CN201191473Y - A/O process segmental influent deep nitric removing fuzzy control teaching apparatus - Google Patents
A/O process segmental influent deep nitric removing fuzzy control teaching apparatus Download PDFInfo
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- CN201191473Y CN201191473Y CNU2007202009928U CN200720200992U CN201191473Y CN 201191473 Y CN201191473 Y CN 201191473Y CN U2007202009928 U CNU2007202009928 U CN U2007202009928U CN 200720200992 U CN200720200992 U CN 200720200992U CN 201191473 Y CN201191473 Y CN 201191473Y
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Abstract
A fuzzy control teaching appliance of A/O step-feed advanced nitrogen removal process used for a sewage treatment system is formed by a raw water container, a water inlet pipe, a control valve, a water feeding pump, a reaction tank and a water outlet pipe which are sequentially connected. The reaction tank is composed of four sections, each section is provided with an anoxic zone and an aerobic zone. A COD sensor and a TKN sensor are internally disposed in the water inlet pipe, each aerobic zone is internally equipped with a DO sensor, acquired COD and TKN density signals are input in an analog-digital converter respectively via a COD determinator and a TNK determinator to be converted into C/N input variable digital signals, a fuzzy control host obtains a influent flow distribution coefficient in accordance with the fuzzy control regulation, and volumes of each aerobic zone and each section to be output variables, thereby respectively controlling the aeration amount of each aerator, the water inflow quantity of each water pump, and the rotation speed of each stirrer. The utility model resolves the nonlinear accurate control and teaching demonstration problems.
Description
(1) technical field
The utility model relates to the control instructional device of a kind of bio-denitrifying sewage system.
(2) background technology
Since entering the seventies in 20th century, along with the body eutrophication problem is day by day appeared suddenly, sewage denitrification and dephosphorization in water pollution control by extensive concern.With the control eutrophication is that the nitrogen phosphorus of purpose removes the main direction of studying that technology has become various countries at present.The sewage drainage standard of the up-to-date promulgation of China (GB18918-2002) requires the content of all pollutant discharging unit's water outlet nitrogen phosphorus to be respectively total phosphorus less than 1mg/L by the grade of admitting water body, and ammonia nitrogen is less than 5mg/L, and total nitrogen is less than 15mg/L (primary standard).Although biological phosphate-eliminating has stability scarcely, adopt traditional technology to carry out biological phosphate-eliminating and assist can guaranteeing still that with chemical dephosphorization water outlet TP concentration remains on below the trace concentration].But the nitrogen in the sewage can only adopt economic, the removal effectively of biological method ability.
In many countries, particularly Chinese, nearly 80% municipal sewage plant adopts Prepositive denitrification (A/O) technology to carry out biological denitrificaion.Sewage directly enters the oxygen-starved area and preferentially carries out anti-nitration reaction in Prepositive denitrification technology, improved nitrogen removal rate, and most of organism is utilized by anti-nitration reaction in the oxygen-starved area, has dwindled the Chi Ronghe residence time of aerobic zone.But for guaranteeing that the abundant denitrification of nitrate nitrogen to improve nitrogen removal rate, often needs nitrification liquid backflow largely, be generally 2-3 times of inflow in Prepositive denitrification technology, this can consume a large amount of energy undoubtedly.And because the formation of Prepositive denitrification technology, water outlet nitrate nitrogen concentration is identical with nitrate nitrogen concentration in the backflow nitrification liquid, and this has just determined that the nitrogen removal rate of Prepositive denitrification technology can be very not high.Other biological denitrification phosphorous removal technique, for example there is above-mentioned shortcoming too in technology such as AAO, UCT.
