A wastewater monitoring method and system based on big data

Abstract

The application provides a wastewater monitoring method based on big data, which comprises the following steps: obtaining first data, wherein the first data is data of a sewage outlet during standard production; obtaining a sewage discharge amount based on the number of opened sewage outlets and corresponding first noise values at each sewage outlet; obtaining second data; obtaining third data, wherein the third data is real-time obtained data, and the third data comprises the number of opened sewage outlets, second noise values, second oxygen demand and second pH values obtained in real time; constructing a target model based on the first data and the second data, wherein the target model is used for comparing the obtained first data and second data with the third data and outputting a comparison result, and the production water demand is monitored in real time according to the comparison result. The application also provides a wastewater monitoring system for big data and an electronic device.

Description

Technical Field

[0001] This invention relates to the field of wastewater monitoring technology, and in particular to a wastewater monitoring method and system based on big data. Background Technology

[0002] Currently, wastewater monitoring methods typically rely on manual sampling and laboratory analysis. Manual sampling has a long cycle and cannot reflect the wastewater discharge status in real time, so by the time problems are discovered, environmental pollution and water waste have often already occurred. Summary of the Invention

[0003] This invention provides a wastewater monitoring method and system based on big data, which aims to solve or partially solve the problems existing in the background art.

[0004] To solve the above-mentioned technical problems, the present invention is implemented as follows:

[0005] In a first aspect, embodiments of the present invention provide a wastewater monitoring method based on big data, specifically a road surface wastewater monitoring method based on big data. The method includes: acquiring first data, which is data from sewage outlets during standardized production, including the number of open sewage outlets and a first noise value corresponding to each sewage outlet, wherein the sewage outlets are connected to and communicate with a wastewater tank; obtaining the discharge volume based on the number of open sewage outlets and the first noise value corresponding to each sewage outlet; and acquiring second data, which is a first oxygen demand and a first pH value of target wastewater during standardized production. The wastewater in the wastewater tank is used to acquire third data, which is real-time data. The third data includes the number of open sewage outlets, a second noise level, a second oxygen demand, and a second pH level, all acquired in real time. The second noise level, the second oxygen demand, and the second pH level are all real-time acquired data. A target model is constructed based on the first and second data. The target model is used to compare the acquired first and second data with the third data and output the comparison result. The production water demand is monitored in real time based on the comparison result.

[0006] In conjunction with the first aspect, in some embodiments, each of the sewage outlets has a data ratio A, satisfying: A = (second noise value / first noise value + second oxygen demand / first oxygen demand + second pH / first pH) / 3; wherein the comparison result output by the target model is B, satisfying: B = (A1 + A2 + ... + An) / n + the number of sewage outlets opened in real time / the total number of sewage outlets; wherein when 1.2 < B, the production water consumption is high and the production water consumption is controlled to decrease; when B > 1.5, the production water consumption is low and the production water consumption is controlled to increase.

[0007] In conjunction with the first aspect, in some embodiments, the distance L1 between the sewage outlet and the wastewater surface in the wastewater tank is obtained, the first noise value corresponding to the sewage outlet is d, and the sewage discharge volume of each sewage outlet is Q, satisfying: The discharge volume of each of the aforementioned discharge outlets is the total discharge volume, and the total discharge volume P satisfies: P = Q1 + Q2 + ... + Qn.

[0008] In conjunction with the first aspect, in some embodiments, a monitoring area is provided in the wastewater pool, the wastewater in the monitoring area is the target wastewater, the width of the monitoring area is W, and the distance from the monitoring area to the sewage outlet in the horizontal direction is L2, satisfying: 4 / W≤L2≤2 / W.

[0009] In conjunction with the first aspect, in some embodiments, the monitoring area is provided with a first zone, a second zone, and a third zone, which are arranged sequentially in the height direction. The depth of the first zone is h1, the depth of the second zone is h2, and the depth of the third zone is h3, satisfying: h1 = h2 / 2 = h3; wherein the wastewater in the second zone is the target wastewater.

