A sewage treatment process monitoring and early warning system and early warning method

Abstract

The present application relates to the technical field of sewage treatment monitoring, and particularly relates to a sewage treatment process monitoring and early warning system and method. The system uses a plurality of characteristic parameters of the biochemical treatment stage of sewage treatment and equipment operation data to train a hybrid neural network prediction model, which can more accurately train the hybrid neural network prediction model. The trained hybrid neural network prediction model is used to predict the dissolved oxygen concentration of the process end monitoring point after biochemical treatment at a plurality of time nodes, and a more accurate prediction result can be obtained. The analysis unit determines the monitoring state based on the variance of the predicted dissolved oxygen concentration at the plurality of time nodes, and adjusts the relevant parameters based on the monitoring state multiple times. The present application can accurately predict the abnormal conditions of the biochemical treatment stage, which is the core stage of sewage treatment, and make corresponding adjustments, thereby improving the efficiency of sewage treatment.

Description

Technical Field

[0001] This invention relates to the technical field of wastewater treatment monitoring, and in particular to a wastewater treatment process monitoring and early warning system and method. Background Technology

[0002] Wastewater treatment technology has evolved from simple physical sedimentation to complex biochemical treatment. In the 19th century, primary treatment relied mainly on screens and natural sedimentation. The invention of activated sludge and biofilm processes in the early 20th century ushered in a new era of biological treatment, significantly improving the removal rate of organic pollutants. With industrial development and increasingly stringent environmental requirements, the focus of 21st-century technology has shifted to advanced treatment (such as nitrogen and phosphorus removal) and resource utilization, while incorporating intelligent control (such as AI-optimized aeration) and low-carbon processes (such as anaerobic ammonia oxidation). Current technological development faces challenges such as the increasing complexity of industrial wastewater composition, high sludge disposal costs, and aging pipe networks, driving innovation in advanced oxidation technologies, sludge-to-energy conversion, and intelligent diversion systems, forming a three-in-one technological system of "pollution control - resource recovery - carbon neutrality."

[0003] Chinese Patent Publication No. CN118348935B discloses an intelligent monitoring and early warning system for wastewater treatment. The invention includes a data acquisition and analysis module, a non-compliant wastewater treatment module, an equipment data acquisition and analysis module, an abnormal equipment analysis module, and an early warning terminal. It analyzes the purified water data from each stage of the wastewater treatment line to obtain the non-compliant treatment stages of each non-compliant wastewater treatment line, and transmits the purified water to the corresponding stage of the idle wastewater treatment line and issues an early warning. Furthermore, it analyzes the equipment data in each non-compliant treatment stage to obtain the abnormal equipment and issues an early warning.

[0004] It is evident that the existing technology has the following problems: it cannot accurately predict abnormal situations in the core stage of wastewater treatment, namely the biochemical treatment stage, and make corresponding adjustments, resulting in low wastewater treatment efficiency. Summary of the Invention

[0005] To address this issue, the present invention provides a wastewater treatment process monitoring and early warning system and method to overcome the problem in the prior art that it cannot accurately predict abnormal situations in the core stage of wastewater treatment, namely the biochemical treatment stage, and make corresponding adjustments, thereby resulting in low wastewater treatment efficiency.

[0006] To achieve the above objectives, the present invention provides a wastewater treatment process monitoring and early warning system, comprising: The parameter acquisition unit is used to periodically monitor several characterization parameters, including dissolved oxygen concentration and nitrate nitrogen content, in the biochemical treatment stage of wastewater treatment via a distributed sensor network. The equipment operation data acquisition unit is used to integrate the PLC control system to acquire equipment operation data, including the output frequency of the frequency converter, the opening degree of the branch pipe electric valve, the sludge return ratio and the aeration frequency. The prediction unit, which is connected to the parameter acquisition unit, is used to train a hybrid neural network prediction model based on the acquired historical time-time characterization parameters, and to predict the dissolved oxygen concentration at several time nodes at the end-of-process monitoring points after biochemical treatment within a preset time period based on the hybrid neural network prediction model, thereby obtaining several predicted dissolved oxygen concentrations. The analysis unit is connected to the prediction unit and the equipment operation data acquisition module respectively. It determines the monitoring status by using the variance of the predicted dissolved oxygen concentration at multiple time nodes predicted by the prediction unit within a preset time period, and adjusts the equipment operation data multiple times based on the monitoring status and the data acquired by the equipment operation data acquisition module, as well as adjusting the sludge return ratio. An adjustment unit, connected to the analysis unit, is used to adjust the corresponding parameters based on a determined monitoring status.