A/O technique subsection water-feeding deep denitrogenation system is external in recent years biological denitrification process newly developed.Compare with traditional A/O technology, adopt segmental influent to have following advantage: (1) organic substrates is long along the pond evenly to distribute, the gap between oxygen supply speed and the oxygen consumption rate had both been dwindled in load balancing to a certain extent, can give full play to the degradation function of active sludge microorganism again; (2) long segmentation enters and mud is back to head end sewage along the pond, and the sludge age of system is than the plug-flow system head of same volume; (3) nitric efficiency height; (4) nitrification liquid directly enters the oxygen-starved area of next section from aerobic zone, has saved the interior circulation step of traditional biological denitrification process; (5) water outlet of anti-nitration reaction directly enters the nitration reaction pond, has replenished the requirement of nitration reaction to basicity.Yet because the segmentation of the formation of reactor and sewage is introduced, the optimal design of A/O technique subsection water-feeding deep denitrogenation system and operation are very tasks of difficulty.The volumetric ratio of oxygen-starved area and aerobic zone, every intersegmental volumetric ratio and the distribution of flow of inlet water are the important parameters of technological design and operation in each section.Sewage characteristic, the C/N of particularly intaking seriously affects the design and the operation of technology than (carbon-nitrogen ratio).Therefore the optimal control operation method of seeking technology is the important prerequisite that realizes the wide application of A/O technique subsection water-feeding system.
Sewage biological treatment system has been said obvious characteristics from the angle of control: 1. time variation.Flow of inlet water and concentration are not constant but present irregular variation, particularly industrial waste water in time.2. non-linear.Active sludge biological is zero-order reaction when being reflected at abundances such as organic substrates, nutrients, oxygen, and organic substrates is degraded with maximum rate; Along with the concentration of substrate that carries out that reacts reduces gradually, biological respinse is subjected to the restriction of substrate and presents first order reaction.3. complicacy.Biologic process for treating sewage has numerous influence factors, as MLSS, DO, sludge age, HRT, sludge loading, F/M, temperature, pH value etc., carry out the influence that denitrogenation dephosphorizing also can be subjected to recycle ratio, return sludge ratio, N/MLSS rate of load condensate, P/MLSS rate of load condensate etc. as need, and be subjected to the influence of a plurality of factors sometimes simultaneously, present strong complicacy.4. uncertain.To the material of the toxic effect of active sludge microorganism, as heavy metal, prussiate etc., can when its concentration surpasses critical concentration, can suppress the propagation of microorganism with the system of entering, even make the microorganism extinction, cause the paralysis of sewage disposal system.
Because the characteristic of sewage biological treatment system makes traditional control theory seem very impracticable, for intelligent control technology provides wide research space, gives full play to the function of its self study, self-adaptation and self-organization.Based Intelligent Control has many branches, and as ANN (Artificial Neural Network) Control, fuzzy control, expert system, chaos controlling, can open up control etc., wherein fuzzy control technology is typical intelligence control method, also is to use more control method.Fuzzy control is fuzzy logic and combining of controlling automatically, be the reasoning of anthropomorphic dummy on the function and a kind of practical control method of decision process, utilize priori or expertise as control law, effectively unknown the or coarse control problem of transaction module.It need not modeling, is a kind of nonlinear Control, has provided sufficient theoretical foundation with omnipotent approximation theory, and promptly fuzzy logic controller is omnipotent, can finish any nonlinear Control task.But the relevant report and the teaching demonstration device that still do not have both at home and abroad up to now, any fuzzy control about the A/O technique subsection water-feeding deep denitrogenation.Its reason is many-sided, comprises that technology is not optimized stable operation as yet, controlled variable is difficult for determining or the like.
(3) utility model content
The purpose of this utility model provides a kind of fuzzy control instructional device of A/O technique subsection water-feeding deep denitrogenation, solve the non-linear accurate control of teaching demonstration A/O segmental influent bio-denitrifying sewage system and optimize the technical matters of moving.