[0010] In conjunction with the first aspect, some embodiments further include: monitoring floating objects within the monitoring area, the floating objects being impurities insoluble in water and floating on the water surface, the area occupied by the floating objects being S1, the area of ​​the monitoring area being S2, and monitoring the ratio of S1 to S2; wherein, under the condition of 1.2≤B≤1.5, when S1<S2 / 10, the production water consumption is low and the production water consumption is controlled to increase; when S1>S2 / 10, the production water consumption is high and the production water consumption is controlled to decrease.

[0011] A second aspect of this invention proposes a system for wastewater monitoring based on big data. The system includes: an execution subject, adapted to compare acquired first data, second data, and third data and output a comparison result; a first execution unit, communicatively connected to the execution subject, configured to acquire first data, which is data from a discharge outlet, including the number of open discharge outlets and a first noise value corresponding to each discharge outlet, wherein the discharge outlets are connected to and communicate with a wastewater tank; a second execution unit, communicatively connected to the execution subject, adapted to acquire discharge volume based on the number of open discharge outlets and the first noise value corresponding to each discharge outlet; and a third execution unit, communicatively connected to the execution subject, adapted to acquire third data, which is real-time acquired data, including the number of open discharge outlets, a second noise value, a second oxygen demand, and a second pH value, wherein the second noise value, the second oxygen demand, and the second pH value are real-time acquired pH values.

[0012] In conjunction with the second aspect, some feasible implementations further include: a signal alarm, which is communicatively connected to the executing entity, and / or, which is communicatively connected to a mobile terminal; wherein the signal alarm is adapted to operate and issue an alarm when the production water demand is abnormal, and when the signal alarm is operating, relevant personnel can adjust the production water demand.

[0013] In conjunction with the second aspect, in some feasible implementations, the second determining module includes: an execution switch, wherein the execution switch is disposed on the execution body, the execution switch being adapted to control the opening and closing of the execution body, and when not in production, relevant personnel can control the execution body to stop through the execution switch, so as to facilitate relevant personnel to perform cleaning and maintenance work on the production line.

[0014] A third aspect of the present invention provides an electronic device, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; the memory is used to store computer programs; and the processor, when executing the program stored in the memory, implements the method steps proposed in the first aspect of the present invention.

[0015] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method as described in the first aspect of the present invention.

[0016] The embodiments of this invention include the following advantages: Real-time acquisition of data such as the number of open sewage outlets, noise levels, oxygen demand, and pH levels through sensors and online monitoring equipment ensures the system can respond instantly to changes in water quality; moreover, when the system detects water quality parameters deviating from the normal range, it can react quickly, alerting relevant personnel to take timely measures to prevent pollution spread through signal alarms; simultaneously, by calculating the data ratio A for each sewage outlet, the deviation between the current water quality status and historical data can be quantified, providing a scientific basis for subsequent decision-making; furthermore, by comparing real-time data with historical data, a comparison result B is output, helping decision-makers quickly understand the changing trends in current production water demand; of course, based on different threshold settings for the comparison result B, the system can automatically adjust the production water consumption: when the A value is between 1.2 and 1.5, production water consumption is reduced; when the A value is greater than or equal to 1.5, production water consumption is increased. This dynamic adjustment mechanism is beneficial for optimizing water resource use and reducing production costs. Furthermore, by monitoring the ratio of the area S1 of floating objects to the total area S2 within the monitoring area, the water usage situation can be further assessed, and the amount of water used can be adjusted accordingly to ensure that water quality meets standards. In particular, by precisely controlling the amount of water used in production, unnecessary waste of water resources can be avoided, production efficiency can be improved, and the operating costs of enterprises can be reduced. Moreover, timely monitoring and control of wastewater discharge and water quality can help prevent environmental pollution accidents and protect the ecological environment. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating a wastewater monitoring method based on big data in an embodiment of the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Big data refers to massive, complex, and diverse datasets, typically characterized by three features: volume, variety, and velocity. Big data is primarily generated from various data collection channels, including the internet, sensors, and social media. With continuous technological advancements, big data holds great potential and possibilities for application in the transportation sector.

