A control rod drive mechanism operation state evaluation method fusing multi-source feature information

Abstract

The application provides a control rod drive mechanism operation state evaluation method fusing multi-source feature information, current data generated in the operation process of the control rod drive mechanism is collected, feature parameters of each action time sequence point in the current signal are intercepted after preprocessing, the feature parameters are screened to obtain key feature parameters, then the uncertainty parameters of the control rod drive mechanism are determined, random variable analysis is performed, action reliability is defined, a multi-field dynamics simulation model of the control rod drive mechanism is constructed, based on the multi-field dynamics simulation model, the random variables are input to perform reliability evaluation on the key feature parameters of the control rod drive mechanism, a running state evaluation model fusing multi-source feature information is constructed through a top-down hierarchical structure, and the running state evaluation of the control rod drive mechanism is realized. Through the application, the efficiency of the operation state management of the control rod drive mechanism is greatly improved, and effective support is provided for the comprehensive and accurate evaluation of the operation state of the control rod drive mechanism.

Description

Technical Field

[0001] This invention relates to the field of nuclear power technology, and in particular to a method for evaluating the operating status of a control rod drive mechanism that integrates multi-source characteristic information. Background Technology

[0002] The control rod drive mechanism is a device used to drive control rods in a nuclear power plant. Currently, during the operation of the control rod drive mechanism, relevant personnel mainly rely on existing monitoring information and operating procedures to judge its operating status through system knowledge and operational experience. Furthermore, activities affecting the safety of the drive mechanism are assessed under the supervision of review technicians. Current operational status assessments of the control rod drive mechanism are primarily based on failure physics methods and data-driven methods. However, in actual engineering, the failure patterns of control rod drive mechanisms are often very complex and difficult to accurately describe using failure physics models, rendering failure physics-based methods unsuitable. Additionally, the long lifespan and complex, variable operating environment of control rod drive mechanisms make it difficult to collect failure data, thus hindering data-driven methods. Effectively combining failure physics and data-driven methods can complement each other to improve the accuracy of reliability assessments, but it cannot account for the various uncertainties inherent in the control rod drive mechanism. Meanwhile, with the continuous development of digitalization and intelligence in nuclear power, more attention is being paid to improving the performance level and ensuring operational safety of complex and large nuclear power equipment, such as control rod drive mechanisms. Therefore, it is extremely important to conduct comprehensive modeling and evaluation of the operating status of control rod drive mechanisms through a system-level approach. Summary of the Invention

[0003] To address the aforementioned issues, this invention provides a method for evaluating the operational status of a control rod drive mechanism by integrating multi-source feature information. Based on the specific structure and working principle of the control rod drive mechanism, an evaluation model integrating multi-source feature information is constructed. This model not only considers the physical characteristics of the control rod drive mechanism but also incorporates engineering practice experience, enabling it to comprehensively reflect the operational status of the control rod drive mechanism.

[0004] A method for evaluating the operating status of a control rod drive mechanism by fusing multi-source feature information includes the following steps:

[0005] Step S1: Preprocess the current signal collected in real time by the control rod drive mechanism, including data cleaning, filtering and noise reduction, and format standardization.

[0006] Step S2: The coil current signal is segmented and then the continuous wavelet transform algorithm is applied to extract the feature parameters of each action timing point in the current signal.

[0007] Step S3: Based on the extracted action timing point feature parameters, and combined with existing engineering experience, key feature parameters related to the evaluation of the operating status of the control rod drive mechanism are screened and calculated. The key feature parameters include the current pull-in time of the lifting coil, the current pull-in time of the moving coil, and the current pull-in time of the holding coil.

[0008] Step S4: Clarify the uncertainty parameters in the design and manufacturing process of the control rod drive mechanism, and use random variables to describe the fluctuation range of the uncertainty parameters. The uncertainty parameters include the gap between the magnetic pole and the armature, the area at the gap magnetic resistance, and the fixed magnetic resistance, so that each random variable follows a normal distribution.

