CN114493381B - Risk source trend monitoring and early warning method for fixed time-space period of chemical industry park - Google Patents
Risk source trend monitoring and early warning method for fixed time-space period of chemical industry park Download PDFInfo
- Publication number
- CN114493381B CN114493381B CN202210390121.6A CN202210390121A CN114493381B CN 114493381 B CN114493381 B CN 114493381B CN 202210390121 A CN202210390121 A CN 202210390121A CN 114493381 B CN114493381 B CN 114493381B
- Authority
- CN
- China
- Prior art keywords
- risk
- area
- chemical industry
- minimum unit
- industry park
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Development Economics (AREA)
- Marketing (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Educational Administration (AREA)
- Alarm Systems (AREA)
Abstract
The invention discloses a risk source trend monitoring and early warning method for a fixed time-space period of a chemical industry park, which belongs to the technical field of monitoring and early warning of the chemical industry park and is used for solving the problems that the risk monitoring mode is single and the integrity and intelligence of monitoring are insufficient in the existing monitoring process of the chemical industry park, and the method comprises the following steps: step S10, performing area division on the chemical industry park; step S20, performing thermal monitoring on each area of the chemical industry park in a space thermal monitoring mode; step S30, acquiring thermal monitoring data once every other fixed space-time period; and step S40, dividing the thermodynamic diagram into different thermodynamic grades, and respectively counting the thermodynamic distribution conditions of each divided chemical industry area according to the thermodynamic diagram.
Description
Technical Field
The invention belongs to the field of risk monitoring, relates to a monitoring and early warning technology for a chemical industry park, and particularly relates to a risk source trend monitoring and early warning method for a fixed time-space period of the chemical industry park.
Background
Risk evaluation, also called safety evaluation, refers to the comprehensive consideration of the probability of risk occurrence, loss amplitude and other factors on the basis of risk identification and estimation. The possibility and the degree of the risk of the system are obtained and compared with the accepted safety standard to determine the risk level of the enterprise, so as to decide whether to take control measures and to what degree. Risk identification and assessment is the basis for risk assessment. Only under the premise of fully revealing various risks and risk factors faced by an enterprise, accurate evaluation can be made.
Among the prior art, when carrying out the risk control to the chemical industry garden, all adopt multiple monitoring sensor to independently detect usually, report to the police when detecting numerical value and surpassing predetermined threshold value promptly, but this kind of mode is intelligent inadequately, can only independently detect the single region in garden, and whole monitoring effect is relatively poor, and current heating power control field all relies on the manual work to supervise usually simultaneously, and the wholeness and the intelligent of the mode of heating power control are relatively poor.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a risk source trend monitoring and early warning method for a chemical industry park with a fixed time-space period.
The technical problem to be solved by the invention is as follows: in the monitoring process of the existing chemical industry park, the risk monitoring mode is single, and the integrity and the intelligence of monitoring are not enough.
The purpose of the invention can be realized by the following technical scheme: a risk source trend monitoring and early warning method for a chemical industry park with a fixed time-space period comprises the following steps:
step S10, performing regional division on the chemical industry park, and setting risk levels for the divided chemical industry park according to the overall distribution condition of the chemical industry park;
step S20, performing thermal monitoring on each area of the chemical industry park in a space thermal monitoring mode;
step S30, acquiring thermal monitoring data once every fixed time-space period, and drawing a thermodynamic diagram of the chemical industry park according to the acquired thermal monitoring data;
step S40, dividing the thermodynamic diagram into different thermodynamic grades, and respectively counting the thermodynamic distribution condition of each divided chemical engineering area according to the thermodynamic diagram;
and step S50, generating the risk level of the chemical industry park according to the counted data.
Further, the step S10 further includes the following sub-steps:
step A10, dividing a chemical industry park into a processing operation area, a product storage area and a living area;
step A20, dividing the processing operation area into a processing equipment concentration area and a transmission equipment concentration area, and setting a processing equipment risk parameter and a transmission equipment risk parameter for the processing equipment concentration area and the transmission equipment concentration area respectively;
step A30, dividing a product storage area into a product centralized storage area and a product transmission storage area, and setting a product centralized risk parameter and a product transmission risk parameter for the product centralized storage area and the product transmission storage area respectively;
and step A40, setting the life zone risk parameters for the life zone.
Further, the step S30 further includes the following sub-steps:
step C10, substituting the processing equipment risk parameter, the transmission equipment risk parameter, the product centralized risk parameter, the product transmission risk parameter and the living area risk parameter into a chemical industry park basic risk formula to obtain a chemical industry park basic risk index;
step C20, when the basic risk index of the chemical industry park is less than or equal to the first basic risk threshold, setting the chemical industry park as a first-level risk monitoring park; when the basic risk index of the chemical industry park is larger than a first risk threshold value and smaller than or equal to a second risk threshold value, setting the chemical industry park as a secondary risk monitoring park; and when the basic risk index of the chemical industry park is greater than the second risk threshold value, setting the chemical industry park as a three-level risk monitoring park.
