A method and system for predicting the lifetime and optimizing the stability of an electron gun cathode

Abstract

The application relates to an electron gun cathode life prediction and stability optimization method and system, wherein the method comprises the following steps: continuously collecting basic parameters and emission parameters in the whole life cycle of an electron gun cathode, and calculating a heating power increment; based on the basic parameters, the emission parameters and the heating power increment, a health state index prediction value of the cathode is calculated, and a failure threshold is set; a residual life prediction model is constructed, the health state index prediction value is input into the residual life prediction model, the health state index curve trend is fitted, the time required for the cathode to reach the failure threshold from the current state is predicted, and the residual life is obtained; based on the health state index and the cathode working temperature, the cathode heating current and the cathode heating power are adjusted, and the cathode heating current and the anode voltage are adjusted according to the vacuum degree. The application can effectively delay the aging process of the cathode and prolong the effective service life of the cathode under the premise of ensuring the stable operation of the electron gun.

Description

Technical Field

[0001] This application relates to the field of electron beam equipment technology, and in particular to a method and system for predicting the lifetime and optimizing the stability of an electron gun cathode. Background Technology

[0002] The electron gun cathode is a core component of electron beam equipment, such as electron microscopes, electron beam lithography machines, X-ray tubes, and accelerators. Its performance directly determines the stability, resolution, and reliability of the entire system. Cathode failure is the most significant failure mode of the electron gun, including issues such as emission current attenuation, increased work function, and depletion or contamination of the active material.

[0003] As the core component of the electron gun, the cathode's performance directly affects the gun's firing capability and lifespan. Its heating mechanism also directly impacts its operational efficiency and lifespan. Currently, cathodes are classified into direct-heated and indirect-heated types. Direct-heated cathodes primarily use pure tungsten as the material, while indirect-heated cathodes include both bombardment and heating types, with a wider range of cathode material options, such as thorium-coated tungsten, thorium oxide, scandium, and lanthanum hexaboride.

[0004] In existing technologies, cathode lifetime prediction mainly relies on accelerated aging tests and empirical models, resulting in low prediction accuracy and an inability to reflect the cathode's actual working condition in real time. Furthermore, in terms of stability control, constant heating power or emission current mode is usually adopted, ignoring the dynamic changes of the cathode material during operation, leading to a sharp decline in cathode performance or sudden failure in the later stages of its life. Meanwhile, in the electrical parameter control of the electron gun cathode, a large operating current and power are usually provided to the electron gun cathode to ensure stable operation of the electron gun. However, excessively high current can lead to spectral broadening, self-absorption, and decreased sensitivity, while also accelerating the wear of the cathode material and shortening the electron gun's life. On the other hand, excessively low current can easily lead to decreased stability, unstable discharge, and easy fluctuations in light intensity, resulting in reduced signal stability.

[0005] Therefore, it is necessary to improve one or more of the problems existing in the above-mentioned related technical solutions.

[0006] It should be noted that the information disclosed in the background section above is only used to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0007] The purpose of this disclosure is to provide a method and system for predicting the lifetime and optimizing the stability of an electron gun cathode, thereby overcoming, to at least some extent, one or more problems caused by the limitations and defects of related technologies.

[0008] In a first aspect, this application provides a method for predicting the lifetime and optimizing the stability of an electron gun cathode, including:

[0009] Throughout the entire lifecycle of the electron gun cathode, basic parameters and emission parameters are continuously collected, and the heating power increment is calculated. The basic parameters include cathode heating power, cathode heating current, and cathode operating temperature, while the emission parameters include set emission current, current fluctuation rate curve, and anode voltage.

[0010] Based on the basic parameters, the emission parameters, and the heating power increment, the predicted health status index of the cathode is calculated, and a failure threshold is set.

[0011] A remaining lifetime prediction model is constructed. The predicted value of the health status index is input into the remaining lifetime prediction model. By fitting the trend of the health status index curve, the time required for the cathode to reach the failure threshold from the current state is predicted, and the remaining lifetime is obtained.

[0012] Based on the health status index and the cathode operating temperature, the cathode heating current and the cathode heating power are adjusted, and the cathode heating current and the anode voltage are adjusted according to the vacuum level.

[0013] In one possible implementation, the step of continuously acquiring basic and emission parameters throughout the entire lifecycle of the electron gun cathode and calculating the heating power increment includes:

[0014] The cathode heating power and cathode heating current are monitored by sensors, and the cathode operating temperature is measured by infrared or colorimetric methods.

