KR20120001126A - Inverter DC resistance spot welding system, its welding process control method and fuzzy controller design method - Google Patents

Abstract

The present invention relates to an inverter DC resistance spot welding system, a welding process control method, and a fuzzy controller design method thereof. The system identification model and simulation are used to design a fuzzy controller for constant current control without a lot of experiments. The conversion factor can be optimized.

Description

Inverter DC resistance spot welding system, its welding process control method and its fuzzy controller design method {INVERTER DC RESISTANCE SPOT WELDING SYSTEM,

The present invention relates to an inverter DC resistance spot welding system, a welding process control method thereof, and a fuzzy controller design method thereof, and more particularly, an inverter DC resistance spot welding system capable of designing a controller with minimal experiment without prior experiments, The present invention relates to a welding process control method and a fuzzy controller design method thereof.

In general, resistance spot welding systems combine mechanical and electrical equipment to adjust the welding current, welding force, and welding time required for welding. To join a metal.

Resistance spot welding is divided into alternating current (DC) welding and direct current (DC) welding according to the welding power supply used. AC power source is 50 ~ 60Hz single phase power source, and the transformer is induced 50 ~ 60Hz welding power source same as main power source on the secondary side. An AC welder controls the welding current by firing a thyristor to adjust the current waveform. The welding current is amplified through the transformer and led to a large current that can be welded.

 The reason why DC resistance spot welders are in the spotlight recently is that manufacturing cost for DC resistance spot welders has been reduced due to the miniaturization and cost reduction of power devices required for inverter configuration such as IGBT, diode, etc., and improved reliability of each device. Because. In addition, the DC resistance spot welder can be finely controlled compared to the AC resistance spot welder. The control of AC resistance spot welding machine, which is widely used in current industrial field, uses thyristor phase control, which allows 120 times of control per second. The AC resistance spot welder cannot cope with the change in dynamic resistance in a short welding process, and a large amount of spatter is generated because of instantaneous heat input. The generated spatters have the disadvantage of causing deterioration of the welding quality and contamination around the weld.

On the other hand, DC resistance spot welding is controlled by pulse width modulation (PWM) of 1kHz, so 2000 times of control is possible. Therefore, DC resistance spot welder can overcome the disadvantage of AC resistance spot welder through fine control. In addition, the advantages of the DC welding machine can save energy by suppressing current loss, which has attracted much attention in the future due to environmental regulations and green IT technology.

Meanwhile, in the case of resistance spot welding system in which mechanical and electrical devices are intricately connected, a mathematical model that can replace the actual system is mainly used to analyze the dynamic characteristics of the system with respect to an external input. . The reason is that it is more efficient to use a mathematical model than the actual system because the control system design has to go through various processes such as selecting the appropriate control algorithm through analysis of the system characteristics and evaluating the characteristics. In particular, when using large currents, such as resistance spot welding systems, the use of mathematical models is essential to eliminate the hazards that arise when the output current response of various system inputs at the control system development stage is excessive. Do.

As a modeling method for mathematical models, we use a governor equation based on the physical principle to approximate each element of the system and express it in the form of a differential equation. However, because welding systems have nonlinear elements in the welding circuit, such as melting of metals, mechanical reactions to the welding gun, switching of electrical elements, etc., it is difficult to mathematically represent and linearize the welding system using physical laws. to be. In fact, as the system becomes more complex, information about all situations is not available, which requires a lot of assumptions about system behavior.

Thus, there is an increasing demand for more efficient methods for modeling resistance spot welding systems.

In addition, there is a need to develop an inverter DC resistance spot welding system that can compensate for the disadvantages of conventional AC single phase AC resistance spot welding.

Embodiments of the present invention provide an inverter DC resistance spot welding system that can compensate for the shortcomings of AC single phase AC resistance spot welding.

An embodiment of the present invention provides a welding process control method for an inverter DC resistance spot welding system using embedded software.

Embodiments of the present invention provide a method of designing a fuzzy controller of an inverter DC resistance spot welding system using a system identification modeling technique.

An embodiment of the present invention provides a fuzzy controller design method of an inverter DC resistance spot welding system that can design a fuzzy controller in an inverter DC resistance spot welding system and adjust a conversion factor of the fuzzy controller.

Embodiments of the present invention provide a method for designing a fuzzy controller of an inverter DC resistance spot welding system that can be performed with a minimum of experiments without many prior experiments.

Inverter DC resistance point welding system according to an embodiment of the present invention for solving the above problems is a power conversion unit for generating a welding current and controlling the amount of current or the conduction time of the welding current; A welding transformer generating a large current transmitted to the object to be welded; A welding part including a welding gun for transmitting an electrode pressing force required to a welding part of the welded object, and a pneumatic device for generating the electrode pressing force; And a welding controller configured to control driving of the welding portion, wherein the power converter includes: a rectifier diode rectifying three-phase AC power; A capacitor for smoothing the rectified power to generate a DC waveform; And an inverter for making the DC waveform generated by the capacitor into an AC having a predetermined pulse width.

