Method and device for detecting strength of filling body based on sound wave spectrum analysis

Abstract

The invention provides a method and a device for detecting the strength of a filling body based on sound wave spectrum analysis, relates to the technical field of mine filling materials, and aims to evaluate the strength by analyzing complete spectrum characteristics of sound waves after the sound waves pass through the filling body. Specifically, when sound waves are propagated in a filling body, parameters such as consolidation degree, compactness and internal defects of the filling body can generate unique influence on frequency, amplitude and phase of sound wave signals, so that the frequency spectrum of the sound wave signals is correspondingly changed. According to the method, the acoustic signals are collected and subjected to spectral analysis such as Fourier transform, a plurality of characteristic parameters including main frequency offset, harmonic energy change and spectrum peak amplitude can be extracted, and a quantitative model between the multiple parameters and the strength of the filling body is established. According to the method, the internal structure and the mechanical property of the filling body can be reflected more comprehensively and accurately, and a new technical scheme which is high in precision, lossless and suitable for on-site rapid detection is provided for quality control of the mine filling body.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of mine filling materials, and in particular, relates to a filling body strength detection method and device based on sound wave spectrum analysis. BACKGROUND

[0002] In the field of mine filling, ensuring the strength of the filling body is crucial for underground safety and mining efficiency. Currently, the mainstream detection methods mainly fall into two categories: destructive and non-destructive. Although destructive sampling is generally considered the most reliable, its time-consuming and labor-intensive nature makes it unsuitable for rapid assessment of early filling body strength, thereby restricting the progress of subsequent mining operations. At the same time, the destructive nature of the sampling process to the filling body itself, as well as the uncertainty of sample representativeness, also limits its application range. To make up for these shortcomings, various non-destructive detection techniques have been developed in the industry, among which ultrasonic and rebound methods are the most common. However, when applied to heterogeneous mine filling bodies, the precision and reliability of these techniques face serious challenges. For example, ultrasonic methods based on sound velocity are susceptible to signal attenuation and distortion due to the complex voids and segregation within the filling body, making a single sound velocity index unable to reliably reflect the strength. The rebound method can only assess the local strength of the filling body surface and cannot represent the overall mechanical properties of the internal filling body, and is easily affected by the surface flatness.

[0003] Reference documents: [1] Yu B, Tian L, Cao J, et al. A filling body strength in-situ testing device based on magnetic impact [P]. Inner Mongolia Autonomous Region: CN202421343810.2, 2025-08-19. [2] Donglongbin, Wang S, Yi H, et al. A filling body damage detection method based on ultrasonic wave velocity [P]. Liaoning Province: CN201910370376.4, 2019-07-30. SUMMARY According to the technical problem of the single sound velocity index being unable to stably and reliably reflect the strength due to the complex voids and segregation phenomena in the filling body, a filling body strength detection method and device based on sound wave spectrum analysis are provided.The application provides a novel filling body strength detection method and device based on sound wave spectrum analysis.The strength is evaluated by analyzing the complete spectrum characteristics of the sound wave after passing through the filling body.Specifically, when the sound wave propagates in the filling body, the consolidation degree, density and internal defects of the filling body will have a unique influence on the frequency, amplitude and phase of the sound wave signal, resulting in corresponding changes in the spectrum of the sound wave signal.The application can extract multiple characteristic parameters including the main frequency shift, harmonic energy change and spectrum peak amplitude by collecting and performing Fourier transform and other spectrum analysis on the sound wave signal, and establish a quantitative model between the multiple parameters and the strength of the filling body.This method can more comprehensively and accurately reflect the internal structure and mechanical properties of the filling body, and provide a new technical solution for the quality control of the mine filling body, which is high-precision, non-destructive and suitable for on-site rapid detection.

