JPS61200453A - Method for detecting casting flaw in continuous casting - Google Patents

Abstract

PURPOSE:To accurately detect a casting flaw, by performing the Fourier transformation of a sequential time temp. detection value at the time of the generation of a past casting flaw and setting casting flaw generating threshold coefficient from the correlation between each term coefficient and a casting flaw generation state. CONSTITUTION:A temp. detection terminal is embedded in a continuous casting mold and a temp. transition pattern is obtained from the detection terminal. A sequential time temp. detection value at the time of the generation of a past casting flaw is subjected to Fourier transformation and casting flaw generation threshold coefficient is set from the correlation between each term coefficient and a casting flaw generation state and the temp. detection value actually measured during continuous casting is subsequently subjected to Fourier transformation to calculate each term coefficient and it is judged that abnormality is generated when each term coefficient exceeds the casting flaw generation threshold coefficient. By this method, a casting flaw can be detected accurately and certainly and the erroneous judgment of the detection of the generation of a casting flaw can be perfectly eliminated.

Description

DETAILED DESCRIPTION OF THE INVENTION [Field of Industrial Application] The present invention relates to a method for detecting casting defects in continuous casting.

[Conventional technology]

In the well-known process of continuous casting, molten steel is poured into a mold,
A slab is manufactured by forming a slab into a predetermined cross section and then continuously pulling it out from below a mold. The initial solidification state of the molten steel in the mold has an important influence on the continuous casting operation.

For example, is there a phenomenon in which the solidified shell generated during the initial solidification process in the mold sticks to the inner surface of the mold and becomes trapped, or inclusions are rolled into the solidified shell? When this happens, the solidified shell breaks just below the mold, causing molten steel to flow out (hereinafter referred to as BO). Furthermore, if powder used as a lubricant flows unevenly into the mold, various defects will occur on the surface of the solidified shell. [σ] Casting defects (such as BO caused by the above-mentioned solidified shell sticking to the inner surface of the mold or the phenomenon in which inclusions are rolled into it, and surface defects caused by uneven inflow of powder, etc.) When a casting defect (hereinafter collectively referred to as a casting defect) occurs, for example, when the above-mentioned BO occurs, it takes a long time to recover from the BO, which significantly reduces productivity.

On the other hand, when surface defects occur, the manufactured slab requires maintenance.

Particularly in recent years, the speed of continuous casting and the direct connection of continuous casting and rolling processes (hereinafter referred to as direct rolling) have been extremely advanced, but the occurrence of casting defects is a major problem in implementing these processes. It was a hindrance.

For this reason, many conventional techniques have been proposed for predicting or detecting casting defects at an early stage. For example, in JP-A-57-152356, a thermocouple is buried in the wall of the mold, and when the temperature detected by the thermocouple rises once above the average temperature in the normal state and then falls, it is predicted as tBO. In addition, Japanese Patent Publication No. 55-84259 discloses a technology that detects temperatures on each opposing surface of the mold σ, compares them with each other, and uses the temperature difference as an index to detect a prior phenomenon of BO generation. is disclosed. Furthermore, JP-A-57-11
Publication No. 5960 discloses a technique for detecting a phenomenon in which large inclusions are rolled into the surface of a solidified shell based on a sudden drop in temperature from the average temperature detected by a thermocouple embedded in the mold. JP-A-57-115962 discloses that an abnormality in the solidified shell is detected by determining the time change from the detected temperature and comparing the time change rate with a predetermined range QJ value. Each technology is ready to be disclosed.

[Problem that the invention seeks to solve]

All of the methods for detecting casting defects based on the prior art described above are based on the absolute value t of
-t: q; used as is and 1 in the casting direction
The absolute value of the temperature detected at a point can be compared with the above-mentioned average temperature in a steady state or the temperature of the opposing wall surface, or the rate of increase or decrease can be determined within a predetermined target range. It was to be compared with.

However, the amount of rise or fall of the rate when a casting defect occurs, and the amount of change thereof per unit time, vary widely depending on the harvesting of the casting defect and the situation at that time, and in extreme cases, even the same casting defect can cause It is normal for the temperature change pattern Fi to vary widely. Because of this QJ, the degree change pattern Q) % t M when a casting defect occurs is complicated, and it could not be expected to detect casting defects with high accuracy using only the conventional method. For example, a change in temperature σ within the mold occurs not only when the above-mentioned casting defects occur, but also when there is a sudden change in the casting speed or the level of the mold. Figure 13: Changes in casting speed and corresponding changes in temperature? FIG. FIG. 13(a) shows a case where the casting speed suddenly decreases (7c), and FIG. 13(b) shows a case where the casting speed suddenly increases. When a casting defect is recognized using the conventional method (rr) judgment criteria using the absolute value of the temperature shown in FIG. Wrong +11 cut,
This resulted in two false alarms.

