Cable aluminum sheath defect grading detection method based on multi-frequency guided waves

Abstract

The invention relates to the technical field of ultrasonic detection, in particular to a cable aluminum sheath defect grading detection method based on multi-frequency guided waves, which comprises the following steps: determining propagation characteristics of each guided wave mode according to a frequency dispersion curve, and determining excitation frequency for detecting a main mode based on the propagation characteristics; arranging and installing a transducer array on the cable aluminum sheath; according to the coarse screening main modal frequency, low-frequency guided waves are emitted, guided wave echo signals are collected, and low-frequency guided wave coarse screening is carried out to determine a suspected defect interval; and transmitting ultrasonic guided waves to the suspected defect interval according to the fine screening main modal frequency, accurately positioning the suspected defect interval, determining a comprehensive score through multi-feature weighting calculation, and determining a defect grade according to the comprehensive score. Low-frequency guided wave coarse screening is combined with wavelet transform and entropy verification, a suspected defect interval can be quickly locked, high-frequency fine screening extracts multi-dimensional defect features through variational mode decomposition, and accurate positioning of defect positions and scientific judgment of grades are achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ultrasonic detection, in particular to a cable aluminum sheath defect grading detection method based on multi-frequency guided waves. BACKGROUND

[0002] As a key component of high-voltage cables in power systems, the cable aluminum sheath plays an important role in protecting high-voltage cables. First, as a waterproof barrier for cables, the aluminum sheath can effectively prevent water from entering and avoid water treeing, thereby ensuring that the insulation layer of the cable is not damaged and playing a waterproof isolation role. Second, the aluminum sheath must meet the requirements of current carrying capacity and its duration during short circuit of high-voltage power systems, so it needs to have excellent thermal stability to withstand high temperature and current impact caused by short circuit. However, the cable aluminum sheath is easily affected by the installation environment, and temperature changes, vibration, ground subsidence, etc. after being put into use will cause mechanical damage; acidic substances in humid environments, electrochemical corrosion, and biological erosion will accelerate aging damage and affect the safety of the power grid, so efficient and accurate non-destructive testing of the cable aluminum sheath is needed.

[0003] Traditional pulse echo ultrasonic and eddy current detection technologies are limited by attenuation and coupling conditions, especially when conducting online detection over a distance of hundreds of meters, their precision and efficiency cannot meet the real-time monitoring needs of high-voltage cable aluminum sheaths. It is difficult to effectively overcome the contradiction between low-frequency signal attenuation and high-frequency signal resolution. Although guided wave technology can rely on multiple reflections of the cavity wall to achieve long-distance propagation, single frequency has a trade-off problem between propagation distance and spatial resolution, low-frequency guided waves have small attenuation but are difficult to accurately locate, and high-frequency guided waves have high resolution but cannot achieve long-distance coverage. SUMMARY

[0004] To solve the above problems, the first aspect of the present application provides a cable aluminum sheath defect grading detection method based on multi-frequency guided waves, comprising: Based on the geometric size and material parameters of the cable aluminum sheath, an ultrasonic guided wave wave motion control equation is established, a frequency equation is derived according to the boundary conditions, and the phase velocity and group velocity dispersion curves of the torsional mode and longitudinal mode are obtained; According to the dispersion curve, the propagation characteristics of each guided wave mode are determined, and the excitation frequency of the detection main mode is determined based on the propagation characteristics, the excitation frequency of the detection main mode including the coarse screening main mode frequency and the fine screening main mode frequency; The transducer array is installed on the cable aluminum sheath, and the mode control parameters of the transducer array are set; The transducer array is driven to emit low-frequency guided waves according to the coarse screening main mode frequency and collect guided wave echo signals, and a low-frequency guided wave coarse screening is performed to determine the suspected defect interval; The mobile transducer array is moved to a suspected defect interval, ultrasonic guided waves are emitted to the suspected defect interval according to a main mode frequency of fine screening, the suspected defect interval is accurately positioned, and defect characteristics of a high-frequency guided wave echo signal are extracted; defect characteristics of multiple frequency bands are acquired respectively, a comprehensive score is determined through multi-feature weighted calculation, and a defect grade is determined according to the comprehensive score.