For achieving the above object, the utility model adopts following technical scheme:
The fuzzy control instructional device of this A/O technique subsection water-feeding deep denitrogenation, be used for A/O biological denitrificaion sewage disposal system, its A/O biological denitrificaion sewage disposal system is linked in sequence and is formed by raw water vessel 33, water inlet pipe 28, by-pass valve control 34, intake pump 2, reaction tank, pipe core 35, second pond 29, rising pipe 30; Wherein reaction tank is formed by four sections, and every section has an oxygen-starved area 31 and an aerobic zone 32, all is equipped with stirrer 4 in each oxygen-starved area, and every section water inlet pipe all connects an intake pump 2, and each intake pump is connected with a by-pass valve control 34; Be equipped with the aerator 3 that is connected with air compressor in each aerobic zone, be communicated with excess sludge pipe 36 and mud return line 37 at the bottom of the pond of second pond, mud return line is communicated with first oxygen-starved area through return sludge pump 38, non-return valve 39, it is characterized in that:
Raw water vessel 33 at above-mentioned reaction tank is built-in with a chemical oxygen demand (COD) sensor, it is COD sensor 5, COD sensor 5 connects COD analyzer 8 through lead, and the signal output port of COD analyzer 8 is connected with COD signal input interface 13 on the fuzzy controller main frame 11;
In the raw water vessel 33 of above-mentioned reaction tank, also be equipped with a kjeldahl nitrogen concentration sensor, be TKN sensor 6, TKN sensor 6 connects the signal output port of TKN analyzer 9, TKN analyzer 9 through lead and is connected with TKN signal input interface 14 on the fuzzy controller main frame 11;
Each is built-in with the dissolved oxygen concentration sensor at the aerobic zone of above-mentioned reaction tank, i.e. DO sensor, and each DO sensor connects DO analyzer 10 through lead, and the signal output port of DO analyzer 10 is connected with DO signal input interface 15 on the fuzzy controller main frame 11;
The signal output interface 12 of above-mentioned fuzzy controller main frame is connected with the signal input 21 of topworks, and respectively to aeration relay 26, intake pump regulator 25, agitator motor relay 27 input control signals of control executing mechanism inside; The aeration rate of aeration relay 26 each aerator of control, the inflow of intake pump regulator 25 each intake pump of control, the rotating speed of agitator motor relay 27 each stirrer of control.
Comprise in the above-mentioned fuzzy controller main frame:
The storer of a, storage execute program, fuzzy control rule and desired data;
B, input equipment with loading routine and data;
C, controlled quentity controlled variable deviation calculation, obfuscation calculating, fuzzy control reasoning, non-Defuzzication calculating, logical operation and the data transfer that can finish in the program are processed the arithmetical unit of handling;
D, can be according to the trend of the needs control program of the result of computing and program, and can be according to the controller of specified control machine each several part coordinated manipulation;
E, can be according to people's the output device that the personnel of output function as a result that handle need be used;
F, with the input analog signal conversion be the analog-digital converter (A/D) of digital signal;
G, the digital signal of output is converted to the digital analog converter (D/A) of analog control signal.
Compared with prior art the utlity model has following characteristics and beneficial effect:
The utility model only needs to measure the C/N ratio in the water inlet in the operational process of A/O technique subsection water-feeding deep denitrogenation system, can realize the optimized distribution of flow and volume.This technology not only can realize the optimized distribution of flow and volume preferably, realizes that the optimization operation of process system ground reaches very high nitrogen removal rate, and has advantages such as input parameter is few, control law is easily understood, difficult generation sludge bulking.
The volume of oxygen-starved area distributes in flow of inlet water in the employing fuzzy control strategy control segmental influent and biological denitrification process and the optimized distribution of volume and each section, promptly regulate the hydraulic detention time of each section oxygen-starved area and aerobic zone, it is not enough caused nitrated or denitrification is incomplete fundamentally to have solved aeration or mixing time.And can control the required reaction time of each biochemical reaction in real time according to the variation of the raw water quality water yield, realize having intelligentized control;
Can draw into water C/N ratio by the online water inlet COD that records, kjeldahl nitrogen concentration, realize the optimized distribution of flow and volume, thereby realize the optimization operation of technology and reach higher nitrogen removal rate;
Realize that by fuzzy control technology each section nitrification and denitrification reaction carries out fully, do not produce the accumulative total of nitrate nitrogen or ammonia nitrogen, the water outlet total nitrogen concentration is only determined by the nitrate nitrogen concentration of the nitrated generation of kjeldahl nitrogen in the final stage water inlet, can be reached higher nitrogen removal rate;
This fuzzy control method and device are only regulated than the optimization that can realize flow and volume by water inlet C/N, have the advantage that input parameter is few, control law is easily understood;
Whole technology is finished by Fuzzy control system, has bookkeeping conveniently, and expense is low, anti impulsion load is strong and difficult generation sludge bulking.
