A Critical Evaluation of the Relationships Between Arealometer Instrument Values and Cotton Fiber Perimeter

Abstract

Arealometer instrument values are computer simulated to study the error in the calculated fiber perimeter P due to instrumental errors. (This airflow device senses the fiber's specific surface at two different specimen compressions; P and wall thickness t are computed from the readings.) Systematic changes over time in instrument values from designated true values are classified into thirteen nontrivial combinations. Each combination results in different P values and, consequently, a unique drift or error in P. Simulations of 50,000 Arealometer observations using actual standard deviation data from a control cotton are also run. These simulations show that random variations in instrument values over time are, in effect, an unordered sequence of the nontrivial combinations. Also, a mean taken from only two to six Arealometer observations— the accepted practice—does not adequately characterize a cotton sample. Fundamental relationships are probed with partial and total derivatives of Arealometer functions. There is more variability in the calculated P than in the t value. The total differential dP accurately measures the error in P, given the error in the instrument values.Two important properties of cotton are its maturity and fineness. The fundamental measure of maturity is fiber wall thickness, and the fundamental measure of fineness is the fiber's cross-sectional perimeter. (All other geometric measures of maturity and fineness, such as fiber wall area, Micronaire, maturity index, and dye maturity, are, in fact, nothing more than different functions or combinations of wall thickness and perimeter. An infinite number of combinations of wall thickness and perimeter are possible [ 13 ] . ) Maturity and fineness also influence end-use properties such as mechanical processability, dye uptake, luster, fiber cohesion, yarn strength, and uniformity.Thus we write, for example, cross-sectional wall area ( WA ) and micronaire ( Mic) as functions of wall thickness and perimeter: See reference 10 for a proof of Equatiori 1. Equation 3 is given without proof; its derivation will be presented elsewhere: Substitution of Equation 1 into Equation 3 yields Equation 4:This labdratory is developing a high speed method of analysis for t and Phrased on near-infrared reflectance spectroscopy ( NIRS ). The speed of analysis by NIRS is comparable to that of high volume instruments ( HVI ) that currently measure several other components of cotton quality.Basic research in this laboratory has shown unequivocally that NIRS senses t and P simultaneously and independently [10][11][12][13][14][15] . Consequently, all the other measures of maturity and fineness may be measured. The observed NIR reflectance is primarily a function of t and P and, to a lesser extent, the impurities in cotton. (See Table I for a comparison of fiber properties sensed by the Micronaire instrument and by NIRS.)The reflectance R can be described by the simplified linear equationwhere OD is the reflectance in optical density units (i.e., log 1 /R) and a, b...

Vibrational spectroscopic investigation of Australian cotton cellulose fibres Part 1. A Fourier transform Raman study†

“…1 Its characterization and classification are important for its primary producers, textile manufacturers and scientists. [2][3][4] There have been many investigations concerning the assessment of cotton fibres before processing. [2][3][4][5][6] Various techniques, including optical, physical and chemical methods, have been developed to classify cotton cellulose.…”

“…[2][3][4] There have been many investigations concerning the assessment of cotton fibres before processing. [2][3][4][5][6] Various techniques, including optical, physical and chemical methods, have been developed to classify cotton cellulose. Before 1960, the classification was carried out by visual analysis using hand and feel inspection methods.…”

Cotton Testing

“…Random variation was addressed thoroughly in a doublecompression instmment, where estimates of linear density and maturity depend on small differences between airflow properties measured at two levels of compression [130]. It showed the effect of varying sample mass -necessary for automated HVI lines -and found 'drift' in the Micromat rather than the step changes of earlier models.…”

Effects of Cotton Fiber Blending and Processing on HVI Measurements—Part I

“…Several characteristics of the cotton fiber assembly influence the air 8ow rate: void fraction, fiber shape, and 5ba orientation [ 11 ] . Low micronaire implies high surface area per unit volume.…”