10881 results about "Textile" patented technology

The invention relates to the technical field of textile machinery fault detection, and discloses a spinning machine fault detection method and system based on deep learning, and the method comprises the steps: collecting vibration, temperature and current signals through a plurality of sensors, constructing a data stream after principal component analysis and dimension reduction, employing a variational auto-encoder to reconstruct an error positioning abnormal data segment, and obtaining a spinning machine fault detection result. The method comprises the following steps: extracting local features of a multi-source signal in combination with a convolutional neural network, dynamically distributing feature weights by using an attention mechanism, screening time sequence key features through a forgetting gate, introducing an LSTM network to model a feature sequence dynamic relationship, completing fault category mapping based on a support vector machine, and triggering LSTM secondary classification calibration for samples with insufficient confidence. A closed-loop technical system of data dimension reduction, anomaly detection, feature optimization, time sequence modeling and classification verification is formed, and efficient analysis and accurate recognition of multi-modal fault features under complex working conditions are achieved.

The invention discloses a textile fabric tearing strength detection method and system, and relates to the technical field of fabric detection.The method comprises the steps that fabric microstructure, macromechanics and component data are synchronously collected through a multi-mode sensing system, and detection modes are dynamically switched based on a real-time recognition result; inputting the space-time correlated defect data into the physical constraint enhanced prediction model to generate a crack propagation trend and a tear strength prediction value; wherein the prediction model is fused with a Griffith crack propagation theory and a hidden Markov model, and double constraints of a material mechanics law and dynamic defect evolution are realized; a non-contact detection module and a flexible contact detection module work cooperatively, and a process optimization scheme is output in combination with an edge and cloud distributed architecture.

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.

The invention discloses a novel textile fabric tensile strength detection device, and relates to the technical field of cloth detection equipment. The device comprises a base, a pressing block is arranged at the top of the base, push plates are arranged on the two sides of the pressing block, and first pressure sensors are installed in the push plates; an adjusting assembly is arranged on the top of the base. A rotating shaft, a gear and a toothed plate of the adjusting assembly are matched with a hydraulic rod and a clamping plate of the clamping assembly, accurate clamping and fan-shaped stretching of the side edge of cloth are achieved, and the defect that a traditional device can only conduct horizontal tension detection is overcome; an adjusting plate, an adjusting groove and a moving shaft of the linkage assembly are driven by a screw rod and a moving sleeve of the driving assembly, so that the cloth generates fan-shaped deformation under the action of lateral tension, the tensile strength of the side edge of the cloth can be evaluated more comprehensively in combination with dual monitoring of a first pressure sensor and a second pressure sensor, the accuracy of detection data is remarkably improved, and the detection efficiency is improved. The device is especially suitable for testing high-strength fabrics with easy-to-tear side edges.

The invention relates to the technical field of three-dimensional image reconstruction, in particular to a VR-based three-dimensional reconstruction method and system for textile culture heritage, and the method comprises the steps: obtaining a multi-view image collection sequence of the textile culture heritage, carrying out the geometric topological feature extraction of the multi-view image collection sequence, generating a three-dimensional point cloud geometric model, and carrying out the reconstruction of the three-dimensional point cloud geometric model. Performing multi-resolution texture feature mapping processing on the three-dimensional point cloud geometric model to generate an initial three-dimensional model fusing geometric topological features and multi-resolution texture features; performing dynamic geometric optimization processing on the initial three-dimensional model based on preset VR display parameters to generate a target three-dimensional model after surface continuity correction; and performing dynamic matching processing on the target three-dimensional model and a preset VR interaction algorithm to generate a VR visual model with a multi-dimensional interaction attribute, and transmitting the VR visual model to a VR display terminal to perform three-dimensional space rendering, so that the three-dimensional reconstruction and interaction intelligence degree of the textile culture heritage can be improved in combination with a VR technology.

