JPH0258092B2 - - Google Patents

Description

Detailed Description of the Invention [Technical field to which the invention pertains] The present invention relates to a plastic molding machine such as an extruder, an injection molding machine, a blow molding machine, etc. that has a melting process of plastic material, and a method for controlling the melting rate of the material melting process, the solid bed This invention relates to a system for automatically diagnosing changes, disappearances, transport and mixing in melt pools and melt zones.

[Prior art and its problems]

Generally, in a plastic molding machine, it is required to uniformly and stably supply melt polymer to the next process, and in particular, in an extruder, a sufficient amount of melt polymer must be ensured.

In order to satisfy these demands, it is essential that the extrusion screw be appropriately designed, but in order to efficiently extrude a variety of melt polymers using a single general-purpose screw, it is necessary to adjust the operating conditions. configuring, monitoring and controlling are essential. Conventionally, such extrusion screw monitoring and control has been performed with reference to the head resin pressure, temperature, screw torque, etc. at the tip of the screw.

On the other hand, when an extruder is roughly divided into a solid transport section, a melting section, and a measuring section, it can be said that most of the performance is determined by the behavior of the melting section. However, in areas far downstream from the head, such as dies, there is a delay in information such as resin pressure and temperature, and deformation occurs due to rounding or combinations, making it difficult to perform appropriate control and cause analysis. It was hot. Attempts have also been made to observe the internal pressure of the screw with an analog recorder, but quantitative analysis has not yet been achieved.

[Problem that the invention seeks to solve]

However, in general, the throughput, stability and uniformity of the material, which define the performance of the extruder, are determined by the conditions of the melting process. Various behavioral analyzes are known during the melting process of plastic materials in such extruders, but since plastic materials are a group of materials that inherently have heterogeneous and unstable characteristics, they are susceptible to disturbance factors. constantly exposed to varying risks.

Possible causes of such material fluctuations include (1) changes in the characteristics of the material itself, (2) fluctuations in operating conditions, and (3) changes in material passages over time. Next, details of the causes of these fluctuations will be explained.

(1) Changes in material properties (average properties and distribution) Apparent specific gravity, thermal properties, surface hardness, friction properties,
compression properties, temperature, moisture absorption, particle shape, molecular weight,
These are changes in crystallinity, blending ratio, etc.

(2) Changes in operating conditions Changes in barrel temperature, screw temperature (cooling), screw rotation speed, feed amount, biting condition, filter clogging, backflow of entrained air, etc.

(3) Changes in material passage over time These are changes in surface deposits, wear, etc.

It is presumed that these causes cause variations in the material during the melting process, and in extreme cases, break-up of the solid bed, starvation phenomenon, unmelted or galled material, etc. occur. Furthermore, it is thought that the cause is often not a single cause but a combination of multiple causes.

Therefore, an object of the present invention is to measure the behavior of the material melting process in a plastic molding machine by measuring the pressure characteristics in the screw groove based on the positional relationship of the flights using a pressure sensor and a position detector, and to obtain the measured waveform.
The pressure distribution waveforms in the screw groove are compared and contrasted with x _i and the reference waveform as y _i , and the degree of deviation between the two waveforms is rms.
An object of the present invention is to provide an automatic diagnosis system for appropriately controlling the material melting process of the molding machine by calculating statistics such as root mean square (root mean square) and similarity r _xy (correlation coefficient).

That is, by comparing the time-series sampling data as the measurement waveform with the time-series reference data as the reference waveform to find the deviation, if the required deviation occurs, it is determined that the plastic material is insufficiently melted. The condition or overmelting condition is diagnosed. Therefore, in such a case, it is necessary to slow down the operation of the screw to restore the molten material to its proper state, or to adjust and control the set temperature of the screw barrel to achieve the proper melted state. control can be realized.

[Means for solving problems]

The automatic diagnosis system for the material melting process in a plastic molding machine according to the present invention is a plastic molding machine configured to extrude and melt a plastic material through a screw, and to extrude, injection mold, or blow mold the molten material. A pressure sensor that detects the pressure in the material melting part and a position sensor that detects the flight position of the screw are provided, and the sampling data obtained from each of these sensors is compared and contrasted with predetermined reference data to determine the correlation. The present invention is characterized in that it includes an arithmetic control unit that calculates the statistical value of and determines whether it is normal or abnormal.

In the above automatic diagnosis system, the pressure sensor may be configured to sample the pressure of the molten material in the solid groove of the screw and the pressure of the molten material in the melt groove in relation to the positions and times of the main flight and the sub-flight. suitable.

Further, the pressure sensor can be constituted by a proximity sensor that generates a predetermined output signal corresponding to the position of the main flight and the position of the sub-flight of the screw in a positional relationship with the pressure sensor with respect to the rotation of the screw.

