Environmental protection sewage treatment method based on big data

Abstract

The invention discloses an environmental protection sewage treatment method based on big data, which belongs to the technical field of environmental protection sewage treatment and comprises the steps of data acquisition and transmission, data analysis and optimization, real-time monitoring and early warning, visual display and decision support, system customization and optimization, data security guarantee and the like. According to the method, the limitation of a traditional sewage treatment method can be overcome, and real-time monitoring, optimal control and efficient operation of sewage treatment are realized. Precise acquisition and analysis of various parameters in the sewage treatment process are realized through a big data technology, a treatment strategy is optimized through a machine learning algorithm, the sewage treatment efficiency and quality are improved, and meanwhile, the energy consumption and the operation cost are reduced. In addition, the system also has high flexibility and expandability, can be customized and optimized according to different sewage treatment requirements and scenes, and provides powerful technical support for the environmental protection cause.

Description

Technical Field

[0001] The invention discloses an environmental protection sewage treatment method based on big data, belonging to the technical field of environmental protection sewage treatment. Background Art

[0002] In the 21st century, with the rapid advancement of urbanization and the continued growth of population, water resource management faces unprecedented challenges. Among them, sewage treatment, as a key link in the field of environmental protection, is of self-evident importance.

[0003] In recent years, big data technology has demonstrated tremendous potential and value across various industries, particularly in the field of environmental protection, where its application is becoming increasingly widespread. Big data not only processes massive amounts of data but also uses advanced analytical techniques to uncover hidden patterns and trends within the data, providing a scientific basis for decision-making. In the field of sewage treatment, the application of big data technology has broken new ground. By collecting and analyzing various parameters during the sewage treatment process, it enables real-time monitoring and optimization of the treatment process, significantly improving treatment efficiency and quality.

[0004] Traditional wastewater treatment methods rely primarily on physical, chemical, and biological methods. While these methods can remove harmful substances from wastewater to a certain extent, they have numerous limitations. For example, physical methods often consume a lot of energy and have limited treatment effectiveness; chemical methods may introduce new pollutants, causing secondary damage to the environment; and biological methods, while relatively environmentally friendly, have long treatment cycles and are significantly affected by environmental factors such as season and temperature. Therefore, exploring more efficient and environmentally friendly wastewater treatment methods is crucial. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to overcome the traditional sewage treatment method. Although it has alleviated the problem of water pollution to a certain extent, there are generally problems such as low efficiency, huge energy consumption, and unstable treatment effect. A big data-based environmental protection sewage treatment method is provided. The method aims to achieve intelligent, precise and efficient sewage treatment through the deep integration of cutting-edge technologies such as big data, cloud computing, the Internet of Things and artificial intelligence, inject new vitality into the environmental protection cause, and thus solve the above problems.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for treating environmentally friendly sewage based on big data, comprising the following steps: Step A: Data collection and transmission To achieve real-time monitoring and optimized control of wastewater treatment, sensors and data acquisition devices are installed at every stage of the treatment process (e.g., primary sedimentation tanks, microbial decomposition treatment tanks, secondary sedimentation tanks, and secondary water treatment tanks). These sensors collect key data in real time, including water quality indicators (e.g., concentration, temperature, pH), equipment operating status (e.g., flow rate, pressure, energy consumption), and microbial growth efficiency. To ensure data accuracy and integrity, sensors and data acquisition devices undergo rigorous calibration and testing. The collected data is transmitted to a big data server and stored in a large parameter database, providing a foundation for subsequent data analysis and optimization.

[0007] Step B: Data Analysis and Optimization Utilizing big data technology and machine learning algorithms, the data collected in Step A is analyzed and processed to identify bottlenecks and deficiencies in the sewage treatment process and propose optimization strategies. Specifically, by comparing historical and real-time data, patterns and trends in water quality changes can be identified. Machine learning algorithms are used to train and learn from historical data to establish predictive models and forecast future water quality changes. Based on the predicted results and real-time data, optimized sewage treatment parameter settings are developed and transmitted to equipment at each stage of the treatment process for precise control. Furthermore, data mining techniques can be used to identify potential energy-saving and consumption-reduction pathways, providing a scientific basis for the optimized operation of sewage treatment systems.