The invention discloses a textile fabric wear resistance detection device, and relates to the technical field of textile fabric wear resistance detection, the textile fabric wear resistance detection device comprises a support mechanism I and a detection mechanism, a sampling mechanism is arranged on a support mechanism II, the detection mechanism is arranged on a support seat II, and an adjusting mechanism I and an adjusting mechanism II are arranged on the detection mechanism. The device has the advantages that the third supporting seat is matched with the sampling mechanism, so that an experiment can be performed without manually cutting experimental cloth into a specified size, the preparation time before the experiment is shortened, and the detection efficiency is improved; the detection mechanism is adjusted through the adjusting mechanism I, so that tests of the same test type but different test strengths can be conveniently carried out, and experiment results can be directly compared; the detection mechanism is adjusted through the adjusting mechanism II, so that tests with different test types and the same force as one group can be conveniently carried out, and experiment results can be directly compared; and through horizontal comparison or vertical comparison, a detection result which is more in line with a use scene is provided.

The invention relates to the technical field of biomechanical measurement and analysis, in particular to a home textile recommendation method and system based on child health data monitoring and analysis. The method comprises the following steps: collecting an original point cloud coordinate set of a sleeping posture of a child; extracting a cervical curvature parameter group according to the extracted cervical curvature parameter group of the skeleton key point spatial distribution diagram; performing cervical vertebra and body position analysis according to the cervical vertebra curvature parameter group to obtain cervical vertebra curvature-body position holographic data; collecting a static pressure baseline data set according to the cervical curvature-body position holographic data; performing body position-pressure correlation analysis according to the static pressure baseline data set to obtain a body position-pressure mapping relation table; and generating a pressure distribution index map according to the body position-pressure mapping relation table. According to the method, the physical sign data, the pressure distribution and the physiological curvature change of the children in the natural sleep state are comprehensively collected and analyzed, so that high-precision, whole-process and personalized healthy home textile recommendation is realized.

The invention relates to the technical field of polyester fibers, in particular to a high-strength wear-resistant polyester fiber and a preparation method thereof. The invention aims to solve the problem that the mechanical strength and wear resistance of the existing polyester fiber are difficult to consider at the same time. The preparation method comprises the following steps: carrying out esterification and polycondensation on terephthalic acid, ethylene glycol, hydroxyl-terminated polydimethylsiloxane and isophthalic acid to obtain modified PET; the preparation method comprises the following steps: respectively carrying out oxidation treatment on graphene and a multi-walled carbon nanotube, and then adding polyether amine for grafting; carrying out melt blending with PET slices to obtain nano master batches; carrying out melt blending on the chopped glass fibers and the PET slices to prepare micron master batches; and mixing the modified PET, the nano master batch and the micron master batch, carrying out ultrasonic dispersion, adding an auxiliary agent, and carrying out melt spinning, three-section stretching and three-section heat setting treatment to obtain the high-strength wear-resistant polyester fiber. Through the synergistic effect of the components and the process, the prepared fiber has excellent mechanical properties and wear resistance, and has wide application prospects in the fields of clothing, home textiles, industry and the like.

The invention belongs to the technical field of position tracking control of rigid multi-joint mechanical arms, and discloses a fuzzy self-adaptive visual servo control method and system for a multi-joint mechanical arm system for placing bobbins in a textile workshop, and the method comprises the steps: constructing an image error model according to the positions of feature points on an image plane; the fuzzy logic system is used for processing uncertain items in the system, the instruction filtering and fuzzy self-adaption technology is used for achieving tracking control over the expected trajectory of the system, the problem of calculation complexity is solved, and adverse effects caused by filtering errors are eliminated. In the process of changing the bobbins, the bobbins are placed on a creel through a multi-degree-of-freedom robotic arm, a clamping jaw at the tail end of the robotic arm is required to accurately grab the bobbins for feeding and discharging, and the requirement for accurate and rapid control of the robotic arm is met, so that research on visual servo control of the robotic arm is of great significance. The method has a good control effect, the problem of calculation complexity in the design process of the controller is solved, the trajectory tracking error is smaller, and the system robustness is higher.

