Steel bar crack damage identification method based on major frequency domain method

Abstract

The invention relates to a steel bar crack damage identification method based on a main effect frequency domain method. The method comprises the steps that piezoelectric sensors are arranged along the longitudinal surface of a steel bar at equal intervals in an array mode; acquiring an admittance-frequency response curve of each piezoelectric sensor; performing frequency band division on the admittance signal, and calculating a damage index in each frequency band; determining a main effect frequency domain of a decoupling damage position and a damage degree; calibrating a function relational expression; and carrying out positioning and quantitative prediction on the crack damage at any position on the reinforcing steel bar by utilizing the calibrated function relation. The method has the beneficial effects that the coupling influence of the damage position and the damage degree on the admittance signal is effectively decoupled in the selected main effect frequency domain, and the mapping relation between the damage index and the damage position and degree is constructed, so that accurate positioning and accurate quantitative evaluation of the steel bar crack damage are realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of steel bar damage detection, and in particular relates to a steel bar crack damage identification method based on a main effect frequency domain method. Background Art

[0002] Reinforced concrete structures are widely used in civil engineering construction due to their durability, fire resistance, and high moldability. Steel bars, due to their lightweight, high-strength, and excellent plasticity, are widely used in reinforced concrete structures. However, under the combined effects of loads and environmental factors, steel bars are prone to crack damage. This not only reduces bearing capacity and risks structural failure, but also accelerates steel corrosion, reduces durability, and increases safety risks. Therefore, steel bar crack damage detection is crucial for proactively identifying hidden safety hazards, preventing sudden structural failure, and protecting social property and personal safety.

[0003] Currently, the main methods for detecting rebar damage include ultrasonic guided waves, magnetic flux leakage detection, and piezoelectric impedance detection. Although piezoelectric impedance technology shows broad application prospects in the field of rebar damage detection, it still faces several challenges in practical engineering applications. For example, existing methods fail to effectively decouple the coupling effect between crack damage location and extent, resulting in chaotic superposition of admittance signals and difficulty in achieving simultaneous, precise location and quantitative assessment of damage. Therefore, the development of a rebar crack damage detection method that can decouple damage location and extent is particularly urgent.

[0004] Patent publication number CN109916999A, titled "A Method, Device, and System for Detecting Steel Bar Damage," works by using a magnetic field generator to transmit a low-frequency signal to a specific location on the component to be tested, causing eddy currents to be generated inside the steel bar at that location. Subsequently, a receiving device acquires the return signal from the location to be tested, thereby determining whether the steel bar inside the component to be tested is damaged. However, this method relies on low-frequency signals and eddy current effects, making it susceptible to interference when dealing with multiple layers of steel bars or complex structures. It also fails to effectively separate the coupling effects of damage location and degree on the signal, thus affecting the accuracy of the judgment. Summary of the Invention

[0005] The purpose of the present invention is to overcome the deficiencies in the prior art and provide a method for identifying steel bar crack damage based on the main effect frequency domain method, which can eliminate the coupling effect of the crack damage position and degree on the admittance signal, and realize the precise positioning and quantitative simultaneous evaluation of steel bar crack damage.

[0006] In a first aspect, a method for identifying steel bar crack damage based on a principal effect frequency domain method is provided, comprising:

[0007] S1, piezoelectric sensors are arranged in an array with equal spacing along the longitudinal surface of the steel bar, and the sensors are coupled to the substrate interface through epoxy resin adhesive;

[0008] S2. Using an impedance analyzer to collect the admittance-frequency response curve of each piezoelectric sensor within a specified frequency band;

[0009] S3. Define a damage index calculation formula, divide the admittance signal into frequency bands, and calculate the damage index in each frequency band; the damage index includes a damage location index and a damage degree index;

[0010] S4. Determine the main effect frequency domain of the decoupling damage location and damage degree through iterative calculation:

[0011] S5. Calibrate a functional relationship based on the main effect frequency domain of the damage location and damage degree and the damage index;

[0012] S6. Use the calibrated functional relationship to locate and quantitatively predict crack damage at any position on the steel bar.

