Textile physical property testing method based on sensor

Abstract

The invention relates to the technical field of textile physical performance testing, and discloses a textile physical performance testing method based on a sensor, and the method comprises the following steps: S1, processing before inspection, S2, preliminary information collection, S3, washing, and S4, low-tension extraction. S5, drying; S6, data processing; and S7, calculating the shrinkage rate. According to the technical scheme, the sample is lifted out of water in a horizontal lifting mode through the tray with the plane, the problem that after the sample is just washed, due to the fact that the self weight of the sample with water is large, the sample is prone to being pulled, and then irreversible deformation is generated is effectively solved, the operation mode is optimized, and the testing precision is effectively improved. By means of the tray with the pressure sensor matrix, whether the position of the sample is correct or not can be tested in the preliminary sample information collection process, it is guaranteed that the initial spreading state of the sample is qualified from the source, and follow-up test errors caused by improper sample spreading are avoided.

Description

Technical Field

[0001] This invention relates to the field of textile physical performance testing technology, specifically a sensor-based method for testing the physical performance of textiles. Background Technology

[0002] Existing textile shrinkage rate tests mostly rely on manual operation. The core process is as follows: first, samples are taken and cut into specifications that meet the test requirements. Then, the samples are placed in a standard environment for humidification. After humidification, physical marks are made on the sample surface. The initial distance between the marks is then measured. The samples are then subjected to standard washing. After washing, the samples are taken out and dried. After drying, the samples are flattened manually, and the final dimensions between each mark are measured. Finally, the shrinkage rate is calculated based on the initial and final dimension data.

[0003] The above testing method has the following problems:

[0004] 1. For flexible textiles, the sample is wet after washing. The wet fabric has low strength and high extensibility. When it is taken out of the washing machine, it is easily stretched and irreversible deformation occurs, which leads to measurement distortion.

[0005] Second, traditional measurement methods only measure the straight-line distance of the sample in the latitude and longitude directions, which can only reflect the overall shrinkage rate of the sample. They cannot effectively reflect areas with local shrinkage anomalies, and the test accuracy is limited. Summary of the Invention

[0006] This invention provides a sensor-based method for testing the physical properties of textiles, which has the advantage of higher testing accuracy and solves the problems mentioned in the background art, such as errors caused by improper operation and the inability to test local abnormal areas.

[0007] This invention provides the following technical solution: a sensor-based method for testing the physical properties of textiles, comprising the following steps:

[0008] S1. Pre-inspection treatment: Cut the fabric to the preset size to obtain a fabric sample, and then pre-treat the sample to release the internal stress of the sample.

[0009] S2. Preliminary Information Acquisition: Place the sample in the tray, capture an overall image of the sample and the tray before washing using a camera, and obtain the initial pressure distribution of the sample through the pressure sensor matrix inside the tray.

[0010] S3. Washing: Place the samples individually into the washing equipment, add detergent, and wash evenly according to the preset washing parameters;

[0011] S4. Low-tension removal: Immerse the tray in the washing machine, then spread the sample out and lay it flat on the tray. Then, while holding it horizontally, remove both from the washing machine and dehydrate them.

[0012] S5. Drying: Flatten the sample on the tray and put it into the drying equipment to dry. After drying, collect images of the sample and the tray and pressure distribution data again.

[0013] S6. Data processing: Compare the pressure distribution before and after washing, identify and mark the local shrinkage abnormal areas that warp or arch due to uneven shrinkage, and then calculate the ratio of the local shrinkage abnormal area to the whole sample to obtain the abnormal shrinkage ratio.

[0014] S7. Calculate the shrinkage rate: Using the size of the tray itself as a fixed reference, calculate the overall shrinkage rate of the sample by the size change of the sample relative to the tray.

[0015] After eliminating the areas with abnormal local shrinkage, only the effective areas with normal pressure and flat fit to the tray are measured to obtain the effective shrinkage rate of the sample.

[0016] As an optional solution to the sensor-based physical property testing method for textiles described in this invention, the tray is a rigid, low-deformation structure, and is used simultaneously as a dimensional reference, a dehydration component, and a sample carrier.

