An intelligent management method for environmental protection equipment integrating Internet of Things and big data

Abstract

The present invention discloses an intelligent management method for environmental protection equipment integrating the Internet of Things and big data, which belongs to the field of waste gas treatment, and includes: setting two waste gas treatment units to collect real-time waste gas parameters; performing big data analysis on the real-time waste gas parameters to evaluate whether the waste gas treatment threshold conditions are met; when the conditions are met, switching to a dual-path working mode to perform synchronous purification treatment on the waste gas; when the real-time waste gas parameters do not meet the waste gas treatment threshold conditions, switching to a cascade working mode to perform graded purification treatment on the waste gas. The working mode of the waste gas treatment unit is dynamically adjusted by real-time waste gas parameters, so as to improve the intelligent management level of environmental protection equipment, and improve the waste gas treatment effect and waste gas treatment efficiency. Precise operation control of environmental protection equipment is achieved through Internet of Things sensors and cloud-based big data analysis, and flexible switching of dual-path and cascade working modes is adopted, so as to achieve the technical effect of improving the intelligent management level of environmental protection equipment and ensuring stable and standard emission of waste gas.

Description

Technical Field

[0001] The present invention relates to the field of waste gas treatment, and in particular to an intelligent management method for environmental protection equipment integrating the Internet of Things and big data. Background Art

[0002] With the continuous advancement of industrialization, the problem of waste gas pollution generated in the industrial production process has become increasingly prominent. In order to control waste gas pollution, industrial workshops generally install environmental protection equipment to treat waste gas. However, there are still some problems with the actual operation of existing environmental protection equipment. First, in the industrial production process, the concentration, composition and other parameters of waste gas often change dynamically, and the existing environmental protection equipment usually treats waste gas according to a fixed operating mode, and cannot be adjusted accordingly according to the real-time waste gas parameters, resulting in poor waste gas treatment effects and substandard emissions. Second, when industrial workshops produce high-concentration waste gas, the waste gas treatment unit has limited processing capacity, and it is difficult for existing environmental protection equipment to achieve one-time emission standards. It is often difficult to process various indicators of waste gas to meet emission standards in one treatment process, which leads to excessive emissions. Summary of the invention

[0003] This application provides an intelligent management method for environmental protection equipment by integrating the Internet of Things and big data, aiming to solve the technical problems in the prior art that environmental protection equipment cannot adapt to changes in exhaust gas parameters in industrial workshops in real time, resulting in substandard exhaust gas emissions, and in the case of high-concentration exhaust gas, it is difficult to meet emission standards due to the limited processing capacity of the exhaust gas treatment unit.

[0004] The present application discloses an intelligent management method for environmental protection equipment integrating the Internet of Things and big data, comprising: setting up environmental protection equipment in an industrial workshop, the environmental protection equipment comprising two identical exhaust gas treatment units, namely a first exhaust gas treatment unit and a second exhaust gas treatment unit; deploying an exhaust gas collection network in the industrial workshop, the exhaust gas collection network consisting of a plurality of Internet of Things sensors, collecting exhaust gas parameters in the industrial workshop through the exhaust gas collection network, and obtaining real-time exhaust gas parameters; transmitting the real-time exhaust gas parameters to a cloud server, performing big data analysis on the real-time exhaust gas parameters in the cloud server, and evaluating whether the real-time exhaust gas parameters meet the exhaust gas treatment threshold conditions of the exhaust gas treatment unit; obtaining the emission standard limit of the industrial workshop, the emission standard limit being the emission index to be achieved after the exhaust gas treatment; when the real-time exhaust gas parameter meets the exhaust gas treatment threshold conditions, switching the first exhaust gas treatment unit and the second exhaust gas treatment unit to a dual-path working mode, and performing synchronous purification treatment on the exhaust gas according to the emission standard limit; when the real-time exhaust gas parameter does not meet the exhaust gas treatment threshold conditions, switching the first exhaust gas treatment unit and the second exhaust gas treatment unit to a cascade working mode, and performing graded purification treatment on the exhaust gas according to the emission standard limit.

[0005] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0006] Since the environmental protection equipment is set up in the industrial workshop, the environmental protection equipment includes two identical exhaust gas treatment units, namely the first exhaust gas treatment unit and the second exhaust gas treatment unit. By setting up two identical exhaust gas treatment units, a hardware foundation is provided for realizing different exhaust gas treatment modes; an exhaust gas collection network is deployed in the industrial workshop. The exhaust gas collection network is composed of multiple Internet of Things sensors. The exhaust gas parameters in the industrial workshop are collected through the exhaust gas collection network to obtain real-time exhaust gas parameters, which provide data support for subsequent big data analysis and processing mode switching; the real-time exhaust gas parameters are transmitted to the cloud server, and the real-time exhaust gas parameters are analyzed by big data in the cloud server to evaluate whether the real-time exhaust gas parameters meet the exhaust gas treatment threshold conditions of the exhaust gas treatment unit. Through cloud big data analysis, it is determined whether the current exhaust gas conditions exceed the processing capacity of the exhaust gas treatment unit, so as to provide a decision-making basis for selecting an appropriate processing mode; the emission standard limit of the industrial workshop is obtained. The emission standard limit is the emission index that needs to be achieved after the exhaust gas treatment, which provides a reference for the evaluation of the treatment effect; when the real-time exhaust gas parameters meet the exhaust gas treatment threshold conditions of the exhaust gas treatment unit, the exhaust gas treatment capacity of the exhaust gas treatment unit is determined, and the processing capacity of the exhaust gas treatment unit is determined ... when the real-time exhaust gas parameters meet the exhaust gas treatment threshold conditions of the exhaust gas treatment unit, the exhaust gas treatment capacity of the exhaust gas treatment unit is determined, and the processing capacity of the exhaust gas treatment unit is determined, and the processing capacity of the exhaust gas treatment unit is determined, and the processing capacity of the exhaust gas treatment unit When the exhaust gas treatment threshold conditions are met, the first exhaust gas treatment unit and the second exhaust gas treatment unit are switched to a dual-path working mode, and the exhaust gas is synchronously purified according to the emission standard limit, so that when the exhaust gas concentration is low, dual-path synchronous treatment is adopted to improve the treatment efficiency; when the real-time exhaust gas parameters do not meet the exhaust gas treatment threshold conditions, the first exhaust gas treatment unit and the second exhaust gas treatment unit are switched to a cascade working mode, and the exhaust gas is graded and purified according to the emission standard limit, so that when the exhaust gas concentration is high, cascade graded treatment is adopted, and the technical solution of achieving standard emission through multiple treatments solves the technical problems that the environmental protection equipment in the prior art cannot adapt to the changes in the exhaust gas parameters of the industrial workshop in real time, resulting in non-standard exhaust gas emissions, and in the case of high-concentration exhaust gas, the exhaust gas treatment unit has limited processing capacity and is difficult to meet the emission standards. The precise operation control of the environmental protection equipment is realized through the Internet of Things sensors and cloud big data analysis, and the dual-path and cascade working modes are flexibly switched, so as to achieve the technical effect of improving the intelligent level of environmental protection equipment management and ensuring stable and standard exhaust gas emissions.

[0007] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 A flow chart of an intelligent management method for environmental protection equipment integrating the Internet of Things and big data is provided for an embodiment of the present application.

