Railway and rail transit project noise influence evaluation system based on CAD

Abstract

The invention discloses a railway and rail transit project noise influence evaluation system based on CAD, and relates to the technical field of environmental protection engineering, and the system comprises the steps: obtaining rail transit project information and source intensity information; capturing and identifying the rail transit project information and the source intensity information to obtain capturing and identifying information, and optimizing and adjusting the capturing and identifying information to obtain optimizing and adjusting information; taking the optimization adjustment information as an input parameter, and obtaining a noise contribution value prediction result table based on a noise prediction model; the background noise and the noise contribution value prediction result are superposed to obtain a target noise value, the target noise value is evaluated to obtain a noise influence evaluation result, the processing method is high in accuracy, the manual operation time is greatly shortened, the coping efficiency of repeated work caused by project adjustment is higher, automatic drawing output can be achieved, and the processing efficiency is improved. And the working efficiency and accuracy of design and environmental impact evaluation and analysis are improved.

Description

Technical Field

[0001] The present application relates to the field of environmental engineering technology, and in particular to a CAD-based noise impact assessment system for railway and rail transit projects. Background Art

[0002] With the development of the transportation industry, the implementation of linear projects such as high-speed railways, intercity railways, urban railways and various types of rail transit has brought about more and more traffic convenience while also having an increasingly prominent impact on the acoustic environment along the lines. In order to control the noise impact of such projects, the environmental impact assessment report is currently mainly used to evaluate them and implement the noise reduction measures proposed.

[0003] For the preparation of environmental impact assessment reports, there are many sensitive points along the rail transit and railway projects, the on-site investigation cycle is long, and the workload is heavy. At present, most of them prepare Excel calculation sheets according to the acoustic environment assessment guidelines for noise prediction and noise mitigation measures analysis, and also need to use independent noise prediction software to draw isoacoustic level diagrams. Therefore, the preparation of environmental impact assessment report prediction sheets has always had the pain points of large manual intervention and low work efficiency. During the preparation process, repeated work often occurs due to project adjustments, resulting in errors and omissions.

[0004] The above contents are only used to assist in understanding the technical solution of the present application and do not constitute an admission that the above contents are prior art. Summary of the invention

[0005] The main purpose of this application is to provide a CAD-based railway and rail transit project noise impact assessment system, aiming to solve the technical problems in the prior art of the preparation of prediction calculation sheets based on environmental impact assessment reports, which have always been plagued by large amounts of manual intervention and low work efficiency.

[0006] To achieve the above objectives, the present application proposes a CAD-based railway and rail transit project noise impact assessment method, the CAD-based railway and rail transit project noise impact assessment method comprising:

[0007] Obtain rail transit project information and source strength information;

[0008] Capturing and identifying the rail transit project information and the source strength information to obtain captured identification information, and optimizing and adjusting the captured identification information to obtain optimized adjustment information;

[0009] Using the optimization adjustment information as an input parameter, obtaining a noise contribution value prediction result based on a noise prediction model;

[0010] The background noise is superimposed on the noise contribution value prediction result to obtain a target noise value, and the target noise value is evaluated to obtain a noise impact evaluation result.

[0011] In one embodiment, the engineering demolition information is obtained according to the rail transit or railway project information;

[0012] Based on the engineering demolition information, the plane outline and noise-sensitive building information of the noise-sensitive building in the topographic map are captured;

[0013] Identify the plane outline and noise-sensitive building information of the noise-sensitive building to obtain captured identification information;

[0014] The captured identification information is detected, and when the captured identification information is abnormal, the captured identification information is optimized and adjusted to obtain optimized adjustment information.

[0015] In one embodiment, identification factors are determined, and the plane outline and noise-sensitive building information of the noise-sensitive building are preliminarily identified based on the identification factors to obtain preliminary sensitive point building information;

[0016] Merging the preliminary sensitive point building information to obtain a preliminary sensitive point table;

[0017] Based on the positional relationship between the preliminary sensitive point table and the track line, hierarchical identification is performed to obtain noise distribution points;

[0018] The captured identification information is obtained according to the noise distribution points and the plane outline of the noise-sensitive building.

[0019] In one embodiment, the initial information parameters of the line configuration are determined and defined, and the information is optimized and adjusted through the house extraction and house analysis functions, and the configured source strength, train type, formation, speed, and train logarithm data are combined as input parameters for noise prediction;

[0020] Noise prediction is performed on the input parameters based on the noise prediction model to obtain a noise contribution value prediction result.

