JP2002088599A - Control system for yarn texturing machine - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an control system for a yarn texturing machine, capable of detecting various kinds of abnormalities of the yarn online. SOLUTION: In this operation control system for a yarn processing machine, capable of controlling an operation state of a yarn processing machine online, the operation control system for a yarn processing machine is equipped with a data collection part for measuring the shape of a finished yarn, subjecting the measured signal to an A/D conversion into measured data of digital value at a fixed sampling period, successively memorizing the measured data at a fixed period and at a point of time when the latest value of measured data is out of a preset control range, memorizing measured data of a fixed period from the point of time besides the measured data memorized at the fixed period of time and with an abnormality treatment part for obtaining an average value of the whole memorized data and detecting an abnormality from the average value.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to the operation of a yarn processing machine such as a false twisting machine and an air processing machine, and more specifically, to the operation management of a yarn processing machine for online management of abnormalities such as the occurrence of thread breakage. About the system.

[0002]

2. Description of the Related Art In a yarn processing machine such as a false twisting machine or an air tasrun machine, a heating device, a processing device, and the like are arranged in a processing process, and the yarn guiding is complicated. ,
This process requires manpower. Further, the quality inspection of the processed yarn package is manually performed so that the product having the abnormal quality, that is, the processed yarn package is not shipped. In addition, the inspection with the processed yarn package is an inspection of the surface layer, and there is an unavoidable problem that the quality abnormality in the inner layer cannot be inspected.

For this quality control, Japanese Patent Laid-Open No. 7-138
Japanese Patent Publication No. 828 discloses a quality control device for a draw false twisting machine, which detects the tension of a running yarn being processed by a draw false twisting machine and evaluates the package quality based on the number of times of accumulation and the accumulated time of fluctuations exceeding a predetermined value. Has been proposed.

Japanese Unexamined Patent Publication No. 2000-119924 discloses a method for detecting loop unevenness of an air-processed yarn by using a yarn sway detecting means including an image pickup means and a yarn running in a yarn passage between a supply roller and a fluid ejection nozzle. There has been proposed a method of detecting loop unevenness of an air-processed yarn by detecting a yarn swaying state of a thread.

[0005]

The above-mentioned prior art is effective in solving the above-mentioned problem in quality control of the processed yarn, but does not consider the management of the abnormal operation. Japanese Patent Application Laid-Open No. 2000-119924 requires an image pickup means, and if it is provided for each weight, there is a problem in terms of equipment cost. There is a problem in application to plying yarn in that a tension detector for measuring by using an automatic operation is used, and a new online operation management system capable of online management from operation abnormality to quality control is required.

SUMMARY OF THE INVENTION The present invention has been made in view of the above-mentioned circumstances, and an operation management system for a yarn processing machine capable of managing various abnormalities online by detecting one yarn characteristic and further managing the quality online. It is intended for.

[0007]

That is, the present invention relates to a yarn processing machine operation management system for managing the operation state of a yarn processing machine online, which measures the form of the processed yarn and outputs the measurement signal. A / D-converts the measurement data into digital values at a predetermined sampling period and sequentially stores the measurement data for a certain period, and stores the measurement data when the latest value of the measurement data is out of a preset management range. A data collection unit that stores measurement data for a certain period from this point in addition to the measurement data of this point, and an abnormality processing unit that calculates an average value of all stored measurement data and detects an abnormality based on the average value. It is an operation management system for a yarn processing machine.

According to the present invention, as described above, the management is performed based on the measurement data of the form of the processed yarn from which much information such as the thickness, the conjugation, and the variation of the processed yarn can be obtained. However, always reduce the processing time by only determining whether or not it is within this management range and collecting data only,
Online processing is enabled by performing abnormal processing only when the deviation is within this range, and abnormality judgment is performed based on the average value of the measurement data for a predetermined period before and after the deviation, and partial yarn breakage, abnormal connection, etc. Thus, accurate and stable detection of various abnormalities such as the above has been achieved, and the object has been achieved.

