Bed screen evaluation method, device and equipment based on supporting feeling and health property and medium

Abstract

The invention discloses a bed screen evaluation method, device and equipment based on supporting feeling and health, and a medium, and the method comprises the steps: collecting physical and mechanical data, including static stiffness characteristic data, dynamic fatigue response data and material creep behavior data, of a to-be-tested bed screen; performing support performance evaluation on the bed screen to be tested based on the static stiffness characteristic data to obtain a support performance index; performing health constraint on the to-be-tested bed screen through the health safety constraint logic to obtain a health and comfort index; quantifying the bed screen to be detected by combining the dynamic fatigue response data and the material creep behavior data to obtain a durability stability index; calculating a score of the bed screen to be tested in combination with a support performance index, a health and comfort index and a durability and stability index; and generating a reverse optimization strategy for the to-be-tested bed screen based on the score of the to-be-tested bed screen. According to the invention, bed screen evaluation with strong supporting feeling and human health can be realized, so that the problems that an existing bed screen is soft and weak, and spine instability is easily caused by long-time leaning are solved.

Description

Technical Field

[0001] This invention relates to the field of furniture design and testing technology, and in particular to a method, apparatus, equipment and medium for evaluating headboards based on support and health. Background Technology

[0002] With the evolution of the "bedroom as a living room" trend, the use of soft headboards has expanded from simply leaning against the pillow before sleep to core areas for prolonged leaning activities such as reading, working, and watching movies, significantly increasing the demands for comfort and functionality. However, current soft headboard designs often overemphasize the "softness" and "sinking feeling" upon initial sitting. This design approach reveals several problems under prolonged leaning scenarios: First, there is a "hammock effect," where insufficient lumbar support modulus can easily lead to lumbar kyphosis (straightening), increasing pressure on the intervertebral discs; second, the ease of getting up is poor, as the material absorbs too much energy and lacks rebound support, making it unfriendly to the elderly or those with lumbar muscle strain; third, durability is poor, as the low-density soft filling layer is prone to plastic deformation (collapse) after long-term pressure. At the same time, current evaluation methods for soft headboards mostly focus on initial experience indicators such as "fit" and "softness," lacking a systematic quantitative evaluation of key long-term use characteristics such as "support stability," "ease of getting up and sitting down," and "long-term fatigue resistance." Therefore, there is an urgent need for a relevant technical solution that can scientifically define the "strong support" characteristics and match the needs of long-term use. Summary of the Invention

[0003] This invention provides a method, device, computer equipment, and storage medium for evaluating headboards based on support and health, aiming to achieve headboard evaluation that combines strong support with human health, thereby solving the problem that existing headboards are "soft and weak" and that prolonged use can easily lead to spinal instability.

[0004] In a first aspect, embodiments of the present invention provide a method for evaluating headboards based on support and health, including: Physical and mechanical data are collected from the bed screen under test; wherein, the physical and mechanical data includes static stiffness characteristic data, dynamic fatigue response data, and material creep behavior data; Based on the static stiffness characteristic data, the support performance of the bed screen under test is evaluated to obtain the corresponding support performance index. The health and safety constraint logic is used to constrain the health of the bed screen under test, and the corresponding health and comfort index is obtained. The durability stability index of the bed screen under test is obtained by combining the dynamic fatigue response data and the material creep behavior data. The test bed headboard is scored by combining the support performance index, health and comfort index, and durability and stability index. A reverse optimization strategy is generated for the bed screen under test based on its score.

[0005] Secondly, embodiments of the present invention provide a headboard evaluation device based on support and health, comprising: The data acquisition unit is used to acquire physical and mechanical data of the bed screen under test; wherein, the physical and mechanical data includes static stiffness characteristic data, dynamic fatigue response data and material creep behavior data; The first evaluation unit is used to evaluate the support performance of the bed headboard under test based on the static stiffness characteristic data, and obtain the corresponding support performance index. The second evaluation unit is used to impose health constraints on the bed headboard under test through health and safety constraint logic to obtain the corresponding health and comfort index. The data quantification unit is used to combine the dynamic fatigue response data and the material creep behavior data to quantify the test bed screen to obtain the durability stability index. The scoring calculation unit is used to calculate a score for the bed headboard under test by combining the support performance index, health and comfort index and durability and stability index. The reverse optimization unit is used to generate a reverse optimization strategy for the bed screen under test based on the score of the bed screen under test.

[0006] Thirdly, embodiments of the present invention provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the headboard evaluation method based on support and health as described in the first aspect.

[0007] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the headboard evaluation method based on support and health as described in the first aspect.

[0008] This invention provides a method, apparatus, computer device, and storage medium for evaluating headboards based on support and health. The method includes: collecting physical and mechanical data of the headboard under test; wherein the physical and mechanical data includes static stiffness characteristic data, dynamic fatigue response data, and material creep behavior data; evaluating the support performance of the headboard under test based on the static stiffness characteristic data to obtain a corresponding support performance index; applying health and safety constraint logic to the headboard under test to obtain a corresponding health and comfort index; quantifying the headboard under test using the dynamic fatigue response data and material creep behavior data to obtain a durability and stability index; calculating a score for the headboard under test based on the support performance index, health and comfort index, and durability and stability index; and generating a reverse optimization strategy for the headboard under test based on the score. This invention collects various physical and mechanical data of the headboard under test, evaluates and quantifies the headboard from multiple dimensions such as support performance, health, and durability, and generates a reverse optimization strategy based on the scoring results. This allows for a comprehensive and systematic evaluation of the headboard's performance, achieving a headboard evaluation that combines strong support with human health, thereby solving the problem of existing headboards being "soft and weak" and prone to spinal instability when leaned against for a long time. Attached Figure Description

[0009] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0010] Figure 1 A flowchart illustrating a headboard evaluation method based on support and health, provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the appearance of a headboard in a headboard evaluation method based on support and health provided in an embodiment of the present invention; Figure 3 This is a schematic cross-sectional view of the headboard in a headboard evaluation method based on support and health provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of the use of a headboard in a headboard evaluation method based on support and health provided in an embodiment of the present invention; Figure 5 This is a schematic block diagram of a headboard evaluation device based on support and health, provided as an embodiment of the present invention. Detailed Implementation

[0011] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0012] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0013] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. 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 indicates otherwise.

