Intrinsic safety screen priority control system and method based on dynamic adjustment

Abstract

The invention discloses an intrinsic safety screen priority control system and method based on dynamic adjustment, and relates to the technical field of intrinsic safety screen control. The system comprises a historical data processing module, a system state analysis module, a priority decision module and a real-time control and feedback module. The historical data processing module collects and analyzes historical records and calculates an adaptation index; the system state analysis module classifies the system operation state according to the information and judges the priority adjustment requirement; the priority decision module is used for generating a new priority sequence by combining information association and feedback according to the category needing to be adjusted; and the real-time control and feedback module identifies real-time information categories, matches priority control, and optimizes a strategy according to a feedback evaluation result. According to the method, the limitation of traditional fixed priority setting is broken through, the problems that key information of the intrinsic safety screen is prone to being neglected and display resources are not distributed in a complex industrial environment are effectively solved through dynamic adjustment, and production safety and efficiency are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intrinsically safe screen control, and in particular to an intrinsically safe screen priority control system and method based on dynamic adjustment. Background Art

[0002] Intrinsically safe display screens (ISDs) are widely used in flammable and explosive hazardous environments such as coal mines and chemical plants. They display various production data and equipment status information, ensuring safe and efficient production operations. In practice, these screens simultaneously receive and process multiple different types of information, such as equipment fault alarms, real-time production parameter data, and operational instructions. However, existing ISD priority control systems often use a fixed priority setting method, presetting the order of priority for each type of information and not adjusting it during operation. This fixed priority setting approach presents numerous problems. For one thing, the originally set priorities may no longer be appropriate when the system is in different operating states. For example, under normal production conditions, equipment fault alarms have the highest priority, but under maintenance, maintenance-related prompts may be more important, and fixed priority settings cannot adapt to such changes. Furthermore, in complex industrial environments, numerous interference factors can cause the importance of some information to change dynamically, and fixed priority settings cannot respond in a timely manner. This can easily lead to critical information being overlooked or secondary information overusing display resources, hindering operators' access to and processing of important information, and thus affecting production safety and efficiency. Summary of the Invention

[0003] The object of the present invention is to provide a dynamic adjustment-based intrinsically safe screen priority control system and method to solve the problems raised in the above background technology.

[0004] In order to solve the above technical problems, the present invention provides the following technical solutions: A method for controlling the priority of an intrinsically safe screen based on dynamic adjustment comprises the following steps: Step S100. Obtain historical priority control records and corresponding historical information over a period of time, and match the historical priority control records with the historical information; based on the correspondence between the historical priority control records and the historical information, evaluate the adaptation index of each historical priority control record; Step S200. Classify the system operation status according to the adaptation index and historical information of each historical priority control record; for each category of system operation status, combined with the corresponding adaptation index, determine whether the preset fixed priority for the corresponding category needs to be adjusted; Step S300. According to the judgment results of each category, the category that needs to be adjusted in priority is obtained; and combined with the feedback results of the corresponding historical control records, a corresponding priority order is generated for each category; Step S400. Obtain real-time information, analyze the real-time information with historical information, and identify the category of the real-time information; match the priority order according to the real-time information category, and perform corresponding priority control, obtain real-time feedback information and evaluate the current priority control effect, and perform corresponding processing based on the evaluation results.

[0005] Furthermore, step S100 includes: S101. Obtain historical priority control records for the security screen over a past period of time, where each historical priority control record includes the priority execution status of various types of information during each information processing, such as the priority order and execution results of equipment fault alarm information, real-time production parameter data, and operation instruction information; based on the timestamp corresponding to the historical priority control record, obtain historical information at the corresponding time point, where the historical information includes but is not limited to the system operating status (normal production, equipment maintenance, etc.), the specific content of various types of information, the time of generation, etc.; each historical priority control record is matched one-to-one with the corresponding historical information according to the timestamp, thereby obtaining a data set D, where D = {(Ri,Hi)}, where Ri represents the i-th historical priority control record, and Hi represents the historical information corresponding to the i-th historical priority control record; S102. For each element in the data set D, calculate the corresponding adaptation index AI i , the corresponding calculation formula is: AI i =Σ k∈[1,N] [W k ·(1-ΔP ik / M k )] / Σ k∈[1,N] W k , among which AI i represents the adaptation index of the i-th historical priority control record, W k represents the weight of the kth type of historical information, and the choice of weight can be determined by expert experience, historical data analysis, or domain knowledge. For example, through a data-driven approach, the contribution of different information types to system performance can be evaluated by analyzing past system behavior, thereby determining the weight of each information type; ΔP ik It represents the priority execution deviation of the i-th historical priority control record on the k-th type of historical information. The corresponding calculation formula is: ΔP ik =|P ik_e -P ik_a |, where P ik_e represents the preset priority order of the kth category of historical information in the i-th historical priority control record, Pik_a It represents the actual priority order of the kth category of historical information of the i-th historical priority control record, and the actual priority order is determined by relevant personnel; Mk represents the maximum value of the priority execution deviation of the kth category of historical information.

