15054 results about "Woven fabric" patented technology

The invention provides a textile defect positioning method, which comprises the following steps: according to an extracted defect feature map, fusing feature maps of different scales, extracting multi-scale defect features, and comprehensively depicting space distribution and combination information of defects; aiming at the condition that multiple flaws exist at the same time, a multi-task learning model is constructed, flaw detection, classification and positioning tasks are carried out at the same time, and a back propagation algorithm is adopted to optimize the multi-task learning model; positioning the defect area by adopting an image segmentation algorithm, obtaining the contour of the defect area according to the positioning result of the defect area and by adopting a Canny edge detection algorithm, and calculating the area and position information of the defect; and based on an evaluation result, a dynamic threshold adjustment algorithm is adopted, a defect judgment threshold is adjusted according to a production batch and a product type, and a threshold parameter is dynamically updated by analyzing historical data and a current production condition.

The invention provides a textile blending proportion defect detection method, which comprises the following steps: carrying out continuous image acquisition on a blended textile in a vibration state, and adjusting the exposure time and frame rate of camera equipment according to vibration frequency and amplitude characteristics to obtain a textile surface image sequence; the obtained textile surface image sequence is preprocessed, and warp and weft areas are segmented according to the surface texture features of the blended textile; based on the abnormal degree evaluation model, constructing a blending proportion flaw classifier, and training the classifier to identify different types of blending proportion flaws by using the warp and weft abnormal features, the fiber distribution features and the texture features as input; according to a blending proportion defect classifier, in combination with defect positioning requirements in a vibration environment, performing real-time tracking on detected different types of defect proportion areas, compensating image displacement caused by vibration, and ensuring that a defect detection result corresponds to an actual textile position.

The invention discloses an intelligent textile production line control method and system, and relates to the technical field of industrial automation, and the method comprises the steps: collecting operation data in a textile production process in real time, and carrying out the data preprocessing; dynamically adjusting process parameters of the textile production line based on the preprocessed data; detecting the quality state in the textile production process in real time, and adjusting the operation of the production line based on the detection result; constructing a multi-feature fusion fault prediction model, and predicting the operation state of the production line equipment; potential faults are recognized in advance according to prediction results, and the operation mode of the production line is adjusted. The method combines multi-feature fusion analysis, dynamically optimizes the equipment operation state, identifies and adjusts potential faults in advance, improves the production quality and efficiency, reduces the maintenance cost and the shutdown risk, is significantly superior to a traditional method, and provides powerful technical support for intelligent upgrading of the textile industry.

A graphene-infused fabric is provided as a sound reducing acoustic layer for object such as a pickleball paddle. The graphene-infused fabric is made from polymer fibers, at least one of which is a graphene-infused polymer fiber. Graphene is blended into a polymer material, and fibers are manufactured from said material such as by extrusion. The graphene-infused polymer is combined with other fibers to be made into a woven or non-woven fabric.

The invention discloses an automatic textile color fastness rating method and system based on a CNN-Transform fusion model, and relates to the technical field of textile digital detection. And then, feature extraction and rating are carried out by using a CNN-Transform fusion model. After the features of the two are fused, weighting is carried out through an attention mechanism, classification is carried out through a full-connection layer, and the color fastness grade probability is determined through a Softmax function. Meanwhile, a cross entropy loss function is combined with a label smoothing technology, an Adam optimizer is utilized, and a learning rate attenuation strategy is matched to train the model. Finally, confidence evaluation and result correction are carried out on the rating result, automatic and high-precision textile color fastness rating is achieved, and the problems that an existing rating method is poor in accuracy, low in consistency, difficult to adapt to fine rating standards and the like are effectively solved.