[0005] The ultrasonic guided wave wave motion control equation is established, the dispersion relation is derived by combining the boundary conditions, the phase velocity and group velocity dispersion curves of the torsional mode and the longitudinal mode are obtained, and the specific method is as follows: The ultrasonic guided wave wave motion control equation of the isotropic elastic medium is established; The isotropic elastic medium vector is subjected to Helmholtz decomposition to obtain an expansion scalar potential function and an isochoric vector function, and the scalar potential and the vector potential control equation is obtained by substituting the ultrasonic guided wave wave motion control equation; The boundary conditions and the displacement components of the particles of the cable aluminum sheath are given, the ultrasonic guided wave wave motion control equation is solved to determine the frequency equation, and the torsional mode and the longitudinal mode are determined; The geometric size and material parameters of the cable aluminum sheath are substituted into the frequency equation to obtain the dispersion curves of the torsional mode and the longitudinal mode.

[0006] The transducer array adopts a wideband ring-shaped piezoelectric transducer array, the wideband ring-shaped piezoelectric transducer array comprises a plurality of piezoelectric sheet assemblies and a ring-shaped base, a plurality of grooves are arranged at equal intervals on the inner side surface of the ring-shaped base, and a piezoelectric sheet assembly is pasted and mounted in each groove, the piezoelectric sheet assembly comprises a piezoelectric sheet and a damping rubber sheet, the damping rubber sheet is attached to the back surface of the piezoelectric sheet, and is used for absorbing non-target mode reverse energy, weakening structural resonance and expanding effective bandwidth; a receiving wire reserved channel is arranged between adjacent two grooves, a signal line electrically connected with the piezoelectric sheet is mounted in the receiving wire reserved channel, and is used for receiving a detection signal of a single piezoelectric sheet; an excitation wire reserved channel is arranged on the outer ring of the ring-shaped base, and is used for connecting a high-voltage excitation line.

[0007] The specific method for performing low-frequency guided wave coarse screening to determine the suspected defect interval is as follows: The defect position is determined according to the first wave arrival time of the guided wave echo signal, the guided wave propagation speed and the emission time; A spatial distance difference threshold is set to group the guided wave echo signals; the spatial distance difference of two echoes is calculated and compared with the spatial distance difference threshold to determine the suspected defect interval.

[0008] The cable aluminum sheath defect grading detection method further comprises verifying the suspected defect interval through wavelet change and entropy value verification, and the specific method is as follows: The guided wave echo signal is subjected to continuous wavelet transform: wherein, is a scale parameter, is a translation parameter, is a mother wavelet; s(t) is a guided wave echo signal; According to the continuous wavelet transform, energy distribution is obtained The signal energy entropy is calculated as: wherein, p i is the energy proportion at the i th scale; The signal energy entropy H of each guided wave echo signal in the suspected defect interval is compared with the energy entropy abnormal value, and if it exceeds the energy entropy abnormal value, the suspected defect interval is verified to be effective.

[0009] The suspected defect interval is accurately positioned, and the defect characteristics of the high-frequency guided wave echo signal are extracted, specifically: The high-frequency guided wave echo signal is subjected to variational mode decomposition to obtain each modal component; The defect characteristics are calculated based on each modal component, and the defect characteristics include envelope peak value, instantaneous frequency and energy; The envelope peak value time is determined according to the envelope peak value, and the accurate defect position is determined according to the guided wave emission time.

[0010] The comprehensive score is determined by multi-feature weighted calculation, and the formula is: wherein, represents the envelope amplitude at the defect position; represents the energy at the defect position; represents the instantaneous frequency at the defect position; represents the time difference at the defect position; is a defect-free state reference parameter; is an empirical weight coefficient, satisfying .