[0014] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0015] Please see below. Figure 1 The present invention provides a method for evaluating headboards based on support and health, which specifically includes steps S101 to S106.

[0016] Step S101: Collect physical and mechanical data of the bed screen to be tested; wherein, the physical and mechanical data includes static stiffness characteristic data, dynamic fatigue response data and material creep behavior data; Step S102: Based on the static stiffness characteristic data, evaluate the support performance of the bed screen under test to obtain the corresponding support performance index; Step S103: Apply health constraints to the bed screen under test through health and safety constraint logic to obtain the corresponding health and comfort index; Step S104: Combine the dynamic fatigue response data and material creep behavior data to quantify the bed screen under test to obtain the durability stability index; Step S105: Calculate a score for the bed headboard under test by combining the support performance index, health and comfort index, and durability and stability index; Step S106: Generate a reverse optimization strategy for the bed screen under test based on the score of the bed screen under test.

[0017] In this embodiment, for the bed headboard under test, physical and mechanical data such as its static stiffness characteristics, dynamic fatigue response, and material creep behavior are first collected; then, the support performance is evaluated based on the static stiffness characteristic data to obtain the support performance index; a health and comfort index is obtained by applying health and safety constraint logic; and a durability and stability index is quantified by combining the dynamic fatigue response data and material creep behavior data; then, the bed headboard score is calculated by comprehensively considering the support performance index, health and comfort index, and durability and stability index; finally, a reverse optimization strategy is generated based on the score.

[0018] This embodiment collects various physical and mechanical data of the headboard under test, evaluates and quantifies the headboard from multiple dimensions such as support performance, health, and durability stability, and generates a reverse optimization strategy based on the scoring results. This allows for a comprehensive and systematic evaluation of the headboard's performance, achieving a headboard evaluation that combines strong support with human health, thereby solving the problem of existing headboards being "soft and weak" and prone to spinal instability when leaned against for a long time.

[0019] In practical applications, combined with Figures 2-4 The headboard described in this embodiment comprises, from the outside in: a leather fabric layer 1, non-adhesive cotton 2, a down and velvet blend 3, a bio-based suspension core 4, medium-density polyurethane foam 5, high-elasticity wide webbing 6, and a wooden frame 7. When the user naturally leans against the headboard, the leather fabric layer provides a comfortable feel, the non-adhesive cotton provides initial cushioning, and the down and velvet blend further enhances softness and fit. The bio-based suspension core is the key support structure; it can adaptively adjust the support force according to the pressure distribution of the body, providing sufficient support for key areas such as the waist, reducing the "hammock effect," and lowering intervertebral disc pressure. The medium-density polyurethane foam assists the bio-based suspension core in providing support, while also possessing a certain degree of elasticity and energy absorption capacity. The high-elasticity wide webbing is used to fix the internal filling material and provides additional elastic support, making it easier for the user to get up. The wooden frame, as the overall support structure of the headboard, ensures the stability and durability of the headboard.

[0020] In one embodiment, step S101 includes: The headboard to be tested is divided into a shoulder and neck area, an upper back area, and a waist area; Equivalent surface hardness was collected for the shoulder and neck area, upper back area, and waist area respectively; The waist reinforcement ratio is calculated based on the equivalent surface hardness of the upper back region and the equivalent surface hardness of the waist region. Based on the preset test points of the bed screen under test, a loading-unloading operation is performed on the bed screen under test, and the loading input power and unloading release power are collected during the loading-unloading process respectively; The full-cycle elastic recovery rate is calculated based on the loading input work and unloading release work, and the equivalent surface hardness, waist reinforcement ratio and full-cycle elastic recovery rate are summarized into the static stiffness characteristic data.

[0021] In addition, step S101 further includes: Based on the original thickness of the bed screen to be tested, the bed screen to be tested is compressed and left to stand still, and the final thickness after restoring is obtained. The compression permanent deformation data is calculated by combining the original thickness and the final thickness, and the compression permanent deformation data is set as the material creep behavior data. The initial reference hardness of the bed screen under test before fatigue is obtained, and multiple dynamic cyclic loads are applied to the back area of ​​the bed screen under test. Then the final hardness of the bed screen under test is obtained. The fatigue cycle retention rate is calculated by combining the initial reference hardness and the final hardness, and the fatigue cycle retention rate is set as the dynamic fatigue response data.

[0022] This embodiment constructs a multi-dimensional data acquisition system based on dynamic stability to collect static stiffness characteristics, dynamic fatigue response, and material creep behavior. Specifically: First, set up the test environment and benchmark settings: (1) All tests were conducted in a standard constant temperature and humidity environment (temperature 23±2℃, relative humidity 55±5%), and the samples were required to be left to stand for at least 24 hours in this environment.

[0023] (2) Define the effective support surface of the soft bed screen as the XY plane, and the normal direction perpendicular to the support surface as the Z axis (loading direction).

[0024] Secondly, a mechanical aging pretreatment simulating the break-in period was performed. To eliminate the initial false hardness of the material and simulate the actual condition after two weeks of user use, a differentiated pretreatment was applied to the bed headboard: (1) Using a universal material testing machine, with a rigid disc indenter with a diameter of Φ100mm and a 5mm rounded corner, high-frequency reciprocating compression is applied to the three core areas of the shoulder and neck, upper back and waist.

[0025] (2) The loading rate is set to 100 mm / min (or frequency 10 times / min), the compression depth is 40% of the nominal thickness, and the number of cycles at a single point is set to 20 times. This is intended to fully eliminate the micropore closure stress and initial mechanical hysteresis inside the polymer material, and ensure that the collected data reflects the true performance of the product after it enters the "stable support period".

