CN118759260A - Sector scanning detection method and system for detecting conductivity of supercapacitor - Google Patents

Abstract

The present invention relates to the field of conductivity detection technology, and in particular to a sector scanning detection method and system for detecting the conductivity of a supercapacitor, the method comprising: monitoring real-time thermoacoustic signals at each monitoring point; extracting real-time signal strength and real-time signal stability of the real-time thermoacoustic signal; adjusting a preset number; adjusting a preset rotation angular velocity; adjusting a preset angle; extracting real-time conductivity; adjusting a preset rotation radius, or correcting the adjusted preset angle; constructing a conductivity distribution map and outputting it. The present invention can efficiently excite and capture the thermoacoustic response of a supercapacitor through the combined use of a pulsed magnetic field and an ultrasonic transducer, and the extraction of real-time signal strength and stability and the dynamic parameter adjustment mechanism ensure that high-quality signal data can be obtained under different conditions, effectively solving the problem of low detection efficiency caused by long detection time and high system pressure due to high sampling density requirements and high computational complexity.

Description

Sector scanning detection method and system for detecting conductivity of supercapacitor

Technical Field

The present invention relates to the technical field of conductivity detection, and in particular to a sector scanning detection method and system for detecting the conductivity of a supercapacitor.

Background Art

The performance of supercapacitors is closely related to the conductivity of their electrode materials. The size of their conductivity determines the charging and discharging performance of supercapacitors. Therefore, the detection of their conductivity plays an extremely important role in the development of supercapacitors. The inductive thermoacoustic detection system is a non-contact detection method that stimulates the supercapacitor material to be tested through a pulsed magnetic field. The eddy currents induced inside the material to be tested absorb thermal expansion under the action of the magnetic field and emit thermoacoustic signals. The ultrasonic transducer arranged on the periphery receives the filtered and amplified ultrasonic signal and reconstructs the conductivity distribution inside the material to be tested. The existing inductive thermoacoustic detection system places the energy storage material to be tested in a pulsed magnetic field, places an ultrasonic transducer around the target to be tested, and rotates around the target to be tested to detect the thermoacoustic signal, thereby reconstructing the conductivity information of the target to be tested.

The technical disadvantages of the current inductive thermoacoustic detection method are as follows: the inductive thermoacoustic detection method is divided into two processes for inverting the conductivity of the target body to be measured according to the thermoacoustic signal. First, the heat absorption function of the target body to be measured is inverted by the time inversion method or the back projection method according to the collected thermoacoustic signal. Secondly, the conductivity distribution information of the target body to be measured is inverted by the least squares iteration algorithm according to the inverted heat absorption function. Since the circular scanning has a maximum observation angle of 360 degrees in a two-dimensional plane, the most information of the target body to be measured can be obtained during the circular scanning process. However, the time inversion method or the back projection method requires a large amount of comprehensive detection information in the inversion process to invert the heat absorption function, which has very high requirements for the sampling density in space and time, which brings a relatively large pressure to the system. The time for collecting thermoacoustic signals is relatively long, which increases the detection time and workload. At the same time, a large amount of detection information also increases the computational complexity of the inversion algorithm.

Summary of the invention

To this end, the present invention provides a sector scanning detection method and system for detecting the conductivity of a supercapacitor, so as to overcome the problems of low detection efficiency caused by high sampling density requirements and high computational complexity resulting in long detection time and high system pressure in the prior art.

To achieve the above object, the present invention provides a sector scanning detection method for detecting the conductivity of a supercapacitor, comprising:

The target object to be measured is placed in a pulsed magnetic field, and a preset number of ultrasonic transducers are used to rotate the target object at a preset rotation radius and a preset rotation angular velocity to monitor the real-time thermoacoustic signal at each monitoring point;

Extracting real-time signal strength and real-time signal stability of real-time thermoacoustic signals;

Adjust the preset quantity according to the real-time signal strength and the preset standard signal strength;

Adjusting the preset rotation angular velocity according to the real-time signal stability and the preset standard signal stability;

Adjust the preset angle according to the maximum value of all real-time signal strengths within the preset rotation time and the preset standard peak range;

Using a preset algorithm based on compressed sensing theory, the conductivity matrix of the target body to be measured is reconstructed through the real-time thermoacoustic signals of each monitoring point, and the real-time conductivity is extracted from the conductivity matrix;

Adjusting a preset rotation radius according to the real-time conductivity and a preset standard conductivity range, or correcting an adjusted preset angle according to the real-time conductivity and a preset standard conductivity range;

A conductivity distribution map is constructed and outputted according to the real-time thermoacoustic signal whose real-time conductivity is within a preset standard conductivity range.

Furthermore, extracting the real-time signal strength of the real-time thermoacoustic signal includes:

The real-time thermoacoustic signal is converted into a digital signal using an analog-to-digital converter, and the root mean square of the digital signal within a preset window time period is calculated to obtain the real-time signal strength.

Furthermore, extracting the real-time signal stability of the real-time thermoacoustic signal includes:

The standard deviation of the real-time thermoacoustic signal converted into a digital signal is calculated to obtain the real-time signal stability.

Further, adjusting the preset number according to the real-time signal strength and the preset standard signal strength includes:

When the real-time signal strength is less than the preset standard signal strength, the preset quantity is increased and adjusted at a preset quantity adjustment ratio according to the real-time signal strength and the preset standard signal strength.

Further, adjusting the preset rotation angular velocity according to the real-time signal stability and the preset standard signal stability includes:

When the real-time signal stability is greater than the preset standard signal stability, the preset rotation angular velocity is reduced and adjusted at a preset stability adjustment ratio according to the real-time signal stability and the preset standard signal stability.

Further, adjusting the preset angle according to the maximum value of all real-time signal strengths within the preset rotation time and the maximum value of the preset standard peak range includes:

When the maximum value of all real-time signal strengths is greater than the maximum value of the preset standard peak range, the preset angle is reduced and adjusted according to the maximum value of all real-time signal strengths, the maximum value of the preset standard peak range and the preset peak adjustment ratio.

