721results about "Textile testing" patented technology

The invention discloses a light aging test instrument, which includes a test cavity, a bottom baseplate, the top cover board which is fixed on the bottom and the top of the test cavity respectively. A lamp socket which fitted with a lamp is right on the centre of the base plate, the photo permeable holes are set at the same height on the side wall of the test cavity. A visual light narrow wave band filter sheet is in the photo permeable hole, and the sample trough is fitted on the photo permeable hole. The test instrument has a compact structure, easy to disassemble and assemble, inflexible for employ, with low cost of the production.

The invention relates to the technical field of fabric quality detection, and particularly discloses an antibacterial fabric quality detection method and device and electronic equipment.The method comprises the steps that chemical and physical quality detection is conducted on antibacterial fabric, chemical and physical quality characteristic values of the antibacterial fabric are obtained through comprehensive analysis, and sterilization testing is conducted on the initial state of the antibacterial fabric; performing comprehensive analysis to obtain an initial state sterilization characteristic value of the antibacterial fabric, performing sterilization test on the antibacterial fabric after the washing durability test, and performing comprehensive analysis to obtain a sterilization characteristic value of the antibacterial fabric after the washing durability test; the chemical and physical quality characteristic value of the antibacterial fabric, the sterilization characteristic value of the antibacterial fabric in the initial state and the sterilization characteristic value of the antibacterial fabric after the washing durability test are imported into an antibacterial fabric quality evaluation model, and the quality of the antibacterial fabric is evaluated. And manual detection is limited, so that the product quality and the market competitiveness can be improved.

A computer-implemented method of training a machine learning model to predict textile composition and / or other textile characteristics. For each of a plurality of textiles, at least one multi-pixel patch is acquired, the at least one patch comprising a subset of multidimensional data that is measured by spectral analysis for each of the plurality of textiles. Additionally, for each of the plurality of textiles, data is obtained that indicates a ratio of fibres included in each textile and / or obtaining data that indicates other textile characteristics. Additionally, a textile dataset is created by associating the at least one patch for each of the plurality of textiles with the respective ratio of fibres and / or the respective other textile characteristics for each of the plurality of textiles. The machine learning model is trained with the textile dataset and the trained machine learning model is stored in a storage medium.

The invention relates to the technical field of spinning quality detection, and discloses a jute spinning product quality detection method and system based on an intelligent sensor. The method comprises the following steps: acquiring real-time process parameters of a jute spinning production line, and synchronously capturing yarn surface temperature field distribution in combination with an infrared thermal imager; performing space-time alignment processing on the yarn tension fluctuation data and the temperature field distribution to generate a fused dynamic process characteristic matrix; according to the tension gradient change rate and the temperature field abnormal region coordinates in the dynamic process characteristic matrix, dividing potential occurrence sections of yarn quality defects; a microstructure image of the yarn in the potential generation section is extracted, a fiber arrangement angle deviation value is measured through a polarized light interferometer, and fiber molecular bond vibration frequency data is obtained in combination with a Raman spectrometer; and inputting the fiber arrangement angle deviation value and the molecular bond vibration frequency data into a cascade quality analysis model, and outputting a quantitative index set of the internal structure defects of the yarns.

Device for identifying structure and composition of a fabric or textile, comprising: a chamber placing over the fabric or textile, with a microscopic camera attached to the chamber, for acquiring an image of the fabric or textile, , a chamber diffused light for illuminating the fabric or textile with diffused light reflected by the chamber, a chamber grazing light, for illuminating the fabric or textile with grazing light, and a rotating mechanism to orient the microscopic camera with the fabric woven alignment; a near infrared spectrometer attached to the surface plate where the fabric is set, to capture an absorption spectrum in multiple wavelengths, ranging from 1550-1950 nm, a white reference aligned over the near infrared spectrometer to calibrate the absorption spectrum and reduce the thickness influence of the fabric; an electronic system for light control, a software for interfacing and control of the acquisition and recognition processes, by carrying out the following steps: activating the chamber diffused light and the chamber grazing light; acquiring, from the microscopic camera, the acquired image; activating the near-infrared light source, acquiring, from the near-infrared spectrometer, the absorption spectrum; and detecting the structural identification and the composition of the textile or fabric, from the acquired image and the near infrared spectrum.