The invention relates to the technical field of composite fiber non-woven fabric manufacturing, in particular to a composite fiber non-woven fabric tensile property testing device which comprises a base, and an n-shaped support and a limiting sliding way located under the horizontal section of the n-shaped support are fixedly installed on the upper end face of the base. And a stretching mechanism for stretching the composite fiber non-woven fabric front and back is arranged on the limiting slide way. The tensile property test of the composite fiber non-woven fabric is completed by adopting an integrated operation model of stretching, twisting and extruding, the test reliability is improved by adopting a fixing mode of combining clamping of upper and lower cambered surfaces with matching of a rubber plate, a convex block and a groove, and meanwhile, the tensile property of the composite fiber non-woven fabric is improved through plane stretching, twisting and plane stretching tests after twisting as well as downward extruding and stretching of a middle section. The composite fiber non-woven fabric tensile property testing device can simulate complex stress conditions possibly faced by the composite fiber non-woven fabric in practical application, so that the tensile property of the composite fiber non-woven fabric in multiple stress states is comprehensively evaluated, multiple testing modes are realized on a single device, and the overall testing efficiency is improved.

A fireproof magnesium oxide board is prepared by mixing the following raw materials, the raw material names and weight parts are as follows: 80-100 parts of magnesium oxide; 20-30 parts of anhydrous magnesium chloride; 10-20 parts of modified expanded vermiculite foaming agent; 20-30 parts of aluminum silicate fiber; 5-10 parts of sawdust; 10-15 parts of fly ash; 8-12 parts of glass magnesium board crushed powder; 1.5-5 parts of non-woven fabric; 10-20 parts of water; wherein the modified expanded vermiculite is prepared by the following steps: (1) Vermiculite is incompletely expanded and calcined; (2) acrylic acid monomer, sodium hydroxide, acrylamide monomer, initiator potassium persulfate, crosslinking aid pentaerythritol polyglycidyl ether, incompletely expanded vermiculite, and water are taken, stirred evenly and ultrasonically dispersed to obtain a first reaction solution, which is placed in a reactor for reaction to obtain a gel material; (3) the gel material is preliminarily crushed and dried, and then further crushed in a ball mill to obtain a fire-resistant expanded vermiculite with water absorption performance.

The invention discloses an automatic testing device and method for multi-directional tensile strength of textiles based on constant tension, and relates to the technical field of tensile strength detection.The automatic testing device comprises a rigid rack system, and a high-elastic fabric optical response mechanism is integrated on a double-stand-column portal frame of the rigid rack system; the fiber damage process is reflected through the light transmittance of light to the fabric and the light spot change; the high-elastic fabric optical response mechanism comprises a sealing light insulation assembly, a light source assembly and an imaging assembly. The light source assembly comprises pulse LED light source arrays arranged at equal intervals in the fabric stretching direction, a lampshade and a transverse movement driving unit. The problems that in the prior art, when the tensile strength of a fabric is detected, only the limit value when a sample is completely broken can be recorded, and microcracks generated by step-by-step failure of fibers in the stretching process cannot be captured are solved. The device has the advantages that when the tensile strength of the fabric is detected, the fiber fracture process in the fabric is directly reflected through the change of light spots formed by light penetrating through the fabric, and the like.

An ink jet textile printing method according to one embodiment of the present disclosure includes a reaction solution attaching step of attaching a reaction solution containing an aggregating agent that aggregates components in an ink, and water to a fabric using an ink jet method, a transparent ink attaching step of attaching a transparent ink composition containing anionic resin particles and water to a fabric using the ink jet method, and a colored ink attaching step of attaching a colored ink composition containing a pigment, resin particles, and water onto a region, to which the transparent ink composition is attached, using the ink jet method, in which the reaction solution attaching step and the transparent ink attaching step include Step 1, and in Step 1, a range of a minimum value of a total attachment amount of the reaction solution and the transparent ink composition per unit area / per unit time is 34 mg / (s·inch2) or more, Step 1: applying the reaction solution and the transparent ink composition to the same region in the fabric in a single scanning of an ink jet head.

