Ergonomic chair air permeability detection method

Abstract

The invention relates to the technical field of air permeability detection, in particular to an ergonomic chair air permeability detection method, which comprises the following steps: acquiring a first airflow passing representation vector set of each surface area of an ergonomic chair in a non-simulation state and a second airflow passing representation vector set of each surface area of the ergonomic chair in a simulation state; determining a ventilation interference type of each surface area according to a comparison condition of the first airflow obstruction characterization quantity and the second airflow obstruction characterization quantity, and determining a detection state simulation mode of each surface area based on the ventilation interference type; whether the air permeability of the surface area is abnormal or not is judged according to the air permeability rate difference value before and after the detection state simulation of the surface area, then the air permeability state of the surface fabric is simulated according to the sitting state, and the detection accuracy of the air permeability of the ergonomic chair in different use states is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of breathability detection, and particularly to a method for detecting the breathability of an ergonomic chair. Background Art

[0002] An ergonomic chair can provide users with a comfortable and healthy sitting experience. Its breathability is one of the key factors affecting user comfort. In actual use, the breathability of an ergonomic chair is affected by various factors such as material properties, structural design, and the stress situation during use. Currently, the detection methods for the breathability of ergonomic chairs are relatively limited. Traditional detection methods may only focus on the breathable performance of the material itself, while ignoring the changes in the breathability of the chair under actual use conditions. Due to differences in structure and function, different surface areas may be affected by different breathable interference factors. Existing detection methods are difficult to comprehensively and accurately evaluate the impact of these factors on breathability. More accurate evaluation of the breathability of ergonomic chairs can provide strong support for product design optimization and quality control.

[0003] For example, Chinese Patent Publication No.: CN118483141A, which discloses a method for detecting the breathability of a fabric. The specific steps are as follows: Step 1, establish a prediction model for the change in fabric surface area based on a neural network algorithm; Step 2, place the fabric on the bottom plate and make the fabric in a flat state; the negative pressure chamber moves downward and clamps the fabric between the negative pressure chamber and the bottom plate; pump air into the negative pressure chamber through the air extraction pipe, and then calculate the measured breathability rate K_measured of the fabric; Step 3, predict the surface area value A_after_change of the fabric after bulging change through the prediction model for the change in fabric surface area, and calculate the correction coefficient; Step 4, correct the measured breathability rate K_measured through the correction coefficient.

[0004] The following problems also exist in the prior art: The prior art does not consider the influence of factors such as the structure and stress of the surface of an ergonomic chair in actual use on breathability, and cannot simulate the breathable state of the surface fabric according to the sitting state, which affects the detection accuracy of the breathability of the ergonomic chair in different use states and is difficult to provide support for product design optimization and quality control. Summary of the Invention

[0005] Therefore, the present invention provides a method for detecting the breathability of an ergonomic chair to overcome the problem that the prior art cannot simulate the breathable state of the surface fabric according to the sitting state, which affects the detection accuracy of the breathability of the ergonomic chair in different use states.

[0006] To achieve the above object, the present invention provides a method for detecting the breathability of an ergonomic chair, including: Obtain the first airflow penetration characterization vector set of each surface area of the ergonomic chair in the non-simulated state on the seating surface and the backrest surface, determine the first airflow obstruction characterization quantity according to the included angle between the vectors in the first airflow penetration characterization vector set, obtain the second airflow penetration characterization vector set of each surface area of the ergonomic chair in the simulated state on the seating surface and the backrest surface, and determine the second airflow obstruction characterization quantity according to the included angle between the vectors in the second airflow penetration characterization vector set; Determine the air permeability interference category of each surface area according to the comparison between the first airflow obstruction characterization quantity and the second airflow obstruction characterization quantity; Based on the air permeability interference category corresponding to each surface area, determine the method for simulating the detection state of each surface area, including, Apply tensile forces in opposite directions with a continuous preset simulation duration along the seating surface and the backrest surface parallel to the surface area; Or, apply compressive forces in opposite directions with a continuous preset simulation duration along the seating surface and the backrest surface perpendicular to the surface area; Respectively obtain the air permeability rates of each surface area before and after the detection state simulation, and determine whether the air permeability of the surface area is abnormal according to the difference in air permeability rates before and after the detection state simulation.

