An electromagnetic transformer vibration characteristic acquisition device

Abstract

The present invention provides a vibration characteristic acquisition device for an electromagnetic transformer, belonging to the technical field of electromagnetic transformers. The device mainly includes: a vibration acquisition cylinder, a support frame, a vibration exciter, an electromagnetic transformer fixing device, a vibration sensor assembly, a frequency selector, and a control chip, etc. The device first fixedly installs the electromagnetic transformer through the vibration acquisition cylinder, and evenly distributes a plurality of three-axis acceleration sensors on the outer wall of the cylinder, which can comprehensively collect the vibration signals of the electromagnetic transformer in three spatial axes. At the same time, the vibration exciter at the bottom of the device can generate excitation signals of different frequencies to perform special vibration stimulation on the electromagnetic transformer installed in the acquisition cylinder, and obtain short-term and long-term vibration characteristics through the control chip, solving the technical problems that the existing methods are vulnerable to external interference and it is difficult to simulate the complex vibration characteristics of the electromagnetic transformer caused by a large amount of vibration in the actual operating environment.

Description

Technical Field

[0001] The present invention belongs to the technical field of electromagnetic transformers, and more particularly, relates to a device for collecting vibration characteristics of electromagnetic transformers. Background Art

[0002] Electromagnetic transformers are an important type of intelligent sensing device in the power system and are widely used in the condition monitoring and fault diagnosis of power equipment such as power transformers, motors, and generators. By non-contact detection of the vibration signals of power equipment, electromagnetic transformers can reflect the changes in the operating state of the equipment and provide an important basis for predictive maintenance. Therefore, how to accurately collect and analyze the vibration characteristics of electromagnetic transformers has become one of the key technologies for the health state monitoring of power equipment.

[0003] There are mainly two existing methods for collecting the vibration characteristics of electromagnetic transformers: one is to directly install the electromagnetic transformer on the device to be detected and measure using the vibration of the device itself; the other is to conduct special vibration stimulation on the electromagnetic transformer on a test bench and measure its vibration response. The former is limited by the complex installation environment of the device to be detected and is easily affected by external interference; although the latter can control the vibration excitation conditions, it is difficult to simulate the complex vibration characteristics of the electromagnetic transformer caused by a large amount of vibration in the actual operating environment. In addition, most of the existing vibration characteristic extraction methods are limited to time-domain and frequency-domain analysis and cannot comprehensively reflect the dynamic characteristics of the vibration of electromagnetic transformers.

[0004] In view of the above problems, there is an urgent need for a device for collecting the vibration characteristics of electromagnetic transformers, which can comprehensively collect the vibration responses of electromagnetic transformers under different excitation conditions in a well-controlled test environment and extract multi-dimensional vibration characteristics including time-domain, frequency-domain, and time-frequency characteristics, providing a reliable data basis for subsequent fault diagnosis and life prediction. Summary of the Invention

[0005] In view of this, the present invention provides a device for collecting the vibration characteristics of electromagnetic transformers, which can solve the technical problems that the existing methods for collecting the vibration characteristics of electromagnetic transformers are easily affected by external interference and it is difficult to simulate the complex vibration characteristics of electromagnetic transformers caused by a large amount of vibration in the actual operating environment.

[0006] The present invention is implemented as follows:

[0007] The present invention provides an electromagnetic transformer vibration characteristic acquisition device, comprising: a vibration acquisition cylinder, a support frame, a vibration exciter, an electromagnetic transformer fixing device, a vibration sensor assembly, a frequency selector, and a control chip; the support frame is equipped with the vibration acquisition cylinder; an electromagnetic transformer fixing device is fixedly installed inside the vibration acquisition cylinder, and the electromagnetic transformer fixing device includes a fixed base and a fixed clamp. The fixed base is fixedly connected to the inner wall of the vibration acquisition cylinder through a shock pad, and the fixed clamp is arranged at the upper end of the fixed base and is used for clamping the electromagnetic transformer; at least three vibration sensor assemblies are evenly arranged circumferentially on the outer wall of the vibration acquisition cylinder. Each vibration sensor assembly includes a sensor body and a sensor mounting seat. The sensor mounting seat is fixed on the outer wall of the vibration acquisition cylinder, and the sensor body is installed in the sensor mounting seat through a shock-absorbing rubber ring; the vibration exciter is fixedly installed at the bottom of the vibration acquisition cylinder, and the vibration exciter includes an exciter body and an exciter control unit. The exciter body is connected to the bottom of the vibration acquisition cylinder, and the exciter control unit is used to control the exciter body to generate vibrations of different frequencies; the input end of the frequency selector is electrically connected to the vibration sensor assembly, and the output end is electrically connected to the control chip; the control chip is electrically connected to the frequency selector and the vibration exciter, and is used to process the vibration signals after frequency selection and control the operation of the vibration exciter; a vibration characteristic generation module is arranged in the control chip, and is used to generate long-term vibration characteristics and short-term vibration characteristics and output them.

[0008] On the basis of the above technical solution, an electromagnetic transformer vibration characteristic acquisition device of the present invention can also be improved as follows:

[0009] Wherein, the frequency selector includes a plurality of band-pass filters and a signal conditioning circuit; the center frequency of each band-pass filter corresponds to an excitation frequency of the vibration exciter; the signal conditioning circuit includes a signal amplifier and an analog-to-digital converter. The input end of the signal amplifier is connected to the output ends of the respective band-pass filters, the input end of the analog-to-digital converter is connected to the output end of the signal amplifier, and the output end of the analog-to-digital converter is connected to the control chip.