When the occurrence of a casting defect is detected, operational action is taken to temporarily stop the Vi casting in actual operation or to extremely reduce the casting speed rIjL. For this reason, when false alarms occur frequently,
For example, quality defects such as step pouring may occur in the slab, it may cause a hindrance to the production of high-temperature slabs, which is important for direct rolling, or it may interfere with matching with subsequent processes. A problem occurs. Therefore, it was difficult to apply the conventional method to actual operation.

The present invention solves all the problems of the prior art, accurately detects casting defects, and prevents erroneous judgment when detecting casting defects.
By doing so, it is possible to prevent the above-mentioned quality defects in slabs, dropping of slabs, and anomassing with subsequent processes.

[Means to solve the problem]

The means of the present invention for solving the above-mentioned problems is a method of embedding a temperature detection hole in the continuous casting mold and detecting casting defects from a temperature transition pattern obtained from the detection end. Time-series temperature detection value at the time of occurrence?
Fourier transform is performed, and a casting defect occurrence threshold coefficient is set from the correlation between each term coefficient and the state of occurrence of casting defects during continuous casting.Fourier transform is then performed to determine each term coefficient. This is a method for detecting casting defects in continuous casting, characterized in that it is determined that an abnormality has occurred when each term coefficient falls within a casting defect occurrence threshold coefficient.

[Effect]

One of the casting defects mentioned above is the restrictive BO, which occurs when a part of the solidified shell sticks to the mold wall surface and breaks in the trap, and the broken part becomes BO when it is pulled out from the mold. . First, a method for detecting this restrictive BOi will be explained.

Is the figure 8g2 an example of the arrangement of temperature detection terminals 2 embedded in the mold l? In the figure, a plurality of temperature detecting ends 2 are arranged at appropriate intervals in the casting direction indicated by arrow a and in the width direction indicated by arrow 2. FIG. 3 ii is a sectional view taken along line XX in FIG. 2; In the same figure, 3 is molten steel and 4 is slab 4.
0 solidified shell.

If a part of the solidified shell 4 sticks to the mold l for some reason,
L) When drawing out the slab 40, solidification is performed immediately below the fixed part 57.
4 breaks and molten steel 3 flows out. Therefore, when the broken part passes, the temperature detection value detected by the temperature detection end 2 rises once as shown in FIG. However, the thickness of the sickle through which the broken part has passed increases because the fixed solidified shell 4 does not move.
It is known that the temperature decreases. However, the above-mentioned temperature change occurs when the casting speed suddenly increases or when the molten metal level drops suddenly, similar to when the solidified shell 4 breaks. The present inventors conducted various investigations and studies on the temperature transition pattern when BO actually occurs, and in order to obtain a pattern that appears only due to BO without being affected by the changing factors of operating conditions σ, the temperature detection end 2 We also attempted mathematical and statistical analysis of the detected temperature values. As a result, each term coefficient obtained by Fourier transforming one time-series temperature detection value is a constraint BO
It was found that the G41 breast pattern was closely related to the occurrence situation.

Next, a method of obtaining coefficients of each term by Fourier transforming one time-series temperature detection value will be explained.

For example, set the predetermined value 7 at the temperature detection terminal 2 in FIG.
4k = 0.1,2. -・----, n -1),
Rimari TCO side - T(n - 13 up to n time series temperature detection values T(k layer; if there is, as an example of Fourier transform for T(k), the sin and cos expansion of ° is as follows (1) Expressed by the formula.

((2π/n)”j) 14(Ako/2)-cos
fj (1)T(j); T(k
)', 7-lier series Ao: Fourier coefficient Ak: f Bk: # Ako; z k ; integer ko: ' (ko=n/23 n ; integer (number of data) j: I π ; pi If the cos coefficient 2 A (j) and the gin coefficient t-s (j) of the Fourier coefficient obtained in the above formula (1) are given, A
(j) and B U) are expressed by the following formula 421, (31).

n; integer (number of data) However, [1≦j≦(n/2) −11 n; Integer (number of data) ml.

T(E): Temperature detection value In the present invention, the coefficients of each term obtained by Fourier transform are Aω and B(
j) say. In this example, the Fourier coefficient is sin
, cos coefficients are used, but for example, real part coefficients, imaginary part coefficients, etc. may be used.