The invention relates to the field of textile materials, and particularly discloses a graphene enhanced polyester yarn and a preparation method thereof.The preparation method comprises the following steps that silicon dioxide aerogel serves as a porous carrier to be loaded with graphene, and a graphene-porous carrier composite material is prepared; the graphene-porous carrier composite material is subjected to modification treatment through vinyl trimethoxy silane and 3-amino propyl triethoxy silane, and then a modified graphene composite material is prepared; reacting the modified graphene composite material, a styrene monomer, an acrylate monomer and an initiator to prepare modified graphene; mixing the prepared modified graphene with polyester chips, and then carrying out melt spinning to prepare graphene enhanced polyester yarns; the invention further discloses the graphene enhanced polyester yarn prepared by adopting the preparation method. The preparation method has the characteristics that the dispersion of the graphene in the polyester is improved, and the direct interface compatibility of the graphene and the polyester fiber is improved, so that the mechanical property of the polyester yarn is improved.

The invention discloses an ancient textile image restoration system based on artificial intelligence. The system comprises a multi-source image acquisition module, a damaged area detection module, a pattern generation module, a color restoration module, a texture synthesis module and a multi-scale fusion module. The system introduces a wavelet guidance-frequency domain attention mechanism and a rotation invariant Haar wavelet basis function to realize accurate identification and classification of a damaged area; a saliency-guided wavelet decomposition control and self-adaptive threshold denoising method is combined, so that the perception capability of slant textures and edge details is improved; the texture synthesis module constructs a hierarchical modeling strategy fusing Gram style loss, Wasserstein style loss and a total variation regular term, and realizes generation of high-quality textures with unified styles and smooth edges; the system can be widely applied to cultural relic digital repair and display scenes.

The invention relates to the technical field of printing and dyeing textile equipment, and discloses an automatic cloth roll dismounting device which comprises a stacking support, a plurality of cloth rolls can be stacked on the stacking support in sequence, and binding ropes are bound to the two ends of each cloth roll; a robot body is arranged on one side of the stacking support, and a first clamp or a second clamp can be installed at the top end of the robot body. Wherein the first clamp and the second clamp are installed in a mutually exclusive mode, that is, only one set of the first clamp and the second clamp can be installed at the same position of the top end of the robot body, the equipment for automatically disassembling the yardage rolls can achieve unstacking of the yardage rolls, cutting off binding ropes and adjusting the orientation of cloth ends of the yardage rolls, meanwhile, automation of the whole carrying and feeding process of the yardage rolls is achieved, and the automation degree is high. The effect of saving labor and corresponding labor cost input in the unwinding link is achieved to the maximum extent, meanwhile, the effective working efficiency of unwinding can be greatly improved, and the labor intensity of workers is relieved.

The invention provides a method for recovering a BHET monomer from a waste polyester textile alcoholysis solution, and is characterized in that the recovery method comprises the following steps: (1) filtering: mixing the waste polyester textile alcoholysis solution with water under a stirring condition, and filtering at 55-70 DEG C; and (2) cooling crystallization: under a stirring condition, carrying out primary cooling on the filtrate obtained by filtering in the step (1) from 55-70 DEG C to 45-55 DEG C, then adding a BHET seed crystal, then carrying out secondary cooling to 5-15 DEG C, and maintaining the temperature for 20-60 min to obtain the BHET monomer. The mixed solution cooling crystallization method is developed on the basis of complexity of components of the waste polyester textile fabric, the problems that in the conventional production process, a BHET crystal product is low in quality, prone to scaling, difficult to filter and dry and the like are solved, and the obtained BHET product is large in particle size, narrow in particle size distribution, high in purity, good in fluidity and high in stability.

