Footwear wearing comfort testing equipment and method

Abstract

The invention discloses a footwear wearing comfort test device and method, and belongs to the technical field of footwear detection. The equipment integrates a full-foot pressure sensing network, a double-ball-screw mechanical loading module, an environment insight module and a bionic intelligent foot model system, and can monitor foot pressure distribution, wearing and taking-off mechanical characteristics, a microenvironment in a shoe and a motion posture in all directions. A simulation system covering more than 20 kinds of dynamic scenes is constructed, a multi-dimensional comfort evaluation model is established based on a deep learning algorithm, and quantitative indexes such as pressure balance degree, buffer performance and microenvironment score are automatically generated. Intelligent data support is provided for shoe product design optimization and industrial standard formulation, the method is particularly suitable for detection of shoe types such as sports shoes and medical orthopedic shoes with strict requirements for comfort, and it is ensured that consumers obtain more comfortable and safer shoe products.

Description

Technical Field

[0001] The present invention belongs to the technical field of footwear testing equipment, and specifically relates to a device and method based on multi-parameter synchronous acquisition and deep fusion analysis that can detect the overall wearing comfort of various types of shoes with ultra-high precision and all-round perspective. The device integrates cutting-edge sensing technology, precision mechanical testing system and intelligent environmental monitoring means to achieve accurate quantitative evaluation of the wearing comfort of shoes in static and dynamic scenarios, and is widely applicable to all types of shoes such as sports shoes, casual shoes, leather shoes, medical orthopedic shoes, children's shoes, high heels, outdoor hiking shoes, etc. Background Art

[0002] There is a lack of current footwear comfort detection technology. On the one hand, pressure detection methods are backward. For example, in the patent No. CN202321097189.1 "A foot detection device", although it can quickly and accurately obtain the user's calcaneal tilt, the structure is simple and the cost is low, it is limited to the detection of calcaneal tilt. For other areas of the foot such as the arch and forefoot during the wearing of shoes, the pressure distribution and comfort conditions fail to provide comprehensive detection data, and cannot meet the needs of overall footwear comfort detection. On the other hand, the reliability of the wearing and removing force test is low. At present, in the field of footwear wearing and removing force testing, when traditional handheld tensile gauges are used to test the peak penetration force, they are affected by multiple factors such as poor manual operation stability, the accuracy limitations of the instrument itself, and the test environment. There are large errors, which makes it difficult to accurately reflect the actual wearing and removing characteristics of the footwear, and it is impossible to provide reliable data for footwear design optimization. Furthermore, the dynamic test scenario is single and industry standards are missing. Most existing equipment can only simulate walking on flat ground, but lacks complex action simulation. In addition, the market testing methods and equipment are disorganized and lack unified standards. The pass rate of footwear comfort labeling is low, which hinders the standardization process of the industry. This invention provides a basis for the formulation of footwear comfort test standards with innovative testing technology and accurate data. Summary of the invention

[0003] The present invention solves the above-mentioned problems through the following innovations.

[0004] The first full-foot pressure sensing network: Integrates up to 2048 MEMS pressure sensing units, which are finely divided according to the anatomy of the human foot. The heel area is a 16×32 matrix, the arch area is a multi-layer arc array according to complex curves, and the forefoot area is a 24×32 honeycomb layout. The unit spacing is as low as 1.5mm, the density exceeds 5 / cm², and the full area covers 0.5mm-level pressure distribution reconstruction to accurately capture the subtlest pressure changes in the foot.

[0005] Construction of mechanical testing system: adopting double ball screw linkage transmission mechanism, matched with high-performance AC servo motor drive, the donning and doffing speed can be precisely controlled between 0.05 - 5cm / s, with an accuracy of ±0.02cm / s; introducing a high-precision force sensor matrix (range 0 - 800N, accuracy ±0.05% FS) to synchronously monitor multi-directional donning and doffing force changes to ensure accurate mechanical testing.

[0006] Create an environmental insight module: Integrate thermistor high-precision temperature sensors (accuracy ±0.1℃), capacitive high-sensitivity humidity sensors (accuracy ±1% RH) and MEMS heat flow sensor arrays to fully monitor the temperature, humidity and heat flow inside the shoes; embed an angle sensor (accuracy ±0.3°) combining a MEMS gyroscope and accelerometer to track the relative movement of the foot and shoe in real time, and evaluate the shoe's wrapping and adaptability characteristics at 360°.