[0007] Furthermore, the analysis unit is also used to calculate the average value of the predicted dissolved oxygen concentration within a preset time period, wherein the calculation process is performed when the monitoring state is determined to be a first state, the first state being that the variance is greater than or equal to a first preset variance; the adjustment unit is also used to increase the output frequency of the inverter based on the difference between the first preset dissolved oxygen concentration and the predicted dissolved oxygen concentration, and the increase in output frequency is proportional to the difference, wherein the adjustment is performed when it is determined that the average value is not within a preset range and the nitrate nitrogen content is greater than a preset content.

[0008] Furthermore, the regulating unit increases the opening degree of the branch pipe electric valve during sewage treatment based on the output frequency of the frequency converter, and the increase in the opening degree of the branch pipe electric valve is proportional to the output frequency of the frequency converter.

[0009] Furthermore, the analysis unit is also used to calculate the integral of the plotted nitrate nitrogen content-time node curve; the adjustment unit is also used to adjust the dosage of Nitrosomonas inoculant based on the ratio of the integral to the preset integral; wherein, after a preset time, the monitoring state and nitrate nitrogen content are re-determined, and the curve is plotted when the monitoring state is the first state and the nitrate nitrogen content is greater than the preset content.

[0010] Furthermore, the adjustment unit is also used to increase the amount of Nitrosomonas inoculant based on the ratio of the integral to the preset integral, and the increase in the amount of Nitrosomonas inoculant is proportional to the ratio.

[0011] Furthermore, the adjustment unit repeatedly adjusts the output frequency of the inverter, the opening degree of the branch pipe electric valve, and the dosage of Nitrosomonas inoculant at least once in sequence. The adjustment is stopped when the number of adjustments equals or is less than the preset number, and the monitoring status is qualified. The analysis unit reduces the sludge return ratio based on the dosage of Nitrosomonas inoculant, and the reduction in the sludge return ratio is proportional to the dosage. Adjustment is performed when the monitoring status is the first state after the adjustment is stopped and the nitrate nitrogen content is greater than the preset content.

[0012] Furthermore, the analysis unit is also used to set up several monitoring points along the length of the aeration tank, and to calculate the difference in dissolved oxygen concentration between two adjacent monitoring points. The operation is performed when the monitoring state is determined to be a second state based on the variance of the dissolved oxygen concentration and the average value of the dissolved oxygen concentration within a preset time period is within a preset range. The second state is when the variance is less than a first preset variance and greater than a second preset variance. The adjustment unit is also used to adjust the aeration frequency based on the difference.

[0013] Furthermore, the adjustment unit is also used to reduce the aeration frequency based on the ratio of the difference to a preset difference, and the reduction in aeration frequency is proportional to the number of aeration points. Adjustment is performed when the difference in dissolved oxygen concentration between two adjacent monitoring points is greater than the preset difference. The adjustment unit is also used to increase the distance between monitoring points based on the ratio of the difference to a preset difference, and the increase in the distance between monitoring points is inversely proportional to the ratio. Adjustment is performed when the difference in dissolved oxygen concentration between two adjacent monitoring points is less than the preset difference.

[0014] Furthermore, the adjustment unit is also used to reduce the sampling time interval based on the distance between monitoring points, and the sampling time interval is proportional to the distance.