The utility model can be applicable to the teaching demonstration of the fuzzy control of A/O technique subsection water-feeding deep denitrogenation.
(4) description of drawings
Below in conjunction with drawings and Examples the utility model is elaborated:
Fig. 1 is a structural representation of the present utility model.
Fig. 2 is the utility model fuzzy control process synoptic diagram.
Fig. 3 adopts test effect synoptic diagram of the present utility model.
Among the figure: the 1-reaction tank, the 2-intake pump, the 3-aerator, the 4-stirrer, the 5-COD sensor, the 6-TKN sensor, the 7-DO sensor, the 8-COD analyzer, the 9-TKN analyzer, the 10-DO analyzer, 11-fuzzy controller main frame, the signal output interface of 12-fuzzy controller main frame, the 13-COD signal input interface, the 14-TKN signal input interface, the 15-DO signal input interface, the 16-power switch, the 17-display interface device, the 18-printer interface, the 19-display, 20-topworks, the signal input of 21-topworks, the signal output of 22-topworks, the 23-power interface, the 24-transformer, 25-intake pump regulator, 26-aerator relay, 27-stirrer relay, the 28-water inlet pipe, the 29-second pond, the 30-rising pipe, the 31-oxygen-starved area, the 32-aerobic zone, the 33-raw water vessel, the 34-by-pass valve control, the 35-pipe core, 36-excess sludge pipe, the 37-mud return line, the 38-return sludge pump, the 39-non-return valve.
(5) embodiment
Embodiment: the fuzzy control instructional device of this A/O technique subsection water-feeding deep denitrogenation has the A/O technique subsection water-feeding biological denitrificaion sewage disposal system of a teaching usefulness, referring to Fig. 1,2, its A/O biological denitrificaion sewage disposal system is linked in sequence and is formed by raw water vessel 33, water inlet pipe 28, by-pass valve control 34, intake pump 2, reaction tank, pipe core 35, second pond 29, rising pipe 30; Wherein reaction tank is formed by four sections, every section has an oxygen-starved area 31 and an aerobic zone 32, with oxygen-starved area, aerobic zone, oxygen-starved area, aerobic zone, oxygen-starved area, aerobic zone, oxygen-starved area, aerobic zone series arrangement, all be equipped with stirrer 4 in each oxygen-starved area, every section water inlet pipe all connects an intake pump 2, and each intake pump is connected with a by-pass valve control 34; Be equipped with the aerator 3 that is connected with air compressor in each aerobic zone, be communicated with excess sludge pipe 36 and mud return line 37 at the bottom of the pond of second pond, mud return line is communicated with first oxygen-starved area through return sludge pump 38, non-return valve 39.
Raw water vessel 33 at above-mentioned reaction tank is built-in with a chemical oxygen demand (COD) sensor, it is COD sensor 5, COD sensor 5 connects COD analyzer 8 through lead, and the signal delivery of COD analyzer 8 is connected with COD signal input interface 13 on the fuzzy controller main frame 11.
In the raw water vessel 33 of above-mentioned reaction tank, also be equipped with a kjeldahl nitrogen concentration sensor, be TKN sensor 6, TKN sensor 6 connects the signal delivery of TKN analyzer 9, TKN analyzer 9 through lead and is connected with TKN signal input interface 14 on the fuzzy controller main frame 11.
Each is built-in with the dissolved oxygen concentration sensor at the aerobic zone of above-mentioned reaction tank, i.e. DO sensor, and each DO sensor connects DO analyzer 10 through lead, and the signal delivery of DO analyzer 10 is connected with DO signal input interface 15 on the fuzzy controller main frame 11.
The signal output interface 12 of above-mentioned fuzzy controller main frame is connected with the signal input 21 of topworks, and respectively to aeration relay 26, intake pump regulator 25, agitator motor relay 27 input control signals of control executing mechanism inside; The aeration rate of aeration relay 26 each aerator of control, the inflow of intake pump regulator 25 each intake pump of control, the rotating speed of agitator motor relay 27 each stirrer of control.
