Direct-current high-voltage generator regulation and control method and system based on intelligent feedback

Abstract

The present invention relates to the technical field of circuit control, and relates to a direct-current high-voltage generator regulation and control method and system based on intelligent feedback. A fuzzy control logic operation is performed on an output current flux value and an input voltage fluctuation factor of a load experimental object, so as to obtain the disturbance amplitude of a voltage fluctuation state for a current flux change trend; if a step-up transformer can execute a PID control technology by adjusting a transformation ratio, PID real-time adjustment parameters are calculated, and a crossover mutation operation of individuals is performed on the basis of a fitness function, so as to generate a first boost regulation and control scheme; and if the step-up transformer cannot execute the PID control technology by adjusting the transformation ratio, a calibrated state feedback controller is constructed on the basis of a state variable of the current step-up transformer and an adjustment signal output amplitude, so as to generate a second boost regulation and control scheme. The present invention achieves intelligent feedback regulation and control by independently analyzing components of direct-current high-voltage generators, improving the stability and accuracy of outputting high-voltage direct current.

Description

A direct-current high-voltage generator regulation method and system based on intelligent feedback TECHNICAL FIELD

[0001] The present application relates to the technical field of circuit control, and in particular to a direct-current high-voltage generator regulation method and system based on intelligent feedback. BACKGROUND

[0002] The direct-current high-voltage generator is a device for generating high-voltage direct current, and is commonly used in scientific experiments, industrial production, medical devices, and power systems. Some current direct-current high-voltage generators only have a feedback loop, and have not yet popularized feedforward control regulation of the circuit, resulting in slow feedback regulation efficiency of the direct-current high-voltage generator, and the internal step-up transformer and rectifier cannot be individually regulated according to the feedback error, resulting in a high error rate in the high-voltage direct current output of the direct-current high-voltage generator, which is not conducive to actual direct current application requirements. At the same time, the direct-current high-voltage generator working in a high-temperature environment is prone to internal voltage changes, and the direct-current high-voltage generator cannot adaptively regulate according to the temperature control condition, greatly reducing the output quality of the direct current. Therefore, a regulation method capable of intelligently feeding back the voltage condition of the direct-current high-voltage generator is needed to solve the above problems.

[0003] SUMMARY

[0004] The present application overcomes the shortcomings of the prior art and provides a direct-current high-voltage generator regulation method and system based on intelligent feedback.

[0005] To achieve the above purpose, the technical solution adopted by the present application is as follows:

[0006] The present application provides a direct-current high-voltage generator regulation method based on intelligent feedback, comprising the following steps:

[0007] Obtain the output current flux value and the input voltage fluctuation factor of the load experimental object of the direct-current high-voltage generator at each target timestamp, and perform fuzzy control logic operation based on the output current flux value and the input voltage fluctuation factor to obtain the disturbance amplitude of the voltage fluctuation state to the current flux change trend;

[0008] If the step-up transformer can perform PID control technology by adjusting the variable ratio, calculate the PID real-time adjustment parameter and perform individual crossover mutation operation based on the fitness function to generate a first step-up regulation scheme when the disturbance amplitude of the voltage fluctuation state to the current flux change trend is greater than the preset disturbance amplitude.

[0009] If the step-up transformer cannot perform PID control technology by adjusting the transformation ratio, a state feedback controller is constructed based on the current state variable of the step-up transformer and the output amplitude of the adjustment signal, and a second step-up control scheme is generated by the state feedback controller;

[0010] The power factor change rate of the load test object at the preset time node is obtained, if the power factor change rate is not in the preset power factor change range, the active power factor correction coefficient of each multi-stage inverter in the circuit of the sub-layout area in the direct current high voltage generator is obtained, the Edmonds-Karp algorithm is introduced to calculate the active power factor correction coefficient, and the sub-order control sequence of all multi-stage inverters in the rectifier bridge is obtained.

[0011] A plurality of groups of actual temperature control parameters fed back by the temperature sensor in the direct current high voltage generator in the preset time period are obtained, and the standard temperature control interval that should be met when the actual steady-state voltage value of the direct current high voltage generator is output is obtained, a radar chart is constructed, and the radar chart is analyzed to adjust the temperature control compensation gain of the direct current high voltage generator.

[0012] Further, in a preferred embodiment of the present application, the output current flux value and the input voltage fluctuation factor of the load test object of the direct current high voltage generator corresponding to each target time stamp are obtained, fuzzy control logic operation is performed based on the output current flux value and the input voltage fluctuation factor, the disturbance amplitude of the voltage fluctuation state to the current flux change trend is obtained, and the specific steps include the following steps:

[0013] The load test object of the direct current high voltage generator is obtained, and a plurality of continuous target time stamps are preset, the output current flux value and the input voltage fluctuation factor of the load test object corresponding to each target time stamp are extracted through test recording;

[0014] The output current flux value and the input voltage fluctuation factor of the load test object corresponding to each target time stamp are analyzed to obtain the current flux change trend and the voltage fluctuation state, and N fuzzy control sets are obtained based on a big data network;

[0015] The membership function between the current flux change trend and each fuzzy control set is calculated by introducing a Gaussian membership function algorithm, the fuzzy control set corresponding to the maximum membership function between the current flux change trend and each fuzzy control set is screened out, and is defined as a first ideal fuzzy control set;

[0016] The membership function between the voltage fluctuation state and each fuzzy control set is calculated based on the Gaussian membership function algorithm, and the fuzzy control set corresponding to the maximum membership function between the voltage fluctuation state and each fuzzy control set is also screened out, and is defined as a second ideal fuzzy control set;

[0017] The current flux change trend and the voltage fluctuation state are respectively correspondingly introduced into the first ideal fuzzy control set and the second ideal fuzzy control set for pairing mapping and quantization based on the maximum membership function, to generate a fuzzy current flux change trend control set and a fuzzy voltage fluctuation state control set;

[0018] A fuzzy control logic algorithm is introduced, preset fuzzy rules in the fuzzy control logic algorithm are extracted, and the fuzzy control logic based on the preset fuzzy rules is used for fuzzy control reasoning operation on the fuzzy current flux change trend control set and the fuzzy voltage fluctuation state control set, to determine an output fuzzy control action;

[0019] The output fuzzy control action is subjected to weighted de-fuzzing processing by a weighted average method, so that the output fuzzy control action is converted into an influence output value, and the disturbance amplitude of the voltage fluctuation state on the current flux change trend is determined based on the influence output value.

