Control rod driving mechanism operation state evaluation method fusing multi-source feature information

Abstract

The invention provides a control rod driving mechanism operation state evaluation method fusing multi-source characteristic information, which comprises the following steps: collecting current data generated in an operation process of a control rod driving mechanism, preprocessing, intercepting characteristic parameters of each action time sequence point in a current signal, screening the characteristic parameters to obtain key characteristic parameters, and evaluating the operation state of the control rod driving mechanism according to the key characteristic parameters. Determining uncertainty parameters of the control rod driving mechanism, performing random variable analysis, defining action reliability, constructing a multi-field dynamics simulation model of the control rod driving mechanism, and inputting random variables to perform reliability evaluation on key characteristic parameters of the control rod driving mechanism based on the multi-field dynamics simulation model; and through a hierarchical structure from top to bottom, an operation state evaluation model fusing multi-source feature information is constructed, and the operation state of the control rod driving mechanism is evaluated. The control rod driving mechanism operation state management efficiency is greatly improved, and effective support is provided for comprehensive and accurate evaluation of the control rod driving mechanism operation state.

Description

Technical Field

[0001] The present 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 by integrating multi-source characteristic information. Background Art

[0002] The control rod drive mechanism is a device used to drive the control rods in a nuclear power plant. At present, in the operation of the control rod drive mechanism, relevant personnel mainly judge its operating status based on existing monitoring information in accordance with the requirements of the operating procedures, through system knowledge and operating experience, and evaluate the activities that affect the safety of the drive mechanism through the supervision of the review technicians. At present, the operating status evaluation of the control rod drive mechanism is mainly based on the failure physics method and the data-driven method. However, in actual engineering, the failure law of the control rod drive mechanism is often very complex and difficult to accurately describe with the failure physics model, which makes the failure physics-based method inapplicable. In addition, the life of the control rod drive mechanism is long and the working environment is complex and changeable, so it is difficult to collect the failure data of the control rod drive mechanism. Therefore, the data-driven method is also difficult. The effective combination of the failure physics and data-driven methods can complement each other to improve the accuracy of reliability evaluation, but it cannot consider various uncertain factors in the control rod drive mechanism. At the same time, with the continuous development of nuclear power digitalization and intelligence, the operation of complex large-scale nuclear power equipment represented by control rod drive mechanism pays more attention to the improvement of performance level and the guarantee of operation safety. Therefore, it is extremely important to comprehensively model and evaluate the operating status of control rod drive mechanism through system-level methods. Summary of the invention

[0003] To solve the above problems, the present invention provides a control rod drive mechanism operating status evaluation method integrating multi-source characteristic information. In combination with the specific structure and working principle of the control rod drive mechanism, a control rod drive mechanism operating status evaluation model integrating multi-source characteristic information is constructed. This model not only takes into account the physical properties of the control rod drive mechanism, but also incorporates engineering practice experience, and can comprehensively reflect the operating status of the control rod drive mechanism.

[0004] A control rod drive mechanism operating state assessment method integrating multi-source characteristic information comprises the following steps:

[0005] Step S1, preprocessing 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, processing the coil current signal in sections respectively, and then applying the continuous wavelet transform algorithm to extract the characteristic parameters of each action timing point in the current signal;

[0007] Step S3, based on the extracted characteristic parameters of each action timing point, combined with existing engineering experience, screen and calculate the key characteristic parameters related to the control rod drive mechanism operation state evaluation, the key characteristic parameters including the lifting coil current pull-in time, the moving coil current pull-in time and the holding coil current pull-in time;

[0008] Step S4, clarifying the uncertainty parameters in the design and manufacturing process of the control rod drive mechanism, and using 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 obeys a normal distribution;