[0009] Step S5: Perform force analysis on the control rod drive mechanism, and then construct a multi-field dynamic simulation model of the control rod drive mechanism. The multi-field dynamic simulation model includes a current calculation module, an electromagnetic force calculation module, an elastic force calculation module, a water resistance calculation module, a gravity calculation module, and a load force calculation module for the coil working circuit. Based on the uncertainty parameters, the above modules are used to calculate the current of the coil, the electromagnetic force of the armature, the elastic force, the water resistance, the gravity, and the load force, respectively.

[0010] Step S6: Based on the multi-field dynamic simulation model, perform simulation analysis on the lifting coil, moving coil and holding coil of the control rod drive mechanism to obtain the curves of the motion state of each part during the lifting or lowering process as a function of the energizing time, that is, the mapping relationship between the motion state and the current.

[0011] Step S7: Define the reliability of the action. Based on the actual situation, set thresholds for the three key characteristic parameters: the pull-in time of the boost coil current, the pull-in time of the moving coil current, and the pull-in time of the holding coil current. Establish an action reliability evaluation model and apply the formula. Reliability calculations are performed on key characteristic parameters, where thres is the coil current pull-in time threshold and t is the coil current pull-in time;

[0012] Step S8: Combine the timing process under actual working conditions to reasonably design the range of key characteristic parameters of the control rod drive mechanism, and obtain the relationship curve between key characteristic parameters and reliability through multi-field dynamic simulation model.

[0013] Step S9: Optimize the efficiency of the reliability calculation algorithm using the kernel density estimation method;

[0014] Step S10: By defining the reliability range, the calculated continuous reliability is mapped to three operating states: excellent, medium, and poor.

[0015] Step S11: Based on the specific structure and working principle of the control rod drive mechanism, construct an operation status evaluation model that integrates multi-source feature information. The evaluation model comprehensively evaluates the operation status of the control rod drive mechanism from both mechanical and electrical aspects. The mechanical aspect includes the pull-in time of the lifting coil current, the pull-in time of the moving coil current, and the pull-in time of the holding coil current. The electrical aspect includes the resistance of the lifting coil, the resistance of the moving coil, and the resistance of the holding coil.

[0016] Step S12: Use the operation status evaluation model that integrates multi-source feature information to evaluate the operation status of the control rod drive mechanism, and obtain the operation status evaluation results of each feature parameter, mechanical part and electrical part, and the control rod drive mechanism as a whole.

[0017] Furthermore, in step S5, the armature in the control rod drive mechanism is subjected to electromagnetic force, elastic force, gravity, water resistance, and load force during its movement. When the lifting armature is in the lifting state, the following applies:

[0018]

[0019] Among them, F e F is the electromagnetic force, F is the spring force, and G is the gravitational force. l For load force, F w Let f be the water resistance, m be the mass lifting the armature, x be the displacement lifting the armature, t be the energizing time, and the gravity G lifting the armature be a constant, with load force F... l To increase the weight of the drive rod assembly driven by the armature during lifting, which is also a constant, the water resistance F... w The water resistance includes the water resistance directly experienced by the hook component during its movement and the water resistance experienced by the drive rod component and the control rod component it drives during their movement. Both of these water resistances will eventually be transmitted to the armature. The value of other resistances f is relatively small, and their impact on the armature's motion state can be ignored.

[0020] Furthermore, the electromagnetic force F e Represented as:

[0021]

[0022] Where Φ is the air gap magnetic flux, μ0 is the permeability in vacuum, S is the area at the gap reluctance, N is the number of coil turns, I is the boost coil current, and R... c For the sum of fixed magnetic reluctance, l g To increase the gap length between the magnetic pole and the armature, let x be the displacement of the armature, and the constraint condition is: 0 ≤ x ≤ l. g .

