38 results about "Sludge volume index" patented technology

The invention relates to a method for starting and stably keeping the micro-expansion of sludge in a synchronous biological nitrogen and phosphorus removal system, belonging to the field of treating sewage biochemically. A device for implementing the method is formed by connecting a water inlet pool, anaerobic cells, hypoxic cells, aerobic cells and a secondary settling pool in sequence. The wall of the secondary settling pool is provided with a sludge height mark so that the degree of expansion of the sludge can be known in real time. Each aerobic cell is provided with an independent dissolved-oxygen probe, and the dissolved-oxygen probe is connected with a dissolved-oxygen instrument. The control platform of a PLC (programmable logic controller) is used for controlling the concentration of the dissolved oxygen in each aerobic cell accurately according to the parameter set value and the feedback signal of the dissolved-oxygen instrument. The micro-expansion of the sludge in the synchronous biological nitrogen and phosphorus removal system is started by reducing the concentration of the dissolved oxygen in each aerobic cell to 0.8-1.0 mg / L, and the dissolved oxygen is regulated according to monitoring result of the SVI (sludge volume index), the height of the sludge in the secondary settling pool, the quality of the effluent of the device and other parameters so as to keep the micro-expansion of the sludge stable. Due to the adoption of the method, the pollutant removal rate is improved, the quality of the effluent is guaranteed, the aeration energy consumption of the water plant is reduced, and the energy-efficient treatment of the effluent is realized.

A soft measurement method for an SVI (sludge volume index) belongs to the field of water treatment. Production conditions of sewage treatment process are severe, random disturbance of the sewage treatment process is serious, and the sewage treatment process is high in nonlinearity, large in time varying and serious in lagging. Almost all municipal sewage treatment plants and most industrial sewage treatment plants in China have sludge bulking to varying degrees every year, sludge bulking is mainly characterized by deterioration of sludge settleability, and the SVI is a parameter indicating the sludge settleability, but the key index is difficult to be measured on line. The soft measurement method based on a self-organizing RBF (radial basis function) neural network aims at solving the problem that the SVI cannot be measured on line in the sewage treatment process, the self-organizing RBF neural network is used for measuring the SVI on line in the sewage treatment process, normal operation of sewage treatment is ensured, cost is reduced, timely monitoring parameters are provided for realizing closed-loop control in the sewage treatment process, and the sewage treatment plants are promoted to run efficiently and stably.

The invention relates to a filamentous sludge bulking recovery method based on a non-nitrification A / O (anaerobic / aerobic) biological phosphorus removal process, and belongs to the field of urban domestic sewage treatment and regeneration. In virtue of an A / O biological phosphorus removal reactor, filamentous bulking is recovered in two stages, and the filamentous sludge bulking recovery method comprises the following steps: firstly keeping load at 0.40-0.50kg COD (chemical oxygen demand) / kg MLSS (mixed liquor suspended solid) / d, regulating reflux ratio to 75%-85%, controlling the aeration of an aerobic stage to form DO (dissolved oxygen) gradient aeration of 1.4mg / L-1.6mg / L, 0.9mg / L-1.0mg / L and 0.9mg / L-1.0 mg / L to eliminate filamentous fungi, reducing the reflux ratio to 45%-55% when an SVI (sludge volume index) value is reduced into the range of 180mL / g-250mL / g, and reducing the aeration to form the DO gradient of 0.9mg / L-1.1mg / L, 0.4mg / L-0.6mg / L and 0.4mg / L-0.6mg / L. Under the operation parameter conditions, the filamentous bulking caused by the DO and high-load impact (1.54kg COD / kg MLSS / d) can be recovered rapidly, the SVI is reduced from 569.8mL / g to below 150mL / g, and the recovery time of bulking of the lighter filamentous fungi is shorter.

