A method for calibrating and measuring high-frequency cavity voltage of a medical cyclotron

Abstract

The present application relates to the technical field of voltage measurement and calibration, and specifically to a method for calibrating the high-frequency cavity voltage of a medical cyclotron. The method comprises: comparing the differences in all peaks and all phases between the I cavity voltage signal and the R cavity voltage signal to determine the voltage difference of the high-frequency cavity voltage at each moment, and determining a first disturbance degree in combination with the load anomaly; determining a second disturbance degree of the high-frequency cavity voltage at each moment based on the spectral oscillation degree and voltage phase anomaly of the high-frequency cavity voltage at each moment; and determining a step size factor adjustment coefficient based on the first and second disturbance degrees to calibrate the high-frequency cavity voltage of the current medical cyclotron. The present application solves the problem of calibration error amplification caused by excessive step size under strong interference, thereby improving the calibration accuracy of the high-frequency cavity voltage of the medical cyclotron.

Description

Technical Field

[0001] The present application relates to the technical field of voltage measurement and calibration, and in particular to a method for calibrating and measuring the high-frequency cavity voltage of a medical cyclotron. Background Art

[0002] A medical cyclotron, a type of particle accelerator, utilizes the combined effects of magnetic and electric fields to induce charged particles into a cyclotron motion, repeatedly accelerating them during this motion through a high-frequency electric field. Primarily used to produce positron-emitting radionuclides, it is a crucial piece of equipment in nuclear medicine. The high-frequency cavity of a medical cyclotron consists of a push-pull resonant cavity composed of symmetrical I and R cavities, with an accelerating electric field formed between the electrodes. Calibration and measurement of the high-frequency cavity voltage is a core technology for ensuring particle acceleration accuracy and device stability. It directly determines the particle acceleration energy gain and influences beam intensity and targeting accuracy.

[0003] During the operation of a medical cyclotron, the high-frequency cavity is in a resonant state. The beam intensity and temperature vary continuously over time, causing the cavity's resonant frequency to shift. The LMS adaptive filtering algorithm is used to calibrate the high-frequency cavity voltage of a medical cyclotron with high real-time and adaptability. The convergence speed of the LMS adaptive filtering algorithm is determined by the step size factor. A higher step size factor allows for rapid convergence, ensuring real-time high-frequency cavity voltage measurement. However, due to the influence of high-intensity beam current and thermal and temperature interference, a higher step size factor can further amplify the calibration offset error of the high-frequency cavity voltage, resulting in reduced calibration accuracy. Summary of the Invention

[0004] In order to solve the above technical problems, the present application provides a high-frequency cavity voltage calibration and measurement method for a medical cyclotron to solve the existing problems.

[0005] The present invention relates to a method for calibrating and measuring the high-frequency cavity voltage of a medical cyclotron using the following technical solutions:

[0006] One embodiment of the present application provides a method for calibrating and measuring the high-frequency cavity voltage of a medical cyclotron, the method comprising the following steps:

[0007] Acquire the I cavity voltage signal and the R cavity voltage signal in the high frequency cavity of the medical cyclotron within a preset time period before each moment, as well as the phases of the I cavity voltage signal at all moments and the phases of the R cavity voltage signal at all moments;

[0008] Each peak in the voltage signal and the trough closest to it are combined into associated peaks and valleys, the peak-to-valley deviations between each pair of associated peaks and valleys are calculated, the rate of change of the peak-to-valley deviations between each pair of associated peaks and valleys in the I-cavity voltage signal is analyzed, and the attenuation rate of each pair of associated peaks and valleys in the I-cavity voltage signal is determined; based on the discrete degree of the attenuation rate of all pairs of associated peaks and valleys in the I-cavity voltage signal, and analyzing the difference in peak-to-valley deviations between each pair of associated peaks and valleys and its adjacent pair of associated peaks and valleys in the R-cavity voltage signal, the load anomaly degree of the high-frequency cavity voltage at each moment is determined; the differences in all peaks and all phases between the I-cavity voltage signal and the R-cavity voltage signal are compared to determine the voltage difference degree of the high-frequency cavity voltage at each moment, and combined with the load anomaly degree, the first disturbance degree of the high-frequency cavity voltage at each moment is determined;

[0009] The difference in voltage amplitude between the I cavity voltage signal and the R cavity voltage signal, as well as the degree of discreteness of all phases in the R cavity voltage signal, are measured to determine the voltage phase anomaly of the high-frequency cavity voltage at each moment; the energy difference between all modal components in the I cavity voltage signal and the R cavity voltage signal are analyzed respectively, and the number of all modal components in the I cavity voltage signal and the R cavity voltage signal are counted to determine the spectral oscillation degree of the high-frequency cavity voltage at each moment, and the second disturbance degree of the high-frequency cavity voltage at each moment is determined in combination with the voltage phase anomaly;

[0010] Based on the first disturbance degree and the second disturbance degree, a step factor adjustment coefficient is determined to adjust the step factor of the LMS adaptive filtering algorithm for calibrating the current high-frequency cavity voltage.

[0011] Preferably, the attenuation rate of each pair of associated peaks and valleys in the I-cavity voltage signal is the product of the peak-to-valley deviation between each pair of associated peaks and valleys in the I-cavity voltage signal and the time interval between the peaks and valleys.

[0012] Preferably, the expression for the load abnormality degree of the high-frequency cavity voltage at each moment is: Where, Indicates the load abnormality of the high-frequency cavity voltage at time i; It represents the result of the accumulation of the differences in peak-to-valley deviations between all adjacent pairs of associated peaks and valleys in the R cavity voltage signal at time i; represents the variance of the decay rate of all pairs of associated peaks and valleys in the voltage signal of cavity I at time i; exp( ) represents an exponential function with a natural constant as the base.

[0013] Preferably, the method for determining the voltage difference of the high-frequency cavity voltage at each moment is:

[0014] Within a preset time period before each moment, all peaks of the I cavity voltage signal and the R cavity voltage signal are arranged in time sequence to form peak sequences of the I cavity voltage signal and the R cavity voltage signal, respectively, and the difference in the peak sequences between the I cavity voltage signal and the R cavity voltage signal is recorded as the peak difference;

[0015] Calculate the sine values ​​of the phase differences between the I cavity voltage signal and the R cavity voltage signal at all times, and calculate the sum of the sine values ​​at all times, which is recorded as the phase difference sum;

[0016] The ratio of the peak difference to the phase difference is taken as the voltage difference of the high-frequency cavity voltage at each moment.

[0017] Preferably, the first disturbance degree of the high-frequency cavity voltage at each moment is a product of the load abnormality degree and the voltage difference degree of the high-frequency cavity voltage at each moment.