[0007] Designed with extremely rich dynamic simulation conditions: the simulation covers more than 20 typical scenarios such as daily walking, running, jumping, going up and down stairs, walking on slopes, and moving sideways. The motion parameters of the foot model are finely adjustable, and combined with pressure, mechanics, and environmental data, the dynamic comfort performance of the shoe is analyzed from all aspects.

[0008] Create an intelligent comprehensive evaluation model: Based on a deep learning algorithm, the model is trained by integrating massive test data to automatically generate a quantitative report on the overall comfort of shoes in multiple dimensions, including pressure balance, arch fit coefficient, cushioning performance index, microenvironment comfort score, and wearing and taking off smoothness index, providing intelligent guidance for improving the quality of shoes.

[0009] The present invention is not only a tool in the field of footwear comfort testing, but also a basis for the construction of future industry standards.

[0010] Equipment structure. This super-precision equipment is collaboratively constructed by the following core modules.

[0011] Full foot pressure detection module.

[0012] Heel area: 512 MEMS pressure sensing units are carefully arranged and tightly embedded in a 0.6mm thick medical silicone substrate (Shore hardness 35A) in a 16×32 matrix. The unit spacing is 1.5mm, the single sensor range is 0 - 250kPa, the non-linear error is ≤ ±0.3% FS, and the temperature drift is < 0.01% FS / ℃.

[0013] Arch area: According to the complex physiological curve of the arch, 768 flexible MEMS pressure sensors are customized and distributed in a multi-layer arc array. The substrate is made of Shore hardness 40A material with a measuring range of 0 - 200kPa. It can accurately sense the dynamic pressure of the arch support. The signal processing uses a combination of ultra-low noise instrument amplifier and high-order low-pass filter to ensure signal purity.

[0014] Forefoot area: 768 MEMS pressure sensing units are embedded in a 24×32 honeycomb layout, with a flexible substrate (Shore hardness 30A) adapted to the curvature of the forefoot, a unit spacing of 1.5mm, and a range of 0-220kPa. The data acquisition units in each area transmit 24-bit digital signals at a rate of 200Hz through a high-speed optical fiber channel to achieve real-time and ultra-precise acquisition of foot pressure.

[0015] Mechanical loading module.

[0016] The core adopts a double ball screw linkage transmission mechanism, driven by a high-performance AC servo motor, with a movement speed of 0.05-5cm / s accurately adjustable and an accuracy of ±0.02cm / s.

[0017] Equipped with a high-precision force sensor matrix, including 4 S-type tension sensors (range 0 - 800N, accuracy ±0.05% FS) and 4 pressure sensors (range 0 - 500N, accuracy ±0.05% FS), which are distributed in a circular manner at the key nodes of the donning and doffing path to capture the changes in force during the donning and doffing process in all directions.

[0018] Equipped with an FPGA + ARM dual-core controller with super computing power, it has 10 built-in finely optimized test modes, which are deeply customized for the mechanical properties of different types of shoes, from the high elasticity requirements of sports shoes to the precise support and adaptation of medical orthopedic shoes, and precise testing.

[0019] Environmental insight module.

[0020] Temperature and humidity monitoring: Selected thermistor high-precision temperature sensors (accuracy ±0.1℃) and capacitive high-sensitivity humidity sensors (accuracy ±1% RH) are distributed three-dimensionally at key parts such as the toe, arch, and heel. Data is collected every 15 seconds to monitor changes in the microenvironment inside the shoe in real time.

[0021] Heat flow monitoring: Introduce MEMS heat flow sensor array to accurately measure the heat accumulation and diffusion rate in the shoe, and analyze the impact of heat distribution on comfort.

[0022] Angle posture monitoring: An angle sensor (accuracy ±0.3°) embedded with a MEMS gyroscope and accelerometer is installed at multiple key connection points of the upper, sole, and vamp to track the relative movement of the foot and shoe in real time, whether turning, jumping, or going up and down stairs, providing full insight into the shoe's wrapping and adaptability characteristics.

[0023] Bionic intelligent auxiliary module.

[0024] It provides an ultra-stable constant temperature and humidity test environment of 23 ± 1℃, 50 ± 3% RH. The simulated foot model is carefully made with a 3D printed titanium alloy skeleton and a multi-layer gradient silicone coating (the hardness gradually changes from Shore 60A on the sole to Shore 40A on the ankle). The arch curvature, toe spacing, etc. are strictly customized in accordance with GB / T 3293.1 - 2017 and the latest research results on human foot biomechanics. It is suitable for testing shoes of various sizes and styles to ensure test accuracy and authenticity.

