JP3120531B2 - Anaerobic digester monitoring device - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION The present invention relates to a method in which a sample sampled from an anaerobic digestion tank for treating sludge is subjected to solid-liquid separation using an ultrafiltration device and then sent to an acid-alkali titration tank for titration. , Total organic acid concentration, total inorganic carbon concentration, total ammonia concentration, total phosphorus concentration, total sulfide concentration
The present invention relates to a monitoring device that continuously monitors a state change in a digestion tank depending on an item.

[0002]

2. Description of the Related Art Generally, biological anaerobic sludge digestion is performed in two steps.
It progresses step by step with different bacterial groups. The first stage is called an “acid generation stage”, and sludge fed into the digestion tank is decomposed into intermediate products such as organic acids by the action of hydrolytic bacteria or acid-producing bacteria. The second stage is called a “methane production stage”, and intermediate products such as organic acids produced in the above-mentioned acid production stage are decomposed into final products such as methane gas, carbon dioxide, and ammonia by the action of methanogens. You.

[0003] The ammonia produced in the second stage is
It has a function to neutralize the organic acid generated in the first stage and a pH buffering ability (ability to resist pH change) together with bicarbonate generated by dissolving carbon dioxide, which is favorable for methanogens. It is useful for creating a weak alkaline environment in the tank.

[0004] Methanogens have a slower growth rate than acid-producing bacteria and are more sensitive to environmental changes. Therefore, it is generally considered that the rate of digestion is determined by the methanogenesis stage. Therefore, for good operation of the digestion tank, it is important to maintain a tank environment suitable for the survival of methanogens.

[0005] From such a viewpoint, it is extremely important to continuously monitor changes in the state of the digestion tank in order to achieve and maintain good anaerobic sludge digestion. In the case of a failure, it takes a long time to recover, so it is the most important task in operation management to quickly detect that the condition in the tank is abnormal. In addition, when aiming for optimal operation control that also takes economy into consideration, the continuous operation of the target digestion tank should be monitored at all times by continuous monitoring, and the conditions within the tank should be used to determine the optimal operation range. It is necessary to control while monitoring so as not to deviate.

Conventionally known digestive tank operation management indices include the following four items.

(1) Management of pH (2) Management of organic acid concentration (3) Management of alkalinity (4) Management of methane gas generation rate (gas generation rate + gas composition) The management of pH in (1) above will be described. In general, in the case of a digestion tank that is operating well, the pH in the tank is maintained near neutrality. However, when an abnormality occurs in the digestion tank, it appears first as a pH abnormality, that is, a phenomenon in which the pH deviates from around neutrality. For example, when the activity of the methanogen in the second stage is weakened, the organic acid generated in the first stage of anaerobic digestion is accumulated without being decomposed, and a pH drop (acidity) phenomenon occurs. If the ammonia production in the second stage is excessive compared to the acid production in the first stage,
A rising phenomenon occurs.

Regarding the management of the organic acid concentration in the above (2), this organic acid is a substrate for methanogens, but when the organic acid concentration increases or the pH decreases, the organic acid is a weak acid. As a result, non-ionized organic acids that are not ionized increase. This non-ionized organic acid is known to become an inhibitory toxic substance for methanogens above a certain concentration, and the rancidity caused by organic matter overload in the digestion tank is caused by the non-ionized organic acid. It is the result of an inhibitory toxic effect. The non-ionized organic acid concentration can be determined from the organic acid concentration as a function of pH.

Next, regarding the alkalinity management of the above (3), sludge in the digestion tank has a high pH buffering ability, and therefore, an abnormality in the digestion tank is remarkably manifested as a pH abnormality.
In many cases, it is in a terminal stage where trouble has progressed considerably. However, a precursor of pH abnormality in the digester can be captured as a change in pH buffering capacity. The alkalinity is an index indicating the buffering capacity of this pH. The alkalinity of anaerobic sludge is mainly due to soluble inorganic carbon.
Soluble inorganic carbon, with the change of ionic charge in the solution,
By changing the form of carbon dioxide, bicarbonate, and carbonic acid, the change in solution pH is buffered. The molar ratio of these three forms of inorganic carbon can be determined by theoretical calculations as a function of pH from the soluble inorganic carbon concentration as the sum of the three forms.

