JPH0448577A - Heat input controlling apparatus for welding electric welded tube - Google Patents

Abstract

PURPOSE:To make feed-forward control easy in all the range of feeding speed by taking out a fuzzy inference result to the feeding speed of a pipe material with representative thickness as an intermediate variable and fuzzily infering the obtained intermediate variable and present thickness to obtain an optimum quantity of heat input. CONSTITUTION:A feeding speed (v) detected by a velocity detector 18 is provided to a first fuzzy inference part group 19a, 19b...19n which carry out fazzy inference to the velocity in the case of the representative thickness t0, t1...t2. The first fuzzy inference par group 19a, 19b...19n obtain fuzzy inference results %P0, %P1...%P2 to feeding speed in the case of the representative thickness as outputs. The obtained intermediate variables %P0, %P1...%P2 together with the present thickness (t) measured by a thickness measuring device 21 are supplied to a second fuzzy inference part 20 and the optimum heat input quantity P in the case of the present thickness is fuzzy-infered in the second fuzzy inference part 20.

Description

DETAILED DESCRIPTION OF THE INVENTION A. Field of Industrial Application This invention relates to a welding heat input control device for electric resistance welded pipes.

B1 Summary of the Invention This invention provides a welding heat input control device for an ERW tube in an ERW tube manufacturing line, which includes: a first fuzzy inference section that outputs a fuzzy inference result for the feed rate of a tube material at a representative plate thickness as an intermediate variable; By providing a second fuzzy inference section that performs fuzzy inference on the obtained intermediate variables and the current plate thickness to obtain the optimal heat input, feedforward control over the entire feed rate range can be easily realized. .

C1 Conventional technology In an ERW tube production line using an induction heating device, heat input control is performed to improve welding quality in ERW tube welding 9 to stabilize quality and significantly improve production yield. .

Figure 7 shows an induction type high frequency electric resistance welded pipe manufacturing line.
■ is a work coil for electromagnetic induction, 2 is a squeeze roll, 3 is the material to be welded, 4 is a V seam, 5 is an electric resistance welded pipe,
6 is a high frequency oscillation device.

The work coil 1 is placed in front of the squeeze roll 2, and when a high-frequency current is applied to the V-seam 4 formed in the material 3 by a multi-stage forming roll (not shown), the edges that butt against each other are It is heated by a high frequency current and then pressure welded by a squeeze roll 2.

In the above-mentioned electric resistance welding tube welding, the following three control means are employed as conventional heat input control means for controlling the high frequency current flowing through the V-seam 4.

(1) Manual control means in which the operator visually observes the temperature (large angle) of the welding part and the shape of the cut weld bead, and manually adjusts the amount of heat input based on these conditions.

(2) Speed-linked control means that detects the feed speed of the material to be welded and adjusts the amount of heat input commensurate with the feed speed using the output of the function generator.

(3) Temperature control means that detects the temperature of the welding part and controls the temperature to be constant.

However, in the heat input control means (1) to (3) above, the following (
It is still insufficient in points a) to (C).

(a) It is not possible to follow rapidly changing factors such as material feed rate fluctuations and plate thickness fluctuations.

(b) Welding cannot be performed when the feed rate is near zero at startup and stop, resulting in oven pipe formation.

(c) Due to these factors, excess or deficiency of heat input occurs, resulting in penetrator (a condition in which oxides such as scale are caught in the weld, resulting in defective welding), cold welding (incomplete welding at low temperature), etc. Weld defects such as these occur, making it impossible to obtain good weld quality.

D9 Problems to be Solved by the Invention In order to solve the problems (a) to (c) mentioned above, the feed rate of the material to be welded is detected and input to a processing unit, and the feed rate and optimal welding input are calculated. It has become possible to calculate the welding heat input corresponding to the detected feed rate based on a relational expression with heat (described later) and perform online control using a feedforward method.

It is known that the linear approximation formula for the feedforward method is given by the following formula for the same outer diameter and the same steel type.

P-(av+b+(e/cv+d)+f)i++ (1
) However, P: Heat input, ■: Feeding speed, t: Plate thickness, a-f
: Parameter, set as follows, for example.

a: moving heating area velocity coefficient, b: static heating reference value, C: static heating area rate coefficient, d: Stationary heating area speed correction value, e: static heating area correction value, f: Stationary heating area acceleration/deceleration correction value.

However, in recent years, it has become possible to produce a wide variety of products in small quantities at the same feed rate, and it is necessary to cover a wide range of plate thicknesses, such as about 1:5. However, since Equation (1) above is a linear approximation, the range of plate thickness that can be covered by Equation (1) is at most a range that can be expressed as t±Δt using the same constant value (even if you estimate It is about ±5%.

For this reason, if it is attempted to cover the plate thickness range of 1:5 that has been required in recent years, the combinations of the above-mentioned a-f as plate thickness parameters will become enormous, making it extremely difficult in practice.

This invention was made in view of the above circumstances, and in heat input control over a wide range of plate thicknesses, feedforward control over the entire feed rate range is easily achieved by performing fuzzy inference using only the control rule for the representative plate thickness. It is an object of the present invention to provide a welding heat input control device for electric resistance welded pipes.

20 Means for Solving the Problems This invention provides a speed detector for detecting the feed speed of a tube material, a speed detector for detecting the feed speed of the tube material, and a feed speed detected by the detector for controlling the welding heat input of an electric resistance welded pipe. a first fuzzy inference unit that outputs the fuzzy inference result for the feed rate of the pipe material as an intermediate variable; the intermediate variables output from this first fuzzy inference unit and the current plate thickness are input;
and a second fuzzy inference unit that performs fuzzy inference on intermediate variables for the current plate thickness and outputs the optimum heat input amount.