[0010] Furthermore, the support frame includes a bottom plate and columns. At least four columns are symmetrically arranged on the bottom plate; the vibration acquisition cylinder is fixedly connected to the columns through a flange; a shock-absorbing support foot is also fixedly installed on the bottom plate, and the shock-absorbing support foot includes a support foot body and a shock-absorbing spring. The lower end of the support foot body contacts the ground, and the upper end is connected to the bottom plate through the shock-absorbing spring.

[0011] Furthermore, the fixed clamp of the electromagnetic transformer fixing device includes a bottom clamping plate and a side clamping plate; the bottom clamping plate is fixed on the fixed base, and the side clamping plate is connected to the bottom clamping plate through a hinge; anti-slip rubber layers are provided on the inner surfaces of the bottom clamping plate and the side clamping plate; a wire groove for accommodating the leads of the electromagnetic transformer is also provided on the bottom clamping plate.

[0012] Further, the sensor body of the vibration sensor assembly is a triaxial acceleration sensor; the sensor mounting seat is cylindrical, and its inner wall is provided with an annular groove, and the shock-absorbing rubber ring is embedded in the annular groove.

[0013] Further, the actuator body of the vibration actuator includes an actuator housing, an actuator coil, and an actuator magnet; the actuator housing is a hollow cylindrical structure; the actuator coil is fixed inside the actuator housing, and the actuator magnet is arranged inside the actuator coil and connected to the actuator housing through an elastic support; the actuator control unit is electrically connected to the actuator coil through a power amplifier.

[0014] Further, the top of the vibration collection cylinder is provided with a detachable top cover; the top cover is provided with an observation window, and the observation window is made of explosion-proof glass; a sealing ring is provided at the edge of the top cover for sealing cooperation with the mouth of the vibration collection cylinder; the frequency selector and the control chip are both arranged on the inner wall of the vibration collection cylinder.

[0015] Among them, the vibration feature generation module is used to perform the following steps:

[0016] S10. Real-time collect the vibration data of the electromagnetic mutual inductor at different excitation frequencies, including triaxial acceleration data, timestamp information, and the input voltage and current data of the vibration actuator;

[0017] S20. Preprocess the collected vibration data, including denoising and data standardization;

[0018] S30. Divide the preprocessed vibration data into short-term data and long-term data, where the continuous time window of the short-term data is the sampling data of 10 seconds to 60 seconds, and the long-term data is the sampling data that has been continuously collected for more than 1 hour since the initial collection;

[0019] S40. Perform multivariate hybrid decomposition calculations on the short-term data and long-term data respectively to obtain the short-term vibration stable component and short-term vibration variable component, and the long-term vibration stable component and long-term vibration variable component;

[0020] S50. Establish short-term and long-term vibration variable coefficient matrices respectively, and calculate short-term and long-term vibration stable coefficient matrices respectively according to the established short-term and long-term vibration variable coefficient matrices;

[0021] S60. Use the short-term and long-term vibration stable coefficient matrices to perform error compensation on the short-term and long-term vibration data respectively, and obtain the short-term corrected vibration data and the long-term corrected vibration data respectively;

[0022] S70. Extract features including time-domain analysis and frequency-domain analysis from the short-term corrected vibration data to construct a short-term vibration feature vector; extract features including time-domain analysis, frequency-domain analysis, and time-frequency analysis from the long-term corrected vibration data to construct a long-term vibration feature vector;

[0023] S80. Normalize the constructed short-term vibration feature vector and long-term vibration feature vector respectively to obtain the final short-term vibration feature and long-term vibration feature.

[0024] Further, establish the vibration variation coefficient matrices for short-term and long-term respectively, specifically including: establish the functional relationship between the short-term vibration stable component, the short-term input parameters of the vibration exciter, and the short-term vibration variation component to obtain the short-term vibration variation coefficient matrix; establish the functional relationship between the long-term vibration stable component, the long-term input parameters of the vibration exciter, and the long-term vibration variation component to obtain the long-term vibration variation coefficient matrix.

[0025] Further, perform error compensation on the short-term and long-term vibration data, specifically: short-term corrected vibration data = short-term original vibration data + short-term vibration error compensation amount; long-term corrected vibration data = long-term original vibration data + long-term vibration error compensation amount.

[0026] Specifically, step S10: Real-time collect the vibration data of the electromagnetic current transformer at different excitation frequencies; in this step, it is necessary to real-time collect the three-axis acceleration data a x , a y , a z , the timestamp information t, as well as the input voltage u and current i data of the vibration exciter. To ensure the collection of high-frequency vibration signals, the sampling frequency should not be lower than 1000 Hz. The specific collected data can be expressed as: t;

[0027] Step S20: Preprocess the collected vibration data; in this step, first perform filter denoising on the collected vibration data x to eliminate the interference of external environmental noise on the vibration signal. The band-pass filter method can be used, and the filtered vibration data is denoted as Then, perform standardization processing on the filtered vibration data to eliminate the differences caused by factors such as the measurement environment and installation conditions. The standardization processing formula is: Among them, is the mean vector of , is the standard deviation vector of . The standardized vibration data is denoted as x norm .

[0028] Step S30: Divide the preprocessed vibration data into short-term data and long-term data; according to the typical usage of electromagnetic current transformers, the collected vibration data is divided into two categories: short-term data and long-term data. The continuous sampling time window of short-term data is the sampling data from 10s to 60s, denoted as x short ; the long-term data is the sampling data that has been continuously collected for more than 1h since the beginning, denoted as x long . This classification is beneficial to the subsequent analysis of short-term and long-term vibration characteristics.