The invention provides a photoelectric detection technology-based foreign fiber removing machine impurity detection method, and belongs to the field of data processing. The method comprises the following steps: obtaining a plurality of interception intervals; obtaining an abnormal factor of each interception interval according to the distribution difference of the signals to be detected in different interception intervals; clustering the to-be-detected signals in each interception interval to obtain an upper bound and a lower bound of a normal clustering cluster and a normal signal range in each interception interval; the final upper bound and the final lower bound of the normal signal range are obtained by combining the difference between the abnormal factors of each interception interval and the abnormal factors of other interception intervals; and obtaining the to-be-cleared degree of each interception interval according to the distribution of the to-be-detected signals in each interception interval. The invention aims to solve the problem that when foreign fibers are cleared through a K-means clustering algorithm, all data need to be clustered every time new data is added, so that abnormity confirmation is carried out on the new data, and the detection efficiency is too low.

The invention belongs to the technical field of textile fabric detection, and particularly relates to a textile fabric tensile strength testing device which comprises two groups of first arc-shaped clamping plates, each group of first arc-shaped clamping plates comprises two first arc-shaped clamping plates, and the first arc-shaped clamping plates are used for clamping a textile fabric; first rectangular blocks are fixedly connected to the two sides of the first arc-shaped clamping plates correspondingly, the two opposite first rectangular blocks slide on one sides of first rectangular strips correspondingly, the first rectangular strips are rotationally arranged on one sides of first supporting blocks correspondingly, rectangular plates are fixedly connected to the lower ends of the two opposite first supporting blocks, and a pipeline is arranged at the upper end between the first arc-shaped clamping plates. The device solves the problems that when the strength and the waterproof performance of the waterproof fabric are tested by adding water, the fabric is horizontally placed, water above the fabric can slide off from the side, water needs to be added to the upper portion of the fabric all the time, and impact force generated by water falling during water adding possibly affects the result of a fabric tensile test.

The present invention provides an article identification apparatus. The apparatus includes spectrometric identification means, optical identification means, at least one light source, computing means and notification means. The computing means, in communication with the spectrometric identification means and the optical identification means, are arranged to resolve, analyse and combine data acquired by the spectrometric identification means and the optical identification means, in use, and identify, based on the acquired data, the material composition and other such features of an article provided for identification, and communicate the same to the notification means.

The invention discloses a garment fabric production and processing flaw detection device and a use method thereof, and relates to the technical field of garment fabric production and processing, the garment fabric production and processing flaw detection device comprises a workbench and a detection assembly, one side of the workbench is connected with a pressure supply assembly, the top of the workbench is provided with a self-adaptive assembly, and the detection assembly is arranged in the middle of the self-adaptive assembly; the detection assembly comprises supporting plates, a rotating plate, a driving rod, a detection cover, a guide rod, a pressing block and a sponge, the supporting plates are arranged in the center of the top of the self-adaptive assembly at equal intervals, and the rotating plate is rotationally connected to the upper ends of the supporting plates. The fan can convey external air filtered by the filter into the pressurizing cavity, at the moment, the top of the workbench is covered with the garment fabric, so that the top of the pressurizing cavity is shielded, air flow can only pass through fine gaps in the garment fabric, and when no broken yarn or hole exists in the surface of the fabric, the air flow can pass through the pressurizing cavity. The air flow penetrating through all parts of the fabric can be uniformly distributed, and the pressure of the air flow is dispersed.

