Power transmission cable non-contact detection method and device and computer program product

Abstract

The invention discloses a non-contact detection method and device for a power transmission cable and a computer program product, and the method comprises the steps: employing an electromagnetic ultrasonic sensor and a magnetostrictive ultrasonic sensor which are installed near the surface of the power transmission cable in advance, and respectively exciting ultrasonic guided waves to be transmitted in an outer metal conductor layer and an inner reinforced core body of the power transmission cable; respectively receiving reflected or scattered guided wave signals caused by defects in the outer metal conductor layer and the inner enhanced core body by using the electromagnetic ultrasonic sensor and the magnetostrictive ultrasonic sensor; the received reflection or scattering guided wave signals of the outer metal conductor layer and the inner enhanced core body are processed respectively, and characteristics representing defects are extracted; fusing the extracted features of the outer metal conductor layer and the extracted features of the inner enhanced core body into a joint feature vector; and inputting the joint feature vector into a classifier, and identifying the type and the position of the defect. According to the invention, the high-efficiency detection of the overall structure damage of the lead is realized, and the detection sensitivity and accuracy are also improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and in particular to a non-contact detection method, device and computer program product for transmission cables. Background Art

[0002] With the acceleration of urbanization, the spatial overlap of urban rail transit networks and high-voltage transmission lines is increasing. This dense infrastructure layout has led to long-term exposure of overhead transmission cables to more complex mechanical stress and electromagnetic environments, and their structural damage problems are becoming increasingly serious and highly hidden. What is particularly critical is that damage inside the conductors (such as broken strands, fatigue cracks, corrosion, etc.) is difficult to effectively identify through conventional visual inspection methods. If such micro-damage is not discovered in time and intervention measures are not taken, it will continue to accumulate and expand, and may eventually induce catastrophic power grid operation accidents such as transmission cable breakage, flashover, and even tower collapse, posing a major threat to power supply security.

[0003] The non-contact detection technologies currently used for transmission cable condition monitoring (such as traditional electromagnetic detection, ultrasonic detection, infrared thermal imaging, etc.) generally have significant technical bottlenecks in practical applications:

[0004] Insufficient sensitivity: It is difficult to effectively identify early and subtle internal damage signals;

[0005] Low positioning accuracy: There is a large error in determining the damage location, which affects maintenance efficiency;

[0006] Many blind spots: Due to limitations in sensor layout, environmental interference, or the structural characteristics of power transmission cables, there are many areas that are difficult to cover.

[0007] Poor adaptability to complex working conditions: unstable performance under complex field conditions such as strong electromagnetic fields, severe weather, and dynamic operation.

[0008] The above limitations make it difficult for existing detection methods to meet the strict requirements of modern power grids for high reliability, high precision and real-time operation of towers and transmission cables for safe and stable operation. Summary of the Invention

[0009] The technical problem to be solved by the embodiments of the present invention is to provide a non-contact detection method, device and computer program product for transmission cables, so as to achieve efficient detection of overall structural damage of the conductor and improve detection sensitivity and accuracy.

[0010] To solve the above technical problems, the present invention provides a non-contact detection method for transmission cables, comprising:

[0011] Step S1, using an electromagnetic ultrasonic sensor and a magnetostrictive ultrasonic sensor pre-installed near the surface of the transmission cable to respectively excite ultrasonic guided waves to propagate in the outer metal conductor layer and the inner reinforced core of the transmission cable;

[0012] Step S2, using the electromagnetic ultrasonic sensor and the magnetostrictive ultrasonic sensor to receive reflected or scattered guided wave signals caused by defects in the outer metal conductor layer and the inner reinforced core respectively;

[0013] Step S3, processing the received reflected or scattered guided wave signals of the outer metal conductor layer and the inner reinforced core respectively to extract features representing the defects;

[0014] Step S4, fusing the extracted outer metal conductor layer features and the inner reinforced core features into a joint feature vector;

[0015] Step S5: input the joint feature vector into a classifier to identify the defect type and location.

[0016] Preferably, before step S1, the method further includes:

[0017] Apply white noise excitation to the transmission cable and measure its resonant frequency;

[0018] The excitation frequencies of the electromagnetic ultrasonic sensor and the magnetostrictive ultrasonic sensor are set based on the resonant frequency.

[0019] Preferably, the excitation frequencies of the electromagnetic ultrasonic sensor and the magnetostrictive ultrasonic sensor are set based on the resonant frequency, specifically by selecting the resonant frequency with the maximum power spectrum energy as the excitation frequency of the sensor excitation unit.