[0011] The second aspect of the present application also provides a cable aluminum sheath defect grading detection system based on multi-frequency guided waves, which is used to realize the cable aluminum sheath defect grading detection method based on multi-frequency guided waves, and comprises: A dispersion calculation module is used to establish an ultrasonic guided wave fluctuation control equation based on the geometric size and material parameters of the cable aluminum sheath, derive a frequency equation according to boundary conditions, and obtain the phase velocity and group velocity dispersion curves of the torsional mode and the longitudinal mode. ​​​The frequency determination module is used for determining the propagation characteristics of each guided wave mode according to the dispersion curve, and determining the excitation frequency of the detection main mode based on the propagation characteristics, wherein the excitation frequency of the detection main mode includes a coarse screening main mode frequency and a fine screening main mode frequency. The parameter setting module is used for setting the mode control parameters of the transducer array. The defect detection module is used for driving the transducer array to emit low-frequency guided waves according to the coarse screening main mode frequency and collect guided wave echo signals, and perform low-frequency guided wave coarse screening to determine a suspected defect interval. The defect detection module is also used for emitting ultrasonic guided waves to the suspected defect interval according to the fine screening main mode frequency, accurately positioning the suspected defect interval, and extracting defect features of high-frequency guided wave echo signals; the defect features of multiple frequency bands are acquired respectively, a comprehensive score is determined through multi-feature weighted calculation, and a defect grade is determined according to the comprehensive score.

[0012] The third aspect of the present application also provides a cable aluminum sheath defect grading detection method based on multi-frequency guided waves, comprising a processor and a memory, wherein the processor realizes the cable aluminum sheath defect grading detection method based on multi-frequency guided waves as described above when executing the computer program stored in the memory.

[0013] The fourth aspect of the present application provides a computer readable storage medium for storing a computer program, wherein the computer program is executed by a processor to realize the cable aluminum sheath defect grading detection method based on multi-frequency guided waves as described above.

[0014] The beneficial effect is that the present application is a cable aluminum sheath defect grading detection method based on multi-frequency guided waves, which obtains accurate dispersion curves by Helmholtz decomposition and boundary condition correction, combines cable aluminum sheath geometry and material parameters, realizes accurate characterization of the propagation characteristics of torsional and longitudinal modes, and provides a theoretical basis for mode selection; the guided wave dispersion curve is calculated based on the geometry and material parameters of the cable aluminum sheath, and the low-frequency long-distance main mode is optimized for coarse screening; and high-frequency guided waves are excited to perform high-resolution fine positioning on the suspected interval.

[0015] By installing a wideband ring-shaped piezoelectric transducer array in the wave trough region, the coupling efficiency of the axisymmetric mode is improved, the non-target mode is suppressed, and the effective bandwidth is widened, thereby ensuring the quality of the excitation and reception signals.

[0016] At the same time, the low-frequency guided wave coarse screening combined with wavelet transform and entropy verification can quickly lock the suspected defect interval, improve the detection efficiency and reduce misjudgment; the high-frequency fine screening extracts multi-dimensional defect features through variational mode decomposition, combines a multi-feature weighted comprehensive score function, realizes accurate positioning of the defect position and scientific judgment of the grade, and improves the accuracy and reliability of defect detection. BRIEF DESCRIPTION OF DRAWINGS

[0017] The objectives, technical solutions and merits of the exemplary embodiments of the present application will become more apparent after reading the following detailed description of the preferred embodiments. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present application.

[0018] In the drawings: Figure 1 Flow chart of the cable aluminum sheath defect grading detection method based on multi-frequency guided waves; Figure 2 Local coordinate system of the cable aluminum sheath of the corrugated pipe structure; Figure 3 Structure diagram of the broadband annular piezoelectric transducer array; 1, piezoelectric sheet assembly; 2, groove; 3, excitation wire reserved channel; 4, receiving wire reserved channel. DETAILED DESCRIPTION

[0019] In order to make the objectives, technical solutions and merits of the exemplary embodiments of the present application clearer, the technical solutions in the exemplary embodiments of the present application are described clearly and completely below. Obviously, the described exemplary embodiments are only some of the embodiments of the present application, not all.

[0020] Embodiment 1 This embodiment takes the high-voltage insulated cable aluminum sheath as the detection object, and the cable aluminum sheath is of a corrugated pipe structure. The specific implementation process of the cable aluminum sheath defect grading detection method based on multi-frequency guided waves is described in detail.

