Dust explosion-proof monitoring control method and system

Abstract

The invention provides a dust explosion-proof monitoring control method and system, and relates to the technical field of industrial equipment monitoring, and the method comprises the steps: collecting environment information through a dust collection device disposed in a production region, building a safety threshold evaluation standard based on an evaluation report, and building an optimized feedback circulation mechanism in the dust collection device, and early warning of potential explosion risks is completed. According to the method, the potential explosion risk can be early warned, the safety state of the production environment can be automatically adjusted to optimize the management process and improve the production efficiency, and compared with the prior art, the prior art focuses on traditional protection measures or post-event processing and is lack of prospective data analysis capability and comprehensive management optimization function, so that the prior art has the potential safety hazard. The safety coefficient of equipment operation is remarkably improved, and the risk of dust explosion is effectively reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial equipment monitoring, and more specifically, to a dust explosion-proof monitoring and control method and system. Background Art

[0002] The current social development is in a period of rapid change and high innovation. The progress of technology has become the core driving force for social development. With the rapid development of information technology, artificial intelligence, big data, and Internet of Things technology, all industries are undergoing profound transformation and upgrading, and intelligent production and automated management have gradually become the mainstream trend. In the industrial field, the requirements for safe production are becoming increasingly strict. Especially in industries such as food and feed production and processing, the potential safety hazard of dust explosion has attracted wide attention. At the same time, the society's awareness of environmental protection and sustainable development is constantly increasing, prompting enterprises to not only pursue economic benefits but also take into account environmental impacts and social responsibilities. In addition, the acceleration of globalization has accelerated the circulation of resources and technologies, promoted international cooperation and exchanges, and provided more possibilities for solving global problems such as climate change and energy crises.

[0003] The current industrial control system has obvious deficiencies in monitoring the concentration of combustible dust in the production environment and cannot provide accurate and timely data support to prevent potential dust explosion risks. To address this technical problem, the present invention proposes a dust explosion-proof monitoring and control method integrating advanced sensing technology and automated control strategies. By collecting various dust concentration information generated during the production process in real time and combining data analysis to predict possible explosion risks, the safety monitoring and automatic adjustment of the production environment can be achieved.

[0004] In order to significantly improve the safety factor of equipment operation, reduce the risk of dust explosion, optimize the management process of industrial production, and improve the overall production efficiency, therefore, a dust explosion-proof monitoring and control solution is needed. Summary of the Invention

[0005] To solve the above technical problems, the present invention is proposed. The present invention provides a dust explosion-proof monitoring and control method and system.

[0006] According to one aspect of the present invention, there is provided a dust explosion-proof monitoring and control method, which includes:

[0007] Collect environmental information through a dust collection device deployed in the production area, and preprocess the environmental information in the central processor of the dust collection device to generate an assessment report reflecting the current environmental information security status;

[0008] Based on the evaluation report, establish a safety threshold evaluation standard. In the safety guarantee system of the dust collection device in the case of environmental information changes, link the environmental data obtained from the preprocessing of environmental information with the safety threshold evaluation standard;

[0009] In the safety guarantee system, after completing the linkage, conduct pre-plan guidance on the safety guarantee system. According to the hierarchical safety guarantee system after pre-plan guidance, establish an optimized feedback loop mechanism in the dust collection device to complete early warning of potential explosion risks.

[0010] Furthermore, the collection of environmental information includes collecting the air composition in a certain production area through the dust collection device and transmitting the air composition to the central processor of the dust collection device;

[0011] The transmission of the air composition to the central processor of the dust collection device includes establishing a self-organizing and adaptive data transmission network function in the production area and locally processing the air composition using the self-organizing function;

[0012] After locally processing the air composition using the adaptive function, transmit it to the dust collection device.

[0013] Furthermore, the preprocessing of environmental information includes, in the stage of local processing of air composition, based on an adaptive data screening mechanism for environmental feature recognition, obtaining the environmental parameters of the production area and screening data segments for analysis;

[0014] Adjust the proportion of environmental parameters through the adaptive function, and after locally processing the air composition using the adaptive function, the adjusted proportion of environmental parameters can be analyzed under the same standard;

[0015] When the air composition is locally processed by the adaptive function, the local processing includes compression or expansion. Through the locally processed air composition, scale or expand the environmental parameters of the production area according to the proportion of local processing.

