CN-120704219-B - Intelligent aeration control system and method for sewage treatment plant

CN120704219BCN 120704219 BCN120704219 BCN 120704219BCN-120704219-B

Abstract

The invention discloses an intelligent aeration control system and method for a sewage treatment plant, and relates to the technical field of sewage treatment control; the system comprises a data acquisition module, an aeration test module, a demand prediction module, a normal state analysis module and an aeration control module: and a data acquisition module: collecting real-time working data of a primary sedimentation tank, test data of an aeration tank, historical working data of the aeration tank and real-time working data, and preprocessing; the technical key points are as follows: the aeration tank is scientifically divided into a plurality of sections, professional monitoring equipment is deployed in each section, multidimensional data are collected, independent collection and test of each section of data can be performed, the running condition and the treatment effect of each section of aeration equipment can be accurately mastered, based on the accurate data, the aeration efficiency evaluation model and the regulation and control strategy are combined, the actual demands of each section can be finely regulated, the resource waste or poor treatment effect caused by one-cut regulation and control is avoided, the efficient and accurate operation of the aeration equipment is realized, and the aeration tank has good use prospect.

Inventors

SUN XIAOFEN
WEI HUANHUAN
LIU YUYANG
TAN ZHENGGANG
LI TIANXIANG
NING SONGJIN
ZHONG LIBIN
LIU FENG

Assignees

江西洪城水业环保有限公司

Dates

Publication Date: 20260508
Application Date: 20250708

Claims (9)

