Sleeve lead ultrasonic detection system and method

Abstract

The invention discloses an ultrasonic detection system and method for a bushing lead. The system comprises a transmitting probe and a receiving probe, and the transmitting probe and the receiving probe are arranged on the outer side wall of a bushing; the fault detection main circuit is electrically connected with the transmitting probe and the receiving probe respectively; the upper computer is electrically connected with the fault detection main circuit and is used for controlling the fault detection main circuit to drive the transmitting probe to transmit an ultrasonic signal into the sleeve; the receiving probe receives and transmits an ultrasonic echo signal obtained after the ultrasonic signal is reflected in the sleeve; and the fault detection main circuit is used for processing the received ultrasonic echo signal into a time signal and then displaying the time signal through the upper computer. According to the invention, the detection time can be shortened, the online detection of the high-voltage bushing lead can be realized, the insulation fault can be accurately and timely found, and the reliable operation of the high-voltage bushing lead can be ensured.

Description

Technical Field

[0001] The invention relates to the field of electrical equipment maintenance, and in particular to a casing lead ultrasonic detection system and method. Background Art

[0002] Power transformers are responsible for the important task of transmitting and distributing electric energy, and their operating reliability is closely related to the safety and stability of the power system.

[0003] As an important component of the power transformer, the bushing's insulation hazards and lead deformation will directly endanger the operational reliability of the power transformer. The deformation of the leads inside the bushing will cause its insulation to deteriorate and its performance to decline, which will threaten the safe operation of the power transformer. In severe cases, it will cause operational failures of the power transformer. In actual operation and maintenance, the basic detection method for the leads inside the bushing is mainly regular preventive testing, which cannot detect defects inside the equipment in a timely manner. When the test time interval is too long, many potential or internal problems cannot be checked in time. Therefore, there is an urgent need for an intuitive and quantitative live monitoring method to effectively evaluate the operating status of the high-voltage bushing leads, which is of great significance for power transformers that require long-term stable operation. Summary of the invention

[0004] The object of the present invention is to provide a bushing lead ultrasonic detection system and method, which can shorten the detection time, realize the online detection of high-voltage bushing leads, and accurately and timely detect insulation faults, thereby ensuring the reliable operation of high-voltage bushing leads.

[0005] In order to solve the above problems, the present invention is implemented by the following technical solutions:

[0006] A casing lead ultrasonic detection system comprises: a transmitting probe and a receiving probe, wherein the transmitting probe and the receiving probe are arranged on the outer wall of the casing; a fault detection main circuit, which is electrically connected to the transmitting probe and the receiving probe respectively; a host computer, which is electrically connected to the fault detection main circuit and is used to control the fault detection main circuit to drive the transmitting probe to transmit an ultrasonic signal into the casing; the receiving probe receives and transmits an ultrasonic echo signal after the ultrasonic signal is reflected in the casing; the fault detection main circuit is used to process the received ultrasonic echo signal into a time signal and then display it through the host computer.

[0007] Optionally, it also includes: a temperature sensor, which is arranged on the top box shell of the transformer and is used to detect the transformer oil in the bushing;

[0008] The fault detection main circuit includes a temperature compensation circuit, which is used to perform temperature compensation on the detected oil temperature and transmit the compensated temperature signal to the host computer for display.

[0009] Optionally, the fault detection main circuit also includes: a main control chip, which communicates with the host computer through an RS232 serial port; an ultrasonic transmitting circuit, a signal optimization module and a driving circuit respectively connected to the main control chip, and the driving circuit is used to power the main control chip; the ultrasonic transmitting circuit is used to generate a high-frequency oscillation signal to control the transmitting probe to transmit the ultrasonic signal; the ultrasonic echo signal is transmitted to the main control chip through the signal optimization module, and is converted into the time signal via the main control chip.

[0010] Optionally, the signal optimization module is used to perform modal decomposition on the received ultrasonic echo signal using ICEEMDAN, and extract the eigenvectors of each operating condition sample after decomposition; perform correlation analysis on the eigenvectors of each operating condition sample obtained by decomposition to determine the effective signal component and the noise component in the ultrasonic echo signal; perform denoising and reconstruct the ultrasonic echo signal according to the effective signal component and the noise component using SVD-LWT; and perform power spectrum analysis on the optimized ultrasonic echo signal to verify the signal quality of the optimized ultrasonic echo signal.

[0011] On the other hand, the present invention also provides a method for optimizing denoising of ultrasonic echo signals of a cannula lead based on adaptive multi-scale decomposition, comprising the following steps:

[0012] Step S1: collecting ultrasonic echo signals from transformer bushings;

[0013] Step S2: Use ICEEMDAN to perform modal decomposition and extract the feature vector of each working condition sample after decomposition;

[0014] Step S3: performing correlation analysis on the characteristic vectors of each working condition sample obtained by decomposition to determine the modal components of the effective signal and the modal components of the noise in the ultrasonic echo signal;

[0015] Step S4: De-noising and reconstructing the echo signal using SVD-LWT according to the modal components of the effective signal and the modal components of the noise, completing the adjustment and optimization of the model parameters, and realizing the denoising of the ultrasonic echo signal.

[0016] Step S5: performing power spectrum analysis on the optimized ultrasonic echo signal.

[0017] Optionally, in step S1, the following steps are included:

[0018] Step S11: placing a transmitting probe on the outer surface of the transformer bushing;

[0019] Step S12: The transmitting probe transmits pulsed ultrasonic waves under the excitation of high-voltage electric pulses:

[0020] The pulsed ultrasonic wave penetrates the porcelain sleeve of the transformer bushing and propagates into the insulating oil inside the transformer bushing;

[0021] Step S13: The ultrasonic wave generates a reflected wave at the interface between the insulating oil and the lead wire, which is received by the receiving probe and converted into an electrical pulse signal:

[0022] When ultrasonic waves propagate to the interface between the insulating oil and the lead wire, a reflected wave is generated due to the difference in acoustic impedance;

[0023] These reflected waves are received by the receiving probe and converted into electrical pulse signals to form ultrasonic echo signals;

[0024] By measuring the time difference between the transmitted wave and the reflected wave and combining the known propagation speed of ultrasound in insulating oil, the distance from the surface of the bushing to the surface of the lead wire is calculated.