[0009] Step S5, performing force analysis on the control rod drive mechanism, and then constructing a multi-field dynamics simulation model of the control rod drive mechanism, the multi-field dynamics simulation model including a current calculation module of the coil working circuit, 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, and based on uncertainty parameters, the above modules are used to calculate the coil current, the armature electromagnetic force, the elastic force, the water resistance, the gravity, and the load force, respectively;

[0010] Step S6, based on the multi-field dynamics simulation model, simulation analysis is performed on the lifting coil, the moving coil and the holding coil of the control rod drive mechanism to obtain a curve of the motion state of each part during the lifting or lowering process as the power-on time changes, that is, a mapping relationship between the motion state and the current;

[0011] Step S7, define the action reliability, set the thresholds of the three key characteristic parameters of the lifting coil current pickup time, the moving coil current pickup time and the holding coil current pickup time according to the actual situation, establish the action reliability evaluation model, and apply the formula Reliability calculation is 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, reasonably designing the range of key characteristic parameters of the control rod drive mechanism in combination with the timing process under actual working conditions, and obtaining the relationship curve between the key characteristic parameters and the reliability through simulation of a multi-field dynamics simulation model;

[0013] Step S9, using a kernel density estimation method to optimize the efficiency of the reliability calculation algorithm;

[0014] Step S10, by defining a reliability range, the calculated continuous reliability is mapped into three operating states: excellent, medium and poor;

[0015] Step S11: Based on the specific structure and working principle of the control rod drive mechanism, a running state evaluation model integrating multi-source characteristic information is constructed. The evaluation model comprehensively evaluates the running state of the control rod drive mechanism from two parts: mechanical and electrical. The mechanical part includes the lifting coil current pull-in time, the moving coil current pull-in time and the holding coil current pull-in time. The electrical part includes the lifting coil resistance, the moving coil resistance and the holding coil resistance.

[0016] Step S12: using an operation status assessment model integrating multi-source characteristic information to assess the operation status of the control rod drive mechanism, and obtaining the operation status assessment results of each characteristic parameter, the mechanical part, the electrical part and the control rod drive mechanism as a whole.

[0017] Further, 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 the movement. When the lifting armature is in the lifting state, there are:

[0018]

[0019] Among them, F e is the electromagnetic force, F is the spring force, G is the gravity, F l is the load force, F w is the water resistance, f is other resistance, m is the mass of the lifting armature, x is the displacement of the lifting armature, t is the power-on time, the gravity G of the lifting armature is a constant, and the load force F l is the gravity of the drive rod assembly driven by the lifting armature, which is also a constant, and the water resistance F w This includes the water resistance directly encountered by the hook component during movement and the water resistance encountered by the drive rod component and the control rod component driven by it during movement. These two parts of water resistance will eventually be transmitted to the armature. The value of other resistance f is relatively small, and its influence on the movement state of the armature can be ignored.

[0020] Furthermore, the electromagnetic force F e It is expressed as:

[0021]

[0022] Where, Φ is the air gap flux, μ 0 is the magnetic permeability in vacuum, S is the area of ​​the gap magnetic resistance, N is the number of coil turns, I is the boost coil current, R c is the sum of fixed magnetic resistance, l g is the gap length between the lifting pole and the lifting armature, x is the lifting armature displacement, and the constraint condition is: 0≤x≤l g .

[0023] Furthermore, the current calculation formula is:

[0024]

[0025] Among them, 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 the change of x, so the current is a function of time t and displacement x;

[0026] The formula for calculating elastic force is: F = -k·Δx + F 0 , where k is a constant, Δx is the spring constant, which is determined by the material properties of the spring, and the negative sign indicates that the elastic force generated by the spring is in the opposite direction of its extension (or compression). 0 is the preload of the spring.

[0027] Furthermore, in step S7, when the pull-in time obeys a normal distribution, then:

[0028]

[0029] Among them, z is the current pickup time of each coil, μ t is the mean value of the current pull-in time of each coil, σ t is the standard deviation of the current pull-in time of each coil.

