Multistage control algorithm for optimizing dynamic characteristics of high-voltage wide-range X-ray power source

Abstract

The invention discloses a multistage control algorithm for optimizing the dynamic characteristics of a high-voltage wide-range X-ray power source. The algorithm fully utilizes the gain of the high-voltage power source in the manner of load, rising edge, and lower-limit frequency segmentation, realizes optimal rising edge control in the full load range, rapidly raises an kV output without overshoot, greatly reduces unnecessary rays generated during exposure, and improves imaging quality. In addition, control parameters are calculated in advance by a fuzzy algorithm and are stored in the controller in the form of data without further calculation. The algorithm runs fast with a small amount of calculation, and occupies less hardware resources.

Description

technical field [0001] The invention belongs to the technical field of power electronics, and in particular relates to a multi-stage control algorithm for optimizing the dynamic characteristics of a high-voltage wide-range X-ray power supply. Background technique [0002] With its strong penetration, ionization, special fluorescence, photosensitivity and biological characteristics, X-ray has been widely used in medical imaging detection, security inspection industry, industrial inspection, radiotherapy, X-ray microscope, etc. However, at the same time, X-rays will cause certain damage to the human body, and useless soft rays are not expected to appear when X-rays are used. At the same time, the soft ray itself will also have a certain impact on the imaging. [0003] The high-voltage power supply is its core component, and its performance directly determines the actual working performance and imaging effect of X-rays; the shorter the rising edge time of the output voltage of...

AI Technical Summary

Problems solved by technology

[0004] However, X-ray equipment (such as medical X-ray machines, industrial inspections) requires high-power power supplies (such as 80kW) with high stability, accuracy and good dynamic characteristics of tens to hundreds of kV. At the same time, it has many working modes, voltage and The load range is very large, and the traditional PI algorithm is difficult to achieve the above requirements; the output kV quality of the high-voltage power supply directly determines the quality of the output X-rays, so higher requirements are put forward for the kV rising speed, overshoot and control accuracy. Under the condition of no overshoot, the rise time is as fast as possible, while the output control accuracy is within 5%

[0005] The traditional single digital PI control algorithm adopts the same PI parameter under all working conditions of the whole equipment; under a wide load range, it is difficult to be compatible with light load and heavy load, and it is not difficult to be compatible with rising edge pair overshoot and rising speed requirements; therefore, its dynamic process in the full load range is poor, and it is difficult to meet high index requirements

In addition, the industry and academia have proposed a PI control method based on load segmentation, that is, different segments according to the load weight, and determine the PI parameter value, but this method does not give a clear segmentation basis and PI parameter determination method. It mainly relies on the debugging experience of engineers, and at the same time, it is impossible to judge the control stability of the equipment; in addition, it lacks segmental control of the rising edge process. Although it is compatible with the influence of load characteristics to a certain extent and improves the dynamic characteristics, it is There is no control optimization in the rising edge process, and it is difficult to achieve the fastest possible rising speed without overshoot; compared with the traditional single PI control, the PI control method based on load segmentation has improved performance, but it still cannot solve the problem of overshoot and rising The contradiction between speeds, the control effect is still poor, so the above control methods (such as PID) are difficult to meet its actual needs, and cannot solve the problem of dynamic characteristic optimization

[0006] In addition, the above-mentioned control algorithm does not have segmentation for the lower limit frequency, and cannot make full use of the gain capability of the circuit, which is one of the reasons why it cannot achieve the optimal dynamic characteristic control target

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