Method and apparatus for on-line quality monitoring in the preparatory apparatus of a spinning mill

The fluctuations in cross-section of fiber slivers are detected by means of a sensor, and from these detections are derived quality parameters, one of which is based on mass non-uniformity. Measurement signals are compared with a limit value for deviations from the desired weight of the monitored sliver, which limit value is formed as a product of mass non-uniformity and a selectable limit-value factor. Any measurement exceeding the limit value is interpreted as the presence of a thick place in the fiber sliver.

FIELD OF THE INVENTION 
The present invention relates to on-line quality monitoring in the 
preparatory apparatus of a spinning mill by measuring fluctuations in 
cross-section of slivers, and by deriving quality parameters from the 
measurement signal thus obtained, where one of the parameters comprises 
mass non-uniformity and deviations of the quality parameters from 
selectable limit values are detected. 
BACKGROUND OF THE INVENTION 
On-line measurement of this type is used, for example, in the data system 
of the USTER SLIVERDATA (USTER is a registered trademark of Zellweger 
Uster AG) which is employed to monitor quality and production in the 
preparatory apparatus of a spinning mill. Within the scope of quality 
monitoring, the silver count and periodic and virtually periodic mass 
fluctuations are checked, in addition to mass non-uniformity. 
It is known that most faults influencing the quality of the final product 
are caused by fluctuations in the silver count, silver non-uniformity, 
periodic mass fluctuations and drafting faults. In addition to this 
certain knowledge, it may be assumed that, on the basis of practical 
experience, short thick places also cause duality problems. This is 
because thick places of such a kind lead to cost-intensive disruptions in 
production and, moreover, influence the quality of the final product and 
the efficiency of all of the process steps. 
It has hitherto been possible to detect short thick places only by 
laboratory tests. These short thick places arise as a result of sliver 
accumulations, defective machine parts, inadequate maintenance and 
cleaning and incorrect machine settings, and can occur very frequently. 
Bearing in mind that 50 bobbins of yarn or more can be manufactured from 
the quantity of sliver produced in only one minute on a modern 
high-performance drafting frame, it becomes clear that the laboratory test 
cannot prevent serious losses of quality. Such a goal is possible only by 
way of on-line monitoring. 
OBJECT OF THE INVENTION 
It is an object of the present invention, therefore, to provide a method 
and system for on-line monitoring in the preparatory apparatus of a 
spinning mill, which allows the detection of short thick places. 
SUMMARY OF THE INVENTION 
The foregoing object is achieved, according to the invention, by comparing 
the measurement signals with a limit value for the deviations from the 
desired weight of the monitored sliver, which limit value is formed as a 
product of the mass non-uniformity and a selectable limit-value factor. 
Any section of the fiber sliver whose measurement exceeds the limit value 
is interpreted as a thick place. 
The method according to the invention allows the reliable detection of 
thick places having a specific length and a specific cross-section. The 
length depends on the speed at which the sliver is being fed and the 
sensing frequency. In a typical exemplary embodiment, the length of a 
detectable thick place can be around 4 cm. However, this does not mean 
that thick places of smaller length would not be detected. Rather, for 
shorter lengths the detection would simply have less than 100% accuracy. 
The advantage of basing the limit value on the mass non-uniformity is that 
the thick places are defined not in terms of their absolute cross-section, 
but rather in terms of the relative increase in cross-section in 
percentages of the desired sliver weight. More precisely, those thick 
places which cause a recognizable fault in the fabric, that is to say 
usually shading, are detected in this way. 
It was previously possible, under certain circumstances, to recognize thick 
places of this kind in a visual check by operating personnel. It is 
virtually no longer possible today. In particular, this is due to the 
increased production speed and to the fact that it is becoming 
increasingly common for machines for producing slivers, such as drafting 
frames, cards and combing machines, to be completely encased, with the 
result that a visual sliver check is no longer possible. On the other 
hand, the number of short thick places tends to increase with an increase 
in production speed, because these features are mainly caused by faults on 
machine parts and suction systems and by an uncontrolled wear of machine 
elements to be maintained. These faults and this wear increase with an 
increase in production speed. 
