A collaborative monitoring system for carbon pollution at enterprise sewage outlets based on the Internet of Things

Abstract

The invention relates to the field of sewage discharge monitoring, and discloses a pollution-carbon collaborative supervision system for enterprise sewage outlets based on the Internet of Things, comprising: firstly, setting up monitoring points at the sewage outlet of each discharge user to monitor the sewage discharged from the sewage outlet; then obtaining pollution-carbon data in the sewage discharge process of each sewage outlet, and transmitting the pollution-carbon data collected by a data acquisition module to a cloud platform for storage; then processing and analyzing the pollution-carbon data of the cloud platform to obtain a sewage treatment evaluation coefficient of each sewage outlet, and comparing the sewage treatment evaluation coefficient with a preset sewage treatment evaluation threshold value; if the sewage treatment evaluation coefficient is ≥ the sewage treatment evaluation threshold value, it is judged that the sewage treatment effect of the current discharge user is poor, otherwise, it is judged that the sewage treatment effect of the current discharge user is good; finally, according to the judgment result of the data processing and analysis module, a warning signal is issued to the discharge user with poor sewage treatment effect.

Description

Technical Field

[0001] The present invention relates to the field of pollution discharge monitoring, and in particular to a pollution-carbon collaborative monitoring system for enterprise sewage outlets based on the Internet of Things. Background Art

[0002] Carbon verification refers to the verification of greenhouse gas emission reports submitted by carbon emission units participating in carbon emission rights trading by third-party service agencies to ensure that the emission data submitted by carbon emission units are valid. Carbon verification can understand the impact of direct and indirect greenhouse gas emissions on the climate and set emission reduction targets by counting greenhouse gases emitted directly and indirectly.

[0003] The carbon emission and heat statistics in wastewater discharged by carbon emission units are often ignored in the carbon verification process. Although the wastewater discharge of carbon emission units is subject to the constraints of pollution discharge permits, there is a lack of monitoring and supervision of the total carbon content, wastewater heat, and energy consumption in the wastewater treatment process.

[0004] Carbon emission units are generally concentrated in urban industrial parks. Since the characteristic pollutants of each unit are different, if the pollution factors such as heavy metal concentration in the discharged sewage exceed the standard, it will directly affect the treatment efficiency of the sewage treatment plant. Therefore, the park management committee has the need to strengthen the supervision of the drainage behavior of the drainage households. Usually, the regulatory authorities set up monitoring stations for conventional pollutants and characteristic pollutants at the outlets of enterprises to monitor the compliance of pollutant discharge permits. However, these test data are generally only used for compliance supervision, and no further data processing is done on the platform side. The data utilization is low, and it fails to provide data value for the regulatory authorities to establish a dynamic drainage household supervision mechanism and for enterprises to reduce costs and increase efficiency. Summary of the invention

[0005] The purpose of the present invention is to provide a coordinated carbon pollution monitoring system for enterprise sewage outlets based on the Internet of Things to solve the above technical problems.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] A coordinated carbon pollution monitoring system for enterprise sewage outlets based on the Internet of Things, including:

[0008] A monitoring module is used to set up monitoring points at the sewage outlet of each discharge user to monitor the sewage discharged from the sewage outlet;

[0009] The data acquisition module is used to obtain the carbon pollution data of each sewage outlet during the sewage discharge process. The carbon pollution data includes: total carbon content, sewage flow, sewage heat and pollutant concentration;

[0010] A communication module, used to transmit the polluted carbon data collected by the data collection module to the cloud platform for storage;

[0011] The data processing and analysis module is used to process and analyze the carbon pollution data of the cloud platform, obtain the sewage treatment evaluation coefficient of each sewage outlet, and compare the sewage treatment evaluation coefficient with the preset sewage treatment evaluation threshold. If the sewage treatment evaluation coefficient ≥ the sewage treatment evaluation threshold, it is judged that the sewage treatment effect of the current discharge user is poor, otherwise, it is judged that the sewage treatment effect of the current discharge user is good;

[0012] The early warning module sends out early warning signals to discharge users with poor sewage treatment effects based on the judgment results of the data processing and analysis module.