Next, when a restrictive BO actually occurs, the heating detection end 2a,
2b, the time-series temperature detected values are Fourier transformed, and the coefficients of each term and the constraint BO obtained by L are obtained.
We investigated all the correlations with the results and explained the example.

It is expressed as follows. In FIG. 5, 6 and 61 are time-series temperature detection values obtained from the temperature detection terminal 2a (61 and 6
Time series with a set time delay @degree detection value)? , 7 is the time-series temperature detection value obtained from the temperature detection terminal 2b? 8 and 81V'i are the regions used for the Fourier transform of the time series @ temperature detection values 6 and 61, and 9 is the region used for the Fourier transform of the time series temperature detection values 7? In this example, the Fourier transform was performed using eight time-series temperature detection values.

Since the number of data used for Fourier transform is 8,
There are 5 cos coefficients A(j) in the above formula (2), (3)
The obtained Ao in the case of j=o is Aa= (2/n). It is expressed as r (ho). In other words, Ao is related to the average value of the absolute values of the temperature detection values, and is not a parameter necessary for recognizing the time-series change in temperature change q, so Ao is excluded in this example. Therefore, each term coefficient obtained in the example of diagram @5 has 4 cos coefficients A(j), si
There are three n coefficients B(j).

FIG. 1 is a diagram showing the results of Fourier transforming the time-series temperature detection values when restrictive BO occurred in the past based on the method described above, and determining the coefficient r of each term.

FIG. 1(a) shows the area 8, and FIG. 1(b) shows the area 9.
, FIG. 1(c) shows the coefficients of each term obtained by Fourier transforming each of the regions 81), and the horizontal axis shows each term (A
(j)=At-A4, BU)=Bs-Bs) is expressed with each term coefficient as an index on the vertical axis. As is clear from FIG. 1, when a restrictive BO occurs, each term coefficient #1 has a constant variation and -no, and each term coefficient varies within a range. Furthermore, it was also confirmed that the temperature sensing end showed a characteristic e-turn depending on the buried position of the shoe and the Fourier transform region.

Therefore, it is possible to set the upper and lower limits of each term by performing Fourier transform on the time-series temperature detection values at the time when f) Restriction 80 occurred in advance and finding the range of dispersion of each term coefficient. In the present invention, the coefficient within the range of upper and lower limit values is defined and used as the casting defect occurrence coefficient. In addition, it has become possible to uniquely detect complex @degree turf when a casting defect occurs.

Once the casting defect occurrence coefficient is set, all the coefficients for each term during actual continuous casting are obtained by Fourier transform of the actually measured temperature detection value, and then the actual temperature detection value is calculated. Compare with the casting defect occurrence coefficient. Based on this comparison, if the coefficients of each term during continuous casting are all within the casting defect generation threshold coefficient, it is determined that there is a casting abnormality because it means that there is an extremely high possibility that a restrictive BO will occur. be able to.

Note that the comparison is made in the Fourier transform region of the time-series temperature detection values obtained at any one of the temperature detection terminals 2, for example, region 8,
Alternatively, by comparing the casting defect generation coefficient and each term coefficient based on the temperature detection value of the temperature detection end 2a in the region 81, the characteristic characteristics according to the buried position of the temperature detection end q and the Fourier transform region can be determined. Casting abnormality from showing the value of? It is possible to judge.

In addition, as shown in the example of Fig. 2, a plurality of two or more temperature detection terminals 2 consecutive in the casting direction are buried, and a casting defect occurrence threshold coefficient is set at each temperature detection terminal embedding position. The coefficients of each term obtained by Fourier transforming the temperature detection value from the temperature detection end 2 are all within the casting defect occurrence threshold coefficient, and when this occurs with a predetermined time difference, it is determined to be abnormal. Alternatively, even with the same temperature detection end 2 as shown in the example of FIG. 5, the Fourier transform region is provided with a set time delay, and each term coefficient is within the casting defect occurrence threshold coefficient as described above. And H: If you create an I# method that determines that an abnormality occurs when there is a fixed time difference.

It is possible to extremely increase the degree of detection of the occurrence of casting defects.

The area in which the time-series temperature detection values are Fourier transformed, the number of temperature detection values, etc. are determined by the type of casting defect and the frequency of occurrence.

It may be set as appropriate depending on various other operating conditions. For example, the determination may be made by providing a continuous range of set time delays and constantly performing Fourier transform calculations from the temperature detection values that change from time to time. Also, it is a trap to reduce the calculation load when performing constant calculations.