By configuring as described above, it is possible to implement the inverter DC resistance point welding system that can compensate for the disadvantages of existing AC resistance point welding and save energy.

The inverter is formed as a full bridge inverter using four IGBTs, two IGBTs of the four IGBTs are bundled to form two pairs of IGBT modules, and a PWM pulse is applied to any one of the two pairs of IGBT modules. When the output of the full bridge is positive, when the PWM pulse is applied to the other module, the output of the full bridge may be negative.

As such, when PWM pulses are alternately applied to the two pairs of IGBT modules, the output of the full bridge may be an AC waveform.

The AC waveform is converted into a DC waveform through the welding transformer, the rectifier diode, and the welding unit.

On the other hand, according to another field of the present invention to solve the above problems, an embodiment of the present invention includes a first process for adjusting the PWM output to a constant current, constant power, constant voltage or constant amount; A second process of monitoring voltage or current; A third process of controlling a welding pressing force applied to the welded object; A fourth process of performing intelligent control; A fifth process of managing a welding process; A sixth process of performing display or crisis management; It provides a welding process control method of the inverter DC resistance spot welding system comprising a; seventh process in communication with the computer terminal (PC).

By controlling the welding process using the embedded software installed in the resistance spot welding system as described above, the welding process can be precisely controlled and the user can be managed to be stably welded by preventing the user from being injured during the welding process. have.

The first process is a process of purging the constant current, the constant voltage, the constant power, or the constant heat amount by selecting a command value of the computer terminal.

The second process is a process of storing the voltage or current measured from the ADC of the controller during welding at a designated position and processing the measurement data using a digital filter.

The third process is a process of applying the welding pressing force to the electrode of the welding gun.

The fourth process is a process of predicting a welding result using a result measured during welding and changing a current and a pressing force command value during welding.

The fifth process is a process of managing the pressurization, stabilization time, energization time or maintenance time of the welding, and coping with the emergency situation of the user.

The sixth process is a process of displaying a command value input by a user and displaying a state of a welding system.

The seventh process is a process of communicating data input by a user in the computer terminal and transmitting data measured during welding to the computer terminal.

The first to seventh processes may be executed simultaneously or independently. Thus, in managing the operation of the welding system and the welding process, it is possible to prevent another process from being affected by any one process.

According to an embodiment of the present invention, the method may further include: modeling the inverter DC resistance spot welding system as a system identification model; Verifying the system identification model; Designing a fuzzy controller using the system identification model obtained as a result of the verification; Verifying the performance of the fuzzy controller; Re-adjusting an optimal coefficient of the fuzzy controller obtained as a result of the verification; And a method of designing a fuzzy controller for an inverter DC resistance spot welding system including a step of optimizing the purge controller.

By designing the fuzzy controller or the intelligent adaptive controller by the above method, it is possible to design the fuzzy controller or the constant current controller of the welding system by using the simulation even without undue experimentation.

Modeling the inverter DC resistance spot welding system includes designing an experiment of the inverter DC resistance spot welding system and measuring inputs and outputs for system identification; Extracting or filtering valid values from the measured input and output; Selecting a structure of the system identification model; Designating a reference value and calculating an optimal system identification model that satisfies the reference value; And verifying the performance of the calculated system identification model.

If the performance is not satisfied at the step of verifying the performance of the system identification model, step 218 of calculating the optimal system identification model may be performed again.

Designing the fuzzy controller may include selecting a structure of the fuzzy controller; Selecting a fuzzy inference method; Extracting a control rule of the fuzzy controller; Modifying a control parameter adjustment or control rule of the fuzzy controller; And evaluating the performance of the fuzzy controller.

The modeling of the system identification model may include obtaining input data reflecting characteristics of the inverter DC resistance spot welding system through experiments, and designing the fuzzy controller may adjust coefficients of the fuzzy controller suitable for the system identification model. Computer simulation can be used to do this.

Re-adjusting the optimal coefficient of the fuzzy controller may use a response surface method to re-adjust the coefficient, and optimizing the fuzzy controller may use a genetic algorithm.

The designing of the fuzzy controller may design a speed type fuzzy PI controller using the system identification model.

The step of selecting the fuzzy inference method uses a simple inference method, and if the performance is not satisfied in the step of evaluating the performance of the fuzzy controller, the conversion factor of the fuzzy controller may be adjusted.

As described above, the inverter DC resistance spot welding system according to the embodiment of the present invention can compensate for the disadvantage of AC single phase AC resistance spot welding.

Inverter DC resistance spot welding system according to an embodiment of the present invention can reduce the energy consumed.