[0020] Further, in a preferred embodiment of the present application, if the step-up transformer can perform PID control technology by adjusting the transformation ratio, the PID real-time adjustment parameter is calculated and individual crossover mutation operation is performed based on the fitness function, to generate a first step-up control scheme, which specifically includes the following steps:

[0021] If the disturbance amplitude of the voltage fluctuation state on the current flux change trend is greater than the preset disturbance amplitude, the model specification information and the control protocol of the step-up transformer in the direct current high-voltage generator are obtained;

[0022] According to the model specification information and the control protocol of the step-up transformer, it is determined whether the step-up transformer can perform PID control technology by adjusting the transformation ratio, and if the step-up transformer can perform PID control technology by adjusting the transformation ratio, the real-time transformation ratio under the current step-up transformer operating state is obtained;

[0023] The desired voltage value required by the load test object under the condition that the step-up transformer can perform PID control technology by adjusting the transformation ratio is obtained, the expected transformation ratio is preset based on the desired voltage value, the error between the real-time transformation ratio and the expected transformation ratio is calculated, the transformation ratio error threshold is obtained, and the PID control technology is executed and the PID control algorithm is introduced at this time;

[0024] The output voltage adjustment operation is performed in the PID control algorithm based on the transformation ratio error threshold, to obtain a real-time proportional control adjustment amount, a real-time integral control adjustment amount and a real-time differential control adjustment amount, the real-time proportional control adjustment amount, the real-time integral control adjustment amount and the real-time differential control adjustment amount are added, and the PID real-time adjustment parameter is obtained;

[0025] A plurality of groups of PID real-time adjustment parameters in a preset time period are acquired, a hash algorithm is introduced to calculate a hash value of each group of PID real-time adjustment parameters, a fitness function of each group of PID real-time adjustment parameters is determined according to the hash value, M populations are randomly generated based on the plurality of groups of PID real-time adjustment parameters, an individual with the highest fitness function is extracted in each population, and a plurality of target parents are obtained;

[0026] The plurality of target parents are subjected to a cross operation and mutation processing one by one to generate a plurality of new individuals, the new individuals with the highest fitness function in the population are screened through continuous iteration, and the new individual with the best fitness function in the population is acquired, and the PID real-time adjustment parameter corresponding to the new individual with the best fitness function is defined as a first voltage boosting control scheme and output.

[0027] Further, in a preferred embodiment of the present application, if the voltage boosting transformer cannot perform PID control technology by adjusting the turns ratio, a state feedback controller is constructed based on the state variable of the current voltage boosting transformer and the output amplitude of the adjustment signal, and a second voltage boosting control scheme is generated by the state feedback controller, specifically including the following steps:

[0028] If the voltage boosting transformer cannot perform PID control technology by adjusting the turns ratio, the state variable of the current voltage boosting transformer and the output amplitude of the adjustment signal are acquired.

[0029] The circuit structure and element characteristics of the voltage boosting transformer are introduced based on Kirchhoff's voltage law, the node current equation and the loop voltage equation are constructed, the state variable is introduced into the node current equation and the loop voltage equation for dynamic description, and the state equation is obtained.

[0030] All interference factors that cause the output amplitude of the adjustment signal to change due to the state variable are obtained based on big data network, the information entropy of the output amplitude of the adjustment signal is calculated, and the conditional entropy of the output amplitude of the adjustment signal after being segmented under the state variable is calculated, the information gain index of the state variable to the output amplitude of the adjustment signal is obtained by subtracting the conditional entropy from the information entropy, all interference factors that cause the output amplitude of the adjustment signal to change due to the state variable are linearly combined based on the information gain index, and a linear output equation is obtained.

[0031] The ideal voltage stabilization value required by the load test object under the condition that the voltage boosting transformer cannot perform PID control technology by adjusting the turns ratio is acquired, a closed-loop control system model is constructed based on the state equation and the linear output equation, the pole placement method is introduced, the preset closed-loop pole position in the pole placement method is based on the ideal voltage stabilization value, and the expected characteristic equation is analyzed according to the closed-loop pole position.

[0032] By solving the desired characteristic equation, a state feedback gain matrix is obtained, the state feedback gain matrix is introduced into the closed-loop control system model to calculate control input adjustment and verification, and finally a state feedback controller with adjustment completed is generated.

[0033] The state feedback controller with adjustment completed is applied to the actual control system of the step-up transformer to obtain an actual step-up control value, which is defined as a second step-up control scheme and output.

[0034] Further, in a preferred embodiment of the present application, if the power factor change rate is not within the preset power factor change range, the active power factor correction coefficient of each multi-stage inverter in the circuit of the sub-layout area is obtained, the Edmonds-Karp algorithm is introduced to calculate the active power factor correction coefficient, and the sub-order control sequence of all multi-stage inverters in the rectifier bridge is obtained.

[0035] The historical power factor of the load test object at the preset time node is obtained, and the power factor change rate is calculated based on the historical power factor, and it is judged whether the power factor change rate is within the preset power factor change range, if not, the circuit layout diagram of the rectifier bridge in the DC high-voltage generator is obtained.

[0036] The circuit layout diagram is divided into several sub-layout areas, and all multi-stage inverters in each sub-layout area are identified and marked, and the active power factor correction coefficient of each multi-stage inverter in the circuit of the sub-layout area is obtained.

[0037] The Edmonds-Karp algorithm is introduced to calculate the active power factor correction coefficient of each multi-stage inverter in the circuit of the sub-layout area, the flow of each edge in the flow network is initialized to construct a residual network, and a path with residual capacity is found from the source node to the sink node in the residual network based on the breadth-first search method, and a target augmented path is obtained.

[0038] The residual capacity of all edges on the target augmented path is calculated, and the minimum residual capacity of each edge is extracted, and the minimum residual capacity of each edge is added to the corresponding edge on the augmented path, the augmented path is calculated and the residual capacity of the edge in the residual network is updated, until the target augmented path cannot be found, and the sub-order control sequence of all multi-stage inverters in the rectifier bridge is obtained.

[0039] Further, in a preferred embodiment of the present application, the plurality of sets of actual temperature control parameters fed back by the temperature sensor in the DC high-voltage generator within a preset time period and the standard temperature control interval that should be met when the actual steady-state voltage value of the DC high-voltage generator is output are used to construct a radar chart, and the radar chart is analyzed to adjust the temperature control compensation gain of the DC high-voltage generator, specifically including the following steps:

[0040] The rated AC power is input to the DC high-voltage generator, the voltage transformer is used to regulate and control the rated AC power through the first voltage regulation scheme or the second voltage regulation scheme, and then the regulated AC power is converted into DC power based on the hierarchical control sequence of all multi-stage inverters in the rectifier bridge. At this time, the plurality of sets of actual temperature control parameters fed back by the temperature sensor in the DC high-voltage generator within a preset time period are obtained.

[0041] The technical field to which the load test object belongs is obtained, the standard temperature control interval that should be met by the DC high-voltage generator when outputting different preset standard steady-state voltage values is obtained in the big data network based on the technical field, the actual steady-state voltage value of the feedback circuit in the DC high-voltage generator is obtained, and the Hamming distance between the actual steady-state voltage value and each preset standard steady-state voltage value is calculated.

[0042] The preset standard steady-state voltage value corresponding to the minimum Hamming distance is extracted, and the standard temperature control interval that should be met when the actual steady-state voltage value of the DC high-voltage generator is output is determined based on the preset standard steady-state voltage value corresponding to the minimum Hamming distance.

[0043] A radar chart is constructed, the standard temperature control interval that should be met when the actual steady-state voltage value of the DC high-voltage generator is output is introduced into the radar chart to obtain a standard temperature control radar chart, and the plurality of sets of actual temperature control parameters fed back by the temperature sensor in the DC high-voltage generator within a preset time period are introduced into the standard temperature control radar chart for fitting, and the radar chart region that is overlapped by the standard temperature control radar chart and the actual temperature control radar chart is removed.