[0018] Preferably, the method for determining the voltage phase anomaly of the high-frequency cavity voltage at each moment is:

[0019] Calculate the Hurst exponent of the voltage amplitude difference between the I cavity voltage signal and the R cavity voltage signal at all times;

[0020] The Hurst exponent is multiplied by the discrete degree of the phase at all moments in the R cavity voltage signal to obtain the voltage phase abnormality of the high-frequency cavity voltage at each moment.

[0021] Preferably, the method for determining the spectral oscillation degree of the high-frequency cavity voltage at each moment is:

[0022] All energy values ​​in each modal component in the I cavity voltage signal and the R cavity voltage signal are respectively combined into an energy sequence of each modal component, and the cumulative sum of the energy sequence differences between all modal components in the I cavity voltage signal and the cumulative sum of the energy sequence differences between all modal components in the R cavity voltage signal are respectively calculated, and recorded as the first sum value and the second sum value, respectively. The result of adding the first sum value and the second sum value is used as the energy difference value of the high-frequency cavity voltage signal;

[0023] The sum of the total number of modal components in the I cavity voltage signal and the total number of modal components in the R cavity voltage signal is calculated, and the ratio of the sum to the energy difference value is used as the spectral oscillation degree of the high-frequency cavity voltage at each moment.

[0024] Preferably, the second disturbance degree of the high-frequency cavity voltage at each moment is a result of forward fusion of the voltage phase anomaly degree and the spectrum oscillation degree of the high-frequency cavity voltage at each moment.

[0025] Preferably, the step size factor adjustment coefficient is determined by:

[0026] The first disturbance degree and the second disturbance degree of the high-frequency cavity voltage at all moments in a preset period before the current moment are respectively used as inputs of the entropy weight method, and the entropy weight of the first disturbance degree and the entropy weight of the second disturbance degree at the current moment are output;

[0027] Calculate the product of the first disturbance degree of the high-frequency cavity voltage at the current moment and its entropy weight, and the product of the second disturbance degree and its entropy weight, respectively, and record them as the first product and the second product;

[0028] Calculate the sum of the first product and the second product, and the sum of the entropy weight of the first disturbance degree and the entropy weight of the second disturbance degree, and record them as the third sum and the fourth sum respectively. Take the ratio of the third sum to the fourth sum as the comprehensive index, and take the inverse of the comprehensive index as the step factor adjustment coefficient at the current moment.

[0029] Preferably, the step size factor of the LMS adaptive filtering algorithm is adjusted to calibrate the current high-frequency cavity voltage, including:

[0030] The I cavity voltage signal and the R cavity voltage signal of the high-frequency cavity within the preset time length before the current moment are respectively used as the input of the adaptive filtering algorithm, and the result of multiplying the preset step size factor in the adaptive filtering algorithm by the step size factor adjustment coefficient at the current moment is used as the step size factor in the current adaptive filtering algorithm, and the filtered I cavity voltage signal and the R cavity voltage signal are output.

[0031] This application has at least the following beneficial effects:

[0032] This application quantifies the load anomaly and structural symmetry destruction caused by beam interference by analyzing the peak-to-valley attenuation, adjacent peak-to-valley difference and peak-to-peak phase contrast of the I and R cavity voltage signals, and generates a first interference degree. This indicator can reflect the degree of interference in real time and provide a basis for the dynamic adjustment of the step size factor of the adaptive filtering algorithm, thereby suppressing noise amplification under strong interference and improving the calibration accuracy of the high-frequency cavity voltage; further, this application quantifies the impact of heat-induced high-frequency cavity structural deformation and performance degradation on the voltage signal by analyzing the amplitude difference, phase discreteness and spectral modal characteristics of the I and R cavity voltages, constructs a second interference degree, and conducts a more accurate assessment of the thermal interference condition of the medical cyclotron, which helps to optimize the adaptive filtering parameters to improve the calibration accuracy of the high-frequency cavity voltage; finally, this application dynamically adjusts the LMS filter step size factor based on the first interference degree and the second interference degree, effectively avoiding the calibration error amplification caused by excessive step size under strong interference, and significantly improving the calibration accuracy of the high-frequency cavity voltage of the medical cyclotron. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0034] Figure 1 A flowchart of a method for calibrating and measuring the high-frequency cavity voltage of a medical cyclotron provided in one embodiment of the present application;

[0035] Figure 2 A schematic diagram of the step factor adjustment coefficient extraction process provided in one embodiment of the present application. DETAILED DESCRIPTION

[0036] To further illustrate the technical means and effectiveness of this application to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effectiveness of a method for calibrating and measuring the high-frequency cavity voltage of a medical cyclotron proposed in this application. In the following description, references to different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0037] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0038] The specific scheme of the high-frequency cavity voltage calibration and measurement method for a medical cyclotron provided by the present application is described in detail below with reference to the accompanying drawings.

[0039] An embodiment of the present application provides a method for calibrating and measuring the high-frequency cavity voltage of a medical cyclotron. Specifically, the following method for calibrating and measuring the high-frequency cavity voltage of a medical cyclotron is provided. Figure 1 , the method comprises the following steps:

[0040] Step S1: Acquire the I cavity voltage signal and the R cavity voltage signal in the high frequency cavity of the medical cyclotron within a preset time period before each moment, as well as the phases of the I cavity voltage signal at all moments and the phases of the R cavity voltage signal at all moments.

[0041] A high-speed data acquisition system (DAQ) is used to synchronously acquire the dual-channel voltage signals of the I and R cavities in the high-frequency cavity of the medical cyclotron. To meet the requirements of the Nyquist sampling theorem and avoid aliasing of voltage signals, the sampling frequency of the high-speed data acquisition system is at least twice the voltage of the high-frequency cavity of the medical cyclotron. The radio frequency synchronization signal provided by the medical cyclotron main control system is used as the trigger source for the acquisition of the high-frequency cavity I and R cavity voltage signals, and the ADC sampling clock is locked to ensure that the data is strictly aligned with the acceleration cycle of the medical cyclotron and eliminate the phase error caused by clock drift. The voltage signals of the I and R cavities in the high-frequency cavity of the medical cyclotron are acquired within a preset time period before each moment. The acquired high-frequency cavity I and R cavity voltage signals are directly connected to the radio frequency phase detector to obtain the phase of the high-frequency cavity I and R cavity voltage signals, respectively.

[0042] It should be noted that the value of the preset time length is set manually. In this embodiment, the value of the preset time length is 5s. In actual application, as other implementation methods, the implementer can also set it by himself based on the specific situation. This embodiment does not impose any special restrictions.

