A method and system for assessing the risk of production operations in a coastal area under the influence of sea fog

Abstract

The present application belongs to the technical field of sea fog risk assessment, and discloses a kind of coastal area production operation risk assessment method and system under the influence of sea fog, the method is by determining evaluation area and carrying out grid division, the grid resolution is calculated;Determine the type of production operation in grid, calculate the space-time density and weight of each operation;Calculate the weight of each level visibility in each grid, determine the visibility distribution characteristics of each grid;Divide the influence risk level of each level visibility on each type of production operation, determine the influence risk value of each level visibility on each type of production operation;Calculate the visibility risk degree value in each grid, obtain the spatial and temporal distribution of coastal area production operation risk degree under the influence of sea fog.The present application can provide basis for the organization and deployment of production operation by assessing the feasibility of different production operations in different regions under the influence of sea fog, and effectively assess the influence of sea fog on various production operations in the region.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of sea fog risk assessment, and particularly relates to a coastal area production operation risk assessment method and system under the influence of sea fog. BACKGROUND

[0002] The risk assessment of production operations in coastal areas is mostly for single offshore production operation risk assessment, such as offshore oil production, offshore wind power platform, offshore rescue and towing operation, etc. The existing sea fog risk assessment is based on the coastline distance, population density and road distribution, and does not consider the different needs of production operations in different seasons, nor does it consider the different influence degrees of sea fog in different seasons. In the existing sea fog risk assessment technology, only one level of visibility less than 1000 meters is considered for the weather phenomenon of sea fog, and the sensitivity of different production operations to different levels of visibility is not considered. At the same time, "fog day" is used as the minimum time unit and the county-level administrative region is used as the basic research unit, and the evaluation result is relatively rough, the precision is insufficient, and the data representativeness is low. In addition, the data used in the meteorological disaster risk assessment technology are mostly reanalysis grid data, which have low resolution and cannot accurately represent the real-time characteristics of meteorological elements in different regions.

[0003] Through the above analysis, the problems and defects of the prior art are that the current risk assessment of production operations in coastal areas is mostly for single offshore production operation risk assessment, and the existing sea fog risk assessment does not consider the different needs of production operations, nor does it consider the different influence degrees of sea fog in different seasons. At the same time, the data used in the existing evaluation method has low accuracy and precision, and cannot accurately reflect the influence degree of different levels of sea fog in different seasons on various production operations, and cannot give fine production deployment suggestions. SUMMARY

[0004] To overcome the problems in the related art, the present application discloses a coastal area production operation risk assessment method and system under the influence of sea fog, and the technical solution is as follows:

[0005] The present application is implemented as follows: the coastal area production operation risk assessment method under the influence of sea fog comprises:

[0006] S1, production operation distribution characteristic analysis: determine the evaluation area and perform grid division, calculate the grid resolution; determine the type of production operation in the grid, and calculate the spatio-temporal density and weight of each operation;

[0007] S2, visibility distribution feature extraction: calculate the weight of each level of visibility in each grid; calculate the product of the weight and the influence level to determine the visibility distribution characteristics of each grid in the evaluation area;

[0008] S3, risk level division: divide the risk level of each level of visibility to each type of production operation, obtain the risk level evaluation result, and determine the risk value of each type of production operation to each level of visibility;

[0009] S4, risk degree calculation and evaluation: calculate the risk degree value of each level of visibility in each month in each grid, and obtain the spatial and temporal distribution of the risk degree of the production operation in the coastal area under the influence of sea fog.

[0010] In step S1, the grid resolution is calculated, including:

[0011] The evaluation area is determined, the grid division of the evaluation area is determined according to the distribution density of the visibility observation station network, and the grid resolution D is calculated, and the expression is:

[0012]

[0013] In the formula, d min is the minimum distance between adjacent visibility observation stations, the grid center is the position of the visibility observation station, and the overlapping and blank parts of the grid are divided by the minimum distance connecting line of the adjacent grid boundaries.