In the automatic diagnosis system, the sampling data obtained by the pressure sensor and the position sensor is calculated, stored, and graphically displayed together with related data such as the pressure of the molten material at the screw head, the screw speed, and the screw barrel temperature. Can be done.

Furthermore, the correlation between the sampling data and the reference data includes the degree of deviation and similarity of pressure waveform patterns and the time-series stability based on the time-series sampling data. The system can be configured to perform a determination of physical stability.

[Embodiments of the invention]

Next, an embodiment of the automatic diagnosis system for the material melting process in a plastic molding machine according to the present invention will be described in detail with reference to the accompanying drawings.

FIG. 1 is an explanatory diagram showing the structure and system configuration of a plastic extruder which is an embodiment of the system of the present invention. That is, in FIG. 1, reference numeral 10 indicates a screw barrel, and this barrel 1
A barrier type screw 12 is inserted and arranged inside the 0. A T-die 14 serving as an extrusion mold is provided at the head portion of the screw 12. Further, the base of the screw 12 is connected to a drive motor 18 via a reduction gear 16. On the other hand, a heater 20 is attached to the outer circumference of the barrel 10, and a heater 20 is attached to the outer circumference of the barrel 10.
A hopper 22 for charging material is provided on the base side of the hopper 22 . Note that an external cooling fan 24 is appropriately provided for the heater 20. The above configuration is the basic configuration of the extruder.

However, in the present invention, the barrel 10 of the extruder is provided with a first pressure sensor 26 for detecting the pressure inside the barrel 10 and a second pressure sensor 28 for detecting the pressure in the screw head, and further Position sensor 30 for detecting the position of the screw flight with respect to the screw end 12a
will be established. The signals detected by the first pressure sensor 26 and the second pressure sensor 28 are selectively supplied to the A/D converter 38 by the multiplexer 36 via signal processors 32 and 34, respectively, and the CPU 4
Enter 0. Further, the signal detected by the position sensor 30 is also input to the CPU 40 via the signal processor 42 . In this way, the pressure data and position data input to the CPU 40 are stored in the internal memory 44 and compared with reference data stored and held in advance. Note that output devices such as a CRT display 46 and a printer 48 and external memories such as a floppy disk 50 are connected to the CPU 40 as appropriate. Further, a buzzer 54 that issues an abnormality alarm is connected to the CPU 40 via an output interface 52.

By the way, the detailed arrangement of the first pressure sensor 26 and the screw 12 that performs the melt extrusion process of the material is shown in FIGS. 2 and 3. In FIGS. 2 and 3, reference numeral 56 indicates a solid groove of the screw 12, 58 a melt groove, 60 a main flight of the screw 12, and 62 a sub-flight. Note that the second pressure sensor 28 is also attached to the screw barrel 10 in the same manner as described above. On the other hand, the position sensor 30
is provided opposite to the signal generating collar 64 attached to the screw end 12a, as shown in FIG.
It is configured to generate a flight position signal as shown in FIG. 5 in response to the rotational deviation. Therefore,
As the position sensor 30, for example, a proximity switch can be suitably used.

Next, the operation of the automatic diagnosis system of the present invention having the above configuration will be explained.

Since changes and abnormalities in the material melting process, that is, in the material melting section of the extruder, appear as internal pressure waveforms in the barrel, the CPU 40 performs the following calculation processing.

1 Sampling of internal pressure waveform The internal pressure waveform is sampled using a pressure sensor and a position sensor. In this case, the reference waveforms are the pressure at the screw head, the screw speed,
It is preferable to also sample the barrel temperature.

(1) Sampling locations shall be limited to one or multiple locations within the molten area.

(2) Input flight position data at the same time to clarify positional relationships within the Skrill Groove.

(3) Perform time-series sampling as necessary.

2 Storage of internal pressure waveform The data of the internal pressure waveform obtained by the sampling is stored in the internal memory 44 via the CPU 40.
to be memorized. In this case, related data is also stored. Note that the storage operation is configured so that it can be executed at any time by keyboard operation via an input interface to the CPU 40 as appropriate.

3 Setting tolerance limits (1) rms (degree of deviation between measured waveform x _i and reference waveform y _i ) However, the screw groove is expanded in the circumferential direction, and the distance from the reference position is expressed as i (i = 1...
n).

(2) r _xy (Similarity between measured waveform x _i and reference waveform y _i : correlation coefficient) r _xy = σ _xy /σ _x σ _y ...(2) However, σ _xy =1/n _o 〓 ⁱ⁼¹ (x _i −) (y _i −) (4) Note that the necessary and sufficient condition for both waveforms to completely match is rms=0. In this case, necessarily r _xy
= 1.0. However, r _xy = 1.0 is only a necessary condition for both waveforms to perfectly match.

4. Graphical display of internal pressure waveform Based on the sampling data, the internal pressure waveform is graphically displayed on, for example, a CRT display (see FIG. 6).

5 Diagnosis by comparison and analysis of internal pressure waveforms (1) Compare the measured waveform with the normal waveform and identify normal or abnormal (see Figure 7).