F6 action The first fuzzy inference section obtains fuzzy inference results (intermediate variables) for the feed rate of the tube material at the representative plate thickness. The intermediate variable obtained by the first fuzzy inference unit and the current plate thickness are inferred by the second fuzzy inference unit to output the optimum heat input amount.

G. Example Embodiments of the present invention will be described below based on the drawings.

In FIG. 1, a pipe material 1 roll-formed into a pipe shape
Reference numeral 1 indicates that the V-seam portion 11A is heated by a high frequency current of a work coil 13 located at the front stage of the squeeze roll 12. The high frequency current supplied to the work coil 13 is obtained by step-up rectifying AC power whose voltage is controlled by a variable power supply section 14 and by a DC high voltage section 15 . This high-voltage DC power is supplied to the high-frequency oscillator 1
6, a high frequency current is taken out from this oscillation section 16, and this high frequency current is taken out from a matching transformer 17.

18 is a speed detector, and this speed detector 18 is connected to the tube material 11.
This is to detect the feed speed V of. The detected feed rate V is determined by a first fuzzy inference unit group 1 that performs fuzzy inference on the feed rate V at representative plate thickness tO+tI...t.
9a, 19b...19n. The first fuzzy inference unit group 19a, 19b...19n outputs fuzzy inference results (intermediate variables) %POr%P1...%P for the feed rate at the representative plate thickness. The resulting intermediate variable %PO+%P.

...%P is supplied to the second fuzzy inference section 20 together with the current plate thickness t measured by the plate thickness gauge 21, and the second fuzzy inference section 20 calculates the optimum heat input amount P at the current plate thickness t.
Fuzzy inference is performed. The optimum heat input amount P is supplied to the variable power supply unit 14, and the variable power supply unit 14 is controlled so that the optimum heat input amount P is obtained.

Next, the operation of the above embodiment will be described.

The speed detector 18 detects the feed speed V of the tube material 11, and the feed speed V is detected by the first fuzzy inference unit group 19a, 19b.
...Supplies to 19n. First fuzzy inference unit group 19a,
19b...19n are fuzzy inference units based on the feed rate vs. control amount (heat input j1) P curve for various plate thicknesses shown in FIG.
Examples of control rules and membership functions for 9b...19n are shown in FIGS. 3 and 4.

FIG. 3 is an example of a control rule for the fuzzy inference section for a plate thickness of 1+, and FIG. 4 is an example of a membership function of the feed rate V and the control amount P.

For example, when the plate thickness t is tl, the feed speed V is V.

, the first fuzzy inference unit 19a executes the control rule R5 shown in FIG. 3 and uses the output as an intermediate variable %Pl''
Sends PH. The obtained intermediate variables are supplied to the second fuzzy inference section 20. Here, when the current plate thickness tl is input to the inference unit 20, the second fuzzy inference unit 20 executes the control rule R7 shown in FIG. The optimum heat input amount P is sent out according to the output.

H1 Effects of the Invention As described above, according to the present invention, in heat input control over a wide range of plate thicknesses, there is no need to express the control equation using a linear approximation formula as in the past, and only the control rule for the representative plate thickness is used. By performing fuzzy inference, there is an advantage that feedforward control can be easily realized over the entire feed speed range of the tube material.

[Brief explanation of drawings]

Fig. 1 is a schematic configuration diagram showing an embodiment of the present invention, Fig. 2 is a characteristic curve diagram of tube material feed rate versus control amount (heat input amount) for various plate thicknesses, and Fig. 3 is a first fuzzy diagram of the plate thickness t. An explanatory diagram showing an example of the control rule of the inference section, FIGS. 4A and 4B are explanatory diagrams of an example of the membership function of the feed rate V and the control amount P, and FIG. 5 is an explanatory diagram showing an example of the control rule of the second fuzzy inference section. Explanation shown -
6 is an explanatory diagram of an example of the membership function of plate thickness t,
FIG. 7 is a schematic perspective view showing an induction type high frequency electric resistance welded tube manufacturing line. 11... Pipe material, 12... Squeeze roll, 13.
...Work coil, 14...Variable power supply section, 15...
High voltage DC section, 16... High frequency oscillation section, 17... Transformer, 18... Speed detector, 19a, 19b... 19
n...first fuzzy inference section, 20...second fuzzy inference section, 21...plate thickness meter. Figure 4A An explanatory diagram of an example of the membership function of the feed rate V Figure 4B An explanatory diagram of an example of the membership function of the control amount P However, t 1 > t
2---->tn R1; IP V=Vot THEN %P+=Pot R2: IFν=2f1t THEN %P+=Tracing Ro
: IF 2/=Z/nl THEN %Pt=Pn+ Fig. 5 An explanatory diagram showing an example of the control rule Fig. 6 An explanatory diagram of an example of the membership function of the thick plate t

Claims (1)

[Claims] (1) In welding heat input control for ERW pipes, a speed detector detects the feed speed of the pipe material, and the feed speed detected by this detector is supplied, and a fuzzy A first fuzzy inference unit outputs the inference result as an intermediate variable, and the intermediate variables output from the first fuzzy inference unit and the current plate thickness are input, and the intermediate variables for the current plate thickness are fuzzy inferred and optimally input. 1. A welding heat input control device for an electric resistance welded pipe, comprising: a second fuzzy inference section that sends out an amount of heat.