[0009] The present invention is particularly effective from the above points when the processed yarn is a combined yarn obtained by combining two or more yarns, but it is apparent from the gist that the present invention can be applied to a single yarn. is there. Further, in the present invention, the abnormality processing unit detects a case where the average value exceeds a preset connection threshold value as a connection abnormality, and detects a case where the average value becomes less than the preset yarn breakage threshold value as occurrence of thread breakage. In addition, it is preferable to perform the forced thread cutting process from the viewpoint of labor saving and stabilization of the process. Furthermore, it is preferable from the aspect of quality control of the package that the abnormality processing unit includes a fluff detecting unit that detects a case where a predetermined number of measurement data continuously exceeds a preset fluff threshold value as fluff.

[0010] In the present invention, the detection of the form of the yarn is preferable in that the photoelectric sensor can stably detect without contact. In particular, a two-optical axis type photoelectric sensor that includes two sets of light receiving elements and light emitting elements whose optical axes cross at right angles to each other and uses the larger output as the sensor output is capable of detecting a yarn that shows a complex form of variation. It is preferable because it can be stably formed.

Further, in the present invention, by providing an index monitoring unit for obtaining and storing an index value relating to quality from the stored measurement data for a certain period of time and displaying the same, it is possible to realize a single system from abnormality to quality control. . At this time, it is preferable from the viewpoint of online processing that the data collection unit and the abnormality processing unit that require urgent processing are processed by interrupt processing with high priority, and the quality management unit is performed by normal processing with normal priority.
As an index, a CV (= standard deviation ÷ average value) obtained by dividing a standard deviation value of measurement data for a certain period stored during the certain period by an average value, and a certain width of this CV as an index Frequency distribution divided in the value range of.

[0012]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described below in detail with reference to an embodiment using an air task run machine. FIG. 1 is an explanatory diagram of a basic configuration of one spindle of an air tasrun machine according to an embodiment.
Actually, this configuration is arranged in parallel with a predetermined weight.

As is apparent from the drawing, the air taslan processing machine of this embodiment has the same configuration as that disclosed in Japanese Patent Application Laid-Open No. H11-107093. That is, the core yarn A and the sheath yarn B to be processed are supplied from the respective packages of the yarn supply stand (not shown) through the yarn cutter 1 for the yarn cutting process. And the core yarn A shown by the dashed line in the figure is:
After passing through the yarn cutter 1, the yarn feeder 7A, the yarn guide 8
Is supplied to the fluid jet machining device 4 below the yarn guide through the yarn guide.

On the other hand, the sheath yarn B shown by a dotted line in the figure also passes through the yarn cutter 1, and thereafter, the yarn feeder 7B, the heating pin 2, the yarn feeder 7C, the yarn feeder 7D, the yarn heating device 3, and the yarn It is heated to a predetermined temperature by the yarn guide composed of the feed roller device 9A and supplied to the fluid jet processing device 4.

Here, the yarn feeders 7A to 7D are composed of a feed roller and an apron belt, and are adapted to press the yarn against the feed roller with an apron belt and feed the yarn at a predetermined speed. Each of the yarn feed roller devices 9A to 9B includes a feed roller and a nip roller, and feeds the yarn at a predetermined speed by pressing the yarn against the feed roller with the nip roller. As the yarn heating device 3, a device incorporating a tube heater based on a heating medium heating method was used.

The core yarn A and the sheath yarn B supplied to the fluid jet processing device 4 are processed by a jet jet and combined to form a predetermined processed yarn C shown by a solid line in the figure. The processing yarn C from the fluid jet processing device 4 is provided with oil by an oiling device (not shown) or the like as necessary, formed on the processing yarn package 6 by the winding machine 5, and is appropriately ball-shaped by a doff device not shown. It is configured to be fried.

In this embodiment, as shown in the drawing, in order to manage the operation status and the quality of the processed yarn package 6 of the product in the air turbulence processing machine having the above-described configuration, the yarn guide before winding is controlled. A yarn sensor 11 for detecting the form of the processed yarn C is provided. This thread sensor 1
For example, a well-known photoelectric sensor or the like may be used as long as it can continuously detect the form of a yarn traveling at a constant speed.