[0006] Furthermore, step S200 includes: S201. For each element in the data set D, extract the historical data features that represent the system operation status, normalize the extracted historical data features, and form a historical feature vector X i , and X i =[x i1 ,x i2 ,...,x im ], where m represents the number of features, x i1 Indicates the first eigenvalue of the historical information corresponding to the i-th element, x i2 represents the second eigenvalue of the historical information corresponding to the i-th element, and so on, x im Represents the mth eigenvalue of the historical information corresponding to the i-th element; Based on the traditional clustering algorithm, the adaptation index AI i As a weighting factor, the distance from the sample point to the cluster center is calculated, and the corresponding calculation formula is: dw(X,C)=[Σ j∈[1,m] AI i ·(x j -c j ) 2 ]^(1 / 2), where X represents the sample point feature vector, C represents the cluster center feature vector, and x j represents the jth eigenvalue of the sample point eigenvector, c j represents the jth eigenvalue of the cluster center eigenvector; according to the preset number of clusters K, after multiple iterative calculations, the system operation status corresponding to the historical information is divided into K categories, which are represented as C1, C2, ..., CK in sequence; S202. For each category, calculate the corresponding category adaptation index average μ_AI b and category adaptation index standard deviation σ_AI b , where b = 1, 2, ..., K; according to the preset adaptation index lower limit threshold Q1 and adaptation index fluctuation threshold Q2, if there is μ_AI b ≥Q1 and σ_AI b ≤Q2, it is determined that the corresponding category does not need to adjust the preset fixed priority; if there is μ_AI b <Q1 or σ_AI b >Q2, it is determined that the corresponding category needs to adjust the preset fixed priority.

[0007] Furthermore, step S300 includes: S301. Based on the judgment results of each category CK, the category Cad that needs to adjust the preset fixed priority is screened out. For each historical control record in the category that needs to adjust the preset fixed priority, the correlation between the various types of information is analyzed to construct the information correlation matrix Auv, where u and v are 1 to N, and a uv =(f uv ×e uv ) / Σ k∈[1,N] Σ r∈[1,N] (f kr ×e kr ), f uv Indicates the number of times information u and information v appear simultaneously in the same historical control record, e uv It represents the impact factor on production safety or efficiency when information u and information v appear simultaneously. It is determined by expert evaluation combined with historical production data. The larger the value, the more significant the impact. kr represents the number of times information k and information r appear simultaneously in the same historical control record, e kr It represents the impact factor on production safety or efficiency when information k and information r appear at the same time; S302. Combined with the information association matrix Auv, for each category that needs to adjust the preset fixed priority, calculate the dynamically adjusted weight W' k , and W' k =W k ×(1+Σ v∈[1,N] a kv -Σ u∈[1,N] a uk ),Σ v∈[1,N] a kv Represents the sum of the correlation between the k-th category information and other categories of information, Σ u∈[1,N] a uk Represents the sum of the correlations between other types of information and the kth type of information; according to the dynamically adjusted weight W' k , and the feedback results of each historical control record, calculate the comprehensive importance index SIk for each type of information corresponding to each category Cad, and SIk=W' k ×[Nkh / (Nkh+Nkw+g)], where Nkh represents the number of times the k-th category of historical information is correctly processed in the corresponding historical control records and has a positive impact on production safety and efficiency improvement, Nkw represents the number of times the k-th category of historical information is delayed or has problems in the corresponding historical control records due to unreasonable priority settings, and g represents a constant, which is infinitesimal. For each category of historical information that needs to adjust the preset fixed priority, the information is sorted in descending order according to the corresponding comprehensive importance index SIk to generate the adjusted priority order.