[0004] The technical means adopted by the application are as follows: A filling body strength detection method based on sound wave spectrum analysis, characterized in that it comprises the following steps: Step 1, starting the detection device and initializing the device; Step 2, selecting the mode of the detection device and synchronously setting the working parameters; Step 3, setting the probe on the surface of the filling body to be detected, and simultaneously emitting a preset sound wave signal into the filling body; Step 4, receiving the sound wave signal and converting the received sound wave signal into a digital signal; Step 5, performing fast Fourier transform and spectrum analysis on the digital signal to obtain multiple key characteristic parameters closely related to the strength of the filling body; Step 6, calculating and outputting the strength value of the filling body to be detected according to the key characteristic parameters.

[0005] Further, in step 1, the device initialization includes cleaning the probe.

[0006] Further, in step 3, the sound wave emission probe and the sound wave receiving probe at the front end of the detection device body are tightly attached to the surface of the filling body to be detected through coupling gel, so that there is no gap between the sound wave emission probe and the sound wave receiving probe and the surface of the filling body.

[0007] Further, the sound wave emission probe and the sound wave receiving probe are arranged on the area of the filling body surface which is flat, has no cracks or loose objects.

[0008] Furthermore, in step 5, several key characteristic parameters closely related to the strength of the filling material are obtained, including: peak amplitude of the spectrum. frequency offset and changes in harmonic energy; Let the time-domain function of the original transmitted signal be... The time-domain function of the received signal is The corresponding spectrum obtained by fast Fourier transform is: ; ; By the spectrum of the received signal The method for finding the maximum amplitude in the spectrum is used to find the peak amplitude of the spectrum. ; ; in, Indicates the spectrum at frequency The amplitude at that point; By finding the transmission spectrum respectively and received spectrum Find the frequency corresponding to the point of maximum amplitude, and then calculate the difference between the two: ; in, Indicates the main frequency of the received signal; Indicates the main frequency of the transmitted signal; The harmonic energy variation is used to assess the integrity and strength of the filling material by analyzing the ratio of harmonic energy to fundamental energy.

[0009] Furthermore, in step 6, the strength value of the filling material to be tested is calculated and output by establishing a multiple regression strength assessment calculation model; the compressive strength of the filling material is regarded as a function of multiple acoustic spectrum characteristic parameters, and a multiple linear regression model is constructed to describe the relationship between compressive strength and acoustic spectrum characteristic parameters: ; in, This represents the predicted strength value of the filling material to be tested; All of these represent key feature parameters extracted from the acoustic spectrum; This represents the constant term, i.e., the intercept; , This represents the regression coefficient corresponding to the key feature parameter. The regression coefficient is calibrated and trained using experimental data.

[0010] Furthermore, the acquisition of the regression coefficients includes the following steps: Sample preparation and testing: Filling blocks with different proportions and ages were prepared using filling materials from the mine under test. The actual compressive strength of each block was determined using a compression testing machine. ; Acoustic data acquisition: Before pressure destruction of the test blocks, acoustic detection is performed on each test block, and the complete acoustic reception signal is recorded; Feature parameter extraction: Perform spectral analysis on the acoustic signal of each test block to calculate the corresponding combination of key feature parameters. ; Regression analysis: Collects sample data to form a regression analysis that includes actual compressive strength values. Combination of key feature parameters The dataset was used; multiple regression analysis was performed on the data using the least squares method to obtain predicted values. Compared with actual strength value The optimal regression coefficient that minimizes the total error between the two.

[0011] Furthermore, the strength value of the filling material calculated in step 6 is displayed on the screen and stored in the built-in memory.

[0012] The present invention also includes a handheld device for testing the strength of filling materials based on acoustic spectrum analysis, comprising: The device consists of a main body, an acoustic wave transmitting probe, an acoustic wave receiving probe, a display screen, operation buttons, a signal processing module, a data analysis module, and a power interface. The front end of the main body of the device is provided with the acoustic wave emitting probe and the acoustic wave receiving probe; the signal processing module and the data analysis module are located inside the main body of the device. The acoustic wave transmitting probe and the acoustic wave receiving probe are electrically connected to the signal processing module and the data analysis module via cables; When the user initiates the test via the operation button, the acoustic wave emitting probe emits an acoustic wave signal towards the filling material to be tested. The acoustic wave signal passes through the filling material and is received by the acoustic wave receiving probe after passing through the filling material. The acoustic wave signal after passing through the filling material is then transmitted to the signal processing module. The signal processing module processes the acoustic wave signal after passing through the filling material to obtain a processed digital signal. The data analysis module extracts key feature parameters from the processed digital signal. The key feature parameters are input into the strength evaluation model to calculate the strength value of the filling material, and the strength value of the filling material is displayed on the display screen.