[0008] Step C: Real-time monitoring and early warning Using a big data platform, various parameters and equipment operating status during the wastewater treatment process are monitored in real time. If an anomaly or an excess of standards is detected, an early warning mechanism is immediately triggered, notifying management personnel for prompt action. This not only prevents production stoppages and environmental pollution incidents caused by equipment failures, but also improves the stability and reliability of wastewater treatment. To achieve this, a comprehensive set of early warning rules and response mechanisms must be established to ensure the accuracy and timeliness of early warning information. Furthermore, training and guidance are required for management personnel to enhance their emergency response capabilities and decision-making skills.

[0009] Step D: Visualization and decision support Data visualization technology can be used to display various parameters and equipment operating status during the sewage treatment process in the form of charts and graphs, helping managers gain an intuitive understanding of the overall operational status of the sewage treatment system. This visualization allows managers to promptly identify and resolve issues, improving the efficiency and quality of sewage treatment. Furthermore, visualization technology can be used for decision support, providing managers with a scientific and intuitive basis for making decisions. For example, by comparing the treatment effects and economic costs of different treatment strategies, the optimal treatment solution can be selected. Furthermore, by analyzing water quality trends and forecasts, a reasonable water quality management plan can be formulated.

[0010] Step E: System Customization and Optimization We customize and optimize sewage treatment systems based on different sewage treatment needs and scenarios. For example, we adjust the placement and parameter settings of sensors and data acquisition devices to target specific water quality indicators or treatment requirements. We optimize sewage treatment strategies and parameter settings based on analysis of historical and real-time data. Furthermore, we integrate other environmental protection technologies and equipment to create a more comprehensive sewage treatment solution. Through system customization and optimization, we can further improve sewage treatment efficiency and quality, while reducing energy consumption and operating costs.

[0011] Step F: Data Security During data collection, transmission, storage, and analysis, necessary data security measures are implemented to ensure data security and integrity. For example, encryption technology is used to encrypt data transmission and storage; a permissions management system is established to restrict data access and operation permissions; and regular data backup and recovery tests are performed to prevent data loss or corruption. These data security measures ensure the security and reliability of data during the sewage treatment process, providing a strong guarantee for the stable operation of the system.

[0012] Compared with the prior art, the present invention has the following beneficial effects: The present invention provides a big data-based sewage treatment method that overcomes the limitations of traditional sewage treatment methods and enables real-time monitoring, optimized control, and efficient operation of sewage treatment. Specifically, the present invention uses big data technology to accurately collect and analyze various parameters in the sewage treatment process, optimizes treatment strategies through machine learning algorithms, improves sewage treatment efficiency and quality, and reduces energy consumption and operating costs. Furthermore, the present invention is highly flexible and scalable, and can be customized and optimized according to different sewage treatment needs and scenarios, providing strong technical support for environmental protection. DETAILED DESCRIPTION

[0013] The following is a clear and complete description of the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of the present invention.

[0014] A method for treating wastewater for environmental protection based on big data, comprising the following steps: 1.1 Data Collection and Transmission Data collection is the first step in the present method. To achieve real-time monitoring and optimized control of wastewater treatment, sensors and data acquisition devices are installed at every stage of the wastewater treatment process (such as the primary sedimentation tank, microbial decomposition treatment tank, secondary sedimentation tank, and secondary water treatment tank). These sensors can collect key data in real time, including water quality indicators (such as concentration, temperature, and pH), equipment operating status (such as flow rate, pressure, and energy consumption), and microbial growth efficiency. To ensure data accuracy and integrity, sensors and data acquisition devices undergo rigorous calibration and testing. The collected data is transmitted to a big data server and stored in a large parameter database, providing a foundation for subsequent data analysis and optimization.