[0023] Furthermore, the formula for calculating current is:

[0024]

[0025] Where E is the terminal voltage of the coil, R is the equivalent resistance of the coil, and L is the inductance value. L changes with x, so the current is a function of time t and displacement x.

[0026] The formula for calculating elastic force is: F = -k·Δx + F0, where k is a constant, Δx is the spring constant, which is determined by the material properties of the spring, the negative sign indicates that the elastic force generated by the spring is opposite to the direction of its elongation (or compression), and F0 is the preload of the spring.

[0027] Furthermore, in step S7, when the absorption time follows a normal distribution, then:

[0028]

[0029] Where z is the pull-in time of the current in each coil, μ t σ is the average pull-in time of the current in each coil. t This represents the standard deviation of the current pull-in time for each coil.

[0030] This invention provides a method for evaluating the operational status of a control rod drive mechanism by integrating multi-source feature information. First, real-time current signals are acquired and preprocessed. Then, a continuous wavelet transform algorithm is used to extract operational feature parameters, such as the timing points of each action, from the monitored current signals. Key feature parameters that accurately reflect the operational status of the drive mechanism are selected, including the pull-in time of the lifting coil current, the pull-in time of the moving coil current, and the pull-in time of the holding coil current. Considering the uncertainties in the design and manufacturing process of the control rod drive mechanism, random variables are used to describe the fluctuation range of these uncertainties. Random variable analysis is performed to define the operational reliability of the control rod drive mechanism. Through in-depth analysis of the multi-field dynamic simulation model of the control rod drive mechanism, the physical mechanism of the control rod drive mechanism is analyzed. This invention effectively integrates theory into the simulation model, focusing on the armature and coil of the control rod drive mechanism. Multi-field dynamic simulation analysis is conducted to simulate the dynamic behavior of the control rod drive mechanism, considering various complex factors and interactions. Through detailed simulation of the dynamic response of the control rod drive mechanism under different conditions, reliability curves of key characteristic parameters are obtained. The intrinsic relationship between key characteristic parameters and operating state is analyzed, and a mapping relationship between reliability and operating state is established. A multi-source characteristic information fusion model for the control rod drive mechanism's operating state is constructed through a top-down hierarchical structure. Based on this model, the operating state of the control rod drive mechanism is evaluated, thereby assessing the operating state of each key characteristic parameter, each part, and the entire control rod drive mechanism. This invention proposes a multi-angle, multi-information-source, multi-level structure method for evaluating the operating state of control rod drive mechanisms. It integrates multi-source characteristic information of the control rod drive mechanism, considering not only the physical characteristics of the control rod drive mechanism but also incorporating engineering practice experience. This will greatly improve the efficiency and accuracy of operating state evaluation management for control rod drive mechanisms, providing a comprehensive and efficient analysis for operating state evaluation. Attached Figure Description

[0031] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0032] Figure 1 This is a flowchart of a method for evaluating the operating status of a control rod drive mechanism that integrates multi-source feature information, provided by an embodiment of the present invention.

[0033] Figure 2 This is a schematic diagram of segmented processing of the lifting current during the lifting process of the control rod drive mechanism, provided by an embodiment of the present invention.

[0034] Figure 3 This is a schematic diagram of the key feature point extraction of the lifting coil current signal, the moving coil current signal and the holding coil current signal during the lifting process of the control rod driving mechanism provided in the embodiment of the present invention. Among them, (1) is the key feature point extraction of the lifting coil current signal during the lifting process, (2) is the key feature point extraction of the moving coil current signal during the lifting process, and (3) is the key feature point extraction of the holding coil current signal during the lifting process.

[0035] Figure 4 The curves of current change over time obtained by dynamic simulation of three coils during the lifting process based on the multi-field dynamic simulation model provided in this embodiment of the invention are as follows: (1) is the curve of current change of lifting coil over time during the lifting process, (2) is the curve of current change of moving coil over time during the lifting process, and (3) is the curve of current change of holding coil over time during the lifting process.