[0016] Furthermore, the establishment of the safety threshold evaluation standard includes identifying the safety range of each parameter of the environmental parameters under different scaling or expansion according to the results of scaling or expansion of the environmental parameters of the production area obtained according to the proportion of local processing;

[0017] Under the scaling or expansion ratio, the safety guarantee system evaluates the environmental parameters from different dimensions, including physical and chemical properties, indirect influencing factors, and comprehensive effects;

[0018] Based on the environmental parameters evaluated by the safety guarantee system from different dimensions, complete the construction of a hierarchical safety guarantee network, and the hierarchical safety guarantee network includes a hardware network layer and a software network layer;

[0019] The hardware network layer includes means for checking indirect influencing factors;

[0020] The software network layer includes means for monitoring and managing physical and chemical properties and comprehensive effects.

[0021] Further, the linkage with the safety threshold evaluation criteria includes introducing a linkage mechanism under the dust collection device, and when the proportion of adjusted environmental parameters can be analyzed under the same standard;

[0022] The safety guarantee system integrates environmental data from physical and chemical properties, comprehensive effects, and indirect influencing factors. The integrated environmental data includes operation logs through the hierarchical safety guarantee network or the software network layer, and a dataset reflecting the current production environment status.

[0023] Further, the dataset reflecting the current production environment status includes, based on the integrated data, the safety guarantee system starts to perform correlation analysis between environmental parameters;

[0024] Analyze the relationship between physical and chemical properties and indirect influencing factors, or analyze the influence of comprehensive effects;

[0025] When the physical and chemical properties increase during a certain period, while the efficiency of indirect influencing factors decreases, the safety guarantee system identifies a potential dust explosion hazard.

[0026] Further, the pre - plan guidance for the safety guarantee system includes, based on the correlation analysis results, the safety guarantee system dynamically adjusts the safety thresholds of each environmental parameter;

[0027] When it is found that the indirect influencing factors decrease, the safety guarantee system reduces the dust concentration of physical and chemical properties and takes measures to increase the indirect influencing factors;

[0028] The safety guarantee system updates the safety thresholds according to different production areas and external environmental conditions;

[0029] The safety guarantee system improves the requirements for controlling comprehensive effects and adjusts the scope of physical and chemical properties or indirect influencing factors.

[0030] Further, the hierarchical safety guarantee system includes protective measures from hardware facility maintenance to software management and then to personnel training;

[0031] At the hardware network layer, the hierarchical safety guarantee system checks and maintains ventilation equipment to ensure its operation;

[0032] At the software network layer, the hierarchical safety guarantee system generates a daily safety report for management reference;

[0033] The protective measures for personnel training include training content for personnel based on the safety report.

[0034] Furthermore, the establishment of the optimized feedback loop mechanism includes enabling operators and technicians at different levels to obtain safety information and improvement suggestions through the hierarchical safety guarantee system. The management can understand the safety status of the overall production environment through daily safety reports, while front-line operators can receive optimization suggestions to formulate operation guides. When the hierarchical safety guarantee system detects a decrease in the indirect influencing factors of dust in a certain production area, the production plan is adjusted to predict dust explosion control.

[0035] According to another aspect of the present invention, there is provided a dust explosion-proof monitoring and control system, which includes:

[0036] S110: A dust collection device, which collects environmental information through dust collection devices deployed in the production area;

[0037] S210: A central processing unit module, which preprocesses the environmental information in the central processing unit of the dust collection device to generate an evaluation report reflecting the current safety status of the environmental information;

[0038] S310: A safety guarantee system module, which, in the case of changes in environmental information, in the safety guarantee system of the dust collection device, and after completing the linkage, provides pre-plan guidance for the safety guarantee system;

[0039] S410: An optimized feedback loop mechanism module, which, according to the hierarchical safety guarantee system after pre-plan guidance, establishes an optimized feedback loop mechanism in the dust collection device to complete early warning of potential explosion risks.