[0013] Preferably, S1 includes:

[0014] S101. Treat the steel bar surface by using sandpaper to polish the piezoelectric sensor attachment area along the steel bar axis and thoroughly wipe the surface to remove the oxide layer, grease, and dust, increase the roughness, and ensure that the contact surface is clean.

[0015] S102, evenly applying glue to the piezoelectric sensor pasting area, installing the piezoelectric sensor to a designated position, applying voltage excitation, and grounding the bottom surface of the piezoelectric sensor;

[0016] S103, using a multimeter to check that the resistance between the two electrodes of the piezoelectric sensor is greater than a preset threshold to ensure the quality of the pasting;

[0017] S104. Continuously arrange piezoelectric sensors on the surface of the steel bar at a preset interval.

[0018] Preferably, S2 includes:

[0019] S201. Use an impedance analyzer at room temperature and determine the sweep frequency range, excitation voltage, and sampling frequency points;

[0020] S202 , connecting the piezoelectric sensor to the impedance analyzer, collecting the admittance signal of each piezoelectric sensor in turn, and generating an admittance-frequency response curve.

[0021] Preferably, in S3, the calculation formula of the damage location index is as follows:

[0022]

[0023] Among them, MF(σ 1i ) represents the damage location index of the i-th piezoelectric sensor, Y ijrepresents the admittance value of the i-th piezoelectric sensor under the j-th damage condition, f1 and f2 represent the starting point and end point of the frequency domain of the admittance signal used for damage location, respectively; Y 1j represents the admittance value of the first piezoelectric sensor under the jth damage condition;

[0024] The calculation formula of the damage degree index is as follows:

[0025]

[0026] Among them, MF(σ 2j ) represents the damage index of the piezoelectric sensor under the jth damage condition, Y i 0 represents the admittance value of the i-th piezoelectric sensor in the intact state, f3 and f4 respectively represent the starting point and end point of the frequency domain of the admittance signal used for damage quantification.

[0027] Preferably, S4 includes:

[0028] S401, dividing the entire frequency domain using a fixed step size, and calculating the damage location index and damage severity index in each frequency domain respectively; defining the difference between the maximum and minimum values ​​of the damage location index of each piezoelectric sensor in each frequency domain as k1, and the difference between the maximum and minimum values ​​of the damage severity index as k2;

[0029] S402, iteratively calculating the ratio of k1 to k2 in each frequency domain, and determining the maximum of the two ratios, i.e., max(k1 / k2) and max(k2 / k1);

[0030] S403. Determine the frequency domain corresponding to max(k1 / k2) as the main effect frequency domain [f1, f2] for damage location, and simultaneously determine the frequency domain corresponding to max(k2 / k1) as the main effect frequency domain [f3, f4] for damage quantification.

[0031] Preferably, S5 includes:

[0032] S501, in the main effect frequency domain [f1, f2], based on the distance between the piezoelectric sensor and the damage, establish the damage index MF (σ 1i ) and fitted the corresponding relationship between MF(σ 1i ) as a function of the damage location;

[0033] S502, in the main effect frequency domain [f3, f4], based on the damage degree, establish the damage index MF (σ 2j ) and fitted the corresponding relationship between MF(σ 2j ) is a functional relationship between the damage degree.

[0034] Preferably, S6 includes:

[0035] S601, the admittance signal collected by S2 is processed by S3 to S5, and then substituted into the MF (σ 1i ) and the damage position, thereby calculating the specific location of the crack damage and locating the damage;

[0036] S602: The admittance signal collected in S2 is processed in sequence from S3 to S5 and then substituted into the MF (σ 2j ) and the degree of damage, so as to accurately calculate the degree of crack damage and achieve accurate quantitative assessment of the damage.

[0037] In a second aspect, a steel bar crack damage identification system based on a principal effect frequency domain method is provided, which is used to execute any of the methods described in the first aspect, including:

[0038] A layout module is used to arrange piezoelectric sensors in an array with equal spacing along the longitudinal surface of the steel bar, and couple the sensors to the substrate interface through epoxy resin adhesive;

[0039] An acquisition module, used to acquire the admittance-frequency response curve of each piezoelectric sensor within a specified frequency band using an impedance analyzer;

[0040] A calculation module is used to define a damage index calculation formula, divide the admittance signal into frequency bands, and calculate the damage index in each frequency band; the damage index includes a damage location index and a damage degree index;

[0041] Iterative module, used to determine the main effect frequency domain of the decoupling damage location and damage extent through iterative calculation:

[0042] A calibration module, configured to calibrate a functional relationship based on the main effect frequency domain of the damage location and damage degree and the damage index;

[0043] The prediction module is used to locate and quantitatively predict crack damage at any position on the steel bar using the calibrated functional relationship.

