provided. A total sludge amt. objective value adder 47 inputting a total sludge amt. objective value calculated from the manual analytical data and the output of the optimizing device 31 of the operation device 27 to output them to a return sludge amt. operation device 41 is provided and, further, a dissolved oxygen objective value adder 49 inputting a dissolved oxygen objective value calculated from the manual analytical data and the output of the optimizing device 49 to output them to an aeration air amt. operation device 43 is provided.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a control device for sewage treatment by an activated sludge method for purifying sewage containing organic substances such as urban sewage and industrial wastewater.

[0002]

2. Description of the Related Art The structure of a conventional sewage treatment control device is shown in FIG. Amount of sewage flowing from the pipeline 1 into the aeration tank 2, p
The H, inflow water suspended matter concentration, and inflow water organic matter concentration are detected by the inflow sewage amount meter 10, the pH meter 11, the suspended matter concentration meter 12, and the organic matter concentration meter 13, and the detection signals are sent to the arithmetic unit 27. Output. The dissolved oxygen concentration of the mixed liquid of the sewage flowing into the aeration tank 2 and the returning sludge returned from the sedimentation tank,
MLSS and water temperature are dissolved oxygen concentration meter 14, MLSS
It is detected by the total 15 and the water temperature gauge 16 and the detection signal is output to the arithmetic unit 27. The organic matter concentration and MLSS of the mixed liquid flowing out from the aeration tank 2 are measured by the organic matter concentration meter 17 and the MLSS.
The detection is performed by the total 18 and the detection signal is output to the arithmetic unit 27. The treated water separated and settled in the settling tank 3 from the mixed solution is supplied to the pipe 7
Is discharged to the outside of the apparatus, and the suspended matter concentration, organic matter concentration and pH of the treated water are detected by the suspended matter concentration meter 19, the organic matter concentration meter 20 and the pH meter 21, and the detection signal is output to the arithmetic unit 27. To do. Amount of returned sludge, concentration of returned sludge,
The excess sludge amount, excess sludge concentration, and aeration air amount are detected by the returned sludge amount measurement device 22, the returned sludge concentration meter 23, the excess sludge extraction amount measurement device 24, the excess sludge concentration device 25, and the aeration air flow measurement device 26. The detection signal is output to the arithmetic unit 27. The signals detected by the MLSS meter 15 and the excess sludge removal amount measuring meter 24 are output to the excess sludge amount calculation device 39.
The signals detected by the inflow sewage meter 10, the MLSS meter 18, and the returned sludge concentration meter 23 are output to the returned sludge amount calculation device 41. The signals detected by the dissolved oxygen concentration meter 14 and the aeration air volume measuring device 26 are used as the aeration air volume calculation device 43.
Output to. 4 is a pipeline for returning sludge to the aeration tank, 5 is an air diffuser provided in the aeration tank, 6 is a blower, and a controller 32
The air flow rate is controlled by. Reference numeral 8 is a return sludge pump provided in the pipe line 4, and the control device 33 controls the amount of return sludge. Reference numeral 9 denotes a drawn-out sludge pump that discharges sludge from the settling tank to the outside, and the controller 34 controls the amount of drawn-out sludge. Reference numeral 27 denotes a computing device, which is an autoregressive model computing device 28, a selecting device 29, a modified autoregressive model computing device 30, an optimizing device 31, a measured value storage device 35, a predicted value computing device 36, a predicted value storage device 3.
7 and a comparison device 38, and stores the detection signal of the measurement value measured by each measuring device in the storage device 35. Reference numeral 40 denotes a surplus sludge amount adding device, which inputs a signal from the surplus sludge amount calculating device 39 and a signal from the optimizing device 31 and outputs the signal to the control device 34. Reference numeral 42 denotes a returning sludge amount adding device, which is adapted to input the signal of the returning sludge amount calculating device 41 and the signal of the optimizing device 31 and output them to the control device 33. Reference numeral 44 is adapted to input the signal of the aeration air volume calculation device 43 and the signal of the optimization device 31 and output them to the control device 32. In this computing device 27, an autoregressive model computing device 28 creates an autoregressive model in the following order from the signals stored in the storage device. In the sewage treatment system, the current process state can be represented in large part by a linear combination of past process states. Now, the process state at time n is represented by a k-dimensional all-variable vector X
Expressed as (n), its autoregressive expression is as follows.