Further, adjusting the preset angle according to the maximum value of all real-time signal strengths within the preset rotation time and the minimum value of the preset standard peak range includes:

When the maximum value of all real-time signal strengths is less than the minimum value of the preset standard peak range, the preset angle is increased and adjusted according to the maximum value of all real-time signal strengths, the minimum value of the preset standard peak range and the peak adjustment ratio.

Furthermore, the method of using a preset algorithm based on compressed sensing theory to reconstruct a conductivity matrix of the target body to be measured through real-time thermoacoustic signals of each monitoring point, and extracting real-time conductivity from the conductivity matrix includes:

Sampling a preset number of random vectors of the thermoacoustic signals randomly monitored by the ultrasonic transducer for a preset number of times within the rotation time to obtain sampling data;

Integrate the sampled data to obtain the corresponding velocity potential function matrix;

An orthogonal basis matrix is selected and the observation matrix is calculated based on the randomly sampled velocity potential function data;

The heat absorption function matrix of the target body to be measured is reconstructed using wavelet basis and Fourier basis as sparse basis;

The conductivity matrix of the target body to be measured is reconstructed using the least squares iterative algorithm;

Extract the real-time conductivity corresponding to each monitoring point from the reconstructed conductivity matrix;

Further, the adjusting the preset rotation radius according to the real-time conductivity and the preset standard conductivity range, or correcting the adjusted preset angle according to the real-time conductivity and the preset standard conductivity range includes:

When the real-time conductivity is greater than the maximum value of the preset standard conductivity range, and the difference between the real-time conductivity and the maximum value of the preset standard conductivity range is greater than the preset standard deviation, the adjusted preset angle is reduced according to the difference, the preset standard deviation and the preset angle correction ratio;

When the real-time conductivity is less than the minimum value of the preset standard conductivity range, and the difference between the real-time conductivity and the maximum value of the preset standard conductivity range is greater than the preset standard deviation, the adjusted preset angle is increased according to the difference, the preset standard deviation and the preset angle correction ratio;

When the real-time conductivity is greater than the maximum value of the preset standard conductivity range, and the difference between the real-time conductivity and the maximum value of the preset standard conductivity range is less than the preset standard deviation value, the preset rotation radius is reduced according to the real-time conductivity, the maximum value of the preset standard conductivity range and the preset radius adjustment ratio;

When the real-time conductivity is less than the minimum value of the preset standard conductivity range, and the difference between the real-time conductivity and the maximum value of the preset standard conductivity range is less than the preset standard deviation value, the preset rotation radius is increased according to the real-time conductivity, the maximum value of the preset standard conductivity range and the preset radius adjustment ratio.

A sector scanning detection system for detecting the conductivity of a supercapacitor, comprising:

A data monitoring module, comprising a preset number of ultrasonic transducers, for rotating at a preset angle with a preset rotation radius and a preset rotation angular velocity, to monitor real-time thermoacoustic signals from a target body to be measured in a pulsed magnetic field at each monitoring point;

A signal extraction module, connected to the data monitoring module, for extracting the real-time signal strength and real-time signal stability of the real-time thermoacoustic signal according to a built-in preset extraction algorithm;

An adjustment module, connected to the signal extraction module, adjusting the preset quantity according to the real-time signal strength and the preset standard signal strength;

The adjustment module is also used to adjust the preset rotation angular velocity according to the real-time signal stability and the preset standard signal stability;

The adjustment module is also used to adjust the preset angle according to the maximum value of all real-time signal strengths within the preset rotation time and the preset standard peak range;

A conductivity reconstruction and extraction module, connected to the adjustment module and the data monitoring module respectively, for reconstructing the conductivity matrix of the target body to be measured through the real-time thermoacoustic signals of each monitoring point using a preset algorithm based on the compressed sensing theory, and extracting the real-time conductivity from the conductivity matrix;

A correction module, connected to the conductivity reconstruction and extraction module, for adjusting a preset rotation radius according to the real-time conductivity and a preset standard conductivity range, or correcting the adjusted preset angle;

The output module is connected to the conductivity reconstruction and extraction module and the correction module respectively, and is used to construct and output a conductivity distribution map according to the real-time thermoacoustic signal whose real-time conductivity is within a preset standard conductivity range.

Compared with the prior art, the beneficial effect of the present invention is that, through the combined use of pulsed magnetic field and ultrasonic transducer, the thermoacoustic response of supercapacitor can be efficiently stimulated and captured, thereby improving the sensitivity and accuracy of detection. The extraction of real-time signal strength and stability and the dynamic parameter adjustment mechanism enhance the adaptive ability of the system and ensure that high-quality signal data can be obtained under different conditions. The algorithm based on compressed sensing theory not only improves the efficiency of data processing, but also reduces the requirements for the number and performance of monitoring equipment. By constructing a conductivity distribution map, it provides users with intuitive and detailed capacitor performance information, which is helpful for the optimization design and quality control of materials, and effectively solves the problem of low detection efficiency caused by high sampling density requirements and high computational complexity, resulting in long detection time and high system pressure.

Furthermore, the RMS value provides an accurate measure of signal power, which helps to distinguish between signals and noise, thereby improving the accuracy of signal detection. The use of an analog-to-digital converter can ensure that the digital processing of the signal is not affected by interference and attenuation that may be encountered during the transmission of the analog signal. By accurately extracting the real-time signal strength, it can provide reliable data support for subsequent signal stability evaluation and system parameter adjustment, thereby optimizing the performance of the entire detection system.

Furthermore, the standard deviation provides an objective measure to quantify signal fluctuations, allowing the stability of the signal to be accurately assessed. A smaller standard deviation means less signal fluctuation, indicating high signal quality and low noise levels, which helps improve the accuracy of signal processing. Real-time monitoring of signal stability allows the system to dynamically adjust parameters, such as adjusting the monitoring frequency or gain of the ultrasonic transducer, to adapt to signal changes, ensuring the continuity and reliability of the measurement.

Furthermore, by adjusting the number of ultrasonic transducers based on the comparison between the real-time signal strength and the preset standard signal strength, the quality of signal acquisition and the system's adaptability can be significantly improved. When the signal strength is insufficient, adding ultrasonic transducers can enhance the signal receiving capability, thereby ensuring the clarity and accuracy of the signal and avoiding measurement errors caused by weak signals.

