Texas Tech University System

Other

Eric Hequet

Hamed Sari-Sarraf

Noureddine Abidi

Brendan Kelly

Zach Hinds

Ajay Pai

Aijun Zhu

Christopher N Turner

Md Abu Sayeed

Disclosed is a system and method for extraction of information of within sample distribution of fiber quality from high-volume instrument (HVI) fibrogram to better predict yarn quality than the standard HVI output. The present invention allows for information on fiber quality to be obtained while avoiding testing samples with more expensive techniques. The disclosed system and method extracts HVI data for collecting a respective set of initial fibrograms from a set of fiber samples and representing them as a distance matrix to form a matrix of transformed fibrogram data, said matrix of transformed fibrogram data comprising a vector of scores to represent each sample and thereafter explaining variation in yarn quality by extracting all of the information available from the fibrogram.

System and method for fibrogram fiber quality evaluation

Fabric wrinkles are automatically evaluated using a reliable, accurate, affordable, and efficient system. Two algorithms are used, the facet model algorithm and the plane-cutting algorithm, to extract features for evaluating wrinkles in fabrics. These algorithms eliminate the need for independent evaluation of a fabric specimen by a technician.

Fabric wrinkle evaluation

A cotton sample is subjected to noninvasive x-ray microtomographic image analysis in order to recognize cotton contaminants in the cotton sample. The cotton contaminants are detected and classified using an x-ray microtomographic system. Once the cotton contaminants in the cotton sample are detected and classified, the cotton sample may be graded based on the type and amount of cotton contaminants present.

Method for identification of cotton contaminants with x-ray microtomographic image analysis

The stickiness of cotton is determined by testing a cotton sample at two or more temperatures. Sticky deposits are recorded at a lower temperature, preferably 27&deg; C. or 34&deg; C., to detect the trehalulose-rich honeydews droplets. Then, the sample is subjected to a higher temperature, preferably 54&deg; C., to detect the non trehalulose-rich honeydew droplets and physiological sugars. By comparing the results at these two temperatures, an accurate grading system for cotton may be produced which can help growers and spinners accurately identify different types of cotton and determine processing problems.

Growing community of inventors

Lubbock, TX, United States of America

Eric Hequet