[0009] Figure 2 A flow chart of a synchronous purification process for waste gas in an intelligent management method for environmental protection equipment integrating the Internet of Things and big data is provided for an embodiment of the present application. DETAILED DESCRIPTION

[0010] The overall idea of ​​the technical solution provided by this application is as follows:

[0011] The embodiment of the present application provides an intelligent management method for environmental protection equipment by integrating the Internet of Things and big data. By setting up two identical exhaust gas treatment units in an industrial workshop and deploying an exhaust gas collection network composed of Internet of Things sensors, the exhaust gas parameters in the industrial workshop are collected in real time. The collected real-time exhaust gas parameters are transmitted to the cloud server for big data analysis. According to the analysis results, it is determined whether the exhaust gas parameters meet the processing threshold conditions of the exhaust gas treatment unit, and the working mode of the exhaust gas treatment unit is dynamically switched in combination with the emission standard limit of the industrial workshop. When the exhaust gas parameters meet the processing threshold conditions, the dual-path working mode is adopted to synchronously purify the exhaust gas; when the exhaust gas parameters do not meet the processing threshold conditions, it is switched to the cascade working mode to perform graded purification treatment on the exhaust gas.

[0012] Through the above technical solution, this application realizes the real-time intelligent adaptive adjustment of environmental protection equipment to industrial workshop exhaust gas, overcoming the defects of the existing technology that the operating mode of environmental protection equipment is fixed and cannot dynamically respond to changes in exhaust gas parameters. At the same time, by flexibly switching between the dual-path working mode and the cascade working mode, it effectively solves the problem that high-concentration exhaust gas is difficult to meet the emission standards in one go.

[0013] After introducing the basic principles of the present application, the non-limiting implementation methods of the present application will be specifically introduced below in conjunction with the drawings in the specification.

[0014] like Figure 1 As shown, the embodiment of the present application provides an intelligent management method for environmental protection equipment integrating the Internet of Things and big data, the method comprising:

[0015] S1: An environmental protection device is installed in an industrial workshop, wherein the environmental protection device includes two identical exhaust gas treatment units, namely a first exhaust gas treatment unit and a second exhaust gas treatment unit.

[0016] Specifically, an environmental protection device for treating industrial waste gas is set in an industrial workshop, and the environmental protection device includes two waste gas treatment units with the same structure and function, namely a first waste gas treatment unit and a second waste gas treatment unit. Each waste gas treatment unit is provided with an independent waste gas inlet and waste gas outlet, so as to flexibly adjust the flow direction and treatment method of the waste gas according to actual needs.

[0017] In practical applications, the first exhaust gas treatment unit and the second exhaust gas treatment unit can be operated in parallel or in series by controlling the opening and closing and connection mode of the exhaust gas inlet. When the two exhaust gas treatment units are in a dual-path working mode, the exhaust gas enters from the two inlets at the same time, is processed by the two exhaust gas treatment units respectively, and then converges to the discharge port for discharge. When the two exhaust gas treatment units are in a cascade working mode, the exhaust gas first enters from the inlet of the first exhaust gas treatment unit, is discharged from the discharge port of the first exhaust gas treatment unit after treatment, and then enters the inlet of the second exhaust gas treatment unit, and is finally discharged from the discharge port of the second exhaust gas treatment unit after further processing.

[0018] By setting up environmental protection equipment containing two identical exhaust gas treatment units in the industrial workshop, the necessary hardware foundation is provided for the subsequent intelligent management and the realization of different working modes.

[0019] S2: deploying an exhaust gas collection network in the industrial workshop, wherein the exhaust gas collection network is composed of a plurality of IoT sensors, and collecting exhaust gas parameters in the industrial workshop through the exhaust gas collection network to obtain real-time exhaust gas parameters.

[0020] Specifically, an exhaust gas collection network is deployed in industrial workshops to collect exhaust gas parameters in real time, providing data support for subsequent big data analysis and equipment control. The exhaust gas collection network consists of multiple IoT sensors, including environmental sensors such as temperature sensors, humidity sensors, and pressure sensors, as well as special sensors for different exhaust gas components, such as sulfur dioxide sensors, nitrogen oxide sensors, and carbon monoxide sensors. By deploying and working together with multiple IoT sensors, an exhaust gas collection network covering the entire industrial workshop is formed.

[0021] In actual applications, each IoT sensor in the exhaust gas collection network continuously collects exhaust gas parameters in different areas and at different times in the industrial workshop according to the preset collection frequency and collection strategy, and summarizes the collected data in real time to obtain real-time exhaust gas parameters. Real-time exhaust gas parameters include multiple indicators such as the temperature, humidity, pressure, and concentration of various exhaust gas components in the industrial workshop, which can fully reflect the exhaust gas conditions in the industrial workshop. Through real-time exhaust gas parameters, the generation and change rules of exhaust gas in the industrial workshop can be grasped, providing a basis for the intelligent control of environmental protection equipment.

[0022] By deploying an exhaust gas collection network composed of multiple IoT sensors in industrial workshops, real-time collection and monitoring of exhaust gas parameters in industrial workshops are achieved, laying a data foundation for subsequent big data analysis and intelligent management of environmental protection equipment.

[0023] S3: Transmitting the real-time exhaust gas parameters to a cloud server, performing big data analysis on the real-time exhaust gas parameters in the cloud server, and evaluating whether the real-time exhaust gas parameters meet the exhaust gas treatment threshold conditions of the exhaust gas treatment unit.

[0024] Specifically, after obtaining the real-time exhaust gas parameters collected by the exhaust gas collection network in the industrial workshop, the real-time exhaust gas parameters are transmitted to the cloud server for big data analysis and processing.

[0025] First, the real-time exhaust gas parameters are transmitted to the cloud server through a wired or wireless network. After receiving the real-time exhaust gas parameters, the cloud server cleans, converts and stores the data to ensure the accuracy and consistency of the data. Then, the cloud server uses big data analysis technology to conduct a comprehensive analysis and mining of the real-time exhaust gas parameters. Based on the big data analysis, the cloud server compares and evaluates the real-time exhaust gas parameters with the preset exhaust gas treatment threshold conditions. Among them, the exhaust gas treatment threshold conditions are the upper or lower limits set for various exhaust gas component concentrations, temperature, humidity and other parameters according to the treatment capacity and process requirements of the exhaust gas treatment unit. When the real-time exhaust gas parameters meet the exhaust gas treatment threshold conditions, it indicates that the exhaust gas conditions in the industrial workshop are within the treatment capacity of the exhaust gas treatment unit. The exhaust gas treatment unit can be optimized by operating parameters and adopting a dual-path working mode to achieve standard emissions. On the contrary, if the real-time exhaust gas parameters exceed the exhaust gas treatment threshold conditions, it means that the exhaust gas conditions in the industrial workshop have exceeded the normal treatment capacity of the exhaust gas treatment unit, and a cascade working mode needs to be adopted to achieve standard emissions.

[0026] By transmitting real-time exhaust gas parameters to the cloud server and using big data analysis technology to evaluate and judge the real-time exhaust gas parameters, real-time matching of the exhaust gas treatment unit's processing capacity and exhaust gas conditions is achieved, providing a basis and guidance for the intelligent control of environmental protection equipment.

[0027] S4: Obtain the emission standard limit of the industrial workshop, where the emission standard limit is the emission index that needs to be achieved after the exhaust gas is treated.

[0028] Specifically, in the process of realizing intelligent control of environmental protection equipment, in addition to obtaining real-time exhaust gas parameters, it is also necessary to clarify the emission standard limits that industrial workshops need to meet. Emission standard limits are established exhaust gas emission indicators that reflect the minimum environmental protection requirements that need to be met after exhaust gas treatment. For example, query and download emission standard documents related to industrial workshops from the official website or database of the environmental protection department, extract the emission limits of various exhaust gas components specified therein, and obtain emission standard limits; connect data with the supervision system of the environmental protection department to obtain the latest emission standard limits in real time, etc.

[0029] The emission standard limits obtained usually include multiple indicators such as concentration limits, rate limits, and removal efficiency of various exhaust gas components. The emission standard limits are stored in the cloud server and associated with the real-time exhaust gas parameters and exhaust gas treatment threshold conditions to form a complete exhaust gas treatment evaluation and control basis. In the subsequent intelligent control process of environmental protection equipment, the cloud server will comprehensively consider the real-time exhaust gas parameters, exhaust gas treatment threshold conditions, and emission standard limits, and dynamically adjust the operating mode and parameters of the environmental protection equipment to ensure that the optimal balance between exhaust gas treatment efficiency and energy consumption is achieved while meeting the emission standard limits.