[0008] Furthermore, step S400 includes: S401. Obtain real-time information and analyze it in the same way as historical information to obtain the real-time feature vector Y i , the real-time feature vector Y i The historical feature mean vectors X of several categories corresponding to the system operation status of the historical information i _μ performs similarity calculation and selects the historical feature mean vector X with the largest similarity i _μ is used as the matching result, and the historical feature mean vector X is obtained i _μ corresponds to the category of the system operating state. If the historical feature mean vector X i If the category of the system operation status corresponding to _μ does not need to adjust the preset fixed priority, the corresponding priority order is generated according to the preset fixed priority; S402. If the historical feature mean vector X i The category of the system operation status corresponding to _μ needs to adjust the preset fixed priority, so the historical feature mean vector X is obtained i _μ corresponds to the adjusted priority order of the system operation status category, and performs corresponding priority control according to the adjusted priority order; obtains real-time feedback information, and calculates the corresponding evaluation index R based on the real-time feedback information, and R=Σ k∈[1,N] [Mkh / (Mkh+Mkw+g)], where Mkh represents the number of times the k-th type of real-time information is correctly processed in the corresponding real-time control record and has a positive impact on production safety and efficiency improvement, and Mkw represents the number of times the k-th type of real-time information is delayed or has problems in the corresponding real-time control record due to unreasonable priority settings. The evaluation index R is compared with the threshold R0. If R≥R0, no processing is performed; otherwise, the relevant personnel are notified and take appropriate measures.

[0009] An intrinsically safe screen priority control system based on dynamic adjustment, comprising: a historical data processing module, a system status analysis module, a priority decision module, and a real-time control and feedback module; The historical data processing module obtains historical priority control records and corresponding historical information over a period of time, and matches the historical priority control records with the historical information; based on the correspondence between the historical priority control records and the historical information, the module evaluates the adaptation index of each historical priority control record; The system status analysis module classifies the system operation status according to the adaptation index and historical information of each historical priority control record; for each category of system operation status, combined with the corresponding adaptation index, it determines whether the preset fixed priority for the corresponding category needs to be adjusted; The priority decision module obtains the categories that need priority adjustment based on the judgment results of each category; and generates the corresponding priority order for each category in combination with the feedback results of the corresponding historical control records; The real-time control and feedback module obtains real-time information, analyzes the real-time information with historical information, and thus identifies the category of real-time information; matches the priority order according to the real-time information category, thereby performing corresponding priority control, obtains real-time feedback information and evaluates the current priority control effect, and performs corresponding processing based on the evaluation results.

[0010] Furthermore, the historical data processing module includes a data acquisition unit and an adaptation index calculation unit; The data collection unit obtains the historical priority control records and corresponding historical information in the past period of time, and matches the historical priority control records with the historical information; the adaptation index calculation unit evaluates the adaptation index of each historical priority control record based on the correspondence between the historical priority control records and the historical information.

[0011] Furthermore, the system status analysis module includes a status clustering unit and a priority adjustment judgment unit; The state clustering unit classifies the system operation state according to the adaptation index and historical information of each historical priority control record; the priority adjustment judgment unit judges whether the preset fixed priority needs to be adjusted for the corresponding category based on the corresponding adaptation index of each category of system operation state.

[0012] Furthermore, the priority decision module includes a correlation analysis and weight adjustment unit and a priority sorting unit; The association analysis and weight adjustment unit obtains the categories that need priority adjustment based on the judgment results of each category, performs association analysis on the categories that need priority adjustment, and dynamically adjusts the weights based on the association analysis; the priority sorting unit generates a corresponding priority order for each category based on the feedback results of the corresponding historical control records.

[0013] Furthermore, the real-time control and feedback module includes a real-time information processing unit and a feedback evaluation unit; The real-time information processing unit obtains real-time information, analyzes the real-time information with historical information, and thus identifies the category of the real-time information; matches the priority order according to the category of the real-time information, and thus performs corresponding priority control; the feedback evaluation unit obtains real-time feedback information and evaluates the current priority control effect, and performs corresponding processing based on the evaluation results.

[0014] Compared with existing technologies, the present invention offers the following advantages: It utilizes a dynamically adjustable priority control approach, enabling it to adjust priorities based on the system's actual operating status and real-time feedback, rather than relying on a fixed priority order. This allows the system to process information more flexibly and rationally under varying production environments and conditions, ensuring that critical data and alarm information are prioritized, and improving the system's ability to respond to emergencies and disruptions. By combining historical priority control records with the adaptation index of historical information, the present invention accurately assesses the impact of different types of information on production safety and efficiency, allowing for precise adjustment of priorities. This prevents the neglect of critical information and the excessive resource consumption of less important information, thereby improving safety and efficiency during the production process. The present invention is adaptable to complex industrial environments and changing production conditions. By combining real-time analysis with historical data, it not only adapts to changes in production status but also dynamically adjusts priorities in complex environments to better address changes in information importance. This avoids the rigidity of fixed priority control approaches and ensures timely and effective information processing. Through dynamic priority adjustment, the present invention ensures that operators have immediate access to the most important information under all circumstances, reducing delays and errors caused by improper information processing, improving decision-making efficiency, and mitigating production safety risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 It is a module schematic diagram of an intrinsically safe screen priority control system based on dynamic adjustment according to the present invention. DETAILED DESCRIPTION