[0044] According to a third aspect, a computer storage medium is provided, wherein a computer program is stored in the computer storage medium; when the computer program is executed on a computer, the computer executes any one of the methods described in the first aspect.

[0045] In a fourth aspect, an electronic device is provided, including:

[0046] Memory, used to store computer programs;

[0047] A processor is used to execute the computer program to implement any method as described in the first aspect.

[0048] The present invention provides a method for identifying steel bar damage based on the principal effect frequency domain method. This method effectively decouples the coupled effects of damage location and damage severity on the admittance signal within a selected principal effect frequency domain, constructing a mapping relationship between the damage index and the damage location and severity, thereby achieving precise location and accurate quantitative assessment of steel bar crack damage. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 1 is a flow chart of a method for identifying steel bar crack damage based on a principal effect frequency domain method provided by an embodiment of the present invention;

[0050] Figure 2 Schematic diagram of the arrangement of piezoelectric sheets for calibration test provided by an embodiment of the present invention;

[0051] Figure 3 is an admittance signal diagram of different damage locations provided by an embodiment of the present invention;

[0052] Figure 4 is an admittance signal diagram of different damage degrees provided by an embodiment of the present invention;

[0053] Figure 5 1 is a flow chart of the main effect frequency domain selection process provided by an embodiment of the present invention;

[0054] Figure 6 is the MF(σ provided by the embodiment of the present invention 1i )-damage position fitting relationship diagram;

[0055] Figure 7 is the MF(σ provided by the embodiment of the present invention 2j )-damage degree fitting relationship diagram;

[0056] Explanation of the accompanying drawings: 1: first piezoelectric sensor; 2: second piezoelectric sensor; 3: third piezoelectric sensor; 4: crack damage; 5: fourth piezoelectric sensor; 6: fifth piezoelectric sensor; 7: sixth piezoelectric sensor; 8: steel bar. DETAILED DESCRIPTION

[0057] The present invention will be further described below with reference to the following examples. The following examples are provided only to facilitate understanding of the present invention. It should be noted that, without departing from the principles of the present invention, it is possible for a person skilled in the art to make various modifications to the present invention, and such improvements and modifications fall within the scope of the claims of the present invention.

[0058] Example 1:

[0059] In order to solve the problems of the prior art, Example 1 of the present application provides a method for identifying steel bar crack damage based on the main effect frequency domain method. By selecting an effective characteristic frequency band to decouple the damage position and degree, it successfully solves the problem that the piezoelectric impedance signal is affected by the coupling of the two, and can simultaneously achieve accurate positioning and quantitative evaluation of crack damage in steel bars at any position.

[0060] Specifically, such as Figure 1 As shown in FIG, the steel bar crack damage identification method based on the main effect frequency domain method includes:

[0061] S1. Arrange piezoelectric sensors in an array with equal spacing along the longitudinal surface of the steel bar, and couple the sensors to the substrate interface through epoxy resin adhesive.

[0062] In S1, according to the actual size of the steel structure to be measured, the piezoelectric sensors are arranged in an array with equal intervals along its longitudinal surface. The interface between the sensor and the substrate is coupled using epoxy resin adhesive, which forms an effective stress wave conduction path after curing.

[0063] Specifically, S1 includes:

[0064] S101. Treat the surface of the steel bar. Use sandpaper to grind the piezoelectric sensor pasting area along the axis of the steel bar and wipe the surface thoroughly to remove the oxide layer, grease and dust, increase the roughness and ensure the contact surface is clean.

[0065] S102, evenly apply glue on the piezoelectric sensor pasting area, install the piezoelectric sensor to a designated position, apply voltage excitation and ground the bottom surface of the piezoelectric sensor.

