Efficient emergency water treatment device and method based on AI intelligent control

Abstract

The invention discloses an efficient emergency water treatment device and method based on AI intelligent control, and the device comprises a water treatment device main body, the water treatment device comprises a flowmeter, a pressure gauge, a thermometer, and a PH tester; the data acquisition module is used for acquiring data of the flowmeter, the pressure gauge, the thermometer and the PH tester; the data analysis module is used for analyzing the collected data by using an AI algorithm; the AI model is used for constructing an AI-based decision support system; the automatic control module is used for realizing automatic control of a water treatment process by utilizing a PLC (Programmable Logic Controller) and an SCADA (Supervisory Control and Data Acquisition) system; and the abnormity detection module identifies abnormal conditions in the operation of the equipment through a mode identification technology. According to the method, the water treatment process is optimized by utilizing machine learning, big data analysis and other AI technologies, the efficiency is improved, and the water quality is ensured to meet the standard.

Description

Technical Field

[0001] The present invention relates to the technical field of water treatment, and in particular to a high-efficiency emergency water treatment device and method based on AI intelligent control. Background Art

[0002] Traditional water treatment plants need to purchase various water treatment equipment, such as reverse osmosis water treatment equipment, when conducting water treatment. Various equipment needs to be operated and monitored on-site by staff during operation to ensure that the equipment operates well. In many cases, problems that operators cannot solve require subsequent maintenance by original design experts.

[0003] With the development of computer and network technology, enterprises are increasingly relying on computers and the Internet for systematic operation and management. Therefore, the later maintenance and operation of sewage treatment systems require professional management and continuous improvement. More and more water treatment plants will choose to cooperate with professional operation and management units, but these operation and management units cannot manage on-site for a long time, and the operation and management units are often short of staff and cannot meet market demand. At present, the network information management platform established between water treatment plants and operation and management units in the market can often only achieve transparent management.

[0004] The existing publication number CN111694286A discloses a high-frequency adjustable water treatment control system based on artificial intelligence, including a physical layer module for collecting physical data and executing instructions on site; a model layer module for performing one-to-one simulation modeling of on-site equipment of the physical layer module; a terminal service layer module, including a cloud server, a hardware end and a software end, and a network layer module connected between the terminal service layer module and the physical layer module and the model layer module through two-way communication; each device can be monitored and managed in real time through the software end. When encountering problems and failures, AI intelligent cloud computing technology can remotely intervene in the physical layer module to solve the problem in combination with the results of expert consultation. Compared with traditional maintenance methods, it saves a lot of manpower and time costs, and the management is more systematic and complete, and the user experience is better.

[0005] Although the existing technology has achieved remote intervention to a certain extent, it cannot treat water and cannot predict subsequent water quality based on past data. For this reason, we propose an efficient emergency water treatment device and method based on AI intelligent control. Summary of the invention

[0006] The purpose of the present invention is to provide an efficient emergency water treatment device and method based on AI intelligent control to solve the problems in the prior art.

[0007] To achieve the above objectives, the present invention provides the following technical solutions: an efficient emergency water treatment device based on AI intelligent control, comprising:

[0008] A water treatment device body, the water treatment device comprising a flow meter, a pressure gauge, a thermometer, and a PH tester;

[0009] A data acquisition module, which is used to collect data from a flow meter, a pressure gauge, a thermometer, and a pH tester;

[0010] A data analysis module, which uses an AI algorithm to analyze the collected data;

[0011] AI model, building an AI-based decision support system;

[0012] An automation control module, wherein the automation control module uses a PLC and SCADA system to realize automatic control of the water treatment process;

[0013] An anomaly detection module, which uses pattern recognition technology to identify abnormal conditions in the operation of the device;

[0014] A fault prediction module predicts possible future faults based on historical data.

