Chemical industry park production environment supervision method and system

Abstract

The invention discloses a chemical industry park production environment supervision method and system, and relates to the technical field of environment detection, and the method comprises the steps: calculating a sealing index S1, a sealing risk index S2 and a leakage rate R, integrating the evaluation results, forming a feature vector V, obtaining a sealing evaluation result Rfinal, and comparing the sealing evaluation result Rfinal with a preset leakage threshold Tth. Potential leakage risks are found in time, and a repair process is triggered. Pollution hidden dangers caused by leakage of the waste gas discharge outlet in the chemical industry park are effectively avoided through the process, the management precision of waste gas discharge is improved, a triggering mechanism is monitored in real time and automatically repaired, the problem of sealing performance of the waste gas discharge outlet can be found and treated in time, and the safety of the waste gas discharge outlet is improved. And a monitoring blind area and an error of manual judgment possibly occurring in a traditional monitoring method are remarkably reduced. Compared with traditional manual detection or periodic inspection, the method has the advantages that accurate sealing performance evaluation and a real-time feedback mechanism are adopted;

Description

Technical Field

[0001] The present invention relates to the technical field of environmental detection, and specifically to a method and system for supervising the production environment of a chemical industrial park. Background Art

[0002] Chemical industrial parks belong to the field of chemical industry. As a high-risk and highly polluting production industry, their environmental supervision work has attracted increasing attention from all parties. Controlling environmental pollution and reducing the impact on the surrounding ecological environment and residents' lives have become important tasks that chemical industrial park managers must face. During the production process of chemical industrial parks, the emissions of waste gas, waste water, solid waste, etc. have become the focus of attention. Especially in the field of waste gas emissions, gas leakage not only causes irreversible pollution to the environment, but may also trigger serious accidents such as fires and explosions. Therefore, waste gas emission management plays a crucial role in the environmental supervision of chemical industrial parks.

[0003] Currently, the monitoring of the airtightness of waste gas emission outlets in chemical industrial parks mainly relies on traditional manual inspections and regular inspections, and these methods have obvious limitations. First of all, it is difficult for manual inspections to achieve 24-hour all-weather monitoring. Especially in large-scale parks, the workload of inspection personnel is relatively heavy, and it is difficult to cover each emission outlet. Secondly, due to the reliance on manual experience in inspections, small leakage points are easily overlooked, resulting in the failure to detect leakage problems at some emission outlets in a timely manner. In addition, the time interval of regular inspections is relatively long. Even if there is leakage at the emission outlet, it may not be processed in a timely manner in the short term, thus causing a certain degree of environmental pollution and even affecting the health of surrounding residents and the safety of park production.

[0004] At the technical level, existing monitoring devices mainly focus on monitoring the composition and concentration of waste gas. Although they can detect the overall emission situation of waste gas, there is no precise monitoring method for the airtightness of the emission outlet itself. The lack of continuous monitoring of the airtightness of waste gas emission outlets has also led to a lag in the park managers' awareness of potential leakage risks, thereby affecting the pollution control effect and overall environmental protection level of the park. Summary of the Invention

[0005] Aiming at the deficiencies of the existing technology, the present invention provides a method and system for supervising the production environment of a chemical industrial park, which solves the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention is realized through the following technical solutions: A method for supervising the production environment of a chemical industrial park includes the following steps:

[0007] S1. Through the pressure device and pressure sensor integrated at the waste gas emission outlet, apply air pressure to simulate the airflow state during waste gas emission, and continuously monitor the change information in the area of the waste gas emission outlet to form a feature set Fraw;

[0008] S2. Preprocess the collected feature set Fraw through data cleaning and data standardization to form the preprocessed standard data set Fnom.

[0009] S3. Substitute the obtained standard data set Fnom into the established airtightness evaluation algorithm for processing and analysis to obtain the airtightness index S1, the airtightness risk index S2, and the leakage rate R, and synchronously perform integration processing to obtain the feature vector V.

[0010] S4. Comprehensively evaluate the current exhaust gas outlet according to the feature vector V to obtain the airtightness evaluation result Rfinal, compare and analyze it with the preset leakage threshold Tthe to obtain the airtightness evaluation result of the current exhaust gas outlet, and trigger the repair process mechanism according to the airtightness evaluation result.

[0011] S5. When the repair process mechanism is triggered, extract the positioning and sealing information of the current exhaust gas outlet, perform integration processing, generate an exhaust gas outlet repair task, and send it to the task list of the relevant department for waiting for processing.

[0012] Preferably, the S1 includes S11 and S12.

[0013] S11. Through the pressure device and pressure sensor integrated at the exhaust gas outlet, specifically, integrate an adjustable pressure device at the exhaust gas outlet to simulate the air flow state during exhaust gas emission. At the same time, the pressure device can control the air pressure Papp through the pressure sensor according to the exhaust gas flow rate in the chemical industrial park and the size data of the outlet to simulate the air flow state during exhaust gas emission.

[0014] Specifically, simulate the air flow during exhaust gas emission through S111, S112, and S113.

[0015] S111. Remotely adjust the gas flow Qin through the wireless network, apply pressure to the air pressure Papp by adjusting the gas flow Qin, and the pressure sensor real-time feedbacks the data value of the air pressure Papp.

[0016] S112. Calculate the working air pressure Gq when the current exhaust gas outlet is working properly according to the outlet size Aexit.

[0017] S113. Continuously adjust the air pressure Papp, and then compare the difference with the working air pressure Gq to obtain the air pressure difference △P until the air pressure difference △P enters the range of [0, 1].