[0007] Further, the process of obtaining the first airflow penetration characterization vector set includes: Obtain the surface point cloud data of the ergonomic chair in the non-simulated state to construct the first surface contour model; Divide the first surface contour model into several surface areas; Determine the unit normal vector of the seating surface and the unit normal vector of the backrest surface according to the point cloud data of each surface area, and determine the vector set composed of the unit normal vector of the seating surface and the unit normal vector of the backrest surface as the first airflow penetration characterization vector set.

[0008] Further, the first airflow obstruction characterization quantity is the vector included angle between the unit normal vector of the seating surface and the unit normal vector of the backrest surface in the first airflow penetration characterization vector set.

[0009] Further, the process of obtaining the second airflow penetration characterization vector set includes: Obtain the surface point cloud data of the ergonomic chair in the simulated state to construct the second surface contour model; Divide the second surface contour model into several surface areas; Determine the unit normal vector of the seating surface and the unit normal vector of the backrest surface according to the point cloud data of each surface area, and determine the vector set composed of the unit normal vector of the seating surface and the unit normal vector of the backrest surface as the second airflow penetration characterization vector set.

[0010] Further, the second air flow obstruction characterization quantity is the vector included angle between the unit normal vector of the seating surface and the unit normal vector of the back surface of the seating surface within the vector set through which the second air flow passes.

[0011] Further, determine the comparison situation between the first air flow obstruction characterization quantity and the second air flow obstruction characterization quantity according to the air permeability interference characterization quantity; Wherein, the air permeability interference characterization quantity is the difference between the first air flow obstruction characterization quantity and the second air flow obstruction characterization quantity.

[0012] Further, the process of determining the air permeability interference category of the surface area includes: If the air permeability interference characterization quantity meets the pore distortion dominant condition, determine that the air permeability interference category of the surface area is the pore distortion characteristic dominant category; If the air permeability interference characterization quantity does not meet the pore distortion dominant condition, determine that the air permeability interference category of the surface area is the pore distortion characteristic non-dominant category; The pore distortion dominant condition is that the air permeability interference characterization quantity exceeds a preset air permeability interference characterization threshold.

[0013] Further, the method for determining the simulation of the detection state includes: If the air permeability interference category of the surface area is the pore distortion characteristic dominant category, determine that the simulation verification method is to apply tensile forces in opposite directions with a continuous preset simulation duration along the seating surface and the back surface of the seating surface parallel to the surface area; If the air permeability interference category of the surface area is the pore distortion characteristic non-dominant category, determine that the simulation verification method is to apply extrusion forces in opposite directions with a continuous preset simulation duration along the seating surface and the back surface of the seating surface perpendicular to the surface area.

[0014] Further, the value of the tensile force applied to the surface area is positively correlated with the second air flow obstruction characterization quantity, and the value of the extrusion force applied to the surface area is positively correlated with the second air flow obstruction characterization quantity.

[0015] Further, determining whether the air permeability of the surface area is abnormal includes: If the air permeability rate difference before and after the simulation of the detection state meets the air permeability attenuation condition, determine that the air permeability of the surface area is normal; If the air permeability rate difference before and after the simulation of the detection state does not meet the air permeability attenuation condition, determine that the air permeability of the surface area is abnormal; Wherein, the air permeability attenuation condition is that the air permeability rate difference exceeds a preset air permeability rate attenuation reference value, and the air permeability rate is determined according to the gas flow rate per unit time.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows. The present invention obtains the first airflow penetration characterization vector set of each surface area of the ergonomic chair in the non-simulation state and the second airflow penetration characterization vector set of each surface area of the ergonomic chair in the simulation state, determines the air permeability interference category of each surface area according to the comparison between the first airflow obstruction characterization quantity and the second airflow obstruction characterization quantity, determines the method for simulating the detection state of each surface area based on the air permeability interference category, and determines whether the air permeability of the surface area is abnormal according to the difference in the air permeability rate of the surface area before and after simulating the detection state. Furthermore, the present invention realizes the simulation of the air permeability state of the surface fabric according to the sitting state, and improves the detection accuracy of the air permeability of the ergonomic chair in different usage states.

