Artificial intelligence multiphase catalytic oxidation system and method

Abstract

The application discloses an artificial intelligence multi-phase catalytic oxidation system and method, which comprises an artificial intelligence system, a multi-phase catalytic oxidation reactor, nanomachines arranged in the multi-phase catalytic oxidation reactor, a gas detection device, a sensor device and a gas purification device; the nanomachines, the gas detection device and the sensor device are wirelessly connected with the artificial intelligence system respectively; and detection data of the gas detection device and the sensor device are transmitted to the artificial intelligence system. The first wireless water quality sensor and the second wireless water quality sensor detect the data of the spraying liquid at the positions, and the data is transmitted to the artificial intelligence system, so as to determine whether there is an inactivation phenomenon of the local catalyst. When the local catalyst has an inactivation problem, the artificial intelligence system sends a command to a control device of the nanomachines, opens a cleaning agent outlet, and releases catalyst cleaning agents, so that the targeted cleaning of the catalyst is realized, and the catalytic ability of the catalyst is recovered.

Description

Technical Field

[0001] This invention belongs to the field of organic waste gas treatment and relates to an artificial intelligence multiphase catalytic oxidation system and method. Background Technology

[0002] Heterogeneous catalytic oxidation technology offers multiple degradation pathways for pollutants in organic waste gases, making it a preferred technology for treating these gases. These pathways include scrubbing absorption, catalytic oxidation by a catalyst, and the synergistic effect of reactive oxygen molecules and the catalyst. The core of this technology lies in utilizing the catalytic action of a solid-phase catalyst to decompose the oxidant, generating highly oxidizing hydroxyl radicals (·OH), thereby accelerating and thoroughly oxidizing and degrading pollutants dissolved in both the liquid and gas phases. Furthermore, compared to traditional homogeneous catalysts, solid-phase catalysts are easier to recover and suitable for continuous operation.

[0003] However, existing heterogeneous catalytic oxidation technologies suffer from catalyst activity degradation during use. During the process of sufficient contact between pollutants and the catalyst, impurities can clog the originally loose and porous catalyst, reducing the effective catalytic surface area. Failure to promptly remove these substances severely impacts the catalytic effect. Furthermore, byproducts generated during the reaction combine with the catalyst, leading to the loss of active sites and affecting the pollutant removal rate of heterogeneous catalytic oxidation technology. Traditional catalyst regeneration techniques typically involve offline cleaning of the catalyst after a period of use, when the pollutant removal rate reaches its limit. This process is complex, delayed, and fails to fully realize the potential of heterogeneous catalytic oxidation technology. Summary of the Invention

[0004] In order to overcome the shortcomings of the prior art, the present invention provides an artificial intelligence heterogeneous catalytic oxidation system and method.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: an artificial intelligence multiphase catalytic oxidation system, comprising an artificial intelligence system, a multiphase catalytic oxidation reactor, and a nanorobot, a gas detection device, a sensor device, and a gas purification device disposed in the multiphase catalytic oxidation reactor. The nanorobot, the gas detection device, and the sensor device are wirelessly connected to the artificial intelligence system. The detection data of the gas detection device and the sensor device are transmitted to the artificial intelligence system. The artificial intelligence system is used to determine whether the local catalyst is deactivated and whether the overall catalyst is deactivated. The nanorobot is used for targeted cleaning of the deactivated catalyst.

[0006] Furthermore, the gas purification device includes a spray device, an active oxygen molecule injection device, and a catalyst packing. The spray device contains a spray liquid, the active oxygen molecule injection device contains active oxygen molecules, and the catalyst packing is composed of several catalysts stacked together. The spray liquid, active oxygen molecules, catalyst, and the catalyst-active oxygen molecule combination products work together to purify the waste gas.

[0007] Furthermore, the multiphase catalytic oxidation reactor includes an upper region, a middle region, and a lower region. The upper region is provided with a gas outlet, the lower region is provided with a spray outlet and a gas inlet, and a support layer is provided between the middle region and the lower region.

[0008] Furthermore, the spraying device is located in the upper layer, the catalyst packing is located in the middle layer, and the active oxygen molecule injection device is located in the lower layer. The flow direction of the active oxygen molecules is the same as the movement direction of the exhaust gas, and the flow direction of the active oxygen molecules is opposite to the spraying direction of the spray liquid.

[0009] Furthermore, the sensor device includes a first wireless water quality sensor and a second wireless water quality sensor. The first wireless water quality sensor is installed on the nanorobot to detect liquid data at the location of the nanorobot. The second wireless water quality sensor is installed at the spray outlet to detect spray liquid data after purifying the exhaust gas. The data detected by the sensor device is transmitted to the artificial intelligence system to obtain the COD of the tested liquid.

[0010] Furthermore, both the first and second wireless water quality sensors are collections of several sensors, including a turbidity sensor, a redox potential sensor, a conductivity sensor, a temperature sensor, and a position sensor.