[0043] Furthermore, in order to prevent the above-mentioned collected data from being disturbed by the external environment, resulting in missing information or different dimensions, which may affect subsequent analysis, as a specific implementation method, this embodiment uses the median filling method and the z-score normalization method to fill in missing values ​​and normalize the voltage signals of the medical cyclotron high-frequency cavity I cavity and R cavity in turn. In actual application, as other implementation methods, the implementer may also adopt other missing value filling methods and normalization processing methods. Regarding the selection of missing value filling methods and normalization processing methods, this embodiment does not impose any special restrictions.

[0044] Among them, the principle of using the median filling method to fill missing data and the principle of using the z-score standardization method to normalize data are both well-known technologies, and the specific filling process and normalization process are not repeated here.

[0045] Step S2: Each peak in the voltage signal and the trough closest to it are combined into associated peaks and valleys, the peak-to-valley deviations between each pair of associated peaks and valleys are calculated, the rate of change of the peak-to-valley deviations between each pair of associated peaks and valleys in the I-cavity voltage signal is analyzed, and the attenuation rate of each pair of associated peaks and valleys in the I-cavity voltage signal is determined; based on the discrete degree of the attenuation rate of all pairs of associated peaks and valleys in the I-cavity voltage signal, and analyzing the difference in peak-to-valley deviations between each pair of associated peaks and valleys and their adjacent pairs of associated peaks and valleys in the R-cavity voltage signal, the load anomaly degree of the high-frequency cavity voltage at each moment is determined; the differences in all peaks and all phases between the I-cavity voltage signal and the R-cavity voltage signal are compared to determine the voltage difference degree of the high-frequency cavity voltage at each moment, and combined with the load anomaly degree, the first disturbance degree of the high-frequency cavity voltage at each moment is determined.

[0046] During the operation of a medical cyclotron, the high-frequency cavity is in a resonant state. High-intensity beam currents affect the cavity's load characteristics, causing changes in the cavity's equivalent capacitance and inductance parameters, leading to a resonant frequency drift. This drift disrupts the matching between the cyclotron's high-frequency power source and the cavity. High-intensity beam currents reduce the cavity's input power, causing the cavity voltage amplitude to decay. The excitation voltage provided to maintain the cavity pressure causes significant fluctuations in the cavity voltage. Furthermore, the cavity load characteristics caused by high-intensity beam currents can disrupt the symmetry of the push-pull resonant cavity structure.

[0047] Specifically, during medical cyclotron operation, when the resonant frequency drift caused by high-intensity beam currents becomes more severe, the high-frequency cavity (I) responsible for energy transfer is affected by the high-order electromagnetic modes excited by the strong beam. This, through the cavity coupling structure, further interferes with the independence of the I / R cavities. Sideband noise in the I cavity couples to the R cavity, significantly increasing the R cavity voltage ripple. Phase jitter in the R cavity is then transmitted to the I cavity through the feedback loop. The beam loading effect also destabilizes the decay rate of the I cavity voltage signal. Furthermore, the high-intensity beam-induced high-frequency cavity loading disrupts the symmetry of the resonant cavity structure, further increasing the phase difference between the I / R cavity voltage signals and the inconsistent response of the I / R cavity voltage signals. In this case, the step size factor of the LMS adaptive filtering algorithm should be reduced to prevent the high-intensity beam interference from severely exacerbating the noise amplification of the LMS adaptive filtering algorithm.

[0048] Based on the above analysis, this embodiment determines the attenuation rate of each pair of associated peaks and valleys in the I-cavity voltage signal by analyzing the rate of change of the peak-to-valley deviation between each pair of associated peaks and valleys in the I-cavity voltage signal; based on the discrete degree of the attenuation rate of all pairs of associated peaks and valleys in the I-cavity voltage signal, and analyzing the difference in peak-to-valley deviation between each pair of associated peaks and valleys and their adjacent pairs of associated peaks and valleys in the R-cavity voltage signal, the load anomaly of the high-frequency cavity voltage at each moment is determined; the difference in all peaks and all phases between the I-cavity voltage signal and the R-cavity voltage signal is compared to determine the voltage difference of the high-frequency cavity voltage at each moment, and combined with the load anomaly, the first disturbance degree of the high-frequency cavity voltage at each moment is determined, which is used to characterize the degree of abnormality of the high-frequency cavity voltage caused by the high-intensity beam during the operation of the medical cyclotron, specifically:

[0049] (1) In this embodiment, each peak in the I cavity voltage signal and the R cavity voltage signal and its nearest trough are combined into associated peaks and troughs, and the difference between the peak value and the trough value between each pair of associated peaks and troughs is calculated and recorded as the peak-to-valley deviation between each pair of associated peaks and troughs.

[0050] (2) Furthermore, this embodiment determines the attenuation rate of each pair of associated peaks and valleys in the I-cavity voltage signal by analyzing the rate of change of the peak-to-valley deviation between each pair of associated peaks and valleys in the I-cavity voltage signal, specifically:

[0051] In this embodiment, the peak-to-valley deviation between each pair of related peaks and valleys in the I-cavity voltage signal is divided by the time interval between the peaks and valleys to be used as the attenuation rate of each pair of related peaks and valleys in the I-cavity voltage signal.

[0052] (3) Furthermore, this embodiment determines the load abnormality of the high-frequency cavity voltage at each moment based on the discrete degree of attenuation rate of all pairs of associated peaks and valleys in the I cavity voltage signal and the difference in peak-valley deviation between each pair of associated peaks and valleys and its adjacent pair of associated peaks and valleys in the R cavity voltage signal. Specifically,

[0053] As an implementation method, in this embodiment, the load abnormality degree of the high frequency cavity voltage at time i is The expression is: Where, It represents the result of the accumulation of the differences in peak-to-valley deviations between all adjacent pairs of associated peaks and valleys in the R cavity voltage signal at time i; represents the variance of the decay rate of all pairs of associated peaks and valleys in the voltage signal of cavity I at time i; exp( ) represents an exponential function with a natural constant as the base.

[0054] It should be noted that, in this embodiment, when calculating the cumulative result of the differences in peak-to-valley deviations between all adjacent pairs of associated peaks and valleys in the R-cavity voltage signal at time i, what is calculated is the deviation of the peak-to-valley deviations between each pair of associated peaks and valleys and the previous pair of associated peaks and valleys adjacent in time sequence. In particular, for the first pair of associated peaks and valleys in time sequence in the R-cavity voltage signal, the difference between the peak-to-valley deviation of the first pair of associated peaks and valleys in the R-cavity voltage signal and the average of the peak-to-valley deviations of all pairs of associated peaks and valleys is added to the calculation process of the peak-to-valley deviation difference value.