[0029] Step S40: Perform multivariate mixed decomposition calculations on short-term data and long-term data respectively; in this step, multivariate mixed decomposition calculations are performed on the preprocessed short-term data x short and long-term data x long respectively, and they are decomposed into stable components and variable components. Performing this calculation on the short-term data x short can obtain the short-term vibration stable component x short-stable and the short-term vibration variable component x short-vary , and the mathematical model is: x short = x short-stable + x short-vary ; performing this calculation on the long-term data x long can obtain the long-term vibration stable component x long-stable and the long-term vibration variable component x long-vary , and the mathematical model is: x long = x long-stable + x long-vary ; the multivariate mixed decomposition in the above formula can be implemented by algorithms such as principal component analysis (PCA) or non-negative matrix factorization (NMF).

[0030] Step S50: Establish the vibration variation coefficient matrices for short-term and long-term; in this step, first establish the functional relationship between the short-term vibration stable component x short-stable , the short-term input parameters u short of the vibration exciter and the short-term vibration variable component x short-vary to obtain the short-term vibration variation coefficient matrix A short : x short-vary = A short x short-stable + B short u short ; where A short is the short-term vibration variation coefficient matrix, and B short is the short-term excitation parameter coefficient matrix. Similarly, establish the functional relationship between the long-term vibration stable component x long-stable , the long-term input parameters u long of the vibration exciter and the long-term vibration variable component x long-vary to obtain the long-term vibration variation coefficient matrix A long : xlong-vary = A long x long-stable + B long u long ; where A long is the long - term vibration variation coefficient matrix, and B long is the long - term excitation parameter coefficient matrix. The above coefficient matrices can be estimated by algorithms such as the least - squares method or the regularized least - squares method.

[0031] Step S60: Perform error compensation on the short - term and long - term vibration data; this step uses the short - term vibration variation coefficient matrix A short and the long - term vibration variation coefficient matrix A long to perform error compensation on the short - term original vibration data x short and the long - term original vibration data x long to obtain the short - term corrected vibration data x short-corr and the long - term corrected vibration data x long-corr . The specific formula is: x short-corr = x short - A short x short-stable ; x long-corr = x long - A long x long-stable ; This can eliminate the variation components in the vibration data caused by the characteristics of the system itself and obtain more accurate vibration characteristics.

[0032] Step S70: Extract features from the short - term and long - term corrected vibration data; this step performs time - domain analysis and frequency - domain analysis on the short - term corrected vibration data x short-corr to extract short - term vibration characteristics including the mean μ short , variance skewness γ short , peak factor k short , center frequency f c,short , etc., and constructs a short - term vibration feature vector f short : Perform time - domain analysis, frequency - domain analysis, and time - frequency analysis on the long - term corrected vibration data x long-corr to extract more comprehensive long - term vibration characteristics and construct a long - term vibration feature vector f long , including time - domain characteristics, frequency - domain characteristics, and time - frequency characteristics, etc.

[0033] Step S80: Normalize the short - term and long - term vibration feature vectors; this step normalizes the constructed short - term vibration feature vector f short and the long - term vibration feature vector f longNormalization is performed separately to eliminate the influence of the dimension on the eigenvalue size, and the final short-term vibration feature f is obtained. short-norm and the long-term vibration feature f long-norm . The normalization formula is: where f is the original eigenvalue, and min(f) and max(f) are the minimum and maximum values of the eigenvalue respectively.

[0034] In summary, this electromagnetic transformer vibration feature acquisition device can collect the vibration data of the electromagnetic transformer at different excitation frequencies in real time, and through a specially designed vibration feature generation module, extract representative short-term and long-term vibration features, providing reliable data support for subsequent electromagnetic transformer condition monitoring and fault diagnosis.

[0035] Compared with the prior art, an electromagnetic transformer vibration feature acquisition device provided by the present invention can collect the vibration data of the electromagnetic transformer at different excitation frequencies in real time, and through a specially designed vibration feature generation module, extract representative short-term and long-term vibration features. The beneficial effects are as follows:

[0036] First of all, the device uses an independent vibration acquisition cylinder, in which an electromagnetic transformer is fixedly installed, and a plurality of vibration sensors are evenly distributed on the outer wall, which can comprehensively collect the three-axis vibration signals of the electromagnetic transformer, avoiding the installation environment interference that may be generated when directly installed on the device to be inspected. At the same time, the built-in vibration exciter of the device can generate excitation signals of different frequencies to perform special vibration stimulation on the electromagnetic transformer, simulating the complex vibration characteristics under the actual operating environment.

[0037] Secondly, the device has an innovative design in the vibration signal processing link. A frequency selector is used to perform band-pass filtering on the vibration signal to eliminate the interference components outside the excitation frequency; and time-domain, frequency-domain and time-frequency features are respectively extracted for short-term and long-term vibration data, and a multi-dimensional feature vector containing short-term and long-term vibration features is constructed. Compared with the existing single time-frequency analysis, this multi-dimensional feature can more comprehensively reflect the vibration dynamic characteristics of the electromagnetic transformer.

[0038] In addition, the device also introduces a method of variable coefficient matrix estimation and error compensation in the vibration data processing link, effectively eliminating the errors caused by factors such as the measurement environment and installation conditions in the vibration data, and improving the accuracy of the vibration features.