[0011] Furthermore, the artificial intelligence system includes a COD analysis model and a COD data module. Data detected by the sensor device is input into the COD analysis model and outputs COD data. The COD data module analyzes the COD data and uses the COD data to determine whether the local catalyst is deactivated.

[0012] An artificial intelligence-based heterogeneous catalytic oxidation method includes the following steps:

[0013] Step 1: The first wireless water quality sensor detects the liquid data at the location of the nanorobot and transmits it to the artificial intelligence system to obtain the COD of the liquid being tested, which is recorded as COD. 1-X ;

[0014] Step 2: The second wireless water quality sensor detects the liquid data of the spray liquid after purifying the waste gas and transmits it to the artificial intelligence system to obtain the COD of the tested liquid, which is recorded as COD2.

[0015] Step 3: Screen the COD located in the catalyst packing area from Step 1. 1-X, denoted as (COD) 1-X ) | ;

[0016] Step 4: Determine (COD) 1-X ) | Is the COD2 greater than the set multiple a? If yes, determine that the catalyst at the location of the current X-sequence nanorobot is deactivated and proceed to step 5; if no, proceed to step 6.

[0017] Step 5: The artificial intelligence system outputs a catalyst deactivation command to the current X-sequence nanorobot. The control device of the current X-sequence nanorobot controls the extension device to unfold, fixing the nanorobot at the deactivated catalyst site. The control device controls the opening of the cleaning agent outlet to release the cleaning agent for targeted cleaning of the deactivated catalyst.

[0018] Step 6: The first wireless VOCs sensor detects the VOCs concentration of the purified gas, and the second wireless VOCs sensor detects the VOCs concentration of the exhaust gas before purification. The detected VOCs concentration data is then transmitted to the artificial intelligence system.

[0019] Step 7: The artificial intelligence system calculates the VOCs removal rate of the exhaust gas and determines whether the overall catalyst is deactivated. If yes, proceed to step 8; otherwise, repeat step 1.

[0020] Step 8: The artificial intelligence system outputs a catalyst deactivation command to all nanorobots. The control devices of all nanorobots control the telescopic devices to unfold, fix the nanorobots to the catalyst around them, and control the opening of the cleaning agent outlet to release the cleaning agent to clean all catalysts until the detected VOCs removal rate in the exhaust gas reaches the threshold.

[0021] Step 9: The first and second magnetic devices adsorb and collect the nanorobots. After collection, the nanorobots are filled with cleaning agents and then put back into the multiphase catalytic oxidation reactor. Under the action of the spray liquid and active oxygen molecules, they are redistributed into the catalyst packing.

[0022] Step 10, End of Step.

[0023] Furthermore, in step 1, the artificial intelligence system obtains the COD 1-X The steps are as follows: The artificial intelligence system uses historical data detected by sensor devices to establish a COD analysis model, and trains and optimizes the COD analysis model; the liquid data detected by the first wireless water quality sensor is transmitted to the COD analysis model to obtain the COD of the measured liquid, which is denoted as COD. 1-X X = 1.2...N, where N is the number of nanorobots and X is the serial number of the nanorobot.

[0024] Furthermore, in step 3, COD located within the catalyst packing region is screened. 1-X The specific steps are as follows:

[0025] Step 3.1: Extract the location data detected by the first wireless water quality sensor, denoted as P. 1-X ;

[0026] Step 3.2: Denote the location of the catalyst packing area as P0;

[0027] Step 3.3, Traverse P 1-X Filter the positional data that is not greater than P0, and denot it as (P 1-X ) | ;

[0028] Step 3.4, obtain and (P) 1-X ) | The corresponding (COD) 1-X ) | .

[0029] In summary, the advantages of this invention are:

[0030] 1) This invention utilizes the characteristic that organic pollutants in exhaust gas dissolve in the spray liquid and are converted into COD to determine whether there is local catalyst deactivation. The first and second wireless water quality sensors detect the data of the spray liquid at the location and transmit this data to the artificial intelligence system. The detected data is analyzed by the established COD analysis model to determine whether there is local catalyst deactivation. When local catalyst deactivation occurs, the artificial intelligence system sends a command to the control device of the nanorobot to open the cleaning agent outlet and release the catalyst cleaning agent to achieve targeted cleaning of the catalyst and restore the catalyst's catalytic ability.

[0031] 2) The first and second wireless VOCs sensors of this invention detect the VOCs concentration in the gas before and after purification in real time and transmit the detected data to the artificial intelligence system. If the VOCs removal rate is less than the threshold for waste gas VOCs removal rate, the entire catalyst is considered deactivated. The artificial intelligence system outputs a catalyst deactivation command to all nanorobots. The control devices of all nanorobots control the extension devices to deploy, fixing the nanorobots to the catalyst around them, and control the opening of the cleaning agent outlet to release the cleaning agent for comprehensive cleaning of the catalyst. After cleaning, the nanorobots made of magnetic materials are collected through a magnetic filter.

