JPH059516A - Method for controlling position of classifying device - Google Patents

Abstract

PURPOSE:To stab].y classify grain size and wt. ratio by calculating dropping locus of raw material from a conveyor and executing feedforward control to position of classifying device. CONSTITUTION:At the time of controlling the position of classifying device for classifying the raw material. dropped from the conveyor for shifting the raw material by separating this in each grain size as layer state, the dropping locus of raw material is calculated with the raw material. layer thickness dropped from the conveyor and conveyor speed, etc., and the position of classifying device is set so as to regulate with the feedforward control. By this method, regardless of variation,$7,the conveyor speed for conveyor and raw material layer thickness, the stable classifying positional control can be executed.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a position control method for a classification device.

[0002]

2. Description of the Related Art Generally, as a method for improving the gas flow distribution in the furnace by the distribution of the contents of the furnace interior of the blast furnace, the charging method is classified according to the particle size and the raw materials of different particle sizes are separately deposited. There is. As a method of classifying the charged material according to the particle size, there are a method of classifying with a screen and then classifying, and a method of classifying a raw material falling from a conveyor with a raw material particle size classifier.

However, although the raw material classification method using a screen has a good particle size classification property, it is impossible to control the weight of the classified large lumps and small lumps, and the classification particle size can be adjusted only by exchanging the sieve mesh. However, there was a problem that it took a lot of time to change the particle size and the running cost increased. for that reason,
Conventionally, there has been used a method of classifying a raw material falling from a conveyor having no such a defect by a raw material particle size classifying device.

Examples of the raw material classification method using such a conveyor include those disclosed in Japanese Patent Application Laid-Open Nos. 2-213405 and 2-214580.
In such a raw material classification method, when the raw material 102 is charged into the furnace top hopper of the blast furnace according to the particle size, segregation of the raw material 102 generated in the conveying process by the conveyor 101 is used as shown in FIG. Raw material particle size classifier 10
Two or more raw materials 103, 10 having different particle sizes depending on 0
It is classified into 4.

That is, the raw material conveyed by the conveyor 101 is classified by utilizing the property that the smaller the particle size, the lower the material, and the larger the particle size, the upper the material is divided. Further, the conveyor 101 and the raw material particle size classification device 10
Large or small ores of different particle sizes classified by 0 are stored in respective storage tanks located below the raw material particle size classification device 100.

On the other hand, in this raw material classification method, in order to secure the stock amounts of large and small ores in each storage tank,
A control method is used in which the weight ratio of large or small ores in each storage tank is measured with each beltweigher and the raw material particle size classifier is fixed at a position where the weight ratio can be used for classification. In this control method, for example, when the fixed position of the raw material particle size classifier is defined by referring to the memory table of the microcomputer regarding the relationship between the position of the classifier and the weight ratio of the large and small ores in each storage tank. And the actual weight ratio
There is a case where the fixed position of the raw material particle size classifier is specified by referring to the table data after correcting the data in the table.

[0007]

However, in this type of control method, when the layer thickness of the raw material 102 on the conveyor 101 in FIG. 4 changes irregularly, as shown in FIG. Since the classification point b of the classifying device is fixed to the back-side falling trajectory c as shown by the dashed line, the classification point b is located at any of the boundary lines d, e, f of the particle size classification indicated by the dotted line. It was not possible to follow (vertical axis).

Therefore, according to the conventional control method, the classified particle size greatly changes with respect to the classification point b, and a stable particle size cannot be obtained. In addition, in such a conventional control method, the weight ratio of the classified raw materials is not stable, so that the stock amounts of the large and small ores in the charging raw material tank become unstable, and the lower limit of those stocks is set. Sometimes cracks occurred.

Therefore, according to the present invention, the position of the classifying device is controlled according to the falling trajectory of the raw material and the weight ratio of the classified large lumps and small lump ores so that the classification point follows the constant position of the raw material layer thickness. The purpose is to enable stable particle size classification and weight ratio classification.

[0010]

As a means for solving the above-mentioned problems, the present invention relates to a position control method of a classifying device for classifying a raw material falling from a conveyor which separates and transports the raw material in layers according to particle size, It is characterized in that the position of the classifying device is feed-forward controlled based on at least a drop trajectory for each particle size calculated from the thickness of the raw material layer falling from the conveyor and the speed of the conveyor.

[0011]

Operation: The position of the classifier is feed-forward-controlled based on at least the particle size-dependent drop trajectory calculated from the material layer thickness falling from the conveyor and the conveyor speed, so that the conveyor speed change and the material layer thickness can be controlled. Stable position control considering changes is possible.

