Intelligent anesthetic waste gas dynamic monitoring and purification system and method

Abstract

The present invention relates to the technical field of waste gas monitoring and purification, in particular to an intelligent dynamic monitoring and purification system for anesthetic waste gas and a method thereof, comprising: a waste gas monitoring device, for: real-time detection of concentration, air pressure, temperature and humidity value parameters of anesthetic waste gas; collecting waste gas composition data through a waste gas detection sensor; a waste gas purification device, wirelessly connected to the waste gas monitoring device, for: receiving waste gas parameter data sent by the waste gas monitoring device; performing multi-stage waste gas purification treatment based on the waste gas parameter data; an intelligent control device, wirelessly connected to the waste gas monitoring device and the waste gas purification device, respectively, for: receiving and analyzing waste gas parameter data transmitted by the waste gas monitoring device; controlling the startup and operation parameters of the waste gas purification device according to the analysis results; executing an artificial intelligence algorithm, optimizing the waste gas purification strategy, organically combining processes such as waste gas monitoring, data analysis, decision control and waste gas purification, and realizing full-process intelligent management of anesthetic waste gas treatment.

Description

Technical Field

[0001] The present invention relates to the technical field of waste gas monitoring and purification, in particular to an intelligent anesthetic waste gas dynamic monitoring and purification system and method thereof. Background Art

[0002] With the development of modern medicine, anesthesia technology is increasingly used in surgery. However, if the waste gas generated during anesthesia is not properly handled, it will not only pose a potential threat to the health of medical staff and patients, but may also affect the safety of surgery. Traditional methods of treating anesthetic waste gas mainly rely on passive ventilation and simple filtration systems, which have many shortcomings.

[0003] First, traditional methods lack real-time monitoring capabilities. The concentration of anesthetic waste gas during surgery may change dramatically due to various factors, and traditional systems are often unable to detect these changes in time, leading to potential safety hazards. Secondly, existing purification devices usually use a single treatment technology, such as activated carbon adsorption or simple chemical decomposition. This method is often not ideal for the purification of complex anesthetic waste gas components. In addition, traditional systems generally lack intelligent control and cannot dynamically adjust the treatment strategy according to actual conditions, resulting in energy waste or insufficient treatment.

[0004] The closest existing technology is usually a simple combination of monitoring system and purification system. Although it improves the treatment effect to a certain extent, there are still many problems. For example, there is a lack of effective linkage mechanism between monitoring data and purification process, which leads to delayed system response; the processing capacity of purification device is difficult to accurately adjust according to actual needs, resulting in low processing efficiency; the system lacks self-learning and optimization capabilities and cannot cope with complex and changing surgical environments. Summary of the invention

[0005] The present invention aims to solve the problems existing in the existing anesthetic waste gas treatment system, such as insufficient real-time monitoring, poor purification effect, low intelligence level, etc., and to provide an anesthetic waste gas treatment system and method capable of realizing dynamic monitoring, multi-stage purification and intelligent control.

[0006] The present invention proposes an intelligent anesthetic waste gas dynamic monitoring and purification system, comprising:

[0007] Exhaust gas monitoring device for:

[0008] Real-time detection of the concentration, pressure, temperature and humidity parameters of anesthetic waste gas;

[0009] Collect exhaust gas composition data through exhaust gas detection sensors;

[0010] An exhaust gas purification device, wirelessly connected to the exhaust gas monitoring device, is used to:

[0011] receiving exhaust gas parameter data sent by the exhaust gas monitoring device;

[0012] Based on the exhaust gas parameter data, performing multi-stage exhaust gas purification processing;

[0013] The intelligent control device is wirelessly connected to the exhaust gas monitoring device and the exhaust gas purification device, and is used to:

[0014] receiving and analyzing exhaust gas parameter data transmitted by the exhaust gas monitoring device;

[0015] According to the analysis results, controlling the startup and operation parameters of the exhaust gas purification device;

[0016] Execute artificial intelligence algorithms to optimize exhaust gas purification strategies.