Furthermore, by adjusting the rotation angular velocity according to the real-time signal stability, the signal acquisition quality can be effectively optimized. When the signal fluctuates greatly, slowing down the rotation angular velocity helps the system to capture signal changes more accurately, reduce signal distortion or omissions caused by rapid rotation, improve the flexibility and adaptability of the system, and ensure that high-quality signal data can be obtained under different measurement conditions.

Furthermore, when the real-time signal strength exceeds the expected high value, reducing the preset angle can achieve a fine scan of the signal high-intensity area, which helps to accurately locate and analyze the signal source. This can not only improve the resolution of monitoring, but also enhance the ability to identify abnormal or critical areas. When the real-time signal strength is lower than the expected value, increasing the preset angle helps to ensure the integrity of the entire monitoring area and avoid missing any important information that may affect the evaluation results.

Furthermore, the reconstructed conductivity matrix is reconstructed using the algorithm of compressed sensing theory, which can effectively recover the complete signal from the sparse sampled data when the signal sampling is far below the Nyquist rate. This greatly reduces the amount of monitoring data required and improves the efficiency of data processing. The accuracy and robustness of data processing are enhanced by the use of integral and orthogonal basis matrices. The use of wavelet basis and Fourier basis as sparse basis can better capture the local characteristics and frequency components of the signal, thereby improving the quality of reconstruction. The application of the least squares iterative algorithm further optimizes the reconstruction process of the conductivity matrix and ensures the accuracy and reliability of the reconstruction results. The real-time conductivity U obtained by this method can provide accurate data support for the electrical properties analysis of the material.

Furthermore, by dynamically adjusting the monitoring parameters by comparing the real-time conductivity with the preset standard conductivity range, an adaptive monitoring strategy is provided, which can accurately respond to different conductivity conditions. When the real-time conductivity is higher or lower than the preset standard conductivity range, the conductivity abnormality area can be more effectively located and evaluated by adjusting the angle or radius, thereby achieving more accurate material property analysis.

Furthermore, the system can adaptively adjust monitoring parameters to ensure high-quality signal data under different conditions, thereby improving the accuracy and repeatability of measurements. The application of compressed sensing theory greatly reduces the need for data acquisition while maintaining high accuracy of reconstruction results. The dynamic adjustment and correction mechanism enables the system to quickly respond to real-time monitoring results and optimize measurement strategies.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a flow chart of a sector scanning detection method for detecting the conductivity of a supercapacitor according to the present embodiment;

FIG2 is a schematic diagram of monitoring real-time thermoacoustic signals at each monitoring point according to the present embodiment;

FIG3 is a logic diagram of determining the adjustment of the preset rotation angular velocity according to the present embodiment;

FIG4 is a schematic diagram of a sector scanning detection system for detecting the conductivity of a supercapacitor according to this embodiment;

Explanation of the reference numerals: 1. Pulsed magnetic field; 2. Target to be measured; 3. Ultrasonic transducer.

DETAILED DESCRIPTION

In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

Please refer to FIG1 , which is a flow chart of the sector scanning detection method for detecting the conductivity of a supercapacitor according to this embodiment;

Please continue to refer to FIG. 2 , which is a schematic diagram of monitoring real-time thermoacoustic signals at each monitoring point in this embodiment;

This embodiment provides a sector scanning detection method for detecting the conductivity of a supercapacitor, comprising:

The target body 2 to be measured is placed in the pulsed magnetic field 1, and a preset number of ultrasonic transducers 3 are used to rotate at a preset angle with a preset rotation radius and a preset rotation angular velocity to monitor the real-time thermoacoustic signal at each monitoring point, wherein the rotation radius refers to the distance between the lowest ultrasonic transducer 3 and the center of the target body to be measured, and the rotation angle is the range in which the ultrasonic transducer 3 rotates around the target body 2 to be measured; wherein the preset angle is less than 360°, so the scanning range is fan-shaped;

Extracting real-time signal strength and real-time signal stability of real-time thermoacoustic signals;

Adjust the preset quantity according to the real-time signal strength and the preset standard signal strength;

Adjusting the preset rotation angular velocity according to the real-time signal stability and the preset standard signal stability;

Adjust the preset angle according to the maximum value of all real-time signal strengths within the preset rotation time and the preset standard peak range;

Using a preset algorithm based on compressed sensing theory to reconstruct the conductivity matrix of the target body to be measured according to the real-time thermoacoustic signals at each monitoring point and extract the real-time conductivity;

Adjusting a preset rotation radius according to the real-time conductivity and a preset standard conductivity range, or correcting an adjusted preset angle according to the real-time conductivity and a preset standard conductivity range;

A conductivity distribution map is constructed and outputted according to the real-time thermoacoustic signal whose real-time conductivity is within a preset standard conductivity range.

First, the supercapacitor to be tested is placed in a pulsed magnetic field, and multiple ultrasonic transducers are used to perform a sector scan of the capacitor at a predetermined rotation radius and speed. During the scanning process, the system monitors and records the real-time thermoacoustic signals generated at each monitoring point. These signals are converted into digital signals by an analog-to-digital converter, and the signal strength and stability are calculated. According to these parameters, the number, angular velocity and angle of rotation of the ultrasonic transducers are dynamically adjusted to optimize the quality and efficiency of signal acquisition by comparing them with the preset standards. Subsequently, the collected thermoacoustic signals are processed and reconstructed using an algorithm based on compressed sensing theory to obtain the conductivity matrix of the capacitor. Finally, based on the comparison results between the real-time conductivity and the preset conductivity range, the rotation radius or angle is further adjusted to ensure the measurement accuracy, and a conductivity distribution map is constructed for output.