[0026] Then, static physical support performance was collected. After preprocessing, the system was allowed to stand for 10 minutes before the formal loading test. (1) Obtaining the equivalent surface hardness (SHR) The pressure head was pressed down at a constant speed of 50 mm / min, and the force-displacement curve was recorded when the load reached 450 N (simulating the leaning force of a heavy-weight person). The shoulder and neck area, upper back area, and lumbar area of ​​the soft bed headboard were tested sequentially. The calculation formula is as follows: ; In the formula, This indicates the equivalent surface hardness of the soft bed, expressed in N / mm. The y-coordinate value (i.e., load value) of the corresponding coordinate point when the load reaches 450N, in N; The y-coordinate value (i.e., load value) of the corresponding coordinate point when the load reaches 50N, in N; The x-coordinate value (i.e., displacement value) of the corresponding coordinate point when the load reaches 450N, in mm; The x-coordinate value (i.e., displacement value) of the corresponding coordinate point when the load reaches 50N, in mm. Of course, in other embodiments, other load values ​​can be selected for equivalent surface hardness calculation.

[0027] (2) Calculation of waist reinforcement ratio (LBR) SHR values ​​were collected from the lumbar region and the upper back region respectively, and the ratio was calculated, i.e.: ; In the formula, The SHR (Self-Rating Length) refers to the arithmetic mean of multiple measurements or multi-point measurements taken within the lumbar region of the soft bed headboard test area. The SHR refers to the arithmetic mean of multiple measurements or multi-point measurements taken within the test area on the back of the soft bed screen.

[0028] (3) Full-cycle elastic recovery rate ( Collection of ) After completing the static hardness test, the indenter was continuously loaded and unloaded at a rate of 50 mm / min at the test point. After loading to 450 N (or 50% deformation), no holding time was set, and the indenter was immediately unloaded to 0 N at the same rate. Based on the acquired hysteresis loop curve, the total input power was calculated using numerical integration. and elastic release function The area under the loading curve is calculated, representing the total work done by the human body on the soft bed screen (i.e., the energy absorbed during the material compression process), and the total input work. The calculation formula is as follows: ; The area under the unloading curve is calculated, representing the effective mechanical energy released when the soft bed backs onto the human body. Elastic release work. The calculation formula is as follows: ; Elastic recovery rate ( Calculation formula: ; In the formula, This represents the applied force value. denoted as unloading force, and x as displacement.

[0029] Unlike memory foam and other high-damping materials ( Typically <40%, primarily focusing on energy absorption and shock absorption), this embodiment's "strong headboard support type" design requires... . high The value means that when the user's back leaves the headboard, the stored elastic potential energy can be quickly converted into kinetic energy, providing a significant "following thrust", effectively reducing the muscle work burden when the elderly or people with back injuries get up, and achieving a "firm yet flexible" support experience.

[0030] (4) Static creep resistance – compressive permanent deformation (CSET) test and calculation The sample was compressed to 30% of its original thickness (H0) and placed in a standard environment (temperature 23±2℃, relative humidity 55±5%) for 24 hours. After unloading, it was allowed to recover for 30 minutes, and its final thickness (H1) was measured. This characterizes the ability of the soft bed screen core material to resist plastic collapse (irreversible thickness loss) caused by static load. The lower the CSET value, the better the dimensional stability of the material, and the less likely it is to develop indentations over long-term use. The calculation formula is as follows: ; The classification is determined based on the calculation results. As a deduction or veto item: Excellent grade: CSET≤3% (high resistance to collapse); Good grade: CSET ≤ 4%; Passing grade (threshold): CSET≤6%.

[0031] (5) Dynamic hardness decay – fatigue cycle retention rate (FR) First, the initial reference hardness of the sample before fatigue was measured ( Ten dynamic cyclic loads were applied to the back region of the sample. The loading force ranged from 300N to 900N, the frequency was set to 1Hz, and the waveform was a sine wave. After the fatigue test, the corresponding hardness index was measured again. ), calculate retention rate: ; Characterizes the ability of a material to maintain its initial support modulus (SHR) after repeated mechanical work. It aims to simulate the decay of support force throughout its entire lifespan. For high-support products, the FR value should be ≥85% to ensure long-term use without softening or instability.

[0032] In one embodiment, step S102 includes: The static support performance of the bed headboard under test is evaluated by using the equivalent surface hardness of the upper back area and the waist reinforcement ratio, and the evaluation results of the static support performance are obtained. The dynamic rebound response performance of the bed screen under test is evaluated using the full-cycle elastic recovery rate, and the evaluation results of the dynamic rebound response performance are obtained. The evaluation results of the static support performance and the evaluation results of the dynamic rebound response performance are combined to form the support performance index.

[0033] The evaluation of the static support performance of the bed headboard by using the equivalent surface hardness of the upper back area and the waist reinforcement ratio, to obtain the evaluation results of the static support performance, includes: The equivalent surface hardness of the upper back area is compared with the first preset index requirement, and the waist reinforcement ratio is compared with the second preset index requirement. When the equivalent surface hardness of the upper back area meets the first preset index requirement and / or the waist reinforcement ratio meets the second preset index requirement, it is determined that the bed screen under test meets the static support performance requirements.

[0034] The dynamic rebound response performance of the bed screen under test is evaluated using the full-cycle elastic recovery rate, and the evaluation results of the dynamic rebound response performance are obtained, including: Compare the full-cycle elastic recovery rate with the third preset indicator requirement; When the full-cycle elastic recovery rate meets the third preset index requirement, it is determined that the bed screen under test has reached the dynamic rebound response performance requirement.

[0035] This embodiment establishes a digital three-dimensional judgment boundary for the "strong support" characteristic based on the collected physical and mechanical data. The bed headboard under test must simultaneously meet the requirements of both "static support performance" (index 1) and "dynamic rebound response" (index 2). Among them, static support performance must meet any one or two of the following characteristic indices: (1) Static support performance - adequacy judgment of benchmark hardness locking and gradient support The headboard under test must meet at least one of the following indicators to establish its static physical support properties: Indicator A: Upper back baseline hardness targeting and locking The equivalent surface hardness (SHR) of the upper back functional area is set to SHR∈(6.0,9.0)N / mm. This range is a "support-comfort" balance zone determined by ergonomic experiments. This hardness can provide efficient force transmission close to that of a rigid body, eliminate the "hammock effect" and abnormal spinal flexion caused by insufficient modulus, and retain the necessary cushioning deformation layer to maintain contact comfort.