[0025] Optionally, step S2 includes:

[0026] Step S21: construct a basic signal containing a noisy signal:

[0027] Take a base signal x and add to it to generate a series of constructed signals x (i) , which can be expressed as:

[0028] x (i )=x+β0E1(w (i) ), (i=1,2,…,N)

[0029] Among them, x (i) is the i-th constructed signal, β0 is the initial noise standard deviation of the signal, and w (i) is the added white noise with zero mean and unit variance, and E1(·) represents the operation of calculating the first inner membrane state function of the signal;

[0030] Step S22: Calculate the local mean and average:

[0031] For each constructed signal x (i) Calculate the local mean and then take the average of all local means to get the i-th residual component r i :

[0032]

[0033] Here M(·) represents the local mean in the signal, and I represents the total number of constructed signals;

[0034] Step S23: Calculate the first modal component:

[0035] The first modal component imf1 is obtained by subtracting the first residual component r1 from the original acquired ultrasonic echo signal x:

[0036] imf1=x-r1

[0037] Step S24: Iteratively calculate subsequent modal components:

[0038] For the kth (k ≥ 2) modal component imf k , using the previous residual component r k-1 Subtract this residual component r k :

[0039] imf k =r k-1 -r k

[0040] And, r k The calculation method is:

[0041]

[0042] Among them, E k (·) is the modal component IMF operation corresponding to the kth calculation, β k-1 is the k-1 noise standard deviation of the signal;

[0043] Step S25: Iteration termination condition:

[0044] When the residual component meets the predetermined termination condition or the modal component is less than the first three-order local extreme values, the iteration stops;

[0045] The step S3 comprises:

[0046] Step S31: Calculate the correlation coefficient between each modal component and the originally acquired ultrasonic echo signal;

[0047] Step S32: according to the size of the correlation coefficient, a threshold is set to filter out the modal components mainly containing valid signals;

[0048] Step S33: discard the modal components determined to be noise, and only retain the modal components of the valid signal.

[0049] Optionally, step S4 includes:

[0050] Step S41: using SVD-LWT processing to accurately reduce the noise of all the modal components and retain the modal components of the effective signal;

[0051] Step S42: reconstructing the transformer bushing lead ultrasonic echo signal after denoising according to the module of the effective signal.

[0052] Optionally, the step S41 includes:

[0053] Step S411: Assume that the long sequence of originally acquired ultrasonic echo signals contains noise a(n) (n=1, 2, ..., L).

[0054] a(n)=s(n)+w(n)

[0055] Among them, s(n) represents the effective signal, and w(n) represents the noise signal;

[0056] Step S412, the denoising process of overlapping segmentation SVD is as follows:

[0057] The original noisy signal sequence a(n) is divided into S signal segments of length l, each signal segment is represented by a i (t i ), where i = 1, 2, ..., S; t i represents the time series of the i-th signal segment;

[0058] Construct the Hankel matrix and perform SVD: For each signal segment a i (t i ), the Hankel matrix is ​​of the form:

[0059]

[0060] Then for each H i Perform singular value decomposition and obtain three matrices U i , C i and V i :

[0061] H i =U i ·C i ·V i T

[0062] The step S42 includes: S421, signal sequence recovery: each processed signal segment a i (t i ) is reconstructed through its corresponding SVD decomposition result to restore the original signal; in the overlapping part, the average value of the two adjacent signal segments is taken; the reconstructed original collected ultrasonic echo signal It can be expressed as:

[0063] Reconstructed a i (t i )

[0064] Among them, "reconstructed a i (t i )" is through U i , C i and Vi reconstructed signal segment;

[0065] Step S422: reconstruct the i (t i ) is processed by LWT to obtain X′ i The specific steps are as follows:

[0066] Step S4221: reconstruct the i (t i ) is divided into effective information sequence q i and the sequence X of noise signal points i , and then the sequence of noise signal points X i Decompose into two disjoint subsets to obtain the even-numbered sequence X of noise signal points e(i-1) and the odd number sequence X of noise signal points o(i-1) ;

[0067] Step S4222: Using the even point sequence X e(i-1) and the odd point sequence X o(i-1) The correlation between

[0068] Use even point sequence X e(i-1) Predict odd point sequence X o(i-1) , and calculate the prediction error d i-1 =X e(i-1) -X o(i-1) ;

[0069] Step S4223: Update the dual point sequence X by using the update operator e(i-1) To update and adjust:

[0070] X′ i =X e(i-1) +α·d i-1

[0071] In the formula, α represents the lifting coefficient;

[0072] Step S4224: according to the updated sequence X of noise signal points i and the effective information sequence q i Get the denoised ultrasonic echo signal h i =q i +X′ i .

[0073] Optionally, step S5 includes:

[0074] Step S51: Denoised ultrasonic echo signal h i Perform fast Fourier transform (FFT) to obtain its spectrum distribution;

[0075] Step S52: performing comparative analysis with the spectrum of the originally collected ultrasonic echo signal to ensure that the main frequency components are retained and the noise components are effectively suppressed;

[0076] Step S53: According to the spectrum analysis result, further adjust the parameters of the denoising algorithm to optimize the signal quality.

[0077] The present invention has the following technical effects:

[0078] Aiming at the problem that high-frequency ultrasonic detection of bushing leads in substations is easily interfered by noise, the present invention proposes a bushing lead ultrasonic detection system and method. The system can shorten the detection time and realize online detection of high-voltage bushing leads. Insulation faults can be accurately and timely discovered, ensuring the reliable operation of high-voltage bushing leads.