[0020] Preferably, the processing of the reflected or scattered waveguide signal of the outer metal conductor layer in step S3 includes:

[0021] Perform envelope analysis on the received signal to extract features that characterize the defect.

[0022] Preferably, the processing of the reflected or scattered guided wave signal of the inner layer reinforced core in step S3 includes:

[0023] Bandpass filtering of the received signal to suppress interference;

[0024] The filtered signal is converted to the frequency domain for spectrum analysis to extract features that characterize the defects.

[0025] Preferably, the feature fusion in step S4 includes:

[0026] Merge the extracted outer metal conductor layer features and inner reinforcement core features into a joint feature vector;

[0027] The joint feature vector is normalized to improve feature comparability.

[0028] Preferably, the extracted outer metal conductor layer feature is X A =[x A1 ,x A2 ,…x An ]∈R n , the extracted inner layer reinforcement core feature is X S =[x S1 ,x S2 ,…x Sm ]∈R n ;

[0029] Construct the joint eigenvector as follows:

[0030] X fusion =[X A ,X S ]∈R n+m

[0031] Among them, x Ai (i=1,2,3,…,n) represents the i-th eigenvector of the outer metal conductor layer; n is the total number of dimensions of the extracted eigenvectors of the outer metal conductor layer; R n Represents X A is an n-dimensional real vector; x Sj (j=1,2,3,…,m) represents the jth eigenvector of the inner layer reinforcement core; m is the total number of dimensions of the extracted inner layer reinforcement core eigenvectors; R m Represents X S is an m-dimensional real vector.

[0032] Preferably, the standardization process is:

[0033]

[0034] Among them, μ i , σ i are features x i The mean and standard deviation of .

[0035] The present invention also provides a non-contact detection device for transmission cables, comprising:

[0036] one or more processors;

[0037] Memory;

[0038] One or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, and the one or more applications are configured to execute the non-contact detection method for power transmission cables.

[0039] The present invention also provides a computer program product, comprising computer instructions, wherein the computer instructions instruct a computer device to execute operations corresponding to the method.

[0040] The implementation of the present invention has the following beneficial effects: innovatively adopting a non-contact detection mode, getting rid of the dependence on coupling agents and requiring no surface cleaning, and being adaptable to transmission cables of different sizes, greatly improving the convenience and applicability of detection; secondly, breaking through the limitations of traditional single-mode detection, using dual-mode detection technology, accurately covering the aluminum stranded wire and the steel core layer, significantly expanding the detection range, reducing blind spots, and achieving synchronous detection of defects in the inner and outer layers of the conductor; furthermore, through optimized design, it can accurately measure the structural resonant frequency, effectively improve the amplitude of the guided wave vibration, and thereby extend the detection distance and improve the detection accuracy; at the same time, the stable system structure design enables the cables, exciters and sensors to remain in fixed positions, reducing frequent movement; in addition, the system responds quickly and can meet the needs of rapid inspections. The present invention integrates the advantages of convenience, efficiency, and high precision, providing a more advanced and reliable technical solution for transmission line detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0042] Figure 1 The present invention is a flowchart of a non-contact detection method for power transmission cables according to a first embodiment of the present invention.

[0043] Figure 2 This is a schematic diagram of a specific process of a non-contact detection method for transmission cables according to an embodiment of the present invention.

[0044] Figure 3 Schematic diagram of the installation of the electromagnetic ultrasonic sensor and the magnetostrictive ultrasonic sensor in the embodiment of the present invention. DETAILED DESCRIPTION

[0045] The following descriptions of the embodiments refer to the accompanying drawings to illustrate specific embodiments in which the present invention may be implemented.

[0046] Please refer to Figure 1 、 Figure 2 As shown, the first embodiment of the present invention provides a non-contact detection method for transmission cables, comprising:

[0047] Step S1, using an electromagnetic ultrasonic sensor and a magnetostrictive ultrasonic sensor pre-installed near the surface of the transmission cable to respectively excite ultrasonic guided waves to propagate in the outer metal conductor layer and the inner reinforced core of the transmission cable;

[0048] Step S2, using the electromagnetic ultrasonic sensor and the magnetostrictive ultrasonic sensor to receive reflected or scattered guided wave signals caused by defects in the outer metal conductor layer and the inner reinforced core respectively;

[0049] Step S3, processing the received reflected or scattered guided wave signals of the outer metal conductor layer and the inner reinforced core respectively to extract features representing the defects;

[0050] Step S4, fusing the extracted outer metal conductor layer features and the inner reinforced core features into a joint feature vector;

[0051] Step S5: input the joint feature vector into a classifier to identify the defect type and location.