[0036] Figure 5 The present invention provides a probability distribution function of the current pull-in time of the three coils during the lifting process and a curve of the reliability changing with the current pull-in time, obtained by simulation based on a multi-field dynamics simulation model. Among them, (1) is the probability distribution function of the current pull-in time of the lifting coil during the lifting process, (2) is the curve of the reliability of the lifting process changing with the current pull-in time of the lifting coil, (3) is the probability distribution function of the current pull-in time of the moving coil during the lifting process, (4) is the curve of the reliability of the lifting process changing with the current pull-in time of the moving coil, (5) is the probability distribution function of the current pull-in time of the holding coil during the lifting process, and (6) is the curve of the reliability of the lifting process changing with the current pull-in time of the holding coil.

[0037] Figure 6 This is a mapping diagram of reliability and operational status assessment provided by an embodiment of the present invention;

[0038] Figure 7 This is the control rod drive mechanism operation status evaluation model that integrates multi-source feature information provided in the embodiments of the present invention;

[0039] Figure 8 This is a flowchart of the operation status evaluation of the control rod drive mechanism provided in an embodiment of the present invention. Detailed Implementation

[0040] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0041] The control rod drive mechanism is a device used in nuclear power plants to drive the control rods. It generally consists of a drive rod assembly, a sealing shell assembly, a magnetic yoke coil assembly, a chuck assembly, and a rod position detector assembly. The magnetic yoke coil assembly is installed on the outside of the sealing shell and includes various components such as three working coils: a lifting coil, a moving coil, and a holding coil. In the magnetic pole armature assembly, after the coil is energized to generate a magnetic field, a magnetic force is generated between the magnetic pole and the armature. When a specific magnetic pole and the armature are attracted, the corresponding chuck moves. The energizing sequence of the three coils corresponds to the action sequence of the chucks, thereby controlling the lifting, lowering, holding, or dropping of the control rods.

[0042] Currently, the operation of nuclear power equipment is shifting from event-based to state-based operation. As one of the complex nuclear power equipment, the control rod drive mechanism has practical engineering significance in comprehensively evaluating its operating status by establishing a system-level operating status assessment model.

[0043] In the control rod drive mechanism of a nuclear reactor, the component structure generates a large amount of important data at various stages of early design, operation, and later maintenance. This data contains key characteristic parameters that reflect the operating status level of the control rod drive mechanism during operation, and is a valuable resource for reliability assessment. By making full use of these data resources and combining them with the specific structure and working principle of the control rod drive mechanism, a control rod drive mechanism operating status assessment model that integrates multi-source characteristic information can be constructed, which can comprehensively and accurately assess and reflect the operating status of the control rod drive mechanism.

[0044] This invention provides a method for evaluating the operating status of a control rod drive mechanism by fusing multi-source feature information, such as... Figure 1 As shown, the method includes:

[0045] Step S1: Preprocess the current signal collected in real time by the control rod drive mechanism, including data cleaning, filtering and noise reduction, and format standardization.

[0046] In this embodiment, the current signal of the control rod drive mechanism is acquired through a dedicated module, with a sampling frequency of 2KHz or 5KHz.

[0047] Step S2: The current signals of the three coils are segmented and processed respectively. Then, a wavelet function is selected and a width range is determined. The continuous wavelet transform algorithm is applied to extract the feature parameters of each action timing point in the current signal.

[0048] During the operation of the control rod drive mechanism, the current of each coil changes periodically according to a certain time sequence. Even at different stages of the same cycle, the current magnitude and state of different coils are different. Therefore, firstly, the current waveform of the complete action cycle is extracted according to the action stage of the control rod drive mechanism. Then, based on the characteristics of the current waveforms of the three coils, the current is segmented and processed separately. Characteristic parameters such as the action timing points in the current signal are analyzed and extracted. Taking the current waveform of the lifting coil during the lifting process as an example, for instance... Figure 2 Divide into segments as shown, and then as follows: Figure 3 As shown in (1), the action timing points that accurately reflect the operating state of the control rod drive mechanism are extracted from the monitored current signal using the continuous wavelet transform algorithm. The moving coil and holding coil are also extracted using the same method. The extraction diagrams are shown in Figure 1. Figure 3 As shown in (2) and (3).