[0010] Further, regarding the management of the methane gas generation rate in the above (4), an abnormality in the activity due to an environmental change of the methane-producing bacterium or an influx of inhibitory toxic substances (sulfides and heavy metals) appears as a decrease in the methane gas generation rate. The generation rate of methane gas is obtained by multiplying the gas generation rate by the partial pressure (concentration) of methane gas in the gas. However, the methane gas partial pressure can also be calculated from the above-mentioned (3) soluble inorganic carbonic acid concentration without directly measuring the methane gas concentration. That is, the methane gas partial pressure can be determined by subtracting the carbon dioxide gas partial pressure from the one partial pressure since most of the digested gas is composed of methane gas and carbon dioxide gas.

Further, the partial pressure of carbon dioxide gas in the digested gas is
From Henry's law (vapor-liquid equilibrium), it can be obtained by theoretical calculation from the concentration of soluble carbon dioxide. The soluble carbon dioxide concentration is determined by theoretical calculation from the soluble inorganic carbon concentration and the pH in the above (3). Therefore, if the generated gas speed, the dissolved inorganic carbon concentration and the pH are known, the methane gas generation speed can be estimated by calculation.

In addition to the above-mentioned items, non-ionized ammonia concentration,
The total phosphorus concentration and total sulfide concentration can be mentioned. That is, ammonia production in the second stage of anaerobic digestion is indispensable for maintaining a neutral pH in the tank when this is appropriate, but when ammonia production is excessive,
This causes an increase in the pH in the tank, creating an unfavorable environment for methane production. Higher p
It has been reported that the accumulation of H and excessive ammonia results in an increase in the concentration of non-ionized free ammonia, which at high concentrations has an inhibitory toxic effect on methanogens. The free ammonia concentration can be determined from the ammonia concentration and the pH.

Further, the digested sludge contains phosphoric acid and hydrogen sulfide in an amount of about several mg / l to several hundreds mg / l. It is necessary to monitor the items of total sulfide concentration.

Other monitoring items include the management of nutrient balance (C / N ratio, trace amount of heavy metal) and temperature in the tank. However, the nutrient balance need not be monitored frequently and continuously unless the composition of the input sludge changes suddenly, and the temperature in the tank is an item that has been well monitored and controlled conventionally.

(With respect to the above technology, for example, as described in Colin, F., “Development of
an automatic equipment f
or the study of acid-base
equilibriafor the control
of auaerobicity digest, "
And French Patent, F. See Colin, 0056117. )

[0016]

In the monitoring means for various digestion tanks described above, it is generally necessary to carry out a solid-liquid separation step of digested sludge as a pretreatment at the time of measurement. As a device using a centrifugal separation method, a method using a supernatant obtained using a sedimentation tank, or once storing digested sludge in a mud receiving tank, and then adding a flocculant in a flocculation tank A method of sedimenting sludge, and a method of using a filtration means using a filter paper in combination with each of the above means have been performed.

However, in each of these methods, the removal rate of the solid component in the sample, for example, the ss component, is low, and such solid component acts as an interfering substance, thereby lowering the measurement accuracy. However, there is a problem in that there is a problem that the measurement device is difficult to automate.

Further, in each of the conventional methods, there is a problem that it is very difficult to continuously monitor all items to be monitored. For example, the following devices are used as existing devices for measuring the above continuous monitor items. pH: pH electrode Organic acid: Liquid chromatography Inorganic carbonic acid: Alkali by IC meter or titration Degree measurement Methane gas ・ ・ ・ ・ ・ ・ Gas chromatograph Gas generation rate ・ ・ ・ ・ ・ ・ Gas flow meter Ammonia ・ ・ ・ ・ ・ ・ Ammonia electrode Conventionally, all analytical equipment necessary for such each analysis is secured. In addition, many instruments require pretreatment and special instruments for samples are required, so that few instruments can be measured continuously. In addition, there is the complexity that a calibration curve must be created for each device during measurement, and the number of operators performing maintenance and inspection must be increased as the number of measurement devices increases.