[0025] Detailed analysis of global pressure.

[0026] Static pressure precision measurement: The system simultaneously activates the pressure sensors in all areas of the foot and continuously collects pressure data for 6 minutes at a frequency of 200Hz. The pressure standard deviation (SD) of the forefoot contact area (area ≥ 75%), the arch support area (area ≥ 65%), and the heel contact area (area ≥ 85%) are accurately calculated. In combination with the research results of cutting-edge ergonomics, when the forefoot pressure standard deviation exceeds 32kPa, the arch pressure standard deviation exceeds 22kPa, and the heel pressure standard deviation exceeds 28kPa, the pressure distribution in the corresponding area is judged to be unqualified, and a visual pressure cloud map is generated through a high-resolution display screen to intuitively and accurately present the details of the uneven pressure distribution in each area.

[0027] Dynamic pressure tracking: The simulated foot model is manipulated to simulate walking at a frequency of 1.5Hz. The inclination angle increases from 0° to 18° during the heel contact phase (0-30% cycle), and the toe lifting action is simulated during the sole-off phase (70%-100% cycle). The inclination angle increases from 0° to 12°, and complex movements such as running, jumping, and going up and down stairs are also incorporated. The system records the pressure change rate ΔP / Δt in each area in real time. If the forefoot ΔP / Δt>65kPa / s and lasts for 4 gait cycles, the arch area ΔP / Δt>45kPa / s and lasts for 3 gait cycles, or the heel area ΔP / Δt>55kPa / s and lasts for 4 gait cycles, the corresponding area buffer performance warning is triggered, and the tester is prompted by intelligent voice.

[0028] Deep insights into microenvironment and exercise adaptability.

[0029] The temperature and humidity inside the shoe are monitored in real time, and data is collected every 15 seconds. When the temperature is higher than 28°C or the humidity is higher than 65%RH and lasts for more than 2 minutes, the microenvironment inside the shoe is judged to be uncomfortable, which may cause stuffiness, sweating and other discomforts in the feet. At the same time, combined with the heat flow sensor data, the heat accumulation area is analyzed to provide optimization direction for the heat dissipation design of the upper and insole.

[0030] Based on the angle sensor data, the relative angle change curve between the foot and the shoe is deeply analyzed when simulating more than 20 complex scenarios. For example, in a slope walking scenario, if the shoe's side tilt angle is greater than 12° and the recovery is slow, it means that the outer side of the shoe is insufficiently supported; in a running scenario, if the toe lifting angle is limited and the angle change is less than 6° for more than 30% of the gait cycle, it indicates that the toe space or flexibility is poor. The system automatically generates an analysis report with pictures and texts and pushes it to the terminal.

[0031] Extremely precise test of putting on and taking off force.

[0032] Shoe-wearing test: Strictly follow the ISO 17707:2018 standard and deeply optimize it, push the foot model at a speed of 3cm / s, and record the maximum penetration force Fmax. According to the latest industry standards and massive ergonomic research data, the maximum penetration force threshold of sports shoes is set at 55N (leather shoes 42N, high heels 32N, children's shoes 48N, outdoor hiking shoes 60N, etc.). When the threshold is exceeded, the equipment automatically stops and marks it as unqualified. At the same time, a high-definition camera is used to capture the moment of wearing and taking off to assist in analyzing the root cause of the problem.

[0033] Shoe removal test: The system pulls back the foot mold at a speed of 3cm / s and records the maximum penetration force Fmax. When the force gradient ΔF / Δt>12N / ms is detected, it is judged as a shoe mouth jam defect. The test data is transmitted to the cloud server in real time through the 5G network. Combined with big data analysis and deep learning models, force-displacement curves, pressure distribution time-space superposition maps, and overall shoe comfort quantitative scores are generated to fully display the shoe wearing comfort characteristics and provide one-stop data support for shoe design and production. Beneficial Effects

[0034] Comfort evaluation: Based on the footwear detection technology, this invention can evaluate the overall wearing comfort of shoes with extreme accuracy and from a full-dimensional perspective. By monitoring the pressure of the entire contact area between the foot and the shoe, the microenvironment inside the shoe, the mechanics and angle changes under motion, and relying on the deep learning model, a comprehensive quantitative evaluation report covering pressure balance, cushioning performance, microenvironment suitability, wrapping flexibility, heat distribution optimization, etc. is generated. This provides consumers with a purchase reference like a professional foot consultant, allowing them to say goodbye to subjective assumptions and understand the comfort performance of shoes in various scenarios based on scientific and detailed data; it presents a comprehensive product improvement direction like a design blueprint for shoe manufacturers, from sole cushioning to upper breathability, from shoe shape cutting to shoe opening tightness, all links can be optimized and upgraded based on accurate data.