Comprise in the fuzzy controller main frame in the utility model:
The storer of a, storage execute program, fuzzy control rule and desired data;
B, input equipment with loading routine and data;
C, controlled quentity controlled variable deviation calculation, obfuscation calculating, fuzzy control reasoning, non-Defuzzication calculating, logical operation and the data transfer that can finish in the program are processed the arithmetical unit of handling;
D, can be according to the trend of the needs control program of the result of computing and program, and can be according to the controller of specified control machine each several part coordinated manipulation;
E, can be according to people's the output device that the personnel of output function as a result that handle need be used;
F, with the input analog signal conversion be the analog-digital converter (A/D) of digital signal;
G, the digital signal of output is converted to the digital analog converter (D/A) of analog control signal.
The fuzzy control method step of using the utility model fuzzy control instructional device is as follows:
(1), in the raw water vessel of reaction tank, places the TKN sensor that is used to gather the COD sensor of chemical oxygen demand COD signal and is used to gather water inlet kjeldahl nitrogen concentration TKN signal; Gather chemical oxygen demand COD and water inlet kjeldahl nitrogen concentration and and then draw the into signal of water C/N ratio, as the fuzzy control input parameter of A/O technique subsection water-feeding deep denitrogenation, the volume of controlling oxygen-starved area in the optimized distribution of flow of inlet water and volume and each section in real time distributes.
(2), utilize above-mentioned COD sensor and TKN sensor water inlet COD and TKN concentration, COD and the TKN concentration signal gathered are imported analog-digital converter A/D through COD analyzer and TNK analyzer respectively, convert into water carbon-nitrogen ratio (C/N) input variable digital signal to.
(3), referring to Fig. 3, with above-mentioned input variable digital signal input fuzzy controller main frame, according to fuzzy control rule, obtain flow of inlet water partition factor (λ) after calculating, obfuscation calculating, fuzzy control reasoning and the non-Defuzzication calculating through the controlled quentity controlled variable deviation, and the volume of the volume of each oxygen-starved area and each section is as output variable; A/O technique subsection water-feeding biological denitrificaion fuzzy control device of the present utility model and method with " water inlet C/N than " as input variable, with the volume of flow of inlet water partition factor, each oxygen-starved area and each aerobic zone as output variable.
(4), convert above-mentioned output variable to the fuzzy control signal through digital analog converter D/A again.
(5), above-mentioned fuzzy control signal controlling topworks, directly the motor of the switch of intake pump, aerator, stirrer is carried out On-line Control and regulates.
Fuzzy control rule in above-mentioned (3) is as follows:
[1], as C/N than low, λ is low so, V
1Low, V
2Low, V
3Height, V
4Height, V
1 lacksHeight, V
2 lackLow, V
3 lackLow, V
4 lackLow;
[2], lower as C/N, low among the λ so than in, V
1In low, V
2In low, V
3Middle high, V
4Middle high, V
1 lacksMiddle high, V
2 lackIn low, V
3 lackIn low, V
4 lackIn low;
[3], as C/N than in, so among the λ, V
1In, V
2In, V
3In, V
4In, V
1 lacksIn, V
2 lackIn, V
3 lackIn, V
4 lackIn;
[4], as C/N than in high, high among the λ so, V
1Middle high, V
2Middle high, V
3In low, V
4In low, V
1 lacksIn low, V
2 lackMiddle high, V
3 lackMiddle high, V
4 lackMiddle high;
[5], as C/N than high, λ height so, V
1Height, V
2Height, V
3Low, V
4Low, V
1 lacksLow, V
2 lackHeight, V
3 lackHeight, V
4 lackHigh;
Above-mentioned each variable all adopts low, in low, in, middle height, high its state of expression draws the relation between fuzzy control input variable and the output variable.
Table 1 is oxygen-starved area aerobic zone volumetric ratio and every section flow in the every section volume, every section under steady state conditions:
Each section total measurement (volume) is with the formal representation of the number percent that accounts for the reactor total measurement (volume); Each section oxygen-starved area volume is with the formal representation of the number percent of the total measurement (volume) that accounts for this section.