[0030] By obtaining the emission standard limits of industrial workshops, the goals and requirements that need to be achieved in waste gas treatment are clarified, providing a decision-making basis for the intelligent control of environmental protection equipment.

[0031] S5: When the real-time exhaust gas parameter meets the exhaust gas treatment threshold condition, the first exhaust gas treatment unit and the second exhaust gas treatment unit are switched to a dual-path working mode, and the exhaust gas is synchronously purified according to the emission standard limit.

[0032] Specifically, when the cloud server performs big data analysis on real-time exhaust gas parameters and finds that the real-time exhaust gas parameters meet the preset exhaust gas treatment threshold conditions, it means that the exhaust gas condition in the current industrial workshop is good, and the exhaust gas generation and pollution level are low. At this time, the cloud server will send a control instruction to the control unit of the environmental protection equipment to switch the first exhaust gas treatment unit and the second exhaust gas treatment unit to a dual-channel working mode.

[0033] In the dual-path working mode, the first exhaust gas treatment unit and the second exhaust gas treatment unit simultaneously receive the exhaust gas generated in the industrial workshop through their respective exhaust gas inlets, and perform synchronous purification treatment on the exhaust gas. The exhaust gas first enters the first exhaust gas treatment unit through the exhaust gas inlet of the first exhaust gas treatment unit, and also enters the second exhaust gas treatment unit through the exhaust gas inlet of the second exhaust gas treatment unit. Then, the first exhaust gas treatment unit and the second exhaust gas treatment unit perform synchronous purification treatment on the exhaust gas according to the operating parameters sent by the cloud server, such as treatment temperature, catalyst dosage, adsorbent regeneration cycle, etc. After purification treatment, the exhaust gas that meets the emission standard limit requirements is discharged from the exhaust gas discharge ports of the first exhaust gas treatment unit and the second exhaust gas treatment unit, respectively, completing the exhaust gas treatment process.

[0034] The dual-channel working mode gives full play to the collaborative processing capabilities of the first exhaust gas treatment unit and the second exhaust gas treatment unit, while ensuring the treatment effect, improving the efficiency and economy of exhaust gas treatment. At the same time, the dual-channel working mode can also extend the service life of environmental protection equipment, reduce equipment wear and maintenance costs. In the dual-channel working mode, the cloud server adjusts the operating parameters of the first exhaust gas treatment unit and the second exhaust gas treatment unit in real time according to the emission standard limit, ensuring that all indicators after exhaust gas treatment can stably meet the standards.

[0035] S6: When the real-time exhaust gas parameter does not meet the exhaust gas treatment threshold condition, the first exhaust gas treatment unit and the second exhaust gas treatment unit are switched to a cascade working mode, and the exhaust gas is subjected to graded purification treatment according to the emission standard limit.

[0036] Specifically, when the cloud server performs big data analysis on the real-time exhaust gas parameters and finds that the real-time exhaust gas parameters do not meet the preset exhaust gas treatment threshold conditions, it means that the exhaust gas condition in the current industrial workshop is poor, the exhaust gas generation is large and the pollution level is high. At this time, the cloud server sends a control instruction to the control unit of the environmental protection equipment to switch the first exhaust gas treatment unit and the second exhaust gas treatment unit to the cascade working mode. In the cascade working mode, the first exhaust gas treatment unit and the second exhaust gas treatment unit perform graded purification treatment on the exhaust gas in series. The exhaust gas first enters the first exhaust gas treatment unit through the exhaust gas inlet of the first exhaust gas treatment unit. The first exhaust gas treatment unit performs preliminary purification treatment on the exhaust gas according to the operating parameters issued by the cloud server to remove most of the pollutants. Then, the exhaust gas treated by the first exhaust gas treatment unit enters the exhaust gas inlet of the second exhaust gas treatment unit through the pipeline. The second exhaust gas treatment unit performs deep purification treatment on the exhaust gas according to the operating parameters issued by the cloud server to further remove the residual pollutants and meet the requirements of the emission standard limit. After two-stage purification treatment, the exhaust gas that meets the standards is discharged from the exhaust gas outlet of the second exhaust gas treatment unit, completing the exhaust gas treatment process.

[0037] The cascade working mode makes full use of the hierarchical processing capabilities of the first exhaust gas treatment unit and the second exhaust gas treatment unit. Through multi-stage purification, it effectively treats industrial exhaust gas with high concentration and complex components to ensure that the exhaust gas treatment meets the emission standards. At the same time, the cascade working mode can also avoid the overload operation of a single treatment unit and improve the stability and reliability of environmental protection equipment. Among them, in the cascade working mode, the cloud server dynamically adjusts the operating parameters of the second exhaust gas treatment unit according to the emission standard limit and the actual treatment effect of the first exhaust gas treatment unit, realizing real-time optimization control of the exhaust gas treatment process.

[0038] Furthermore, the embodiment of the present application also includes:

[0039] Integrate multiple types of exhaust gas detection sensors to build sensor integration nodes;

[0040] According to the detection range of the sensor integrated node, the industrial workshop is divided into regions based on the detection range to obtain a plurality of workshop sub-regions;

[0041] A plurality of sensor integration nodes are respectively arranged in a plurality of workshop sub-areas, and the plurality of sensor integration nodes are aggregated to form the exhaust gas collection network.

[0042] In a feasible implementation, the exhaust gas collection network is composed of multiple sensor integrated nodes, and the comprehensive collection and monitoring of exhaust gas parameters in industrial workshops are achieved through distributed sensor integrated nodes.

[0043] In order to achieve the synchronous collection of multiple exhaust gas components and parameters in industrial workshops, a sensor integration node is constructed. The sensor integration node is an integrated collection unit composed of multiple types of exhaust gas detection sensors. Multiple exhaust gas parameters can be detected simultaneously on one node. For example, a sensor integration node can integrate sulfur dioxide sensors, nitrogen oxide sensors, carbon monoxide sensors, dust sensors, etc. to achieve synchronous monitoring of the concentrations of different exhaust gas components; at the same time, the sensor integration node is equipped with environmental parameter sensors such as temperature, humidity, and pressure to achieve the collection of exhaust gas environmental parameters. By integrating multiple types of exhaust gas detection sensors, the sensor integration node can fully reflect the exhaust gas conditions in the area where the node is located, and provide rich parameter support for subsequent data analysis and equipment control.

[0044] Since the distribution and concentration of exhaust gas in industrial workshops have certain spatial differences, in order to achieve refined collection and monitoring of exhaust gas parameters, the industrial workshop is divided into regions. According to the detection range of the sensor integration node, the space of the industrial workshop is grid-divided to obtain multiple workshop sub-regions. Specifically, according to the sensor type, sensitivity, installation height and other parameters of the sensor integration node, the effective detection range of a single sensor integration node is obtained. Then, taking the detection range of the sensor integration node as the basic unit, the plane and space of the industrial workshop are divided to obtain multiple workshop sub-regions of appropriate size and uniform distribution. Each workshop sub-region represents a relatively independent exhaust gas monitoring unit, which can reflect the exhaust gas status characteristics in the region. After obtaining the workshop sub-region division results, a sensor integration node is deployed in each workshop sub-region to achieve effective collection of exhaust gas parameters in the region. The specific layout location and number of sensor integration nodes are designed according to factors such as the size, shape, exhaust gas distribution characteristics and other factors of the workshop sub-region to ensure that the sensor integration node can cover the entire workshop sub-region. After completing the deployment of sensor integration nodes in all workshop sub-areas, the sensor integration nodes distributed in different areas will be networked and aggregated to form an exhaust gas collection network covering the entire industrial workshop. The exhaust gas collection network performs data transmission and node management through wired or wireless means to achieve distributed, real-time collection and monitoring of exhaust gas parameters in industrial workshops.