[0044] If there is no actual temperature control radar chart in the remaining standard temperature control radar chart after removal, the area value of the remaining standard temperature control radar chart is obtained, and the temperature control compensation gain of the DC high-voltage generator is adjusted based on the area value.

[0045] If there is an actual temperature control radar chart in the remaining standard temperature control radar chart after removal, the area deviation value between the remaining standard temperature control radar chart and the remaining actual temperature control radar chart is calculated, a hash algorithm is introduced to calculate the hash function between the area deviation value and the minimum Hamming distance, and the temperature control compensation gain of the DC high-voltage generator is adjusted based on the hash function.

[0046] The second aspect of the present application provides a kind of based on intelligent feedback's direct current high voltage generator control system, the kind of based on intelligent feedback's direct current high voltage generator control system includes memory and processor, a kind of based on intelligent feedback's direct current high voltage generator control method program is stored in the memory, when the kind of based on intelligent feedback's direct current high voltage generator control method program is executed by the processor, the following steps are realized:

[0047] The output current flux value corresponding to each target timestamp of the load test object of the direct current high voltage generator and the input voltage fluctuation factor are obtained, and fuzzy control logic operation is carried out based on the output current flux value and the input voltage fluctuation factor to obtain the disturbance amplitude of the voltage fluctuation state to the current flux change trend.

[0048] If the step-up transformer can perform PID control technology by adjusting the transformation ratio, the PID real-time adjustment parameter is calculated and individual crossover mutation operation is carried out based on the fitness function to generate a first step-up control scheme based on the condition that the disturbance amplitude of the voltage fluctuation state to the current flux change trend is greater than the preset disturbance amplitude.

[0049] If the step-up transformer cannot perform PID control technology by adjusting the transformation ratio, a state feedback controller is constructed based on the state variables and the adjustment signal output amplitude of the current step-up transformer, and a second step-up control scheme is generated through the state feedback controller.

[0050] The power factor change rate of the load test object at the preset time node is obtained, and if the power factor change rate is not within the preset power factor change range, the active power factor correction coefficient of each multi-stage inverter in the circuit of the sub-layout area in the direct current high voltage generator is obtained, the Edmonds-Karp algorithm is introduced to calculate the active power factor correction coefficient, and the hierarchical control sequence of all multi-stage inverters in the rectifier bridge is obtained.

[0051] A plurality of groups of actual temperature control parameters fed back by the temperature sensor in the direct current high voltage generator within a preset time period are obtained, and the standard temperature control interval that should be met when the actual steady-state voltage value of the direct current high voltage generator is output is obtained, a radar chart is constructed, and the radar chart is analyzed to adjust the temperature control compensation gain of the direct current high voltage generator.

[0052] The present application solves the technical defects in the background art, and has the following beneficial technical effects:

[0053] The output current flux value of the load experiment object and the input voltage fluctuation factor are subjected to fuzzy control logical operation, so as to obtain the disturbance amplitude of the voltage fluctuation state on the current flux change trend; based on the condition that the disturbance amplitude of the voltage fluctuation state on the current flux change trend is greater than a preset disturbance amplitude, if the step-up transformer can execute PID control technology by adjusting the variable ratio, the PID real-time adjustment parameters are calculated and individual crossover mutation operation is performed based on the fitness function, so as to generate a first step-up regulation scheme; if the step-up transformer cannot execute PID control technology by adjusting the variable ratio, a state feedback controller is constructed based on the state variables and the adjustment signal output amplitude of the current step-up transformer, so as to generate a second step-up regulation scheme; the active power factor correction coefficient of each multi-stage inverter in the circuit in the sub-layout area where the multi-stage inverter is located is obtained, the Edmonds-Karp algorithm is introduced to calculate the active power factor correction coefficient, so as to obtain the sub-order regulation sequence of all multi-stage inverters in the rectifier bridge; a radar chart composed of actual temperature control parameters and standard temperature control intervals is constructed, and the radar chart is analyzed to adjust the temperature control compensation gain of the direct current high-voltage generator. The step-up transformer, the rectifier bridge and the temperature control link of the direct current high-voltage generator are independently analyzed to realize intelligent feedback regulation, so as to improve the stability and accuracy of the output high-voltage direct current of the direct current high-voltage generator. BRIEF DESCRIPTION OF DRAWINGS

[0054] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings of other embodiments can be obtained by those skilled in the art without creative labor.

[0055] Fig. 1 shows a first method flowchart of a direct current high-voltage generator regulation method based on intelligent feedback;

[0056] Fig. 2 shows a second method flowchart of a direct current high-voltage generator regulation method based on intelligent feedback;

[0057] Fig. 3 shows a third method flowchart of a direct current high-voltage generator regulation method based on intelligent feedback;

[0058] Fig. 4 shows a system framework diagram of a direct current high-voltage generator regulation system based on intelligent feedback. DETAILED DESCRIPTION

[0059] In order to enable the above-mentioned objects, features and advantages of the present application to be more clearly understood, the following further describes the present application with reference to the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0060] In the following description, a large number of specific details are set forth in order to facilitate a thorough understanding of the present application, but the present application can also be implemented in other manners different from those described herein, and therefore, the scope of protection of the present application is not limited to the specific embodiments disclosed below.

[0061] The first aspect of the present application provides a smart feedback-based DC high-voltage generator regulation method, as shown in FIG. 1, comprising the following steps:

[0062] S102: Obtain the output current flux value and the input voltage fluctuation factor of the load test object of the DC high-voltage generator at each target timestamp, and perform fuzzy control logic operation based on the output current flux value and the input voltage fluctuation factor to obtain the disturbance amplitude of the voltage fluctuation state to the current flux change trend;

[0063] S104: If the voltage fluctuation state to the current flux change trend has a disturbance amplitude greater than a preset disturbance amplitude, and the step-up transformer can perform PID control technology by adjusting the transformation ratio, calculate the PID real-time adjustment parameter and perform individual crossover mutation operation based on the fitness function to generate a first step-up regulation scheme;

[0064] S106: If the step-up transformer cannot perform PID control technology by adjusting the transformation ratio, construct a state feedback controller based on the state variables and the adjustment signal output amplitude of the current step-up transformer to generate a second step-up regulation scheme through the state feedback controller;

[0065] S108: Obtain the power factor change rate of the load test object at a preset time node, and if the power factor change rate is not within a preset power factor change range, obtain the active power factor correction coefficient of each multi-stage inverter in the sub-layout area circuit of the DC high-voltage generator, introduce the Edmonds-Karp algorithm to calculate the active power factor correction coefficient, and obtain the hierarchical regulation sequence of all multi-stage inverters in the rectifier bridge;

[0066] S110: Obtain a plurality of groups of actual temperature control parameters fed back by the temperature sensor in the DC high-voltage generator within a preset time period, and obtain the standard temperature control interval that should be met when the DC high-voltage generator outputs an actual steady-state voltage value, construct a radar chart, and analyze the radar chart to adjust the temperature control compensation gain of the DC high-voltage generator.