The invention discloses a method for quickly culturing aerobic granular sludge and a sequencing batch reaction device. The method includes that in an alternate anaerobic / aerobic sequencing batch reactor, municipal sewage is used as incoming water, and anaerobic digestion sludge and aerobic sludge (mixing ratio being 1:1) are used as inoculating sludge; at the early stage of starting, enhancing of sludge settling performance improvement and initial aerobic granular crystal nucleus formation and accelerating and optimizing of aerobic granular sludge formation and thorough granulation are realized by inoculating high-concentration sludge (20g / L) and adopting a low sludge load (0.056kgCOD / kgSS d) running mode. The method has the advantages that granules are formed quickly, so that the problem that aerobic sludge granules are difficult to form and too long in forming time is solved; an aerobic granular sludge 'crystal nucleus hypothesis' quick mode is realized; cultured aerobic granular sludge is compact in structure, high in stability and faint yellow in appearance, average grain diameter is 750um, sludge volume index (SVI) is 20-35mL / g, and removal rates of COD, TN and TP can reach 92%, 81% and 85% respectively; the method is simple in process, convenient in operation and low in cost.

The invention discloses a method for improving precipitation performance of filamentous bulking sludge. The method comprises the steps of 1), crushing and screening organics, such as corn, wheat, sorghum and rice; 2), measuring the concentration of activated sludge in a biological reaction tank such as an aeration tank and a precipitation tank, and quantifying filamentous bacteria for the bulking sludge; 3), putting into the filamentous bulking sludge according to the weight ratio for preparing the screened organics per gram of the sludge or the weight ratio for preparing the organics per meter of the length of each filamentous bacterium; 4), keeping other conditions in the biological reaction tank unchanged, and increasing stirring; and 5), measuring the MLSS (mixed liquor suspended solid) value and the SVI (sludge volume index) value in the biological reaction tank, so that the improvement of the precipitation performance of the filamentous bulking sludge is achieved. The method can enable the filamentous bacteria causing sludge bulking to grow in adhering and twining manners and change a spreading growing manner of the filamentous bacteria, so that the filamentous bacteria grow densely, the problem that solids and liquid are hard to separate is solved, and the effluent quality of sewage treatment is improved.

A method for regulating and controlling sludge quality in membrane bioreactor belongs to the technical field of biological treatment for waste water. In the invention, simulation waste water is taken as treating object, the EPS content in the sludge is regulated and controlled by sequencing batch operation instead of continuous operation of the traditional MBR process so as to change settlement performance and hydrophobicity of the sludge and delay membrane pollution. The water discharged by the MBR system arrives at first-level A standard of pollutant discharge standard of the national town sewage treatment plant and quality standard for city sewage recycling-city water use; the suspended solid concentration MLSS in the mixed liquid in the MBR is 8.4-13.0 g / L; the volatile solid concentration VSS is 4.7-10.4 g / L; the relative hydrophobicity of the sludge is 66.5-88.6%; the sludge volume index SVI is 32.2-40.7 mL / gMLSS; and the total weight of ecto-polymer of sludge EPS is 19.3-26.5 mg / gVSS. The method has simple operation, low operation cost, good stability, low residual sludge yield, good water quality and high theoretical value, thereby being capable of being applied in engineering practice.

The invention discloses a method for remedying filamentous expanded aerobic granular sludge in the wastewater treatment process in the technical field of environmental protection and resource integration - water pollution prevention and control. The method adopts feeding and specific operation conditions to selectively enrich zoogloeae to remedy filamentous expanded aerobic granular sludge. The method comprises the steps of: firstly providing culture conditions which facilitate the growth of zoogloeae in the granular sludge, i.e. improving inlet water concentration of an aerobic granular sludge reactor through feeding, so as to regulate inlet water chemical oxygen demand (COD) to 1000-1500mg / L and carbon to nitrogen ratio (C:N) to 6.7-10; then setting a sequencing batch mode with a certain operation cycle to guarantee sludge load to reach 1.0-1.5g COD / g SS.d; and finally using shearing force provided by high aeration intensity (4-7L / min) to strengthen the falling of filamentous bacteria on the surface of the granular sludge and draining the falling suspended filamentous bacteria out of the reactor at a water drainage stage. By adopting the method, the sludge volume index (SVI) of the filamentous expanded granular sludge can be decreased to 20-40ml / g from a value above 50ml / g, and the stable structure, the settling property and the wastewater treatment capacity of the granular sludge can be restored.