[0017] Preferably, the exhaust gas monitoring device comprises:

[0018] Exhaust gas detection sensor, including:

[0019] Sensor housing;

[0020] A fixing bracket disposed on the top of the sensor housing;

[0021] Three groups of L-shaped metal bars are slidably inserted into the mounting slots on the fixing bracket;

[0022] A stepper motor is fixed to the side of the fixed bracket and is used to drive the L-shaped metal rod to rotate;

[0023] Wherein, the surface of the L-shaped metal rod is coated with a palladium-cobalt hydroxide-titanium nitride nanocomposite material as a sensitive layer.

[0024] Preferably, the L-shaped metal rod comprises a sensing part and a driving part, wherein:

[0025] A limit block adapted to the installation slot is provided between the sensing part and the driving part;

[0026] A miniature camera is installed on the bottom of the sensing part to monitor the surgical environment in real time and identify anesthetic waste gas.

[0027] Preferably, the exhaust gas purification device comprises:

[0028] An ozone generator for preparing ozone;

[0029] an ozone decomposition device, connected to the ozone generation device, and used to receive and decompose the ozone;

[0030] A catalytic reaction device, connected to the ozone decomposition device, for catalyzing the decomposed ozone;

[0031] The filtering device is connected to the catalytic reaction device and is used to remove by-products generated by the catalytic reaction.

[0032] Preferably, a cleaning component is provided in the ozone generating device, including:

[0033] Ozone generator;

[0034] Negative ion generator, used to ionize water molecules in the air to generate negative ions;

[0035] Water mist sprinklers to increase air humidity;

[0036] A fan is used to drive air flow;

[0037] The negative ions generated by the negative ion generator react with the ozone to reduce the ozone concentration.

[0038] Preferably, an ultrasonic transducer is installed in the ozone decomposition device to generate ultrasonic vibration to accelerate ozone decomposition.

[0039] Preferably, the catalytic reaction device comprises:

[0040] An ultraviolet lamp for providing ultraviolet light;

[0041] The multi-layer metal mesh plate works in conjunction with the ultraviolet lamp to introduce ozone into the catalytic reaction zone and realize ultraviolet light catalysis.

[0042] Preferably, the intelligent control device comprises:

[0043] Single chip microcomputer, used to control the operation of each module of the system;

[0044] A Bluetooth module, electrically connected to the single chip computer, for realizing wireless communication;

[0045] Memory, used to store control programs and data;

[0046] Among them, the single chip microcomputer executes artificial intelligence algorithm, including four stages: data collection, data analysis, data processing and data output.

[0047] Preferably, the artificial intelligence algorithm uses a long short-term memory network (LSTM) to perform time series data analysis, and its optimizer is stochastic gradient descent.

[0048] The control method of the intelligent anesthetic waste gas dynamic monitoring and purification system as described above comprises the following steps:

[0049] S01, monitoring the concentration, air pressure, temperature and humidity parameters of anesthetic waste gas in real time through the waste gas monitoring device, and sending the data to the intelligent control device;

[0050] S02, the intelligent control device sets the exhaust gas emission standard and analyzes the specific gas signal in the received exhaust gas parameter data in real time;

[0051] S03, the intelligent control device inputs the exhaust gas parameter data into the artificial intelligence big data algorithm to determine the abnormal deviation of the exhaust gas parameters;

[0052] S04, the intelligent control device determines whether the exhaust gas purification device needs to be started according to the abnormal deviation, and controls the exhaust gas purification device to start when the specific gas signal exceeds the standard;

[0053] S05, starting the ozone generating device, the ozone decomposing device and the catalytic reaction device to perform multi-stage purification treatment on the exhaust gas;

[0054] S06, using the ultrasonic transducer to purify ozone by ultrasonic vibration;

[0055] The process of determining the abnormal deviation of the exhaust gas parameters in step S03 includes:

[0056] K1. Obtain multiple historical data and divide them into training sets and test sets;

[0057] K2. Standardize the data;

[0058] K3, perform PCA dimensionality reduction on the data;

[0059] K4. Calculate the weight of each feature for each category;

[0060] K5. Sum the weights to obtain the abnormal deviation of each data.

[0061] The beneficial effects of the present invention are mainly reflected in the following aspects:

[0062] The intelligent anesthetic waste gas dynamic monitoring and purification system and method of the present invention have achieved significant technological breakthroughs and performance improvements in many aspects through innovative system architecture design and advanced artificial intelligence algorithm application.