[0021] Referring to Figure 1 , the method specifically implements the following steps: S1, based on the geometric size and material parameters of the cable aluminum sheath, an ultrasonic guided wave wave motion control equation is established, a frequency equation is derived according to the boundary conditions, and the phase velocity and group velocity dispersion curves of the torsional mode and the longitudinal mode are obtained; The high-voltage insulated cable aluminum sheath selected in this embodiment has the following geometric parameters: inner radius r1=42mm, outer radius r2=47mm, corrugated period T=50mm, and corrugated amplitude h=5mm. The material parameters are: Young's modulus E=70GPa, Poisson's ratio 0.33, density ρ=2700kg / m 3 , longitudinal wave speed c L =6300m / s, and transverse wave speed c S =3100m / s.

[0022] Since the cable aluminum sheath is of a corrugated pipe structure, the propagation process of the ultrasonic guided wave in the cable aluminum sheath is an elastic wave propagation process.

[0023] The dispersion relation is derived by combining the boundary conditions to obtain the phase velocity and group velocity dispersion curves of the torsional mode and the longitudinal mode, and the specific method is as follows: S101, the ultrasonic guided wave wave motion control equation of the isotropic elastic medium is: Wherein, lambda and mu are Lame constants, lambda is approximately 3.67*1010Pa, mu is approximately 2.61*1010Pa; u represents the displacement vector of the isotropic medium; and p is the density of the aluminum sheath. It is a three-dimensional Laplace operator.

[0024] S102, the isotropic elastic medium vector is decomposed by Helmholtz to obtain the dilatational scalar potential function and the isochoric vector function, which is substituted into the ultrasonic guided wave wave motion control equation to obtain the control equation of the scalar potential and the vector potential; The isotropic elastic medium vector is decomposed by Helmholtz, , wherein, is the dilatational scalar potential function, is the isochoric vector function.

[0025] Substituted into the ultrasonic guided wave wave motion control equation to obtain: .

[0026] S103, the boundary conditions of the cable aluminum sheath and the displacement component of the particle are given, and the ultrasonic guided wave wave motion control equation is solved to determine the frequency equation, and the torsional mode and the longitudinal mode are determined. For an infinite long pipeline, the stress-free boundary condition is .

[0027] The displacement component of the particle is given as: .

[0028] Solving the wave equation can obtain the corresponding displacement field.

[0029] When the aluminum sheath guided wave detection is carried out, the L(0,2) mode and the T(0,1) mode are usually used, the L(0,2) mode is a single mode propagation, the frequency dispersion coefficient is <0.01 m / (s*Hz), the axial attenuation coefficient is <0.2 dB / m, and the long-distance propagation requirement is met; the transverse resolution of the T(0,1) mode can reach 1 cm, and there is no aliasing with other modes, and the precise positioning requirement is met. These two modes are axisymmetric modes, so n=0 is taken, and the frequency equation is: .

[0030] The frequency equation is decomposed as: , , .

[0031] wherein, and respectively correspond to the longitudinal mode and the torsional mode.

[0032] S104, substituting the geometric size and material parameters of the cable aluminum sheath into the frequency equation to obtain the dispersion curves of the torsional mode and the longitudinal mode.

[0033] Meanwhile, for the corrugated pipe structure of the cable aluminum sheath, the S103 further includes modifying the boundary conditions of the corrugated pipe structure, and the boundary conditions of the cable aluminum sheath are that the three stress components in the tangent plane of the boundary function are zero.

[0034] As shown in Figure 2 , a local coordinate system of the corrugated pipe structure of the cable aluminum sheath is established, the angle between the new coordinate system and the original cylindrical coordinate system is , and the coordinate transformation matrix is: In the formula, .

[0035] Based on the coordinate transformation matrix, the stress state matrix in the new coordinate system is obtained, the original stress matrix is solved by displacement components, and the dispersion curves of the phase velocity and the group velocity of the corrugated pipe torsional mode and the longitudinal wave mode can be obtained.

[0036] S2, determining the propagation characteristics of each guided wave mode according to the dispersion curve, and determining the excitation frequency of the detection main mode based on the propagation characteristics, the excitation frequency of the detection main mode including the coarse screening main mode frequency and the fine screening main mode frequency; The propagation characteristics of each guided wave mode are determined according to the dispersion curve calculated by each guided wave mode, including the phase velocity, the group velocity and the change trend of the frequency.