[0021] Firstly, this application proposes a wastewater monitoring method based on big data; please refer to [link to relevant documentation]. Figure 1 This includes the following steps:

[0022] S100 acquires the first data, which is the data of the sewage outlet during standardized production. The first data includes the number of sewage outlets opened and the first noise value corresponding to each sewage outlet. The sewage outlets are connected to and communicate with the wastewater pool.

[0023] Understandably, the system first needs to collect basic data on wastewater discharge outlets. This data, collected during normal production, includes the number of outlets open and the initial noise level at each outlet. This data reflects the basic status of wastewater discharge.

[0024] The S200 obtains the sewage discharge volume based on the number of open sewage outlets and the first noise value corresponding to each sewage outlet.

[0025] Based on the number of open sewage outlets and the corresponding noise levels, the sewage discharge volume S300 of each sewage outlet is calculated to obtain the second data. The second data is the first oxygen demand and the first pH of the target wastewater during standardized production. The target wastewater is the wastewater in the wastewater pool.

[0026] Next, the system also needs to obtain the water quality parameters of the target wastewater in the wastewater pond during normal production, including the first oxygen demand (BOD) and the first pH value, which reflect the degree of pollution of the wastewater.

[0027] The S400 acquires third data, which is real-time data. The third data includes the number of open sewage outlets, the second noise level, the second oxygen demand, and the second pH level. The second noise level, the second oxygen demand, and the second pH level are all real-time data.

[0028] The system acquires real-time data on the number of open discharge outlets, noise levels, oxygen demand, and pH levels. This data is used to monitor the dynamic changes in wastewater discharge in real time.

[0029] The S500 constructs a target model based on the first and second data. The target model is used to compare the acquired first and second data with the third data and output the comparison results. Based on the comparison results, the production water demand can be monitored in real time.

[0030] Based on the collected first data (basic information of the sewage outlet) and second data (water quality parameters of wastewater in the wastewater pond), a target model is constructed. The purpose of this target model is to compare and analyze the real-time acquired third data with historical data and output the comparison results. According to the comparison results output by the target model, the system can monitor the demand for production water in real time and adjust the production water consumption accordingly to ensure that wastewater discharge meets environmental protection standards. At the same time, it can control the actual water consumption in production, thereby reducing water waste while ensuring normal production.

[0031] Understandably, estimating sewage discharge by monitoring noise levels at the discharge outlet generally means that higher noise levels indicate faster wastewater flow or larger flow rates, and vice versa. This method does not require direct flow measurement but rather estimates the flow rate indirectly, simplifying the complexity of the monitoring equipment.

[0032] By monitoring oxygen demand (BOD) and pH, the degree of wastewater pollution can be understood. BOD reflects the content of organic matter in the water, while pH reflects the acidity or alkalinity of the water body. Comparing real-time data (third data) with historical data (first and second data) aims to identify differences between the current water quality and normal conditions. Significant differences indicate potential abnormal discharges or unreasonable water consumption in production.

[0033] By building a predictive model, the relationship between real-time data and historical data can be analyzed, and the trend of wastewater discharge in the future can be predicted. At the same time, based on the prediction results, the system can automatically or manually adjust the production water consumption to ensure that wastewater discharge meets environmental protection requirements.

[0034] Therefore, the system can monitor wastewater discharge in real time and issue timely warnings when anomalies are detected, helping enterprises to take swift measures to avoid environmental pollution caused by excessive emissions. Moreover, by dynamically adjusting the amount of water used in production, it not only ensures production needs but also avoids water waste, achieving the goal of water conservation and emission reduction. At the same time, it ensures that wastewater discharge complies with national or local environmental protection standards, reducing the legal risks faced by enterprises due to illegal discharge.

[0035] According to some embodiments of the present invention, each sewage outlet has a data ratio A, satisfying: A = (second noise value / first noise value + second oxygen demand / first oxygen demand + second pH / first pH) / 3; wherein the comparison result output by the target model is B, satisfying: B = (A1 + A2 + ... + An) / n + number of sewage outlets opened in real time / total number of sewage outlets; wherein when 1.2 < B, production water consumption is high and production water consumption is controlled to decrease, and when B > 1.5, production water consumption is low and production water consumption is controlled to increase.

