A multi-dimensional monitoring system and method for medical wastewater treatment

Abstract

The present application relates to medical waste water treatment technical field, disclose a kind of medical waste water treatment multidirectional monitoring system and method, including following module: pretreatment module, the use state and service life of grid in grid filtration process are monitored and controlled, biological treatment module, medical waste water is biologically treated by biological conversion technology, sensing monitoring module, data processing module, supplementary treatment module, abnormal feedback module.The present application can still guide the wastewater that a small amount of overproof data exists in single processing process into make-up pool by the supplementary treatment module established, and detect the abnormal data content in it by sensing equipment, and according to specific detection data, carry out make-up purification pertinently, and in the process of make-up purification in make-up pool, biological treatment module and pretreatment module can still maintain normal operating state, to avoid subsequent wastewater accumulation and affect the overall processing efficiency of medical waste water.

Description

Technical Field

[0001] This invention relates to the field of medical wastewater treatment technology, specifically to a multi-directional monitoring system and method for medical wastewater treatment. Background Technology

[0002] Medical wastewater refers to wastewater containing various harmful substances and pathogens generated by medical institutions, including hospitals, clinics, and laboratories. This wastewater mainly comes from the diagnosis, surgery, and laboratory testing processes in medical activities and contains various drug residues, bacteria, viruses, cell culture media, radioactive substances, and chemical reagents.

[0003] In the current medical wastewater treatment process, complete sets of medical wastewater treatment equipment are often used to purify the medical wastewater, thereby reducing pollution caused by leakage or excessive contact with the external environment during the treatment process.

[0004] However, in actual use, if the water quality discharged after a single medical wastewater treatment process still does not meet the discharge standards, it is often necessary to recycle it to the medical wastewater treatment device for secondary purification. This results in subsequent wastewater not being purified in a timely manner and greatly increases the time consumed in the medical wastewater purification process. In view of this, we propose a multi-dimensional monitoring system and method for medical wastewater treatment. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a multi-dimensional monitoring system and method for medical wastewater treatment, which solves the problem that the existing technology requires a relatively long time to recycle the medical wastewater purification process when the single purification is incomplete.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a multi-directional monitoring system and method for medical wastewater treatment, comprising the following modules:

[0007] The pretreatment module monitors and controls the usage status and service life of the bar screen during the bar filtration process, and automatically adds a certain proportion of chemicals according to the influent volume. At the same time, it digitally displays the sedimentation time of the sedimentation tank through the pulse count.

[0008] The biological treatment module treats medical wastewater by controlling microbial transformation, gas introduction, and membrane treatment capacity. At the same time, water samples are periodically extracted using water sampling equipment to detect microbial content.

[0009] The sensing and monitoring module is used to monitor various parameters in medical wastewater through different types of sensor devices, including pH value, turbidity, dissolved oxygen content, temperature, ammonia nitrogen, and total phosphorus.

[0010] The data processing module processes, analyzes, and stores the collected data, and uses algorithms to identify water quality anomalies and predict the water quality trend after treatment.

[0011] The supplementary treatment module adjusts the pretreatment and biological treatment modules to perform supplementary treatment in response to water quality anomalies reported by the data processing module. In addition, when supplementary treatment occurs multiple times, the processing flow of the pretreatment and biological treatment modules is optimized.

[0012] The anomaly feedback module summarizes the abnormal data that still exists after processing by the supplementary processing module and the abnormal status reported by the data processing module, and reports it to the corresponding control terminal.

[0013] Preferably, the pretreatment module is mainly used for preliminary treatment of the medical wastewater to be treated, and includes the following modules:

[0014] The bar screen filter module removes large solid particles from medical wastewater by controlling the bar screen filter device and monitors the bar screen's usage status and duration. When the bar screen usage reaches the preset value, it automatically activates the backup bar screen and lifts the original bar screen to wait for replacement.

[0015] The chemical dosing module automatically adds appropriate amounts of chemical agents, including neutralizers and coagulants, to remove harmful substances from medical wastewater based on its water quality.

[0016] The pretreatment monitoring module monitors various parameters inside the sedimentation tank in real time during the pretreatment process, including the usage status of the bar screen, the cumulative usage time of the sedimentation tank, the current sedimentation time, and the amount of chemical solution added, to ensure that the pretreatment effect reaches the optimal state.

[0017] The effluent regulation module is used to regulate the flow rate and water quality of medical wastewater discharged into the biological treatment module, so as to maintain the stable operation of the biological treatment module.

[0018] Preferably, the biological treatment module is mainly used to remove organic pollutants from medical wastewater through microbial action, and includes the following modules:

[0019] The activated sludge module uses microorganisms in the activated sludge to biodegrade organic matter in medical wastewater, converting organic matter into inorganic matter, while controlling the stirring device to start and turn the activated sludge at regular intervals.

[0020] The aeration module controls the air pump to introduce oxygen into the activated sludge, ensuring the normal growth and metabolic activities of microorganisms, while promoting the suspension and mixing of the sludge.

[0021] The biofilm module uses microorganisms in a biofilm reactor to biologically treat medical wastewater. The microorganisms on the biofilm can form a stable ecosystem, improving the efficiency of medical wastewater treatment.

[0022] The biological treatment monitoring module monitors various parameters in the biological treatment process in real time, including the concentration of activated sludge, aeration rate, and biofilm growth, to ensure that the biological treatment effect reaches the optimal state. At the same time, water samples are periodically extracted through water sampling equipment to test the microbial content in order to evaluate the effectiveness of the biological treatment.

[0023] Preferably, the sensing and monitoring module is used to control multiple sets of sensing devices to monitor the parameters of medical wastewater during the treatment process in real time, and includes the following modules:

[0024] The pH sensor module is used to monitor the acidity and alkalinity of medical wastewater in real time to ensure a suitable acid-base environment for the medical wastewater during the biological treatment process.

[0025] The turbidity sensor module is used to monitor the turbidity of medical wastewater in real time, that is, the content of suspended particulate matter in medical wastewater, in order to evaluate the effectiveness of medical wastewater treatment.