[0066] For example, the glue coating thickness is recommended to be less than 0.1mm, covering 80% of the back surface of the piezoelectric sensor to avoid overflow. In addition, use non-metallic tweezers to gently press the piezoelectric sensor onto the designated position of the steel bar, apply a 1V voltage excitation, and ground the bottom surface of the piezoelectric sensor.

[0067] S103, using a multimeter to check that the resistance between the two electrodes of the piezoelectric sensor is greater than a preset threshold to ensure the pasting quality.

[0068] For example, the preset threshold is 1 MΩ, and in the event of a short circuit the piezoelectric sensor needs to be re-attached.

[0069] S104. Continuously arrange piezoelectric sensors on the surface of the steel bar at a preset interval d.

[0070] S2. Use an impedance analyzer to collect the admittance-frequency response curve of each piezoelectric sensor within a specified frequency band.

[0071] In S2, an impedance analyzer is used to perform a frequency sweep test on the deployed piezoelectric sensor array to obtain an admittance signal, and then the admittance-frequency response curve of each piezoelectric sensor can be formed.

[0072] Specifically, S2 includes:

[0073] S201. Use an impedance analyzer at room temperature and determine the sweep frequency range, excitation voltage, and sampling frequency points;

[0074] S202 , connecting the piezoelectric sensor to the impedance analyzer, collecting the admittance signal of each piezoelectric sensor in turn, and generating an admittance-frequency response curve.

[0075] S3. Define a damage index calculation formula, divide the admittance signal into frequency bands, and calculate the damage index in each frequency band; the damage index includes a damage location index and a damage degree index.

[0076] In S3, the calculation formula of the damage location index is as follows:

[0077]

[0078] Among them, MF(σ 1i ) represents the damage location index of the i-th piezoelectric sensor, Y ij represents the admittance value of the i-th piezoelectric sensor under the j-th damage condition, f1 and f2 represent the starting point and end point of the frequency domain of the admittance signal used for damage location, respectively; Y 1j represents the admittance value of the first piezoelectric sensor under the jth damage condition;

[0079] The calculation formula of the damage degree index is as follows:

[0080]

[0081] Among them, MF(σ 2j ) represents the damage index of the piezoelectric sensor under the jth damage condition, Y i 0 represents the admittance value of the i-th piezoelectric sensor in the intact state, f3 and f4 respectively represent the starting point and end point of the frequency domain of the admittance signal used for damage quantification.

[0082] S4. Determine the main effect frequency domain of the decoupling damage location and damage degree through iterative calculation.

[0083] Specifically, the variation pattern of the damage index in different frequency bands with the damage location and damage degree is obtained through iterative calculation, and the main effect frequency domain of the decoupled damage location and damage degree is determined.

[0084] S5. Calibrate a functional relationship based on the main effect frequency domain of the damage location and damage degree and the damage index.

[0085] Specifically, the functional relationship between the damage index and the damage position in the main effect frequency domain of damage positioning is calibrated; the functional relationship between the damage degree and the damage index is calibrated using the piezoelectric sensor closest to the damage position in the main effect frequency domain of damage quantification.

[0086] S6. Use the calibrated functional relationship to locate and quantitatively predict crack damage at any position on the steel bar.

[0087] Example 2:

[0088] Based on Example 1, Example 2 of the present application provides a more specific method for identifying steel bar crack damage based on the main effect frequency domain method, including:

[0089] S1. Arrange piezoelectric sensors in an array with equal spacing along the longitudinal surface of the steel bar, and couple the sensors to the substrate interface through epoxy resin adhesive.

[0090] For example, an HRB400 steel bar with a diameter of 12 mm and a length of 500 mm was used as the test object. A crack with a width of 1 mm and a length of l was introduced in the middle of the bar. The length l was gradually increased from 3 mm to 11 mm in 2-mm increments, for a total of five damage conditions: Conditions 1, 2, 3, 4, and 5. Three piezoelectric sensors were placed 50 mm apart on either side of the crack, with a spacing of 50 mm.

[0091] S2. Use an impedance analyzer to collect the admittance-frequency response curve of each piezoelectric sensor within a specified frequency band.