[0036] It should be noted that in actual production, the factory controls the number of open discharge outlets based on the actual production tasks. That is, the number of open discharge outlets is reduced when production is light and increased when production is heavy. For example, n can be any positive integer greater than 0, such as 1, 2, or 3. For instance, when the number of open discharge outlets is 3 and the total number of discharge outlets is 20, according to B = (A1 + A2 + ... + An) / n + real-time number of open discharge outlets / total number of discharge outlets, we can derive B = (A1 + A2 + A3) / 3 + 3 / 20. It can be understood that each discharge outlet has a data ratio B, used to represent the relative change between the current real-time data (second noise value, second oxygen demand, second pH) and the historical baseline data (first noise value, first oxygen demand, first pH). Based on different ranges of the data ratio B, the system will adopt different production water consumption adjustment strategies: when 1.2 < B, it is considered that the production water consumption is too high and the production water consumption should be reduced; when B > 1.5, it is considered that the production water consumption is too low and the production water consumption should be increased; when 1.2 ≤ B ≤ 1.5, the production water consumption is appropriate.

[0037] According to some embodiments of the present invention, the distance L1 between the sewage outlet and the wastewater surface in the wastewater tank is obtained, the first noise value corresponding to the sewage outlet is d, and the sewage discharge volume of each sewage outlet is Q, satisfying: The discharge volume of each discharge outlet is the total discharge volume, P, which satisfies: P = Q1 + Q2 + ... + Qn.

[0038] It is understandable that by monitoring the noise level d at the sewage outlet, the sewage discharge volume Q can be indirectly calculated. There is a certain correlation between the noise level and the wastewater flow rate. The higher the noise level, the higher the wastewater flow rate. The distance L1, as the denominator, can play a standardization role, making the sewage discharge volume calculation at different locations more accurate. The larger L1 is, the longer the flow path of the wastewater after entering the wastewater pool, which affects the mixing and diffusion of the wastewater.

[0039] Therefore, by combining the noise value d and the distance L1, the discharge volume Q of each discharge outlet can be obtained, and then the total discharge volume P can be obtained by summing them up. This calculation method makes the estimation of wastewater discharge volume more accurate.

[0040] According to some embodiments of the present invention, a monitoring area is provided in the wastewater pool, the wastewater in the monitoring area is the target wastewater, the width of the monitoring area is W, and the distance from the monitoring area to the sewage outlet in the horizontal direction is L2, satisfying: 4 / W≤L2≤2 / W.

[0041] Understandably, setting up specific monitoring areas within the wastewater pond ensures that the collected data is more representative and reflects the overall water quality within the pond. The selection of monitoring areas should consider the wastewater flow patterns and mixing conditions to ensure the accuracy and reliability of the data. A range was set for the horizontal distance L2 between the monitoring area and the discharge outlet: 4 / W ≤ L2 ≤ 2 / W. This distance was set to ensure that the wastewater within the monitoring area was sufficiently mixed, thus accurately reflecting the overall water quality of the wastewater pond.

[0042] It should be noted that too close a distance may cause the monitoring results to be overly affected by local emissions, while too far a distance may cause the monitoring results to lag behind the actual emissions.

[0043] According to some embodiments of the present invention, a first zone, a second zone, and a third zone are set in the monitoring area. The first zone, the second zone, and the third zone are arranged sequentially in the height direction. The depth of the first zone is h1, the depth of the second zone is h2, and the depth of the third zone is h3, satisfying: h1=h2 / 2=h3; wherein the wastewater in the second zone is the target wastewater.

[0044] In some embodiments, by setting up three zones at different heights within the monitoring area, the water quality within the wastewater pond can be comprehensively monitored. Zones at different heights reflect the water quality characteristics at different levels within the wastewater pond, helping to more accurately assess the overall water quality of the wastewater pond.

[0045] The depth h1 of zone 1 is half the depth h2 of zone 2, and the depth h3 of zone 3 is equal to h1. This setting ensures that the depth ratios between different zones are coordinated, which helps to ensure the representativeness of the monitoring data.