[0017] The tray is equipped with adsorption holes and a pressure sensor matrix. The adsorption holes can be connected to external vacuum equipment for vacuum adsorption and dehydration of samples on the tray surface.

[0018] As an optional solution to the sensor-based textile physical property testing method of the present invention, the method for marking the local shrinkage abnormality area is as follows:

[0019] Images of the sample and the tray are acquired using an industrial camera. A Cartesian coordinate system is established with the tray as the reference. Based on the coordinate information of all pressure sensors contained in the identified local shrinkage anomaly area, a closed contour of the anomaly area is generated using the contour enclosing method.

[0020] The abnormal shrinkage areas are filled with colored highlights to clearly distinguish them from the normal areas, allowing testers to visually identify the location, shape, and extent of the abnormality through the display device.

[0021] A center point marker is generated at the geometric center of the abnormal area, and the coordinates of the center point in the pallet coordinate system are output to achieve accurate physical positioning of the abnormal area.

[0022] As an optional solution of the sensor-based physical performance testing method for textiles described in this invention, in step S2, after obtaining the initial pressure distribution value of the sample through the pressure sensor matrix, the uniformity of the initial pressure distribution is judged. If the pressure value is within the set uniform range and there are no local pressure abrupt changes or pressure missing areas, the initial flat laying state of the sample is deemed qualified, and subsequent testing steps are continued.

[0023] If the pressure values ​​are unevenly distributed, or there are areas with excessively high or low pressure or areas with missing pressure, the initial flatness of the sample is deemed unqualified. The sample is then readjusted until the values ​​measured by the pressure sensor matrix meet the requirements.

[0024] When the sample is found to be substandard, the specific location of the substandard area is marked on the sample image captured by the industrial camera.

[0025] As an optional solution to the sensor-based textile physical property testing method of the present invention, in step S6, when identifying local shrinkage anomaly areas, anomaly area neighborhood judgment logic is used to eliminate isolated point misjudgments, specifically:

[0026] A neighborhood determination threshold is set. When a single sensor is abnormal, a preset number of neighboring sensors must be detected. Only when the sensor and at least two neighboring sensors meet the abnormality determination conditions and form a continuous sensor cluster is the area determined to be a local shrinkage abnormal area. If only a single sensor is abnormal and the surrounding sensors are normal, the abnormality is determined to be an isolated point interference and is not included in the local shrinkage abnormal area.

[0027] As an optional solution of the sensor-based physical property testing method for textiles described in this invention, in step S7, after removing local shrinkage abnormal areas, the effective area must meet the minimum area limit. Specifically, a minimum effective area threshold is preset, which is set according to the total sample area and is 50%-70% of the total sample area. After removing invalid areas, the total area of ​​the remaining effective areas is calculated. If the proportion of the total effective area to the total sample area is lower than the preset minimum area threshold, the test is deemed invalid, and the system prompts for resampling and retesting.

[0028] As an optional solution of the sensor-based physical performance testing method for textiles described in this invention, in step S7, when removing local shrinkage abnormal areas, a buffer zone of a preset width is expanded outward based on the closed contour of the abnormal area, and the buffer zone area and the original abnormal area are removed as invalid areas.

[0029] As an optional solution of the sensor-based physical property testing method for textiles described in this invention, the preliminary information acquisition in step S2 is carried out by a vision acquisition unit under fixed height, fixed focal length and uniform lighting conditions to capture an overall image containing the complete outline of the sample and the complete outline of the tray, and to record the pixel size and relative position relationship of the sample and the tray in the image.

[0030] The matrix pressure sensor embedded inside the starter tray collects the initial pressure value of the sample on each sensor, records the fixed coordinates of each pressure sensor and the corresponding initial pressure data, forming a complete pressure distribution matrix before washing, which serves as a benchmark for subsequent anomaly identification.

[0031] As an optional solution to the sensor-based method for testing the physical properties of textiles described in this invention, the specific steps for secondary information acquisition in step S5 are as follows:

[0032] Under the same shooting conditions as in step S2, take another overall image of the sample and the tray, and record the pixel size and relative positional relationship between the sample and the tray after washing.