In the present embodiment, the yarn sensor 11 is
A two-optical axis photoelectric sensor comprising two sets of light-emitting elements and light-receiving elements whose optical axes are orthogonal to each other as disclosed in, for example, Japanese Patent Application Laid-Open No. 1-350269, and outputs the larger of the two output signals as a sensor measurement signal. Was used. Then, the measurement was performed such that the processed yarn C passed through the intersection of the optical axes in the same manner as disclosed in the publication. This makes it possible to detect the morphological change stably and accurately under a wide range of processing conditions up to a processing speed of 600 m / min with a processing yarn of up to 500 denier even with a processed yarn showing a complex morphological change, especially a plied yarn. It was confirmed that data necessary for detection and quality control could be obtained online.

In the operation management system of this embodiment, the operation status and the quality index of the processed yarn are continuously and continuously managed on the basis of the measurement signal from the yarn sensor 11. Less than,
The details will be described with reference to FIGS. FIG. 2 is a block diagram of the basic configuration of the operation management system of this example, FIG. 3 is a data collection unit of the management means, FIG. 4 is an abnormality processing unit, FIG. 5 is an index monitoring unit, and FIG. It is a flowchart of a part.

The operation management system of the present embodiment has the following configuration as shown in FIG. That is, a yarn sensor 11 provided on each weight for detecting the form of the yarn, a scanning circuit 12 for sequentially switching and outputting the measurement signal from the yarn sensor 11 for each weight, and an A / D conversion of the measurement signal from the scanning circuit 12 An A / D conversion circuit 13 for converting the data into digital value measurement data, an interface circuit 14 for receiving the measurement data from the A / D conversion circuit 13, and a computer 15 for reading and processing the measurement data of the interface circuit 14.
And management means stored in the computer 1
5, the thread cutter 1 of the corresponding weight is operated via the interface circuit 14 based on the processing result of the management means stored in the storage unit 5 to perform the thread break processing.

The management means stored in the computer 15 includes:
It comprises a data collection unit shown in FIG. 3, an abnormality processing unit shown in FIG. 4, an index monitoring unit shown in FIG. 5, and a display unit shown in FIG.
It is configured to operate as follows. Although not shown, the management means can transmit and receive necessary information via the interface circuit 14 with a control device of the machine.

The management means of the operation management system includes a data collection unit shown in FIG.
Collect the measurement data from 1. This data collection unit is configured to be activated at a constant cycle by an interrupt signal from a timer having the highest priority of processing. In this example, this period can be selected from 0.1 ms to 5 ms. This cycle has a processing speed of 300m
In the sampling interval at the yarn length in the case of / minute,
This corresponds to 0.5 mm to 25 mm, which is a sufficiently small sampling interval for measurement of morphological variation, and can sufficiently cope with a processing speed of about 600 m / min in the above-described cycle.

When the data collection unit is started, it first enters a weight number setting step, and first sets a weight number for data collection to, for example, a first weight. Then, first, a winding flag determination step indicating whether or not the weight is being wound is entered,
It is determined whether or not the winding flag is ON.

If the winding flag is not ON (NO), a winding start determining step is entered to determine whether or not the weight has started winding based on a signal from the winding machine. If the winding is to be started, the process proceeds to "YES", and in the winding flag setting step, the winding flag is set to ON, and the process proceeds to a data reading step described later. "N" which is not the winding start
In the case of "O", the data collection of the weight is skipped, and the process proceeds to a step of determining the end of all weights described later.

When the winding flag is ON and when the above-mentioned winding is started, a data reading step is entered, and the weight of the set weight number, that is, the yarn sensor 11 of the first weight, specifically, the above-mentioned first weight Read the measurement signal as follows. That is, a first weight selection command is issued to the scanning circuit 12 to cause the first
The weight yarn sensor 11 is selected and connected to the A / D conversion circuit 13, and the A / D conversion circuit 13 samples and A / D converts the measurement signal, and obtains the measurement data via the interface circuit 14. Read.

Then, in the next data storage step, the current value of the read measurement data is stored in both the abnormality determination storage area and the index storage area. The memory for abnormality determination is stored in a ring memory system for sequentially storing measurement data during the latest fixed time. The storage for the index stores measurement data during a certain period of time. In this example, this storage time range is set so that the measurement data for one second is stored for each weight in both memories. In this example, since the interruption period is 2 milliseconds, 500 pieces of measurement data are stored for each weight.