[0015] To achieve the above objectives, the present invention provides a method for monitoring and early warning of wastewater treatment processes, comprising: A distributed sensor network deployed in the biochemical treatment stage of wastewater treatment periodically monitors several characterization parameters, including dissolved oxygen concentration and nitrate nitrogen content. The integrated PLC control system acquires equipment operation data, including the output frequency of the frequency converter, the opening degree of the branch pipe electric valve, the sludge return ratio, and the aeration frequency. Based on the acquired historical time-time characterization parameters, a hybrid neural network prediction model is trained, and based on the hybrid neural network prediction model, the dissolved oxygen concentration at several time nodes of the process end monitoring points after biochemical treatment within a preset time period is predicted, thus obtaining several predicted dissolved oxygen concentrations. The monitoring status is determined based on the variance of the predicted dissolved oxygen concentration at multiple time nodes predicted by the prediction unit within a preset time period. Based on the monitoring status and the data obtained by the equipment operation data acquisition module, the equipment operation data is adjusted multiple times, and the sludge return ratio is adjusted. The corresponding parameters are adjusted based on the determined monitoring status.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention utilizes several characterization parameters of the biochemical treatment stage of wastewater treatment and equipment operation data to train a hybrid neural network prediction model, which can train the hybrid neural network prediction model more accurately; and uses the trained hybrid neural network prediction model to predict the dissolved oxygen concentration at several time points at the end of the process after biochemical treatment, which can obtain more accurate prediction results; the analysis unit uses the variance of the predicted dissolved oxygen concentration at multiple time points to determine the monitoring status, and adjusts the equipment operation parameters and sludge return ratio multiple times based on the monitoring status, so as to accurately predict the abnormal situation of the core stage of wastewater treatment, namely the biochemical treatment stage, and make corresponding adjustments, thereby improving the efficiency of wastewater treatment.

[0017] Furthermore, this invention analyzes the nitrate nitrogen content by assessing the dissolved oxygen concentration and adjusts the inverter's output frequency based on the nitrate nitrogen content. This allows for more accurate adjustment of the inverter's output frequency, which in turn adjusts the aeration intensity by adjusting the fan speed, thus overcoming oxygen limitations and restarting nitrifying bacteria activity. This further improves the efficiency of wastewater treatment in the biological treatment stage.

[0018] Furthermore, by adjusting the opening degree of the branch pipe electric valve during sewage treatment based on the output frequency of the frequency converter, the present invention can increase the fan speed to open the branch pipe electric valve more, thereby reducing pipeline resistance and further improving the efficiency of sewage treatment by improving the efficiency of the biochemical treatment stage.

[0019] Furthermore, this invention adjusts the dosage of Nitrosomonas inoculant based on the integral of the nitrate nitrogen content-time curve. By more precisely dispensing the Nitrosomonas inoculant, the nitrification system can be quickly rebuilt, allowing wastewater treatment to return to normal, thereby further improving the efficiency of wastewater treatment.

[0020] Furthermore, this invention achieves a qualified monitoring status by repeatedly adjusting the above parameters sequentially. If the status is still unqualified, the sludge return ratio is adjusted. Due to the enhanced nitrification after adding the bacterial agent, the nitrate load in the anoxic tank increases. If the carbon source for denitrification is insufficient, adjusting the sludge return ratio more accurately can reduce the return of nitrate to the anaerobic section, alleviate the inhibition of polyphosphate-accumulating bacteria, and thus further improve the efficiency of wastewater treatment in the biological treatment stage.

[0021] Furthermore, this invention sets up several monitoring points along the length of the aeration tank when the monitoring state is in the second state, and adjusts the aeration frequency based on the difference in dissolved oxygen concentration between two adjacent monitoring points. This can break the vicious cycle of "excessive oxygen supply - inhibition of microbial activity - further decline in oxygen consumption capacity" by reducing the aeration frequency, thereby further improving the efficiency of wastewater treatment.

[0022] Furthermore, this invention adjusts the aeration frequency and the distance between monitoring points by using the difference in dissolved oxygen concentration between two adjacent monitoring points, which can more accurately adjust the aeration frequency and the distance between monitoring points, thereby further improving the efficiency of wastewater treatment.

[0023] Furthermore, the present invention adjusts the sampling time interval based on the distance of the monitoring point, which can more accurately adjust the sampling time interval, thereby improving the efficiency of sewage treatment through more effective sampling. Attached Figure Description

[0024] Figure 1 This is a schematic diagram of the wastewater treatment process monitoring and early warning system in an embodiment of the present invention; Figure 2 This is a flowchart illustrating the steps of the wastewater treatment process monitoring and early warning method in an embodiment of the present invention. Figure 3 This is a flowchart illustrating the steps of determining the monitoring status as the first state based on the comparison result between the variance and a pre-stored preset variance in an embodiment of the present invention. Figure 4 This is a flowchart illustrating the steps of determining the monitoring status as the second state based on the comparison result between the variance and a pre-stored preset variance in an embodiment of the present invention. Detailed Implementation

[0025] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0026] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0027] It should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0028] Please see Figure 1 As shown, it is a schematic diagram of the wastewater treatment process monitoring and early warning system in an embodiment of the present invention.