A method for building a filamentous bacterium SVI (sludge volume index) characteristic model is an important branch of the technical field of advanced manufacture, and is also an important part of the field of water treatment. In order to solve the problems that filamentous bacterium sludge expansion is caused by numerous factors and a mechanism model is difficultly built, based on filamentous bacterium sludge expansion causation factor analysis, dynamic characteristics of filamentous bacterium growth are extracted, and model parameters are corrected by a data statistical method. An SVI is predicted by the aid of relevant process variables and a filamentous bacterium sludge expansion mechanism, the problem of difficulty in building a sludge expansion model is solved, adaptability of the model to environmental differences in the sewage treatment process is improved, and monitoring of abnormal conditions of the sewage treatment process is guaranteed. Experimental results indicate that the model can rapidly and effectively predict the SVI, is high in prediction accuracy and has excellent adaptability to the environmental differences, and efficient stable operation and monitoring of the abnormal conditions of the sewage treatment process are guaranteed.

The invention relates to a method for rapidly solving sticky sludge bulking problem and belongs to the field of biochemical wastewater treatment. For a sticky sludge bulking problem caused by a high organic load, a means that inflow water supply is diluted and an operation mode of a reactor is changed is adopted, so that a system operates under the conditions of low inflow water organic load and high substrate concentration gradient; the sludge settleability is controlled in real time and conditions are improved in real time by detecting parameters such as a sludge volume index, an extracellular polymeric substance and a Zeta potential in an operation process. Practice shows that the sludge settleability can be obviously improved by continuously operating the method for rapidly solving the sticky sludge bulking problem for 2-8 days; in a later operation process, recurrence of the sticky sludge bulking problem can be effectively prevented by improving an inflow water and operation mode of a system. The method for rapidly solving the sticky sludge bulking problem has the advantages of short period, low recurrence rate, low economic cost and small influence on sludge activity and can be taken as an alternative scheme for rapidly and efficiently solving the sticky sludge bulking problem in an activated sludge process system.

The invention provides a sludge expansion intelligent identification method based on a self-organizing type II fuzzy neural network, and belongs to the technical field of intelligent detection. The sludge volume index (SVI) concentration of the sewage treatment plant is an important index to measure the sludge bulking phenomenon in the activated sludge process. As the sludge volume index (SVI) cannot be monitored online and the sludge expansion frequent fault type is difficult to judge, the soft measuring model of the sludge volume index (SVI) is established based on the self-organizing type II fuzzy neural network to complete real-time detection of the sludge volume index (SVI) concentration and determine the sludge expansion fault type through combination with the target correlation identification algorithm. The results show that the intelligent identification method can quickly obtain the sludge volume index (SVI) concentration, accurately identify the sludge expansion fault type, improve the quality and the efficiency of sewage treatment and ensure the stable and safe operation of the sewage treatment process.

The invention discloses a method for inhibiting activated sludge bulking and belongs to the technical field of sludge preparation. A purely natural plant extract solution added with copper sulfate, magnesium chloride and sodium chloride is adopted to inhibit bacterium growth, then aeration treatment is performed, the compactness of sludge is increased, and the settling property of the sludge is improved, so that the method for inhibiting activated sludge bulking is obtained. Examples prove that the method is simple to operate and easy to implement, the settling property is improved, growth of bacteria is effectively inhibited, so that sludge particles are hardened and cannot lose easily, the finally measured SVI (sludge volume index) is decreased from original 120-150 mL / g to 80-100 mL / g, SV is dropped from 50%-55% to 10%-12%, and bulking disappears gradually.