[0039] Generally speaking, the electromagnetic mutual inductor vibration characteristic acquisition device proposed by the present invention can comprehensively collect the vibration responses of the electromagnetic mutual inductor under different excitation conditions in a well-controlled test environment, and extract representative short-term and long-term vibration characteristics through innovative signal processing algorithms, solving the technical problems existing in the existing methods for collecting the vibration characteristics of electromagnetic mutual inductors, such as being vulnerable to external interference and difficult to simulate the complex vibration characteristics of electromagnetic mutual inductors caused by a large amount of vibration in the actual operating environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 FIG. is a schematic structural diagram of an electromagnetic mutual inductor vibration characteristic acquisition device provided by the present invention;

[0041] Figure 2 FIG. is a schematic internal structure diagram of a vibration exciter;

[0042] Figure 3 FIG. is a schematic internal structure diagram of a vibration sensor assembly;

[0043] Figure 4 FIG. is a schematic electrical connection diagram of the device;

[0044] Figure 5 FIG. is a flowchart of the steps executed by a vibration characteristic generation module;

[0045] Figure 6 FIG. is a comparison diagram of vibration acceleration time histories in the X, Y, and Z axes;

[0046] Figure 7 FIG. is a power spectral density analysis diagram of three-axis vibration signals;

[0047] Figure 8 FIG. is a comparison diagram of short-term and long-term characteristics of X-axis vibration;

[0048] Figure 9 FIG. is an effect diagram of vibration data error compensation;

[0049] In the drawings, the list of components represented by each reference numeral is as follows:

[0050] 10, support frame; 11, bottom plate; 12, column; 121, flange; 13, shock-absorbing foot; 131, foot body; 132, shock-absorbing spring; 20, vibration acquisition cylinder; 21, vibration exciter; 211, exciter housing; 212, exciter coil; 213, exciter magnet; 214, elastic support; 215, power amplifier; 216, exciter control unit; 31, fixed base; 32, bottom clamping plate; 33, side clamping plate; 41, vibration sensor assembly; 410, sensor body; 411, sensor mounting seat; 412, annular groove; 50, top cover; 52, observation window; 90, electromagnetic mutual inductor. Detailed implementation manners

[0051] To make the objectives, technical solutions and advantages of the implementation manners of the present invention clearer, the technical solutions in the implementation manners of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the implementation manners of the present invention.

[0052] As Figures 1-4 shown, it is a schematic structural diagram of a vibration characteristic acquisition device for an electromagnetic transformer provided by the present invention, including: a support frame 10, a vibration acquisition cylinder 20, a vibration exciter, an electromagnetic transformer fixing device, a vibration sensor assembly, a frequency selector, and a control chip; which are described in detail as follows:

[0053] Support frame 10: The support frame includes a bottom plate 11 and 4 symmetrically arranged columns 12. Four columns are fixed on the bottom plate, and the vibration acquisition cylinder is fixedly connected to the columns through a flange 121. Four shock-absorbing feet are also fixed on the bottom plate, and each shock-absorbing foot includes a foot body 131 and a shock-absorbing spring 132. The lower end of the foot body contacts the ground, and the upper end is connected to the bottom plate through the shock-absorbing spring, which is used to reduce the influence of ground vibration on the entire device.

[0054] Vibration acquisition cylinder 20: The vibration acquisition cylinder in this implementation manner has a cylindrical structure, and the material is selected as high-temperature-resistant stainless steel. The upper end of the vibration acquisition cylinder is provided with a detachable top cover 50, and an observation window 52 is provided on the top cover. The observation window is made of explosion-proof glass. A sealing ring is provided at the edge of the top cover for sealing cooperation with the cylinder mouth of the vibration acquisition cylinder. A shock-absorbing pad is fixed on the inner wall of the vibration acquisition cylinder, and the shock-absorbing pad is used to support the electromagnetic transformer fixing device, which plays a role in reducing the interference of external vibration on the measurement of the electromagnetic transformer.

[0055] Electromagnetic transformer fixing device: The electromagnetic transformer fixing device includes a fixed base 31 and a fixed clamp. The fixed base is fixedly connected to the inner wall of the vibration acquisition cylinder through a shock-absorbing pad. The fixed clamp is arranged at the upper end of the fixed base and is used to clamp the electromagnetic transformer 90 to be measured. The fixed clamp includes a bottom clamping plate 32 and a side clamping plate 33. The bottom clamping plate is fixed on the fixed base, and the side clamping plate is connected to the bottom clamping plate through a hinge. Anti-slip rubber layers are provided on the inner surfaces of the bottom clamping plate and the side clamping plate to increase the clamping force on the electromagnetic transformer. A wire groove for accommodating the leads of the electromagnetic transformer is also provided on the bottom clamping plate.

[0056] Vibration sensor assembly 41: The vibration sensor assembly includes a sensor body 410 and a sensor mounting base 411. The sensor body is a three-axis acceleration sensor for measuring the vibration acceleration of the vibration collection cylinder in three spatial axes. The sensor mounting base is cylindrical, and its inner wall is provided with an annular groove 412. The sensor body is installed in the sensor mounting base through a shock-absorbing rubber ring, and the shock-absorbing rubber ring is embedded in the annular groove to play a role in shock absorption. Three vibration sensor assemblies are evenly arranged along the circumferential direction on the outer wall of the vibration collection cylinder.

[0057] Vibration exciter 21: The vibration exciter includes an exciter body and an exciter control unit. The exciter body includes an exciter housing 211, an exciter coil 212, and an exciter magnet 213. The exciter housing is a hollow cylindrical structure. The exciter coil is fixed inside the exciter housing, and the exciter magnet is arranged inside the exciter coil and connected to the exciter housing through an elastic support member 214. The exciter control unit 216 is electrically connected to the exciter coil through a power amplifier 215 and is used to control the exciter body to generate vibrations of different frequencies. The vibration exciter is fixedly installed at the bottom of the vibration collection cylinder.