[0079] In order to shorten the detection time and improve the detection accuracy, the present invention also provides a method, which is specifically a joint denoising method combining improved CEEMDAN (ICEEMDAN), singular value decomposition (SVD) and lifting wavelet transform (LWT). The method first uses ICEEMDAN to decompose the ultrasonic echo signal to effectively separate the high-frequency interference signal and the low-frequency signal containing the main ultrasonic energy. Subsequently, these IMF components are accurately noise-reduced through SVD-LWT processing, and the effective components are retained. Through this process, the denoised casing lead ultrasonic signal can be reconstructed. Finally, through experimental research and comparative analysis, the present invention verifies the effectiveness and practicality of the denoising method. BRIEF DESCRIPTION OF THE DRAWINGS

[0080] Figure 1 A schematic diagram of probe placement in a casing lead ultrasonic detection system provided in an embodiment of the present invention;

[0081] Figure 2 A schematic cross-sectional structure diagram of a sleeve lead provided by an embodiment of the present invention;

[0082] Figure 3 A structural block diagram of a casing lead ultrasonic detection system provided by an embodiment of the present invention;

[0083] Figure 4a The original echo signal of the casing lead collected by an embodiment of the present invention;

[0084] Figure 4b An embodiment of the present invention is based on Figure 4a an echo reconstruction signal of the casing lead obtained after processing;

[0085] Figure 5 is a modal component of an ultrasonic echo signal in a casing in an embodiment of the present invention;

[0086] Figure 6a and 6b The echo signal processed by different processing techniques in one embodiment of the present invention;

[0087] Figure 7 A schematic flow chart of a method for optimizing and denoising a casing lead ultrasonic echo signal based on adaptive multi-scale decomposition provided in one embodiment of the present invention. DETAILED DESCRIPTION

[0088] The following is a further detailed description of a casing lead ultrasonic detection system and method proposed by the present invention in combination with the accompanying drawings and specific embodiments. According to the following description, the advantages and features of the present invention will be clearer. It should be noted that the drawings are in a very simplified form and use non-precise proportions, which are only used to conveniently and clearly assist in explaining the purpose of the embodiments of the present invention. In order to make the purposes, features and advantages of the present invention more obvious and easy to understand, please refer to the accompanying drawings. It should be noted that the structures, proportions, sizes, etc. illustrated in the drawings of this specification are only used to match the contents disclosed in the specification for people familiar with this technology to understand and read, and are not used to limit the limiting conditions for the implementation of the present invention, so they have no technical substantive significance. Any structural modification, change in proportional relationship or adjustment of size, without affecting the effects that the present invention can produce and the purposes that can be achieved, should still fall within the scope of the technical content disclosed by the present invention.

[0089] As described in the background art, in the prior art, the basic detection method for the lead wire in the casing is mainly a regular preventive test. This method cannot detect the defects inside the equipment in a timely manner, and many potential or internal problems cannot be checked in time.

[0090] Since the 1980s, my country's power system has been testing the insulation performance of high-voltage bushings by regular preventive tests. However, there is little research on the detection of deformation faults of high-voltage bushing leads. The method of regular offline maintenance has some disadvantages: First, since traditional detection methods require power outages to test, it is difficult to flexibly select the test cycle according to the insulation condition of the equipment. In addition, the operating voltage level of power equipment is gradually increasing, currently reaching 110kV~750kV, and even up to 1100kV. In the current preventive test process, the test voltage applied is only 10kV or less. Compared with the actual operating voltage of the equipment, it is still very low, which can easily lead to the fact that even if there is a large insulation fault in the equipment, the data measured by some field tests may still be within the normal range of the reference value, or the test results show that its insulation condition is still good, resulting in the insulation fault cannot be accurately and timely discovered. After the maintenance is completed, it is very easy to put the equipment with insulation fault into operation again without repair, which will eventually lead to serious accidents and huge economic losses.

[0091] At present, the basic means of monitoring high-voltage bushing leads is regular preventive testing. However, this method also has some disadvantages. It cannot detect defects inside the equipment sensitively. When the test time interval is too long, many potential or internal problems cannot be discovered in time, and the test needs to be conducted offline. Although the current monitoring method has improved the sensitivity of monitoring to a certain extent, there are still some problems in terms of reliability and practicality. At present, there is no good online detection method for deformation failure of high-voltage bushing leads.

[0092] Moreover, existing ultrasonic signal denoising techniques, especially those combining wavelet transform (WT) and singular value decomposition (SVD), although effective in dealing with a certain degree of noise, show limitations in dealing with nonlinear and non-stationary signals. This is because WT and SVD are mainly suitable for processing linear and stationary signals, which may not effectively remove noise or extract key features when facing complex industrial ultrasonic signals. In addition, these methods have limited processing capabilities for highly complex or diversified noise sources, especially in environments where multiple noise sources coexist, the denoising effect may not be satisfactory. In industrial detection environments, the characteristics of ultrasonic signals may vary from scene to scene. However, traditional denoising methods, such as wavelet transform based on fixed wavelet basis and standard singular value decomposition, often lack the necessary adaptability. This means that they may not provide the optimal denoising effect under different detection conditions.

[0093] Aiming at the problem that high-frequency ultrasonic detection of bushing leads in substations is susceptible to noise interference, the present invention proposes a joint denoising method based on ICEEMDAN (Improved Complete Set Empirical Mode Decomposition Additive Noise)-SVD (Singular Value Decomposition)-LWT (Lifting Wavelet Transform), which is intended to process nonlinear and non-stationary ultrasonic signals, especially in complex industrial environments. By introducing ICEEMDAN, the present invention can more accurately decompose and process complex signals, thereby improving the accuracy of denoising and signal quality. The method combining ICEEMDAN, SVD and LWT can more comprehensively identify and remove diverse noise components, and such a comprehensive processing method significantly improves the denoising effect. In addition, the method of the present invention is also enhanced in terms of adaptability and flexibility, and can automatically adjust the denoising strategy according to the specific characteristics of the signal and environmental conditions, thereby maintaining high efficiency and flexibility in a changing application environment. Based on this, the bushing lead ultrasonic detection system provided by the present invention can detect bushing leads in real time online.

[0094] Combination Figure 1 to Figure 3 As shown, this embodiment provides a bushing lead ultrasonic detection system, wherein the bushing refers to a transformer bushing.

[0095] The casing lead ultrasonic detection system includes: a transmitting probe 21 and a receiving probe 22, wherein the transmitting probe 21 and the receiving probe 22 are arranged on the outer wall of the casing 10. A fault detection main circuit 30 is electrically connected to the transmitting probe 21 and the receiving probe 22, respectively. A host computer 40 is electrically connected to the fault detection main circuit 30, and is used to control the fault detection main circuit 30 to drive the transmitting probe 21 to transmit an ultrasonic signal into the casing 10. The receiving probe 22 receives and transmits an ultrasonic echo signal after the ultrasonic signal is reflected in the casing 10. The fault detection main circuit 30 is used to process the received ultrasonic echo signal into a time signal and then display it through the host computer 40.