[0033] Simultaneously, the pressure data of the sample on each sensor is collected again through the pressure sensor matrix to form a pressure distribution matrix after washing; the pressure data of the sensors at the same coordinate position before and after washing are compared, and the pressure change rate D of each sensor is calculated, where D=(Pbefore-Pafter) / Pbefore, Pbefore is the initial pressure value of the sensor at that coordinate position before washing, and Pafter is the pressure value of the sensor at that coordinate position after washing; a pressure change rate threshold is set, and the area where the sensor with a pressure change rate D exceeds the threshold is identified as a local shrinkage abnormal area.

[0034] Subsequently, a planar coordinate system was established with the tray as the reference. Based on the coordinates of all sensors in the abnormal area, the closed contour of the abnormal area was generated, and the specific location, coverage area and corresponding pressure change rate of the abnormal area were marked to clarify the degree of abnormality.

[0035] As an optional embodiment of the sensor-based method for testing the physical properties of textiles according to the present invention, the specific steps for releasing stress in step S1 are as follows:

[0036] First, the sample is placed in a standard environment with a temperature of 20±2℃ and a relative humidity of 65±5%RH for 24±2 hours to complete the pre-humidification. Then, the sample is suspended and left to stand for 12±2 hours to eliminate residual stress generated during fabric production and cutting, thus obtaining the pretreated sample.

[0037] The present invention has the following beneficial effects:

[0038] 1. This sensor-based method for testing the physical properties of textiles uses a flat tray to lift the sample from the water horizontally, effectively avoiding the problem that the sample is easily stretched and deformed due to its weight and water content immediately after washing. By optimizing the operation method, the testing accuracy is effectively improved.

[0039] 2. This sensor-based method for testing the physical properties of textiles allows for the collection of contact pressure distribution data for each area of ​​the sample by setting up a pressure sensor matrix on the tray. It records whether each sensor position is covered by the sample. Under normal circumstances, if the shrinkage rate of the sample is uniform, there will be no local bulging or collapse. If the shrinkage rate of the sample is uneven, there will definitely be local bulging or collapse. Utilizing this characteristic, local abnormal areas can be effectively identified. By detecting local abnormal areas, the overall shrinkage rate test accuracy of the sample is improved.

[0040] 3. This sensor-based method for testing the physical properties of textiles uses a tray equipped with a pressure sensor matrix to test the correctness of the sample's position during the initial sample information collection process. This ensures that the initial spread of the sample is qualified from the source, avoiding subsequent testing errors caused by improper spread. By using a computer combined with algorithms, the specific locations of unqualified areas are marked on the collected sample images, which can effectively improve spread efficiency, reduce the difficulty of manual operation, reduce the influence of human subjectivity, and achieve standardized spread. Attached Figure Description

[0041] Figure 1 This is a flowchart of the testing process for the present invention.

[0042] Figure 2 This is a diagram of the test system of the present invention.

[0043] Figure 3 This is a schematic diagram of the tray structure of the present invention. Detailed Implementation

[0044] 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 embodiments of the present invention, and not all embodiments. 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.

[0045] Example 1, please refer to Figures 1 to 3 A sensor-based method for testing the physical properties of textiles includes the following steps:

[0046] S1. Pre-test treatment: Cut the fabric to the preset size to obtain a fabric sample. Then, pre-treat the sample to release the internal stress. The cutting size is set according to the test requirements, usually 30cm×30cm, to ensure that the sample edges are flat, undamaged, and without skipped stitches.

[0047] S2. Preliminary Information Acquisition: Place the sample in the tray, capture an overall image of the sample and the tray before washing using a camera, and obtain the initial pressure distribution of the sample through the pressure sensor matrix inside the tray.

[0048] S3. Washing: Place the sample individually into the washing equipment, add detergent and wash evenly according to the preset washing parameters. The preset washing parameters are: washing temperature 40±2℃, washing time 30min, and rotation speed 120r / min.