The invention relates to the technical field of garment quality inspection, in particular to an intelligent detection method based on textile fabric garment production quality, which comprises the following steps: determining that the garment production quality problem type has dominant defects, or determining whether the garment has hidden defects; performing vibration detection on the clothes to capture the vibration modes of the clothes in the plurality of detection grids, and determining whether the production quality problem type is a microscopic quality problem with hidden defects or not; a microscopic quality detection strategy is adopted when the clothes have hidden defects, a potential defect area is output for visual and tactile collaborative detection, a macroscopic quality detection strategy is adopted when the clothes have dominant defects, and a detection grid corresponding to the dominant defects is output to confirm the types of the dominant defects; and determining a detection mode of the visual and tactile collaboration device according to the detection condition, and adjusting the initial height and the moving speed of the visual and tactile collaboration device. According to the invention, visual and tactile collaborative detection is carried out on the textile fabric clothes, so that the accuracy of hidden defect identification is improved.

The invention discloses an intelligent detection method and device for a cotton water miscellaneous micronaire value based on multi-source information fusion, and relates to the field of cotton quality detection.The method comprises the steps that the weight, the initial air pressure difference, the cotton sample image, the resistance value, the environment temperature and the environment humidity of a to-be-detected cotton sample are obtained; according to the initial air pressure difference and the weight, the compensated air pressure difference is determined through a weight compensation model; according to the cotton sample image, utilizing an image segmentation technology to extract the impurity area percentage and the impurity grain number of the cotton sample to be detected, and determining the impurity content of the cotton sample to be detected; according to the resistance value, the environment temperature and the environment humidity, utilizing a moisture regain prediction model to determine the moisture regain of the cotton sample to be detected; and determining the micronaire value of the cotton sample to be tested by using a Stacking ensemble learning model according to the compensated air pressure difference, impurity content and moisture regain. According to the method, the moisture regain, the impurity rate and the micronaire value of the cotton can be accurately detected in a non-standard detection environment.

The invention discloses a new material yarn quality detection system, and relates to the technical field of new material yarn detection, the new material yarn quality detection system comprises a yarn quality detection platform, the yarn quality detection platform is in communication connection with a performance data acquisition module, a defect identification module, a yarn performance detection module, a comprehensive quality evaluation module and a visual display module, the modules are in electric signal connection; and the performance data acquisition module is used for acquiring physical and mechanical performance data of the new material yarn by using an intelligent sensing system. By integrating an intelligent sensing technology, a machine learning algorithm and multi-module cooperative work, high-precision and high-efficiency detection of the new material yarn is realized, appearance defects of the yarn are concerned in the detection process, the mechanical property and environmental adaptability of the yarn are deeply evaluated, and the detection accuracy is improved. The performance of the yarn under the mechanical performance and environmental conditions can be comprehensively analyzed, the use performance of the yarn can be deeply known, and the special requirements of different fields for the yarn performance are met.

The invention belongs to the technical field of detection devices, and particularly relates to a cable surface defect detection device which comprises a conveying assembly and a detection assembly, the conveying assembly comprises a winding roller and a driving motor, the output end of the driving motor is fixedly connected with one end of the winding roller, and the conveying assembly drives the winding roller to rotate through the driving motor; and when the winding roller rotates, the cable can be wound to achieve conveying work of the cable, the detection assembly comprises a gear ring, a gear, a transmission assembly, a rotating positioning plate and a plurality of detectors, and the gear ring is fixedly installed on the outer wall of the winding roller. When the conveying assembly conveys the mooring rope, the detection assembly enables the detector to rotate around the mooring rope, the mooring rope is detected while the detector rotates, the mooring rope can be comprehensively detected, the mooring rope does not need to be detected many times, detection is convenient and comprehensive, and the detection effect of the device is guaranteed while the detection efficiency is improved.