[0015] 1.2 Data Analysis and Optimization Data analysis and optimization are the core links of the method of the present invention. Using big data technology and machine learning algorithms, the collected data is analyzed and processed to identify bottlenecks and deficiencies in the sewage treatment process and to propose optimization strategies. Specifically, by comparing historical data with real-time data, the patterns and trends of water quality changes can be identified; machine learning algorithms are used to train and learn historical data to establish a predictive model to predict future changes in water quality; based on the prediction results and real-time data, optimized sewage treatment parameter settings are formed, and these parameters are transmitted to the equipment in each treatment link to achieve precise control. In addition, data mining technology can also be used to discover potential energy-saving and consumption-reducing paths, providing a scientific basis for the optimized operation of sewage treatment systems.

[0016] 1.3 Real-time monitoring and early warning Real-time monitoring and early warning are key safeguards for the method of the present invention. Through a big data platform, various parameters and equipment operating status during the sewage treatment process can be monitored in real time. Once an anomaly or an excess of standards is detected, an early warning mechanism is immediately triggered, notifying management personnel for prompt action. This not only avoids production shutdowns and environmental pollution incidents caused by equipment failures, but also improves the stability and reliability of sewage treatment. To achieve this function, a comprehensive set of early warning rules and response mechanisms must be established to ensure the accuracy and timeliness of early warning information. Furthermore, training and guidance are required for management personnel to improve their emergency response capabilities and decision-making skills.

[0017] 1.4 Visualization and Decision Support Visualization is another key component of the present method. Using data visualization technology, various parameters and equipment operating status during the sewage treatment process are displayed in the form of charts, graphs, and other forms, helping managers gain an intuitive understanding of the overall operational status of the sewage treatment system. Through visualization, managers can promptly identify and resolve problems, improving the efficiency and quality of sewage treatment. Furthermore, visualization technology can be used for decision support, providing managers with a scientific and intuitive basis for decision-making. For example, by comparing the treatment effects and economic costs of different treatment strategies, the optimal treatment solution can be selected. Furthermore, by analyzing water quality trends and forecasts, a reasonable water quality management plan can be formulated.

[0018] 1.5 System customization and optimization We customize and optimize sewage treatment systems based on different sewage treatment needs and scenarios. For example, we adjust the placement and parameter settings of sensors and data acquisition devices to target specific water quality indicators or treatment requirements. We optimize sewage treatment strategies and parameter settings based on analysis of historical and real-time data. Furthermore, we integrate other environmental protection technologies and equipment to create a more comprehensive sewage treatment solution. Through system customization and optimization, we can further improve sewage treatment efficiency and quality, while reducing energy consumption and operating costs.

[0019] 1.6 Data Security During data collection, transmission, storage, and analysis, necessary data security measures are implemented to ensure data security and integrity. For example, encryption technology is used to encrypt data transmission and storage; a permissions management system is established to restrict data access and operation permissions; and regular data backup and recovery tests are performed to prevent data loss or corruption. These data security measures ensure the security and reliability of data during the sewage treatment process, providing a strong guarantee for the stable operation of the system.

[0020] Effects and advantages of the present invention.

[0021] 2.1 Improve sewage treatment efficiency and quality The method of this invention can significantly improve the efficiency and quality of sewage treatment. Real-time monitoring and optimized control ensure that all parameters in the sewage treatment process are always optimal. Data analysis and mining techniques can identify potential energy-saving and consumption-reduction pathways and optimization strategies. Visualization and decision support technologies provide managers with a scientific and intuitive basis for decision-making. These measures, working together, can significantly improve the efficiency and quality of sewage treatment, meeting increasingly stringent environmental protection requirements.

[0022] 2.2 Reduce energy consumption and operating costs The method of the present invention can also effectively reduce the energy consumption and operating costs of sewage treatment systems. By real-time monitoring of equipment operating status and energy consumption, excessive energy consumption can be promptly identified and resolved. By optimizing treatment strategies and parameter settings, energy consumption and chemical usage can be reduced during the treatment process. Data mining techniques can be used to identify potential energy-saving pathways and optimization strategies, further reducing operating costs. These measures, taken together, can achieve the goals of energy conservation, consumption reduction, cost reduction, and efficiency improvement for sewage treatment systems.