[0096] It can be seen that the bushing lead ultrasonic detection system provided in this embodiment can detect bushing leads in real time online. It can monitor transformer bushings in an intuitive and quantitative manner to effectively evaluate the operating status of high-voltage bushing leads, which is of great significance for power transformers that need long-term stable operation.

[0097] like Figure 3 As shown, it also includes: a temperature sensor (not shown), which is arranged on the top box shell of the transformer (not shown) for detecting the transformer oil in the bushing 10; the fault detection main circuit 30 includes a temperature compensation circuit 36 ​​for temperature compensation of the detected oil temperature and transmitting the compensated temperature signal to the host computer 40 for display.

[0098] In this embodiment, the fault detection main circuit 30 further includes: a main control chip 33, which communicates with the host computer 40 through an RS232 serial port (not shown).

[0099] The ultrasonic transmitting circuit 34, the signal optimization module 35 and the driving circuit 32 are respectively connected to the main control chip 33. The driving circuit 32 is used to power the main control chip 33. The ultrasonic transmitting circuit 34 is used to generate a high-frequency oscillation signal to control the transmitting probe 21 to transmit the ultrasonic signal. The ultrasonic echo signal is transmitted to the main control chip 33 through the signal optimization module 35, and is converted into the time signal by the main control chip 33.

[0100] It can be understood that the transmitting probe 21 transmits pulsed ultrasonic waves under the excitation of high-voltage electric pulses: the pulsed ultrasonic waves penetrate the porcelain sleeve of the bushing 10 and propagate in the insulating oil inside the transformer bushing 10; the ultrasonic waves generate reflected waves at the interface between the insulating oil and the lead 11, which are received by the receiving probe 22 and converted into electrical pulse signals, i.e., ultrasonic echo signals: when the ultrasonic waves propagate to the interface between the insulating oil and the lead 11, reflected waves are generated due to the difference in acoustic impedance; these reflected waves are received by the transmitting probe 22 and converted into electrical pulse signals to form ultrasonic echo signals. By measuring the time difference between the transmitted wave and the reflected wave, combined with the known propagation speed of ultrasonic waves in the insulating oil, the distance from the surface of the bushing 10 to the surface of the lead 11 can be calculated.

[0101] In this embodiment, the signal optimization module 35 is used to perform modal decomposition on the received ultrasonic echo signal using ICEEMDAN, and extract the feature vector of each working condition sample after decomposition;

[0102] The characteristic vectors of each working condition sample obtained by decomposition are subjected to correlation analysis to determine the effective signal component and the noise component in the ultrasonic echo signal. The ultrasonic echo signal is denoised and reconstructed using SVD-LWT according to the effective signal component and the noise component. The power spectrum analysis is performed on the optimized ultrasonic echo signal to verify the signal quality of the optimized ultrasonic echo signal.

[0103] Based on the collected ultrasonic echo signals, the feature vector of each working condition sample can be extracted. The feature vector of each working condition sample is usually obtained by extracting features from the ultrasonic echo signals collected under different working conditions. The feature vector is composed of specific time domain or frequency domain features extracted from each IMF (modal component). The "working condition" in the working condition sample refers to the system state under different operating conditions, such as different signal characteristics caused by changes in temperature, pressure, mechanical vibration, transformer oil temperature, environmental noise, etc., but the present invention is not limited to this.

[0104] The signal optimization module provided in this embodiment combines the improved CEEMDAN (ICEEMDAN), singular value decomposition (SVD) and lifting wavelet transform (LWT) to denoise the received or collected ultrasonic echo signal. The signal optimization module first uses ICEEMDAN to decompose the ultrasonic echo signal to effectively separate the high-frequency interference signal and the low-frequency signal containing the main ultrasonic energy. Subsequently, these IMF components are accurately noise-reduced through SVD-LWT processing, and the effective components are retained. Through this process, we can reconstruct the denoised cannula lead ultrasonic signal. Finally, through experimental research and comparative analysis, the denoising method adopted by the signal optimization module is effective and practical.

[0105] Please continue to refer to Figure 3 As shown, the casing lead ultrasonic detection system provided in this embodiment is powered by a 24V stabilized power supply 31. On the one hand, the stabilized power supply 31 supplies power to the main control chip 33 through the driving circuit 32, and on the other hand, it generates a high-frequency oscillation signal through the ultrasonic transmitting circuit 34 to stimulate the transmitting probe 21 to generate the pulsed ultrasonic wave.

[0106] In this embodiment, the host computer 40 or the fault detection main circuit 30 is connected to a liquid crystal screen 41. The liquid crystal screen 41 is used to display the time signal processed by the signal optimization module and the dynamic temperature signal transmitted by the temperature compensation circuit.

[0107] In order to verify the effectiveness of the bushing lead detection system provided in this embodiment, the lead wire inside the bushing porcelain sleeve is tested under laboratory conditions. The laboratory purchased a national standard 35kV, model BJ-35 / 800 bushing outer porcelain sleeve. The bushing outer porcelain sleeve has a certain thickness, and the transmission parameters of the bushing lead ultrasonic detection hardware system need to be debugged so that the ultrasonic wave can effectively penetrate the bushing porcelain sleeve and enter the transformer oil.

[0108] A 1MHz underwater ultrasonic probe was selected as the ultrasonic sensor, and a continuous pulse of 12 cycles was modulated as the excitation of the ultrasonic transducer. Through the ultrasonic transmitting circuit, a 1MHz pulse voltage of about 200V was excited, so that the ultrasonic wave penetrated the outer porcelain sleeve. The 35kV bushing porcelain bottle with the lead installed was placed in the container, and the bushing was filled with transformer oil after the porcelain bottle was fixed. A coupling agent was applied to a suitable detection point outside the porcelain bottle, and a 1MHz ultrasonic transducer was placed at the detection position outside the porcelain bottle. The bushing lead detection hardware system was used for measurement.

[0109] The nondestructive detection system for the lead wire status in the power transformer bushing is applied to the 35kV bushing of the No. 1 main transformer of the 35kV substation of the State Grid Shanghai Pudong Power Supply Company. Since it was put into trial operation, after several months of research and testing, the problems encountered during the test process have been systematically optimized and improved. At present, the system is operating stably.

[0110] The project has successfully completed the specific contents specified in the project task book. The systematic research has achieved the expected results and can meet the needs of practical applications. All indicators have reached the expected goals and played due role in the transformer bushing operating status evaluation and fault diagnosis methods in the power system.