When the above data storage is completed, the process proceeds to the next step of determining the number of index data, and it is determined whether or not the stored number of index data has reached the predetermined value of 500 in this example. When the number reaches 500, the process proceeds to “YES”, and in an index flag setting step, an index flag for controlling the execution of the processing is set to ON by an index monitoring unit described later, and the weight of the weight in the index storage area is set. Is stored in the evaluation storage area.

After the processing or the number of stored index data is 5
In the case of "NO" of less than 00, the process immediately proceeds to the abnormality flag determination step. In this step, it is determined whether or not an abnormal flag indicating that data collection is being performed in an abnormal state where the measured data is out of the management range is ON. If the abnormality flag is not ON, the process proceeds to "NO", and enters a step of determining the current value stored above.

In this step, it is determined whether or not the current value is within a preset management range. When the abnormality is out of the control range, the process proceeds to “NO”, the abnormality flag is set to ON in the abnormality flag setting step, and then, in the collected data saving step, 500 measurement values stored in the abnormality determination storage area are set. The data is stored in the past abnormality storage area.

After this process is completed or immediately when the present value is within the management range, ie, “YES”, a step of determining whether or not the entire weight is completed is started. Then, in this determination step,
Whether or not data collection for all spindles has been completed is determined by the spindle number. In the case of “YES” of the end of all the spindles, this processing is exited and the operation is suspended until the next interrupt timing. On the other hand, in the case of “NO” indicating that all the spindles are not completed, a spindle number incrementing step is performed, the spindle number to be processed is incremented by one, the process returns to the winding flag determination step, and the process proceeds to data collection of the next spindle, for example, the second spindle.

As described above, the data collecting unit always holds the data for one second in this example for the last fixed time for abnormality determination, and once the measured data of the yarn sensor 11 is out of the management range, further holds the data for a certain period thereafter. Time In this example, one second of measurement data is stored. In addition, the measurement data for the index is repeatedly stored every second for a predetermined time in this example.

If the abnormality flag is ON in the above-described abnormality flag determination step, the flow advances to "YES" to enter the abnormality data number determination step. In this step, the number of abnormal data collected and stored after the occurrence of the abnormality in which the current value is out of the management range is 500 corresponding to one second.
It is determined whether or not the number has been reached. In the case of “NO” which has not been reached, the process proceeds to the spindle number increment step, and proceeds to data collection of the next spindle.

When the number reaches 500, the "YES" direction, that is, the data collection for the abnormalities of the weight is ended, and the data enters the point A in FIG. 3, that is, the abnormality processing unit shown in FIG. The following abnormal processing is performed on the weight. First, an average calculation step is entered, and in this example, an average value of 1000 pieces of measured data of the weights stored in the past abnormality storage area and the current abnormality storage area is obtained.
As described above, in the present invention, since the average value of the data before and after the instantaneous value deviates from the management range is used, accurate detection reflecting the situation before and after the instantaneous value can be performed.

Next, the process proceeds to a determination step of the entrainment, in which it is judged whether or not there is an entrainment abnormality, which is an extra thread such as an adjacent weight, mixed into the spindle, which is one of the problems in the plying process.
This determination is made by comparing the average value just obtained with a preset connection threshold value. If the average value exceeds the entrapment threshold, it is determined that an entrapment abnormality has occurred, and “Y
ES ”. Then, proceed to the abnormality processing step,
The yarn cutter 1 is operated for the weight to perform the thread cutting process for forcibly cutting the yarn and holding the yarn end, and at the same time, the winding machine is stopped. Then, a winding flag reset step is entered, and the winding flag is turned off.

Thereafter, the step of storing the abnormal data is started, and the details of the abnormality, that is, the connection abnormality, the time of occurrence, and the above-mentioned 1000 measurement data before and after this are stored in the weight management file of the relevant weight. Note that an empirical value obtained by an actual test or the like is used as the connection threshold. Further, it was confirmed that stable and accurate detection was possible by the discrimination based on the average value.