[0040] Compared with the prior art, by integrating advanced sensing technologies and automated control strategies, the present invention realizes precise and real-time monitoring and management of the concentration of combustible dust in the production environment. Against the backdrop of the rapid transformation and high innovation in current social development, especially in industries such as food and feed that are prone to dust explosion hazards, this invention not only meets the increasingly stringent requirements for safe production but also effectively improves the enterprise's environmental management level and social responsibility. The present invention utilizes a self-organizing and self-adaptive data transmission network, combined with a multi-level security guarantee system, including both the hardware network level and the software network level, to achieve a comprehensive assessment of physical and chemical properties, indirect influencing factors, and comprehensive effects, dynamically adjust the safety threshold, and provide early warnings and emergency plan guidance through optimizing the feedback loop mechanism. The present invention significantly improves the recognition accuracy and response speed of potential dust explosion risks, ensuring the safety and reliability of the production environment. In addition, by generating daily safety reports and personnel training content, it further enhances employees' safety awareness and emergency handling capabilities, promotes the development of intelligent production and automated management, and provides strong technical support for enterprises to achieve a win-win situation between economic benefits and environmental protection. In the process of globalization, such an efficient and precise safety monitoring solution also provides more possibilities for solving global problems such as climate change and energy crisis. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings. In the drawings:

[0042] Figure 1 It is a system block diagram of a dust explosion-proof monitoring and control method according to an embodiment of the present invention.

[0043] Figure 2 It is a flowchart of a dust explosion-proof monitoring and control method according to an embodiment of the present invention.

[0044] Figure 3 It is a linkage schematic diagram of a dust explosion-proof monitoring and control method according to an embodiment of the present invention.

[0045] Figure 4 It is a flowchart for establishing and optimizing the feedback loop mechanism of a dust explosion-proof monitoring and control method according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0046] Next, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments of the present invention. It should be understood that the present invention is not limited by the exemplary embodiments described herein.

[0047] As mentioned in the above background art, the current social development is in an era of rapid change and high innovation. The progress of technology has become the core driving force for social development. With the rapid development of information technology, artificial intelligence, big data, and Internet of Things technology, all industries are undergoing profound transformation and upgrading. Intelligent production and automated management have gradually become the mainstream trend. In the industrial field, the requirements for safe production are becoming increasingly strict. Especially in the production and processing industries such as food and feed, the potential safety hazard of dust explosion has attracted wide attention. At the same time, the society's awareness of environmental protection and sustainable development is constantly increasing, prompting enterprises to not only pursue economic benefits but also take into account environmental impacts and social responsibilities. In addition, the acceleration of globalization has accelerated the circulation of resources and technologies, promoted international cooperation and exchanges, and provided more possibilities for solving global problems such as climate change and energy crises.

[0048] The current industrial control systems have obvious deficiencies in monitoring the concentration of combustible dust in the production environment and cannot provide accurate and timely data support to prevent potential dust explosion risks. To address this technical problem, the present invention proposes a dust explosion-proof monitoring and control method that integrates advanced sensing technology and automated control strategies. By collecting various types of dust concentration information generated during the production process in real time and combining data analysis to predict possible explosion risks, it realizes the safety monitoring and automatic adjustment of the production environment.

[0049] Embodiment 1

[0050] Referring to Figures 1 to 4 , this is the first embodiment of the present invention. This embodiment provides a dust explosion-proof monitoring and control method, including:

[0051] S1: Collect environmental information through dust collection devices deployed in the production area, and preprocess the environmental information in the central processor of the dust collection device to generate an assessment report reflecting the current environmental information security status.

[0052] Among them, collecting environmental information includes collecting the air composition in a certain production area through the dust collection device and transmitting the air composition to the central processor of the dust collection device.

[0053] Transmitting the air composition to the central processor of the dust collection device includes establishing a self-organizing and adaptive data transmission network function in the production area and using the self-organizing function to locally process the air composition.

[0054] In the dust collection device, the collected air components are first locally processed to ensure the quality of the data and the effectiveness of the preliminary analysis. This process includes removing impurities and interfering substances that may exist in the air, such as removing larger particulate matter through physical filtration methods and using chemical adsorbents to remove specific types of gaseous pollutants. Then, local environmental adjustment techniques are used to adjust the humidity and temperature in the sample to standard conditions, thus ensuring the consistency and accuracy of subsequent analysis. This local processing not only improves the purity of the air component samples but also lays a foundation for more accurate data analysis.

[0055] After the local processing of the air components using the adaptive function, they are transmitted to the dust collection device.

[0056] The data transmission network consists of multiple distributed nodes. These nodes can automatically adjust their connection status and communication paths according to changes in the surrounding environment and network load conditions to ensure the stability and reliability of data transmission. This self-organizing feature enables the network to maintain optimal performance in complex and changing industrial environments without frequent manual intervention.