[0063] From a macro perspective, the present invention builds a closed-loop intelligent control system, which organically combines waste gas monitoring, data analysis, decision control and waste gas purification, and realizes the intelligent management of the whole process of anesthetic waste gas treatment. This overall architecture design not only greatly improves the response speed and processing efficiency of the system, but also leaves ample room for future expansion and optimization.

[0064] In terms of module collaboration, the three core modules of the present invention - the exhaust gas monitoring device, the exhaust gas purification device and the intelligent control device - form a close information interaction and functional collaboration relationship. The data collected in real time by the exhaust gas monitoring device is analyzed and processed by the intelligent control device to directly guide the adjustment of the working parameters of the exhaust gas purification device. This rapid feedback mechanism effectively solves the problem of disconnection between monitoring and processing in traditional systems.

[0065] From the perspective of resolving technical contradictions, the present invention cleverly balances the contradiction between system performance and energy consumption. By adopting multi-stage purification technology and intelligent control strategy, the system can dynamically adjust the treatment intensity according to the actual pollution level, while ensuring the purification effect and minimizing energy waste. In addition, the present invention also solves the contradiction between efficient purification and safety, especially in the ozone treatment link, innovatively introducing negative ion generators and water mist sprayers, effectively reducing the potential harm of ozone to the environment.

[0066] The multi-stage purification design of the present invention has obvious advantages in terms of complementary and superimposed effects. The combined use of multiple treatment technologies such as ozone oxidation, ultrasonic decomposition, and photocatalytic reaction not only expands the system's ability to treat different types of anesthetic waste gas, but also achieves a doubling of the treatment effect through the complementary advantages of various technologies.

[0067] From a microscopic perspective, the present invention has unique features in sensor design, data analysis algorithm and control strategy. For example, the innovative design of the L-shaped metal rod sensor greatly improves the sensitivity and accuracy of exhaust gas detection; the application of the LSTM network enables the system to have the ability to predict and intervene in advance, which is particularly important when dealing with emergencies.

[0068] In general, the present invention realizes the intelligent, efficient and safe treatment of anesthetic waste gas through the innovative design of system architecture, the rational application of advanced technology and the deep collaboration between modules. This not only significantly improves the safety of the operating room environment, but also provides a new technical paradigm for the field of medical waste gas treatment, which has broad application prospects and important social value. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 It is a logic block diagram of the whole system of the present invention.

[0070] Figure 2 The present invention is a flow chart of the method. DETAILED DESCRIPTION

[0071] See also Figure 1-2The present invention provides an intelligent anesthetic waste gas dynamic monitoring and purification system and method thereof. The system comprises a waste gas monitoring device 1, a waste gas purification device 2 and an intelligent control device 3, and these three main parts are interconnected by wireless communication to form a complete closed-loop control system.

[0072] The waste gas monitoring device 1 is the sensing unit of the system, which is mainly used to detect various parameters of anesthetic waste gas in the operating room in real time. Specifically, the waste gas monitoring device 1 can detect key parameters such as the concentration, air pressure, temperature and humidity of anesthetic waste gas. Real-time monitoring of these parameters is crucial for evaluating the safety of the operating room environment. For example, excessive concentration of anesthetic waste gas may have an adverse effect on the health of medical staff and patients. In one embodiment of the present invention, the waste gas monitoring device 1 can collect data every 5 seconds. This sampling frequency can ensure the real-time nature of the data without bringing too much computational burden to the system.

[0073] The exhaust gas monitoring device 1 and the exhaust gas purification device 2 are wirelessly connected, and this design effectively improves the flexibility and scalability of the system. After receiving the data from the exhaust gas monitoring device 1, the exhaust gas purification device 2 will perform corresponding purification processing based on the data. For example, when it is detected that the concentration of a certain harmful gas exceeds a preset threshold, the exhaust gas purification device 2 will automatically start the corresponding purification module. In a preferred embodiment of the present invention, the exhaust gas purification device 2 adopts a multi-stage purification technology, including ozone treatment, catalytic decomposition and activated carbon adsorption, etc. This multi-stage purification method can effectively remove various types of harmful gases.

[0074] The intelligent control device 3 is the core of the system, and it maintains wireless connection with both the exhaust gas monitoring device 1 and the exhaust gas purification device 2. The intelligent control device 3 receives the data from the exhaust gas monitoring device 1, analyzes and processes it through the built-in artificial intelligence algorithm, and then controls the operating parameters of the exhaust gas purification device 2 according to the analysis results. For example, when it is detected that the concentration of a certain anesthetic gas in the operating room is on an upward trend, the intelligent control device 3 may start the corresponding purification module in advance to prevent the concentration from reaching a dangerous level.