[0058] Frequency filter and control chip: The input end of the frequency filter is electrically connected to the vibration sensor assembly, and the output end is electrically connected to the control chip. The frequency filter includes a plurality of band-pass filters and a signal conditioning circuit. The center frequency of each band-pass filter corresponds to an excitation frequency of the vibration exciter. The signal conditioning circuit includes a signal amplifier and an analog-to-digital converter. The input end of the signal amplifier is connected to the output ends of the band-pass filters, the input end of the analog-to-digital converter is connected to the output end of the signal amplifier, and the output end of the analog-to-digital converter is connected to the control chip.

[0059] The control chip is electrically connected to the frequency filter and the vibration exciter and is used to process the vibration signals after frequency screening and control the operation of the vibration exciter. A vibration feature generation module is provided in the control chip for generating long-term vibration features and short-term vibration features and outputting them.

[0060] Specifically, the principle of the present invention is: In a good test environment, an electromagnetic mutual inductor is excited by a special vibration excitation device, and its three-axis vibration signals are collected; by using methods such as frequency filtering, coefficient of variation matrix estimation, and vibration data correction, multi-dimensional features that can represent the vibration dynamic characteristics of the electromagnetic mutual inductor are extracted.

[0061] Specifically, the device first fixedly installs the electromagnetic mutual inductor through the vibration collection cylinder, and evenly distributes a plurality of three-axis acceleration sensors on the outer wall of the cylinder, which can comprehensively collect the vibration signals of the electromagnetic mutual inductor in three spatial axes. At the same time, the vibration exciter at the bottom of the device can generate excitation signals of different frequencies to perform special vibration stimulation on the electromagnetic mutual inductor installed in the collection cylinder.

[0062] In the vibration signal processing section, the device uses a frequency filter to perform band-pass filtering on the collected vibration data, effectively removing the interference components outside the excitation frequency. Then, time-domain, frequency-domain, and time-frequency features are respectively extracted for short-term and long-term vibration data, and a multi-dimensional feature vector containing short-term and long-term vibration features is constructed. Such multi-dimensional features can more comprehensively reflect the vibration dynamic characteristics of the electromagnetic transformer.

[0063] In addition, the device also introduces methods for variable coefficient matrix estimation and vibration data error compensation. First, the functional relationships between the variable components, stable components, and excitation parameters in short-term and long-term vibration data are established to obtain the variable coefficient matrix; then, these matrices are used to correct the original vibration data, eliminating the errors caused by factors such as measurement environment and installation conditions. This method can improve the accuracy and representativeness of vibration features.

[0064] In summary, the electromagnetic transformer vibration feature acquisition device proposed in the present invention makes full use of special vibration excitation and signal processing algorithms, and can comprehensively collect the vibration response of the electromagnetic transformer and extract representative short-term and long-term vibration features under relatively ideal test conditions.

[0065] The following gives an embodiment of a specific application scenario of the present invention: A certain power enterprise intends to perform condition monitoring and fault diagnosis on the electromagnetic transformers in a certain substation, and for this purpose, purchases the electromagnetic transformer vibration feature acquisition device proposed in the present invention. The main components of this device are as follows:

[0066] 1. Vibration acquisition cylinder: Made of stainless steel, with an inner diameter of 500 mm and a height of 800 mm. A detachable observation window is provided at the top of the cylinder body, made of tempered glass, with a diameter of 300 mm. A rubber sealing ring is provided at the edge of the top cover for sealing with the cylinder body. Shock-absorbing pads are evenly distributed on the inner wall of the cylinder, with a thickness of 15 mm and a hardness of 35 Shore A.

[0067] 2. Support frame: The bottom plate has a size of 1000 mm × 1000 mm and is made of 8 mm thick steel plate. Four columns with a diameter of 50 mm and a height of 1200 mm are provided at the four corners of the bottom plate, and the vibration acquisition cylinder is fixed to the columns through 4 flange plates. Four shock-absorbing feet are fixed on the bottom plate, and each foot consists of a foot body with a height of 70 mm and a shock-absorbing spring with a diameter of 100 mm and a stiffness of 10 N / mm.

[0068] 3. Electromagnetic Transformer Fixing Device: The fixing base is made of a steel plate with a thickness of 20 mm and dimensions of 500 mm × 500 mm, and is fixed to the inner wall of the vibration acquisition cylinder through shock pads. The fixing clamp includes a bottom clamping plate at the lower part and a side clamping plate at the upper part. The bottom clamping plate is fixed on the fixing base, and the side clamping plate is connected to the bottom clamping plate through a hinge. The inner surfaces of the clamping plates are all coated with an anti-slip rubber layer with a thickness of 3 mm to increase the clamping force on the electromagnetic transformer. A wire groove with a width of 10 mm and a depth of 15 mm is also provided on the bottom clamping plate for placing the leads of the electromagnetic transformer.

[0069] 4. Vibration Sensor Assembly: There are 3 in total, using triaxial acceleration sensors with a measurement range of ±50 g and a bandwidth of 0.5 Hz to 2000 Hz. The diameter of the sensor body is 25 mm and the height is 35 mm. The sensor mounting base is cylindrical, with an inner diameter of 30 mm, a height of 40 mm, and a wall thickness of 5 mm. An annular groove with a width of 5 mm is provided on the inner wall for installing a shock-absorbing rubber ring. The sensor body is installed in the mounting base through a shock-absorbing rubber ring with a thickness of 6 mm. The 3 sensor assemblies are evenly distributed along the outer wall of the vibration acquisition cylinder.

