Impedance matching cooperative control method for multi-frequency electromagnetic detection of composite material defects

Abstract

The application discloses an impedance matching cooperative control method for multi-frequency electromagnetic detection of composite material defects and relates to the electromagnetic detection field, and the implementation comprises the following processes: obtaining a defect type and a defect depth confidence degree output by an electromagnetic detection system, calculating error indexes, i.e., a defect false alarm rate and a defect missed detection rate, based on a false alarm rate and a missed detection rate of the defect type, calculating impedance matching coefficients and multi-frequency excitation weight configurations for the purpose of minimizing a target function constructed by the error indexes, generating a cooperative control strategy based on the updated impedance matching coefficients and the multi-frequency excitation weight, and storing the cooperative control strategy into a control logic module, and taking the generated cooperative control strategy as a driving script of a next round of detection tasks.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of electromagnetic detection, and particularly relates to an impedance matching and cooperative control method for multi-frequency electromagnetic detection of composite material defects. BACKGROUND

[0002] Multi-frequency excitation composite electromagnetic detection is a nondestructive testing method combining multi-frequency eddy current detection and magnetic flux leakage detection. The method utilizes the high sensitivity of multi-frequency eddy current detection for material surface and the characteristics of magnetic flux leakage detection for near-surface detection, and can effectively detect fatigue inclined cracks on the material surface and near-surface buried defects, which are the two most important defects on high-speed rails. According to different excitation and response signals, the material can be detected from the surface to the near-surface in all directions, and according to the depth information, various parameter information of the defects can be analyzed.

[0003] When the multi-frequency excitation electromagnetic detection technology is applied to composite materials, the electromagnetic field distortion caused by the anisotropic conductivity of the composite material will occur due to the characteristics of the composite material, such as anisotropy, multi-layer superposition, and non-uniform distribution of electrical conductivity. At this time, in the composite material, the anisotropic conductivity will distort the normal electromagnetic field when there is no defect, resulting in distorted or submerged defect data. Specifically, when the excitation coil sends power into the space magnetic field, if the radiation impedance of the coil itself does not match the coupling impedance in the current material environment, part of the energy will be bounced back to the coil, resulting in a weakened excitation field, a decreased signal-to-noise ratio, and submerged defect data. After the magnetic field enters the composite material, due to the anisotropy, stratification, and defects, local "magnetic-electric property mutations" will occur, causing secondary reflection (multiple scattering), resulting in detection signal distortion, increased defect quantization error, and distorted data. SUMMARY

[0004] The purpose of the present application is to provide an impedance matching and cooperative control method for multi-frequency electromagnetic detection of composite material defects, which is based on the impedance matching of the multi-frequency composite signal generated during the multi-frequency electromagnetic detection process and the composite material. On this basis, after the defect data of the composite material is detected according to the multi-frequency composite signal, feedback is performed for readjusting the impedance matching process in the multi-frequency composite signal generation process, thereby forming a closed-loop control, and solving the technical problems of fixed excitation parameters, control feedback lag, and system performance fluctuation in traditional electromagnetic detection methods.

[0005] The impedance matching and cooperative control method for multi-frequency electromagnetic detection of composite material defects comprises the following processes:

[0006] Step S100: Obtain the defect type and defect depth confidence of the output of the electromagnetic detection system, calculate the error index based on the false alarm rate and the missed detection rate of the defect type; defect false alarm rate and defect missed detection rate;

[0007] ;

[0008] wherein, represents the false positive rate of defect type ; represents the false negative rate of defect type ; represents the number of false recognition as defect type ; represents the number of true defect type not recognized; represents the number of correctly recognized defect type ;

[0009] Step S200: Calculate the impedance matching coefficient and the multi-frequency excitation weight configuration for the purpose of minimizing the objective function constructed by the error index;

[0010] The objective function is as follows:

[0011] ;