[0018] Preferably, after simulating the airflow state during exhaust gas emission by controlling the air pressure Papp, the sealing information of the exhaust gas emission port is monitored in real time through a pressure sensor, a flow rate sensor, and a gas concentration sensor integrated at the exhaust gas emission port. The sealing information includes the air pressure Papp fluctuation information in the area of the exhaust gas emission port, marked as the pressure difference △Praw, the flow rate Vraw of the monitored airflow, and the change in the gas concentration in the area of the exhaust gas emission port, marked as the gas concentration Craw.

[0019] The change information in the area of the exhaust gas emission port is reflected by the pressure difference △Praw, the flow rate Vraw, and the gas concentration Craw, and after integration, the feature set Fraw is obtained.

[0020] Preferably, the S2 includes S21;

[0021] S21: By performing data cleaning preprocessing and data standardization preprocessing on the collected feature set Fraw, a preprocessed standard data set Fnom is formed.

[0022] Among them, the data cleaning preprocessing is preprocessed through S211, S212, and S213;

[0023] S211: Perform missing value preprocessing on each feature parameter in the feature set Fraw. When there are missing values, use the mean filling method to handle the missing values;

[0024] S212: Then perform outlier preprocessing on the feature set Fraw after missing value preprocessing. Identify each feature parameter in the feature set Fraw using the Z-Score method. When outliers are identified, replace them with the mean of the feature parameters to handle the outliers;

[0025] S213: Then perform noise data removal preprocessing on the feature set Fraw after outlier preprocessing, including using a smoothing method to perform noise data removal preprocessing;

[0026] The data standardization preprocessing standardizes the feature set Fraw after noise data removal preprocessing to eliminate the dimensional difference between different feature parameters, and forms a preprocessed standard data set Fnom;

[0027] The standard data set Fnom includes the standard pressure difference △Pnom, the standard flow rate Vnom, and the standard gas concentration Cnom.

[0028] Preferably, the S3 includes S31 and S32;

[0029] S31. Substitute the obtained standard data set Fnom into the established airtightness evaluation algorithm for processing and analysis to obtain the airtightness index S1, the airtightness risk index S2, and the leakage rate R, so as to reflect the airtightness state of the exhaust gas outlet.

[0030] S32. Integrate and process the obtained airtightness index S1, airtightness risk index S2, and leakage rate R to construct a feature vector V for comprehensive evaluation, so as to reflect the overall airtightness state of the exhaust gas outlet.

[0031] Preferably, the airtightness index S1 is obtained through the following calculation formula:

[0032]

[0033] In the formula, exp represents the natural exponential function, Pmax represents the upper limit value of the pressure difference, Vmax represents the upper limit value of the flow rate, Cmax represents the upper limit value of the gas concentration, and α1, α2, and α3 respectively represent the influence coefficients of the standard pressure difference △Pnom, the standard flow rate Vnom, and the standard gas concentration Cnom on the airtightness index S1.

[0034] The airtightness risk index S2 is obtained through the following calculation formula:

[0035]

[0036] In the formula, Thj represents the ambient temperature of the current exhaust gas outlet, Tmax represents the upper limit value of the ambient temperature, Qin represents the gas flow rate, Hmax represents the upper limit value of the gas flow rate discharged by the gas flow rate, and β1, β2, and β3 respectively represent the influence coefficients of the airtightness index S1, the ratio result of the ambient temperature Thj to the upper limit value Tmax of the temperature, and the ratio result of the gas flow rate Qin to the upper limit value Hmax of the gas flow rate.

[0037] The leakage rate R is obtained through the following calculation formula:

[0038]

[0039] In the formula, γ1 and γ2 respectively represent the influence coefficients of the ratio result of the standard flow rate Vnom to the upper limit value Vmax of the flow rate and the ratio result of the standard gas concentration Cnom to the upper limit value Cmax of the gas concentration, and δ represents the adjustment coefficient of the ratio result of the standard pressure difference △Pnom to the upper limit value Pmax of the pressure difference.

[0040] Preferably, the S4 includes S41 and S42;

[0041] S41, comprehensively evaluating the current exhaust gas outlet according to the characteristic vector V, obtaining a sealing evaluation result Rfinal, and verifying the comprehensive sealing of the exhaust gas outlet according to the sealing evaluation result Rfinal;

[0042] The sealing evaluation result Rfinal is obtained by the following calculation formula:

[0043]

[0044] Wherein, e represents the exponential function, r1, r2 and r3 represent the adjustment coefficients of the sealing index S1, sealing risk index S2 and leakage rate R in the characteristic vector V respectively, and ln represents the logarithmic function.

[0045] Preferably, S42, comparing and analyzing the obtained sealing evaluation result Rfinal with a preset leakage threshold Tthe, obtaining the sealing evaluation result of the current exhaust gas outlet, and triggering the repair process mechanism according to the sealing evaluation result;

[0046] The sealing evaluation results are obtained by the following comparative analysis:

[0047] When the sealing evaluation result Rfinal ≤ the leakage threshold Tthe, the sealing evaluation result is obtained as an abnormal result, triggering the repair process mechanism;

[0048] When the sealing evaluation result Rfinal>the leakage threshold Tthe, the sealing evaluation result is obtained as no abnormal result, and the repair process mechanism is not triggered.