[0075] An important feature of the present invention is the innovative design of the exhaust gas detection sensor 11. The exhaust gas detection sensor 11 includes a sensor housing, a fixing bracket, three sets of L-shaped metal rods and a stepper motor. This design cleverly combines mechanical structure and electrical measurement principles. The fixing bracket is set on the top of the sensor housing and has three mounting slots for mounting the L-shaped metal rods. The L-shaped metal rods can slide in the mounting slots, and this design allows the sensor to adjust the detection position as needed.

[0076] The stepper motor is fixed on the side of the fixed bracket to drive the L-shaped metal rod to rotate. By controlling the rotation of the L-shaped metal rod, the relative position between the metal rods can be changed, thereby generating different induced electromotive forces. The advantage of this design is that complex electrical measurements can be achieved through simple mechanical movement, greatly improving the sensitivity and accuracy of the sensor.

[0077] Another innovative point of the present invention is the special material coated on the surface of the L-shaped metal rod. This palladium-cobalt hydroxide-titanium nitride nanocomposite material is used as a sensitive layer and has excellent gas adsorption performance and electrochemical properties. For example, this material has a high sensitivity to common anesthetic gases such as sevoflurane and isoflurane, and can be detected at the ppb level. The preparation method of the material is also an important innovative point of the present invention. By accurately controlling the proportion of each component and the preparation process, a sensitive material with optimal performance can be obtained.

[0078] The design of the L-shaped metal rod is also very unique, including two main parts: the sensing part and the driving part. There is a limit block between the sensing part and the driving part. The design of this limit block ensures the stability of the L-shaped metal rod in the installation slot. More noteworthy is that a miniature camera is installed on the bottom surface of the sensing part. This miniature camera can not only monitor the surgical environment in real time, but also assist in identifying anesthetic waste gas through image recognition technology. For example, by analyzing the fog conditions in the operating room, the concentration level of anesthetic waste gas can be preliminarily judged.

[0079] The system of the present invention realizes intelligent and dynamic monitoring and purification of anesthetic waste gas in the operating room through this innovative sensor design, combined with advanced data analysis algorithms and multi-stage purification technology. This not only improves the safety of the operating room environment, but also provides a new technical path for the field of medical waste gas treatment. The waste gas purification device 2 of the present invention is the core execution unit of the entire system, and its design concept fully reflects the advanced concept of multi-stage purification. The waste gas purification device 2 mainly includes an ozone generator 21, an ozone decomposition device 22, a catalytic reaction device 23 and a filter device 24. This multi-stage purification design can not only effectively treat various types of anesthetic waste gases, but also minimize the risk of secondary pollution.

[0080] The ozone generator 21 is the first checkpoint in the waste gas purification process. As a strong oxidant, ozone can effectively oxidize and decompose a variety of organic substances, including common anesthetic gases such as sevoflurane and isoflurane. In one embodiment of the present invention, the ozone generator 21 uses a high-voltage discharge method to generate ozone, which can efficiently and stably generate ozone with a controllable concentration. Preferably, the concentration of ozone generated can be dynamically adjusted according to the data transmitted by the waste gas monitoring device 1 to achieve the best purification effect.

[0081] However, ozone itself is also a harmful gas, so the present invention sets an innovative cleaning component in the ozone generator 21. This cleaning component includes a negative ion generator 211, a water mist sprayer 212 and a fan 213. The negative ion generator 211 can generate a large number of negative ions, which can react with ozone to reduce the ozone concentration. The water mist sprayer 212 further promotes the decomposition of ozone by increasing the air humidity. This design not only improves the purification efficiency, but also greatly reduces the potential harm of ozone to the human body.

[0082] The ozone decomposition device 22 is another innovative feature of the present invention. In order to accelerate the decomposition process of ozone, the present invention installs an ultrasonic transducer 221 in the ozone decomposition device 22. The high-frequency vibration generated by the ultrasonic transducer 221 can significantly accelerate the decomposition speed of ozone. In a preferred embodiment of the present invention, the operating frequency of the ultrasonic transducer 221 is set within the range of 20-40kHz, which can effectively decompose ozone without generating significant noise pollution.