[0023] 2.3 Enhance system stability and reliability Real-time monitoring, early warning mechanisms, and visualization technology can enhance the stability and reliability of sewage treatment systems. Real-time monitoring allows for the timely detection and resolution of abnormalities; early warning mechanisms prevent production stoppages and environmental pollution incidents caused by equipment failures; and visualization technology helps managers intuitively understand system operating conditions and make informed decisions. These measures, working together, ensure the stable operation and reliable output of sewage treatment systems.

[0024] 2.4 High flexibility and scalability The method of the present invention is also highly flexible and scalable. It can be customized and optimized according to different sewage treatment needs and scenarios. With the continuous development of big data technology and the continuous expansion of application scenarios, the method system and technical means of the present invention can be further enriched and improved. Through integration with other environmental protection technologies and equipment, even more comprehensive environmental protection solutions can be formed. These characteristics give the method of the present invention broad application prospects and far-reaching social significance.

[0025] The following is a specific embodiment to further illustrate the technical solution and implementation effect of the present invention.

[0026] 3.1 Background of the Implementation A certain city's sewage treatment plant faced problems such as large fluctuations in water quality, low treatment efficiency, and high energy consumption. To improve sewage treatment efficiency and quality and reduce operating costs, the plant decided to adopt the method of the present invention for renovation and upgrading.

[0027] 3.2 Implementation steps and measures (1) Sensors and data acquisition devices are installed in key links of sewage treatment, such as primary sedimentation tanks, microbial decomposition treatment tanks, secondary sedimentation tanks and secondary water treatment tanks, to collect data such as water quality indicators, equipment operating status and microbial reproduction efficiency in real time.

[0028] (2) The collected data is transmitted to a big data server and stored in a parameter database. The data is analyzed and processed using big data technology and machine learning algorithms to form an optimized sewage treatment strategy and transmit it to the equipment in each treatment link for precise control.

[0029] (3) Establish a real-time monitoring and early warning mechanism and a visualization display platform. Use the big data platform to monitor various parameters and equipment operating status during the sewage treatment process in real time. Once an abnormality or exceeding the standard is found, the early warning mechanism will be triggered immediately and the management personnel will be notified to handle it. Use data visualization technology to display the overall operating status of the sewage treatment system in the form of charts, curves, etc. for the reference and decision-making of management personnel.

[0030] 3.3 Implementation Effect and Evaluation After the renovation and upgrading, the sewage treatment efficiency and quality of the sewage treatment plant have been significantly improved; energy consumption and operating costs have been greatly reduced; and system stability and reliability have been significantly enhanced. This is specifically reflected in the following aspects: Water quality indicators are stably up to standard: through real-time monitoring and optimized control, water quality indicators are stably up to national emission standards or even higher levels.

[0031] Significant reduction in energy consumption: By optimizing processing strategies and parameter settings and using data mining technology to discover energy-saving approaches, energy consumption has been reduced by approximately 30% compared to before the transformation.

[0032] Reduced operating costs: By reducing the use of chemicals and reducing equipment failure maintenance costs, operating costs have dropped by about 20% compared to before the transformation.

[0033] Enhanced system stability: Through real-time monitoring and early warning mechanisms as well as visual display technology and other measures, system stability has been significantly enhanced to avoid production stoppages and environmental pollution incidents.

[0034] This invention proposes a big data-based environmentally friendly wastewater treatment method. Through real-time monitoring, data analysis and optimization, early warning mechanisms, and visual display, it achieves precise control and efficient operation of wastewater treatment. This method offers significant technical advantages and promising applications, and is of great significance for promoting the development of environmental protection. With the continued development of big data technology and the expansion of its application scenarios, the methodological system and technical means of this invention will be further enriched and improved. Furthermore, its integration with other environmental protection technologies and equipment will form a more comprehensive environmental protection solution.