[0067] Further, in a preferred embodiment of the present application, the output current flux value and the input voltage fluctuation factor of the load test object of the DC high-voltage generator at each target timestamp are obtained, and fuzzy control logic operation is performed based on the output current flux value and the input voltage fluctuation factor to obtain the disturbance amplitude of the voltage fluctuation state on the current flux change trend, specifically including the following steps:

[0068] A load test object of a DC high-voltage generator is obtained, and a plurality of continuous target timestamps are preset. The output current flux value and the input voltage fluctuation factor of the load test object at each target timestamp are extracted through test records;

[0069] The output current flux value and the input voltage fluctuation factor of the load test object at each target timestamp are analyzed to obtain the current flux change trend and the voltage fluctuation state, and N fuzzy control sets are obtained based on big data networks;

[0070] Gaussian membership function algorithm is introduced to calculate the membership function between the current flux change trend and each fuzzy control set, and the fuzzy control set corresponding to the maximum membership function between the current flux change trend and each fuzzy control set is selected as the first ideal fuzzy control set;

[0071] Gaussian membership function algorithm is introduced to calculate the membership function between the voltage fluctuation state and each fuzzy control set, and the fuzzy control set corresponding to the maximum membership function between the voltage fluctuation state and each fuzzy control set is selected as the second ideal fuzzy control set;

[0072] The current flux change trend and the voltage fluctuation state are respectively introduced into the first ideal fuzzy control set and the second ideal fuzzy control set based on the maximum membership function for pairing mapping and quantization to generate a fuzzy current flux change trend control set and a fuzzy voltage fluctuation state control set;

[0073] Fuzzy control logic algorithm is introduced, preset fuzzy rules in the fuzzy control logic algorithm are extracted, and fuzzy control reasoning operation is performed on the fuzzy current flux change trend control set and the fuzzy voltage fluctuation state control set based on the fuzzy logic of the preset fuzzy rules to determine the output fuzzy control action;

[0074] The output fuzzy control action is weighted and de-fuzzled by weighted average method to convert the output fuzzy control action into an impact output value, and the disturbance amplitude of the voltage fluctuation state on the current flux change trend is determined based on the impact output value.

[0075] It needs to be explained that through investigation and analysis, most of the direct current high voltage generators on the market only have a feedback loop inside based on the error between the system output and the expected output to adjust the controller output, and the feedforward control is still not popularly set, and when the high voltage direct current output by the direct current high voltage generator is unstable, the voltage inspection regulation and control after the feedback loop needs to be waited for before acting on the load test object, which greatly reduces the regulation and control rate and wastes the test time cost; and the present application analyzes and calculates the output current flux value and the input voltage fluctuation factor through the fuzzy control logic algorithm, so as to obtain the disturbance amplitude of the voltage fluctuation state to the current flux change trend; the disturbance amplitude of the voltage fluctuation state to the current flux change trend is the stable output interference degree of the voltage fluctuation state to the current flux change trend; according to the disturbance amplitude of the voltage fluctuation state to the current flux change trend, the controller output of the direct current high voltage generator can be adjusted in advance to offset the influence of load change on the system. Unlike feedback control, feedforward control does not need to wait for the error of the control circuit, but adjusts in advance according to known information; in voltage regulation, feedforward control can use known load change information or other system disturbance information to adjust the output of the voltage controller in advance to reduce system response time and steady-state error, thereby improving the voltage regulation rate and quality of the direct current high voltage generator.

[0076] Further, in a preferred embodiment of the present application, if the step-up transformer can perform PID control technology by adjusting the turns ratio, the PID real-time adjustment parameters are calculated and individual crossover mutation operation is performed based on the fitness function to generate a first step-up regulation scheme, specifically including the following steps:

[0077] If the disturbance amplitude of the voltage fluctuation state to the current flux change trend is greater than the preset disturbance amplitude, the model specification information and control protocol of the step-up transformer in the direct current high voltage generator are obtained;

[0078] According to the step-up transformer model specification information and control protocol, it is judged whether the step-up transformer can perform PID control technology by adjusting the turns ratio, and if the step-up transformer can perform PID control technology by adjusting the turns ratio, the real-time turns ratio under the current step-up transformer operating state is obtained;

[0079] The expected voltage value required by the load test object under the condition that the step-up transformer can perform PID control technology by adjusting the turns ratio is obtained, the expected turns ratio is preset based on the expected voltage value, the error between the real-time turns ratio and the expected turns ratio is calculated to obtain the turns ratio error threshold, and at this time, the PID control technology is executed and the PID control algorithm is introduced;

[0080] Perform output voltage adjustment operation in the PID control algorithm based on the variable ratio error threshold to obtain real-time proportional control adjustment, real-time integral control adjustment and real-time differential control adjustment, and add the real-time proportional control adjustment, the real-time integral control adjustment and the real-time differential control adjustment to obtain the PID real-time adjustment parameter;

[0081] Obtain a plurality of groups of the PID real-time adjustment parameter groups in a preset time period, introduce a hash algorithm to calculate a hash value of each group of the PID real-time adjustment parameter, determine an adaptive function of each group of the PID real-time adjustment parameter group according to the hash value, randomly generate M populations based on a plurality of groups of the PID real-time adjustment parameter groups, extract an individual with the highest adaptive function in each population to obtain a plurality of target parents;

[0082] Perform cross operation and mutation processing on the plurality of target parents one by one to generate a plurality of new individuals, continuously iterate to screen a new individual with the highest adaptive function in the population, obtain the PID real-time adjustment parameter corresponding to the new individual with the best adaptive function in the population, define the first boost control scheme and output.

[0083] It should be noted that if the disturbance amplitude of the voltage fluctuation state on the current flux change trend is greater than the preset disturbance amplitude, it indicates that the voltage fluctuation tends to be unstable and has a greater impact on the flux of the direct current, and therefore the boost behavior of the boost transformer in the direct current high voltage generator needs to be further analyzed. Since the boost transformer generates an electromotive force through the electromagnetic coupling between the primary and secondary windings, thereby increasing the voltage, adjusting the turns ratio of the primary and secondary windings can achieve precise control of the output voltage, and the PID control technology is used to adjust the output voltage of the boost transformer, so some types and control protocols of the boost transformer can support the adjustment of the turns ratio to execute the PID control technology. Therefore, when the boost transformer can execute the PID control technology by adjusting the turns ratio, the turns ratio error threshold of the boost transformer is analyzed by executing the PID control algorithm in the PID control technology to obtain the PID real-time adjustment parameter. Since the plurality of groups of the PID real-time adjustment parameters in the preset time period contain a plurality of fuzzy or erroneous control parameters, which are not optimal control parameters, the optimal adjustment parameter needs to be selected as the control scheme output. Therefore, first, the performance of each group of the PID real-time adjustment parameter is evaluated by the adaptive function, and the smaller the adaptive function, the better the PID real-time adjustment parameter setting. Then, the individual with the highest adaptive function is selected as the parent for cross mutation operation of the new individual, and finally this process is repeatedly performed to select the individual with the best adaptive PID parameter from the population. Genetic optimization can achieve faster and more accurate adjustment of the output voltage of the transformer to meet the application requirements of the load test object.