[0037] Through screening of the frequency curve, the frequency band with low dispersion, concentrated ability and high mode number stability is selected as the excitation frequency of the detection main mode. Among them, the 20kHz-60kHz frequency band is preferably selected as the coarse screening main mode frequency; 120kHz is selected as the fine screening main mode frequency.

[0038] S3, arranging and installing a transducer array on the cable aluminum sheath, and setting the mode control parameters of the transducer array; In this embodiment, a wideband ring piezoelectric transducer array is arranged and installed on the surface of the cable aluminum sheath. As Figure 3As shown, the broadband annular piezoelectric transducer array comprises a plurality of piezoelectric sheet assemblies 1 and an annular base, the inner side of the annular base is provided with a plurality of grooves 2 at equal intervals, and each groove 2 is provided with a piezoelectric sheet assembly 1 pasted and mounted therein, the piezoelectric sheet assembly 1 comprises a piezoelectric sheet and a damping rubber sheet, the damping rubber sheet is attached to the back of the piezoelectric sheet, used for absorbing non-target modal reverse energy, weakening structural resonance and expanding effective bandwidth; a receiving wire reserved channel 4 is arranged between two adjacent grooves 2, the receiving wire reserved channel 4 is provided with a signal line electrically connected with the piezoelectric sheet, used for receiving the detection signal of a single piezoelectric sheet; an excitation wire reserved channel 3 is arranged on the outer ring of the annular base, used for connecting a high-voltage excitation line to excite each piezoelectric sheet assembly 1 to perform ultrasonic detection.

[0039] By arranging the broadband annular piezoelectric transducer array on the outer wall of the cable aluminum sheath corrugated pipe structure, the broadband annular piezoelectric transducer array is preferentially attached to the valley area, i.e. the position with the minimum radial height of the pipe wall, which has the highest coupling efficiency for the axisymmetric modal, and can meet the amplitude margin of low-frequency long-distance excitation and high-frequency precise positioning excitation.

[0040] In addition, due to the unevenness of the valley surface, a dry coupling agent coating is arranged on the valley surface of the cable aluminum sheath corrugated pipe structure before the transducer array is installed; the dry coupling agent is epoxy resin glue, the coating is scraped flat to the same height as the peak surface to form a unified transducer array installation plane, so as to balance the low-frequency coupling stability and high-frequency interface flatness.

[0041] The modal control parameters are designed to improve the excitation efficiency of the selected modal, the frequency domain excitation parameters are adjusted, the excitation signal adopts a Gaussian modulated sinusoidal pulse with a center frequency of the selected frequency band and a period number of 3-5 periods, so as to control the frequency bandwidth within 10 kHz, thereby improving the modal energy concentration and suppressing the excitation of non-target modal.

[0042] S4, driving the transducer array to emit low-frequency guided waves according to the main modal frequency of the rough screening and collect guided wave echo signals to perform low-frequency guided wave rough screening to determine a suspected defect interval; Driving the transducer array to excite a Gaussian modulated sinusoidal pulse of 3-5 periods in the cable aluminum sheath to obtain long-distance propagation echo.

[0043] The method for performing low-frequency guided wave rough screening to determine a suspected defect interval is as follows: S4.1, determining the defect position according to the first wave arrival time of the guided wave echo signal, according to the guided wave propagation speed and the emission time, the formula is as follows: Wherein, represents the guided wave propagation speed; t0 is the emission time; t iis the first wave arrival time of the i-th defect echo; L i is the defect position.

[0044] S4.2, set the spatial distance difference threshold to group the guided wave echo signals; according to the time difference between two echoes, calculate the spatial distance difference and compare it with the spatial distance difference threshold to determine the suspected defect interval; Set the spatial distance difference threshold L th Obtain the time difference between two echoes Then the spatial distance difference is: If , the two echoes belong to the same defect multiple reflection group; if , the defect position of the echo is classified into the suspected defect interval.

[0045] Meanwhile, the S4 also includes verifying the suspected defect interval through wavelet change and entropy value verification.