[0017] Furthermore, by constructing the first surface contour model and the second surface contour model, the present invention can comprehensively reflect the surface morphology of the ergonomic chair in the non-simulation state and the sitting state. The first airflow penetration characterization vector set and the second airflow penetration characterization vector set determined based on this include the unit normal vector information of the sitting surface and the sitting back surface in different states. It can be understood that after dividing the surface contour model of the ergonomic chair into several surface areas and then determining the unit normal vector, the characteristic differences of different surface areas of the chair can be fully considered, avoiding the possible different effects of factors such as the shape and curvature of different areas on airflow penetration. Furthermore, the evaluation of the airflow obstruction condition of each surface area covers the characteristics of multiple dimensions related to airflow penetration.

[0018] Furthermore, by determining the difference between the first airflow obstruction characterization quantity and the second airflow obstruction characterization quantity as the air permeability interference characterization quantity, the present invention can quantify the difference in the airflow obstruction situation of the ergonomic chair in the non-simulation state and the simulation state. When the calculated difference in the air permeability interference characterization quantity is large, it means that from the non-simulation state to the simulation state, the angle change between the unit normal vectors of the sitting surface and the sitting back surface of the surface area is obvious. A large angle change may be due to large lateral displacement or twisting of the body on the chair surface fabric when sitting on the chair. These actions will cause a large degree of deformation and distortion of the fiber structure of the fabric, and then lead to the distortion of the original air permeability channels, changing the originally smooth airflow channels, resulting in a large change in the obstruction suffered by the airflow when passing through, and ultimately reflecting a large impact on the air permeability state. When the difference in the air permeability interference characterization quantity is small, it indicates that from the non-simulation state to the simulation state, the angle change between the unit normal vectors of the sitting surface and the sitting back surface of the surface area is small. The main influence on the fabric surface when the human body sits on the chair may come from gravity, and the fabric may be compacted, narrowing or even partially blocking the air permeability channels. Furthermore, the present invention realizes the quantitative distinction of the air permeability state of the surface fabric according to the sitting state.

[0019] Furthermore, by determining the relationship between the air permeability interference characterization quantity and the preset air permeability interference characterization threshold, the present invention classifies the air permeability interference categories of the surface area into a dominant category of pore distortion characteristics and a non-dominant category of pore distortion characteristics. By accurately judging and classifying the air permeability interference categories of the surface area, the ergonomic chair can more accurately match the actual working conditions in the detection link, realizing the simulation of the air permeability state of the surface fabric according to the sitting state, and improving the detection accuracy of the air permeability of the ergonomic chair under different usage states.

[0020] Furthermore, the present invention selects a targeted detection state simulation method according to the air permeability interference category. For different air permeability interference categories, different simulation verification methods are selected. For the dominant category of pore distortion characteristics, since the change of the air permeability state in this area is mainly affected by the pore distortion caused by the transverse movement, a method of applying a tensile force parallel to the surface is used to simulate the influence of the possible lateral displacement on the fabric when the human sitting posture changes. For the non-dominant category of pore distortion characteristics, since the air permeability problem in this category is mainly caused by the blockage of the air permeability channel due to gravity, a vertical extrusion force is applied to simulate the compaction effect of gravity on the fabric. Furthermore, the simulation of the air permeability state of the surface fabric according to the sitting state is realized, and the detection accuracy of the air permeability of the ergonomic chair under different usage states is improved.

[0021] Furthermore, the present invention establishes a positive correlation between the magnitudes of the tensile force and the extrusion force and the second air flow obstruction characterization quantity, which can make the simulation conditions closer to the actual situation and avoid the distortion of the detection results caused by too large or too small acting forces. Furthermore, the simulation of the air permeability state of the surface fabric according to the sitting state is realized, and the detection accuracy of the air permeability of the ergonomic chair under different usage states is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 It is a step diagram of the air permeability detection method for the ergonomic chair according to the embodiment of the present invention; Figure 2 It is a step diagram of obtaining the first air flow penetration characterization vector set according to the embodiment of the present invention; Figure 3 It is a step diagram of obtaining the second air flow penetration characterization vector set according to the embodiment of the present invention; Figure 4 It is a logic flow diagram of determining the air permeability interference category of the surface area according to the embodiment of the present invention; Figure 5 It is a logic flow diagram of determining whether the air permeability of the surface area is abnormal according to the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0023] In order to make the objectives and advantages of the present invention clearer, the present invention will be further described below in conjunction with the embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0024] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the present invention and do not limit the protection scope of the present invention.

[0025] It should be noted that in the description of the present invention, the terms indicating the direction or positional relationship such as "upper", "lower", "inner", "outer", etc. are based on the direction or positional relationship shown in the drawings. This is only for convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be construed as a limitation of the present invention.