[0026] The dissolved oxygen sensor module is used to monitor the dissolved oxygen content in medical wastewater in real time to ensure the normal growth and metabolic activities of microorganisms during the biological treatment process.

[0027] A temperature sensor module is used to monitor the temperature of medical wastewater in real time to assess the microbial activity during the biological treatment process;

[0028] The ammonia nitrogen and phosphorus sensor module is used to monitor the ammonia nitrogen and phosphorus content in medical wastewater in real time to evaluate the removal effect of nitrogen and phosphorus elements in medical wastewater.

[0029] The sensor data aggregation module aggregates the data collected by each sensor module and uploads it to the data processing module for analysis and storage via the data transmission interface.

[0030] Preferably, the data processing module is used to receive and analyze real-time data uploaded by the sensor monitoring module, and includes the following modules:

[0031] The data receiving module is used to receive real-time data uploaded by the sensing and monitoring module, and to perform signal filtering and signal standardization processing on the transmitted data.

[0032] The data analysis module processes and analyzes the received real-time data, including calculating the average, standard deviation, and rate of change statistics, to evaluate the effectiveness of medical wastewater treatment.

[0033] The anomaly detection module uses a preset anomaly detection algorithm to detect anomalies in the analyzed data and identify water quality anomalies.

[0034] The trend prediction module uses prediction algorithms based on historical and real-time data to predict the trend of water quality after treatment, providing a basis for optimizing the treatment process.

[0035] The data processing results output module displays the processing and analysis results through a user interface or control terminal for operators to refer to and make decisions.

[0036] Preferably, the supplementary processing module is used to supplement the water quality anomalies reported by the data processing module, and includes the following modules:

[0037] The supplementary processing judgment module determines whether a supplementary processing procedure needs to be initiated based on the result of the anomaly judgment module.

[0038] The pretreatment supplementary processing module, when continuous supplementary processing is required, provides feedback to the grid filter module, the liquid dosing module and the pretreatment monitoring module in the pretreatment module to optimize the pretreatment effect;

[0039] The biological treatment supplementary treatment module, when continuous supplementary treatment is needed, feeds back to the activated sludge module, aeration module, biofilm module and biological treatment monitoring module in the biological treatment module to optimize the biological treatment effect;

[0040] The supplementary processing record module records detailed information for each supplementary processing step, including processing time, reason, process, and result, providing a basis for subsequent optimization of the processing flow.

[0041] The process optimization module analyzes the causes and proposes optimization suggestions based on the repeated occurrence of supplementary treatment, thereby optimizing the treatment processes of the pretreatment and biological treatment modules and improving the treatment effect of medical wastewater.

[0042] Preferably, the anomaly feedback module is used to summarize and report anomaly data and processing status, and includes the following modules:

[0043] The abnormal data aggregation module aggregates the abnormal data identified by the sensing and monitoring module and the abnormal status reported by the data processing module.

[0044] The anomaly report generation module generates anomaly reports based on the summarized anomaly data and handling status, including the cause of the anomaly, the scope of impact, and handling suggestions. The generated anomaly reports are then submitted to relevant management departments or technical personnel via email, SMS, or remote control terminal to facilitate timely handling and resolution of problems.

[0045] The exception handling tracking module tracks the process and results of exception handling to ensure that exceptions are properly handled and resolved.

[0046] The exception handling feedback module summarizes the results and feedback of exception handling, providing a basis for subsequent optimization of the processing flow and improvement of processing effectiveness.

[0047] A method for multi-dimensional monitoring of medical wastewater treatment includes the following steps:

[0048] S1: Medical wastewater pretreatment

[0049] The pretreatment module performs preliminary treatment on medical wastewater, including steps such as grid filtration, chemical dosing, and pH adjustment, to remove large particles and adjust the pH in the medical wastewater, preparing it for subsequent biological treatment processes.

[0050] S2: Biological treatment and purification

[0051] The pretreated medical wastewater is introduced into the biological treatment module, where organic pollutants and nutrients are removed through biological treatment methods including activated sludge, aeration, and biofilm, thereby achieving the purpose of medical wastewater treatment.

[0052] S3: Real-time Data Monitoring

[0053] During the biological treatment process, various parameters of medical wastewater, including pH value, turbidity, dissolved oxygen, temperature, ammonia nitrogen, and phosphorus, are monitored in real time through a sensor monitoring module to ensure the stability and effectiveness of the biological treatment process.

[0054] S4: Data Analysis and Judgment

[0055] The real-time data collected by the sensor monitoring module is transmitted to the data processing module. Through steps including data reception, analysis, anomaly detection, and trend prediction, the treatment effect of medical wastewater is evaluated and predicted, providing a basis for subsequent supplementary treatment.

[0056] S5: Targeted supplementary treatment

[0057] Based on the abnormal water quality reported in the data processing module, targeted supplementary treatment is carried out through the supplementary treatment module, including optimizing the pretreatment and biological treatment processes to improve the treatment effect of medical wastewater.

[0058] S6: Summary of Abnormal Data

[0059] The abnormal data and processing status are summarized and reported to the abnormal feedback module, an abnormal report is generated and reported to the relevant management department or technical personnel so that the problem can be handled and resolved in a timely manner.

[0060] S7: Self-optimizing purification process

[0061] Based on the repeated occurrence of supplementary treatment, the causes were analyzed through the treatment process optimization module, and optimization suggestions were proposed for managers to choose from. The treatment processes of the pretreatment module and the biological treatment module were optimized to improve the treatment effect of medical wastewater.

[0062] Preferably, the real-time data monitoring in S3 is mainly used for multi-dimensional monitoring of medical wastewater during the treatment process, including the following steps:

[0063] S301: Real-time monitoring started

[0064] Before starting the biological treatment process, the sensing and monitoring module is activated to ensure that all sensor modules are in normal working order and ready for real-time data monitoring.

[0065] S302: Data Acquisition and Transmission

[0066] The system uses multiple sensor modules, including pH, turbidity, dissolved oxygen, temperature, ammonia nitrogen, and phosphorus sensors, to collect various parameters of medical wastewater in real time. The data is then transmitted to the data processing module for analysis and storage via a data transmission interface.