[0032] 3) This invention uses a gas detection device and a sensor device to monitor local catalyst deactivation and overall catalyst deactivation in real time, thereby achieving the effect of immediate restoration of catalyst catalytic capacity, realizing online cleaning, and is simple to operate, which is conducive to giving full play to the potential of heterogeneous catalytic oxidation technology. Attached Figure Description

[0033] Figure 1 This is a schematic diagram of the overall structure of the present invention.

[0034] Figure 2 This is a schematic diagram of the overall structure of the nanorobot of the present invention.

[0035] Figure 3 This is a frontal sectional view of the nanorobot of the present invention.

[0036] Figure 4 This is a schematic diagram of the unfolded nanorobot and telescopic device of the present invention.

[0037] Figure 5 a is a front view of the telescopic device of the present invention in the unextended (closed) state.

[0038] Figure 5 b is a top view of the telescopic device of the present invention in the unextended (closed) state.

[0039] Figure 6 a is a top view of the telescopic device of the present invention in its extended state.

[0040] Figure 6 b is a front view of the telescopic device of the present invention in its unfolded state.

[0041] Figure 7 This is a schematic diagram of the telescopic device of the present invention in operation.

[0042] The diagram shows the following components: 1. Gas outlet; 2. First wireless VOCs sensor; 3. First magnetic device; 4. Spray device; 5. Catalyst packing; 6. Support layer; 7. Active oxygen molecule injection port; 8. Second magnetic device; 9. Spray outlet; 10. Second wireless water quality sensor; 11. Gas inlet; 12. Second wireless VOCs sensor; 13. Multiphase catalytic oxidation reactor; 14. Nanorobot; 15. Cleaning agent outlet; 16. First wireless water quality sensor; 17. Battery compartment; 18. Cleaning agent compartment; 19. Anti-corrosion layer; 20. Communication device; 21. Control device; 22. Battery; 23. Telescopic device. Detailed Implementation

[0043] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, unless otherwise specified, the following embodiments and features described therein can be combined with each other.

[0044] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0045] In this embodiment of the invention, all directional indicators (such as up, down, left, right, front, back, lateral, longitudinal, etc.) are only used to explain the relative positional relationship and movement of each component in a specific posture. If the specific posture changes, the directional indicator will also change accordingly.

[0046] Due to installation errors and other reasons, the parallel relationship referred to in the embodiments of the present invention may actually be an approximate parallel relationship, and the perpendicular relationship may actually be an approximate perpendicular relationship.

[0047] Example 1:

[0048] like Figure 1-4 As shown, an artificial intelligence multiphase catalytic oxidation system includes an artificial intelligence system, a multiphase catalytic oxidation reactor 13, and nanorobots 14, gas detection devices, sensor devices, and gas purification devices disposed in the multiphase catalytic oxidation reactor 13. The nanorobots 14, gas detection devices, and sensor devices are wirelessly connected to the artificial intelligence system. The gas detection device detects the VOCs concentration of organic waste gas before and after purification by the gas purification device. The nanorobots 14 are used for targeted cleaning of deactivated catalysts.

[0049] The gas purification device includes a spray device 4, an active oxygen molecule injection device 7, and a catalyst packing 5. The spray device 4 is equipped with a spray liquid, the active oxygen molecule injection device 7 is equipped with active oxygen molecules, and the catalyst packing 5 is composed of several catalysts stacked together. The spray liquid, active oxygen molecules, catalysts, and the products of catalyst and active oxygen molecules work synergistically to purify organic waste gas.

[0050] The spray solution is preferably H2O2 liquid with a mass fraction of 15-30%. Active oxygen molecules are generated by an active oxygen molecule generator (not shown in the figure), and the active oxygen molecules include ·OH⁻ and HO₂. —O2 + O, O( 1 D) O — O2 — O2(a 1 Δ g It contains one or more molecules such as O3, and the catalyst is a carbon-based catalyst. The spray liquid can absorb active oxygen molecules and VOCs in the exhaust gas, so that organic pollutants can be dissolved in the spray liquid.

[0051] The multiphase catalytic oxidation reactor 13 is divided into functional zones, including an upper zone, a middle zone, and a lower zone. The upper zone, the middle zone, and the lower zone are interconnected. The upper zone is the gas outlet section and is equipped with a gas outlet 1. The lower zone is the gas inlet section and is equipped with a spray outlet 9 and a gas inlet 11. The waste gas flows along the gas inlet 11, the middle zone, and the gas outlet 1 to remove organic pollutants (VOCs) from the waste gas.

[0052] A support layer 6 is provided between the middle and lower regions to support the catalytic packing 5.