[0084] Further, in a preferred embodiment of the present application, if the step-up transformer cannot perform PID control technology by adjusting the turns ratio, a state feedback controller is constructed based on the state variable of the current step-up transformer and the output amplitude of the adjustment signal, and a second step-up control scheme is generated by the state feedback controller, specifically including the following steps:

[0085] If the step-up transformer cannot perform PID control technology by adjusting the turns ratio, the state variable of the current step-up transformer and the output amplitude of the adjustment signal are obtained;

[0086] The circuit structure and element characteristics of the step-up transformer are introduced based on Kirchhoff's voltage law to construct node current equations and loop voltage equations, and the state variable is introduced into the node current equations and loop voltage equations for dynamic description to obtain a state equation;

[0087] All interference factors that cause the output amplitude of the adjustment signal to change based on the state variable are obtained based on big data networks, the information entropy of the output amplitude of the adjustment signal is calculated, and the conditional entropy of the output amplitude of the adjustment signal after being divided under the state variable is calculated. The information gain index of the state variable to the output amplitude of the adjustment signal is obtained by subtracting the conditional entropy from the information entropy, and all interference factors that cause the output amplitude of the adjustment signal to change based on the information gain index are linearly combined to obtain a linear output equation;

[0088] The ideal voltage stabilization value required by the load test object under the condition that the step-up transformer cannot perform PID control technology by adjusting the turns ratio is obtained, a closed-loop control system model is constructed based on the state equation and the linear output equation, and the pole placement method is introduced. The ideal voltage stabilization value is used to preset the closed-loop pole position in the pole placement method, and the expected characteristic equation is analyzed based on the closed-loop pole position;

[0089] The state feedback gain matrix is obtained by solving the expected characteristic equation, and the state feedback gain matrix is introduced into the closed-loop control system model to calculate the control input adjustment and verification, and finally a state feedback controller is generated;

[0090] The state feedback controller is applied to the actual control system of the step-up transformer to obtain the actual step-up control value, which is defined as the second step-up control scheme and output.

[0091] It should be noted that if the step-up transformer cannot perform PID control technology by adjusting the transformation ratio, the voltage needs to be adaptively adjusted by the control system of the direct current high-voltage generator, and at present, the direct current high-voltage generator based on the existence of such a step-up transformer is generally controlled and feedback adjusted through the feedback loop set in the control system. The feedback response needs to consume a lot of time, and the feedback rate is slow. Therefore, the dynamic step-up behavior of the step-up transformer is described as a set of state equations and linear output equations in the present application, a closed-loop control system is constructed combining the state equations and the linear output equations, and the pole placement method is introduced to design and adjust the parameters of the closed-loop control system to obtain the state feedback controller. The state feedback controller can form a state space control for the control system of the step-up transformer, and realize accurate adjustment of the step-up behavior of the step-up transformer. Among them, the state equation describes the evolution law of the state of the step-up transformer with time, and the linear output equation maps the state of the step-up transformer to the output variable, which is usually the measurement value or control target of the step-up transformer. The state feedback controller adjusts the behavior of the system by measuring the step-up state of the step-up transformer and taking it as a feedback signal, so as to realize the expected performance index, dynamically adjust the control input according to the change of the step-up state of the step-up transformer, achieve accurate regulation and control of the step-up transformer, ensure the stability and performance of the voltage step-up of the step-up transformer, and improve the reliability of the output high-voltage direct current.

[0092] Further, in a preferred embodiment of the present application, if the power factor change rate is not within the preset power factor change range, the active power factor correction coefficient of each multi-stage inverter in the circuit of the sub-layout area is obtained, the Edmonds-Karp algorithm is introduced to calculate the active power factor correction coefficient, and the sub-order control sequence of all multi-stage inverters in the rectifier bridge is obtained, as shown in FIG. 2, which specifically includes the following steps:

[0093] S202: Obtain the historical power factor of the load test object at the preset time node, calculate the power factor change rate combined with the historical power factor, and determine whether the power factor change rate is within the preset power factor change range. If not, obtain the circuit layout diagram of the rectifier bridge in the direct current high-voltage generator;

[0094] S204: Divide the circuit layout diagram into several sub-layout areas, identify and mark all multi-stage inverters in each sub-layout area, and obtain the active power factor correction coefficient of each multi-stage inverter in the circuit of the sub-layout area;

[0095] S206: introduce the Edmonds-Karp algorithm to calculate the active power factor correction coefficient of each multi-stage inverter in the circuit of the sub-layout area it is in, initialize the flow of each boundary in the flow network, build a residual network, and find a path with residual capacity from the source node to the sink node of the residual network based on the breadth-first search method to obtain the target augmented path;

[0096] S208: calculate the residual capacity of all boundaries on the target augmented path, and extract the minimum residual capacity of each boundary. Add the minimum residual capacity of each boundary to the corresponding boundary on the augmented path, and continuously calculate the augmented path and update the residual capacity of the edges in the residual network until the target augmented path cannot be found. The order of the multi-stage inverter in the rectifier bridge is obtained.

[0097] It should be noted that the boosted alternating current needs to be rectified by the rectifier bridge in the DC high voltage generator before it can be converted into direct current, so efficient regulation of the rectifier bridge circuit can also improve the stability of the output voltage; The rectifier bridge circuit usually has a multi-stage inverter to perform current diversion, but the multi-stage inverter in the rectifier bridge circuit of the DC high voltage generator cannot be regulated in stages and in the best sequence, resulting in errors in power factor control when the multi-stage inverter diverts current, making the output voltage and current unstable, reducing the stability of the high-voltage DC rectifier output, and making it difficult to ensure the quality of high-voltage DC use; Therefore, the present application first obtains the active power factor correction coefficient of each multi-stage inverter in the rectifier bridge circuit in the circuit layout diagram; The active power factor correction coefficient is the adjusted input current waveform of each multi-stage inverter in the historical regulation process, which is used to improve the power factor; Then introduce the Edmonds-Karp algorithm to calculate the active power factor correction coefficient of each multi-stage inverter in the circuit of the sub-layout area it is in, to analyze the phased regulation priority of each multi-stage inverter and make a sequence, which can improve the performance and order of the multi-stage inverter in the rectifier bridge circuit to convert alternating current, thereby ensuring the stability of the high-voltage DC output; Wherein, the Edmonds-Karp algorithm finds the augmented path and updates the flow continuously, and the algorithm can finally find the maximum flow. Since BFS is used to find the augmented path, it is guaranteed that the path found each time is the shortest, so that the algorithm is more accurate and reliable in calculating the phased regulation priority of the multi-stage inverter.

[0098] Further, in a preferred embodiment of the present application, the plurality of sets of actual temperature control parameters fed back by the temperature sensor in the DC high-voltage generator within a preset time period and the standard temperature control interval that should be met when the DC high-voltage generator outputs an actual steady-state voltage value are used to construct a radar chart, and the radar chart is analyzed to adjust the temperature control compensation gain of the DC high-voltage generator, as shown in FIG. 3, which specifically includes the following steps:

[0099] S302: A rated AC power supply is input to the DC high-voltage generator, the step-up transformer is controlled to step up the rated AC power by the first step-up control scheme or the second step-up control scheme, and then the stepped-up AC power supply is converted into DC output based on the sub-stage control sequence of all the multi-stage inverters in the rectifier bridge. At this time, a plurality of sets of actual temperature control parameters fed back by the temperature sensor in the DC high-voltage generator within a preset time period are obtained.