In table 1, different water inlet C/N have been drawn than under the condition by test, the optimal allocation that anoxic is removed volume in every section flow and volume and each section.Sequence (1) for example, at water inlet C/N than being that the flow of inlet water partition factor that obtains is 1, the first section (V under 6.09 the situation
1), second section (V
2), the 3rd section (V
3), the 4th section (V
4) volume be respectively 0.2938V
Always, 0.25V
Always, 0.2375V
Always, 0.2188V
Always(V
AlwaysKnown), and the shared volume in oxygen-starved area is respectively 0.1064V in each section
1, 0.25V
2, 0.2632V
3, 0.2857V
4Wherein the flow of each section can pass through Q=λ
3Q+ λ
2Q+ λ q+q calculates, in the formula: Q
AlwaysBe total flow of inlet water, λ is the assignment of traffic coefficient, and q is the flow of inlet water of final stage.
λ represents the flow of inlet water partition factor;
V
1Represent first section volume;
V
2Represent first section volume;
V
3Represent first section volume;
V
4Represent first section volume;
V
1 lacksRepresent the volume of first section oxygen-starved area;
V
2 lackRepresent the volume of first section oxygen-starved area;
V
3 lackRepresent the volume of first section oxygen-starved area;
V
4 lackRepresent the volume of first section oxygen-starved area.
Sequence (2)-(11) also adopting said method can draw different water inlet C/N than under the condition, the optimal allocation that anoxic is removed volume in every section flow and volume and each section.
According to table 1 and table 2, set up fuzzy control rule, referring to table 3.
The domain of table 3 input and output variable and obfuscation and non-Defuzzication method
| Output and input variable | Domain | Fuzzy method | The non-Defuzzication method |
| Water inlet C/N ratio | [6.09 15.5] | Discretize | Mamdani |
| The volume of first section oxygen-starved area | [3.6％ 10.6％] | Discretize | Mamdani |
| The volume of second section oxygen-starved area | [25％ 45.1％] | Discretize | Mamdani |
| The volume of the 3rd section oxygen-starved area | [26.3％ 37.5％] | Discretize | Mamdani |
| The volume of the 4th section oxygen-starved area | [28.5％ 48.4％] | Discretize | Mamdani |
| The assignment of traffic coefficient | [1 4] | Discretize | Mamdani |
| First section volume | [29％ 60％] | Discretize | Mamdani |
| Second section volume | [25％ 29％] | Discretize | Mamdani |
| The 3rd section volume | [12.5％ 23.7％] | Discretize | Mamdani |
| The 4th section volume | [8.1％ 21.8％] | Discretize | Mamdani |
Result of study shows, the fuzzy concept when sticking with paste variable and describe the people and control activity with the normal state pattern suits, so the utility model also adopts normal state type subordinate function.Utilize fuzzy logic control case (Fuzzy LogicToolbox ofMATLAB 6.5) in the MATLAB language to set up the subordinate function of each fuzzy variable subclass, determining of [in low low in high] critical control point wherein is then according to the experimental studies results of table 1.Only pass through water inlet C/N than a parameter according to table 1, just can determine the assignment of traffic of whole technology and the optimized distribution of volume, and can finally reach very high nitrogen removal rate, have typical single input, the characteristics of exporting more, in actual application, can reduce the complicacy of control system greatly.
The conclusion that compbined test draws is built together and has been found 5 fuzzy control rules, is shown in Table 2.Fuzzy control rules adopts IF ... THEN ... formal representation.
The method of the domain of each input and output variable and obfuscation and non-Defuzzication is listed in the table 3.To each variable, all adopt low, and in low, in, middle height, height describe its state.
Utilizing fuzzy logic control case (Fuzzy Logic Toolbox ofMATLAB 6.5) in the MATLAB language to set up fuzzy control optimizes moving model and draws relation between fuzzy control input variable and the output variable.The relation of the input and output variable of the fuzzy control model of setting up by experiment, be fuzzy control input and output curved surfaces, by this curved surface, can draw the optimal allocation of different water inlet C/N than oxygen-starved area volume in every section flow under the condition and volume and each section.For example at water inlet C/N than being under 10 the condition, can get the optimal flow rate distribution coefficient through Cha Tu is that 2.25, first to fourth sections every section best volume is assigned as 42%V
Always, 26.75%V
Always, 19%V
Always, 15.8%V
Always, the shared volume in each section oxygen-starved area is respectively 7.7%V
1, 34%V
2, 31.5%V
3, 37%V
4Thereby, just realized the advanced nitrogen optimization operation of A/O technique subsection water-feeding
A/O technique subsection water-feeding deep denitrogenation fuzzy control method and control and the adjusting of device by the unlatching realization volume of adjusting aerator and stirring motor; Realize the control and the adjusting of flow of inlet water by regulating intake pump.