[0045] By integrating multiple types of exhaust gas detection sensors to build sensor integration nodes, and dividing the industrial workshop into regions according to the detection range of the sensor integration nodes, sensor integration nodes are deployed in each region, and finally an exhaust gas collection network covering the entire industrial workshop is formed. This distributed, multi-parameter, grid-based exhaust gas collection solution can comprehensively, accurately, and in real time reflect the exhaust gas conditions in the industrial workshop, and provide reliable data support for the intelligent control and optimization management of environmental protection equipment. At the same time, this exhaust gas collection network also has strong scalability and flexibility, and can be optimized and adjusted according to the actual situation of the industrial workshop to meet the exhaust gas monitoring needs under different working conditions.

[0046] Furthermore, the embodiment of the present application also includes:

[0047] A preset exhaust gas parameter table, the exhaust gas parameter table including a plurality of exhaust gas parameters, each of the exhaust gas parameters corresponding to an exhaust gas detection sensor of the sensor integrated node;

[0048] Collecting exhaust gas parameter data of corresponding workshop sub-areas through each of the sensor integrated nodes to obtain multiple sets of exhaust gas parameter data;

[0049] For each exhaust gas parameter in the exhaust gas parameter table, searching for a corresponding parameter value in multiple groups of exhaust gas parameter data, and selecting the maximum value therein as the real-time value of the exhaust gas parameter;

[0050] The real-time exhaust gas parameters are generated according to the real-time values ​​of the exhaust gas parameters in the exhaust gas parameter table.

[0051] In a preferred embodiment, in order to standardize and unify the collection and representation of exhaust gas parameters, an exhaust gas parameter table is preset. The exhaust gas parameter table is a structured data template that defines the types, names, units and other attributes of the exhaust gas parameters to be collected. Each exhaust gas parameter item in the exhaust gas parameter table corresponds to an exhaust gas detection sensor in the sensor integration node. For example, the "sulfur dioxide concentration" parameter in the exhaust gas parameter table corresponds to the sulfur dioxide sensor in the sensor integration node; the "nitrogen oxide concentration" parameter corresponds to the nitrogen oxide sensor in the sensor integration node, and so on. By presetting the exhaust gas parameter table, the types and contents of the exhaust gas parameters that need to be collected by the exhaust gas collection network can be clarified to ensure the standardization and consistency of the collected data. After clarifying the types of exhaust gas parameters that need to be collected, each sensor integration node in the exhaust gas collection network collects the exhaust gas parameters of the workshop sub-area where it is located. Specifically, each sensor integration node uses its integrated various types of exhaust gas detection sensors to periodically collect various exhaust gas parameters in the workshop sub-area according to the preset sampling frequency and time interval, such as sulfur dioxide concentration, nitrogen oxide concentration, carbon monoxide concentration, dust concentration, temperature, humidity, etc. The collected exhaust gas parameter data are packaged and labeled in the format of the exhaust gas parameter table to form a set of structured exhaust gas parameter data. Since multiple sensor integration nodes are deployed in the industrial workshop, the exhaust gas collection network can obtain multiple sets of exhaust gas parameter data from different workshop sub-areas within a complete sampling cycle, reflecting the exhaust gas conditions in different areas, and providing a data basis for subsequent exhaust gas parameter fusion.

[0052] Due to the differences in exhaust gas conditions in different workshop sub-areas, in order to fully reflect the overall exhaust gas level in the industrial workshop, multiple sets of exhaust gas parameter data are fused. For each exhaust gas parameter in the exhaust gas parameter table, find its corresponding parameter value in multiple sets of exhaust gas parameter data, and select the maximum value as the real-time value of the exhaust gas parameter. For example, for the exhaust gas parameter "sulfur dioxide concentration", find all the sampling values ​​of "sulfur dioxide concentration" in multiple sets of exhaust gas parameter data, and select the maximum value as the real-time value of "sulfur dioxide concentration". By finding the exhaust gas parameter value with the most serious exhaust gas pollution in the industrial workshop, it is ensured that the real-time exhaust gas parameter can reflect the worst exhaust gas condition and avoid missing any risk of exceeding the standard. By performing maximum value screening on each exhaust gas parameter in the exhaust gas parameter table, the parameter value reflecting the real-time exhaust gas condition of the entire industrial workshop is obtained. After obtaining the real-time values ​​of each exhaust gas parameter in the exhaust gas parameter table, these real-time values ​​are assembled and packaged according to the structure of the exhaust gas parameter table to generate a complete real-time exhaust gas parameter.

[0053] By presetting the exhaust gas parameter table, the collection content and format of the exhaust gas collection network are standardized. Through the distributed collection of each sensor integrated node, multiple groups of exhaust gas parameter data in different areas and at different times are obtained. By screening and fusing the maximum values ​​of multiple groups of exhaust gas parameter data, real-time exhaust gas parameters reflecting the real-time exhaust gas conditions of the entire industrial workshop are generated, providing a decision-making basis for the intelligent control of environmental protection equipment.

[0054] Furthermore, the embodiment of the present application also includes:

[0055] Constructing a historical operation database of the exhaust gas treatment unit, wherein each historical operation data in the historical operation database includes an intake exhaust gas parameter, an operation parameter and a corresponding exhaust gas emission parameter after treatment of the exhaust gas treatment unit;

[0056] Based on the emission standard limit, the historical operation database is retrieved by using big data analysis to obtain a standard-compliant operation data set corresponding to the emission standard limit;

[0057] Retrieving historical operating parameters of the exhaust gas treatment unit from the standard-compliant operating data set, and determining the maximum load operating parameters of the exhaust gas treatment unit under the condition of meeting the emission standard limit;

[0058] According to the maximum load operating parameter, determining an intake exhaust gas parameter that can be processed by the exhaust gas treatment unit under the maximum load operating parameter as the exhaust gas treatment threshold condition;

[0059] When each exhaust gas parameter in the real-time exhaust gas parameters is within the range specified by the exhaust gas treatment threshold condition, determining that the real-time exhaust gas parameter satisfies the exhaust gas treatment threshold condition;

[0060] When any exhaust gas parameter of the real-time exhaust gas parameters is outside the range specified by the exhaust gas treatment threshold condition, it is determined that the real-time exhaust gas parameter does not meet the exhaust gas treatment threshold condition.

[0061] In a preferred embodiment, in order to realize the big data analysis of the exhaust gas treatment unit, a historical operation database covering the historical operation of the exhaust gas treatment unit is first constructed. In the historical operation database, each historical operation data contains three types of key parameters, namely, intake exhaust gas parameters, operation parameters and exhaust gas emission parameters after treatment. Among them, the intake exhaust gas parameters represent the real-time exhaust gas parameters when the exhaust gas treatment unit treats the exhaust gas at this historical moment; the operation parameters represent the actual operation data of the exhaust gas treatment unit at this historical moment, such as the treatment temperature, the amount of catalyst, etc.; the exhaust gas emission parameters after treatment represent the parameters such as the concentration of exhaust gas components measured at the exhaust port after being treated by the exhaust gas treatment unit. By collecting and storing historical data during the long-term operation of the exhaust gas treatment unit, a historical operation database that comprehensively reflects the working conditions and performance of the exhaust gas treatment unit is formed, providing a data basis for subsequent big data analysis. After the historical operation database of the exhaust gas treatment unit is constructed, the historical operation data that meets the emission standard requirements is screened out from the historical operation database according to the emission standard limit. Specifically, the historical operation database is searched and filtered using big data analysis technology to find all historical operation data in which the exhaust gas emission parameters after treatment meet the emission standard limits, forming a standard operation data set. The standard operation data set reflects the operating conditions under which the exhaust gas treatment unit can stably meet the emission standard requirements under different intake and exhaust gas parameters and operating parameters, providing a reference for the subsequent analysis of the maximum treatment capacity of the exhaust gas treatment unit.