By combining the use of pulsed magnetic fields and ultrasonic transducers, the thermoacoustic response of supercapacitors can be efficiently stimulated and captured, improving the sensitivity and accuracy of detection. The extraction of real-time signal strength and stability and the dynamic parameter adjustment mechanism enhance the system's adaptive ability and ensure that high-quality signal data can be obtained under different conditions. The algorithm based on compressed sensing theory not only improves the efficiency of data processing, but also reduces the requirements for the number and performance of monitoring equipment. By constructing a conductivity distribution map, it provides users with intuitive and detailed capacitor performance information, which is helpful for material optimization design and quality control.

Specifically, extracting the real-time signal strength of the real-time thermoacoustic signal includes:

The real-time thermoacoustic signal is converted into a digital signal using an analog-to-digital converter, and the root mean square of the digital signal within a preset window time period is calculated to obtain the real-time signal strength, where: , I is the real-time signal strength, T is the preset window time period, v(t) is the real-time voltage value in the digital signal at time t, and dt is the unit time interval.

First, an analog-to-digital converter is used to convert the received analog thermoacoustic signal into digital form for further digital signal processing. Next, a preset window time period is selected, and the root mean square calculation of the digital signal is performed during this time period. The root mean square value is an effective measure of the signal power. It is obtained by calculating the average of the squares of all sampling points of the signal within the window and then taking the square root. This value reflects the strength of the signal and is a key step in analyzing signal characteristics and subsequent processing.

The RMS value provides an accurate measure of signal power, which helps to distinguish between signals and noise, thereby improving the accuracy of signal detection. The use of an analog-to-digital converter can ensure that the digital processing of the signal is not affected by the interference and attenuation that may be encountered during the transmission of the analog signal. By accurately extracting the real-time signal strength, it can provide reliable data support for subsequent signal stability evaluation and system parameter adjustment, thereby optimizing the performance of the entire detection system.

Specifically, the real-time signal stability of the extracted real-time thermoacoustic signal includes:

Calculate the standard deviation of the real-time thermoacoustic signal converted into a digital signal to obtain the real-time signal stability, where: , S is the real-time signal stability, and v' is the average value of all real-time voltage values within the window time period.

First, the real-time thermoacoustic signal is converted into a digital signal through an analog-to-digital converter. This conversion ensures the accuracy of the signal and the feasibility of subsequent processing. Then, within a specific time window, these digitized signal samples are analyzed to calculate the deviation of each sample value from the signal average value within the window. These deviations are squared, summed, and then divided by the number of samples to obtain the variance. Finally, the square root of the variance is taken to obtain the standard deviation, which quantifies the degree of signal fluctuation, that is, the stability of the signal.

The standard deviation provides an objective measure to quantify signal fluctuations, allowing the stability of the signal to be accurately assessed. A smaller standard deviation means less signal fluctuation, indicating high signal quality and low noise levels, which helps improve the accuracy of signal processing. Real-time monitoring of signal stability allows the system to dynamically adjust parameters, such as adjusting the monitoring frequency or gain of the ultrasonic transducer, to adapt to signal changes, ensuring the continuity and reliability of the measurement.

Specifically, adjusting the preset number according to the real-time signal strength and the preset standard signal strength includes:

When the real-time signal strength is less than the preset standard signal strength, the preset quantity is increased and adjusted according to the preset quantity adjustment ratio based on the real-time signal strength and the preset standard signal strength, wherein W’=W+a1×(I-I0), W’ is the adjusted preset quantity, W is the preset quantity, a1 is the preset quantity adjustment ratio, and I0 is the preset standard signal strength.

The preset quantity adjustment ratio a1 is a proportional coefficient for adjusting the preset quantity W. When there is a difference between the real-time signal strength I and the preset standard signal strength I0, this proportional coefficient determines the amplitude of the adjustment of the preset quantity W according to the difference. It depends on the sensitivity requirements of the system and the response speed of the system, which is usually determined by experiments or experience. In this embodiment, it is necessary to respond quickly to the change of signal strength, and the preset quantity adjustment ratio a1 is set to 0.5.

First, the intensity of the thermoacoustic signal is monitored and calculated in real time to obtain the value of the real-time signal intensity. Subsequently, the real-time signal intensity is compared with the preset standard signal intensity. If the real-time signal intensity is found to be lower than the preset standard signal intensity, the number of ultrasonic transducers used is automatically increased according to the difference between the two and the preset quantity adjustment ratio. This increased amount is calculated according to the predetermined adjustment ratio to ensure that the signal intensity meets or exceeds the required standard.

By adjusting the number of ultrasonic transducers based on the comparison between the real-time signal strength and the preset standard signal strength, the quality of signal acquisition and the system's adaptability can be significantly improved. When the signal strength is insufficient, adding ultrasonic transducers can enhance the signal reception capability, thereby ensuring the clarity and accuracy of the signal and avoiding measurement errors caused by weak signals.

Please continue to refer to FIG. 3 , which is a determination logic diagram for determining and adjusting the preset rotation angular velocity in this embodiment;

Specifically, adjusting the preset rotation angular velocity according to the real-time signal stability and the preset standard signal stability includes:

When the real-time signal stability is greater than the preset standard signal stability, the preset rotation angular velocity is reduced and adjusted by the preset stability adjustment ratio according to the real-time signal stability and the preset standard signal stability, wherein V’=V-a2×(S-S0), V’ is the adjusted preset rotation angular velocity, V is the preset rotation angular velocity, a2 is the preset stability adjustment ratio, and S0 is the preset standard signal stability.

The preset stability adjustment ratio a2 is a proportional factor for adjusting the rotation angular velocity according to the change in signal stability. It depends on the system's sensitivity requirements for signal stability and the required adjustment response speed. It is usually set to a value less than 1 to ensure a smooth adjustment effect. In this embodiment, it is set to 0.3 based on system performance requirements and experimental results. It can ensure the system's sensitive response to stability changes, while avoiding excessive or insufficient adjustments and improving system stability.

The fluctuation of the signal is quantified by calculating the standard deviation of the signal. The system compares the obtained real-time signal stability with the preset standard signal stability. When the real-time signal stability exceeds the preset standard signal stability, that is, the signal fluctuation is large, the system will adjust the ratio according to the difference between the two and a preset stability, and reduce the preset rotation angular velocity of the ultrasonic transducer accordingly. This adjustment is intended to increase the time resolution of signal acquisition by slowing down the rotation angular velocity, thereby obtaining a more stable and reliable signal.