[0029] The system includes a parameter acquisition unit, a device operation data acquisition unit, a prediction unit, an analysis unit, and an adjustment unit.

[0030] The parameter acquisition unit is used to periodically monitor several characterization parameters, including dissolved oxygen concentration and nitrate nitrogen content, in the distributed sensor network deployed during the biochemical treatment stage of wastewater treatment. The equipment operation data acquisition unit is used to integrate the PLC control system to acquire equipment operation data, including the output frequency of the frequency converter, the opening degree of the branch pipe electric valve, the sludge return ratio and the aeration frequency. The prediction unit is connected to the parameter acquisition unit. It is used to train a hybrid neural network prediction model based on the acquired historical time-based characterization parameters, and to predict the dissolved oxygen concentration at several time nodes at the end-of-process monitoring points after biochemical treatment within a preset time period based on the hybrid neural network prediction model, thereby obtaining several predicted dissolved oxygen concentrations. The analysis unit is connected to the prediction unit and the equipment operation data acquisition module respectively. It is used to determine the monitoring status based on the variance of the predicted dissolved oxygen concentration at multiple time nodes predicted by the prediction unit within a preset time period, and to adjust the equipment operation data multiple times based on the monitoring status and the data acquired by the equipment operation data acquisition module, as well as to adjust the sludge return ratio. The adjustment unit is connected to the analysis unit and is used to adjust the corresponding parameters based on a determined monitoring status.

[0031] Specifically, the power drive link for wastewater treatment is a frequency converter directly connected to the blower motor via a cable. The blower speed is controlled by adjusting the output frequency. After the blower outlet is purified by the air filter, compressed air is delivered to the aerator at the bottom of the aeration tank through a pipeline of a predetermined material, releasing tiny bubbles to achieve oxygen transfer. The main pipeline branches into multiple branches, each equipped with an electric regulating valve. The air volume distribution in each aeration tank zone is controlled by the valve opening.

[0032] Specifically, as the core equipment in the biochemical treatment stage, the aeration tank needs to maintain a specific dissolved oxygen concentration to meet the metabolic needs of microorganisms. First, the total air source is provided by the blower in the sewage treatment process, and the frequency converter controls the total air output by adjusting the blower speed. Second, the opening of each aeration branch is dynamically adjusted by the branch pipe electric valve according to the dissolved oxygen monitoring value of each zone to achieve balanced air distribution in the aeration tank.

[0033] Specifically, the preset time period is set to 12 hours, and the monitoring is performed every 0.5 hours.

[0034] Specifically, the hybrid neural network prediction model employs a CNN-LSTM hybrid architecture, achieving high-precision prediction of dissolved oxygen concentration through multimodal feature fusion. The data preprocessing layer fuses input data into a multidimensional tensor and generates temporal samples using a sliding window, preserving dynamic features. Finally, conventional data processing methods, such as normalization and missing data handling, are used to complete data preprocessing. The model's main architecture consists of a CNN branch and an LSTM branch. The CNN branch uses 1D convolutional layers to extract spatial features of process parameters, while the LSTM branch uses a bidirectional LSTM to capture temporal dependencies and incorporates an attention mechanism to focus on key time periods. By concatenating the abstract features from the CNN with the temporal features from the LSTM, 1×1 convolutional dimensionality reduction is achieved, and finally, the data is mapped to the predicted dissolved oxygen concentration value through a fully connected network. During training, adjustments to the loss function, learning rate, and the implementation of an early stopping mechanism enable the hybrid neural network prediction model to output more accurate predictions. Please see Figure 2 As shown, it is a flowchart of the steps of the wastewater treatment process monitoring and early warning method in an embodiment of the present invention.