[0014] In step S1, the spatio-temporal density of each operation is calculated, including:

[0015] The production operation distribution in each grid area is analyzed, the type and number n i of each type of production operation in the grid are determined, the spatial density S i of each type of operation is calculated, and the expression is:

[0016]

[0017] In the formula, i is the serial number of each type of production operation in the grid;

[0018] Each type of production operation is analyzed, the operation days a ij and the operation time b ij in each month in a year are determined, the operation time density s ij is calculated, and the expression is:

[0019] s ij = a ij × b ij

[0020] In the formula, j is the serial number of the month.

[0021] In step S1, the weight of each type of operation is calculated, and the expression is:

[0022]

[0023] In the formula, Gij The weight in the grid for each month for each industry is g, and the total number of jobs in the grid is N.

[0024] In step S2, the weight of each level of visibility in each grid is calculated, including:

[0025] The sea fog visibility site observation data is divided into 6 levels: no fog > 10 km, light fog 1-10 km, heavy fog 0.5-1 km, thick fog 0.2-0.5 km, strong thick fog 0.05-0.2 km, and very strong thick fog 0-0.05 km, with impact levels of 0, 1, 2, 3, 4, and 5 respectively.

[0026] Further, the calculation of the weight of each level of visibility in each grid includes:

[0027] By analyzing historical observation data, the weight of each level of visibility in each grid g is determined for each month. j ;

[0028]

[0029] In the formula, f j is the number of occurrences of single-level visibility for all stations in the grid in the hourly visibility observation data for each month, M j is the total amount of visibility data for all stations in the grid in each month.

[0030] In step S3, the impact risk level of each level of visibility on each type of production work is divided, including:

[0031] The impact risk of each level of visibility on each type of production work is set as: no impact, very small impact, small impact, strong impact, very strong impact, and unable to work, with risk levels of 0, 1, 2, 3, 4, and 5 respectively.

[0032] In step S3, the risk level assessment result is obtained, including:

[0033] A design expert scoring table is designed to investigate various types of production work, and the risk level assessment result of each level of visibility affecting this type of production work is obtained.

[0034] The average value of the scoring of the impact risk of all levels of visibility on this type of production work is taken as the impact risk value X i of each level of visibility on this type of production work.

[0035] In step S4, the risk degree calculation and evaluation, including:

[0036] According to the production work weight G ij , the visibility impact risk value X i , and the visibility weight g j, calculate the visibility risk degree value X of each type of production operation in each grid in each month at each level ij , the expression is:

[0037] X ij =G ij x x i x g j

[0038] The sum of the visibility risk values of all levels is calculated to obtain the spatial and temporal distribution of the production operation risk in the coastal area under the influence of sea fog.

[0039] Another purpose of the application is to provide a sea fog influenced coastal area production operation risk assessment system for regulating the sea fog influenced coastal area production operation risk assessment method, which comprises:

[0040] The production operation distribution characteristic analysis module is used to determine the evaluation area and carry out grid division, calculate the grid resolution; determine the type of production operation in the grid, calculate the spatio-temporal density and weight of each operation;

[0041] The visibility distribution characteristic extraction module is used to calculate the weight of each level of visibility in each grid; calculate the product of the weight and the influence level to determine the visibility distribution characteristics of each grid in the evaluation area;

[0042] The risk level division module is used to divide the influence risk level of each level of visibility, obtain the risk level evaluation result of each expert, and determine the influence risk value of this type of production operation on each level of visibility;

[0043] The risk degree calculation and evaluation module is used to calculate the visibility risk degree value of each grid in each month at each level, and finally obtain the spatial and temporal distribution of the production operation risk in the coastal area under the influence of sea fog

[0044] In combination with all the above technical solutions, the application has the following advantages and positive effects:

[0045] The application provides a sea fog risk assessment method for various production operations in a region and different levels of visibility influence risk, which can evaluate the risk generated by different levels of visibility on different production operations at different times, and provide more detailed reference for the arrangement of land and sea production operations in the coastal area. The application investigates and analyzes the spatial and temporal characteristics of the distribution of production operation types, multi-level visibility, and the influence risk of each level of visibility on various production operations, calculates the regional grid risk degree distribution, and thus gives the fine production operation risk under the influence of sea fog in the evaluation area, thereby providing a basis for annual production operation arrangement.