By adjusting the preset rotation angular velocity according to the real-time signal stability, the signal acquisition quality can be effectively optimized. When the signal fluctuates greatly, slowing down the rotation angular velocity helps the system to capture signal changes more finely, reduce signal distortion or omissions caused by rapid rotation, improve the flexibility and adaptability of the system, and ensure that high-quality signal data can be obtained under different measurement conditions.

Specifically, adjusting the preset angle according to the maximum value of all real-time signal strengths within the preset rotation time and the maximum value of the preset standard peak range includes:

When the maximum value of all real-time signal strengths is greater than the maximum value of the preset standard peak range, the preset angle is reduced and adjusted according to the maximum value of all real-time signal strengths, the maximum value of the preset standard peak range and the preset peak adjustment ratio, wherein D’=D-a3×(I-Imax), D’ is the adjusted preset angle, D is the preset angle, a3 is the preset peak adjustment ratio, and Imax is the maximum value of the preset standard peak range.

The preset peak adjustment ratio a3 is a proportional factor for adjusting the preset angle according to the change in the signal strength peak value. It depends on the system's sensitivity to the signal strength peak value and the required adjustment amplitude. It is usually set to a value less than 1, and in this embodiment is set to 0.05 to ensure smooth and effective angle adjustment.

Specifically, adjusting the preset angle according to the maximum value of all real-time signal strengths within the preset rotation time and the minimum value of the preset standard peak range includes:

When the maximum value of all real-time signal strengths is less than the minimum value of the preset standard peak range, the preset angle is adjusted according to the maximum value of all real-time signal strengths, the minimum value of the preset standard peak range and the preset peak adjustment ratio, where D’=D+a3×(Imin-I), Imin is the minimum value of the preset standard peak range.

First, the real-time signal strength of all monitoring points is collected within the preset rotation time, and the maximum value of these signal strengths is determined. This maximum value is compared with the boundary value of the preset standard peak range. If the maximum value of the real-time signal strength exceeds the maximum value of the preset standard peak range, the preset angle is reduced according to the excess ratio and the preset peak adjustment ratio to scan the area with high signal strength more carefully. On the contrary, if the maximum value of the real-time signal strength is lower than the minimum value of the preset standard peak range, the preset angle is increased according to the insufficient ratio and the peak adjustment ratio to expand the monitoring range and ensure that the signal strength area that may be missed is covered.

When the signal strength exceeds the expected high value, reducing the preset angle can achieve a fine scan of the high-intensity signal area, which helps to accurately locate and analyze the signal source. This not only improves the resolution of monitoring, but also enhances the ability to identify abnormal or critical areas. When the real-time signal strength is lower than the expected value, increasing the preset angle helps to ensure the integrity of the entire monitoring area and avoid missing any important information that may affect the evaluation results.

Specifically, the method of using a preset algorithm based on compressed sensing theory to reconstruct the conductivity matrix of the target body to be measured through the real-time thermoacoustic signals of each monitoring point, and extracting the real-time conductivity from the conductivity matrix includes:

Sampling N random vectors of the M-times of thermoacoustic signals randomly monitored by the ultrasonic transducer within the rotation time to obtain sampling data;

Integrate the sampled data to obtain the corresponding velocity potential function matrix ;

Select an orthogonal basis matrix and calculate the observation matrix K based on the randomly sampled velocity potential function data;

The heat absorption function matrix Q' of the target body to be measured is reconstructed using wavelet basis and Fourier basis as sparse basis;

Reconstruct the conductivity matrix of the target body using the least squares iterative algorithm ;

Extract the real-time conductivity U corresponding to each monitoring point from the reconstructed conductivity matrix;

Among them, the sound pressure fluctuation equation satisfied by the thermoacoustic signal is:

;

Where p(r, t) is the thermal acoustic signal received by the ultrasonic transducer at the monitoring point r, ² p(r,t) is the sum of the second-order derivatives of the thermoacoustic signal p(r,t) in space, c _s ² represents the square of the sound velocity of the wave, Q(r′) is the intensity of the thermoacoustic source at position r′, t is the time, (t) is the Dirac function at time t, C _P is the specific heat capacity of the material, β is the volume expansion coefficient of the material, r′ represents the position of the target body to be measured, and the velocity potential function of the thermoacoustic signal vibration is introduced. (r, t), (r, t) is the velocity potential function matrix The relationship between the display form at the monitoring point r and time t and the sound pressure is:

;

Then the velocity potential wave equation of the thermoacoustic signal vibration is:

;

By selectively solving the above equation using Green's function and Dirac function, the expression of velocity potential can be obtained as follows:

, R is the preset rotation radius, l is the integral variable for the range of integration and the amount of change during the integration process;

The matrix form is expressed by the moment method as follows:

F = K × Q ;

Where F is the velocity potential function (r, t), Q is the column vector corresponding to the intensity Q(r′) of the thermal acoustic source of the target body to be measured at position r′, and K is the matrix related to the sound field. Assuming that there are y discrete points in the detection area, the number of ultrasonic transducers is m, and the time points at which each ultrasonic transducer collects data are n, then the velocity potential function corresponding to the collected acoustic signal is (r,t) is discretized into (r _k ,t _l ), where [1:m], [1:n], F is an m×n dimensional column vector. K is a matrix with m×n rows and y columns. If the coefficient matrix K is non-singular, then the generalized inversion method can be used to solve it, that is, the heat absorption coefficient distribution is:

Q = K ^-1 F;

The signal collected by the ultrasonic transducer is randomly sampled and the corresponding velocity potential function moment is formed. And the measurement matrix K, then use the wavelet basis and Fourier basis as the sparse basis to reconstruct the distribution of the heat absorption function of the target to be measured.