The invention belongs to the technical field of recycled polyester, and particularly relates to a waste polyester textile recycling method which comprises the following steps: decolorizing colored waste polyester textiles by adopting a decolorizing agent which is more than one of dimethyl carbonate, diethyl carbonate and methyl ethyl carbonate; the depolymerization agent is adopted to depolymerize the decolored polyester textile to obtain the terephthalate, and the depolymerization rate of the decolored polyester textile is 98.0-100%; firstly, terephthalate is converted into DMT, and then DMT, ethylene glycol, a catalyst and a functional additive are subjected to a repolymerization reaction to obtain regenerated PET. According to the method, a process of decoloring and depolymerizing sequentially is adopted, and decoloring and depolymerizing are coordinated, so that the process is simplified, the energy consumption and pollution are reduced, and the economical efficiency and sustainability of waste polyester textile recycling are improved.

The invention discloses a preparation method of a composite phase-change temperature-adjusting organic fiber membrane with a flexible core-shell structure, and belongs to the field of intelligent textile materials.The preparation method comprises the following steps that polyacrylonitrile (PAN) serves as a sheath layer material, n-octadecane serves as a core layer phase-change material, and the composite phase-change fiber membrane is prepared through a melt spinning method and a coaxial electrostatic spinning technology. According to the invention, the fiber membrane with high melting enthalpy value (171.6 J / g), excellent thermal stability (the latent heat is still 117.7 J / g after 100 times of heating-cooling circulation) and excellent mechanical properties (the tensile strength is 2.418 MPa, the tensile yield stress is 2.331 MPa, the tensile strain at break is 36.5%, and the elastic modulus is 58.226 MPa) can be prepared; a new thought is provided for preparing intelligent textiles with good flexibility and efficient heat management capability.

The invention relates to the field of yarn spinning, in particular to a real-time quality rating method and system for yarn spinning. The method comprises the following steps: acquiring a space-time charge data set, and generating a yarn electrostatic state data set through a multi-mode sensing fusion strategy; on the basis of the yarn static state data set, yarn spinning quality defects are recognized by combining yarn form data collected in real time, two-dimensional dynamic rating is executed according to defect types and severity, and yarn real-time quality rating is generated; according to the yarn real-time quality rating, carrying out change trend analysis on the yarn real-time quality rating to generate a yarn subsequent quality change trend; and executing a corresponding process regulation and control instruction according to the subsequent quality change trend of the yarn, and outputting a quality rating log. In the yarn spinning process, process look-ahead optimization is achieved, quality tracing is perfected, and the accuracy and real-time performance of quality rating are improved.

The present invention relates to an electrospun fiber, a process for preparing the same, a nonwoven fabric comprising the electrospun fiber, as well as corresponding uses and articles. The inventive electrospun fiber comprises a polymer, a surface-reacted calcium carbonate and a pharmaceutically or nutraceutically active ingredient, wherein at least a part of the pharmaceutically or nutraceutically active ingredient is present within the pores of the surface-reacted calcium carbonate. The inventive fibers may be used e.g. in yarns, transdermal patches, intrabuccal patches, implantable textiles, wound dressings and / or medical tapes.

Devices and methods of harvesting textile hemp are presented. The methods comprise mowing the hemp and wherein the cut stems are held between crossed conveyor belts and then rotated 90° from vertical to horizontal, taken over one or more times by other belts, to be deposited in parallel swaths on the field.

The invention relates to a textile product defect identification method based on improved YOLOv11. The method comprises the following steps: acquiring a textile product defect image data set; performing pretreatment; dividing into a training set and a verification set; the method comprises the following steps: introducing MConv into a YOLOv11 backbone network, adding a CCIAP module behind a C2PSA module, and applying BiFPN in a path aggregation network; performing prediction through YOLO Head to obtain N prediction feature maps; the overall loss of the network is calculated, and network parameters are optimized through back propagation; predicting the verification set image through a network to output AP values of various categories; repeating the above steps to obtain a trained YOLOv11 network; and detecting the test image or video by using the trained detector to obtain a detection result. According to the method, the MConv is introduced into the YOLOv11 network to enlarge the receptive field, the CCIAP module is added behind the C2PSA to improve the feature extraction capability, and the BiFPN is applied to the Neck layer to enhance the feature fusion capability, so that the target detection precision is improved and the real-time detection of textile product flaws is realized under the condition that the reasoning speed is not influenced.