[0021] In one embodiment, a noise contribution value prediction result table is retrieved according to the background noise and the noise contribution value prediction result;

[0022] Determine the daytime noise contribution value and nighttime noise contribution value of the sensitive point according to the noise contribution value prediction result table;

[0023] The daytime noise contribution value and the nighttime noise contribution value are respectively superimposed with the daytime background value and the nighttime background value to obtain an environmental noise prediction table;

[0024] The target noise value is determined according to the environmental noise prediction table, and the target noise value is evaluated against a benchmark to obtain a noise impact evaluation result.

[0025] In one embodiment, a final measure table is obtained based on the defined basic principles of measures according to the noise impact assessment result;

[0026] A CAD format measure plan drawing with a standard frame size is generated based on the final measure table, and the measure plan drawing is exported as a PDF format atlas.

[0027] In one embodiment, the rail transit or railway project information includes the predicted line master plan, broken link table, bridge table, tunnel table, slope table, station table, train model and vehicle formation information, driving organization information, topographic map of a certain range on both sides of the line, red line of engineering demolition range, and acoustic environment functional area segmentation table. The source strength information includes the source strength information of bridge sections and ground sections under corresponding boundary conditions listed in the inspection reports and guiding documents currently issued by relevant national departments, the source strength information of bridge sections and ground sections under corresponding boundary conditions measured in currently operating railway and rail transit projects, and the source strength information of bridge sections and ground sections of test sections under corresponding boundary conditions provided by manufacturers.

[0028] In addition, to achieve the above purpose, the present application also proposes a CAD-based railway and rail transit project noise impact assessment device, the CAD-based railway and rail transit project noise impact assessment device comprising:

[0029] Database module, used to obtain rail transit project information and source strength information;

[0030] An information capture and identification module, used to capture and identify the rail transit project information and the source strength information to obtain captured identification information, and optimize and adjust the captured identification information to obtain optimized adjustment information;

[0031] A noise prediction module, used to use the optimization adjustment information as an input parameter and obtain a noise contribution value prediction result based on a noise prediction model;

[0032] The noise evaluation module is used to superimpose the background noise with the noise contribution value prediction result to obtain a target noise value, and to perform a benchmark evaluation on the target noise value to obtain a noise impact evaluation result.

[0033] In addition, to achieve the above-mentioned purpose, the present application also proposes a CAD-based railway and rail transit project noise impact assessment device, the device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the CAD-based railway and rail transit project noise impact assessment method as described above.

[0034] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the CAD-based railway and rail transit project noise impact assessment method as described above are implemented.

[0035] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, it implements the steps of the CAD-based railway and rail transit project noise impact assessment method as described above.

[0036] One or more technical solutions proposed in the present application have at least the following technical effects: obtaining rail transit project information and source strength information; capturing and identifying the rail transit project information and the source strength information to obtain captured identification information, and optimizing and adjusting the captured identification information to obtain optimized adjustment information; using the optimized adjustment information as input source strength, and obtaining a noise contribution value prediction result table and background noise based on a noise prediction model; superimposing the background noise with the noise contribution value prediction result to obtain a target noise value, and evaluating the target noise value to obtain a noise impact evaluation result. This processing method has high accuracy and greatly reduces manual operation time. It is also more efficient in dealing with repetitive work caused by project adjustments, and can realize automatic drawing, thereby improving the work efficiency and accuracy of design, environmental impact assessment and analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0038] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0039] Figure 1 A flow chart of the first embodiment of the noise impact assessment method for railway and rail transit projects based on CAD provided in this application;

[0040] Figure 2 This is a schematic diagram of the module structure of a CAD-based railway and rail transit project noise impact assessment device according to an embodiment of the present application;

[0041] Figure 3 This is a schematic diagram of the equipment structure of the hardware operating environment involved in the CAD-based railway and rail transit project noise impact assessment method in the embodiment of the present application.

[0042] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0043] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0044] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0045] The main solution of the embodiment of the present application is: obtaining rail transit project information and source strength information; capturing and identifying the rail transit project information and the source strength information to obtain captured identification information, and optimizing and adjusting the captured identification information to obtain optimized adjustment information; using the optimized adjustment information as an input parameter to obtain a noise contribution value prediction result based on a noise prediction model; superimposing the background noise with the noise contribution value prediction result to obtain a target noise value, benchmarking and evaluating the target noise value to obtain a noise impact evaluation result.

[0046] In this embodiment, for ease of description, the following description is made by taking the identification of CAD-based railway and rail transit project noise impact assessment equipment as the execution subject.

[0047] Due to the large number of sensitive points along the rail transit and railway projects, the long on-site investigation cycle and heavy workload, at present, most of them are based on the acoustic environment assessment guidelines to compile Excel calculation sheets for noise prediction and noise mitigation measures analysis, and also need to use independent noise prediction software to draw isoacoustic level diagrams. Therefore, the preparation of environmental impact assessment report prediction calculation sheets has always been a pain point of large manual intervention and low work efficiency. During the preparation process, repeated work often occurs due to project adjustments, resulting in errors and omissions.