[0046] The wastewater in the second zone is defined as the target wastewater, meaning that the water quality data in this zone will be used as the main reference. The second zone is located in the middle of the wastewater pool and can better reflect the water quality of the entire wastewater pool.

[0047] According to some embodiments of the present invention, the monitoring method further includes: monitoring floating objects within a monitoring area, wherein the floating objects are impurities that are insoluble in water and float on the water surface, the area occupied by the floating objects is S1, the area of ​​the monitoring area is S2, and monitoring the ratio of S1 to S2; wherein, under the condition of 1.2≤B≤1.5, when S1<S2 / 10, production water consumption is low and the increase in production water consumption is controlled; when S1>S2 / 10, production water consumption is high and the decrease in production water consumption is controlled. It should be noted that when S1=S2 / 10, the current production water consumption is maintained.

[0048] Understandably, image recognition technology or other physical methods are used to monitor insoluble impurities floating on the water surface within a monitored area, and the area S1 occupied by these impurities is calculated. The presence of floating matter usually reflects some problems in the wastewater treatment process, such as the failure of suspended solids to settle or filter completely. The area S1 of floating matter is compared with the total area S2 of the monitored area to calculate the proportion of floating matter. This proportion can be used as an indicator to evaluate the effectiveness of wastewater treatment.

[0049] The production water consumption is dynamically adjusted based on the percentage of floating debris. When the percentage of floating debris is low, it indicates that the wastewater treatment effect is good, and the production water consumption can be appropriately increased. Conversely, when the percentage of floating debris is high, it indicates that there is a problem with the wastewater treatment, and the production water consumption needs to be reduced to reduce wastewater discharge. The cause should then be identified and improved.

[0050] It is worth mentioning that the ratio of S1 to S2 will be further determined only when 1.2≤B≤1.5. That is, when 1.2≤B≤1.5, if S1<S2 / 10, the production water consumption will be increased, and after S1=S2 / 10, the value of B will be determined and the production water consumption will be controlled according to the value of B. Similarly, if S1>S2 / 10, the production water consumption will be decreased, and after S1=S2 / 10, the value of B will be determined and the production water consumption will be controlled according to the value of B.

[0051] Therefore, in summary, this invention uses sensors and online monitoring equipment to acquire real-time data such as the number of open sewage outlets, noise levels, oxygen demand, and pH, ensuring the system can respond instantly to changes in water quality. Furthermore, when the system detects water quality parameters deviating from normal ranges, it can react quickly, alerting relevant personnel via alarm signals to take timely measures to prevent pollution spread. Simultaneously, by calculating the data ratio A for each sewage outlet, the deviation between the current water quality status and historical data can be quantified, providing a scientific basis for subsequent decision-making. Moreover, by comparing real-time data with historical data, a comparison result B is output, helping decision-makers quickly understand the changing trends in current production water demand. Of course, based on different threshold settings for the comparison result B, the system can automatically adjust production water consumption: reducing production water consumption when A is between 1.2 and 1.5, and increasing production water consumption when A is greater than or equal to 1.5. This dynamic adjustment mechanism is beneficial for optimizing water resource use and reducing production costs. Furthermore, by monitoring the ratio of the area S1 of floating objects to the total area S2 within the monitoring area, the water usage situation can be further assessed, and the amount of water used can be adjusted accordingly to ensure that water quality meets standards. In particular, by precisely controlling the amount of water used in production, unnecessary waste of water resources can be avoided, production efficiency can be improved, and the operating costs of enterprises can be reduced. Moreover, timely monitoring and control of wastewater discharge and water quality can help prevent environmental pollution accidents and protect the ecological environment.