According to the welding process control method according to an embodiment of the present invention, since the welding process is controlled using embedded software, various situations that may occur during the welding process may be considered, and the user may stably perform the welding process.

Inverter DC resistance spot welding system according to an embodiment of the present invention can represent the user's input graphically, so that various input patterns can be made into a waveform, and after the welding shows the measured data to the user to complete the welding to the user Can be delivered quickly and accurately.

In the fuzzy controller design method according to the embodiment of the present invention, since the fuzzy controller of the inverter DC resistance spot welding system is designed by using a system identification technique, many assumptions about the system operation are not required, and the controller can be easily configured even if the system becomes complicated. Can be designed.

The fuzzy controller design method according to the embodiment of the present invention may improve the controller performance again when the performance of the controller is unsatisfactory.

Fuzzy controller design method according to an embodiment of the present invention can easily design a fuzzy controller with a minimum of experiments without prior experiment.

1 is a view schematically showing an inverter DC resistance spot welding system according to an embodiment of the present invention.
FIG. 2 is a block diagram schematically showing the configuration of the welding system according to FIG. 1.
3 shows a schematic circuit of the welding system according to FIG. 1.
4 is a view showing a change in the current waveform in the welding system according to FIG.
5 is a view showing a switching control operation of the inverter of the welding system according to FIG.
6 shows a relationship between processes of the embedded software used in the welding system according to FIG. 1.
FIG. 7 shows an example of a graphical user interface (GUI) of a welding management program used for the welding system according to FIG. 1.
8 through 10 are flowcharts illustrating a method of designing a fuzzy controller of an inverter DC resistance spot welding system according to an exemplary embodiment of the present invention.
FIG. 11 is a diagram illustrating a configuration of a fuzzy PI controller used in a fuzzy controller design of an inverter DC resistance spot welding system according to an exemplary embodiment of the present invention.
FIG. 12 is a diagram illustrating membership functions of an input and an output used in the fuzzy controller according to FIG. 11.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. However, the present invention is not limited or limited by the embodiments. Like reference numerals in the drawings denote like elements.

1 is a view schematically showing an inverter DC resistance spot welding system according to an embodiment of the present invention, FIG. 2 is a block diagram schematically showing the configuration of the welding system according to FIG. 1, FIG. 3 is according to FIG. 1. 4 is a schematic circuit diagram of a welding system, FIG. 4 is a view illustrating a current waveform in a welding system according to FIG. 1, and FIG. 5 is a diagram illustrating a switching control operation of an inverter of the welding system according to FIG. 1. .

1 to 5, an inverter DC resistance spot welding system 100 according to an embodiment of the present invention generates a welding current and controls an amount of current or an energization time of the generated welding current. Power conversion unit 130, a welding transformer 170 for generating a large current transmitted to the object to be welded, a welding gun for transmitting the electrode pressing force required to the welding site of the welded object and a pneumatic device for generating the electrode pressing force The welding unit 190 and a welding unit controller 110 for controlling the driving of the welding unit 170 may be included. Here, the welding driver 150 may be configured in the form of a welding robot, but is not limited thereto and may be implemented in various forms.

The power converter 130 may control the magnitude of the welding current applied to the welded object (for example, a thin plate such as an automobile body), a time for applying the weld current to the welded object, that is, an energization time. The welding transformer 170 may include a transformer for generating a large current. The welding unit 190 may include a welding gun that physically transmits electrode force to a welded portion of the welded object, a pneumatic device such as a pneumatic valve and a pneumatic cylinder that generates electrode pressure, a welding jig, and the like. It may include. The welding gun is a pneumatic type device. When a servo-gun is used as the welding gun, a pressing force may be generated by using a motor instead of a pneumatic device.

In addition, the power converter 130 includes a rectifier diode for rectifying three-phase AC power, a condenser for smoothing the rectified power to generate a DC waveform, and a predetermined pulse from the DC waveform generated by the capacitor. It may include an inverter for making an alternating current having a width. A more detailed description of the power converter 130 will be described later.

On the other hand, as shown in Figure 2, the inverter DC resistance point welding system 100 according to an embodiment of the present invention may include three large modules. That is, the power module may include a power module, a control module, and a driving module. The power module is mainly composed of IGBT and transformer, the control module is composed of DSP and LCD which are high speed processors, and the drive module can be composed of pneumatic valve and pneumatic device to generate electrode pressure on the welding gun. As such, the three modules that make up the resistance spot welding system 100 may interact with each other to perform a desired welding process. Here, the welding gun may be electrically connected to the power module (E) and mechanically connected to the drive module (M).

FIG. 3 is a simplified circuit diagram of the power converter 130 and the welding transformer 170 of the inverter DC resistance spot welding system 100 according to an exemplary embodiment of the present invention, and FIG. In the inverter DC resistance spot welding system 100 according to an embodiment of the present invention is shown a change in the waveform. The conversion principle of the welding current will be described with reference to FIGS. 3 and 4 as follows.