[0049] S4. Low-tension removal: Immerse the tray in the washing machine, then spread the sample out and lay it flat on the tray. Then, while holding it horizontally, remove both from the washing machine and dehydrate them.

[0050] S5. Drying: Flatten the sample on the tray and put it into the drying equipment to dry. After drying, collect images of the sample and the tray and pressure distribution data again.

[0051] The drying process adopts a constant temperature and constant air mode, without clamping, squeezing, stretching, or manual flattening, to avoid external force causing sample deformation. The drying temperature of the drying device is set at 60±2℃ and the air speed is 0.5m / s. The moisture content of the sample is monitored in real time by a humidity sensor. When the moisture content drops below 8%, the drying is automatically stopped to avoid over-drying and sample deformation, ensuring that the sample shrinks naturally without additional deformation.

[0052] It should be noted that the size of the pallet may change slightly due to the high temperature. Therefore, data collection should be carried out only after the pallet has cooled down.

[0053] S6. Data processing: Compare the pressure distribution before and after washing, identify and mark the local shrinkage abnormal areas that warp or arch due to uneven shrinkage, and then calculate the ratio of the local shrinkage abnormal area to the whole sample to obtain the abnormal shrinkage ratio.

[0054] S7. Calculate the shrinkage rate: Using the size of the tray itself as a fixed reference, calculate the overall shrinkage rate of the sample by the size change of the sample relative to the tray.

[0055] After eliminating the areas with abnormal local shrinkage, only the effective areas with normal pressure and flat fit to the tray are measured to obtain the effective shrinkage rate of the sample.

[0056] The tray has a rigid, low-deformation structure and is used as a dimensional reference component, a dehydration component, and a sample carrier.

[0057] The tray is equipped with adsorption holes and a pressure sensor matrix. The adsorption holes can be connected to external vacuum equipment for vacuum adsorption and dehydration of samples on the tray surface.

[0058] Compared to the existing method of directly scooping samples out of the water by hand, this technical solution uses a flat tray to lift the sample out of the water horizontally, without pulling or dragging, thus avoiding stretching and deformation of the wet sample. By optimizing the operation method, the testing accuracy is effectively improved.

[0059] Since data needs to be collected before washing, a tray is needed to support the sample, and data needs to be collected after washing, a tray is also needed. Therefore, this technical solution directly uses a tray with stable dimensions as a reference object. The size information of the tray and the sample is collected before and after washing. By comparing the changes in the size of the sample before and after washing, the shrinkage rate can be directly obtained. The shrinkage rate is calculated by the formula: ((sample size before washing / tray size) - (sample size after washing / tray size)) ÷ (sample size before washing / tray size) × 100%.

[0060] Compared to traditional visual inspection techniques for calculating shrinkage rate, this shrinkage rate technology uses a tray as a reference object, which naturally provides a reference. Even slight changes in camera movement, tilt, or height will not affect the measurement results. In contrast, traditional visual inspection techniques rely entirely on the data collected by the camera for calculation. If the collected data is inaccurate, the results will also be inaccurate. This technology combines the reference component and the dehydration component into one, which not only makes the operation simpler but also makes the results more accurate.

[0061] By setting up a pressure sensor matrix on the tray, it is possible to further test local abnormal areas of the sample. Specifically, the pressure sensor matrix can collect contact pressure distribution data for each area of ​​the sample and record whether each sensor position is covered by the sample. Under normal circumstances, if the shrinkage rate of the sample is uniform, there will be no local bulging or collapse. If the shrinkage rate of the sample is uneven, there will definitely be local bulging or collapse. The pressure value of this local abnormal area will inevitably be different from that of other areas. Using this characteristic, local abnormal areas can be effectively identified. If there are many or severe local abnormal areas, it indicates that there are also problems with product quality. By detecting local abnormal areas, the overall sample shrinkage rate test accuracy is improved.

[0062] During the calculation, first, the total number of sensors Ntotal corresponding to the total sample area is counted. Then, the number of sensors corresponding to the local abnormal areas is counted, resulting in Nabnormal. Subtracting Nabnormal from Ntotal gives the number of sensors Nnormal in the normal areas. ，The algorithm converts the measured number and location of sensors into the location and area of ​​local abnormal and normal regions, and then substitutes these values ​​into the formula. This allows us to obtain the ratio of the local abnormal area to the normal area.