[0012] wherein, represents the spatial area covered by the current defect detection map; represents the preset risk weight of defect type (such as 0.5 for crack, 0.3 for delamination, and 0.2 for micro-pore); represents the depth confidence of defect type at position ; represents the total number of defect types; represents the false positive rate of defect type d at position x; represents the false negative rate of defect type d at position x;

[0013] The impedance matching coefficient optimization function is obtained for the purpose of minimizing the objective function:

[0014] ;

[0015] The multi-frequency excitation weight optimization function is obtained for the purpose of minimizing the objective function:

[0016] ;

[0017] wherein, : impedance matching coefficient at time ; : impedance adjustment step size coefficient; : current multi-frequency excitation weight vector; represents the excitation frequency band adjustment step size coefficient; denotes the gradient vector of the functional with respect to the excitation configuration; denotes the variational derivative of the functional with respect to the impedance matching coefficient.

[0018] Step S300: Based on the updated impedance matching coefficient and the multi-frequency excitation weight obtained in step S200, a collaborative control strategy is generated and stored in the control logic module.

[0019]

[0020] wherein, denotes the optimal collaborative control strategy; denotes the set of all feasible control strategies; denotes the selection from the set of all feasible control strategies denotes the time-space domain of the system operation phase; denotes the cost function between the control strategy and the impedance coefficient, the multi-frequency excitation configuration, and the system scenario constraint, respectively; denotes the constraint term;

[0021] Step S400: The generated collaborative control strategy is used as the driving script for the next round of detection task.

[0022] As a specific embodiment, the number of real defects not identified, the number of misidentified defect types, and the number of correctly identified defect types in step S100 are obtained from historical detection data, as follows:

[0023] The historical detection batch is sampled and sectioned for re-inspection. The historical detection data is compared to determine whether the historical detection result is correct, thereby obtaining the historical detection data of each defect, and thereby obtaining the number of real defects not identified, the number of misidentified defect types, and the number of correctly identified defect types.

[0024] As a specific embodiment, the cost function of the control strategy and the impedance coefficient is as follows:

[0025] ;

[0026] In the formula: and denote the weight coefficient; denotes the impedance of the probe under the control strategy C; denotes the target impedance of the composite material; denotes the maximum value of the impedance of the composite material; denotes the reflected power under the control strategy C and the impedance matching coefficient denotes the incident power.

[0027] ​​As an embodiment, the cost function of the control policy with respect to the multi-frequency excitation configuration is as follows:

[0028] ;

[0029] wherein: and denote the weight coefficients; denotes the weight of the kth frequency at time t+1; denotes the optimal weight of the kth frequency under the control policy C; denotes the standard deviation of the kth frequency; denotes the target signal-to-noise ratio; denotes the actual signal-to-noise ratio under the control policy C.

[0030] As an embodiment, the cost function of the control policy with respect to the system constraints is as follows:

[0031] ;

[0032] wherein: , , , denote the penalty weight of each constraint; denotes the total power consumption under the control policy C; denotes the power consumption budget of the system; denotes the system response time under the control policy C; the maximum allowed system response time; denotes the kth frequency; denotes the memory usage under the control policy C; denotes the memory usage limit; denotes 0 when the frequency fk is not in the range , otherwise 1.

[0033] As an embodiment, the collaborative control policy comprises: multi-frequency excitation timing control; impedance adjustment period setting; parallel signal acquisition scheduling; model update policy trigger signal control instruction.

[0034] As an embodiment, the multi-frequency excitation timing control denotes ;

[0035] ; ; ;

[0036] wherein: denotes the frequency the emission amplitude; the frequency the emission time; the frequency the switching interval time after emission, which depends on the system response time and ; the amplitude reference value; the weight of the kth frequency, obtained from the multi-frequency excitation weight vector; the total excitation time.

[0037] impedance adjustment period ;

[0038] wherein: the maximum adjustment period allowed by the system; a proportional constant; the impedance matching coefficient vector at the current time; the impedance matching coefficient vector at the previous time.