[0049] Preferably, the S5 includes S51;

[0050] S51. When the repair process mechanism is triggered, the current exhaust gas outlet positioning and sealing information is extracted, and then integrated and processed to generate an exhaust gas outlet repair task, and sent to the pending task list of the relevant department for processing, and a secondary inspection is performed to verify the repair result of the exhaust gas outlet repair task according to the status of the exhaust gas outlet repair task; specifically, when the exhaust gas outlet repair task in the pending task list is marked as repaired, a secondary inspection is performed to verify the repair result of the exhaust gas outlet repair task;

[0051] Among them, the exhaust gas outlet location is composed of the exhaust gas outlet number ID and the park's three-dimensional coordinates (x, y, z);

[0052] The sealing information is composed of the sealing evaluation result Rfinal and the eigenvector V, which is used by maintenance personnel from relevant departments to understand the current sealing condition of the exhaust gas outlet.

[0053] A production environment supervision system for a chemical industrial park, comprising an exhaust port simulation data acquisition module, a data preprocessing module, a data analysis module, a comprehensive evaluation module, and a repair generation module;

[0054] The exhaust port simulation data acquisition module uses a pressure device and a pressure sensor integrated at the exhaust port to simulate the airflow state during exhaust gas emission by applying air pressure, and real-time monitors the change information in the exhaust port area to form a feature set Fraw;

[0055] The data preprocessing module performs data cleaning preprocessing and data standardization preprocessing on the acquired feature set Fraw to form a preprocessed standard data set Fnom;

[0056] The data analysis module processes and analyzes the obtained standard data set Fnom by substituting it into the established airtightness evaluation algorithm to obtain the airtightness index S1, the airtightness risk index S2, and the leakage rate R, and synchronously performs integration processing to obtain the feature vector V;

[0057] The comprehensive evaluation module comprehensively evaluates the current exhaust port according to the feature vector V to obtain the airtightness evaluation result Rfinal, and compares and analyzes it with the preset leakage threshold Tthe to obtain the sealing evaluation result of the current exhaust port, and triggers a repair process mechanism according to the sealing evaluation result;

[0058] When the repair process mechanism is triggered, the repair generation module extracts the positioning and sealing information of the current exhaust port, then performs integration processing to generate an exhaust port repair task, and sends it to the task list of the relevant department for processing.

[0059] The present invention provides a production environment supervision method and system for a chemical industrial park, having the following beneficial effects:

[0060] (1) By calculating the sealing index S1, the sealing risk index S2, and the leakage rate R, and integrating these evaluation results, a feature vector V is formed, and the sealing evaluation result Rfinal is obtained. By comparing it with the preset leakage threshold Tthe, potential leakage risks can be detected in a timely manner and the repair process can be triggered. This process effectively avoids the pollution hazards caused by leakage at the exhaust gas outlets in chemical industrial parks, improves the management accuracy of exhaust gas emissions. The advantage of this method lies in its dynamic, real-time monitoring, and automated repair trigger mechanism, which can detect and handle sealing problems at the exhaust gas outlets in a timely manner, significantly reducing the monitoring blind spots and errors in manual judgment that may occur in traditional monitoring methods. Compared with traditional manual inspections or periodic checks, this method ensures the effective monitoring and management of the sealing of exhaust gas outlets through precise sealing evaluations and real-time feedback mechanisms, thereby reducing the risk of environmental pollution and ensuring the environmental compliance and production safety of chemical industrial parks.

[0061] (2) Through the sealing index S1, the sealing risk index S2, and the leakage rate R, the calculation methods of these indicators are based on complex mathematical models, which can not only reflect the sealing status of the exhaust gas outlets but also conduct multi-dimensional quantitative evaluations of sealing based on factors such as air flow velocity, gas concentration, and air pressure. In particular, the design of the sealing index S1 combines the natural exponential and logarithmic forms, which can rapidly decline when any parameter increases, thus accurately reflecting the high risk when the sealing is poor. The leakage rate R is ensured to smoothly reflect the changes in air flow velocity, gas concentration, and pressure difference through the combination of exponential functions, and finally ensures that the calculation results are limited within a reasonable range of 0 to 1. Overall, this method can monitor the status of exhaust gas outlets in a more detailed and comprehensive manner, achieving a comprehensive and all-round evaluation of the sealing and leakage risks of exhaust gas outlets.

[0062] (3) Through the sealing evaluation result Rfinal. This evaluation not only reflects the overall sealing status of the exhaust gas outlets but also can judge whether there is a sealing abnormality by comparing the evaluation result with the leakage threshold Tthe. By integrating and processing the location information and sealing evaluation results of the exhaust gas outlets, a repair task for the exhaust gas outlets is generated and sent to the relevant departments for processing, forming an efficient repair and verification mechanism. Once the repair task is marked as repaired, the system will perform a secondary detection to verify the repair effect of the exhaust gas outlets, ensuring the thoroughness and effectiveness of the repair work, and ultimately achieving a comprehensive and systematic management of the exhaust gas outlets. This refined and automated supervision method not only improves the safety management level of the park but also effectively reduces the error rate and delay of manual intervention, providing efficient, accurate, and real-time environmental protection support. Description of the Drawings

[0063] Figure 1Schematic diagram of the steps of a method for supervising the production environment of a chemical industrial park according to the present invention;

[0064] Figure 2 Block diagram schematic diagram of a system for supervising the production environment of a chemical industrial park according to the present invention. Specific implementation manners

[0065] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0066] Embodiment 1

[0067] The present invention provides a method for supervising the production environment of a chemical industrial park. Please refer to Figure 1 , including the following steps:

[0068] S1. Through the pressure device and pressure sensor integrated at the waste gas discharge port, simulate the air flow state during waste gas discharge by applying air pressure, and real-time monitor the change information in the waste gas discharge port area to form a feature set Fraw;

[0069] S2. Through data cleaning preprocessing and data standardization preprocessing of the collected feature set Fraw, form a preprocessed standard data set Fnom;

[0070] S3. According to the obtained standard data set Fnom, substitute it into the established airtightness evaluation algorithm for processing and analysis, obtain the airtightness index S1, the airtightness risk index S2, and the leakage rate R, and synchronously perform integration processing to obtain the feature vector V;

[0071] S4. According to the feature vector V, comprehensively evaluate the current waste gas discharge port, obtain the airtightness evaluation result Rfinal, compare and analyze it with the preset leakage threshold Tthe, obtain the airtightness evaluation result of the current waste gas discharge port, and trigger the repair process mechanism according to the airtightness evaluation result;

[0072] S5. When the repair process mechanism is triggered, extract the positioning and sealing information of the current waste gas discharge port, and then perform integration processing to generate a waste gas discharge port repair task, and send it to the waiting task list of the relevant department for processing.