[0046] The method is a quantitative risk assessment method, which can evaluate the feasibility of different production operations in different regions under the influence of sea fog, provide basis for the organization and deployment of production operations, effectively evaluate the influence of sea fog on various production operations in the region, and strengthen the risk management of production operations in the season and region with frequent sea fog. Through the fine risk assessment products for various production operations, reference basis can be provided for the production industry in the sea fog affected area for production schedule arrangement, resource allocation, energy efficiency management, etc., which can effectively save production resources and improve production efficiency. The present application provides a fine weather disaster risk assessment method for coastal areas, provides a new regional division scheme for efficient use of high-precision observation data, and performs hierarchical risk assessment on a single weather disaster (sea fog). On the basis of the binary evaluation of risk "yes or no", the risk is quantified by level, which can provide risk assessment basis for the production industry to effectively avoid potential risks and effectively improve production efficiency in low-risk areas.

[0047] The present application quantifies the risk of sea fog on production operations, clearly indicates the potential risk of sea fog on some low-risk industries, for example, for the hoisting operation in the coastal port, the production enterprises generally believe that sea fog has no effect on their operation, but according to the investigation of the present application, when the visibility is less than 100 meters, it will have great risk to the overhead hoisting operation, therefore, for the sea fog phenomenon with the influence level of 5 (the highest level) in the present application, the risk level will also reach 5 (the highest level), and for the low-visibility phenomenon below level 4, the risk level is also low, therefore, in the coastal port area, the area with high visibility weight of level 5 needs to be cautious in arranging overhead hoisting operation in the month with high visibility risk value; in addition, the present method also provides basis for relaxing the production time limit of some high-impact industries of sea fog and improving production efficiency, for example, for the highway transportation industry in the sea fog frequent area, temporary speed limit or route adjustment is often carried out due to fog, and the investigation in the present method shows that the risk of high-speed driving is low for sea fog phenomenon with visibility influence level 0-2, and production adjustment is not needed to prevent reducing production efficiency. The present application quantifies the risk of different levels of sea fog on production operations at different times, improves the fineness of sea fog risk assessment, and overcomes the technical bias that there is no application effect for sea fog risk assessment in the past. BRIEF DESCRIPTION OF DRAWINGS

[0048] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure;

[0049] Figure 1 The present application provides a sea fog influenced coastal area production operation risk assessment method flow chart. DETAILED DESCRIPTION

[0050] In order to make the above objectives, characteristics and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application are described in detail below with reference to the drawings. In the following description, a large number of specific details are set forth in order to facilitate a thorough understanding of the present application. However, the present application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without departing from the spirit of the present application, so the present application is not limited to the specific implementations disclosed below.

[0051] The innovation of the present application is that the present application includes the spatial distribution and time characteristics of different levels of sea fog, calculates the risk degree of multi-level sea fog in space and time, and gives the spatial and temporal characteristics of the risk degree of multi-level sea fog for various production operations, providing more detailed reference for production operation arrangement. First, the grid division method makes full use of all visibility station observation data, and irregular grid division is performed according to the site distribution, so that the calculation result is more accurate. Second, the influence of multi-level low visibility on various operations is comprehensively calculated, and the influence degree of different types of production operations in different regions and at different times can be accurately given, providing detailed basis for the operation region and operation period arrangement of production operations.

