Refinery VOCs real-time monitoring and control system

Abstract

The invention relates to the technical field of environment monitoring and control, in particular to a refinery VOCs (volatile organic compounds) real-time monitoring and control system which comprises an environment data acquisition module, a data processing module, a source positioning module, an intelligent control module, a feedback and optimization module and a user interaction module. The data processing module carries out cleaning, abnormal value detection and trend analysis on the collected environment data, the source positioning module provides source information, and the intelligent control module automatically generates a control strategy according to the source positioning information and a trend prediction result, adjusts operation parameters of related equipment in a refinery plant, and controls the operation of the refinery plant. And the feedback and optimization module monitors the effect of the control strategy in real time and dynamically optimizes the control strategy according to feedback. The user interaction module provides a visual interface and a remote access function, through accurate monitoring and intelligent control, efficient management of VOCs emission of the refinery plant is achieved, the precision and stability of the system are improved, and environmental pollution is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental monitoring and control, and in particular to a refinery VOCs real-time monitoring and control system. Background Art

[0002] With the continuous acceleration of the industrialization process, the volatile organic compounds (VOCs) emitted by refineries and other heavy industrial enterprises during the production process pose a serious threat to the environment and human health. VOCs are not only one of the important sources of air pollution, but also participate in photochemical reactions under the action of sunlight to generate ozone and fine particulate matter (PM2.5), leading to deterioration of air quality. Therefore, how to effectively monitor and control the emission of VOCs has become an important task in the environmental protection management of refineries.

[0003] However, traditional VOCs monitoring systems often rely on a few fixed monitoring points, making it difficult to achieve comprehensive coverage of the entire refinery area. In addition, the data collection process is easily disturbed by noise and outliers, resulting in insufficient accuracy and reliability of monitoring data, and unable to accurately reflect the actual emission of VOCs. In addition, traditional monitoring and control systems lack the support of intelligent algorithms and cannot dynamically adjust and optimize control strategies, resulting in limited stability and continuous improvement capabilities of the system in long-term operation. Summary of the invention

[0004] Based on the above objectives, the present invention provides a refinery VOCs real-time monitoring and control system.

[0005] The refinery VOCs real-time monitoring and control system includes an environmental data acquisition module, a data processing module, a VOCs source location module, an intelligent control module, a feedback and optimization module, and a user interaction module, among which;

[0006] The environmental data acquisition module is installed in key areas of the refinery to collect environmental data in real time, including temperature, humidity, wind speed and VOCs concentration;

[0007] The data processing module is used to pre-process and deeply analyze the collected environmental data, including a data cleaning unit, an outlier detection unit and a trend analysis unit;

[0008] The source positioning module determines the emission source of VOCs based on the analysis results of the data processing module, using the wind field model and meteorological data. The source positioning module includes a source analysis unit and a positioning algorithm unit;

[0009] The intelligent control module is used to automatically adjust the operating parameters of relevant equipment in the refinery according to the source information provided by the source positioning module and the trend prediction results provided by the data processing module to reduce VOCs emissions. The intelligent control module includes a control algorithm unit and an execution unit, which automatically generates a control strategy and implements it through the execution unit;

[0010] The feedback and optimization module is used to monitor the effect of the control strategy in real time and dynamically adjust the control strategy according to the effect feedback. The feedback and optimization module includes an effect evaluation unit and an optimization algorithm unit. By evaluating the control effect, the control measures are further optimized.

[0011] The user interaction module includes a visual interface and a remote access function, which is used to provide users with real-time monitoring data, analysis reports and control status, and support users to remotely monitor and operate the system.

[0012] Optionally, the environmental data acquisition module specifically includes:

[0013] Temperature sensor: used to monitor the ambient temperature of key areas of the refinery in real time;

[0014] Humidity sensor: used to monitor ambient humidity;

[0015] Wind speed sensor: used to monitor wind speed inside and outside the refinery;

[0016] VOCs concentration sensor: used to detect the concentration of VOCs in the air.

[0017] Optionally, the data processing module specifically includes:

[0018] Data cleaning unit: used to clean the collected environmental data, remove noise and invalid data, and ensure the accuracy of the data. Data cleaning adopts a rule-based cleaning algorithm and makes corrections in combination with context information;

[0019] Outlier detection unit: Detect outliers in data using statistical analysis and machine learning models;

[0020] Trend analysis unit: used to perform time series analysis on environmental data and predict the trend of VOCs concentration changes.