[0111] The nondestructive detection system for the status of the inner bushing lead of the power transformer was tested in a substation. The system was used to detect the 35kV bushing of the No. 1 main transformer of the 35kV substation of the State Grid Shanghai Pudong Power Supply Company to see if there was a safety hazard of breakdown and discharge in the bushing lead of the transformer.

[0112] The measured dimensions of this type of bushing are as follows: the perimeter of the outer porcelain bushing end screen is 69cm, and the perimeter of the riser is 167cm. Therefore, the measurement probe is selected as a 1MHz ultrasonic hydroacoustic transducer with a blind area of ​​3-5cm, which meets the requirements of the lead deformation detection of this type of bushing. The amplitude of the transducer echo signal is 700mV. Debug the main control circuit and move the transducer along the periphery of the riser to capture the effective echo signal of the nearest lead in the bushing.

[0113] The host computer sends out ultrasonic excitation signals through the RS232 serial port. The transducer echo signal amplitude is 700mV and the center frequency is 1MHz. A 110 / 35kV Siemens transformer that was shut down for maintenance was selected for the experiment. The A-phase high-voltage bushing was selected, and the probe was attached to the outer surface of the bushing using a coupling agent. The control circuit was debugged and the transducer was moved along the outer periphery of the bushing to capture the ultrasonic echo signal. Four groups of signals were collected to detect whether there was any deformation at the end of the transformer bushing lead. In order to facilitate data analysis, a group of echo signals were extracted. The echo signals collected by the data acquisition card are shown in the figure below. Figure 4a As shown, the measured echo signal is saved and imported into the host computer through the data acquisition card. Figure 4a The echo data waveform of the end of the casing lead captured inside the riser.

[0114] Figure 4a It can be seen that under the field test conditions, the ultrasonic detection casing lead is seriously interfered by noise, the signal-to-noise ratio is very low, and the lead echo signal can only be captured by some frequency changes. The echo signal after denoising is as follows Figure 4b shown.

[0115] The temperature compensation module is selected and placed on the transformer top box shell. After fitting and compensating the oil temperature, the propagation speed of ultrasonic waves in the transformer oil is obtained. The shortest distance between the lead wire and the riser shell is calculated.

[0116] Experimental results: According to the distance manufacturing tolerance table of the bushing leads of this type of transformer and the unshielded insulation distance table of the high-voltage line end leads, it is judged that the distance between the ends of the test bushing leads meets the minimum insulation distance. The test bushing of the main transformer of this substation does not have the safety hazard of breakdown and discharge at the lead ends.

[0117] It is understandable that the above parameters such as the model and size of the device are only required for testing, and the technical solution of the present invention is not limited thereto.

[0118] like Figure 7 As shown, this embodiment provides a method for optimizing and denoising the ultrasonic echo signal of a cannula lead based on adaptive multi-scale decomposition, comprising the following steps:

[0119] Step S1: Collect ultrasonic echo signals from transformer bushings (such as Figure 4a shown).

[0120] Step S2: Use ICEEMDAN to perform modal decomposition and extract the feature vector of each working condition sample after decomposition.

[0121] Step S3: performing correlation analysis on the characteristic vectors of each working condition sample obtained by decomposition to determine the modal components of the effective signal and the modal components of the noise in the ultrasonic echo signal.

[0122] Step S4: De-noising and reconstructing the echo signal using SVD-LWT according to the modal components of the effective signal and the modal components of the noise (e.g. Figure 4b As shown), the adjustment and optimization of the model parameters are completed to achieve the denoising of the ultrasonic echo signal.

[0123] Step S5: Perform power spectrum analysis on the optimized / denoised ultrasonic echo signal to further verify the signal quality and ensure the accuracy and integrity of the denoising effect.

[0124] This embodiment provides a casing lead ultrasonic detection / echo signal optimization denoising method based on adaptive multi-scale decomposition. First, the ultrasonic echo signal is decomposed by ICEEMDAN to effectively separate the high-frequency interference signal and the low-frequency signal containing the main ultrasonic energy. Subsequently, these IMF components are accurately noise-reduced through SVD-LWT processing, and the effective components are retained. Through this process, we can reconstruct the casing lead ultrasonic signal after denoising. Finally, through experimental research and comparative analysis, this paper verifies the effectiveness and practicality of the denoising method. It has certain value in engineering experiments.

[0125] In this embodiment, combined with Figure 1 to Figure 3 As shown, in step S1, the following steps are included:

[0126] Step S11 : placing the transmitting probe 21 on the outer surface of the transformer bushing 10 .

[0127] Step S12: The transmitting probe 22 transmits pulsed ultrasonic waves under the excitation of high-voltage electric pulses.

[0128] The pulse ultrasonic wave penetrates the porcelain sleeve of the transformer bushing 10 and enters the insulating oil inside the transformer bushing 10 to propagate.

[0129] Step S13: The ultrasonic wave generates reflected waves at the interface between the insulating oil and the lead wire 11, which are received by the receiving probe 22 and converted into electrical pulse signals. When the ultrasonic wave propagates to the interface between the insulating oil and the lead wire 11, reflected waves are generated due to the difference in acoustic impedance. These reflected waves are received by the receiving probe 21 and converted into electrical pulse signals to form ultrasonic echo signals.

[0130] By measuring the time difference between the transmitted wave and the reflected wave, combined with the known propagation speed of ultrasound in insulating oil, the distance from the surface of the bushing to the surface of the lead can be calculated.

[0131] In this embodiment, step S2 includes:

[0132] Step S21: construct a basic signal x containing a noisy signal:

[0133] Take a base signal x and add to it to generate a series of constructed signals x (i) , which can be expressed as:

[0134] x (i) =x+β0E1(w (i) ), (i=1,2,…,N) (1)

[0135] Among them, x (i) is the i-th constructed signal, β0 is the initial noise standard deviation of the signal, and w (i) is the added zero-mean unit variance white noise, and E1(·) represents the operation of calculating the first inner membrane state function of the signal;

[0136] Step S22: Calculate the local mean and average:

[0137] For each constructed signal x (i) Calculate the local mean and then take the average of all local means to get the i-th residual component r i :

[0138]

[0139] Here M(·) represents the local mean in the signal, and I represents the total number of constructed signals;

[0140] Step S23: Calculate the first modal component:

[0141] The first modal component imf1 is obtained by subtracting the first residual component r1 from the original signal (the original acquired ultrasonic echo signal) x:

[0142] imf1=x-r1 (3)

[0143] Step S24: Iteratively calculate subsequent modal components:

[0144] For the kth (k ≥ 2) modal component imf k , using the previous residual component r k-1 Subtract this residual component r k :

[0145] imf k =rk-1 -r k (4)

[0146] And, r k The calculation method is:

[0147]

[0148] Among them, E k (·) is the modal component IMF operation corresponding to the kth calculation, β k-1 is the noise standard deviation of the signal at the k-1th order;

[0149] Step S25: Iteration termination condition:

[0150] The iteration stops when the residual component meets the predetermined termination condition or the modal component is smaller than the first three order local extreme values.