[0035] The steps for monitoring and early warning during the wastewater treatment process are as follows: S1, through the parameter acquisition unit, a distributed sensor network deployed in the biochemical treatment stage of wastewater treatment periodically monitors several characterization parameters, including dissolved oxygen concentration and nitrate nitrogen content; S2 acquires equipment operation data through the integrated PLC control system in the equipment operation data acquisition unit, including the output frequency of the frequency converter, the opening degree of the branch pipe electric valve, the sludge return ratio, and the aeration frequency. S3, the prediction unit connected to the parameter acquisition unit trains a hybrid neural network prediction model based on the acquired historical time characteristics parameters, and predicts the dissolved oxygen concentration at several time nodes at the end monitoring points of the process after biochemical treatment within a preset time period based on the hybrid neural network prediction model, thereby obtaining several predicted dissolved oxygen concentrations. S4, the analysis unit, which is connected to the prediction unit and the equipment operation data acquisition module respectively, determines the monitoring status based on the variance of the predicted dissolved oxygen concentration at multiple time nodes predicted by the prediction unit within a preset time period, and adjusts the equipment operation data multiple times based on the monitoring status and the data acquired by the equipment operation data acquisition module, and adjusts the sludge return ratio. S5, the corresponding parameters are adjusted by the adjustment unit connected to the analysis unit based on the determined monitoring status.

[0036] Please see Figure 3The diagram shows the steps of determining the monitoring state as the first state based on the comparison result between the variance and a pre-stored preset variance in an embodiment of the present invention. The analysis unit in this embodiment is further used to calculate the average value of the predicted dissolved oxygen concentration within a preset time period. The calculation process is performed when the monitoring state is determined to be the first state, where the variance is greater than or equal to a first preset variance. The adjustment unit is further used to increase the output frequency of the inverter based on the difference between the first preset dissolved oxygen concentration and the predicted dissolved oxygen concentration, and the increase in output frequency is proportional to the difference. Adjustment is performed when the average value is determined to be outside the preset range and the nitrate nitrogen content is greater than a preset content.

[0037] Specifically, the variance L0 can be divided into a first preset variance L1 and a second preset variance L2. The first preset variance L1 is set to 0.24, and the second preset variance L2 is set to 0.15. It should be noted that in other embodiments, the values ​​of L1 and L2 can also be determined according to the needs of wastewater treatment. The comparison process between variance L and L1 and L2 is as follows: If the variance L is greater than or equal to the first preset variance L1, it indicates that the dissolved oxygen concentration fluctuates greatly within the preset time period, and the monitoring state is determined as the first state. If the variance L is less than the first preset variance L1 and greater than the second preset variance L2, it indicates that the dissolved oxygen concentration fluctuates greatly during this period, and the monitoring state is determined as the second state. If the variance L is less than or equal to the second preset variance L2, it indicates that the fluctuation of dissolved oxygen concentration is relatively gentle during this period, and the monitoring status is determined to be qualified.

[0038] Specifically, when the monitoring status is in the first state, the average dissolved oxygen concentration at multiple time points within a preset time period is calculated, and it is determined whether the average value is within a preset range. The preset range is a dissolved oxygen concentration between 1.5 mg / L and 4 mg / L. If the average value is less than 1.5 mg / L, it indicates that the dissolved oxygen concentration fluctuates drastically and is severely exceeding the standard, requiring determination of the cause based on the nitrate nitrogen content.

[0039] Specifically, taking the aerobic end of the traditional activated sludge process as an example, when the nitrate nitrogen content is consistently greater than 15-20 mg / L, it indicates that the aerobic bacteria are hypoxic and the nitrification reaction is stagnant. Based on the increased accumulation of nitrate nitrogen, the carbon consumption of denitrification increases, resulting in a decrease in the rate of organic matter degradation. Therefore, the aeration intensity can be adjusted by adjusting the fan speed to overcome the oxygen limitation and restart the activity of nitrifying bacteria. In this embodiment, the fan speed is adjusted by adjusting the output frequency of the frequency converter.

[0040] Specifically, if the preset difference between the first preset dissolved oxygen concentration and the predicted dissolved oxygen concentration is Q0 = 0.2 mg / L, then the comparison process based on the difference Q and the preset difference Q0 is as follows: If the difference Q is less than or equal to the preset difference Q0, the output frequency of the inverter will be adjusted to 1.2 times the original output frequency. If the difference Q is greater than the preset difference Q0, the output frequency of the inverter will be adjusted to 1.5 times the original output frequency.

[0041] Specifically, after adjusting the inverter's output frequency, i.e., increasing the fan speed, the branch pipe electric valve needs to be opened wider to reduce pipeline resistance. The inverter's preset output frequency is R0 = 50Hz. The comparison process between the current output frequency and the preset output frequency is as follows: If the output frequency R of the inverter is less than or equal to the preset output frequency R0, then the opening degree of the branch electric valve will be adjusted to 1.4 times the original opening degree. If the output frequency R of the inverter is greater than the preset output frequency R0, the opening degree of the branch electric valve will be adjusted to 1.7 times the original opening degree.