Further, the chemical industry park basis risk formula is configured as:
(ii) a The method comprises the following steps of obtaining a risk index of a chemical industry park, obtaining a risk parameter of a processing device, obtaining a risk parameter of a transmission device, obtaining a risk index of a processing device, obtaining a risk parameter of a transmission device, obtaining a risk parameter of a product concentration by Ccpf, obtaining a risk parameter of a product transmission by Ccpc, obtaining a risk parameter of a living area by Csf and obtaining a basic risk conversion coefficient by f 1.
Further, the step S30 further includes the following sub-steps:
step C30, setting hexagons such as units as the minimum unit area of the thermodynamic diagram, and setting a plurality of thermodynamic grades according to the image generated by the thermodynamic diagram;
step C40, when the chemical industry park is a first-level risk monitoring park, when a thermodynamic diagram is drawn, and when images of two or more thermodynamic grades appear in any minimum unit area, the lowest thermodynamic grade is selected as the thermodynamic grade of the minimum unit area;
step C50, when the chemical industry park is a secondary risk monitoring park, when a thermodynamic diagram is drawn, and when two or more than two thermodynamic grade images appear in any minimum unit area, the thermodynamic grade with the largest area ratio is selected as the thermodynamic grade of the minimum unit area;
and step C60, when the chemical industry park is a three-level risk monitoring park, when a thermodynamic diagram is drawn, and when images of two or more thermodynamic grades appear in any minimum unit area, selecting the maximum thermodynamic grade as the thermodynamic grade of the minimum unit area.
Further, the step S40 includes the following sub-steps:
step D10, when the number of the minimum unit areas with different thermal levels of each area in the chemical industry park in the thermodynamic diagram is counted, when the minimum unit areas are simultaneously positioned in two or more areas, the areas are set as common thermal areas, and the common thermal areas can be calculated in any one area;
step D20, counting the number of minimum unit areas with different thermal grades in the processing equipment concentration area in the thermodynamic diagram, and respectively setting the minimum unit areas to be S1 jj-Snjj, wherein S1jj is the number of the minimum unit areas with the first thermal grade in the processing equipment concentration area in the thermodynamic diagram, and Snjj is the number of the minimum unit areas with the nth thermal grade in the processing equipment concentration area in the thermodynamic diagram;
step D30, counting the number of minimum unit areas with different thermal grades in the transmission equipment concentration area in the thermodynamic diagram, and respectively setting the minimum unit areas to be S1 cj-Sncj, wherein S1cj is the number of the minimum unit areas with the first thermal grade in the transmission equipment concentration area in the thermodynamic diagram, and Sncj is the number of the minimum unit areas with the nth thermal grade in the transmission equipment concentration area in the thermodynamic diagram;
step S40, counting the number of minimum unit areas with different thermal grades in the product centralized storage area in the thermodynamic diagram, and respectively setting the minimum unit areas to be S1 cc-Sncc, wherein S1cc is the number of the minimum unit areas with the first thermal grade in the product centralized storage area in the thermodynamic diagram, and Sncc is the number of the minimum unit areas with the nth thermal grade in the product centralized storage area in the thermodynamic diagram;
step S50, counting the number of minimum unit areas with different heat grades in the product transmission storage area in the thermodynamic diagram, and respectively setting the minimum unit areas to be S1 cf-Sncf, wherein S1cf is the number of the minimum unit areas with the first heat grade in the product transmission storage area in the thermodynamic diagram, and Sncf is the number of the minimum unit areas with the nth heat grade in the product transmission storage area in the thermodynamic diagram;
and step S60, counting the number of minimum unit areas of different heat levels in the life area in the thermodynamic diagram, and respectively setting the minimum unit areas to be S1 sf-Snsf, wherein S1sf is the number of the minimum unit areas of the first heat level in the life area in the thermodynamic diagram, and Snsf is the number of the minimum unit areas of the nth heat level in the life area in the thermodynamic diagram.
Further, the step S50 includes the following sub-steps:
step E10, substituting the number of minimum unit areas with different thermal power grades in the processing equipment concentration area in the thermodynamic diagram and the risk parameters of the processing equipment into a risk formula of the processing equipment concentration area to obtain a risk index of the processing equipment concentration area;
step E20, substituting the number of minimum unit areas with different thermal power grades in the transmission equipment concentration area in the thermodynamic diagram and the transmission equipment risk parameters into a transmission equipment concentration area risk formula to obtain a transmission equipment concentration area risk index;
step E30, substituting the number of minimum unit areas with different thermal power grades in the product centralized storage area in the thermodynamic diagram and the product centralized risk parameters into a product centralized storage area risk formula to obtain a product centralized storage area risk index;
step E40, substituting the number of minimum unit areas with different thermal power grades in the product transmission storage area in the thermodynamic diagram and the risk parameters of the processing equipment into a product transmission storage area risk formula to obtain a product transmission storage area risk index;
and E50, substituting the number of the minimum unit areas with different thermal grades in the living area in the thermodynamic diagram and the living area risk parameters into a living area risk formula to obtain a living area risk index.