The invention discloses a textile production defect detection method and system based on image processing, and belongs to the field of textile defect detection. According to the method, the point cloud data is generated by collecting the surface deformation stripes, and the penetrability reflection signal containing the sound wave propagation time is obtained through the multi-frequency ultrasonic probe. Denoising the point cloud data and then positioning a surface deformation candidate area based on a curvature gradient and a normal vector deflection angle; and an internal abnormal region is determined by separating and extracting a reflection wave amplitude value and a time delay parameter through an ultrasonic frequency band. And matching the surface point cloud coordinates with the ultrasonic propagation time by adopting an iterative nearest point algorithm to establish feature association between the normal vector deflection angle and the reflected wave amplitude. And dynamically distributing fusion weights for the surface features and the internal features according to the curvature gradient change rate and the amplitude attenuation rate to generate a multi-modal defect distribution diagram. And geometric shape and reflection intensity parameters are extracted and matched with a preset defect template to realize type and position judgment, and the method can be suitable for production defect detection of the thick textile with a multi-layer composite material structure.

The invention provides a textile defect type identification method, and relates to the technical field of textile defect identification, and the method specifically comprises the steps: collecting original images of a plurality of textile samples, and carrying out the detailed marking; adjusting the original image to 224 * 224 pixels, constructing a CNN model, extracting feature maps of different convolutional layers, and generating a fusion feature vector in combination with the weights of the feature layers; performing pooling processing on the fused feature map to generate a single-channel space attention map, and obtaining a weighted feature map in combination with a channel attention weight; constructing a segmentation model, outputting a mask after training, and identifying a normal region and a defect region; analyzing and identifying a defect area and extracting related features through a connected component to form a feature set; and a comprehensive scoring coefficient is constructed based on the features, so that the textile defect type can be accurately identified. According to the method, the recognition capability on fine defects can be effectively enhanced, and finer deviations can be captured, so that the recognition rate is remarkably improved.

The invention provides a textile pattern dislocation identification method, which comprises the following steps of: performing geometric transformation analysis on extracted pattern contour information, calculating a relative position relationship of each part of a pattern, establishing a pattern moisture deformation model, and judging whether the pattern is dislocated or deformed by comparing the difference between the current pattern and a reference model; on the basis of the corrected pattern, adding a special waterproof mark on the surface of the wet textile, manufacturing a microscopic mark which does not influence the fabric performance, and capturing the position of the waterproof mark through infrared imaging equipment to serve as an auxiliary reference point for pattern positioning; and based on the waterproof mark position of the pattern, tracking the motion trail of the waterproof fabric, calculating the image distortion degree according to the motion vector field, correcting the moving waterproof mark fabric image in real time, and eliminating the influence of motion blur on waterproof mark identification.

The invention discloses a textile design optimization method based on artificial intelligence, and relates to the technical field of artificial intelligence, and the method comprises the steps: constructing a textile processing digital twinborn model; multi-modal data acquisition and feature fusion: providing data input by deploying a sensor array and fusing features; simulation and deduction are carried out based on a digital twinborn model, a diagnosis result of the state sensing module is used as model input, the predictive control module carries out advanced simulation and optimization calculation by using a prediction model, and the collaborative scheduling module realizes global optimization based on the model and outputs a precise control instruction; and executing the precise control instruction, returning the executed real data as feedback, and updating and correcting the S1 digital twinborn model to form a closed loop. According to the method, refinement, real-time adaptive optimization and efficient cooperative control of the textile processing process can be achieved, the processing quality and consistency are remarkably improved, the waste and defective rate is reduced, and the method has the self-evolution capacity.

The invention relates to a non-woven fabric surface quality image recognition method and system, and belongs to the technical field of image data processing, and the method comprises the following steps: S1, collecting an original image of the surface of a non-woven fabric under a uniform illumination condition; s2, preprocessing the original image; s3, performing multi-scale texture analysis on the optimized image, extracting structural features of the surface of the non-woven fabric, and performing wavelet transform decomposition to obtain high-frequency detail information; s4, judging whether surface defects exist or not by utilizing a pre-trained defect classification model based on the structural features and the high-frequency detail information; s5, if the defect is detected, calculating the area proportion of the defect area, comparing the area proportion with a preset threshold value, and if the area proportion exceeds the preset threshold value, judging that the non-woven fabric is an unqualified product; if no defect is detected, judging that the non-woven fabric is a qualified product; s6, outputting a detection result, wherein the detection result comprises a defect position and a defect type; the non-woven fabric surface detection device has the beneficial effect of improving the non-woven fabric surface detection quality.