A device and a method of whole lifecycle multi-indicator synchronous detection of yarns or fabrics are provided. The device includes a hairiness detection unit, a first guide unit, a tension adjustment unit, and a friction unit. The device is used for circularly rubbing a closed-loop object to be detected with a preset length on the friction unit, and collecting hairiness data in real time through the hairiness detection unit. The tension adjustment unit is a free-falling tension adjustment unit used to automatically adjust tension of the object to be detected in real time to ensure the stability of friction and transmission of the object to be detected. By arranging the circulating friction closed-loop circuit and arranging the free-falling tension adjustment unit on the circuit, the friction stability is improved. The synchronous and rapid detection of multiple indicators of the object to be detected can be realized.

The invention discloses a method and device for detecting the uniformity of non-woven fabric through a flash evaporation method, relates to the field of fabric production and detection, and can solve the technical problem that an existing method for detecting the uniformity of the non-woven fabric through the flash evaporation method is large in delay performance. Performing time sequence analysis processing on the rolling pressure data and the light transmission intensity data to obtain a pressure change curve and a light transmission change curve; obtaining a uniformity curve of the detection sample based on an interpolation algorithm according to the pressure change curve and the light transmission change curve; marking outliers of the uniformity curve of the detection sample based on a maximum likelihood estimation method to obtain an outlier set; and according to a density-based clustering algorithm, obtaining a clustering analysis result of the outlier set, and according to the clustering analysis result, obtaining a uniformity detection result of the detection sample so as to adjust process parameters according to the uniformity detection result.

The present invention discloses a clothing defect detection method and device, which relate to the field of clothing production inspection, including a tooling plate, a connecting crossbar is provided at one end of the tooling plate, a guide rod is provided at the center position of one end of the connecting crossbar close to the tooling plate, a telescopic rod is movably provided at the bottom of the guide rod, and a slot is provided on the tooling plate, and a defect detection device is provided in the slot. The present invention sets the corresponding parameters in the control system in advance according to the material, style and color characteristics of the clothing before the detection process is started. During the detection, the rotating shaft rotates flexibly according to the instruction, and the adapted color filter is accurately selected, and the image acquisition device efficiently captures the details of the clothing image through the through slot. This intelligent process can accurately identify and locate various color defects, minor damages and sewing defects, greatly improving the accuracy and comprehensiveness of the detection.

The invention discloses a method for detecting the lasting antibacterial performance of an antibacterial non-woven fabric, and relates to the technical field of antibacterial performance detection. The method comprises the following steps: carrying out multi-dimensional data acquisition on the antibacterial non-woven fabric to obtain a multi-dimensional data set; extracting a plurality of bacterial colony image features; performing antibacterial analysis on the surface of the antibacterial non-woven fabric on the plurality of environmental data to generate a plurality of antibacterial correlation coefficients; carrying out antibacterial performance attenuation modeling, constructing an antibacterial attenuation model, carrying out antibacterial performance trend analysis, and drawing an antibacterial performance attenuation trend curve; carrying out antibacterial contribution calculation according to the antibacterial performance attenuation trend curve to obtain an antibacterial contribution degree, carrying out antibacterial durability analysis on the antibacterial non-woven fabric to obtain a durable antibacterial analysis result, and generating an antibacterial suggestion. The technical problem that in the prior art, the evaluation dimension is single in the antibacterial property durability detection process of the antibacterial non-woven fabric, and consequently the accuracy of the detection result is insufficient is solved, and the technical effect of improving the comprehensiveness and accuracy of antibacterial property detection is achieved.

The invention discloses an intelligent slub yarn parameter acquisition device, and relates to the technical field of slub yarn detection. The device comprises a device body, supporting legs are arranged at the corners of the bottom of the device body, an intelligent collector is arranged on the front face of the device body, an L-shaped frame is arranged on the back of the device body, a take-up roller is arranged in the L-shaped frame, a main shaft roller is arranged on the left side of the bottom of the inner wall of the device body, and two auxiliary wire rollers are symmetrically arranged at the bottom of the inner wall of the device body; a driving assembly is arranged at the bottom in the device body. According to the invention, the distance between the acquisition assembly and the slub yarn can be continuously changed, the appearance and detail drawings of the slub yarn at different distances are acquired by the acquisition assembly, and the acquired data are intelligently analyzed by the intelligent acquisition device, so that the acquired sample contains detailed data such as details and overall appearance, and the detection accuracy is improved. The reduction of the detection and analysis accuracy of the whole parameters of the slub yarn is avoided.