[0013] Furthermore, the detection device is charged by connecting to a power source through the power interface.

[0014] Compared with the prior art, the present invention has the following advantages: High precision: Traditional ultrasonic methods rely on only the single parameter of sound velocity, while this invention uses multiple parameters of sound wave spectrum characteristics for comprehensive evaluation, which can more comprehensively and accurately reflect the internal structure and mechanical properties of the filling body, effectively overcome the interference caused by heterogeneity, and significantly improve the detection accuracy and reliability.

[0015] Speed: The device features an integrated, portable design that enables rapid on-site non-destructive testing and real-time acquisition of early strength data of the backfill material. This provides a basis for quick decision-making in subsequent mining operations and significantly improves production efficiency.

[0016] Non-destructive: This invention uses a non-destructive testing method that does not cause any damage to the filling material. It allows for multiple monitoring of the same filling material, dynamically monitoring its curing process and facilitating more precise filling quality management. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Fig. 1 This is a schematic diagram of the structure of the rapid detection device for filling strength based on acoustic spectrum analysis of the present invention.

[0019] Fig. 2 This is a schematic diagram of the overall process of the present invention.

[0020] In the diagram: 1. Main body of the device; 2. Acoustic wave transmitting probe; 3. Acoustic wave receiving probe; 4. Display screen; 5. Operation buttons; 6. Data analysis module; 7. Signal processing module; 8. Power interface; 9. Acoustic wave signal. Detailed Implementation

[0021] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0022] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0023] like Figs. 1-2 As shown, the present invention provides a method for detecting the strength of filling materials based on acoustic spectrum analysis, characterized by comprising the following steps: Step 1: Start the detection device and initialize it; the device initialization includes cleaning the probes. First, check the appearance of the main body 1 of the detection device to confirm that there is no obvious damage. Start cleaning the acoustic wave emitting probe 2 and the acoustic wave receiving probe 3. Press and hold the power button (or power-on button) in the operation button for about 3 seconds until the display screen 4 lights up and the device enters the power-on self-test program.

[0024] 3. After the self-test is completed, the display screen (4) will show the initial operation interface, including information such as battery level, current mode, date and time. Confirm that the device has sufficient power. If the power is low, you need to connect the charger through the power interface (8) to charge it.

[0025] Step 2: Select the mode of the detection device and simultaneously set the operating parameters. On the initial operation interface, select "Detection Mode" or "Setting Mode" using the navigation keys in operation button 5. Here, select "Detection Mode". After entering detection mode, if necessary, you can access the "Parameter Setting" menu through operation button 5 to adjust advanced parameters such as acoustic emission power, sampling frequency, and signal processing algorithm according to the type of filling material to be tested and the estimated strength range. Generally, the default parameters can be used for preliminary detection. After confirming that all parameter settings are correct, return to the main interface of the detection mode and wait for measurement.

[0026] Step 3: Place the probe on the surface of the filler to be tested, and simultaneously emit a preset acoustic signal into the filler. In Step 3, the acoustic emitting probe and acoustic receiving probe at the front end of the main body of the detection device are tightly attached to the surface of the filler to be tested using coupling gel, ensuring that there are no gaps between the acoustic emitting probe and the acoustic receiving probe and the surface of the filler. Both the acoustic emitting probe and the acoustic receiving probe are placed in a flat area on the surface of the filler to be tested, free of cracks or loose materials.

[0027] Step 4: Receive the sound wave signal and convert the received sound wave signal into a digital signal; Step 5: Perform Fast Fourier Transform and Spectral Analysis on the digital signal to obtain multiple key characteristic parameters closely related to the strength of the filling material.