The invention relates to the field of disposable hygienic products, in particular to a high-diffusion baby paper diaper and a preparation method thereof.The prepared baby paper diaper has the advantages of being good in flow guide effect and high in absorption efficiency. The absorption core layer comprises a top layer non-woven fabric, a middle non-woven fabric, a bulky non-woven fabric, a bottom layer non-woven fabric, a wood pulp fiber layer, a first absorption material layer and a second absorption material layer, the first absorption material layer comprises first polymer water-absorbent resin particles and first wood pulp fibers, and the second absorption material layer comprises second polymer water-absorbent resin particles. The second absorbing material layer is arranged between the bulky non-woven fabric and the bottom layer non-woven fabric, part of the second macromolecule water-absorbent resin particles on the second absorbing material layer are embedded in pores of the bulky non-woven fabric, and the first absorbing material layer is arranged between the bulky non-woven fabric and the middle non-woven fabric. And a part of the first high-molecular water-absorbent resin particles on the first absorbing material layer are embedded in pores of the bulky non-woven fabric.

The invention relates to the technical field of textile informatization and block chain encryption traceability, in particular to a textile quality block chain encryption traceability method, which comprises the following steps of: implanting quantum dot-nucleic acid mixed fingerprints into yarns in a spinning stage and generating distributed identities; in the production link, process data are collected in a trusted execution environment, and are packaged into an encrypted packet by using homomorphic encryption, zero-knowledge proof and threshold signature; and after a batch threshold value is reached, calculating a batch commitment and a fragmentation commitment, fragmenting through erasure coding, writing the commitment and the proof into the directed acyclic graph according to a fixed field, and confirming through a Byzantine fault-tolerant consensus. Consumer off-line fingerprint comparison and homomorphic verification can realize authenticity identification, and after networking, batch certification is verified and credits are pledged. And when the time lock expires, the historical quality data is decrypted by multiple subjects in a combined manner, and maintenance suggestion hash is generated and written into subsequent transactions, closed-loop tracing from production to maintenance is realized, and anti-counterfeiting, privacy protection and quality improvement are realized at the same time.

The invention relates to the technical field of textiles. The invention discloses a textile dyeing uniformity detection system, a detection method and a dyeing method. The device comprises a light source supply device which is arranged above a textile and is used for providing light sources with two wavelengths and generating monochromatic coherent light, a dielectric layer supply device for forming a uniform dielectric layer, a reflective light path device for splitting beams and guiding the beams to form an interference area, and an image acquisition device for acquiring interference fringe images, the angle adjusting device is used for adjusting irradiation and acquisition angles; and the image processing device is used for analyzing signals and identifying non-uniform dyeing areas and flaws. A high-precision detection system is constructed, the light source and the dielectric layer cooperate to realize micron-sized defect recognition, the visibility of interference fringes is improved to 0.8 or above, and the dynamic tension frame guarantees the precision. The reflective light path and angle adjusting device adapts to a complex environment, a detection method and a dyeing method are cooperated, and through pretreatment, quantitative analysis and multi-dimensional verification, the misjudgment rate is greatly reduced, and the detection speed adapts to production.