The point in time when the temperature detection value starts to rise or fall from the normal average temperature is detected using simple logic such as conventional deviation detection, and the above region is set as a temperature rise or fall 9J detection trigger to perform Fourier transform calculation. It is also possible to do so.

The buried position of the temperature detection end 2 is 2% below the molten steel level 10L in the mold, which is more than 100L below the molten steel level 10, because it is possible to accurately detect the mold temperature without being affected by changes in the molten steel level. preferable. Also, when burying multiple pieces in the casting direction, the vertical interval of 7 is 50cm.
This separation is effective in accurately understanding the movement of the solidified shell fracture location.

By the way, the above description has been about the restraint 9BO, but the present inventors have investigated f) the rolling-in property in which large inclusions are rolled into the solidified shell 4 in the mold, and when the rolled-in part 7 is pulled out from the mold, it becomes BO. As for BO, the correlation between its occurrence and each term coefficient was investigated in the same way as for the above-mentioned restrictive BO.

A typical temperature change when entrainment BO occurs is shown in FIG. Therefore, in the same manner as for the above-mentioned restrictive BO, the time-series temperature detection values when the engraved BO occurred in the past were subjected to Fourier transformation, and the coefficients of each term were determined, as well as the casting defect generation threshold coefficient. FIG. 7 shows an example of the results, and it was confirmed that there is a close relationship between the two, similar to the restrictive BO.

Next, Figure 8 is a diagram showing the coefficients of each term obtained by Fourier transforming the time-series temperature detection values at the time of occurrence of vertical cracks on the surface due to uneven inflow of powder, and Figure 9 is a diagram showing representative warping. FIG. In addition, Figure 10 is a diagram showing the coefficients of each term obtained by Fourier transforming the time series @ degree detection values when hot water wrinkles occur due to uneven inflow of fleas, and Figure 11 is a representative diagram. FIG. 3 is a diagram showing typical temperature change patterns. As can be seen from FIG. 8 and the @lO diagram, each term coefficient Vi obtained by Fourier transformation is the constraint BO.

Similar to the embossed BO, it also has a close correlation with vertical cracks and surface defects of Yujigin.

Therefore, a casting defect occurrence threshold coefficient is determined and set in advance for each type of casting defect, and each term coefficient t is obtained by Fourier transforming the time-series temperature detection values actually measured during continuous casting.
-6 By making a comparison with the casting defect occurrence threshold coefficient described above, it is also possible to detect the occurrence of seven σJ stocks in addition to the occurrence of casting defects. or.

Upper and lower limits of the casting defect occurrence threshold coefficient On the other hand, it is also possible to quantify with high precision the upper and lower limits of the temperature change pattern when a casting defect occurs, and it is possible to actually measure the upper and lower limits of this temperature change pattern. Does abnormality also occur by determining whether or not seven turns of temperature change occur? can be detected.

FIG. 12 is a block diagram showing an example of a specific method for determining the occurrence of an abnormality based on the present invention. The temperature detection values of the temperature detection ends 2a to 2c embedded in the mold 1 are input to the casting abnormality occurrence confirmation section 11 and each term coefficient calculation section 13, respectively.

When the occurrence of casting defects such as BO or surface defects is actually confirmed, a command is issued to the casting abnormality occurrence confirmation section 11 via the defect confirmation command device 110t, and the time-series temperature detection values of each temperature detection terminal 2 at the time of 7 are sent. is input to the casting defect occurrence threshold coefficient setting section 12. The casting defect occurrence threshold coefficient setting unit 12 Fourier transforms the time-series temperature detection values for each casting defect that has occurred in the past as described above, calculates coefficients for each term, and sets the casting defect occurrence threshold coefficient.

On the other hand, the temperature detection value actually measured during continuous casting by the temperature detection end 2 is input to each term coefficient calculation unit 13, and each term coefficient calculation unit 1
3, the coefficients of each term are calculated from time to time, and the results are input to the comparison section 14.

The comparison unit 14 compares the casting defect occurrence threshold coefficient inputted from the casting defect occurrence threshold coefficient setting unit 12t with each term coefficient during continuous casting inputted from the each term coefficient calculation unit 13, and calculates the series fi,
During casting, when each term coefficient satisfies the casting defect occurrence threshold coefficient and falls within the casting defect occurrence threshold coefficient, an abnormality occurrence command is issued to the command unit 15.

Therefore, the operator can confirm the occurrence of machining defects and seqJ rice harvesting based on the commands issued by the command unit 15, and immediately take appropriate operational action. You can take it. Note that it is also possible to perform sequence control in which various operational actions are automatically executed based on commands from the command unit 15.