[0039] As a specific embodiment, the impedance adjustment period is as follows:

[0040] ;

[0041] wherein: the maximum adjustment period allowed by the system; a proportional constant; the impedance matching coefficient vector at the current time; the impedance matching coefficient vector at the previous time.

[0042] As a specific embodiment, the parallel signal acquisition scheduling:

[0043] ;

[0044] ;

[0045] ;

[0046] wherein: the frequency set responsible for acquisition by the mth acquisition channel; the weight of the frequency in all frequencies; the distribution threshold of the mth channel, the frequency whose weight ranking is higher than the threshold is distributed to the channel; the sampling rate of the mth channel; the maximum sampling rate allowed by the system; the oversampling coefficient; This represents the maximum frequency allocated in channel m; This represents the trigger delay time for the m-th channel; Indicates the basic synchronization delay; This represents a specific delay adjustment for channel m.

[0047] As one specific implementation method, the model update strategy trigger signal Including signal-to-noise ratio performance degradation trigger conditions Power reflection anomaly triggering conditions Impedance mismatch exceeding the limit triggering condition The details are as follows:

[0048] ;

[0049] ;

[0050] ;

[0051] ;

[0052] In the formula, This is an indicator function that takes the value 1 when the condition is true and 0 otherwise. Indicates the target signal-to-noise ratio; Indicates the actual signal-to-noise ratio; Indicates the signal-to-noise ratio trigger threshold; Indicates reflected power; Indicates incident power; Indicates the power transmit trigger threshold; Indicates the probe impedance; Indicates the target impedance of the composite material; This represents the maximum impedance of the composite material. This indicates the impedance mismatch trigger threshold.

[0053] Compared with existing technologies, it has the following advantages:

[0054] This invention, for the first time in the field of electromagnetic detection technology, proposes an edge closed-loop strategy that uses feedback error to drive the parameter adjustment of an electromagnetic detection system. This solves the technical problems of fixed excitation parameters and impedance excitation parameters, as well as control feedback lag in traditional electromagnetic detection methods.

[0055] This invention considers the constraints of the system scenario rather than pursuing only single detection performance (such as a high signal-to-noise ratio) while ignoring hardware system limitations. This makes the overall system performance more stable under dynamic load and multi-tasking conditions in the detection scenario.

[0056] In the application, the depth confidence and defect risk weight are introduced into the target function, so that the system can concentrate on optimizing the detection ability of high-risk defects by giving higher weight to high-risk defects.

[0057] In the application, the multi-frequency excitation timing control is included in the coordination strategy, so that the optimal excitation frequency can be adaptively adjusted for different defects, thereby improving the sensitivity of the detection system.

[0058] In the application, the model update strategy trigger signal is included in the coordination control strategy, so that when the performance of the detection system degrades, the parameters can be automatically updated and adjusted, so that the electromagnetic detection system can have stronger autonomy.

[0059] In the application, the detection system adjusts the impedance and excitation signal frequency of the probe through dynamic impedance coefficient and multi-frequency excitation weight adjustment, so that the detection system has stronger adjustability. BRIEF DESCRIPTION OF DRAWINGS

[0060] In order to more clearly illustrate the specific embodiments of the present application or the technical solutions in the prior art, the drawings needed in the specific embodiments or the prior art description will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application, and those skilled in the art can obtain other drawings without creative labor on the basis of these drawings.

[0061] Figure 1 is the flowchart shown in the present application. DETAILED DESCRIPTION

[0062] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0063] According to the embodiments of the present application, a multi-frequency electromagnetic detection composite material defect impedance matching cooperative control method is provided. It should be noted that the steps shown in the flowchart of the drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from here.

[0064] In the present embodiment, a multi-frequency electromagnetic detection composite material defect impedance matching cooperative control method is provided

[0065] In the existing electromagnetic detection of material defects, the electromagnetic detection system scans, and the response signal collected by the probe is mapped to form a three-dimensional visual expression according to the actual physical coordinates. This visual expression is defined as a detection map. The detection type and defect confidence can be determined by extracting the features of the detection signal and comparing the extracted features with the defects in the defect feature library.