[0026] Please refer to Figure 1 As shown, it is a step diagram of the ergonomic chair breathability detection method according to an embodiment of the present invention. The ergonomic chair breathability detection method of the present invention includes: Step S100, obtaining a first airflow penetration characterization vector set of each surface area of the ergonomic chair in the non-simulation state on the seating surface and the backrest surface, determining a first airflow obstruction characterization quantity according to the included angle between the vectors in the first airflow penetration characterization vector set, obtaining a second airflow penetration characterization vector set of each surface area of the ergonomic chair in the simulation state on the seating surface and the backrest surface, and determining a second airflow obstruction characterization quantity according to the included angle between the vectors in the second airflow penetration characterization vector set; In implementation, a camera can be used to capture and record data on the positions of the head, shoulders, elbows, wrists, buttocks, knees, ankles, etc. of a human body in a natural sitting posture, complete the recording of various motion and posture data, and apply these data to the simulation of the ergonomic chair, so that the state of the chair can be correspondingly matched with different sitting postures such as forward tilt, backward tilt, and lateral tilt of the actual human body movements, which will not be elaborated here.

[0027] Step S200, determining the air permeability interference category of each surface area according to the comparison between the first airflow obstruction characterization quantity and the second airflow obstruction characterization quantity; Step S300, determining the method for simulating the detection state of each surface area based on the air permeability interference category corresponding to each surface area, including, Applying tensile forces in opposite directions with a continuous preset simulation duration along the seating surface and the backrest surface parallel to the surface area; Or, applying compressive forces in opposite directions with a continuous preset simulation duration along the seating surface and the backrest surface perpendicular to the surface area; Specifically, the preset simulation duration can be determined by those skilled in the art according to the requirements of detection accuracy. When the fabric durability of the surface area meets the standard, the longer the duration of applying tensile force and extrusion force, the more obvious the impact on the fabric of each surface area during sitting. In the present invention, the value range of the preset simulation duration is 3 - 12 h. Preferably, the preset simulation duration is 8 h.

[0028] Step S400: Obtain the air permeability rates of each surface area before and after simulating the detection state respectively, and determine whether the air permeability of the surface area is abnormal according to the difference in air permeability rates before and after the detection state simulation.

[0029] Specifically, the sitting surface of the ergonomic chair is the surface area that directly contacts the main parts of the human body such as the buttocks and back, and the back of the sitting surface refers to the surface area on the chair that is opposite to the sitting surface and does not directly contact the main parts of the human body such as the buttocks and back.

[0030] Specifically, please refer to Figure 2 As shown, it is a step diagram for obtaining the first airflow penetration characterization vector set in an embodiment of the present invention. The process of obtaining the first airflow penetration characterization vector set includes: Step S101: Obtain the surface point cloud data of the ergonomic chair in the non - simulated state to construct the first surface contour model; Step S102: Divide the first surface contour model into several surface areas; Step S103: Determine the unit normal vector A1 of the sitting surface and the unit normal vector A2 of the back of the sitting surface according to the point cloud data of each surface area, and determine the vector set composed of the unit normal vector of the sitting surface and the unit normal vector of the back of the sitting surface as the first airflow penetration characterization vector set {A1, A2}.

[0031] Specifically, the starting point of the vector of the unit normal vector A1 of the sitting surface is on the sitting surface, and the end point of the vector is a point in the direction away from the ground. Similarly, the starting point of the vector of the unit normal vector A2 of the back of the sitting surface is on the sitting surface, and the end point of the vector is a point in the direction away from the ground.

[0032] In implementation, the unit normal vector of the sitting surface and the unit normal vector of the back of the sitting surface can be determined based on the method of plane fitting. First, perform pre - processing operations such as denoising and filtering on the obtained point cloud data to remove possible noise points and outliers, use methods such as the least - squares method to fit the plane, and then determine the unit normal vector of the sitting surface and the normal vector of the back of the sitting surface according to the coefficients of the plane equation, and determine the final unit normal vector. The denoising and filtering of point cloud data, fitting the plane by the least - squares method, and determining the normal vector of the plane are prior arts and will not be elaborated here.

[0033] Specifically, the first airflow obstruction characterization quantity is the vector angle between the unit normal vector of the seating surface and the unit normal vector of the backrest surface within the first airflow traversing characterization vector set.