(2) In the case of an abnormality, first determine whether it is stable over time.

(3) Next, sequentially compare various abnormal waveforms and select the waveform with the highest similarity.

(4) If there are no highly similar patterns, record them as is.

6 Diagnostic processing (1) Alarm Message output (display, record), buzzer, etc.

(2) Control Emergency measures such as slowing down, and other stabilization controls (for example, controlling the set temperature of the screw barrel).

A flowchart of a program for performing the above arithmetic processing is shown in FIG.

〔Effect of the invention〕

As is clear from the embodiments described above, according to the present invention, in a plastic molding machine having a screw including a melting process, the internal pressure of the molten material is detected in relation to the flight position of the screw, and as a result, The internal pressure waveform based on the obtained sampling data is compared with a reference waveform stored in advance, and statistics such as the degree of deviation rms and similarity r _xy are calculated, and based on this, a diagnosis of normality or abnormality is automatically performed. Therefore, generation of an alarm and switching to appropriate control can be easily and reliably achieved.

Therefore, according to the present invention, abnormal phenomena in the material melting process can be diagnosed and predicted, and based on this, an alarm can be issued and a transition to appropriate control can be reliably performed. It is possible to improve the productivity and stability of plastic films and sheets, etc., as well as to achieve higher precision.

Although the preferred embodiments of the present invention have been described above, it goes without saying that various design changes can be made without departing from the spirit of the present invention.

[Brief explanation of drawings]

FIG. 1 is an explanatory diagram showing the main parts of an extruder and the system configuration as an embodiment of the automatic diagnosis system for the material melting process in a plastic molding machine according to the present invention, and FIG. 2 shows the pressure sensor shown in FIG. 1. FIG. 3 is an enlarged longitudinal sectional view of the main part showing the mounting state of the pressure sensor shown in FIG. 2;
Fig. 4 is an enlarged side view of the main parts showing the mounting state of the position sensor shown in Fig. 1, Fig. 5 is an output characteristic diagram of the pressure sensor shown in Fig. 2, and Fig. 6 is a diagram showing the position sensor sampled by the system of the present invention. FIG. 7 is an explanatory diagram showing a comparative display example of internal pressure waveform reference data and measured data; FIG. 8 is a flowchart showing an example of a program of the system of the present invention. 10...Skuriyu Barrel, 12...Skuriyu,
14...T-die, 16...Reducer, 18...Drive motor, 20...Heater, 22...Hopper, 24
... Cooling fan, 26 ... First pressure sensor, 2
8...Second pressure sensor, 30...Position sensor, 3
2, 34... Signal processor, 36... Multiplexer, 38... A/D converter, 40... CPU, 4
2...Signal processor, 44...Internal memory, 46...
...CRT display, 48...Printer, 50
...Floppy disk, 52...Output interface, 54...Buzzer, 56...Solid groove, 5
8... Melt groove, 60... Main flight, 62...
Sub-flight, 64... Collar for signal generation.

Claims (1)

[Scope of Claims] 1. In a plastic molding machine configured to extrude and melt a plastic material through a screw and extrusion mold, injection mold or blow mold the molten material, a pressure for detecting the pressure at the material melting part of the screw. A sensor and a position sensor for detecting the flight position of the screw are provided, and the sampling data obtained from each of these sensors is compared and contrasted with predetermined reference data to calculate the correlation statistics and determine whether it is normal or not. An automatic diagnosis system for the material melting process in a plastic molding machine, characterized by being provided with a calculation control section for determining abnormalities. 2. In the automatic diagnosis system according to claim 1, the pressure sensor compares the pressure of the molten material in the solid groove of the screw and the pressure of the molten material in the melt groove with the positions and times of the main flight and the sub-flight. An automatic diagnosis system for material melting process in a plastic molding machine configured to perform sampling in relation to each other. 3. In the automatic diagnosis system according to claim 1, the pressure sensor outputs a predetermined output signal corresponding to the position of the main flight and the position of the sub-flight of the screw in relation to the rotation of the screw with respect to the pressure sensor. This is an automatic diagnosis system for the material melting process in a plastic molding machine, which consists of a proximity sensor. 4. In the automatic diagnosis system according to any one of claims 1 to 3, the sampling data obtained by the pressure sensor and the position sensor is used to calculate the pressure of the molten material at the screw head, the screw speed, the screw barrel temperature, etc. An automatic diagnosis system for material melting process in a plastic molding machine configured to calculate, store and graphically display related data. 5. In the automatic diagnosis system according to any one of claims 1 to 4, the correlation between the sampling data and the reference data is based on the degree of deviation and similarity of the pressure waveform pattern and the time-series sampling data. and temporal stability based on
An automatic diagnosis system for the material melting process in a plastic molding machine, which is configured to identify whether it is normal or abnormal and to determine chronological stability during abnormal times.