[0012]

Embodiments of the present invention will be described below with reference to the drawings. FIG. 1 is a system diagram showing an embodiment of the present invention, in which ore for blast furnace charging containing different grain sizes conveyed by a conveyor belt conveyor 1 in the preceding stage is transferred to a classification belt conveyor 2, The ore falling from the classifying belt conveyor 2 is classified by a classifying device 3 into two particle sizes, a large lump and a small lump, and stored in a storage tank (not shown). The conveyor belt conveyor 1 has a drive pulley 1a connected to a drive motor 1b and is driven by rotating the drive motor 1b. In addition, the classification belt conveyor 2 includes a tail pulley 2a arranged below the conveying conveyor 1.
And a head pulley 2b disposed diagonally above the head pulley 2b, and the head pulley 2b is connected to a drive motor 2d that is driven to rotate at a constant speed via an eddy current joint 2c. The conveyor speed is controlled by controlling the value of the current supplied to the joint 2c. Classifier 3
Is a tip carriage 3a movably arranged in a horizontal direction at a position lowered from a discharge side end of the classification belt conveyor 2 by a preset predetermined vertical distance L, and is arranged on the tip carriage 3a. A linear classifying chip 3b for classifying the fine-grained raw material and the coarse-grained raw material, a pinion attached to the rotary shaft of the drive motor 3c, and a rack shaft meshing with the pinion, for moving the tip carrier 3a in the left-right direction. And a linear movement mechanism 3d configured to control the lateral position of the classifying tip 3b by rotating the driving motor 3c, and thereby the classifying point and the weight ratio of the falling raw material are arbitrarily set. Can be changed to

On the other hand, on the discharge side of the conveyer 1 for transportation, a layer thickness sensor 4 for detecting the raw material layer thickness, for example, an ultrasonic sensor, is arranged at a position above it, and the conveyor 2 for classification is also provided. Similarly, a layer thickness sensor 5 for detecting the raw material layer thickness is provided on the head pulley 2b side of the same, a pulse generator 6 is connected to the pulley 1c of the conveyor 1 for conveyance, and a pulse generator 6 is connected to the pulley 2a of the conveyor 2 for classification. 7 are connected, and pulse signals corresponding to the transfer speeds of the conveyors 1 and 2 are output from the pulse generators 6 and 7.

Further, belt wears 8 and 9 for respectively detecting the weights of the fine-grain raw material and the coarse-grain raw material classified by the classifying device 3 are provided. The speed of the classification conveyor 2 is controlled by the conveyor speed control device 10, and the horizontal position of the classification device 3 is controlled by the classification position control device 2.
Controlled by 0.

The conveyor speed control device 10 receives the pulse signals of the pulse generators 6 and 7 and converts them into conveyor speeds, and speed conversion units 11 and 12, respectively.
The layer thickness detection value h _F of the layer thickness sensor 4 and the conveyor velocity detection value V _CF output from the velocity conversion unit 11 are input, and a velocity setting for calculating the velocity set value V _CRT of the classification conveyor 2 based on these is input. The value calculator 13 and the speed setting value calculator 1
A subtracter 14 for calculating a deviation between the speed detection value V _CR of the actual classification conveyor 2 which is output from the third speed setting value V _CRT and the speed converting unit 12, PID based on the deviation signal of the subtracter 14 And a speed control unit 15 for performing a control calculation to obtain a drive current value for the eddy current joint 2c.

The speed setting value calculation unit 13 sets the speed setting value V _CRT of the classification conveyor to a function represented by the following equation (1), and sets the raw material layer thickness h _R on the classification conveyor 2 to the maximum allowable layer thickness h. _It is calculated so that it will approximately match _max . _{V CR = f 1 (h F} , V CF, W F, W R, h max) (1) Here, V _CF is the speed of the transport conveyor 1, W _F is transporting conveyor belt 1 of the belt width, W _R Is the belt width of the classification conveyor 2 and h _max is the maximum allowable layer thickness of the classification conveyor 2.

The classification position control device 20 detects the raw material layer thickness detection value h _{R of the} classification conveyor 2 output from the layer thickness sensor 5 and the classification conveyor 2 output from the speed conversion unit 12 of the conveyor speed control device 10. conveyor speed V _CR is input, classifying the calculated raw distance by particle size L _S, L _L based on these, and calculates a classification position command value L _P based these particle size by feed distance L _S, the L _L The position calculation unit 21 and the classification position correction unit 22 that corrects the classification position command value L _P calculated by the classification position calculation unit 21 based on the deviation between the actual weight ratio of the fine-grain raw material and the coarse-grain raw material and the set weight ratio. And a motor control unit 23 that performs PID control of the electric motor 3c according to the deviation between the classified position command value L _A output from the classified position correction unit 22 and the actual classified position detection value L _P1 .