The present invention discloses a measuring device for processing clothing fabrics, including a measuring schematic component, a measuring accommodating cylinder, a measuring support frame, a clamping moving component, a U-shaped base of the device and a fabric body. The present invention belongs to the technical field of clothing fabric measurement, and specifically refers to a measuring device for processing clothing fabrics; in order to solve the problem that the results of existing clothing fabric measurements are not convenient to read, the present invention proposes a measuring schematic component, a suspension made by mixing electrorheological fluid and pigment powder can make significant and eye-catching marks on the fractures of multiple groups of fabric bodies, can maintain the shapes of the fracture moments of multiple groups of fabric bodies, can indicate the specific positions of the fractures, can be clearly observed through a transparent through-diagram shell, can measure the shapes of the fractures of the fabric body and the width of the jagged fractures through a horizontal measuring scale, the operation is simple, and the test results can be read more directly.

The invention is suitable for the field of fabric performance detection, and provides a thermal-wet comfort fiber fabric performance detection method and system, and the system comprises a data recording detection module, an antibacterial performance calculation module, a performance change model module, a barrier efficiency analysis module, a comfort performance simulation module, and a performance expression report generation module. According to the method, by introducing the dynamic humidity simulation environment, the actual use scene of the fiber fabric under different damp and hot conditions can be truly restored, the humidity simulation environment serves as a core variable in each step, the influence of humidity on the microbial activity and the adjusting effect of odor release are comprehensively analyzed, and the method has good application prospects. And the effect of humidity in barrier performance and comprehensive performance evaluation. Besides, an antibacterial efficiency index and a barrier efficiency index are innovatively introduced into the method, and the antibacterial performance and the odor release control capability are combined, so that the actual effect of the fabric serving as the microbial barrier is comprehensively evaluated.

The invention relates to the field of textile shrinkage detection, in particular to a knitted fabric shrinkage rate prediction method and system.The knitted fabric shrinkage rate prediction method comprises the steps that according to pixel points of a soaked knitted fabric, arrangement and distribution of knitted lines in the same knitted fabric area are analyzed, and the layout compactness of the knitted lines is obtained; according to the layout compactness of the knitting lines, the shrinkage degree of the fabric soaked in water is obtained based on the consistency condition of overall layout of the knitting lines in different knitting fabric areas; according to the shrinkage degree of the fabric soaked in water, the stretching condition of mutual penetrating and interweaving of knitting lines in the same knitted fabric area is analyzed, and the interweaving friction strength is obtained; according to the interweaving friction strength, based on the termination trend condition of the knitting line shrinkage progress in the same knitted fabric area at the continuous moment, the knitting line shrinkage deformation condition in the same knitted fabric area is analyzed, and a shrinkage prediction index of the knitted fabric area is obtained; and predicting the shrinkage rate of the knitted fabric. The accuracy of predicting the shrinkage rate of the knitted fabric is improved.

A stretchable fiber optic pressure sensor is a sensing device that uses stretchable optical fibers that deform in response to an applied force. A deformation of a fiber causes a decrease in an intensity or alters a duration of the transmitted light due to a bend, crease, or dent in the fiber. The sensor may be configured to determine a pressure or force as applied by an appendage of a user. Multiple sensors may be configured to be in contact with multiple appendages, such as insoles inserted in shoes to determine walking attributes such as a gait, posture, pace, toe-walking, limping, stumbling, foot drop, swaying, or shuffling of a user. The sensor is configurable to transmit data associated with the applied pressure or force to a user's mobile device or computer to monitor or diagnose health issues associated with walking attributes determined through the use of the sensor.