The invention discloses a textile fabric rolling and packing device which comprises a rolling mechanism, a packing mechanism and a bearing platform, the rolling mechanism comprises a deviation rectifying assembly, a detecting assembly and a rolling frame, the packing mechanism comprises a conveying belt assembly and a rack, an upper film guiding seat is arranged above the rack, a lower film guiding seat is arranged below the rack, and the upper film guiding seat and the lower film guiding seat are arranged on the conveying belt assembly. An upper film roller is arranged on one side of the upper film guiding base, a lower film roller is arranged on one side of the lower film guiding base, and a pushing assembly is arranged on one side of the conveying belt assembly. According to the technical key points, the packaging mechanism is additionally arranged on one side of the winding mechanism, the winding mechanism is used for winding the textile cloth, the packaging mechanism is used for packaging the wound textile cloth roll, the whole device can wind the textile cloth and can also automatically package the wound material roll, manual packaging is replaced, the production efficiency is improved, and the production cost is reduced. The material coil packing machine is suitable for packing long and heavy material coils, time and labor are saved, and the labor intensity of workers is reduced.

Embodiments described herein generally relate to textile structures comprising core spun yarns, and associated methods for manufacturing. One example embodiment is a textile structure including one or more layers of warp yarns interwoven with one or more layers of weft yarns, wherein at least one of the one or more layers of warp yarns and one or more layers of weft yarns include one or more core spun yarns.

A textile fabric is provided, including: a main body and at least one film layer. The main body includes two surfaces opposite to each other, and each of the two surfaces has a surface texture being concave and convex. The at least one film layer is coveringly disposed on at least one of the two surfaces, and each said film layer is concave and convex corresponding to the surface texture. Therefore, the at least one film layer has an appearance corresponding to the surface texture, and the textile fabric has good toughness, is waterproof and is not easily damaged, which solves the problems of insufficient structural strength and poor durability of a conventional textile fabric.

The invention relates to the technical field of textile machinery, and discloses a covering yarn machine spindle speed and twist control system which comprises a data acquisition module, a global control module, an individual diagnosis module, a power execution module and a man-machine interaction module. The actual average speed of the whole machine is calculated by collecting the speed of each spindle in real time, and PID closed-loop control is carried out on the actual average speed and a set value, so that the systematic speed deviation of the whole machine is accurately corrected. Meanwhile, the individual diagnosis module calculates spindle difference signals of the speeds of the spindles and the average speed of the whole machine in parallel, time domain and frequency domain analysis is carried out on the signals, and hidden faults such as steady-state deviation, periodic fluctuation and transient impact existing in a single spindle are accurately recognized. And finally, the system carries out visual early warning through a human-computer interaction interface and provides a predictive maintenance instruction. According to the method, high-precision control of the twist and high consistency of products are achieved, an effective predictive maintenance mechanism is established, and the production quality and the intelligent level are remarkably improved.

The invention relates to the field of cooling of human body protective clothing, in particular to a cooling fabric based on phase change microcapsules. The cooling fabric comprises a polyester fiber layer, a phase change microcapsule layer and a PTFE waterproof breathable film layer. The polyester fiber layer is made of skin-friendly polyester fibers, has excellent moisture absorption and sweat releasing performance and can improve wearing comfort. The phase-change microcapsule layer is formed by uniformly embedding microcapsules coated with a phase-change material into the textile structure, and absorbs heat and generates phase change when the environment temperature rises, so that the temperature of the fabric is reduced; the PTFE waterproof breathable film layer has waterproof and breathable functions, can prevent external liquid from permeating, allows water vapor to permeate, and enhances environmental adaptability. By optimizing the spinning method of the phase-change microcapsules, the phase-change heat exchange efficiency can be improved while the air permeability of the fabric is kept, and the cooling performance of the fabric at high temperature is ensured. The fabric can be widely applied to high-temperature work clothes, outdoor sportswear and intelligent temperature control textiles, and has the advantages of being high in temperature adjusting capacity, comfortable, breathable and the like.