[0066] Based on the prior art, as shown in Figure 1 , the impedance matching and collaborative control method for multi-frequency electromagnetic detection of composite material defects, the implementation process is as follows:

[0067] Step S100: Obtain the defect type and defect depth confidence output by the electromagnetic detection system, calculate the error index based on the false alarm rate and the missed detection rate of the defect type; defect false alarm rate and defect missed detection rate;

[0068] ;

[0069] In the formula, represents the false alarm rate of the defect type ; represents the missed detection rate of the defect type ; represents the number of false recognition as the defect type ; represents the number of true defect types not recognized; represents the number of correctly recognized defect types .

[0070] Step S200: Calculate the impedance matching coefficient and multi-frequency excitation weight configuration according to the minimization of the target function constructed by the error index.

[0071] The target function is as follows:

[0072] ;

[0073] In the formula, represents the spatial area covered by the current defect detection map; represents the preset risk weight of the defect type (such as 0.5 for cracks, 0.3 for delamination, and 0.2 for micro-pores); represents the depth confidence of the defect type at position ; represents the total number of defect types; represents the false alarm rate of the defect type d at position x; represents the missed detection rate of the defect type d at position x.

[0074] The following parameter (impedance matching coefficient) optimization function is derived by using variational method to solve the objective function with the objective of minimizing the objective function:

[0075] ;

[0076] The following parameter (multi-frequency excitation weight) optimization function is derived by using steepest descent algorithm constructed in vector form to solve the objective function with the objective of minimizing the objective function:

[0077] ;

[0078] wherein, : impedance matching coefficient at time ; : impedance adjustment step size coefficient (empirical value 0.01~0.1); : current multi-frequency excitation weight vector, such as : excitation frequency band adjustment step size coefficient; : gradient vector of functional with respect to excitation configuration; : variational derivative of functional with respect to matching coefficient.

[0079] Step S300: Based on the updated impedance matching coefficient and multi-frequency excitation weight obtained in step S200, a collaborative control strategy is generated and stored in the control logic module.

[0080] This step takes the updated impedance matching coefficient parameter and the multi-frequency excitation weight vector as the core input, constructs a type of multi-constrained scheduling collaborative control equation, and performs constraint mapping based on the optimality principle, which is defined as follows:

[0081]

[0082] wherein, represents the optimal collaborative control strategy; represents the set of all feasible control strategies; represents the selection from the set of all feasible control strategies ; represents the time and space domain of the system running phase; respectively represent the functional relationship between the control strategy and the impedance, multi-frequency excitation configuration, system scene constraint; represents the constraint term.

[0083] Step S400: The generated collaborative control strategy is used as the driving script for the next round of detection task.

[0084] In some feasible embodiments, the number of real defects not identified, the number of defects misidentified as defect types, and the number of correctly identified defect types in step S100 are obtained from historical detection data, as follows:

[0085] After sampling and sectioning the historical detection batch, ultrasonic and / or CT re-inspection (manual re-inspection if necessary) is performed, and the historical detection data are compared to determine whether the historical detection results are correct, thereby obtaining the historical detection data of each defect, and thereby obtaining the number of defect types misidentified, the number of defects not identified, and the number of accurately identified defects.

[0086] In some feasible embodiments, the feature data of the standard defects are obtained based on the standard defect detection atlas, which is implemented as follows:

[0087] A standard defect sample of the composite material is prepared, which has different types, sizes, and positions of defects pre-prepared thereon, covering the types of defects in the defect feature library. Then, an electromagnetic detection system is used to scan and detect each pre-prepared defect, and the collected detection data are mapped and associated with the defect types, sizes, and positions, thereby obtaining the standard defect features.

[0088] That is, in the present application, a defect database can be established, and for any defect type, the feature data and the historical detection data of the defect are recorded.