[0021] Optionally, the source positioning module specifically includes:

[0022] Source analysis unit: Analyze VOCs emission sources in combination with trend analysis results of the data processing module;

[0023] Positioning algorithm unit: Use wind field model and meteorological data to determine the emission source of VOCs. The positioning algorithm adopts the upwind field tracking algorithm. The basic formula of the algorithm is:

[0024]

[0025] Among them, x(t) is the source position, x0 is the initial position, and v(x(t′), t′) is the wind speed vector.

[0026] Optionally, the intelligent control module specifically includes:

[0027] Control algorithm unit: Based on the source information provided by the source location module, the control strategy is generated using the algorithm based on model predictive control. The optimization goal of the model predictive control algorithm is:

[0028]

[0029] Among them, y(t+k|t) is the predicted output, y ref (t+k) is the reference output, Δu(t+k|t) is the control input increment, Q and R are weight matrices;

[0030] Execution unit: used to implement control strategies and automatically adjust the operating parameters of related equipment in the refinery, including adjusting valve opening, fan speed and heater power.

[0031] Optionally, the feedback and optimization module specifically includes:

[0032] Effect evaluation unit: monitors the implementation effect of the control strategy in real time and uses the evaluation method based on fuzzy logic to evaluate the control effect;

[0033] Optimization algorithm unit: Based on the effect evaluation results, the genetic algorithm is used to optimize the control strategy.

[0034] Optionally, the user interaction module specifically includes:

[0035] Visualization interface: used to display real-time monitoring data, analysis reports and control status. The interface is built with data visualization tools such as Grafana or Tableau and supports multiple chart types, including line charts, bar charts and pie charts.

[0036] Remote access function: Through the Internet or local area network, users are supported to remotely monitor the operating status of the system and perform operations. Remote access uses the HTTPS encryption protocol to ensure the security of data transmission.

[0037] Optionally, the intelligent control module further includes:

[0038] Early warning system: When the VOCs concentration reaches the preset threshold, the early warning signal is automatically triggered. The early warning information is notified to the user in real time through the visual interface and remote access function of the user interaction module. The setting of the early warning threshold is based on environmental regulations and corporate standards.

[0039] Beneficial effects of the present invention:

[0040] In the present invention, the environmental data acquisition module integrates multiple sensors, such as temperature, humidity, wind speed and VOCs concentration sensors, and can realize comprehensive and accurate real-time monitoring of VOCs emissions in key areas of the refinery. Through the data cleaning, outlier detection and trend analysis units in the data processing module, the collected environmental data are deeply analyzed, noise and outliers are effectively filtered, and the accuracy and reliability of the data are improved. The source positioning module accurately locates the emission source of VOCs through the wind field model and meteorological data, and combined with the automatic control strategy of the intelligent control module, it realizes accurate regulation of related equipment in the refinery, effectively reduces the emission of VOCs, and improves the efficiency of environmental protection and safe production.

[0041] The present invention adopts a feedback and optimization module, monitors the effect of the control strategy in real time, and uses fuzzy logic and genetic algorithms to dynamically evaluate and optimize the control strategy, so that the system can adaptively adjust under complex working conditions to ensure continuous optimization of VOCs control effects. This adaptability and optimization capability not only improves the intelligence level of the system, but also enhances the stability and reliability of the system in long-term operation, ensuring continuous improvement of VOCs emission control in the refinery. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0043] Figure 1 Schematic diagram of a system flow of an embodiment of the present invention. DETAILED DESCRIPTION

[0044] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. At the same time, it is explained here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments, and those skilled in the art may also adopt other alternatives to implement some known technologies; and the accompanying drawings are only for more specific description of the embodiments, and are not intended to specifically limit the present invention.

[0045] It should be noted that the references to "one embodiment", "an embodiment", "an exemplary embodiment", "some embodiments" and the like in the specification indicate that the embodiments described may include specific features, structures or characteristics, but not every embodiment may include the specific features, structures or characteristics. In addition, when a specific feature, structure or characteristic is described in conjunction with an embodiment, it should be within the knowledge of a person skilled in the art to implement such feature, structure or characteristic in conjunction with other embodiments (whether or not explicitly described).

[0046] In general, a term can be understood, at least in part, from its use in context. For example, depending, at least in part, on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending, at least in part, on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0047] like Figure 1 As shown, the refinery VOCs real-time monitoring and control system includes an environmental data acquisition module, a data processing module, a VOCs source positioning module, an intelligent control module, a feedback and optimization module, and a user interaction module, among which;

[0048] Environmental data acquisition modules are installed in key areas of the refinery to collect real-time environmental data, including temperature, humidity, wind speed and VOCs concentration;

[0049] The data processing module is used to pre-process and deeply analyze the collected environmental data, including a data cleaning unit, an outlier detection unit, and a trend analysis unit;