[0036] Indicator B: Active lumbar gradient support The lumbar reinforcement ratio (LBR) was set to LBR > 1.25. This means that a significant longitudinal stiffness gradient (ΔK ≥ 25%) was constructed, forming a heterogeneous mechanical structure with "strong lumbar support and flexible back accommodation". This structure can actively fill the gaps in the physiological curvature of the lumbar spine and resist the tendency of posterior pelvic tilt.

[0037] (2) Dynamic rebound response - high-energy elastic potential energy feedback mechanism Requirement for overall elasticity recovery rate of soft bed screen High resilience means that the material has low mechanical hysteresis loss. When the user changes posture or gets up, the stored elastic potential energy can be quickly converted into kinetic energy, providing sensitive follow-up support and reducing the muscle work load when getting up.

[0038] In one embodiment, step S103 includes: Set the peak surface pressure and use the peak surface pressure to constrain the pressure test of the bed screen under test; The lumbar lordosis retention rate is set to anchor the neutral spinal morphology of the bed headboard under test.

[0039] This embodiment addresses the potential risk of localized compression from rigid support structures by introducing health and safety constraint logic. It constructs a biomechanical evaluation system based on a dual constraint of "pressure and posture," establishing an evaluation standard for "painless contact under rigid support." (1) Microcirculation pressure safety threshold (a veto indicator) Set peak surface pressure (P) peak The safety boundary is P. peak <9.0 kPa. This value takes into account both the physiological limit of capillary occlusion pressure in the human body and the influence of pressure exposure time. If P during the test... peak Exceeding this threshold for more than 1-2 hours indicates a high risk of obstructing blood microcirculation and causing tissue ischemia. This indicator has the highest priority; exceeding it renders the sample unqualified for health.

[0040] (2) Spinal neutral position morphological anchoring The lumbar lordosis retention rate (LLR) is set to be closer to 1.0 or slightly larger than 1.11 to avoid abnormal stress on sensitive areas such as the lumbar region caused by excessive spinal deviation. Secondly, by locking this range, the spine is forcibly guided into a neutral position with low shear force, fundamentally avoiding muscle fatigue and abnormal intervertebral disc pressure caused by postural compensation. Specifically: Lower limit constraint (0.9): Prevent lumbar kyphosis and ensure that the spine does not collapse due to insufficient support; Upper limit constraint (1.11): Allows for slight lordosis correction, designed to counteract the tendency of lumbar straightening common in modern sedentary populations.

[0041] In one embodiment, step S105 includes: The test bed panel is scored using a multidimensional weighted performance scoring system according to the following formula: ; Where S represents the score of the bed screen under test, W1, W2, and W3 are all weighting coefficients, and P supp H represents the support performance index. health D represents the health and comfort index. durability This indicates the durability and stability index.

[0042] To overcome the limitations of single-index evaluation, this embodiment constructs a multi-dimensional weighted performance scoring system of "support-health-durability" to achieve a comprehensive score for the headboard. In practical applications, the specific weighting coefficients can be: W1=0.4, W2=0.3, W3=0.3. The evaluation logic for each dimension index is as follows: (1) Support performance index P supp (Weight 40%) This indicator primarily assesses the product's static mechanical structure. It focuses on two parameters: lumbar reinforcement ratio (LBR) and standard stiffness (SHR), aiming to quantify the ability of the soft headboard to provide "precise zoned support" and "anti-kyphosis," ensuring that it meets the benchmark physical characteristics of "strong support."

[0043] (2) Health and comfort index H health (Weight 30%) This indicator primarily assesses the biomechanical compatibility of the human-bed interface. It focuses on peak pressure (P0). peak The pressure distribution gradient should be considered. While ensuring strong support, the pressure distribution should be uniform, without sudden high-pressure points, to prevent soft tissue damage or discomfort caused by excessive local shear force.

[0044] (3) Durability stability index D durability (Weight 30%) This metric incorporates a time dimension to assess the material's long-term resistance to degradation. It is quantified using fatigue hardness loss rate (FR) and compressive settling (CSET). The requirement is that the product maintains its initial support stiffness after undergoing standard cyclic loading, preventing support failure due to the collapse of the filler material.

[0045] This embodiment breaks through the limitation of traditional evaluations that only focus on the "initial state" and creatively introduces the durability dimension (D). durability This is used as a core evaluation item. It emphasizes that "strong support" must be "support stability throughout the entire life cycle," effectively avoiding the pseudo-support defects of some products on the market that are "too hard when first used and collapse after prolonged use."

[0046] In one embodiment, step S106 includes: The score of the bed screen under test is compared with a preset score threshold; When the score of the bed headboard under test is lower than the preset score threshold, optimization analysis is performed by combining the support performance index, health and comfort index and durability and stability index, and a corresponding optimization strategy is generated based on the results of the optimization analysis.

[0047] Specifically, the optimization analysis is performed by combining the support performance index, health and comfort index, and durability and stability index, and a corresponding optimization strategy is generated based on the results of the optimization analysis, including: When the result of the optimization analysis is the internal support problem of the bed screen under test, an optimization strategy for structural hierarchy gradient enhancement correction is generated; When the optimization analysis results indicate a problem with the surface tactile feel of the bed screen under test, an optimization strategy for fine-tuning the interface softening is generated. When the optimization analysis results in a durability and stability problem of the bed screen under test, an optimization strategy for improving material filling is generated.