[0100] S304: The technical field to which the load test object belongs is obtained, the standard temperature control interval that should be met by the DC high-voltage generator when outputting different preset standard steady-state voltage values is obtained in the big data network based on the technical field, the actual steady-state voltage value of the feedback circuit in the DC high-voltage generator is obtained, and the Hamming distance between the actual steady-state voltage value and each preset standard steady-state voltage value is calculated.

[0101] S306: The preset standard steady-state voltage value corresponding to the minimum Hamming distance is extracted, and the standard temperature control interval that should be met when the DC high-voltage generator outputs the actual steady-state voltage value is determined based on the preset standard steady-state voltage value corresponding to the minimum Hamming distance.

[0102] S308: A radar chart is constructed, the standard temperature control interval that should be met when the DC high-voltage generator outputs the actual steady-state voltage value is introduced into the radar chart to obtain a standard temperature control radar chart, the plurality of sets of actual temperature control parameters fed back by the temperature sensor in the DC high-voltage generator within a preset time period are introduced into the standard temperature control radar chart for fitting, and the radar chart region that is overlapped by the standard temperature control radar chart and the actual temperature control radar chart is removed.

[0103] S310: If there is no actual temperature control radar chart in the remaining standard temperature control radar chart after removal, the area value of the remaining standard temperature control radar chart is obtained, and the temperature control compensation gain of the DC high-voltage generator is adjusted based on the area value.

[0104] S312: If there is an actual temperature control radar chart in the remaining standard temperature control radar chart after removal, the area deviation value between the remaining standard temperature control radar chart and the remaining actual temperature control radar chart is calculated, a hash algorithm is introduced to calculate a hash function between the area deviation value and the minimum Hamming distance, and the temperature control compensation gain of the DC high-voltage generator is adjusted based on the hash function.

[0105] It should be noted that the direct current high voltage generator will be affected by the environmental temperature factor in the actual operation process, and the temperature change may cause errors in the control parameters of the step-up transformer, the rectifier bridge circuit and other elements, thereby affecting the stability of the output voltage. The present application outputs high voltage direct current by executing the first step-up regulation scheme, the second step-up regulation scheme and the step-by-step regulation sequence of all multi-stage inverters in the rectifier bridge, and obtains a plurality of groups of actual temperature control parameters fed back by the temperature sensor in the direct current high voltage generator within a preset time period, a standard temperature control interval that the actual steady-state voltage value output by the direct current high voltage generator should conform to, and combines the standard temperature control interval and the actual temperature control parameters for area analysis in the radar chart, thereby generating accurate regulation parameters for temperature control compensation gain adjustment of the direct current high voltage generator, reducing the regulation error caused by temperature change of the direct current high voltage generator, and improving the stability of the output voltage.

[0106] In addition, the direct current high voltage generator regulation method based on intelligent feedback further includes the following steps:

[0107] Obtain voltage supply abnormal data of the direct current high voltage generator, and obtain a maximum voltage load threshold of a target load test object, generate a voltage regulation abnormal phrase based on the voltage supply abnormal data and the maximum voltage load threshold;

[0108] Obtain voltage regulation elements of the direct current high voltage generator, and obtain maximum voltage regulation reference and regulation characteristics of each voltage regulation element;

[0109] Introduce a least square algorithm to calculate a fitting function between the voltage regulation abnormal phrase and the maximum voltage regulation reference and regulation characteristics of each voltage regulation element, and determine an abnormal correlation degree of each voltage regulation element causing the voltage regulation abnormal phrase according to the fitting function;

[0110] Extract all voltage regulation elements corresponding to the maximum voltage regulation reference and regulation characteristics with an abnormal correlation degree greater than a preset abnormal correlation degree, and define them as suspected regulation failure elements;

[0111] Introduce a Markov chain Monte Carlo method, construct a probability sampling estimation model based on the Markov chain Monte Carlo method, obtain actual regulation parameter groups of each suspected regulation failure element within a preset time period, import the actual regulation parameter groups of each suspected regulation failure element within the preset time period into the probability sampling estimation model for probability estimation, and obtain a probability of regulation abnormality of each suspected regulation failure element;

[0112] If the probability of each suspected regulation fault element appearing regulation abnormality is greater than the preset regulation abnormality probability, the suspected regulation fault element corresponding to the preset regulation abnormality probability is marked for maintenance, and is uploaded to the maintenance log of the direct-current high-voltage generator.

[0113] It should be noted that each voltage regulation mechanism in the direct-current high-voltage generator has a certain service life. When the service life is reached or is affected by external environmental factors, the voltage regulation element will fail and be damaged, resulting in a large error in the voltage regulation of the direct-current high-voltage generator or even unable to continue normal work, affecting the user's experience of using high-voltage direct-current electricity. The regulation characteristics include regulation sensitivity, response speed and robustness. The present application can calculate, judge and locate the fault of the internal voltage regulation element according to the voltage supply abnormal data of the direct-current high-voltage generator, so as to perform fault marking to facilitate maintenance personnel to quickly maintain and manage the direct-current high-voltage generator, improve the maintenance rate and the user's experience, and at the same time, high-quality maintenance can be performed on the voltage regulation mechanism with high abnormal probability, reducing the failure frequency of the direct-current high-voltage generator and improving the reliability.

[0114] The second aspect of the present application provides a direct-current high-voltage generator regulation system based on intelligent feedback, which comprises a memory 41 and a processor 42. The memory 41 stores a direct-current high-voltage generator regulation method program based on intelligent feedback. When the program is executed by the processor 42, the following steps are implemented as shown in FIG. 4:

[0115] The output current flux value and the input voltage fluctuation factor of the load experimental object of the direct-current high-voltage generator at each target timestamp are obtained, and fuzzy control logic operation is performed based on the output current flux value and the input voltage fluctuation factor to obtain the disturbance amplitude of the voltage fluctuation state on the current flux change trend.

[0116] If the boost transformer can perform PID control technology by adjusting the variable ratio, the PID real-time adjustment parameter is calculated and individual crossover mutation operation is performed based on the fitness function to generate a first boost regulation scheme under the condition that the disturbance amplitude of the voltage fluctuation state on the current flux change trend is greater than the preset disturbance amplitude.

[0117] If the boost transformer cannot perform PID control technology by adjusting the variable ratio, a state feedback controller is constructed based on the state variable and the adjustment signal output amplitude of the current boost transformer, and a second boost regulation scheme is generated through the state feedback controller.

[0118] The power factor change rate of the load test object at a preset time node is acquired, if the power factor change rate is not in a preset power factor change range, then the active power factor correction coefficient of each multi-stage inverter in the circuit of the sub-layout region is acquired, the Edmonds-Karp algorithm is introduced to calculate the active power factor correction coefficient, and the sub-order control sequence of all multi-stage inverters in the rectifier bridge is obtained.