[0151] The ICEEMDAN denoising method is used to decompose the original signal into multiple IMF components and residual components r, such as Figure 5 Shown: In Figure 5 In the figure, from the signal amplitude point of view, IMF1, IMF2, and IMF3 all contain large signal energy and are similar to the casing lead echo signal waveform, but there is obvious Gaussian noise interference in the IMF2 and IMF3 waveforms. IMF4 to IMF7 are gradually attenuated smooth curves with small signal energy.

[0152] Furthermore, the step S3 includes:

[0153] Step S31: Calculate the correlation coefficient between each modal component and the original signal (the originally acquired ultrasonic echo signal).

[0154] Step S32: according to the size of the correlation coefficient, a threshold is set to screen out the modal components (IMF) mainly containing valid signals.

[0155] Step S33: discard the modal components determined to be noise and only retain the modal components of the effective signal to improve the denoising effect.

[0156] To better understand the above step S3, the following example is used to illustrate: For example, suppose we use ICEEMDAN to decompose an ultrasonic echo signal and obtain five IMF components (IMF1, IMF2, IMF3, IMF4, IMF5). Next, we calculate the correlation coefficient between each IMF and the original signal and obtain the following result:

[0157] IMF1: correlation coefficient is 0.1; IMF2: correlation coefficient is 0.3; IMF3: correlation coefficient is 0.7; IMF4: correlation coefficient is 0.9; IMF5: correlation coefficient is 0.2.

[0158] In this case, we need to set a threshold to filter out the modal components that mainly contain valid signals. For example, we can set the correlation coefficient threshold to 0.5.

[0159] After screening according to this threshold, only the IMF components with correlation coefficients greater than or equal to 0.5 are retained. In this way, we screen out IMF3 and IMF4 because their correlation coefficients are 0.7 and 0.9, respectively, indicating that they have a high correlation with the original signal and mainly contain valid signals.

[0160] The other IMF components (IMF1, IMF2, IMF5) have low correlation coefficients and may contain mainly noise or other invalid signals, so they are screened out. This step can effectively retain the signal components useful for analysis and reduce noise interference.

[0161] In this embodiment, step S4 includes:

[0162] Step S41: using SVD-LWT processing to accurately reduce the noise of all the modal components and retain the modal components of the effective signal;

[0163] Step S42: reconstructing the transformer bushing lead ultrasonic echo signal that has been subjected to denoising processing (the ultrasonic echo signal after denoising) according to the module of the effective signal.

[0164] In this embodiment, step S41 includes: singular value decomposition theory, for any dimensional real matrix A∈R m×n , if there exists an orthogonal matrix U∈R m×m and V∈R n×n , R is the real number field, A can be decomposed into

[0165] A=UCV T (6)

[0166] Generally, the denoising process of the continuous overlapping segmentation SVD method includes signal sequence overlapping segmentation, SVD denoising and signal sequence restoration.

[0167] Step S411: Assume that the long sequence of the original signal contains noise a(n) (n=1, 2, ..., L).

[0168] a(n)=s(n)+w(n) (7)

[0169] Among them, s(n) represents the effective signal and w(n) represents the noise signal.

[0170] Step S412, the denoising process of overlapping segmentation SVD is as follows:

[0171] The original noisy signal sequence a(n) is divided into S segments of length l, each segment is represented by a i (t i ), where i = 1, 2, ..., S; t i represents the time series of the i-th signal segment.

[0172] Construct the Hankel matrix and perform SVD: For each signal segment a i (t i ), the Hankel matrix is ​​of the form:

[0173]

[0174] Then for each H i Perform singular value decomposition and obtain three matrices U i , C i and V i :

[0175] H i =U i ·C i ·V i T (9)

[0176] The step S42 includes: S421, signal sequence recovery: each processed signal segment a i (t i ) is reconstructed through its corresponding SVD decomposition result to restore the original signal; in the overlapping part, the average value of the two adjacent signal segments is taken; the reconstructed original signal can be expressed as:

[0177]

[0178] Among them, "reconstructed a i (t i )" is obtained by using the matrix U i , C i and V i Reconstructed signal segment.

[0179] Step S422: reconstruct the i (t i ) is processed by LWT to obtain X′ i The specific steps are as follows:

[0180] Step S4221: reconstruct the i (t i ) is divided into effective information sequence q iand the sequence X of noise signal points i , and then the sequence of noise signal points X i Decompose into two disjoint subsets to obtain the even-numbered sequence X of noise signal points e(i-1) and the odd number sequence X of noise signal points o(i-1) ;

[0181] Step S4222: Using the even point sequence X e(i-1) and the odd point sequence X o(i-1) The correlation between

[0182] Use even point sequence X e(i-1) Predict odd point sequence X o(i-1) , and calculate the prediction error

[0183] d i-1 =X e(i-1) -X o(i-1) (11)

[0184] Step S4223: Update the dual point sequence X by using the update operator e(i-1) To update and adjust:

[0185] X′ i =X e(i-1) +α·d i-1 (12)

[0186] In the formula, α represents the improvement coefficient.

[0187] Step S4224: according to the updated sequence X of noise signal points i and the effective information sequence q i Get the denoised ultrasonic echo signal h i =q i +X′ i .

[0188] It can be seen that by using the update operator, X is maintained e(i-1) Some frequency components at the decomposition process are reduced, and the aliasing effect is reduced; using detailed signals and update operations to improve X e(i-1) , thereby improving the accuracy of signal reconstruction.

[0189] In this embodiment, step S5 includes:

[0190] Step S51: Denoised ultrasonic echo signal h i Perform fast Fourier transform (FFT) to obtain its spectrum distribution.