The invention relates further to an apparatus for carrying out the method, 
with a sensor for sensing the sliver cross-section and with an evaluation 
unit for processing the sensor signals, which has a first channel for 
determining the mass non-uniformity. In the apparatus according to the 
invention, the evaluation unit has a second channel for analyzing the 
sensor signals to determine whether they exceed a first adjustable limit 
value, which corresponds to an increase in cross-section of the sliver, 
and the size of which is also determined by the mass non-uniformity 
determined in the first channel.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT 
To facilitate an understanding of the invention, a known system of the type 
in which it can be employed will first be described. FIG. 1 shows the 
structure of an USTER SLIVERDATA system for monitoring production and 
quality in the preparatory apparatus of a spinning mill. A measuring 
member 1 for detecting fluctuations in cross-section of the monitored 
fiber sliver 2 is arranged, for each delivery line, on the machine to be 
monitored for the production of a fiber sliver, for example, on a card, 
drafting frame or combing machine. Since the measuring member itself is 
not a subject of the present invention, it is not explained in detail 
here. For further information regarding such a device, attention is drawn 
to U.S. Pat. No. 4,864,853, in which a preferred measuring member for 
fluctuations in sliver cross-section is described. 
The measurement signal from the measuring member 1 is connected to a 
processor 4 via a so-called machine station 3. A common processor 4 can be 
provided for a group of measuring members 1, up to sixteen in number. The 
machine station 3 also possesses, in addition to the input for the 
measurement signals from the measuring member 1, an input for signals fed 
by way of a line 5 from a production sensor (not shown), which serves to 
record speed as well as running and stopping times. This recording takes 
place by monitoring the rotational speed of a shaft, such as, for example, 
a delivery cylinder or calendar, that rotates in proportion to the 
production speed. 
The signals from the production sensor likewise pass via the machine 
station 3 into the processor 4, which calculates quality and production 
data from the measured values recorded for the individual deliveries, 
compares this data with limit values set by the user, and, if a limit 
value is exceeded, activates the competent machine station 3, whereupon 
the latter initiates a corresponding action. This action is either the 
activation of a warning lamp 6 in the event of minor, albeit acceptable 
faults or, by way of a line 7, the emission of a stop signal for stopping 
the machine in the event of serious faults. 
As illustrated, each machine station 1 also has stop connections 8 for 
automatically recording the cause of a standstill by means of machine 
signals, and a connection for a so-called numerical machine terminal 9. 
The latter device is an input and output station, via which various codes 
can be input and data retrieved. 
The processor 4 is connected to a central unit 10, the essential functions 
of which are to interrogate the processors periodically, process and store 
the measured values and machine signals, control the dialogue with the 
users and output data to higher-level systems. Video and/or printer 
terminals (not shown) connected to the central unit 10 serve as dialogue 
stations. 
The quality data calculated by the processor 4 is as follows: 
mass non-uniformity (coefficient of variation of the sliver count) in CV%; 
spectrogram of the mass fluctuations to indicate periodic and non-periodic 
drafting faults; 
average sliver-count deviation from a desired value (weight) in A%. 
To enable the system to be used as a warning system, warning limits are 
entered for each of the quality parameters, and when these are exceeded, a 
warning lamp 6 (FIG. 1) begins to flash at the corresponding delivery 
line. In addition to the warning limits, a stop factor greater than one is 
also entered, and this is used to stop the machine when the measured 
parameter exceeds the warning limit times stop factor. 
The coefficient of variation is averaged over the total analysis length of 
the spectrogram. For this purpose, the spectrograms of the individual 
delivery lines are determined in succession by the processor 4. This value 
is periodically updated, the interval between the individual updates 
depending on the train of machines and being, for example, between 15 
minutes and several hours. 