[0048] In actual testing, if the headboard performance does not fully meet the design standards, this embodiment proposes a reverse engineering optimization strategy based on "modulus gradation." Through targeted structural adjustments and material upgrades, it achieves precise improvement in multiple performance indicators. The specific correction scheme is as follows: (1) Gradient enhancement correction for “insufficient lumbar support” (LBR<1.25) ① Structural heterogeneity: Abandoning the approach of simply increasing the thickness of a single material, a high-modulus reinforced insert is embedded in the core layer of the waist core support area (140mm-180mm from the seat surface). The insert material can be high-density EPE (expanded polyethylene) or independent pocket spring modules, constructing a composite support core that is "rigid inside and flexible outside".

[0049] ② Geometric shape preset: Adjust the forward protrusion of the waistline (L) protThe range is from 30mm to 40mm. By utilizing the geometric interference fit between the soft filling material and the curve of the human lumbar spine, a passive physical reaction force is generated to fill the gap in the lumbar spine.

[0050] (2) Regarding "overly hard touch" (P) peak Interface softening fine-tuning (>6.0kPa) Employing a "rigid-flexible decoupling" strategy, the high-rigidity support structure of the bottom and core layers remains unchanged, with only a 2-3cm thick low-rebound memory foam or latex layer added to the outermost layer in contact with the human body. The "thin, soft layer" on the surface increases the contact area, dispersing the shear force and normal pressure on the skin's surface; the "thick, hard core" in the deeper layer provides the necessary reaction force for the skeleton, achieving the ideal "soft skin, hard bone" tactile feel.

[0051] (3) For “poor durability” (CSET > 6% or FR < 85) Improved filling of ) Adjusting the polyurethane foam formulation to increase the isocyanate index or introducing high resilience (HR) reactive factors can improve the crosslinking density of the foam and optimize the hysteresis loss characteristics of the material, thereby enhancing fatigue resistance and ensuring that structural collapse does not occur under long-term cyclic loading.

[0052] In a practical application scenario, this embodiment proposes a soft bed headboard design with an embedded high-hardness lumbar support. The overall structure adopts an integrated composite filling structure, including the following parts: Fabric layer: Made of leather, providing a basic tactile experience and aesthetic texture for the soft headboard; Composite filling layer surface: Made of non-adhesive cotton material, the material's indentation hardness characteristic value HB25% is 0.42±0.03N, HB40% is 0.89±0.05N, HB65% is 2.39±0.03N, and the compression deformation characteristic is 5.67±0.28. It has lightweight, breathable, and primary cushioning characteristics, which can effectively improve the softness of the initial touch. Composite filling core layer: The composite structure is composed of down-filled material and bio-based suspended core material. The indentation hardness characteristic value of the bio-based suspended core material is 6.64±0.47N for HB25%, 9.47±0.31N for HB40%, and 14.73±0.06N for HB65%, with a compression deformation characteristic of 1.95±0.12. The whole structure has good support and air circulation. The bottom layer of the composite filling layer is made of medium-density polyurethane foam. The indentation hardness characteristic value of the material is 9.94±1.54N for HB25%, 11.03±0.82N for HB40%, and 13.38±0.36N for HB65%. The compression deformation characteristic is 1.26±0.02, which has a good support effect. Bottom support structure: The basic support element is a uniformly distributed high-elasticity wide webbing with a spacing of approximately 68mm. The average breaking strength of the wide webbing is 1711.98N and the average elongation at break is 322.89%. This is used to enhance the overall resilience and durability of the soft bed and avoid the risk of collapse during long-term use.

[0053] Based on the evaluation method provided in this embodiment, the equivalent surface hardness, waist reinforcement ratio, and elastic recovery rate of the upper back functional area of ​​the soft bed headboard were tested. The results are shown in Table 1 below: Table 1 (1) Based on the judgment criteria for the static support performance dimension in this embodiment: The sample to be tested must meet at least one of the following criteria to establish its static physical support properties: Indicator A: Upper back baseline hardness targeting and locking The equivalent surface hardness (SHR) of the upper back functional area is set to SHR∈(6.0,9.0)N / mm. This range is a "support-comfort" balance zone determined by ergonomic experiments. This hardness can provide efficient force transmission close to that of a rigid body, eliminate the "hammock effect" and abnormal spinal flexion caused by insufficient modulus, and retain the necessary cushioning deformation layer to maintain contact comfort.

[0054] Indicator B: Active lumbar gradient support Set the waist reinforcement ratio (LBR) to be This means that a significant longitudinal stiffness gradient (ΔK≥25%) is constructed, forming a heterogeneous mechanical structure with "strong lumbar support and flexible back accommodation". This structure can actively fill the gaps in the physiological curvature of the lumbar spine and resist the tendency of posterior pelvic tilt.

[0055] As can be seen, the equivalent surface hardness of the upper back functional area of ​​the soft headboard is 3.04±0.04 N / mm, and the lumbar reinforcement ratio is 1.32. Although it does not meet the targeted locking requirement of index A for the upper back reference hardness, it meets the threshold requirement range of index B for the lumbar reinforcement ratio, thus achieving a support effect of strong lumbar support and flexible back contact. Therefore, the soft headboard meets the judgment requirements for the static support performance dimension in this embodiment.

[0056] (2) Based on the determination criteria for the dynamic rebound response dimension in this embodiment: Requirement for overall elasticity recovery rate of soft bed screen High resilience means that the material has low mechanical hysteresis loss. When the user changes posture or gets up, the stored elastic potential energy can be quickly converted into kinetic energy, providing sensitive follow-up support and reducing the muscle work load when getting up.

[0057] As can be seen, the overall elastic recovery rate of the soft headboard is 62.10±6.88%, exceeding the threshold requirement range for the dynamic rebound response dimension. This indicates that the soft headboard has relatively good resilience and can provide significant "following thrust," effectively reducing the muscle workload when elderly people or those with back injuries get up, achieving a "firm yet flexible" support experience. Therefore, the soft headboard meets the judgment requirements for the dynamic rebound response dimension in this embodiment.

[0058] In summary, this soft headboard meets the requirements of both "static support performance" and "dynamic rebound response," thus conforming to the design requirements of a "strong support" soft headboard.