On the other hand, when the average value is equal to or less than the connection threshold,
It is determined that there is no abnormal connection, and the process proceeds to “NO” to enter a thread break determination step. In this step, it is determined whether or not a yarn break has occurred, including a partial break in which only a part of the yarn unique to the combined yarn breaks. This determination is made by comparing the average value with a preset yarn breakage threshold value. Then, when the average value is less than the thread breakage threshold, the process proceeds to “YES” as thread breakage occurrence, and enters an abnormality processing step as in the case of a stuck-in abnormality, and performs the same thread breakage processing and stop of the winder. Then, the winding flag is turned off in the winding flag reset step, and the same data storage is performed in the abnormal data storing step. It should be noted that an empirical value obtained by an actual test or the like is used for the thread breakage threshold, and the value is assumed to be able to detect partial breakage. In addition, it was confirmed that partial breakage could be stably and accurately detected by the discrimination based on the average value.

If the average value is equal to or larger than the thread break threshold, it is determined that no thread break has occurred, and the process proceeds to "NO" to enter a next fluff occurrence determination step. In this step, it is determined whether or not significant fluff has occurred due to abnormal quality. This determination is made by storing
The measurement is performed by comparing each of the 00 measurement data with a preset fluff threshold value. In this example, the case where the predetermined number of measurement data continuously exceeds the fluff threshold is detected as fluff, and it is determined that fluff has occurred. If a fluff occurs, the process proceeds to "YES", and the abnormal processing is not performed. Then, the process enters an abnormal data storage step, in which data associated with the fluff is stored as in the case of the thread breakage described above. In addition, from the viewpoint of quality control, it is preferable to comprehensively manage the fluff in terms of the number of fluffs in the processed yarn package, the size of each fluff, and the like. This is the above processing. However, when the number of fluffs exceeds a predetermined number, a configuration in which abnormal processing is performed automatically as in the case of thread breakage when the number of fluffs exceeds a predetermined number is effective and can be applied from the viewpoint of labor saving in production.

There is no measurement data exceeding the fluff threshold value.
In the case of “O”, it is determined that there is no abnormality due to mere instantaneous fluctuation, or if any of the above-mentioned abnormalities occur, after the processing of storing the abnormal data, enter the step of resetting the abnormal flag, and turn off the abnormal flag together with the past. Clear the abnormal storage area for minutes. This completes the abnormal processing of the weight,
Returning to the point B in FIG. 3, the process proceeds to a step of determining the end of the entire weight.
As described above, the abnormal processing unit that requires the abnormal processing including the prompt thread disconnection processing is processed at the highest priority level continuously with the data collection unit as only the simple data comparison processing.

As described above, in this example, the measurement data for a predetermined time before and after the occurrence of the abnormality is stored, and the final determination of the occurrence of the abnormality is made based on the average value. Detection has been realized. In addition, the classification of the abnormality is performed in a single process after collecting the measurement data for a predetermined time, and in other cases, the data is collected only in a process of determining whether or not the current value of the instantaneous value is within the control range. Processing can be performed with a short sampling cycle, high-speed online management has been realized, and thread breakage processing that requires urgent treatment has been realized without any problems. Thus, the present invention realizes an online operation management system of a yarn processing machine that is accurate, highly reliable, and excellent in responsiveness.

On the other hand, the index monitoring unit obtains a quality index based on the measurement data collected and stored in the data collection unit, and in this example, obtains an index CV, which will be described later, which has been confirmed to have a correlation with a visual inspection, and monitors it as shown in FIG. The configuration is as shown in FIG. This index monitoring unit is processed at a lower priority level than the interrupt processing, and is started when the machine starts operating.

Then, a weight number setting step is firstly performed. Here, a weight for first processing the weight number, for example, the first weight of the machine base.
Set on the weight. Next, the process proceeds to a determination step during operation to determine whether or not the machine is operating. If the machine is not operating and stops, the process proceeds to “NO” and the process ends. That is, in the present example, the following index monitoring process is repeatedly executed during the operation, and the process is terminated only when the operation is stopped.