[0053] The spray device 4 is located in the upper layer, the catalyst packing 5 is located in the middle layer, and the active oxygen molecule injection device 7 is located in the lower layer. That is, the spray device 4 and the active oxygen molecule injection device 7 are located on the upper and lower sides of the catalyst packing 5. The flow direction of the active oxygen molecules is the same as the movement direction of the exhaust gas, and they both move from the lower layer to the middle layer of the multiphase catalytic oxidation reactor 13. The flow direction of the active oxygen molecules is opposite to the spraying direction of the spray liquid. The middle layer of the multiphase catalytic oxidation reactor 13 where the catalyst packing 5 is located is the purification area of ​​the exhaust gas.

[0054] The sensor device includes a first wireless water quality sensor 16 and a second wireless water quality sensor 10. The first wireless water quality sensor 16 is disposed on the nanorobot 14 and is used to detect the data of the liquid being tested at the location of the nanorobot 14. The second wireless water quality sensor 10 is located at the spray outlet 9 in the lower region of the multiphase catalytic oxidation reactor 13 and is used to detect the data of the spray liquid after purifying the waste gas. The data detected by the sensor device is transmitted to the artificial intelligence system to obtain the COD (COD is chemical oxygen demand) of the liquid being tested.

[0055] In this embodiment, the first wireless water quality sensor 16 and the second wireless water quality sensor 10 are both collections of several sensors. They contain the same types of sensors, including a turbidity sensor, a redox potential sensor, a conductivity sensor, a temperature sensor, and a position sensor. The data detected by the first wireless water quality sensor 16 and the second wireless water quality sensor 10 are transmitted to an artificial intelligence system for data analysis to obtain the COD of the liquid being tested.

[0056] The position sensor of the first wireless water quality sensor 16 detects the current position of the nanorobot 14, thereby determining the location of the nanorobot 14 and the distribution of all nanorobots 14.

[0057] Among them, the first wireless water quality sensor 16 is a miniature sensor.

[0058] This embodiment obtains the COD of the liquid under test through the synergistic effect of data detection from turbidity sensors, redox potential sensors, conductivity sensors, and temperature sensors, as well as data analysis from an artificial intelligence system. This replaces the traditional, expensive COD detection sensors, effectively reducing costs.

[0059] The artificial intelligence system analyzes the data transmitted by the first wireless water quality sensor 16 and the second wireless water quality sensor 10 as follows:

[0060] The artificial intelligence system includes a COD analysis model and a COD data module. Data detected by the sensor device is input into the COD analysis model, which outputs COD data with location information. The COD data module analyzes the COD data. The COD analysis model is built using historical data detected by the sensor device. Data detected by the sensor device is input into the COD analysis model, which outputs COD data. The establishment and training of the COD analysis model follows the conventional model establishment and training methods, which will not be elaborated here.

[0061] The COD data module analyzes COD data as follows:

[0062] The detection data of the first wireless water quality sensor 16 is transmitted to the COD analysis model to obtain the COD of the liquid being measured at the location of the nanorobot 14, denoted as COD. 1-X The location data is denoted as P1- X COD 1-X The catalyst at the location of nanorobot 14 (number X) represents the degradation effect of pollutants on the local catalyst, where X = 1.2...N, N is the number of nanorobots 14, and X is the serial number of the nanorobot 14. Generally, one nanorobot 14 is equipped with multiple first wireless water quality sensors 16 to ensure the accuracy of the detection data. In this embodiment, the detection data transmitted to the COD analysis model is the average data detected by multiple first wireless water quality sensors 16 on one nanorobot 14. The data detected by the first wireless water quality sensors 16 can characterize the current location of the nanorobot 14 and the COD of the liquid being measured at that location. The location area of ​​the catalyst packing 5 is a set value, denoted as P0. The process iterates through P... 1-X The comparison locations within P0 are selected to obtain the COD of the liquid being tested corresponding to each comparison location. The COD of the liquid being tested at locations that meet the set conditions is recorded as (COD). 1-X )| The detection data from the second wireless water quality sensor 10 is transmitted to the COD analysis model to obtain the COD2 of the spray liquid after purifying the waste gas. COD2 represents the overall degradation effect of the catalyst on pollutants. The higher the COD, the higher the pollutant content in the liquid, and the lower the purification capacity of the gas purification device. Under the condition that the flow rates of the spray liquid and active oxygen molecules remain unchanged, the catalyst is deactivated. 1-X ) | Compared with COD2, if (COD 1-X ) | If the COD2 exceeds the set multiple a, the catalyst at the location of the current X-sequence nanorobot 14 will be deactivated, and the artificial intelligence system will output a catalyst deactivation command to the current X-sequence nanorobot 14.