[0016] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0017] See also Figure 1 , the present invention provides a technical solution: An intrinsically safe screen priority control system based on dynamic adjustment, comprising: a historical data processing module, a system status analysis module, a priority decision module, and a real-time control and feedback module; The historical data processing module obtains historical priority control records and corresponding historical information over a period of time, and matches the historical priority control records with the historical information; based on the correspondence between the historical priority control records and the historical information, the module evaluates the adaptation index of each historical priority control record; The system status analysis module classifies the system operation status according to the adaptation index and historical information of each historical priority control record; for each category of system operation status, combined with the corresponding adaptation index, it determines whether the preset fixed priority for the corresponding category needs to be adjusted; The priority decision module obtains the categories that need priority adjustment based on the judgment results of each category; and generates the corresponding priority order for each category in combination with the feedback results of the corresponding historical control records; The real-time control and feedback module obtains real-time information, analyzes the real-time information with historical information, and thus identifies the category of real-time information; matches the priority order according to the real-time information category, thereby performing corresponding priority control, obtains real-time feedback information and evaluates the current priority control effect, and performs corresponding processing based on the evaluation results.

[0018] The historical data processing module includes a data acquisition unit and an adaptation index calculation unit; The data collection unit obtains the historical priority control records and corresponding historical information in the past period of time, and matches the historical priority control records with the historical information; the adaptation index calculation unit evaluates the adaptation index of each historical priority control record based on the correspondence between the historical priority control records and the historical information.

[0019] The system status analysis module includes a status clustering unit and a priority adjustment judgment unit; The state clustering unit classifies the system operation state according to the adaptation index and historical information of each historical priority control record; the priority adjustment judgment unit judges whether the preset fixed priority needs to be adjusted for the corresponding category based on the corresponding adaptation index of each category of system operation state.

[0020] The priority decision module includes an association analysis and weight adjustment unit and a priority sorting unit; The association analysis and weight adjustment unit obtains the categories that need priority adjustment based on the judgment results of each category, performs association analysis on the categories that need priority adjustment, and dynamically adjusts the weights based on the association analysis; the priority sorting unit generates a corresponding priority order for each category based on the feedback results of the corresponding historical control records.

[0021] The real-time control and feedback module includes a real-time information processing unit and a feedback evaluation unit; The real-time information processing unit obtains real-time information, analyzes the real-time information with historical information, and thus identifies the category of the real-time information; matches the priority order according to the category of the real-time information, and thus performs corresponding priority control; the feedback evaluation unit obtains real-time feedback information and evaluates the current priority control effect, and performs corresponding processing based on the evaluation results.

[0022] A method for controlling the priority of an intrinsically safe screen based on dynamic adjustment comprises the following steps: Step S100. Obtain historical priority control records and corresponding historical information over a period of time, and match the historical priority control records with the historical information; based on the correspondence between the historical priority control records and the historical information, evaluate the adaptation index of each historical priority control record; Step S200. Classify the system operation status according to the adaptation index and historical information of each historical priority control record; for each category of system operation status, combined with the corresponding adaptation index, determine whether the preset fixed priority for the corresponding category needs to be adjusted; Step S300. According to the judgment results of each category, the category that needs to be adjusted in priority is obtained; and combined with the feedback results of the corresponding historical control records, a corresponding priority order is generated for each category; Step S400. Obtain real-time information, analyze the real-time information with historical information, and identify the category of the real-time information; match the priority order according to the real-time information category, and perform corresponding priority control, obtain real-time feedback information and evaluate the current priority control effect, and perform corresponding processing based on the evaluation results.