[0003]

[Equation 1]

However, X (n-m) is a vector of all variables before time n before time n, U (n) is a white noise vector, A
(M) is the regression coefficient matrix of the autoregressive model, and M is the optimum order of the autoregressive model. The element a _ij (m) of the regression coefficient A (m) in the equation (1) is obtained as the solution of the following simultaneous linear equations.

[0005]

[Equation 2]

However, R _ih is a mutual function of the elements of the i, h row of X. The element of the white noise vector U (n) is ei
Given (n), its variance σ ei ² is as follows.

[0007]

[Equation 3]

The optimum order M of the model is a value that minimizes MFPE (M) in the equation (4) indicating the prediction error.

[0009]

[Equation 4]

However, N is the number of data,

[0011]

[Equation 5]

‖D _M ‖ is the variance-covariance matrix estimate.
In this way, the autoregressive coefficient, the model order, and the variance of white noise (specific noise) are obtained, and the autoregressive model is created. Next, in order to keep the controlled variables of the sewage treatment device, that is, the treated water organic matter concentration, the treated water suspended matter concentration, and the MLSS constant, among the many system variables that make up this autoregressive model, It is necessary to select the contributing system variables. In a closed loop in which K system variables are connected by transfer elements, the transfer element x connecting a _ij (f) to the variables x _i (f) and x _j (f)
and x frequency response function of _j to (f) from _i (f), u
If _i (f) is a representation in the frequency region of internal noise of x _i (f),

[0013]

[Equation 6]

Is obtained. here,

[0015]

[Equation 7]

[0016]

[0017]

[Equation 8]

Here, b _ij (f) represents the influence of the intrinsic noise u _j (f) of the j-th variable on the i-th system variable x _i (f) through the feedback loop.
The expression in the power spectrum region of Expression (7) is

[0019]

[Equation 9]

However, p (u _j ) (f) is the power spectral density of the intrinsic noise u _{j at} the frequency f. Furthermore, the part of the power spectral density p _ii (f) of x _i (f) at frequency f that contributes to u _j (f) is q
_{If ij} (f), then q _ij (f) = | b _ij (f) | ² · P (U _j ) (f) (9). Here, q _ij (f) of is referred to as a noise contribution rate.
That is, for example, the contribution rates of the system variables B, C, and D to a certain system variable A are 35%, 40%, and 2 respectively.
If it is determined to be 5%, it means that the system variable A is affected in the order of the system variables C, B, and D. Further, the variation range of the measurement value can be easily estimated by obtaining the standard deviation. The standard deviation S is obtained from the equation (10),

[0021]

[Equation 10]

It can be considered that 99.7% of the measured value falls within the range of X _i obtained by the equation (11).

[0023]

[Equation 11]