First, the 50 ~ 60 Hz three-phase 440V AC power source, which is the main power source, is rectified by using a rectifier diode and smoothed by a condenser. The combination of diodes and capacitors is called a DC-link. Passing through the capacitor of the DC link, noise such as ripple is removed, resulting in a clean waveform DC waveform. Since the output of the DC-link is direct current, an Insulated Gate Bipolar Transistor (IGBT) can be used to generate an alternating current of the desired pulse width.

As shown in FIG. 5, the inverter of the power converter 130 of the resistance spot welding system 100 according to an embodiment of the present invention may be configured as a full-bridge inverter using four IGBTs. Can be. The inverter may be switched at a cycle of 1 kHz using a PWM (Pulse Width Modulation) control technique to generate an AC of 1 kHz square wave at the primary side of the welding transformer 170. Since the transformer of the welding transformer 170 has a 55: 1 turns ratio, the current may be amplified and the voltage may decrease when passing through the weld transformer 170. Finally, the alternating current passing through the welding transformer 170 is rectified back to the diode to generate a direct current welding current. The rectified waveform is pulsed and needs smoothing. Since the welding gun of the welding part 190 is made of copper, it has its own resistance and inductance. Therefore, due to the inductance component present in the welding gun, it can be smoothed to have a direct current form without attaching a reactor. Finally, the converted large current is transmitted to the object to be welded through the welding gun, and the resistance spot welding may be performed by generating heat by the contact resistance of the welded part of the object to be welded.

As described above, the inverter of the power converter 130 according to an embodiment of the present invention may be provided with four IGBTs to generate an AC having a square waveform.

That is, as shown in FIG. 5, the inverter of the power converter 130 is formed as a full bridge inverter using four IGBTs, and two IGBT modules are bundled by binding two IGBTs among the four IGBTs. Can be formed. When a PWM pulse is applied to the IGBT 1 and the IGBT 4 as shown in FIG. 5A, the output of the full bridge circuit may output a positive waveform. On the contrary, when the PWM pulses are applied to the IGBT 2 and the IGBT 3 as shown in FIG. 5B, the output of the full bridge circuit may have a negative waveform. As such, when PWM pulses are alternately applied to the IGBT module including the IGBT 1 and the IGBT 4 and the IGBT module including the IGBT 2 and the IGBT 3, the output of the full bridge circuit may be an AC waveform. That is, when a PWM pulse is applied to one of the two pairs of IGBT modules, the output of the full bridge becomes positive, and when the PWM pulse is applied to the other module, the output of the full bridge becomes negative. When PWM pulses are alternately applied to the two pairs of IGBT modules, the output of the full bridge may be an AC waveform.

The AC waveform may be converted into a DC waveform through a welding gun of the welding transformer 170, the rectifier diode, and the welding unit 190. At this time, when a waveform having a large PWM duty ratio is applied, the current increases, and when a waveform having a small duty ratio is input, the current decreases.

On the other hand, the inverter DC resistance spot welding system 100 according to an embodiment of the present invention may be embedded with embedded software (Embedded Software) for controlling the welding process.

That is, the inverter DC resistance spot welding system 100 according to an embodiment of the present invention, the first process (P1) for adjusting the PWM output to a constant current, constant power, constant voltage or constant amount, the second to monitor the voltage or current Process P2, third process P3 for controlling welding pressing force applied to the welded object, fourth process P4 for performing intelligent control, fifth process P5 for managing welding process, display or crisis Embedded software may be mounted that includes a sixth process P6 for performing management and a seventh process P7 for communicating with a computer terminal.

FIG. 6 is a diagram showing the interprocess relationships of the embedded software used in the welding system 100 according to FIG. 1. Referring to FIG. 6, the first process P1 is a process of purging the constant current, the constant voltage, the constant power, or the constant heat amount by selecting a command value of the computer terminal PC. The first process P1 may be referred to as a process of managing the PWM output to be a constant current, constant voltage, constant power, or constant heat amount. The second process P2 monitors the voltage or current measured from the analog-to-digital converter (ADC) of the weld controller 110 during welding or stores the measured voltage or current at a designated location, and measures the measured data using a digital filter. Is the process of machining. The third process P3 is a process of controlling the welding pressing force or applying the electrode to the welding gun. The fourth process P4 is an intelligent control process, which is a process having a function of predicting welding results using the results measured during welding and improving weldability by changing the current and the pressing force command value during welding. The fifth process P5 is a process of managing a welding process during welding, and is a process of managing pressurization, stabilization time, energization time, or maintenance time of the welding, and coping with an emergency situation of a user. The sixth process P6 is a display and crisis management process, in which a command value input by a user is displayed on an LCD or the like and the state of the welding unit 190 is displayed. The seventh process P7 is a process for communicating with a computer terminal PC, which transmits data input by a user in the computer terminal PC through communication, and transmits data measured during welding to the computer terminal PC. Process.