[0048] This application provides a solution in which only part of the information and requirements are input, and the correction and adjustment process is manually operated. If the project is adjusted later, the database can be directly overwritten, and the repetitive work is small, which greatly reduces the time cost. According to the module calculation and a small amount of manual correction, the acoustic monitoring plan along the line can be directly obtained, which shortens the internal work time of the environmental impact assessment. In the absence of monitoring data, based on the prediction of the noise contribution value, the impact of the project implementation on the surrounding sound environment can be preliminarily understood, which can be used to guide the design work in the early stages of the design. The noise distribution map can be automatically drawn, and the sound barrier / soundproof window measure plan can be automatically drawn, which improves the work efficiency of the draftsman and reduces the possibility of errors and omissions.

[0049] It can be seen from the above embodiments that the present application obtains rail transit or railway project information and source strength information; captures and identifies the rail transit or railway project information and the source strength information to obtain capture identification information, and optimizes and adjusts the capture identification information to obtain optimization adjustment information; uses the optimization adjustment information as an input parameter to obtain a noise contribution value prediction result based on a noise prediction model; superimposes the background noise with the noise contribution value prediction result to obtain a target noise value, and benchmarks and evaluates the target noise value to obtain a noise impact evaluation result. This processing method has high accuracy and greatly reduces manual operation time. It is also more efficient in dealing with repetitive work caused by project adjustments, and can realize automatic drawing, thereby improving the work efficiency and accuracy of design, environmental impact assessment and analysis.

[0050] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a CAD-based railway and rail transit project noise impact assessment device, etc. The following takes the CAD-based railway and rail transit project noise impact assessment device as an example to illustrate this embodiment and the following embodiments.

[0051] Based on this, the embodiment of the present application provides a CAD-based railway and rail transit project noise impact assessment method, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the CAD-based railway and rail transit project noise impact assessment method of the present application.

[0052] In this embodiment, the CAD-based railway and rail transit project noise impact assessment method includes steps S10 to S40:

[0053] Step S10, obtaining rail transit project information and source strength information.

[0054] It should be noted that rail transit project information includes but is not limited to the predicted line master plan, broken chain table, bridge table, tunnel table, slope table, station table, train model and vehicle formation information, driving organization information, topographic map of a certain range on both sides of the line (including noise-sensitive buildings), red line of project demolition range, and acoustic environment functional area segmentation table. Source strength information includes the source strength information of bridge sections and ground sections under the corresponding boundary conditions listed in the test reports and guidance documents currently issued by relevant national departments; it also includes the source strength information of bridge sections and ground sections under the corresponding boundary conditions measured in the currently operating railway and rail transit projects; it also includes the source strength information of bridge sections and ground sections of the test sections under the corresponding boundary conditions provided by the manufacturer.

[0055] It should be understood that noise-sensitive buildings refer to buildings used for living, scientific research, medical care, culture and education, office work for government agencies and groups, social welfare, etc. The red line of the project demolition scope refers to the scope of house acquisition and demolition determined due to the implementation of the project. The topographic map of a certain range on both sides of the line should include but not be limited to information such as ground elevation, building plan projection map and number of building floors, names of sensitive points, etc. The segmentation table of acoustic environment functional zones refers to the segmentation table sorted along the line mileage according to the local acoustic functional zone division and other relevant information.

[0056] In the specific implementation, when obtaining rail transit or railway project information and source strength information, the rail transit project information and source strength information can be obtained through the project information component and the source strength information component in the database module. The source strength information component can continuously supplement and improve the line form, bridge form, vehicle type, vehicle axle weight, vehicle speed, turning radius, and roadbed form of the corresponding boundary conditions based on the information source it contains. The measured source strength information should also include information on the administrative district where the test is located. The line forms are mainly bridges, roadbeds, and tunnels. The bridge forms are mainly box girders without baffles, box girders with baffles, and U-shaped beams. The roadbed forms are mainly ballasted roadbeds and ballastless roadbeds.

[0057] Step S20, capturing and identifying the rail transit project information and the source strength information to obtain captured identification information, and optimizing and adjusting the captured identification information to obtain optimized adjustment information.

[0058] In the specific implementation, the information capture and identification module includes an information capture and identification component and a correction and adjustment component. The sensitive point information capture component includes three parts: sensitive point information capture, sensitive point identification, and correction and adjustment. After obtaining the rail transit project information and source strength information from the database module, it can be captured and identified to obtain the captured identification information. When capturing, the plane outline of the noise-sensitive building in the topographic map can be captured according to the requirements of the input line range on both sides, and represented in the topographic map using predefined colors. Then, the captured noise-sensitive building is identified based on the identification factors to obtain the captured identification information, and then the captured information is optimized and adjusted. Specifically, the manual adjustment window provided by the correction and adjustment component can be used to operate in the preliminary sensitive point table formed by the identification component. The sensitive points can be further merged, split, deleted, mileage corrected, name corrected, distance corrected, elevation corrected, etc. according to the actual situation on site to obtain the final sensitive point table.