1. The intelligent aeration control system of the sewage treatment plant is characterized by comprising: The data acquisition module acquires real-time working data of the primary sedimentation tank, aeration tank test data, historical working data of the aeration tank and real-time working data and performs pretreatment; The aeration test module is used for extracting the pretreated aeration tank test data according to the segmentation standard of the aeration tank, analyzing the segmented aeration data, generating an evaluation value, and comparing the evaluation value with a preset maintenance value; If the evaluation value is less than the maintenance value, not processing; Otherwise, deleting the evaluation value, and carrying out the aeration tank test again after maintaining the aeration equipment to obtain the evaluation value; The demand prediction module is used for inputting the real-time working data of the primary sedimentation tank and the real-time working data of the aeration tank into a trained prediction model to predict aeration demand data; the normal analysis module is used for analyzing historical working data of the aeration tank, formulating an aeration grade index and a corresponding regulation strategy, and correcting aeration demand data by adopting an evaluation value; the aeration control module is used for calculating a change value of the corrected aeration demand data by taking the corrected aeration demand data as a reference value and comparing the change value with a set standard interval; If the change value is in the standard interval, executing a regulation strategy for correcting the corresponding aeration demand level of the aeration demand data; If the change value is higher than the upper limit value of the standard interval, executing a regulation strategy for correcting the aeration demand data to correspond to the higher aeration demand level by one level; if the change value is lower than the lower limit value of the standard interval, maintaining the current state and executing an abnormal supervision strategy; the aeration tank test is to operate each section of aeration tank according to preset standard aeration parameters under the stable working condition, the test duration is T, test data are collected, an evaluation value is calculated based on the test data, and a formula for calculating the evaluation value is as follows: wherein Epg is an evaluation value, ps is the power of the aeration equipment, B is a pressure loss coefficient, As the pressure loss data of the current aeration apparatus, The reference pressure loss in the initial state is V which is the water volume of each part after the aeration tank is segmented, Is the increment of the dissolved oxygen concentration of the water body in the time T, The concentration of saturated dissolved oxygen at the current sewage temperature is shown, and A is the water quality correction coefficient.
2. The intelligent aeration control system of the sewage treatment plant according to claim 1, wherein the real-time working data of the primary sedimentation tank comprises a water outlet index, an instantaneous water outlet flow and a sludge proportion, the historical working data of the aeration tank and the real-time working data comprise dissolved oxygen, ammonia nitrogen concentration, sludge concentration, oxidation-reduction potential, a water outlet index, the instantaneous water outlet flow and the sludge proportion, and the historical working data of the aeration tank further comprise actual oxygen demand data.
3. The intelligent aeration control system for a sewage treatment plant according to claim 2, wherein the preprocessing of the collected data comprises the steps of cleaning and converting, specifically as follows: abnormal value processing, namely detecting abnormal values by adopting a Laida criterion, and identifying and removing data points exceeding a normal fluctuation range; and (3) processing the missing values, namely estimating the missing values by utilizing the data trend of adjacent time points, and filling the missing values by adopting a linear interpolation method based on a time sequence: Normalization processing, namely performing normalization processing on all data subjected to outlier processing and missing value processing.
4. The intelligent aeration control system for a sewage treatment plant according to claim 3, wherein the predictive model adopts an autoregressive integrated moving average model, and the training steps of the predictive model are as follows: dividing the historical working data of each section of aeration tank into a training set and a testing set according to the proportion of 7:3; Carrying out stationarity analysis on the original oxygen demand time sequence by adopting unit root test, if the original oxygen demand time sequence does not meet stationarity conditions, converting the original oxygen demand time sequence into a stationary sequence through differential operation, and determining differential order; model grading, namely drawing a processed autocorrelation function and partial autocorrelation function graph, combining a red pool information criterion and a Bayesian information criterion, adopting a particle swarm optimization algorithm to determine an autoregressive order and a moving average order, and constructing a preliminary model; parameter estimation, namely carrying out parameter estimation on the preliminary model by using training set data, and solving model parameters by adopting a maximum likelihood estimation method; And (3) model testing, namely inputting test set data into a trained model to predict, and evaluating model prediction accuracy by adopting root mean square error and average absolute error.
5. The intelligent aeration control system for a sewage treatment plant according to claim 4, wherein the step of analyzing historical operating data of the aeration tank and formulating the aeration level index is as follows: data preparation, namely calling historical actual oxygen demand data of N times of last aeration tanks of each section from a database; calculating the mean value and standard deviation of the N times of historical actual oxygen demand data; grading, namely grading the actual oxygen demand of each section of aeration tank into H grades according to a statistical principle and the calculated mean value and standard deviation; And (3) strategy formulation, namely acquiring the upper limit value of the actual oxygen demand data in the H grades, presetting the parameters of the aeration equipment according to the upper limit value, and summarizing to generate regulation strategies to obtain H regulation strategies.
6. The intelligent aeration control system for a sewage treatment plant according to claim 5, wherein the step of correcting the aeration demand data using the evaluation value comprises the steps of: Based on the evaluation value, the oxygen supply efficiency reduction ratio is calculated, and the specific formula is as follows In the formula, G is the oxygen supply efficiency reduction ratio, en is the unit oxygen supply energy consumption under normal conditions, css is the pressure loss correction coefficient, and Css is 0< 1; based on the oxygen supply efficiency reduction proportion adjustment aeration demand data, the specific formula is: In which, in the process, In order to adjust the aeration demand data after the adjustment, Is predicted aeration demand data.
7. The intelligent aeration control system for sewage treatment plant according to claim 6, wherein the formula for calculating the aeration demand change value is In which, in the process, As a value of the variation in the aeration demand, For the corrected real-time predicted aeration demand data, Is the last set of aeration demand data that is modified.
8. The intelligent aeration control system of the sewage treatment plant according to claim 7, wherein the abnormal supervision strategy is executed to keep the reference value unchanged, a next group of variation values are calculated, if the three continuous variation values are lower than the lower limit value of the standard interval, detection early warning is sent out to wait for feedback, and if the feedback is abnormal, maintenance is carried out; If the feedback error-free signal is received, real-time corrected aeration demand data is calculated, and a regulation strategy corresponding to the aeration demand level of the real-time corrected aeration demand data is executed.
9. An intelligent aeration control method for a sewage treatment plant, which uses the system of any one of claims 1 to 8, and is characterized by comprising the following steps: collecting real-time working data of a primary sedimentation tank, test data of an aeration tank, historical working data of the aeration tank and real-time working data, and preprocessing; Extracting pretreated aeration tank test data according to the segmentation standard of the aeration tank, analyzing segmented aeration data, generating an evaluation value, and comparing the evaluation value with a preset maintenance value; If the evaluation value is less than the maintenance value, not processing; Otherwise, deleting the evaluation value, and carrying out the aeration tank test again after maintaining the aeration equipment to obtain the evaluation value; inputting real-time working data of the primary sedimentation tank and real-time working data of the aeration tank into a trained prediction model, and predicting aeration demand data; Analyzing historical working data of an aeration tank, formulating an aeration grade index and a corresponding regulation strategy, and correcting aeration demand data by adopting an evaluation value; calculating a change value of the corrected aeration demand data by taking the corrected aeration demand data as a reference value, and comparing the change value with a set standard interval; If the change value is in the standard interval, executing a regulation strategy for correcting the corresponding aeration demand level of the aeration demand data; If the change value is higher than the upper limit value of the standard interval, executing a regulation strategy for correcting the aeration demand data to correspond to the higher aeration demand level by one level; if the change value is lower than the lower limit value of the standard interval, maintaining the current state, and executing an abnormal supervision strategy.