The classification position correction unit 22 detects the raw material layer thickness detection value h _{R of the} classification conveyor 2 output from the layer thickness sensor 5 and the classification conveyor 2 output from the speed conversion unit 12 of the conveyor speed control device 10. Conveyor speed V _CR is entered,
Based on these, a raw material trajectory calculation unit 24 that calculates the raw material flight distances L _L and L _S by particle size by performing the function calculation of the following formula (2), and a classification weight ratio setter 25 that sets the classification set weight ratio α. , The set classification weight ratio α of the classification weight ratio setting device 25 and the flight distance L _L calculated by the raw material trajectory calculation unit 24,
A classification position command calculation unit 26 that calculates a classification position command value L _P by performing a function calculation of the following formula (3) based on L _S.

L_L= F₂(R, h_R, V_CR, T) (2) L_S= F₃(R, h_R, V_CR, T) (3) L_P= F_Four(L_L, L_S, Α) (4) where r is the radius of the head pulley 2b and h_RIs for classification
Material layer thickness of Nveya 2, V _CRIs the conveyor of the classification conveyor 2.
Y speed, t is vertical fall distance of raw material, α is preset
It is the set weight ratio for classification.

The classification position correction unit 22 is composed of the belt wear 8,
The actual fine-grain raw material weight detection value and the coarse-grain raw material weight detection value output from 9 are input, and the actual weight-ratio calculating unit 27 and the actual weight-ratio calculating unit 27 that calculate the weight ratios of the two are based on the input values. A subtractor 28 for calculating a deviation ε between the weight ratio α _R and the classification set weight ratio α output from the classification weight ratio setting device 25, and a weight ratio deviation ε output from the subtractor 28.
A correction value calculation unit 29 that calculates a classification position command value L _PA by performing PID calculation based on the above, and a classification position command value L _PA output from the correction value calculation unit 29 are added, and the classification position command value L _PA is added. _And an adder 30 for calculating _A.

The motor control unit 23 receives a detection signal corresponding to the rotation angle of the electric motor 3c output from the synchro 3e, and detects the current position of the classifying device 3 based on the detection signal. _A subtracter 32 that calculates a deviation between the current position of the current position detector 31 and the classified position correction command value L _A output from the classified position correction unit 22, and a PID based on the deviation output from the subtractor 32 A motor drive circuit 33 is provided which performs control calculation to calculate a motor drive current and outputs this drive current to the electric motor 3c.

Next, the operation of the embodiment of the present invention will be described. The raw material conveyed by the conveyer 1 is dropped onto the classifying conveyor 2 at its end position, and is obliquely conveyed by the classifying conveyor 2 to the dropping position on the side of the head pulley 2b which is obliquely above. In the conveying process, the fine-grained raw material is segregated and present in the lower layer and the coarse-grained raw material in the upper layer by the percolation, and when falling from the head pulley 2b side,
Due to the inertial flight, the coarse-grained raw material having a large mass falls along a falling trajectory farther than the fine-grained raw material, and a difference in flight distance occurs between the coarse-grained raw material and the fine-grained raw material.

At this time, in the classifying conveyor 2, the speed set value calculation unit 13 in the conveyor speed control device 10 calculates the equation (1), and the raw material layer thickness _{R is set} to the maximum allowable layer thickness h.
_The speed is controlled so that it approximately matches _max . Therefore, the width of the falling raw material falling at the position of the head pulley 2b of the classification conveyor 2 can be made large and substantially constant, and the classification efficiency can be improved.

As described above, in order to make the falling material width large and substantially constant, the conveyor speed V _CR of the classification conveyor 2 is set to the layer thickness sensor 5 and the pulse generator 7, respectively.
The raw material layer thickness detection value h _R and the conveyor speed detection value V _CR are calculated by the drop trajectory calculation unit 24 by the above equations (2) and (3), and the flight distances L _L and L _{S for} each particle size are detected. By calculating, the arrival position by particle size of the raw material actually falling from the classification conveyor 2 is predicted.

Then, the flying distances L _L and L _{S for each} particle size and the classification set weight ratio α preset by the classification weight ratio setting device 25 are input to the classification position command calculation unit 26, and the classification position command calculation unit 26 is input. By performing the calculation of the above-described equation (4), the classification position command value L _P of the classifying device 3 of the classifying device 3 for obtaining a predetermined classification accuracy is calculated. At this time, if it is assumed that the classification set weight ratio α set by the classification weight ratio setter 25 and the actual weight ratio α _R substantially match,
Since the classified position correction value L _PA from the classified position command correction unit 22 is substantially zero, the position command value L _P is supplied to the motor control unit 23 as it is.