[0013] As a further technical solution, the process of collecting carbon pollution data at each monitoring point is as follows:

[0014] The total carbon content data is obtained by testing with a total organic carbon analyzer;

[0015] The pollutant concentration data is obtained through detection by characteristic pollutant detection equipment; the pollutant concentration data includes oil concentration, ammonia nitrogen concentration and total phosphorus concentration in water;

[0016] Among them, the oil concentration in water is detected by an oil-in-water analyzer, the ammonia nitrogen concentration is detected by an ammonia nitrogen analyzer, and the total phosphorus concentration is detected by a total phosphorus analyzer;

[0017] The sewage flow and sewage heat are detected by an integrated or split pipe segment electromagnetic flow calorimeter.

[0018] As a further technical solution, the process of processing the pollution carbon data is as follows:

[0019] The detected total carbon content, sewage flow, sewage heat, oil concentration in water, ammonia nitrogen concentration and total phosphorus concentration are compared with their corresponding preset thresholds respectively;

[0020] If at least one item exceeds the corresponding preset threshold and / or at least one fluctuation value within a unit time exceeds the preset fluctuation threshold, the sewage outlet is marked as abnormal, and the data within a working cycle from the current moment is traced back for the next analysis;

[0021] Otherwise, the sewage outlet shall not be marked.

[0022] As a further technical solution, the process of judging whether the fluctuation value within a unit time exceeds a preset fluctuation threshold is as follows:

[0023] The total carbon content, sewage flow, sewage heat, oil concentration in water, ammonia nitrogen concentration and total phosphorus concentration are recorded as the first, second, third, ..., sixth parameters in sequence;

[0024] Each parameter is randomly sampled M times in a unit time, and the value of the kth parameter at the mth sampling time point is set to F km;

[0025] pass Calculate the fluctuation value B of the kth parameter k , and then through B k -B k0 Compare with 0;

[0026] If B k -B k0 >0, then determine the fluctuation value B of the kth parameter in unit time k Exceeding the preset fluctuation threshold B k0 .

[0027] As a further technical solution, the process of obtaining the sewage treatment assessment coefficient is as follows:

[0028] Total carbon TOC μ , sewage flow Q μ , sewage heat T μ , Oil concentration in water R μ , ammonia nitrogen concentration D μ and total phosphorus concentration P μ Substitute into the following formula:

[0029]

[0030] Calculate the sewage treatment assessment coefficient A of the μth sewage outlet μ ;

[0031] Among them, TOC th , Q th , T th , R th , D th , P th are the preset thresholds for total carbon, sewage flow, sewage heat, oil concentration in water, ammonia nitrogen concentration, and total phosphorus concentration, respectively, a , b , c , d , f , g is the preset weight factor, B1, B2, B3, B4, B5, B6 are the fluctuation values ​​of the 1st, 2nd, 3rd, ..., 6th parameters in the previous unit time respectively, is the judgment function.

[0032] As a further technical solution, the expression of the judgment function is:

[0033]

[0034] When each parameter is lower than or equal to the corresponding preset threshold,

[0035] When at least one parameter exceeds the corresponding preset threshold,

[0036] Among them, x i is the change value of the parameter exceeding the preset threshold within a working cycle, β i is the weight coefficient, and n is the number of parameters that exceed the corresponding preset threshold.

[0037] As a further technical solution, by the following formula:

[0038]

[0039] Calculate the change value of the current parameter within a working cycle;

[0040] Among them, θ1 and θ2 are preset proportional coefficients, ω1 and ω2 are influencing factors, and max{F k} is the maximum value of the current parameter in a working cycle, min{F k} is the minimum value of the current parameter within a working cycle.

[0041] As a further technical solution, the system also includes a visualization module for displaying the judgment results of the data processing and analysis module.