[0046] Continuous wavelet transform is performed on the guided wave echo signal: In the formula, is the scale parameter, is the translation parameter, is the mother wavelet; s(t) is the guided wave echo signal.

[0047] According to the energy distribution obtained by continuous wavelet transform , the signal energy entropy is calculated as: Where, p i is the energy proportion at the i-th scale.

[0048] Compare the signal energy entropy H of each guided wave echo signal in the suspected defect interval with the energy entropy abnormal value, if it exceeds the energy entropy abnormal value, verify that the suspected defect interval is valid.

[0049] S5, move the transducer array to the suspected defect interval, emit ultrasonic guided waves to the suspected defect interval according to the high-resolution precision screening master mode frequency, accurately position the suspected defect interval, and extract the defect features of the high-frequency guided wave echo signal; obtain the defect features of multiple frequency bands respectively, determine the comprehensive score through multi-feature weighted calculation, and determine the defect grade according to the comprehensive score; For each suspected defect interval, reposition or move the transducer array, use phased array phase delay control to realize directional excitation according to the selected high-resolution precision screening master mode frequency, and collect high-frequency guided wave echo signals.

[0050] The suspected defect interval is accurately positioned, and a defect feature of a high-frequency guided wave echo signal is extracted, specifically: S501, the high-frequency guided wave echo signal is subjected to variational mode decomposition to obtain each modal component, and the variational mode decomposition formula is: In the formula, u k (t) represents the kth modal component; ω k represents the center frequency of the kth mode; δ(t) is a unit impulse function; * represents convolution operation; s(t) represents the original guided wave echo signal; min{u k , ω k} represents the minimization optimization of u k and ω k .

[0051] S502, the defect feature is calculated based on each modal component, and the defect feature includes envelope peak value, instantaneous frequency and energy, and the formula is: In the formula, represents the Hilbert transform operator.

[0052] S503, the envelope peak value time is determined according to the envelope peak value, and the accurate defect position is determined according to the guided wave transmission time.

[0053] The defect features of multiple frequency bands are respectively acquired, a comprehensive score is determined through multi-feature weighted calculation, and the defect grade is determined according to the comprehensive score, and the specific operation is as follows: S511, the defect features of different frequency bands are acquired, and a comprehensive score function of multi-feature weighting is constructed, and the formula is: Wherein, represents the envelope amplitude at the defect position; represents the energy at the defect position; represents the instantaneous frequency at the defect position; represents the time difference at the defect position; is a defect-free state reference parameter; is an empirical weight coefficient, which satisfies .

[0054] ​​​S512, according to the calculated comprehensive score, evaluate the defect grading decision table to determine the defect risk of the cable aluminum sheath.

[0055] The defect grading decision table is shown in Table 1.

[0056] Table 1 Defect Grading Decision Table In addition, the embodiment also provides a cable aluminum sheath defect grading detection system based on multi-frequency guided waves, comprising: A dispersion calculation module is configured to establish an ultrasonic guided wave fluctuation control equation based on geometric dimensions and material parameters of the cable aluminum sheath, derive a frequency equation according to boundary conditions, and obtain phase velocity and group velocity dispersion curves of torsional modes and longitudinal modes. A frequency determination module is configured to determine propagation characteristics of each guided wave mode according to the dispersion curves, and determine excitation frequencies of detection main modes based on the propagation characteristics, wherein the excitation frequencies of the detection main modes include coarse screening main mode frequencies and fine screening main mode frequencies. A parameter setting module is configured to set mode regulation parameters of a transducer array. A defect detection module is configured to drive the transducer array to emit low-frequency guided waves according to the coarse screening main mode frequencies and collect guided wave echo signals, and perform low-frequency guided wave coarse screening to determine a suspected defect interval. The defect detection module is also configured to emit ultrasonic guided waves to the suspected defect interval according to the fine screening main mode frequencies, accurately position the suspected defect interval, and extract defect features of high-frequency guided wave echo signals; obtain defect features of multiple frequency bands respectively, determine a comprehensive score through multi-feature weighted calculation, and determine a defect grade according to the comprehensive score.