[0030] The present invention provides a control rod drive mechanism operation status assessment method that integrates multi-source characteristic information. First, real-time current signals are collected and preprocessed. Then, the continuous wavelet transform algorithm is used to extract operation characteristic parameters such as each action timing point in the monitored current signal. The key characteristic parameters that can accurately reflect the operation status of the drive mechanism are screened out, including the lifting coil current pull-in time, the moving coil current pull-in time and the holding coil current pull-in time. The uncertainty parameters in the design and manufacturing process of the control rod drive mechanism are considered, and the fluctuation range of the uncertainty parameters is described by using random variables. Random variable analysis is performed to define the operation reliability of the control rod drive mechanism. The physical mechanism of the control rod drive mechanism is analyzed by deeply analyzing the multi-field dynamics simulation model of the control rod drive mechanism. The control rod drive mechanism armature and coil are taken as the main body, and multi-field dynamics simulation analysis is carried out to simulate the dynamic behavior of the control rod drive mechanism, and various complex factors and interactions are considered. Through the detailed simulation of the dynamic response of the control rod drive mechanism under different conditions, the reliability curve of the key characteristic parameters is obtained, the intrinsic relationship between the key characteristic parameters and the operating state is analyzed, and the mapping relationship between the reliability and the operating state is established. Through the top-down hierarchical structure, multi-source characteristic information is integrated to construct a control rod drive mechanism operating state evaluation model that integrates multi-source characteristic information. The control rod drive mechanism operating state evaluation work is carried out according to the evaluation model, so as to evaluate the key characteristic parameters, parts and the overall operating state of the control rod drive mechanism. The control rod drive mechanism operating state evaluation method with multi-angle, multi-information source and multi-level structure proposed by the present invention integrates the multi-source characteristic information of the control rod drive mechanism, not only considers the physical characteristics of the control rod drive mechanism, but also integrates the engineering practice experience, which will greatly improve the efficiency and accuracy of the control rod drive mechanism operating state evaluation management, and provide a comprehensive and efficient analysis for the control rod drive mechanism operating state evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0032] Figure 1 It is a flow chart of a control rod drive mechanism operation status evaluation method integrating multi-source characteristic information provided by an embodiment of the present invention;

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

[0034] Figure 3 1 is a schematic diagram of extracting key feature points of a lifting coil current signal, a moving coil current signal and a holding coil current signal during a lifting process of a control rod drive mechanism provided by an embodiment of the present invention, wherein (1) is the extraction of key feature points of the lifting coil current signal during the lifting process, (2) is the extraction of key feature points of the moving coil current signal during the lifting process, and (3) is the extraction of key feature points of the holding coil current signal during the lifting process;

[0035] Figure 4 It is a curve diagram of the current variation over time obtained by dynamically simulating the three coils in the lifting process based on the multi-field dynamics simulation model provided by the embodiment of the present invention, wherein (1) is a curve of the lifting coil current variation over time in the lifting process, (2) is a curve of the moving coil current variation over time in the lifting process, and (3) is a curve of the holding coil current variation over time in 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 obtained by simulating the multi-field dynamics simulation model and a curve showing the reliability changing with the current pull-in time, wherein (1) is the probability distribution function of the current pull-in time of the lifting coil during the lifting process, (2) is the curve showing 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 showing 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 showing the reliability of the lifting process changing with the current pull-in time of the holding coil;

[0037] Figure 6 is a mapping relationship diagram between reliability and operating status evaluation provided by an embodiment of the present invention;

[0038] Figure 7 The control rod drive mechanism operation state assessment model provided by the embodiment of the present invention integrates multi-source characteristic information;

[0039] Figure 8 It is a flow chart of the control rod drive mechanism operating status evaluation provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] The control rod drive mechanism is a device used to drive the control rod in a nuclear power plant. It is generally composed of a drive rod component, a sealed shell component, a yoke coil component, a hook component, and a rod position detector component. The yoke coil component is installed on the outside of the sealed shell and includes various components such as three working coils: a lifting coil, a moving coil, and a holding coil. In the pole-armature assembly, after the coil is energized to generate a magnetic field, a magnetic force is generated between the pole and the armature. When a specific pole and the armature are attracted, the corresponding hook can be driven to move. The energization sequence of the three coils corresponds to the action sequence of the hook, thereby realizing the control of the lifting, lowering, holding or dropping of the control rod.