The first to seventh processes P1 to P7 may be simultaneously or independently executed to control the melting process of the inverter DC resistance spot welding system to be stably welded. That is, the welding process control method of the inverter DC resistance spot welding system 100 according to an embodiment of the present invention may be performed by the first to seventh processes (P1 to P7).

Meanwhile, referring to FIG. 6, it can be seen that the first to seventh processes P1 to P7 operate in association with each other. The HMI process (Human Machine Interface Process) shown in FIG. 6 allows a user to start a welding system using a teaching panel (not shown) or the like to operate the resistance spot welding system 100. When the teaching panel and the user's computer terminal to communicate.

In other words, the first to seventh processes P1 to P7 mounted on the resistance spot welding system 100 operate independently and simultaneously with each other to control the welding process of the resistance spot welding system 100. It can be called an operating process and a management process.

FIG. 7 shows an example of a graphical user interface (GUI) of a welding management program used for the welding system according to FIG. 1. As shown in FIG. 7, the graphical user interface of the management program of the inverter DC resistance spot welding system 100 according to an embodiment of the present invention may graphically represent a user input. Input patterns can be waveformd, and various current waveforms can be graphically implemented. It may play a role in transmitting data generated by a user to a digital signal processor (DSP), which is a controller of a welding system. In addition, the welding unit 190 may have a function of showing data measured after welding to a user, and may have a function of storing a welding result in a database. To this end, the graphical user interface of the management program shown in FIG. 7 includes a menu for selecting a control mode, a current mode, a pressure mode, a menu for transmitting welding setting information, and And a menu for storing the welding measurement information.

Hereinafter, a method of designing a fuzzy controller of the inverter DC resistance spot welding system 100 according to an embodiment of the present invention will be described with reference to the drawings.

8 to 10 are flowcharts illustrating a method for designing a fuzzy controller of an inverter DC resistance spot welding system according to an embodiment of the present invention, and FIG. 11 is a flowchart of an inverter DC resistance spot welding system according to an embodiment of the present invention. FIG. 12 is a diagram illustrating a configuration of a fuzzy PI controller used in a fuzzy controller design, and FIG. 12 is a diagram illustrating membership functions of inputs and outputs used in the fuzzy controller according to FIG. 11.

The purge controller of the inverter DC resistance spot welding system 100 according to an exemplary embodiment of the present invention enables the power converter 130 to precisely control the strength of the welding current or the energization time, and performs the process under the optimum welding conditions. As a constant current controller that can be performed, conventionally, designers have been able to design in a trial and error manner by performing a number of practical experiments. However, the intelligent adaptive controller design method according to an embodiment of the present invention calculates a controller using computer simulation, performs a minimum experiment, and compares the experimental result with the controller obtained through computer simulation to design an optimal controller. Can be. That is, the fuzzy controller design method according to an embodiment of the present invention can provide a method of reducing the number of experiments and designing an optimal controller having excellent performance relatively easily. Hereinafter, with reference to the drawings will be described in more detail.

Referring to FIG. 8, the design method of the fuzzy controller of the inverter DC resistance spot welding system 100 according to an embodiment of the present invention models the inverter DC resistance spot welding system 100 as a system identification model. Step 210, verifying the system identification model 220, designing a fuzzy controller using the system identification model obtained as a result of verification 230, and verifying the performance of the fuzzy controller. 240, re-adjusting an optimal coefficient of the fuzzy controller obtained from the verification result 250, and optimizing the fuzzy controller 260.

The method of designing a fuzzy controller of the resistance spot welding system 100 as described above is a method for effectively designing a constant current controller and tuning a coefficient in the inverter DC resistance spot welding system 100. The welding system can be modeled with a system identification model to verify the system identification model, and a fuzzy controller can be designed using the obtained system identification model. Here, the fuzzy controller may be referred to as a kind of intelligent adaptation controller.

In addition, a computer simulation may be used to adjust scaling factors of the fuzzy controller suitable for the system identification model, and a genetic algorithm may be used as a method of optimizing the coefficients of the fuzzy controller. In addition, since there is a difference between the system identification model and the actual inverter DC resistance spot welding system 100, the response surface method is applied to apply the optimal coefficient of the fuzzy controller obtained by computer simulation to the actual resistance spot welding system. To readjust the coefficients.