The invention provides a textile state detection and analysis system, and relates to the field of state detection.The textile state detection and analysis system comprises the steps that firstly, a to-be-detected textile surface image is obtained and preprocessed, then a double-branch feature extraction network is constructed synchronously, and local edge features of microscopic flaws and a global distribution rule of a macrostructure are captured respectively; local details and global semantics are further associated through cross-scale feature fusion, multi-scale image coding features of the surface of the to-be-detected textile are generated, finally, defect positioning, classification and confidence evaluation are performed on the fused features in combination with a pre-trained deep learning model, and whether an alarm signal is sent out or not is automatically judged according to a detection result. Therefore, defect detection can still keep high sensitivity in a complex light environment, false detection and missing detection of a shadow or overexposure area are effectively inhibited, and the accuracy and reliability of defect detection are remarkably improved.

The invention discloses an intelligent identification and sorting method for waste textiles, and belongs to the technical field of textile recovery. An intelligent identification and sorting method for waste textiles comprises the steps of scanning recycled waste textiles by using a hyperspectral camera, obtaining hyperspectral image data of the waste textiles, preprocessing the obtained hyperspectral image data to improve data quality, constructing a material identification model, inputting dimension-reduced hyperspectral features into the model, and identifying the waste textiles according to the dimension-reduced hyperspectral features. Through training and learning spectral feature differences of different materials, the materials of the waste textiles are accurately identified; recording the surface condition of the waste spinning through a monitoring device, and analyzing the influence of the surface condition on spectrum identification; according to the material recognition result and the surface recognition result, sorting equipment is controlled to carry out sorting operation on polyester textiles in the waste textiles; a sorting result is fed back to a control system, the sorting accuracy rate is recorded, and the performance of the recognition model and the sorting equipment is evaluated and optimized.

A method for producing a textile material, such as a shoe upper, including providing a shaping carrier, such as a last; providing a plasticizing unit for melting a polymer composition to provide a molten polymer composition; providing a depositing unit with a dosing head which includes at least one nozzle; applying the molten polymer composition via the at least one nozzle on the shaping carrier in a filament forming a plurality of loops on the shaping carrier. The depositing unit and / or the shaping carrier are in a first movement moved relative to each other such that the at least one nozzle moves along a drive path which runs on the shaping carrier. During forming each loop, the dosing head and / or the at least one nozzle is moved in a second movement along a loop depositing path with a path length such that the length of each loop formed on the carrier is larger than the path length of the depositing path.

The present invention belongs to the field of tensile testing technology, and in particular, is a tensile strength testing device for textile fabrics, comprising a bottom plate, a support plate fixed on the top of the bottom plate, a mounting plate fixed on the top of the support plate, a stretching mechanism arranged on the mounting plate for stretching the fabric, a water tank arranged above the mounting plate, the water tank being fixed on the mounting plate through a pair of support frames, a plurality of evenly distributed water outlet pipes arranged at the bottom of the water tank, a pressing plate arranged in the water tank, a pressing rod fixed on the top of the pressing plate, a gathering groove arranged on the top of the mounting plate, and a drainage port penetrating the mounting plate arranged on the bottom wall of the gathering groove. In the present invention, the pressing plate is pushed downward by pressing the pressing rod, and the water in the water tank flows onto the fabric through the water outlet pipe, the water penetrates the fabric and drips into the gathering groove, and then flows down through the drainage port, and the water flow at the drainage port is observed. If a large water flow appears at a certain point, it means that the fabric has been torn at the corresponding position above the water flow.

The invention discloses textile air permeability detection equipment with a stable stretching structure, and relates to the technical field of textile detection, the textile air permeability detection equipment comprises a base, a supporting column is arranged at the upper end of the base, and an adjusting assembly is arranged at the upper end of the supporting column and used for stretching a textile; according to the textile air permeability detection equipment with the stable stretching structure, when the driving part is started, the adjusting plate is driven to rotate, and the outer surface of the positioning block is in sliding connection with the inner wall of the movable groove, so that when the adjusting plate moves, the positioning block is synchronously driven to move along the inner wall of the movable groove. Wherein the limiting blocks are rotatably mounted on the limiting plates, and the extension rods are limited through the limiting blocks, so that the extension rods rotate around the ends of the limiting blocks when moving, arc-shaped plates arranged at the ends of the extension rods are synchronously driven to move, and the inner wall of the textile is further stretched; and the state of the interior of the textile when the articles are stored is simulated.