[0062] After obtaining the standard operation data set, the maximum processing load of the exhaust gas treatment unit under the condition of meeting the emission standard limit is further analyzed. Specifically, in the standard operation data set, the historical operation parameters of the exhaust gas treatment unit are retrieved, and a set of operation parameters with the highest operation load are found as the maximum load operation parameters of the exhaust gas treatment unit. The maximum load operation parameters indicate the maximum processing capacity and the most stringent operating conditions that the exhaust gas treatment unit can withstand under the premise of ensuring standard emissions, reflecting the limit processing capacity of the exhaust gas treatment unit. After determining the maximum load operation parameters of the exhaust gas treatment unit, the range of intake and exhaust gas parameters that the exhaust gas treatment unit can process under the operating parameters is further analyzed. Specifically, in the standard operation data set, the historical operation data corresponding to the maximum load operation parameters are found, and the intake and exhaust gas parameters therein are extracted as the exhaust gas treatment threshold conditions, indicating the maximum capacity that the exhaust gas treatment unit can effectively process under the maximum load operation parameters. After obtaining the exhaust gas treatment threshold conditions, they are compared with the real-time exhaust gas parameters to determine whether the real-time exhaust gas parameters meet the exhaust gas treatment threshold conditions. Specifically, for each exhaust gas parameter in the real-time exhaust gas parameters, such as exhaust gas component concentration, temperature, humidity, etc., check whether its value is within the corresponding parameter threshold range specified by the exhaust gas treatment threshold condition. If each parameter in the real-time exhaust gas parameters meets the requirements of the exhaust gas treatment threshold condition, it is determined that the real-time exhaust gas parameters meet the exhaust gas treatment threshold condition as a whole, indicating that the current exhaust gas condition is suitable for treatment in a dual-path working mode, and that standard emissions can be achieved. Conversely, if any parameter in the real-time exhaust gas parameters exceeds the specified range of the exhaust gas treatment threshold condition, it is determined that the real-time exhaust gas parameters do not meet the exhaust gas treatment threshold condition as a whole, indicating that the current exhaust gas condition exceeds the processing capacity of the exhaust gas treatment unit under the maximum load operating parameters, and a cascade working mode is required for exhaust gas treatment to ensure standard emissions.

[0063] The method for determining the exhaust gas treatment threshold conditions based on big data analysis fully considers the historical operating experience and actual treatment capacity of the exhaust gas treatment unit, and can more accurately and dynamically reflect the adaptability of the exhaust gas treatment unit to real-time exhaust gas, thereby achieving dynamic optimization of the treatment effect and operating efficiency of environmental protection equipment and improving the intelligence level of environmental protection equipment.

[0064] Further, such as Figure 2 As shown, the embodiment of the present application also includes:

[0065] For the exhaust gas treatment unit, an exhaust gas treatment simulation model is established, wherein the exhaust gas treatment simulation model is used to simulate the treatment efficiency and energy consumption level of the exhaust gas treatment unit under different operating parameters;

[0066] In the target-reaching operation data set, searching for multiple groups of intake and exhaust gas parameters similar to the real-time exhaust gas parameters, and constructing an operation parameter optimization space based on multiple groups of historical operation parameters corresponding to the multiple groups of intake and exhaust gas parameters;

[0067] Using the exhaust gas treatment simulation model, evaluating the treatment efficiency and energy consumption level of different operating parameter combinations in the operating parameter optimization space, and selecting the optimal synchronous operating parameters;

[0068] The first exhaust gas treatment unit and the second exhaust gas treatment unit are controlled to operate synchronously according to the optimal synchronous operation parameters to purify the exhaust gas.

[0069] In a feasible implementation, when the real-time exhaust gas parameters meet the exhaust gas treatment threshold conditions, the first exhaust gas treatment unit and the second exhaust gas treatment unit are switched to a dual-path working mode, and the exhaust gas is simultaneously purified according to the emission standard limit.

[0070] In order to achieve the optimal selection of the operating parameters of the exhaust gas treatment unit under the dual-path working mode, a waste gas treatment simulation model that can reflect the actual working characteristics of the exhaust gas treatment unit is first established. The exhaust gas treatment simulation model is constructed based on the physical structure, chemical reaction mechanism, heat and mass transfer laws, etc. of the exhaust gas treatment unit. By inputting different operating parameters, the exhaust gas treatment simulation model can simulate and calculate the corresponding treatment efficiency and energy consumption level. Among them, the treatment efficiency represents the removal rate of various pollutants in the exhaust gas by the exhaust gas treatment unit under given operating parameters; the energy consumption level represents the amount of resources such as electricity and heat consumed by the exhaust gas treatment unit under given operating parameters. The exhaust gas treatment simulation model quantitatively predicts the performance of the exhaust gas treatment unit under different operating parameters, provides a quantitative basis for the optimization of operating parameters, and reduces the time and cost of actual experiments.

[0071] After the exhaust gas treatment simulation model is established, it is necessary to determine the initial search range for the optimization of the operating parameters. Specifically, in the obtained standard operation data set, multiple groups of intake and exhaust gas parameters similar to the current real-time exhaust gas parameters are searched. The similarity judgment is based on the numerical differences, change trends and other factors of each exhaust gas parameter, and several groups of historical intake and exhaust gas parameters closest to the real-time exhaust gas parameters are selected. Then, the historical operating parameters corresponding to these similar intake and exhaust gas parameters are extracted to form a set containing multiple groups of operating parameters as the operating parameter optimization space. The operating parameter optimization space limits the approximate range of adjustment of the operating parameters of the exhaust gas treatment unit. Searching for the optimal operating parameter combination in this space can reduce the amount of optimization calculation and improve the optimization efficiency. At the same time, since the operating parameter optimization space is determined based on historical operating conditions similar to the real-time exhaust gas parameters, the operating parameter combination obtained by optimization has a higher degree of match with the current actual exhaust gas conditions, and can better meet the needs of real-time exhaust gas standard treatment.

[0072] After determining the optimal space for the operating parameters, the exhaust gas treatment simulation model is used to evaluate and compare the various operating parameter combinations in the optimal space one by one. Specifically, each set of operating parameters is input into the exhaust gas treatment simulation model to simulate and calculate the corresponding treatment efficiency and energy consumption level. In the calculation process, the real-time exhaust gas parameters are used as the intake and exhaust conditions, and the emission standard limit is set as the constraint target of the treatment efficiency, and the operating cost and environmental protection requirements of the exhaust gas treatment unit are comprehensively considered. By exhaustively enumerating all the operating parameter combinations in the optimal space, the treatment efficiency and energy consumption level of the exhaust gas treatment unit under each parameter combination are obtained, and based on this, the parameter combination with high treatment efficiency and low energy consumption level is selected as the optimal synchronous operation parameter. After obtaining the optimal synchronous operation parameter, it is sent to the first exhaust gas treatment unit and the second exhaust gas treatment unit, and the operating status of the two exhaust gas treatment units is adjusted in real time so that they can operate synchronously according to the optimal synchronous operation parameter. In the dual-path working mode, the exhaust gas enters the air inlet of the first exhaust gas treatment unit and the second exhaust gas treatment unit at the same time, and is synchronously purified by the two exhaust gas treatment units respectively, and finally discharged from the exhaust port to meet the standards. Since the two exhaust gas treatment units adopt the optimal combination of operating parameters, the treatment efficiency in the exhaust gas purification process is maximized and the energy consumption level is minimized, achieving a balance between environmental protection and economic benefits.

[0073] Through the dual-path synchronous control method based on simulation optimization, the historical operation data and real-time exhaust gas parameters of the exhaust gas treatment unit are fully utilized, which can dynamically adapt to the changes in the demand for exhaust gas treatment to meet the standards, and improve the intelligent control level of environmental protection equipment. At the same time, the use of optimal synchronous operation parameters can extend the service life of the exhaust gas treatment unit, reduce the maintenance and replacement frequency of the equipment, and provide strong support for clean production and sustainable development.