[0015] Record the set emission current and monitor the current fluctuation rate curve and anode voltage; wherein, the current fluctuation rate curve is a joint curve of emission current and current fluctuation rate;

[0016] The heating power increment is calculated based on the current heating power required to maintain the same emission current and the initial heating power.

[0017] In one possible implementation, the formula for calculating the heating power increment is:

[0018]

[0019] in, For heating power increment, To maintain the current heating power required to produce the same emission current, This represents the initial heating power.

[0020] In one possible implementation, the step of calculating the predicted health status index of the cathode based on the basic parameters, the emission parameters, and the heating power increment, and setting a failure threshold, includes:

[0021] Based on the historical data of the electron gun cathode, a health status index calculation function is constructed;

[0022] Set the initial parameters for the basic parameters and the transmission parameters, and set the failure threshold;

[0023] Based on the basic parameters, the emission parameters, and the heating power increment, the predicted value of the health status index of the cathode is obtained through the health status index calculation function.

[0024] In one possible implementation, the health status index calculation function is:

[0025]

[0026] in, This is a predicted value for the health status index. As the first weight, For heating power increment, This is the initial heating power. As the second weight, To set the transmission current, The noise level or coefficient of variation of the transmitted current. As the third weight, The cathode operating temperature, This is the initial cathode operating temperature.

[0027] In one possible implementation, the step of constructing a remaining lifetime prediction model, inputting the predicted health status index value into the remaining lifetime prediction model, and predicting the time required for the cathode to reach the failure threshold from its current state by fitting the trend of the health status index curve, to obtain the remaining lifetime, includes:

[0028] The remaining life prediction model is constructed based on historical data;

[0029] The predicted health status index is input into the remaining life expectancy prediction model to fit the curve of the health status index decaying over time.

[0030] Based on the trend curve, the time required for the predicted health status index to drop from its current value to the failure threshold is calculated, which is then taken as the remaining lifespan.

[0031] In one possible implementation, the remaining lifetime prediction model is:

[0032]

[0033] in, , This is a predicted value for the health status index. The first fitted parameter is... The second fitting parameter, The third fitting parameter, For lifespan, For the current time, It is a natural constant. The remaining lifespan.

[0034] In one possible implementation, the steps of adjusting the cathode heating current and the cathode heating power based on the health status index and the cathode operating temperature, and adjusting the cathode heating current and the anode voltage according to the vacuum level, include:

[0035] When the predicted value of the health status index is less than the adjustment threshold and the predicted value of the health status index decreases, the set emission current is adjusted down according to the current fluctuation curve.

[0036] Based on the set emission current, the cathode heating power is finely adjusted to minimize and stabilize the cathode operating temperature required for the set emission current.

[0037] When the vacuum level is detected to increase by 50% to 100%, the set emission current and the anode voltage are reduced.

[0038] In one possible implementation, the method of adjusting the set transmission current according to the current fluctuation rate curve is as follows:

[0039] Determine the current transmit current and current fluctuation rate;

[0040] Find the volatility corresponding to the current based on the pre-calibrated curve, and determine whether it exceeds the upper limit of the current volatility in the optimal stability operating area.

[0041] If the current operating point is in the high current region, reduce the emission current to move the operating point to the left into the optimal stability operating region;

[0042] The transmitting current is adjusted in small steps, and the change in current volatility is monitored. If the volatility decreases after the current is reduced, the adjustment continues in that direction. If the volatility increases, the adjustment is reversed.

[0043] Secondly, this application provides an electron gun cathode lifetime prediction and stability optimization system, the system being used to perform the above-described method, the system comprising:

[0044] The data acquisition module is used to continuously acquire basic parameters and emission parameters throughout the entire life cycle of the electron gun cathode, and calculate the heating power increment; wherein, the basic parameters include cathode heating power, cathode heating current and cathode operating temperature, and the emission parameters include set emission current, current fluctuation rate curve and anode voltage;

[0045] The SOH calculation module is used to calculate the predicted value of the cathode's health status index based on the basic parameters, the emission parameters, and the heating power increment, and to set a failure threshold.

[0046] The lifespan prediction module is used to construct a remaining lifespan prediction model. The predicted value of the health status index is input into the remaining lifespan prediction model. By fitting the trend of the health status index curve, the time required for the cathode to reach the failure threshold from the current state is predicted, and the remaining lifespan is obtained.