[0059] Furthermore, based on the technical solution of this embodiment, the static creep resistance and dynamic hardness decay of the soft bed screen were tested. The obtained compression set (CSET) result was less than 3%, which is excellent and has high resistance to collapse; the obtained fatigue cycle retention (FR) result was ≥85%, indicating that the soft bed screen can be used for a long time without softening or becoming unstable.

[0060] Furthermore, based on the technical solution of this embodiment, the microcirculation pressure safety threshold and spinal neutral position anchoring of the soft bed headboard were tested. The obtained peak surface pressure (P) peak The pressure was 6.36 ± 1.33 kPa, which is less than the set safety boundary of 9.0 kPa, meeting the microcirculation pressure safety threshold requirements. The obtained lumbar lordosis retention rate (LLR) was 0.96, which is within the set threshold range of LLR ∈ (0.9, 1.11), and the result is close to 1.0. This indicates that the soft headboard has a good ability to maintain the natural curvature of the spine and can effectively avoid abnormal stress on sensitive areas such as the lumbar region caused by excessive spinal deviation.

[0061] In conclusion, the soft bed screen design proposed in this embodiment is ultimately rated as a good support product.

[0062] In summary, compared with existing technologies, the headboard evaluation method based on support and health provided in this embodiment has the following significant advantages: (1) Most existing technologies use a subjective "soft / hard" approach to qualitatively describe the backrest feel of soft beds, lacking engineering standards. This embodiment innovatively constructs a quantitative feature model with a benchmark equivalent hardness (SHR∈6.0-9.0N / mm) and lumbar reinforcement ratio (LBR>1.25) as the core. It transforms the vague physical sensation into measurable numerical indicators, accurately defining the "strong support" benchmark suitable for long-term leaning scenarios such as reading and office work. It clarifies the R&D goals for furniture manufacturers and effectively avoids the "hammock effect" and abnormal spinal flexion caused by insufficient support modulus.

[0063] (2) Traditional hard headboards can easily cause excessive pressure on the back contact surface, hindering blood microcirculation. This embodiment constructs a system based on a "pressure safety fuse mechanism" (… The system employs a modulus gradation system of "soft skin and firm bone" and "micro-flexible surface." By using the low-modulus surface material to disperse shear force and the high-modulus core material to lock the bone position, a composite mechanical feel of "soft skin and firm bone" is successfully achieved. While forcibly maintaining the neutral position of the human spine, it ensures that there is no risk of ischemia in the subcutaneous tissue, greatly improving the comfort of users leaning on it for extended periods.

[0064] (3) Addressing the quality problem of upholstered furniture in the market that is "hard at first but collapses at last," this embodiment breaks through the traditional evaluation model that only focuses on the initial state and innovatively introduces the time dimension, incorporating the durability dimension (weight 30%) into the core evaluation system. By assessing the fatigue hardness loss rate (FR) and compression set (CSET), inferior products that only have "false initial hardness" are screened out. This ensures that the product can still maintain the gradient support characteristics of "hard in the waist and flexible in the back" after a long period of leaning, effectively extending the effective service life of the product.

[0065] (4) Unlike the high damping energy absorption characteristics of traditional memory foam materials, this embodiment explicitly requires the soft bed screen to have a high elasticity recovery rate. Utilizing the low mechanical hysteresis loss characteristics of high-resilience materials, the elastic potential energy stored when the body leans against the mattress is converted into kinetic energy the instant the body stands up, providing a sensitive "follow-up thrust". This significantly reduces the muscle workload of the elderly, pregnant women, and people with lumbar muscle strain when standing up, and improves the user-friendliness of the soft bed screen's human-computer interaction.

[0066] (5) This embodiment not only provides a set of evaluation standards, but also a set of reverse optimization methods based on "modulus gradation". When the sample does not meet the standard, it clearly indicates the ways to make corrections through specific methods such as "structural heterogeneity (embedded hard core)", "morphological pre-setting (geometric interference)" and "interface softening". It transforms the traditional "trial and error" R&D into evidence-based "directed optimization", which significantly shortens the development cycle of high-performance soft bed screens.

[0067] (6) This embodiment is specifically designed for high-frequency bedtime reading and bedroom office scenarios in modern life, as well as for people with high body weight (BMI>24) or mild lumbar spine problems. By anchoring the lumbar lordosis retention rate (LLR), it actively fills the gap in the lumbar region and resists posterior pelvic tilt, playing a role similar to a "soft orthosis" and effectively preventing chronic lumbar and back injuries caused by poor sitting posture.

[0068] Figure 5 A schematic block diagram of a headboard evaluation device 500 based on support and health, provided in an embodiment of the present invention, the device 500 comprising: The data acquisition unit 501 is used to acquire physical and mechanical data of the bed screen under test; wherein, the physical and mechanical data includes static stiffness characteristic data, dynamic fatigue response data and material creep behavior data; The first evaluation unit 502 is used to evaluate the support performance of the bed headboard under test based on the static stiffness characteristic data, and obtain the corresponding support performance index. The second evaluation unit 503 is used to impose health constraints on the bed headboard under test through health and safety constraint logic to obtain the corresponding health and comfort index. The data quantization unit 504 is used to combine the dynamic fatigue response data and the material creep behavior data to quantify the test bed screen to obtain the durability stability index. The scoring calculation unit 505 is used to calculate a score for the bed headboard under test by combining the support performance index, health and comfort index and durability and stability index. The reverse optimization unit 506 is used to generate a reverse optimization strategy for the bed screen under test based on the score of the bed screen under test.

[0069] In one embodiment, the data acquisition unit 501 includes: The area division unit is used to divide the headboard under test into the shoulder and neck area, the upper back area, and the waist area; The area acquisition unit is used to acquire equivalent surface hardness data for the shoulder and neck area, upper back area, and waist area, respectively. The first calculation unit is used to calculate the waist reinforcement ratio based on the equivalent surface hardness of the upper back region and the equivalent surface hardness of the waist region. The energy acquisition unit is used to perform loading-unloading operations on the bed screen under test based on the preset test points of the bed screen under test, and to collect the loading input energy and unloading release energy respectively during the loading-unloading process; The second calculation unit is used to calculate the full-cycle elastic recovery rate based on the loading input work and unloading release work, and to summarize the equivalent surface hardness, waist reinforcement ratio and full-cycle elastic recovery rate into the static stiffness characteristic data.