Therefore, the present invention solves such a problem that occurs when monitoring the digestion tank in the related art, increases the removal rate of solid components during the solid-liquid separation process before measurement, and increases the number of measurements. Eliminates the need to use equipment
It is an object of the present invention to provide a method for monitoring an anaerobic digestion tank that can automate all measurement steps.

[0020]

In order to achieve the above object, the present invention provides a filtrate tank in which digested sludge is stored, a digested sludge in the filtrate tank sampled and introduced, and a pH meter. Equipped with an acid titration tank and an alkali titration tank provided, and a titration mechanism for dispensing a reagent in an amount corresponding to the value determined by the control unit into the acid titration tank and the alkali titration tank by a dispenser. In an apparatus that continuously monitors the digestion state of sludge based on the acid-alkali equilibrium theory based on the sample solution pH value and the titration amount of the reagent, the apparatus may be configured such that the filtrate tank and the acid and alkali titration tank are connected. In addition, an anaerobic digestion tank monitoring device provided with an ultrafiltration device for performing solid-liquid separation of digested sludge stored in the filtrate tank.

[0021]

[Action] According to the monitoring device for such an anaerobic digestion tank,
A certain amount of digested sludge stored in the filtrate tank is subjected to solid-liquid separation by an ultrafiltration device, and then sampled and sent to an acid and alkali titration tank. Titration reagents are sequentially added to the acid titration tank and the alkali titration tank based on the action of a titration mechanism using a dispenser or the like, and titration is performed until a predetermined pH value is obtained. Is sent to the control unit to perform a process based on the acid-alkali equilibrium theory, and the total organic acid concentration, ammonia concentration, total inorganic carbon concentration, and the like are continuously monitored.

During the above operation, solid-liquid separation of digested sludge is performed by an ultrafiltration device, so that solid components as a substance that interferes with the measurement hardly remain in the sample, and the measurement accuracy as a monitor device is improved. Can be done. In addition, since the configuration of the solid-liquid separation device itself is simplified, the measurement device can be automated.

[0023]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, an embodiment of a monitoring device for an anaerobic digestion tank according to the present invention will be described in detail.

FIG. 1 is a schematic view for explaining an embodiment of the present invention. In FIG. 1, reference numeral 1 denotes a filtrate tank, into which digested sludge 20 flows from a digestion tank (not shown). Is stored. 2 is an ultrafiltration apparatus, 3 is an acid titration tank, and 4 is an alkali titration tank. The acid titration tank 3 and the alkali titration tank 4 are provided with pH meters 5, 5 and thermometers 6, 6, respectively. .

Reference numerals 7a and 7b denote dispensers for adding a titration reagent to each of the acid titration tank 3 and the alkali titration tank 4, reference numeral 8 denotes a sequence controller, and reference numeral 9 denotes a personal computer which is controlled by the sequence controller 8 and the personal computer 9. The unit 10 is configured. 11 is a pump for sampling digested sludge, and 12 is a two-way valve.

The basic operation of this embodiment will be described below. First, a certain amount (for example, 100 ml) of digested sludge 20 sent into the filtrate tank 1 from a digestion tank (not shown) is subjected to solid-liquid separation by the ultrafiltration device 2 based on the action of the sampling pump 11, and then a two-way valve is provided. It is sent to the acid titration tank 3 and the alkali titration tank 4 via 12.

Next, the acid titration tank 3 and the alkali titration tank 4
HCl and NaOH, which are titration reagents, are dispensed using the dispensers 7a and 7b and the electric burette, for example, with a pitch amount of 0.05-.
0.10 ml sequentially, pH 2.0 and 1 respectively.
The titration is performed until the value reaches 0.0, and the titration amount and the pH values measured by the pH meters 5 and 5 are combined with the sequence controller 8 and the personal computer 9 constituting the control unit 10.
Then, a treatment based on the acid-alkali equilibrium theory described later is performed, and in addition to the total organic acid concentration (A), the ammonia concentration (N), the total inorganic carbon concentration (T), and the like are monitored. The processing can be performed only by the personal computer 9 without using the sequence controller 8.
Further, the measured data is corrected by the liquid temperature value measured by the thermometers 6,6.

