Soft-switch hidden-arc welding contrarariant power supply with double closed-loop control

Abstract

With being connected to the slope compensation sector in parallel, the current and voltage detection sector is connected to the phase shift type pulse width modulation sector. The current and voltage detection sector through the error amlifier is also connected to the controller, which is connected to the driver sector. The output of the drive sector is connected to the inversion bridge. The above sectors constitute the peak current control circuit in the internal ring. Fuzzy intelligent control is adopted in average current control in the external ring. The magnetic switch is connected between the secondary of the high frequency power transformer and secondary high frequency rectification filtration sector. In the invention, the double closed loop controls raise the dynamic performances of the system; the open structure typed power transformer increases the thermal efficiency of power sources.

Description

(1) Technical field [0001] The invention relates to the technical field of mechatronics, in particular to the technical field of high-frequency soft-switching inverter technology and double-closed-loop intelligent control, and specifically refers to a soft-switching submerged arc welding inverter power supply with double-closed-loop control. (2) Background technology [0002] At present, in the field of submerged arc welding, due to the large current and high power required by the process, the traditional submerged arc welding power supply is mainly based on silicon rectifier and thyristor rectifier. The rectifier power supply is relatively reliable and technically mature, but The equipment is bulky, heavy, high in energy consumption, low in efficiency, and due to its structural reasons, its dynamic characteristics are not ideal enough. The more advanced hard-switching inverter has small size, high efficiency, high technical content and high added value, but the working envi...

AI Technical Summary

Problems solved by technology

At present, due to high-frequency parasitic oscillation, frequent and complex load changes, electromagnetic interference, magnetic bias and other reasons, the power supply of ordinary inverter welding machines has problems of insufficient reliability, especially in the case of high power.

[0004] (2) Harmonic interference At present, the inverter welding machines on the market basically work in hard switching mode, and the harmonics generated during the switching process will feed back to the power grid, causing pollution to the power grid; at the same time, it will also cause serious electromagnetic interference

However, this advantage has not been paid enough attention to and reflected in the existing products. In terms of arc control, it is still limited to the traditional control mode and design ideas, and the performance advantages of the inverter have not been fully utilized.

[0006] (4) Power factor problem Inverter welding machines working with hard switches have distortions in their working waveforms and high-order harmonics, which reduce the power factor

[0007] (5) The high-frequency power transformer has large transmission power and serious temperature rise, which is limited by the production level of magnetic materials and the production cost of welding machines. The window of magnetic materials and the effective magnetic conduction area cannot be too large, which increases the structural design, thermal design and electrical design of the transformer. technical difficulty

The design idea of ​​the welding system is still based on the traditional arc control method. The adjustment performance of the control system is not well combined with the control performance of the inverter arc welding power supply. The main reason is that the response speed and adjustment accuracy of the wire feeding system are difficult to guarantee. , although the use of fuzzy control technology has achieved certain results, fuzzy control basically stays in manual adjustment and design of fuzzy control rules, and the selection of membership functions is relatively subjective. Since the optimization of fuzzy control rules involves a huge search space, traditional The optimization method has a large amount of calculation, and there are many constraints on the performance evaluation function, so it is difficult to obtain the optimal control rule

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