[0052] In the embodiment 1 as shown in the table, the production operation risk assessment method under the influence of sea fog provided by the present application specifically includes the following steps: Figure 1

[0053] S1, production operation distribution characteristic analysis: determine the evaluation region and perform grid division, calculate the grid resolution; determine the type of production operation in the grid, calculate the space-time density and weight of each type of operation;

[0054] S2, visibility distribution characteristic extraction: calculate the weight of each level of visibility in each grid; calculate the product of the weight and the influence level, and determine the visibility distribution characteristics of each grid in the evaluation region;

[0055] S3, risk level division: divide the influence risk level of each level of visibility on each type of production operation, obtain the risk level assessment result, and determine the influence risk value of each type of production operation on each level of visibility;

[0056] S4, risk degree calculation and evaluation: calculate the risk degree value of each level of visibility in each month in each grid, and obtain the spatial and temporal distribution of the production operation risk degree in the coastal area under the influence of sea fog.

[0057] Taking the hoisting operation of a port in Jiaozhou Bay as an example, the position is located at the south side of Qingdao Subsea Tunnel,

[0058] ​S1, according to the distribution of visibility observation sites in Qingdao, the location is divided into a certain station grid (the distance between the station is about 6km); the distribution density of this kind of production operation in the grid is higher, about 15% according to the investigation; the operation time density is evenly distributed throughout the year, without seasonal variation, and the operation time density is about 36 hours per month; therefore, the weight of this industry in this grid is 5.4 per month.

[0059] S2, using the visibility observation data of a certain visibility per hour from 2015 to 2023, the visibility weight of six levels is calculated, and the results are shown in Table 1.

[0060] Table 1: Visibility weight of each level

[0061]

[0062] S3, for this industry, the expert scoring table 2 is designed.

[0063] Table 2: Expert scoring table

[0064]

[0065] Three experts were selected from the hoisting operation management personnel in the port area to score, and the average score is shown in Table 3.

[0066] Table 3: Expert scoring table

[0067]

[0068] S4, combined with the industry weight, the visibility weight and the visibility influence risk, the final calculation of the risk degree of the hoisting operation in the grid under the influence of sea fog is shown in Table 4.

[0069] Table 4: Operation risk degree time distribution table

[0070]

[0071] S1, production operation distribution characteristics investigation.

[0072] 1.1 Determine the evaluation area, determine the grid division of the evaluation area according to the distribution density of visibility observation data, calculate the grid resolution D, unit km:

[0073]

[0074] In the formula, d min is the minimum distance between adjacent visibility observation sites, the grid center is the position of the visibility observation site, and the overlapping and blank parts of the grid are divided by the minimum distance connecting line of the adjacent grid boundary.

[0075] The grid division method in this region is a dynamic grid division method based on the minimum distance dmin between visibility stations with irregular scattered distribution. The region is divided into grids of varying number and size. Areas without stations within a 20km*20km range are not gridded or evaluated.

[0076] The formula for calculating the grid resolution D is an original invention, which can dynamically divide the grid according to the distribution of visibility stations and can be applied to all visibility observation station data to the maximum extent.

[0077] 1.2 Investigate the distribution of production operations within each grid area to determine the types and quantities of each type of production operation within the grid. i Calculate the spatial density S for each type of operation. i The expression is:

[0078]

[0079] In the formula, i is the sequence number of each production operation within the grid;

[0080] Utilizing the space density S of each workspace i It can represent the distribution density of each production operation within the grid.

[0081] 1.3 Analyze each type of production operation to determine the number of operating days (a) for each month within the year. ij and homework duration b ij Calculate the task time density s ij The expression is:

[0082] s ij =a ij ×b ij

[0083] In the formula, j is the month number.

[0084] 1.4 Calculate the weight of each task using the following expression:

[0085]

[0086] In the formula, G ij Each month, each industry is assigned a weight within the grid, and N is the total number of job types within the grid; using the weight G... ij The combination of space and time represents the concentration of each production operation within the grid.

[0087] S2, Visibility distribution characteristics survey.

[0088] 2.1 According to Chinese standards, the visibility data of sea fog stations are divided into six levels: no fog >10km, light fog 1-10km, heavy fog 0.5-1km, dense fog 0.2-0.5km, very dense fog 0.05-0.2km, and extremely dense fog 0-0.05km, with impact levels of 0, 1, 2, 3, 4, and 5, respectively.