As is known, periodic faults and virtually periodical faults, so-called 
drafting waves, can be recognized from the spectrogram; the former by 
means of chimneys and the latter by means of hills. To analyze the 
spectrogram, the latter is subdivided into test regions, and for each 
region it is determined, by means of filters and warning limits, whether 
to trigger a warning in response to a fault magnitude of a hill or 
chimney. Monitoring is based essentially on a comparison of the values in 
the test region or test window with values obtained from the so-called 
base windows surrounding the test window. The warning is triggered when 
the ratio of the values in the test window to those in the base windows 
becomes higher than the warning limit. 
A series of production data calculated by the central unit 10 is also added 
to the quality data calculated by the processor 4. Production data of this 
kind includes, for example, the number of doffings or sliver can changes, 
actual efficiency, quantity produced, theoretically possible production 
per hour at 100% efficiency, time per doffing or sliver can change, number 
of machine standstills, total stop time, measured delivery speed. 
The monitoring of the sliver feed to detect short thick places, in 
accordance with the present invention, takes place within the machine 
station 3. Referring to FIG. 2, the machine station 3 processes the 
measurement signal MS from the measuring member 1 in three channels. In a 
first channel K1, the coefficient of variation of the sliver count for 
short fluctuations is determined in a known manner to produce an output 
value CV%; in a second channel K2, the sliver-count deviation from the 
desired value is determined as a value A%, and in a third channel K3, 
monitoring of short thick places DS takes place. This double calculation, 
based on the previous configuration of an USTER SLIVERDATA system, of the 
coefficient of variation and sliver-count deviation in the processor 4, on 
the one hand, and in the machine station 3 on the other hand, is not 
essential to the present invention. The values for CV% and A% can be 
obtained from the processor 4. Alternatively, the double calculation can 
be avoided by integrating the functions of the processor 4 into the 
machine station 3. 
In the first channel K1, fluctuations of the sliver count of a cut length 
of approximately 4 cm within sliver pieces of 100 m are measured. In the 
second channel K2, which in contrast to the channel K1 is a long-term 
channel, the sliver-count deviation from the desired value is measured, 
the measuring member 1 (FIG. 1) being calibrated to this desired value 
whenever the processed articles or materials and the sliver count are 
changed. The deviations of the sliver count from the desired value are 
integrated, so that the variation over time of the sliver count is 
calculated and stored in the channel K2. 
In the third channel K3, a monitoring of the fiber sliver 2 (FIG. 1) in 
respect of short thick places DS, that is to say periodically occurring 
increases in cross-section of a specific size, takes place. The thick 
places, which can occur in large numbers, arise as a result of sliver 
accumulations, defective machine parts, inadequate maintenance and 
cleaning and incorrect machine settings. They cause disruptions in 
production which are highly cost-intensive, and, moreover, they influence 
the quality of the final product and the efficiency of all of the process 
steps. 
It has hitherto been possible to detect short thick places only by way of 
laboratory tests, that is to say off-line, but this is insufficient in 
practice. This is because, in sliver sorting per layer, only 0.02% of the 
material produced is inspected in the laboratory, so that the results of 
laboratory tests are no longer statistically representative of the entire 
production. In addition, 50 bobbins of yarn or more can be manufactured 
from the quantity of sliver produced in only one minute by a modern 
high-performance drafting unit. 
To record the thick places DS, a thick place is first defined as a specific 
increase in cross-section relative to the desired value, for example as an 
increase in cross-section of at least 40%, and a limit value for the 
deviation from the desired sliver weight is established. This 
establishment of the limit value takes place by forming the product of a 
factor K times the average non-uniformity CV% calculated in the channel 
K1. The factor K itself depends on how many times the limit value can be 
exceeded per 100 m of sliver. The higher the value K, therefore, the fewer 
the number of times that the limit can be exceeded. 
In this respect, the desired sliver weight is not static, but rather a 
dynamic quantity. In the operating state, the average value of the sliver 
weight over the last 100 m is calculated in each case, and the working 
point of the system is thereby determined. If this working point, that is 
to say the average value, deviates from the desired sliver weight, then 
the limit value is corrected accordingly. 