[0047] The parameter control module is used to adjust the cathode heating current and the cathode heating power based on the health status index and the cathode operating temperature, and to adjust the cathode heating current and the anode voltage according to the vacuum degree.

[0048] The technical solution provided in this application may include the following beneficial effects:

[0049] This application presents a method and system for predicting the lifespan and optimizing the stability of electron gun cathodes. It can calculate the health status index based on the fusion of multi-dimensional parameters and set a failure threshold. By combining the remaining lifespan prediction model with the fitting trend curve, it can achieve a quantitative assessment of the cathode health status and an accurate prediction of the remaining lifespan. Furthermore, it can dynamically adjust the heating current, heating power, and anode voltage according to the health status, cathode operating temperature, and vacuum level. This ensures the stability of electron gun operation, slows down cathode aging and wear, and extends its effective service life, providing strong support for the reliable operation and maintenance of electron beam equipment.

[0050] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0051] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure. It is obvious that the drawings described below are merely some embodiments of this disclosure, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0052] Figure 1 A flowchart illustrating the electron gun cathode lifetime prediction and stability optimization method in an exemplary embodiment of this disclosure is shown.

[0053] Figure 2 A detailed flowchart of step S100 of the electron gun cathode lifetime prediction and stability optimization method in an exemplary embodiment of this disclosure is shown.

[0054] Figure 3 A detailed flowchart of step S200 of the electron gun cathode lifetime prediction and stability optimization method in an exemplary embodiment of this disclosure is shown.

[0055] Figure 4 A detailed flowchart of step S300 of the electron gun cathode lifetime prediction and stability optimization method in an exemplary embodiment of this disclosure is shown.

[0056] Figure 5 A detailed flowchart of step S400 of the electron gun cathode lifetime prediction and stability optimization method in an exemplary embodiment of this disclosure is shown.

[0057] Figure 6 This diagram illustrates the decay of the cathode health status index over time in the electron gun cathode lifetime prediction and stability optimization method according to an exemplary embodiment of this disclosure.

[0058] Figure 7 The curve showing the relationship between emission current and cathode stability in the electron gun cathode lifetime prediction and stability optimization method in an exemplary embodiment of this disclosure is shown.

[0059] Figure 8 This diagram illustrates the structure of the electron gun cathode lifetime prediction and stability optimization system in an exemplary embodiment of this disclosure. Detailed Implementation

[0060] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that this disclosure will be more comprehensive and complete, and will fully convey the concept of the exemplary embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0061] First, the cathode, as the core component of the electron gun, directly affects the gun's firing capability and lifespan. The cathode's heating mechanism directly impacts its performance and lifespan. Cathodes are classified as directly heated or indirectly heated. Directly heated cathodes typically use pure tungsten as the material. Indirectly heated cathodes include both bombardment and heating types, with a wider range of material options, such as thorium-coated tungsten, thorium oxides, scandates, and lanthanum hexaboride. Material selection must consider factors such as low work function, high melting point, low evaporation rate, and good air stability to extend the cathode's lifespan. Field emission electron guns require a firing rate greater than 10 voltammetry near the cathode surface. 6A strong electric field of volts per centimeter is used to enhance emission intensity. The compound layer of the heated cathode is fixed to a thin-walled base, typically a nickel or molybdenum tube, beneath which a heat-resistant, insulating spiral tungsten filament is placed. When current passes through the filament, it heats up, which in turn heats the cathode. Once the cathode reaches the temperature required for electron emission, it begins to emit electrons. The heating mechanism of the bombardment cathode involves applying a bombardment voltage of several hundred to several thousand volts between the thermonuclear filament and the cathode. Under this voltage, electrons emitted by the thermonuclear filament bombard the cathode, heating it to a certain temperature, thus causing a large number of electrons to be emitted from its surface. Temperature directly affects electron emission capability and cathode lifetime. Typically, the current intensity of the electron gun is maintained above 1 mA, with pulsed electron currents reaching the ampere level, and its lifetime exceeds 100 hours. The physical processes occurring near the cathode of the electron gun are quite similar to those in an electron diode. In a diode, the flow of current depends on the movement of electrons emitted from the cathode. The operation of the diode gun is similar to that of an electron diode, with the cathode electron flow affected by the heating voltage and the anode voltage. When a certain forward voltage U is applied between the cathode and anode of the diode a At that time, as the filament heating voltage U f As the anode current I gradually increases, a It will also change accordingly, thus obtaining an I a / U f The relationship curve shows that as temperature increases, space charge increases. When the cathode temperature is not too high and the number of emitted electrons is small, the area between the anode and cathode remains an accelerating field, allowing electrons to easily reach the anode. However, as more electrons are emitted from the cathode, the space charge density gradually increases, causing the potential gradient on the cathode surface to gradually decrease. When the cathode heating temperature is relatively low, all electrons emitted from the cathode can reach the anode. In this case, the anode current is mainly affected by the cathode emission temperature; this state is called temperature limitation. Under these conditions, changes in the cathode heating temperature have a significant impact on the emission current.