[0070] In one embodiment, the data acquisition unit 501 further includes: The thickness acquisition unit is used to compress and allow the bed screen to stand still based on its original thickness, and to acquire the final thickness after restoring. The first setting unit is used to calculate the compression permanent deformation data by combining the original thickness and the final thickness, and set the compression permanent deformation data as the material creep behavior data; The hardness acquisition unit is used to acquire the initial reference hardness of the bed screen under test before fatigue, and to apply multiple dynamic cyclic loads to the back area of ​​the bed screen under test, and then acquire the final hardness of the bed screen under test. The second setting unit is used to calculate the fatigue cycle retention rate by combining the initial reference hardness and the final hardness, and set the fatigue cycle retention rate as the dynamic fatigue response data.

[0071] In one embodiment, the first evaluation unit 502 includes: The static evaluation unit is used to evaluate the static support performance of the bed headboard under test by using the equivalent surface hardness of the upper back area and the waist reinforcement ratio, and to obtain the evaluation results of the static support performance. The dynamic evaluation unit is used to evaluate the dynamic rebound response performance of the bed screen under test using the full-cycle elastic recovery rate, and obtain the evaluation result of the dynamic rebound response performance. The result summarization unit is used to summarize the evaluation results of the static support performance and the evaluation results of the dynamic rebound response performance and set them as the support performance index.

[0072] In one embodiment, the static evaluation unit includes: The first comparison unit is used to compare the equivalent surface hardness of the upper back area with the first preset index requirement, and to compare the waist reinforcement ratio with the second preset index requirement. The first determination unit is used to determine that the bed screen under test meets the static support performance requirements when the equivalent surface hardness of the upper back area meets the first preset index requirement and / or the waist reinforcement ratio meets the second preset index requirement.

[0073] In one embodiment, the dynamic evaluation unit includes: The second comparison unit is used to compare the full-cycle elastic recovery rate with the third preset index requirement; The second determination unit is used to determine that the bed screen under test has reached the dynamic rebound response performance requirement when the full-cycle elastic recovery rate meets the third preset index requirement.

[0074] In one embodiment, the second evaluation unit 503 includes: A pressure constraint unit is used to set the peak pressure on the body surface and to constrain the pressure test of the bed screen under test using the peak pressure on the body surface. The morphological anchoring unit is used to set the lumbar lordosis retention rate to anchor the neutral spinal morphology of the bed headboard under test.

[0075] In one embodiment, the scoring calculation unit 505 includes: The weighted calculation unit is used to calculate and score the bed screen under test according to the following formula, using a multi-dimensional weighted performance scoring system: ; Where S represents the score of the bed screen under test, W1, W2, and W3 are all weighting coefficients, and P supp H represents the support performance index. health D represents the health and comfort index. durability This indicates the durability and stability index.

[0076] In one embodiment, the reverse optimization unit 506 includes: The third comparison unit is used to compare the score of the bed screen under test with a preset score threshold. The optimization analysis unit is used to perform optimization analysis in combination with the support performance index, health and comfort index and durability and stability index when the score of the bed headboard under test is lower than the preset score threshold, and generate a corresponding optimization strategy based on the results of the optimization analysis.

[0077] In one embodiment, the optimization analysis unit includes: The first generation unit is used to generate an optimization strategy for structural hierarchy gradient enhancement correction when the result of the optimization analysis is the internal support problem of the bed screen under test. The second generation unit is used to generate an optimization strategy for interface softening and fine-tuning when the result of the optimization analysis is a problem with the surface tactile feel of the bed screen under test. The third generation unit is used to generate an optimization strategy for improving material filling when the result of the optimization analysis is a durability and stability problem of the bed screen under test.

[0078] Since the embodiments of the apparatus and the embodiments of the method correspond to each other, please refer to the description of the embodiments of the method for the embodiments of the apparatus, which will not be repeated here.

[0079] This invention also provides a computer-readable storage medium storing a computer program thereon, which, when executed, can perform the steps provided in the above embodiments. The storage medium may include various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0080] This invention also provides a computer device, which may include a memory and a processor. The memory stores a computer program, and when the processor calls the computer program in the memory, it can implement the steps provided in the above embodiments. Of course, the computer device may also include various network interfaces, power supplies, and other components.

[0081] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to in the method section. It should be noted that those skilled in the art can make various improvements and modifications to this application without departing from the principles of this application, and these improvements and modifications also fall within the protection scope of the claims of this application.

[0082] It should also be noted that, in this specification, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

Claims

1. A bed screen evaluation method based on support feeling and health, characterized by, The method comprises the following steps: collecting physical and mechanical data of the bed screen to be tested; wherein the physical and mechanical data comprises static stiffness characteristic data, dynamic fatigue response data and material creep behavior data; evaluating the support performance of the bed screen to be tested based on the static stiffness characteristic data to obtain a corresponding support performance index; constraining the health of the bed screen to be tested through health and safety constraint logic to obtain a corresponding health and comfort index; quantifying the durability and stability index of the bed screen to be tested in combination with the dynamic fatigue response data and the material creep behavior data; calculating the score of the bed screen to be tested in combination with the support performance index, the health and comfort index and the durability and stability index; generating a reverse optimization strategy for the bed screen to be tested based on the score of the bed screen to be tested.

2. The bed screen assessment method based on support feeling and health according to claim 1, characterized by, The collecting of the physical and mechanical data of the bed screen to be tested comprises the following steps: dividing the bed screen to be tested into a shoulder and neck area, an upper back area and a waist area; collecting equivalent surface hardness of the shoulder and neck area, the upper back area and the waist area respectively; calculating the waist reinforcement ratio according to the equivalent surface hardness of the upper back area and the equivalent surface hardness of the waist area; loading and unloading the bed screen to be tested based on the preset test points of the bed screen to be tested, and collecting loading input work and unloading release work respectively during the loading and unloading process; calculating the full cycle elastic recovery rate according to the loading input work and the unloading release work, and combining the equivalent surface hardness, the waist reinforcement ratio and the full cycle elastic recovery rate into the static stiffness characteristic data.