[0073] In this embodiment, by integrating a pressure device and a pressure sensor, the airflow state during waste gas emission is simulated, and the change information of the waste gas emission port is monitored in real time, generating a feature set Fraw, which provides a reliable data source for subsequent analysis. Then, through data cleaning and standardization preprocessing, the accuracy and consistency of the data are ensured, generating a standard data set Fnom, which provides high-quality input data for the sealability assessment. In the sealability assessment stage, the established algorithm is used to deeply analyze the data, calculating the sealability index S1, the sealability risk index S2, and the leakage rate R. By integrating these assessment results, a feature vector V is formed, making the assessment more comprehensive and accurate. Based on the feature vector V, this method further comprehensively assesses the waste gas emission port, obtaining the sealability assessment result Rfinal, and comparing it with the preset leakage threshold Tthe to timely detect potential leakage risks and trigger the repair process. This process effectively avoids the pollution hazards caused by leakage at the waste gas emission ports in chemical industrial parks, improving the management accuracy of waste gas emissions. The advantage of this method lies in its dynamic, real-time monitoring, and automated repair trigger mechanism, which can timely detect and handle sealability problems at the waste gas emission ports, significantly reducing the monitoring blind spots and manual judgment errors that may occur in traditional monitoring methods. Compared with traditional manual detection or periodic inspections, this method ensures the effective monitoring and management of the sealability of waste gas emission ports through accurate sealability assessment and real-time feedback mechanisms, thereby reducing the risk of environmental pollution and ensuring the environmental protection compliance and production safety of chemical industrial parks.

[0074] Embodiment 2

[0075] This embodiment is an explanatory description based on Embodiment 1. Please refer to Figure 1 , specifically: S1 includes S11 and S12;

[0076] S11. By integrating a pressure device and a pressure sensor at the waste gas emission port, specifically, a pressure device with adjustable pressure is integrated at the waste gas emission port to simulate the airflow state during waste gas emission. At the same time, the pressure device can control the air pressure Papp through the pressure sensor according to the waste gas flow rate in the chemical industrial park and the size data of the emission port to simulate the airflow state during waste gas emission;

[0077] Specifically, the airflow during waste gas emission is simulated through S111, S112, and S113;

[0078] S111. Remotely adjust the gas flow rate Qin through a wireless network, apply pressure to the air pressure Papp by adjusting the gas flow rate Qin, and the pressure sensor provides real-time feedback on the data value of the air pressure Papp;

[0079] S112. Calculate according to the size Aexit of the discharge port to obtain the working air pressure Gq when the current waste gas discharge port is operating normally;

[0080] S113. Continuously adjust the air pressure Papp, and then compare the difference with the working air pressure Gq to obtain the air pressure difference △P until the air pressure difference △P enters the range of [0, 1].

[0081] S12. After simulating the air flow state during waste gas discharge by controlling the air pressure Papp, then monitor the sealing information of the waste gas discharge port in real time through the pressure sensor, flow rate sensor and gas concentration sensor integrated at the waste gas discharge port. The sealing information includes the air pressure Papp fluctuation information in the area of the waste gas discharge port, marked as the pressure difference △Praw, the flow rate Vraw of the monitored air flow, and the change in the gas concentration in the area of the waste gas discharge port, marked as the gas concentration Craw;

[0082] Among them, the pressure difference △Praw is obtained by installing a pressure sensor on both sides of the discharge port to record the air pressure difference inside and outside the discharge port in real time, so as to judge whether there is leakage or poor sealing. Specifically, it is obtained through the calculation formula ΔPraw = Papp - Pout, where Pout represents the actual air pressure of the waste gas discharge port;

[0083] The flow rate Vraw is monitored by the installed flow rate sensor for the flow rate Vraw of the gas. If the flow rate Vraw is abnormal, it may mean that the gas fails to flow normally or there is leakage at the discharge port. Specifically, it is obtained through The calculation formula;

[0084] The gas concentration Craw is monitored by the installed gas concentration sensor for the gas concentration in the area of the waste gas discharge port (such as the preset concentration of several harmful gases) to judge whether leakage occurs;

[0085] The change information in the area of the waste gas discharge port is reflected by the pressure difference △Praw, the flow rate Vraw and the gas concentration Craw, and after integration, the feature set Fraw is obtained.