[0070] 5. Vibration Exciter: The exciter body adopts a hollow cylindrical structure, with an outer diameter of 150 mm and a height of 200 mm. An exciter coil with a diameter of 100 mm and a height of 150 mm is provided inside, and the coil is wound with 2 mm copper wire. The exciter magnet has a diameter of 90 mm and a height of 100 mm, is made of neodymium iron boron permanent magnet material, and is connected to the exciter housing through 4 radial springs. The exciter control unit is driven by a power amplifier and can output a sine wave excitation signal in the range of 0.1 Hz to 200 Hz.

[0071] 6. Frequency Sorter: It includes 6 band-pass filters and a signal conditioning circuit. The center frequencies of each band-pass filter are 10 Hz, 25 Hz, 50 Hz, 75 Hz, 100 Hz, and 150 Hz respectively, and the 3 dB bandwidth is ±2 Hz. The signal conditioning circuit consists of an amplifier with a gain of 20 dB and an analog-to-digital converter with a 16-bit resolution and a sampling rate of 100 kHz.

[0072] 7. Control Chip: Adopts a high-performance ARM Cortex-M7 processor with a main frequency of 480 MHz and has rich peripheral interfaces. It has 16 GB of FLASH and 2 GB of SDRAM built-in. The control chip is connected to the upper computer through an Ethernet interface to achieve data transmission and parameter setting.

[0073] The working process of the device is as follows: First, place the electromagnetic mutual inductor to be measured on the fixing device and clamp it firmly with the fixing fixture. Then, start the vibration exciter to generate a sine wave excitation signal in the range of 0.1 Hz to 200 Hz, driving the electromagnetic mutual inductor to produce a vibration response. Three vibration sensor assemblies collect the acceleration data of the electromagnetic mutual inductor in three spatial axes in real time, and input the data into a frequency filter for band-pass filtering.

[0074] The vibration data output by the frequency filter is amplified and subjected to analog-to-digital conversion, and then transmitted to the control chip for subsequent processing. The control chip first classifies and stores the short-term data (10 s to 60 s) and long-term data (more than 1 h), and then extracts the time-domain features (mean value, variance, skewness, peak factor, etc.), frequency-domain features (frequency center, energy spectrum, etc.) and time-frequency features (wavelet energy, Hilbert-Huang energy spectrum, etc.) respectively, and constructs a multi-dimensional feature vector containing short-term and long-term vibration features.

[0075] In order to eliminate the errors caused by factors such as measurement environment and installation conditions, the control chip also adopts the method of variable coefficient matrix estimation and error compensation. First, establish the functional relationship between the variable components, stable components and excitation parameters in the short-term and long-term vibration data to obtain the variable coefficient matrix; then use these matrices to correct the original vibration data, eliminating the errors caused by environmental factors. After the final obtained short-term and long-term vibration feature vectors are normalized, they are output to the host computer for subsequent analysis and application. The specific steps are as follows:

[0076] 1. Collect vibration data in real time First, install the electromagnetic mutual inductor to be measured in the vibration acquisition device, and generate a sine wave excitation signal of 0.1 Hz to 200 Hz through the vibration exciter. Three vibration sensor assemblies collect the acceleration data of the electromagnetic mutual inductor in three spatial axes (x, y, z axes) in real time, and the sampling frequency is 2000 Hz. At the same time, record the input voltage and current data of the vibration exciter. After 1 h of continuous collection, a total of 180,000 data points are obtained.

[0077] Figure 6 Shows the comparison of the vibration acceleration time histories of the electromagnetic mutual inductor in the X, Y, and Z axes. By separately plotting the data of the three axes, the vibration feature differences in different axes can be clearly observed. It can be seen from the figure that the vibration amplitude of the X axis is the largest, while the vibration of the Y axis is relatively small, which reflects the obvious differences in the vibration response characteristics of the electromagnetic mutual inductor in different directions. Figure 7It is a power spectral density analysis diagram of the three-axis vibration signal. This diagram uses logarithmic coordinates to show the energy distribution of the three-axis vibration signals in the frequency domain. It can be observed that there are significant energy peaks at specific frequency points, and these peaks correspond to the natural frequency or forced vibration frequency of the electromagnetic current transformer. By analyzing these frequency characteristics, the working state and potential faults of the equipment can be judged.

[0078] 2. Preprocess the vibration data. First, filter and denoise the collected vibration data using a 4th-order Butterworth band-pass filter with a passband frequency of 0.5 Hz to 1000 Hz, effectively removing high-frequency noise. Then, standardize the filtered vibration data to eliminate the differences caused by factors such as the measurement environment and installation conditions. The standardization formula is as follows: where, x norm is the standardized data, x is the original data, is the mean of the original data, and σ x is the standard deviation of the original data.

[0079] 3. Classify short-term and long-term vibration data. According to the typical usage of the electromagnetic current transformer, the preprocessed vibration data is divided into two categories: short-term data and long-term data. The continuous sampling time window for short-term data is 30 s, and the long-term data is 1 h of data collected continuously from the beginning. Figure 8 The short-term characteristics and long-term characteristics of the X-axis vibration are intuitively compared in the form of a histogram. The comparison of five statistical characteristics, namely the mean, variance, skewness, peak factor, and frequency center, is shown in the figure. It can be found that there are certain differences between the long-term characteristics and short-term characteristics, and this difference reflects the time-varying nature of the vibration characteristics of the electromagnetic current transformer, which is of great significance for equipment condition monitoring.