The invention discloses a sludge expansion fault identification method based on a recursive RBF (radial basis function) neural network, belongs to the field of control and water treatment and aims to solve the problems that sludge expansion in the sewage treatment process is difficult to accurately detect and reasons causing sludge expansion are difficult to identify. The sludge expansion fault identification method based on the recursive RBF neural network is designed, a soft measurement model of an SVI (sludge volume index) is established on the basis of the recursive RBF neural network, real-time prediction of the SVI concentration is completed. Once sludge expansion is detected, the fault variables causing sludge expansion are accurately identified with a fault variable identification (CVI) algorithm. By means of the method, the sewage treatment process can be controlled in advance according to fault variables, and the occurrence rate of sludge expansion is reduced.

The invention provides a sludge bulking inhibition method based on self-adaptive segmented sliding mode control, and aims to inhibit sludge bulking in order to solve the problems that abnormal sludgebulking working conditions are likely to occur in a sewage treatment process and are unlikely to transit to normal working conditions. According to the method of the invention, a fuzzy neural networkis adopted to obtain the water quality parameters of a sewage treatment operation process, predict a sludge volume index in real time and judge the working condition of the operation process, and provides a reference signal for the switching of a controller; and a segmented sliding mode controller with a self-adaptive switching mechanism is designed to regulate and control dissolved oxygen concentration and nitrate nitrogen concentration; and a biochemical reaction process is coordinated, the sludge settling characteristic is improved, and it can be guaranteed that the normal working conditionis recovered when sludge bulking occurs in the sewage treatment process.

The invention relates to the technical field of textile, and especially relates to a textile printing and dyeing wastewater processing technology. The technology is characterized in that physical, biological and biological processing methods are adopted to carry out multiple processing operations of textile wastewater, and the processed wastewater can be discharged in a standard reaching manner and also can be returned to a workshop for recycle in order to reach a water cycling use purpose; the environmental conditions of a biological aeration tank comprise a dissolved oxygen of 3-4mg / L, a temperature of 35-40DEG C, a pH value of 7.5-8.5, a sludge settlement ratio of about 28% to about 32%, a sludge concentration of 2-4g / L, and a sludge volume index of 90-110ml / g; and the retention time of the wastewater in the biological aeration tank is 40-60h. The technology has the advantages of stable and reliable operation, low processing cost, simple operation and the like.

A sludge bulking fault identification method based on a recursive RBF neural network belongs to the field of control and also belongs to the field of water treatment. Aiming at the problems that sludge bulking is difficult to accurately detect and the cause of sludge bulking is difficult to identify in the process of sewage treatment, the present invention designs a sludge bulking fault identification method based on recursive RBF neural network. The soft-sensing model of the sludge volume index SVI completes the real-time prediction of the sludge volume index SVI concentration. Once the occurrence of sludge bulking is detected, the fault variable identification CVI algorithm is used to accurately identify the fault variables that cause sludge bulking. The method can control the sewage treatment process in advance according to the fault variable, reducing the occurrence rate of sludge bulking.

The invention relates to a dirt dispersion agent for processing wastewater with high phosphorus content and high calcium content by using activated sludge. The dirt dispersion agent is prepared from the following raw materials including acrylic acid-2-acrylamido-2-methylpropanesulfonic acid copolymer, 2-phosphonobutane-1,2,4-tricarboxylic acid and polyamino polyether methylene phosphonic acid. The dirt dispersion agent is used for processing the high phosphorus content and high calcium content wastewater by using the activated sludge, can effectively suppress deposition of partial calcium salt on the activated sludge surface and relieve compressibility of activated sludge volume index by the calcium salt, thereby releasing a flocculation volume of the activated sludge, enabling the activated sludge to keep relatively good bioactivity, reducing sludge-producing rate, obviously reducing content of inorganic ash in the sludge, reducing output of calcium sludge and increasing removal rate of COD.