[0052] Specifically, as mentioned above, transmission cables widely use aluminum-steel-core stranded conductor (ACSR), which consists of an outer layer of aluminum stranded wire and an inner layer of steel core. This complex structure and harsh service environment make it prone to potential risks such as strand breakage, corrosion, and cracks. Because the layers of stranded wire are in grid-like contact, the energy of ultrasonic guided waves propagating through each structural layer is primarily concentrated in the excitation layer. At the same time, considering that transmission cables may also include other cable types with similar structures (outer layer conductive material, inner layer high-strength core material) (such as aluminum-clad steel wire and certain types of carbon fiber composite core conductors), in order to achieve efficient full-layer and full-volume testing of transmission cables, it is necessary to excite and receive ultrasonic guided waves separately for the outer metal conductor layer and the inner reinforced core.

[0053] like Figure 3 As shown, in an embodiment of the present invention, both an electromagnetic ultrasonic (EMAT) sensor and a magnetostrictive ultrasonic (MSUT) sensor are installed near the surface of a transmission cable. A certain gap is maintained between the sensors and the surface of the transmission cable, and no physical contact is required. This is particularly suitable for operations in energized or hazardous environments.

[0054] Specifically, an electromagnetic ultrasonic sensor is used for the outer metal conductor layer. Taking aluminum stranded wire as an example, the electromagnetic ultrasonic sensor is suspended near the surface of the aluminum stranded wire, eliminating the need for direct contact with the wire. The electromagnetic ultrasonic sensor consists of an electromagnetic ultrasonic excitation unit and a receiving unit. The electromagnetic ultrasonic excitation unit consists of an excitation coil (which generates an alternating magnetic field by passing an alternating current) and a static magnet (which provides a biased static magnetic field). When an alternating current is passed through the excitation coil, the static magnet generates a varying magnetic field, inducing eddy currents within the conductor. The interaction between the eddy currents and the static magnetic field generates mechanical vibrations due to the Lorentz force effect, which in turn excites ultrasonic guided waves that propagate along the aluminum stranded wire. As the guided waves propagate through the aluminum layer, they are reflected or scattered when they encounter defects such as cracks, broken strands, and corrosion. The electromagnetic ultrasonic receiving unit also consists of a coil (which can be used with the excitation coil or independently) and a static magnet. When the reflected or scattered guided waves return and cause tiny vibrations at particles on the conductor surface, they cut through the magnetic field lines, inducing a voltage signal in the receiving coil. Using a combination of time domain features and spectrum analysis, damage signals are extracted and defects are located.

[0055] For the inner reinforced core, a magnetostrictive ultrasonic sensor is used, which includes a magnetostrictive ultrasonic excitation unit and a receiving unit. The magnetostrictive ultrasonic excitation unit contains an excitation coil (applying an alternating magnetic field) and a bias magnetic field source (a permanent magnet or a DC electromagnet, providing a static bias magnetic field). The alternating magnetic field induces periodic strain in ferromagnetic materials with magnetostrictive effect (such as steel core), exciting ultrasonic guided waves that propagate along the steel core. During the propagation of ultrasonic guided waves in the steel core, they encounter internal defects such as broken wires, corrosion, and cracks, resulting in reflection or scattering. The magnetostrictive receiving unit is also composed of a coil and a bias magnetic field source. When the returning ultrasonic wave causes strain in the ferromagnetic material, its magnetization state changes (inverse magnetostrictive effect / Villari effect), resulting in a change in the magnetic flux in the coil, thereby inducing a voltage signal. The internal defect state is identified and evaluated through frequency domain analysis, waveform feature extraction, and other means.

[0056] When processing the reflected or scattered waveguide signal received by EMAT, the received time domain signal s(t) is firstly subjected to envelope analysis, and its analytical signal s is obtained by Hilbert transform. a (t):

[0057] s a (t)=s(t)+j·H{s(t)} (1)

[0058] Where H{s(t)} represents the Hilbert transform. The envelope of the signal is:

[0059]

[0060] The envelope signal A(t) can be effectively used to identify the arrival time of the defect reflection echo, thereby estimating the distance d between the defect and the excitation source:

[0061]

[0062] Where v is the waveguide propagation velocity (it can take different values in the aluminum layer or steel core), t a is the arrival time of the echo signal, and t0 is the excitation time point.

[0063] When processing the reflected or scattered waveguide signal received by the MSUT, first, the original echo signal s(t) is bandpass filtered to remove power frequency interference and system low-frequency noise, and extract the effective waveguide frequency band. Then, the fast Fourier transform (FFT) is used to convert the time domain signal into the frequency domain:

[0064]

[0065] The spectrum function S(f) is obtained, and its main frequency variation, spectrum width, peak shift, and other indicators are analyzed. Defects will cause changes in the spectral morphology of the reflected wave, such as energy redistribution, disappearance of high-frequency components, or enhancement of low-frequency components. The spectral morphology can be used to assess the internal defect status.