[0042] Beneficial effects of the present invention:

[0043] The present invention collects and transmits pollution and carbon data through the monitoring module, the data acquisition module and the communication module, and then processes and analyzes the pollution and carbon data of the cloud platform through the data processing and analysis module. It can not only coordinate the supervision of the sewage treatment and carbon emission conditions of each sewage outlet, but also make an overall response with the sewage treatment evaluation coefficient. Obviously, the more sewage outlets with good sewage treatment effects each discharge user has, the better the sewage treatment effect of the discharge user, and vice versa, the worse the sewage treatment effect. Through the above judgment, an early warning can be issued to the discharge users with poor sewage treatment effects, so as to achieve the purpose of effectively urging and improving the discharge users. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The present invention will be further described below in conjunction with the accompanying drawings.

[0045] Figure 1 It is a system structure block diagram of the present invention. DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe 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 creative work are within the scope of protection of the present invention.

[0047] See also Figure 1 As shown, the present invention is a coordinated carbon pollution monitoring system for enterprise sewage outlets based on the Internet of Things, comprising:

[0048] A monitoring module is used to set up monitoring points at the sewage outlet of each discharge user to monitor the sewage discharged from the sewage outlet;

[0049] The data acquisition module is used to obtain the carbon pollution data of each sewage outlet during the sewage discharge process. The carbon pollution data includes: total carbon content, sewage flow, sewage heat and pollutant concentration;

[0050] A communication module, used to transmit the polluted carbon data collected by the data collection module to the cloud platform for storage;

[0051] The data processing and analysis module is used to process and analyze the carbon pollution data of the cloud platform, obtain the sewage treatment evaluation coefficient of each sewage outlet, and compare the sewage treatment evaluation coefficient with the preset sewage treatment evaluation threshold. If the sewage treatment evaluation coefficient ≥ the sewage treatment evaluation threshold, it is judged that the sewage treatment effect of the current discharge user is poor, otherwise, it is judged that the sewage treatment effect of the current discharge user is good;

[0052] The early warning module sends out early warning signals to discharge users with poor sewage treatment effects based on the judgment results of the data processing and analysis module.

[0053] The process of collecting carbon pollution data at each monitoring point is as follows:

[0054] The total carbon content data is obtained by testing with a total organic carbon analyzer;

[0055] The pollutant concentration data is obtained through detection by characteristic pollutant detection equipment; the pollutant concentration data includes oil concentration, ammonia nitrogen concentration and total phosphorus concentration in water;

[0056] Among them, the oil concentration in water is detected by an oil-in-water analyzer, the ammonia nitrogen concentration is detected by an ammonia nitrogen analyzer, and the total phosphorus concentration is detected by a total phosphorus analyzer;

[0057] The sewage flow and sewage heat are detected by an integrated or split-type pipe-section electromagnetic flow calorimeter. It should be noted that the detection and installation process of the above-mentioned various instruments are all existing technologies, which will not be repeated here; the auxiliary unit in the attached figure is used to assist in data collection, and the specific description is as follows: the data acquisition and transmission unit is composed of a host computer control screen and a data transmission DTU (or VPN), which can be integrated into a monitoring camera as needed; the water collection and distribution unit is composed of a pressure reducing valve, a water collection pipeline, a pre-filter, a diaphragm pump and a water distribution tank installed on the sewage pipe, which can conveniently provide test water samples for the analysis unit; an optional sample retention unit can be used. When the water quality exceeds the standard, the automatic sample retention device can collect water samples in the water distribution tank and store them in a cold storage; the security unit includes an access control system, an analyzer leakage alarm, a smoke sensor, etc., and a proximity sensor can be set as needed; the above-mentioned specific installation and detection are all existing technologies, and those skilled in the art can achieve them by selecting conventional technologies, so there is no need to repeat them.