The invention relates to the technical field of textile detection, and discloses a textile quantitative chemical analysis automatic detection device, which comprises a frame body, and a liquid feeding mechanism, a dissolving, cleaning and filtering mechanism, a water bath circulation mechanism and a waste liquid discharge mechanism which are arranged on the frame body, the waste liquid discharging mechanism pumps out waste liquid in the dissolving, cleaning and filtering mechanism through a pipeline, and the water bath circulating mechanism is located outside the dissolving, cleaning and filtering mechanism and used for regulating and controlling the environment temperature. According to the automatic detection device for the quantitative chemical analysis of the textiles, solvent filling, fiber dissolving, liquid adding and cleaning, neutralizing, filtering and classified liquid discharging operation can be carried out on a detected sample at multiple stations, only the sample needs to be put into the crucible in the testing process, detection personnel can leave after the crucible is pressed, and all tests are completed automatically.

The invention relates to the technical field of textile measurement, in particular to a yarn twist measuring method, system and device. The method comprises the following steps: firstly, acquiring length variable sequences corresponding to an untwisting process and a twisting process of a test sample according to change characteristics of yarn length values of the untwisting process and the twisting process of the test sample; according to the numerical value change condition in the neighborhood reference range of the length variable of the untwisting process and the twisting process of the test sample, obtaining all deformation variable amplitudes of the test sample; and correcting the pre-applied tension value according to all the deformation variable amplitudes of all the test samples of the test yarn to obtain the corrected pre-applied tension value of the test yarn. According to the method, deep analysis is carried out by testing the uneven thickness distribution condition of the yarn, the corrected pre-tension value is reasonably set, and the accuracy of the yarn twist testing result is improved.

The invention relates to the field of fabric elasticity testing, in particular to an underwear elasticity and recovery performance testing method based on a human body model.The underwear elasticity and recovery performance testing method comprises the specific steps that firstly, the size of each part of a sample is measured, and the original size Xi0 is obtained; simulating actual wearing of the underwear sample finished product on a human body model device, and measuring the size of each part in a stretching state after the underwear sample finished product is stretched for a certain time to obtain a stretching size XiS; then, the sample is detached and spread on a horizontal table top to be relaxed and recovered, the sizes of all the parts of the sample are measured again after specified relaxation time, and the recovered size XiR is obtained; and finally, calculating the residual elongation and the elastic recovery rate through the following formula: the residual elongation Ei is equal to 100 * (XiR-Xi0) / Xi0, the elastic recovery rate Ri is equal to 100 * (XiS-XiR) / (XiS-Xi0); wherein i = 1, 2,..., i; compared with the prior art, for testing the three-dimensional structure and the dynamic wearing scene of the integrally-formed sports underwear, the problem that an existing testing means is disjointed with the actual use scene of the product is effectively solved.

The utility model discloses an airflow method drying rate tester for textiles, which comprises a shell, a flow sensor, a temperature sensor and a controller, wherein a mounting cavity is formed in the shell; the air source is arranged in the mounting cavity, and the air source is used for exhausting air outwards to drive external airflow to enter the air bellow along the test port; the water drop detection plate and the driving device are arranged in the mounting cavity; the driving device is connected with the water drop detection plate, is used for driving the water drop detection plate to translate and corresponds to / is staggered with the test port along the height direction; a temperature sensing unit and a wind speed sensor are arranged above the corresponding test port of the shell; the liquid dropping device comprises a dropper and a liquid supply device, the dropper is correspondingly arranged above the test port, the liquid supply device is arranged in the shell and connected with the dropper, and the liquid supply device drops liquid to the test port through the dropper; through the arrangement of the air bellow, the air source, the water drop detection plate, the temperature sensing unit, the air speed sensor and the liquid dropping device, the airflow method drying rate detection of the textile is realized, so that full-automatic measurement is realized, and the accuracy and the test efficiency of the whole test are greatly improved.