[0015] Preferably, the water treatment device body includes a filter box, a water treatment pump, a filter membrane, a first safety filter, a second safety filter and a water storage tank. The water outlet of the filter box is connected to a first electric ball valve, and the first electric ball valve is respectively connected to the water treatment pump and the first safety filter through pipelines. The pipeline between the first electric ball valve and the first safety filter is installed with a second electric ball valve, and the first safety filter is connected to the bottom of the water storage tank through a pipeline; the first safety filter is respectively connected to the filter membrane and the second safety filter through pipelines, the filter membrane and the second safety filter are connected through pipelines, and the filter membrane is connected to the top of the water storage tank through a pipeline.

[0016] Preferably, a conductivity meter is installed on the pipeline between the filter membrane and the water storage tank.

[0017] Preferably, a plurality of lower partitions are installed at equal intervals at the bottom of the filter box, a plurality of upper partitions are installed at equal intervals at the top of the filter box, the lower partitions and the upper partitions are spaced apart, and the middle of the filter box is filled with an activated carbon layer.

[0018] Preferably, a water inlet pipe and a water outlet are respectively provided on both sides of the filter box, and a pre-filter is installed on the filter box at the water inlet pipe.

[0019] Preferably, a thermometer, a pH tester, a safety valve, a pressure gauge, an exhaust port and a breathing port are arranged on the top of the filter box, and a plurality of sewage pipes are opened on the side of the filter box.

[0020] Preferably, the upper partitions at both ends extend to the bottom of the filter box, and the upper partitions located at the water outlet are provided with rectangular holes.

[0021] An efficient emergency water treatment method based on AI intelligent control, using the efficient emergency water treatment device based on AI intelligent control; comprising the following steps:

[0022] S1. Introduce the water to be treated into the filter box through the water inlet pipe, and pre-filter the water through the pre-filter and activated carbon layer in the filter box;

[0023] S2, the filtered water is then filtered through the filter membrane, the first security filter and the second security filter;

[0024] S3, collect data from flow meter, pressure gauge, thermometer, and pH tester through the data acquisition module to monitor water quality and equipment operation status in real time;

[0025] S4, the data analysis module uses AI algorithms to analyze the collected data and identify water quality trends and potential problems;

[0026] S5. Predict water quality changes and equipment failures through AI models;

[0027] S6. Identify abnormal conditions in the operation of the equipment through pattern recognition technology of the abnormality detection module;

[0028] S7. The fault prediction module predicts possible future faults based on historical data, and performs maintenance or replaces parts in advance.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] 1. The data acquisition module collects data from flow meters, pressure gauges, thermometers, and pH testers to monitor water quality and equipment operating status in real time. The data analysis module uses AI algorithms to analyze the collected data to identify water quality trends and potential problems. Water quality changes and equipment failures are predicted through AI models. The pattern recognition technology of the anomaly detection module identifies abnormal conditions in equipment operation. The fault prediction module predicts possible future failures based on historical data, and performs maintenance or replaces parts in advance. Machine learning, big data analysis, and other AI technologies are used to optimize the water treatment process, improve efficiency, and ensure that water quality meets standards. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0032] Figure 1It is a schematic diagram of the structure of the present invention;

[0033] Figure 2 is a side view of the filter box of the present invention;

[0034] Figure 3 It is a cross-sectional view of the filter box of the present invention.

[0035] In the figure: 1. Filter box; 2. Drain pipe; 3. Water inlet pipe; 4. Thermometer; 5. PH tester; 6. Safety valve; 7. Pressure gauge; 8. Exhaust port; 9. Breathing port; 10. Water treatment pump; 11. Filter membrane; 12. Conductivity meter; 13. First safety filter; 14. Second safety filter; 15. Water storage tank; 16. Pre-filter; 17. Activated carbon layer; 18. Lower partition; 19. Upper partition; 20. Drain port. DETAILED DESCRIPTION

[0036] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention.

[0037] See also Figure 1-3 In an embodiment of the present invention, a high-efficiency emergency water treatment device based on AI intelligent control includes:

[0038] The water treatment device body includes a flow meter, a pressure gauge 7, a thermometer 4, and a PH tester 5;

[0039] A data acquisition module, which is used to collect data from a flow meter, a pressure gauge 7, a thermometer 4, and a PH tester 5;

[0040] A data analysis module, which uses an AI algorithm to analyze the collected data;

[0041] AI model, building an AI-based decision support system;

[0042] An automation control module, wherein the automation control module uses a PLC and SCADA system to realize automatic control of the water treatment process;

[0043] An anomaly detection module, which uses pattern recognition technology to identify abnormal conditions in the operation of the device;

[0044] A fault prediction module predicts possible future faults based on historical data.