The invention discloses a sludge volume index (SVI) soft measuring method based on a self-organized T-S fuzzy nerve network and belongs to both the field of control and the field of sewage treatment. The accurate prediction of an SVI is the guarantee for normal operation of a sewage treatment process. The method comprises: first of all, taking the output quantity of a rule layer, i.e., the space activation intensity of the rule layer as a basis for determining whether a fuzzy rule is increased; secondly, on the basis of generating a new fuzzy rule, taking the output quantity of a membership function layer as a basis for determining whether a fuzzy set is increased; and finally obtaining a self-organized T-S fuzzy recursion nerve network by using a gradient decrease algorithm to adjust the weight value parameter of a model and the center value and width of a Gauss function, and establishing an SVI on-line soft measuring model based on an SOTSFEN such that real-time detection of the SVI is realized, and an effective method is provided for preventing sludge expansion.

The invention provides a method for controlling synthesis stability of polyhydroxyalkanoate of the mixed flora through sodium chloride and relates to a method for restoring stability of a production technology for the mixed flora with polyhydroxyalkanoate. The method for controlling the synthesis stability comprises the steps that sodium chloride is added to a PHA synthesis bacterium gathering reactor where sludge bulking occurs, the sludge settling ratio SV30 and MLSS of the reactor are detected, and the sludge volume index SVI is calculated; if the SV30 is lower than 50%, the SVI is lower than 200, and the duration time exceeds one SRT, normal salt-free operation can be restored; if bulking is not obviously improved, the addition amount of the sodium chloride continues to be increased until all indexes reach the demand, and normal operation is restored. According to the method, the situation can be quickly relieved in short time that due to filamentous fungus swelling, the domestication reactor is unstable, and even the severe sludge loss is caused. The situation is prevented in time that due to an unstable technology, the biomass and PHA yield are reduced. The operation loss isreduced.

The invention relates to a method for inhibiting the activated sludge bulking of an SBR pool, and belongs to the field of sewage treatment. A platform is constructed beside the SBR pool, and a self-sucking pump (2) is placed on the platform; a pipeline (3) positioned on one head of the self-sucking pump (2) extends into the SBR pool (1), and the other head of the self-sucking pump (2) is connected with a venturi ejector (4); and an air duct (6) is connected to a venturi pipe (5) of the venturi ejector (4), the air duct (6) is directly connected with an ozone generator (7), and the outlet of the venturi ejector (4) is connected with a spray nozzle (9). According to the method, the ozone generator (7) is started, the self-sucking pump (2) is started at the same time, active sludge and sewage which are positioned in SBR simultaneously enter the venturi ejector (4) to be mixed with ozone and are sprayed from the spray nozzle (9) through a pipeline (8) under the action of the self-sucking pump; the sludge volume index range of raw wastewater is 500-710, the sludge settling ratio range of the raw wastewater is 50%-65%, after the raw wastewater is treated by a device, the sludge volume index range is detected to be 55-75, and the sludge settling ratio range is detected to be 12%-18%.

The invention discloses a sludge volume index distributed soft measurement method, and relates to a sludge treatment measurement control method, which comprises the steps of data collection, data arrangement and cleaning, base model construction, SVI model distributed training construction and SVI model deployment operation. The data is taken from historical measurement data of each waterline monitoring workstation. The data arrangement and cleaning comprises the steps of converting the collected data into data samples taking days as units, eliminating abnormal values, filling missing values and standardizing variables. A random configuration network model is used in a base model under a distributed architecture, and an alternating direction method of multiplier (ADMM) is used in a distributed optimization algorithm, and the constructed SVI soft measurement model can be respectively deployed to each waterline workstation and is used for calculating SVI. Compared with an SVI measurementmodel trained by a single waterline, the SVI measurement model obtained by the method has the advantage that the generalization performance and robustness are enhanced.

The invention provides a landfill leachate treatment system and treatment method. The landfill leachate treatment system comprises an anoxic pool, an aerobic pool and a membrane pool which are arranged sequentially, wherein a pure oxygen aeration device is arranged in the aerobic pool. According to the landfill leachate treatment system, the pure oxygen aeration device is arranged in the aerobic pool, oxygen utilization ratio of the landfill leachate treatment system can be increased, sludge volume index and emission load of volatile organic compounds can be reduced, and the number of equipment and supporting facilities can be reduced, so that the cost of a garbage power plant is reduced.