If the vehicle is running, the process proceeds to "YES", and the following index monitoring process is performed. First, an index flag determination step is entered, and it is determined whether or not the index flag of the weight is ON, that is, whether or not collection of index data has been completed. If not completed, the process proceeds to “NO”, enters a weight number raising step, advances the weight number, and proceeds to a determination step of determining the end of all weights.

In this step, it is determined whether or not all the weights have been completed based on the weight number. If all the weights have not been completed, the process proceeds to “NO”, returns to the above-described determination step during operation, and proceeds to the next weight process. On the other hand, in the case of end of all weights,
Proceeding to "YES", the process returns to the above-mentioned weight number setting step, and processing is performed from the first weight. That is, the index monitoring process is sequentially executed for each weight as long as the vehicle is in operation.

By the way, as described above, the index flag is turned ON when the number of index data collected and stored by the data collection unit reaches 500, so that the determination step is "YES", and the following index monitoring processing is performed. Be executed.
That is, the index monitoring process is executed every 500 data collections, that is, at a period of approximately one second.

First, an average calculation step is entered, and the average value of the stored 500 pieces of measurement data for one second is obtained. Next, the process proceeds to a standard deviation calculation step, and a standard deviation value of the measured data is obtained. Then, in the next CV calculation step, an index CV is obtained by the following equation.

[0046]

## EQU1 ## CV = standard deviation value ÷ average value

Next, a CV determination step is entered, and the obtained CV value is compared with a preset CV threshold. And
If this value is equal to or larger than the CV threshold, it is determined as "CV abnormality" and "YE
S ”, enter the CV abnormal data storage step,
The CV abnormality is stored as an abnormality content in the weight-specific abnormality file together with the time of occurrence and the CV value.

After this processing or in the case of “NO” which is less than the CV threshold, immediately enter the CV data storage step,
The CV value and the measurement time, specifically, the processing time are stored in the V file. Next, a step for determining the end of winding is entered.
It is determined whether or not the winding of the processed yarn package of the weight has been completed due to full winding or the like. This determination is made based on a signal from the winder or the like. If the winding is in progress, the process proceeds to “NO”, the index monitoring process of the weight is ended, and the process returns to the weight number raising step described above.

On the other hand, in the case of "YES" indicating that the winding of the processed yarn package has been completed due to full winding or the like, the process proceeds to a winding flag reset step, and the winding flag is reset.
Next, the process enters a package file creation step, and creates a package file in which data necessary for displaying the processed yarn package is collected. In this example, the index C stored in each of the weight-based abnormal file and the weight-based CV file is used.
A package file is created in which the time-series data from the beginning of the V winding, the CV abnormality, the distribution of the time-series occurrence from the beginning of the fluff generation, and the like are aggregated. After this processing,
As in the case of "NO", the process returns to the weight number raising step.

As described above, for the package processed by all the weights, data of CV and fluff necessary for quality control are collected and stored for each package. Then, the management system of this example displays the result on a display unit of the management means in response to a request. The display unit in this example is
It is configured as shown in FIG.

When a display request is input from an input device such as a keyboard of the computer 15, the computer 15 starts up, and first enters a display setting step to set contents to be displayed, for example, a weight, a range of a package, and the like. For this setting, a setting table in a predetermined format is displayed and input to the setting table. In this example, a weight range, a package range, and display contents can be specified. As the display contents, the time series distribution and the number of fluff occurrences of the specified package, CV history, average value, frequency distribution, cumulative frequency distribution, and the like, totaling of all abnormalities, time series distribution, and the like can be designated and displayed. .

Then, when the input is completed, the process enters a data extraction processing step, in which data necessary for the designated display is extracted and processed. That is, the data of the designated weight and package is read from the package file, and if the processing according to the contents, for example, the average value of the CV, the average value for each package is obtained and stored in a predetermined storage area. Then, a display step is entered, and the display is performed on a display device such as a liquid crystal display of the computer 15 in a designated display method, for example, a graph. Next, a display end determination step is entered, and it is determined whether there is a display end request from the input device. If there is a display end request, display end processing is performed in an end processing step, and the display unit ends the processing.