Modeling the inverter DC resistance spot welding system 100 with a system identification model among the design methods (210), verifying the system identification model (220), the system identification model obtained as a result of the verification Designing a fuzzy controller (230) and verifying the performance of the fuzzy controller (240) using computer simulation is a step of using a computer simulation, and re-adjust the optimal coefficient of the fuzzy controller obtained as a result of the verification The step 250 and the step 260 of optimizing the purge controller may be referred to as experiments using an actual resistance spot welding system 100 and comparing the experimental results with those obtained by computer simulation.

Table 1 summarizes the design sequence and method used of the controller of the inverter DC resistance spot welding system 100 according to an embodiment of the present invention.

Process Algorithm

System identification model

System modeling ARX model or ANN model Controller design Fuzzy PI Controller Performance index
(Performance Index) IAE (integral of the absolute error) Modulus adjustment
(Parameter tuning) Scaling factor
(GE, GDE, GDU) Optimization algorithm Genetic algorithm
(Genetic Algorithm)
Real system
(Resistance spot welding system) Performance index IAE (integral of the absolute error) Modulating
(Parameter re-tuning) Scaling factor
(GE, GDE, GDU) Optimization algorithm Response surface method
(Response surface method)

On the other hand, as shown in Figure 9, the step of modeling the inverter DC resistance point welding system 100 as a system identification model (210) design an experiment of the inverter DC resistance point welding system 100 and input for system identification And measuring output 212, extracting or filtering valid values from the measured input and output 214, selecting a structure of the system identification model 216, specifying a reference value and specifying the reference value. Calculating 218 an optimal system identification model that satisfies, verifying 222 the performance of the calculated system identification model, and verifying 224 the optimal model. Here, if the performance is not satisfied at step 222 of verifying the performance of the system identification model, step 218 of calculating the optimal system identification model is performed again. The system identification modeling step 210 may be repeatedly performed until a desired reference model is obtained by selecting a model structure, selecting an optimal model index, and analyzing the model.

As a modeling method for mathematical models, we use a governor equation based on the physical principle to approximate each element of the system and express it in the form of a differential equation. However, since the resistance spot welding system 100 has nonlinear elements present in the welding circuit such as melting of metal, mechanical reaction to the welding gun, switching of electrical elements, and so on, the welding system is mathematically represented using physical laws. And linearization is difficult. In fact, as the system becomes more complex, information about all situations is not available, which requires a lot of assumptions about system behavior. Therefore, an efficient method is required for modeling a welding system. To this end, the present invention introduces a system identification technique. System identification is a method of mathematically expressing the relationship between inputs and outputs without using physical equations in an unknown system. The mathematical models include linear and nonlinear models. Linear models include ARX, ARXMAX, OE, BJ, and models. Nonlinear models include NARMA and Nonlinear ARX using artificial neural networks.

In designing an experiment of the inverter DC resistance spot welding system 100 and measuring inputs and outputs for system identification 212 and extracting or filtering valid values from the measured inputs and outputs 214 In the on / off pulse signal applied to the IGBT, the section size corresponding to on can be defined as the PWM control value in the welding controller and the welding current output from the welding system can be defined as the value measured in the ADC of the welding controller. have. In operation 212, the input and output measurement may be performed to obtain input data reflecting characteristics of the inverter DC resistance spot welding system 100.

On the other hand, the design method according to an embodiment of the present invention defines the model structure as shown in the following [Equation 1] in the step 216 of selecting the structure of the system identification model.

Here, y is an output, u is an input, e is white noise, and various models may exist depending on whether A, B, C, D, or F polynomials exist.

One embodiment of the present invention after determining the model structure based on the above [Equation 1], and examines the performance of the system identification model in the error or satisfactory range required by the inverter DC resistance point welding system 100, Performance is verified by comparing their performance against various model structures. Through this process, the system identification modeling method according to an embodiment of the present invention is a system identification model of the ARMAX (25, 18, 15) model is most suitable for the inverter DC resistance spot welding system 100 according to an embodiment of the present invention Was selected. Here, ARMAX is an "autoregressive moving average model with exogenous inputs model", and 25, 18, and 15 are values corresponding to A, B, and C of Equation 1, respectively. Using the ARMAX (25,18,15) model according to the input of each verification data, the current value by the system identification model and the current value of the resistance spot welding system 100 measured by actual experiments were compared. We can see that the model (25,18,15) appears similar to the output of the actual welding system according to various input types.

Hereinafter, a step of designing a fuzzy controller with reference to the drawings will be described.

In the resistance point welding system according to an embodiment of the present invention, since the resistivity varies according to the welded object and the resistance changes during welding, robust control characteristics are required, and therefore, it is preferable to use a fuzzy controller. In the present invention, to design a fuzzy controller for constant current control, a speed-type fuzzy PI (Proportional Integral) controller is designed using the aforementioned system identification model. In the inverter DC resistance spot welding system 100 according to an embodiment of the present invention, since the IGBT is turned on / off at a switching frequency of 1 kHz, a control input is generated every 0.5 msec from the microcontroller of the control board. You can. In addition, since the total welding current flow time is usually about several hundred msec, the selection of the controller considering the high speed microprocessor and the calculation speed is required for precise control during the short process. In the present invention, we use a speed-type fuzzy PI controller using simple reasoning for continuous control rule extraction in single loop control.