[0057] Then, a cable aluminum sheath defect grading detection method and device based on multi-frequency guided waves are also provided, comprising a processor and a memory, wherein the processor implements the cable aluminum sheath defect grading detection method based on multi-frequency guided waves as described above when executing a computer program saved in the memory.

[0058] Finally, a computer readable storage medium for storing a computer program is provided, wherein the computer program is executed by a processor to implement the cable aluminum sheath defect grading detection method based on multi-frequency guided waves as described above.

[0059] Based on the exemplary embodiments shown in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of the present application. In addition, although the disclosure is introduced according to one or more examples, it should be understood that each aspect of the disclosure can also constitute a complete technical solution independently.

[0060] Also, the terms "comprise", "comprising", "has", "having", "includes" and "including" are intended to be open and permits the inclusion of items, components, elements, members, steps, and the like that are not expressly listed, but which are related to the products or devices described herein.

[0061] The term "module" as used in the present application refers to any known or later developed hardware, software, firmware, artificial intelligence, fuzzy logic, or combination of hardware and / or software code that is capable of performing the functions associated with that element.

Claims

1. A multi-frequency guided wave based cable aluminum sheath defect grading detection method, characterized in that, The method comprises the steps of: Based on the geometric size and material parameters of the cable aluminum sheath, the ultrasonic guided wave wave motion control equation is established, the frequency equation is derived according to the boundary conditions, and the phase velocity and group velocity dispersion curves of the torsional mode and the longitudinal mode are obtained; According to the propagation characteristics of each guided wave mode, the excitation frequency of the detection main mode is determined based on the propagation characteristics, and the excitation frequency of the detection main mode includes the coarse screening main mode frequency and the fine screening main mode frequency; The transducer array is arranged and installed on the cable aluminum sheath, and the mode control parameters of the transducer array are set; The transducer array is driven to emit low-frequency guided waves according to the coarse screening main mode frequency and collect guided wave echo signals, and coarse screening of low-frequency guided waves is performed to determine the suspected defect interval; The transducer array is moved to the suspected defect interval, ultrasonic guided waves are emitted to the suspected defect interval according to the fine screening main mode frequency, the suspected defect interval is accurately positioned, and the defect characteristics of high-frequency guided wave echo signals are extracted; The defect characteristics of multiple frequency bands are obtained respectively, the comprehensive score is determined through multi-feature weighted calculation, and the defect grade is determined according to the comprehensive score.

2. The multi-frequency guided-wave based cable aluminum sheath defect grading detection method according to claim 1, characterized in that, The method for establishing the ultrasonic guided wave wave motion control equation, deriving the dispersion relationship combined with the boundary conditions, and obtaining the phase velocity and group velocity dispersion curves of the torsional mode and the longitudinal mode is as follows: The ultrasonic guided wave wave motion control equation of the isotropic elastic medium is established; The isotropic elastic medium vector is Helmholtz decomposed to obtain the expansion scalar potential function and the constant volume vector function, which are substituted into the ultrasonic guided wave wave motion control equation to obtain the control equation of the scalar potential and the vector potential; The boundary conditions and the displacement components of the cable aluminum sheath are given, and the ultrasonic guided wave wave motion control equation is solved to determine the frequency equation and determine the torsional mode and the longitudinal mode; The geometric size and material parameters of the cable aluminum sheath are substituted into the frequency equation to obtain the dispersion curves of the torsional mode and the longitudinal mode.

3. The multi-frequency guided-wave based cable aluminum sheath defect grading detection method according to claim 1, characterized in that, The transducer array adopts a wideband ring-shaped piezoelectric transducer array, which comprises a plurality of piezoelectric sheet assemblies and a ring-shaped base. The inner side surface of the ring-shaped base is provided with a plurality of grooves at equal intervals, and each groove is provided with a piezoelectric sheet assembly. The piezoelectric sheet assembly comprises a piezoelectric sheet and a damping rubber sheet, and the damping rubber sheet is attached to the back of the piezoelectric sheet to absorb the reverse energy of the non-target mode, weaken the structure resonance, and expand the effective bandwidth. A receiving wire reserved channel is arranged between adjacent two grooves, and a signal line electrically connected with the piezoelectric sheet is arranged in the receiving wire reserved channel to receive the detection signal of a single piezoelectric sheet. An excitation wire reserved channel is arranged on the outer ring of the ring-shaped base to connect a high-voltage excitation line.