[0052] Based on the same inventive concept, this invention also proposes a system for wastewater monitoring using big data. The system is applied to the wastewater monitoring method based on big data described in any of the above embodiments. The system includes: an execution entity adapted to compare acquired first data, second data, and third data and output the comparison result; and a first execution unit communicatively connected to the execution entity, the first execution unit being used to acquire the first data, which is data from sewage outlets. The first data includes the number of open sewage outlets and a corresponding first noise value at each sewage outlet. The sewage outlets are connected to a wastewater tank. The system is connected to the execution body; a second execution unit, which is communicatively connected to the execution body, is adapted to obtain the discharge volume based on the number of open discharge outlets and the corresponding first noise value at each discharge outlet; and a third execution unit, which is communicatively connected to the execution body, is adapted to obtain third data, which is real-time data, including the number of open discharge outlets, the second noise value, the second oxygen demand, and the second pH value. The second noise value is the real-time noise value, the second oxygen demand is the real-time oxygen demand, and the second pH value is the real-time pH value.

[0053] According to some embodiments of the present invention, the system further includes: a signal alarm, which is communicatively connected to the execution entity, and / or, which is communicatively connected to a mobile terminal; wherein the signal alarm is adapted to operate and issue an alarm when the production water demand is abnormal, and when the signal alarm is operating, relevant personnel can adjust the production water demand.

[0054] Understandably, by monitoring wastewater discharge data, water quality parameters, and production water consumption in real time, the system can identify whether there are any abnormalities in production water demand. Abnormal situations may include, but are not limited to, sudden increases or decreases in production water consumption, or water quality parameters exceeding normal ranges.

[0055] When the system detects an anomaly, the alarm is activated and sends an alert to relevant personnel. The alert can be sent in various ways, such as audible alarms, SMS messages, emails, or mobile app push notifications. Upon receiving the alert, relevant personnel can quickly take measures to adjust production water requirements to ensure wastewater discharge meets environmental standards and avoids unnecessary resource waste.

[0056] According to some embodiments of the present invention, the system further includes: an execution switch, the execution switch being disposed on the execution body, the execution switch being adapted to control the opening and closing of the execution body, and when not in production, relevant personnel can control the execution body to stop through the execution switch, so as to facilitate relevant personnel to perform cleaning and maintenance work on the production line.

[0057] Understandably, an execution switch, as a physical or digital switch, allows relevant personnel to manually or via system commands control the status of the execution unit. When it is necessary to stop the execution unit, it can be turned off using the execution switch; when production needs to be resumed, the execution unit can be started again using the execution switch. Controlling the start and stop of the execution unit via the execution switch allows for easy shutdown of the system during non-production periods, providing a safe working environment for maintenance personnel, and also facilitating cleaning and other maintenance work.

[0058] It should be noted that although the system itself can achieve automated monitoring and management, manual control is still necessary in some cases, especially when maintenance or emergency shutdown is required.

[0059] Based on the same inventive concept, embodiments of this application also propose an electronic device, which includes:

[0060] At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the wastewater monitoring method based on big data according to the embodiments of this application.

[0061] Furthermore, to achieve the above objectives, embodiments of this application also propose a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the wastewater monitoring method based on big data according to embodiments of this application.

[0062] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, embodiments of the present invention can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, embodiments of the present invention can take the form of computer program products implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0063] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A system that specifies functions in one or more boxes.

[0064] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including an instruction set implemented in a process. Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0065] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal equipment, causing a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable terminal equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0066] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. "And / or" indicates that either one or both can be chosen. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal device. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes said element.

[0067] The above provides a detailed description of a wastewater monitoring method based on big data provided by the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A wastewater monitoring method based on big data, characterized in that, include: Acquire first data, which is the data of the sewage outlet during standardized production. The first data includes the number of sewage outlets opened and the first noise value corresponding to each sewage outlet. The sewage outlets are connected to and communicate with the wastewater pool. The amount of sewage discharged is obtained based on the number of openings of the sewage outlets and the first noise value corresponding to each sewage outlet. Acquire second data, which is the first oxygen demand and the first pH of the target wastewater during standardized production, wherein the target wastewater is the wastewater in the wastewater pool; The third data is real-time data, which includes the number of sewage outlets opened, the second noise value, the second oxygen demand, and the second pH value. The second noise value is the real-time noise value, the second oxygen demand is the real-time oxygen demand, and the second pH value is the real-time pH value. in A target model is constructed based on the first data and the second data. The target model is used to compare the acquired first data, second data and third data with the third data and output the comparison result. The production water demand is monitored in real time based on the comparison result. Each of the aforementioned discharge outlets has a data ratio A, satisfying: A = (Second noise value / First noise value + Second oxygen demand / First oxygen demand + Second pH / First pH) / 3; The comparison result output by the target model is B, which satisfies: B = (A1 + A2 + ... + An) / n + the number of sewage outlets opened in real time / the total number of sewage outlets; in When 1.2 < B, the production water consumption is high and the production water consumption is controlled to decrease; when B > 1.5, the production water consumption is low and the production water consumption is controlled to increase.