The major feature of the present embodiment is that the ultrafiltration apparatus 2 is employed as a solid-liquid separating means for the digested sludge 20 stored in the filtrate tank 1. This ultrafiltration device (Ultrafilter) has the function of filtering even colloidal particles. Generally, an appropriate semipermeable membrane is prepared into an ultrafiltration membrane, which is formed into a bag or held on a support. And a structure in which the colloid particles and the solvent are separated by pressurization or decompression. The size of the mesh of the above-mentioned filtration membrane can be obtained roughly from the difficulty of filtering proteins and dyes.

When the solid-liquid separation effect of the ultrafiltration device 2 is compared with a conventionally used centrifugal separation device or a solid-liquid separation method using filter paper, the conventional centrifugal separation device remains in the filtrate. Ss component as a solid component (Suspended so
lid, suspended matter in water) is several hundred to several thousand mg / l,
Further, when filter paper is used, the ss component is several tens to 1,000 mg /
On the other hand, when the ultrafiltration device 2 is used, the remaining ss component has a value that can hardly be detected. Therefore, when measuring each item to be monitored, the ss component does not act as an interfering substance,
Measurement accuracy can be improved. In addition, since the configuration of the solid-liquid separation device itself is simplified, there is an advantage that the measurement device can be automated.

The monitor device employed in the present invention is a single monitor device having the following five items: (1) total organic acid concentration (non-ionized organic acid concentration), and (2) total inorganic carbon concentration (alkaliness + Gas composition), (3) total ammonia concentration (free ammonia concentration), (4) total phosphorus concentration (phosphoric acid), and (5) total sulfide concentration (hydrogen sulfide). Specifically, all of the above items to be continuously monitored can be measured from a pH-titration data pair as a digester monitor.

Next, an acid-alkali equilibrium theory which is a basic principle of the present invention will be described. That is, in the present embodiment, the concentration of the 17 or less substances at the maximum or less is determined from the acid-alkali titration curve for the sludge in the digestion tank.

[0032] ^{[H +], [OH -} ], [CH 3 COO -], [CH 3 COO
H], [H ₂ CO ₃ ], [HCO ₃ ⁻ ], [CO ₃ ^2- ], pCO ₂ , [NH ₄ ⁺ ],
_{[NH 4 OH], [PO} 4 3-], [HPO 4 2-], [H 2 PO 4 -] [H 3 P
^{_{O 4], [S 2-]}} , [HS -], [ organic acids H ₂ S] digestion tank are acetic, propionic acid, butyric acid, etc. These organic acids respectively 1.76 × 10 ^-5 , 1.34 × 10
^-5 and 1.54 × 10 ^-5 have relatively similar ionization constants. Therefore, when these organic acids are collectively considered as acetic acid in a lump, it can be assumed that the ionization constant is 1.5 × 10 ⁻⁵ .

Then, the following chemical equilibrium relational expression is established between the above substance concentrations.

[0034]

(Equation 1)

[0035]

(Equation 2)

[0036]

(Equation 3)

[0037]

(Equation 4)

[0038]

(Equation 5)

[0039]

(Equation 6)

The expressions (1) to (6) except the expression (3) are as follows:
The following equation can be modified according to the total organic acid concentration (A), total ammonia concentration (N), total inorganic carbon concentration (T), and hydrogen ion concentration.

[0041]

(Equation 7)

[0042]

(Equation 8)

[0043]

(Equation 9)

[0044]

(Equation 10)

[0045]

[Equation 11]

Further, in the acid-alkali equilibrium, a charge balance equation is established. This is the rule that the sum of the charges of the positive ions is equal to the sum of the charges of the negative ions. This can be expressed by equation (12).

[0047]

(Equation 12)

Where [Z] is the sum of the net cation concentrations. In the actual sample, the above organic acids, ammonia,
In addition to ions such as inorganic carbon, several mg of phosphoric acid and hydrogen sulfide
/ L to several hundred mg / l. However, metals such as iron, zinc, copper, lead, and cadmium react with dissolved sulfides to form insoluble metal sulfides. In the case of sulfides, only a part is involved in the above-mentioned balance equation.