[0034] In implementation, obtain the unit normal vector A1 of the seating surface and the unit normal vector A2 of the backrest surface, calculate the cosine value of the vector angle according to the vector dot product formula, and use the inverse trigonometric function to determine the vector angle between the unit normal vector of the seating surface and the unit normal vector of the backrest surface. This is prior art and will not be elaborated here.

[0035] Specifically, please refer to Figure 3 As shown, it is a step diagram for obtaining the second airflow traversing characterization vector set in an embodiment of the present invention. The process of obtaining the second airflow traversing characterization vector set includes: Step S111, obtain the surface point cloud data of the ergonomic chair in the simulated state to construct a second surface contour model; Step S112, divide the second surface contour model into several surface regions; Step S113, determine the unit normal vector B1 of the seating surface and the unit normal vector B2 of the backrest surface according to the point cloud data of each surface region, and determine the vector set composed of the unit normal vector of the seating surface and the unit normal vector of the backrest surface as the second airflow traversing characterization vector set {B1, B2}.

[0036] Specifically, the starting point of the vector of the unit normal vector A1 of the seating surface is on the seating surface, and the end point of the vector is a point in the direction away from the ground. Similarly, the starting point of the vector of the unit normal vector A2 of the backrest surface is on the seating surface, and the end point of the vector is a point in the direction away from the ground.

[0037] In implementation, the surface point cloud data of the ergonomic chair can be obtained by a 3D laser scanner, and the unit normal vector of the seating surface and the unit normal vector of the backrest surface in the simulated state can be determined based on the method of plane fitting. First, perform preprocessing operations such as denoising and filtering on the obtained point cloud data to remove possible noise points and outliers, use methods such as the least squares method to fit the plane, and then determine the unit normal vector of the seating surface and the normal vector of the backrest surface according to the coefficients of the plane equation, and determine the final unit normal vector. The denoising and filtering of point cloud data, fitting the plane by the least squares method, and determining the normal vector of the plane are prior art and will not be elaborated here.

[0038] Specifically, the second airflow obstruction characterization quantity is the vector angle between the unit normal vector of the seating surface and the unit normal vector of the backrest surface within the second airflow traversing characterization vector set.

[0039] In implementation, the unit normal vector B1 of the seating surface and the unit normal vector B2 of the back of the seat are obtained, and the cosine value of the vector included angle is calculated according to the vector dot product formula, and the included angle between the unit normal vector of the seating surface and the unit normal vector of the back of the seat is determined by using the inverse trigonometric function. This is the prior art and will not be elaborated here.

[0040] Specifically, by constructing the first surface contour model and the second surface contour model, the present invention can comprehensively reflect the surface morphology of the ergonomic chair in the non-simulation state and the seating state. Based on this, the first airflow penetration characterization vector set and the second airflow penetration characterization vector set determined include the unit normal vector information of the seating surface and the back of the seat in different states. It can be understood that by dividing the surface contour model of the ergonomic chair into several surface areas and then determining the unit normal vector, the characteristic differences of different surface areas of the chair can be fully considered, avoiding the possible different effects of factors such as the shape and curvature of different areas on airflow penetration. Furthermore, the evaluation of the airflow obstruction situation of each surface area covers multiple dimensions of features related to airflow penetration.

[0041] Specifically, according to the air permeability interference characterization quantity, the comparison situation between the first airflow obstruction characterization quantity and the second airflow obstruction characterization quantity is determined; Wherein, the air permeability interference characterization quantity is the difference between the first airflow obstruction characterization quantity and the second airflow obstruction characterization quantity.

[0042] Specifically, by determining the difference between the first airflow obstruction characterization quantity and the second airflow obstruction characterization quantity as the air permeability interference characterization quantity, the present invention can quantify the difference in the airflow obstruction situation of the ergonomic chair in the non-simulation state and the simulation state. When the calculated difference in the air permeability interference characterization quantity is large, it means that from the non-simulation state to the simulation state, the included angle between the unit normal vectors of the seating surface and the back of the seat of the surface area changes significantly. The large change in the included angle may be due to large lateral displacement or twisting of the body on the chair surface fabric when sitting on the chair. These actions will cause a large degree of deformation and distortion of the fiber structure of the fabric, and then lead to the distortion of the original air permeability channels, changing the originally smooth airflow channels, resulting in a large change in the obstruction of the airflow when passing through, and finally reflecting a large impact on the air permeability state. When the difference in the air permeability interference characterization quantity is small, it indicates that from the non-simulation state to the simulation state, the included angle between the unit normal vectors of the seating surface and the back of the seat of the surface area changes little. The main influence of the human body sitting on the chair on the fabric surface may come from gravity, and the fabric may be compacted, making the air permeability channels narrower or even partially blocked. Furthermore, the quantification and differentiation of the air permeability state of the surface fabric according to the seating state are realized.