[0045] The main body of the water treatment device includes a filter box 1, a water treatment pump 10, a filter membrane 11, a first security filter 13, a second security filter 14 and a water storage tank 15. The water outlet of the filter box 1 is connected to a first electric ball valve, which is respectively connected to the water treatment pump 10 and the first security filter 13 through pipelines. The pipeline between the first electric ball valve and the first security filter 13 is installed with a second electric ball valve. The first security filter 13 is connected to the bottom of the water storage tank 15 through a pipeline; the first security filter 13 is respectively connected to the filter membrane 11 and the second security filter 14 through pipelines, and the filter membrane 11 is connected to the top of the water storage tank 15 through a pipeline; the treated water is introduced into the filter box 1 through the water inlet pipe 3, and the water is pre-filtered through the pre-filter 16 and the activated carbon layer 17 in the filter box 1; the filtered water is then filtered through the filter membrane 11, the first security filter 13 and the second security filter 14.

[0046] A conductivity meter 12 is installed at the pipeline between the filter membrane 11 and the water storage tank 15; a plurality of lower baffles 18 are installed at equal intervals at the bottom end of the filter box 1, and a plurality of upper baffles 19 are installed at equal intervals at the top end of the filter box 1, the lower baffles 18 and the upper baffles 19 are arranged at intervals, and the middle of the filter box 1 is filled with an activated carbon layer 17; a water inlet pipe 3 and a drain port 20 are respectively arranged on both sides of the filter box 1, and a pre-filter 16 is installed at the water inlet pipe 3 of the filter box 1; a thermometer 4, a PH tester 5, a safety valve 6, a pressure gauge 7, an exhaust port 8 and a breathing port 9 are arranged on the top of the filter box 1, and a plurality of sewage pipes 2 are opened on the side of the filter box 1; the upper baffles 19 at both ends extend to the bottom of the filter box 1, and the upper baffles 19 located at the water outlet are opened with rectangular holes.

[0047] An efficient emergency water treatment method based on AI intelligent control, using the efficient emergency water treatment device based on AI intelligent control; comprising the following steps:

[0048] S1, introducing the water to be treated into the filter box 1 through the water inlet pipe 3, and pre-filtering the water through the pre-filter 16 and the activated carbon layer 17 in the filter box 1;

[0049] S2, the filtered water is then filtered through the filter membrane 11, the first security filter 13 and the second security filter 14;

[0050] S3, collect data from flow meter, pressure gauge, thermometer 4, and pH tester through data acquisition module, and monitor water quality and equipment operation status in real time;

[0051] S4, the data analysis module uses AI algorithms to analyze the collected data and identify water quality trends and potential problems;

[0052] S5. Predict water quality changes and equipment failures through AI models;

[0053] S6. Identify abnormal conditions in the operation of the equipment through pattern recognition technology of the abnormality detection module;

[0054] S7. The fault prediction module predicts possible future faults based on historical data, and performs maintenance or replaces parts in advance.

[0055] The working principle of the present invention is: the water to be treated is introduced into the filter box 1 through the water inlet pipe 3, and the water is pre-filtered through the pre-filter 16 and the activated carbon layer 17 in the filter box 1; the filtered water is then re-filtered through the filter membrane 11, the first safety filter 13 and the second safety filter 14; the data of the flow meter, pressure gauge, thermometer 4 and pH tester are collected through the data acquisition module to monitor the water quality and equipment operation status in real time; the data analysis module uses the AI ​​algorithm to analyze the collected data to identify water quality change trends and potential problems; the AI ​​model is used to predict water quality changes and equipment failures; the pattern recognition technology of the anomaly detection module is used to identify abnormal conditions in equipment operation; the fault prediction module predicts possible future faults based on historical data, and performs maintenance or replacement of components in advance.