The invention discloses a phase change energy storage waterborne polyurethane nanofiber membrane and a preparation method thereof. Lignin-based phase change microcapsules are prepared by combining ultraviolet crosslinking with lignin shell packaging, and then the nanofiber membrane containing the phase change microcapsules is prepared through an electrostatic spinning technology. And finally, constructing the waterborne polyurethane phase change fiber membrane with asymmetric wettability through a low-temperature plasma technology. According to the invention, lignin is self-assembled to form nanoparticles, and ultraviolet light induces free radical polymerization to form a polymer film, so that the packaging capability of the phase change material is improved. The phase change microcapsule prepared by the method is high in packaging efficiency and excellent in phase change performance, the preparation process is green and environment-friendly, the technological operation is simple, the temperature of the prepared phase change energy storage waterborne polyurethane nanofiber membrane conforms to the comfortable temperature range of a human body, and the phase change energy storage waterborne polyurethane nanofiber membrane has excellent temperature regulation, waterproof and moisture permeable performance and is suitable for being used in the field of water treatment. Good application prospects are realized in the field of functional textiles with functions of intelligent temperature regulation, water resistance and air permeability and the like.

The invention provides a PVDF (Polyvinylidene Fluoride) nanofiltration membrane constructed on the basis of microwave-enhanced bridging interfacial polymerization as well as a preparation method and application of the PVDF nanofiltration membrane. The method comprises the following steps: reacting PVDF powder with an organic alkali to prepare a modified film-forming solution, blade-coating the modified film-forming solution on a non-woven fabric supporting layer, placing the non-woven fabric supporting layer in an ethanol-water or methanol-water coagulating bath, and preparing a PVDF supporting film by virtue of assistance of an ice template; weighing the functionalized nano material and an amino silane coupling agent, performing ultrasonic dispersion, and adding a catalyst for reaction to obtain dispersion liquid; immersing a PVDF support membrane into the dispersion liquid to obtain a modified membrane; immersing the modified membrane into an aqueous solution containing an amine monomer and an organic solution containing an acyl chloride monomer, and carrying out microwave radiation. The interface reaction rate and selectivity are enhanced through the microwave excitation effect, and meanwhile, the hydrophilicity and reaction activity of the PVDF base membrane are cooperatively regulated and controlled, so that the separation efficiency and the anti-pollution capacity of the membrane are remarkably improved. The obtained PVDF nanofiltration membrane has high flux, high selectivity and excellent structural stability, and is suitable for efficient purification and resource recovery application in a complex water system.

The invention relates to the technical field of air permeability testing devices, in particular to a non-woven fabric air permeability detecting device which comprises a bottom plate, a lower barrel fixedly connected to the bottom plate in a suspended mode and an upper barrel arranged above the lower barrel, an opening of the upper barrel and an opening of the lower barrel are oppositely arranged, a liftable bearing disc is arranged in the lower barrel, a vertical plate is fixedly connected to one side of the bottom plate, and the vertical plate is fixedly connected to the other side of the bottom plate. A C-shaped lifting frame is slidably connected to the vertical plate, a first linear module used for driving the lifting frame to ascend and descend is installed on the vertical plate, the upper portion of the lifting frame is fixedly connected with the upper barrel, and the lower portion of the lifting frame slidably penetrates through the side wall of the lower barrel and is fixedly connected with the bearing disc. Through cooperation of the rotating ring, the curved guide rail and the linkage mechanism, the multiple clamps synchronously move in the radial direction, multidirectional uniform drawing force can be applied when the cloth is clamped, the tension is monitored in real time in combination with the tension sensor, the stretching amount is accurately adjusted, and air permeability detection of the cloth under different stretching degrees is achieved.