[0057] S1.1: The preprocessing of environmental information includes, during the local processing stage of air components, an adaptive data screening mechanism based on environmental feature recognition to obtain the environmental parameters of the production area and screen data segments for analysis.

[0058] By adjusting the ratio of environmental parameters through the adaptive function, after the local processing of air components using the adaptive function, the adjusted ratio of environmental parameters can be analyzed under the same standard.

[0059] When the adaptive function performs local processing on air components, the local processing includes compression or expansion. Based on the locally processed air components, the environmental parameters of the production area are scaled or expanded according to the ratio of the local processing.

[0060] Further, specifically, after the air composition undergoes the local processing stage, the proportion of environmental parameters is adjusted through an adaptive function to ensure that all data can be compared and analyzed under the same standard. For example, when the initially collected air composition data shows a temperature range of 20°C to 30°C and a humidity range of 40% to 60%, and the ideal analysis standard is set with a temperature of 25°C and a humidity of 50% as the reference point. When the actual environmental parameters deviate from these reference values, the system will automatically adjust the proportion so that the data collected under different conditions can be evaluated under a unified standard. If a data segment shows a temperature of 28°C and a humidity of 55%, then this data will be compressed or expanded to reflect the rate of change relative to the reference conditions. For example, the temperature can be scaled by a ratio of (28 - 25) / 5 = 0.6, and the humidity can be adjusted by a ratio of (55 - 50) / 10 = 0.5, thus ensuring the consistency and comparability of the data.

[0061] Furthermore, after the above-mentioned adaptive adjustment is completed, the local processing also includes operations of compressing or expanding the air composition data to optimize its representation form. This means that for data outside the normal range, appropriate mathematical transformations (such as ratio scaling or normalization) are performed to facilitate subsequent analysis. For example, if the particulate matter concentration in a certain segment of air composition data is much higher than the average level, a specific scaling factor will be used to compress this data so that it can be presented on the same scale as other data, facilitating the identification of trends and anomalies. This fine-tuning not only improves the accuracy of data analysis but also ensures the response speed and reliability of the entire monitoring system, effectively preventing potential safety hazards. In this way, precise monitoring and management of the dust explosion risk in the production environment can be achieved.

[0062] In the dust explosion prevention monitoring and control system, choosing a temperature of 25°C and a humidity of 50% as the reference point for adaptive adjustment and ratio scaling is not the only option, but is based on the principles of wide applicability and flexibility. These values are selected because they are close to the ideal operating conditions of many industrial production environments, which helps to maintain the best operating state of the equipment and control the dust concentration within a safe range. However, these reference values can be dynamically adjusted according to specific production requirements and changes in the external environment. For example, under different seasons or specific production process conditions, more suitable reference temperatures and humidities can be selected. In addition, for data outside the normal range, compression or expansion is performed through mathematical transformations such as ratio scaling or normalization to ensure that all data can be compared and analyzed under a unified standard. This method not only improves the accuracy of data analysis but also guarantees the response speed and reliability of the system, effectively preventing potential safety hazards.

[0063] S2: Establish a safety threshold evaluation standard based on the evaluation report. In the safety guarantee system of the dust collection device in the case of environmental information changes, link the environmental data obtained from the preprocessing of environmental information with the safety threshold evaluation standard.

[0064] Among them, establishing the safety threshold evaluation standard includes identifying the safety ranges of each parameter of the environmental parameters under different scaling or expansion according to the results of scaling or expansion of the environmental parameters obtained in the production area according to the local processing ratio.

[0065] Under the scaling or expansion ratio, the safety guarantee system evaluates the environmental parameters from different dimensions, including physical and chemical properties (such as the particle size distribution of dust), indirect influencing factors (such as the efficiency change of the ventilation system), and comprehensive effects (such as the impact of the combined action of temperature and humidity on the dust explosion risk).

[0066] Based on the environmental parameters evaluated by the safety guarantee system from different dimensions, complete the construction of a hierarchical safety guarantee network, which includes a hardware network layer and a software network layer.

[0067] The hardware network layer includes those for checking indirect influencing factors.

[0068] The software network layer includes those for monitoring and managing physical and chemical properties and comprehensive effects.

[0069] S2.1: Linking with the safety threshold evaluation standard includes introducing a linkage mechanism under the dust collection device when the ratio of adjusting environmental parameters can be analyzed under the same standard.