[0043] Specifically, please refer to Figure 4As shown, it is a logic flowchart for determining the air permeability interference category of the surface area in an embodiment of the present invention. The process of determining the air permeability interference category of the surface area includes: If the air permeability interference characterization quantity meets the pore distortion dominant condition, then determine that the air permeability interference category of the surface area is the pore distortion characteristic dominant category; If the air permeability interference characterization quantity does not meet the pore distortion dominant condition, then determine that the air permeability interference category of the surface area is the pore distortion characteristic non-dominant category; The pore distortion dominant condition is that the air permeability interference characterization quantity exceeds a preset air permeability interference characterization threshold.

[0044] In practice, through a large number of air permeability performance experiments on the ergonomic chair fabric under various conditions such as different pressures and different sitting postures, collect data on the air permeability interference characterization quantity, analyze the distribution and change rules of the data, and find a critical value that can clearly distinguish whether pore distortion dominates the air permeability interference. In the present invention, the value range of the preset air permeability interference characterization threshold is [25°, 35°], and preferably, the value of the preset air permeability interference characterization threshold is 30°.

[0045] Specifically, the present invention divides the air permeability interference category of the surface area into the pore distortion characteristic dominant category and the pore distortion characteristic non-dominant category by determining the relationship between the air permeability interference characterization quantity and the preset air permeability interference characterization threshold. By accurately judging and classifying the air permeability interference category of the surface area, the ergonomic chair can more accurately match the actual working conditions in the detection link, realizing the simulation of the air permeability state of the surface fabric according to the sitting state, and improving the detection accuracy of the air permeability of the ergonomic chair under different use states.

[0046] Specifically, the methods for determining the simulation of the detection state include: If the air permeability interference category of the surface area is the pore distortion characteristic dominant category, then determine that the simulation verification method is to apply tensile forces in opposite directions with a continuous preset simulation duration along the sitting surface and the back surface parallel to the surface area; If the air permeability interference category of the surface area is the pore distortion characteristic non-dominant category, then determine that the simulation verification method is to apply extrusion forces in opposite directions with a continuous preset simulation duration along the sitting surface and the back surface perpendicular to the surface area.

[0047] Specifically, the sample to be tested can be installed on a hydraulic control fixture, which contacts and fixes with the seating surface and the back of the seat respectively. Set the test parameters, including the magnitude of the pulling force, the preset simulation duration, etc. Start the hydraulic controller, and the fixture applies the corresponding pulling force according to the set parameters. The measurement and control system monitors the data such as the magnitude and time of the pulling force in real time, ensuring that the pulling force is in the direction parallel to the seating surface and the back of the seat, and the duration reaches the preset simulation duration. Similarly, the fixture can also contact with the seating surface and the back of the seat respectively, set the test parameters, including the magnitude of the extrusion force, the preset simulation duration, etc. Start the hydraulic controller, and the fixture applies the corresponding extrusion force according to the set parameters. The measurement and control system monitors the data such as the magnitude and time of the extrusion force in real time, ensuring that the extrusion force is in the direction perpendicular to the seating surface and the back of the seat, and the duration reaches the preset simulation duration. This is the prior art and will not be elaborated here.

[0048] Specifically, the present invention selects a targeted detection state simulation method according to the air permeability interference category. For different air permeability interference categories, different simulation verification methods are selected. For the dominant category of pore distortion characteristics, since the change of the air permeability state in such areas is mainly affected by the pore distortion caused by lateral movement, the method of applying a pulling force parallel to the surface is adopted to simulate the influence of the lateral displacement that may occur when the human body changes its sitting posture on the fabric. For the non-dominant category of pore distortion characteristics, since the air permeability problem in this category is mainly caused by the blockage of the air permeability channel due to gravity, a vertical extrusion force is applied to simulate the compaction effect of gravity on the fabric. Furthermore, the air permeability state of the surface fabric is simulated according to the sitting state, improving the detection accuracy of the air permeability of the ergonomic chair in different use states.