[0059] In a feasible implementation manner, the step of identifying the plane outline and noise-sensitive building information of the noise-sensitive building to obtain captured identification information includes:

[0060] Determine identification factors, and preliminarily identify the plane outline and noise-sensitive building information of the noise-sensitive building based on the identification factors to obtain preliminary sensitive point building information;

[0061] Merging the preliminary sensitive point building information to obtain a preliminary sensitive point table;

[0062] Based on the positional relationship between the preliminary sensitive point table and the track line, hierarchical identification is performed to obtain noise distribution points;

[0063] The captured identification information is obtained according to the noise distribution points and the plane outline of the noise-sensitive building.

[0064] In the specific implementation, the process of identifying the plane outline and noise-sensitive building information of noise-sensitive buildings can be described as follows: according to the input line range requirements on both sides, combined with the red line of the project demolition range of the project information component in the database module, the plane outline of the noise-sensitive building in the topographic map is captured, and the plane outline is marked with a defined color in the topographic map to determine the sensitive point information. When capturing the sensitive point information, the name information, location information, the nearest ground elevation information, the roof elevation information, the number of floors and other information of the captured noise-sensitive building plane outline in the database module are also included. The input line range requirements on both sides are the evaluation range of this project, that is, the maximum horizontal distance from the center line of the outer track of the line (i.e., the center line of the left or right line). The sensitive point identification component further identifies the sensitive point information processed by the information capture component, and identifies it according to factors such as distribution, location, name, and building characteristics to form a preliminary sensitive point house. The identification factors include but are not limited to the corresponding number of floors and location information of the plane outline of the evaluation building in the database module. The extracted preliminary sensitive point houses are analyzed and calculated, including but not limited to mileage analysis, horizontal distance from the line, height difference from the track surface, sensitive point name analysis, acoustic environment functional area analysis, number of floors analysis, etc. After the house analysis is completed, the sensitive point houses are merged, and the merged sensitive points are given a unified name in the preliminary sensitive point table. After the sensitive points are generated, the nearest building in the first row facing the line and the nearest building in the first row facing the line in different functional areas in the back row are taken to arrange the noise monitoring / prediction points in layers. The layered layout rules can be customized, and the noise points can also be arranged manually. The noise point layout logic is: the nearest building in the first row is the plane outline of the noise-sensitive building with the closest horizontal distance to the line among the merged sensitive points at this location, and it is marked with a defined color in the topographic map. The nearest building in the first row facing the line in the back row is: the nearest building outside the boundary line of the next functional area in the merged sensitive points at this location; and it is marked with a defined color in the topographic map. The next order of functional area boundary refers to: the next sequence line of Class 4b or Class 4a in the functional area boundary where the sensitive point is located in the database, that is, if there is only Class 2 area, the next order of functional area boundary is to take the nearest noise-sensitive building plane outline outside the Class 2 area line and mark it with a defined color in the topographic map. The functional areas are arranged in the order of Class 4b>Class 4a>Class 3>Class 2>Class 1>Class 0, and the higher order functional area is taken for the overlapping functional areas. If the evaluated building is higher than 2 floors, it is necessary to make a layered point prediction, and fixed or indefinite interval floors can be selected according to the requirements.

[0065] Step S30: taking the optimization adjustment information as an input parameter and obtaining a noise contribution value prediction result based on a noise prediction model.

[0066] It should be noted that the input parameters are selected by comparing the project information group in the database module with the line type, bridge type, vehicle type, vehicle axle weight, vehicle speed, line straight or curve radius, roadbed type and other information in the source strength information component through the project information component and the source strength selection component, and the appropriate parameters are selected as the prediction input parameters. The priority of the parameter selection comparison information can be manually defined in the above comparison information.

[0067] In the specific implementation, the noise prediction module includes a source strength selection component and a calculation component. The calculation component can generate a background noise monitoring plan and a noise contribution value prediction result table based on the final sensitive point table using its built-in acoustic prediction calculation method. The principle of the noise prediction model is the built-in acoustic prediction calculation method, which can perform acoustic predictions based on the input source strength information to obtain a noise contribution value prediction result table and background noise. Among them, the built-in acoustic prediction calculation method is an acoustic prediction calculation method entered in accordance with relevant national requirements, specifications and guidelines. It can calculate emission noise and environmental noise, as well as calculate the length and height of the sound barrier taken at the line at the excessive sensitive point according to the corresponding conditions of the specified sound barrier measures.