[0055] It should be noted that there are many methods for measuring the differences between data. In this embodiment, the absolute value of the difference between the peak-to-valley deviations of adjacent pairs of associated peaks and valleys is used as the difference between the peak-to-valley deviations of adjacent pairs of associated peaks and valleys. In actual application, as other implementation methods, the implementer may also adopt other methods for measuring the differences between data, such as the square or ratio of the difference, based on the specific circumstances. This embodiment does not impose any special restrictions on the selection of methods for measuring the differences between data.

[0056] According to the load anomaly of the high-frequency cavity voltage at each moment, it can be understood that if the cumulative difference between the peak-to-valley deviations of all adjacent pairs of associated peaks and valleys in the R cavity voltage signal at moment i is greater, it means that the amplitude fluctuation of the R cavity voltage signal in adjacent cycles is greater, indicating that the peak-to-valley deviation of the R cavity voltage signal fluctuates greatly and is very unstable. This is because the R cavity voltage signal has received stronger interference, such as sideband noise coupling, which makes the waveform of the R cavity voltage signal unstable, and the corresponding load anomaly is greater; at the same time, if the variance of the attenuation rate of all pairs of associated peaks and valleys in the I cavity voltage signal at moment i is greater, it means that the attenuation rate of the I cavity voltage signal varies greatly at different moments, reflecting that the more serious the instability of the attenuation rate of the I cavity voltage signal, the more serious the interference fluctuation on the load characteristics of the I cavity itself, and the greater the corresponding load anomaly;

[0057] On the contrary, if the cumulative difference of the peak-to-valley deviations between all adjacent pairs of associated peaks and valleys in the R-cavity voltage signal at time i is smaller, it means that the degree of change in the amplitude fluctuation of the R-cavity voltage signal in adjacent cycles is smaller, indicating that the fluctuation of the peak-to-valley deviation of the R-cavity voltage signal is very small and relatively stable, which means that the R-cavity voltage signal is subject to weak interference, its waveform is relatively smooth, and the corresponding load anomaly is smaller; at the same time, if the variance of the attenuation rate of all pairs of associated peaks and valleys in the I-cavity voltage signal at time i is smaller, it means that the attenuation rate of the I-cavity voltage signal is very small at different times, reflecting that the attenuation rate of the I-cavity voltage signal is very stable, indicating that the interference fluctuation of the load characteristics of the I-cavity itself is smaller, and the corresponding load anomaly is smaller.

[0058] (4) Furthermore, this embodiment determines the voltage difference of the high-frequency cavity voltage at each moment by comparing the differences in all peaks and all phases between the I cavity voltage signal and the R cavity voltage signal, specifically:

[0059] Within a preset time period before each moment, all peaks of the I cavity voltage signal and the R cavity voltage signal are arranged in time sequence to form peak sequences of the I cavity voltage signal and the R cavity voltage signal, respectively, and the difference in the peak sequences between the I cavity voltage signal and the R cavity voltage signal is recorded as the peak difference;

[0060] It should be noted that there are many methods for measuring the differences between sequences. In this embodiment, the JS divergence of the peak sequence between the I-cavity voltage signal and the R-cavity voltage signal is used as the difference between the peak sequences between the I-cavity voltage signal and the R-cavity voltage signal. In actual application, as other implementation methods, the implementer may also select Euclidean distance or other methods for measuring the differences between sequences based on specific circumstances. This embodiment does not impose any special restrictions on the selection of methods for measuring the differences between sequences.

[0061] The calculation method of JS divergence is a well-known technology, and its specific calculation process will not be repeated here.

[0062] Further, the sine values ​​of the phase differences between the I cavity voltage signal and the R cavity voltage signal at all times are calculated, and the sum of the sine values ​​at all times is calculated and recorded as the phase difference sum;

[0063] Furthermore, the ratio of the peak difference to the phase difference is used as the voltage difference of the high-frequency cavity voltage at each moment.

[0064] According to the voltage difference of the high-frequency cavity voltage at each moment, it can be understood that the greater the difference in the peak sequence between the I cavity voltage signal and the R cavity voltage signal, that is, the greater the peak difference, the greater the difference in the time distribution of the peak appearance of the I cavity voltage signal and the R cavity voltage signal, that is, the greater the difference in the time distribution of the peak appearance of the two cavity voltage signals, the more dissimilar, which usually means that the symmetric structure of the resonant cavity is destroyed, and the corresponding voltage difference is greater; at the same time, if the sine value of the phase difference value at all moments in the I cavity voltage signal and the R cavity voltage signal is larger, it means that the phase difference between the high-frequency cavity I cavity and R cavity voltage signals is larger, indicating that the phase angle orthogonality of the I cavity and R cavity voltage signals is more unstable, which means that the difference in the time and phase relationship between the I cavity and R cavity voltage signals is greater, and the corresponding voltage difference is larger;

[0065] On the contrary, if the difference in the peak sequence between the I cavity voltage signal and the R cavity voltage signal is smaller, that is, the peak difference is smaller, it means that the difference in the time distribution of the peak appearance of the I cavity voltage signal and the R cavity voltage signal is smaller, that is, the time distribution of the peak appearance of the two cavity voltage signals is more similar, which usually means that the symmetric structure of the resonant cavity is better maintained, and the corresponding voltage difference is smaller; at the same time, if the sine value of the phase difference between the I cavity voltage signal and the R cavity voltage signal at all times is smaller, it means that the phase difference between the high-frequency cavity I cavity and the R cavity voltage signal is smaller, indicating that the phase angle orthogonality of the I cavity and R cavity voltage signals is more stable, which means that the difference in the time and phase relationship between the I cavity and R cavity voltage signals is smaller, and the corresponding voltage difference is smaller.

[0066] (5) Furthermore, this embodiment determines the first disturbance degree of the high-frequency cavity voltage at each moment by comprehensively considering the voltage difference of the high-frequency cavity voltage at each moment and combining the load abnormality, specifically:

[0067] As a specific implementation, in this embodiment, the result of multiplying the load abnormality degree and the voltage difference degree of the high-frequency cavity voltage at each moment is used as the first disturbance degree of the high-frequency cavity voltage at each moment.