[0092] For example, an Agilent E4990A precision impedance analyzer was used to obtain the admittance signals of each piezoelectric sensor under different damage conditions and at different damage locations. The impedance analyzer's sweep frequency range was set from 1 to 600 kHz, the excitation voltage was maintained at 1V, and the sampling frequency was set at 600 points. The admittance test data was transmitted from the impedance analyzer to a computer for subsequent processing and analysis. The laboratory ambient temperature was maintained at approximately 20°C. Figure 3 Figure 2 is the admittance signal diagram at different damage locations. As the distance between the piezoelectric sensor and the damage increases, the admittance shows an overall decreasing trend. Figure 4 Figure 2 is the admittance signal diagram for different damage degrees. As the damage worsens, the admittance amplitude increases slightly.

[0093] S3. Define a damage index calculation formula, divide the admittance signal into frequency bands, and calculate the damage index in each frequency band; the damage index includes a damage location index and a damage degree index.

[0094] This application uses the root mean square deviation in the main effect frequency domain to quantify the difference in the admittance signal before and after damage in a specific frequency domain. The damage index MF (σ 1i ), used for damage location, this index reveals the law of admittance value changing with damage location. Figure 2 As shown in FIG, the MF(σ1) values ​​of the first piezoelectric sensor 1 and the second piezoelectric sensor 2 are calculated based on the admittance value of the third piezoelectric sensor 3. In addition, the damage index MF(σ1) for damage quantitative evaluation is defined. 2j ), explore the relationship between the admittance value and the damage degree, and calculate the MF(σ2) value of each damage condition based on the admittance value under the non-destructive condition.

[0095] S4. Determine the main effect frequency domain of the decoupling damage location and damage degree through iterative calculation.

[0096] S4 includes:

[0097] S401. Divide the entire frequency domain using a fixed step size (e.g., every 10 kHz is divided into one frequency band), and calculate the damage location index and damage severity index in each frequency domain respectively; and define the difference between the maximum and minimum values ​​of the damage location index of each piezoelectric sensor in each frequency domain as k1, and the difference between the maximum and minimum values ​​of the damage severity index as k2;

[0098] S402, iteratively calculating the ratio of k1 to k2 in each frequency domain, i.e., using the ratio of k1 to k2 in each frequency band as an iteration basis, systematically approaching the maximum values ​​of the two ratios, i.e., max(k1 / k2) and max(k2 / k1);

[0099] S403. After iterative calculation, the frequency domain corresponding to max(k1 / k2) is determined as the main effect frequency domain [f1, f2] for damage location, and the frequency domain corresponding to max(k2 / k1) is determined as the main effect frequency domain [f3, f4] for damage quantification.

[0100] Among them, iterative calculation is a numerical calculation method that successively approximates the optimal solution by recursively evaluating the ratio between k1 and k2 in each frequency band. The admittance signal in the frequency domain [f1, f2] is insensitive to changes in the damage degree, while the admittance signal in the frequency domain [f3, f4] is insensitive to changes in the damage location. Therefore, a linear relationship between MF (σ1) and damage location is fitted within [f1, f2] for damage location. The variation pattern of MF (σ2) with damage degree is obtained within [f3, f4] for damage quantification. Ultimately, the main effect frequency domain [f1, f2] for damage location is determined to be 360-370kHz, and the main effect frequency domain for damage quantification is determined to be 380-390kHz.

[0101] S5. Calibrate a functional relationship based on the main effect frequency domain of the damage location and damage degree and the damage index.

[0102] S5 includes:

[0103] S501. In the main effect frequency domain [f1, f2] (360-370kHz), the damage index MF (σ 1i ) and fitted the corresponding relationship between MF(σ 1i ) and the damage location, thereby achieving damage location in the subsequent S6.

[0104] For example, Figure 6 is MF(σ 1i )-damage position fitting relationship diagram, the fitting formula is:

[0105] RMMFS(σD 11i )=-0.1371x+6.597

[0106] Where x is the distance between the piezoelectric sensor and the damage, in cm.

[0107] S502, in the main effect frequency domain [f3, f4] (380-390kHz), based on the damage degree, establish the damage index MF (σ 2j ) and fitted the corresponding relationship between MF(σ 2j ) and the damage degree, so as to achieve quantitative damage assessment in the subsequent S6.

[0108] For example, Figure 7 is MF(σ 2j )-damage degree fitting relationship diagram, the fitting formula is:

[0109] RMMF(SσD 2j2 )=0.03706x+0.07167

[0110] Where x is the length of the crack damage, in mm.