[0063] Substitute the previously measured data into the calculation formula. ,in:

[0064] S represents the overall shrinkage rate of the sample;

[0065] L0 is the actual area of ​​the sample relative to the tray before washing;

[0066] L1 represents the actual area of ​​the sample relative to the tray after washing.

[0067] When calculating the results, removing outlier data will yield the effective shrinkage rate of the sample.

[0068] Compared to the traditional method of measuring the straight-line distance between the warp and weft of a sample to detect its shrinkage rate, this technical solution can obtain data on local abnormal areas, the proportion of local abnormal areas to normal areas, the overall shrinkage rate of the sample, and the effective shrinkage rate of the sample. This can help users understand the quality issues related to the shrinkage rate of textiles from multiple dimensions.

[0069] Example 2 is an explanation based on Example 1. For details, please refer to [link / reference]. Figures 1 to 3 The method for marking the local shrinkage anomaly region is as follows:

[0070] Images of the sample and the tray are acquired using an industrial camera. A Cartesian coordinate system is established with the tray as the reference. Based on the coordinate information of all pressure sensors contained in the identified local shrinkage anomaly area, a closed contour of the anomaly area is generated using the contour enclosing method.

[0071] The abnormal shrinkage areas are filled with colored highlights to clearly distinguish them from the normal areas, allowing testers to visually identify the location, shape, and extent of the abnormality through the display device.

[0072] A center point marker is generated at the geometric center of the abnormal area, and the coordinates of the center point in the pallet coordinate system are output to achieve accurate physical positioning of the abnormal area, making it convenient for testers to quickly find the corresponding location.

[0073] In step S2, after obtaining the initial pressure distribution value of the sample through the pressure sensor matrix, the uniformity of the initial pressure distribution is judged. If the pressure value is within the set uniform range and there are no local pressure abrupt changes or pressure missing areas, the initial flat state of the sample is determined to be qualified, and subsequent test steps are continued.

[0074] If the pressure values ​​are unevenly distributed, or there are areas with excessively high or low pressure or areas with missing pressure, the initial flatness of the sample is deemed unqualified. The sample is then readjusted until the values ​​measured by the pressure sensor matrix meet the requirements.

[0075] When the sample is found to be substandard, the specific location of the substandard area is marked on the sample image captured by the industrial camera.

[0076] The pressure uniformity threshold can be pre-calibrated according to the sample material and thickness. For example, the pressure uniformity threshold for thin fabrics such as cotton and silk is set to ±15%, while the pressure uniformity threshold for heavy fabrics such as denim and canvas is set to ±20%. The criterion for pressure mutation is: the difference between the pressure value of a single sensor and the average pressure value of the surrounding area exceeds 30%. The criterion for pressure loss is: the sensor pressure value is lower than 0.5 Pa.

[0077] By using a tray equipped with a pressure sensor matrix, the correctness of the sample position can be tested during the initial sample information collection process. This ensures that the initial sample spreading state is qualified from the source, avoiding subsequent testing errors caused by improper sample spreading. By using a computer combined with algorithms, the specific location of unqualified areas can be marked on the collected sample images, which can effectively improve the efficiency of sample spreading, reduce the difficulty of manual operation, reduce the influence of human subjectivity, and achieve standardized sample spreading.

[0078] In step S6, when identifying local shrinkage anomaly regions, the anomaly region neighborhood judgment logic is used to eliminate isolated point misjudgments. Specifically:

[0079] A neighborhood determination threshold is set. When a single sensor is abnormal, a preset number of neighboring sensors must be detected. Only when the sensor and at least two neighboring sensors meet the abnormality determination conditions and form a continuous sensor cluster is the area determined to be a local shrinkage abnormal area. If only a single sensor is abnormal and the surrounding sensors are normal, the abnormality is determined to be an isolated point interference and is not included in the local shrinkage abnormal area to avoid misjudgment caused by a single sensor abnormality.