[0068] According to the first disturbance degree of the high-frequency cavity voltage at each moment, it can be understood that the first disturbance degree reflects the overall abnormality degree of the high-frequency cavity voltage signal caused by the high-intensity beam interference; if the load abnormality degree of the high-frequency cavity voltage at the current moment is greater, it means that the load characteristic abnormality of the high-frequency cavity voltage signal caused by the high-intensity beam is more serious, the overall beam interference condition is worse, and the corresponding first disturbance degree is greater; at the same time, if the voltage abnormality degree of the high-frequency cavity voltage at the current moment is greater, it means that the symmetry of the resonant cavity structure caused by the high-intensity beam is seriously destroyed, and the overall beam interference condition is worse. At this time, the step size factor of the adaptive filtering algorithm should be reduced to avoid the high-intensity beam interference from seriously aggravating the noise amplification phenomenon, resulting in the measurement calibration of the high-frequency cavity voltage.

[0069] On the contrary, if the load anomaly of the high-frequency cavity voltage at the current moment is smaller, it means that the load characteristic anomaly of the high-frequency cavity voltage signal caused by the high-intensity beam is milder, the overall beam interference condition is better, and the corresponding first disturbance is smaller; at the same time, if the voltage anomaly of the high-frequency cavity voltage at the current moment is smaller, it means that the degree of symmetry destruction of the resonant cavity structure caused by the high-intensity beam in the high-frequency cavity voltage signal is milder, the overall beam interference condition is better, and the corresponding first disturbance is smaller.

[0070] Thus, this embodiment quantifies the load anomaly and structural symmetry destruction caused by beam interference by analyzing the peak-to-valley attenuation, adjacent peak-to-valley differences, and peak-to-peak phase contrast of the I and R cavity voltage signals, and generates a first disturbance index. This index can reflect the degree of interference in real time and provide a basis for the dynamic adjustment of the step size factor of the adaptive filtering algorithm, thereby suppressing noise amplification under strong interference and improving the calibration accuracy of the high-frequency cavity voltage.

[0071] Step S3: Measure the difference in voltage amplitude between the I cavity voltage signal and the R cavity voltage signal, as well as the degree of discreteness of all phases in the R cavity voltage signal, to determine the voltage phase anomaly of the high-frequency cavity voltage at each moment; respectively analyze the energy difference between all modal components in the I cavity voltage signal and the R cavity voltage signal, and count the number of all modal components in the I cavity voltage signal and the R cavity voltage signal to determine the spectral oscillation degree of the high-frequency cavity voltage at each moment, and combine the voltage phase anomaly to determine the second disturbance degree of the high-frequency cavity voltage at each moment.

[0072] Evaluating the disturbance state of a medical cyclotron during operation based solely on the first disturbance of the high-frequency cavity voltage still has certain drawbacks. This approach fails to consider the significant heat generated by the electron beam impacting the target, which increases the temperature of the high-frequency cavity resistors. The thermal expansion and contraction of the high-frequency cavity resistors in a medical cyclotron can cause microscopic changes in the cavity, disrupting the original resonant frequency of the cavity. This temperature increase can also reduce the quality factor of the medical cyclotron cavity, increasing energy loss and weakening beam stability.

[0073] Specifically, during the operation of a medical cyclotron, when the heat generated by the electron beam striking the target material causes the high-frequency cavity's resistor components to expand and contract, causing more severe damage to the cavity's resonant frequency, the greater the impact of this thermal expansion and deformation on the mechanical symmetry of the medical cyclotron's high-frequency cavity. This increases the difference in distributed capacitance between the I and R cavities, the voltage amplitude difference between the two cavities continues to grow, and the phase jump of the R cavity, which is responsible for phase regulation, becomes more pronounced. Simultaneously, temperature gradient changes cause the local resonance point of the high-frequency cavity to drift significantly, leading to a significant superposition of multimodal oscillations and an increase in the spectral entropy of the two cavities. In this case, the step size factor of the adaptive filtering algorithm should be compressed to suppress noise amplification and improve adaptive filtering accuracy.

[0074] Based on the above analysis, this embodiment determines the voltage phase anomaly of the high-frequency cavity voltage at each moment by measuring the difference in voltage amplitude between the I cavity voltage signal and the R cavity voltage signal, as well as the degree of discreteness of all phases in the R cavity voltage signal; analyzes the energy difference between all modal components in the I cavity voltage signal and the R cavity voltage signal respectively, and counts the number of all modal components in the I cavity voltage signal and the R cavity voltage signal to determine the spectral oscillation degree of the high-frequency cavity voltage at each moment. Combined with the voltage phase anomaly, the second disturbance degree of the high-frequency cavity voltage at each moment is determined to characterize the disturbance of the high-frequency cavity voltage caused by heat during the operation of the medical cyclotron. The specific process is as follows:

[0075] (1) This embodiment determines the voltage phase anomaly of the high-frequency cavity voltage at each moment by measuring the difference in voltage amplitude between the I cavity voltage signal and the R cavity voltage signal, as well as the discrete degree of all phases in the R cavity voltage signal. Specifically,

[0076] In this embodiment, the Hurst exponent of the voltage amplitude difference between the I cavity voltage signal and the R cavity voltage signal at all times is calculated;

[0077] The calculation method of the Hurst index is a well-known technique, and its specific calculation process will not be described in detail.

[0078] Furthermore, the Hurst exponent is multiplied by the discrete degree of the phase at all moments in the R cavity voltage signal to obtain the voltage phase abnormality of the high-frequency cavity voltage at each moment.

[0079] It should be noted that there are many methods for measuring the degree of data discreteness. In this embodiment, the coefficient of variation of the phase at all times in the R-cavity voltage signal is used as the degree of discreteness of the phase at all times in the R-cavity voltage signal. In actual application, as other implementation methods, the implementer may also adopt other methods for measuring the degree of data discreteness such as variance or standard deviation in combination with specific circumstances. This embodiment does not impose any special restrictions on the selection of methods for measuring the degree of data discreteness.

[0080] The calculation method of the coefficient of variation is a well-known technique, and the specific calculation process will not be described in detail.

[0081] According to the voltage phase anomaly of the high-frequency cavity voltage at each moment, it can be understood that if the Hurst exponent of the voltage amplitude difference between the I cavity voltage signal and the R cavity voltage signal at all moments is larger, it means that the high-frequency cavity voltage amplitude difference shows stronger persistence. Combined with the voltage difference, this means that the voltage difference between the I cavity and the R cavity may not be random, but has a certain regularity and trend, which usually indicates that the voltage difference caused by heat is relatively persistent, indicating that the heat generated by the electron beam hitting the target causes the high-frequency cavity resistance element to expand and contract, which damages the high-frequency cavity resonant frequency more seriously. Therefore, the corresponding voltage phase anomaly is greater; at the same time, if the phase discreteness of the R cavity voltage signal at all moments is greater, it means that the phase jump or fluctuation of the R cavity voltage signal is more severe, and the R cavity voltage signal is more unstable, reflecting that the heat generated by the electron beam hitting the target causes the phase stability of the R cavity responsible for phase regulation to deteriorate, and the corresponding voltage phase anomaly is also greater.

