WO2024061122A1 - Method for assessing fire severity for non-metal material of railway vehicle - Google Patents

Abstract

A method for assessing fire severity for a non-metal material of a rail vehicle, which method is relates to the technical field of rail vehicles and aims to solve the technical problems of the accuracy of risk analysis being insufficient and it not being possible to properly guide fireproofing design work for vehicles due to the fact that technicians subjectively determine the severity of fire accidents which may have been caused by non-metal materials. The method comprises: establishing a target layer; performing screening to obtain a criterion layer, and determining, by using an analytic hierarchy process, influence weights of the criterion layer on the target layer and corresponding weight values; and obtaining the weight values of a specific mounting position of a mounting position and a specific material, and then performing dimensionless processing on same and calculating fire severity assessment values. By means of the method for assessing fire severity, a specific position which needs to be strengthened on a rail vehicle is obtained, thereby improving the overall fireproofing design performance of the rail vehicle.

Description

A fire severity assessment method for non-metallic materials in rail vehicles Technical field

The invention relates to a method for evaluating the fire severity of non-metallic materials of rail vehicles, and belongs to the technical field of rail vehicles.

Background technique

Whether the risk is acceptable is judged by estimating the frequency of hazard occurrence and the expected consequences of the accident (i.e. risk matrix). Existing rail vehicle fire risk analysis uses semi-quantitative analysis methods.

In the existing fire risk analysis technology for non-metallic materials in rail vehicles, qualitative methods are used to evaluate the severity of possible fire accidents, which are generally classified qualitatively according to casualties or property losses, for example: possible minor injuries. Injury; minor injury and/or secondary injury with significant impact on the environment; one death and/or multiple serious injuries and/or major injury with significant impact on the environment; multiple deaths and/or multiple serious injuries and/or catastrophic harm resulting in significant damage to the environment.

When designing and planning a rail vehicle project, the risk matrix format used in the project will be determined. During the design phase, designers will identify possible hazards on the vehicle and need to conduct a risk analysis on the possible hazards. Due to the current In the risk matrix, accident severity is classified qualitatively, so designers make subjective decisions about the severity of fire accidents that may be caused by non-metallic materials. The subjective judgment method used to identify the severity of accidents lacks quantitative basis, resulting in individual differences among different analysts, insufficient accuracy of risk analysis, and cannot guide vehicle fire protection design work well.

Contents of the invention

The object of the present invention is to overcome the deficiencies in the prior art and provide a rail vehicle non-metallic material fire The severity evaluation method quantitatively obtains the severity evaluation value of fire consequences by conducting weight analysis on the relevant properties of non-metallic materials that affect fire, combined with the properties of non-metallic materials of rail vehicles, and effectively improves the accuracy of fire risk assessment of non-metallic materials of rail vehicles. Spend.

In order to achieve the above objects, the present invention is achieved by adopting the following technical solutions:

The present invention provides a method for evaluating the severity of fire of non-metallic materials of rail vehicles, the method comprising:

Collect all non-metallic materials on rail vehicles; establish a target layer and select any collected non-metallic materials for testing after a fire;

Screen the criterion layer to determine the influencing factors of non-metallic materials, including exposure area s, installation location L, weight g, and material M; use the expert evaluation method to construct the influence matrix _A1 of the influencing factors of non-metallic materials listed in the criterion layer on the rail vehicle fire in the target layer, and obtain the weight set _wA1 of the influence of the influencing factors of non-metallic materials on the severity of the fire;

The criterion layer refines the program layer. The program layer includes: the specific installation position l subdivided by the installation position L and the specific material m subdivided by the material M. The expert evaluation method is used to construct a matrix A ₂ for the specific installation position factors. The material M of the criterion layer The specific material m factors are used to construct the matrix A ₃ , and the weight set w _A2 that the specific installation position l affects on the installation position factors in the criterion layer and the weight set w _A3 that the specific material affects the material factors in the criterion layer are obtained;

The values of the exposed area s and weight g of non-metallic materials in the criterion layer are dimensionally processed using the sum of squares normalization method; the weight set w _A2 of the specific installation position is used as the dimensionless value of the installation position, and the weight of the specific material is Set w _A3 as the dimensionless value of the material;

Calculate the fire severity evaluation value of the rail vehicle, and obtain the fire severity evaluation of the rail vehicle through the sum of the dimensionless values of each influencing factor of the non-metallic material and the product of w _A1 /w _A2 /w _A3 values, and sort the obtained fire severity evaluation values of rail vehicles to improve the overall fire protection design performance of rail vehicles.

Furthermore, the collection of non-metallic materials also includes information about the system to which the non-metallic material belongs, the name of the device and the material name of the non-metallic material.

Furthermore, in the program layer, the specific installation locations include inside the passenger compartment, above the roof, underframe and bogie, inside the driver's cabin and on the outer surface of the vehicle body. The specific materials include greasy non-metallic materials and non-greasy non-metallic materials.

Furthermore, the influence weight of the criterion layer on the target layer is determined. The specific process includes:

Combined with the analytic hierarchy process proportional scale table, a pairwise comparison is made through the exposure area, material weight, installation position, and material's impact scale on fire. a _ij represents the comparison result of the i-th factor of non-metallic materials relative to the j-th factor. , where a _ij =1/a _ji ; define the pairwise comparison matrix A ₁ =(a _ij ) _n1×n1 , and obtain the following pairwise comparison matrix:

Calculate the normalized feature vector b _i : Obtain the weight vector w _iA1 : (where the matrix order n1=4);

It can be obtained that w _iA1 = {0.59, 0.28, 0.08, 0.05}; w _1A1 = 0.59; w _2A1 = 0.28; w _3A1 = 0.08; w _4A1 = 0.05;

Carry out consistency check and calculate the maximum characteristic root λ _A1 of matrix A ₁ =4.25; consistency index CI _A1 =(λ _A1 -n ₁ )/(n ₁ -1)=0.08 (where n ₁ =4);

When n ₁ = 4, the random consistency RI = 0.9, CI _A1 /RI < 0.1, the consistency test is passed, and each impact is obtained The weight values of factors affecting fire severity: exposure area weight w _1A1 = 0.59; weight weight w _2A1 = 0.28; location weight w _3A1 = 0.08; material weight w _4A1 = 0.05.

Further, determine the impact weight of the scheme layer on the criterion layer. The specific process includes:

Combined with the analytic hierarchy process proportional scale table, a pairwise comparison was made on the scale of the impact of the installation position on the fire degree through the specific installation positions in the passenger compartment, above the roof, underframe and bogie, driver's compartment, and on the outer surface of the car body. c _ij represents the comparison result of the i-th factor with respect to the j-th factor, where c _ij =1/c _ji ; define the pairwise comparison matrix A ₂ =(c _ij ) _n2×n2 , and obtain the following pairwise comparison matrix A ₂ :

Combined with the proportional scale table of the analytic hierarchy process, a pairwise comparison of the influence scale of the material level on the fire degree was carried out through grease and non-grease. d _ij represents the comparison result of the i-th factor relative to the j-th factor, where d _ij = 1 /d _ji ; define the pairwise comparison matrix A ₃ = (d _ij ) _n3×n3 , and obtain the following pairwise comparison matrix:

Calculate the normalized eigenvector (weight vector) for matrix A ₂ weight vector

(where n ₂ =5); we can get w _A2 ={0.48,0.04,0.1,0.3,0.05};

Calculate the normalized eigenvector (weight vector) for matrix A ₃ weight vector

(where n ₃ =2) we can get w _A3 ={0.875,0.125};

Conduct consistency check: calculate the maximum eigenvalue λ _A2 of matrix A ₂ = 5.44, and calculate the maximum eigenvalue λ _A3 = 2 of matrix A ₃ ;

consistency index

When checking n ₂ = 5, the random consistency RI = 1.14; CIA2/RI (n2 = 5) < 0.1, the consistency test passes, CI _A3 = 0, the consistency test passes;

After consistency testing, the weight values are as follows:

Among the specific location factors: w _{inside the passenger compartment} = 0.48, w _{above the roof} = 0.04, w _{underframe and bogie} = 0.1, w _{inside the driver's cab} = 0.3, w _{outer surface of the car body} = 0.05; among the material factors: w _grease = 0.875, w _non-grease = 0.125.

Furthermore, the numerical values of the influencing factors of non-metallic materials in the criterion layer and scheme layer are processed in a dimensionless manner:

The values of the exposed area s _γ , material weight g _γ , installation position L _γ , and material M _γ of any required evaluation of non-metallic material γ are subjected to dimensionless processing, and the corresponding dimensionless processing values are marked as s _γ ' , g _γ ', l _γ ', m _γ ',

l _γ ′＝w _{specific installation position} ; m _γ ′＝w _{grease/non-grease} .

Furthermore, the fire severity evaluation value of non-metallic materials of rail vehicles is h _γ :
h _γ =s _γ ′×w _s +g _γ ′×w _g +l _γ ′×w _L +m _γ ′×w _M

Compared with the prior art, the beneficial effects achieved by the present invention are:

The invention provides a method for evaluating the fire severity of non-metallic materials on rail vehicles. The target layer is established as the non-metallic materials on the rail vehicle, and the criterion layer of non-metallic materials is screened out to find out the influencing factors for judging the severity of the fire. After analytic hierarchy process, matrix construction and dimensionless processing, the fire severity evaluation value of rail vehicles is obtained; quantitatively obtaining the fire consequence severity evaluation value can effectively improve the accuracy of fire risk assessment of non-metallic materials of rail vehicles, and based on The evaluation value sorting situation can be used to determine the systems and components that need to be focused on in the fire protection design of rail vehicles to improve the overall fire protection design of rail vehicles. able.

Description of drawings

FIG1 is a flow chart of a method for evaluating the severity of fire of non-metallic materials of rail vehicles provided by the present invention.

Detailed ways

This evaluation method measures the weight and exposed area of the non-metallic materials used in each system equipment on the rail vehicle, and records their installation position and specific material information on the vehicle. The non-metallic material fire hazard assessment of each system component is constructed through the analytic hierarchy process. Severity rating. The Analytical Hierarchy Process is a commonly used method for problem decision-making in operations research. This method decomposes the relevant elements of the decision-making problem into levels such as goals, criteria, plans, etc. The scale of the Analytical Hierarchy Process is as shown below, t _ij represents the i-th The comparison result of the factor relative to the jth factor, where t _ij =1/t _ji ; define the pairwise comparison matrix T = (t _ij )n _× n, and use the method of solving the eigenvector of the pairwise comparison matrix to obtain each The priority weight of each element at one level to an element at the previous level is then hierarchically merged into the final weight of each remark scheme to the final target by weighted summation. When determining the weights between factors at each level, the consistent matrix method is used, that is, various factors are compared with each other to improve accuracy.

It should be understood that when used in this specification and the appended claims, the term "comprises" indicates The presence of described features, integers, steps, operations, elements and/or components does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and/or sets thereof.

It should also be understood that the terminology used in the specification of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this specification and the appended claims, the singular forms "a", "an" and "the" are intended to include the plural forms unless the context clearly dictates otherwise.

It will be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items. .

Example 1:

This embodiment provides a method for evaluating the fire severity of non-metallic materials in rail vehicles, as shown in Figure 1. The method includes:

First, collect all non-metallic materials included on the rail vehicle, including relevant information such as the system to which the non-metallic material belongs, the name of the equipment, and the material name of the non-metallic material. The system to which it belongs and the name of the equipment are used to evaluate the impact on fire. Larger systems and equipment are positioned to further formulate fire risk management and control measures, including setting up fire detection devices at specific locations, changing the materials of currently used non-metallic materials to non-metallic materials with better smoke and fire resistance, etc. Secondly, construct an analytic hierarchy process model, which includes three levels: the target layer, and the criterion layer under the target layer. The program layer is located under the principles layer.

Establish a target layer and select any non-metallic material from all collected non-metallic materials as an evaluation reference object to evaluate the severity of rail vehicle fires for testing.

At the screening criterion layer, select and clarify the various influencing factors of non-metallic materials on rail vehicles. The selected influencing factors include exposed area s, installation position L, weight g, and material M. and passed expert evaluation Method to construct the impact matrix A ₁ of the exposed area s, installation position L, weight g, and material M of the non-metallic materials listed in the criterion layer on the rail vehicle in the target layer after the fire.

Referring to the proportional scale table of the Analytical Hierarchy Process and using a questionnaire, five rail vehicle fire protection experts conducted a pairwise comparison of the exposed area, material weight, installation location, and material's impact on fire. a _ij represents non-metallic materials. The comparison result of the i-th factor with respect to the j-th factor, where a _ij =1/a _ji ; define the pairwise comparison matrix A ₁ = (a _ij ) _n1×n1 , and obtain the following pairs of four influencing factors Compare matrix A ₁ :

The weight set w _iA1 of the influence factors of non-metal material exposed area s, installation position L, weight g and material M on fire severity is: w _iA1 = {exposed area weight value w _1A1 , weight weight value w _2A1 , position weight Value w _3A1 , material weight value w _4A1 }.

And after normalized feature vector b _i : Obtain the weight vector w _iA2 : (where the matrix order n1=4).

It can be obtained that w _iA1 = {0.59, 0.28, 0.08, 0.05}; w _1A1 = 0.59; w _2A1 = 0.28; w _3A1 = 0.08; w _4A1 = 0.05; w _iA1 represents the weight of the i-th influencing factor in the A1 matrix, according to The ranking of each influencing factor in the criterion layer is that the weight of the first influencing factor (exposure area) in the A1 matrix is w _1A1 = 0.59; the weight of the second influencing factor (material weight) in the A1 matrix is w _2A1 = 0.28; the weight of the third influencing factor in the A1 matrix is w 1A1 = 0.28. The weight of the first influencing factor (installation position) is w _3A1 = 0.08; the weight of the fourth influencing factor (material) in the A1 matrix is w _4A1 = 0.05.

And conduct consistency test, calculate the maximum characteristic root λ _A1 =4.25 of matrix A ₁ ; consistency index CI _A1 = (λ _A1 -n ₁ )/(n ₁ -1) = 0.08 (where n ₁ =4);

When n ₁ = 4, the random consistency RI = 0.9, CI _A1 /RI < 0.1, the consistency test is passed, and the weight value of each influencing factor on the fire severity is obtained, that is, the exposure area weight w _1A1 = 0.59; weight weight ; w _2A1 = 0.28; position weight w _3A1 = 0.08; material weight w _4A1 = 0.05.

The criterion layer is refined into a plan layer. The solution layer includes a specific installation location l subdivided by the installation location L and a specific material m subdivided by the material M. The specific installation locations include inside the passenger compartment, above the roof, underframe and bogie, inside the driver's cabin and on the outer surface of the vehicle body.

The specific materials subdivided include greasy non-metallic materials and non-greasy non-metallic materials. The expert evaluation method is used to construct a matrix A ₂ for the specific installation position factors, and a matrix A ₃ is constructed based on the specific material m factors of the material M in the criterion layer. The weight set w _A2 = { w _{inside the passenger compartment} , w _{above the roof} , w _{underframe and bogie} , w _{inside the cab} , w _{outside surface of the car body} }; the weight set of the influence of specific materials on the material factors in the criterion layer is w _A3 = {w _grease , w _non-grease }.

Determine the impact weight of the scheme layer on the criterion layer. The specific process is as follows:

Combined with the analytic hierarchy process proportion scale table, the specific installation positions in the passenger compartment, above the roof, underframe and bogie, driver's compartment, and outer surface of the car body were compared in pairs on the scale of the impact of the installation position on the fire extent, c _ij represents the comparison result of the i-th factor with respect to the j-th factor, where c _ij =1/c _ji ; define the pairwise comparison matrix A ₂ =(c _ij ) _n2×n2 , and obtain the following pairwise comparison matrix A ₂ :

And by referring to the analytic hierarchy process proportion scale table, a pairwise comparison is made between grease and non-grease on the scale of the impact of the material level on the fire extent. d _ij represents the comparison result of the i-th factor relative to the j-th factor, where d _ij =1/d _ji ; define the pairwise comparison matrix A ₃ =(d _ij ) _n3×n3 , and obtain the following pairwise comparison matrix:

Calculate the normalized eigenvector (weight vector) for matrix A ₂ weight vector

(where n ₂ =5); we can get w _A2 ={0.48,0.04,0.1,0.3,0.05};

Calculate the normalized eigenvector (weight vector) for matrix A ₃ weight vector

Among them, n ₃ =2, we can get w _A3 ={0.875,0.125}.

And conduct a consistency test: calculate the maximum characteristic root λ _A2 = 5.44 of matrix A ₂ , calculate the maximum characteristic root λ _A3 = 2 of matrix A ₃ ; consistency index

When checking n ₂ =5, random consistency RI = 1.14; CIA2/RI (n2 = 5) < 0.1, the consistency test passes, CI _A3 = 0, the consistency test passes;

After consistency testing, the weight values are as follows:

Among the specific location factors: w _{inside the passenger compartment} = 0.48, w _{above the roof} = 0.04, w _{chassis and bogie} = 0.1, w _{inside the driver's cabin} = 0.3, w _{car body outer surface} = 0.05; among the material factors: w _grease = 0.875, w _non-grease = 0.125.

Due to the different unit systems used for the weight and exposed area of non-metallic materials, the specific location and specific material are qualitative descriptions. In order to facilitate the establishment of mathematical models of evaluation indicators, the influencing factors are dimensionally treated, and the non-metallic materials in the criterion layer are The exposed area s and weight g are dimensionally processed using the sum of squares normalization method; the weight set w _A2 of the specific installation location in the scheme layer is used as the non-dimensional value of the installation location and the weight set w _A3 of the specific material. As a dimensionless value of the material.

The numerical values of influencing factors of non-metallic materials in the criterion layer and scheme layer are dimensionally processed as follows:

The values of the exposed area s _γ , material weight g _γ , installation position L _γ , and material M _γ of any required evaluation of non-metallic material γ are subjected to dimensionless processing, and the corresponding dimensionless processing values are marked as s _γ ' , g _γ ', l _γ ', m _γ ':

l _γ ′＝w _{specific installation position} ; m _γ ′＝w _{grease/non-grease} .

The fire severity evaluation value of the rail vehicle is calculated by the sum of the product of the dimensionless value of each influencing factor of the non-metallic material and the weight value. The fire severity evaluation value of the non-metallic material of the rail vehicle is h _γ according to the dimensionless value of each influencing factor and the weight value of each influencing factor:
h _γ =s _γ ′×w _s +g _γ ′×w _g +l _γ ′×w _L +m _γ ′×w _M ;

The obtained fire severity evaluation values of rail vehicles are sorted, and the systems and components that need to be focused on in the fire protection design of rail vehicles are obtained. The fire severity of specific locations in the ranking is compared to help improve the overall fire protection design performance of rail vehicles. .

Example 2:

Using the fire severity evaluation method for rail vehicle non-metallic materials in Example 1, combined with the actual situation, it is assumed that a certain urban rail vehicle new construction project collects non-metallic material information as follows:

Referring to the dimensionless processing in Embodiment 1, the following table can be drawn:

Combining the above two tables, the fire severity evaluation value of rail vehicles is h _γ formula:
h _γ =s _γ ′×w _s +g _γ ′×w _g +l _γ ′×w _L +m _γ ′×w _M
h ₁ =0.5065×0.59+0.9886×0.28+0.48×0.08+0.125×0.05=0.620293
h ₂ =0.0119×0.59+0.0069×0.28+0.05×0.08+0.125×0.05=0.019203
h ₃ =0.0043×0.59+0.0006×0.28+0.1×0.08+0.125×0.05=0.009755
h ₄ =0.0003×0.59+0.0059×0.28+0.3×0.08+0.125×0.05=0.032079
h ₅ =0.8621×0.59+0.1289×0.28+0.48×0.08+0.125×0.05=0.589381
h ₆ =0×0.59+0.0774×0.28+0.1×0.08+0.875×0.05=0.073422

It can be seen from the calculation results that h1 and h5 have the highest fire severity evaluation values, which means that the fire consequences of non-metallic materials such as floor cloth and air-conditioning ducts are the most serious. In the design stage, it is necessary to focus on the above-mentioned floor cloth and air-conditioning ducts. Fireproof performance, but also pay attention to the fireproof design of the vehicle around other equipment mentioned above.

Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media that include computer-usable program code.

These computer program instructions may also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.

The above are only preferred embodiments of the present invention. It should be noted that those of ordinary skill in the art can also make several improvements and modifications without departing from the technical principles of the present invention. These improvements and modifications It should also be regarded as the protection scope of the present invention.

Claims (7)

1. A method for evaluating the fire severity of non-metallic materials in rail vehicles, characterized in that the method includes:

   Collect all non-metallic materials on rail vehicles; establish a target layer and select any collected non-metallic materials for testing after a fire;

   Screen the criterion layer to determine the influencing factors of non-metallic materials. The influencing factors include exposed area s, installation position L, weight g, and material M. The expert evaluation method is used to construct the influence factors of non-metallic materials listed in the criterion layer on the target layer track. The influence matrix A ₁ after the vehicle fire is used to obtain the weight set w _A1 of the impact of various influencing factors of non-metallic materials on the severity of the fire;

   The criterion layer refines the program layer. The program layer includes: the specific installation position l subdivided by the installation position L and the specific material m subdivided by the material M. The expert evaluation method is used to construct a matrix A ₂ for the specific installation position factors. The material M of the criterion layer The specific material m factors are used to construct the matrix A ₃ , and the weight set w _A2 that the specific installation position l affects on the installation position factors in the criterion layer and the weight set w _A3 that the specific material affects the material factors in the criterion layer are obtained;

   The values of the exposed area s and weight g of non-metallic materials in the criterion layer are dimensionally processed using the sum of squares normalization method; the weight set w _A2 of the specific installation position is used as the dimensionless value of the installation position, and the weight of the specific material is Set w _A3 as the dimensionless value of the material;

   Calculate the fire severity evaluation value of the rail vehicle, and obtain the fire severity evaluation value of the rail vehicle through the sum of the dimensionless values of each influencing factor of the non-metallic material multiplied by w _A1 /w _A2 /w _A3 , and The obtained fire severity evaluation values of rail vehicles are sorted to improve the overall fire protection design performance of rail vehicles.
2. A method for evaluating the fire severity of non-metallic materials in rail vehicles according to claim 1, The characteristic is that the collection of non-metallic materials also includes information about the system to which the non-metallic material belongs, the name of the equipment and the material name of the non-metallic material.
3. A method for evaluating the fire severity of non-metallic materials in rail vehicles according to claim 1, characterized in that in the scheme layer, the specific installation locations include inside the passenger compartment, above the roof, underframe and bogie, in the driver's room and on the vehicle. External surface, specific materials include greasy non-metallic materials and non-greasy non-metallic materials.
4. A method for evaluating the fire severity of non-metallic materials in rail vehicles according to claim 3, characterized in that the influence weight of the criterion layer on the target layer is determined, and the specific process includes:

   Combined with the analytic hierarchy process proportion scale table, a pairwise comparison is made through the exposure area, material weight, installation position, and material's impact scale on fire. a _ij represents the comparison result of the i-th factor of non-metallic materials relative to the j-th factor. , where a _ij =1/a _ji ; define the pairwise comparison matrix A ₁ =(a _ij ) _n1×n1 , and obtain the following pairwise comparison matrix:
   

   Calculate the normalized feature vector b _i : Obtain the weight vector w _iA1 : (where the matrix order n1=4);

   It can be obtained that w _iA1 ={0.59,0.28,0.08,0.05};

   Conduct a consistency test and calculate the maximum eigenvalue of matrix A ₁ λ _A1 = 4.25; the consistency index CI _A1 = (λ _A1 -n ₁ )/(n ₁ -1) = 0.08 (where n ₁ = 4);

   When n ₁ = 4, the random consistency RI = 0.9, CI _A1 /RI < 0.1, the consistency test is passed, and the weight value of each influencing factor on the fire severity is obtained: exposure area weight w _1A1 = 0.59; weight weight w _2A1 = 0.28; position weight w _{3A1 =} 0.08; material weight w _4A1 = 0.05.
5. A method for evaluating the severity of fires in non-metallic materials of rail vehicles according to claim 4, characterized in that determining the impact weight of the scheme layer on the criterion layer, the specific process includes:

   Combined with the analytic hierarchy process proportional scale table, a pairwise comparison was made on the scale of the impact of the installation position on the fire degree through the specific installation positions in the passenger compartment, above the roof, underframe and bogie, driver's compartment, and on the outer surface of the car body. c _ij represents the comparison result of the i-th factor with respect to the j-th factor, where c _ij =1/c _ji ; define the pairwise comparison matrix A ₂ =(c _ij ) _n2×n2 , and obtain the following pairwise comparison matrix A ₂ :
   

   Combined with the proportional scale table of the analytic hierarchy process, a pairwise comparison of the influence scale of the material level on the fire degree was carried out through grease and non-grease. d _ij represents the comparison result of the i-th factor relative to the j-th factor, where d _ij = 1 /d _ji ; define the pairwise comparison matrix A ₃ = (d _ij ) _n3×n3 , and obtain the following pairwise comparison matrix:
   

   Calculate the normalized eigenvector (weight vector) for matrix A ₂ weight vector (where n ₂ =5); we can get w _A2 ={0.48,0.04,0.1,0.3,0.05};

   Calculate the normalized eigenvector (weight vector) for matrix A ₃ weight vector (where n ₃ =2) we can get w _A3 ={0.875,0.125};

   Conduct consistency check: calculate the maximum eigenvalue λ _A2 of matrix A ₂ = 5.44, and calculate the maximum eigenvalue λ _A3 = 2 of matrix A ₃ ;

   consistency index

   When n ₂ = 5, random consistency RI = 1.14;

   CIA2/RI(n2=5)<0.1, the consistency test passes; CI _A3 =0, the consistency test passes;

   After consistency testing, the weight values are as follows:

   Among the specific location factors: w _{inside the passenger compartment} = 0.48, w _{above the roof} = 0.04, w _{underframe and bogie} = 0.1, w _{inside the cab} = 0.3, w _{outside surface of the car body =} 0.05;

   Among the material factors: w _grease = 0.875, w _non-grease = 0.125.
6. The method for evaluating the severity of fire of non-metallic materials in rail vehicles according to claim 5 is characterized in that the numerical values of the influencing factors of non-metallic materials in the criterion layer and the scheme layer are dimensionally processed in the following manner:

   The values of the exposed area s _γ , material weight g _γ , installation position L _γ , and material M _γ of any required evaluation of non-metallic material γ are subjected to dimensionless processing, and the corresponding dimensionless processing values are marked as s _γ ' , g _γ ', l _γ ', m _γ ', l _γ ′＝w _{specific installation position} ; m _γ ′＝w _{grease/non-grease} .
7. A method for evaluating the fire severity of non-metallic materials of rail vehicles according to claim 6, characterized in that the fire severity evaluation value of non-metallic materials of the rail vehicle is h _γ :
   h _γ =s _γ ′×w _s +g _γ ′×w _g +l _γ ′×w _L +m _γ ′×w _M .