[0050] The source location module determines the emission source of VOCs based on the analysis results of the data processing module, using the wind field model and meteorological data. The source location module includes a source analysis unit and a location algorithm unit;

[0051] The intelligent control module is used to automatically adjust the operating parameters of relevant equipment in the refinery to reduce VOCs emissions based on the source information provided by the source positioning module and the trend prediction results provided by the data processing module. The intelligent control module includes a control algorithm unit and an execution unit, which automatically generates a control strategy and implements it through the execution unit;

[0052] The feedback and optimization module is used to monitor the effect of the control strategy in real time and dynamically adjust the control strategy according to the effect feedback. The feedback and optimization module includes an effect evaluation unit and an optimization algorithm unit. By evaluating the control effect, the control measures can be further optimized.

[0053] The user interaction module includes a visual interface and remote access functions, which are used to provide users with real-time monitoring data, analysis reports and control status, and support users to remotely monitor and operate the system.

[0054] The environmental data collection module specifically includes:

[0055] Temperature sensor: used to monitor the ambient temperature of key areas of the refinery in real time;

[0056] Humidity sensor: used to monitor ambient humidity;

[0057] Wind speed sensor: used to monitor wind speed inside and outside the refinery;

[0058] VOCs concentration sensor: used to detect the concentration of VOCs in the air, using a photoionization detector or infrared gas analyzer.

[0059] The data processing module specifically includes:

[0060] Data cleaning unit: used to clean the collected environmental data, remove noise and invalid data, and ensure the accuracy of the data. Data cleaning adopts a rule-based cleaning algorithm and makes corrections in combination with context information;

[0061] Outlier detection unit: Use statistical analysis and machine learning models to detect outliers in the data. The model uses the isolation forest algorithm. The abnormality calculation formula of the isolation forest algorithm is:

[0062]

[0063] Where c(n) is the average path length of the data set, and x is the data point to be detected;

[0064] Trend analysis unit: used to perform time series analysis on environmental data and predict the trend of VOCs concentration changes. The trend analysis uses the autoregressive integral moving average model. The prediction formula of the model is:

[0065] y t =c+φ1y t-1 +φ2y t-2 +…+θ1∈ t-1 +θ2∈ t-2 +∈ t ;

[0066] Among them, y t is the time series data, φ i is the autoregressive parameter, θ i is the moving average parameter, ∈ t is the error term.

[0067] The source location module specifically includes:

[0068] Source analysis unit: Analyze VOCs emission sources in combination with trend analysis results of the data processing module;

[0069] Positioning algorithm unit: Use wind field model and meteorological data to determine the emission source of VOCs. The positioning algorithm adopts the upwind field tracking algorithm. The basic formula of the algorithm is:

[0070]

[0071] Among them, x(t) is the source position, x0 is the initial position, and v(x(t′), t′) is the wind speed vector.

[0072] The intelligent control module specifically includes:

[0073] Control algorithm unit: Based on the source information provided by the source location module, the control strategy is generated using the algorithm based on model predictive control. The optimization goal of the model predictive control algorithm is:

[0074]

[0075] Among them, y(t+k|t) is the predicted output, y ref (t+k) is the reference output, Δu(t+k|t) is the control input increment, Q and R are weight matrices;

[0076] Execution unit: used to implement control strategies and automatically adjust the operating parameters of related equipment in the refinery, including adjusting valve opening, fan speed and heater power.

[0077] The feedback and optimization module specifically includes:

[0078] Effect evaluation unit: monitor the effect of the implementation of the control strategy in real time, and use the evaluation method based on fuzzy logic to evaluate the control effect. The basic formula of fuzzy logic is:

[0079]

[0080] Among them, μ(x) is the membership function, x is the input variable, and a and b are fuzzy parameters;

[0081] Optimization algorithm unit: According to the effect evaluation results, the control strategy is optimized using a genetic algorithm. The fitness function of the genetic algorithm is:

[0082]

[0083] Among them, f(x) is the fitness, w i is the weight, x i Score for the review.

[0084] The user interaction module specifically includes:

[0085] Visualization interface: used to display real-time monitoring data, analysis reports and control status. The interface is built with data visualization tools such as Grafana or Tableau and supports multiple chart types, including line charts, bar charts and pie charts.

[0086] Remote access function: Through the Internet or local area network, users are supported to remotely monitor the operating status of the system and perform operations. Remote access uses the HTTPS encryption protocol to ensure the security of data transmission.

[0087] The intelligent control module further comprises:

[0088] Early warning system: When the VOCs concentration reaches the preset threshold, the early warning signal is automatically triggered. The early warning information is notified to the user in real time through the visual interface and remote access function of the user interaction module. The setting of the early warning threshold is based on environmental regulations and corporate standards.