[0058] In this embodiment, a comprehensive processing method for carbon pollution data is provided. The carbon pollution data is first collected and transmitted through the monitoring module, the data acquisition module, and the communication module. Then, the carbon pollution data of the cloud platform is processed and analyzed through the data processing and analysis module to obtain the sewage treatment assessment coefficient of each sewage outlet. The sewage treatment assessment coefficient is compared with the preset sewage treatment assessment threshold. If the sewage treatment assessment coefficient ≥ the sewage treatment assessment threshold, it is judged that the sewage treatment effect of the current discharge user is poor. Otherwise, it is judged that the sewage treatment effect of the current discharge user is good. Through the above technical scheme, it is possible to coordinate the sewage treatment situation and carbon emission situation of each sewage outlet, and to respond as a whole with the sewage treatment assessment coefficient. Obviously, the more sewage outlets with good sewage treatment effects each discharge user has, the better the sewage treatment effect of the discharge user. Conversely, the worse the sewage treatment effect is. Through the above judgment, an early warning can be issued to the discharge user with poor sewage treatment effect, so as to achieve the purpose of effectively urging the discharge user to improve.

[0059] The process of processing the pollution carbon data is as follows:

[0060] The detected total carbon content, sewage flow, sewage heat, oil concentration in water, ammonia nitrogen concentration and total phosphorus concentration are compared with their corresponding preset thresholds respectively;

[0061] If at least one item exceeds the corresponding preset threshold and / or at least one fluctuation value within a unit time exceeds the preset fluctuation threshold, the sewage outlet is marked as abnormal, and the data within a working cycle from the current moment is traced back for the next analysis;

[0062] Otherwise, the sewage outlet is not marked. Through the above technical solution, sewage outlets including one or both of the above situations are marked as abnormal, thereby reducing invalid analysis objects for subsequent analysis, thereby improving analysis efficiency.

[0063] The process of judging whether the fluctuation value within a unit time exceeds the preset fluctuation threshold is as follows:

[0064] The total carbon content, sewage flow, sewage heat, oil concentration in water, ammonia nitrogen concentration and total phosphorus concentration are recorded as the first, second, third, ..., sixth parameters in sequence;

[0065] Each parameter is randomly sampled M times in a unit time, and the value of the kth parameter at the mth sampling time point is set to F km ;

[0066] pass Calculate the fluctuation value B of the kth parameter k , and then through B k -B k0 Compare with 0;

[0067] If B k -B k0 >0, then determine the fluctuation value B of the kth parameter in unit time k Exceeding the preset fluctuation threshold B k0 .

[0068] Through the above technical solution, by analyzing the various parameters in the previous unit time, the standard deviation is used to Calculate the fluctuation value B of the kth parameter k , so as to accurately reflect the fluctuations of various parameters in the previous unit time. Obviously, the larger the fluctuation value, the greater the fluctuation of the parameter, that is, the more unstable it is, and the higher the possibility of carbon emissions and excessive sewage discharge.

[0069] The process of obtaining the sewage treatment assessment coefficient is as follows:

[0070] Total carbon TOC μ , sewage flow Q μ , sewage heat T μ , Oil concentration in water R μ , ammonia nitrogen concentration D μ and total phosphorus concentration P μ Substitute into the following formula:

[0071]

[0072] Calculate the sewage treatment assessment coefficient A of the μth sewage outlet μ ;

[0073] Among them, TOC th , Q th , T th , R th , D th , P th are the preset thresholds for total carbon, sewage flow, sewage heat, oil concentration in water, ammonia nitrogen concentration, and total phosphorus concentration, respectively, a , b , c , d , f , g is a preset weight factor, determined based on historical data and empirical data analysis. B1, B2, B3, B4, B5, and B6 are the fluctuation values ​​of the 1st, 2nd, 3rd, ..., 6th parameters in the previous unit time, respectively. is the judgment function.