[0080] Adjacent sensors are defined as those that are horizontally or vertically adjacent to the sensor in question, excluding those that are diagonally adjacent.

[0081] When a single sensor malfunctions, at least three adjacent sensors must be detected.

[0082] The abnormal condition is that the pressure change rate D exceeds the preset threshold.

[0083] This step can effectively eliminate isolated point interference, avoid abnormal misjudgments caused by single sensor errors, dust interference, etc., improve the accuracy of identifying local shrinkage anomaly areas, ensure that the abnormal area identification results are true and reliable, and provide an accurate basis for subsequent invalid area removal and quality assessment.

[0084] In step S7, after removing abnormal shrinkage areas, the effective area must meet the minimum area limit. Specifically, a minimum effective area threshold is preset, which is set according to the total sample area and is 50%-70% of the total sample area. After removing invalid areas, the total area of ​​the remaining effective areas is calculated. If the proportion of the total effective area to the total sample area is lower than the preset minimum area threshold, the test is deemed invalid, and the system prompts for resampling and retesting to avoid distortion of the shrinkage rate calculation results due to insufficient effective area and to ensure the reliability of the test data.

[0085] For example, if the total area of ​​the sample is 900cm² (30cm×30cm) and the preset minimum area threshold is 70%, then the total area of ​​the effective region must be ≥630cm², otherwise the test will be invalid.

[0086] In step S7, when removing local shrinkage abnormal areas, a buffer zone of a preset width is extended outward based on the closed contour of the abnormal area. The buffer zone area and the original abnormal area are treated as invalid areas and removed together. The buffer zone area is the transition area between the abnormal area and the effective area. This area has problems such as uneven stress and unstable dimensional deformation. Removing it together can avoid interference from the transition area, improve the accuracy of the effective area data, and ensure the reliability of the shrinkage rate calculation results.

[0087] The width of the buffer zone is the spacing between 1 and 3 pressure sensors, which can be adjusted according to the sample thickness and testing accuracy. For thin fabrics, it is set to 1 spacing, and for thick fabrics, it is set to 3 spacings.

[0088] For example, if the pressure sensor spacing is 10mm and the buffer zone width is set to two spacings, i.e., 20mm, then the area within 20mm outside the outline of the abnormal area is considered as the buffer zone and is removed along with the abnormal area.

[0089] The preliminary information collection in step S2 involves capturing an overall image containing the complete outline of the sample and the complete outline of the tray at a fixed height (usually 50-80cm), with a fixed focal length and uniform illumination, using a vision acquisition unit. The pixel size and relative positional relationship between the sample and the tray in the image are recorded.

[0090] The matrix pressure sensor embedded inside the starter tray collects the initial pressure value of the sample on each sensor, records the fixed coordinates of each pressure sensor and the corresponding initial pressure data, forming a complete pressure distribution matrix before washing, which serves as a benchmark for subsequent anomaly identification.

[0091] The specific steps for secondary information collection in step S5 are as follows:

[0092] Under the same shooting conditions as in step S2, take another overall image of the sample and the tray, and record the pixel size and relative positional relationship between the sample and the tray after washing.

[0093] Simultaneously, the pressure data of the sample on each sensor is collected again through the pressure sensor matrix to form a pressure distribution matrix after washing; the pressure data of the sensors at the same coordinate position before and after washing are compared, and the pressure change rate D of each sensor is calculated, where D=(Pbefore-Pafter) / Pbefore, Pbefore is the initial pressure value of the sensor at that coordinate position before washing, and Pafter is the pressure value of the sensor at that coordinate position after washing; a pressure change rate threshold is set, and the area where the sensor with a pressure change rate D exceeds the threshold is identified as a local shrinkage abnormal area.

[0094] Subsequently, a planar coordinate system was established with the tray as the reference. Based on the coordinates of all sensors in the abnormal area, the closed contour of the abnormal area was generated, and the specific location, coverage area and corresponding pressure change rate of the abnormal area were marked to clarify the degree of abnormality.