[0063] In this embodiment, a is set to 0.7;

[0064] The gas detection device includes a first wireless VOCs sensor 2 and a second wireless VOCs sensor 12. The first wireless VOCs sensor 2 is located at the gas outlet 1 in the upper region of the multiphase catalytic oxidation reactor 13, and the second wireless VOCs sensor 12 is located at the gas inlet 11 in the layer region of the multiphase catalytic oxidation reactor 13. The first wireless VOCs sensor 2 detects the concentration of VOCs in the purified gas (VOCs are organic pollutants), and the second wireless VOCs sensor 12 detects the concentration of VOCs in the gas before purification. The first wireless VOCs sensor 2 and the second wireless VOCs sensor 12 transmit the detected data to the artificial intelligence system.

[0065] The artificial intelligence system includes a VOCs removal rate statistics module. The VOCs removal rate statistics module receives data detected by the gas detection device and obtains the VOCs removal rate of the exhaust gas at the current moment. Specifically, the concentration of VOCs in the purified gas detected by the first wireless VOCs sensor 2 is recorded as A, the concentration of VOCs in the gas before purification detected by the second wireless VOCs sensor 12 is recorded as B, the VOCs removal rate of the exhaust gas is recorded as C, C = (B / A) x 100%, and the threshold of the VOCs removal rate of the exhaust gas is recorded as D. If C is less than D, it is considered that the overall catalyst is deactivated, and the artificial intelligence system outputs a catalyst deactivation command to all nanorobots 14.

[0066] In this embodiment, D is set to 60%;

[0067] Nanorobot 14 is used for targeted cleaning of deactivated catalyst. Nanorobot 14 includes cleaning agent tank 18 and control device 21. The cleaning agent tank 18 is connected to the control device 21. The control device 21 receives commands from the artificial intelligence system and responds to the commands by controlling the cleaning agent tank 18.

[0068] To prevent the nanorobot 14 from changing position during the release of the agent, which would lead to low cleaning efficiency, the nanorobot 14 is equipped with several telescopic devices 23 on its exterior. The telescopic devices 23 are connected to the control device 21. In response to the command of the control device 21, the telescopic devices 23 will stop extending when they come into contact with the catalyst in the area they are in during the extension process. After all the telescopic devices 23 on the nanorobot 14 have come into contact with the catalyst, the nanorobot 14 is fixed in its current position, and then the deactivated catalyst is targeted for cleaning.

[0069] The cleaning agent tank 18 contains a cleaning catalyst and a cleaning agent. The cleaning agent is 0.5% heteropoly acid or 0.1% dilute sulfuric acid by mass. To monitor the content of the cleaning agent in the cleaning agent tank 18, the cleaning agent tank 18 is equipped with a weight sensor (not shown in the figure). The weight sensor transmits the detected data to the artificial intelligence system. Through the detection data of the first wireless water quality sensor 16 of the nanorobot 14 and the weight sensor, the current location of the nanorobot 14 and the content of the cleaning agent can be obtained.

[0070] Preferably, the artificial intelligence system includes a display screen that shows the distribution location of all nanorobots 14 and the cleaning agent content of the nanorobots 14 for easy viewing by the user.

[0071] The cleaning agent compartment 18 is equipped with a cleaning agent outlet 15. The control device 21 controls whether the cleaning agent is released by controlling the opening and closing of the cleaning agent outlet 15.

[0072] When targeted cleaning of deactivated catalysts is required, such as Figure 7 As shown, the control device 21 controls the telescopic device 23 to unfold, fixing the nanorobot 14 to the deactivated catalyst site. The control device 21 also controls the cleaning agent outlet 15 to open, releasing the cleaning agent, thereby enabling the nanorobot 14 to perform targeted cleaning of the deactivated catalyst.

[0073] The exterior of the cleaning agent compartment 18 also includes an anti-corrosion layer 19.

[0074] The nanorobot 14 also includes a battery compartment 17, which is fixedly connected to a cleaning agent compartment 18 to form the overall structure of the nanorobot 14. The control device 21 is located inside the battery compartment 17, which also contains a communication device 20 and a battery 22. The artificial intelligence system remotely transmits data to the control device 21 through the communication device 20, and the battery 22 supplies power to the communication device 20 and the control device 21.

[0075] In this embodiment, the nanorobot 14 is made of ferromagnetic material and has magnetism. The nanorobot 14 is spherical in shape and is a microrobot. The first wireless water quality sensor 16 is disposed on the outside of the nanorobot 14 and is a micro sensor.

[0076] The AI-powered multiphase catalytic oxidation system also includes a magnetic filtration device, comprising a first magnetic device 3 and a second magnetic device 8. The first magnetic device 3 and the second magnetic device 8 adsorb and collect the nanorobots 14 that have detached from the catalyst packing 5. The first magnetic device 3 is located in the upper region of the multiphase catalytic oxidation reactor, between the spray device 4 and the gas outlet 1. The second magnetic device 8 is located in the lower region of the multiphase catalytic oxidation reactor, between the support layer 6 and the spray outlet 9.