[0049] Therefore _{^{[H +], [NH 4}} +], [HCO 3 -], [CO 3
^{_{2-], [CH 3 COO -}} ], [OH -] plus the sum of the charges of all ions other than the ion - constant (sum of cationic charge negative sum of ionic charge) as the cation concentration of net [Z] Can be treated.

[NH ₄ ⁺ ], [HC
The concentrations of O ₃ ⁻ ], [CO ₃ ²⁻ ], [CH ₃ COO ⁻ ], and [OH ⁻ ] are, as described above, the total organic acid concentration (A), the total ammonia concentration (N), and the total inorganic concentration. It can be expressed by equation (13) by the carbon concentration (T) and the hydrogen ion concentration.

[0051]

(Equation 13)

Since the hydrogen ion concentration can be easily measured with a pH meter, the unknowns in the charge balance equation are the total organic acid concentration (A), total ammonia concentration (N), and total inorganic carbon concentration (T). There are four items of net cation concentration (Z). Here, from the relationship between the unknowns of the simultaneous equations and the number of equations, four equations are required to obtain four unknowns.

One is obtained by measuring the pH of an untitrated sample. The other three can be obtained by achieving three different pH values by acid or alkali titration. However, in this case, the net cation concentration (Z) is modified by the acid or alkali titer.

For example, when acid (HCl) is injected at X1 mol / L and the pH becomes pH 1,

[0055]

[Equation 14]

Is as follows. Therefore, as long as the pH of the sample that has not been titrated and the titration when three different pH values are achieved by titration are known, four simultaneous equations are established, and by solving this simultaneous equation, four unknowns are calculated. The organic acid concentration (A), total ammonia concentration (N), total inorganic carbon concentration (T) and net cation concentration (Z) can be determined. However, in practice, the measurement error of the instrument is naturally included in the pH value and the titration amount, so that it is necessary to statistically obtain four unknowns from four or more data (all titration point data) by multiple regression analysis. .

By obtaining the above four unknowns, other ion concentrations can be calculated using the equations (7) to (11). In particular, it is derived based on an acid-alkali equilibrium theory (chemical equilibrium equation, charge balance equation) (Equation 1
4) From hydrogen ion concentration (pH), total inorganic carbon concentration (T), total ammonia concentration (N), total organic acid concentration (A)
Relationship can be determined.

Therefore, first, an acid or an alkali is automatically injected into the sample by a predetermined amount, and each pH titer (X mole) is recorded and stored, and the values are applied to the above (Equation 14) to obtain four unknowns T. , N, A and Z. A multiple regression analysis method is employed as a method for calculating these four unknowns.

That is, (Equation 14) can be transformed into the following multiple regression equation (Equation 15). y = Z + b1 · N + b2 · T + b3 · A (15) Here, y = X1− [H ⁺ ] + Ke / [H ⁺ ] ·· (16) b1 = 1 / (1 + Kn / [H ⁺ ]) (17) b2 = -1 / (1+ [H ⁺ ] / K1 + K2 / [H ⁺ ]) -2 / (1+ [H ⁺ ] / K2 + [H ⁺ ] ² / K1 / K2) · (18) b3 = −1 / (1+ [H ⁺ ] / Ka) (19) On the other hand, sample The phosphoric acid contained therein dissociates into the following three steps.

[0060] ^{_{H 3 PO 4 ← → H +}} + H 2 PO 4 - · ························· (20) H 2 PO 4 - ← → H ⁺ + HPO ₄ ^2-・ ・ ・ ・ ・ ・ ・ ・ ・ ・ (21) HPO ₄ ^2- ← → H ⁺ + PO ₄ ^3-・································································································· (22) Hydrogen sulfide contained in the sample dissociates in the following two stages.

[0061] ^{_{H 2 S ← → H + +}} HS - · · · · · · · · · ························· (23) HS ^- ← → H ⁺ + S ^2-・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ ・ (24) The total phosphorus concentration (P) and the total sulfide concentration (S) are determined as follows.