[0089] Specifically, in the present application, the impedance matching coefficient is a vector containing the PWM duty cycle, the excitation phase, and the capacitance value of the capacitance array.

[0090] In step S200, the objective function is constructed based on the error index. The objective function is an edge feedback loss functional, and its construction aims to express the feedback performance measurement under the coupling control of the three factors of spatial distribution consistency, defect type confidence weight, and error penalty, thereby providing a high-order objective function for subsequent parameter optimization. This optimization strategy is based on the optimal control theory and gradient optimization theory in functional analysis, solves the problem of the reverse influence of multiple dependent variables on the signal control model, and realizes the continuous and differentiable adjustment of the parameters.

[0091] In a specific implementation case, in step S300, the impedance matching function relationship is as follows:

[0092] ;

[0093] In the formula: and represent the weight coefficients; represents the impedance of the probe under the control strategy C; represents the target impedance of the composite material; represents the maximum value of the impedance of the composite material; represents the reflected power under control strategy C and impedance matching coefficient represents the reflected power under control strategy C and impedance matching coefficient represents the incident power.

[0094] The multi-frequency excitation function relationship is as follows:

[0095] ;

[0096] In the formula: and represent the weight coefficient; represents the weight of the kth frequency at t+1 time; represents the optimal weight of the kth frequency under control strategy C; represents the standard deviation of the kth frequency; represents the target signal-to-noise ratio; represents the actual signal-to-noise ratio under control strategy C.

[0097] The system constraint function relationship is as follows:

[0098] ;

[0099] In the formula: , , , represents the penalty weight of each constraint; represents the total power consumption under control strategy C; represents the power consumption budget of the system; represents the system response time under control strategy C; the maximum allowed system response time; represents the kth frequency; represents the memory usage under control strategy C; represents the memory usage limit; represents 0 when the frequency fk is not in the range , otherwise 1.

[0100] Further, in step S300, the finally generated collaborative control strategy includes: multi-frequency excitation timing control; impedance adjustment period setting; parallel signal acquisition scheduling; model update strategy trigger signal control instruction.

[0101] Multi-frequency excitation timing control represents ;

[0102] ; ; ;

[0103] wherein: denotes the emission amplitude of frequency ; denotes the emission time of frequency ; denotes the switching interval time after emission of frequency ; and denotes the amplitude reference value; denotes the weight of the kth frequency, obtained from the multi-frequency excitation weight vector; denotes the total excitation time.

[0104] impedance adjustment period as follows:

[0105] ;

[0106] wherein: denotes the maximum adjustment period allowed by the system; is a proportionality constant; denotes the impedance matching coefficient vector at the current time; denotes the impedance matching coefficient vector at the previous time.

[0107] Parallel signal acquisition scheduling:

[0108] ;

[0109] ;

[0110] ;

[0111] wherein: denotes the set of frequencies responsible for acquisition by the mth acquisition channel; denotes the rank position of the weight of frequency in all frequencies; denotes the allocation threshold of channel m, frequencies whose weight rank is higher than the threshold are allocated to this channel; denotes the sampling rate of the mth channel; denotes the maximum sampling rate allowed by the system; denotes the oversampling coefficient; denotes the maximum value of allocated frequencies in channel m; denotes the trigger delay time of the mth channel; denotes the basic synchronization delay; denotes the specific delay adjustment amount of channel m.

[0112] Model update strategy trigger signal The trigger condition includes a signal-to-noise ratio performance reduction trigger condition , a power reflection abnormality trigger condition , an impedance mismatch exceeding trigger condition , and the specific conditions are as follows:

[0113] ;

[0114] ;

[0115] ;

[0116] ;

[0117] In the formula, is an indicator function, which takes 1 when the condition is true, and 0 otherwise; represents the target signal-to-noise ratio; represents the actual signal-to-noise ratio; represents the signal-to-noise ratio trigger threshold; represents the reflected power; represents the incident power; represents the power emission trigger threshold; represents the probe impedance; represents the composite target impedance; represents the maximum value of the composite impedance; represents the impedance mismatch trigger threshold.