[0023] Step S100 includes: S101. Obtain historical priority control records for the security screen over a past period of time, where each historical priority control record includes the priority execution status of various types of information during each information processing, such as the priority order and execution results of equipment fault alarm information, real-time production parameter data, and operation instruction information; based on the timestamp corresponding to the historical priority control record, obtain historical information at the corresponding time point, where the historical information includes but is not limited to the system operating status (normal production, equipment maintenance, etc.), the specific content of various types of information, the time of generation, etc.; each historical priority control record is matched one-to-one with the corresponding historical information according to the timestamp, thereby obtaining a data set D, where D = {(Ri,Hi)}, where Ri represents the i-th historical priority control record, and Hi represents the historical information corresponding to the i-th historical priority control record; S102. For each element in the data set D, calculate the corresponding adaptation index AI i , the corresponding calculation formula is: AI i =Σk∈[1,N] [W k ·(1-ΔP ik / M k )] / Σ k∈[1,N] W k , among which AI i represents the adaptation index of the i-th historical priority control record, W k represents the weight of the kth type of historical information, and the choice of weight can be determined by expert experience, historical data analysis, or domain knowledge. For example, through a data-driven approach, the contribution of different information types to system performance can be evaluated by analyzing past system behavior, thereby determining the weight of each information type; ΔP ik It represents the priority execution deviation of the i-th historical priority control record on the k-th type of historical information. The corresponding calculation formula is: ΔP ik =|P ik_e -P ik_a |, where P ik_e represents the preset priority order of the kth category of historical information in the i-th historical priority control record, P ik_a It represents the actual priority order of the kth category of historical information of the i-th historical priority control record, and the actual priority order is determined by relevant personnel; Mk represents the maximum value of the priority execution deviation of the kth category of historical information.

[0024] Step S200 includes: S201. For each element in the data set D, extract the historical data features that represent the system operation status, normalize the extracted historical data features, and form a historical feature vector X i , and X i =[x i1 ,x i2 ,...,x im ], where m represents the number of features, x i1 Indicates the first eigenvalue of the historical information corresponding to the i-th element, x i2 represents the second eigenvalue of the historical information corresponding to the i-th element, and so on, x im Represents the mth eigenvalue of the historical information corresponding to the i-th element; Based on the traditional clustering algorithm, the adaptation index AI i As a weighting factor, the distance from the sample point to the cluster center is calculated, and the corresponding calculation formula is: dw(X,C)=[Σ j∈[1,m] AI i ·(x j -c j ) 2 ]^(1 / 2), where X represents the sample point feature vector, C represents the cluster center feature vector, and x jrepresents the jth eigenvalue of the sample point eigenvector, c j represents the jth eigenvalue of the cluster center eigenvector; according to the preset number of clusters K, after multiple iterative calculations, the system operation status corresponding to the historical information is divided into K categories, which are represented as C1, C2, ..., CK in sequence; S202. For each category, calculate the corresponding category adaptation index average μ_AI b and category adaptation index standard deviation σ_AI b , where b = 1, 2, ..., K; according to the preset adaptation index lower limit threshold Q1 and adaptation index fluctuation threshold Q2, if there is μ_AI b ≥Q1 and σ_AI b ≤Q2, it is determined that the corresponding category does not need to adjust the preset fixed priority; if there is μ_AI b <Q1 or σ_AI b >Q2, it is determined that the corresponding category needs to adjust the preset fixed priority.

[0025] In this example, it is assumed that the feature vectors in dataset D contain three dimensions: device temperature, device pressure, and device operating status. Through normalization and calculation of the adaptation index, the feature vector and adaptation index of each record are obtained. In weighted cluster analysis, it is assumed that the system classifies these historical records into three categories: normal status, maintenance status, and fault status. The mean and standard deviation of the adaptation index are calculated for each category. For example, the mean adaptation index for the normal status category is 0.85, with a standard deviation of 0.02; the mean adaptation index for the maintenance status category is 0.45, with a standard deviation of 0.15; and the mean adaptation index for the fault status category is 0.2, with a standard deviation of 0.25. Based on the preset thresholds Q1 = 0.6 and Q2 = 0.1, the system determines that the maintenance status category and the fault status category require priority adjustment.