[0068] In a feasible implementation manner, the step of using the optimization adjustment information as an input parameter and obtaining a noise contribution value prediction result based on a noise prediction model includes:

[0069] Determine and define the initial information parameters of the line configuration, optimize and adjust the information through functions such as house extraction and house analysis, and combine the configured source strength, train type, formation, speed, number of train pairs and other data as input parameters for noise prediction;

[0070] Noise prediction is performed on the input parameters based on the noise prediction model to obtain a noise contribution value prediction result.

[0071] In the specific implementation, the noise prediction model is used to predict the noise of the input parameters. According to the acoustic prediction calculation method recorded in the relevant national requirements, specifications and guidelines, the emission noise and environmental noise can be calculated, and the length and height of the sound barrier taken at the line at the sensitive point where the standard is exceeded can be calculated according to the corresponding conditions of the specified sound barrier measures. The corresponding conditions of the specified sound barrier measures are that when the background noise exceeds the standard, if the corresponding daytime environmental noise and nighttime environmental noise are greater than the daytime and nighttime standard values, sound barrier measures need to be taken; when the background noise exceeds the standard, according to the recorded incremental requirements, if the daytime increase and the nighttime increase exceed the incremental requirements, sound barrier measures need to be taken. Background noise does not exceed the standard refers to the situation where the daytime and nighttime background noise are both less than the daytime and nighttime standard values. When the background noise exceeds the standard, it means that the daytime and nighttime background noise are greater than the daytime and nighttime standard values, and the incremental requirement refers to the maximum limit of the difference between the predicted value of environmental noise and the predicted value of background noise at the same point. In addition, the daytime increase refers to the difference between the predicted value of daytime environmental noise and the background noise value at the same point, which can be expressed as:

[0072] Δ 昼间 =n 环境噪声预测值 -n 背景噪声值

[0073] The night increase refers to the difference between the predicted value of ambient noise at night and the predicted value of background noise at the same point, which can be expressed as:

[0074] Δ 夜间 =n 环境噪声预测值 -n 背景噪声值

[0075] The background noise monitoring program includes but is not limited to the name of the sensitive point, the starting point of the mileage pile number of the corresponding line, the end point of the mileage pile number of the corresponding line, the floor information of the sensitive point, the horizontal distance from the line, the height difference from the track surface, the functional area information of the sensitive point, and the location of the measuring point. The emission noise contribution value prediction result includes but is not limited to the starting point of the mileage pile number of the corresponding line, the end point of the mileage pile number of the corresponding line, the floor information of the sensitive point, the horizontal distance from the line, the height difference from the track surface, the functional area information of the sensitive point, the vehicle speed, the daytime noise emission value, the nighttime noise emission value, the daytime standard value, the nighttime standard value, the daytime excess, and the nighttime excess. The daytime standard value and the nighttime standard value are the noise values ​​that meet the requirements of the functional area based on the information of the sensitive point functional area. The daytime excess is the daytime noise emission value minus the daytime standard value. The nighttime excess is the nighttime noise emission value minus the nighttime standard value.

[0076] Step S40, superimposing the background noise with the noise contribution value prediction result to obtain a target noise value, performing a benchmark evaluation on the target noise value to obtain a noise impact evaluation result.

[0077] It should be noted that the target noise value refers to the noise value obtained by superimposing the background noise and the noise result, while the noise impact assessment result refers to the impact of the current noise value on the surrounding environment.

[0078] In the specific implementation, the environmental noise prediction and measures module includes prediction and measures components, which can superimpose the background noise and noise contribution value prediction results, superimpose the background noise of the same sensitive point during the day with the daytime noise contribution value, and superimpose the background noise of the same sensitive point at night with the nighttime noise contribution value, and obtain the daytime environmental noise prediction value and the nighttime environmental noise prediction value respectively. After superposition, the target noise value can be obtained, and the target noise value can be compared with the standard noise value to determine the relationship between the current target noise value and the standard noise value, and then obtain the evaluation result of the impact of noise on the environment.

[0079] In a feasible implementation manner, the steps of superimposing the background noise with the noise contribution value prediction result to obtain a target noise value, evaluating the target noise value, and obtaining a noise impact evaluation result include:

[0080] According to the noise contribution value prediction result, retrieve the noise contribution value prediction result table;

[0081] Determine the daytime noise contribution value and nighttime noise contribution value of the sensitive point according to the noise contribution value prediction result table;

[0082] The daytime background noise and the nighttime background noise are respectively superimposed with the daytime noise contribution value and the nighttime noise contribution value to obtain an environmental noise prediction table;

[0083] The target noise value is determined according to the environmental noise prediction table, and the target noise value is evaluated against a benchmark to obtain a noise impact evaluation result.