[0042] Specifically, the analysis unit described in this embodiment of the invention is further used to calculate the integral of the plotted nitrate nitrogen content-time node curve; the adjustment unit is further used to adjust the dosage of Nitrosomonas inoculant based on the ratio of the integral to the preset integral; wherein, after a preset time, the monitoring state and nitrate nitrogen content are re-determined, and the curve is plotted when the monitoring state is the first state and the nitrate nitrogen content is greater than the preset content.

[0043] Specifically, after a preset time, the system is re-tested. If the monitoring status is still in the first state and the nitrate nitrogen content is still greater than the preset content, a nitrate nitrogen content-time curve is plotted, and the integral of the curve is calculated. Based on the ratio of the integral to the preset integral, the dosage of Nitrosomonas inoculant is adjusted. By adding Nitrosomonas inoculant, the nitrification system is quickly rebuilt, and the wastewater treatment is restored to a normal state. The Nitrosomonas inoculant is set with a preset dosage in real time according to the current water quality threshold before any abnormality occurs in the wastewater treatment, so that it can be added in time when an abnormality occurs.

[0044] Specifically, if the preset ratio T0 of the line integral to the preset integral is 0.85, then the comparison process based on the ratio T and the preset ratio T0 is as follows: If the ratio T is less than or equal to the preset ratio T0, the dosage of Nitrosomonas inoculant will be adjusted to 1.2 times the original preset dosage. If the ratio T is greater than the preset ratio T0, the dosage of Nitrosomonas inoculant will be adjusted to 1.5 times the original preset dosage.

[0045] Specifically, in this embodiment of the invention, the adjustment unit repeatedly adjusts the output frequency of the inverter, the opening degree of the branch pipe electric valve, and the dosage of Nitrosomonas inoculant at least once. The adjustment is stopped when the number of adjustments equals or is less than a preset number, and the monitoring status is qualified. The analysis unit reduces the sludge return ratio based on the dosage of Nitrosomonas inoculant, and the reduction in the sludge return ratio is proportional to the dosage. Adjustment is performed when the monitoring status is the first state after the adjustment is stopped and the nitrate nitrogen content is greater than the preset content.

[0046] Specifically, after a preset time, the current monitoring status is rechecked. If the monitoring status is still in the first state and the nitrate nitrogen content is still greater than the preset content, the output frequency of the inverter, the opening degree of the branch pipe electric valve, and the dosage of Nitrosomonas inoculant are adjusted sequentially at least once until the number of adjustments equals the preset number or the number of adjustments is less than the preset number, at which point the monitoring status is qualified, and the adjustment of the above parameters is stopped.

[0047] Specifically, if the monitoring status remains in the first state and the nitrate nitrogen content is still greater than the preset content after adjustment is stopped, it indicates that nitrification is enhanced after adding the bacterial agent, leading to an increase in nitrate load in the anoxic tank. If the denitrification carbon source is insufficient, the sludge return ratio needs to be reduced to decrease nitrate return to the anaerobic zone and alleviate polyphosphate accumulation inhibition. Therefore, the sludge return ratio is adjusted based on the dosage of Nitrosomonas bacterial agent. The preset dosage of Nitrosomonas bacterial agent is U0 = 300L. The comparison process between the dosage U and the preset dosage U0 is as follows: If the dosage U is less than or equal to the preset dosage U0, the sludge return ratio will be adjusted to 0.9 times the original sludge return ratio. If the dosage U is greater than the preset dosage U0, the sludge return ratio will be adjusted to 0.71 times the original sludge return ratio.

[0048] Please see Figure 4 The diagram shows the steps of determining the monitoring state as the second state based on the comparison result between the variance and a pre-stored preset variance in an embodiment of the present invention. The analysis unit in this embodiment is further configured to set several monitoring points along the length of the aeration tank, and to calculate the difference in dissolved oxygen concentration between two adjacent monitoring points. The operation is performed when the monitoring state is determined to be the second state based on the variance of the dissolved oxygen concentration, and the average dissolved oxygen concentration within a preset time period is within a preset range. The second state is defined as a variance less than a first preset variance and greater than a second preset variance. The adjustment unit is further configured to adjust the aeration frequency based on the difference.