[0026] Step S300 includes: S301. Based on the judgment results of each category CK, the category Cad that needs to adjust the preset fixed priority is screened out. For each historical control record in the category that needs to adjust the preset fixed priority, the correlation between the various types of information is analyzed to construct the information correlation matrix Auv, where u and v are 1 to N, and a uv =(f uv ×e uv ) / Σ k∈[1,N] Σ r∈[1,N] (f kr ×e kr ), f uv Indicates the number of times information u and information v appear simultaneously in the same historical control record, e uvIt represents the impact factor on production safety or efficiency when information u and information v appear simultaneously. It is determined by expert evaluation combined with historical production data. The larger the value, the more significant the impact. kr represents the number of times information k and information r appear simultaneously in the same historical control record, e kr It represents the impact factor on production safety or efficiency when information k and information r appear at the same time; S302. Combined with the information association matrix Auv, for each category that needs to adjust the preset fixed priority, calculate the dynamically adjusted weight W' k , and W' k =W k ×(1+Σ v∈[1,N] a kv -Σ u∈[1,N] a uk ),Σ v∈[1,N] a kv Represents the sum of the correlation between the k-th category information and other categories of information, Σ u∈[1,N] a uk Represents the sum of the correlations between other types of information and the kth type of information; according to the dynamically adjusted weight W' k , and the feedback results of each historical control record, calculate the comprehensive importance index SIk for each type of information corresponding to each category Cad, and SIk=W' k ×[Nkh / (Nkh+Nkw+g)], where Nkh represents the number of times the k-th category of historical information is correctly processed in the corresponding historical control records and has a positive impact on production safety and efficiency improvement, Nkw represents the number of times the k-th category of historical information is delayed or has problems in the corresponding historical control records due to unreasonable priority settings, and g represents a constant, which is infinitesimal. For each category of historical information that needs to adjust the preset fixed priority, the information is sorted in descending order according to the corresponding comprehensive importance index SIk to generate the adjusted priority order.

[0027] Step S400 includes: S401. Obtain real-time information and analyze it in the same way as historical information to obtain the real-time feature vector Y i , the real-time feature vector Y i The historical feature mean vectors X of several categories corresponding to the system operation status of the historical information i _μ performs similarity calculation and selects the historical feature mean vector X with the largest similarity i _μ is used as the matching result, and the historical feature mean vector X is obtained i _μ corresponds to the category of the system operating state. If the historical feature mean vector X iIf the category of the system operation status corresponding to _μ does not need to adjust the preset fixed priority, the corresponding priority order is generated according to the preset fixed priority; S402. If the historical feature mean vector X i The category of the system operation status corresponding to _μ needs to adjust the preset fixed priority, so the historical feature mean vector X is obtained i _μ corresponds to the adjusted priority order of the system operation status category, and performs corresponding priority control according to the adjusted priority order; obtains real-time feedback information, and calculates the corresponding evaluation index R based on the real-time feedback information, and R=Σ k∈[1,N] [Mkh / (Mkh+Mkw+g)], where Mkh represents the number of times the k-th type of real-time information is correctly processed in the corresponding real-time control record and has a positive impact on production safety and efficiency improvement, and Mkw represents the number of times the k-th type of real-time information is delayed or has problems in the corresponding real-time control record due to unreasonable priority settings. The evaluation index R is compared with the threshold R0. If R≥R0, no processing is performed; otherwise, the relevant personnel are notified and take appropriate measures.

[0028] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0029] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A method for controlling intrinsically safe screen priority based on dynamic adjustment, characterized by: The method comprises the following steps: Step S100. Obtain historical priority control records and corresponding historical information over a period of time, and match the historical priority control records with the historical information; based on the correspondence between the historical priority control records and the historical information, evaluate the adaptation index of each historical priority control record; Step S200. Classify the system operation status according to the adaptation index and historical information of each historical priority control record; for each category of system operation status, combined with the corresponding adaptation index, determine whether the preset fixed priority for the corresponding category needs to be adjusted; Step S300. According to the judgment results of each category, the category that needs to be adjusted in priority is obtained; and combined with the feedback results of the corresponding historical control records, a corresponding priority order is generated for each category; Step S400. Obtain real-time information, analyze the real-time information with historical information, and identify the category of the real-time information; match the priority order according to the real-time information category, and perform corresponding priority control, obtain real-time feedback information and evaluate the current priority control effect, and perform corresponding processing based on the evaluation results.

2. The method for controlling the priority of an intrinsically safe screen based on dynamic adjustment according to claim 1, characterized in that: The step S100 includes: S101. Obtain historical priority control records for the security screen over a past period of time, where each historical priority control record includes the priority execution status of each type of information during each information processing; obtain historical information at the corresponding time point based on the timestamp corresponding to the historical priority control record, and associate each historical priority control record with the corresponding historical information based on the timestamp, thereby obtaining a data set D, where D = {(Ri,Hi)}, where Ri represents the i-th historical priority control record, and Hi represents the historical information corresponding to the i-th historical priority control record; S102. For each element in the data set D, calculate the corresponding adaptation index AI i , the corresponding calculation formula is: AI i =Σ k∈[1,N] [W k ·(1-ΔP ik / M k )] / Σ k∈[1,N] W k , among which AI i represents the adaptation index of the i-th historical priority control record, W k represents the weight of the k-th category of historical information, ΔP ik It represents the priority execution deviation of the i-th historical priority control record on the k-th type of historical information. The corresponding calculation formula is: ΔP ik =|P ik_e -P ik_a |, where P ik_e represents the preset priority order of the kth category of historical information in the i-th historical priority control record, P ik_a It represents the actual priority order of the kth category of historical information of the i-th historical priority control record, and the actual priority order is determined by relevant personnel; Mk represents the maximum value of the priority execution deviation of the kth category of historical information.

