A method and apparatus for casting thin strip including assembling a pair of counter-rotating casting rolls forming a gap between the casting surfaces of the rolls at a nip between the rolls through which metal strip can be casted; assembling side dams adjacent end portions of the rolls to permit a casting pool of molten metal to be formed on the casting surfaces; counter-rotating the rolls such that the casting surfaces each travel inwardly toward the nip to form metal shells on the surfaces of the rolls and deliver a cast strip downwardly from the gap between the rolls with a mushy internal portion; and providing a drive mechanism to oscillate the gap amplitude between the casting rolls between ±5 and ±50 microns at a frequency between 1 and 7 hertz to vary thickness of the mushy in the cast strip and reduce chatter during casting.

The present disclosure relates to a casting apparatus and a casting method. The casting method includes injecting a molten material into a mold by using a nozzle, forming a static magnetic field applied region and a non-static magnetic field applied region in a width direction of the mold and controlling a flow of the molten material in a longitudinal direction of the mold, and drawing a cast slab. Through this, as the flow of the molten material accommodated in a container is locally controlled, cleanliness of the molten material may be secured, and a quality of a product may be improved.

A prediction method for mold breakout based on feature vectors and hierarchical clustering is disclosed, which comprises: respectively extracting temperature feature vectors of historical data under sticking breakout and normal conditions and on-line actually measured data to establish a feature vector sample set; performing normalization and hierarchical clustering on the sample set; and checking and judging whether the feature vectors extracted on line belong to a breakout cluster, and then identifying and predicting mold breakout. The method avoids the steps of tedious adjustment and modification of alarm threshold and other parameters, overcomes the artificial dependence of the previous breakout prediction method, has good robustness and mobility; and through temperature feature extraction, achieves accurate identification of sticking breakout temperature patterns, avoids missing alarms and significantly reduces the number of times of false alarms, and greatly reduces the data calculation amount and calculation time, guaranteeing the timeliness of on-line prediction.

A prediction method for mold breakout based on feature vectors and hierarchical clustering is disclosed, which comprises: respectively extracting temperature feature vectors of historical data under sticking breakout and normal conditions and on-line actually measured data to establish a feature vector sample set; performing normalization and hierarchical clustering on the sample set; and checking and judging whether the feature vectors extracted on line belong to a breakout cluster, and then identifying and predicting mold breakout. The method avoids the steps of tedious adjustment and modification of alarm threshold and other parameters, overcomes the artificial dependence of the previous breakout prediction method, has good robustness and mobility; and through temperature feature extraction, achieves accurate identification of sticking breakout temperature patterns, avoids missing alarms and significantly reduces the number of times of false alarms, and greatly reduces the data calculation amount and calculation time, guaranteeing the timeliness of on-line prediction.

A method detects a level of a melt contained by an oscillating mold. The method includes a) sensing radiation interacted with the melt and generating from the sensed radiation radiation signals, such that the generated radiation signals are varied by the mold oscillation, b) determining a radiation signal variation of the generated radiation signals, c) determining an oscillation deflection variation of the oscillating mold, and d) determining from the determined oscillation deflection variation and the determined radiation signal variation, the level of the melt.

A method detects a level of a melt contained by an oscillating mold. The method includes a) sensing radiation interacted with the melt and generating from the sensed radiation radiation signals, such that the generated radiation signals are varied by the mold oscillation, b) determining a radiation signal variation of the generated radiation signals, c) determining an oscillation deflection variation of the oscillating mold, and d) determining from the determined oscillation deflection variation and the determined radiation signal variation, the level of the melt.

A method and apparatus for casting thin strip including assembling a pair of counter-rotating casting rolls forming a gap between the casting surfaces of the rolls at a nip between the rolls through which metal strip can be cast; assembling side dams adjacent end portions of the rolls to permit a casting pool of molten metal to be formed on the casting surfaces; counter-rotating the rolls such that the casting surfaces each travel inwardly toward the nip to form metal shells on the surfaces of the rolls and deliver a cast strip downwardly from the gap between the rolls with a mushy internal portion; and providing a drive mechanism to oscillate the gap amplitude between the casting rolls between 5 and 50 microns at a frequency between 1 and 7 hertz to vary thickness of the mushy internal portion in the cast strip and reduce chatter during casting.

A monitoring device (6) records variables that are characteristic of operating parameters of a continuous casting mold (1) for casting a metal strand (2). The monitoring device (6) records at least some of the characteristic variables by independently performing measurements during the casting of the metal strand (2). The monitoring device (6) forms groups (G1, G2) of operating parameters and independently tests whether the operating parameters of the respective group (G1, G2) satisfy a respective predetermined stability criterion. The monitoring device (6) accepts the operating parameters into a database (12). The monitoring device (6) determines those data records (11) contained in the database (12) that coincide in their input variables with the basic operating parameters and determines admissible operating parameter ranges for supplementary operating parameters. The monitoring device (6) independently tests whether the supplementary operating parameters lie within the admissible operating parameter ranges.

A primary object of this invention is to provide a method for operating a continuous casting machine with which a mold can oscillate with a predetermined oscillation waveform since the start of operation of an oscillator. This invention is a method for operating a continuous casting machine, the method comprising: withdrawing a slab from a mold while vertically oscillating the mold with an oscillation waveform represented by the following formula (1) by selecting a value of according to a value of b so that the following formula (1) satisfies r(0)=0:
r(t)=(S/2){sin(t+)+b cos 2(t+)+b}(1)
where r(t): displacement of the mold (mm), S: vibration stroke of the mold S (mm), : angular velocity (=2f) (rad/s), f: oscillation frequency of the mold (Hz), t: time(s), : initial phase (), and b: non-sine coefficient (0<b0.25).

A control device (1) for an oscillating table (6), comprising: a closed and pressurized hydraulic circuit (20), a hydraulic actuator (21) connected to said hydraulic circuit (20) and adapted to be connected to the mobile part of the oscillating table (6) to adjust the position thereof, in which said hydraulic actuator (21) is a double-acting cylinder having a first chamber (21a) and a second chamber (21b) delimited from each other by a sliding piston (22) rigidly connected to a first rod (31a) which is rigidly restrainable to said mobile part, in which said hydraulic circuit (20) comprises at least one reversible hydraulic pump (9) directly connected to at least one of said first chamber (21a) and second chamber (21b).