[0062] This example embodiment first provides a method for predicting the lifetime and optimizing the stability of an electron gun cathode. This method can be applied to a terminal device, such as a mobile terminal like a mobile phone, desktop computer, personal digital assistant, laptop, tablet, or smartwatch. (Reference) Figure 1 As shown, the method may include the following steps:

[0063] Step S100: Continuously collect basic parameters and emission parameters throughout the entire life cycle of the electron gun cathode, and calculate the heating power increment; wherein, the basic parameters include cathode heating power, cathode heating current and cathode operating temperature, and the emission parameters include set emission current, current fluctuation rate curve and anode voltage.

[0064] Step S200: Based on the basic parameters, the emission parameters and the heating power increment, calculate the predicted health status index of the cathode and set the failure threshold.

[0065] Step S300: Construct a remaining lifetime prediction model. Input the predicted value of the health status index into the remaining lifetime prediction model. By fitting the trend of the health status index curve, predict the time required for the cathode to reach the failure threshold from the current state, and obtain the remaining lifetime.

[0066] Step S400: Based on the health status index and the cathode operating temperature, adjust the cathode heating current and the cathode heating power, and adjust the cathode heating current and the anode voltage according to the vacuum degree.

[0067] The aforementioned method can comprehensively capture the operational status of the electron gun cathode throughout its entire lifecycle. By continuously collecting multi-dimensional basic parameters and emission parameters and calculating the heating power increment, it provides complete data support for subsequent analysis. Based on this, the cathode aging status is quantified into a health status index prediction value, and a failure threshold is set to clarify the degree of cathode health degradation and failure boundary, solving the problems of quantification and ambiguous early warning in traditional methods. At the same time, a remaining life prediction model is constructed and the health status index curve trend is fitted to accurately predict the remaining life of the cathode, realizing the transformation from passive maintenance to proactive prediction, and significantly reducing equipment downtime losses and maintenance costs. Finally, based on the health status index, cathode operating temperature, and vacuum degree, the heating current, heating power, and anode voltage are dynamically optimized, which not only ensures the stability of electron gun operation but also effectively slows down the cathode aging process and extends its effective service life.

[0068] Below, we will refer to Figures 2 to 5 The steps of the method described above in this example embodiment will be explained in more detail.

[0069] In step S100, basic parameters and emission parameters are continuously collected throughout the entire life cycle of the electron gun cathode, and the heating power increment is calculated; wherein, the basic parameters include cathode heating power, cathode heating current and cathode operating temperature, and the emission parameters include set emission current, current fluctuation rate curve and anode voltage.

[0070] It should be noted that parameter acquisition needs to cover the entire process of the cathode from startup and stable operation to aging and failure. The acquisition frequency can be set to 1-10 minutes / time according to the equipment operating conditions to ensure data continuity. The heating power increment is the core indicator reflecting cathode aging. As the emission capability decreases after the cathode ages, a higher heating power is required to maintain the target emission current.

[0071] In one embodiment, such as Figure 2 As shown, step S100 may include the following sub-steps.

[0072] In step S110, the cathode heating power and cathode heating current are monitored by sensors, and the cathode operating temperature is measured by infrared or colorimetric methods.

[0073] It should be noted that power sensors and current sensors with an accuracy class of ≥0.5 can be selected to ensure that the measurement error of the basic parameters is within the allowable range; the infrared method is suitable for cathodes with temperatures ≥800℃, and the colorimetric method is suitable for medium and low temperature scenarios. Both methods need to be calibrated regularly to ensure the accuracy of temperature data.