In order to make the system as user-friendly as possible, a plurality of 
different settings, for example, eight detecting alternatives, is 
established, and from these the user can select the one which seems the 
most suitable for the current situation. The user consequently need not 
input a plurality of numerical values, but it is sufficient to input the 
respective detecting alternative, for example by means of a digit or a 
letter. 
The following Table 1 gives an example of how the detecting alternatives 
can be set up: 
TABLE 1 
______________________________________ 
EV GN GA Km 
______________________________________ 
1 1 5.0 .multidot. CV% 
100 
2 1 5.4 .multidot. CV% 
1,000 
3 1 5.8 .multidot. CV% 
10,000 
4 2 4.7 .multidot. CV% 
10,000 
5 5 3.7 .multidot. CV% 
10,000 
6 10 3.2 .multidot. CV% 
10,000 
7 20 2.9 .multidot. CV% 
10,000 
8 50 2.3 .multidot. CV% 
10,000 
______________________________________ 
In the first column of the table, eight detecting alternatives EV are 
given; the second column contains the associated limit values GN for the 
number of times the limit value is permitted to be exceeded over 100 m of 
sliver; and the third column contains the values GA (GA=K times CV%) for 
the deviation from the desired sliver weight (or from the average value of 
the sliver weight over 100 m). Finally, the fourth column indicates over 
how many kilometers of sliver the machine can be stopped one time or an 
alarm can be triggered as a result of normal statistical fluctuations in 
non-uniformity. 
In alternatives 1 to 3, where GN=1, the machine is stopped each time the 
limit is exceeded, with the probability of a stop as a result of the 
normal statistical fluctuations in non-uniformity being between 100 and 
10,000 km of sliver. In the remaining alternatives, a limit value GN of 2, 
5, 10, 20 or 50 is used for the number of overlimit conditions. In this 
case, the probability of a stop as a result of the normal statistical 
fluctuations in non-uniformity is per 10,000 km of sliver. In operation, 
the machine station counts the number of times a thick place is detected 
over a given length of the sliver being monitored, and triggers an alarm 
condition, e.g. actuates a warning light and/or stops the machine, when 
the limit number GN is reached. 
An example of the establishment of a limit value for thick places DS is 
given below: 
It is assumed that the detecting alternative EV is 3; the desired sliver 
weight=Nm 0.28 (corresponding to 3.57 g/m), and CV%=3. The deviation value 
GA is calculated as GA=5.8.times.CV%=5.8.times.3%=17.4%. 
The limit value is therefore 3.57.times.17.4%=0.62 g/m. The absolute limit 
value is equal to the desired sliver weight plus the limit value and this 
gives 3.57+0.62=4.19 g/m (around the desired sliver weight). 
The limit value for thick places DS therefore amounts to 4.19 g/m in the 
present case. If this limit value is exceeded once over a length of 100 m 
of sliver, the machine is stopped. An alarm without a stop is triggered if 
the limit value is a few per cent lower. 
The operating conditions of the system are such that the fiber sliver 2 is 
sensed 420 times per second, and the measured values are averaged over 
sliver lengths of 4 cm. This gives, at a maximum delivery speed for the 
foreseeable future of 1000 m per minute, at least one, and at lower 
delivery speeds, more than one, measured value per 4 cm of sliver length. 
This means, in turn, that thick places with a length of 4 cm are recorded 
with a certainty of 100%. Statistical analyses show that even 
substantially shorter thick places with a length of only 1 cm are still 
recorded with a probability of 40%. 
If the detecting alternative EV, once selected, is too sensitive, the 
existing limit can be broadened individually by the input of additional 
percentages. If, for example, in alternative 3 the CV is equal to 3.1%, 
then the deviation value GA amounts to 18%. An input of +6% then gives a 
new limit of 24%. The inputs and indications of the setting alternatives 
EV and the input of additional percentages take place by means of the 
numerical machine terminal 9 (FIG. 1). PG,13