As described above, in this example, the data collection unit which is not allowed to delay the processing processes the highest priority interrupt processing to ensure reliable data collection, and the quality monitoring unit which allows the time delay in the processing is the same. At a lower priority level, the display unit processes only when necessary, and can be sufficiently processed by a computer such as an inexpensive microcomputer.

As described above, the present invention has been described based on an example in which the present invention is applied to an air task run machine. However, it is apparent from the gist that the present invention is not limited to such an embodiment. For example, it is effective in the processing of ply yarn, but can also be applied to the processing of single yarn. The processing method can be applied to not only the air taslan processing but also false twist processing.

[0055]

As described above, the present invention realizes on-line operation management, including quality control, which has been difficult in the past, especially in the processing of yarns, particularly in the processing of twin yarns. It is intended to realize the stable production of the process, the quality control that can guarantee the quality from the start to the full winding of the package in the quality control, the labor saving, and the great contribution to the stable production.

[Brief description of the drawings]

FIG. 1 is an explanatory diagram of a basic configuration of an air task run machine to which the present embodiment is applied.

FIG. 2 is a block diagram of a basic configuration of the operation management system according to the present embodiment.

FIG. 3 is a flowchart of the data collection unit.

FIG. 4 is a flowchart of the abnormality processing unit.

FIG. 5 is a flowchart of the index management unit.

FIG. 6 is a flowchart of the display unit.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 Thread cutter 2 Heating pin 3 Thread heating device 4 Fluid jet processing device 5 Winding machine 6 Processing thread package 7A to 7D Thread feed device 8 Thread guide 9A to 9B Thread feed roller device 11 Thread sensor 12 Scanning circuit 13 A / D Conversion circuit 14 Interface circuit 15 Computer

Claims (10)

[Claims] An operation management system for a yarn processing machine for managing the operation status of a yarn processing machine online, the form of a processed yarn is measured, and a measurement signal of the measured value is converted into digital value measurement data at a predetermined sampling cycle. The A / D conversion is performed, and the measured data for a certain period is sequentially stored, and when the latest value of the measured data is out of a preset management range, the measured data for the certain period is further added from this time. An operation of a yarn processing machine, comprising: a data collection unit that stores measurement data for a predetermined period; and an abnormality processing unit that calculates an average value of all stored measurement data and detects an abnormality based on the average value. Management system. 2. The operation management system for a yarn processing machine according to claim 1, wherein the processed yarn is a combined yarn obtained by combining two or more yarns. 3. An abnormality in which yarn breakage including partial yarn breakage in which a part of yarns to be twinned breaks or / and extra yarns to be twined out are abnormal. 2. The operation management system of the yarn processing machine according to item 2. 4. An abnormality processing unit detects a connection abnormality when the average value exceeds a preset connection threshold value, and detects a thread breakage when the average value is less than a preset thread break threshold value,
The operation management system for a yarn processing machine according to claim 3, wherein a forced thread cutting process is performed. 5. The yarn according to claim 1, wherein the abnormality processing section further comprises a fuzz detecting section for detecting, when the predetermined number of measurement data continuously exceeds a preset fuzz threshold value, as a fuzz. Operation management system for strip processing machines. 6. The operation management system for a yarn processing machine according to claim 1, wherein a form of the yarn is detected by a photoelectric sensor. 7. The photoelectric sensor according to claim 6, wherein the photoelectric sensor comprises two sets of light receiving elements and light emitting elements whose optical axes are orthogonal to each other, and uses a larger output as a sensor output.
Operation management system of the yarn processing machine described. 8. The operation management system for a yarn processing machine according to claim 1, further comprising an index monitoring unit that obtains an index relating to quality from the stored measurement data for a predetermined period, stores the index, and displays the index. 9. A CV (= standard deviation value ÷ average value) obtained by dividing a standard deviation value of measurement data for a predetermined period stored by the index for each predetermined period by an average value thereof, and / or a constant width of the CV. The operation management system for a yarn processing machine according to claim 8, wherein the frequency distribution is a frequency distribution divided in a value range of: 10. The operation management system for a yarn processing machine according to claim 1, wherein the yarn processing machine is an air processing machine or a false twisting machine.