3. The bed screen assessment method based on support feeling and health according to claim 1, characterized by, The collecting of the physical and mechanical data of the bed screen to be tested further comprises the following steps: compressing and standing the bed screen to be tested based on the original thickness of the bed screen to be tested, and obtaining the final thickness after standing recovery; calculating the compression permanent deformation data in combination with the original thickness and the final thickness, and setting the compression permanent deformation data as the material creep behavior data; obtaining the initial reference hardness of the bed screen to be tested without fatigue, and applying multiple dynamic cyclic loads to the back area of the bed screen to be tested, and then obtaining the final hardness of the bed screen to be tested; calculating the fatigue cycle retention rate in combination with the initial reference hardness and the final hardness, and setting the fatigue cycle retention rate as the dynamic fatigue response data.

4. The bed screen assessment method based on support feeling and health according to claim 2, characterized by, The evaluating of the support performance of the bed screen to be tested based on the static stiffness characteristic data to obtain the corresponding support performance index comprises the following steps: evaluating the static support performance of the bed screen to be tested by using the equivalent surface hardness of the upper back area and the waist reinforcement ratio to obtain the evaluation result of the static support performance; evaluating the dynamic rebound response performance of the bed screen to be tested by using the full cycle elastic recovery rate to obtain the evaluation result of the dynamic rebound response performance; combining and setting the evaluation result of the static support performance and the evaluation result of the dynamic rebound response performance as the support performance index.

5. The bed screen assessment method based on support feeling and health according to claim 4, characterized by, The evaluating of the static support performance of the bed screen to be tested by using the equivalent surface hardness of the upper back area and the waist reinforcement ratio to obtain the evaluation result of the static support performance comprises the following steps: comparing the equivalent surface hardness of the upper back area with the first preset index requirement, and comparing the waist reinforcement ratio with the second preset index requirement; When the equivalent surface hardness of the upper back area meets the first preset index requirement and / or the waist reinforcement ratio meets the second preset index requirement, it is determined that the bed screen to be tested meets the static support performance requirement.

6. The bed screen assessment method based on support feeling and health according to claim 4, wherein, The full-cycle elastic recovery rate is used to evaluate the dynamic rebound response performance of the bed screen to be tested, and an evaluation result of the dynamic rebound response performance is obtained, including: The full-cycle elastic recovery rate is compared with a third preset index requirement; When the full-cycle elastic recovery rate meets the third preset index requirement, it is determined that the bed screen to be tested meets the dynamic rebound response performance requirement.

7. The bed screen assessment method based on support feeling and health according to claim 1, wherein, The health safety constraint logic is used to constrain the health of the bed screen to be tested, and a corresponding health comfort index is obtained, including: A body surface peak pressure is set, and the pressure test of the bed screen to be tested is constrained by using the body surface peak pressure; A lumbar lordosis retention rate is set to anchor the spinal neutral position form of the bed screen to be tested.

8. The bed screen assessment method based on support feeling and health according to claim 1, wherein, The support performance index, the health comfort index, and the durability stability index are combined to calculate a score of the bed screen to be tested, including: The multi-dimensional weighted performance score system is used to calculate the score of the bed screen to be tested according to the following formula: ； Wherein, S represents the score of the bed screen to be tested, W1, W2, W3 are weight coefficients, P supp represents the support performance index, H health represents the health comfort index, D durability represents the durability and stability index.

9. The bed screen assessment method based on support and health according to claim 1, wherein, Based on the score of the bed screen to be tested, a reverse optimization strategy is generated for the bed screen to be tested, including: The score of the bed screen to be tested is compared with a preset score threshold; When the score of the bed screen to be tested is lower than the preset score threshold, optimization analysis is performed in combination with the support performance index, the health comfort index, and the durability stability index, and a corresponding optimization strategy is generated according to the result of the optimization analysis.

10. The bed screen assessment method based on support and health according to claim 1, wherein, The optimization analysis is performed in combination with the support performance index, the health comfort index, and the durability stability index, and a corresponding optimization strategy is generated according to the result of the optimization analysis, including: When the result of the optimization analysis is an internal support problem of the bed screen to be tested, an optimization strategy of structure level gradient enhancement correction is generated; When the result of the optimization analysis is a surface touch problem of the bed screen to be tested, an optimization strategy of interface softening fine tuning is generated; When the result of the optimization analysis is a durability stability problem of the bed screen to be tested, an optimization strategy of material filling improvement is generated.

11. A bed screen assessment device based on support and health, characterized by, It includes: A data acquisition unit is configured to acquire physical and mechanical data of the bed screen to be tested, wherein the physical and mechanical data includes static stiffness characteristic data, dynamic fatigue response data, and material creep behavior data; A first evaluation unit is configured to evaluate the support performance of the bed screen to be tested based on the static stiffness characteristic data, and obtain a corresponding support performance index; A second evaluation unit is configured to constrain the health of the bed screen to be tested by health safety constraint logic, and obtain a corresponding health comfort index; A data quantification unit is configured to quantify the durability stability index of the bed screen to be tested in combination with the dynamic fatigue response data and the material creep behavior data; A score calculation unit is configured to calculate a score of the bed screen to be tested in combination with the support performance index, the health comfort index, and the durability stability index; A reverse optimization unit is configured to generate a reverse optimization strategy for the bed screen to be tested based on the score of the bed screen to be tested.

12. A computer device, comprising: The computer readable storage medium stores a computer program, and the computer program is executed by the processor to realize the bed screen assessment method based on support feeling and health as claimed in any one of claims 1 to 10.

13. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is executed by the processor to realize the bed screen assessment method based on support feeling and health as claimed in any one of claims 1 to 10.

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