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

[0043] In the control rod drive mechanism of a nuclear reactor, a large amount of important data is generated in the component structure during the early design, working tasks and later maintenance stages. These data contain key characteristic parameters that reflect the operating status level of the control rod drive mechanism during operation, and are 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 is constructed, which can comprehensively and accurately assess and reflect the operating status of the control rod drive mechanism.

[0044] The present invention provides a control rod drive mechanism operating state evaluation method that integrates multi-source feature information, such as Figure 1 As shown, the method includes:

[0045] Step S1, preprocessing 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 control rod drive mechanism current signal is collected by a dedicated module, and the sampling frequency is 2KHz or 5KHz.

[0047] Step S2, the current signals of the three coils are processed in sections respectively, then a wavelet function is selected, a width range is determined, and a continuous wavelet transform algorithm is applied to extract characteristic parameters of each action timing point in the current signal;

[0048] During the operation of the control rod drive mechanism, the current of each set of coils changes periodically according to a certain timing sequence. Even at different stages of the same cycle, the current magnitude and state of different coils are different. Therefore, the current waveform of the complete action cycle is first extracted according to the action stage of the control rod drive mechanism, and then the current is segmented according to the current waveform characteristics of the three sets of coils. The characteristic parameters such as the action timing points in the intercepted current signal are analyzed. Taking the current waveform of the lifting coil in the lifting process as an example, Figure 2 As shown, then segment as Figure 3 As shown in (1) in the figure, the action timing points contained in the monitored current signal that can accurately reflect the operating state of the control rod drive mechanism are extracted through the continuous wavelet transform algorithm. The moving coil and the holding coil are also extracted in the same way. The extraction schematic diagrams are shown in Figure 3 As shown in (2) and (3).

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

[0050]

[0051] 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. S_mean and S_std are used to represent the mean and standard deviation of the area at the gap magnetic resistance, lg_mean and lg_std are used to represent the mean and standard deviation of the gap between the magnetic pole and the armature, respectively. c _mean and R c _std represents the mean and standard deviation of the fixed reluctance and respectively, as shown in the following table. Combined with the dimensional error of the control rod drive mechanism manufacturing process, based on the existing engineering experience, each random variable is made to obey the normal distribution, then:

[0052]

[0053] Changes in the clearance of the moving pairs of the control rod drive mechanism are often due to dimensional errors, which may be caused by the manufacturing process. Dimensional errors will affect the geometry and mutual fit of mechanical parts, and thus affect the clearance of the moving pairs. This change may cause instability and performance degradation of the control rod drive mechanism during operation. Therefore, it is necessary to set and solve the uncertainty parameters in combination with the errors in the manufacturing process.

[0054] Step S5, performing force analysis on the control rod drive mechanism, and then constructing a multi-field dynamics simulation model of the control rod drive mechanism, the multi-field dynamics simulation model including a current calculation module of the coil working circuit, 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, and based on uncertainty parameters, the above modules are used to calculate the coil current, the armature electromagnetic force, the elastic force, the water resistance, the gravity, and the load force, respectively;

[0055] Combined with the operation mechanism of the control rod drive mechanism, taking the lifting armature in the control rod drive mechanism as an example, it will be subjected to electromagnetic force, elastic force, gravity, water resistance and load force during the lifting process, and the force analysis is performed on it:

[0056]