[0083] The catalytic reaction device 23 further improves the purification efficiency of the system. The device mainly includes an ultraviolet lamp 231 and a multi-layer metal mesh plate 232. The ultraviolet lamp 231 provides ultraviolet light, while the metal mesh plate 232 serves as a catalyst carrier. The synergistic effect of the two can effectively decompose various organic substances that are difficult to remove. For example, for some anesthetic waste gas components that are not sensitive to ozone oxidation, efficient removal can be achieved through ultraviolet light catalysis. In one embodiment of the present invention, the metal mesh plate 232 uses a nano-scale TiO2 coating, which has extremely strong catalytic activity under ultraviolet light irradiation.

[0084] The filter device 24 is the last line of defense in the entire purification process, and is mainly used to remove byproducts generated in the previous stages. The present invention adopts a multi-layer composite filter material design, including an activated carbon layer, a HEPA filter, and an electrostatic adsorption layer. This multi-layer design can effectively remove various particulate matter and residual gases, ensuring that the exhausted gas meets safety standards.

[0085] The waste gas purification device 2 of the present invention realizes efficient treatment of various types of anesthetic waste gas through this multi-stage purification design. At the same time, through the coordination of the intelligent control device 3, each purification unit can dynamically adjust the working parameters according to the real-time monitoring data, which not only ensures the purification effect but also optimizes energy consumption. This intelligent and dynamic purification scheme not only improves the safety of the operating room environment, but also provides a new technical paradigm for the field of medical waste gas treatment. The intelligent control device 3 of the present invention is the brain of the entire system, responsible for coordinating the work of the waste gas monitoring device 1 and the waste gas purification device 2. The intelligent control device 3 is mainly composed of a single-chip microcomputer 31, a Bluetooth module 32 and a memory 33. This structural design not only ensures the intelligence level of the system, but also takes into account cost-effectiveness.

[0086] The single-chip microcomputer 31 is the core processing unit of the intelligent control device 3. In the preferred embodiment of the present invention, a 32-bit microcontroller of the ARM Cortex-M4 series is used. This series of microcontrollers has the characteristics of high performance and low power consumption, and is very suitable for the application scenario of this system. The single-chip microcomputer 31 is responsible for executing complex artificial intelligence algorithms, which include four main stages: data acquisition, data analysis, data processing and data output.

[0087] The Bluetooth module 32 realizes wireless communication between the intelligent control device 3 and other modules. The present invention uses Bluetooth 5.0 technology, which has lower power consumption and higher transmission speed than traditional Wi-Fi communication. In a medical environment, the low power consumption characteristic can reduce electromagnetic interference to other medical equipment, while high-speed transmission ensures timely processing of real-time data.

[0088] The memory 33 is used to store control programs and data. The present invention adopts a hierarchical storage architecture, including high-speed SRAM and large-capacity Flash storage. This design not only meets the needs of real-time data processing, but also can store a large amount of historical data for subsequent analysis.

[0089] An important innovation of the present invention lies in the application of artificial intelligence algorithms. In particular, a long short-term memory network (LSTM) is used for time series data analysis. The LSTM network is a special recurrent neural network that is particularly suitable for processing and predicting important events with relatively long intervals and delays in time series. In the scenario of anesthetic waste gas monitoring, the LSTM network can effectively capture the long-term trend of waste gas concentration changes, providing a powerful tool for predictive maintenance and abnormal warning.

[0090] The mathematical model of the LSTM network can be expressed as follows:

[0091]

[0092] Among them, f t ,i t ,o t Respectively represent the forget gate, input gate and output gate, C t Indicates the unit state, h t represents the hidden state, x t represents input, W and b represent weight and bias respectively.

[0093] The LSTM network of the present invention uses stochastic gradient descent (SGD) as an optimizer. The update rule of SGD is as follows:

[0094]

[0095] Among them, θ represents the model parameters, η represents the learning rate, and J represents the loss function.

[0096] In practical applications, the system of the present invention will dynamically adjust the hyperparameters of the LSTM network according to different surgical types and patient conditions. For example, for long-term surgery, the number of LSTM memory cells may be increased to capture longer-term trends; and for rapidly changing anesthesia processes, the learning rate may be adjusted to increase the response speed of the model.