[0080] 4. Perform multivariate hybrid decomposition calculation. For the preprocessed short-term data and long-term data, perform multivariate hybrid decomposition calculation respectively to decompose them into stable components and variable components. Performing this calculation on the short-term data can obtain the short-term vibration stable component x short-stable and the short-term vibration variable component x short-vary ; performing this calculation on the long-term data can obtain the long-term vibration stable component x long-stable and the long-term vibration variable component x long-vary . The mathematical model of multivariate hybrid decomposition is as follows: x = x stable + x vary ; where, x is the original vibration data vector, x stable is the stable component vector, and x vary is the variable component vector. The principal component analysis (PCA) algorithm is used to implement this calculation process.

[0081] 5. Establish the coefficient of variation matrix Based on the calculation results of the previous step, first establish the functional relationship between the short-term vibration stable component x short-stable , the short-term input parameters u short of the vibration exciter, and the short-term vibration variation component x short-vary to obtain the short-term vibration coefficient of variation matrix A short : x short-vary = A short x short-stable + B short u short ; Similarly, establish the functional relationship between the long-term vibration stable component x long-stable , the long-term input parameters u long of the vibration exciter, and the long-term vibration variation component x long-vary to obtain the long-term vibration coefficient of variation matrix A long : x long-vary = A long x long-stable + B long u long ; The above coefficient matrices A short and A long are estimated by the least squares method.

[0082] 6. Vibration data error compensation Using the short-term vibration coefficient of variation matrix A short and the long-term vibration coefficient of variation matrix A long established in the previous step, perform error compensation on the short-term original vibration data x short and the long-term original vibration data x long to obtain the short-term corrected vibration data x short-corr and the long-term corrected vibration data x long-corr : x short-corr = x short - A short x short-stable ; x long-corr = x long - A long x long-stable ; This can effectively eliminate the variation components in the vibration data caused by the characteristics of the system itself and obtain more accurate vibration characteristics.

[0083] 7. Vibration feature extraction For the short-term corrected vibration data x short-corr , extract short-term vibration features including the mean μ short , variance , skewness γ short , peak factor k short , frequency center f c,short , etc., and construct a short-term vibration feature vector f short .

[0084] For the vibration data x after long-term correction long-corr , more comprehensive long-term vibration characteristics are extracted, including: time-domain characteristics: mean μ long , variance skewness γ long , peak factor k long , etc.; frequency-domain characteristics: frequency center f c,long , spectral entropy S long , harmonic factor H long , etc.; time-frequency characteristics: wavelet energy E wv,long , Hilbert-Huang energy spectrum E HHT,long , etc.

[0085] These characteristics constitute the long-term vibration feature vector f long . Figure 9 The effect of vibration data error compensation is shown in detail. The upper part shows the original X-axis vibration data, and it can be seen that there is a certain baseline drift and noise interference; the lower part is the data after error compensation, and it can be clearly seen that the baseline of the data is more stable and the vibration characteristics are clearer. This compensation process helps to improve the accuracy of subsequent feature extraction.

[0086] 8. Feature vector normalization Finally, the constructed short-term vibration feature vector f short and the long-term vibration feature vector f long are respectively normalized to eliminate the influence of dimension on the eigenvalue size, and the final short-term vibration feature f short-norm and the long-term vibration feature f long-norm are obtained. The normalization formula is: where f is the original eigenvalue, and min(f) and max(f) are the minimum and maximum values of the eigenvalue respectively.

[0087] Through the above implementation scheme, the vibration characteristic acquisition device of this electromagnetic mutual inductor can comprehensively collect the vibration responses of the electromagnetic mutual inductor under different excitation conditions in a good test environment, and extract representative ones by using innovative signal processing algorithms.

[0088] The above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, and all should be covered by the protection scope of the present invention.

Claims

1. An electromagnetic transformer vibration characteristic acquisition device, characterized in that, Including: A vibration acquisition cylinder, a support frame, a vibration exciter, an electromagnetic mutual inductor fixing device, a vibration sensor assembly, a frequency selector, and a control chip; the support frame is equipped with the vibration acquisition cylinder; an electromagnetic mutual inductor fixing device is fixedly installed inside the vibration acquisition cylinder, and the electromagnetic mutual inductor fixing device includes a fixed base and a fixed clamp. The fixed base is fixedly connected to the inner wall of the vibration acquisition cylinder through a shock pad, and the fixed clamp is arranged at the upper end of the fixed base and is used for clamping the electromagnetic mutual inductor; at least 3 vibration sensor assemblies are evenly arranged circumferentially on the outer wall of the vibration acquisition cylinder. Each vibration sensor assembly includes a sensor body and a sensor mounting seat. The sensor mounting seat is fixed on the outer wall of the vibration acquisition cylinder, and the sensor body is installed in the sensor mounting seat through a shock-absorbing rubber ring; the vibration exciter is fixedly installed at the bottom of the vibration acquisition cylinder, and the vibration exciter includes an exciter body and an exciter control unit. The exciter body is connected to the bottom of the vibration acquisition cylinder, and the exciter control unit is used to control the exciter body to generate vibrations of different frequencies; the input end of the frequency selector is electrically connected to the vibration sensor assembly, and the output end is electrically connected to the control chip; the control chip is electrically connected to the frequency selector and the vibration exciter, and is used to process the vibration signals after frequency selection and control the operation of the vibration exciter; a vibration feature generation module is arranged in the control chip, which is used to generate long-term vibration features and short-term vibration features and output them.