[0118] The present application is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, as well as combinations of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing apparatus to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing apparatus produce a device that implements the functions specified in the flowcharts and / or block diagrams. Figure 1 The device that implements the functions specified in one or more flows and / or blocks Figure 1 one or more blocks.

[0119] So far, the embodiments of the present disclosure have been described in detail. In order to avoid obscuring the concept of the present disclosure, some details known in the art are not described. Those skilled in the art can fully understand how to implement the technical solutions disclosed herein according to the above description. Those skilled in the art should understand that the above embodiments can be modified or some technical features can be replaced equivalently without departing from the scope and spirit of the present disclosure. The scope of the present disclosure is defined by the appended claims.

Claims

1. A method for impedance matching and coordinated control of multi-frequency electromagnetic detection of defects in composite materials, characterized in that, Its implementation includes the following processes: Step S100: Obtain the confidence level of the defect type and defect depth output by the electromagnetic detection system; calculate the error index based on the false alarm rate and false negative rate of the defect type; and the false alarm rate and false negative rate of the defect. ； In the formula, Indicates the defect type False alarm rate; Indicates the defect type The false detection rate; This indicates that it was mistakenly identified as a defect type. Quantity; Indicates the actual defect type Unidentified quantity; Indicates the correctly identified defect type quantity; Step S200: Calculate the impedance matching coefficient and multi-frequency excitation weight configuration with the aim of minimizing the objective function constructed from the error index; objective function as follows: ； In the formula, This indicates the spatial area covered by the current defect detection map; Indicates the defect type Preset risk weights; Indicates the location upper defect type The depth confidence; Indicates the total number of defect types; This represents the false alarm rate for defect type d at location x; This represents the rate of missed detection for defect type d at location x; With the objective function minimization as the goal, the impedance matching coefficient optimization function is obtained: ； With the objective function minimization as the goal, the multi-frequency excitation weight optimization function is obtained: ； in, :time The impedance matching coefficient; Impedance adjustment step size coefficient; : Current multi-frequency excitation weight vector; This indicates the step size coefficient for adjusting the excitation frequency band; Let represent the gradient vector of the functional with respect to the activation configuration; This represents the variational derivative of the functional with respect to the impedance matching coefficient; Step S300: Based on the updated impedance matching coefficient and multi-frequency excitation weight obtained in step S200, generate a cooperative control strategy and store it in the control logic module; ； in, This represents the optimal cooperative control strategy; Represents the set of all feasible control strategies; This represents the set of all feasible control strategies. Select from; The time-space domain represents the stage of system operation; These represent the cost functions between the control strategy and the impedance coefficient, the multi-frequency excitation configuration, and the system scenario constraints, respectively. Indicates constraint terms; Step S400: Use the generated collaborative control strategy as the driving script for the next round of detection tasks.

2. The impedance matching and coordinated control method for multi-frequency electromagnetic detection of composite material defects according to claim 1, characterized in that, The number of unidentified true defects and the number of defects misidentified as defect types in step S100, as well as the number of correctly identified defect types, are obtained from historical inspection data, as detailed below: After sampling and dissecting historical inspection batches for re-inspection, the results are compared with historical inspection data to determine whether the historical inspection results are correct. This yields historical inspection data for each defect, which in turn determines the number of unidentified defects, the number of defects misidentified as defect types, and the number of correctly identified defect types.

3. The impedance matching and coordinated control method for multi-frequency electromagnetic detection of composite material defects according to claim 1, characterized in that, The cost function of the control strategy and impedance coefficient is as follows: ； In the formula: and Indicates the weighting coefficient; This represents the impedance of the probe under control strategy C; Indicates the target impedance of the composite material; This represents the maximum impedance of the composite material. Indicates control strategy C and impedance matching coefficient The reflected power below; This indicates the incident power.