[0070] The safety guarantee system integrates environmental data from physical and chemical properties, comprehensive effects, and indirect influencing factors. Integrating environmental data includes a dataset reflecting the current production environment state through the operation logs under the hierarchical safety guarantee network or the software network layer.

[0071] S2.2: The dataset reflecting the current production environment state includes that on the basis of the integrated data, the safety guarantee system starts to conduct correlation analysis between environmental parameters.

[0072] Analyze the relationship between physical and chemical properties and indirect influencing factors, or analyze the impact of comprehensive effects.

[0073] When the physical and chemical properties rise within a certain period of time while the efficiency of indirect influencing factors decreases, the safety guarantee system identifies potential dust explosion hazards.

[0074] Furthermore, introduce a linkage mechanism and adjust the environmental parameter ratio. After the air composition has been locally processed such as compressed or expanded, first standardize all environmental parameters. For example, unify parameters such as temperature and humidity to set standard conditions, such as 25°C and 50% humidity, and at the same time adjust the dust concentration to a standard unit such as mg / m³. The formula is as follows:

[0075]

[0076] Among them, represents the standardized temperature, represents the actual temperature, represents the set minimum temperature range, represents the set maximum temperature range.

[0077] Ratio scaling and expansion. For data outside the normal range, perform appropriate mathematical transformations such as ratio scaling or normalization for subsequent analysis. For example, if the particulate matter concentration in a certain section of air composition data is much higher than the average level, use a specific scaling factor to compress this data:

[0078]

[0079] Among them, represents the normalized dust concentration, represents the actual dust concentration, represents the average dust concentration.

[0080] Based on the scaled or expanded environmental parameters, the safety guarantee system is evaluated from multiple dimensions, including physical and chemical properties such as the particle size distribution of dust particles, indirect influencing factors such as the efficiency change of the ventilation system, and comprehensive effects such as the combined effect of temperature and humidity on the risk of dust explosion. According to these evaluation results, specific safety thresholds for the current production conditions are generated. For example, in a high-humidity environment, the system will automatically lower the upper limit of the safety concentration of some hygroscopic dusts; while under high-temperature conditions, the requirement for ventilation efficiency may be increased to reduce the dust concentration.

[0081] Integrate environmental data and perform correlation analysis. Based on the integrated data, the safety guarantee system begins to perform correlation analysis between environmental parameters. For example, analyze the relationship between the particle size distribution of dust particles and the efficiency of the ventilation system, or study the combined effect of temperature and humidity on the risk of dust explosion.

[0082]

[0083] Among them, represents the dust explosion risk index, represents the comprehensive evaluation function, Indicates physicochemical property indicators, Indicates the ventilation system efficiency.

[0084] Early warning mechanism: When the physicochemical properties increase within a certain period of time and the indirect influencing factors, such as the decrease in the ventilation system efficiency, the safety guarantee system identifies potential dust explosion prevention hazards and immediately issues an alarm. For example, if the dust concentration in a certain area continues to rise and the ventilation system cannot respond in time, the system will recommend starting a local exhaust device or adjusting the working mode of production equipment.

[0085] S3: Transmitting the air composition to the central processor of the dust collection device includes establishing a self-organizing and self-adaptive data transmission network function within the production area and locally processing the air composition using the self-organizing function.

[0086] Among them, guiding the pre-plan for the safety guarantee system includes dynamically adjusting the safety thresholds of various environmental parameters by the safety guarantee system based on the correlation analysis results.

[0087] When it is found that the indirect influencing factor decreases, the safety guarantee system reduces the dust concentration of the physicochemical property and takes measures to increase the indirect influencing factor.

[0088] The safety guarantee system updates the safety thresholds according to different production areas and external environmental conditions.

[0089] During the summer, the safety guarantee system improves the requirements for comprehensive effect control and adjusts the range of physicochemical properties or indirect influencing factors.

[0090] S3.1: The hierarchical safety guarantee system includes protective measures from hardware facility maintenance to software management and then to personnel training;

[0091] At the hardware network level, the hierarchical safety guarantee system checks and maintains the ventilation equipment to ensure its operation;

[0092] At the software network level, the hierarchical safety guarantee system generates a daily safety report for management reference;

[0093] The protective measures for personnel training include training content for personnel based on the safety report.

[0094] At the hardware network level, check the indirect influencing factor. The hardware network level is mainly used to check the indirect influencing factor, such as the efficiency change of the ventilation system. For example, by installing sensors on the ventilation duct to monitor parameters such as wind speed and air volume in real time and transmitting them to the central processing unit for analysis.