Further, the processing equipment concentration area risk formula is configured as:
the risk formula of the transmission equipment concentration area is configured as follows:
the product centralized storage area risk formula is configured as follows:
the product transfer storage area risk formula is configured to:
the living area risk formula is configured to:
(ii) a Wherein Fjj is a risk index of a processing equipment concentration area, Fcj is a risk index of a transmission equipment concentration area, Fcc is a risk index of a product concentration storage area, Fcf is a risk index of a product transmission storage area, Fsf is a risk index of a living area, and s1 to sn are respectively a risk conversion coefficient from a first thermal grade to an nth thermal grade.
Further, the step S50 further includes the following sub-steps:
step E60, substituting the risk index of the processing equipment concentration area, the risk index of the transmission equipment concentration area, the risk index of the product concentration storage area, the risk index of the product transmission storage area, the risk index of the living area and the basic risk index of the chemical industry park into a chemical industry park risk formula to obtain the risk index of the chemical industry park;
step E70, when the risk index of the chemical industry park is larger than or equal to the first risk threshold of the chemical industry park, outputting a first-level monitoring risk grade signal; when the risk index of the chemical industry park is greater than or equal to the risk threshold of the second chemical industry park and smaller than the risk threshold of the first chemical industry park, outputting a secondary monitoring risk level signal; and when the risk index of the chemical industry park is smaller than the risk threshold of the second chemical industry park, outputting a three-level monitoring risk level signal.
Further, the chemical industry park risk formula is configured as:
Compared with the prior art, the invention has the beneficial effects that: the invention divides the chemical industry park into areas, sets the risk level for the divided chemical industry park according to the overall distribution condition of the chemical industry park, and then carries out thermal power monitoring on each area of the chemical industry park in a space thermal power monitoring mode, then, once thermal monitoring data is obtained every other fixed space-time period, thermodynamic diagrams of a chemical industry park are drawn according to the obtained thermal monitoring data, the thermodynamic diagrams are divided into different thermodynamic grades, respectively counting the thermodynamic distribution condition of each divided chemical area according to the thermodynamic diagram, and finally generating the risk grade of the chemical industry park according to the counted data, the invention can carry out thermodynamic monitoring on the basis of the basic risk parameters of different parks, thereby improve the pertinence of garden control, simultaneously through the integrated processing to the monitored data, can improve the wholeness and the intelligence of the risk monitoring in chemical industry garden.
Drawings
In order to facilitate understanding for those skilled in the art, the present invention will be further described with reference to the accompanying drawings.
FIG. 1 is a flow chart of a method of the present invention;
fig. 2 is a reference diagram for minimum unit area division in the thermodynamic diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
Referring to fig. 1, a method for monitoring and warning a trend of a risk source in a chemical industry park with a fixed time-space period includes the following steps:
step S10, performing regional division on the chemical industry park, and setting risk levels for the divided chemical industry park according to the overall distribution condition of the chemical industry park;
the step S10 further includes the following sub-steps: step A10, dividing a chemical industry park into a processing operation area, a product storage area and a living area; step A20, dividing the processing operation area into a processing equipment concentration area and a transmission equipment concentration area, and setting processing equipment risk parameters and transmission equipment risk parameters for the processing equipment concentration area and the transmission equipment concentration area respectively; step A30, dividing a product storage area into a product centralized storage area and a product transmission storage area, and setting a product centralized risk parameter and a product transmission risk parameter for the product centralized storage area and the product transmission storage area respectively; and step A40, setting the life zone risk parameters for the life zone. The method can be suitable for various chemical industry parks, and different basic parameters are set for different chemical industry parks due to different regional divisions of different chemical industry parks, so that the risk coefficient of each chemical industry park can be better predicted.
Step S20, performing thermal monitoring on each area of the chemical industry park in a space thermal monitoring mode;
step S30, acquiring thermal monitoring data once every fixed time-space period, and drawing a thermodynamic diagram of the chemical industry park according to the acquired thermal monitoring data; the step S30 further includes the following sub-steps:
step C10, substituting the processing equipment risk parameter, the transmission equipment risk parameter, the product centralized risk parameter, the product transmission risk parameter and the living area risk parameter into a chemical industry park basic risk formula to obtain a chemical industry park basic risk index; the chemical industry park basic risk formula is configured as follows:
(ii) a The method comprises the following steps of obtaining a risk index of a chemical industry park, obtaining a risk parameter of a processing device, obtaining a risk parameter of a transmission device, obtaining a risk parameter of a living area, obtaining a risk factor of a living area, obtaining a risk index of a living area, obtaining a risk parameter of a processing device, obtaining a risk parameter of a living area, obtaining a risk parameter of the living area, obtaining a risk factor of the living area, obtaining a basic risk conversion coefficient of the living area, and obtaining a value of f1, wherein Fhgj is a basic risk index of the chemical industry park, Cjjs is a risk parameter of the processing device, Ccscs is a risk parameter of the transmission device, Ccpf is a risk parameter of the product concentration, Ccpc is a risk parameter of the product transmission, Ccf is a risk parameter of the living area, f1 is a basic risk conversion coefficient, and f1 is between 1 and 2.