Therefore, the motor control unit 23 performs PID control according to the deviation between the position command value L _P and the actual position detection value L _PA of the classifying device 3, and supplies the motor drive current to the electric motor 3c. As a result, the electric motor 3c is driven in the forward and reverse directions, and the classifier 3 is feedforward-controlled to an optimum position that maintains a predetermined classification accuracy. for that reason,
By controlling the drive of the electric motor 3c based on the control signal from the motor control unit 23, it is possible to compensate the change of the drop trajectory due to the change of the conveyor speed and the change of the raw material layer thickness. Thus, the position of the classification point a of the classification device 3 between the falling trajectories b and c is set to the boundary d of each particle size division,
It is possible to control to a stable position that follows e and f.

As described above, in the state in which the position of the classifying device 3 is feed-forward controlled, the set classification weight ratio α set by the classification weight ratio setting device 25 and the actual weight ratio α are set.
_{When the} deviation from _R occurs, these deviations ε are output from the subtractor 28 to the correction value calculation unit 29, so that the correction value calculation unit 29 corrects the classification position correction value L of the classification device 3 according to the deviation ε.
Calculating a _PA, which classification position command value L _P to be added classified position command correction value L of the classifying position computing unit 21 by the adder 30
_A is calculated.

Therefore, for example, the fine-grain raw material (or coarse-grain raw material) decreases, the weight ratio α _R becomes larger (smaller) than the set weight ratio α, and the classification position correction calculated by the correction value calculation unit 28 is performed. The value becomes a negative (or positive) value,
Since this is added to the classified position command value L _P by the adder 30, the classified position command value L _A becomes small (or large),
The electric motor 3c is driven in reverse (or forward), and the classifier 3 moves to the right (or left) in response to this, so that the fine-grain raw material (or coarse-grain raw material) classified by the classification chip 3b increases. Then, the classification position of the classification device 3 is feedback-controlled so as to eliminate the deviation of the weight ratio.

As described above, in the above-described embodiment, the classifying position of the classifying device 3 is feed-forward controlled according to the flight distance of the raw material falling from the classifying conveyor 2 according to the particle size. It is possible to perform stable classification position control regardless of changes in the conveyor speed and the raw material layer thickness, and improve the classification accuracy. Also,
By performing a feedback correction of the classification position command value based on the deviation between the set weight ratio α of the fine-grain raw material and the coarse-grain raw material and the actual weight ratio α _R , stable weight ratio control can be performed, and the stock in the storage tank Has the advantage that it can be stabilized.

In the above embodiment, the classification conveyor 2
The maximum allowable raw material layer thickness h _max by the conveyor speed control device 10
Although the case where the speed is controlled so as to maintain the above is described, the present invention is not limited to this, and the classification conveyor 2
May be controlled at a constant speed, and the classification position may be feed-forward controlled according to the fluctuation of the raw material layer thickness. Further, in the above embodiment, the case where the rack and pinion 3d is applied as the linear drive mechanism of the classifying device 3 has been described, but the present invention is not limited to this, and the screw shaft is rotationally driven by the motor and the nut that meshes with the screw shaft is configured. A straight drive mechanism or a chain may be wound between a pair of sprockets and the chain may be wound around and a part of the chain may be fixed to the cut carriage 3a to reciprocate the cut carriage 3a. Any other linear drive mechanism can be applied.

Further, in the above embodiment, the case where the classifying position of the classifying device 3 is detected by the position detector including the synchro is described, but the present invention is not limited to this, and the amount of movement of the rack shaft is directly detected. You may do it. Furthermore, the classifying tip 3b is not limited to a triangular cross section, and an arbitrary shape such as an arc shape can be selected according to the flight distance according to the particle size.

[0032]

As described above, according to the present invention, the classifying position of the classifying device is feed-forward controlled according to the flight distance of the raw material falling from the conveyor according to the particle size. Regardless of the variation in layer thickness, stable classification position control can be performed, and the effect of improving classification accuracy can be obtained.

Therefore, when applied to the raw material classifying device at the front stage of the storage tank which constitutes the furnace top charging device of the blast furnace, it is possible to stabilize the stock of the storage tank and to stabilize the operation of the blast furnace by stabilizing the grain size. ..

[Brief description of drawings]

FIG. 1 is an overall explanatory view of an embodiment of the present invention.

FIG. 2 is a control block diagram of an embodiment of the present invention.

FIG. 3 is a diagram for explaining the operation of the embodiment of the present invention.

FIG. 4 is a diagram for explaining an example of a conventional classification method.

FIG. 5 is a diagram for explaining the operation of a conventional classification method.

[Explanation of symbols]

 1 Conveyor 2 Conveyor 3 Classification device 24 Falling locus calculation unit 26 Classification position command calculation unit

Claims (1)

Claim: What is claimed is: 1. A method of controlling the position of a classifying device for classifying a raw material that drops from a conveyor that separates and transports a raw material in layers according to particle size, wherein the position of the classifying device falls at least from the conveyor. A method for controlling the position of a classifier, wherein feedforward control is performed based on a particle size-specific drop trajectory calculated from a raw material layer thickness and a conveyor speed.