[0086] In this embodiment, by simulating the airflow state during waste gas emission, the air pressure, airflow velocity, and gas concentration changes at the waste gas emission port are monitored in real time, the sealing information of the waste gas emission port area is comprehensively obtained, and the feature set Fraw is generated. By applying air pressure and adjusting the gas flow rate, the air pressure data feedback in real time by the pressure sensor enables the air pressure difference △Praw to be accurately regulated within the range of 0 to 1. Complemented by this, the airflow velocity Vraw monitored by the flow velocity sensor and the gas concentration data Craw obtained by the gas concentration sensor provide an accurate basis for the early diagnosis of sealing problems. This multi-parameter and multi-dimensional real-time monitoring method enables the sealing problems of the waste gas emission port to be detected in time before serious leakage occurs, reducing the risk of uncontrolled leakage of pollutants. Compared with traditional monitoring methods, by real-time monitoring multiple key parameters in the waste gas emission port area, it can comprehensively reflect the sealing state of the emission port, rather than relying solely on a single index of air pressure or flow velocity. This integrated monitoring method not only greatly improves the accuracy of the emission port sealing detection, but also provides a more dynamic and sensitive management means for chemical industrial parks. In the current waste gas emission monitoring technology, there are often deficiencies such as scattered monitoring data and insufficient timeliness of response. Through the comprehensive analysis of the air pressure difference △Praw, airflow velocity Vraw, and gas concentration Craw, more comprehensive and rapid feedback can be achieved, providing important support for optimizing repair plans and improving environmental supervision efficiency. This real-time and comprehensive monitoring method helps chemical industrial parks identify potential leakage hazards earlier during operation, control the pollutant emission risk from the source, and improve the environmental protection level.

[0087] Embodiment 3

[0088] This embodiment is an explanatory description carried out in Embodiment 2. Please refer to Figure 1 , specifically: The S2 includes S21;

[0089] S21. By performing data cleaning preprocessing and data standardization preprocessing on the collected feature set Fraw, a preprocessed standard data set Fnom is formed;

[0090] Among them, the data cleaning preprocessing is carried out through S211, S212, and S213 for preprocessing;

[0091] S211. Perform missing value preprocessing on each feature parameter in the feature set Fraw. When there are missing values, use the mean filling method to handle the missing values;

[0092] S212. Then perform outlier preprocessing on the feature set Fraw after missing value preprocessing. Identify each feature parameter in the feature set Fraw using the Z-Score method. When outliers are identified, handle the outliers by replacing them with the mean of the feature parameters;

[0093] S213. Then, perform preprocessing for removing noise data on the feature set Fraw after preprocessing the outliers, including using a smoothing method to perform preprocessing for removing noise data.

[0094] Perform preprocessing for data standardization by standardizing the feature set Fraw after preprocessing for removing noise data, eliminating the dimensional differences between different feature parameters, and forming the standardized data set Fnom after preprocessing.

[0095] The standardized data set Fnom includes the standard pressure difference △Pnom, the standard flow rate Vnom, and the standard gas concentration Cnom.

[0096] S3 includes S31 and S32;

[0097] S31. According to the obtained standardized data set Fnom, substitute it into the established sealing performance evaluation algorithm for processing and analysis, obtain the sealing performance index S1, the sealing performance risk index S2, and the leakage rate R, so as to reflect the sealing state of the exhaust gas outlet.

[0098] S32. According to the obtained sealing performance index S1, the sealing performance risk index S2, and the leakage rate R, perform integration processing to construct the feature vector V for comprehensive evaluation, so as to reflect the overall sealing state of the exhaust gas outlet.

[0099] The sealing performance index S1 is obtained through the following calculation formula:

[0100]

[0101] In the formula, exp represents the natural exponential function, Pmax represents the upper limit value of the pressure difference, Vmax represents the upper limit value of the flow rate, Cmax represents the upper limit value of the gas concentration, α1, α2, and α3 respectively represent the influence coefficients of the standard pressure difference △Pnom, the standard flow rate Vnom, and the standard gas concentration Cnom on the sealing performance index S1. The purpose of this formula is to use the combination of logarithm and exponent to ensure that when any parameter increases, the sealing performance index drops rapidly, reflecting the high risk when the sealing performance is poor.

[0102] The sealing performance risk index S2 is obtained through the following calculation formula:

[0103]

[0104] In the formula, Thj represents the ambient temperature of the current exhaust gas outlet, Tmax represents the upper limit value of the ambient temperature, Qin represents the gas flow rate, Hmax represents the upper limit value of the gas flow rate discharged by the gas flow rate, and β1, β2, and β3 respectively represent the influence coefficients of the sealing index S1, the proportional result of the ambient temperature Thj to the upper limit value Tmax of the temperature, and the proportional result of the gas flow rate Qin to the upper limit value Hmax of the gas flow rate. The purpose of this formula is to enhance the influence by the way of the sum of cubes ratio to ensure that the risk index increases rapidly at high temperatures and high gas flow rates;

[0105] The leakage rate R is obtained through the following calculation formula:

[0106]

[0107] In the formula, γ1 and γ2 respectively represent the influence coefficients of the proportional result of the standard flow rate Vnom to the upper limit value Vmax of the flow rate and the proportional result of the standard gas concentration Cnom to the upper limit value Cmax of the gas concentration, and δ represents the adjustment coefficient of the proportional result of the standard pressure difference △Pnom to the upper limit value Pmax of the pressure difference. The purpose of this formula is that the leakage rate R is proportional to the flow rate Vnom and the gas concentration Cnom, and is proportional to the square of the standard pressure difference △Pnom, reflecting the strong influence of the flow rate and the concentration on the leakage rate. At the same time, through the combination of exponential functions, it is ensured that the formula can smoothly reflect the changes of the flow rate, the pressure difference, and the gas concentration, and the result will be limited within the range of 0 to 1.