Total phosphorus concentration (P) = [H ₃ PO ₄ ] + [H ₂ PO ₄ ⁻ ] + [HPO ₄ ²⁻ ] + [PO ₄ ³⁻ ] ··· (25) K3 = ([ H +] [H 2 PO 4 -]) / [H 3 PO 4] K4 = ([H +] [HPO 4 2-]) / [H 2 PO 4 2- ^{] K5 = ([H +]} [PO 4 3-]) / [HPO 4 2-] [H 2 PO 4 -] = P / ([H +] / K3 + K4 / [H +] +1) [HPO 4 2 ^{-] = P / ([H} +] 2 / K3 / K4 + [H +] / K4 + 1) [PO 4 3-] = P / ([H +] 3 / K3 / K4 / K5 + [H +] 2 / K4 / ^{K5 + [H +] / K5} ) total sulphide concentration ^{(S) = [HS -]} + [H 2 S] + [S 2-] ··········· (26) K6 = ( ^{[H +] [HS -]} ) / [H 2 S] K7 = ([H +] [S 2-]) / [HS -] [HS ^- ] = S / (K7 [H ⁺ ] + [H ⁺ ] / K6 + 1) [ ^S2- ] = S / ([H ⁺ ] ² / K6 / K7 + [H ⁺ ] / K7 + 1) The above (25) ( Considering the total phosphorus concentration (P) and the total sulfide concentration (S) in the expression (26), the expression (15) becomes as follows.

Y = Z + b1 · N + b2 · T + b3 · A + b4 · P + b5 · S (27) where y = X1− [H ⁺ ] + Ke / [H ⁺ ]... (28) b1 = 1 / (1 + Kn / [H ⁺ ]) ... ... (29) b2 = -1 / (1+ [H ⁺ ] / K1 + K2 / [H ⁺ ]) -2 / (1+ [H ⁺ ] / K2 + [H ⁺ ] ² / K1 / K2) (30) b3 = -1 / (1+ [H ⁺ ] / Ka) (31) b4 = -1 / (1+ [H ⁺ ] / K3 + K4 / [H ⁺ ]) -2 / (1+ [H ⁺ ] / K4 + [H ⁺ ] ² / K3 / K4) -3 / ([H ⁺ ] / K5 + [H ⁺ ] ^{2 / K4 / K5 + [H} +] 3 / K3 / K4 / K ) ····················· (32) b5 = -1 / (1+ [H +] / K6 + K7 / [H +]) -2 / (1+ [ (H ⁺ ] / K7 + [H ⁺ ] ² / K6 / K7) (33) From the titration amounts X1 and pH at all observation points (titration points) obtained by acid-alkali titration, y, b1, b2, b3 , B
By calculating 4, b5 and using the multiple regression analysis method, the values of T, N, A, Z, P and S that are statistically most suitable for all the titration data can be calculated.

In this embodiment, four or more (pH-titration)
A method of statistically determining unknowns from multiple data pairs by multiple regression analysis was adopted.

In order for the multiple regression analysis method to work effectively for its application object, the error (ε) included in the multiple regression equation has four assumptions: (1) unbiasedness, (2) equal variance , (3)
Uncorrelation, (4) normality must be satisfied. When these (1) to (4) are summarized, "the errors follow a normal distribution of mean 0 and variance (σ ² ) independently of each other".

However, in reality, these preconditions are usually not satisfied, and if the variance of the error (ε) is not uniform, the accuracy of estimation by the ordinary least squares method cannot be guaranteed. .

Therefore, there is an error analysis method as a method for examining whether or not the above error satisfies the precondition. An example in which this error analysis method is applied to the present embodiment will be described below. FIG. 6 is a pH-titration curve when the filtrate obtained by centrifuging the digester sludge and then filtering the supernatant is used as a measurement sample and alkali NaOH or acid HCl is titrated to the measurement sample. (〇) in FIG. 6 indicates an actually measured value, and a solid line indicates a curve calculated using the acid-alkali equilibrium theory.

