Span Length 

Span Length:

Span length is the distance exceeded by a stated percentage of fibers from a random catch point in drafting zone. 2.5% and 50% span length are the most commonly used by industry.

 2.5% Span Length and 50% Span Length:

x % Span length is the distance spanned by x %of fibers in the specimen being tested when the fibers are parallelized and randomly distributed and where the initial starting point of the scanning in the test is considered 100%. This length is measured using “Digital Fibrograph‘.

Significance of 2.5% Span Length-

American dept. of agriculture shows that 2.5% span length best matches with the staple length assessed by the classer and hence 2.5%span has become a universal standard for evaluating cotton.

 2.5% staple length is suitable for the spinning process.

The South India Textile Research Association (SITRA) gives the following empirical relationships to estimate the Effective Length and Mean Length from the Span lengths.

Uniformity Ratio:

The ratio between 50% span length and 2.5% span length is called uniformity ratio, express as a percentage.

Estimation full length from span length:

In the High Volume Fiber Tester, full length obtained from the span length distribution by constructing tangents on the Fibrogram. The tangent to the Fibrograph drawn from the 100% point of fibers and extrapolating to the lengths axis indicates the Mean length (ML). Similarly drawing a tangent from the 50% point of fibers and extrapolating to the lengths axis indicates the Upper Half Mean length (UHML).

Floating Fiber Index (FFI):

Fibers in the drafting zone that are not clamped by either of the pairs of rollers of drafting zone are referred to as floating fiber index. It is expressed as a percentage and calculated by the following equation.

Short Fiber Content (SFC):

SFC can be calculated from the output of the fibrogram

          SFC% = 50.01− 0.766×2.5%SL − 81.48× 50%SL

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Span Length

Fibrograph Method

Fibrograph Method or Photoelectric Scanning Method:

The original idea of the photoelectric scanning or Fibrograph method has been developed by Hertel in 1940 for testing cotton lint. This test method is much faster than the array method and is used widely in fiber laboratories for measuring fiber length and length distribution. These tests are performed with a Fibrograph instrument, which is a photoelectric device (fig.).

In Fibrograph, fiber samples are presented in the form of a pair of carefully prepared fringes. The light transmitted through these fringes is monitored by photoelectric current. The amount of light passing through the fiber sample is linearly proportional to the number of fibers in the light path. The changes in the photoelectric current are recorded graphically in the form of a Fibrogram as shown in Fig. From this Fibrogram various length parameters of practical interest, such as span length, mean length (OM), upper-half mean length (OR) and index of uniformity, given as the ratio of OM to OR, can be analyzed.

      

Preparation of Test Specimen

Test specimen can be prepared from the laboratory sample by on of the following method.

1) Hand Combing Method

Pick up a handful of cotton from the laboratory sample and separate it into two parts by pulling so as to expose a fresh surface of projecting fibers. Holding one of the hand combs in one hand and the opened lump of cotton in the other, transfer some of the projecting fibers on to the comb. Pick fresh lumps of cotton, and proceed in the same manner so that a pair of combs is filled with sufficient quantity of fibers drawn from 8 to 10 randomly picked lumps. Hold one comb in each hand, and untangle and parallelize the projecting fibers by mutual combing. The pair of combed beards constitutes the test specimen.

2) Fibro-Sampler Method

Mount one of the fibro-sample combs in the comb holder of the Fibro sampler, with the teeth uppermost. Place the laboratory sample in the cage and press it against the perforated surface. Maintain the pressure and rotate the sample holder round the drum counter-clockwise through 360°. Remove the loaded comb from the holder. Turn the sample in the cage to expose a fresh surface, and mount fibers in one more comb. Either one or a pair of combed beards constitute the test specimen depending upon the model of the instrument being used.

Fibrogram:

Fibrogram is an arrangement of fibers from shortest to longest in terms of span lengths. Fibrogram test are required for determining the length uniformity of fibers in the sample of cotton.