[0049] Step S3: Based on the extracted feature parameters of each action timing point, and combined with existing engineering experience, key feature parameters related to the evaluation of the operating status of the control rod drive mechanism are screened and calculated. The key feature parameters include the pull-in time of the lifting coil current, the pull-in time of the moving coil current, and the pull-in time of the holding coil current, as shown in the table below:

[0050]

[0051] Step S4: Identify the uncertainty parameters in the design and manufacturing process of the control rod drive mechanism, and use random variables to describe the fluctuation range of these uncertainty parameters. The uncertainty parameters include the gap between the magnetic pole and the armature, the area at the gap magnetic resistance, and the fixed magnetic resistance. Let S_mean and S_std represent the mean and standard deviation of the area at the gap magnetic resistance, respectively, and lg_mean and lg_std represent the mean and standard deviation of the gap between the magnetic pole and the armature, respectively. R c _mean and R c Let _std represent the mean and standard deviation of the fixed reluctance, as shown in the table below. Considering the dimensional errors in the manufacturing process of the control rod drive mechanism, and based on existing engineering experience, assuming each random variable follows a normal distribution, then:

[0052]

[0053] Variations in the clearance of kinematic pairs in a control rod drive mechanism often stem from dimensional errors, which may be caused by the manufacturing process. Dimensional errors affect the geometry and mating relationships of mechanical components, thereby affecting the clearance of kinematic pairs. Such variations may lead to instability and performance degradation in the control rod drive mechanism during operation. Therefore, it is necessary to set and solve the uncertainty parameters in conjunction with manufacturing process errors.

[0054] Step S5: Perform force analysis on the control rod drive mechanism, and then construct a multi-field dynamic simulation model of the control rod drive mechanism. The multi-field dynamic simulation model includes a current calculation module, an electromagnetic force calculation module, an elastic force calculation module, a water resistance calculation module, a gravity calculation module, and a load force calculation module for the coil working circuit. Based on the uncertainty parameters, the above modules are used to calculate the current of the coil, the electromagnetic force of the armature, the elastic force, the water resistance, the gravity, and the load force, respectively.

[0055] Based on the operating mechanism of the control rod drive mechanism, taking the lifting armature in the control rod drive mechanism as an example, it is subjected to electromagnetic force, elastic force, gravity, water resistance, and load force during the lifting process. A force analysis is then performed on it:

[0056]

[0057] Among them, F e F is the electromagnetic force, F is the spring force, and G is the gravitational force. l For load force, F w Let f be the water resistance, f be other resistances, m be the mass of the lifting armature, x be the displacement of the lifting armature, and t be the energizing time. The gravity G of the lifting armature is a constant, and the load force F... l To increase the weight of the drive rod assembly driven by the armature during lifting, which is also a constant, the water resistance F... w The resistance includes the water resistance directly experienced by the hook component during movement and the water resistance experienced by the drive rod component and the control rod component it drives during movement. Both of these water resistances will eventually be transmitted to the armature. The value of other resistances f is relatively small and their influence on the armature's motion state can be ignored.

[0058] Electromagnetic force F e Represented as:

[0059]

[0060] Where Φ is the air gap magnetic flux, μ0 is the permeability in vacuum, S is the area at the gap reluctance, N is the number of coil turns, I is the boost coil current, and R... c For the sum of fixed magnetic reluctance, l g To increase the gap length between the magnetic pole and the armature, let x be the displacement of the armature, and the constraint condition is: 0 ≤ x ≤ l. g .

[0061] The formula for calculating current is:

[0062]

[0063] Where E is the terminal voltage of the coil, R is the equivalent resistance of the coil, and L is the inductance value. L changes with x, so the current is a function of time t and displacement x.