[0111] S6. Use the calibrated functional relationship to locate and quantitatively predict crack damage at any position on the steel bar.

[0112] S6 includes:

[0113] S601, the admittance signal collected by S2 is processed by S3 to S5, and then substituted into the MF (σ 1i ) and the damage position, thereby calculating the specific location of the crack damage and locating the damage;

[0114] S602: The admittance signal collected in S2 is processed in sequence from S3 to S5 and then substituted into the MF (σ 2j ) and the degree of damage, so as to accurately calculate the degree of crack damage and achieve accurate quantitative assessment of the damage.

[0115] For example, damage location was performed using the formula in S501, and the results showed that the positioning error under different damage conditions was controlled within 3%. Furthermore, the damage extent was quantitatively assessed by combining the two piezoelectric sensors closest to the damage, and the damage extent was calculated using the formula in S502. The quantitative error under different damage levels did not exceed 5%.

[0116] It should be noted that the parts in this embodiment that are the same or similar to those in Example 1 can be referenced to each other and will not be described in detail in this application.

[0117] Example 3:

[0118] Based on Example 2, Example 3 of the present application provides a steel bar crack damage identification system based on the main effect frequency domain method, including:

[0119] A layout module is used to arrange piezoelectric sensors in an array with equal spacing along the longitudinal surface of the steel bar, and couple the sensors to the substrate interface through epoxy resin adhesive;

[0120] An acquisition module, used to acquire the admittance-frequency response curve of each piezoelectric sensor within a specified frequency band using an impedance analyzer;

[0121] A calculation module is used to define a damage index calculation formula, divide the admittance signal into frequency bands, and calculate the damage index in each frequency band; the damage index includes a damage location index and a damage degree index;

[0122] Iterative module, used to determine the main effect frequency domain of the decoupling damage location and damage extent through iterative calculation:

[0123] A calibration module, configured to calibrate a functional relationship based on the main effect frequency domain of the damage location and damage degree and the damage index;

[0124] The prediction module is used to locate and quantitatively predict crack damage at any position on the steel bar using the calibrated functional relationship.

[0125] It should be noted that the system provided in this embodiment is a system corresponding to the method provided in Example 2. Therefore, the parts in this embodiment that are the same or similar to those in Example 2 can be referenced to each other and will not be repeated in this application.

Claims

1. A steel bar crack damage identification method based on the main effect frequency domain method, characterized in that: include: S1, piezoelectric sensors are arranged in an array with equal spacing along the longitudinal surface of the steel bar, and the sensors are coupled to the substrate interface through epoxy resin adhesive; S2. Using an impedance analyzer to collect the admittance-frequency response curve of each piezoelectric sensor within a specified frequency band; S3. Define a damage index calculation formula, divide the admittance signal into frequency bands, and calculate the damage index in each frequency band; the damage index includes a damage location index and a damage degree index; S4. Determine the main effect frequency domain of the decoupling damage location and damage degree through iterative calculation: S5. Calibrate a functional relationship based on the main effect frequency domain of the damage location and damage degree and the damage index; S6. Use the calibrated functional relationship to locate and quantitatively predict crack damage at any position on the steel bar.

2. The steel bar crack damage identification method based on the main effect frequency domain method according to claim 1 is characterized in that: S1 includes: S101. Treat the steel bar surface by using sandpaper to polish the piezoelectric sensor attachment area along the steel bar axis and thoroughly wipe the surface to remove the oxide layer, grease, and dust, increase the roughness, and ensure that the contact surface is clean. S102, evenly applying glue to the piezoelectric sensor pasting area, installing the piezoelectric sensor to a designated position, applying voltage excitation, and grounding the bottom surface of the piezoelectric sensor; S103, using a multimeter to check that the resistance between the two electrodes of the piezoelectric sensor is greater than a preset threshold to ensure the quality of the pasting; S104. Continuously arrange piezoelectric sensors on the surface of the steel bar at a preset interval.

3. The steel bar crack damage identification method based on the main effect frequency domain method according to claim 2 is characterized in that S2 include: S201. Use an impedance analyzer at room temperature and determine the sweep frequency range, excitation voltage, and sampling frequency points; S202 , connecting the piezoelectric sensor to the impedance analyzer, collecting the admittance signal of each piezoelectric sensor in turn, and generating an admittance-frequency response curve.