[0084] In the specific implementation, the prediction and measures component will enter the background noise data after monitoring according to the background noise monitoring scheme obtained by the automatic point placement and emission noise prediction module, call the emission noise contribution value prediction result table in the automatic point placement and emission noise prediction module, and superimpose the daytime background noise and nighttime background noise of the corresponding sensitive point with their daytime noise contribution value and nighttime noise contribution value respectively, so as to obtain the environmental noise prediction table and the final measures table. The environmental noise prediction table includes but is not limited to the starting point of the mileage pile number of the corresponding line, the end point of the mileage pile number of the corresponding line, the floor information of the sensitive point, the horizontal distance from the line, the height difference from the track surface, the functional area information of the sensitive point, the vehicle speed, the daytime noise emission value, the nighttime noise emission value, the daytime environmental noise prediction value, the nighttime environmental noise prediction value, the daytime standard value, the nighttime standard value, the daytime environmental noise excess, and the nighttime environmental noise excess. The superposition is the superposition calculation in the built-in acoustic prediction calculation method of the calculation component. The daytime environmental noise prediction value is obtained by superimposing the daytime background noise and the daytime noise emission value of the same sensitive point. The nighttime environmental noise prediction value is obtained by superimposing the nighttime background noise and the nighttime noise emission value of the same sensitive point. The daytime excess of environmental noise is the predicted value of the daytime environmental noise at the same sensitive point minus the daytime standard value. The nighttime excess of environmental noise is the predicted value of the nighttime environmental noise at the same sensitive point minus the nighttime standard value. The final measures table includes but is not limited to the name of the sensitive point, the starting point of the mileage pile number of the corresponding line, the end point of the mileage pile number of the corresponding line, the floor information of the sensitive point, the horizontal distance from the line, the height difference from the track surface, the functional area information of the sensitive point, the speed, the daytime noise emission value, the nighttime noise emission value, the daytime environmental noise predicted value, the nighttime environmental noise predicted value, the daytime standard value, the nighttime standard value, the daytime increase, the nighttime increase, the daytime excess of environmental noise, the nighttime excess of environmental noise, the mileage pile number starting point of the corresponding line of the sound barrier, the mileage pile number end point of the corresponding line of the sound barrier, and the height of the sound barrier.

[0085] In a feasible implementation manner, the background noise is superimposed on the noise contribution value prediction result to obtain a target noise value, and the target noise value is benchmarked and evaluated to obtain the noise impact evaluation result, and the step further includes:

[0086] Obtain a final measures table based on the noise impact assessment results;

[0087] A CAD format measure plan drawing with a standard frame size is generated based on the final measure table, and the measure plan drawing is exported as a PDF format atlas.

[0088] In a specific implementation, the environmental noise prediction and measures module also includes a drawing output component, which can automatically generate a CAD format measure plan drawing of a standard frame size according to the final measures table, and can choose to automatically export a PDF format atlas.

[0089] The present embodiment provides a CAD-based noise impact assessment method for railway and rail transit projects, which obtains rail transit project information and source strength information; captures and identifies the rail transit project information and the source strength information to obtain capture identification information, and optimizes and adjusts the capture identification information to obtain optimization adjustment information; uses the optimization adjustment information as an input parameter to obtain a noise contribution value prediction result table based on a noise prediction model; superimposes the monitored background noise with the noise contribution value prediction result to obtain a target noise value, and benchmarks and evaluates the target noise value to obtain a noise impact assessment result. The processing method has high accuracy and greatly reduces manual operation time. It is also more efficient in dealing with repeated work caused by project adjustments, and can realize automatic drawing, thereby improving the work efficiency and accuracy of design, environmental impact assessment and analysis.

[0090] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the CAD-based railway and rail transit project noise impact assessment method of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0091] This application also provides a CAD-based railway and rail transit project noise impact assessment device, please refer to Figure 2 The CAD-based railway and rail transit project noise impact assessment device comprises:

[0092] Database module 10, used to obtain rail transit project information and source strength information;

[0093] The information capture and identification module 20 is used to capture and identify the rail transit project information and the source strength information to obtain captured identification information, and optimize and adjust the captured identification information to obtain optimized adjustment information;

[0094] A noise prediction module 30, configured to use the optimization adjustment information as an input parameter and obtain a noise contribution value prediction result based on a noise prediction model;

[0095] The noise evaluation module 40 is used to superimpose the background noise with the noise contribution value prediction result to obtain a target noise value, and evaluate the target noise value to obtain a noise impact evaluation result.

[0096] The CAD-based railway and rail transit project noise impact assessment device provided by the present application adopts the CAD-based railway and rail transit project noise impact assessment method in the above-mentioned embodiment, which can solve the technical problems in the prior art that the preparation of the prediction calculation sheet based on the environmental impact assessment report has always been subject to large manual intervention and low work efficiency. Compared with the prior art, the beneficial effects of the CAD-based railway and rail transit project noise impact assessment device provided by the present application are the same as the beneficial effects of the CAD-based railway and rail transit project noise impact assessment method provided by the above-mentioned embodiment, and the other technical features of the CAD-based railway and rail transit project noise impact assessment device are the same as the features disclosed in the above-mentioned embodiment method, which will not be repeated here.

[0097] The present application provides a CAD-based railway and rail transit project noise impact assessment device, and the CAD-based railway and rail transit project noise impact assessment device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the CAD-based railway and rail transit project noise impact assessment method in the above-mentioned embodiment one.

[0098] Reference below Figure 3 , which shows a schematic diagram of the structure of a CAD-based railway and rail transit project noise impact assessment device suitable for implementing the embodiment of the present application. The CAD-based railway and rail transit project noise impact assessment device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions: tablet computers), PMPs (Portable Media Players: portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 3 The CAD-based railway and rail transit project noise impact assessment device shown is merely an example and should not bring any limitation to the functions and scope of application of the embodiments of the present application.

[0099] like Figure 3As shown, the CAD-based railway and rail transit project noise impact assessment device may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the CAD-based railway and rail transit project noise impact assessment device are also stored. The processing device 1001, ROM1002, and RAM1004 are connected to each other via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 1009. The communication device 1009 can allow the CAD-based railway and rail transit project noise impact assessment device to communicate wirelessly or wired with other devices to exchange data. Although the figure shows a CAD-based railway and rail transit project noise impact assessment device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have alternatively.

[0100] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0101] The CAD-based railway and rail transit project noise impact assessment device provided by the present application adopts the CAD-based railway and rail transit project noise impact assessment method in the above-mentioned embodiment, which can solve the technical problems of large manual intervention and low work efficiency in the preparation of prediction calculation sheets based on environmental impact assessment reports in the prior art. Compared with the prior art, the beneficial effects of the CAD-based railway and rail transit project noise impact assessment device provided by the present application are the same as the beneficial effects of the CAD-based railway and rail transit project noise impact assessment method provided by the above-mentioned embodiment, and the other technical features of the CAD-based railway and rail transit project noise impact assessment device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0102] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0103] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0104] The present application provides a computer-readable storage medium having computer-readable program instructions (i.e., computer programs) stored thereon, and the computer-readable program instructions are used to execute the CAD-based railway and rail transit project noise impact assessment method in the above-mentioned embodiment.

[0105] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0106] The above-mentioned computer-readable storage medium may be included in the CAD-based railway and rail transit project noise impact assessment device; or it may exist independently without being assembled into the CAD-based railway and rail transit project noise impact assessment device.

[0107] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the CAD-based railway or rail transit project noise impact assessment device, the CAD-based railway or rail transit project noise impact assessment device:

[0108] Obtain rail transit project information and source strength information;

[0109] Capturing and identifying the rail transit project information and the source strength information to obtain captured identification information, and optimizing and adjusting the captured identification information to obtain optimized adjustment information;

[0110] Using the optimization adjustment information as an input parameter, a noise contribution value prediction result table is obtained based on a noise prediction model;

[0111] The background noise is superimposed on the noise contribution value prediction result to obtain a target noise value, and the target noise value is evaluated to obtain a noise impact evaluation result.

[0112] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0113] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a sequence different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0114] The modules involved in the embodiments of the present application may be implemented by software or hardware, wherein the name of the module does not limit the unit itself in some cases.

[0115] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned CAD-based railway and rail transit project noise impact assessment method, which can solve the technical problems of large manual intervention and low work efficiency in the preparation of prediction calculation sheets based on environmental impact assessment reports in the prior art. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the CAD-based railway and rail transit project noise impact assessment method provided by the above-mentioned embodiment, and will not be repeated here.

[0116] The present application also provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the above-mentioned CAD-based railway and rail transit project noise impact assessment method.

[0117] The computer program product provided by this application can solve the technical problems in the prior art that the preparation of prediction calculation sheets based on environmental impact assessment reports has always been subject to large manual intervention and low work efficiency. Compared with the prior art, the beneficial effects of the computer program product provided by this application are the same as the beneficial effects of the CAD-based railway and rail transit project noise impact assessment method provided in the above embodiment, and will not be repeated here.

[0118] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A CAD-based noise impact assessment method for railway and rail transit projects, characterized in that: The CAD-based railway and rail transit project noise impact assessment method includes: Obtain rail transit project information and source strength information; The rail transit project information and the source strength information are captured and identified to obtain captured identification information, and the captured identification information is optimized and adjusted to obtain optimized adjustment information; Using the optimization adjustment information as an input parameter, obtaining a noise contribution value prediction result based on a noise prediction model; The background noise is superimposed on the noise contribution value prediction result to obtain a target noise value, and the target noise value is evaluated to obtain a noise impact evaluation result.

2. The method according to claim 1, characterized in that The steps of capturing and identifying the rail transit project information and the source strength information to obtain captured identification information, and optimizing and adjusting the captured identification information to obtain optimized adjustment information include: Obtaining engineering demolition scope information according to the rail transit project information; Based on the engineering demolition scope information, the plane outline and noise-sensitive building information of the noise-sensitive building in the topographic map are captured; Identify the plane outline and noise-sensitive building information of the noise-sensitive building to obtain captured identification information; The captured identification information is detected, and when the captured identification information is abnormal, the captured identification information is optimized and adjusted to obtain optimized adjustment information.

3. The method according to claim 2, characterized in that The step of identifying the plane outline and noise-sensitive building information of the noise-sensitive building to obtain captured identification information comprises: Determine identification factors, and preliminarily identify the plane outline and noise-sensitive building information of the noise-sensitive building based on the identification factors to obtain the horizontal distance of the sensitive point building from the line, the mileage range, and the height difference with the track surface; Merging the preliminary sensitive point building information to obtain a preliminary sensitive point table; Based on the positional relationship between the preliminary sensitive point table and the track line, hierarchical identification is performed to obtain noise distribution points; The captured identification information is obtained according to the noise distribution points and the plane outline of the noise-sensitive building.

4. The method according to claim 1, characterized in that The step of using the optimization adjustment information as an input parameter and obtaining a noise contribution value prediction result based on a noise prediction model comprises: Determine and define the initial information parameters of the line configuration, optimize and adjust the information through the housing extraction and housing analysis functions, and combine the configured source strength, train type, formation, speed, and train logarithm data as input parameters for noise prediction; The noise contribution value prediction result is obtained by performing noise prediction on the input source strength based on the noise prediction model.

5. The method according to claim 1, characterized in that The step of superimposing the background noise with the noise contribution value prediction result to obtain a target noise value, and evaluating the target noise value to obtain a noise impact evaluation result comprises: Retrieving a noise contribution value prediction result table according to the noise contribution value prediction result; Determine the daytime noise contribution value and nighttime noise contribution value of the sensitive point according to the noise contribution value prediction result table; The daytime noise contribution value and the nighttime noise contribution value are respectively superimposed with the daytime background value and the nighttime background value to obtain an environmental noise prediction table; The target noise value is determined according to the environmental noise prediction table, and the target noise value is evaluated against a benchmark to obtain a noise impact evaluation result.

6. The method according to claim 1, characterized in that After the step of superimposing the background noise with the noise contribution value prediction result to obtain a target noise value, and performing benchmark evaluation on the target noise value to obtain a noise impact evaluation result, the following step further comprises: According to the noise impact assessment results, a final measure table is obtained based on the defined basic principles of measures; A CAD format measure plan drawing with a standard frame size is generated based on the final measure table, and the measure plan drawing is exported as a PDF format atlas.

7. The method according to claim 1, characterized in that The rail transit project information includes the predicted line master plan, broken chain table, bridge table, tunnel table, slope table, station table, train model and vehicle formation information, driving organization information, topographic map of a certain range on both sides of the line, red line of engineering demolition range, and segmentation table of acoustic environment functional areas. The source strength information includes the source strength information of bridge sections and ground sections under the corresponding boundary conditions listed in the inspection reports and guiding documents currently issued by relevant national departments, the source strength information of bridge sections and ground sections under the corresponding boundary conditions actually measured in the currently operating railway and rail transit projects, and the source strength information of bridge sections and ground sections of the test sections under the corresponding boundary conditions provided by the manufacturer.

8. A CAD-based noise impact assessment device for railway and rail transit projects, characterized in that: The device comprises: Database module, used to obtain rail transit project information and source strength information; An information capture and identification module, used to capture and identify the rail transit project information and the source strength information to obtain captured identification information, and optimize and adjust the captured identification information to obtain optimized adjustment information; A noise prediction module, used to use the optimization adjustment information as an input parameter and obtain a noise contribution value prediction result based on a noise prediction model; The noise evaluation module is used to superimpose the background noise with the noise contribution value prediction result to obtain a target noise value, evaluate the target noise value, and obtain a noise impact evaluation result.

9. A CAD-based noise impact assessment device for railway and rail transit projects, characterized in that: The device comprises: a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the CAD-based railway and rail transit project noise impact assessment method as described in any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the CAD-based railway and rail transit project noise impact assessment method as described in any one of claims 1 to 7 are implemented.

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