Accordingly, by obtaining the magnitude of the difference (residual difference) between the actually measured value and the calculated value and the appearance frequency, the distribution diagram shown in the histogram of FIG. 7 is obtained. From FIG. 7, it can be seen that the residual is not a normal distribution, and the distribution may have two peaks depending on the sample, so that sufficient accuracy cannot be obtained only by applying the multiple regression analysis method.

Therefore, the present embodiment employs a method of determining the unknowns Z, T, N, A, P, and S based on the flowchart shown in FIG. That is, first in step 101,
The measured data such as the relationship between the pH and the titer and the water temperature are read. Then, in step 102, a plurality of water quality items Z, T, and Z are applied by applying a multiple regression analysis method based on the above (Equation 27).
Calculate N, A, P, S. However, since the multiple regression analysis result is used as the initial value of the optimization process, it is sufficient that the approximate value is obtained. In the multiple regression analysis, if the number of variables is increased more than necessary, the overall accuracy will decrease. That there is,
Since the concentration of total phosphorus and sulfide is lower than the other items (total organic acid, total inorganic carbon, and total ammonia concentration), multiple regression analysis can be performed with only 4 items of Z, T, N, and A. it can. In this case, equation (15) may be used as the multiple regression equation. When all phosphorus and sulfides are included, the formula (27)
Is used.

Next, initial values Z ₀ , T ₀ , N ₀ , A ₀ , P ₀ , for optimizing the water quality data such as Z, T, N, A, P, and S read in step 103. The setting of S ₀ is performed, and the optimization processing is performed in step 104. Items to be optimized are, for example, T, N, A, Z, T, N,
A, Z, T, N, A, P, Z, T, N, A, S,
Combinations of Z, T, N, A, S, P, etc. can be considered, but the initial value of the optimization process needs to be changed depending on which item is selected. For example, when it is desired to optimize the above Z, T, N, and A, the four items of the result of the multiple regression analysis (set as four items according to the optimization process) are initialized to the initial values (Z ₀ ,
T ₀ , N ₀ , A ₀ ).

In general, multiple regression analysis is used as an initial value for the optimization process, but an arbitrary value within the range of the upper and lower limit set values of each of Z, T, N, A, P, and S is set to the initial value. It is also possible to use

Various methods have been proposed as optimization techniques. In this embodiment, the simplex method is used. The simplex method is one of a nonlinear programming method and a direct search method. Specifically, assuming that the number of parameters to be optimized is NPA%, NPA% + 1
The error evaluation is directly performed using a combination of these parameters. In the case of a digester monitor, the above parameters are Z, T,
N, A, P, and S. Then, using this result,
In step 105, an evaluation function is calculated, and a search for a new parameter that reduces the evaluation error is performed. After that, the new combination is replaced with the combination that previously indicated the maximum error evaluation, and convergence check is performed in step 106.

By repeating the above steps 104, 105, and 106, when the combination of NPA% + 1 parameters is converged while moving to the optimum point, and the difference in the evaluation error between the combination of NPA% + 1 parameters becomes sufficiently small. And the optimization process is terminated.

In the present embodiment, the initial value of the optimization process is arbitrarily set within the range of the unknown number of T, N, A, P, and S items to be monitored.

In the following, an artificial sample containing T, N, A, P, and S was prepared to prepare a data pair of pH-titration based on the present titration method. The results of comparison with the sample preparation concentrations are shown in FIGS. FIG.
Fig. 4 shows the results when only multiple regression analysis was performed, and Fig. 4 shows the results when multiple regression analysis and optimization processing were combined. The dashed lines in FIGS. 3 and 4 show the ideal relationship (theoretical calculation value) between the titration method and the artificial sample preparation concentration. As is clear from FIG. 4, it is understood that the combination of the optimization processing with the multiple regression analysis significantly improves the measurement accuracy as compared with the case of FIG. 3 in which only the multiple regression analysis is performed.