4. The multi-frequency guided-wave based cable aluminum sheath defect grading detection method according to claim 1, characterized in that, The method for performing low-frequency guided wave coarse screening to determine the suspected defect interval is as follows: According to the first wave arrival time of the guided wave echo signal, the defect position is determined according to the guided wave propagation velocity and the emission time; A spatial distance difference threshold is set to group the guided wave echo signals. According to the time difference between two echoes, the spatial distance difference is calculated and compared with the spatial distance difference threshold to determine the suspected defect interval.

5. The multi-frequency guided-wave based cable aluminum sheath defect grading detection method according to claim 4, characterized in that, The suspected defect interval is further verified by wavelet change and entropy value verification, specifically as follows: The guided wave echo signal is subjected to continuous wavelet transform: wherein is a scale parameter, is a translation parameter, is a mother wavelet; s(t) is a guided wave echo signal; According to the continuous wavelet transform, an energy distribution is obtained The signal energy entropy is calculated as wherein p i is the energy proportion at the i-th scale; The signal energy entropy H of each guided wave echo signal of the suspected defect interval is compared with the energy entropy abnormal value, and if it exceeds the energy entropy abnormal value, the suspected defect interval is verified to be effective.

6. The multi-frequency guided-wave based cable aluminum sheath defect grading and detection method according to claim 1, characterized in that, The suspected defect interval is accurately positioned, and the defect features of the high-frequency guided wave echo signal are extracted, specifically: The high-frequency guided wave echo signal is subjected to variational mode decomposition to obtain each modal component; The defect features are calculated based on each modal component, and the defect features include envelope peak value, instantaneous frequency and energy; The envelope peak time is determined according to the envelope peak value, and the accurate defect position is determined according to the guided wave emission time.

7. The multi-frequency guided-wave based cable aluminum sheath defect grading and detection method according to claim 6, characterized in that, The comprehensive score is determined by multi-feature weighted calculation, and the formula is: wherein, represents the envelope amplitude at the defect location; represents the energy at the defect location; represents the instantaneous frequency at the defect location; represents the time difference at the defect location; is the reference parameter for the defect-free state; is the empirical weighting coefficient, satisfying .​​​ 8. A multi-frequency guided wave based cable aluminum sheath defect grading detection system for implementing the multi-frequency guided wave based cable aluminum sheath defect grading detection method of claim 1, characterized in that, It includes: The frequency dispersion calculation module is used to establish the ultrasonic guided wave wave motion control equation based on the geometric size and material parameters of the cable aluminum sheath, derive the frequency equation according to the boundary conditions, and obtain the phase velocity and group velocity dispersion curves of the torsional mode and the longitudinal mode; The frequency determination module is used to determine the propagation characteristics of each guided wave mode according to the dispersion curve, and determine the excitation frequency of the detection main mode based on the propagation characteristics, wherein the excitation frequency of the detection main mode includes the coarse screening main mode frequency and the fine screening main mode frequency; The parameter setting module is used to set the mode regulation parameters of the transducer array; The defect detection module is used to drive the transducer array to emit low-frequency guided waves according to the coarse screening main mode frequency and collect guided wave echo signals, and perform low-frequency guided wave coarse screening to determine the suspected defect interval; The defect detection module is also used to emit ultrasonic guided waves to the suspected defect interval according to the fine screening main mode frequency, accurately position the suspected defect interval, and extract the defect features of the high-frequency guided wave echo signal; The defect features of multiple frequency bands are obtained respectively, the comprehensive score is determined by multi-feature weighted calculation, and the defect grade is determined according to the comprehensive score.

9. A method and equipment for graded detection of defects in aluminum sheath of cables based on multi-frequency guided waves, characterized in that, It includes a processor and a memory, wherein the processor executes the computer program saved in the memory to realize the multi-frequency guided wave based cable aluminum sheath defect grading detection method of any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, A computer program is used for storing, wherein the computer program is executed by a processor to realize the multi-frequency guided wave based cable aluminum sheath defect grading detection method of any one of claims 1-7.

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