At any instant in time, fibers caught by the roller nips will depend on the randomness of their overlapping lengths; therefore, not all the length of a given fiber projects into draft zone. The lengths that project into the draft zone are called the span lengths, and the cumulative frequency distribution of the span length gives the Fibrogram.

Digital Fibrograph:

The digital fibrograph gives the tests results in digits or numerical form. Suppose In the 2.5% span the length is 1.14 inch while in the 50 percent span the length is 0.52 inch. The uniformity ratio is 46%.

Fibro sampler is used in later models to clamp the fibers on the comb. Fiber sample is put inside the cylinder of sampler. Fiber comb, with 13 needles/inch, is rotated around the fibro sampler, with pressure applied on the cotton, during which it picks up fibers projecting from the holes of sampler. The instrument is consequently insensitive to the presence of very short fibres, and in practice the Fibrogram has its origin at a point representing a length of 0.15 inch (3.8 mm).

Digital Fibrogram may be analyzed graphically to yield various length parameters of interest to the producers and users of cotton. The tangent to the curve at its starting point A cuts OY at P and OX at M. Then OM is the mean length of the fibers in the original population longer than 0.15 inch (3.8 mm). If OP is bisected at Q and the tangent to the curve from Q cuts OX at R, then OR is the upper-half mean length, UHML, and the ratio of OM to OR is a valid index of uniformity.

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Fibrograph Method

Length parameters of cotton fibers

Definition of length is based on two criteria- one based on its ‘full length’ i.e. end to end lengths (staple length, ML, EL, UHML,UQL) and the other based on ‘span length’(2.5% span length,50% span length, ML & UHML).

Mean length:

It is the arithmetic mean of the length of all the fibers present in a sample of the cotton. It can be calculated by number or weight of fibers.

Let us consider three fibers length (mm) and weight are  l₁,l₂,l₃ and w₁,w_2,w₃ respectively.

Upper Half Mean Length (UHML):

UHML is the mean length by the number of fibers in the largest half by weight of fibers in a cotton sample, usually measured from the fibrogram. Upper half mean length is normally equivalent to the staple length.

Uniformity Index (UI):

The ratio between mean length (ML) & Upper half quartile length is called uniformity index, express as a percentage.

Staple length:

The most frequent length in a fibrous sample is called staple length. Staple length is one of the most important factors of cotton quality because both fiber fineness and fiber tensile strength are associated with staple length. The longer staples are usually finer and stronger than the shorter staples.

Staple length can be of following types:

Staple diagram:

Graphical representation of the end aligned fiber beard (arrangement of fibers by the length in decreasing order starting from a horizontal line) is called staple diagram.

Cumulative frequency fiber length distribution (CFD) is also called the staple diagram (in short staple spinning) or diagram of Hauteur (worsted spinning). It is produced by sorting, either by number or by weight, the straightened lengths of the individual fibers making the sample. Generally, the CFD is obtained manually by the Suter-Webb method.

Coefficient of fiber length variation (CV %):

The coefficient of variation of fiber length CV % is the ratio of σ divided by the mean length ML. Where σ is the standard deviation of fiber length.

 Modal Length:

Modal length is the length in a fiber length frequency diagram, which has the highest frequency of occurrence. The modal length for long staple cotton is more than the mean length because of the progressive increase in the skewness of the fiber length distribution with increasing staple length.

Calculation of fiber length (on the basis of number & weight) from staple diagram

a) Mean Length (ML):

b) Upper Quartile Length (UQL):

UQL is the value of length for which 75% of all the observed values are lower, and 25% higher in the fiber sample.

c) Short Fiber Content (SFC):

SFC is the percentage by number or weight of fibers less than a specified length, 0.5 inches (12.7mm) for cotton, typically 25 or 40mm for wool.

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Length parameters of cotton fibers

Shirley Comb Sorter Method

Fiber length measurement

 As single fiber measurement takes time and hand stapling requires experience, alternative methods have been developed. There are two methods for laboratory analysis used to measure fiber length.