[0074] Furthermore, the embodiment of the present application also includes:

[0075] Inputting each set of operating parameters in the operating parameter optimization space into the exhaust gas treatment simulation model to simulate and obtain the treatment efficiency and energy consumption level corresponding to each set of operating parameters;

[0076] According to the energy consumption level obtained by the simulation, each group of operating parameters is sorted to obtain a parameter sequence arranged from low to high according to the energy consumption level;

[0077] In the parameter sequence, selecting the operating parameter combination with the lowest energy consumption as the optimal synchronous operating parameter;

[0078] When there are multiple operating parameter combinations with the same energy consumption level, the operating parameter combination with the highest processing efficiency is selected as the optimal synchronous operating parameter.

[0079] In a preferred embodiment, after determining the operating parameter optimization space, first, each set of operating parameters in the operating parameter optimization space is input into the exhaust gas treatment simulation model one by one for simulation calculation. Specifically, for each set of operating parameters, the corresponding parameter values ​​are set in the exhaust gas treatment simulation model, such as treatment temperature, catalyst dosage, etc., and then. Using the real-time exhaust gas parameters as the intake exhaust gas conditions, the simulation model is run for numerical simulation. By solving the physical and chemical process equations inside the exhaust gas treatment unit, the various indicators of the exhaust gas after treatment are calculated to obtain the treatment efficiency and energy consumption level under this set of operating parameters. Repeat the above process, simulate and evaluate all parameter combinations in the operating parameter optimization space one by one, and finally obtain a simulation result set containing the performance indicators of each parameter combination, including the treatment efficiency and energy consumption level corresponding to each set of operating parameters.

[0080] After obtaining the simulation result set of each group of operating parameters in the operating parameter optimization space, these parameter combinations are sorted and screened. First, according to the energy consumption level index of each parameter combination, they are arranged in order from low to high energy consumption to form an ordered parameter sequence. The lower the energy consumption level, the lower the operating cost of the exhaust gas treatment unit under the parameter combination, the better the energy saving effect, and the higher the ranking in the parameter sequence. Through the sorting of energy consumption levels, a batch of parameter combinations with better energy-saving performance are preliminarily screened out to provide a reference for further optimization. Then, in the parameter sequence obtained by sorting according to the energy consumption level, the operating parameter combination with the lowest energy consumption is selected as the optimal synchronous operating parameter under the dual-channel working mode, which means that among all optional operating schemes, the exhaust gas can be treated to the standard with the minimum energy consumption, which represents the best energy efficiency state of the exhaust gas treatment unit. The optimal synchronous operating parameters are sent to the first exhaust gas treatment unit and the second exhaust gas treatment unit, and they are operated synchronously according to the optimal synchronous operating parameters to minimize the energy cost of exhaust gas treatment and improve the economic benefits of environmental protection equipment.

[0081] In another embodiment, there may be multiple operating parameter combinations with the same minimum energy consumption level. In this case, it is difficult to determine the only optimal synchronous operating parameter based on the energy consumption level index alone. In order to further optimize, the processing efficiency is introduced as a criterion. Specifically, among the parameter combinations with the lowest energy consumption level, the respective processing efficiency indexes are compared, and the operating parameter combination with the highest processing efficiency is selected as the optimal synchronous operating parameter, so as to maximize the exhaust gas treatment effect while ensuring the lowest energy consumption, and achieve a win-win situation of environmental protection and economic benefits.

[0082] By comprehensively considering the energy consumption level and treatment efficiency of the exhaust gas treatment unit, the optimal synchronous operating parameters that take into account both energy saving and emission reduction are finally screened out. The analytical capabilities of the simulation model are fully utilized, which avoids blind parameter adjustment and trial and error in actual operation, shortens the optimization time, and reduces the optimization cost.

[0083] Furthermore, the embodiment of the present application also includes:

[0084] Determining a pre-exhaust gas treatment unit and a post-exhaust gas treatment unit according to the first exhaust gas treatment unit and the second exhaust gas treatment unit;

[0085] Obtaining full-load operating parameters of the pre-exhaust gas treatment unit as optimal primary operating parameters, inputting the real-time exhaust gas parameters and the optimal primary operating parameters into the exhaust gas treatment simulation model, and simulating to obtain intermediate exhaust gas parameters;

[0086] Taking the intermediate exhaust gas parameters as the post-real-time exhaust gas parameters of the post-exhaust gas treatment unit, constructing a post-operation parameter optimization space;

[0087] Based on the exhaust gas treatment simulation model, taking the emission standard limit as a target, parameter optimization is performed in the post-operation parameter optimization space to obtain the optimal secondary operation parameters;

[0088] The front exhaust gas treatment unit is controlled with the optimal primary operating parameters, and the rear exhaust gas treatment unit is controlled with the optimal secondary operating parameters to perform graded purification treatment on the exhaust gas.

[0089] In a preferred embodiment, after the first exhaust gas treatment unit and the second exhaust gas treatment unit are switched to the cascade working mode, first, the order of the first exhaust gas treatment unit and the second exhaust gas treatment unit in the exhaust gas treatment process is determined. By comparing the processing capacity and historical operation data of the two exhaust gas treatment units, one of the exhaust gas treatment units is designated as the front exhaust gas treatment unit and the other is designated as the rear exhaust gas treatment unit, so as to achieve graded purification of exhaust gas and give full play to the synergy of the two exhaust gas treatment units. After determining the front exhaust gas treatment unit, its full load operation parameters are obtained as the optimal primary operation parameters. The full load operation parameters represent the optimal operating conditions of the front exhaust gas treatment unit under full load, which are obtained by querying the historical operation database or optimizing and calculating using the exhaust gas treatment simulation model. Then, the real-time exhaust gas parameters and the optimal primary operation parameters are input into the exhaust gas treatment simulation model to simulate the processing process of the front exhaust gas treatment unit on the real-time exhaust gas, and obtain the intermediate exhaust gas parameters after the primary treatment. The intermediate exhaust gas parameters reflect the processing effect of the front exhaust gas treatment unit and are an important basis for the subsequent optimization of the operating parameters of the rear exhaust gas treatment unit.

[0090] After obtaining the intermediate exhaust gas parameters, they are used as the intake exhaust gas conditions of the post-exhaust gas treatment unit, that is, the post-real-time exhaust gas parameters. Based on the post-real-time exhaust gas parameters and referring to the historical operation data of the post-exhaust gas treatment unit, a post-operation parameter optimization space containing multiple sets of feasible operation parameters is constructed. The optimization space limits the range of adjustment of the operation parameters of the post-exhaust gas treatment unit, and searches for the optimal combination of operation parameters within this range, reduces the optimization calculation amount, and improves the optimization efficiency. At the same time, since the optimization space is dynamically generated according to the intermediate exhaust gas parameters, the obtained optimal operation parameters are more matched with the exhaust gas condition after the primary treatment, and can better meet the needs of graded purification. After constructing the post-operation parameter optimization space, the exhaust gas treatment simulation model is used to meet the emission standard limit as the optimization goal, and the optimal combination of operation parameters is searched in the optimization space as the optimal secondary operation parameters. Specifically, each set of operation parameters and post-real-time exhaust gas parameters in the optimization space are input into the exhaust gas treatment simulation model to simulate the treatment process of the post-exhaust gas treatment unit and calculate the exhaust gas emission index after the secondary treatment. Through exhaustive search and comparison, we find the operating parameter combination that can meet the emission standard limit, and select the parameter combination with the best treatment effect and the lowest energy consumption level as the optimal secondary operating parameters. This parameter combination represents the optimal operating state of the post-exhaust gas treatment unit in the secondary treatment stage of graded purification, which can minimize energy consumption and operating costs while ensuring standard emissions.