[0049] Specifically, the value of the pulling force applied to the surface area is positively correlated with the second air flow obstruction characterization quantity, and the value of the extrusion force applied to the surface area is positively correlated with the second air flow obstruction characterization quantity.

[0050] Specifically, the present invention establishes a positive correlation between the magnitudes of the pulling force and the extrusion force and the second air flow obstruction characterization quantity, which can make the simulation conditions closer to the actual situation, avoid the distortion of the detection results caused by too large or too small acting forces. Furthermore, the air permeability state of the surface fabric is simulated according to the sitting state, improving the detection accuracy of the air permeability of the ergonomic chair in different use states.

[0051] Specifically, please refer to Figure 5 as shown, which is the logic flow chart for the present invention embodiment to determine whether the air permeability of the surface area is abnormal. Determining whether the air permeability of the surface area is abnormal includes: If the difference in air permeability rate before and after the simulation of the detection state meets the air permeability attenuation condition, it is determined that the air permeability of the surface area is normal; If the difference in air permeability rates before and after simulating the detection state does not meet the air permeability attenuation condition, it is determined that the air permeability of the surface area is abnormal; Among them, the air permeability attenuation condition is that the difference in air permeability rates exceeds a preset reference value for air permeability rate attenuation, and the air permeability rate is determined according to the gas flow rate per unit time.

[0052] Specifically, through air permeability rate detection experiments on a large number of samples of different materials, collecting air permeability rate data before and after simulating the detection state, and conducting statistical analysis. For general fabric materials or common seat air permeability materials, the reference value for air permeability rate attenuation may be between 50 - 100 cm 3 / min. Preferably, the preset reference value for air permeability rate attenuation is 70 cm 3 / min. For some high-performance air permeability materials, the reference value for air permeability rate attenuation may be set between 30 - 60 cm 3 / min. Preferably, the preset reference value for air permeability rate attenuation is 45 cm 3 / min.

[0053] In implementation, the air permeability rate of each surface area before and after simulating the detection state can be obtained through an air permeability tester. The air permeability tester generally consists of a gas source chamber, a flow monitoring system, a timer, a data processing system, etc. The gas source chamber provides a stable air flow. When detecting the air permeability rate, a fixed amount of gas in the gas source chamber is passed through the fabric of each surface area, and the gas flow rate of the gas in the gas source chamber flowing through the fabric of the surface area per unit time is determined according to the flow monitoring system. The data processing system determines the ratio of the gas loss amount to the unit time as the air permeability rate.

[0054] Specifically, the present invention can also use devices such as an alarm buzzer to give an alarm prompt according to the determination result of the abnormal air permeability of the surface area. Alarm buzzers are widely used in industrial process production and finished product detection fields, which will not be elaborated here.

[0055] The implementation carrier of the embodiment of the present invention can specifically be a chip, a component or a module. The chip includes a connected processor and a memory; among them, the memory is used to store instructions. When the processor calls and executes the instructions, the chip can execute the ergonomic chair air permeability detection method provided by the above embodiment. This embodiment also provides a readable storage medium, in which computer program code is stored. When the computer program code runs on a computer, the computer executes the above relevant method steps to implement the ergonomic chair air permeability detection method provided by the above embodiment.

[0056] So far, the technical solution of the present invention has been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, those skilled in the art can easily understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0057] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent substitution, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for detecting the air permeability of an ergonomic chair, characterized in that: include: Obtain a first airflow crossing characterization vector set of each surface area of ​​the ergonomic chair on the seating surface and the back seating surface in a non-simulation state, and determine a first airflow obstruction characterization amount according to the angle between the vectors in the first airflow crossing characterization vector set; obtain a second airflow crossing characterization vector set of each surface area of ​​the ergonomic chair on the seating surface and the back seating surface in a simulation state, and determine a second airflow obstruction characterization amount according to the angle between the vectors in the second airflow crossing characterization vector set; Determine the air permeability interference category of each surface area according to a comparison between the first airflow obstruction characterization amount and the second airflow obstruction characterization amount; Determining a method for simulating the detection state of each surface area based on the air permeability interference category corresponding to each surface area includes: Applying pulling forces in opposite directions for a preset simulation time along the seating surface and the seating back surface parallel to the surface area; Or, applying a squeezing force in opposite directions for a predetermined simulation time along a seating surface and a seating back surface perpendicular to the surface area; The air permeability of each surface area before and after the detection state simulation is respectively obtained, and whether the air permeability of the surface area is abnormal is determined according to the difference in the air permeability before and after the detection state simulation.