[0089] The present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention. In order to make the public have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details. In addition, in order to avoid unnecessary confusion about the essence of the present invention, well-known methods, processes, procedures, components and circuits are not described in detail.

[0090] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. The refinery VOCs real-time monitoring and control system is characterized by: It includes environmental data acquisition module, data processing module, source positioning module, intelligent control module, feedback and optimization module and user interaction module, among which; The environmental data acquisition module is used to collect environmental data in real time, including temperature, humidity, wind speed and VOCs concentration; The data processing module is used to pre-process and deeply analyze the collected environmental data, including a data cleaning unit, an outlier detection unit and a trend analysis unit; The source positioning module determines the emission source of VOCs based on the analysis results of the data processing module, using the wind field model and meteorological data. The source positioning module includes a source analysis unit and a positioning algorithm unit; The intelligent control module is used to automatically adjust the operating parameters of relevant equipment in the refinery according to the source information provided by the source positioning module and the trend prediction results provided by the data processing module to reduce VOCs emissions. The intelligent control module includes a control algorithm unit and an execution unit, which automatically generates a control strategy and implements it through the execution unit; The feedback and optimization module is used to monitor the effect of the control strategy in real time and dynamically adjust the control strategy according to the effect feedback. The feedback and optimization module includes an effect evaluation unit and an optimization algorithm unit. By evaluating the control effect, the control measures are further optimized. The user interaction module includes a visual interface and a remote access function, which is used to provide users with real-time monitoring data, analysis reports and control status, and support users to remotely monitor and operate the system.

2. The refinery VOCs real-time monitoring and control system according to claim 1, characterized in that: The environmental data acquisition module specifically includes: Temperature sensor: used to monitor the refinery ambient temperature in real time; Humidity sensor: used to monitor ambient humidity; Wind speed sensor: used to monitor wind speed inside and outside the refinery; VOCs concentration sensor: used to detect the concentration of VOCs in the air.

3. The refinery VOCs real-time monitoring and control system according to claim 2, characterized in that: The data processing module specifically includes: Data cleaning unit: used to clean the collected environmental data, remove noise and invalid data, and ensure the accuracy of the data. Data cleaning adopts a rule-based cleaning algorithm and makes corrections in combination with context information; Outlier detection unit: Detect outliers in data using statistical analysis and machine learning models; Trend analysis unit: used to perform time series analysis on environmental data and predict the trend of VOCs concentration changes.

4. The refinery VOCs real-time monitoring and control system according to claim 3, characterized in that: The source positioning module specifically includes: Source analysis unit: Analyze VOCs emission sources in combination with trend analysis results of the data processing module; Positioning algorithm unit: Use wind field model and meteorological data to determine the emission source of VOCs. The positioning algorithm adopts the upwind field tracking algorithm. The basic formula of the algorithm is: Among them, x(t) is the source position, x0 is the initial position, and v(x(t′), t′) is the wind speed vector.

5. The refinery VOCs real-time monitoring and control system according to claim 4, characterized in that: The intelligent control module specifically includes: Control algorithm unit: Based on the source information provided by the source location module, the control strategy is generated using the algorithm based on model predictive control. The optimization goal of the model predictive control algorithm is: Among them, y(t+k|t) is the predicted output, y ref (t+k) is the reference output, Δu(t+k|t) is the control input increment, Q and R are weight matrices; Execution unit: used to implement control strategies and automatically adjust the operating parameters of related equipment in the refinery, including adjusting valve opening, fan speed and heater power.

6. The refinery VOCs real-time monitoring and control system according to claim 5, characterized in that: The feedback and optimization module specifically includes: Effect evaluation unit: monitors the implementation effect of the control strategy in real time and uses the evaluation method based on fuzzy logic to evaluate the control effect; Optimization algorithm unit: Based on the effect evaluation results, the genetic algorithm is used to optimize the control strategy.

7. The refinery VOCs real-time monitoring and control system according to claim 6, characterized in that: The user interaction module specifically includes: Visual interface: used to display real-time monitoring data, analysis reports and control status, supporting multiple chart types, including line charts, bar charts and pie charts; Remote access function: Through the Internet or local area network, users are supported to remotely monitor the operating status of the system and perform operations. Remote access uses the HTTPS encryption protocol to ensure the security of data transmission.

8. The refinery VOCs real-time monitoring and control system according to claim 7, characterized in that: The intelligent control module further comprises: Early warning system: When the VOCs concentration reaches the preset threshold, the early warning signal is automatically triggered. The early warning information is notified to the user in real time through the visual interface and remote access function of the user interaction module. The setting of the early warning threshold is based on environmental regulations and corporate standards.

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