Description

Intelligent aeration control system and method for sewage treatment plant Technical Field The invention relates to the technical field of sewage treatment control, in particular to an intelligent aeration control system and method for a sewage treatment plant. Background Under the double challenges of water resource shortage and water pollution aggravation, sewage treatment plants are generated as key facilities for guarding urban water environment. The method is like a huge urban kidney, and the domestic sewage and industrial wastewater are purified layer by means of physical treatment such as grating interception, sand setting precipitation and the like, biodegradation technology such as an activated sludge method and a biomembrane method, and advanced treatment means such as chemical coagulation and disinfection, so that pollutants are effectively reduced, water resource recycling is realized, and the method becomes a core force for maintaining ecological balance and promoting sustainable development. In a complex flow of sewage treatment, a biological treatment stage is a core link for removing pollutants, and efficient metabolism of microorganisms is not sufficient, an aeration system is used as key equipment for conveying oxygen to a reaction tank, the control technology directly influences the efficiency and energy consumption of sewage treatment, aeration control can accurately meet the requirement of microorganisms on dissolved oxygen by intelligently adjusting aeration quantity, organic matters in sewage are ensured to be fully degraded, energy waste caused by excessive aeration can be avoided, and the sewage treatment system becomes an important technological break for improving the operation efficiency of sewage treatment plants and realizing green low-carbon treatment. The invention patent with the patent name of CN105152308B in the prior patent grant publication discloses a control method and a control system for the aeration of an MBR aerobic tank, which comprises the following steps of collecting an ammonia nitrogen concentration signal of a membrane tank, obtaining a first residual value between the ammonia nitrogen concentration signal and an ammonia nitrogen preset concentration value, obtaining a dissolved oxygen preset concentration value of the aerobic tank through a first-order PI algorithm, collecting a dissolved oxygen concentration signal of the aerobic tank, obtaining a second residual value between the dissolved oxygen concentration signal and the dissolved oxygen preset concentration value, obtaining an aeration value of the aerobic tank through a second-order PI algorithm, and controlling a plurality of blowers according to the aeration value of the aerobic tank and a blower performance curve; The central idea of the scheme recorded in the patent is that the dissolved oxygen preset concentration value and the aeration value are calculated through a double-order PI algorithm by collecting the ammonia nitrogen concentration signal of the membrane tank and the dissolved oxygen concentration signal of the aerobic tank, the blower is controlled by combining a blower performance curve, and the system also comprises a signal validity verification and water quantity compensation mechanism, and a control strategy is switched according to the working states of a water inlet flowmeter, an online ammonia nitrogen meter and an online dissolved oxygen meter so as to realize accurate aeration control, stabilize water quality and reduce energy consumption; however, the solution described in the above patent has the following drawbacks when in use: In the process of aeration control, a mode of centralized data acquisition and a mode of centralized maintenance are adopted, the local blocking condition of aeration equipment is not considered, during actual use, the partial area of the aeration equipment is seriously blocked, the aeration effect of the partial area is greatly reduced, stable oxygen supply cannot be realized according to the mode, and the aeration energy consumption is greatly improved; In addition, the existing aeration control generally adopts a real-time accurate prediction mode, is influenced by environment or other factors when in use, the water flow can change, the data volume to be processed is large at the moment, the equipment parameters can be frequently adjusted greatly at the moment, the service life of the equipment is influenced, the energy waste and the unstable processing effect are caused, the abnormal improvement of the cost is caused, and the energy-saving requirement is not met. Disclosure of Invention (One) solving the technical problems Aiming at the defects of the prior art, the intelligent aeration control system and method for the sewage treatment plant are provided, an aeration tank is scientifically divided into a plurality of functional sections, a plurality of professional monitoring devices are deployed in each section, multidimensional data such as fl