[0082] On the contrary, if the Hurst exponent of the voltage amplitude difference between the I cavity voltage signal and the R cavity voltage signal at all times is smaller, it means that the high-frequency cavity voltage amplitude difference shows weaker persistence and is closer to random fluctuations. Combined with the voltage difference, this means that the voltage difference between the I cavity and the R cavity is more likely to be random, lacking obvious regularity and trend, which usually indicates that the voltage difference caused by heat is relatively unstable or has a small impact, indicating that the heat generated by the electron beam hitting the target causes the high-frequency cavity resistance element to expand and contract, which has relatively little damage to the high-frequency cavity resonant frequency. Therefore, the corresponding voltage phase anomaly is smaller; at the same time, if the phase discreteness of the R cavity voltage signal at all times is smaller, it means that the phase jump or fluctuation of the R cavity voltage signal is smoother, and the R cavity voltage signal is more stable, reflecting that the heat generated by the electron beam hitting the target has little effect on the phase stability of the R cavity responsible for phase regulation, and the corresponding voltage phase anomaly is also smaller.

[0083] (2) Furthermore, this embodiment analyzes the energy differences between all modal components in the I cavity voltage signal and the R cavity voltage signal, and counts the number of all modal components in the I cavity voltage signal and the R cavity voltage signal to determine the spectral oscillation degree of the high-frequency cavity voltage at each moment, specifically:

[0084] As a specific implementation, in this embodiment, firstly, the I cavity voltage signal and the R cavity voltage signal are divided into multiple modal components respectively using the empirical mode decomposition algorithm;

[0085] Furthermore, all energy values ​​in each modal component in the I cavity voltage signal and the R cavity voltage signal are respectively combined into an energy sequence of each modal component, and the cumulative sum of the energy sequence differences between all modal components in the I cavity voltage signal and the cumulative sum of the energy sequence differences between all modal components in the R cavity voltage signal are respectively calculated and recorded as a first sum value and a second sum value, respectively. The result of adding the first sum value and the second sum value is taken as the energy difference value of the high-frequency cavity voltage signal;

[0086] It should be noted that there are many commonly used modal decomposition algorithms. In this embodiment, the empirical mode decomposition algorithm (EMD) is used to decompose the I cavity voltage signal and the R cavity voltage signal. In actual application, as other implementation methods, the implementer may also adopt other decomposition methods such as the variational mode decomposition algorithm based on specific circumstances. Regarding the selection of the modal decomposition algorithm, this embodiment does not impose any special restrictions.

[0087] The empirical mode decomposition algorithm is a well-known technology, and the specific process of using it to perform modal decomposition on the signal will not be described in detail.

[0088] It should be noted that there are many methods for measuring the differences between sequences. In this embodiment, the DTW distance of the energy sequences between all modal components in the I-cavity voltage signal is used as the energy sequence difference between all modal components in the I-cavity voltage signal. In actual application, as other implementation methods, the implementer may also adopt other methods for measuring the differences between sequences, such as Euclidean distance or Manhattan distance, according to specific circumstances. This embodiment does not impose any special restrictions on the selection of methods for measuring the differences between sequences. The energy sequence differences between all modal components in the R-cavity voltage signal are also measured using the DTW distance.

[0089] The calculation method of the DTW distance is a well-known technology, and its specific calculation process is not repeated here.

[0090] Furthermore, this embodiment calculates the sum of the total number of modal components in the I cavity voltage signal and the total number of modal components in the R cavity voltage signal, and uses the ratio of the sum to the energy difference value as the spectral oscillation degree of the high-frequency cavity voltage at each moment.

[0091] According to the spectral oscillation degree of the high-frequency cavity voltage at each moment, it can be understood that if the sum of the total number of modal components in the I cavity voltage signal and the total number of modal components in the R cavity voltage signal is larger, it means that there are more oscillation modes obtained after modal decomposition of the I cavity voltage signal and the R cavity voltage signal. This indicates that the heat interference generated by the electron beam hitting the target may make the spectral structure of the high-frequency cavity voltage signal more complex, containing more oscillation components of different frequencies, or the non-stationarity of the signal itself is enhanced, and the corresponding spectral oscillation degree is larger; at the same time, if the difference in energy sequence between all modal components in the I cavity voltage signal is smaller, and the difference in energy sequence between all modal components in the R cavity voltage signal is smaller, it means that the aliasing of the modal components in the high-frequency voltage signal is more serious, that is, the heat generated by the electron beam hitting the target material interferes with the high-frequency cavity voltage more seriously. Therefore, the larger the corresponding spectral oscillation degree, the more the step size factor in the adaptive filtering algorithm should be reduced to improve the calibration accuracy of the high-frequency cavity voltage.

[0092] On the contrary, if the sum of the total number of modal components in the I-cavity voltage signal and the total number of modal components in the R-cavity voltage signal is smaller, it means that the I-cavity voltage signal and the R-cavity voltage signal have fewer oscillation modes after modal decomposition. This indicates that the thermal interference generated by the electron beam impacting the target material may make the spectral structure of the high-frequency cavity voltage signal relatively simple, containing fewer oscillation components, or the non-stationarity of the signal itself is weakened, and the corresponding spectral oscillation degree is smaller; at the same time, if the difference in energy sequences between all modal components in the I-cavity voltage signal is greater, and the difference in energy sequences between all modal components in the R-cavity voltage signal is greater, it means that the discrimination of the modal components in the high-frequency voltage signal is higher and the aliasing is milder.

[0093] (3) Furthermore, this embodiment determines the second disturbance degree of the high-frequency cavity voltage at each moment based on the spectrum oscillation degree and voltage phase abnormality degree of the high-frequency cavity voltage at each moment, specifically:

[0094] In this embodiment, the result of forward fusion of the voltage phase anomaly degree and the spectrum oscillation degree of the high-frequency cavity voltage at each moment is used as the second disturbance degree of the high-frequency cavity voltage at each moment.

[0095] It should be understood that forward fusion refers to combining two or more indicators through addition or multiplication to obtain a comprehensive indicator, thereby more comprehensively and accurately evaluating a phenomenon or problem. This fusion method is not limited to simple arithmetic operations and can also include more complex statistical models and analysis methods. Implementers can choose according to their specific circumstances and this embodiment does not impose any special restrictions.