Step C20, when the basic risk index of the chemical industry park is less than or equal to the first basic risk threshold, setting the chemical industry park as a first-level risk monitoring park; when the basic risk index of the chemical industry park is larger than a first risk threshold value and smaller than or equal to a second risk threshold value, setting the chemical industry park as a secondary risk monitoring park; when the basic risk index of the chemical industry park is larger than a second risk threshold value, setting the chemical industry park as a third-level risk monitoring park; the first risk threshold value is smaller than the second risk threshold value, step C30, a hexagon of a unit and the like is set as a minimum unit area of the thermodynamic diagram, and a plurality of thermodynamic levels are set according to an image generated by the thermodynamic diagram;
referring to fig. 2, in step C40, when the chemical industry park is a first-level risk monitoring park, when an thermodynamic diagram is drawn, and when images of two or more thermodynamic levels appear in any minimum unit area, the lowest thermodynamic level is selected as the thermodynamic level of the minimum unit area; step C50, when the chemical industry park is a secondary risk monitoring park, when a thermodynamic diagram is drawn, and when two or more than two thermodynamic grade images appear in any minimum unit area, the thermodynamic grade with the largest area ratio is selected as the thermodynamic grade of the minimum unit area; wherein, the minimum unit area adopts the design of equal hexagon, step C60, when the chemical industry park is a three-level risk monitoring park, when a thermodynamic diagram is drawn, when images of two or more thermal grades appear in any minimum unit area, the maximum thermal grade is selected as the thermal grade of the minimum unit area, wherein the risk coefficient of the first-level risk monitoring park is smaller than that of the second-level risk monitoring park, and the risk coefficient of the second-level risk monitoring park is smaller than that of the three-level risk monitoring park, therefore, in the selection of the minimum unit area, when images of two or more thermal grades appear in one minimum unit area, the first-level risk monitoring park selects the lowest thermal grade, the second-level risk monitoring park selects the thermal grade with the largest area ratio, and the third-level risk monitoring park selects the maximum thermal grade, the setting of the garden of each level can be more closely attached.
Step S40, dividing the thermodynamic diagram into different thermodynamic grades, and respectively counting the thermodynamic distribution condition of each divided chemical engineering area according to the thermodynamic diagram; the step S40 includes the following sub-steps: step D10, when the number of the minimum unit areas with different thermal levels of each area in the chemical industry park in the thermodynamic diagram is counted, when the minimum unit areas are simultaneously positioned in two or more areas, the areas are set as common thermal areas, and the common thermal areas can be calculated in any one area;
step D20, counting the number of minimum unit areas with different thermal grades in the processing equipment concentration area in the thermodynamic diagram, and respectively setting the minimum unit areas to be S1 jj-Snjj, wherein S1jj is the number of the minimum unit areas with the first thermal grade in the processing equipment concentration area in the thermodynamic diagram, and Snjj is the number of the minimum unit areas with the nth thermal grade in the processing equipment concentration area in the thermodynamic diagram;
step D30, counting the number of minimum unit areas with different thermal grades in the transmission equipment concentration area in the thermodynamic diagram, and respectively setting the minimum unit areas to be S1 cj-Sncj, wherein S1cj is the number of the minimum unit areas with the first thermal grade in the transmission equipment concentration area in the thermodynamic diagram, and Sncj is the number of the minimum unit areas with the nth thermal grade in the transmission equipment concentration area in the thermodynamic diagram;
step S40, counting the number of minimum unit areas with different thermal levels in the product centralized storage area in the thermodynamic diagram, and respectively setting the minimum unit areas to be S1cc to Sncc, wherein S1cc is the number of the minimum unit areas with the first thermal level in the product centralized storage area in the thermodynamic diagram, and Sncc is the number of the minimum unit areas with the nth thermal level in the product centralized storage area in the thermodynamic diagram;
step S50, counting the number of minimum unit areas with different heat grades in the product transmission storage area in the thermodynamic diagram, and respectively setting the minimum unit areas to be S1 cf-Sncf, wherein S1cf is the number of the minimum unit areas with the first heat grade in the product transmission storage area in the thermodynamic diagram, and Sncf is the number of the minimum unit areas with the nth heat grade in the product transmission storage area in the thermodynamic diagram;
and step S60, counting the number of minimum unit areas of different heat levels in the life area in the thermodynamic diagram, and respectively setting the minimum unit areas to be S1 sf-Snsf, wherein S1sf is the number of the minimum unit areas of the first heat level in the life area in the thermodynamic diagram, and Snsf is the number of the minimum unit areas of the nth heat level in the life area in the thermodynamic diagram.