[0067] S303: Multi-directional data acquisition

[0068] The internal substance content of the same batch of medical wastewater is recorded by the sensing devices inside the inlet, sedimentation tank and drainage pipe, and a corresponding material change line graph is generated. The processing capacity of the medical wastewater treatment system is fed back through the image data of the line graph.

[0069] S304: Real-time Data Display

[0070] The collected real-time data is displayed through a user interface or control terminal, allowing operators to understand the changes in various parameters during the medical wastewater treatment process and adjust treatment strategies in a timely manner.

[0071] S305: Anomaly Warning and Handling

[0072] During real-time data monitoring, the anomaly detection module performs anomaly detection on the collected data. Once anomaly data is detected, an anomaly warning mechanism is immediately triggered, and a warning message is sent to the operator through the user interface or control terminal to remind the operator to handle the abnormal situation in a timely manner.

[0073] Preferably, the self-optimization of the purification process in S7 is mainly determined by the processing frequency of the targeted supplementary treatment in S5 to determine whether a self-optimization procedure needs to be executed, including the following steps:

[0074] S701: Initial Threshold Setting

[0075] Set a frequency threshold for targeted supplementary processing. When the execution frequency of targeted supplementary processing in S5 exceeds this threshold, it is determined that a self-optimization program needs to be executed.

[0076] S702: Self-optimization analysis program

[0077] Based on historical data and processing records of targeted supplementary treatments in S5, the reasons for frequent supplementary treatments were analyzed, including factors such as poor pretreatment effect and unreasonable parameter settings of biological treatment module.

[0078] S703: Generation of Analysis Results

[0079] Based on the analysis results, targeted optimization suggestions are proposed, including adjusting the dosage of the chemical solution, optimizing aeration parameters, and replacing the activated sludge.

[0080] S704: Optimize continuous monitoring

[0081] The optimization suggestions will be pushed to the management personnel, who will then select and implement them based on the actual situation. After the optimization suggestions are implemented, the treatment effect of medical wastewater will continue to be monitored to observe whether there is any improvement. If necessary, steps S701 to S705 can be repeated to continuously optimize the treatment process.

[0082] This invention provides a multi-directional monitoring system and method for medical wastewater treatment. It has the following beneficial effects:

[0083] 1. The present invention, through the establishment of a supplementary treatment module, can introduce wastewater with a small amount of excessive data in the single treatment process into a replenishment tank, and detect the abnormal data content inside it through a sensor device, and perform targeted replenishment and purification based on the specific detection data. During the replenishment and purification process in the replenishment tank, the biological treatment module and the pretreatment module can still maintain normal operation, thereby avoiding the subsequent accumulation of wastewater and affecting the overall treatment efficiency of medical wastewater.

[0084] 2. The self-optimization algorithm established in this invention can automatically start after the replenishment pool continuously reaches the operating threshold frequency. It generates corresponding detection records based on the sensors distributed inside the replenishment pool, analyzes the causes of multiple abnormal data, and generates corresponding optimization suggestions to the processing terminal based on the analyzed data. This allows managers to confirm the optimization data of the pretreatment module and the biological treatment module based on the feedback data.

[0085] 3. This invention, by installing multiple sets of sensors at the inlet, sedimentation tank, and inside the drain pipe, can analyze and record data on medical wastewater before, during, and after purification in real time, and generate corresponding line graphs showing the changes in the content of different substances in the medical wastewater. The feedback data from these line graphs allows people to understand the purification status of medical wastewater from multiple perspectives, and to evaluate the purification capacity of the medical wastewater purification equipment based on this data. Attached Figure Description

[0086] Figure 1 This is a flowchart of the multi-faceted monitoring system for medical wastewater treatment;

[0087] Figure 2 This is a flowchart of the preprocessing module of the present invention;

[0088] Figure 3 This is a flowchart of the biological treatment module of the present invention;

[0089] Figure 4 This is a flowchart of the sensing and monitoring module of the present invention;

[0090] Figure 5 This is a flowchart of the data processing module of the present invention;

[0091] Figure 6 This is a flowchart of the supplementary processing module of the present invention;

[0092] Figure 7 This is a flowchart of the exception feedback module of the present invention;

[0093] Figure 8 This is a flowchart of a multi-faceted monitoring method for medical wastewater treatment;

[0094] Figure 9 This is a flowchart of the method S3 of the present invention;

[0095] Figure 10 This is a flowchart of the method S7 of the present invention. Detailed Implementation

[0096] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0097] Please see the appendix Figure 1 -Appendix Figure 7 This invention provides a multi-directional monitoring system for medical wastewater treatment, comprising the following modules:

[0098] The pretreatment module monitors and controls the usage status and service life of the bar screen during the bar filtration process, and automatically adds a certain proportion of chemicals according to the influent volume. At the same time, it digitally displays the sedimentation time of the sedimentation tank through the pulse count.

[0099] The biological treatment module treats medical wastewater by controlling microbial transformation, gas introduction, and membrane treatment capacity. At the same time, water samples are periodically extracted using water sampling equipment to detect microbial content.

[0100] The sensing and monitoring module is used to monitor various parameters in medical wastewater through different types of sensor devices, including pH value, turbidity, dissolved oxygen content, temperature, ammonia nitrogen, and total phosphorus.

[0101] The data processing module processes, analyzes, and stores the collected data, and uses algorithms to identify water quality anomalies and predict the water quality trend after treatment.

[0102] The supplementary treatment module adjusts the pretreatment and biological treatment modules to perform supplementary treatment in response to water quality anomalies reported by the data processing module. In addition, when supplementary treatment occurs multiple times, the processing flow of the pretreatment and biological treatment modules is optimized.

[0103] The anomaly feedback module summarizes the abnormal data that still exists after processing by the supplementary processing module and the abnormal status reported by the data processing module, and reports it to the corresponding control terminal.