[0089] 2.2 Organize historical observation data and determine the visibility weight g for each level within each grid for each month. j ;

[0090]

[0091] In the formula, f j M represents the number of times a single level of visibility occurs at all stations within this grid each month in the hourly visibility observation data. j This represents the total visibility data for all stations within the grid each month.

[0092] Using the visibility weight g of each level within each grid in each month j It can represent the frequency of occurrence / impact frequency of low visibility phenomena at each level within the grid.

[0093] 2.3 Calculate the product of the weight and the influence level to determine the monthly visibility distribution characteristics of each grid in the assessment area.

[0094] S3, risk level classification.

[0095] 3.1 The impact risk of each level of visibility on each type of production operation is set into four levels: 0. No impact, 1. Very small impact, 2. Small impact, 3. Strong impact, 4. Very strong impact, 5. Operation impossible;

[0096] 3.2 Design an expert scoring sheet, conduct expert surveys on various production operations, and obtain each expert's risk level assessment results for each visibility level affecting that category of production operations;

[0097] 3.3 Take the average score of all experts for the visibility impact risk of this type of production operation at this level as the visibility impact risk value x of this type of production operation for each level.

[0098] S4, Risk Calculation and Assessment.

[0099] Based on production operation weight G ij Visibility impact risk value X i and visibility weight g j Calculate the visibility risk value X for each type of production operation within each grid at each level for each month. ij The expression is:

[0100] Xij = G ij x x i x g j

[0101] The sum of the visibility risk values of all levels is calculated to obtain the spatial and temporal distribution of the production operation risk degree of the coastal area under the influence of sea fog.

[0102] The method for calculating the visibility risk value using the three weights is first proposed.

[0103] In example 2, the production operation risk assessment system under the influence of sea fog provided by the present application comprises:

[0104] A production operation distribution feature analysis module is configured to determine an evaluation area and perform grid division, calculate a grid resolution, determine the types of production operations in the grid, and calculate the spatial and temporal density and weight of each operation;

[0105] A visibility distribution feature extraction module is configured to calculate the weight of each level of visibility in each grid, calculate the product of the weight and the influence level, and determine the visibility distribution feature of each grid in the evaluation area;

[0106] A risk level division module is configured to divide the influence risk level of each level of visibility, obtain the risk level assessment result of each expert, and determine the influence risk value of the type of production operation on each level of visibility.

[0107] A risk degree calculation and evaluation module is configured to calculate the risk degree value of each grid at each level of visibility in each month, and finally obtain the spatial and temporal distribution of the production operation risk degree of the coastal area under the influence of sea fog.

[0108] The above is only a preferred specific embodiment of the present application, but the protection scope of the present application is not limited thereto, and any modification, equivalent replacement and improvement made by those skilled in the art within the technical range disclosed by the present application, as long as it is within the spirit and principles of the present application, should be covered within the protection scope of the present application.

Claims

1. A method for assessing the risk of production operations in coastal areas under the influence of sea fog, characterized in that, The method comprises: S1, production operation distribution characteristic analysis: determining an evaluation area and performing grid division, calculating grid resolution; determining production operation types in the grid, calculating the spatio-temporal density and weight of each operation; S2, visibility distribution characteristic extraction: calculating the weight of each level of visibility in each grid; calculating the product of the weight and the influence level to determine the visibility distribution characteristic of each grid in the evaluation area; S3, risk level division: dividing the influence risk level of each level of visibility on each type of production operation to obtain a risk level evaluation result and determine the influence risk value of each type of production operation on each level of visibility; S4, risk degree calculation and evaluation: calculating the risk degree value of each level of visibility in each month in each grid to obtain the spatial and temporal distribution of the production operation risk degree in the coastal area under the influence of sea fog; In step S1, the grid resolution is calculated, including: Determine the evaluation area, according to the distribution density of the visibility observation station network, determine the grid division of the evaluation area, calculate the grid resolution The expression is: ； In the formula, is the minimum distance between adjacent visibility observation sites, the grid center is the position of the visibility observation site, and the blank part of the grid is divided by the minimum distance connecting line of the adjacent grid boundaries; In step S1, the spatio-temporal density of each operation is calculated, including: Analyze the distribution of production jobs within each grid region to determine the types of production jobs and the number of each type within the grid Calculate the spatial density of each type of job The expression is ； wherein is the serial number of each production job within the grid; Analyze each production job to determine the number of job days per month within the year and the length of the job Calculate the job time density expressed as: ； In the formula, is the month number; In step S1, the weight of each operation is calculated, and the expression is: ； wherein is the weight for each month for each industry within the grid, is the total number of job categories within the grid.