[0077] The first magnetic device 3 and the second magnetic device 8 are preferably electromagnets, which are magnetic when energized and non-magnetic when de-energized.

[0078] The first magnetic device 3 adsorbs and collects the nanorobots 14 that move upward with the active oxygen molecules and detach from the catalyst packing 5, preventing them from being lost as the gas flows out of the gas outlet 1. The second magnetic device 8 adsorbs and collects the nanorobots 14 that move downward with the spray liquid and detach from the catalyst packing 5, preventing them from being lost as the spray liquid flows out of the spray outlet 9.

[0079] Due to their small size and weight, nanorobots 14 are distributed in the catalyst packing 5 under the action of the spray liquid and active oxygen molecules. When nanorobots 14 release the cleaning agent, their weight gradually decreases. Under the action of the spray liquid and active oxygen molecules, nanorobots 14 move downward with the spray liquid or move upward with the active oxygen molecules, detaching from the catalyst packing 5 until they are adsorbed and collected by the first magnetic device 3 and the second magnetic device 8. After collection, the nanorobots are filled with cleaning agent and put back into the multiphase catalytic oxidation reactor, where they are redistributed into the catalyst packing 5 under the action of the spray liquid and active oxygen molecules.

[0080] The implementation process of this embodiment is as follows: the spray device 4 and the active oxygen molecule injection device are started, active oxygen molecule gas and spray liquid are released, active oxygen molecule gas and catalyst form products, the catalyst packing area 5 forms a purification zone for the waste gas, the waste gas enters the multiphase catalytic oxidation reactor along the gas inlet, and under the action of the spray liquid, active oxygen molecule gas, catalyst and the products formed by active oxygen molecule gas and catalyst, the organic pollutants in the waste gas are purified, and the purified gas is discharged along the gas outlet 1. During this process, the first wireless water quality sensor 16 and the second wireless water quality sensor 10 detect the data of the liquid being measured at their respective locations, and the artificial intelligence system... Based on the detection data from the first wireless water quality sensor 16 and the second wireless water quality sensor 10, it is determined whether the catalyst at the location of the nanorobot 14 is deactivated. If deactivated, the artificial intelligence system outputs a catalyst deactivation command to the current X-sequence nanorobot 14. The control device 21 of the current X-sequence nanorobot 14 controls the extension device 23 to unfold, fixing the nanorobot 14 to the deactivated catalyst site. The control device 21 controls the cleaning agent outlet 15 to open, releasing the cleaning agent to achieve targeted cleaning of the deactivated catalyst. This continues until the artificial intelligence system detects that the catalyst at that location has reactivated. At this point, the artificial intelligence system sends a stop cleaning command and controls... Device 21 controls the telescopic device 23 to reset, and the cleaning agent outlet 15 is closed; the first wireless VOCs sensor 2 and the second wireless VOCs sensor 12 detect the VOCs concentration of the gas before and after gas purification in real time and transmit the detected data to the artificial intelligence system. The artificial intelligence system obtains the VOCs removal rate based on the detection data from the two locations. If the VOCs removal rate is less than the threshold for the removal rate of VOCs in the exhaust gas, it is considered that the overall catalyst is deactivated. The artificial intelligence system outputs a catalyst deactivation command to all nanorobots 14, and the control device 21 of all nanorobots 14 controls the telescopic device 23 to unfold, fixing the nanorobots 14. The catalyst is positioned in the surrounding area. The control device 21 controls the opening of the cleaning agent outlet 15 to release the cleaning agent and thoroughly clean the catalyst until the detected VOCs removal rate reaches the threshold of the exhaust gas VOCs removal rate. The artificial intelligence system sends a stop cleaning command, the control device 21 controls the telescopic device 23 to reset, and the cleaning agent outlet 15 closes. After cleaning, the first magnetic device 3 and the second magnetic device 8 adsorb and collect the nanorobots 14. After collection, the nanorobots are filled with cleaning agent and put back into the multiphase catalytic oxidation reactor. Under the action of the spray liquid and active oxygen molecules, they are redistributed into the catalyst packing 5.

[0081] This application also provides an artificial intelligence-based heterogeneous catalytic oxidation method, which specifically includes the following steps;

[0082] Step 1: The first wireless water quality sensor 16 detects the liquid data at the location of the nanorobot 14 and transmits it to the artificial intelligence system to obtain the COD of the liquid, which is recorded as COD. 1-X ;

[0083] Step 2: The second wireless water quality sensor 10 detects the liquid data of the spray liquid after purifying the waste gas and transmits it to the artificial intelligence system to obtain the COD of the tested liquid, which is recorded as COD2.

[0084] Step 3: Screen the COD located in region 5 of the catalyst packing in Step 1. 1-X , denoted as (COD) 1-X ) | ;

[0085] Step 4: Determine (COD) 1-X ) | Is the COD2 greater than the set multiple a? If yes, determine that the catalyst at the location of the current X-sequence nanorobot 14 is deactivated and proceed to step 5; otherwise, proceed to step 6.