[0091] After obtaining the optimal primary and secondary operating parameters, they are sent to the pre-exhaust gas treatment unit and the post-exhaust gas treatment unit respectively, and the operating status of the two exhaust gas treatment units is adjusted in real time so that they can operate in coordination according to the optimal parameter combination to form a complete hierarchical purification process. Specifically, the exhaust gas first enters the pre-exhaust gas treatment unit, and undergoes primary purification treatment under the control of the optimal primary operating parameters to remove most pollutants; then, the exhaust gas after primary treatment enters the post-exhaust gas treatment unit, and undergoes secondary purification treatment under the control of the optimal secondary operating parameters to further remove residual pollutants until the emission standard limit requirements are met. Through the coordinated optimization control of the front and rear exhaust gas treatment units, the efficiency of the exhaust gas hierarchical purification process is maximized and the cost is minimized, achieving a balanced unity of environmental protection and economic benefits.

[0092] Furthermore, the embodiment of the present application also includes:

[0093] Obtaining historical pre-times of the first exhaust gas treatment unit and the second exhaust gas treatment unit to obtain a first historical pre-time and a second historical pre-time;

[0094] When the first historical pre-time number is less than the second historical pre-time number, the first exhaust gas treatment unit is set as a pre-exhaust gas treatment unit, and the second exhaust gas treatment unit is set as a post-exhaust gas treatment unit;

[0095] When the first historical pre-time number is greater than the second historical pre-time number, the first exhaust gas treatment unit is set as a post-exhaust gas treatment unit, and the second exhaust gas treatment unit is set as a pre-exhaust gas treatment unit;

[0096] When the first historical pre-time number is equal to the second historical pre-time number, the pre-exhaust gas treatment unit and the post-exhaust gas treatment unit are randomly set.

[0097] In a preferred embodiment, in order to determine the front and rear exhaust gas treatment units, first, the number of times the first exhaust gas treatment unit and the second exhaust gas treatment unit played the leading role in the past cascade working mode is obtained, which are respectively referred to as the first historical leading number and the second historical leading number. Specifically, by querying the historical operation records of the environmental protection equipment, the number of times the first exhaust gas treatment unit and the second exhaust gas treatment unit were respectively operated as the leading exhaust gas treatment unit in all previous cascade working modes is counted, and the first historical leading number and the second historical leading number are obtained, reflecting the frequency of the two exhaust gas treatment units assuming the leading role in the past cascade work. Subsequently, the leading exhaust gas treatment unit and the rear exhaust gas treatment unit are determined according to the first historical leading number and the second historical leading number. Among them, the exhaust gas treatment unit with fewer historical leading times has a relatively small accumulated full load workload, and is more suitable for assuming the leading role in this cascade work and the preliminary purification task of high-concentration exhaust gas; while the exhaust gas treatment unit with more historical leading times has a relatively large accumulated full load workload, and is more suitable for assuming the rear role and deeply purifying the exhaust gas that has been preliminarily treated. By rotating the front and rear roles, the load intensity of the two exhaust gas treatment units can be dynamically balanced to avoid long-term full-load operation of a certain exhaust gas treatment unit and accelerate aging, thereby extending the overall service life of the equipment and reducing the operation and maintenance costs of environmental protection facilities. At the same time, by rotating the front and rear roles, the working capacity of the two exhaust gas treatment units can be synchronized and balanced, avoiding the inability to use unified operating parameters due to inconsistent processing capacity in the dual-channel working mode.

[0098] Therefore, after comparing the first historical pre-number and the second historical pre-number, when the first historical pre-number is less than the second historical pre-number, it means that the first exhaust gas treatment unit has played the pre-number role less times in the past cascade work, and the first exhaust gas treatment unit is set as the pre-number exhaust gas treatment unit in this cascade working mode, and the second exhaust gas treatment unit with a larger number of historical pre-number is set as the post-number exhaust gas treatment unit. On the contrary, when the first historical pre-number is greater than the second historical pre-number, the first exhaust gas treatment unit is set as the post-number exhaust gas treatment unit, and the second exhaust gas treatment unit is set as the pre-number exhaust gas treatment unit. When the first historical pre-number and the second historical pre-number are equal, the two exhaust gas treatment units have the same frequency of playing the pre-number role in the past cascade work, and their workloads are basically the same. At this time, the pre- and post-number exhaust gas treatment units are set randomly.

[0099] By fully considering the historical workload of the two exhaust treatment units when determining the front and rear exhaust treatment units, and by dynamically balancing the allocation frequency of their front roles, the synchronization and consistency of processing capabilities can be achieved, thereby maximizing the synergistic efficiency of the two exhaust treatment units, extending their service life, and providing guarantee for unified parameter control in dual-path working mode.

[0100] In summary, the environmental protection equipment intelligent management method integrating the Internet of Things and big data provided by the embodiment of the present application has the following technical effects:

[0101] Environmental protection equipment is set up in the industrial workshop. The environmental protection equipment includes two identical exhaust gas treatment units, namely the first exhaust gas treatment unit and the second exhaust gas treatment unit, to provide necessary hardware facilities for realizing flexible exhaust gas treatment mode. An exhaust gas collection network is deployed in the industrial workshop. The exhaust gas collection network is composed of multiple IoT sensors. The exhaust gas parameters in the industrial workshop are collected through the exhaust gas collection network to obtain real-time exhaust gas parameters, providing a data basis for subsequent intelligent decision-making and equipment control. The real-time exhaust gas parameters are transmitted to the cloud server, and the real-time exhaust gas parameters are analyzed by big data in the cloud server to evaluate whether the real-time exhaust gas parameters meet the exhaust gas treatment threshold conditions of the exhaust gas treatment unit. The big data analysis technology is used for processing and mining, and the current exhaust gas condition is intelligently judged whether it exceeds the equipment processing capacity, providing a decision-making basis for the working mode switching. The emission standard limit of the industrial workshop is obtained. The emission standard limit is the emission index that needs to be achieved after the exhaust gas treatment, which provides a reference for evaluating the treatment effect and ensuring that the exhaust gas emissions meet environmental protection requirements. When the real-time exhaust gas parameters meet the exhaust gas treatment threshold conditions, the first exhaust gas treatment unit and the second exhaust gas treatment unit are switched to the dual-path working mode, and the exhaust gas is synchronously purified according to the emission standard limit. When the exhaust gas concentration is low, the dual-path synchronous processing mode is adopted to give full play to the capabilities of the two processing units and improve the exhaust gas treatment efficiency. When the real-time exhaust gas parameters do not meet the exhaust gas treatment threshold conditions, the first exhaust gas treatment unit and the second exhaust gas treatment unit are switched to the cascade working mode, and the exhaust gas is graded and purified according to the emission standard limit. When the exhaust gas concentration is high, the cascade graded processing mode is adopted. Through multiple treatments, the exhaust gas concentration is gradually reduced, and finally the emission is up to standard. By flexibly switching between the dual-path and cascade working modes, the intelligent level of environmental protection equipment management is improved, ensuring that the exhaust gas is stably up to standard.

[0102] Any step of the method described above can be stored as a computer instruction or program in an unlimited computer memory, and can be called and recognized by an unlimited computer processor to implement any method in the embodiments of the present application, without any unnecessary restrictions.

[0103] Furthermore, the first or second mentioned above may not only represent an order relationship, but may also represent a specific concept, and / or refer to multiple elements that can be selected individually or in full. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these changes and variations.