The invention relates to the technical field of hygienic product detection, in particular to a hygienic product finished product performance detection method, which comprises the following steps: S1, obtaining a hygienic product to be detected, and determining a performance index of hygienic product detection; s2, comparing the detection parameters obtained under the performance indexes, generating a detection data set according to the detection parameters, and generating a performance index difference curve according to the difference detected by the detection data set according to the performance indexes; s3, judging index difference distribution of the performance index difference curve, and calibrating an index difference region of the performance index difference curve; s4, historical detection parameters on the index difference area are called, multi-dimensional feature indexes of the detection parameters on the current index difference area are obtained through matching, and then difference degree factors of the multi-dimensional feature indexes are generated; s5, tracing the hygienic product detection process according to the difference degree factor to obtain a decision sequence of hygienic product detection; and the detection efficiency and accuracy of the hygienic products are improved.

A down-proof performance tester relates to the field of down jacket performance detection equipment, and comprises a base, a console, a rotating box, an ion fan, a ventilation mechanism and a collection mechanism, and the console is arranged on the base; the rotating box is driven by the console to rotate; an outlet capable of discharging down feather is formed in the bottom of the rotating box; the ion fan faces the rotating box; the ventilation mechanism comprises a plurality of ventilation holes, a first guide rail and a shielding plate, and the ventilation holes are formed in the face, opposite to the ion fan, of the rotating box; the first guide rails are formed on two sides of the vent holes; the baffle plate is movably arranged between the two first guide rails so as to open or seal the ventilation hole; the collecting mechanism is connected with the outlet and can seal or open the outlet to collect down feather. After the box rotation is finished, the baffle plate is lifted, the ion fan is started, and the air is blown into the rotation box through the ventilation holes, so that static electricity in the rotation box can be eliminated, down feather adhered to the inner wall of the rotation box falls off, the down feather is collected through the collecting mechanism below, the down feather detection device is more convenient and quicker, and the detection efficiency is improved.

The utility model discloses an elastic fabric snagging performance testing device which comprises a working table, a transversely arranged guide rail structure is connected to the working table, at least one sliding table is movably arranged on the guide rail structure, three rod pieces with adjustable angles are connected to the sliding table, sliding grooves are formed in the rod pieces, and the sliding grooves are connected with the sliding table. A connecting rod is arranged in each sliding groove in a sliding mode, the upper ends of the connecting rods slide in the sliding grooves, and the lower ends of the connecting rods are connected with nail hammers. Each sliding table is correspondingly provided with a rolling mechanism, each rolling mechanism comprises two side plates, three rollers capable of synchronously rotating are connected between the side plates, the rollers are in a circular truncated cone shape, the heads and the tails of the adjacent rollers are arranged in an inverted mode, and the three rollers in the same rolling mechanism make contact with the three nail hammers on the corresponding sliding table respectively. The snagging performance test of the elastic fabric has the technical characteristics of being comprehensive, accurate, high in stability and the like.

The invention relates to the technical field of cotton yarn detection, and discloses a synchronous detection method for multiple performance indexes of cotton textile yarns. The method comprises the following steps: acquiring a current surface image parameter of a yarn body appearance layer, a current internal structure parameter of a fiber structure layer and a current molecular motion parameter of a molecular chain layer corresponding to a current production batch of to-be-detected yarn; performing layered performance analysis on each parameter to obtain a first current performance state evaluation value of the yarn body appearance layer, a second current performance state evaluation value of the fiber structure layer and a third current performance state evaluation value of the molecular chain layer; and finally, performing matching judgment on each evaluation value and a preset performance state evaluation reference range, and triggering a corresponding detection calibration operation according to a result. According to the method, multi-level parameters can be synchronously obtained, comprehensive performance evaluation is realized, the problems of single detection dimension, low efficiency, poor result association, lag and the like in the prior art are solved, the detection reliability and consistency are improved, and production quality control and process optimization are assisted.