[0064] The formula for calculating elastic force is:

[0065] F = -k·Δx + F0

[0066] Where k is a constant, Δx is the spring constant, which is determined by the material properties of the spring, the negative sign indicates that the elastic force generated by the spring is opposite to the direction of its elongation (or compression), and F0 is the preload of the spring.

[0067] After performing force analysis on the control rod drive mechanism, a multi-field dynamic simulation model of the control rod drive mechanism is built in Simulink to simulate various dynamic changes of the control rod drive mechanism during the lifting process.

[0068] Step S6: Based on the multi-field dynamic simulation model, perform simulation analysis on the lifting coil, moving coil and holding coil of the control rod drive mechanism to obtain the curves of the motion state of each part during the lifting or lowering process as a function of the energizing time, that is, the mapping relationship between the motion state and the current.

[0069] Based on the multi-field dynamic simulation model of the control rod drive mechanism, the lifting process of each coil is dynamically simulated, and the results are as follows: Figure 4 The curves showing the change of current waveforms in each coil over the energizing time are shown.

[0070] Step S7: Define the reliability of the action. Based on the actual situation, set thresholds for the three key characteristic parameters: the pull-in time of the boost coil current, the pull-in time of the moving coil current, and the pull-in time of the holding coil current. Establish an action reliability evaluation model and apply the formula. Reliability calculations are performed on key characteristic parameters, where thres is the current pull-in time threshold for each coil set according to actual conditions, and t is the current pull-in time for each coil.

[0071] When the coil current pull-in time follows a normal distribution, then:

[0072]

[0073] Where z is the pull-in time of the current in each coil, μ t σ is the average pull-in time of the current in each coil. t The standard deviation of the pull-in time of the current in each coil;

[0074] In one working cycle of the control rod drive mechanism, the current pull-in time of the lifting coil, moving coil, and holding coil corresponding to the lifting armature, moving armature, and holding armature, respectively, all have strict time requirements. Therefore, in order to ensure the smooth completion of one action step, the current pull-in time of these coils must be within a certain time. Based on the functional and performance requirements of the armature and coils, and combined with the general reliability definition of components, the reliability of the action can be defined as the ability of the coil current pull-in time to meet the specified lower limit requirements of the performance parameters under its specified working conditions and within its specified working time, and it is measured by reliability.

[0075] Step S8: Combine the timing process under actual working conditions to reasonably design the range of key characteristic parameters of the control rod drive mechanism, and obtain the relationship curve between key characteristic parameters and reliability through multi-field dynamic simulation model.

[0076] Based on reliability calculations and considering the timing process under actual operating conditions, uncertainty parameters are rationally designed. Taking the lifting coil as an example, as shown in the table below, random variables are set to describe the fluctuation range of the uncertainty parameters. Through dynamic simulation using a multi-field dynamics simulation model, the probability distribution function of the current pull-in time of the three coils during the lifting process and the curve of reliability changing with pull-in time are obtained. Figure 5 As shown.

[0077]

[0078] Step S9: Optimize the efficiency of the reliability calculation algorithm using the kernel density estimation method;

[0079] Kernel density estimation is used to optimize the efficiency of reliability calculation algorithms, enabling operational status assessment to be completed within one step of the control rod drive mechanism. Reliability calculation involves integral operations, and traditional integral operation methods usually require strict integral calculation of the distribution function of system performance. Such calculations are very time-consuming in complex systems like control rod drive mechanisms. Therefore, kernel density estimation, a non-parametric statistical method, is used to optimize the efficiency of integral operations. Compared with traditional integral operations, it can produce results faster and realize real-time assessment of control rod drive mechanisms.

[0080] Step S10: By defining the reliability range, the calculated continuous reliability is mapped to three operating states: excellent, medium, and poor.