[0086] Step 5: The artificial intelligence system outputs a catalyst deactivation command to the current X-sequence nanorobot 14. The control device 21 of the current X-sequence nanorobot 14 controls the telescopic device 23 to unfold, fixing the nanorobot 14 to the deactivated catalyst site. The control device 21 controls the cleaning agent outlet 15 to open, releasing the cleaning agent.

[0087] Step 6: The first wireless VOCs sensor 2 detects the VOCs concentration of the purified gas, and the second wireless VOCs sensor 12 detects the VOCs concentration of the exhaust gas before purification. The detected VOCs concentration data is then transmitted to the artificial intelligence system.

[0088] Step 7: The artificial intelligence system calculates the VOCs removal rate of the exhaust gas and determines whether the overall catalyst is deactivated. If yes, proceed to step 8; otherwise, repeat step 1.

[0089] Step 8: The artificial intelligence system outputs a catalyst deactivation command to all nanorobots 14. The control device 21 of all nanorobots 14 controls the telescopic device 23 to unfold, fixing the nanorobots 14 to the catalyst around them. The control device 21 controls the cleaning agent outlet 15 to open, releasing the cleaning agent to clean all catalysts until the detected VOCs removal rate of the exhaust gas reaches the threshold.

[0090] Step 9: The first magnetic device 3 and the second magnetic device 8 adsorb and collect the nanorobots 14. After collection, the nanorobots are filled with cleaning agent and then put back into the multiphase catalytic oxidation reactor. Under the action of the spray liquid and active oxygen molecules, they are redistributed into the catalyst packing 5.

[0091] Step 10, End of Step.

[0092] The aforementioned first wireless water quality sensor 16 is disposed on the nanorobot 14. Both the first wireless water quality sensor 16 and the second wireless water quality sensor 10 include a turbidity sensor, a redox potential sensor, a conductivity sensor, a temperature sensor, and a position sensor.

[0093] In step 1, the artificial intelligence system obtains COD 1-X The steps are as follows: The artificial intelligence system uses historical data detected by the sensor device to establish a COD analysis model, and trains and optimizes the COD analysis model; the liquid data detected by the first wireless water quality sensor 16 is transmitted to the COD analysis model to obtain the COD of the measured liquid, which is denoted as COD. 1-X X = 1.2...N, where N is the number of nanorobots 14 and X is the serial number of nanorobot 14;

[0094] The steps for the AI ​​system to obtain COD2 in step 2 are the same as in step 1, and will not be repeated here.

[0095] In step 3, COD samples located within region 5 of the catalyst packing are screened. 1-X The specific steps are as follows:

[0096] Step 3.1: Extract the location data detected by the first wireless water quality sensor 16, denoted as P. 1-X ;

[0097] Step 3.2: Denote the location of the catalyst packing 5 as P0;

[0098] Step 3.3, Traverse P 1-X Filter the positional data that is not greater than P0, and denot it as (P 1-X ) | ;

[0099] Step 3.4, obtain and (P) 1-X ) | The corresponding (COD) 1-X ) | ;

[0100] The specific steps for step 7 are as follows:

[0101] Step 7.1: The VOCs concentration of the purified gas detected by the first wireless VOCs sensor 2 is recorded as A, the VOCs concentration of the exhaust gas before purification detected by the second wireless VOCs sensor 12 is recorded as B, and the VOCs removal rate of the exhaust gas is recorded as C, C = (B / A) x 100%.

[0102] Step 7.2: Set the threshold for VOCs removal rate in exhaust gas, denoted as D;

[0103] Step 7.3: Determine if C is less than D. If so, determine that the entire catalyst is deactivated.

[0104] Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort should fall within the scope of protection of the present invention.

Claims

1. An artificial intelligence-based heterogeneous catalytic oxidation system, characterized in that: The reactor comprises an artificial intelligence system, a multiphase catalytic oxidation reactor, and nanorobots, gas detection devices, sensor devices, and gas purification devices installed within the reactor. The nanorobots, gas detection devices, and sensor devices are wirelessly connected to the artificial intelligence system. Data from the gas detection devices and sensor devices is transmitted to the artificial intelligence system, which determines whether localized catalyst deactivation and overall catalyst deactivation are occurring. The nanorobots are used for targeted cleaning of the deactivated catalyst. The multiphase catalytic oxidation reactor includes an upper region, a middle region, and a lower region. The upper region has a gas outlet, the lower region has a spray outlet and a gas inlet, and the middle and lower regions... A support layer is provided between the layers. The sensor device includes a first wireless water quality sensor and a second wireless water quality sensor. The first wireless water quality sensor is installed on the nanorobot to detect liquid data at the location of the nanorobot. The second wireless water quality sensor is installed at the spray outlet to detect spray liquid data after purifying the exhaust gas. The data detected by the sensor device is transmitted to the artificial intelligence system to obtain the COD of the tested liquid. The artificial intelligence system includes a COD analysis model and a COD data module. The data detected by the sensor device is input into the COD analysis model and outputs COD data. The COD data module analyzes the COD data and determines whether the local catalyst is deactivated based on the COD data.