2. The wastewater monitoring method based on big data according to claim 1, characterized in that, The distance L1 between the sewage outlet and the wastewater surface in the wastewater tank is obtained, the first noise value corresponding to the sewage outlet is d, and the sewage discharge volume of each sewage outlet is Q, satisfying: in The discharge volume of each of the aforementioned discharge outlets is the total discharge volume, P, which satisfies: P = Q1 + Q2 + ... + Qn.

3. The wastewater monitoring method based on big data according to claim 2, characterized in that, A monitoring area is set up in the wastewater pool. The wastewater in the monitoring area is the target wastewater. The width of the monitoring area is W. The distance from the monitoring area to the sewage outlet in the horizontal direction is L2, which satisfies: 4 / W≤L2≤2 / W.

4. The wastewater monitoring method based on big data according to claim 3, characterized in that, The monitoring area is divided into a first zone, a second zone, and a third zone, which are arranged sequentially in the height direction. The depth of the first zone is h1, the depth of the second zone is h2, and the depth of the third zone is h3, satisfying: h1 = h2 / 2 = h3. in The wastewater in the second zone is the target wastewater.

5. The wastewater monitoring method based on big data according to claim 4, characterized in that, Also includes: The floating objects in the monitoring area are impurities that are insoluble in water and float on the water surface. The area occupied by the floating objects is S1, and the area of ​​the monitoring area is S2. The ratio of S1 to S2 is monitored. in Under the condition that 1.2≤B≤1.5, when S1<S2 / 10, the production water consumption is low and the production water consumption is controlled to increase; when S1>S2 / 10, the production water consumption is high and the production water consumption is controlled to decrease.

6. A system for a wastewater monitoring method based on big data, characterized in that, The wastewater monitoring method based on big data according to any one of claims 1-5, the system comprising: An execution entity, which is adapted to compare the acquired first data, second data, and third data and output the comparison result; The first execution unit is communicatively connected to the execution body. The first execution unit is used to acquire first data, which is data of the sewage outlet. The first data includes the number of sewage outlets opened and the first noise value corresponding to each sewage outlet. The sewage outlet is connected to and communicates with the wastewater pool. The second execution unit is communicatively connected to the execution body. The second execution unit is adapted to obtain the discharge volume based on the number of openings of the discharge outlets and the first noise value corresponding to each discharge outlet. The third execution unit is communicatively connected to the execution body. The third execution unit is adapted to acquire third data, which is real-time acquired data. The third data includes the number of sewage outlets opened, the second noise value, the second oxygen demand, and the second pH value, which are all acquired in real time. The second noise value is the noise value acquired in real time, the second oxygen demand is the oxygen demand acquired in real time, and the second pH value is the pH value acquired in real time.

7. The system for wastewater monitoring based on big data according to claim 6, characterized in that, Also includes: A signal alarm, wherein the signal alarm is communicatively connected to the executing entity, and / or, wherein the signal alarm is communicatively connected to a mobile terminal; in The signal alarm is adapted to operate and issue an alarm when the production water demand is abnormal, and when the signal alarm is operating, relevant personnel can adjust the production water demand.

8. The system for wastewater monitoring based on big data according to claim 7, characterized in that, Also includes: An execution switch is provided on the execution body. The execution switch is adapted to control the opening and closing of the execution body. When not in production, relevant personnel can use the execution switch to control the execution body to stop, so that relevant personnel can perform cleaning and maintenance work on the production line.

9. An electronic device, characterized in that, include: The system includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus. The memory is used to store computer programs; When the processor executes the program stored in the memory, it implements the method as claimed in any one of claims 1 to 5.

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