The invention relates to a marine active sludge product, and a preparation method and a water treatment application of the marine active sludge product. The marine active sludge product is rich in salt-tolerant microorganisms and halophilic microorganisms from the ocean or other salt environments, and exists in a form of particle flocculent active sludge or a separation composite inoculant; the product has a DO (dissolved oxygen) content of 0.1-4.0mg / L, an ambient temperature of 0-50 DEG C, a salt concentration of 2-34% and a pH (potential of hydrogen) value of 5-9; and when the product exists in the form of the active sludge, an SVI (sludge volume index) of the product is 50-200mL / g, and an MLVSS (mixed liquor volatile suspended solid) is 1.2-7.5g / L. According to the preparation method, a halophilic microorganism culture technology and an active sludge culture technology are fused for use innovatively; a novel microorganism purification system for high-salt organic wastewater treatment is prepared; an operating system with high wastewater degradation capability, and economical operating cost and temperature is achieved; and an application range is wide. The invention further provides a relevant water treatment method. The water treatment capability and the application range of the marine active sludge product is improved and expanded, and the practicability is better.

The invention discloses a sewage treatment aeration system control method based on microbial communities, and belongs to the field of wastewater treatment. The method comprises the following steps: firstly, constructing a long short-term memory (LSTM) network model on the basis of sludge concentration, sludge volume index, dissolved oxygen concentration and active sludge microflora structure data; training the model by adopting sludge concentration, sludge volume index, dissolved oxygen concentration and activated sludge microflora structure data obtained under the conditions that a sewage treatment system normally runs and the sludge performance is good, and then calculating the optimal aeration rate in an application state by adopting the trained model and performing aeration control. The dissolved oxygen regulation and control method provided by the invention can effectively reduce the abundance of microorganisms causing poor sludge performance (sludge bulking or foaming) in a sewage treatment system, so that the efficient and stable operation of the system is guaranteed.

A soft measurement method for an SVI (sludge volume index) belongs to the field of water treatment. Production conditions of sewage treatment process are severe, random disturbance of the sewage treatment process is serious, and the sewage treatment process is high in nonlinearity, large in time varying and serious in lagging. Almost all municipal sewage treatment plants and most industrial sewage treatment plants in China have sludge bulking to varying degrees every year, sludge bulking is mainly characterized by deterioration of sludge settleability, and the SVI is a parameter indicating the sludge settleability, but the key index is difficult to be measured on line. The soft measurement method based on a self-organizing RBF (radial basis function) neural network aims at solving the problem that the SVI cannot be measured on line in the sewage treatment process, the self-organizing RBF neural network is used for measuring the SVI on line in the sewage treatment process, normal operation of sewage treatment is ensured, cost is reduced, timely monitoring parameters are provided for realizing closed-loop control in the sewage treatment process, and the sewage treatment plants are promoted to run efficiently and stably.

The invention relates to a method for forecasting sludge volume index in the sewage treatment process and belongs to the field of sewage treatment. The sewage treatment process is severe in production condition and serious in random interference and has the features of being strong in nonlinearity, large in time varying and severe in hysteresis. Sludge volume of different degrees exists in almost all of the municipal sewage plants and most of industrial sewage treatment plants in China every year. The main features of the sludge volume are that sludge settleability is worsened, the sludge volume index (SVI) represents the parameter of the sludge settleability, but the SVI which is criticality index is difficultly measured online. In order to solve the problem that the SVI in the sewage treatment process cannot be measured online, the forecasting method based on an integrated nerve network is adopted to achieve real-time forecasting of the SVI in the sewage treatment process, and good effect is obtained.