[0097] The present invention also provides a control method for an intelligent anesthetic waste gas dynamic monitoring and purification system. The method comprises the following steps:

[0098] S01: The concentration, pressure, temperature and humidity parameters of the anesthetic waste gas are monitored in real time by the waste gas monitoring device 1, and the data are sent to the intelligent control device 3. In one embodiment of the present invention, the monitoring frequency can be set to once every 5 seconds, which can ensure the real-time nature of the data without bringing too much computing burden to the system.

[0099] S02: The intelligent control device 3 sets the exhaust gas emission standard and analyzes the specific gas signal in the received exhaust gas parameter data in real time. The system of the present invention can flexibly set the emission standard according to the regulatory requirements of different countries and regions. For example, for sevoflurane, the emission limit can be set to 2ppm, which is a safety standard adopted by many countries.

[0100] S03: The intelligent control device 3 inputs the exhaust gas parameter data into the artificial intelligence big data algorithm to determine the abnormal deviation of the exhaust gas parameter. This step is one of the core innovations of the present invention, which allows the system to not only rely on fixed thresholds, but also to identify potential abnormal trends.

[0101] S04: The intelligent control device 3 determines whether it is necessary to start the exhaust gas purification device 2 according to the abnormal deviation. When the specific gas signal exceeds the standard, the exhaust gas purification device 2 is controlled to start. The system of the present invention adopts a progressive start-up strategy, that is, the purification intensity is gradually increased according to the degree of abnormality. This method can effectively treat exhaust gas and optimize energy consumption.

[0102] S05: Start the ozone generator 21, the ozone decomposition device 22 and the catalytic reaction device 23 to perform multi-stage purification on the waste gas. This multi-stage treatment process can effectively treat various types of anesthetic waste gas, ensuring the comprehensiveness of the purification effect.

[0103] S06: purify ozone by ultrasonic vibration using ultrasonic transducer 221. This step significantly improves the decomposition efficiency of ozone and reduces the potential harm of ozone to the environment.

[0104] In particular, in step S03, the process of determining the abnormal deviation of the exhaust gas parameter includes the following sub-steps:

[0105] K1: Acquire multiple historical data and divide them into training sets and test sets. The system of the present invention will save at least 3 months of historical data, so that the impact of seasonal changes on exhaust gas parameters can be fully considered.

[0106] K2: Standardize the data. The standardization process uses the Z-score method, that is:

[0107]

[0108] Among them, x is the original data, μ is the mean, and σ is the standard deviation.

[0109] K3: Perform PCA dimensionality reduction on the data. PCA can effectively reduce the dimension of the data and improve the efficiency of subsequent analysis. The system of the present invention usually retains the principal components that can explain 95% of the variance.

[0110] K4: Calculate the weight of each feature for each category. Here, the information gain method is used to calculate the weight:

[0111] IG(Y,X)=H(Y)-H(Y|X),

[0112] Among them, H(Y) is the entropy of category Y, and H(Y|X) is the conditional entropy of Y given feature X. K5: Sum the weights to get the abnormal deviation of each data. The final abnormal deviation calculation formula is:

[0113]

[0114] Among them, w i is the weight of the i-th feature, z i is the standardized feature value.

[0115] K5: Sum the weights to get the abnormal deviation of each data. The final abnormal deviation calculation formula is:

[0116]

[0117] Among them, w i is the weight of the i-th feature, z i is the standardized feature value.

[0118] Through this method, the system of the present invention can accurately identify potential abnormal situations and provide a reliable basis for timely treatment of anesthetic waste gas. This dynamic monitoring and control method based on artificial intelligence greatly improves the intelligence level and operation efficiency of the system and provides a strong guarantee for the safety of the operating room environment.

[0119] 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. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. Intelligent anesthetic waste gas dynamic monitoring and purification system, characterized by: include: Exhaust gas monitoring device for: Real-time detection of concentration, pressure, temperature and humidity parameters of anesthetic waste gas; Collect exhaust gas composition data through exhaust gas detection sensors; An exhaust gas purification device, wirelessly connected to the exhaust gas monitoring device, is used to: receiving exhaust gas parameter data sent by the exhaust gas monitoring device; Based on the exhaust gas parameter data, performing multi-stage exhaust gas purification processing; The intelligent control device is wirelessly connected to the exhaust gas monitoring device and the exhaust gas purification device, and is used to: receiving and analyzing exhaust gas parameter data transmitted by the exhaust gas monitoring device; According to the analysis results, controlling the startup and operation parameters of the exhaust gas purification device; Execute artificial intelligence algorithms to optimize exhaust gas purification strategies.