[0056] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An efficient emergency water treatment device based on AI intelligent control, characterized in that: include: A water treatment device body, the water treatment device comprising a flow meter, a pressure gauge (7), a thermometer (4), and a pH tester (5); A data acquisition module, the data acquisition module is used to collect data from a flow meter, a pressure gauge (7), a thermometer (4), and a pH tester (5); A data analysis module, which uses an AI algorithm to analyze the collected data; AI model, building an AI-based decision support system; An automation control module, wherein the automation control module uses a PLC and SCADA system to realize automatic control of the water treatment process; An anomaly detection module, which uses pattern recognition technology to identify abnormal conditions in the operation of the device; A fault prediction module predicts possible future faults based on historical data.

2. According to claim 1, a high-efficiency emergency water treatment device based on AI intelligent control is characterized in that: The water treatment device body comprises a filter box (1), a water treatment pump (10), a filter membrane (11), a first safety filter (13), a second safety filter (14) and a water storage tank (15); the water outlet of the filter box (1) is connected to a first electric ball valve; the first electric ball valve is respectively connected to the water treatment pump (10) and the first safety filter (13) through a pipeline; the pipeline between the first electric ball valve and the first safety filter (13) is installed with a second electric ball valve; the first safety filter (13) is connected to the bottom of the water storage tank (15) through a pipeline; the first safety filter (13) is respectively connected to the filter membrane (11) and the second safety filter (14) through a pipeline; the filter membrane (11) and the second safety filter (14) are connected through a pipeline; the filter membrane (11) is connected to the top of the water storage tank (15) through a pipeline.

3. According to claim 2, a high-efficiency emergency water treatment device based on AI intelligent control is characterized in that: A conductivity meter (12) is installed on the pipeline between the filter membrane (11) and the water storage tank (15).

4. According to claim 2, a high-efficiency emergency water treatment device based on AI intelligent control is characterized in that: A plurality of lower partitions (18) are installed at equal intervals at the bottom end of the filter box (1), and a plurality of upper partitions (19) are installed at equal intervals at the top end of the filter box (1). The lower partitions (18) and the upper partitions (19) are arranged at intervals, and the middle of the filter box (1) is filled with an activated carbon layer (17).

5. According to claim 4, a high-efficiency emergency water treatment device based on AI intelligent control is characterized in that: A water inlet pipe (3) and a water outlet (20) are respectively arranged on both sides of the filter box (1), and a pre-filter (16) is installed on the filter box (1) at the water inlet pipe (3).

6. According to claim 5, a high-efficiency emergency water treatment device based on AI intelligent control is characterized in that: The top of the filter box (1) is provided with a thermometer (4), a pH tester (5), a safety valve (6), a pressure gauge (7), an exhaust port (8) and a breathing port (9), and the side of the filter box (1) is provided with a plurality of sewage discharge pipes (2).

7. According to claim 5, a high-efficiency emergency water treatment device based on AI intelligent control is characterized in that: The upper baffles (19) at both ends extend to the bottom of the filter box (1), and the upper baffles (19) located at the water outlet are provided with rectangular holes.

8. An efficient emergency water treatment method based on AI intelligent control, characterized in that: A high-efficiency emergency water treatment device based on AI intelligent control according to any one of claims 1 to 7 is used; comprising the following steps: S1, introducing the water to be treated into the filter box (1) through the water inlet pipe (3), and pre-filtering the water through the pre-filter (16) and the activated carbon layer (17) in the filter box (1); S2, the filtered water is then filtered through the filter membrane (11), the first security filter (13) and the second security filter (14); S3, collect data from the flow meter, pressure gauge, thermometer (4), and pH tester through the data acquisition module to monitor water quality and equipment operation status in real time; S4, the data analysis module uses AI algorithms to analyze the collected data and identify water quality trends and potential problems; S5. Predict water quality changes and equipment failures through AI models; S6. Identify abnormal conditions in the operation of the equipment through pattern recognition technology of the abnormality detection module; S7. The fault prediction module predicts possible future faults based on historical data, and performs maintenance or replaces parts in advance.

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