[0074] In step S120, the set emission current is recorded and the current fluctuation rate curve and anode voltage are monitored; wherein, the current fluctuation rate curve is a joint curve of emission current and current fluctuation rate.

[0075] It should be noted that the current fluctuation rate curve needs to be plotted in real time, with the horizontal axis representing the emission current and the vertical axis representing the fluctuation rate (fluctuation rate = standard deviation / average value × 100%). The monitoring period should be consistent with the parameter acquisition period. Anode voltage monitoring should exclude external power supply fluctuation interference and retain the voltage change data related to cathode characteristics through filtering.

[0076] In step S130, the heating power increment is calculated based on the current heating power required to maintain the same emission current and the initial heating power.

[0077] It should be noted that the initial heating power is the average heating power after the cathode has been running stably for 1 hour in a rated emission current and standard vacuum environment under brand new conditions; the current heating power needs to be measured under the same emission current and vacuum conditions as the initial state to avoid the influence of environmental variables on the accuracy of incremental calculation.

[0078] The formula for calculating the heating power increment is as follows:

[0079]

[0080] in, For heating power increment, To maintain the current heating power required to produce the same emission current, This represents the initial heating power.

[0081] In step S200, based on the basic parameters, the emission parameters and the heating power increment, the predicted health status index of the cathode is calculated, and a failure threshold is set.

[0082] It should be noted that the health status index ranges from 0 to 1, where 1 represents a brand new cathode and 0 represents complete failure. The failure threshold needs to be set according to the cathode application scenario. For critical equipment such as electron beam lithography machines, it is usually set to 0.3, while for ordinary equipment it can be set to 0.2 to ensure sufficient maintenance time is reserved.

[0083] In one embodiment, such as Figure 3 As shown, step S200 may include the following sub-steps.

[0084] In step S210, a health status index calculation function is constructed based on the historical data of the electron gun cathode.

[0085] It should be noted that weight , , The sum of the three values ​​is determined by the analytic hierarchy process (AHP). Among them, w1 (the weight of the heating power increment) is usually taken as 0.4-0.6, because this indicator is most sensitive to aging. The historical data should include the full life cycle parameters of at least three batches of the same type of cathode to ensure the universality of the calculation function.

[0086] The health status index calculation function is as follows:

[0087]

[0088] in, This is a predicted value for the health status index. As the first weight, For heating power increment, This is the initial heating power. As the second weight, To set the transmission current, The noise level or coefficient of variation of the transmitted current. As the third weight, The cathode operating temperature, This is the initial cathode operating temperature.

[0089] It should be noted that, The noise level or dispersion coefficient of the transmitted current can be understood as the stability of the transmitted current, i.e., the standard deviation of the transmitted current divided by the average value of the transmitted current. The standard deviation represents the magnitude of the fluctuation in the transmitted current. The smaller the percentage value, the more stable the emission current.

[0090] In step S220, the initial parameters of the basic parameters and the transmission parameters are set, and the failure threshold is set.

[0091] It should be noted that the initial parameters should be collected within 2 hours of stable operation after the cathode is started, and 10 sets of data should be recorded continuously and the average value should be taken to avoid the influence of initial state fluctuations on the baseline value; the failure threshold should be verified through multiple accelerated aging tests to ensure that when the health status index drops to this value, the cathode emission performance cannot meet the minimum operating requirements of the equipment.

[0092] In step S230, based on the basic parameters, the emission parameters, and the heating power increment, the predicted value of the health status index of the cathode is obtained through the health status index calculation function.

[0093] It should be noted that the calculation cycle of the health status index is synchronized with the parameter acquisition cycle, and the health status index value is updated in real time. If a certain set of parameters is abnormal, such as a sensor failure causing a sudden change in data, the moving average of the first 3 sets of data should be used instead to ensure the reliability of the calculation results.

[0094] In step S300, a remaining lifetime prediction model is constructed. The predicted value of the health status index is input into the remaining lifetime prediction model. By fitting the trend of the health status index curve, the time required for the cathode to reach the failure threshold from the current state is predicted, and the remaining lifetime is obtained.

[0095] It should be noted that the choice of remaining life prediction model should be determined based on the cathodic degradation trend. Linear models are suitable for the early aging stage, while exponential and inverse proportional models are suitable for the mid-to-late rapid degradation stage. The model construction should include more than 50 sets of historical health status index data and corresponding time points to ensure prediction accuracy.