2. The risk assessment method for the production operation in the coastal area under the sea fog influence according to claim 1, characterized in that, In step S2, the weight of each level of visibility in each grid is calculated, including: The sea fog visibility site observation data is divided into six levels: no fog > 10 km, light fog 1-10 km, heavy fog 0.5-1 km, thick fog 0.2-0.5 km, strong thick fog 0.05-0.2 km, and extremely strong thick fog 0-0.05 km, and the influence levels are 0, 1, 2, 3, 4, and 5 respectively.

3. The risk assessment method for the production operation in the coastal area under the sea fog influence according to claim 2, characterized in that, The calculation of the weight of each level of visibility in each grid includes: Analyzing historical observation data to determine a visibility weight for each level within each grid for each month ; ； wherein is the number of occurrences of each single visibility class for all stations within the grid for each month of the hourly visibility observation data, is the total amount of visibility data for each month for all stations within the grid.

4. The risk assessment method for the production operation in the coastal area under the sea fog influence according to claim 1, characterized in that, In step S3, the influence risk level of each level of visibility on each type of production operation is divided, including: The influence risk of each level of visibility on each type of production operation is set as: no influence, very small influence, small influence, strong influence, very strong influence, and no operation, and the risk levels are 0, 1, 2, 3, 4, and 5 respectively.

5. The risk assessment method for the production operation in the coastal area under the sea fog influence according to claim 1, characterized in that, In step S3, the risk level evaluation result is obtained, including: A design expert scoring table is designed, and each type of production operation is investigated to obtain the risk level evaluation result of each level of visibility affecting the type of production operation; Taking the average value of the risk score of the influence of all levels of visibility on the production operation as the risk value of the influence of the production operation on each level of visibility .

6. The risk assessment method for the production operation in the coastal area under the sea fog influence according to claim 1, characterized in that, In step S4, the risk degree calculation and evaluation includes: According to the production job weight , the visibility impact risk value and the visibility weight , the visibility risk degree value of each type of production job in each level of visibility in each month in each grid is calculated , expressed as: ； The sum of the visibility risk values of all levels is calculated to obtain the spatial and temporal distribution of the production operation risk degree in the coastal area under the influence of sea fog.

7. A system for assessing the risk of production operations in coastal areas under the influence of sea fog, characterized in that it comprises: The system is used to control the sea fog influence under the coastal area production operation risk evaluation method according to any one of claims 1-6, and the system comprises: A production operation distribution characteristic analysis module is used to determine an evaluation area and perform grid division, calculate grid resolution; determine production operation types in the grid, calculate the spatio-temporal density and weight of each operation; An visibility distribution characteristic extraction module is used to calculate the weight of each level of visibility in each grid; calculate the product of the weight and the influence level to determine the visibility distribution characteristic of each grid in the evaluation area; A risk level division module is used to divide the influence risk level of each level of visibility, obtain the risk level evaluation result of each expert, and determine the influence risk value of each type of production operation on each level of visibility; The risk degree calculation and evaluation module is used for calculating the visibility risk degree value of each grid point in each month and each level, and finally obtaining the spatial and temporal distribution of the production operation risk degree of the coastal area under the influence of sea fog.

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