Step S50, generating the risk level of the chemical industry park according to the counted data, wherein the step S50 comprises the following substeps:
step E10, substituting the number of minimum unit areas with different thermal power grades in the processing equipment concentration area in the thermodynamic diagram and the processing equipment risk parameters into a processing equipment concentration area risk formula to obtain a processing equipment concentration area risk index; the risk formula of the processing equipment concentration area is configured as follows:
(ii) a Step E20, substituting the number of minimum unit areas with different thermal power grades in the transmission equipment concentration area in the thermodynamic diagram and the transmission equipment risk parameters into a transmission equipment concentration area risk formula to obtain a transmission equipment concentration area risk index; the risk formula of the transmission equipment concentration area is configured as follows:
(ii) a Step E30, substituting the number of minimum unit areas with different thermal power grades in the product centralized storage area in the thermodynamic diagram and the product centralized risk parameters into a product centralized storage area risk formula to obtain a product centralized storage area risk index; the product centralized storage area risk formula is configured as follows:
(ii) a Step E40, substituting the number of minimum unit areas with different thermal power grades in the product transmission storage area in the thermodynamic diagram and the risk parameters of the processing equipment into a product transmission storage area risk formula to obtain a product transmission storage area risk index; the product transport storage area risk formula is configured to:
(ii) a Step E50, substituting the number of the minimum unit areas with different thermal power grades in the living area in the thermodynamic diagram and the living area risk parameters into a living area risk formula to obtain a living area risk index; the living area risk formula is configured to:
. Wherein Fjj is a processing equipment concentration region risk index, Fcj is a transmission equipment concentration region risk index, Fcc is a product concentration storage region risk index, Fcf is a product transmission storage region risk index, Fsf is a living area risk index, s1 to sn are respectively a first thermal power grade risk conversion coefficient to an nth thermal power grade risk conversion coefficient, and specifically, s1 to sn can be respectively set to specific values 1 to n.
Step E60, substituting the risk index of the processing equipment concentration area, the risk index of the transmission equipment concentration area, the risk index of the product concentration storage area, the risk index of the product transmission storage area, the risk index of the living area and the basic risk index of the chemical industry park into a chemical industry park risk formula to obtain the risk index of the chemical industry park; the chemical industry park risk formula is configured as follows:
(ii) a The system comprises a processing device, a storage area, a living area, a processing device, a storage area, a living area and a storage area, wherein Fhgh is a risk index of the chemical industry park, k1 is a risk conversion coefficient of the processing device, k2 is a risk conversion coefficient of the processing device, k3 is a risk conversion coefficient of the product centralized storage area, k4 is a risk conversion coefficient of the product transmission storage area, and k5 is a risk conversion coefficient of the living area, wherein the value range of k1 to k5 is 1 to 2, and the specific gravity of each corresponding risk index in the risk index of the whole park is specifically set by reference; step E70, when the risk index of the chemical industry park is larger than or equal to the first risk threshold of the chemical industry park, outputting a first-level monitoring risk grade signal; when the risk index of the chemical industry park is greater than or equal to the risk threshold of the second chemical industry park and smaller than the risk threshold of the first chemical industry park, outputting a secondary monitoring risk level signal; and when the risk index of the chemical industry park is smaller than the risk threshold of the second chemical industry park, outputting a three-level monitoring risk level signal.
Step E80, when the risk index of the processing equipment concentration area is larger than or equal to the risk threshold value of the first processing equipment concentration area, outputting a risk signal of the first-level processing equipment concentration area; when the risk index of the processing equipment concentration area is greater than or equal to a risk threshold of a second processing equipment concentration area and smaller than a risk threshold of a first processing equipment concentration area, outputting a risk signal of a secondary processing equipment concentration area; when the risk index of the processing equipment concentration area is smaller than the risk threshold of the second processing equipment concentration area, outputting a risk signal of the three-level processing equipment concentration area;
when the risk index of the transmission equipment concentration area is greater than or equal to the risk threshold of the first transmission equipment concentration area, outputting a risk signal of the first-level transmission equipment concentration area; when the risk index of the transmission equipment concentration area is greater than or equal to a risk threshold of a second transmission equipment concentration area and smaller than a risk threshold of a first transmission equipment concentration area, outputting a risk signal of a secondary transmission equipment concentration area; when the risk index of the transmission equipment concentration area is smaller than a risk threshold value of a second transmission equipment concentration area, outputting a risk signal of the third-level transmission equipment concentration area;