[0096] In one embodiment, such as Figure 4 As shown, step S300 may include the following sub-steps:

[0097] In step S310, the remaining life prediction model is constructed based on historical data.

[0098] It should be noted that after the model is built, it needs to be validated on a test set, and the prediction error needs to be controlled within ±10%. Otherwise, historical data needs to be added and the model refitted.

[0099] The remaining lifetime prediction model is as follows:

[0100]

[0101] in, , This is a predicted value for the health status index. The first fitted parameter is... The second fitting parameter, The third fitting parameter, For lifespan, For the current time, It is a natural constant. The remaining lifespan.

[0102] It should be noted that the process of cathode degradation can be described by various mathematical models. It is an exponential decay model. It is an inverse proportional function decay model. The linear decay model is used when the sample size is small. The parameters a, b, and c are obtained by fitting historical data. Curve fitting techniques such as least squares are used to fit the historical SOH data and time data to the selected degradation model to obtain the model parameters.

[0103] In step S320, the predicted value of the health status index is input into the remaining life expectancy prediction model to fit the trend curve of the health status index decaying over time.

[0104] It should be noted that, as Figure 6 The figure shows the trend curve of the health status index decaying over time. To fit the trend curve, the goodness of fit R² needs to be calculated. The curve is considered valid only if R² ≥ 0.85. If the goodness of fit is insufficient, the integrity of historical data needs to be checked or the prediction model needs to be changed. If necessary, other model types such as polynomial fitting can be added.

[0105] In step S330, based on the trend curve, the time required for the predicted health status index to drop from the current value to the failure threshold is calculated as the remaining lifespan.

[0106] It should be noted that the remaining lifespan is determined through... Calculate, where, For the current time, The remaining lifetime can be directly solved for linear models; for nonlinear models, numerical methods such as the bisection method can be used.

[0107] In step S400, based on the health status index and the cathode operating temperature, the cathode heating current and the cathode heating power are adjusted, and the cathode heating current and the anode voltage are adjusted according to the vacuum degree.

[0108] It should be noted that the core objective of parameter adjustment is to slow down the aging rate of the cathode while ensuring the basic operating performance of the equipment. The adjustment threshold should be set to 1.5-2 times the failure threshold. For example, if the failure threshold is 0.3, the adjustment threshold should be set to 0.45-0.6 to prevent the cathode from rapidly approaching the failure state.

[0109] In one embodiment, such as Figure 5 As shown, step S400 may include the following sub-steps:

[0110] In step S410, when the predicted value of the health status index is less than the adjustment threshold and the predicted value of the health status index decreases, the set emission current is adjusted down according to the current fluctuation rate curve.

[0111] It should be noted that the initial step size for reducing the transmitting current is 5%-10% of the rated current. If the fluctuation rate still exceeds the standard after adjustment, it can be adjusted repeatedly, but the cumulative reduction should not exceed 30% of the rated current to avoid excessively sacrificing the working efficiency of the equipment. The optimal stability operating range needs to be calibrated through pre-testing, which usually corresponds to the range of current fluctuation rate ≤2%.

[0112] In step S420, the cathode heating power is finely adjusted according to the set emission current to minimize and stabilize the cathode operating temperature required for setting the set emission current.

[0113] It should be noted that the heating power should be fine-tuned in small steps, with each adjustment not exceeding 3% of the current power, to avoid sudden changes in cathode temperature that could damage the material. After adjustment, it is necessary to monitor for 3-5 acquisition cycles to confirm that the emission current is stable and the temperature does not fluctuate abnormally before fixing the current power parameters.

[0114] In step S430, when the vacuum level is detected to increase by 50% to 100%, the set emission current and the anode voltage are reduced.

[0115] It should be noted that the normal operating range is usually 10. -4 -10 -6 Pa; The reduction in anode voltage needs to match the emission current, and is generally reduced by the same proportion to ensure that the electron beam acceleration efficiency and focusing performance meet the basic requirements.

[0116] In one embodiment, the method for adjusting the set transmission current according to the current fluctuation curve is as follows:

[0117] Determine the current transmit current and current fluctuation rate;

[0118] Find the volatility corresponding to the current based on the pre-calibrated curve, and determine whether it exceeds the upper limit of the current volatility in the optimal stability operating area.