In the process of reconstructing the conductivity matrix using an algorithm based on compressed sensing theory, N random vectors are first sampled from the M thermoacoustic signals randomly monitored by the ultrasonic transducer during the rotation time to obtain sampled data. Next, these sampled data are integrated to obtain the velocity potential function matrix. Then, an orthogonal basis matrix is selected, and these velocity potential function data are used to calculate the observation matrix. After that, the wavelet basis and Fourier basis are used as sparse basis to reconstruct the thermal absorption function matrix Q' of the target body. On this basis, the least squares iterative algorithm is used to optimize and reconstruct the conductivity matrix. Finally, the real-time conductivity U corresponding to each monitoring point is extracted from this reconstructed conductivity matrix.

The reconstruction of the conductivity matrix using the algorithm of compressed sensing theory can effectively recover the complete signal from the sparse sampled data when the signal sampling is far below the Nyquist rate, which greatly reduces the amount of monitoring data required and improves the efficiency of data processing. The accuracy and robustness of data processing are enhanced by the use of integral and orthogonal basis matrices. The use of wavelet basis and Fourier basis as sparse basis can better capture the local characteristics and frequency components of the signal, thereby improving the reconstruction quality. The application of the least squares iterative algorithm further optimizes the reconstruction process of the conductivity matrix and ensures the accuracy and reliability of the reconstruction results. The real-time conductivity U obtained by this method can provide accurate data support for the electrical properties analysis of the material.

Specifically, the adjusting the preset rotation radius according to the real-time conductivity and the preset standard conductivity range, or correcting the adjusted preset angle according to the real-time conductivity and the preset standard conductivity range includes:

When the real-time conductivity is greater than the maximum value of the preset standard conductivity range, and the difference between the real-time conductivity and the maximum value of the preset standard conductivity range is greater than the preset standard deviation, the adjusted preset angle is reduced according to the difference, the preset standard deviation and the preset angle correction ratio, wherein D"=D'-a4×(U-Umax), D" is the corrected adjusted preset angle, a4 is the preset angle correction ratio, U is the real-time conductivity, and Umax is the maximum value of the preset standard conductivity range;

When the real-time conductivity is less than the minimum value of the preset standard conductivity range, and the difference between the real-time conductivity and the maximum value of the preset standard conductivity range is greater than the preset standard deviation, the adjusted preset angle is increased according to the difference, the preset standard deviation and the preset angle correction ratio, wherein D”=D’+a4×(Umin-U), and Umin is the minimum value of the preset standard conductivity range;

When the real-time conductivity is greater than the maximum value of the preset standard conductivity range, and the difference between the real-time conductivity and the maximum value of the preset standard conductivity range is less than the preset standard deviation value, the preset rotation radius is reduced according to the real-time conductivity, the maximum value of the preset standard conductivity range and the preset radius adjustment ratio, wherein R'=R-a5×(U-Umax), R' is the adjusted preset rotation radius, R is the preset rotation radius, and a5 is the preset radius adjustment ratio;

When the real-time conductivity is less than the minimum value of the preset standard conductivity range, and the difference between the real-time conductivity and the maximum value of the preset standard conductivity range is less than the preset standard deviation value, the preset rotation radius is increased according to the real-time conductivity, the maximum value of the preset standard conductivity range and the preset radius adjustment ratio, wherein R'=R+a5×(Umin-U).

In the process of adjusting the preset rotation radius or correcting the preset angle, the system first evaluates the relationship between the real-time conductivity U and the preset standard conductivity range (Umin, Umax). If the real-time conductivity U exceeds Umax and the difference between U and Umax is greater than the preset standard deviation, the system uses the preset angle correction ratio a4 to reduce the adjusted preset angle D' according to the difference to narrow the monitoring focus and more accurately locate the high conductivity area. On the contrary, if U is lower than Umin and the difference between U and Umax is greater than the preset standard deviation, the system increases the adjusted preset angle D' to expand the monitoring range and capture the low conductivity area that may be missed. If U exceeds Umax but the difference is less than the preset standard deviation, the system uses the preset radius adjustment ratio a5 to reduce the preset rotation radius R to improve the monitoring accuracy. If U is lower than Umin and the difference is less than the preset standard deviation, the system increases the preset rotation radius R to ensure full coverage of the low conductivity area.

Dynamically adjusting monitoring parameters by comparing real-time conductivity with a preset standard conductivity range provides an adaptive monitoring strategy that can accurately respond to different conductivity conditions. When the real-time conductivity is higher or lower than the preset standard conductivity range, by adjusting the angle or radius, the conductivity anomaly area can be more effectively located and evaluated, thereby achieving more accurate material property analysis.

Please continue to refer to FIG. 4 , which is a schematic diagram of a sector scanning detection system for detecting the conductivity of a supercapacitor in this embodiment;

This embodiment provides a sector scanning detection system for detecting the conductivity of a supercapacitor, comprising:

The data monitoring module includes a preset number of ultrasonic transducers 3, which are used to rotate at a preset angle with a preset rotation radius and a preset rotation angular velocity to monitor the real-time thermoacoustic signal of the target body 2 to be measured in the pulsed magnetic field 1 at each monitoring point;

A signal extraction module, connected to the data monitoring module, for extracting the real-time signal strength and real-time signal stability of the real-time thermoacoustic signal according to a built-in preset extraction algorithm;

An adjustment module, connected to the signal extraction module, adjusting the preset quantity according to the real-time signal strength and the preset standard signal strength;

The adjustment module is also used to adjust the preset rotation angular velocity according to the real-time signal stability and the preset standard signal stability;

The adjustment module is also used to adjust the preset angle according to the maximum value of all real-time signal strengths within the preset rotation time and the preset standard peak range;

A conductivity reconstruction and extraction module, connected to the adjustment module and the data monitoring module respectively, for reconstructing the conductivity matrix of the target body to be measured through the real-time thermoacoustic signals of each monitoring point using a preset algorithm based on the compressed sensing theory, and extracting the real-time conductivity from the conductivity matrix;

A correction module, connected to the conductivity reconstruction and extraction module, for adjusting a preset rotation radius according to the real-time conductivity and a preset standard conductivity range, or correcting the adjusted preset angle;

The output module is connected to the conductivity reconstruction and extraction module and the correction module respectively, and is used to construct and output a conductivity distribution map according to the real-time thermoacoustic signal whose real-time conductivity is within a preset standard conductivity range.