2. The system according to claim 1, characterized in that The exhaust gas monitoring device comprises: Exhaust gas detection sensor, including: Sensor housing; A fixing bracket disposed on the top of the sensor housing; Three groups of L-shaped metal bars are slidably inserted into the mounting slots on the fixing bracket; A stepper motor is fixed to the side of the fixed bracket and is used to drive the L-shaped metal rod to rotate; Wherein, the surface of the L-shaped metal rod is coated with a palladium-cobalt hydroxide-titanium nitride nanocomposite material as a sensitive layer.

3. The system according to claim 2, characterized in that The L-shaped metal rod comprises a sensing part and a driving part, wherein: A limit block adapted to the installation slot is provided between the sensing part and the driving part; A miniature camera is installed on the bottom of the sensing part to monitor the surgical environment in real time and identify anesthetic waste gas.

4. The system according to claim 1, characterized in that The exhaust gas purification device comprises: An ozone generator for preparing ozone; an ozone decomposition device, connected to the ozone generation device, and used to receive and decompose the ozone; A catalytic reaction device, connected to the ozone decomposition device, for catalyzing the decomposed ozone; The filtering device is connected to the catalytic reaction device and is used to remove by-products generated by the catalytic reaction.

5. The system according to claim 4, characterized in that The ozone generating device is provided with a cleaning component, including: Ozone generator; Negative ion generator, used to ionize water molecules in the air to generate negative ions; Water mist sprinklers to increase air humidity; A fan, used to drive air flow; The negative ions generated by the negative ion generator react with the ozone to reduce the ozone concentration.

6. The system according to claim 4, characterized in that An ultrasonic transducer is installed in the ozone decomposition device to generate ultrasonic vibration to accelerate ozone decomposition.

7. The system according to claim 4, characterized in that The catalytic reaction device comprises: An ultraviolet lamp for providing ultraviolet light; The multi-layer metal mesh plate works in conjunction with the ultraviolet lamp to introduce ozone into the catalytic reaction zone and realize ultraviolet light catalysis.

8. The system according to claim 1, characterized in that The intelligent control device comprises: Single chip microcomputer, used to control the operation of each module of the system; A Bluetooth module, electrically connected to the single chip computer, for realizing wireless communication; Memory, used to store control programs and data; Among them, the single chip microcomputer executes artificial intelligence algorithm, including four stages: data collection, data analysis, data processing and data output.

9. The system according to claim 8, characterized in that The artificial intelligence algorithm uses a long short-term memory network (LSTM) to analyze time series data, and its optimizer is stochastic gradient descent.

10. A control method for the intelligent anesthetic waste gas dynamic monitoring and purification system according to any one of claims 1 to 9, characterized in that: The following steps are involved: S01, monitoring the concentration, air pressure, temperature and humidity parameters of anesthetic waste gas in real time through the waste gas monitoring device, and sending the data to the intelligent control device; S02, the intelligent control device sets the exhaust gas emission standard and analyzes the specific gas signal in the received exhaust gas parameter data in real time; S03, the intelligent control device inputs the exhaust gas parameter data into the artificial intelligence big data algorithm to determine the abnormal deviation of the exhaust gas parameters; S04, the intelligent control device determines whether the exhaust gas purification device needs to be started according to the abnormal deviation, and when the specific gas signal exceeds the standard, controls the exhaust gas purification device to start; S05, starting the ozone generating device, the ozone decomposing device and the catalytic reaction device to perform multi-stage purification treatment on the exhaust gas; S06, using the ultrasonic transducer to purify ozone by ultrasonic vibration; The process of determining the abnormal deviation of the exhaust gas parameters in step S03 includes: K1. Obtain multiple historical data and divide them into training sets and test sets; K2. Standardize the data; K3, perform PCA dimensionality reduction on the data; K4. Calculate the weight of each feature for each category; K5. Sum the weights to obtain the abnormal deviation of each data.

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