[0095]

[0096] Among them, Indicates the ventilation system efficiency, represents the actual air volume, represents the required air volume.

[0097] At the software network level, monitor and manage physical and chemical properties and comprehensive effects. The software network level is used to monitor and manage physical and chemical properties, such as the particle size distribution of dust, and comprehensive effects, such as the combined action of temperature and humidity. For example, by integrating data such as operation logs and equipment maintenance records, a dataset reflecting the current production environment state is formed.

[0098]

[0099] Among them, represents the physical and chemical property index, represents the particle size distribution of dust, represents the humidity, represents the temperature.

[0100] S3.2: Establish an optimization feedback loop mechanism, including enabling operators and technicians at different levels to obtain safety information and improvement suggestions by using a hierarchical security guarantee system. The management level understands the safety status of the overall production environment through daily safety reports, while front-line operators can receive optimization suggestions to formulate operation guides. When the hierarchical security guarantee system detects a decrease in the indirect influencing factors of dust in a certain production area, adjust the production plan and predict dust explosion control.

[0101] Referring to Figures 1 to 4 , this is the second embodiment of the present invention. This embodiment provides a method for monitoring and controlling dust explosion. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through simulation experiments.

[0102] Premise, in a large grain processing factory, due to a large amount of dust generated during the production process, there is a serious risk of dust explosion. Factory managers need to monitor and manage these dust concentrations in real time to ensure safe production. However, the existing industrial control systems have obvious deficiencies in monitoring the concentration of combustible dust, unable to provide accurate and timely data support, and it is difficult to effectively prevent potential dust explosion risks. In addition, with the increasing requirements of society for environmental protection and sustainable development, enterprises also need to take into account environmental impacts and social responsibilities.

[0103] First, in the grain processing factory, multiple dust collection devices are deployed. These devices can collect multi-dimensional environmental information in real-time, including air components such as the size distribution of dust particles, temperature, and humidity. The data collected is first transmitted to the central processor through a self-organizing and self-adaptive data transmission network for preprocessing. For example, when the initially collected air component data shows a temperature range of 20°C to 30°C and a humidity range of 40% to 60%, these data are normalized to set standard conditions, such as 25°C and 50% humidity, and their representation is optimized through compression or expansion operations to ensure that all data can be compared and analyzed under the same standard.

[0104] Based on the preprocessed environmental data, an assessment report reflecting the current environmental information security status is generated, and a dynamic safety threshold evaluation standard is established. This standard identifies the safety ranges of various parameters under different conditions according to the results of scaling or expanding the environmental parameters of the production area obtained, such as temperature, humidity, and dust concentration, according to the proportion of local processing. For example, in a high-humidity environment, the system will automatically lower the upper limit of the safety concentration of some hygroscopic dust; while in high-temperature conditions, the requirement for ventilation efficiency may be increased to reduce the dust concentration.

[0105] Suppose that within a certain period, the dust concentration rises significantly while the efficiency of the ventilation system decreases. The safety guarantee system will immediately identify this potential dust explosion hazard and issue a warning. At this time, the safety guarantee system will not only recommend starting the local exhaust device or adjusting the working mode of the production equipment, but also dynamically adjust various safety thresholds to ensure that it is always in the optimal state.

[0106] Secondly, based on the above correlation analysis results, the safety guarantee system dynamically adjusts the safety thresholds of various environmental parameters. For example, when it is found that the efficiency of the ventilation system decreases, the safety guarantee system will recommend measures to increase the ventilation volume and update the safety thresholds in real-time according to different production areas and external environmental conditions. Especially during the high-temperature period in summer, the system will increase the requirements for comprehensive effect control and adjust the range of physical and chemical properties or indirect influencing factors.

[0107] Finally, the above technical steps are applicable to a large grain processing factory. A large amount of dust is generated during the production process, especially in the grain crushing and packaging links. Since these dusts are highly flammable, the factory faces a serious risk of dust explosion. The traditional monitoring system cannot provide accurate and timely data support to prevent potential dust explosion risks, resulting in large loopholes in the factory's safety management. In addition, with the increasing awareness of environmental protection and sustainable development in society, the factory not only needs to ensure safe production but also take into account environmental impacts and social responsibilities.