[0035] Promotion of industry standards: During product development, companies can use this device to simulate multiple wearing scenarios, quickly develop new comfortable footwear products, and greatly shorten the development cycle; the key link of quality control provides a standardized and intelligent testing process for the quality control of finished shoes, ensuring that the shoes entering the market meet high standards of comfort; in terms of standard setting, the accumulated large amount of accurate test data will become the basis for building a unified comfort test standard for the industry, filling the gaps in the current lack of industry standards, and driving the footwear industry to develop in the direction of high quality and high comfort. This invention is not only an innovation in the field of footwear testing, but also a trend in future footwear research and development, laying the foundation for unifying industry standards and upgrading product quality. DETAILED DESCRIPTION

[0038] Example 1 (high-performance sports shoe test), set the donning and doffing speed to 3 cm / s, the dynamic test tilt angle to 15°, and execute the following process.

[0039] a. Figure 2 As shown, the high-performance sports shoes to be tested are fixed on the ultra-precision test bench, and the foot mold (such as Figure 1 Insert the shoe into the shoe cavity until the fifth metatarsal process is perfectly aligned with the heel, ensuring that the foot mold is positioned to fit the high-performance design of the sports shoe.

[0040] b. Start a 6-minute static test. When the pressure in the first metatarsal area (coordinates X = 20.5mm, Y = 8.2mm) is greater than 180kPa for 12 seconds, a red laser warning is triggered, prompting the operator that the pressure in this area is too high and that the insole or the forefoot power nest design of the sole needs to be checked, such as whether the shock absorbing material needs to be upgraded or the sole pattern needs to be optimized to enhance grip and pressure dispersion.

[0041] c. Perform 60 dynamic walking cycles. If the peak change rate of forefoot pressure is greater than 70 kPa / s for 6 consecutive times, it is determined that the forefoot cushioning layer may have failed. If the peak change rate of heel pressure is greater than 60 kPa / s for 4 consecutive times, combined with the angle sensor data, if the heel tilt angle is greater than 10° and recovers slowly, it indicates that the heel stabilization system design needs to be improved. At the same time, monitor the temperature inside the shoe. If it exceeds 32°C, it is recommended to optimize the upper breathable structure.

[0042] Example 2 (customized medical orthopedic shoe test), adjustment parameters: donning and doffing speed 2cm / s, static test extended to 12 minutes, dynamic tilt disabled. For medical orthopedic shoes, focus on monitoring the pressure value of the arch support area (coordinate X = 22 - 28mm), and set the alarm threshold to 125kPa.

[0043] Disabling dynamic tilt is to reduce interference and more accurately monitor the pressure distribution in the arch support area. In the 12-minute static test, if the standard deviation of the arch support area pressure is greater than 22kPa, combined with the 3D scanning feedback of the simulated foot model, it is determined whether the arch support structure in the shoe fits the patient's unique arch curve and whether the hardness, shape or position of the support pad needs to be fine-tuned.

[0044] During the putting on and taking off test, if the insertion force is greater than 42N, the shoe opening structure is analyzed to see whether it is too hard or too tight, which is not conducive to the patient putting on and taking off. Combined with the heat flow data, it provides a scalpel-like precise basis for the personalized customization of medical orthopedic shoes, ensuring that every pair of orthopedic shoes can bring the best comfort and rehabilitation assistance to patients. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1: 3D structure diagram of the foot model, with multiple MEMS arrays on the instep, forefoot, arch, heel and other parts.

[0046] Figure 2: Schematic diagram of the donning and doffing force test.

Claims

1. A footwear comfort test device, characterized in that: include: Pressure detection module, mechanical loading module, environmental insight module, bionic intelligent assistance module and intelligent comprehensive evaluation module; The pressure detection module is used to collect the contact pressure distribution between the foot and the shoe in real time; The mechanical loading module is used to simulate the donning and doffing process and accurately measure the donning and doffing force; The environmental insight module is used to monitor the temperature and humidity inside the shoe, the heat flow, and the relative movement posture between the foot and the shoe; The bionic intelligent auxiliary module is used to provide a constant temperature and humidity test environment and a simulated foot model; The intelligent comprehensive evaluation module is used to generate a quantitative report on the overall comfort level of the shoe based on multi-dimensional data.