The workflow of the sector scanning detection system starts with the data monitoring module, which uses a preset number of ultrasonic transducers to monitor the real-time thermoacoustic signals of the target body to be measured in the pulsed magnetic field according to the preset rotation radius, speed and angle. The signal extraction module processes the received signal and extracts the signal strength and stability. The adjustment module dynamically adjusts the preset number, preset rotation angular velocity and preset angle of the ultrasonic transducers according to the comparison of the extracted signal parameters with the preset standard signal strength to optimize signal acquisition. The conductivity reconstruction and extraction module uses the compressed sensing theory algorithm to reconstruct the conductivity matrix and extract the real-time conductivity in combination with the monitoring data. The correction module adjusts the rotation radius or correction angle according to the comparison result between the real-time conductivity and the preset range to improve the measurement accuracy. Finally, the output module constructs and outputs the conductivity distribution map to provide intuitive data for analysis and evaluation.

The system can adaptively adjust monitoring parameters to ensure high-quality signal data under different conditions, thereby improving the accuracy and repeatability of measurements. The application of compressed sensing theory greatly reduces the need for data acquisition while maintaining high accuracy of reconstruction results. Dynamic adjustment and correction mechanisms enable the system to quickly respond to real-time monitoring results and optimize measurement strategies.

In this embodiment, the setting of the preset value is generally based on the following factors:

The number of ultrasonic transducers depends on the size and complexity of the monitored target and the required signal coverage.

Typical setup: The number may vary from a few to dozens.

In this embodiment, it is assumed that 5 ultrasonic transducers are provided.

Rotation radius: depends on the size of the monitoring target and the required monitoring depth.

Typical settings: The radius may vary from a few centimeters to several meters.

In this embodiment: assume that it is set to 0.2 meters.

Angular velocity of rotation: affects the temporal resolution of signal acquisition.

Typical settings: Speeds may vary from a few degrees to tens of degrees per second.

In this embodiment: assume that it is set to 10 degrees/second.

Preset angle: affects the distribution density of monitoring points.

Common settings: The angle range may be from 0 to 360 degrees, and the specific angle is determined according to monitoring requirements.

In this embodiment: it is assumed that the entire 360-degree range is used for monitoring.

Preset standard signal strength: used to compare with the real-time signal strength to determine whether the number of ultrasonic transducers needs to be adjusted.

Normal setting: Set according to system sensitivity and expected signal strength.

In this embodiment: assume that it is set to 1000mV.

Preset standard signal stability: used to compare with the real-time signal stability to determine whether the rotation angular velocity needs to be adjusted.

Normal setting: Set according to signal stability requirements.

In this embodiment: assume that it is set to 50mV.

Preset standard peak range: used to compare with the maximum value of real-time signal strength and adjust the preset angle.

Normal setting: set according to the expected fluctuation range of the signal.

In this embodiment: assume that the maximum value is set to 1500mV and the minimum value is set to 500mV.

Preset standard conductivity range: used to compare with real-time conductivity and adjust the rotation radius or angle.

Normal settings: Set according to the expected conductivity characteristics of the material.

In this embodiment: assume that the maximum value is set to 0.01S/m and the minimum value is set to 0.001S/m.

The preset angle correction ratio a4 is an adjustment ratio for calculating the angle, and the preset radius adjustment ratio a5 is an adjustment ratio for calculating the radius.

Normal setting: set according to the system response speed and adjustment accuracy requirements.

In this embodiment: these ratios need to be determined through experiments according to specific applications, and the preset angle correction ratio a4 and the preset radius adjustment ratio a5 are respectively set to 0.1.

The advantages of this configuration in this embodiment are:

Using five ultrasonic transducers can provide adequate signal coverage while avoiding overly complex systems.

The preset rotation radius of 0.2 meters allows comprehensive monitoring of medium-sized supercapacitors.

The rotation angular velocity of 10 degrees/second provides good temporal resolution while avoiding signal blurring that may be caused by excessive rotation.

Setting the preset standard signal strength and the preset standard signal stability within a reasonable range can ensure that the system is sensitive to signal changes while avoiding over-adjustment.

By setting a preset standard peak range, the system can adaptively adjust the monitoring preset angle to focus on areas with abnormal signal strength.

The preset standard conductivity range setting allows the system to identify and adjust conductivity anomalies, improving measurement accuracy.

The settings of the preset angle correction ratio and the preset radius adjustment ratio enable the system to make fine adjustments based on real-time data and optimize the monitoring strategy.

So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims (10)

1. A sector scan detection method for detecting supercapacitor conductivity, comprising:

Placing a target body to be detected in a pulse magnetic field, rotating a preset angle with a preset rotating radius and a preset rotating angular speed by using a preset number of ultrasonic transducers, and monitoring real-time thermoacoustic signals at all monitoring points;

Extracting the real-time signal intensity and the real-time signal stability of the real-time thermo-acoustic signal;

adjusting the preset quantity according to the real-time signal strength and the preset standard signal strength;

the preset rotation angular velocity is adjusted according to the real-time signal stability and the preset standard signal stability;

adjusting a preset angle according to the maximum value of all real-time signal intensities in the preset rotation time and a preset standard peak value range;

Using a preset algorithm based on a compressed sensing theory, reconstructing a conductivity matrix of a target body to be detected through real-time thermo-acoustic signals of all monitoring points, and extracting real-time conductivity from the conductivity matrix;

Adjusting the preset rotation radius according to the real-time conductivity and a preset standard conductivity range, or correcting the adjusted preset angle according to the real-time conductivity and the preset standard conductivity range;

And constructing a conductivity distribution diagram according to the real-time thermo-acoustic signal with the real-time conductivity within the preset standard conductivity range and outputting the conductivity distribution diagram.

2. The sector scanning detection method for detecting supercapacitor conductivity according to claim 1, wherein extracting the real-time signal strength of the real-time thermo-acoustic signal comprises:

And converting the real-time thermo-acoustic signal into a digital signal by using an analog-to-digital converter, and calculating the root mean square of the digital signal in a preset window time period to obtain the real-time signal intensity.