[0108] The comparison between the present invention and the prior art is shown in Table 1 below:

[0109] Table 1 Comparison Table between the Present Invention and the Prior Art

[0110] Comparison dimension Prior art Technical solution of the present invention Advantages of the present invention Data collection and analysis Data collection is inaccurate and lacks real-time nature Collect data in real time through a self-organizing and adaptive network, and perform standardization processing and multi-dimensional analysis Improve data accuracy and analysis efficiency, and ensure real-time monitoring and dynamic adjustment Safety threshold assessment Fixed threshold, unable to adapt to complex environmental changes Dynamically generate safety thresholds and conduct comprehensive assessments based on physical and chemical properties, indirect factors and comprehensive effects Flexibly adapt to different production conditions, and significantly improve the accuracy and safety of early warnings Early warning mechanism Single early warning and lagging response Evaluate environmental parameters multi-dimensionally, issue early warnings in a timely manner and provide optimization suggestions Achieve early warning, quickly identify potential hazards and take measures Feedback and improvement Lack of feedback mechanism, and it is difficult to optimize the system Introduce an optimization feedback loop mechanism, continuously learn historical data, and continuously optimize judgment logic and safety strategies Continuously improve the system performance and enhance the safety and reliability of long-term operation Environmental protection and responsibility Only focus on production safety and ignore environmental protection and social responsibilities Comprehensively consider work safety, environmental protection and social responsibilities to meet the needs of sustainable development Meet the requirements of society for green production and sustainable development, and enhance the social responsibility of enterprises

[0111] Table 1 addresses the deficiencies of the prior art in dust explosion prevention and monitoring control through innovative designs such as real-time data acquisition, dynamic safety threshold assessment, multi-dimensional warning mechanisms, and optimized feedback loops. Compared with traditional methods, the present invention not only improves the intelligence level and response speed of the system but also takes into account environmental protection and social responsibility, providing more efficient and reliable safety guarantees for modern industrial production.

[0112] In summary, by integrating advanced sensing technologies and automated control strategies, the present invention achieves precise and real-time monitoring and management of the concentration of combustible dust in the production environment. Against the backdrop of rapid social development and high innovation, especially in industries prone to dust explosion hazards such as food and feed, the invention not only meets the increasingly stringent requirements for work safety but also effectively improves the enterprise's environmental management level and social responsibility. The present invention utilizes a self-organizing and adaptive data transmission network, combined with a multi-level security guarantee system, including the hardware network level and the software network level, to achieve a comprehensive assessment of physical and chemical properties, indirect influencing factors, and comprehensive effects, dynamically adjust the safety threshold, and provide early warnings and emergency plan guidance through an optimized feedback loop mechanism. The present invention significantly improves the recognition accuracy and response speed to potential dust explosion risks, ensuring the safety and reliability of the production environment. In addition, by generating daily safety reports and personnel training content, it further enhances employees' safety awareness and emergency handling capabilities, promotes the development of intelligent production and automated management, and provides strong technical support for enterprises to achieve a win-win situation between economic benefits and environmental protection. In the process of globalization, such an efficient and precise safety monitoring solution also provides more possibilities for solving global problems such as climate change and energy crises.

Claims

1. A dust explosion-proof monitoring and control method, characterized in that, Including: Collect environmental information through a dust collection device deployed in the production area, preprocess the environmental information in the central processor of the dust collection device, and generate an evaluation report reflecting the current environmental information security status; Based on the evaluation report, establish a safety threshold evaluation standard. In the case of changes in environmental information, in the safety guarantee system of the dust collection device, link the environmental data obtained from the preprocessing of environmental information with the safety threshold evaluation standard; In the safety guarantee system, after completing the linkage, conduct pre-plan guidance on the safety guarantee system. According to the hierarchical safety guarantee system after pre-plan guidance, establish an optimized feedback loop mechanism in the dust collection device to complete early warning of potential explosion risks.

2. The dust explosion-proof monitoring and control method according to claim 1, wherein The collection of environmental information includes collecting the air composition in a certain production area through the dust collection device and transmitting the air composition to the central processor of the dust collection device; The transmission of the air composition to the central processor of the dust collection device includes establishing a self-organizing and adaptive data transmission network function in the production area and locally processing the air composition using the self-organizing function; After locally processing the air composition using the adaptive function, transmit it to the dust collection device.