[0191] Step S52: performing comparative analysis with the spectrum of the original signal to ensure that the main frequency components are retained and the noise components are effectively suppressed.

[0192] Step S53: According to the spectrum analysis result, further adjust the parameters of the denoising algorithm to optimize the signal quality.

[0193] Furthermore, step S52 also includes the following steps: based on the analysis of the correlation results, the amplitude step and phase correction are performed on the optimized signal to further improve the authenticity and reliability of the signal.

[0194] In order to verify the effectiveness of the denoising algorithm proposed in this embodiment, the EEMD-SVD-LWT denoising method and the EEMD+soft threshold denoising method (ST) are used for denoising respectively. The results are as follows: Figure 6a and 6b The signal-to-noise ratio and mean error of the proposed method and the two comparison methods are shown in Table 1.

[0195] Table 1 Comparison of the effects of various denoising methods

[0196]

[0197] From the data analysis in Table 1, it can be concluded that after using the EEMD-SVD-LWT denoising technology, it is observed that this method has the weakest performance in terms of signal-to-noise ratio and the largest average error. Especially when processing ultrasonic echo signals, the starting position is mostly filtered out, making it difficult to identify, and the signal waveform is unstable. This shows that the signal has been distorted to a certain extent, making the denoising effect unsatisfactory. The EEMD-ST algorithm has filtered out the interference noise to a large extent and suppressed the appearance of singular points, but it has also filtered out some effective information. Relatively speaking, the signal processed by ICEEMDAN-SVD-LWT performs best in terms of signal-to-noise ratio and average error, and the starting position of the ultrasonic echo signal is more completely retained, and the signal distortion is also minimal, indicating that this method is the most ideal in denoising effect. Further analysis of the algorithm's operating efficiency shows that the running times of the EEMD-SVD-LWT, EEMD-ST, and ICEEMDAN-SVD-LWT denoising methods are 4.324 seconds, 3.275 seconds, and 2.784 seconds, respectively, indicating that ICEEMDAN-SVD-LWT has the shortest computing time and the highest efficiency.

[0198] In summary, this embodiment discloses a method for optimizing denoising of casing lead ultrasonic echo / detection signal based on adaptive multi-scale decomposition. First, the ultrasonic echo signal is decomposed by ICEEMDAN to effectively separate high-frequency interference signals and low-frequency signals containing main ultrasonic energy. Subsequently, these IMF components are accurately noise-reduced by SVD-LWT processing, and the effective components are retained. Through this process, we can reconstruct the casing lead ultrasonic signal after denoising. Finally, through experimental research and comparative analysis, this paper verifies the effectiveness and practicality of the denoising method.

[0199] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0200] It should be noted that the devices and methods disclosed in the embodiments of this article can also be implemented in other ways. The device implementation described above is only schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to multiple embodiments of this article. In this regard, each box in the flowchart or block diagram can represent a part of a module, program or code, and the module, program segment or part of the code contains one or more executable instructions for implementing the specified logical function, and the module, program segment or part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented by a dedicated hardware-based system for performing a specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0201] In addition, the functional modules in the various embodiments of this document may be integrated together to form an independent part, or each module may exist independently, or two or more modules may be integrated to form an independent part.

[0202] Although the content of the present invention has been described in detail through the above preferred embodiments, it should be appreciated that the above description should not be considered as a limitation of the present invention. After reading the above content, it will be apparent to those skilled in the art that various modifications and substitutions of the present invention will occur. Therefore, the protection scope of the present invention should be limited by the appended claims.

Claims

1. A casing lead ultrasonic detection system, characterized in that: include: Transmitter probe, A receiving probe, wherein the transmitting probe and the receiving probe are arranged on the outer side wall of the casing; A fault detection main circuit is electrically connected to the transmitting probe and the receiving probe respectively; A host computer, which is electrically connected to the fault detection main circuit and is used to control the fault detection main circuit to drive the transmitting probe to transmit an ultrasonic signal into the casing; The receiving probe receives and transmits an ultrasonic echo signal after the ultrasonic signal is reflected in the casing; The fault detection main circuit is used for processing the received ultrasonic echo signal into a time signal and then displaying it through the host computer.

2. The casing lead ultrasonic detection system according to claim 1, characterized in that: Also includes: A temperature sensor is arranged on the top box shell of the transformer and is used to detect the transformer oil in the bushing; The fault detection main circuit includes a temperature compensation circuit, which is used to perform temperature compensation on the detected oil temperature and transmit the compensated temperature signal to the host computer for display.

3. The casing lead ultrasonic detection system according to claim 1, characterized in that: The fault detection main circuit also includes: The main control chip communicates with the host computer via the RS232 serial port; an ultrasonic transmitting circuit, a signal optimization module and a driving circuit respectively connected to the main control chip, The driving circuit is used to supply power to the main control chip; The ultrasonic transmitting circuit is used to generate a high-frequency oscillation signal to control the transmitting probe to transmit the ultrasonic signal; The ultrasonic echo signal is transmitted to the main control chip through the signal optimization module and converted into the time signal by the main control chip.

4. The casing lead ultrasonic detection system according to claim 1, characterized in that: The signal optimization module is used to perform modal decomposition on the received ultrasonic echo signal using ICEEMDAN, and extract the characteristic vector of each working condition sample after decomposition; Performing correlation analysis on the characteristic vectors of each working condition sample obtained by decomposition to determine the effective signal component and the noise component in the ultrasonic echo signal; De-noising and reconstructing the ultrasonic echo signal by using SVD-LWT according to the effective signal component and the noise component; A power spectrum analysis is performed on the optimized ultrasonic echo signal to verify the signal quality of the optimized ultrasonic echo signal.

5. A method for optimizing denoising of ultrasonic echo signals of cannula leads based on adaptive multi-scale decomposition, characterized in that: The following steps are involved: Step S1: collecting ultrasonic echo signals from transformer bushings; Step S2: Use ICEEMDAN to perform modal decomposition and extract the feature vector of each working condition sample after decomposition; Step S3: performing correlation analysis on the characteristic vectors of each working condition sample obtained by decomposition to determine the modal components of the effective signal and the modal components of the noise in the ultrasonic echo signal; Step S4: De-noising and reconstructing the echo signal using SVD-LWT according to the modal components of the effective signal and the modal components of the noise, completing the adjustment and optimization of the model parameters, and realizing the denoising of the ultrasonic echo signal. Step S5: performing power spectrum analysis on the optimized ultrasonic echo signal.