[0104] The pretreatment module is mainly used for the preliminary treatment of the medical wastewater to be treated, and includes the following modules:

[0105] The bar screen filter module removes large solid particles from medical wastewater by controlling the bar screen filter device and monitors the bar screen's usage status and duration. When the bar screen usage reaches the preset value, it automatically activates the backup bar screen and lifts the original bar screen to wait for replacement.

[0106] The chemical dosing module automatically adds appropriate amounts of chemical agents, including neutralizers and coagulants, to remove harmful substances from medical wastewater based on its water quality.

[0107] The pretreatment monitoring module monitors various parameters inside the sedimentation tank in real time during the pretreatment process, including the usage status of the screen, the cumulative usage time of the sedimentation tank, the current sedimentation time, and the dosage of the chemical solution, ensuring that the pretreatment effect reaches the optimal state.

[0108] Firstly, the condition of the bar screen is one of the key factors for the normal operation of the sedimentation tank. The main function of the bar screen is to intercept large particles of impurities, preventing them from entering the sedimentation tank and thus avoiding pipe blockage and affecting the sedimentation effect. Therefore, real-time monitoring of the bar screen's condition is crucial. This can be achieved by installing sensors and a monitoring system. Once the bar screen becomes clogged or damaged, the system will immediately issue an alarm so that timely measures can be taken for cleaning and repair. The system can also maintain the bar screen's interception effectiveness by activating a backup bar screen and raising the current bar screen.

[0109] Secondly, the cumulative usage time and current settling time of the sedimentation tank are also important monitoring parameters. The cumulative usage time can help us understand the aging degree of the sedimentation tank, so as to carry out maintenance and replacement in a timely manner. The current settling time directly affects the settling effect. If the settling time is too short, impurities cannot be fully settled; if the settling time is too long, it will affect production efficiency. Therefore, by monitoring the settling time in real time, we can ensure that the sedimentation tank operates in the best condition.

[0110] In addition, the dosage of the chemical solution is also one of the important parameters in the operation of the sedimentation tank. The amount of chemical solution directly affects the sedimentation effect. If the dosage is insufficient, impurities cannot be effectively removed; if the dosage is excessive, it will be wasteful and may pollute the environment. Therefore, by monitoring the dosage of the chemical solution in real time, the amount of chemical solution added can be precisely controlled, thereby achieving the best sedimentation effect.

[0111] In summary, real-time monitoring of various parameters within the sedimentation tank can ensure optimal pretreatment results, which not only improves production efficiency and reduces production costs but also protects the environment and enhances product quality.

[0112] The effluent regulation module is used to regulate the flow rate and water quality of medical wastewater discharged into the biological treatment module, so as to maintain the stable operation of the biological treatment module.

[0113] The biological treatment module is mainly used to remove organic pollutants from medical wastewater through microbial action, and includes the following modules:

[0114] The activated sludge module uses microorganisms in the activated sludge to biodegrade organic matter in medical wastewater, converting organic matter into inorganic matter, while controlling the stirring device to start and turn the activated sludge at regular intervals.

[0115] The aeration module controls the air pump to introduce oxygen into the activated sludge, ensuring the normal growth and metabolic activities of microorganisms, while promoting the suspension and mixing of the sludge.

[0116] The biofilm module uses microorganisms in a biofilm reactor to biologically treat medical wastewater. The microorganisms on the biofilm can form a stable ecosystem, which improves the efficiency of medical wastewater treatment.

[0117] The biological treatment monitoring module monitors various parameters in the biological treatment process in real time, including the concentration of activated sludge, aeration rate, and biofilm growth, to ensure that the biological treatment effect reaches the optimal state. At the same time, water samples are periodically extracted through water sampling equipment to test the microbial content in order to evaluate the effectiveness of the biological treatment.

[0118] Biological treatment, as a highly efficient and environmentally friendly wastewater treatment method, relies on the core technology of using the metabolic activity of microorganisms to decompose organic matter into harmless substances. Therefore, real-time monitoring of key parameters during the biological treatment process, including activated sludge concentration, aeration rate, and biofilm growth, is an important means to ensure that the biological treatment effect reaches its optimal state.

[0119] The concentration of activated sludge is a crucial parameter in biological treatment processes, directly impacting the removal efficiency of organic matter from wastewater. Real-time monitoring of activated sludge concentration allows for timely adjustments to sludge return flow and excess sludge discharge, maintaining sludge concentration stability and ensuring treatment effectiveness. Furthermore, aeration rate is another key factor in biological treatment. Aeration not only provides oxygen to microorganisms but also mixes them, ensuring thorough contact between the sludge and wastewater. Precise control of aeration rate can prevent decreased treatment efficiency due to insufficient aeration and energy waste caused by excessive aeration.

[0120] In addition to activated sludge concentration and aeration rate, biofilm growth is also an important monitoring target in the biological treatment process. Biofilm is formed by microorganisms attaching to the surface of a carrier. It has high biomass and activity and can effectively degrade organic matter in wastewater. By regularly observing the growth of biofilm, we can understand information such as biofilm thickness, types and quantities of attached microorganisms, and thus judge the effectiveness of biological treatment.

[0121] In order to more accurately evaluate the effectiveness of biological treatment, it is also necessary to regularly extract water samples using water sampling equipment to test the microbial content. Microbial content is one of the important indicators for measuring the effectiveness of biological treatment. It reflects the degree of degradation of organic matter in wastewater and the activity of microorganisms. By detecting the microbial content in water samples, potential problems in the biological treatment process can be identified in a timely manner, including various issues such as reduced microbial activity and decreased treatment efficiency, so that corresponding measures can be taken for adjustment and optimization.

[0122] The sensing and monitoring module is used to control multiple sets of sensing devices to monitor the parameters of medical wastewater during the treatment process in real time, and includes the following modules:

[0123] The pH sensor module is used to monitor the acidity and alkalinity of medical wastewater in real time to ensure a suitable acid-base environment for the medical wastewater during the biological treatment process.

[0124] The turbidity sensor module is used to monitor the turbidity of medical wastewater in real time, that is, the content of suspended particulate matter in medical wastewater, in order to evaluate the effectiveness of medical wastewater treatment.