Claims

1. An intelligent management method for environmental protection equipment integrating the Internet of Things and big data, characterized in that: The method comprises: An environmental protection device is arranged in an industrial workshop, wherein the environmental protection device comprises two identical exhaust gas treatment units, namely a first exhaust gas treatment unit and a second exhaust gas treatment unit; Deploy an exhaust gas collection network in the industrial workshop, wherein the exhaust gas collection network is composed of a plurality of IoT sensors, and exhaust gas parameters in the industrial workshop are collected through the exhaust gas collection network to obtain real-time exhaust gas parameters; Transmitting the real-time exhaust gas parameters to a cloud server, performing big data analysis on the real-time exhaust gas parameters in the cloud server, and evaluating whether the real-time exhaust gas parameters meet the exhaust gas treatment threshold conditions of the exhaust gas treatment unit; Obtaining the emission standard limit value of the industrial workshop, wherein the emission standard limit value is the emission index that needs to be achieved after the exhaust gas is treated; When the real-time exhaust gas parameter meets the exhaust gas treatment threshold condition, the first exhaust gas treatment unit and the second exhaust gas treatment unit are switched to a dual-path working mode to perform synchronous purification treatment on the exhaust gas according to the emission standard limit; When the real-time exhaust gas parameter does not meet the exhaust gas treatment threshold condition, switching the first exhaust gas treatment unit and the second exhaust gas treatment unit to a cascade working mode, and performing graded purification treatment on the exhaust gas according to the emission standard limit; Wherein, an exhaust gas collection network is deployed in the industrial workshop, and the exhaust gas collection network is composed of multiple Internet of Things sensors, including: Integrate multiple types of exhaust gas detection sensors to build sensor integration nodes; According to the detection range of the sensor integrated node, the industrial workshop is divided into regions based on the detection range to obtain a plurality of workshop sub-regions; Arrange a plurality of sensor integration nodes in a plurality of workshop sub-areas respectively, and aggregate the plurality of sensor integration nodes to form the exhaust gas collection network; Wherein, the exhaust gas parameters in the industrial workshop are collected through the exhaust gas collection network to obtain real-time exhaust gas parameters, including: A preset exhaust gas parameter table, the exhaust gas parameter table including a plurality of exhaust gas parameters, each of the exhaust gas parameters corresponding to an exhaust gas detection sensor of the sensor integrated node; Collecting exhaust gas parameter data of corresponding workshop sub-areas through each of the sensor integrated nodes to obtain multiple sets of exhaust gas parameter data; For each exhaust gas parameter in the exhaust gas parameter table, searching for a corresponding parameter value in multiple groups of exhaust gas parameter data, and selecting the maximum value therein as the real-time value of the exhaust gas parameter; Generate the real-time exhaust gas parameter according to the real-time value of each exhaust gas parameter in the exhaust gas parameter table; The first exhaust gas treatment unit and the second exhaust gas treatment unit are switched to a cascade working mode, and the exhaust gas is subjected to graded purification treatment according to the emission standard limit, including: Determining a pre-exhaust gas treatment unit and a post-exhaust gas treatment unit according to the first exhaust gas treatment unit and the second exhaust gas treatment unit; Obtaining full-load operating parameters of the pre-exhaust gas treatment unit as optimal primary operating parameters, inputting the real-time exhaust gas parameters and the optimal primary operating parameters into the exhaust gas treatment simulation model, and simulating to obtain intermediate exhaust gas parameters; Taking the intermediate exhaust gas parameters as the post-real-time exhaust gas parameters of the post-exhaust gas treatment unit, constructing a post-operation parameter optimization space; Based on the exhaust gas treatment simulation model, taking the emission standard limit as a target, parameter optimization is performed in the post-operation parameter optimization space to obtain the optimal secondary operation parameters; The front exhaust gas treatment unit is controlled with the optimal first-level operating parameters, and the rear exhaust gas treatment unit is controlled with the optimal second-level operating parameters to perform graded purification treatment on the exhaust gas; Among them, the pre-exhaust gas treatment unit and the post-exhaust gas treatment unit are determined, including: Obtaining historical pre-times of the first exhaust gas treatment unit and the second exhaust gas treatment unit to obtain a first historical pre-time and a second historical pre-time; When the first historical pre-time number is less than the second historical pre-time number, the first exhaust gas treatment unit is set as a pre-exhaust gas treatment unit, and the second exhaust gas treatment unit is set as a post-exhaust gas treatment unit; When the first historical pre-time number is greater than the second historical pre-time number, the first exhaust gas treatment unit is set as a post-exhaust gas treatment unit, and the second exhaust gas treatment unit is set as a pre-exhaust gas treatment unit; When the first historical pre-time number is equal to the second historical pre-time number, the pre-exhaust gas treatment unit and the post-exhaust gas treatment unit are randomly set.

2. The environmental protection equipment intelligent management method according to claim 1, characterized in that: Performing big data analysis on the real-time exhaust gas parameters in the cloud server to evaluate whether the real-time exhaust gas parameters meet the exhaust gas treatment threshold conditions of the exhaust gas treatment unit, including: Constructing a historical operation database of the exhaust gas treatment unit, wherein each historical operation data in the historical operation database includes an intake exhaust gas parameter, an operation parameter and a corresponding exhaust gas emission parameter after treatment of the exhaust gas treatment unit; Based on the emission standard limit, the historical operation database is retrieved by using big data analysis to obtain a standard-compliant operation data set corresponding to the emission standard limit; Retrieving historical operating parameters of the exhaust gas treatment unit from the standard-compliant operating data set, and determining the maximum load operating parameters of the exhaust gas treatment unit under the condition of meeting the emission standard limit; According to the maximum load operating parameter, determining an intake exhaust gas parameter that can be processed by the exhaust gas treatment unit under the maximum load operating parameter as the exhaust gas treatment threshold condition; When each exhaust gas parameter in the real-time exhaust gas parameters is within the range specified by the exhaust gas treatment threshold condition, determining that the real-time exhaust gas parameter satisfies the exhaust gas treatment threshold condition; When any exhaust gas parameter of the real-time exhaust gas parameters is outside the range specified by the exhaust gas treatment threshold condition, it is determined that the real-time exhaust gas parameter does not meet the exhaust gas treatment threshold condition.

3. The environmental protection equipment intelligent management method according to claim 2, characterized in that: Switching the first exhaust gas treatment unit and the second exhaust gas treatment unit to a dual-path working mode, and performing synchronous purification treatment on the exhaust gas according to the emission standard limit, includes: For the exhaust gas treatment unit, an exhaust gas treatment simulation model is established, wherein the exhaust gas treatment simulation model is used to simulate the treatment efficiency and energy consumption level of the exhaust gas treatment unit under different operating parameters; In the target-reaching operation data set, searching for multiple groups of intake and exhaust gas parameters similar to the real-time exhaust gas parameters, and constructing an operation parameter optimization space based on multiple groups of historical operation parameters corresponding to the multiple groups of intake and exhaust gas parameters; Using the exhaust gas treatment simulation model, evaluating the treatment efficiency and energy consumption level of different operating parameter combinations in the operating parameter optimization space, and selecting the optimal synchronous operating parameters; The first exhaust gas treatment unit and the second exhaust gas treatment unit are controlled to operate synchronously according to the optimal synchronous operation parameters to purify the exhaust gas.

4. The environmental protection equipment intelligent management method according to claim 3, characterized in that: The exhaust gas treatment simulation model is used to evaluate the treatment efficiency and energy consumption level of different operating parameter combinations in the operating parameter optimization space, and the optimal synchronous operating parameters are screened out, including: Inputting each set of operating parameters in the operating parameter optimization space into the exhaust gas treatment simulation model to simulate and obtain the treatment efficiency and energy consumption level corresponding to each set of operating parameters; According to the energy consumption level obtained by the simulation, each group of operating parameters is sorted to obtain a parameter sequence arranged from low to high according to the energy consumption level; In the parameter sequence, selecting the operating parameter combination with the lowest energy consumption as the optimal synchronous operating parameter; When there are multiple operating parameter combinations with the same energy consumption level, the operating parameter combination with the highest processing efficiency is selected as the optimal synchronous operating parameter.

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