A non-destructive, inline, multi-channel fabric conductivity measurement system uses an array of opposing paired transmit/receive microwave horns on opposite sides of a fabric material moving in a production line, each horn pair corresponding to a channel in the system. A processor-based controller can control channel hopping, frequency hopping, and measurement orientation to acquire measurements of material conductivity and anisotropy, which measurements can be analyzed for defects that can be flagged in real time during production. Measurements and/or analyses can be stored to make roll-to-roll, batch-to-batch, day-to-day, or production-phase-to-production-phase comparisons useful in identifying the sources of production problems and/or the causes of corrections.

The disclosure relates to determining thermal insulation levels of clothing a user should wear when traveling to a destination. To do this, a thermal insulation level of clothing worn by a user and levels worn by a crowd can be analyzed from images including the user or the crowd. A thermal sensitivity bias for the user can be determined by comparing those levels for similar locations. Environment data can then be collected for the destination. A thermal insulation level of clothing worn by the crowd for the destination can be predicted based on the environment data. This level can be adjusted with the bias for the user to generate a thermal insulation level of clothing to be worn by the user at the destination. An image having clothing with that level can be displayed to recommend a style of clothing for the user to wear at the destination.

Embodiments include a system for test fitting fabric, comprising a flat structure comprising a test surface defined by four sidewalls and an interface configured to attach the fabric to the test surface. The four sidewalls include a first sidewall and a second sidewall substantially perpendicular to the first sidewall. The test surface comprises a first adjustable dimension substantially parallel to the second sidewall and a second adjustable dimension substantially parallel to the first sidewall. The system also includes a user interface configured to receive one or more inputs for adjusting the first adjustable dimension and the second adjustable dimension; a first mechanism configured to, in response to the one or more inputs, automatically move the first sidewall to adjust the first adjustable dimension; and a second mechanism configured to, in response to the one or more inputs, automatically move the second sidewall to adjust the second adjustable dimension.

Disclosed is a fabric identifying system including a fabric identifying apparatus for identifying the type of a fabric of clothing and a server. The fabric identifying apparatus includes an image camera for obtaining image information on a fabric structure of clothing, a fabric identifier for performing a function of identifying the type of the fabric based on the fabric structure of the image information. The server includes an artificial intelligence model learner for generating a fabric type identifying engine for learning the fabric structure of the image information of the received clothing through a deep neural network, the server is configured to transmit the learned fabric type identifying engine to the fabric identifying apparatus. According to the present disclosure, it is possible to identify the type of the fabric of the clothing by using the artificial intelligence (AI), the artificial intelligence based screen recognition technology, and the 5G network.

Fiber emitters, such as carbon nanotube (CNT) yarns, are used to create infrared (IR) transmitters that can operate at high data rates, can shift spectral response, and can emit polarized light, for example by alignment of the fiber emitters in close proximity and in parallel directions. These fiber emitters can, for example, be used in patches that can be bonded to fabric or to an object, or can be woven into fabric during fabrication of a textile. The fiber emitters can be used in a variety of methods, including for friend or foe identification, communications, and identification of objects

A method and system for inspection of an item, and a use thereof, are presented. The method comprises acquiring a plurality of projection images of an item at a plurality of projection angles for performing a tomographic reconstruction of the item. A plurality of objects are detected in the tomographic reconstruction and each object has a generic shape described by a parametric three-dimensional numerical model. Said detection comprises determining initial estimates of position and/or orientation of each object and at least one geometrical parameter of the three-dimensional model for each object. The initial estimates are iteratively refining by using a projection-matching approach, in which forward projection images are simulated for the objects according to operating parameters of the radiation imaging device and a difference metric between acquired projection images and simulated forward projection images is reduced at each iteration step.

An apparatus (100) for measuring not only the reflected radiation but also the fluorescence emission of a textile sample (106), which includes a presentation subsystem (102) having a viewing window (108). A radiation subsystem (114) has a tunable radiation source (120) for directing a desired radiation (122) having a wavelength range and an intensity through the viewing window (108) toward the sample (106), and thereby causing the sample (106) to produce a fluorescence (124). A sensing subsystem (126) has an imager (130) for capturing the reflected radiation and fluorescence (124) in an array of pixels. A control subsystem (132) has a processor (136) for controlling the presentation subsystem (102), the radiation subsystem (114), and the sensing subsystem (126), and creates a reflected radiation and fluorescence image containing both spectral information and spatial information in regard to the reflected radiation and fluorescence (124) of the sample (106).

The present invention relates to polypropylene non-woven fabric having excellent loft property, a method for preparing polypropylene non-woven fabric having excellent loft property, and a method for evaluating the properties of the polypropylene resin.

A sensor for measuring the degradation of a fabric property is disclosed. The sensor includes a conductive track and a sacrificial material coupled to the conductive track, such that degradation of the sacrificial material results in reduction or loss of electrical conductivity of the conductive track. A method of measuring the performance degradation of a fabric, using a sensor is also provided. The method includes the step of measuring the electrical resistance of the sensor, and comparing the result to a known or empirically measured value to estimate the remaining useful life of the fabric performance.

The present disclosure especially relates to a method, carried out by one or more devices, said method comprising: non-destructively determining structural information that is characteristic of at least part of the structure of a textile (202); ascertaining at least one treatment parameter of the textile (202) at least partly on the basis of said structural information; and outputting or initiating output of the at least one treatment parameter.