3. The method for controlling the priority of an intrinsically safe screen based on dynamic adjustment according to claim 2, characterized in that: The step S200 includes: S201. For each element in the data set D, extract the historical data features that represent the system operation status, normalize the extracted historical data features, and form a historical feature vector X i , and X i =[x i1 ,x i2 ,...,x im ], where m represents the number of features, x i1 Indicates the first eigenvalue of the historical information corresponding to the i-th element, x i2 represents the second eigenvalue of the historical information corresponding to the i-th element, and so on, x im Represents the mth eigenvalue of the historical information corresponding to the i-th element; Based on the traditional clustering algorithm, the adaptation index AI i As a weighting factor, the distance from the sample point to the cluster center is calculated, and the corresponding calculation formula is: dw(X,C)=[Σ j∈[1,m] AI i ·(x j -c j ) 2 ]^(1 / 2), where X represents the sample point feature vector, C represents the cluster center feature vector, and x j represents the jth eigenvalue of the sample point eigenvector, c j represents the jth eigenvalue of the cluster center eigenvector; according to the preset number of clusters K, after multiple iterative calculations, the system operation status corresponding to the historical information is divided into K categories, which are represented as C1, C2, ..., CK in sequence; S202. For each category, calculate the corresponding category adaptation index average μ_AI b and category adaptation index standard deviation σ_AI b , where b = 1, 2, ..., K; according to the preset adaptation index lower limit threshold Q1 and adaptation index fluctuation threshold Q2, if there is μ_AI b ≥Q1 and σ_AI b ≤Q2, it is determined that the corresponding category does not need to adjust the preset fixed priority; if there is μ_AI b <Q1 or σ_AI b >Q2, it is determined that the corresponding category needs to adjust the preset fixed priority.

4. The method for controlling the priority of an intrinsically safe screen based on dynamic adjustment according to claim 3, characterized in that: The step S300 includes: S301. Based on the judgment results of each category CK, the category Cad that needs to adjust the preset fixed priority is screened out. For each historical control record in the category that needs to adjust the preset fixed priority, the correlation between the various types of information is analyzed to construct the information correlation matrix Auv, where u and v are 1 to N, and a uv =(f uv ×e uv ) / Σ k∈[1,N] Σ r∈[1,N] (f kr ×e kr ), f uv Indicates the number of times information u and information v appear simultaneously in the same historical control record, e uv represents the impact factor on production safety or efficiency when information u and information v appear simultaneously; f kr represents the number of times information k and information r appear simultaneously in the same historical control record, e kr It represents the impact factor on production safety or efficiency when information k and information r appear at the same time; S302. Combined with the information association matrix Auv, for each category that needs to adjust the preset fixed priority, calculate the dynamically adjusted weight W' k , and W' k =W k ×(1+Σ v∈[1,N] a kv -Σ u∈[1,N] a uk ),Σ v∈[1,N] a kv Represents the sum of the correlation between the k-th category information and other categories of information, Σ u∈[1,N] a uk Represents the sum of the correlations between other types of information and the kth type of information; according to the dynamically adjusted weight W' k , and the feedback results of each historical control record, calculate the comprehensive importance index SIk for each type of information corresponding to each category Cad, and SIk=W' k ×[Nkh / (Nkh+Nkw+g)], where Nkh represents the number of times the k-th category of historical information is correctly processed in the corresponding historical control records and has a positive impact on production safety and efficiency improvement, Nkw represents the number of times the k-th category of historical information is delayed or has problems in the corresponding historical control records due to unreasonable priority settings, and g represents a constant, which is infinitesimal. For each category of historical information that needs to adjust the preset fixed priority, the information is sorted in descending order according to the corresponding comprehensive importance index SIk to generate the adjusted priority order.