[0066] Extract multidimensional feature vectors from the signals received by EMAT and MSUT respectively. Assumption: X A =[x A1 ,x A2 ,…x An ]∈R n Indicates the signal characteristics of the aluminum strand layer (EMAT); X S =[x S1 ,x S2 ,…x Sm ]∈R n Indicates the steel core (MSUT) signal characteristics:

[0067] Construct the joint eigenvector as follows:

[0068] X fusion =[X A ,X S ]∈R n+m (5)

[0069] Among them, x Ai (i=1,2,3,…,n) represents the i-th eigenvector of the aluminum stranded wire layer (such as x A1 Indicates the peak amplitude of the echo, x A2 represents the envelope rise time); n is the total number of extracted feature vector dimensions (such as envelope peak, arrival time, energy integral and other time domain features); R n Represents XA is an n-dimensional real vector (i.e., all eigenvectors are real numbers); x Sj (j=1,2,3,…,m) represents the jth eigenvector of the steel core (e.g. x S1 represents the center frequency of the spectrum, x S2 represents the low-frequency band energy ratio); m is the total number of extracted feature vector dimensions (such as envelope peak, arrival time, energy integral and other time domain features); R m Represents X S is an m-dimensional real vector (i.e., all eigenvectors are real numbers).

[0070] At the same time, in order to improve the comparability of different characteristics, standardization is required:

[0071]

[0072] Among them, μ i , σ i are features x i The mean and standard deviation of .

[0073] Subsequently, the fused high-dimensional feature vector is input into the classifier (convolutional neural network CNN) to achieve joint recognition of damage type (cracks, corrosion, broken strands) and location.

[0074] It's important to note that after contactlessly installing electromagnetic and magnetostrictive ultrasonic sensors on transmission cables, they inherently exhibit significant damping, causing ultrasonic guided waves to rapidly attenuate with distance. Therefore, to increase the excitation amplitude and propagation distance of ultrasonic guided waves, it's necessary to measure the resonant frequency of the transmission cable using a white noise signal. This white noise signal is applied to the exciter for a period of time, and the signals received by the sensors are collected and stored. These signals are then processed to calculate the resonant frequency of the structure.

[0075] For a structural vibration system under a simplified model, a preliminary estimate can be made using the natural frequency theory formula. For example, if the conductor is equivalent to a one-dimensional axial vibrating rod, its natural frequency can be estimated using the following formula:

[0076]

[0077] Where n is the vibration mode order, L is the effective length of the conductor, E is the equivalent Young's modulus, and ρ is the material density. When the tension on the conductor changes, its natural frequency changes. Therefore, by adding white noise to the conductor and measuring the natural frequency, abnormal conditions can be detected.

[0078] After measuring the resonant frequency of the structure, the resonant frequency with the largest power spectrum energy is selected as the excitation frequency of the sensor excitation unit.

[0079] Corresponding to the non-contact detection method for power transmission cables described in the first embodiment of the present invention, the second embodiment of the present invention further provides a non-contact detection device for power transmission cables, comprising:

[0080] one or more processors;

[0081] Memory;

[0082] One or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, and the one or more applications are configured to execute the non-contact detection method for transmission cables described in the aforementioned embodiment 1 of the present invention.

[0083] Corresponding to the non-contact detection method for transmission cables described in the aforementioned embodiment 1 of the present invention, embodiment 3 of the present invention also provides a computer program product, including computer instructions, which instruct a computer device to perform operations corresponding to the non-contact detection method for transmission cables described in the aforementioned embodiment 1 of the present invention.

[0084] Preferably, the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor, or the processor may be any conventional processor. The processor is the control center of the device, and various parts of the device are connected using various interfaces and lines.

[0085] The memory mainly includes a program storage area and a data storage area, wherein the program storage area can store an operating system, an application program required for at least one function, etc., and the data storage area can store related data, etc. In addition, the memory can be a high-speed random access memory, or a non-volatile memory, such as a plug-in hard disk, a smart memory card (SmartMedia Card, SMC), a secure digital (Secure Digital, SD) card, and a flash card, etc., or the memory can also be other volatile solid-state storage devices.

[0086] It should be noted that the above-mentioned device may include but is not limited to a processor and a memory, which can be understood by those skilled in the art.