[0049] Specifically, since the variance of dissolved oxygen concentration is large at this time, but the average value of dissolved oxygen concentration is within the preset range, it means that the dissolved oxygen concentration varies around the maximum value of the preset range. At this time, several monitoring points are set along the length of the aeration tank, and the difference in dissolved oxygen concentration between two connected monitoring points is calculated. Since the oxygen consumption rate of microorganisms is limited by the substrate concentration, the oxygen mass transfer efficiency decreases during the high dissolved oxygen period, and excess oxygen escapes in the form of bubbles, resulting in energy waste. Therefore, by reducing the aeration frequency based on the difference, the vicious cycle of "excessive oxygen supply - inhibition of microbial activity - further decline in oxygen consumption capacity" can be broken.

[0050] Specifically, if the preset difference in dissolved oxygen concentration between two connected monitoring points is V0 = 0.1 mg / L, then the comparison process based on the difference V and the preset difference V0 is as follows: If the difference V is greater than the preset difference V0, the preset ratio W0 between the difference and the preset difference is set to 1.2. If the ratio W is less than or equal to the preset ratio W0, the aeration frequency is adjusted to 0.94 times the original aeration frequency; if the ratio W is greater than the preset ratio W0, the aeration frequency is adjusted to 0.81 times the original aeration frequency. If the difference V is less than or equal to the preset difference V0, the preset ratio M0 between the difference and the preset difference is set to 0.86. If the ratio M is less than or equal to the preset ratio M0, the distance of the monitoring point is adjusted to 1.9 times the original distance; if the ratio M is greater than the preset ratio M0, the distance of the monitoring point is adjusted to 1.2 times the original distance.

[0051] Specifically, by adjusting the distance between monitoring points and reducing the sampling time interval based on the distance between the monitoring points, abnormalities in wastewater treatment can be detected more promptly. Taking a large-scale aeration tank as an example, excluding the three monitoring points at the front, middle, and end of the aeration tank, the preset distance N0 for the remaining monitoring points is 55m. The comparison process between distance N and the preset distance N0 is as follows: If the distance N is less than or equal to the preset distance N0, the sampling time interval will be adjusted to 0.95 times the original time interval; If the distance N is greater than the preset distance N0, the sampling time interval will be adjusted to 0.89 times the original time interval.

[0052] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

[0053] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A wastewater treatment process monitoring and early warning system, characterized in that, include: The parameter acquisition unit is used to periodically monitor several characterization parameters, including dissolved oxygen concentration and nitrate nitrogen content, in the biochemical treatment stage of wastewater treatment via a distributed sensor network. The equipment operation data acquisition unit is used to integrate the PLC control system to acquire equipment operation data, including the output frequency of the frequency converter, the opening degree of the branch pipe electric valve, the sludge return ratio and the aeration frequency. The prediction unit, which is connected to the parameter acquisition unit, is used to train a hybrid neural network prediction model based on the acquired historical time-time characterization parameters, and to predict the dissolved oxygen concentration at several time nodes at the end-of-process monitoring points after biochemical treatment within a preset time period based on the hybrid neural network prediction model, thereby obtaining several predicted dissolved oxygen concentrations. An analysis unit, which is connected to the prediction unit and the equipment operation data acquisition module respectively, is used to determine the monitoring status based on the variance of the predicted dissolved oxygen concentration at multiple time nodes predicted by the prediction unit within a preset time period, and to adjust the equipment operation data multiple times based on the monitoring status and the data acquired by the equipment operation data acquisition module, as well as to adjust the sludge return ratio. An adjustment unit, connected to the analysis unit, is used to adjust the corresponding parameters based on a determined monitoring status.

2. The wastewater treatment process monitoring and early warning system according to claim 1, characterized in that, The analysis unit is also used to calculate the average value of the predicted dissolved oxygen concentration within a preset time period, wherein the calculation process is performed when the monitoring state is determined to be a first state, and the first state is when the variance is greater than or equal to a first preset variance. The adjustment unit is also used to increase the output frequency of the inverter based on the difference between the first preset dissolved oxygen concentration and the predicted dissolved oxygen concentration, and the increase in output frequency is proportional to the difference. The adjustment is performed when the average value is not within the preset range and the nitrate nitrogen content is greater than the preset content.