After using the utility model, the unstable state running test result of A/O technique subsection water-feeding deep denitrogenation system is referring to Fig. 3, from experimental result as can be seen the unstable state operational process A/O segmental influent technology reached average 94.32% nitrogen removal rate.In the process of the test, the water outlet ammonia nitrogen concentration is zero, and the water outlet total nitrogen concentration is only determined by the water outlet nitrate concentration.The water outlet total nitrogen concentration all is lower than 2.41mg/L in 3 months process of the test.And the sludge volume index value changes between 82mL/g to 97mL/g, and average 91mL/g has embodied stability preferably.
Embodiment: pilot plant test adopts the real-life sewage of Beijing University of Technology's dependents' district discharging, and its water-quality guideline situation is as shown in table 4.
Table 4 water inlet sewage quality
| Project | COD (mg/L) | NH 4 +-N (mg/L) | NO 2 --N (mg/L) | NO 3 --N (mg/L) | TKN (mg/L) |
| Maximal value | 440 | 50 | 0.128 | 0.9 | 54 |
| Minimum value | 258 | 29 | 0 | 0 | 33 |
| Mean value | 336 | 41.4 | 0.05 | 0.75 | 45.6 |
The pilot plant test reactor is made up of anoxic/aerobic/anoxic/aerobic plug flow reactor and vertical sedimentation basin, and reactor size is 1400mm * 460mm * 600mm (two gallery), and useful volume is 320L (being 360L to the maximum).With A/O technique subsection water-feeding deep denitrogenation fuzzy control method described in the utility model and device is guidance, has carried out 3 months by a definite date unstable state operation research.Keep inflow constant in the process of the test, and influent quality change and present certain time variation in time.Find that in process of the test each section nitration reaction and anti-nitration reaction all carry out fully.From experimental result as can be seen the unstable state operational process A/O segmental influent technology reached 100% ammonia nitrogen removal frank, average 94.32% nitrogen removal rate.The terminal ammonia nitrogen concentration of each section aerobic zone all below detection line, reaches nitrated fully.And in each section oxygen-starved area, the accumulation of nitrate does not all take place.In the process of the test, the water outlet total nitrogen concentration is only determined by the water outlet nitrate concentration.The water outlet total nitrogen concentration all is lower than 2.41mg/L in 3 months process of the test.And the sludge volume index value changes between 82mL/g to 97mL/g, and average 91mL/g has embodied stability preferably.