2. The vibration characteristic acquisition device of an electromagnetic mutual inductor according to claim 1, characterized in that The frequency selector includes a plurality of band-pass filters and a signal conditioning circuit; the center frequency of each band-pass filter corresponds to an excitation frequency of the vibration exciter; the signal conditioning circuit includes a signal amplifier and an analog-to-digital converter. The input end of the signal amplifier is connected to the output ends of the band-pass filters, the input end of the analog-to-digital converter is connected to the output end of the signal amplifier, and the output end of the analog-to-digital converter is connected to the control chip.

3. The vibration characteristic acquisition device of an electromagnetic mutual inductor according to claim 2, wherein The support frame includes a bottom plate and columns. At least 4 columns are symmetrically arranged on the bottom plate; the vibration acquisition cylinder is fixedly connected to the columns through a flange; a shock-absorbing support foot is also fixedly installed on the bottom plate. The shock-absorbing support foot includes a support foot body and a shock-absorbing spring. The lower end of the support foot body contacts the ground, and the upper end is connected to the bottom plate through the shock-absorbing spring.

4. An electromagnetic transformer vibration characteristic acquisition device according to claim 3, characterized in that, The fixed clamp of the electromagnetic mutual inductor fixing device includes a bottom clamping plate and a side clamping plate; the bottom clamping plate is fixed on the fixed base, and the side clamping plate is connected to the bottom clamping plate through a hinge; anti-slip rubber layers are provided on the inner surfaces of the bottom clamping plate and the side clamping plate; a wire groove for accommodating the leads of the electromagnetic mutual inductor is also provided on the bottom clamping plate.

5. The electromagnetic mutual inductor vibration characteristic acquisition device according to claim 4, characterized in that, The sensor body of the vibration sensor assembly is a three-axis acceleration sensor; the sensor mounting seat is cylindrical, and an annular groove is provided on its inner wall, and the shock-absorbing rubber ring is embedded in the annular groove.

6. An electromagnetic transformer vibration characteristic acquisition device according to claim 5, characterized in that, The exciter body of the vibration exciter includes an exciter housing, an exciter coil, and an exciter magnet; the exciter housing is a hollow cylindrical structure; the exciter coil is fixed inside the exciter housing, and the exciter magnet is arranged inside the exciter coil and is connected to the exciter housing through an elastic support; the exciter control unit is electrically connected to the exciter coil through a power amplifier.

7. An electromagnetic transformer vibration characteristic acquisition device according to claim 6, characterized in that, A detachable top cover is provided at the top of the vibration acquisition cylinder; an observation window is provided on the top cover, and the observation window is made of explosion-proof glass; a sealing ring is provided at the edge of the top cover for sealing cooperation with the barrel mouth of the vibration acquisition cylinder; the frequency selector and the control chip are both arranged on the inner wall of the vibration acquisition cylinder.

8. An electromagnetic transformer vibration characteristic acquisition device according to claim 1, characterized in that, The vibration feature generation module is used to perform the following steps: S10. Real-time collect the vibration data of the electromagnetic mutual inductor at different excitation frequencies, including three-axis acceleration data, timestamp information, and the input voltage and current data of the vibration exciter; S20. Preprocess the collected vibration data, including denoising and data standardization; S30. Divide the preprocessed vibration data into short-term data and long-term data, where the continuous time window of the short-term data is the sampling data of 10 seconds to 60 seconds, and the long-term data is the sampling data that has been continuously collected for more than 1 hour since the initial collection; S40. Perform multivariate hybrid decomposition calculations on the short-term data and the long-term data respectively to obtain the short-term vibration stable component and the short-term vibration variable component, and the long-term vibration stable component and the long-term vibration variable component; S50. Establish short-term and long-term vibration variable coefficient matrices respectively, and calculate short-term and long-term vibration stable coefficient matrices respectively according to the established short-term and long-term vibration variable coefficient matrices; S60. Use the short-term and long-term vibration stable coefficient matrices to perform error compensation on the short-term and long-term vibration data respectively, and obtain the short-term corrected vibration data and the long-term corrected vibration data respectively; S70. Perform feature extraction including time-domain analysis and frequency-domain analysis on the short-term corrected vibration data to construct a short-term vibration feature vector; perform feature extraction including time-domain analysis, frequency-domain analysis and time-frequency analysis on the long-term corrected vibration data to construct a long-term vibration feature vector; S80. Perform normalization processing on the constructed short-term vibration feature vector and long-term vibration feature vector respectively to obtain the final short-term vibration feature and long-term vibration feature.

9. The vibration characteristic acquisition device of an electromagnetic transformer according to claim 8, characterized in that, The establishment of the short-term and long-term vibration variable coefficient matrices specifically includes: establishing the functional relationship between the short-term vibration stable component, the short-term input parameters of the vibration exciter and the short-term vibration variable component to obtain the short-term vibration variable coefficient matrix; establishing the functional relationship between the long-term vibration stable component, the long-term input parameters of the vibration exciter and the long-term vibration variable component to obtain the long-term vibration variable coefficient matrix.

10. An electromagnetic transformer vibration characteristic acquisition device according to claim 9, characterized in that, The error compensation for the short-term and long-term vibration data is specifically: the short-term corrected vibration data is the sum of the short-term original vibration data and the short-term vibration error compensation amount; the long-term corrected vibration data is the sum of the long-term original vibration data and the long-term vibration error compensation amount.

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