[0057] Among them, F e is the electromagnetic force, F is the spring force, G is the gravity, F l is the load force, F w is the water resistance, f is other resistance, m is the mass of the lifting armature, x is the displacement of the lifting armature, t is the power-on time, among which the gravity G of the lifting armature is a constant, and the load force F l is the gravity of the drive rod assembly driven by the lifting armature, which is also a constant, and the water resistance F w Including the water resistance directly encountered by the claw component when it moves and the water resistance encountered by the driving rod component and the control rod component driven by it when they move. These two parts of water resistance will eventually be transmitted to the armature. The value of other resistance f is relatively small, and the influence on the movement state of the armature can be ignored.

[0058] Electromagnetic force F e It is expressed as:

[0059]

[0060] Where, Φ is the air gap flux, μ 0 is the magnetic permeability in vacuum, S is the area of ​​the gap magnetic resistance, N is the number of coil turns, I is the boost coil current, R c is the sum of fixed magnetic resistance, l g is the gap length between the lifting pole and the lifting armature, x is the lifting armature displacement, and the constraint condition is: 0≤x≤l g .

[0061] The current calculation formula is:

[0062]

[0063] Among them, 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 the change of 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+F 0

[0066] Where k is a constant, Δx is the spring constant, which is determined by the material properties of the spring, and the negative sign indicates that the elastic force generated by the spring is in the opposite direction of its extension (or compression). 0 is the preload of the spring.

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

[0068] Step S6, based on the multi-field dynamics simulation model, simulation analysis is performed on the lifting coil, the moving coil and the holding coil of the control rod drive mechanism to obtain a curve of the motion state of each part during the lifting or lowering process as the power-on time changes, that is, a mapping relationship between the motion state and the current;

[0069] Based on the multi-field dynamics simulation model of the control rod drive mechanism, the lifting process of each coil is dynamically simulated and the following results are obtained: Figure 4 The curves shown are the changes of the current waveforms of each coil with the power-on time.

[0070] Step S7, define the action reliability, set the thresholds of the three key characteristic parameters of the lifting coil current pickup time, the moving coil current pickup time and the holding coil current pickup time according to the actual situation, establish the action reliability evaluation model, and apply the formula Reliability calculation is performed on key characteristic parameters, where thres is the current pull-in time threshold of each coil set according to actual conditions, and t is the current pull-in time of each coil;

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

[0072]

[0073] Among them, z is the current pickup time of each coil, μ t is the mean value of the current pull-in time of each coil, σ t is the standard deviation of the current pull-in time of each coil;

[0074] In a working cycle of the control rod drive mechanism, there are strict time requirements for 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. Therefore, in order to ensure the smooth completion of an action step, it is required that the current pull-in time of these coils must be within a certain time. According to the function and performance requirements of the armature and the coil, combined with the general reliability definition of the components, the action reliability can be defined as the ability of the coil current pull-in time to meet the specified allowable lower limit requirements under its specified working conditions and within the specified working time, and the reliability is used to measure it.

[0075] Step S8, reasonably designing the range of key characteristic parameters of the control rod drive mechanism in combination with the timing process under actual working conditions, and obtaining the relationship curve between the key characteristic parameters and the reliability through simulation of a multi-field dynamics simulation model;

[0076] Based on the calculation of reliability, the uncertainty parameters are reasonably designed in combination with the timing process under actual working conditions. Taking the lifting coil as an example, the random variables are set to describe the fluctuation range of the uncertainty parameters as shown in the following table. The probability distribution function of the current pull-in time of the three coils in the lifting process and the curve of the reliability changing with the pull-in time are obtained through dynamic simulation of the multi-field dynamics simulation model, as shown in the figure below. Figure 5 shown.