1. Fibers sorter method/Array method-is much slower but results are more accurate.


2. Fibrograph– is the more rapid test but results are not detailed or accurate.

Fiber sorter method:

The fiber sorter is an instrument which enables the sample to be fractionalized into length groups. The Baer sorter, the Shirley comb sorter, and the Suter-Webb sorter are the most popular method of the fiber sorter. Basically, the operation involves four main steps:

1. Preparation of a fringe or tuft with all fibers aligned at one end.


2. The separation or withdrawal of fibers in order of decreasing length.


3. The preparation of a sorter diagram by laying the fibers on a black velvet pad in decreasing order of length, the fibers parallel and their lower ends aligned along a horizontal base line as shown in Figure.


4. The analysis of the sorter diagram.

Suter-Webb array (SW):

This method consists of a bed of upright and parallel combs which control the fibers and arranged it in the form of an array of uniform density in the descending order of length. In this way enable the sample (fibers) to be fractionated into length groups for determining cumulative fiber length distribution by weight in parameters upper quartile length (UQL), mean length (ML) and % short fibers (SFC) as illustrated in Fig. and dispersion percentage which is expressed as (CV%). The disadvantages of this device are time-consuming (2 hrs. per sample) and calls for considerable operator skill in sampling and preparing the diagram (Fig.).

The Shirley comb sorter Method

Principle

A sample of fibers is arranged in the form of an array in the descending order of length, and from a tracing of this array some fiber length parameters are calculated.

Apparatus

a) Two set of combs

b) Fiber grip

c) Teasing needle

d) Aluminum depressor

e) Velvet pad, and

f) Rectangular perspex scale (160 x 80 mm) marked in 5 mm squares.

 

Construction:

1) This instrument consists of a two set of combs (top & bottom) arranged at fixed intervals to hold the fibers and keep them straight.

2) Here 8 top combs and 9 bottom combs are used, each comb are spaced 6 mm (¼ inch) apart except the first two bottom comb which is 3/16 inch apart.

3) The distance from a row of bottom needles to a row of top needles is 3mm (1/8 inch).

4) An aluminum depressor, grip, teasing needles, velvet pad etc. are also used.

Procedure:

1. A bundle of fibers prepared by one of the zoning methods is straightened by hand and pressed into the lower set of combs is impaled in the combs with the ends of fibers protruding, as illustrated in the left-hand side of Fig.A


2. The end of the bundle is straightened by gripping the ends of the outermost fibers with a wide clamp and withdrawing them a few at a time.


3. The whole sample is then transferred in this way, a few fibers at a time, to position B at the other end of the combs and placed there so that the fiber ends coincide with the first comb.


4. The sample is pressed down into the bottom combs and the top combs are then lowered onto the sample.


5. The rear combs are moved out of the way one at a time until the ends of the longest fibers are exposed.


6. The exposed fibers are then removed by the grip and laid on a black velvet pad. The next comb is then removed, so exposing the fibres which constitute the next length group and these are removed and laid next to the first set of fibres, making sure that all the fibres are laid with a common base line.


7. Then trace the outline of the fiber array prepared on a sheet of translucent paper (see Fig. C)

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Shirley Comb Sorter Method

Fiber Length and Length Distribution

                      Fiber Length & Length Distribution

Cotton Fiber Length Analysis

Cotton are graded by HVI measurements on the following parameters:

• Fineness


• Fiber length & Length uniformity


• Strength & Elongation


• Micronaire


• Color


• Maturity


• Extraneous matter (trash, leaf & neps)

Fiber Length & Length Distribution

Fiber length

After fineness, length is the most important property of a fiber. The length of cotton is directly related to its spinning performance. Knowledge of fiber length is necessary to manufacture a yarn of specific size on ring spinning system and typically longer fibers are used to manufacture fine yarns. Longer fibers are generally more uniform, finer, and stronger than shorter ones. Yarn quality parameters such as strength, elongation, hairiness, and evenness are strongly correlated to the length of cotton fibers.