3. The sector scanning detection method for detecting supercapacitor conductivity according to claim 2, wherein extracting the real-time signal stability of the real-time thermo-acoustic signal comprises:

And calculating the standard deviation of the real-time thermo-acoustic signal converted into the digital signal to obtain the real-time signal stability.

4. A sector scanning detection method for detecting supercapacitor conductivity according to claim 3, wherein said adjusting the preset number according to the real-time signal strength and the preset standard signal strength comprises:

When the real-time signal strength is smaller than the preset standard signal strength, the preset number is increased and adjusted according to the real-time signal strength and the preset standard signal strength in a preset number adjusting proportion.

5. The sector scanning detection method for detecting supercapacitor conductivity according to claim 4, wherein said adjusting the preset rotational angular velocity according to the real-time signal stability and the preset standard signal stability includes:

When the real-time signal stability is greater than the preset standard signal stability, the preset rotation angle speed is reduced and adjusted according to the real-time signal stability and the preset standard signal stability by using a preset stability adjustment proportion.

6. The sector scanning detection method for detecting supercapacitor conductivity according to claim 5, wherein adjusting the preset angle according to the maximum value of all real-time signal intensities and the maximum value of the preset standard peak range within the preset rotation time includes:

And when the maximum value of all the real-time signal intensities is larger than the maximum value of the preset standard peak value range, reducing and adjusting the preset angle according to the maximum value of all the real-time signal intensities, the maximum value of the preset standard peak value range and the preset peak value adjusting proportion.

7. The sector scanning detection method for detecting supercapacitor conductivity according to claim 6, wherein adjusting the preset angle according to a maximum value of all real-time signal intensities within a preset rotation time and a minimum value of a preset standard peak range comprises:

And when the maximum value of all the real-time signal intensities is smaller than the minimum value of the preset standard peak value range, increasing and adjusting the preset angle according to the maximum value of all the real-time signal intensities, the minimum value of the preset standard peak value range and the peak value adjusting proportion.

8. The sector scanning detection method for detecting supercapacitor conductivity according to claim 7, wherein reconstructing a conductivity matrix of a target object to be detected from real-time thermo-acoustic signals of each monitoring point using a preset algorithm based on a compressed sensing theory, and extracting real-time conductivity from the conductivity matrix comprises:

Sampling a random vector of a preset sampling number of thermo-acoustic signals of preset monitoring times randomly monitored by an ultrasonic transducer in rotation time to obtain sampling data;

integrating the sampled data to obtain a corresponding velocity potential function matrix;

selecting an orthogonal base matrix, and calculating an observation matrix according to the speed potential function data of random sampling;

Reconstructing a heat absorption function matrix of the target body to be detected by using the wavelet basis and the Fourier basis as sparse basis;

reconstructing a conductivity matrix of the target body to be detected by using a least square iterative algorithm;

And extracting the real-time conductivity corresponding to each monitoring point from the reconstructed conductivity matrix.

9. The sector scanning detection method for detecting supercapacitor conductivity according to claim 8, wherein the adjusting the preset radius of rotation according to the real-time conductivity and the preset standard conductivity range or correcting the adjusted preset angle according to the real-time conductivity and the preset standard conductivity range includes:

when the real-time conductivity is larger than the maximum value of the preset standard conductivity range and the difference between the real-time conductivity and the maximum value of the preset standard conductivity range is larger than the preset standard difference, reducing the adjusted preset angle according to the difference, the preset standard difference and the preset angle correction proportion;

when the real-time conductivity is smaller than the minimum value of the preset standard conductivity range and the difference between the real-time conductivity and the maximum value of the preset standard conductivity range is larger than the preset standard difference, the adjusted preset angle is increased according to the difference, the preset standard difference and the preset angle correction proportion;

When the real-time conductivity is larger than the maximum value of the preset standard conductivity range and the difference between the real-time conductivity and the maximum value of the preset standard conductivity range is smaller than the preset standard difference, reducing the preset rotation radius according to the real-time conductivity, the maximum value of the preset standard conductivity range and the preset radius adjustment proportion;

When the real-time conductivity is smaller than the minimum value of the preset standard conductivity range and the difference between the real-time conductivity and the maximum value of the preset standard conductivity range is smaller than the preset standard difference, the preset rotation radius is increased according to the real-time conductivity, the maximum value of the preset standard conductivity range and the preset radius adjustment proportion.

10. Sector scanning detection system for detecting the conductivity of supercapacitors, based on a sector scanning detection method for detecting the conductivity of supercapacitors according to any one of claims 1-9, characterized in that it comprises:

The data monitoring module comprises a preset number of ultrasonic transducers, is used for rotating at a preset angle with a preset rotation radius and a preset rotation angular velocity, and monitors real-time thermoacoustic signals from a target body to be detected in the pulse magnetic field at each monitoring point;

The signal extraction module is connected with the data monitoring module and used for extracting the real-time signal intensity and the real-time signal stability of the real-time thermo-acoustic signal according to a built-in preset extraction algorithm;

The adjusting module is connected with the signal extracting module and is used for adjusting the preset quantity according to the real-time signal strength and the preset standard signal strength;

The adjusting module is also used for adjusting a preset rotation angular velocity according to the real-time signal stability and the preset standard signal stability;

the adjusting module is also used for adjusting a preset angle according to the maximum value of all real-time signal intensities in the preset rotation time and a preset standard peak value range;

The conductivity reconstruction extraction module is respectively connected with the adjustment module and the data monitoring module and is used for reconstructing a conductivity matrix of the target body to be detected through real-time thermo-acoustic signals of all monitoring points by using a preset algorithm based on a compressed sensing theory and extracting real-time conductivity from the conductivity matrix;

The correction module is connected with the conductivity reconstruction extraction module and is used for adjusting the preset rotation radius according to the real-time conductivity and the preset standard conductivity range or correcting the adjusted preset angle;

The output module is respectively connected with the conductivity reconstruction extraction module and the correction module and is used for constructing and outputting a conductivity distribution diagram according to the real-time thermoacoustic signal of which the real-time conductivity is in the preset standard conductivity range.