[0125] The dissolved oxygen sensor module is used to monitor the dissolved oxygen content in medical wastewater in real time to ensure the normal growth and metabolic activities of microorganisms during the biological treatment process.

[0126] A temperature sensor module is used to monitor the temperature of medical wastewater in real time to assess the microbial activity during the biological treatment process;

[0127] The ammonia nitrogen and phosphorus sensor module is used to monitor the ammonia nitrogen and phosphorus content in medical wastewater in real time to evaluate the removal effect of nitrogen and phosphorus elements in medical wastewater.

[0128] The sensor data aggregation module aggregates the data collected by each sensor module and uploads it to the data processing module for analysis and storage via the data transmission interface.

[0129] The data processing module is used to receive and analyze real-time data uploaded by the sensor monitoring module, and includes the following modules:

[0130] The data receiving module is used to receive real-time data uploaded by the sensing and monitoring module, and to perform signal filtering and signal standardization processing on the transmitted data.

[0131] The data analysis module processes and analyzes the received real-time data, including calculating the average, standard deviation, and rate of change statistics, to evaluate the effectiveness of medical wastewater treatment.

[0132] The anomaly detection module uses a preset anomaly detection algorithm to perform anomaly detection on the analyzed data, identifying any anomalies that persist in the water quality even after purification.

[0133] In water quality monitoring and analysis, the application of anomaly detection algorithms has become increasingly important. These algorithms, based on statistical and mathematical models, analyze processed water quality data to identify anomalies that still exist even after purification treatment.

[0134] First, medical wastewater purification is a complex process involving multiple technologies. Although these technologies are very mature, in actual operation, due to various factors, including equipment aging, operational errors, and raw material quality issues, the purified water quality may still be abnormal.

[0135] To promptly detect and address these anomalies, we introduced an anomaly detection algorithm. This algorithm first performs a comprehensive analysis of the purified water quality data, including statistical analysis and comparison of various indicators such as pH, turbidity, and heavy metal content. Then, based on preset thresholds and models, it determines whether these data are normal. If any indicator is found to exceed the normal range, the algorithm marks it as an anomaly and generates a corresponding report.

[0136] In addition to timely detection of anomalies, algorithms can also help us analyze the causes of anomalies. Through in-depth analysis of abnormal data, we can identify the specific factors that cause the anomalies and take corresponding measures to improve them. For example, if an abnormal increase in pH value is found, it may be due to excessive acidity in the water. In this case, we can adjust the amount of chemical reagents used in the purification process to reduce the content of acidity.

[0137] In addition, anomaly detection algorithms can also be used to optimize the water purification process. By analyzing a large amount of data, we can identify bottlenecks and problems in the purification process, thereby improving the purification process and increasing purification efficiency and quality. For example, if we find that a certain chemical agent is not effective in the purification process, we can consider replacing it with other more effective agents.

[0138] The trend prediction module uses prediction algorithms based on historical and real-time data to predict the trend of water quality after treatment, providing a basis for optimizing the treatment process.

[0139] The data processing results output module displays the processing and analysis results through a user interface or control terminal for operators to refer to and make decisions.

[0140] The supplementary processing module is used to supplement the water quality anomalies reported by the data processing module, and includes the following modules:

[0141] The supplementary processing judgment module determines whether a supplementary processing procedure needs to be initiated based on the result of the anomaly judgment module.

[0142] The pretreatment supplementary processing module, when continuous supplementary processing is required, provides feedback to the grid filter module, the liquid dosing module and the pretreatment monitoring module in the pretreatment module to optimize the pretreatment effect;

[0143] The biological treatment supplementary treatment module, when continuous supplementary treatment is needed, feeds back to the activated sludge module, aeration module, biofilm module and biological treatment monitoring module in the biological treatment module to optimize the biological treatment effect;

[0144] This supplementary treatment module controls the operation of each component inside the replenishment tank. When it is determined that the purified medical wastewater still does not meet the discharge standards, it controls the operation of the components inside the replenishment tank and receives the medical wastewater discharged from the biological treatment module. Based on the specific abnormal parameters, it performs supplementary purification treatment. During the replenishment treatment process, the module monitors the water quality changes inside the replenishment tank in real time to ensure the effectiveness of the replenishment treatment. Based on the treatment steps taken in the replenishment treatment, it proposes an optimization scheme for the treatment process of the biological treatment module and the pretreatment module.

[0145] The supplementary processing record module records detailed information for each supplementary processing step, including processing time, reason, process, and result, providing a basis for subsequent optimization of the processing flow.

[0146] The process optimization module analyzes the causes and proposes optimization suggestions based on the repeated occurrence of supplementary treatment, thereby optimizing the treatment processes of the pretreatment and biological treatment modules and improving the treatment effect of medical wastewater.

[0147] The anomaly feedback module is used to summarize and report anomaly data and processing status, and includes the following modules:

[0148] The abnormal data aggregation module aggregates the abnormal data identified by the sensing and monitoring module and the abnormal status reported by the data processing module.

[0149] The anomaly report generation module generates anomaly reports based on the summarized anomaly data and handling status, including the cause of the anomaly, the scope of impact, and handling suggestions. The generated anomaly reports are then submitted to relevant management departments or technical personnel via email, SMS, or remote control terminal to facilitate timely handling and resolution of problems.

[0150] The exception handling tracking module tracks the process and results of exception handling to ensure that exceptions are properly handled and resolved.

[0151] The exception handling feedback module summarizes the results and feedback of exception handling, providing a basis for subsequent optimization of the processing flow and improvement of processing effectiveness.

[0152] Please see the appendix Figure 8 -Appendix Figure 10 A method for multi-dimensional monitoring of medical wastewater treatment, characterized by the following steps:

[0153] S1: Medical wastewater pretreatment

[0154] The pretreatment module performs preliminary treatment on medical wastewater, including steps such as grid filtration, chemical dosing, and pH adjustment, to remove large particles and adjust the pH in the medical wastewater, preparing it for subsequent biological treatment processes.

[0155] S2: Biological treatment and purification

[0156] The pretreated medical wastewater is introduced into the biological treatment module, where organic pollutants and nutrients are removed through biological treatment methods including activated sludge, aeration, and biofilm, thereby achieving the purpose of medical wastewater treatment.