Depending on the variety, cotton fiber length varies from 0.9 inches to about 1.6 inches. It has a fineness (diameter) of 18 microns (18/1000 of a millimeter) and an average length of 1.1 inches. Long-staple cotton has a fineness (diameter) of less than 15 microns and an average length of over 1.125 inches long. Long staple cotton is produced in small quantities due to the high cost of growing and processing it.

Fiber Length Distribution

Length distribution is also an important consideration during the spinning process when fiber lengths are sufficiently long to meet yarn spinning requirements. It can be calculated by number or weight of fibers. The following schematic in figure below helps better understanding the difference between both distributions:

Four “ideal” fibers are shown with the same linear density or ‘weight’. For example, we assume all 4 fibers weigh together 300g:

      By number, 50% of the fibers are short fibers.

      By weight, 33% of all fibers are short fibers.

Both length distributions are used in the industry today. The by number distribution usually gives you more accurate results when optimizing your processes in spinning. The by weight distribution is used by mills that have been used to results of the comb sorter array methods such as the Suter-Webb-Array. However, it is really e spinning mill to decide what values they prefer to work with.

Advantage of longer average fiber length

In general,a longer average fiber length is to be preferred because it confers a number of advantages.

Firstly, longer fibers are easier to process.

Secondly, more even yarns can be produced from longer fibers because there are fewer fiber ends in a given length of yarn.

Thirdly, a higher strength yarn can be produced from them for the same level of twist. Alternatively, a yarn of the same strength can be produced but with a lower level of twist, thus giving a softer yarn.

 Following are the most length distribution parameters in use in deferent countries:

 Mean length (ML)

 Upper half mean length (UHML)

 Upper quartile Length (UQL)/Upper quartile mean length (UQML)

 Effective length

 Span lengths, SL

 2.5% span length

 50% span length

 Modal length

 Uniformity index (UI%) and

 Uniformity ratio (UR%)

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Fiber Length and Length Distribution

Graphical Representation of Mass Variations

Graphical representations are aimed at providing easy analysis possibilities as well as providing more complete information than the numerical estimates. The following graphical representations are common with the latest generation evenness testers.

Spectrogram

 3D Spectrogram

 Variance Length Curve

 3D Variance Length Curve

 Normal Diagram

 Cut Length Diagram

 Histogram

Spectrogram

The numerical values such as U% or CV% are not influenced by the periodic variations. A spectrogram is used to measure the periodic or nearly periodic mass variations in a sliver, roving and yarn by analyzing the frequencies at which faults occur electronically.

The spectrogram (or spectrograph) is a graphical representation specifically designed for identification and analysis of the periodic faults. It is a representation of the mass variations in the frequency domain. In other words, a spectrogram shows how many times a mass variation repeats itself in a tested length of yarn. The figure shows an example of the spectrogram for a yarn.

The wavelength of a spectrogram directly indicates the distance over which the periodic fault repeats. Frequency and wavelength are related as follows

Arrangement of Spectrogram

►In a spectrogram, the X-axis represents the wavelengths and Y-axis represents the amplitude of the faults as shown in Figure. Often a logarithmic scale is given for the X-axis to cover the maximum range of wavelengths.

►The spectrogram consists of shaded and non-shaded areas. If a periodic fault passes through the measuring head for a minimum of 25 times, then it is considered as significant which is displayed by shaded area. When a fault repeats for about 6 to 25 times within the tests length of the material, then it is considered as unessential which is displayed by non-shaded area. Faults which occur less than 6 times will not appear in the spectrogram.

►A spectrogram starts at 1.1 cm if the testing speed is 25 to 200 m/min. It starts at 2.0cm if the testing speed is 400 m/min and it starts at 4 cm if the speed is 800 m/min. For spun material the maximum wavelength range is 1.28 km.

►Wavelength range covered by an evenness tester depends on the test speed and the evaluation time. With staple fiber yarns it covers a wavelength range 2 cm to 1280m and with filament yarns a range of 2 cm to 2560m.

►In the following spectrogram, periodic fault is shown at 7.7cm wavelength

3D Spectrogram

This 3D spectrogram may be used to identify whether the fault is present in a single output/delivery or common to all samples. If the samples are from the same machine and all the spectrograms indicate the same fault, then it can be concluded that the fault is due to a common problem such as main drive elements.