2. A footwear wearing comfort testing device according to claim 1, characterized in that: The pressure detection module includes: a heel area pressure sensing unit, an arch area pressure sensing unit, and a forefoot area pressure sensing unit; The heel area pressure sensing units are arranged in a 16×32 matrix, with a unit spacing of ≤1.5mm and a density of ≥5 / cm²; The arch area pressure sensing units are distributed in a multi-layer arc array along the physiological curve of the arch; The pressure sensing unit in the forefoot area is arranged in a 24×32 honeycomb pattern to adapt to the curvature of the forefoot.

3. A footwear wearing comfort testing device according to claim 1, characterized in that: The mechanical loading module includes: a double ball screw linkage transmission mechanism and a high-precision force sensor matrix; The double ball screw linkage transmission mechanism is driven by a high-performance AC servo motor, and the donning and doffing speed can be precisely controlled between 0.05-5cm / s, with an accuracy of ±0.02cm / s; The high-precision force sensor matrix includes an S-type tension sensor and a pressure sensor with a measuring range of 0-800N and an accuracy of ±0.05% FS.

4. A footwear wearing comfort testing device according to claim 1, characterized in that: The environmental insight module includes: a thermistor temperature sensor, a capacitive humidity sensor, a MEMS heat flow sensor array, and an angle sensor; The thermistor temperature sensor has an accuracy of ±0.1°C; The capacitive humidity sensor has an accuracy of ±1% RH; The MEMS heat flux sensor array is used to measure the heat accumulation and diffusion rate in the shoe; The angle sensor is composed of a MEMS gyroscope and an accelerometer, with an accuracy of ±0.3°.

5. The footwear wearing comfort testing device according to claim 1, characterized in that: The bionic intelligent auxiliary module includes: 3D printed titanium alloy frame and multi-layer gradient silicone coating, with hardness gradually changing from 60A at the sole to 40A at the ankle; The test environment is kept at a constant temperature and humidity, with the temperature controlled at 23±1°C and the humidity controlled at 50±3% RH.

6. The footwear wearing comfort testing device according to claim 1, characterized in that: The intelligent comprehensive evaluation module includes: A comfort evaluation model based on deep learning algorithms is used to generate a quantitative report including pressure balance, arch fit coefficient, cushioning performance index, microenvironment comfort score, and wearing and taking off smoothness index; Data visualization interface, used to display pressure cloud diagrams, force-displacement curves, and angle change graphs.

7. A method for testing the wearing comfort of footwear, characterized in that: The following steps are involved: a. Collect the contact pressure distribution between the foot and the shoe through the pressure detection module; b. Simulate the donning and doffing process through the mechanical loading module and measure the donning and doffing force; c. Provide a constant temperature and humidity test environment and simulated foot model through the bionic intelligent auxiliary module; d. Monitor the temperature and humidity inside the shoe, heat flow, and the relative movement of the foot and shoe through the environmental insight module; e. Generate a quantitative report on the overall comfort of the shoes through an intelligent comprehensive evaluation module.

8. A footwear wearing comfort testing method according to claim 7, characterized in that: The pressure distribution acquisition step comprises: Static pressure test: collect pressure data continuously for 6 minutes at a frequency of 200 Hz, and calculate the standard deviation of pressure in the forefoot, arch and heel contact areas; Dynamic pressure test: simulates more than 20 typical scenarios such as walking, running, jumping, etc., and records the pressure change rate of each area in real time.

9. A footwear wearing comfort testing method according to claim 7, characterized in that: The step of measuring the putting on and taking off force comprises: Shoe-wearing test: Push the foot mold at a speed of 3cm / s and record the maximum penetration force Fmax; Shoe-off test: Pull back the foot mold at a speed of 3cm / s and record the maximum penetration force Fmax.

10. A footwear wearing comfort testing method according to claim 7, characterized in that: The comfort quantification report generation step comprises: Based on deep learning algorithms, it integrates pressure, mechanics, environment and motion posture data to generate a multi-dimensional comfort score; The test data is transmitted to the cloud server in real time via the network for big data analysis and model optimization.

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