As shown in FIG. 10, the method 230 for designing the speed-type fuzzy PI controller, that is, the design of the fuzzy controller of FIG. Step 234, extracting the control rule of the fuzzy controller 236, adjusting the control parameter of the fuzzy controller or modifying the control rule 238, and evaluating the performance of the fuzzy controller 239. It may include.

11 shows a fuzzy PI controller used in one embodiment of the present invention. In Figure 11 the plant uses the ARMAX (25, 18, 15) model described above, where Ref and Yk are the target values and the actual output of the welding system, respectively. The difference between the error (e) and the change amount (Δe) of the error as the input variable of the controller, and the change amount of output (Δu) as the output of the controller. The relationship between the error (e), the change amount (Δe) of the error, and the output (u) is shown in [Equation 2].

As such, designing the fuzzy controller 230, that is, selecting the structure of the fuzzy controller 232, may use computer simulation to adjust the coefficients of the fuzzy controller appropriate for the system identification model. Here, in the step 234 of selecting the fuzzy inference method, a simple inference method may be used. Fuzzy inference methods can be classified into three types: fuzzification, fuzzy inference engine, and defuzzyification. Fuzzy is an isosceles triangle method that converts the stochastic characteristics of input values into appropriate fuzzy numbers when they are considered uncertain due to disturbance. In addition, the fuzzy inference method uses a min-max method, and the non-fuzzy method may use a center of gravity method.

The control rule extracted in step 236 of extracting the fuzzy control rule may configure fuzzy sets for the inputs (e, Δe) and output (u) of Equation 2 in seven steps. Also, membership functions for the inputs e, Δe and output u are as shown in FIG. 12 (a) is a membership function of the error e, FIG. 12 (b) is a membership function of the amount of change Δe of the error, and FIG. 12 (c) is a membership function of the output u.

On the other hand, if the performance of the designed fuzzy controller is not satisfactory in the step 240 of verifying the performance of the fuzzy controller, the performance of the fuzzy controller may be improved again. The performance of the fuzzy controller is mainly based on scaling factors of input / output variables, It can be influenced by membership functions and control rules. In the present invention, a method of adjusting the conversion factor is used as a method for improving the performance of the fuzzy controller (see 250 of FIG. 8).

Optimizing the fuzzy controller 260 uses a genetic algorithm to adjust the conversion factor of the fuzzy controller. In the present invention, the scaling factor is adjusted to improve the control performance of the fuzzy controller, and the objective function is an integrated index of the absolute error (IAE) index as a performance index. The conversion factor value is selected and optimized, and genetic algorithm is used as an optimization algorithm. The conversion factor of the simulation, which optimized the fuzzy controller of the system identification model, was converged in the 53rd generation by genetic algorithm, and GE = 0.4936, GD = 2.48683, GDU = 221.035.

On the other hand, a fuzzy controller designed using a system identification model and an optimization algorithm and simulated is much more efficient in terms of time and cost than adjusting the fuzzy controller for the actual plant, that is, the welding system. However, since the system identification model basically includes modeling errors due to the complexity and nonlinearity of the actual system, a controller designed based on the system identification model may need to be re-adjusted by applying it to the actual welding system. As such, step 250 of re-adjusting the optimal coefficient of the fuzzy controller may re-adjust or optimize the fuzzy control conversion coefficient using a response surface method.

By applying the fuzzy control conversion factor of the computer simulation to the actual resistance spot welding system, it can be seen that the fuzzy controller designed by the computer simulation works well because the system identification model represents the actual welding system. Although many prior experiments have been conducted to design the existing controller, in the present invention, only the system identification model and the simulation can design the controller sufficiently.

While the present invention has been described in connection with what is presently considered to be practical exemplary embodiments, it is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. Accordingly, the spirit of the present invention should not be construed as being limited to the embodiments described, and all of the equivalents or equivalents of the claims, as well as the following claims, belong to the scope of the present invention .