[0119] If the current operating point is in the high current region, reduce the emission current to move the operating point to the left into the optimal stability operating region;

[0120] The transmitting current is adjusted in small steps, and the change in current volatility is monitored. If the volatility decreases after the current is reduced, the adjustment continues in that direction. If the volatility increases, the adjustment is reversed.

[0121] It should be noted that, as Figure 7As shown, the upper limit of the current fluctuation rate in the optimal stability operating region is the threshold value of the upper limit of the current fluctuation rate corresponding to the optimal stability operating region of the cathode, which is calibrated through pre-testing. If there is no pre-calibrated curve, the optimal operating range of the cathode can be found by monitoring the current fluctuation rate in real time. Furthermore, if the current operating point is in the low current region, the emission current needs to be increased appropriately. However, this application mainly focuses on the stability decline caused by cathode degradation, so in most cases, the current is reduced to extend the lifespan. At the same time, after multiple adjustments, the current fluctuation rate is reduced to an acceptable range (e.g., within the optimal stability operating region) or reaches an equilibrium point. This method, by systematically reducing the emission current, significantly improves stability and extends the cathode lifespan while sacrificing a small amount of performance, achieving the optimal balance between performance and lifespan.

[0122] Furthermore, this example embodiment also provides an electron gun cathode lifetime prediction and stability optimization system. (Reference) Figure 8 As shown, the system may include:

[0123] The data acquisition module is used to continuously acquire basic parameters and emission parameters throughout the entire life cycle of the electron gun cathode, and calculate the heating power increment; wherein, the basic parameters include cathode heating power, cathode heating current and cathode operating temperature, and the emission parameters include set emission current, current fluctuation rate curve and anode voltage;

[0124] The SOH calculation module is used to calculate the predicted value of the cathode's health status index based on the basic parameters, the emission parameters, and the heating power increment, and to set a failure threshold.

[0125] The lifespan prediction module is used to construct a remaining lifespan prediction model. The predicted value of the health status index is input into the remaining lifespan prediction model. By fitting the trend of the health status index curve, the time required for the cathode to reach the failure threshold from the current state is predicted, and the remaining lifespan is obtained.

[0126] The parameter control module is used to adjust the cathode heating current and the cathode heating power based on the health status index and the cathode operating temperature, and to adjust the cathode heating current and the anode voltage according to the vacuum degree.

[0127] The aforementioned system can comprehensively capture the operating status of the electron gun cathode throughout its entire life cycle, quantify its health degradation level through multi-dimensional parameter fusion, and accurately predict its remaining lifespan. At the same time, it dynamically optimizes electrical parameters based on health status and operating conditions, effectively slowing down the cathode aging process and extending its effective service life while ensuring the stability of electron gun operation. This provides technical support for the intelligent operation and maintenance and efficient and reliable operation of electron guns.

[0128] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the appended claims.

Claims

1. An electron gun cathode lifetime prediction and stability optimization method, characterized in that, The application relates to a method for predicting the remaining life of an electron gun cathode. The method comprises the following steps: continuously collecting basic parameters and emission parameters of the electron gun cathode in the whole life cycle of the cathode, and calculating a heating power increment; wherein the basic parameters include a cathode heating power, a cathode heating current and a cathode working temperature, and the emission parameters include a set emission current, a current fluctuation rate curve and an anode voltage; Based on the basic parameters, the emission parameters and the heating power increment, a health state index prediction value of the cathode is calculated, and a failure threshold is set; A remaining life prediction model is constructed, the health state index prediction value is input into the remaining life prediction model, the time required for the cathode to reach the failure threshold from the current state is predicted by fitting the health state index curve trend, and the remaining life is obtained; Based on the health state index and the cathode working temperature, the cathode heating current and the cathode heating power are adjusted, and the cathode heating current and the anode voltage are adjusted according to the vacuum degree.

2. The method of claim 1, wherein the method further comprises: The step of continuously collecting basic parameters and emission parameters of the electron gun cathode in the whole life cycle of the cathode, and calculating a heating power increment, comprises the following steps: The cathode heating power and the cathode heating current are monitored through a sensor, and the cathode working temperature is measured through infrared method or colorimetric method; The set emission current is recorded, and the current fluctuation rate curve and the anode voltage are monitored; wherein the current fluctuation rate curve is a joint curve of the emission current and the current fluctuation rate; The heating power increment is calculated according to the current heating power and the initial heating power required to maintain the same emission current.