[0157] S3: Real-time Data Monitoring

[0158] During the biological treatment process, various parameters of medical wastewater, including pH value, turbidity, dissolved oxygen, temperature, ammonia nitrogen, and phosphorus, are monitored in real time through a sensor monitoring module to ensure the stability and effectiveness of the biological treatment process.

[0159] S4: Data Analysis and Judgment

[0160] The real-time data collected by the sensor monitoring module is transmitted to the data processing module. Through steps including data reception, analysis, anomaly detection, and trend prediction, the treatment effect of medical wastewater is evaluated and predicted, providing a basis for subsequent supplementary treatment.

[0161] S5: Targeted supplementary treatment

[0162] Based on the abnormal water quality reported in the data processing module, targeted supplementary treatment is carried out through the supplementary treatment module, including optimizing the pretreatment and biological treatment processes to improve the treatment effect of medical wastewater.

[0163] S6: Summary of Abnormal Data

[0164] The abnormal data and processing status are summarized and reported to the abnormal feedback module, an abnormal report is generated and reported to the relevant management department or technical personnel, so as to handle and resolve the problem in a timely manner;

[0165] S7: Self-optimization of the purification process

[0166] Based on the repeated occurrence of supplementary treatment, the causes were analyzed through the treatment process optimization module, and optimization suggestions were proposed for managers to choose from. The treatment processes of the pretreatment module and the biological treatment module were optimized to improve the treatment effect of medical wastewater.

[0167] The real-time data monitoring in S3 is mainly used for multi-faceted monitoring of medical wastewater during the treatment process, including the following steps:

[0168] S301: Real-time monitoring started

[0169] Before starting the biological treatment process, the sensing and monitoring module is activated to ensure that all sensor modules are in normal working order and ready for real-time data monitoring.

[0170] S302: Data Acquisition and Transmission

[0171] The system uses multiple sensor modules, including pH, turbidity, dissolved oxygen, temperature, ammonia nitrogen, and phosphorus sensors, to collect various parameters of medical wastewater in real time. The data is then transmitted to the data processing module for analysis and storage via a data transmission interface.

[0172] S303: Multi-directional data acquisition

[0173] The internal substance content of the same batch of medical wastewater is recorded by the sensing devices inside the inlet, sedimentation tank and drainage pipe, and a corresponding material change line graph is generated. The processing capacity of the medical wastewater treatment system is fed back through the image data of the line graph.

[0174] Specifically, we install sensors inside the inlet, sedimentation tank, and drainage pipe to achieve multi-dimensional real-time monitoring of the substance content in medical wastewater. These sensors can accurately measure various indicators in the wastewater, including pH value, chemical oxygen demand (COD), and biological oxygen demand (BOD), and transmit the data to the central processing system. The central processing system generates a line graph of substance changes based on the received data. Through this line graph, we can intuitively see the changes in the substance content of the wastewater during the treatment process.

[0175] In generating the line chart, we employed image processing technology. First, the system preprocesses the data collected by the sensing devices, including data cleaning and noise reduction steps, to ensure the accuracy and reliability of the data. Then, the system draws the line chart based on the processed data. During the drawing process, the system selects different colors and line styles according to different material indicators to better distinguish and identify them. At the same time, the system also marks key data points on the line chart, including maximum, minimum, and average values, so that users can quickly obtain key information.

[0176] By analyzing the line graph data, we can comprehensively assess the treatment capacity of the medical wastewater treatment system. First, by observing the trend of the line graph, we can understand the changing trend of the substance content in the wastewater during the treatment process. If the line graph shows a significant decrease in substance content, it indicates that the system's treatment capacity is good; if the line graph shows a slow trend in substance content change, it indicates that the system may have some problems and requires further inspection and maintenance. Second, by comparing the line graphs at different time periods, we can understand the stability and sustainability of the system's treatment capacity. If the line graph shows a consistent trend across different time periods, it indicates that the system has high stability and sustainability; if the line graph shows large fluctuations across different time periods, it indicates that the system may be affected by external factors and requires corresponding measures for improvement.

[0177] In addition to assessing the system's processing capacity, this line graph can also provide strong support for the optimization and improvement of medical wastewater treatment systems. By comparing and analyzing line graphs from different time periods or under different conditions, we can identify problems and bottlenecks in the system and then formulate corresponding optimization and improvement plans. For example, if the COD content is found to be significantly higher in a certain time period, we can conduct in-depth research on that time period to find out the reasons for the high COD content and take corresponding measures to improve it.

[0178] S304: Real-time Data Display

[0179] The collected real-time data is displayed through a user interface or control terminal, allowing operators to understand the changes in various parameters during the medical wastewater treatment process and adjust treatment strategies in a timely manner.

[0180] S305: Anomaly Warning and Handling

[0181] During real-time data monitoring, the anomaly detection module performs anomaly detection on the collected data. Once anomaly data is detected, an anomaly warning mechanism is immediately triggered, and a warning message is sent to the operator through the user interface or control terminal to remind the operator to handle the abnormal situation in a timely manner.

[0182] The self-optimization of the purification process in S7 is mainly determined by the processing frequency of the targeted supplementary treatment in S5 to determine whether the self-optimization procedure needs to be executed, including the following steps:

[0183] S701: Initial Threshold Setting

[0184] Set a frequency threshold for targeted supplementary processing. When the execution frequency of targeted supplementary processing in S5 exceeds this threshold, it is determined that a self-optimization program needs to be executed.

[0185] S702: Self-optimization analysis program

[0186] Based on historical data and processing records of targeted supplementary treatments in S5, the reasons for frequent supplementary treatments were analyzed, including factors such as poor pretreatment effect and unreasonable parameter settings of biological treatment module.

[0187] S703: Generation of Analysis Results

[0188] Based on the analysis results, targeted optimization suggestions are proposed, including adjusting the dosage of the chemical solution, optimizing aeration parameters, and replacing the activated sludge.