Theoretical spectrogram

If the CV of a yarn is zero then the spectrogram consists of a straight line. If the yarn has a completely random distribution of staple fibers, the staple length L has an effect on the spectrogram.

Case 1: The spectrogram of a fault free yarn consisting of all fibers with equal length (e.g. staple fiber yarn) will be as shown in Fig.a. It will be started at zero point corresponding to the staple length and a maximum value at 2.7 times the staple length.

Case 2: The spectrogram of a fault free yarn consisting of natural or variable length fibers will be as shown in Fig.b. In this spectrogram, the maximum amplitude lies at a wavelength of 2.82 x Mean fiber length.

Spectrogram with common periodic faults

Mainly two types of periodic faults are shown in the spectrogram. They are-

►1. Hill type faults

►2. Chimney type faults

Hill type faults

A hill type fault, where several adjacent peaks are noticed, is normally due to drafting waves caused by factors such as improper draft zone settings, improper top roller pressure, too many short fibers in the material, etc.

Chimney type faults

A chimney type fault, consisting of one or more ‘peaks’ or ‘chimneys’, is normally due to a mechanical fault such as eccentric roller/gear, improper meshing, missing gear teeth, missing teeth in the timing belts, damaged bearings, etc.

If the height of the peak (P) above the basic spectrogram at any wavelength equals or oversteps by 50% of the height of the basic spectrum at that wavelength i.e. P≥B/2, then it can be considered to be sufficiently serious fault.

Causes of periodic fault in fiber assembly

►Drafting waves are responsible for periodic faults. Drafting waves caused by factors such as improper draft zone settings, improper top roller pressure, too many short fibers in the material, etc. These produce chimney type fault/spectrogram.

► Mechanical fault such as eccentric roller/gear, oval shape roller, improper meshing, missing gear teeth, missing teeth in the timing belts, damaged bearings, defective apron, etc. are responsible for periodic faults. These mechanical faults produce chimney type fault/spectrogram.

Variance Length Curve

The variance length curve is a graphical representation of the coefficient of variation value CV for various cut lengths. It is produced by calculating the CV for different cut lengths and plotting it against the cut length on log-log paper. A perfect yarn would produce a straight line plot. A curve is a useful tool for examining long-term non-periodic variations in a yarn. The better is the evenness of the yarn the lower is the curve and the steeper is the angle it makes with the cut length axis. This is shown in Fig.(a), where the variance length curve for an actual cotton yarn is compared with a curve for an ideal yarn. The measured curve deviates from the theoretical curve in the region where there is long-term variation in the yarn. The variance length curve of a poor fiber assembly lies above the curve of a good fiber assembly as is shown in Fig.(b), where the poor yarn diverges from the good yarn at the longer cut lengths.

Normal Diagram

The Normal Diagram represents a graphical plot of the basic mass variations of the textile material over its length. The reference length for the mass values is the basic measured length of 1cm.

The diagram provides additional information on the mass variations which cannot be obtained with other forms of representation – either numerical or graphical. The following are some of the information which can be usefully applied for process control.

→both periodic and non-periodic variation in the material

→extreme thick places / thin places

→slow changes in the mean value

→step changes in the mean value

Cut Length Diagram

The cut length diagram is a graphical representation similar to a normal diagram but represents mass variations over specified cut lengths like 1,3,10, 100m etc. The variations over lengths lesser than the cut length of the diagram are suppressed.

With the help of diagrams of different cut lengths, the following information can be obtained:

→Checking of the functioning of auto leveler fitted draw frames.

→Checking of count variation (with cut length 100m).

→Setting of the sensitivity of the count channel in the latest generation Yarn Clearers.

Histogram

A frequency distribution diagram of the mass variation in yarns, rovings and slivers, from which one can identify whether the overall thick and thin places are evenly distributed in the material. For an evenly distributed material, the shape of the curve should be a bell shaped one.