[0081] like Figure 6 The mapping of continuous reliability to three operating states (excellent, average, and poor) makes the results more intuitive and facilitates understanding of the overall operating status of the control rod drive mechanism. Reliability ranges are defined for key characteristic parameters, categorized into excellent, average, and poor operating states, further reflecting the operating status of the control rod drive mechanism. The operating state levels are shown in the table below:

[0082]

[0083] Step S11: Based on the specific structure and working principle of the control rod drive mechanism, construct an operation status evaluation model that integrates multi-source feature information. The evaluation model comprehensively evaluates the operation status of the control rod drive mechanism from both mechanical and electrical aspects. The mechanical aspect includes the pull-in time of the lifting coil current, the pull-in time of the moving coil current, and the pull-in time of the holding coil current. The electrical aspect includes the resistance of the lifting coil, the resistance of the moving coil, and the resistance of the holding coil.

[0084] Operational status assessment model such as Figure 7 As shown, this evaluation model performs a hierarchical analysis of the structure and function of the control rod drive mechanism, extracting key characteristic parameters affecting its function and dividing it layer by layer until the performance indicators at the bottom level cannot be further subdivided. These key characteristic parameters in the mechanical part have complex coupling relationships; the mechanical part is only operating normally when all key characteristic parameters are in normal operating condition. In the electrical part, the magnetic circuit composed of the energized coil, magnetic poles, armature, and magnetic ring is related to the coil current and armature position, and there is inevitably coupling between the three coil magnetic circuits, which will affect each other. Given the complexity of the control rod drive mechanism system, it is difficult to intuitively and accurately understand the changes in its electrical circuit during dynamic processes based solely on theoretical analysis and calculation. Therefore, in practical engineering applications, the resistance operating state threshold can be dynamically adjusted according to requirements. Similar to the mechanical part, the electrical part is only operating normally when all key characteristic parameters are in normal operating condition. This model not only considers the physical characteristics of the control rod drive mechanism but also incorporates engineering practice experience, comprehensively reflecting the operating state of the control rod drive mechanism.

[0085] Step S12: Use the operation status evaluation model that integrates multi-source feature information to evaluate the operation status of the control rod drive mechanism, and obtain the operation status evaluation results of each key feature parameter, mechanical part and electrical part, and the control rod drive mechanism as a whole.

[0086] Based on a runtime status assessment model that integrates multi-source feature information, modeling and calculation are performed from the bottom up, employing methods such as... Figure 8 The process shown is used to evaluate the operating status of the control rod drive mechanism. The final evaluation results of the operating status of each key characteristic parameter, mechanical and electrical parts, and the control rod drive mechanism as a whole can be obtained. The results are output in the form of scores and status levels, thus completing the evaluation of the operating status of the control rod drive mechanism.

[0087] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions 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 invention.