[0096] Preferably, as a specific implementation, in this embodiment, the product of the voltage phase anomaly degree and the spectrum oscillation degree of the high-frequency cavity voltage at each moment is used as the second disturbance degree of the high-frequency cavity voltage at each moment.

[0097] According to the second disturbance degree of the high-frequency cavity voltage at each moment, it can be understood that if the voltage phase anomaly of the high-frequency cavity voltage at the current moment is greater, it means that the heat generated by the electron beam hitting the target material causes the capacitance difference and phase jump of the high-frequency cavity voltage signal to be more serious, and the overall thermal drift interference is stronger, which means that the thermal interference of the high-frequency cavity voltage signal is more serious. Therefore, the second disturbance degree of the high-frequency cavity voltage is greater; at the same time, if the spectrum oscillation degree of the high-frequency cavity voltage at the current moment is greater, it means that the modal aliasing and spectrum complexity caused by heat are higher, the overall thermal drift interference is stronger, which means that the interference degree of the high-frequency cavity voltage signal is more serious, and the corresponding second disturbance degree is greater;

[0098] On the contrary, if the voltage phase anomaly of the high-frequency cavity voltage at the current moment is smaller, it means that the heat generated by the electron beam hitting the target material causes the capacitance difference and phase jump of the high-frequency cavity voltage signal to be smaller, and the overall thermal drift interference is weaker, which means that the thermal interference of the high-frequency cavity voltage signal is less serious, and therefore, the second interference degree of the high-frequency cavity voltage is smaller; at the same time, if the spectrum oscillation of the high-frequency cavity voltage at the current moment is smaller, it means that the modal aliasing and spectrum complexity caused by heat are lower, and the overall thermal drift interference is weaker, which means that the interference degree of the high-frequency cavity voltage signal is less serious, and the corresponding second interference degree is smaller.

[0099] Thus, this embodiment has quantified the impact of heat-induced high-frequency cavity structural deformation and performance degradation on the voltage signal by analyzing the amplitude difference, phase dispersion, and spectral modal characteristics of the I and R cavity voltages. This has achieved a more accurate assessment of the thermal interference condition of the medical cyclotron, and helped to optimize the adaptive filtering parameters to improve the calibration accuracy of the high-frequency cavity voltage.

[0100] Step S4: Based on the first disturbance degree and the second disturbance degree, a step factor adjustment coefficient is determined to adjust the step factor of the LMS adaptive filtering algorithm for calibrating the current high-frequency cavity voltage.

[0101] During the operation of a medical cyclotron accelerator, when the degree of interference of the temperature gradient change caused by the high-intensity beam and heat on the high-frequency cavity voltage is higher, the step size factor of the LMS adaptive filtering algorithm should be limited when calibrating and measuring the high-frequency cavity voltage to avoid error expansion.

[0102] Therefore, this embodiment determines a step factor adjustment coefficient based on the first disturbance degree and the second disturbance degree, which is used to characterize the degree of reduction of the step factor when the high-frequency cavity voltage is calibrated using the LMS adaptive filtering algorithm. Specifically, it is:

[0103] In this embodiment, the first and second disturbances of the high-frequency cavity voltage at all times within a preset period before the current moment are respectively used as inputs of the entropy weight method, and the entropy weight of the first and second disturbances at the current moment is output.

[0104] It should be noted that the value of the preset time period length is set manually. In this embodiment, the value of the preset time period length is 5s. In actual application, as other implementation methods, the implementer can also set it by himself based on the specific situation. This embodiment does not impose any special restrictions.

[0105] The entropy weight method is a well-known technology, and the specific process of calculating the entropy weights of the first disturbance degree and the second disturbance degree using the entropy weight method will not be described in detail.

[0106] Further, the product of the first disturbance degree of the high-frequency cavity voltage at the current moment and its entropy weight, and the product of the second disturbance degree and its entropy weight are calculated respectively, and are recorded as the first product and the second product respectively;

[0107] Furthermore, the sum of the first product and the second product, and the sum of the entropy weight of the first disturbance degree and the entropy weight of the second disturbance degree are calculated respectively, and recorded as the third sum and the fourth sum respectively. The ratio of the third sum to the fourth sum is taken as the comprehensive index, and the inverse of the comprehensive index is taken as the step factor adjustment coefficient at the current moment.

[0108] Preferably, the step size factor adjustment coefficient extraction process diagram provided in this embodiment is as follows: Figure 2 shown.

[0109] Furthermore, this embodiment uses the I cavity voltage signal and the R cavity voltage signal of the high-frequency cavity within a preset time length before the current moment as inputs of the adaptive filtering algorithm, multiplies the preset step size factor in the LMS adaptive filtering algorithm by the step size factor adjustment coefficient at the current moment as the step size factor in the current LMS adaptive filtering algorithm, outputs the filtered I cavity voltage signal and the R cavity voltage signal, and completes the calibration of the high-frequency cavity voltage.

[0110] The LMS adaptive filtering algorithm is a well-known technology, and the specific process of filtering the voltage signal using the LMS adaptive filtering algorithm will not be described in detail.

[0111] It should be noted that the value of the preset step factor is set manually. In this embodiment, the preset step factor is the default step factor of the LMS adaptive filtering algorithm, which is 32. In actual application, as other implementation methods, the implementer can also set it by himself based on the specific situation. This embodiment does not impose any special restrictions.

[0112] Thus, this embodiment quantifies the effects of high-intensity beam current and thermal temperature gradient on the high-frequency cavity voltage by analyzing the load anomaly, voltage difference, phase anomaly, and spectral characteristics of the I and R cavity voltage signals, forming the first and second disturbance indexes. Based on this, the LMS filter step factor is dynamically adjusted, effectively avoiding the calibration error amplification caused by excessive step size under strong interference, and significantly improving the calibration accuracy of the high-frequency cavity voltage of the medical cyclotron.