[0189] S704: Optimize continuous monitoring

[0190] The optimization suggestions will be pushed to the management personnel, who will then select and implement them based on the actual situation. After the optimization suggestions are implemented, the treatment effect of medical wastewater will continue to be monitored to observe whether there is any improvement. If necessary, steps S701 to S705 can be repeated to continuously optimize the treatment process.

[0191] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A multi-directional monitoring system for medical wastewater treatment, characterized in that, Includes the following modules: The pretreatment module monitors and controls the usage status and service life of the bar screen during the bar filtration process, and automatically adds a certain proportion of chemicals according to the influent volume. At the same time, it digitally displays the sedimentation time of the sedimentation tank through the pulse count. The biological treatment module treats medical wastewater by controlling microbial transformation, gas introduction, and membrane treatment capacity. At the same time, water samples are periodically extracted using water sampling equipment to detect microbial content. The sensing and monitoring module is used to monitor various parameters in medical wastewater through different types of sensor devices, including pH value, turbidity, dissolved oxygen content, temperature, ammonia nitrogen, and total phosphorus. The data processing module processes, analyzes, and stores the collected data, and uses algorithms to identify water quality anomalies and predict the water quality trend after treatment. The supplementary treatment module adjusts the pretreatment and biological treatment modules to perform supplementary treatment in response to water quality anomalies reported by the data processing module. In addition, when supplementary treatment occurs multiple times, the processing flow of the pretreatment and biological treatment modules is optimized. The supplementary processing module is used to supplement the water quality anomalies reported by the data processing module, and includes the following modules: The supplementary processing judgment module determines whether a supplementary processing procedure needs to be initiated based on the result of the anomaly judgment module. The pretreatment supplementary processing module, when continuous supplementary processing is required, provides feedback to the grid filter module, the liquid dosing module and the pretreatment monitoring module in the pretreatment module to optimize the pretreatment effect; The biological treatment supplementary treatment module, when continuous supplementary treatment is required, provides feedback regulation to the activated sludge module, aeration module, biofilm module, and biological treatment monitoring module in the biological treatment module to optimize the biological treatment effect. The supplementary processing record module records detailed information for each supplementary processing step, including processing time, reason, process, and result, providing a basis for subsequent optimization of the processing flow. The process optimization module analyzes the causes and proposes optimization suggestions based on the repeated occurrence of supplementary treatment, thereby optimizing the treatment processes of the pretreatment and biological treatment modules and improving the treatment effect of medical wastewater. The anomaly feedback module summarizes the abnormal data that still exists after the supplementary processing module and the abnormal status reported by the data processing module, and reports it to the corresponding control terminal. The anomaly feedback module is used to summarize and report anomaly data and processing status, and includes the following modules: The abnormal data aggregation module aggregates the abnormal data identified by the sensing and monitoring module and the abnormal status reported by the data processing module. The anomaly report generation module generates anomaly reports based on the summarized anomaly data and handling status, including the cause of the anomaly, the scope of impact, and handling suggestions. The generated anomaly reports are then submitted to relevant management departments or technical personnel via email, SMS, or remote control terminal to facilitate timely handling and resolution of problems. The exception handling tracking module tracks the process and results of exception handling to ensure that exceptions are properly handled and resolved. The exception handling feedback module summarizes the results and feedback of exception handling, providing a basis for subsequent optimization of the processing flow and improvement of processing effectiveness.

2. The multi-directional monitoring system for medical wastewater treatment according to claim 1, characterized in that, The pretreatment module is mainly used for the preliminary treatment of the medical wastewater to be treated, and includes the following modules: The bar screen filter module removes large solid particles from medical wastewater by controlling the bar screen filter device and monitors the bar screen's usage status and duration. When the bar screen usage reaches the preset value, it automatically activates the backup bar screen and lifts the original bar screen to wait for replacement. The chemical dosing module automatically adds appropriate amounts of chemical agents, including neutralizers and coagulants, to remove harmful substances from medical wastewater based on its water quality. The pretreatment monitoring module monitors various parameters inside the sedimentation tank in real time during the pretreatment process, including the usage status of the bar screen, the cumulative usage time of the sedimentation tank, the current sedimentation time, and the amount of chemical solution added, to ensure that the pretreatment effect reaches the optimal state. The effluent regulation module is used to regulate the flow rate and water quality of medical wastewater discharged into the biological treatment module, so as to maintain the stable operation of the biological treatment module.

3. The multi-directional monitoring system for medical wastewater treatment according to claim 1, characterized in that, The biological treatment module is mainly used to remove organic pollutants from medical wastewater through microbial action, and includes the following modules: The activated sludge module uses microorganisms in the activated sludge to biodegrade organic matter in medical wastewater, converting organic matter into inorganic matter, while controlling the stirring device to start and turn the activated sludge at regular intervals. The aeration module controls the air pump to introduce oxygen into the activated sludge, ensuring the normal growth and metabolic activities of microorganisms, while promoting the suspension and mixing of the sludge. The biofilm module uses microorganisms in a biofilm reactor to biologically treat medical wastewater. The microorganisms on the biofilm can form a stable ecosystem, improving the efficiency of medical wastewater treatment. The biological treatment monitoring module monitors various parameters in the biological treatment process in real time, including the concentration of activated sludge, aeration rate, and biofilm growth, to ensure that the biological treatment effect reaches the optimal state. At the same time, water samples are periodically extracted through water sampling equipment to test the microbial content in order to evaluate the effectiveness of the biological treatment.

4. The multi-directional monitoring system for medical wastewater treatment according to claim 1, characterized in that, The sensing and monitoring module is used to control multiple sets of sensing devices to monitor the parameters of medical wastewater during the treatment process in real time, and includes the following modules: The pH sensor module is used to monitor the acidity and alkalinity of medical wastewater in real time to ensure a suitable acid-base environment for the medical wastewater during the biological treatment process. The turbidity sensor module is used to monitor the turbidity of medical wastewater in real time, that is, the content of suspended particulate matter in medical wastewater, in order to evaluate the effectiveness of medical wastewater treatment. The dissolved oxygen sensor module is used to monitor the dissolved oxygen content in medical wastewater in real time to ensure the normal growth and metabolic activities of microorganisms during the biological treatment process. A temperature sensor module is used to monitor the temperature of medical wastewater in real time to assess the microbial activity during the biological treatment process; The ammonia nitrogen and phosphorus sensor module is used to monitor the ammonia nitrogen and phosphorus content in medical wastewater in real time to evaluate the removal effect of nitrogen and phosphorus elements in medical wastewater. The sensor data aggregation module aggregates the data collected by each sensor module and uploads it to the data processing module for analysis and storage via the data transmission interface.