when the risk index of the product centralized storage area is greater than or equal to the risk threshold of the first product centralized storage area, outputting a first-level product centralized storage area risk signal; when the risk index of the product centralized storage area is greater than or equal to the risk threshold of the second product centralized storage area and smaller than the risk threshold of the first product centralized storage area, outputting a risk signal of the secondary product centralized storage area; when the risk index of the product centralized storage area is smaller than the risk threshold of the second product centralized storage area, outputting a risk signal of the third-level product centralized storage area;
when the risk index of the product transmission storage area is larger than or equal to the risk threshold of the first product transmission storage area, outputting a first-level product transmission storage area risk signal; when the risk index of the product transmission storage area is greater than or equal to the risk threshold of the second product transmission storage area and smaller than the risk threshold of the first product transmission storage area, outputting a risk signal of the secondary product transmission storage area; when the risk index of the product transmission storage area is smaller than the risk threshold of the second product transmission storage area, outputting a risk signal of the third-level product transmission storage area;
when the living area risk index is larger than or equal to the first living area risk threshold, outputting a first-stage living area risk signal; when the living area risk index is greater than or equal to the second living area risk threshold and smaller than the first living area risk threshold, outputting a secondary living area risk signal; and when the living area risk index is smaller than the second living area risk threshold, outputting a third-level living area risk signal.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (5)
1. A risk source trend monitoring and early warning method for a chemical industry park with a fixed time-space period is characterized by comprising the following steps:
step S10, performing regional division on the chemical industry park, and setting risk levels for the divided chemical industry park according to the overall distribution condition of the chemical industry park;
step S20, performing thermal monitoring on each area of the chemical industry park in a space thermal monitoring mode;
step S30, acquiring thermal monitoring data once at intervals of a fixed space-time period, and drawing a thermodynamic diagram of a chemical industry park according to the acquired thermal monitoring data;
step S40, dividing the thermodynamic diagram into different thermodynamic grades, and respectively counting the thermodynamic distribution condition of each divided chemical engineering area according to the thermodynamic diagram;
step S50, generating a risk grade of the chemical industry park according to the counted data;
wherein the step S10 further includes the following sub-steps:
step A10, dividing a chemical industry park into a processing operation area, a product storage area and a living area;
step A20, dividing the processing operation area into a processing equipment concentration area and a transmission equipment concentration area, and setting a processing equipment risk parameter and a transmission equipment risk parameter for the processing equipment concentration area and the transmission equipment concentration area respectively;
step A30, dividing a product storage area into a product centralized storage area and a product transmission storage area, and setting a product centralized risk parameter and a product transmission risk parameter for the product centralized storage area and the product transmission storage area respectively;
step A40, setting living area risk parameters for a living area;
the step S30 further includes the following sub-steps:
step C10, substituting the processing equipment risk parameter, the transmission equipment risk parameter, the product centralized risk parameter, the product transmission risk parameter and the living area risk parameter into a chemical industry park basic risk formula to obtain a chemical industry park basic risk index;
step C20, when the basic risk index of the chemical industry park is less than or equal to the first basic risk threshold, setting the chemical industry park as a first-level risk monitoring park; when the basic risk index of the chemical industry park is larger than a first risk threshold value and smaller than or equal to a second risk threshold value, setting the chemical industry park as a secondary risk monitoring park; when the basic risk index of the chemical industry park is larger than a second risk threshold value, setting the chemical industry park as a third-level risk monitoring park;
the chemical industry park basic risk formula is configured as follows:
(ii) a The method comprises the following steps of A, acquiring a risk index of a chemical industry park, Cjjs, Ccscs, Ccpcs, Ccpf, Ccpc and f1, wherein Fhgj is a basic risk index of the chemical industry park, Cjjs is a risk parameter of processing equipment, Ccscs is a risk parameter of transmission equipment, Ccpf is a centralized risk parameter of products, Ccpc is a transmission risk parameter of products, Csf is a risk parameter of a living area, and f1 is a basic risk conversion coefficient;
the step S30 further includes the following sub-steps:
step C30, setting hexagons such as units as the minimum unit area of the thermodynamic diagram, and setting a plurality of thermodynamic grades according to the image generated by the thermodynamic diagram;
step C40, when the chemical industry park is a first-level risk monitoring park, when a thermodynamic diagram is drawn, and when images of two or more thermodynamic grades appear in any minimum unit area, the lowest thermodynamic grade is selected as the thermodynamic grade of the minimum unit area;
step C50, when the chemical industry park is a secondary risk monitoring park, when a thermodynamic diagram is drawn, and when two or more than two thermodynamic grade images appear in any minimum unit area, the thermodynamic grade with the largest area ratio is selected as the thermodynamic grade of the minimum unit area;
step C60, when the chemical industry park is a three-level risk monitoring park, when a thermodynamic diagram is drawn, and when images with two or more thermodynamic grades appear in any minimum unit area, the maximum thermodynamic grade is selected as the thermodynamic grade of the minimum unit area;
the step S40 includes the following sub-steps:
step D10, when the number of the minimum unit areas with different thermal levels of each area in the chemical industry park in the thermodynamic diagram is counted, when the minimum unit areas are simultaneously positioned in two or more areas, the areas are set as common thermal areas, and the common thermal areas can be calculated in any one area;
step D20, counting the number of minimum unit areas with different thermal grades in the processing equipment concentration area in the thermodynamic diagram, and respectively setting the minimum unit areas to be S1 jj-Snjj, wherein S1jj is the number of the minimum unit areas with the first thermal grade in the processing equipment concentration area in the thermodynamic diagram, and Snjj is the number of the minimum unit areas with the nth thermal grade in the processing equipment concentration area in the thermodynamic diagram;
step D30, counting the number of minimum unit areas with different thermal grades in the transmission equipment concentration area in the thermodynamic diagram, and respectively setting the minimum unit areas to be S1 cj-Sncj, wherein S1cj is the number of the minimum unit areas with the first thermal grade in the transmission equipment concentration area in the thermodynamic diagram, and Sncj is the number of the minimum unit areas with the nth thermal grade in the transmission equipment concentration area in the thermodynamic diagram;
step S40, counting the number of minimum unit areas with different thermal grades in the product centralized storage area in the thermodynamic diagram, and respectively setting the minimum unit areas to be S1 cc-Sncc, wherein S1cc is the number of the minimum unit areas with the first thermal grade in the product centralized storage area in the thermodynamic diagram, and Sncc is the number of the minimum unit areas with the nth thermal grade in the product centralized storage area in the thermodynamic diagram;
step S50, counting the number of minimum unit areas with different heat grades in the product transmission storage area in the thermodynamic diagram, and respectively setting the minimum unit areas to be S1 cf-Sncf, wherein S1cf is the number of the minimum unit areas with the first heat grade in the product transmission storage area in the thermodynamic diagram, and Sncf is the number of the minimum unit areas with the nth heat grade in the product transmission storage area in the thermodynamic diagram;
and step S60, counting the number of minimum unit areas of different heat levels in the life area in the thermodynamic diagram, and respectively setting the minimum unit areas to be S1 sf-Snsf, wherein S1sf is the number of the minimum unit areas of the first heat level in the life area in the thermodynamic diagram, and Snsf is the number of the minimum unit areas of the nth heat level in the life area in the thermodynamic diagram.
2. The method for monitoring and warning the trend of risk sources in the fixed space-time period of the chemical industry park as claimed in claim 1, wherein the step S50 comprises the following sub-steps:
step E10, substituting the number of minimum unit areas with different thermal power grades in the processing equipment concentration area in the thermodynamic diagram and the processing equipment risk parameters into a processing equipment concentration area risk formula to obtain a processing equipment concentration area risk index;
step E20, substituting the number of minimum unit areas with different thermal power grades in the transmission equipment concentration area in the thermodynamic diagram and the transmission equipment risk parameters into a transmission equipment concentration area risk formula to obtain a transmission equipment concentration area risk index;
step E30, substituting the number of minimum unit areas with different thermal power grades in the product centralized storage area in the thermodynamic diagram and the product centralized risk parameters into a product centralized storage area risk formula to obtain a product centralized storage area risk index;
step E40, substituting the number of minimum unit areas with different thermal power grades in the product transmission storage area in the thermodynamic diagram and the risk parameters of the processing equipment into a product transmission storage area risk formula to obtain a product transmission storage area risk index;
and E50, substituting the number of the minimum unit areas with different thermal grades in the living area in the thermodynamic diagram and the living area risk parameters into a living area risk formula to obtain a living area risk index.
3. The method as claimed in claim 2, wherein the risk source trend monitoring and early warning method for the chemical industry park with the fixed time-space period is characterized in that the risk formula of the processing equipment concentration area is configured as follows:
the risk formula of the transmission equipment concentration area is configured as follows:
the product centralized storage area risk formula is configured as follows:
the product transport storage area risk formula is configured to:
the living area risk formula is configured to:
4. The method for monitoring and warning the trend of risk sources in the fixed space-time period of the chemical industry park as claimed in claim 3, wherein the step S50 further comprises the following sub-steps:
step E60, substituting the risk index of the processing equipment concentration area, the risk index of the transmission equipment concentration area, the risk index of the product concentration storage area, the risk index of the product transmission storage area, the risk index of the living area and the basic risk index of the chemical industry park into a chemical industry park risk formula to obtain the risk index of the chemical industry park;
step E70, when the risk index of the chemical industry park is larger than or equal to the first risk threshold of the chemical industry park, outputting a first-level monitoring risk grade signal; when the risk index of the chemical industry park is greater than or equal to the risk threshold of the second chemical industry park and smaller than the risk threshold of the first chemical industry park, outputting a secondary monitoring risk grade signal; and when the risk index of the chemical industry park is smaller than the risk threshold of the second chemical industry park, outputting a three-level monitoring risk level signal.