[0077]

[0078] Step S9, using a kernel density estimation method to optimize the efficiency of the reliability calculation algorithm;

[0079] The kernel density estimation calculation method is used to optimize the efficiency of the reliability calculation algorithm, so that the operation status evaluation can be completed within the time of one step of the control rod drive mechanism. The reliability calculation involves integral operations. Traditional integral operation methods usually require strict integral calculations of the distribution function of the system performance. It is very time-consuming to calculate in a complex system such as a control rod drive mechanism. Therefore, a non-parametric statistical method such as kernel density estimation is used to optimize the efficiency of integral operations. Compared with traditional integral operations, it can produce results faster and realize real-time evaluation of the control rod drive mechanism.

[0080] Step S10, by defining a reliability range, the calculated continuous reliability is mapped into three operating states: excellent, medium and poor;

[0081] like Figure 6 As shown, the continuous reliability is mapped into three operating states: excellent, medium and poor, making the result more intuitive and convenient for understanding the overall operating status of the control rod drive mechanism. The range of reliability is defined for key characteristic parameters, which are divided into three operating states: excellent, medium and poor, and the operating status of the control rod drive mechanism is further fed back. The operating status level classification is shown in the following table:

[0082]

[0083] Step S11: Based on the specific structure and working principle of the control rod drive mechanism, a running state evaluation model integrating multi-source characteristic information is constructed. The evaluation model comprehensively evaluates the running state of the control rod drive mechanism from two parts: mechanical and electrical. The mechanical part includes the lifting coil current pull-in time, the moving coil current pull-in time and the holding coil current pull-in time. The electrical part includes the lifting coil resistance, the moving coil resistance and the holding coil resistance.

[0084] The operating status assessment model is as follows Figure 7 As shown in the figure, the evaluation model comprehensively analyzes the structure and function of the control rod drive mechanism, extracts the key characteristic parameters that affect the function of the control rod drive mechanism, and divides them down layer by layer until the bottom performance indicators cannot be further divided. There is a complex coupling relationship between these key characteristic parameters under the mechanical part. When all key characteristic parameters are in normal operation, the operation state of the mechanical part is normal; in the electrical part, the magnetic circuit composed of the energized coil, magnetic pole, armature and magnetic ring is related to the coil current and the armature position, and there must be coupling between the three coil magnetic circuits, which will affect each other. Facing the complex system of the control rod drive mechanism, it is difficult to intuitively and accurately know the changes of its electrical circuit in the dynamic process based on theoretical analysis and calculation. Therefore, when applied to actual engineering, the resistance operation state threshold can be dynamically adjusted according to the needs. Similar to the mechanical part, when all key characteristic parameters are in normal operation, the operation state of the electrical part is normal. This model not only considers the physical characteristics of the control rod drive mechanism, but also incorporates engineering practice experience, which can fully reflect the operation state of the control rod drive mechanism.

[0085] Step S12, using an operation status assessment model integrating multi-source characteristic information to assess the operation status of the control rod drive mechanism, and obtaining operation status assessment results of each key characteristic parameter, the mechanical part, the electrical part and the control rod drive mechanism as a whole;