[0035] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A method for treating environmentally friendly sewage based on big data, characterized in that: The following steps are involved: Step A: Data collection and transmission In order to achieve real-time monitoring and optimized control of sewage treatment, it is necessary to set up sensors and data acquisition devices in each link of sewage treatment; These sensors can collect key data such as water quality indicators, equipment operating status, and microbial reproduction efficiency in real time. The collected data will be transmitted to the big data server and stored in the parameter database, providing a basis for subsequent data analysis and optimization. Step B: Data Analysis and Optimization Utilizing big data technology and machine learning algorithms, the data collected in step A is analyzed and processed to identify bottlenecks and deficiencies in the sewage treatment process and propose optimization strategies. Specifically, by comparing historical data with real-time data, patterns and trends in water quality changes can be identified. Machine learning algorithms are used to train and learn from historical data to establish a predictive model to predict future water quality changes. Based on the predicted results and real-time data, optimized sewage treatment parameter settings are formed and transmitted to equipment in each treatment link for precise control. Data mining technology can also be used to discover potential energy-saving and consumption-reduction pathways, providing a scientific basis for the optimized operation of the sewage treatment system. Step C: Real-time monitoring and early warning Through the big data platform, various parameters and equipment operating status of the sewage treatment process are monitored in real time. Once an abnormality or exceeding the standard is detected, the early warning mechanism is immediately triggered, notifying management personnel for timely handling. This not only avoids production stoppages and environmental pollution incidents caused by equipment failure, but also improves the stability and reliability of sewage treatment. To achieve this function, it is necessary to establish a comprehensive set of early warning rules and response mechanisms to ensure the accuracy and timeliness of early warning information. It also requires training and guidance for management personnel to improve their emergency response capabilities and decision-making level. Step D: Visualization and decision support By using data visualization technology, various parameters and equipment operating status in the sewage treatment process can be displayed in the form of charts, curves, etc., which helps managers to intuitively understand the overall operating status of the sewage treatment system; through visualization, managers can discover and solve problems in a timely manner, improve the efficiency and quality of sewage treatment, and use visualization technology for decision support, providing managers with scientific and intuitive decision-making basis; by comparing the treatment effects and economic costs under different treatment strategies, the optimal treatment plan can be selected; and by analyzing water quality change trends and prediction results, a reasonable water quality management plan can be formulated.

2. The method for treating wastewater for environmental protection based on big data according to claim 1, characterized in that The following steps are also included: Step E: System Customization and Optimization The sewage treatment system is customized and optimized according to different sewage treatment needs and scenarios; the layout and parameter settings of sensors and data acquisition devices are adjusted according to specific water quality indicators or treatment requirements; sewage treatment strategies and parameter settings are optimized based on the analysis results of historical data and real-time data; and other environmental protection technologies and equipment are combined to form a more complete sewage treatment solution. Through system customization and optimization, the efficiency and quality of sewage treatment can be further improved, and energy consumption and operating costs can be reduced.

3. The method for treating wastewater for environmental protection based on big data according to claim 2, characterized in that The following steps are also included: Step F: Data Security During the process of data collection, transmission, storage and analysis, necessary data security measures are taken to ensure the security and integrity of the data; encryption technology is used to encrypt the transmission and storage of data; a permission management system is established to limit access to and operation rights of the data; data is backed up and restored regularly to prevent data loss or damage; through data security measures, the data in the sewage treatment process can be ensured to be safe and reliable, providing strong guarantees for the stable operation of the system.

4. The environmental protection sewage treatment method based on big data according to claim 1 is characterized by: The various links in step A include a primary sedimentation tank, a microbial decomposition treatment tank, a secondary sedimentation tank and a secondary water treatment tank.

5. The environmental protection sewage treatment method based on big data according to claim 1 is characterized by: The water quality indicators in step A include concentration, temperature and pH value; The parameters of the equipment operating status in step A include flow, pressure, and energy consumption.

6. The environmental protection sewage treatment method based on big data according to claim 1 is characterized by: To ensure the accuracy and integrity of the data collected in step A, the sensors and data acquisition devices need to be rigorously calibrated and tested.