[0074] In this embodiment, a method for evaluating the sewage treatment coefficient of the current sewage outlet is provided, by using the total carbon content TOC μ , sewage flow Q μ , sewage heat T μ , Oil concentration in water R μ , ammonia nitrogen concentration D μ and total phosphorus concentration P μ Establish a correlation model to achieve the purpose of synergistically responding to the overall situation of sewage treatment and carbon emissions, and then play a role in concise display of judgment results and effective supervision of carbon pollution; specifically, through Calculate the sewage treatment assessment coefficient A of the μth sewage outlet μ Obviously, if each parameter is closer to or exceeds the preset threshold, the sewage treatment effect of the sewage outlet is worse, which is reflected in the sewage treatment evaluation coefficient A. μ On, then A μ The larger the value, the more likely it is that there will be problems with the processing effect of each parameter.

[0075] The expression of the judgment function is:

[0076]

[0077] When each parameter is lower than or equal to the corresponding preset threshold,

[0078] When at least one parameter exceeds the corresponding preset threshold,

[0079] Among them, x i is the change value of the parameter exceeding the preset threshold within a working cycle, β i is the weight coefficient, which is obtained based on historical data analysis, and n is the number of parameters that exceed the corresponding preset threshold.

[0080] By the following formula:

[0081]

[0082] Calculate the change value of the current parameter within a working cycle;

[0083] Among them, θ1 and θ2 are preset proportional coefficients, which are selected and determined based on historical data, ω1 and ω2 are influencing factors, and the initial setting ω1=ω2=1 can be adjusted according to historical data and empirical data to change the sensitivity, max{F k} is the maximum value of the current parameter in a working cycle, min{F k} is the minimum value of the current parameter within a working cycle.

[0084] In this embodiment, a method for obtaining a judgment function is provided, in which when each parameter is lower than or equal to the corresponding preset threshold, When at least one parameter exceeds the corresponding preset threshold, Obviously, the better the sewage treatment situation is when no parameter exceeds the corresponding preset threshold, the more effective the side reaction supervision is; therefore, by judging the function Make real-time adjustments to the sewage treatment assessment coefficient A μ The degree of influence, among which, Obviously, if the number of items that exceed the corresponding preset threshold is greater, it means that the sewage treatment effect discharged from the sewage outlet is worse. Then, by analyzing the change trend in the entire working cycle, The change is greater than The larger the change, the worse the trend of the parameter. The change range and The closer the change range is, the more normal the trend of the parameter is, and max{F k}-min{F k} can indicate the amplitude of the overall parameters within the working cycle. The larger the amplitude, the greater the overall fluctuation of the parameters, and therefore the greater the possibility of deterioration. Therefore, the trend analysis of abnormal parameters is realized by combining the above cumulative changes and extreme value changes, and the sewage treatment assessment coefficient A is accurately calculated. μ to improve the final judgment accuracy.

[0085] The system also includes a visualization module for displaying the judgment results of the data processing and analysis module to achieve the purpose of intuitive display.

[0086] It should be noted that the calculation formulas and various parameters involved in the calculation in the present invention have been dimensionally processed in advance, and the process of dimensionless processing is well known in the industry and will not be described here.