4. The steel bar crack damage identification method based on the main effect frequency domain method according to claim 3 is characterized in that: In S3, the calculation formula of the damage location index is as follows: Among them, MF(σ 1i ) represents the damage location index of the i-th piezoelectric sensor, Y ij represents the admittance value of the i-th piezoelectric sensor under the j-th damage condition, f1 and f2 represent the starting point and end point of the frequency domain of the admittance signal used for damage location, respectively; Y 1j represents the admittance value of the first piezoelectric sensor under the jth damage condition; The calculation formula of the damage degree index is as follows: Among them, MF(σ 2j ) represents the damage index of the piezoelectric sensor under the jth damage condition, Y i 0 represents the admittance value of the i-th piezoelectric sensor in the intact state, f3 and f4 respectively represent the starting point and end point of the frequency domain of the admittance signal used for damage quantification.

5. The steel bar crack damage identification method based on the main effect frequency domain method according to claim 4 is characterized in that S4 include: S401, dividing the entire frequency domain using a fixed step size, and calculating the damage location index and damage severity index in each frequency domain respectively; defining the difference between the maximum and minimum values ​​of the damage location index of each piezoelectric sensor in each frequency domain as k1, and the difference between the maximum and minimum values ​​of the damage severity index as k2; S402, iteratively calculating the ratio of k1 to k2 in each frequency domain, and determining the maximum of the two ratios, i.e., max(k1 / k2) and max(k2 / k1); S403. Determine the frequency domain corresponding to max(k1 / k2) as the main effect frequency domain [f1, f2] for damage location, and simultaneously determine the frequency domain corresponding to max(k2 / k1) as the main effect frequency domain [f3, f4] for damage quantification.

6. The steel bar crack damage identification method based on the main effect frequency domain method according to claim 5 is characterized in that S5 include: S501, in the main effect frequency domain [f1, f2], based on the distance between the piezoelectric sensor and the damage, establish the damage index MF (σ 1i ) and fitted the corresponding relationship between MF(σ 1i ) as a function of the damage location; S502, in the main effect frequency domain [f3, f4], based on the damage degree, establish the damage index MF (σ 2j ) and fitted the corresponding relationship between MF(σ 2j ) is a functional relationship between the damage degree.

7. The steel bar crack damage identification method based on the main effect frequency domain method according to claim 6 is characterized in that S6 include: S601, the admittance signal collected by S2 is processed by S3 to S5, and then substituted into the MF (σ 1i ) and the damage position, thereby calculating the specific location of the crack damage and locating the damage; S602: The admittance signal collected in S2 is processed in sequence from S3 to S5 and then substituted into the MF (σ 2j ) and the degree of damage, so as to accurately calculate the degree of crack damage and achieve accurate quantitative assessment of the damage.

8. A steel bar crack damage identification system based on the main effect frequency domain method, characterized in that: Used to perform the method according to any one of claims 1 to 7, comprising: A layout module is used to arrange piezoelectric sensors in an array with equal spacing along the longitudinal surface of the steel bar, and couple the sensors to the substrate interface through epoxy resin adhesive; An acquisition module, used to acquire the admittance-frequency response curve of each piezoelectric sensor within a specified frequency band using an impedance analyzer; A calculation module is used to define a damage index calculation formula, divide the admittance signal into frequency bands, and calculate the damage index in each frequency band; the damage index includes a damage location index and a damage degree index; Iterative module, used to determine the main effect frequency domain of the decoupling damage location and damage extent through iterative calculation: A calibration module, configured to calibrate a functional relationship based on the main effect frequency domain of the damage location and damage degree and the damage index; The prediction module is used to locate and quantitatively predict crack damage at any position on the steel bar using the calibrated functional relationship.

9. A computer storage medium, characterized in that The computer storage medium stores a computer program; when the computer program is run on a computer, the computer executes the method according to any one of claims 1 to 7.

10. An electronic device, characterized in that: include: Memory, used to store computer programs; A processor, configured to execute the computer program to implement the method according to any one of claims 1 to 7.

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