3. The method of claim 2, wherein the method further comprises: The calculation formula of the heating power increment is as follows: wherein, is the heating power increment, is the current heating power required to maintain the same emission current, is the initial heating power.

4. The method of claim 1, wherein the method further comprises: The step of calculating the health state index prediction value of the cathode based on the basic parameters, the emission parameters and the heating power increment, and setting a failure threshold, comprises the following steps: A health state index calculation function is constructed based on historical data of the electron gun cathode; Initial parameters of the basic parameters and the emission parameters are set, and a failure threshold is set; The health state index prediction value of the cathode is obtained through the health state index calculation function according to the basic parameters, the emission parameters and the heating power increment.

5. The method of claim 4, wherein the method further comprises: The health state index calculation function is as follows: wherein, is a health status index prediction value, is a first weight, is a heating power increment, is an initial heating power, is a second weight, is a set emission current, is a noise level or dispersion coefficient of the emission current, is a third weight, is a cathode operating temperature, is an initial cathode operating temperature.

6. The method of claim 1, wherein the method further comprises: The step of constructing a remaining life prediction model, inputting the health state index prediction value into the remaining life prediction model, fitting the health state index curve trend, predicting the time required for the cathode to reach the failure threshold from the current state, and obtaining the remaining life, comprises the following steps: The remaining life prediction model is constructed according to historical data; The health state index prediction value is input into the remaining life prediction model, and a variation trend curve of the health state index with time is fitted out; Based on the variation trend curve, the time required for the health state index prediction value to drop from the current value to the failure threshold is calculated as the remaining life.

7. The method of claim 6, wherein the method further comprises: determining a stability of the electron gun cathode; and determining a lifetime of the electron gun cathode based on the stability of the electron gun cathode. The remaining life prediction model is as follows: wherein, , is a health status index prediction value, is a first fitting parameter, is a second fitting parameter, is a third fitting parameter, is a lifetime time, is a current time, is a natural constant, is a remaining lifetime.

8. The method of claim 1, wherein the method further comprises: determining a stability of the electron gun cathode; and determining a lifetime of the electron gun cathode. The step of adjusting the cathode heating current and the cathode heating power based on the health state index and the cathode working temperature, and adjusting the cathode heating current and the anode voltage according to the vacuum degree, comprises the following steps: when the health state index prediction value is less than the adjustment threshold value and the health state index prediction value decreases, adjusting the set emission current according to the current fluctuation rate curve; based on the set emission current, fine-tuning the cathode heating power to minimize and stabilize the cathode operating temperature required for setting the set emission current; when a 50% to 100% increase in vacuum degree is monitored, reducing the set emission current and the anode voltage.

9. The method of claim 8, wherein the method further comprises: The method for adjusting the set emission current according to the current fluctuation rate curve comprises: determining the current emission current and the current fluctuation rate; based on a pre-calibration curve, finding the fluctuation rate corresponding to the current emission current, and determining whether the fluctuation rate exceeds the upper limit of the current fluctuation rate in the optimal stability operating zone; when the current operating point is in the high current zone, reducing the emission current to move the operating point to the left into the optimal stability operating zone; adjusting the emission current in small steps, and monitoring the change in the current fluctuation rate; when the fluctuation rate decreases after reducing the current, continue to adjust in the same direction; and when the fluctuation rate increases, adjust in the opposite direction.

10. An electron gun cathode lifetime prediction and stability optimization system, characterized by, The system is used to perform the method according to any one of claims 1 to 9, and the system comprises: a data acquisition module configured to continuously acquire basic parameters and emission parameters of the cathode of the electron gun throughout the entire life cycle of the cathode, and to calculate a heating power increment; wherein the basic parameters comprise a cathode heating power, a cathode heating current, and a cathode operating temperature, and the emission parameters comprise a set emission current, a current fluctuation rate curve, and an anode voltage; an SOH calculation module configured to calculate a health state index prediction value of the cathode based on the basic parameters, the emission parameters, and the heating power increment, and to set a failure threshold value; a life prediction module configured to construct a residual life prediction model, input the health state index prediction value into the residual life prediction model, and predict a time required for the cathode to reach the failure threshold value from a current state by fitting a trend of the health state index curve, to obtain a residual life; a parameter control module configured to adjust the cathode heating current and the cathode heating power based on the health state index and the cathode operating temperature, and to adjust the cathode heating current and the anode voltage based on a vacuum degree.

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