The invention belongs to the technical field of textiles, and particularly discloses an antibacterial cool-feeling polyester fiber containing plant extracts, a textile and a preparation method of the antibacterial cool-feeling polyester fiber. The antibacterial cool-feeling polyester fiber containing the plant extract comprises polyester and composite functional cellulose aerogel, the composite functional cellulose aerogel comprises cellulose aerogel, aluminum nitride and the plant extract, the aluminum nitride and the plant extract are loaded on the cellulose aerogel, and the plant extract comprises polygonum cuspidatum extract. The polyester fiber has a good antibacterial cool feeling characteristic and can be widely applied to the fields of household articles, clothes and the like.

The invention relates to the technical field of textile dyeing sewage treatment, in particular to textile dyeing sewage treatment equipment. Comprising a purification box and a pretreatment box, and the interior of the pretreatment box communicates with the interior of the purification box; a sewage collecting box is fixedly connected to the purifying box, an auxiliary box is fixedly connected to the purifying box, an incomplete gear is driven by a first motor to rotate in the anticlockwise direction, so that a first conveying roller and a second conveying roller rotate synchronously, synchronous movement of a filter screen conveying belt is achieved, the filter screen conveying belt moves uninterruptedly while filtering is conducted, and the filtering efficiency is improved. The filter screen conveying belt entering the cleaning box is deeply cleaned through the wadding scraping mechanism and the deep cleaning mechanism, the filtering effect of the filter screen conveying belt is effectively improved, the filtering effect of sewage is improved through secondary filtering, the device enables sewage to be filtered more thoroughly, meanwhile, self-cleaning of the filter screen conveying belt can be conducted, and the service life of the filter screen conveying belt is prolonged. Manual replacement and manual cleaning are not needed, and the workload of workers is effectively reduced.

A woven silt fence fabric includes two or more distinctly different colors of warp yarns in the machine direction. The woven silt fence fabric includes a first woven fabric portion to be installed in the ground having a first color that is distinctly different from a second color of a second woven fabric portion to be installed and remain exposed above the ground.

The invention relates to the field of disposable hygienic products, in particular to a paper diaper with a fluffy non-woven fabric core body of a net structure and a preparation process of the paper diaper, and mainly solves the problems that in the prior art, macromolecular water-absorbent resin particles of an online water-absorbent paper core body are difficult to enter fluffy non-woven fabric, and the strength is poor. The paper diaper body comprises a liquid-permeable surface layer, an absorption core layer and a liquid-tight bottom layer which are sequentially stacked from top to bottom; the absorption core layer comprises a first fluffy non-woven fabric, a second fluffy non-woven fabric compounded on the lower surface of the first fluffy non-woven fabric and macromolecular water-absorbent resin particles laid on the upper surface of the first fluffy non-woven fabric; at least two material storage areas are arranged on the first fluffy non-woven fabric side by side in the transverse direction, holes are punched or embossed on the first fluffy non-woven fabric in each material storage area, and the macromolecular water-absorbent resin particles comprise first macromolecular water-absorbent resin particles which are distributed in each material storage area.

The invention relates to a decolorizing method of waste colored polyester textiles. The decolorizing method comprises the following steps: A, adding an organic solvent of which the solubility parameter is similar to that of polyester into a reducing agent solution to serve as a mixed decolorizing solvent; b, the waste colored polyester textiles are soaked in the mixed decolorizing solvent, solid-liquid separation is performed after decolorizing treatment, and decolorized polyester textiles and a primary decolorizing solvent are obtained; c, soaking the colored waste polyester textile into a primary decoloring solvent, and performing solid-liquid separation after decoloring treatment to obtain a decolored polyester textile and a secondary decoloring solvent; d, repeating the step C until the waste colored polyester textiles are difficult to decolorize, and at the moment, obtaining a deep-color decolorizing solvent which is repeatedly decolorized; e, drying the decolored textile to obtain a regenerated white polyester textile; and F, distilling the repeatedly decolored deep-color decoloring solvent, rectifying, and recovering to obtain the regenerated decoloring solvent. The problems of high energy consumption, low efficiency and the like of an existing decolorization process system can be solved.