[0108] In this embodiment, through the fine preprocessing and standardization of the monitoring data of the exhaust gas outlet, the accuracy and stability of the sealing performance evaluation are further improved. The data cleaning and preprocessing include missing value processing, outlier identification and replacement, noise data removal, etc. Through these fine processing steps, it is ensured that each parameter in the feature set Fraw can reflect the real state of the exhaust gas outlet and eliminate the errors caused by data inconsistency, noise and other factors. After the standardization processing, a standard data set Fnom is formed to ensure that different parameters have the same dimension, eliminate the interference caused by the dimension difference, and make the subsequent sealing performance evaluation more objective and accurate.

[0109] By substituting the standardized data into the airtightness evaluation algorithm, the airtightness index S1, the airtightness risk index S2, and the leakage rate R are obtained. The calculation methods of these indicators are based on complex mathematical models, which can not only reflect the airtightness status of the waste gas emission port, but also conduct a multi-dimensional quantitative evaluation of the airtightness according to factors such as air flow velocity, gas concentration, and air pressure. Especially the design of the airtightness index S1, which combines the natural exponent and logarithm, can rapidly decline when any parameter increases, thus accurately reflecting the high risk when the airtightness is poor. The leakage rate R, through the combination of exponential functions, ensures that it can smoothly reflect the changes in air flow velocity, gas concentration, and pressure difference, and finally ensures that the calculation result is limited within a reasonable range of 0 to 1. Overall, this method can monitor the status of the waste gas emission port more carefully and comprehensively, provide efficient and accurate airtightness evaluation for enterprises, give early warnings in a timely manner and reduce the possible environmental pollution risks. Different from the traditional single-parameter monitoring method, this solution realizes the comprehensive and all-round evaluation of the airtightness and leakage risk of the waste gas emission port through the refined processing of multi-dimensional data and the in-depth mining of complex algorithms, greatly improving the efficiency and accuracy of the chemical industrial park in environmental monitoring, and providing more efficient and intelligent technical support for environmental protection.

[0110] Example 4

[0111] This example is an explanatory note based on Example 3. Please refer to Figure 1 , specifically: The S4 includes S41 and S42;

[0112] S41. Comprehensively evaluate the current waste gas emission port according to the eigenvector V, obtain the airtightness evaluation result Rfinal, and verify the comprehensive airtightness of the waste gas emission port according to the result of the airtightness evaluation result Rfinal;

[0113] The airtightness evaluation result Rfinal is obtained through the following calculation formula:

[0114]

[0115] In the formula, e represents the exponential function, r1, r2, and r3 respectively represent the adjustment coefficients of the airtightness index S1, the airtightness risk index S2, and the leakage rate R in the eigenvector V, and ln represents the logarithmic function.

[0116] S42. Compare and analyze the obtained airtightness evaluation result Rfinal with the preset leakage threshold Tthe, obtain the sealing evaluation result of the current waste gas emission port, and trigger the repair process mechanism according to the sealing evaluation result;

[0117] The sealing evaluation result is obtained through the following comparison and analysis method:

[0118] When the sealing evaluation result Rfinal ≤ the leakage threshold Tthe, the sealing evaluation result is obtained as an abnormal result, triggering the repair process mechanism;

[0119] When the sealing evaluation result Rfinal>the leakage threshold Tthe, the sealing evaluation result is obtained as no abnormal result, and the repair process mechanism is not triggered.

[0120] The S5 includes S51;

[0121] S51. When the repair process mechanism is triggered, the current exhaust gas outlet positioning and sealing information is extracted, and then integrated and processed to generate an exhaust gas outlet repair task, and sent to the pending task list of the relevant department for processing, and a secondary inspection is performed to verify the repair result of the exhaust gas outlet repair task according to the status of the exhaust gas outlet repair task; specifically, when the exhaust gas outlet repair task in the pending task list is marked as repaired, a secondary inspection is performed to verify the repair result of the exhaust gas outlet repair task;

[0122] Among them, the exhaust gas outlet location is composed of the exhaust gas outlet number ID and the park's three-dimensional coordinates (x, y, z);

[0123] The sealing information is composed of the sealing evaluation result Rfinal and the eigenvector V, which is used by maintenance personnel from relevant departments to understand the current sealing condition of the exhaust gas outlet.

[0124] In this embodiment, the monitoring and repair efficiency of the exhaust gas outlet is effectively improved through accurate sealing evaluation and repair mechanism. By comprehensively evaluating the sealing index S1, sealing risk index S2 and leakage rate R in the feature vector V, combined with the calculation method of the exponential and logarithmic functions, the sealing evaluation result Rfinal is obtained. This evaluation not only reflects the overall sealing status of the exhaust gas outlet, but also can judge whether there is a sealing abnormality based on the comparison of the evaluation results with the leakage threshold Tthe. When Rfinal is less than or equal to the leakage threshold, the system can automatically trigger the repair process mechanism, respond to and deal with possible leakage problems in a timely manner, ensure that the exhaust gas emissions of the park meet environmental protection requirements, and reduce the risk of environmental pollution. On the basis of achieving real-time monitoring and accurate judgment, this evaluation method also integrates the exhaust gas outlet positioning information and sealing evaluation results to generate exhaust gas outlet repair tasks and send them to relevant departments for processing, forming a set of efficient repair and verification mechanisms. Once the repair task is marked as repaired, the system will perform secondary detection to verify the repair effect of the exhaust gas outlet, ensure the thoroughness and effectiveness of the repair work, and finally achieve comprehensive and systematic management of the exhaust gas outlet. This refined and automated supervision method not only improves the safety management level of the park, but also effectively reduces the error rate and delay of manual intervention, providing efficient, accurate and real-time environmental protection support.