A textile fabric is provided, including: a main body and a film layer. The main body includes two surfaces opposite to each other, and the film layer is coveringly disposed on one of the two surfaces. A side of the film layer opposite to the main body includes at least one first surface portion and at least one second surface portion, and a glossiness of the at least one first surface portion is different from a glossiness of the at least one second surface portion.

The present application discloses a shapewear garment comprising an upper, middle, and lower portion, along with an abdominal compression panel. The upper portion wraps around the wearer's chest and upper back. The middle portion, positioned below the upper, comprises an abdominal and lower back covering. The lower portion extends around the wearer's front crotch area and buttocks. The abdominal compression panel, combined with the abdominal covering, has a higher modulus of elasticity than the other portions. A bust support area on the upper portion's outer surface features greater textile tension than surrounding areas.

The invention relates to the technical field of textile detection, and discloses a textile defect detection device which comprises a detection table, the detection table comprises two fixing plates, and the two fixing plates are connected through two fixing rods; the limiting mechanisms are arranged on the two sides of the fixing plate respectively; the video recording system is arranged between the inner walls of the two fixing plates and is used for textile video recording; and the two guide cylinders are rotationally connected between the two fixing plates. Through the design of the flattening mechanism, the textile is always kept in a flat state in the detection process, detection errors caused by wrinkles or wrinkles are avoided, the detection precision of the video recording system is remarkably improved, the video recording system can carry out real-time video recording on the textile and transmit data to a computer for analysis, rapid and accurate defect detection is achieved, and the detection efficiency is improved. The device realizes automatic winding and unwinding of textiles through the driving motor and the belt pulley set, reduces manual intervention, and improves the detection efficiency.

The invention provides a textile cloth defect real-time detection method and system based on multi-modal feature fusion, and the method comprises the steps: collecting visual image data, infrared thermal imaging data and ultrasonic acoustic data of textile cloth through a multi-sensor array, and forming multi-modal input; performing time sequence alignment and noise filtering preprocessing on the multi-modal data to eliminate motion artifacts and environmental interference; a parallel feature extraction module is used for extracting texture features from the visual data, extracting temperature distribution features from the thermal imaging data and extracting acoustic impedance features from the acoustic data. By deeply fusing complementary information of three modes of vision, thermal imaging and ultrasonic wave, the detection capability is improved, the vision mode captures surface texture details, the thermal imaging mode reveals thermodynamic anomalies related to friction and materials, the ultrasonic wave mode perceives subcutaneous structure defects, hidden flaws which cannot be recognized by a single mode can be found, and the detection efficiency is improved. Therefore, the omission ratio is greatly reduced, and flaw types are distinguished more accurately.

The invention relates to the technical field of textile detection, in particular to a computer-aided textile color fastness prediction method, which comprises the following steps: acquiring multi-source data before and after a textile color fastness test through computer control equipment, including digital images, reflection spectrum data, process parameters and dye characteristic component data, carrying out pretreatment; extracting color difference features and spectrum similarity features, and screening by adopting a dimension reduction algorithm to form a core feature vector; a machine learning algorithm is adopted to construct a color fastness prediction model, parameters are optimized in combination with cross validation and an early stop mechanism, model fine tuning is executed, and a final optimization model is obtained; and outputting a color fastness grade prediction result, and carrying out spectrum similarity secondary verification. According to the method, objective, efficient and high-precision prediction of the color fastness grade of the textile is realized, and the problems of high subjectivity and low efficiency of traditional manual evaluation are solved.