Claims (1)
1. the fuzzy control instructional device of an A/O technique subsection water-feeding deep denitrogenation, be used for A/O biological denitrificaion sewage disposal system, its A/O biological denitrificaion sewage disposal system is linked in sequence and is formed by raw water vessel (33), water inlet pipe (28), by-pass valve control (34), intake pump (2), reaction tank, pipe core (35), second pond (29), rising pipe (30); Wherein reaction tank is formed by four sections, and every section has an oxygen-starved area (31) and an aerobic zone (32), all is equipped with stirrer (4) in each oxygen-starved area, and every section water inlet pipe all connects an intake pump (2), and each intake pump is connected with a by-pass valve control (34); Be equipped with the aerator (3) that is connected with air compressor in each aerobic zone, be communicated with excess sludge pipe (36) and mud return line (37) at the bottom of the pond of second pond, mud return line is communicated with first oxygen-starved area through return sludge pump (38), non-return valve (39), it is characterized in that:
Raw water vessel (33) at above-mentioned reaction tank is built-in with a chemical oxygen demand (COD) sensor, be COD sensor (5), COD sensor (5) connects COD analyzer (8) through lead, and the signal output port of COD analyzer (8) is connected with COD signal input interface (13) on the fuzzy controller main frame (11);
In the raw water vessel (33) of above-mentioned reaction tank, also be equipped with a kjeldahl nitrogen concentration sensor, be TKN sensor (6), TKN sensor (6) connects the signal output port of TKN analyzer (9), TKN analyzer (9) through lead and is connected with TKN signal input interface (14) on the fuzzy controller main frame (11);
Each is built-in with the dissolved oxygen concentration sensor at the aerobic zone of above-mentioned reaction tank, it is the DO sensor, each DO sensor connects DO analyzer (10) through lead, and the signal output port of DO analyzer (10) is connected with DO signal input interface (15) on the fuzzy controller main frame (11);
The signal output interface of above-mentioned fuzzy controller main frame (12) is connected with the signal input (21) of topworks, and respectively to aeration relay (26), intake pump regulator (25), agitator motor relay (27) input control signal of control executing mechanism inside; Aeration relay (26) is controlled the aeration rate of each aerator, and intake pump regulator (25) is controlled the inflow of each intake pump, and agitator motor relay (27) is controlled the rotating speed of each stirrer.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CNU2007202009928U CN201191473Y (en) | 2007-09-11 | 2007-09-11 | A/O process segmental influent deep nitric removing fuzzy control teaching apparatus |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CNU2007202009928U CN201191473Y (en) | 2007-09-11 | 2007-09-11 | A/O process segmental influent deep nitric removing fuzzy control teaching apparatus |
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|---|---|
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| CN102063062A (en) * | 2011-02-18 | 2011-05-18 | 哈尔滨工业大学 | Sludge bulking control expert system for diagnosis based on filamentous bacteria population structure |
| CN102358676A (en) * | 2011-10-24 | 2012-02-22 | 沈阳建筑大学 | Four-stage three-phase fluidized bed step-feed deep nitrogen removal system |
| WO2012109900A1 (en) * | 2011-02-14 | 2012-08-23 | 华南理工大学 | Method and system for wastewater treatment based on dissolved oxygen control by fuzzy neural network |
| CN109879431A (en) * | 2019-04-19 | 2019-06-14 | 长春工程学院 | The subsection water inflow A of short distance nitration/O technique corn starch wastewater denitrogenation method |
| CN110745948A (en) * | 2019-09-27 | 2020-02-04 | 中车环境科技有限公司 | Sectional water inlet deep dephosphorization and denitrification process |
| CN111732187A (en) * | 2020-06-30 | 2020-10-02 | 南京工业大学 | Intelligent control method for sewage treatment water quality based on sludge reflux ratio |
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2007
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
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| WO2012109900A1 (en) * | 2011-02-14 | 2012-08-23 | 华南理工大学 | Method and system for wastewater treatment based on dissolved oxygen control by fuzzy neural network |
| US9747544B2 (en) | 2011-02-14 | 2017-08-29 | South China University Of Technology | Method and system for wastewater treatment based on dissolved oxygen control by fuzzy neural network |
| CN102063062A (en) * | 2011-02-18 | 2011-05-18 | 哈尔滨工业大学 | Sludge bulking control expert system for diagnosis based on filamentous bacteria population structure |
| CN102358676A (en) * | 2011-10-24 | 2012-02-22 | 沈阳建筑大学 | Four-stage three-phase fluidized bed step-feed deep nitrogen removal system |
| CN109879431A (en) * | 2019-04-19 | 2019-06-14 | 长春工程学院 | The subsection water inflow A of short distance nitration/O technique corn starch wastewater denitrogenation method |
| CN109879431B (en) * | 2019-04-19 | 2021-07-23 | 长春工程学院 | Corn starch wastewater denitrification method adopting short-cut nitrification and segmented water inlet A/O (anaerobic/oxic) process |
| CN110745948A (en) * | 2019-09-27 | 2020-02-04 | 中车环境科技有限公司 | Sectional water inlet deep dephosphorization and denitrification process |
| CN111732187A (en) * | 2020-06-30 | 2020-10-02 | 南京工业大学 | Intelligent control method for sewage treatment water quality based on sludge reflux ratio |
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