 

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Graphical Representation of Mass Variations

                    Yarn Evenness II It’s Classification

Evenness, Unevenness, regularity, and irregularity are common terms used to describe the degree of uniformity of a textile product. In the textile field, the uniformity of products like the lap, sliver, roving or yam is expressed in terms of evenness or regularity or in terms of unevenness or irregularity.

A yarn which is not uniform is said to be irregular or to contain yarn defects or faults. These faults vary in their cross-sectional size and length. Fig. shows a plot of fault cross-sectional size against fault length.

 

In the above plot, three distinct categories of yarn faults are represented based on their size, length and their frequency of occurrence.

 Unevenness or Irregularity

 Imperfections

 Objectionable yarn faults

Unevenness or Irregularity

The irregularity or unevenness of a yarn is commonly defined as the variation in fineness along its length and more appropriately as the variation in mass per unit length along the yam’. It is expressed as U% or CV%.

The following yam properties are usually subject to variation.

→ Weight per unit length

→ Twists per inch

→ Diameter

→ Strength

Classification of Yarn Irregularity

Generally two types of variation are shown in yarns (especially spun yarns).

 1. Random Variation

 2. Periodic Variation

Random Variation:

Random variation is a variation that occurs randomly in a textile material without any definite pattern or order is called random variation. This is caused mainly due to the natural variations in the fiber properties.

If a yarn was cut into one-inch lengths and the weight of each consecutive length is determined and then the weights are plotted in a graph against the lengths.

 When the plotted points are joined to form a graph. It represents an irregularity trace.

 A mean line is drawn to indicate the average value of the weight of the one-inch lengths of yarn.

 Thus the deviation of each point or value from the mean can be observed. If the deviations from the mean are of a random nature and no definite pattern of variation is visible, as seen in the figure, then the variation is called ‘random variation.

Periodic Variation:

Periodic variation is a variation that occurs at definite length sequences in the textile material.

If a yarn were cut into one-inch lengths and the cross sections of each consecutive length are determined and then the cross sections are plotted in a graph against the lengths. The plots are joined to form a graph as shown and a line indicating the mean value is drawn.

 Usually two terminologies ‘wavelength’ and ‘amplitude’ are used to describe the periodic variation.

 Figure illustrates these two terms. The wavelength is the distance from one peak of the wave to the next on the same side of the mean line and amplitude is a measure of the size of the deviation from the mean level.

 If the deviations from the mean are in a definite sequence, the variation is called ‘periodic variation‘.

Classification of Periodic Variation

Periodic variations may be classified according to their wavelength,using the fiber length as a length unit.

Classification of Periodic Variation

Periodic Variation	Wavelength
Short term variation	1 to 10 times the fiber length
Medium term variation	10 to 100 times the fiber length
Long term variation	100 to 1000 ( or more) times the fiber length

The different classes of periodic variation affect the appearance of the woven or knitted fabrics in different ways. The amplitudes of short term variations are generally greater than those of the longer term variations. This is because they are usually the result of faulty processing at the last machine and they have had no chance of being reduced in amplitude by drafting and doubling.

Moire effect:

Periodic variations in the range of 1 cm to 50 cm are normally repeated a number of times within the woven or knitted fabric width, which results in the fact periodic thick places or thin places, will lie near to each other. This produces, in most cases, a “MOIRE EFFECT”. This effect is particularly intensive for the naked eyes if the finished product is observed at a distance of approx. 50 cm to 1m.

Causes of Irregularities

The factors determining the single zone drafting wave irregularity are:

 Strictly Random Occurring Faults

1. The size of draft


2. The count of the input material


3. Multiple inputs or doubling


4. Roller or drafting zone setting


5. The degree of parallelism, length, and fineness of fibers in the input material

 Strictly periodic occurring faults

6. Eccentricity of roller shaft


7. Belt life comes to end


8. Bearings out dated


9. Apron faults


10. Rubber cots faults


11. Waste between gear meshing


12. 12. Damaged Gear teeth

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Yarn Evenness II It's Classification