3. The wastewater treatment process monitoring and early warning system according to claim 2, characterized in that, The regulating unit increases the opening degree of the branch pipe electric valve during sewage treatment based on the output frequency of the frequency converter, and the increase in the opening degree of the branch pipe electric valve is proportional to the output frequency of the frequency converter.

4. The wastewater treatment process monitoring and early warning system according to claim 3, characterized in that, The analysis unit is also used to calculate the integral of the plotted nitrate nitrogen content-time node curve; The adjustment unit is also used to adjust the dosage of Nitrosomonas inoculant based on the ratio of the integral to the preset integral. Specifically, after a preset time, the monitoring status and nitrate nitrogen content are redefined, and a curve is plotted when the monitoring status is the first state and the nitrate nitrogen content is greater than the preset content.

5. The wastewater treatment process monitoring and early warning system according to claim 4, characterized in that, The adjustment unit is also used to increase the amount of Nitrosomonas inoculant based on the ratio of the integral to the preset integral, and the increase in the amount of Nitrosomonas inoculant is proportional to the ratio.

6. The wastewater treatment process monitoring and early warning system according to claim 5, characterized in that, The adjustment unit repeatedly adjusts the output frequency of the inverter, the opening degree of the branch electric valve, and the dosage of Nitrosomonas bacteria agent at least once. The adjustment is stopped when the number of adjustments equals the preset number or the number of adjustments is less than the preset number, and the monitoring status is qualified. The analysis unit reduces the sludge return ratio based on the dosage of Nitrosomonas inoculant, and the reduction in the sludge return ratio is proportional to the dosage. Adjustment is performed when the monitored state is the first state after the adjustment is stopped and the nitrate nitrogen content is greater than the preset content.

7. The wastewater treatment process monitoring and early warning system according to claim 1, characterized in that, The analysis unit is also used to set up several monitoring points along the length of the aeration tank, and to calculate the difference in dissolved oxygen concentration between two adjacent monitoring points. The operation is performed when the monitoring state is determined to be the second state based on the variance of the dissolved oxygen concentration and the average value of the dissolved oxygen concentration within the preset time period is within the preset range. The second state is when the variance is less than the first preset variance and greater than the second preset variance. The adjustment unit is also used to adjust the aeration frequency based on the difference.

8. The wastewater treatment process monitoring and early warning system according to claim 7, characterized in that, The adjustment unit is also used to reduce the aeration frequency based on the ratio of the difference to the preset difference, and the reduction in aeration frequency is proportional to the number of aeration points. The adjustment is made when the difference in dissolved oxygen concentration between two adjacent monitoring points is greater than the preset difference. The adjustment unit is also used to increase the distance between monitoring points based on the ratio of the difference to a preset difference, and the increase in the distance between monitoring points is inversely proportional to the ratio. The adjustment is performed when the difference in dissolved oxygen concentration between two adjacent monitoring points is less than the preset difference.

9. The wastewater treatment process monitoring and early warning system according to claim 8, characterized in that, The adjustment unit is also used to reduce the sampling time interval based on the distance between monitoring points, and the sampling time interval is proportional to the distance.

10. A method for monitoring and early warning of wastewater treatment processes, characterized in that, include: A distributed sensor network deployed in the biochemical treatment stage of wastewater treatment periodically monitors several characterization parameters, including dissolved oxygen concentration and nitrate nitrogen content. The integrated PLC control system acquires equipment operation data, including the output frequency of the frequency converter, the opening degree of the branch pipe electric valve, the sludge return ratio, and the aeration frequency. Based on the acquired historical time-time characterization parameters, a hybrid neural network prediction model is trained, and based on the hybrid neural network prediction model, the dissolved oxygen concentration at several time nodes of the process end monitoring points after biochemical treatment within a preset time period is predicted, thus obtaining several predicted dissolved oxygen concentrations. The monitoring status is determined based on the variance of the predicted dissolved oxygen concentration at multiple time nodes predicted by the prediction unit within a preset time period. Based on the monitoring status and the data obtained by the equipment operation data acquisition module, the equipment operation data is adjusted multiple times, and the sludge return ratio is adjusted. The corresponding parameters are adjusted based on the determined monitoring status.

Images