Claims

1. A method for evaluating the operating status of a control rod drive mechanism by integrating multi-source feature information, characterized in that, The method includes: Step S1: Preprocess the current signal collected in real time by the control rod drive mechanism, including data cleaning, filtering and noise reduction, and format standardization. Step S2: The coil current signal is segmented and then the continuous wavelet transform algorithm is applied to extract the feature parameters of each action timing point in the current signal. Step S3: Based on the extracted action timing point feature parameters, and combined with existing engineering experience, key feature parameters related to the evaluation of the operating status of the control rod drive mechanism are screened and calculated. The key feature parameters include the current pull-in time of the lifting coil, the current pull-in time of the moving coil, and the current pull-in time of the holding coil. Step S4: Clarify the uncertainty parameters in the design and manufacturing process of the control rod drive mechanism, and use random variables to describe the fluctuation range of the uncertainty parameters. The uncertainty parameters include the gap between the magnetic pole and the armature, the area at the gap magnetic resistance, and the fixed magnetic resistance, so that each random variable follows a normal distribution. Step S5: Perform force analysis on the control rod drive mechanism, and then construct a multi-field dynamic simulation model of the control rod drive mechanism. The multi-field dynamic simulation model includes a current calculation module, an electromagnetic force calculation module, an elastic force calculation module, a water resistance calculation module, a gravity calculation module, and a load force calculation module for the coil working circuit. Based on the uncertainty parameters, the above modules are used to calculate the current of the coil, the electromagnetic force of the armature, the elastic force, the water resistance, the gravity, and the load force, respectively. Step S6: Based on the multi-field dynamic simulation model, perform simulation analysis on the lifting coil, moving coil and holding coil of the control rod drive mechanism to obtain the curves of the motion state of each part during the lifting or lowering process as a function of the energizing time, that is, the mapping relationship between the motion state and the current. Step S7: Define the reliability of the action. Based on the actual situation, set thresholds for the three key characteristic parameters: the pull-in time of the boost coil current, the pull-in time of the moving coil current, and the pull-in time of the holding coil current. Establish an action reliability evaluation model and apply the formula. Reliability calculations are performed on key characteristic parameters, among which, It is the coil current pull-in time threshold. This refers to the coil current pull-in time. When the current pull-in time follows a normal distribution, then: ； ； in, The pull-in time of each coil current. This represents the average pull-in time of the current in each coil. The standard deviation of the pull-in time of the current in each coil; Step S8: Combine the timing process under actual working conditions to reasonably design the range of key characteristic parameters of the control rod drive mechanism, and obtain the relationship curve between key characteristic parameters and reliability through multi-field dynamic simulation model. Step S9: Optimize the efficiency of the reliability calculation algorithm using the kernel density estimation method; Step S10: By defining the reliability range, the calculated continuous reliability is mapped to three operating states: excellent, medium, and poor. Step S11: Based on the specific structure and working principle of the control rod drive mechanism, construct an operation status evaluation model that integrates multi-source feature information. The evaluation model comprehensively evaluates the operation status of the control rod drive mechanism from both mechanical and electrical aspects. The mechanical aspect includes the pull-in time of the lifting coil current, the pull-in time of the moving coil current, and the pull-in time of the holding coil current. The electrical aspect includes the resistance of the lifting coil, the resistance of the moving coil, and the resistance of the holding coil. Step S12: Use the operation status evaluation model that integrates multi-source feature information to evaluate the operation status of the control rod drive mechanism, and obtain the operation status evaluation results of each feature parameter, mechanical part and electrical part, and the control rod drive mechanism as a whole.

2. The method according to claim 1, characterized in that, In step S5, the armature in the control rod drive mechanism is subjected to electromagnetic force, elastic force, gravity, water resistance, and load force during its movement. When the lifting armature is in the lifting state, the following applies: ； in, Electromagnetic force, For spring force, For gravity, For load capacity, For water resistance, For other resistance, To improve the quality of the armature, To increase the displacement of the armature, To increase the energizing time, the weight of the armature is increased. The load force is a constant. To increase the weight of the drive rod assembly driven by the armature during lifting, which is also a constant, the water resistance... This includes the water resistance directly experienced by the hook component during its movement, as well as the water resistance experienced by the drive rod component and the control rod component it drives during their movement. Both of these water resistances will eventually be transmitted to the armature.

3. The method according to claim 2, characterized in that, Electromagnetic force Represented as: ； in, For air gap magnetic flux, Permeability in vacuum Let be the area at the gap reluctance. The number of coil turns. To increase the coil current, The sum of fixed magnetic reluctance, To increase the gap length between the magnetic poles and the armature, the constraints are as follows: .

4. The method according to claim 2, characterized in that, The formula for calculating current is: ； in, The terminal voltage of the coil. This is the equivalent resistance of the coil. This is the inductance value. along with It changes with time, so current is time. and displacement The function; The formula for calculating elastic force is: ； in, It is a constant. It is the spring constant, determined by the material properties of the spring. The negative sign indicates that the elastic force generated by the spring is opposite to the direction of its extension or compression. This is the preload of the spring.

Images