2. The artificial intelligence heterogeneous catalytic oxidation system according to claim 1, characterized in that: The gas purification device includes a spray device, an active oxygen molecule injection device, and a catalyst packing. The spray device contains a spray liquid, the active oxygen molecule injection device contains active oxygen molecules, and the catalyst packing is composed of several catalysts stacked together. The spray liquid, active oxygen molecules, catalyst, and the product of catalyst and active oxygen molecules working together purify the waste gas.

3. The artificial intelligence heterogeneous catalytic oxidation system according to claim 2, characterized in that: The spraying device is located in the upper layer, the catalyst packing is located in the middle layer, and the active oxygen molecule injection device is located in the lower layer. The flow direction of the active oxygen molecules is the same as the movement direction of the exhaust gas, and the flow direction of the active oxygen molecules is opposite to the spraying direction of the spray liquid.

4. The artificial intelligence heterogeneous catalytic oxidation system according to claim 3, characterized in that: Both the first and second wireless water quality sensors are collections of several sensors, including a turbidity sensor, a redox potential sensor, a conductivity sensor, a temperature sensor, and a position sensor.

5. An artificial intelligence-based heterogeneous catalytic oxidation method, characterized in that: Includes the following steps: Step 1: The first wireless water quality sensor detects the liquid data at the location of the nanorobot and transmits it to the artificial intelligence system to obtain the COD of the liquid being tested, which is recorded as COD. 1-X ; Step 2: The second wireless water quality sensor detects the liquid data of the spray liquid after purifying the waste gas and transmits it to the artificial intelligence system to obtain the COD of the tested liquid, which is recorded as COD2. Step 3: Screen the COD located in the catalyst packing area from Step 1. 1-X , denoted as (COD) 1-X ) | ; Step 4: Determine (COD) 1-X ) | Is the COD2 greater than the set multiple a? If yes, determine that the catalyst at the location of the current X-sequence nanorobot is deactivated and proceed to step 5; if no, proceed to step 6. Step 5: The artificial intelligence system outputs a catalyst deactivation command to the current X-sequence nanorobot. The control device of the current X-sequence nanorobot controls the extension device to unfold, fixing the nanorobot at the deactivated catalyst site. The control device controls the opening of the cleaning agent outlet to release the cleaning agent for targeted cleaning of the deactivated catalyst. Step 6: The first wireless VOCs sensor detects the VOCs concentration of the purified gas, and the second wireless VOCs sensor detects the VOCs concentration of the exhaust gas before purification. The detected VOCs concentration data is then transmitted to the artificial intelligence system. Step 7: The artificial intelligence system calculates the VOCs removal rate of the exhaust gas and determines whether the overall catalyst is deactivated. If yes, proceed to step 8; otherwise, repeat step 1. Step 8: The artificial intelligence system outputs a catalyst deactivation command to all nanorobots. The control devices of all nanorobots control the telescopic devices to unfold, fix the nanorobots to the catalyst around them, and control the opening of the cleaning agent outlet to release the cleaning agent to clean all catalysts until the detected VOCs removal rate in the exhaust gas reaches the threshold. Step 9: The first and second magnetic devices adsorb and collect the nanorobots. After collection, the nanorobots are filled with cleaning agent and then placed back into the multiphase catalytic oxidation reactor. Under the action of the spray liquid and active oxygen molecules, they are redistributed into the catalyst packing. Step 10, End of Step.

6. The artificial intelligence heterogeneous catalytic oxidation method according to claim 5, characterized in that: In step 1, the artificial intelligence system obtains COD 1-X The steps are as follows: The artificial intelligence system uses historical data detected by sensor devices to build a COD analysis model, and trains and optimizes the COD analysis model; the liquid data detected by the first wireless water quality sensor is transmitted to the COD analysis model to obtain the COD of the measured liquid, which is denoted as COD. 1-X X = 1.2...N, where N is the number of nanorobots and X is the serial number of the nanorobot.

7. The artificial intelligence heterogeneous catalytic oxidation method according to claim 5, characterized in that: In step 3, COD located within the catalyst packing region is screened. 1-X The specific steps are as follows: Step 3.1: Extract the location data detected by the first wireless water quality sensor, denoted as P. 1-X ; Step 3.2: Denote the location of the catalyst packing area as P0; Step 3.3, Traverse P 1-X Filter the positional data that is not greater than P0, and denot it as (P 1-X ) | ; Step 3.4, obtain and (P) 1-X ) | The corresponding (COD) 1-X ) | .

Images