2. The method for detecting air permeability of an ergonomic chair according to claim 1, characterized in that: The process of obtaining the first airflow crossing characterization vector set includes: Acquire surface point cloud data of the ergonomic chair in a non-simulation state to construct a first surface contour model; dividing the first surface contour model into a plurality of surface regions; The unit normal vector of the seating surface and the unit normal vector of the back seating surface are determined according to the point cloud data of each surface area, and a vector set consisting of the unit normal vector of the seating surface and the unit normal vector of the back seating surface is determined as a first airflow crossing characterization vector set.

3. The method for detecting air permeability of an ergonomic chair according to claim 2, characterized in that: The first airflow obstruction characterization quantity is the vector angle between the unit normal vector of the seating surface and the unit normal vector of the back seating surface in the first airflow crossing characterization vector set.

4. The method for detecting air permeability of an ergonomic chair according to claim 1, characterized in that: The process of obtaining the second airflow crossing characterization vector set includes: Acquire surface point cloud data of the ergonomic chair in a simulation state to construct a second surface contour model; dividing the second surface contour model into a plurality of surface regions; The unit normal vector of the seating surface and the unit normal vector of the back seating surface are determined according to the point cloud data of each surface area, and a vector set consisting of the unit normal vector of the seating surface and the unit normal vector of the back seating surface is determined as a second airflow crossing characterization vector set.

5. The method for detecting air permeability of an ergonomic chair according to claim 4, characterized in that: The second airflow obstruction characterization quantity is the vector angle between the unit normal vector of the seating surface and the unit normal vector of the back seating surface in the second airflow crossing characterization vector set.

6. The method for detecting air permeability of an ergonomic chair according to claim 5, characterized in that: Determine, according to the air permeability interference characterization amount, a comparison between the first airflow obstruction characterization amount and the second airflow obstruction characterization amount; The air permeability interference characterization value is the difference between the first airflow obstruction characterization value and the second airflow obstruction characterization value.

7. The method for detecting air permeability of an ergonomic chair according to claim 6, characterized in that: The process of determining the air permeability interference category of a surface area includes: If the air permeability interference characterization quantity meets the pore distortion explicit condition, determining the air permeability interference category of the surface area as the pore distortion feature explicit category; If the air permeability interference characterization quantity does not meet the pore distortion explicit condition, determining the air permeability interference category of the surface area as a pore distortion feature non-explicit category; The pore distortion explicit condition is that the air permeability interference characterization value exceeds a preset air permeability interference characterization threshold.

8. The method for detecting air permeability of an ergonomic chair according to claim 7, characterized in that: Methods for determining the detection status simulation include: If the air permeability interference category of the surface area is a dominant category of pore distortion characteristics, the simulation verification method is determined to be applying a pulling force in opposite directions for a preset simulation time along the seating surface and the seating back surface parallel to the surface area; If the air permeability interference category of the surface area is a non-explicit category of pore distortion characteristics, the simulation verification method is determined to be to apply extrusion pressure in opposite directions along the seating surface and the back seating surface perpendicular to the surface area, respectively, for the preset simulation time period.

9. The method for detecting air permeability of an ergonomic chair according to claim 8, characterized in that: The value of the pulling force applied to the surface area is positively correlated with the second airflow obstruction characterization value, and the value of the squeezing force applied to the surface area is positively correlated with the second airflow obstruction characterization value.

10. The method for detecting air permeability of an ergonomic chair according to claim 1, characterized in that: Determining whether the air permeability of a surface area is abnormal includes: If the difference in air permeability before and after the detection state simulation satisfies the air permeability attenuation condition, it is determined that the air permeability of the surface area is normal; If the difference in air permeability before and after the detection state simulation does not satisfy the air permeability attenuation condition, it is determined that the air permeability of the surface area is abnormal; The air permeability attenuation condition is that the air permeability rate difference exceeds a preset air permeability rate attenuation reference value, and the air permeability rate is determined according to the gas flow rate per unit time.

Images