[0095] The specific steps for releasing stress in step S1 are as follows:

[0096] First, the sample is placed in a standard environment with a temperature of 20±2℃ and a relative humidity of 65±5%RH for 24±2 hours to complete the pre-humidification. Then, the sample is suspended and left to stand for 12±2 hours to eliminate the residual stress generated during the fabric production and cutting process, thus obtaining the pre-treated sample.

[0097] Example 3 is an explanation based on Example 1. For details, please refer to [link / reference]. Figure 3 This embodiment discloses a sensor-based physical performance testing system for textiles, which includes a central processing unit, an information acquisition module, a tray module, a drying device, and a squeezing and dehydrating device.

[0098] The tray module is equipped with a pressure sensor matrix and adsorption holes. The drying equipment is used to dry the samples on the tray. The extrusion dehydration equipment has an extrusion plate, which can apply pressure and dehydrate the samples on the tray as a whole. Combined with the adsorption holes on the tray, it can effectively improve the dehydration efficiency, thereby improving the drying efficiency. The information acquisition module collects the measurement information of the pressure sensor matrix and the image information of the sample and the tray. The central processing unit is used to process the information and control the various devices.

[0099] It should be noted that, in this document, 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 process, method, article, or apparatus.

[0100] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A sensor-based method for testing the physical properties of textiles, characterized in that: Includes the following steps: S1. Pre-inspection treatment: Cut the fabric to the preset size to obtain a fabric sample, and then pre-treat the sample to release the internal stress of the sample. S2. Preliminary Information Acquisition: Place the sample in the tray, capture an overall image of the sample and the tray before washing using a camera, and obtain the initial pressure distribution of the sample through the pressure sensor matrix inside the tray. S3. Washing: Place the samples individually into the washing equipment, add detergent, and wash evenly according to the preset washing parameters; S4. Low-tension removal: Immerse the tray in the washing machine, then spread the sample out and lay it flat on the tray. Then, while holding it horizontally, remove both from the washing machine and dehydrate them. S5. Drying: Flatten the sample on the tray and put it into the drying equipment to dry. After drying, collect images of the sample and the tray and pressure distribution data again. S6. Data processing: Compare the pressure distribution before and after washing, identify and mark the local shrinkage abnormal areas that warp or arch due to uneven shrinkage, and then calculate the ratio of the local shrinkage abnormal area to the whole sample to obtain the abnormal shrinkage ratio. S7. Calculate the shrinkage rate: Using the size of the tray itself as a fixed reference, calculate the overall shrinkage rate of the sample by the size change of the sample relative to the tray. After eliminating the areas with abnormal local shrinkage, only the effective areas with normal pressure and flat fit to the tray are measured to obtain the effective shrinkage rate of the sample.

2. The sensor-based method for testing the physical properties of textiles according to claim 1, characterized in that: The tray has a rigid, low-deformation structure and is used as a dimensional reference component, a dehydration component, and a sample carrier. The tray is equipped with adsorption holes and a pressure sensor matrix. The adsorption holes can be connected to external vacuum equipment for vacuum adsorption and dehydration of samples on the tray surface.

3. The sensor-based method for testing the physical properties of textiles according to claim 1, characterized in that: The method for marking the local shrinkage anomaly region is as follows: Images of the sample and the tray are acquired using an industrial camera. A Cartesian coordinate system is established with the tray as the reference. Based on the coordinate information of all pressure sensors contained in the identified local shrinkage anomaly area, a closed contour of the anomaly area is generated using the contour enclosing method. The abnormal shrinkage areas are filled with colored highlights to clearly distinguish them from the normal areas, allowing testers to visually identify the location, shape, and extent of the abnormality through the display device. A center point marker is generated at the geometric center of the abnormal area, and the coordinates of the center point in the pallet coordinate system are output to achieve accurate physical positioning of the abnormal area.