〔Example〕

The size of the slab is 250mm thick x 1000mm wide.
- The invention was implemented during continuous casting of killed steel. Mold 1 and Temperature Sensing End 2 in this Example] The embedding position was a hole shown in FIG. 14, and a thermocouple was embedded as the temperature sensing end at a depth of 15 cm in the rough inner surface of the mold.

During casting at a casting speed of 1.6 m/min, did the temperature detection values actually measured at the temperature detection terminals 2a and 2b embedded in the long side of the mold in row A change as shown in Fig. 15? All the coefficients of each term fell within the preset casting defect generation threshold coefficient during restrictive BO. Therefore, it was determined that the abnormality was caused by restrictive BO, and the casting speed IJj was lowered to 0.2 m/min, and this state was maintained for 230 seconds, thereby completely preventing the occurrence of BO.

〔Effect of the invention〕

The present invention Q) is a method that allows casting defects to be detected accurately and reliably. As a result, it is possible to completely eliminate the misjudgment of detection of casting defects that occurred frequently in the past, and it becomes possible to perform continuous casting operations that match the schedule of high-temperature casting production and post-processing.

Also, the manufactured slab has excellent surface defects such as step pouring and no surface defects.

[Brief explanation of drawings]

FIG. 1 is a diagram showing an example of the results of determining the coefficient of occurrence of casting defects when a restrictive BOO is produced based on the present invention, and FIG. 2 is a perspective view showing an example of a mold used for carrying out the present invention. Figure 3ii is a sectional view taken along the line X-X in Figure 2, Figure 4 is a diagram showing temperature changes during the formation of restrictive BOO, and Figure 5 is a graph showing the time series of temperature detection values based on the present invention. Figure 6 is a diagram showing the area to be converted into IJ process. Figure 6 is a diagram showing a typical snacking pattern when BO is generated due to intrusion. Figure 7 is a diagram showing the area where casting defects are generated when BOO is generated based on the present invention. The figure which shows the result +77- example calculated for a coefficient. Fig. 8 is a diagram showing an example of no σ as a result of determining the casting defect occurrence coefficient when a vertical crack occurs based on the present invention, and Fig. 9 is a diagram showing a typical temperature change pattern when a vertical crack occurs. FIG. 10 is a diagram showing an example of the results of determining the casting defect occurrence coefficient when wrinkling occurs based on the present invention. FIG. 11 is a diagram showing a typical temperature change pattern at the time of occurrence of hot water, and FIG. 12 is a block diagram showing an example of a specific method for determining the occurrence of an abnormality based on the present invention. 131/ is a diagram showing the relationship between general casting speed changes and mold temperature changes (1); Figures 14 to 16 show embodiments of the present invention.
Figure 4 is a perspective view of the mold, Figure 15 is a diagram showing the temperature change pattern, Figure 6 Fi is the time-series temperature detection value in Figure 15, ft is Fourier transformed, and is the coefficient of each term determined? FIG. l: mold, 2, 2 II to 2 c: temperature detection end,
3; Molten steel, 4; Solidified shell, 40: Slab, 5; Fixed part, 6.
61: Time-series temperature detection values obtained from the temperature detection end 2a,
7; @time series @degree detection value obtained from degree detection end 2b, 8
: Time series temperature detection value 6 q) Region used for Fourier transformation, 81: Region used for Fourier transformation of time series temperature detection value 61, 9: Time series temperature detection value 7 fy Region used for Fourier transformation, 10; Molten steel level, 11: Casting abnormality occurrence confirmation section, 110; Defect 5M command device, 12: Casting defect occurrence coefficient setting section, 13: Each term coefficient calculation section, 14: Comparison section. 15; Directive Department Agent, Patent Attorney Masamitsu Akizawa, and 2 others b - Yu Haku Rin Station Sagi - Yug Kotsuru Resentment Heise Shou Goshu 1? FA Minwari N@, vIR visit〈 (0> I16 (b) Fig.

Claims (1)

[Claims] (1) In a method of embedding a temperature detection end in a continuous casting mold and detecting casting defects from the temperature transition pattern obtained from the detection end, the time-series temperature detection values at the time of past casting defects are Fourier transformed, A casting defect occurrence threshold coefficient is set from the correlation between each term coefficient and the casting defect occurrence situation, and then the temperature detection value actually measured during continuous casting is Fourier transformed to obtain each term coefficient. A method for detecting casting defects in continuous casting, characterized in that it is determined that an abnormality has occurred when the value falls within the casting defect occurrence threshold coefficient.