3. The dust explosion-proof monitoring and control method according to claim 1, wherein The preprocessing of environmental information includes, during the local processing stage of the air composition, based on an adaptive data screening mechanism for environmental feature recognition, obtaining the environmental parameters of the production area and screening data segments for analysis; Adjust the ratio of environmental parameters through the adaptive function, and after locally processing the air composition using the adaptive function, the adjusted ratio of environmental parameters can be analyzed under the same standard; When the air composition is locally processed by the adaptive function, the local processing includes compression or expansion. Through the locally processed air composition, scale or expand the obtained environmental parameters of the production area according to the ratio of local processing.

4. The dust explosion-proof monitoring and control method according to claim 1, wherein, The establishment of the safety threshold evaluation standard includes identifying the safety range of each parameter of the environmental parameters under different scaling or expansion based on the results of scaling or expansion of the obtained environmental parameters of the production area according to the ratio of local processing; Under the scaling or expansion ratio, the safety guarantee system evaluates the environmental parameters from different dimensions, including physical and chemical properties, indirect influencing factors, and comprehensive effects; Based on the environmental parameters evaluated from different dimensions by the safety guarantee system, complete the construction of a hierarchical safety guarantee network, and the hierarchical safety guarantee network includes a hardware network layer and a software network layer; The hardware network layer includes those for checking indirect influencing factors; The software network layer includes those for monitoring and managing physical and chemical properties and comprehensive effects.

5. The dust explosion-proof monitoring and control method according to claim 1, wherein The linkage with the safety threshold evaluation standard includes introducing a linkage mechanism under the dust collection device when the adjusted ratio of environmental parameters can be analyzed under the same standard; The safety guarantee system integrates environmental data from physical and chemical properties, comprehensive effects, and indirect influencing factors. The integration of environmental data includes operation logs through the hierarchical safety guarantee network or the software network layer, and a dataset reflecting the current production environment status.

6. The dust explosion-proof monitoring and control method according to claim 5, wherein The dataset reflecting the current production environment status includes, based on the integrated data, the security assurance system starts to conduct correlation analysis among environmental parameters; Analyze the relationship between physical and chemical properties and indirect influencing factors, or analyze the impact of comprehensive effects; When the physical and chemical properties increase within a certain period while the efficiency of indirect influencing factors decreases, the security assurance system identifies potential dust explosion hazards.

7. The dust explosion-proof monitoring and control method according to claim 1, wherein The pre-plan guidance for the security assurance system includes, based on the correlation analysis results, the security assurance system dynamically adjusts the safety thresholds of various environmental parameters; When it is found that the indirect influencing factors decrease, the security assurance system reduces the dust concentration of physical and chemical properties and takes measures to increase the indirect influencing factors; The security assurance system updates the safety thresholds according to different production areas and external environmental conditions; The security assurance system raises the requirements for the control of comprehensive effects and adjusts the scope of physical and chemical properties or indirect influencing factors.

8. The dust explosion-proof monitoring and control method according to claim 1, wherein, The hierarchical security assurance system includes protective measures from hardware facility maintenance to software management and then to personnel training; At the hardware network level, the hierarchical security assurance system checks and maintains ventilation equipment to ensure its operation; At the software network level, the hierarchical security assurance system generates a daily security report for management reference; The protective measures for personnel training include training content for personnel based on the security report.

9. The dust explosion-proof monitoring and control method according to claim 1, characterized in that The establishment of the optimization feedback loop mechanism includes using the hierarchical security assurance system to enable operators and technicians at different levels to obtain security information and improvement suggestions. The management can understand the safety status of the overall production environment through the daily security report, and front-line operators can receive optimization suggestions to formulate operation guidelines. When the hierarchical security assurance system discovers a decrease in the indirect influencing factors of dust in a certain production area, it adjusts the production plan and predicts dust explosion control.

10. A dust explosion-proof monitoring and control system, characterized in that, Including: Dust collection device, which collects environmental information through dust collection devices deployed in production areas; Central processing unit module, which pre-processes environmental information in the central processing unit of the dust collection device and generates an assessment report reflecting the current environmental information security status; Security assurance system module, which, in the case of changes in environmental information, in the security assurance system of the dust collection device, and after completing the linkage, conducts pre-plan guidance for the security assurance system; Optimization feedback loop mechanism module, which, according to the hierarchical security assurance system after pre-plan guidance, establishes an optimization feedback loop mechanism in the dust collection device to complete early warning of potential explosion risks.

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