5. The multi-directional monitoring system for medical wastewater treatment according to claim 1, characterized in that, The data processing module is used to receive and analyze real-time data uploaded by the sensor monitoring module, and includes the following modules: The data receiving module is used to receive real-time data uploaded by the sensing and monitoring module, and to perform signal filtering and signal standardization processing on the transmitted data. The data analysis module processes and analyzes the received real-time data, including calculating the average, standard deviation, and rate of change statistics, to evaluate the treatment effect of medical wastewater. The anomaly detection module uses a preset anomaly detection algorithm to detect anomalies in the analyzed data and identify water quality anomalies. The trend prediction module uses prediction algorithms based on historical and real-time data to predict the trend of water quality after treatment, providing a basis for optimizing the treatment process. The data processing results output module displays the processing and analysis results through a user interface or control terminal for operators to refer to and make decisions.

6. A method for multi-directional monitoring of medical wastewater treatment, based on the multi-directional monitoring system for medical wastewater treatment described in claim 1, characterized in that, Includes the following steps: S1: Medical wastewater pretreatment The pretreatment module performs preliminary treatment on medical wastewater, including steps such as grid filtration, chemical dosing, and pH adjustment, to remove large particles and adjust the pH in the medical wastewater, preparing it for subsequent biological treatment processes. S2: Biological treatment and purification The pretreated medical wastewater is introduced into the biological treatment module, where organic pollutants and nutrients are removed through biological treatment methods including activated sludge, aeration, and biofilm, thereby achieving the purpose of medical wastewater treatment. S3: Real-time Data Monitoring During the biological treatment process, various parameters of medical wastewater, including pH value, turbidity, dissolved oxygen, temperature, ammonia nitrogen, and phosphorus, are monitored in real time through a sensor monitoring module to ensure the stability and effectiveness of the biological treatment process. S4: Data Analysis and Judgment The real-time data collected by the sensor monitoring module is transmitted to the data processing module. Through steps including data reception, analysis, anomaly detection and trend prediction, the treatment effect of medical wastewater is evaluated and predicted, providing a basis for subsequent supplementary treatment. S5: Targeted supplementary treatment Based on the abnormal water quality reported in the data processing module, targeted supplementary treatment is carried out through the supplementary treatment module, including optimizing the pretreatment and biological treatment processes to improve the treatment effect of medical wastewater. S6: Summary of Abnormal Data The abnormal data and processing status are summarized and reported to the abnormal feedback module, an abnormal report is generated and reported to the relevant management department or technical personnel so that the problem can be handled and resolved in a timely manner. S7: Self-optimizing purification process Based on the repeated occurrence of supplementary treatment, the causes were analyzed through the treatment process optimization module, and optimization suggestions were proposed for managers to choose from. The treatment processes of the pretreatment module and the biological treatment module were optimized to improve the treatment effect of medical wastewater.

7. The method for multi-directional monitoring of medical wastewater treatment according to claim 6, characterized in that, The real-time data monitoring in S3 is mainly used for multi-dimensional detection of medical wastewater during the treatment process, including the following steps: S301: Real-time monitoring started Before starting the biological treatment process, activate the sensing and monitoring module to ensure that all sensor modules are in normal working order and ready for real-time data monitoring. S302: Data Acquisition and Transmission The system uses multiple sensor modules, including pH, turbidity, dissolved oxygen, temperature, ammonia nitrogen, and phosphorus sensors, to collect various parameters of medical wastewater in real time. The data is then transmitted to the data processing module for analysis and storage via a data transmission interface. S303: Multi-directional data acquisition The internal substance content of the same batch of medical wastewater is recorded by the sensing devices inside the inlet, sedimentation tank and drainage pipe, and a corresponding material change line graph is generated. The processing capacity of the medical wastewater treatment system is fed back through the image data of the line graph. S304: Real-time Data Display The collected real-time data is displayed through a user interface or control terminal, allowing operators to understand the changes in various parameters during the medical wastewater treatment process and adjust treatment strategies in a timely manner. S305: Anomaly Warning and Handling During real-time data monitoring, the anomaly detection module performs anomaly detection on the collected data. Once anomaly data is detected, an anomaly warning mechanism is immediately triggered, and a warning message is sent to the operator through the user interface or control terminal to remind the operator to handle the abnormal situation in a timely manner.

8. The method for multi-directional monitoring of medical wastewater treatment according to claim 6, characterized in that, The self-optimization of the purification process in S7 is mainly determined by the processing frequency of the targeted supplementary treatment in S5 to determine whether the self-optimization procedure needs to be executed, including the following steps: S701: Initial Threshold Setting Set a frequency threshold for targeted supplementary processing. When the execution frequency of targeted supplementary processing in S5 exceeds this threshold, it is determined that a self-optimization program needs to be executed. S702: Self-optimization analysis program Based on historical data and processing records of targeted supplementary treatments in S5, the reasons for frequent supplementary treatments were analyzed, including factors such as poor pretreatment effect and unreasonable parameter settings of biological treatment module. S703: Generation of Analysis Results Based on the analysis results, targeted optimization suggestions are proposed, including adjusting the dosage of the chemical solution, optimizing aeration parameters, and replacing the activated sludge. S704: Optimize continuous monitoring The optimization suggestions will be pushed to the management personnel, who will then select and implement them based on the actual situation. After the optimization suggestions are implemented, the treatment effect of medical wastewater will continue to be monitored to observe whether there is any improvement. If necessary, steps S701 to S704 can be repeated to continuously optimize the treatment process.

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