[0086] The operation status evaluation model based on the fusion of multi-source feature information is modeled and calculated from the bottom up, using Figure 8 The process shown is used to evaluate the operating status of the control rod drive mechanism, and finally the operating status evaluation results of each key characteristic parameter, the mechanical part, the electrical part and the control rod drive mechanism as a whole can be obtained. The results are output in the form of scores and status levels, thereby completing the operating status evaluation 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, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements 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 control rod drive mechanism operating state assessment method integrating multi-source characteristic information, characterized in that: The method comprises: Step S1, preprocessing 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, processing the coil current signal in sections respectively, and then applying the continuous wavelet transform algorithm to extract the characteristic parameters of each action timing point in the current signal; Step S3, based on the extracted characteristic parameters of each action timing point, combined with existing engineering experience, screen and calculate the key characteristic parameters related to the control rod drive mechanism operation state evaluation, the key characteristic parameters including the lifting coil current pull-in time, the moving coil current pull-in time and the holding coil current pull-in time; Step S4, clarifying the uncertainty parameters in the design and manufacturing process of the control rod drive mechanism, and using 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 obeys a normal distribution; Step S5, performing force analysis on the control rod drive mechanism, and then constructing a multi-field dynamics simulation model of the control rod drive mechanism, the multi-field dynamics simulation model including a current calculation module of the coil working circuit, 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, and based on uncertainty parameters, the above modules are used to calculate the coil current, the armature electromagnetic force, the elastic force, the water resistance, the gravity, and the load force, respectively; Step S6, based on the multi-field dynamics simulation model, simulation analysis is performed on the lifting coil, the moving coil and the holding coil of the control rod drive mechanism to obtain a curve of the motion state of each part during the lifting or lowering process as the power-on time changes, that is, a mapping relationship between the motion state and the current; Step S7, define the action reliability, set the thresholds of the three key characteristic parameters of the lifting coil current pickup time, the moving coil current pickup time and the holding coil current pickup time according to the actual situation, establish the action reliability evaluation model, and apply the formula Reliability calculation is performed on key characteristic parameters, where thres is the coil current pull-in time threshold and t is the coil current pull-in time; Step S8, reasonably designing the range of key characteristic parameters of the control rod drive mechanism in combination with the timing process under actual working conditions, and obtaining the relationship curve between the key characteristic parameters and the reliability through simulation of a multi-field dynamics simulation model; Step S9, using a kernel density estimation method to optimize the efficiency of the reliability calculation algorithm; Step S10, by defining a reliability range, the calculated continuous reliability is mapped into three operating states: excellent, medium and poor; Step S11: Based on the specific structure and working principle of the control rod drive mechanism, a running state evaluation model integrating multi-source characteristic information is constructed. The evaluation model comprehensively evaluates the running state of the control rod drive mechanism from two parts: mechanical and electrical. The mechanical part includes the lifting coil current pull-in time, the moving coil current pull-in time and the holding coil current pull-in time. The electrical part includes the lifting coil resistance, the moving coil resistance and the holding coil resistance. Step S12: using an operation status assessment model integrating multi-source characteristic information to assess the operation status of the control rod drive mechanism, and obtaining operation status assessment results of each characteristic parameter, the mechanical part, the 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 the movement. When the lifting armature is in the lifting state, there are: Among them, F e is the electromagnetic force, F is the spring force, G is the gravity, F l is the load force, F w is the water resistance, f is other resistance, m is the mass of the lifting armature, x is the displacement of the lifting armature, t is the power-on time, the gravity G of the lifting armature is a constant, and the load force F l is the gravity of the drive rod assembly driven by the lifting armature, which is also a constant, and the water resistance F w This includes the water resistance directly encountered by the hook component during movement and the water resistance encountered by the drive rod component and the control rod component driven by it during movement. These two parts of water resistance will eventually be transmitted to the armature. The value of other resistance f is relatively small, and its influence on the movement state of the armature can be ignored.

3. The method according to claim 2, characterized in that Electromagnetic force F e It is expressed as: Where Φ is the air gap flux, μ0 is the magnetic permeability in vacuum, S is the area of ​​the gap reluctance, N is the number of coil turns, I is the boost coil current, and R c is the sum of fixed magnetic resistance, l g is the gap length between the lifting pole and the lifting armature, x is the lifting armature displacement, and the constraint condition is: 0≤x≤l g .

4. The method according to claim 2, characterized in that: The current calculation formula is: Among them, 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 the change of x, so the current is a function of time t and displacement x; The formula for calculating elastic force is: F=-kΔx+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 extension (or compression), and F0 is the preload of the spring.

5. The method according to claim 1, characterized in that In step S7, when the current pickup time obeys the normal distribution, then: Among them, z is the current pull-in time of each coil, μ t is the mean value of the current pull-in time of each coil, σ t is the standard deviation of the current pull-in time of each coil.

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