The invention discloses a device for monitoring settling performance of activated sludge in situ and a detection method. The device comprises a cabin for placing a sample and an ultrasonic time domain reflectometer for determination and analysis, wherein a sample stagnation area is arranged inside the cabin body, and a sample inlet and a sample outlet are formed outside the cabin body; the sample inlet is communicated with the top of the sample stagnation area, and the sample outlet is communicated with a side wall of the sample stagnation area; a stirring device is arranged at the bottom of the sample stagnation area, and an ultrasonic probe is arranged at the top of the sample stagnation area; and the ultrasonic time domain reflectometer is in signal connection with the ultrasonic probe. The detection method comprises steps of sampling, stirring, ultrasonic treatment and data detection, and the sedimentation performance of the activated sludge is obtained by taking the longitudinal coordinate time displacement at the time point of 30 minutes as an index for measuring the sludge volume index of the activated sludge. The portable device disclosed by the invention can be used for measuring the settling performance of a sludge sample on a test site.

The invention discloses a method for inhibiting activated sludge bulking and belongs to the technical field of sludge preparation. A purely natural plant extract solution added with copper sulfate, magnesium chloride and sodium chloride is adopted to inhibit bacterium growth, then aeration treatment is performed, the compactness of sludge is increased, and the settling property of the sludge is improved, so that the method for inhibiting activated sludge bulking is obtained. Examples prove that the method is simple to operate and easy to implement, the settling property is improved, growth of bacteria is effectively inhibited, so that sludge particles are hardened and cannot lose easily, the finally measured SVI (sludge volume index) is decreased from original 120-150 mL / g to 80-100 mL / g, SV is dropped from 50%-55% to 10%-12%, and bulking disappears gradually.

The present invention proposes a sludge bulking suppression method based on self-adaptive segmental sliding mode control, aiming at the problem that abnormal sludge bulking is easy to occur in the sewage treatment process, and it is difficult to transition to normal working conditions, and realizes the suppression of sludge bulking . The present invention adopts fuzzy neural network to obtain water quality parameters in the sewage treatment operation process to predict the sludge volume index in real time to judge the working conditions of the operation process, provide reference signals for the switching of the controller, and design a segmented sliding mode control with an adaptive switching mechanism The device regulates the dissolved oxygen concentration and nitrate nitrogen concentration, coordinates the biochemical reaction process, improves the sludge settling characteristics, and can ensure that the sewage treatment process returns to normal working conditions when sludge bulking occurs.

The invention relates to a method for rapidly solving sticky sludge bulking problem and belongs to the field of biochemical wastewater treatment. For a sticky sludge bulking problem caused by a high organic load, a means that inflow water supply is diluted and an operation mode of a reactor is changed is adopted, so that a system operates under the conditions of low inflow water organic load and high substrate concentration gradient; the sludge settleability is controlled in real time and conditions are improved in real time by detecting parameters such as a sludge volume index, an extracellular polymeric substance and a Zeta potential in an operation process. Practice shows that the sludge settleability can be obviously improved by continuously operating the method for rapidly solving the sticky sludge bulking problem for 2-8 days; in a later operation process, recurrence of the sticky sludge bulking problem can be effectively prevented by improving an inflow water and operation mode of a system. The method for rapidly solving the sticky sludge bulking problem has the advantages of short period, low recurrence rate, low economic cost and small influence on sludge activity and can be taken as an alternative scheme for rapidly and efficiently solving the sticky sludge bulking problem in an activated sludge process system.

A method for building a filamentous bacterium SVI (sludge volume index) characteristic model is an important branch of the technical field of advanced manufacture, and is also an important part of the field of water treatment. In order to solve the problems that filamentous bacterium sludge expansion is caused by numerous factors and a mechanism model is difficultly built, based on filamentous bacterium sludge expansion causation factor analysis, dynamic characteristics of filamentous bacterium growth are extracted, and model parameters are corrected by a data statistical method. An SVI is predicted by the aid of relevant process variables and a filamentous bacterium sludge expansion mechanism, the problem of difficulty in building a sludge expansion model is solved, adaptability of the model to environmental differences in the sewage treatment process is improved, and monitoring of abnormal conditions of the sewage treatment process is guaranteed. Experimental results indicate that the model can rapidly and effectively predict the SVI, is high in prediction accuracy and has excellent adaptability to the environmental differences, and efficient stable operation and monitoring of the abnormal conditions of the sewage treatment process are guaranteed.