[0125] Example 5

[0126] A production environment supervision system for a chemical industrial park. Refer to Figure 2 , specifically: it includes an exhaust port simulation data acquisition module, a data preprocessing module, a data analysis module, a comprehensive evaluation module, and a repair generation module;

[0127] The exhaust port simulation data acquisition module, through a pressure device and a pressure sensor integrated at the exhaust port, simulates the airflow state during exhaust gas emission by applying air pressure and real-time monitors the change information in the exhaust port area to form a feature set Fraw;

[0128] The data preprocessing module preprocesses the collected feature set Fraw through data cleaning preprocessing and data standardization preprocessing to form a preprocessed standard data set Fnom;

[0129] The data analysis module, according to the obtained standard data set Fnom, substitutes it into the established airtightness evaluation algorithm for processing and analysis, obtains the airtightness index S1, the airtightness risk index S2, and the leakage rate R, and synchronously performs integration processing to obtain the feature vector V;

[0130] The comprehensive evaluation module comprehensively evaluates the current exhaust port according to the feature vector V, obtains the airtightness evaluation result Rfinal, compares and analyzes it with the preset leakage threshold Tthe, obtains the sealing evaluation result of the current exhaust port, and triggers the repair process mechanism according to the sealing evaluation result;

[0131] When the repair generation module triggers the repair process mechanism, it extracts the positioning and sealing information of the current exhaust port, then performs integration processing, generates a repair task for the exhaust port, and sends it to the waiting task list of the relevant department for processing.

[0132] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for supervising the production environment of a chemical park, characterized by: The following steps are involved: S1, through the pressure device and pressure sensor integrated at the exhaust gas outlet, the air flow state during exhaust gas emission is simulated by applying air pressure, and the change information of the exhaust gas outlet area is monitored in real time to form a feature set Fraw; S2, by performing data cleaning preprocessing and data standardization preprocessing on the collected feature set Fraw, a preprocessed standard data set Fnom is formed; S3, according to the acquired standard data set Fnom, substitute it into the established sealing evaluation algorithm for processing and analysis, obtain the sealing index S1, the sealing risk index S2 and the leakage rate R, and simultaneously perform integration processing to obtain the feature vector V; S4. Comprehensively evaluate the current exhaust gas outlet according to the characteristic vector V, obtain the sealing evaluation result Rfinal, and compare and analyze it with the preset leakage threshold Tthe to obtain the sealing evaluation result of the current exhaust gas outlet, and trigger the repair process mechanism according to the sealing evaluation result; S5. When the repair process mechanism is triggered, the current exhaust gas outlet positioning and sealing information is extracted, integrated and processed, and the exhaust gas outlet repair task is generated and sent to the pending task list of the relevant department for processing.

2. A method for supervising production environment in a chemical park according to claim 1, characterized in that: Said S1 includes S11 and S12; S11, by integrating a pressure device and a pressure sensor at the exhaust gas discharge port, specifically integrating a pressure device with adjustable pressure at the exhaust gas discharge port to simulate the airflow state during exhaust gas discharge, and at the same time, the pressure device can control the air pressure Papp by controlling the pressure sensor according to the exhaust gas flow rate and the size data of the discharge port of the chemical park to simulate the airflow state during exhaust gas discharge; Specifically, the airflow during the exhaust emission is simulated through S111, S112 and S113; S111, remotely adjusting the gas flow Qin through a wireless network, applying pressure Papp by adjusting the gas flow Qin, and feeding back the data value of the pressure Papp in real time through a pressure sensor; S112, calculating, based on the size of the exhaust outlet Aexit, the working pressure Gq of the exhaust outlet when it is currently operating normally; S113, by continuously adjusting the air pressure Papp, and then comparing the difference with the working air pressure Gq, the air pressure difference △P is obtained, until the air pressure difference △P enters the range of [0, 1].

3. A method for supervising production environment in a chemical park according to claim 2, characterized in that: S12, after simulating the airflow state during exhaust gas emission by controlling the air pressure Papp, the sealing information of the exhaust gas emission port is monitored in real time through the pressure sensor, flow rate sensor and gas concentration sensor integrated in the exhaust gas emission port, wherein the sealing information includes monitoring the fluctuation information of the air pressure Papp in the exhaust gas emission port area, marked as the pressure difference △Praw, monitoring the flow rate Vraw of the airflow, and monitoring the change of the gas concentration in the exhaust gas emission port area, marked as the gas concentration Craw; The pressure difference △Praw, flow velocity Vraw and gas concentration Craw are used to reflect the change information of the exhaust gas outlet area, and after integration, the feature set Fraw is obtained.

4. A method for supervising production environment in a chemical park according to claim 3, characterized in that: Said S2 includes S21; S21, performing data cleaning preprocessing and data standardization preprocessing on the collected feature set Fraw to form a preprocessed standard data set Fnom; Among them, data cleaning preprocessing is performed through S211, S212 and S213; S211, performing missing value preprocessing on each feature parameter in the feature set Fraw, and when there are missing values, performing missing value processing by using the mean filling method; S212, performing outlier preprocessing on the feature set Fraw after the missing value preprocessing, by using the Z-Score method to identify each feature parameter in the feature set Fraw, and when an outlier is identified, replacing it with the mean value of the feature parameter to perform outlier processing; S213, performing noise data removal preprocessing on the feature set Fraw after the outlier preprocessing, including performing noise data removal preprocessing using a smoothing method; Data standardization preprocessing standardizes the feature set Fraw of noise data removal preprocessing to eliminate the dimensional differences between different feature parameters and form the preprocessed standard data set Fnom; The standard data set Fnom includes a standard pressure difference ΔPnom, a standard flow rate Vnom and a standard gas concentration Cnom.