[0119] A plurality of groups of actual temperature control parameters fed back by the temperature sensor in the DC high-voltage generator in a preset time period are acquired, and a standard temperature control interval that should be met when the DC high-voltage generator outputs an actual steady-state voltage value is acquired, a radar chart is constructed, and the radar chart is analyzed to adjust the temperature control compensation gain of the DC high-voltage generator.

[0120] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited thereto, any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for regulating a direct current high voltage generator based on intelligent feedback, characterized in that, The method comprises the following steps: Obtaining the output current flux value and the input voltage fluctuation factor of the load test object of the direct-current high-voltage generator at each target timestamp, and performing fuzzy control logic operation based on the output current flux value and the input voltage fluctuation factor to obtain the disturbance amplitude of the voltage fluctuation state on the current flux change trend; If the step-up transformer can perform PID control technology by adjusting the transformation ratio, the PID real-time adjustment parameter is calculated and individual crossover mutation operation is performed based on the fitness function to generate a first step-up control scheme. If the step-up transformer cannot perform PID control technology by adjusting the transformation ratio, a state feedback controller is constructed based on the state variables and the adjustment signal output amplitude of the current step-up transformer, and a second step-up control scheme is generated through the state feedback controller. If the power factor change rate is not within the preset power factor change range, the active power factor correction coefficient of each multi-stage inverter in the sub-layout area circuit of the direct-current high-voltage generator is obtained, and the Edmonds-Karp algorithm is introduced to calculate the active power factor correction coefficient to obtain the hierarchical control sequence of all multi-stage inverters in the rectifier bridge. The actual temperature control parameters fed back by the temperature sensor in the direct-current high-voltage generator within a preset time period are obtained, and the standard temperature control interval that should be met when the actual steady-state voltage value of the direct-current high-voltage generator is output is obtained, a radar chart is constructed, and the radar chart is analyzed to adjust the temperature control compensation gain of the direct-current high-voltage generator.

2. The method of claim 1, wherein the method further comprises: The method comprises the following steps: Obtaining the output current flux value and the input voltage fluctuation factor of the load test object of the direct-current high-voltage generator at each target timestamp, and performing fuzzy control logic operation based on the output current flux value and the input voltage fluctuation factor to obtain the disturbance amplitude of the voltage fluctuation state on the current flux change trend, comprising the following steps: Obtaining the load test object of the direct-current high-voltage generator, and presetting a plurality of continuous target timestamps, and extracting the output current flux value and the input voltage fluctuation factor of the load test object at each target timestamp through test records; Based on the output current flux value and the input voltage fluctuation factor of the load test object at each target timestamp, the current flux change trend and the voltage fluctuation state are obtained, and N fuzzy control sets are obtained based on a big data network; The Gaussian membership function algorithm is introduced to calculate the membership function between the current flux change trend and each fuzzy control set, and the fuzzy control set corresponding to the maximum membership function between the current flux change trend and each fuzzy control set is screened out and defined as the first ideal fuzzy control set; The Gaussian membership function algorithm is introduced to calculate the membership function between the voltage fluctuation state and each fuzzy control set, and the fuzzy control set corresponding to the maximum membership function between the voltage fluctuation state and each fuzzy control set is screened out and defined as the second ideal fuzzy control set; The current flux change trend and the voltage fluctuation state are respectively correspondingly introduced into the first ideal fuzzy control set and the second ideal fuzzy control set for pairing mapping and quantization based on the maximum membership function, to generate a fuzzy current flux change trend control set and a fuzzy voltage fluctuation state control set; The fuzzy control logic algorithm is introduced, preset fuzzy rules in the fuzzy control logic algorithm are extracted, and the fuzzy control logic based on the preset fuzzy rules is used for fuzzy control reasoning operation on the fuzzy current flux change trend control set and the fuzzy voltage fluctuation state control set, to determine the output fuzzy control action; The output fuzzy control action is weighted and de-fuzzled by using the weighted average method, so that the output fuzzy control action is converted into an impact output value, and the disturbance amplitude of the voltage fluctuation state on the current flux change trend is determined based on the impact output value.

3. The method of claim 1, wherein the method further comprises: If the voltage fluctuation state has a disturbance amplitude greater than a preset disturbance amplitude on the current flux change trend, and the step-up transformer can perform PID control technology by adjusting the transformation ratio, the PID real-time adjustment parameter is calculated and individual crossover and mutation operations are performed based on the fitness function, to generate a first step-up control scheme, which specifically includes the following steps: If the voltage fluctuation state has a disturbance amplitude greater than a preset disturbance amplitude on the current flux change trend, the model specification information and control protocol of the step-up transformer in the direct current high-voltage generator are obtained; According to the model specification information and control protocol of the step-up transformer, it is determined whether the step-up transformer can perform PID control technology by adjusting the transformation ratio, and if so, the real-time transformation ratio under the current step-up transformer operating state is obtained; The desired voltage value required by the load test object under the condition that the step-up transformer can perform PID control technology by adjusting the transformation ratio is obtained, the desired transformation ratio is preset based on the desired voltage value, the error between the real-time transformation ratio and the desired transformation ratio is calculated, and the transformation ratio error threshold is obtained, at which time the PID control technology is performed and the PID control algorithm is introduced; Based on the transformation ratio error threshold, the output voltage adjustment operation is performed in the PID control algorithm, to obtain the real-time proportional control adjustment amount, the real-time integral control adjustment amount, and the real-time differential control adjustment amount, which are added together to obtain the PID real-time adjustment parameter; A plurality of groups of the PID real-time adjustment parameter groups in a preset time period are obtained, a hash algorithm is introduced to calculate the hash value of each group of the PID real-time adjustment parameter, the fitness function of each group of the PID real-time adjustment parameter is determined according to the hash value, M populations are randomly generated based on a plurality of groups of the PID real-time adjustment parameter groups, the individual with the highest fitness function in each population is extracted to obtain a plurality of target parents; The plurality of target parents are cross-operated and subjected to mutation processing one by one, to generate a plurality of new individuals, the new individual with the highest fitness function in the population is screened out through continuous iteration, the PID real-time adjustment parameter corresponding to the new individual with the best fitness function in the population is obtained, and is defined as the first step-up control scheme. The second voltage regulation scheme is outputted.