6. The method for optimizing and denoising the casing lead ultrasonic detection signal based on adaptive multi-scale decomposition according to claim 5 is characterized in that: In step S1, the following steps are included: Step S11: placing a transmitting probe on the outer surface of the transformer bushing; Step S12: The transmitting probe transmits pulsed ultrasonic waves under the excitation of high-voltage electric pulses: The pulsed ultrasonic wave penetrates the porcelain sleeve of the transformer bushing and propagates into the insulating oil inside the transformer bushing; Step S13: The ultrasonic wave generates a reflected wave at the interface between the insulating oil and the lead wire, which is received by the receiving probe and converted into an electrical pulse signal: When ultrasonic waves propagate to the interface between the insulating oil and the lead wire, a reflected wave is generated due to the difference in acoustic impedance; These reflected waves are received by the receiving probe and converted into electrical pulse signals to form ultrasonic echo signals; By measuring the time difference between the transmitted wave and the reflected wave and combining the known propagation speed of ultrasound in insulating oil, the distance from the surface of the bushing to the surface of the lead wire is calculated.

7. The method for optimizing and denoising the casing lead ultrasonic echo signal based on adaptive multi-scale decomposition according to claim 6, characterized in that: The step S2 comprises: Step S21: construct a basic signal containing a noisy signal: Take a base signal x and add to it to generate a series of constructed signals x (i) , which can be expressed as: x (i) =x+β0E1(w (i) ),(i=1,2,…,N) Among them, x (i) is the i-th constructed signal, β0 is the initial noise standard deviation of the signal, and w (i) is the added white noise with zero mean and unit variance, and E1(·) represents the operation of calculating the first inner membrane state function of the signal; Step S22: Calculate the local mean and average: For each constructed signal x (i) Calculate the local mean and then take the average of all local means to get the i-th residual component r i : Here M(·) represents the local mean in the signal, and I represents the total number of constructed signals; Step S23: Calculate the first modal component: The first modal component imf1 is obtained by subtracting the first residual component r1 from the original acquired ultrasonic echo signal x: imf1=x-r1 Step S24: Iteratively calculate subsequent modal components: For the kth (k ≥ 2) modal component imf k , using the previous residual component r k-1 Subtract this residual component r k : imf k =r k-1 -r k And, r k The calculation method is: Among them, E k (·) is the modal component IMF operation corresponding to the kth calculation, β k-1 is the noise standard deviation of the signal at the k-1th order; Step S25: Iteration termination condition: When the residual component meets the predetermined termination condition or the modal component is less than the first three-order local extreme values, the iteration stops; The step S3 comprises: Step S31: Calculate the correlation coefficient between each modal component and the originally acquired ultrasonic echo signal; Step S32: according to the size of the correlation coefficient, a threshold is set to filter out the modal components mainly containing valid signals; Step S33: discard the modal components determined to be noise, and only retain the modal components of the valid signal.

8. The method for optimizing and denoising the casing lead ultrasonic echo signal based on adaptive multi-scale decomposition according to claim 7, characterized in that: The step S4 comprises: Step S41: using SVD-LWT processing to accurately reduce the noise of all the modal components and retain the modal components of the effective signal; Step S42: reconstructing the transformer bushing lead ultrasonic echo signal after denoising according to the module of the effective signal.

9. The method for optimizing and denoising the casing lead ultrasonic echo signal based on adaptive multi-scale decomposition according to claim 8, characterized in that: The step S41 comprises: Step S411: Assume that the long sequence of originally acquired ultrasonic echo signals contains noise a(n) (n=1, 2, ..., L). a(n)=s(n)+w(n) Among them, s(n) represents the effective signal, and w(n) represents the noise signal; Step S412, the denoising process of overlapping segmentation SVD is as follows: The original noisy signal sequence a(n) is divided into S signal segments of length l, each signal segment is represented by a i (t i ), where i = 1, 2, ..., S; ti represents the time series of the i-th signal segment; Construct the Hankel matrix and perform SVD: For each signal segment a i (t i ), the Hankel matrix is ​​of the form: Then for each H i Perform singular value decomposition and obtain three matrices U i , C i and V i : H i =U i ·C i ·V i T The step S42 includes: S421, signal sequence recovery: each processed signal segment a i (t i ) is reconstructed through its corresponding SVD decomposition result to restore the original signal; in the overlapping part, the average value of the two adjacent signal segments is taken; the reconstructed original collected ultrasonic echo signal It can be expressed as: Reconstructed a i (t i ) Among them, "reconstructed a i (t i )" is through U i , C i and V i reconstructed signal segment; Step S422: reconstruct the i (t i ) is processed by LWT to obtain X′ i The specific steps are as follows: Step S4221: reconstruct the i (t i ) is divided into effective information sequence q i and the sequence X of noise signal points i , and then the sequence X of noise signal points i Decompose into two disjoint subsets to obtain the even-numbered sequence X of noise signal points e(i-1) and the odd number sequence X of noise signal points o(i-1) ; Step S4222: Using the even point sequence X e(i-1) and the odd point sequence X o(i-1) The correlation between Use even point sequence X e(i-1) Predict odd point sequence X o(i-1) , and calculate the prediction error d i-1 =X e(i-1) -X o(i-1) ; Step S4223: Update the dual point sequence X by using the update operator e(i-1) To update and adjust: X′ i =X e(i-1) +a·d i-1 In the formula, α represents the lifting coefficient; Step S4224: according to the updated sequence X of noise signal points i and the effective information sequence q i Get the denoised ultrasonic echo signal h i =q i +X′ i .

10. The method for optimizing and denoising the casing lead ultrasonic echo signal based on adaptive multi-scale decomposition according to claim 9, characterized in that: Step S5 includes: Step S51: Denoised ultrasonic echo signal h i Perform fast Fourier transform (FFT) to obtain its spectrum distribution; Step S52: performing comparative analysis with the spectrum of the originally collected ultrasonic echo signal to ensure that the main frequency components are retained and the noise components are effectively suppressed; Step S53: According to the spectrum analysis result, further adjust the parameters of the denoising algorithm to optimize the signal quality.

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