[0087] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A coordinated monitoring system for carbon pollution at enterprise sewage outlets based on the Internet of Things, characterized in that: include: A monitoring module is used to set up monitoring points at the sewage outlet of each discharge user to monitor the sewage discharged from the sewage outlet; The data acquisition module is used to obtain the carbon pollution data of each sewage outlet during the sewage discharge process. The carbon pollution data includes: total carbon content, sewage flow, sewage heat and pollutant concentration; A communication module, used to transmit the polluted carbon data collected by the data collection module to the cloud platform for storage; The data processing and analysis module is used to process and analyze the carbon pollution data of the cloud platform, obtain the sewage treatment evaluation coefficient of each sewage outlet, and compare the sewage treatment evaluation coefficient with the preset sewage treatment evaluation threshold. If the sewage treatment evaluation coefficient ≥ the sewage treatment evaluation threshold, it is judged that the sewage treatment effect of the current discharge user is poor, otherwise, it is judged that the sewage treatment effect of the current discharge user is good; The early warning module sends out early warning signals to discharge users with poor sewage treatment effects based on the judgment results of the data processing and analysis module; The process of obtaining the sewage treatment assessment coefficient is as follows: Total carbon TOC μ , sewage flow Q μ , sewage heat T μ , Oil concentration in water R μ , ammonia nitrogen concentration D μ and total phosphorus concentration P μ Substitute into the following formula: Calculate the sewage treatment assessment coefficient A of the μth sewage outlet μ ; Among them, TOC th , Q th , T th , R th , D th , P th are the preset thresholds for total carbon, sewage flow, sewage heat, oil concentration in water, ammonia nitrogen concentration, and total phosphorus concentration, respectively, a , b , c , d , f , g is the preset weight factor, B1, B2, B3, B4, B5, B6 are the fluctuation values ​​of the 1st, 2nd, 3rd, ..., 6th parameters in the previous unit time respectively, is the judgment function; The expression of the judgment function is: When each parameter is lower than or equal to the corresponding preset threshold, When at least one parameter exceeds the corresponding preset threshold, Among them, x i is the change value of the parameter exceeding the preset threshold within a working cycle, β i is the weight coefficient, n is the number of parameters exceeding the corresponding preset threshold; By the following formula: Calculate the change value of the current parameter within a working cycle; Among them, θ1 and θ2 are preset proportional coefficients, ω1 and ω2 are influencing factors, and max{F k } is the maximum value of the current parameter in a working cycle, min{F k } is the minimum value of the current parameter within a working cycle.

2. According to the Internet of Things-based enterprise sewage outlet carbon pollution collaborative supervision system of claim 1, it is characterized by: The process of collecting carbon pollution data at each monitoring point is as follows: The total carbon content data is obtained by testing with a total organic carbon analyzer; The pollutant concentration data is obtained through detection by characteristic pollutant detection equipment; the pollutant concentration data includes oil concentration, ammonia nitrogen concentration and total phosphorus concentration in water; Among them, the oil concentration in water is detected by an oil-in-water analyzer, the ammonia nitrogen concentration is detected by an ammonia nitrogen analyzer, and the total phosphorus concentration is detected by a total phosphorus analyzer; The sewage flow and sewage heat are detected by an integrated or split pipe segment electromagnetic flow calorimeter.

3. The IoT-based enterprise sewage outlet carbon pollution collaborative supervision system according to claim 2 is characterized in that: The process of processing the pollution carbon data is as follows: The detected total carbon content, sewage flow, sewage heat, oil concentration in water, ammonia nitrogen concentration and total phosphorus concentration are compared with their corresponding preset thresholds respectively; If at least one item exceeds the corresponding preset threshold and / or at least one fluctuation value within a unit time exceeds the preset fluctuation threshold, the sewage outlet is marked as abnormal, and the data within a working cycle from the current moment is traced back for the next analysis; Otherwise, the sewage outlet shall not be marked.

4. The IoT-based enterprise sewage outlet carbon pollution collaborative monitoring system according to claim 3 is characterized in that: The process of judging whether the fluctuation value within a unit time exceeds the preset fluctuation threshold is as follows: The total carbon content, sewage flow, sewage heat, oil concentration in water, ammonia nitrogen concentration and total phosphorus concentration are recorded as the first, second, third, ..., sixth parameters in sequence; Each parameter is randomly sampled M times in a unit time, and the value of the kth parameter at the mth sampling time point is set to F km ; pass Calculate the fluctuation value B of the kth parameter k , and then through B k -B k0 Compare with 0; If B k -B k0 >0, then determine the fluctuation value B of the kth parameter in unit time k Exceeding the preset fluctuation threshold B k0 .

5. According to the Internet of Things-based enterprise sewage outlet carbon pollution collaborative supervision system of claim 1, it is characterized by: The system also includes a visualization module for displaying the judgment results of the data processing and analysis module.

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