100: Inverter DC Resistance Spot Welding System
110: welding unit controller 130: power conversion unit
150: welding robot 170: welding transformer
190: weld

Claims (21)

A power conversion unit generating a welding current and controlling an amount of current or an energization time of the welding current;
A welding transformer generating a large current transmitted to the object to be welded;
A welding part including a welding gun for transmitting an electrode pressing force required to a welding portion of the welded object, and a pneumatic device for generating the electrode pressing force; And
And a welder controller configured to control driving of the welder.
The power converter,
Rectification diodes for rectifying three-phase AC power;
A capacitor for smoothing the rectified power to generate a DC waveform; And
An inverter for making a DC waveform generated by the capacitor into an AC having a predetermined pulse width;
Inverter DC resistance spot welding system comprising a.
The method of claim 1,
The inverter is formed as a full bridge inverter using four IGBTs, and binds two IGBTs of the four IGBTs to form two pairs of IGBT modules.
When the PWM pulse is applied to any one of the two pairs of IGBT modules, the output of the full bridge is positive, the output of the full bridge is negative when the PWM pulse is applied to the other module, the inverter DC resistance Spot welding system.
The method of claim 2,
The inverter DC resistance point welding system of claim 2, wherein the output of the full bridge becomes an AC waveform when a PWM pulse is alternately applied to the two pairs of IGBT modules.
The method of claim 3,
And the AC waveform converts a DC waveform through the welding transformer, the rectifier diode, and the welding portion.
In the method for controlling the welding process of the inverter DC resistance spot welding system according to any one of claims 1 to 4,
A first process of adjusting the PWM output to be a constant current, constant power, constant voltage or constant heat amount;
A second process of monitoring voltage or current;
A third process of controlling a welding pressing force applied to the welded object;
A fourth process of performing intelligent control;
A fifth process of managing a welding process;
A sixth process of performing display or crisis management; And
A seventh process of communicating with the computer terminal;
Welding process control method of the inverter DC resistance point welding system comprising a.
The method of claim 5,
And the first process purge-controls the constant current, the constant voltage, the constant power, or the constant heat amount by selecting a command value of the computer terminal.
The method of claim 6,
The second process is a welding process control method of the inverter DC resistance point welding system, which stores the voltage or current measured from the ADC of the controller during welding in a specified position, and processing the measurement data using a digital filter. .
The method of claim 7, wherein
And the third process applies the welding pressing force to an electrode of the welding gun.
The method of claim 8,
And said fourth process uses the results measured during welding to predict welding results and to change the current and force command values during welding.
10. The method of claim 9,
The fifth process is a welding process control method of the inverter DC resistance point welding system, which manages the pressurization, stabilization time, energization time or maintenance time of the welding, and copes with the emergency situation of the user.
The method of claim 10,
And said sixth process displays a command value input by a user and displays a state of a welding system.
The method of claim 11,
And the seventh process communicates data input by a user in the computer terminal and transmits data measured during welding to the computer terminal.
The method of claim 5,
And wherein the first to seventh processes are executed simultaneously or independently.
A method for designing a controller of an inverter DC resistance spot welding system according to any one of claims 1 to 4,
Modeling the inverter DC resistance spot welding system as a system identification model;
Verifying the system identification model;
Designing a fuzzy controller using the system identification model obtained as a result of the verification;
Verifying the performance of the fuzzy controller;
Re-adjusting an optimal coefficient of the fuzzy controller obtained as a result of the verification; And
Optimizing the fuzzy controller;
Fuzzy controller design method of the inverter DC resistance spot welding system comprising a.
The method of claim 14,
Modeling the inverter DC resistance spot welding system,
Designing an experiment of the inverter DC resistance spot welding system and measuring inputs and outputs for system identification;
Extracting or filtering valid values from the measured input and output;
Selecting a structure of the system identification model;
Designating a reference value and calculating an optimal system identification model that satisfies the reference value; And
Verifying the performance of the calculated system identification model;
Fuzzy controller design method of the inverter DC resistance spot welding system comprising a.
16. The method of claim 15,
If the performance is not satisfied in the step of verifying the performance of the system identification model, the step of calculating the optimal system identification model is performed again, fuzzy controller design method of the inverter DC resistance point welding system.
The method of claim 14,
Designing the fuzzy controller,
Selecting a structure of the fuzzy controller;
Selecting a fuzzy inference method;
Extracting a control rule of the fuzzy controller;
Modifying a control parameter adjustment or control rule of the fuzzy controller; And
Evaluating the performance of the fuzzy controller;
Fuzzy controller design method of the inverter DC resistance spot welding system comprising a.
The method of claim 17,
The modeling of the system identification model may include obtaining input data reflecting characteristics of the inverter DC resistance spot welding system through experiments.
And designing the purge controller uses computer simulation to adjust the coefficients of the purge controller suitable for the system identification model.
The method of claim 14,
Re-adjusting the optimal coefficient of the fuzzy controller may re-adjust the coefficient using a response surface method,
And optimizing the fuzzy controller using a genetic algorithm.
The method of claim 14,
The designing of the fuzzy controller may include designing a speed type fuzzy PI controller using the system identification model.
The method of claim 17,
The step of selecting the fuzzy inference method using a simple reasoning method,
And if the performance is not satisfied in evaluating the performance of the fuzzy controller, adjusting the conversion factor of the fuzzy controller.

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