5. A method for supervising production environment in a chemical park according to claim 4, characterized in that: The S3 includes S31 and S32; S31, according to the acquired standard data set Fnom, substitute it into the established sealing evaluation algorithm for processing and analysis, obtain the sealing index S1, the sealing risk index S2 and the leakage rate R, and reflect the sealing status of the exhaust gas discharge port; S32, integrating the acquired sealing index S1, sealing risk index S2 and leakage rate R, constructing a comprehensive evaluation feature vector V to reflect the overall sealing status of the exhaust gas outlet.

6. A method for supervising production environment in a chemical park according to claim 5, characterized in that: The sealing index S1 is obtained by the following calculation formula: Wherein, exp represents the natural exponential function, Pmax represents the upper limit of the pressure difference, Vmax represents the upper limit of the flow rate, Cmax represents the upper limit of the gas concentration, α1, α2 and α3 represent the influence coefficients of the standard pressure difference △Pnom, the standard flow rate Vnom and the standard gas concentration Cnom on the sealing index S1 respectively; The sealing risk index S2 is obtained by the following calculation formula: Wherein, Thj represents the ambient temperature of the current exhaust gas outlet, Tmax represents the upper limit of the ambient temperature, Qin represents the gas flow rate, Hmax represents the upper limit of the gas flow rate discharged by the gas flow rate, β1, β2 and β3 represent the influence coefficients of the sealing index S1, the ratio of the ambient temperature Thj to the upper limit of the temperature Tmax and the ratio of the gas flow rate Qin to the upper limit of the gas flow rate Hmax respectively; The leakage rate R is obtained by the following calculation formula: In the formula, γ1 and γ2 respectively represent the influence coefficients of the ratio of the standard flow rate Vnom to the flow rate upper limit Vmax and the ratio of the standard gas concentration Cnom to the gas concentration upper limit Cmax, and δ represents the adjustment coefficient of the ratio of the standard pressure difference △Pnom to the pressure difference upper limit Pmax.

7. A method for supervising production environment in a chemical park according to claim 1, characterized in that: The S4 includes S41 and S42; S41, comprehensively evaluating the current exhaust gas outlet according to the characteristic vector V, obtaining a sealing evaluation result Rfinal, and verifying the comprehensive sealing of the exhaust gas outlet according to the sealing evaluation result Rfinal; The sealing evaluation result Rfinal is obtained by the following calculation formula: Wherein, e represents the exponential function, r1, r2 and r3 represent the adjustment coefficients of the sealing index S1, sealing risk index S2 and leakage rate R in the characteristic vector V respectively, and ln represents the logarithmic function.

8. A method for supervising production environment in a chemical park according to claim 7, characterized in that: S42, comparing and analyzing the obtained sealing evaluation result Rfinal with the preset leakage threshold Tthe, obtaining the sealing evaluation result of the current exhaust gas outlet, and triggering the repair process mechanism according to the sealing evaluation result; The sealing evaluation results are obtained by the following comparative analysis: When the sealing evaluation result Rfinal ≤ the leakage threshold Tthe, the sealing evaluation result is obtained as an abnormal result, triggering the repair process mechanism; When the sealing evaluation result Rfinal>the leakage threshold Tthe, the sealing evaluation result is obtained as no abnormal result, and the repair process mechanism is not triggered.

9. A method for supervising production environment in a chemical park according to claim 1, characterized in that: The S5 includes S51; S51. When the repair process mechanism is triggered, the current exhaust gas outlet positioning and sealing information is extracted, and then integrated and processed to generate an exhaust gas outlet repair task, and sent to the pending task list of the relevant department for processing, and a secondary inspection is performed to verify the repair result of the exhaust gas outlet repair task according to the status of the exhaust gas outlet repair task; specifically, when the exhaust gas outlet repair task in the pending task list is marked as repaired, a secondary inspection is performed to verify the repair result of the exhaust gas outlet repair task; Among them, the exhaust gas outlet location is composed of the exhaust gas outlet number ID and the park's three-dimensional coordinates (x, y, z); The sealing information is composed of the sealing evaluation result Rfinal and the eigenvector V, which is used by maintenance personnel from relevant departments to understand the current sealing condition of the exhaust gas outlet.

10. A chemical park production environment supervision system, applied to a chemical park production environment supervision method according to any one of claims 1 to 9, characterized in that: It includes an exhaust port simulation data acquisition module, a data preprocessing module, a data analysis module, a comprehensive evaluation module and a repair generation module; The exhaust port simulation data acquisition module uses a pressure device and a pressure sensor integrated at the exhaust port to simulate the airflow state during exhaust gas emission by applying air pressure, and monitors the change information of the exhaust port area in real time to form a feature set Fraw; The data preprocessing module performs data cleaning preprocessing and data standardization preprocessing on the collected feature set Fraw to form a preprocessed standard data set Fnom; The data analysis module substitutes the acquired standard data set Fnom into the established sealing evaluation algorithm for processing and analysis, obtains the sealing index S1, the sealing risk index S2 and the leakage rate R, and simultaneously performs integration processing to obtain the feature vector V; The comprehensive evaluation module comprehensively evaluates the current exhaust gas outlet according to the characteristic vector V, obtains the sealing evaluation result Rfinal, and compares and analyzes it with the preset leakage threshold Tthe, obtains the sealing evaluation result of the current exhaust gas outlet, and triggers the repair process mechanism according to the sealing evaluation result; When the repair process mechanism is triggered, the repair generation module extracts the current exhaust gas outlet positioning and sealing information, integrates and processes it, generates an exhaust gas outlet repair task, and sends it to the pending task list of the relevant department for processing.

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