[0113] It should be noted that the order in which the embodiments of the present application are presented is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. Furthermore, the foregoing descriptions of specific embodiments of this specification are provided. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential sequence shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0114] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0115] The above-described embodiments are only used to illustrate the technical solutions of the present application, and not to limit them. Modifications to the technical solutions described in the aforementioned embodiments, or equivalent replacements of some of the technical features therein, do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A method for calibrating and measuring the high-frequency cavity voltage of a medical cyclotron, characterized in that: The method comprises the following steps: Acquire the I cavity voltage signal and the R cavity voltage signal in the high frequency cavity of the medical cyclotron within a preset time period before each moment, as well as the phases of the I cavity voltage signal at all moments and the phases of the R cavity voltage signal at all moments; Each peak in the voltage signal and the trough closest to it are combined into associated peaks and valleys, the peak-to-valley deviations between each pair of associated peaks and valleys are calculated, the rate of change of the peak-to-valley deviations between each pair of associated peaks and valleys in the I-cavity voltage signal is analyzed, and the attenuation rate of each pair of associated peaks and valleys in the I-cavity voltage signal is determined; based on the discrete degree of the attenuation rate of all pairs of associated peaks and valleys in the I-cavity voltage signal, and analyzing the difference in peak-to-valley deviations between each pair of associated peaks and valleys and its adjacent pair of associated peaks and valleys in the R-cavity voltage signal, the load anomaly degree of the high-frequency cavity voltage at each moment is determined; the differences in all peaks and all phases between the I-cavity voltage signal and the R-cavity voltage signal are compared to determine the voltage difference degree of the high-frequency cavity voltage at each moment, and combined with the load anomaly degree, the first disturbance degree of the high-frequency cavity voltage at each moment is determined; The difference in voltage amplitude between the I cavity voltage signal and the R cavity voltage signal, as well as the degree of discreteness of all phases in the R cavity voltage signal, are measured to determine the voltage phase anomaly of the high-frequency cavity voltage at each moment; the energy difference between all modal components in the I cavity voltage signal and the R cavity voltage signal are analyzed respectively, and the number of all modal components in the I cavity voltage signal and the R cavity voltage signal are counted to determine the spectral oscillation degree of the high-frequency cavity voltage at each moment, and the second disturbance degree of the high-frequency cavity voltage at each moment is determined in combination with the voltage phase anomaly; Determining a step factor adjustment coefficient based on the first disturbance degree and the second disturbance degree to adjust the step factor of the LMS adaptive filtering algorithm for calibrating the current high-frequency cavity voltage; The expression of the load abnormality of the high-frequency cavity voltage at each moment is: Where, Indicates the load abnormality of the high-frequency cavity voltage at time i; It represents the result of the accumulation of the differences in peak-to-valley deviations between all adjacent pairs of associated peaks and valleys in the R cavity voltage signal at time i; represents the variance of the decay rate of all pairs of associated peaks and valleys in the voltage signal of cavity I at time i; exp( ) represents an exponential function with a natural constant as the base; The first disturbance degree of the high-frequency cavity voltage at each moment is the product of the load abnormality degree and the voltage difference degree of the high-frequency cavity voltage at each moment; The method for determining the spectral oscillation degree of the high-frequency cavity voltage at each moment is: The empirical mode decomposition algorithm is used to divide the voltage signals of cavity I and cavity R into multiple modal components respectively; All energy values ​​in each modal component in the I cavity voltage signal and the R cavity voltage signal are respectively combined into an energy sequence of each modal component, and the cumulative sum of the energy sequence differences between all modal components in the I cavity voltage signal and the cumulative sum of the energy sequence differences between all modal components in the R cavity voltage signal are respectively calculated, and recorded as the first sum value and the second sum value, respectively. The result of adding the first sum value and the second sum value is used as the energy difference value of the high-frequency cavity voltage signal; Calculate the sum of the total number of modal components in the voltage signal of cavity I and the total number of modal components in the voltage signal of cavity R, and use the ratio of the sum to the energy difference value as the spectral oscillation degree of the high-frequency cavity voltage at each moment; The second disturbance degree of the high-frequency cavity voltage at each moment is the result of the forward fusion of the voltage phase anomaly degree and the spectrum oscillation degree of the high-frequency cavity voltage at each moment; The method for determining the step size factor adjustment coefficient is: The first disturbance degree and the second disturbance degree of the high-frequency cavity voltage at all moments in a preset period before the current moment are respectively used as inputs of the entropy weight method, and the entropy weight of the first disturbance degree and the entropy weight of the second disturbance degree at the current moment are output; Calculate the product of the first disturbance degree of the high-frequency cavity voltage at the current moment and its entropy weight, and the product of the second disturbance degree and its entropy weight, respectively, and record them as the first product and the second product; Calculate the sum of the first product and the second product, and the sum of the entropy weight of the first disturbance degree and the entropy weight of the second disturbance degree, and record them as the third sum and the fourth sum respectively. Take the ratio of the third sum to the fourth sum as the comprehensive index, and take the inverse of the comprehensive index as the step factor adjustment coefficient at the current moment.

2. The method for calibrating and measuring the high-frequency cavity voltage of a medical cyclotron according to claim 1, wherein: The attenuation rate of each pair of associated peaks and valleys in the I-cavity voltage signal is the result of the peak-to-valley deviation between each pair of associated peaks and valleys in the I-cavity voltage signal divided by the time interval between the peaks and valleys.

3. The method for calibrating and measuring the high-frequency cavity voltage of a medical cyclotron according to claim 1, wherein: The method for determining the voltage difference of the high-frequency cavity voltage at each moment is: Within a preset time period before each moment, all peaks of the I cavity voltage signal and the R cavity voltage signal are arranged in time sequence to form peak sequences of the I cavity voltage signal and the R cavity voltage signal, respectively, and the difference in the peak sequences between the I cavity voltage signal and the R cavity voltage signal is recorded as the peak difference; Calculate the sine values ​​of the phase differences between the I cavity voltage signal and the R cavity voltage signal at all times, and calculate the sum of the sine values ​​at all times, which is recorded as the phase difference sum; The ratio of the peak difference to the phase difference is taken as the voltage difference of the high-frequency cavity voltage at each moment.

4. The method for calibrating and measuring the high-frequency cavity voltage of a medical cyclotron according to claim 1, wherein: The method for determining the voltage phase anomaly of the high-frequency cavity voltage at each moment is as follows: Calculate the Hurst exponent of the voltage amplitude difference between the I cavity voltage signal and the R cavity voltage signal at all times; The Hurst exponent is multiplied by the discrete degree of the phase at all moments in the R cavity voltage signal to obtain the voltage phase abnormality of the high-frequency cavity voltage at each moment.

5. The method for calibrating and measuring the high-frequency cavity voltage of a medical cyclotron according to claim 1, wherein: The step size factor of the LMS adaptive filtering algorithm is adjusted to calibrate the current high-frequency cavity voltage, including: The I cavity voltage signal and the R cavity voltage signal of the high-frequency cavity within the preset time length before the current moment are respectively used as the input of the adaptive filtering algorithm, and the result of multiplying the preset step size factor in the adaptive filtering algorithm by the step size factor adjustment coefficient at the current moment is used as the step size factor in the current adaptive filtering algorithm, and the filtered I cavity voltage signal and the R cavity voltage signal are output.

Images