4. The sensor-based method for testing the physical properties of textiles according to claim 1, characterized in that: In step S2, after obtaining the initial pressure distribution value of the sample through the pressure sensor matrix, the uniformity of the initial pressure distribution is judged. If the pressure value is within the set uniform range and there are no local pressure abrupt changes or pressure missing areas, the initial flat state of the sample is determined to be qualified, and subsequent test steps are continued. If the pressure values ​​are unevenly distributed, or there are areas with excessively high or low pressure or areas with missing pressure, the initial flatness of the sample is deemed unqualified. The sample is then readjusted until the values ​​measured by the pressure sensor matrix meet the requirements. When the sample is found to be substandard, the specific location of the substandard area is marked on the sample image captured by the industrial camera.

5. The sensor-based method for testing the physical properties of textiles according to claim 1, characterized in that: In step S6, when identifying local shrinkage anomaly regions, the anomaly region neighborhood judgment logic is used to eliminate isolated point misjudgments. Specifically: A neighborhood determination threshold is set. When a single sensor is abnormal, a preset number of neighboring sensors must be detected. Only when the sensor and at least two neighboring sensors meet the abnormality determination conditions and form a continuous sensor cluster is the area determined to be a local shrinkage abnormal area. If only a single sensor is abnormal and the surrounding sensors are normal, the abnormality is determined to be an isolated point interference and is not included in the local shrinkage abnormal area.

6. The sensor-based method for testing the physical properties of textiles according to claim 5, characterized in that: In step S7, after removing the abnormal shrinkage areas, the effective area must meet the minimum area limit. Specifically, a minimum effective area threshold is preset, which is set according to the total sample area and is 50%-70% of the total sample area. After removing the invalid areas, the total area of ​​the remaining effective areas is calculated. If the proportion of the total effective area to the total sample area is lower than the preset minimum area threshold, the test is deemed invalid, and the system prompts for resampling and retesting.

7. The sensor-based method for testing the physical properties of textiles according to claim 6, characterized in that: In step S7, when removing local shrinkage abnormal areas, a buffer zone of a preset width is expanded outward based on the closed contour of the abnormal area, and the buffer zone area and the original abnormal area are treated as invalid areas and removed.

8. The sensor-based method for testing the physical properties of textiles according to claim 1, characterized in that: The preliminary information acquisition in step S2 involves capturing an overall image containing the complete outline of the sample and the complete outline of the tray using a vision acquisition unit under fixed height, fixed focal length, and uniform lighting conditions, and recording the pixel size and relative positional relationship between the sample and the tray in the image. The matrix pressure sensor embedded inside the starter tray collects the initial pressure value of the sample on each sensor, records the fixed coordinates of each pressure sensor and the corresponding initial pressure data, forming a complete pressure distribution matrix before washing, which serves as a benchmark for subsequent anomaly identification.

9. The sensor-based method for testing the physical properties of textiles according to claim 1, characterized in that: The specific steps for secondary information collection in step S5 are as follows: Under the same shooting conditions as in step S2, take another overall image of the sample and the tray, and record the pixel size and relative positional relationship between the sample and the tray after washing. Simultaneously, the pressure data of the sample on each sensor is collected again through the pressure sensor matrix to form a pressure distribution matrix after washing; the pressure data of the sensors at the same coordinate position before and after washing are compared, and the pressure change rate D of each sensor is calculated, where D=(Pbefore-Pafter) / Pbefore, Pbefore is the initial pressure value of the sensor at that coordinate position before washing, and Pafter is the pressure value of the sensor at that coordinate position after washing; a pressure change rate threshold is set, and the area where the sensor with a pressure change rate D exceeds the threshold is identified as a local shrinkage abnormal area. Subsequently, a planar coordinate system was established with the tray as the reference. Based on the coordinates of all sensors in the abnormal area, the closed contour of the abnormal area was generated, and the specific location, coverage area and corresponding pressure change rate of the abnormal area were marked to clarify the degree of abnormality.

10. The sensor-based method for testing the physical properties of textiles according to claim 1, characterized in that: The specific steps for releasing stress in step S1 are as follows: First, the sample is placed in a standard environment with a temperature of 20±2℃ and a relative humidity of 65±5%RH for 24±2 hours to complete the pre-humidification. Then, the sample is suspended and left to stand for 12±2 hours to eliminate residual stress generated during fabric production and cutting, thus obtaining the pretreated sample.

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