4. The method of claim 1, wherein the method further comprises: If the step of executing the PID control technology by adjusting the variable ratio is not applicable to the step-up transformer, a state feedback controller is constructed based on the state variable of the current step-up transformer and the output amplitude of the adjustment signal, and a second step-up regulation scheme is generated by the state feedback controller, which specifically includes the following steps: If the step of executing the PID control technology by adjusting the variable ratio is not applicable to the step-up transformer, a state feedback controller is constructed based on the state variable of the current step-up transformer and the output amplitude of the adjustment signal, and a second step-up regulation scheme is generated by the state feedback controller, which specifically includes the following steps: The circuit structure and element characteristics of the step-up transformer are introduced based on Kirchhoff's voltage law, the node current equation and the loop voltage equation are constructed, the state variable is introduced into the node current equation and the loop voltage equation for dynamic description, and the state equation is obtained. All interference factors that affect the output amplitude of the adjustment signal due to the state variable are obtained based on big data network, the information entropy of the output amplitude of the adjustment signal is calculated, the conditional entropy of the output amplitude of the adjustment signal after being divided under the state variable is calculated, the information gain index of the state variable to the output amplitude of the adjustment signal is obtained by subtracting the conditional entropy from the information entropy, and all interference factors that cause the output amplitude of the adjustment signal to change due to the state variable are linearly combined based on the information gain index to obtain a linear output equation. The ideal steady voltage value required by the load test object under the condition that the step-up transformer cannot execute the PID control technology by adjusting the variable ratio is obtained, a closed-loop control system model is constructed based on the state equation and the linear output equation, the pole placement method is introduced, and the ideal steady voltage value is used to preset the closed-loop pole position in the pole placement method, and the expected characteristic equation is analyzed according to the closed-loop pole position. The state feedback gain matrix is obtained by solving the expected characteristic equation, the state feedback gain matrix is introduced into the closed-loop control system model to calculate the control input adjustment and verification, and finally the state feedback controller is generated. The state feedback controller is applied to the actual control system of the step-up transformer to obtain the actual step-up regulation value, which is defined as the second step-up regulation scheme and outputted.

5. The method of claim 1, wherein the method further comprises: If the power factor change rate of the load test object at the preset time node is not within the preset power factor change range, the active power factor correction coefficient of each multi-stage inverter in the circuit of the sub-layout area is obtained, the Edmonds-Karp algorithm is introduced to calculate the active power factor correction coefficient, and the hierarchical regulation sequence of all multi-stage inverters in the rectifier bridge is obtained, which specifically includes the following steps: The historical power factor of the load test object at the preset time node is obtained, the power factor change rate is calculated based on the historical power factor, and it is judged whether the power factor change rate is within the preset power factor change range. The circuit layout diagram of the rectifier bridge in the direct current high voltage generator is obtained. The circuit layout diagram is divided into several sub-layout areas, and all multi-stage inverters in each sub-layout area are identified and marked, the active power factor correction coefficient of each multi-stage inverter in the circuit of the sub-layout area is obtained, and the hierarchical regulation sequence of all multi-stage inverters in the rectifier bridge is obtained. The Edmonds-Karp algorithm is introduced to calculate the active power factor correction coefficient of each multi-stage inverter in the circuit of the sub-layout region where the inverter is located, to initialize the flow of each boundary in the flow network, to construct a residual network, and to find a path with residual capacity from the source node to the sink node of the residual network based on the breadth-first search method to obtain a target augmented path; The residual capacity of all boundaries on the target augmented path is calculated, and the minimum residual capacity of each boundary is extracted. The minimum residual capacity of each boundary is added to the corresponding boundary on the augmented path. The augmented path is continuously calculated and the residual capacity of the edges in the residual network is updated until no target augmented path can be found. The hierarchical control sequence of all multi-stage inverters in the rectifier bridge is obtained.

6. The method of claim 1, wherein the method further comprises: The actual temperature control parameters fed back by the temperature sensor in the DC high-voltage generator within a preset time period are obtained, and the standard temperature control interval that should be met when the DC high-voltage generator outputs an actual steady-state voltage value is obtained, a radar chart is constructed, and the radar chart is analyzed to adjust the temperature control compensation gain of the DC high-voltage generator. The specific steps include the following steps: The rated AC power supply is input into the DC high-voltage generator, and the first or second step-up control scheme is used to control the step-up transformer to step up the rated AC power. Then, based on the hierarchical control sequence of all multi-stage inverters in the rectifier bridge, the stepped-up AC power supply is converted into DC output. At this time, the actual temperature control parameters fed back by the temperature sensor in the DC high-voltage generator within a preset time period are obtained. The technical field to which the load test object belongs is obtained, the standard temperature control interval that should be met by the DC high-voltage generator when outputting different preset standard steady-state voltage values is obtained in the big data network based on the technical field, the actual steady-state voltage value of the feedback circuit in the DC high-voltage generator is obtained, and the Hamming distance between the actual steady-state voltage value and each preset standard steady-state voltage value is calculated. The preset standard steady-state voltage value corresponding to the minimum Hamming distance is extracted, and the standard temperature control interval that should be met when the DC high-voltage generator outputs the actual steady-state voltage value is determined based on the preset standard steady-state voltage value corresponding to the minimum Hamming distance. A radar chart is constructed, the standard temperature control interval that should be met when the DC high-voltage generator outputs the actual steady-state voltage value is introduced into the radar chart to obtain a standard temperature control radar chart, and the multiple sets of actual temperature control parameters fed back by the temperature sensor in the DC high-voltage generator within a preset time period are introduced into the standard temperature control radar chart for fitting, and the radar chart region that is overlapped by the standard temperature control radar chart and the actual temperature control radar chart is removed. If there is no actual temperature control radar chart in the remaining standard temperature control radar chart after removal, the area value of the remaining standard temperature control radar chart is obtained, and the temperature control compensation gain of the DC high-voltage generator is adjusted based on the area value. If there is an actual temperature control radar chart in the remaining standard temperature control radar chart after removal, the area deviation value between the remaining standard temperature control radar chart and the remaining actual temperature control radar chart is calculated, a hash algorithm is introduced to calculate the hash function between the area deviation value and the minimum Hamming distance, and the temperature control compensation gain of the DC high-voltage generator is adjusted based on the hash function. The number of pairs of direct current high voltage generator temperature control compensation gain adjustment.

7. A smart feedback based direct current high voltage generator regulating system, characterized in that, The intelligent feedback-based DC high voltage generator control system includes a memory and a processor, the memory stores an intelligent feedback-based DC high voltage generator control method program, and the processor executes the program to implement the following steps: Obtain the output current flux value and input voltage fluctuation factor of the load test object of the DC high voltage generator at each target timestamp, perform fuzzy control logic operation based on the output current flux value and input voltage fluctuation factor, and obtain the disturbance amplitude of the voltage fluctuation state to the current flux change trend; If the step-up transformer can perform PID control technology by adjusting the variable ratio, calculate the PID real-time adjustment parameter and perform individual crossover mutation operation based on the fitness function to generate a first step-up control scheme; If the step-up transformer cannot perform PID control technology by adjusting the variable ratio, construct a state feedback controller based on the state variables and adjustment signal output amplitude of the current step-up transformer, and generate a second step-up control scheme through the state feedback controller; Obtain the power factor change rate of the load test object at the preset time node, if the power factor change rate is not within the preset power factor change range, obtain the active power factor correction coefficient of each multi-stage inverter in the sub-layout area circuit of the DC high voltage generator, introduce the Edmonds-Karp algorithm to calculate the active power factor correction coefficient, and obtain the hierarchical control sequence of all multi-stage inverters in the rectifier bridge. Obtain the actual temperature control parameters fed back by the temperature sensor in the DC high voltage generator within the preset time period, and obtain the standard temperature control interval that should be met when the DC high voltage generator outputs the actual steady-state voltage value, construct a radar chart, and analyze the radar chart to adjust the temperature control compensation gain of the DC high voltage generator.

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