4. The impedance matching and coordinated control method for multi-frequency electromagnetic detection of composite material defects according to claim 1, characterized in that, The cost function of the control strategy and multi-frequency excitation configuration is as follows: ； In the formula: and Indicates the weighting coefficient; This represents the weight of the k-th frequency at time t+1; This represents the optimal weight for the k-th frequency under control strategy C; This represents the standard deviation of the k-th frequency; Indicates the target signal-to-noise ratio; This represents the actual signal-to-noise ratio under control strategy C.

5. The impedance matching and coordinated control method for multi-frequency electromagnetic detection of composite material defects according to claim 1, characterized in that, The cost function of the control strategy and system constraints is as follows: ； In the formula: , , , Indicates the penalty weight of each constraint; This represents the total power consumption under control strategy C; This represents the system's power consumption budget; This indicates the system response time under control strategy C; Maximum allowed system response time; Indicates the k-th frequency; This indicates the amount of memory used under control policy C; Indicates memory usage limits; This indicates that when frequency fk is not present The value is 0 if it is within the specified range, and 1 otherwise.

6. The impedance matching and coordinated control method for multi-frequency electromagnetic detection of composite material defects according to claim 1, characterized in that, Cooperative control strategy Includes: multi-frequency excitation timing control; impedance adjustment period setting; parallel signal acquisition scheduling; model update strategy trigger signal control instructions.

7. The impedance matching and coordinated control method for multi-frequency electromagnetic detection of composite material defects according to claim 6, characterized in that, Multi-frequency excitation timing control Represented as ; ； ； ； In the formula: Represents frequency The launch amplitude; Represents frequency Launch time; Represents frequency The switching interval after transmission depends on the system response time. and ; Indicates the amplitude reference value; The weight representing the k-th frequency is obtained from the multi-frequency excitation weight vector; Indicates the total incentive time; Impedance adjustment period ; In the formula: Indicates the maximum allowable adjustment period of the system; It is a proportionality constant; This represents the impedance matching coefficient vector at the current moment; This represents the impedance matching coefficient vector at the previous moment.

8. The impedance matching and coordinated control method for multi-frequency electromagnetic detection of composite material defects according to claim 6, characterized in that, Impedance adjustment period as follows: ； In the formula: Indicates the maximum allowable adjustment period of the system; It is a proportionality constant; This represents the impedance matching coefficient vector at the current moment; This represents the impedance matching coefficient vector at the previous moment.

9. The impedance matching and coordinated control method for multi-frequency electromagnetic detection of composite material defects according to claim 6, characterized in that, Parallel signal acquisition scheduling: ； ； ； In the formula: This represents the set of frequencies that the m-th acquisition channel is responsible for acquiring; Represents frequency The weight's ranking position among all frequencies; This represents the allocation threshold for channel m; frequencies with a weight ranking higher than this threshold are allocated to this channel. This represents the sampling rate of the m-th channel; Indicates the maximum allowed sampling rate of the system; Indicates the oversampling coefficient; This represents the maximum frequency allocated in channel m; This represents the trigger delay time for the m-th channel; Indicates the basic synchronization delay; This represents a specific delay adjustment for channel m.

10. The impedance matching and coordinated control method for multi-frequency electromagnetic detection of composite material defects according to claim 6, characterized in that, Model update strategy trigger signal Including signal-to-noise ratio performance degradation trigger conditions Power reflection anomaly triggering conditions Impedance mismatch exceeding the limit triggering condition The details are as follows: ； ； ； ; In the formula, This is an indicator function that takes the value 1 when the condition is true and 0 otherwise. Indicates the target signal-to-noise ratio; Indicates the actual signal-to-noise ratio; Indicates the signal-to-noise ratio trigger threshold; Indicates reflected power; Indicates incident power; Indicates the power transmit trigger threshold; Indicates the probe impedance; Indicates the target impedance of the composite material; This represents the maximum impedance of the composite material. This indicates the impedance mismatch trigger threshold.

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