Therefore, the measured value obtained momentarily is (1
Normal, depending on whether it is included in the fluctuation range of equation (1),
It is possible to make an abnormality determination. In the selection device 29, the output from the autoregressive model calculation device 28 (9)
Based on the equation (10), the degree of influence of the system variable on the controlled variable, that is, the concentration of the organic matter in the treated water, the concentration of the suspended matter, and the concentration of the MLSS in the aeration tank is calculated and output to the modified autoregressive model calculation device 30. In the modified autoregressive model computing device 30, the measured value of the storage device 35 is applied to create a modified autoregressive model. The modified autoregressive model computing device 30 creates a modified autoregressive model composed only of variables having an important influence on the quality of treated water, and outputs it to the optimizing device 31 as a mathematical model. The output from the modified autoregressive model computing device 30 is also input to the prediction computing device 36.
The measured value collected at the current time is also applied to the modified autoregressive model to calculate the measured value at the future time, and the predicted value is output to the prediction storage device 37. The comparison device 38 compares the measured value with the prediction value at the time stored in the prediction storage device 37, and calculates the prediction error. As a result of the calculation, when it is determined that the prediction error is large, that is, when the modified autoregressive model used is not appropriate, a signal is output to the autoregressive model operation device 28 to output the autoregressive model Update. In this way, when the modified autoregressive model used is determined to be inappropriate as a model, the model is automatically updated. Next optimization device 31
Then, the measured values are input to the modified autoregressive model every moment, the optimization control signal is calculated, and the control signal is sent to the excess sludge amount addition device 40, the returned sludge amount addition device 42, and the aeration air amount addition device 44. Output. On the other hand, in the surplus sludge amount calculation device 39, the surplus sludge amount is calculated from the aeration tank MLSS and the surplus sludge withdrawal amount at the current time so that the aeration tank MLSS becomes approximately constant, and this value is added to the surplus sludge amount. Device 4
Output to 0. Further, in the returned sludge amount calculation device 41, the amount of the returned sludge is adjusted so that the total amount of the sludge in the settling tank 3 becomes substantially constant from the inflow sewage amount, the MLSS of the mixed liquid flowing out from the aeration tank 2, and the returned sludge concentration. Calculation is performed and this value is output to the returned sludge amount addition device 42. Further, the aeration air volume calculation device 43 calculates the aeration air volume from the dissolved oxygen concentration and the aeration air volume so that the dissolved oxygen concentration in the aeration tank 2 becomes substantially constant, and outputs this value to the aeration air volume addition device 44. In the excess sludge amount addition device 40, the returned sludge amount addition device 42, and the aeration air amount addition device 44, the optimization control signal from the optimization device 31 and the signals from the respective arithmetic devices are added, and the addition signals are withdrawn sludge. The control device 34 for the pump, the control device 33 for the returning sludge pump, and the control device 32 for the blower are provided. Then, control is performed by the output signals of these control devices. In such a sewage treatment control device,
By maintaining the MLSS and dissolved oxygen concentration in the aeration tank and the total amount of sludge in the settling tank at approximately constant values, the system is stabilized and the stabilization of treated water is optimized by a modified autoregressive model. This is realized by the system.

[0025]

However, the conventional ones have the following problems. (1) The autoregressive model computing device 28 creates an autoregressive model by using the signal stored in the storage device 35 for a certain period of time. The control signals output to the returning sludge amount adding device 42 and the aeration air amount adding device 44 are signals that fluctuate irregularly (hereinafter referred to as noise). Therefore, when the absolute value of this noise becomes large, the quality of the treated water may be adversely affected. For example, aeration tank 2 when it rains
The amount of sewage that flows into the air increases, but the aeration air volume adding device 4
If the noise given to 4 happens to be a large negative value,
It is considered that the amount of air becomes insufficient and the concentration of organic matter in the treated water or the concentration of suspended solids in the treated water shows a high value. (2) The creation period of the autoregressive model is a specific item for stabilizing the system, such as MLSS in the aeration tank,
Since the dissolved oxygen concentration, the total amount of sludge in the sedimentation tank, etc. may deviate from the target values, the operators of the treatment plant may feel uneasy. Further, even when the control is performed after the autoregressive model is created, the control signal from the arithmetic unit of the upper control system is the excess sludge amount addition device 40 and the returned sludge amount addition device 42 of the lower control system.
And the aeration air amount adding device 44, the same situation occurs. The present invention has been improved in order to eliminate such drawbacks, the target value of a specific item for preventing the deterioration of the quality of the treated water even during the autoregressive model creation, and for stabilizing the system. The purpose is to realize an optimum control system by an autoregressive model in which the water quality of treated water is used as a controlled variable by reducing the deviation from.

[0026]

A first aspect of the present invention is a linear model including a lower-level control system for stabilizing a specific item of an activated sludge treatment control device and a lower-level control system as a part of the treatment device. MLS calculated from hand analysis data in a sewage treatment controller equipped with a higher-level control system using
MLSS target value addition device that inputs the S target value and the output of the optimization device of the arithmetic device of the upper control system and outputs it to the surplus sludge amount calculation device, the total sludge amount target value calculated from the manual analysis data, and the upper control Of the target value of the total sludge amount that inputs the output of the optimization device of the system arithmetic device and outputs it to the returned sludge amount arithmetic device, the dissolved oxygen target value calculated from the hand analysis data and the arithmetic device of the upper control system An output of the optimizing device is input and an aeration air volume calculation device is provided. A second invention is a lower control system for stabilizing a specific item of an activated sludge treatment control device, and an upper control system using a linear model including this lower control system as a part of the treatment device. In the provided sewage treatment control device, a dissolved air target value calculated from the hand analysis data and the output of the optimization device of the arithmetic device of the upper control system are input and an aeration air amount arithmetic device is provided. A third aspect of the present invention is to provide a lower control system for stabilizing a specific item of the activated sludge treatment control device and an upper control system using a linear model including the lower control system as a part of the treatment device. In the equipped sewage treatment control device, the total sludge amount target value calculated from the hand analysis data and the output of the optimization device of the arithmetic unit of the upper control system are input and output to the returned sludge amount arithmetic unit. An adding device and an aeration air amount calculating device for inputting the dissolved oxygen target value calculated from the hand analysis data and the output of the optimizing device of the calculating device of the upper control system are provided.

[0027]

[Effect] Therefore, even during the period of creating the autoregressive model, it is possible to prevent the deterioration of the treated water quality and to reduce the deviation from the target value of the specific items for the purpose of stabilizing the system to reduce the fluctuation of the treated water quality. A control system that suppresses can be realized.

[0028]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be specifically described below based on the embodiment shown in FIG. FIG. 1 shows a configuration diagram of the sewage treatment control device. The same parts as those in FIG. 2 are designated by the same reference numerals, and detailed description thereof will be omitted. Reference numeral 45 denotes an MLSS target value adding device, which calculates the MLSS target value 46 calculated from the hand analysis data and the output of the optimizing device 31 and outputs it to the surplus sludge amount calculation device 39. Reference numeral 47 is a total sludge amount target value adding device, which calculates the total sludge amount target value 48 calculated from the hand analysis data and the output of the optimizing device 31 and outputs it to the returned sludge amount calculating device 41. Reference numeral 49 denotes a dissolved oxygen target value addition device, which calculates the dissolved oxygen target value 50 calculated from the hand analysis data and the output of the optimization device 31 and outputs it to the aeration air amount calculation device 43. The target from the optimization device 31 now. When the value adjustment amount is SPopt and the target value calculated from the hand analysis data is SPman, the output signal SPout from the MLSS target value adding device, the total sludge amount target value adding device and the dissolved oxygen target value adding device is (12). Given by the formula. SPout = F (SPopa ＋ SPman, L, H) ................................ (12) SPopa = F (SPopt, ー D, D) ... (13) However, L and H are the upper and lower limits of the target value, D is the amplitude of the target value adjustment amount, and F ( X0, Y1, Y2) is a function defined by the following formula F (X0, Y1, Y2) = Y1 (X0 <Y1) .................. ( 14-1) = X0 (Y1 ≤ X0 ≤ Y2) .................. (14-2) = Y2 (X0> Y2) ....... ........... (14-3) Here, L and H are determined from the performance of the operating equipment and the state of the process, and D is the upper control system for all control systems. It is decided based on the degree of contribution. Such a control signal from each target value addition device is used to calculate the excess sludge amount calculation device 39 and the returned sludge amount calculation device 41.
And outputting to the aeration air amount adding device 43,
MLSS and dissolved oxygen concentration in the aeration tank, or the total amount of sludge in the settling tank, which are the specific items for stabilizing the system, can be maintained at values close to the target values, and fluctuations in the treated water quality can be controlled. It becomes possible to suppress.