The five graphs shown in FIG. 5 show that the total organic acid concentration (A) is 10 mg / l and 100 mg / l
1, 200 mg / l, 400 mg / l, 500 mg / l
3 shows the relationship between the pH and the titer in the case of. According to FIG. 5, it can be seen that there is a difference in the variation range of the pH with respect to the difference in the total organic acid concentration (A) depending on the pH range. In this example, the difference in the total organic acid concentration (A) is from pH 4 to pH 6 and pH 7 to
It can be seen that it appears particularly well in the pH range of 9. Therefore, in order to improve the calculation accuracy of the total organic acid concentration, it is necessary to pay attention so that the actually measured value and the calculated value of the pH-titration in the above-mentioned pH range coincide with each other.

In this embodiment, by using an evaluation function in which a specific pH range is weighted in advance, when the characteristic pH range is calculated, the weighting coefficient is made larger than the other pH ranges to monitor T, A means for calculating an evaluation function using N, A, P, and S as parameters is employed. Thereby, the measurement accuracy of the total organic acid concentration can be further improved.

Further, in the multiple regression analysis, the unknowns Z,
Since the concentration ranges of T, N, A, P, and S cannot be specified, negative values that are physically meaningless may be output as calculated values. However, optimization processing is performed in addition to multiple regression analysis. By carrying out (1), it becomes possible to put constraint conditions such as upper and lower limits on each unknown, and there is an effect that the stability of the calculation result is enhanced.

[0079]

As described above in detail, according to the anaerobic digester monitoring apparatus of the present invention, a certain amount of digested sludge stored in the filtrate tank is separated into solid and liquid by the ultrafiltration device. Since the sample is sampled and sent to an acid and alkali titration tank, almost no solid component as a measurement interfering substance remains in the measurement sample, and the measurement accuracy as a monitor device can be improved. In addition, since the configuration of the solid-liquid separation device itself is simplified, the measurement device can be automated.

Then, the digestion state of the sludge is continuously determined from the titration by the automatic dispenser based on the acid-alkali titration algorithm for the reagent corresponding to the value obtained by the control unit, and the pH value of the sampling solution and the titration amount of the reagent. By using a relatively simplified device, the total inorganic carbon concentration, total ammonia concentration, and total organic acid concentration, which are the control indices for continuously monitoring the water quality in the digestion tank, can be monitored by relatively simplified equipment. The measurement can be performed with high accuracy and automatically in an unmanned state, and the process can be fully automated in combination with the simplification of the configuration of the solid-liquid separation device.

[Brief description of the drawings]

FIG. 1 is a schematic diagram showing an embodiment of a monitoring device for an anaerobic digestion tank according to the present invention.

FIG. 2 is a chart showing an example of a monitoring method using the apparatus of the present invention.

FIG. 3 is a graph comparing a result obtained when only multiple regression analysis based on the present invention is performed with a theoretical calculation value.

FIG. 4 is a graph comparing a result obtained when a multiple regression analysis and an optimization process based on the present invention are combined with a theoretical calculation value.

FIG. 5 is a graph showing a comparison between measured and calculated values of pH-titration for each total organic acid concentration.

FIG. 6: pH when alkali or acid is titrated to a measurement sample
A graph showing a comparison between a measured value of a titration curve (marked with ○) and a calculated value (solid line) using the acid-alkali equilibrium theory.

FIG. 7 is a histogram showing the frequency of occurrence of a residual between the actually measured value and the calculated value in FIG. 6;

──────────────────────────────────────────────────続 き Continued on front page (58) Field surveyed (Int.Cl. ⁷ , DB name) C02F 11 / 04,3 / 28

Claims (1)

(57) [Claims] 1. A filtrate tank in which digested sludge is stored, an acid titration tank and an alkali titration tank in which digested sludge in the filtrate tank is sampled and introduced, and a pH meter is provided, respectively, and a control unit. A titration mechanism for dispensing the reagent in an amount corresponding to the determined value to the acid titration tank and the alkali titration tank by a dispenser, based on a solution pH value of the sampling and a titration amount of the reagent, An apparatus for continuously monitoring the digestion state of sludge from an acid-alkali equilibrium theory, wherein a solid-liquid separation of digested sludge stored in the filtrate tank is performed between the filtrate tank and the acid and alkali titration tank. An anaerobic digester monitoring device, comprising an ultrafiltration device for performing the process.