5. The method for controlling the priority of an intrinsically safe screen based on dynamic adjustment according to claim 4, characterized in that: The step S400 includes: S401. Obtain real-time information and analyze it in the same way as historical information to obtain the real-time feature vector Y i , the real-time feature vector Y i The historical feature mean vectors X of several categories corresponding to the system operation status of the historical information i _μ performs similarity calculation and selects the historical feature mean vector X with the largest similarity i _μ is used as the matching result, and the historical feature mean vector X is obtained i _μ corresponds to the category of the system operating state. If the historical feature mean vector X i If the category of the system operation status corresponding to _μ does not need to adjust the preset fixed priority, the corresponding priority order is generated according to the preset fixed priority; S402. If the historical feature mean vector X i The category of the system operation status corresponding to _μ needs to adjust the preset fixed priority, so the historical feature mean vector X is obtained i _μ corresponds to the adjusted priority order of the system operation status category, and performs corresponding priority control according to the adjusted priority order; obtains real-time feedback information, and calculates the corresponding evaluation index R based on the real-time feedback information, and R=Σ k∈[1,N] [Mkh / (Mkh+Mkw+g)], where Mkh represents the number of times the k-th type of real-time information is correctly processed in the corresponding real-time control record and has a positive impact on production safety and efficiency improvement, and Mkw represents the number of times the k-th type of real-time information is delayed or has problems in the corresponding real-time control record due to unreasonable priority settings. The evaluation index R is compared with the threshold R0. If R≥R0, no processing is performed; otherwise, the relevant personnel are notified and take appropriate measures.

6. A dynamic adjustment-based intrinsically safe screen priority control system, applied to a dynamic adjustment-based intrinsically safe screen priority control method according to any one of claims 1 to 5, characterized in that: The system includes: a historical data processing module, a system status analysis module, a priority decision module and a real-time control and feedback module; The historical data processing module obtains historical priority control records and corresponding historical information within a past period of time, and matches the historical priority control records with the historical information; based on the correspondence between the historical priority control records and the historical information, evaluates the adaptation index of each historical priority control record; The system status analysis module classifies the system operation status according to the adaptation index and historical information of each historical priority control record; for each category of system operation status, combined with the corresponding adaptation index, determines whether the preset fixed priority for the corresponding category needs to be adjusted; The priority decision module obtains the category that needs priority adjustment based on the judgment result of each category; and generates a corresponding priority order for each category in combination with the feedback result of the corresponding historical control record; The real-time control and feedback module obtains real-time information, analyzes the real-time information and historical information, and thus identifies the category of the real-time information; matches the priority order according to the real-time information category, thereby performing corresponding priority control, obtains real-time feedback information and evaluates the current priority control effect, and performs corresponding processing based on the evaluation results.

7. The intrinsically safe screen priority control system based on dynamic adjustment according to claim 6, characterized in that: The historical data processing module includes a data acquisition unit and an adaptation index calculation unit; The data acquisition unit obtains historical priority control records and corresponding historical information over a period of time in the past, and matches the historical priority control records with the historical information; the adaptation index calculation unit evaluates the adaptation index of each historical priority control record based on the correspondence between the historical priority control records and the historical information.

8. The intrinsically safe screen priority control system based on dynamic adjustment according to claim 6, characterized in that: The system status analysis module includes a status clustering unit and a priority adjustment judgment unit; The state clustering unit classifies the system operation state according to the adaptation index and historical information of each historical priority control record; the priority adjustment judgment unit judges whether the preset fixed priority needs to be adjusted for the corresponding category based on the corresponding adaptation index of each category of system operation state.

9. The intrinsically safe screen priority control system based on dynamic adjustment according to claim 6, characterized in that: The priority decision module includes an association analysis and weight adjustment unit and a priority sorting unit; The association analysis and weight adjustment unit obtains the category that needs priority adjustment based on the judgment result of each category, performs association analysis on the category that needs priority adjustment, and dynamically adjusts the weight in combination with the association analysis; the priority sorting unit generates a corresponding priority order for each category in combination with the feedback results of the corresponding historical control records.

10. The intrinsically safe screen priority control system based on dynamic adjustment according to claim 6, characterized in that: The real-time control and feedback module includes a real-time information processing unit and a feedback evaluation unit; The real-time information processing unit acquires real-time information, analyzes the real-time information and historical information, and thereby identifies the category of the real-time information; The priority order is matched according to the real-time information category, thereby performing corresponding priority control; the feedback evaluation unit obtains the real-time feedback information and evaluates the current priority control effect, and performs corresponding processing according to the evaluation result.

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