5. The method according to claim 4, wherein the risk source trend monitoring and early warning method for the chemical industry park at the fixed time-space period is characterized in that the risk formula of the chemical industry park is configured as follows:
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210390121.6A CN114493381B (en) | 2022-04-14 | 2022-04-14 | Risk source trend monitoring and early warning method for fixed time-space period of chemical industry park |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210390121.6A CN114493381B (en) | 2022-04-14 | 2022-04-14 | Risk source trend monitoring and early warning method for fixed time-space period of chemical industry park |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114493381A CN114493381A (en) | 2022-05-13 |
| CN114493381B true CN114493381B (en) | 2022-06-17 |
Family
ID=81487444
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210390121.6A Active CN114493381B (en) | 2022-04-14 | 2022-04-14 | Risk source trend monitoring and early warning method for fixed time-space period of chemical industry park |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114493381B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115410346A (en) * | 2022-10-28 | 2022-11-29 | 北京融信数联科技有限公司 | Industrial park monitoring method and system and readable storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102033527A (en) * | 2010-10-11 | 2011-04-27 | 刘征涛 | Monitoring and stationing method of liquid environmental risk sources in chemical industrial park |
| CN103268109A (en) * | 2013-05-24 | 2013-08-28 | 常州大学 | Chemical industrial park risk management information system based on GIS |
| WO2019148788A1 (en) * | 2018-01-31 | 2019-08-08 | 中国矿业大学 | Method for preventing rock bursts by means of active support reinforcement and active pressure relief |
| CN111798127A (en) * | 2020-07-02 | 2020-10-20 | 北京石油化工学院 | Chemical industry park inspection robot path optimization system based on dynamic fire risk intelligent assessment |
| CN112163745A (en) * | 2020-09-17 | 2021-01-01 | 武汉大学 | Regional security risk analysis method and system based on combined model |
-
2022
- 2022-04-14 CN CN202210390121.6A patent/CN114493381B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102033527A (en) * | 2010-10-11 | 2011-04-27 | 刘征涛 | Monitoring and stationing method of liquid environmental risk sources in chemical industrial park |
| CN103268109A (en) * | 2013-05-24 | 2013-08-28 | 常州大学 | Chemical industrial park risk management information system based on GIS |
| WO2019148788A1 (en) * | 2018-01-31 | 2019-08-08 | 中国矿业大学 | Method for preventing rock bursts by means of active support reinforcement and active pressure relief |
| CN111798127A (en) * | 2020-07-02 | 2020-10-20 | 北京石油化工学院 | Chemical industry park inspection robot path optimization system based on dynamic fire risk intelligent assessment |
| CN112163745A (en) * | 2020-09-17 | 2021-01-01 | 武汉大学 | Regional security risk analysis method and system based on combined model |
Non-Patent Citations (1)
| Title |
|---|
| 开发园区多类型应急设施协同选址研究;孙立;《中国优秀博硕士学位论文全文数据库(硕士)社会科学Ⅰ辑(月刊)》;20200415;正文第32-40页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114493381A (en) | 2022-05-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109583680B (en) | Power stealing identification method based on support vector machine | |
| CN114493381B (en) | Risk source trend monitoring and early warning method for fixed time-space period of chemical industry park | |
| CN112216071A (en) | Intelligent chemical monitoring and early warning platform based on big data | |
| CN108733966A (en) | A kind of multidimensional electric energy meter field thermodynamic state verification method based on decision woodlot | |
| CN109459998A (en) | Steel manufacture process monitoring and alarming system and method | |
| CN107273234A (en) | A kind of time series data rejecting outliers and bearing calibration based on EEMD | |
| CN116739645A (en) | Order abnormity supervision system based on enterprise management | |
| CN112365186A (en) | Health degree evaluation method and system for electric power information system | |
| CN113536440A (en) | Data processing method based on BIM operation and maintenance management system | |
| CN112288298A (en) | Desulfurization system health condition evaluation method based on online data | |
| CN116703158A (en) | Risk assessment model construction method for imported food risk early warning | |
| CN116187885A (en) | Intelligent management system for grain and oil supply chain | |
| CN117353315B (en) | Device for controlling power generation voltage based on transient fluctuation of photovoltaic and wind power generation voltage | |
| CN108122059B (en) | Production risk identification method and automatic early warning system for pharmaceutical manufacturing enterprise | |
| CN110764043B (en) | Equipment quality condition evaluation method suitable for continuous measurement results | |
| CN116681307B (en) | River four-disorder supervision traceability display method and system based on multi-terminal fusion feedback | |
| CN117171176A (en) | Electricity consumption big data self-upgrading supervision platform based on artificial intelligence | |
| CN117217531A (en) | Factory safe operation risk data processing method based on artificial intelligence | |
| CN115222153B (en) | Low-carbon scheduling optimizing method and system for thermal power enterprises | |
| CN116664152A (en) | Supply chain full-flow node tracing system and method | |
| CN106650154B (en) | Nuclear power conventional island equipment reliability monitoring method based on thermal performance index | |
| CN116307700A (en) | Electric power system and risk assessment device and method thereof | |
| CN111413656B (en) | On-line monitoring and early warning method and system for metering process capability of automatic verification system | |
| CN103324154A (en) | Device and method for monitoring boilers | |
| CN118114187B (en) | Method, system, device and storage medium for detecting abnormal production line of flexible board |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |