A method for extracting seat body pressure simulation results

Abstract

The invention discloses a method for extracting seat body pressure simulation results, which belongs to the technical field of automobile ergonomics. The method comprises the following steps: opening a seat body pressure simulation result cloud map in a finite element post-processing module, intercepting the body pressure cloud maps of a seat cushion and a backrest; obtaining the planarized cloud map in the normal direction of a seat cushion or backrest reference plane, and intercepting the body pressure cloud map of a contact surface toward the seat; encoding the colors in the cloud map, and mapping them with the corresponding median of a contact pressure interval in a post-processing setting, so as to complete the conversion of color information into body pressure numerical information; dividing the cloud map into small grids, selecting the colors in each small grid and comparing them with the previously encoded colors, so as to obtain the body pressure numerical value corresponding to the grid, and combining the grid coordinates as the position information to complete the conversion of the regional position information into the body pressure distribution information; finally, obtaining the body pressure numerical values ​​corresponding to all grids after the seat contact surface is gridded in the reference plane, so as to realize the extraction of the seat body pressure simulation results.

Description

Technical Field

[0001] The invention belongs to the technical field of automobile ergonomics, and in particular relates to a method for extracting seat body pressure simulation results. Background Art

[0002] Body pressure characteristics are one of the important static properties of car seats. It refers to the pressure characteristics generated by the contact load and material deformation between the seat and the occupant when the driver and the occupant remain stable after the driver and the occupant sit on the seat in a certain posture. It specifically includes two aspects: numerical characteristics and distribution characteristics. The body pressure value of the car seat should be within a reasonable range: on the one hand, excessive local body pressure will increase the stress in the human tissue and cause foreign body sensation, and long-term excessive body pressure will cause hypoxia and pressure damage to the human tissue; on the other hand, insufficient body pressure will lead to weak support of the seat, which will lead to deterioration of the driving posture and cause fatigue. The body pressure distribution of the car seat should also be reasonable: generally, the peak body pressure should be located below the ischial tuberosity, where most of the body weight is borne; the body pressure decreases layer by layer from the peak center to the outside, the isobaric lines are smooth and round, and the body pressure gradient is slow; the legs have a certain support but not too large to affect the blood return of the lower limbs, etc. The car seat is the interface with the largest contact area between the occupants and the car, and the body pressure characteristics are the most intuitive feeling of the occupants on the seat during driving. Studies have shown that the body pressure characteristics of the seat are most significantly correlated with the subjective comfort of the seat. Therefore, it is very important to study and test the body pressure characteristics of car seats.

[0003] In traditional research, the body pressure characteristics of seats are measured by real people after the samples or examples are manufactured, and by using a body pressure cushion composed of a series of pressure sensors arranged on a flexible pad. However, this method requires accurate sensor calibration in the early stage, and the body pressure cushion will deform due to force, which will have a great impact on the measured results. The most important thing is that the actual measurement must be based on the manufactured sample examples, which is costly and inefficient in the research and design process. Therefore, modern seat design and research all use CAE body pressure simulation methods to obtain the body pressure characteristics of seats. CAE seat body pressure simulation technology uses computer CAE software to perform finite element or biomechanical modeling of seats and target occupants, apply loads and boundary conditions, and perform explicit dynamics analysis for complex contacts and loads, so as to obtain the body pressure characteristics of seats through simulation calculations. Its essence is large deformation nonlinear explicit dynamics finite element analysis. If reasonable interactions and contact properties are set between people and chairs, this technology can be used to obtain relatively reliable body pressure characteristics of seats relatively quickly, simply and flexibly. After the specific values ​​and distribution are output, they can be used for seat inspection and research.

[0004] After using general finite element software to simulate the body pressure of the seat, it is necessary to perform post-processing to extract the seat body pressure simulation results. Body pressure belongs to the field variable of contact pressure. Its distribution can be displayed on the geometric model through a cloud map to display the calculation results of a certain analysis step or moment. After dividing the body pressure value into intervals, different colored blocks are used to intuitively display the body pressure value and distribution. For the specific value at a certain point, it is necessary to select the node at the corresponding position and then output the contact pressure at the node as the body pressure value here. Since the actual work often requires the body pressure distribution between the entire human-chair interface, it is necessary to establish a point set for the nodes on the contact surface in advance and obtain the node numbers in the point set. In the post-processing process, the corresponding deformed coordinates and result values ​​are output according to the previously obtained numbers. The deformed coordinates are flattened by geometric transformation to flatten the body pressure distribution results. After the body pressure numerical simulation results are numbered and corresponded to their positions one by one, the data results of the seat body pressure simulation are obtained, which is convenient for subsequent inspection and research.

[0005] In the process of post-processing the seat body pressure simulation, although the body pressure distribution characteristics can be intuitively obtained through the cloud map, the body pressure values ​​at each point on the contact surface are still needed in actual work. However, using general finite element technology, the body pressure simulation values ​​and distribution are based on a finite number of unit surfaces or nodes. Therefore, the result data is essentially a series of contact pressures at unit surfaces or nodes. The amount of data is very large and difficult to extract directly. In addition, the node spacing of the seat surface changes greatly after complex contact and nonlinear large deformation. The change in spacing has a great impact on the interpolation of the body pressure value, making it difficult to accurately planarize the body pressure distribution. Some special locations such as grooves, holes and other areas with very complex contact contours and deformations are almost impossible to perform plane conversion, resulting in large errors or even errors in the body pressure data. For the extraction of simulation results of these special parts, it is still necessary to rely on manual node screening and data output. This makes the extraction of seat body pressure simulation results affected by certain subjective factors and requires certain experience and skills. In addition, the post-processing process is relatively complicated and cumbersome, requires a high time cost, and has limited accuracy, which has a certain impact on the subsequent seat body pressure characteristic inspection, analysis and research work. Summary of the invention

[0006] In view of the above-mentioned problems existing in the prior art, the present invention provides a method for extracting seat body pressure simulation results, which can conveniently, quickly and accurately extract the body pressure simulation results of a seat that has undergone complex contact and large nonlinear deformation, especially the body pressure distribution at complex deformation and special contours can be planarized, and the body pressure values ​​at each node can be accurately extracted and arranged to obtain the accurate body pressure characteristics of the seat.

[0007] The present invention is achieved through the following technical solutions:

[0008] A method for extracting seat body pressure simulation results comprises the following steps:

[0009] Step 1: Capture the simulation result cloud map;

[0010] Step 2: Grid cloud map;

[0011] Step 3: Color coding of cloud map;

[0012] Step 4: Grid color recognition;

[0013] Step 5: Map the relationship and output the results.

[0014] Furthermore, the interception of the simulation result cloud map described in step 1 specifically includes the following contents:

[0015] Open the calculated seat pressure simulation result cloud map in the finite element post-processing module, and intercept the pressure cloud maps of the seat cushion and backrest respectively;

[0016] The interception directions of the body pressure cloud maps of the seat cushion and backrest are the normal directions of their respective reference planes, and the body pressure cloud maps of the contact surfaces are intercepted toward the seat.

[0017] Furthermore, the gridded cloud map described in step 2 specifically includes the following contents:

[0018] Flatten and grid the cloud images of the seat cushion and backrest captured in step 1; use the grid to divide the cloud image into several small square areas. The gridded areas cover the entire cloud image, and the cloud images of different parts cannot be in the same small square area.

[0019] Furthermore, the color coding of the cloud map described in step 3 specifically includes the following contents:

[0020] The colors contained in the cloud map captured in step 1 are extracted, that is, a series of colors in the cloud map legend, and they are matched one by one with the corresponding median of the body pressure value interval, and the encoding is completed using the mapping relationship between the cloud map color and the body pressure value; the number of different colors in the cloud map, that is, the number of intervals divided within the body pressure value range, reflects the resolution of the cloud map for the simulation results, and indirectly affects the result extraction accuracy. The more different colors in the cloud map, the higher the result extraction accuracy, and the number of different colors in the cloud map is not less than 10.

[0021] Furthermore, the grid color recognition described in step 4 specifically includes the following contents:

[0022] Identify and record the color and area of ​​each small square in the grid cloud map completed in step 2; if there is more than one color in a small square, record all the colors contained therein and the area they each occupy.

[0023] Furthermore, the mapping relationship described in step 5 and the output result specifically include the following contents:

[0024] The color of each small square in the grid identified in step 4 is compared with the color of the cloud map encoded in step 3 and the encoding is completed. The body pressure simulation numerical result corresponding to each small square is output according to the mapping relationship between the cloud map color and the body pressure value; if there are multiple colors in a small square, different weighted output methods are selected according to work or research needs; finally, the seat body pressure simulation result matrix is ​​extracted, and the elements of the matrix are equal to the number of small squares divided by the grid and correspond one to one.

[0025] Furthermore, the selection of different weighted output methods specifically includes maximum / minimum value method, midpoint value method, average value method and area method;

[0026] The maximum / minimum value method refers to assuming that a small square with multiple colors has only one color, and the body pressure value corresponding to the color is the maximum / minimum of the body pressure values ​​corresponding to these colors;

[0027] The midpoint value method refers to assuming that a small square with multiple colors has only one color, and the color is the color at the center of the small square;

[0028] The average value method refers to taking the arithmetic average of the body pressure values ​​corresponding to the multiple colors contained in the small square, and taking the arithmetic average as the body pressure value corresponding to the entire small square;

[0029] The area method refers to taking a weighted average of the body pressure values ​​corresponding to multiple colors contained in a small square using the area of ​​each color as a weight, and taking the weighted average as the body pressure value corresponding to the entire small square.

[0030] Compared with the prior art, the advantages of the present invention are as follows:

[0031] By utilizing a seat body pressure simulation result extraction method of the present invention, the seat body pressure simulation result can be directly extracted through the body pressure cloud map obtained by finite element simulation, and the mature general finite element software post-processing results can be directly utilized, thereby avoiding the deviation caused by data screening and conversion to the greatest extent. In addition, by customizing the color (or grayscale) coding and the corresponding body pressure value in the cloud map, the results of cloud maps of various types and body pressure ranges can be extracted, which is a universal method that can be widely used. By writing a script or program based on this method, there is no need for tedious node selection and pre-processing work, and the seat body pressure simulation results can be extracted conveniently, quickly and accurately. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following is a brief introduction to the drawings required for the specific embodiments or the description of the prior art. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn according to the actual scale.

[0033] Figure 1 It is a flow chart of a method for extracting seat body pressure simulation results of the present invention;

[0034] Figure 2 A schematic diagram of the interception direction of the simulation result cloud map;

[0035] Figure 3 This is a grid diagram of the cloud map;

[0036] In the figure: H point 1, seat cushion reference plane 2, backrest reference plane 3, seat cushion 4, backrest 5, headrest 6, seat cushion cloud map 7, backrest cloud map 8. DETAILED DESCRIPTION

[0037] In order to clearly and completely describe the technical solution and its specific working process of the present invention, the specific implementation methods of the present invention are as follows in conjunction with the accompanying drawings of the specification:

[0038] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements, unless otherwise clearly defined. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0039] In the present invention, unless otherwise clearly specified and limited, a first feature being "above" or "below" a second feature may mean that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. Moreover, a first feature being "above", "above" or "above" a second feature may mean that the first feature is directly above or obliquely above the second feature, or simply means that the first feature is higher in level than the second feature. A first feature being "below", "below" or "below" a second feature may mean that the first feature is directly below or obliquely below the second feature, or simply means that the first feature is lower in level than the second feature.

[0040] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0041] Example 1

[0042] The contact pressure cloud map in the post-processing process of general finite element software is obtained by reasonably interpolating and visualizing the simulation results of each node after calculation, which contains accurate body pressure characteristic calculation result information. If the cloud map is accurately plane-identified, and the color information on it is converted into body pressure numerical information, and the regional position information on it is converted into body pressure distribution information, the seat body pressure simulation result data can be extracted through the cloud map. The direction of obtaining the planarized cloud map is the normal direction of the seat cushion or backrest reference plane, and the body pressure cloud map of the contact surface is intercepted toward the seat; the color (or grayscale) in the cloud map is encoded and mapped with the corresponding median of the contact pressure interval in the post-processing settings to complete the conversion of color information to body pressure numerical information; the cloud map is divided into a series of grids of sufficiently small size, the color (or grayscale) in each small grid is selected and compared with the previously encoded color (or grayscale) to obtain the body pressure value corresponding to the grid, and combined with the grid coordinates as the position information, the conversion of the regional position information to the body pressure distribution information is completed; finally, the body pressure values ​​corresponding to all grids after the seat contact surface is gridded in the reference plane can be obtained, and the seat body pressure simulation results can be extracted.

[0043] like Figure 1 FIG. 1 is a flow chart of a method for extracting seat body pressure simulation results according to the present embodiment. The method specifically includes the following steps:

[0044] Step 1: Capture the simulation result cloud map, as follows:

[0045] In the finite element post-processing module, open the calculated seat pressure simulation result cloud map and intercept the pressure cloud maps of the seat cushion and backrest respectively. The directions for intercepting the cloud maps are shown in the attached figure. Figure 2 As shown in the figure, the interception direction of the seat cushion and backrest body pressure cloud map is the normal direction of their respective reference planes, and the body pressure cloud map of the contact surface is intercepted toward the seat. When intercepting, ensure that the cloud maps of the two components are independent and complete.

[0046] Step 2: Grid cloud map, as follows:

[0047] As attached Figure 3 As shown in the figure, the cloud images of the cushion and backrest captured in step 1 are flattened and gridded; the cloud images are divided into several small square areas with the gridded areas covering the entire cloud image, and the cloud images of different parts cannot be in the same small square area. The side length of the small square or the number of grids is set according to the required result extraction accuracy. The smaller the side length of the small square and the larger the number of grids, the higher the result extraction accuracy. It is recommended that the side length of the small square be less than 30mm.

[0048] Step 3: Cloud image color (grayscale) coding, as follows:

[0049] The colors (grayscale) contained in the cloud map captured in step 1 are extracted, that is, a series of colors (grayscale) in the cloud map legend, and they are matched one by one with the corresponding median of the body pressure value interval, and the encoding is completed using the mapping relationship between the cloud map color and the body pressure value. The number of different colors (grayscale) in the cloud map, that is, the number of intervals divided within the body pressure value range, reflects the resolution of the cloud map for the simulation results, and indirectly affects the result extraction accuracy. The more different colors (grayscale) in the cloud map, the higher the result extraction accuracy. It is recommended that the number of different colors (grayscale) in the cloud map be no less than 10.

[0050] Step 4: Grid color (grayscale) identification, as follows:

[0051] Identify and record the color (grayscale) and area of ​​each small square in the grid cloud map completed in step 2; if there is more than one color (grayscale) in a small square, record all the colors (grayscales) contained therein and their respective areas.

[0052] Step 5: Map the relationship and output the results, as follows:

[0053] Compare the color (grayscale) of each small square in the grid identified in step 4 with the color (grayscale) of the cloud map encoded in step 3 and complete the encoding. Output the body pressure simulation numerical result corresponding to each small square according to the mapping relationship between the cloud map color and the body pressure value. If there are multiple colors (grayscale) in a small square, select different weighted output methods according to work or research needs. Weighted output methods include maximum (minimum) value method, midpoint value method, average value method, area method, etc. The maximum (minimum) value method refers to assuming that a small square with multiple colors (grayscales) has only one color (grayscale), and the body pressure value corresponding to this color (grayscale) is the largest (smallest) of the body pressure values ​​corresponding to these colors (grayscales); the midpoint value method refers to assuming that a small square with multiple colors (grayscales) has only one color (grayscale), and this color (grayscale) is the color (grayscale) at the center of the small square; the average value method refers to taking the arithmetic average of the body pressure values ​​corresponding to the multiple colors (grayscales) contained in the small square, and taking the arithmetic average as the body pressure value corresponding to the entire small square; the area method refers to taking the weighted average of the body pressure values ​​corresponding to the multiple colors (grayscales) contained in the small square with the area of ​​each color (grayscale) as the weight, and taking the weighted average as the body pressure value corresponding to the entire small square. Finally, the seat body pressure simulation result matrix can be extracted, and the elements of the matrix are equal to the number of small squares divided by the grid and correspond one to one.

[0054] Example 2

[0055] The body pressure simulation of a certain chair has been completed using general finite element CAE software, and now it is necessary to extract the numerical value of the body pressure simulation result on the human-chair contact surface.

[0056] Step 1: Capture the simulation result cloud map, as follows:

[0057] In the finite element post-processing module, open the calculated seat pressure simulation result cloud map and intercept the pressure cloud maps of the seat cushion and backrest respectively. The directions for intercepting the cloud maps are shown in the attached figure. Figure 2 As shown in the figure, the interception direction of the seat cushion and backrest body pressure cloud map is the normal direction of their respective reference planes, and the body pressure cloud map of the contact surface is intercepted toward the seat. When intercepting, ensure that the cloud maps of the two components are independent and complete. The number of different colors in the cloud map reflects the resolution of the cloud map for the simulation results, which indirectly affects the result extraction accuracy. According to the required slightly finer result extraction accuracy, the number of different colors in the cloud map is selected as 18.

[0058] Step 2: Grid cloud map, as follows:

[0059] As attached Figure 3As shown in the figure, the cloud images of the seat cushion and backrest captured in step 1 are flattened and gridded; the cloud images are divided into several small square areas with the gridded areas covering the entire cloud image, and the cloud images of different parts cannot be in the same small square area. The required result extraction accuracy is slightly finer, and the side length of the small square is selected to be 10mm.

[0060] Step 3: Color coding of cloud map, as follows:

[0061] The 18 colors in the cloud map legend captured in step 1 are extracted, and are matched one by one with the corresponding median values ​​of the body pressure value intervals, and the encoding is completed using the mapping relationship between the cloud map colors and the body pressure values.

[0062] Step 4: Grid color identification, as follows:

[0063] Identify and record the color and area of ​​each small square in the grid cloud map completed in step 2; if there is more than one color in a small square, record all the colors contained therein and the areas they occupy.

[0064] Step 5: Map the relationship and output the results, as follows:

[0065] Compare the color of each small square in the grid identified in step 4 with the color of the cloud map encoded in step 3 and complete the encoding. Output the body pressure simulation numerical result corresponding to each small square according to the mapping relationship between the cloud map color and the body pressure value. In the case where there are multiple colors in a small square, the area method is selected as the weighted output method according to the needs of subsequent research. Take the weighted average of the body pressure values ​​corresponding to the multiple colors contained in the small square with the area of ​​each color as the weight, and use the weighted average as the body pressure value corresponding to the entire small square. Finally, output the body pressure values ​​corresponding to all small squares, and you can extract the body pressure simulation result matrix of the seat.

[0066] The preferred embodiments of the present invention are described in detail above in conjunction with the accompanying drawings. However, the present invention is not limited to the specific details in the above embodiments. Within the technical concept of the present invention, a variety of simple modifications can be made to the technical solution of the present invention, and these simple modifications all belong to the protection scope of the present invention.

[0067] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present invention will not further describe various possible combinations.

[0068] In addition, various embodiments of the present invention may be arbitrarily combined, and as long as they do not violate the concept of the present invention, they should also be regarded as the contents disclosed by the present invention.

Claims

1. A seat body pressure simulation result extraction method, characterized in that: The specific steps include: Step 1: Capture the simulation result cloud map; Step 2: Grid cloud map; Step 3: Color coding of cloud map; Step 4: Grid color recognition; Step 5: Map the relationship and output the result; The color coding of the cloud map described in step 3 specifically includes the following contents: Extract the colors contained in the cloud image captured in step 1, that is, a series of colors in the cloud image legend, and correspond them to the median of the corresponding body pressure value interval one by one, and complete the encoding using the mapping relationship between the cloud image color and the body pressure value; The grid color recognition described in step 4 specifically includes the following contents: Identify and record the color and area of ​​each small square in the grid cloud map completed in step 2; if there is more than one color in a small square, record all the colors contained therein and the area they occupy; The mapping relationship described in step 5 and the output results include the following: The color of each small square in the grid identified in step 4 is compared with the color of the cloud map encoded in step 3 and the encoding is completed. The body pressure simulation numerical result corresponding to each small square is output according to the mapping relationship between the cloud map color and the body pressure value; if there are multiple colors in a small square, different weighted output methods are selected according to work or research needs; finally, the seat body pressure simulation result matrix is ​​extracted, and the elements of the matrix are equal to the number of small squares divided by the grid and correspond one to one.

2. A seat body pressure simulation result extraction method as claimed in claim 1, characterized in that: The interception of the simulation result cloud map described in step 1 specifically includes the following contents: Open the calculated seat pressure simulation result cloud map in the finite element post-processing module, and intercept the pressure cloud maps of the seat cushion and backrest respectively; The interception directions of the body pressure cloud maps of the seat cushion and backrest are the normal directions of their respective reference planes, and the body pressure cloud maps of the contact surfaces are intercepted toward the seat.

3. A seat body pressure simulation result extraction method as claimed in claim 2, characterized in that: The gridded cloud map described in step 2 specifically includes the following contents: Flatten and grid the cloud images of the seat cushion and backrest captured in step 1; use the grid to divide the cloud image into several small square areas. The gridded areas cover the entire cloud image, and the cloud images of different parts cannot be in the same small square area.

4. The seat body pressure simulation result extraction method according to claim 1, characterized in that: The number of different colors in the cloud map, that is, the number of intervals divided within the body pressure value range, reflects the resolution of the cloud map for the simulation results and indirectly affects the accuracy of result extraction. The more different colors in the cloud map, the higher the accuracy of result extraction. The number of different colors in the cloud map is not less than 10.

5. The seat body pressure simulation result extraction method according to claim 1, characterized in that: The different weighted output methods selected specifically include maximum / minimum value method, midpoint value method, average value method and area method; The maximum / minimum value method refers to assuming that a small square with multiple colors has only one color, and the body pressure value corresponding to the color is the maximum / minimum of the body pressure values ​​corresponding to these colors; The midpoint value method refers to assuming that a small square with multiple colors has only one color, and the color is the color at the center of the small square; The average value method refers to taking the arithmetic average of the body pressure values ​​corresponding to the multiple colors contained in the small square, and taking the arithmetic average as the body pressure value corresponding to the entire small square; The area method refers to taking a weighted average of the body pressure values ​​corresponding to multiple colors contained in a small square using the area of ​​each color as a weight, and taking the weighted average as the body pressure value corresponding to the entire small square.

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