[0087] From the above description, it can be seen that compared with the existing technology, the beneficial effects of the present invention are: innovative use of non-contact detection mode, getting rid of the dependence on coupling agents and no need for surface cleaning, can be adapted to transmission cables of different sizes, greatly improving the convenience and applicability of detection; secondly, breaking through the limitations of traditional single-mode detection, using dual-mode detection technology, accurately covering the aluminum stranded wire and the steel core layer, significantly expanding the detection range, reducing blind spots, and realizing synchronous detection of defects in the inner and outer layers of the conductor; thirdly, through optimized design, it can accurately measure the structural resonant frequency, effectively improve the guided wave vibration amplitude, and thus extend the detection distance and improve the detection accuracy; at the same time, the stable system structure design enables the cable, exciter and sensor to remain in a fixed position, reducing frequent movement; in addition, the system responds quickly and can meet the needs of rapid inspections. The present invention integrates the advantages of convenience, efficiency, high precision, etc., and provides a more advanced and reliable technical solution for transmission line detection.

[0088] The above disclosure is merely a preferred embodiment of the present invention and is not intended to limit the scope of the present invention. Therefore, equivalent changes made according to the claims of the present invention are still within the scope of the present invention.

Claims

1. A non-contact detection method for transmission cables, characterized in that: include: Step S1, using an electromagnetic ultrasonic sensor and a magnetostrictive ultrasonic sensor pre-installed near the surface of the transmission cable to respectively excite ultrasonic guided waves to propagate in the outer metal conductor layer and the inner reinforced core of the transmission cable; Step S2, using the electromagnetic ultrasonic sensor and the magnetostrictive ultrasonic sensor to receive reflected or scattered guided wave signals caused by defects in the outer metal conductor layer and the inner reinforced core respectively; Step S3, processing the received reflected or scattered guided wave signals of the outer metal conductor layer and the inner reinforced core respectively to extract features representing the defects; Step S4, fusing the extracted outer metal conductor layer features and the inner reinforced core features into a joint feature vector; Step S5: input the joint feature vector into a classifier to identify the defect type and location.

2. The method according to claim 1, characterized in that Before step S1, the method further includes: Apply white noise excitation to the transmission cable and measure its resonant frequency; The excitation frequencies of the electromagnetic ultrasonic sensor and the magnetostrictive ultrasonic sensor are set based on the resonant frequency.

3. The method according to claim 2, characterized in that The excitation frequencies of the electromagnetic ultrasonic sensor and the magnetostrictive ultrasonic sensor are set based on the resonant frequency, specifically by selecting the resonant frequency with the maximum power spectrum energy as the excitation frequency of the sensor excitation unit.

4. The method according to claim 1, wherein The processing of the reflected or scattered waveguide signal of the outer metal conductor layer in step S3 includes: Perform envelope analysis on the received signal to extract features that characterize the defect.

5. The method according to claim 1, wherein The processing of the reflected or scattered waveguide signal of the inner layer reinforcement core in step S3 includes: Bandpass filtering of the received signal to suppress interference; The filtered signal is converted to the frequency domain for spectrum analysis to extract features that characterize the defects.

6. The method according to claim 1, characterized in that The feature fusion in step S4 includes: Merge the extracted outer metal conductor layer features and inner reinforcement core features into a joint feature vector; The joint feature vector is normalized to improve feature comparability.

7. The method according to claim 6, characterized in that Assume that the extracted outer metal conductor layer feature is X A =[x A1 ,x A2 ,…x An ]∈R n , the extracted inner layer reinforcement core feature is X S =[x S1 ,x S2 ,…x Sm ]∈R n ; Construct the joint eigenvector as follows: X fusion =[X A ,X S ]∈R n+m Among them, x Ai (i=1,2,3,…,n) represents the i-th eigenvector of the outer metal conductor layer; n is the total number of dimensions of the extracted eigenvectors of the outer metal conductor layer; R n Represents X A is an n-dimensional real vector; x Sj (j=1,2,3,…,m) represents the jth eigenvector of the inner layer reinforcement core; m is the total number of dimensions of the extracted inner layer reinforcement core eigenvectors; R m Represents X S is an m-dimensional real vector.

8. The method according to claim 6, characterized in that The standardization process is as follows: Among them, μ i , σ i are features x i The mean and standard deviation of .

9. A non-contact detection device for power transmission cables, characterized in that: include: one or more processors; Memory; One or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, and the one or more applications are configured to execute the non-contact detection method for power transmission cables according to any one of claims 1 to 8.

10. A computer program product, characterized in that The method comprises computer instructions, wherein the computer instructions instruct a computer device to perform operations corresponding to the method according to any one of claims 1 to 8.

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