[0029]

As described above, according to the present invention, it is possible to prevent the quality of treated water from deteriorating even during the preparation of an autoregressive model, and to stabilize the controlled variable during control. It is possible to realize an optimal control system using the autoregressive model. Further, in both of the above-mentioned periods, the measured values of the specific items for stabilizing the system can be maintained at values close to the target values, so that the operator of the processing plant is not anxious.

[Brief description of drawings]

FIG. 1 is a configuration diagram of an embodiment of a sewage treatment control device according to the present invention.

FIG. 2 is a block diagram of a conventional sewage treatment control device.

[Explanation of symbols]

2 Aeration tank 3 Settling tank 10 Inflow sewage amount meter 11 Inflow water pH meter 12 Inflow water suspended matter concentration meter 13 Inflow water organic matter concentration meter 14 Dissolved oxygen content meter 15 MLSS concentration meter 16 Water temperature meter 17 Aeration tank outflow Water organic matter concentration meter 18 MLSS concentration meter 19 Treated water suspended matter concentration meter 20 Treated water organic matter concentration meter 21 Treated water pH meter 22 Return sludge amount meter 23 Return sludge concentration meter 24 Excess sludge extraction meter 25 Excess sludge Concentration meter 26 Aeration air amount measuring device 27 Computing device 31 Optimizing device 34 Controlling device for extraction sludge pump 35 Measured value storage device 36 Predicted value calculation device 37 Predicted value storage device 38 Comparison device 39 Excess sludge amount calculation device 40 Excess sludge amount addition Device 41 Return sludge amount calculation device 42 Return sludge amount addition device 43 Aeration air amount calculation device 44 Aeration air amount addition device 45 ML S target value adding unit 46 MLSS target value 47 total sludge amount target value adding unit 48 hands analyzed total sludge amount target value 49 dissolved oxygen target value adding unit 50 dissolved oxygen target value

Claims (3)

[Claims] 1. A lower control system for stabilizing a specific item of an activated sludge treatment control device, and an upper control system using a linear model including this lower control system as part of the treatment device. In the sewage treatment control device, the MLSS target value addition device that inputs the MLSS target value calculated from the hand analysis data and the output of the optimization device of the arithmetic device of the upper control system and outputs it to the surplus sludge amount arithmetic device, Total sludge amount target value calculated from the analysis data and the output of the optimization device of the arithmetic unit of the upper control system are input and output to the returned sludge amount arithmetic unit, and the calculation from the manual analysis data A sewage treatment control device comprising: an aeration air flow rate calculation device for inputting the dissolved oxygen target value and the output of the optimization device of the calculation device of the upper control system. 2. A lower control system for stabilizing a specific item of an activated sludge treatment control device, and a higher control system using a linear model including this lower control system as a part of the treatment device. In the sewage treatment control device, the sewage treatment device is provided with the dissolved air target value calculated from the hand analysis data and the output of the optimization device of the arithmetic device of the upper control system, and an aeration air amount arithmetic device. Control device. 3. A lower control system for stabilizing a specific item of an activated sludge treatment control device, and an upper control system using a linear model including this lower control system as a part of the treatment device. In the sewage treatment control device, the total sludge amount target value calculated from the hand analysis data and the output of the optimization device of the arithmetic unit of the upper control system are input and output to the returned sludge amount arithmetic unit. A sewage treatment control device comprising: a device, and a dissolved air target value calculated from hand analysis data and an output of an optimization device of an arithmetic device of an upper control system, and an aeration air amount arithmetic device.