[0028] Key characteristic parameters refer to quantitative indicators extracted from the spectrum of the received acoustic signal that can sensitively reflect changes in the internal physical and mechanical properties of the filling material (such as density, compactness, elastic modulus, and microcrack distribution), such as dominant frequency shift, harmonic energy variation, and peak amplitude of the spectrum. These physical and mechanical properties are directly related to the macroscopic strength of the filling material, and therefore these parameters are also indirectly closely related to strength, indicating the strength value of the filling material.

[0029] In a preferred embodiment, in this application, step 5 involves obtaining several key characteristic parameters closely related to the strength of the filling material, including: peak amplitude of the spectrum. frequency offset And changes in harmonic energy.

[0030] Let the time-domain function of the original transmitted signal be... The time-domain function of the received signal is The corresponding spectrum obtained by fast Fourier transform is: ; ; By the spectrum of the received signal The method for finding the maximum amplitude in the spectrum is used to find the peak amplitude of the spectrum. The peak amplitude of the spectrum This reflects the degree of attenuation of sound wave energy after passing through the filling material. The denser and more complete the filling material, the fewer defects, the smaller the energy attenuation, and the larger the amplitude of the received signal. Higher strength filling materials are usually denser, so this value is positively correlated with strength.

[0031] ; in, Indicates the spectrum at frequency The amplitude at that point; frequency offset This refers to the phenomenon where, as sound waves propagate through a medium, the nonlinear elastic effects of the material generate harmonic components, causing a shift in the peak frequency of the received signal relative to the transmitted signal. The degree of this shift is related to the nonlinear elastic parameters and microstructural damage state of the material, and the degradation of the material's mechanical properties can be indirectly assessed through nonlinear acoustic parameters. This can be achieved by finding the transmitted spectrum... and received spectrum Find the frequency corresponding to the point of maximum amplitude, and then calculate the difference between the two: ; in, Indicates the main frequency of the received signal; Indicates the main frequency of the transmitted signal; The harmonic energy variation is used to assess the integrity and strength of the filling material by analyzing the ratio of harmonic energy to fundamental energy. Harmonic energy variation refers to the phenomenon where higher-order harmonics are generated when sound waves propagate within the filling material due to nonlinear interfaces such as microcracks and pores. The more internal defects and the more non-uniform the structure of the filling material, the lower the compressive strength, the more significant the nonlinear effect, and the stronger the energy of the harmonic components.

[0032] Taking the second harmonic energy ratio as an example, ; in, Indicates the main frequency of the received signal. This represents the center frequency of the second harmonic. This represents a small frequency integration bandwidth set around the center frequency for the purpose of calculating energy. It is proportional to the signal energy. The higher the value, the more internal defects there are, and the lower the strength.

[0033] Step 6: Calculate and output the strength value of the filling material to be tested based on the key characteristic parameters. In Step 6, the strength value of the filling material to be tested is calculated and output by establishing a multiple regression strength assessment calculation model; the compressive strength of the filling material is regarded as a function of multiple acoustic spectrum characteristic parameters, and a multiple linear regression model is constructed to describe the relationship between compressive strength and acoustic spectrum characteristic parameters: ; in, This represents the predicted strength value of the filling material to be tested; All of these represent key feature parameters extracted from the acoustic spectrum; This represents the constant term, i.e., the intercept; , These represent the regression coefficients corresponding to the key feature parameters. The regression coefficients are calibrated and trained using experimental data. Obtaining the regression coefficients includes the following steps: Sample preparation and testing: Filling blocks with different proportions and ages were prepared using filling materials from the mine under test. The actual compressive strength of each block was determined using a compression testing machine. ; Acoustic data acquisition: Before pressure destruction of the test blocks, acoustic detection is performed on each test block, and the complete acoustic reception signal is recorded; Feature parameter extraction: Perform spectral analysis on the acoustic signal of each test block to calculate the corresponding combination of key feature parameters. ; Regression analysis: Collects sample data to form a regression analysis that includes actual compressive strength values. Combination of key feature parameters The dataset was used; multiple regression analysis was performed on the data using the least squares method to obtain predicted values. Compared with actual strength value The optimal regression coefficient that minimizes the total error between the two.

[0034] Furthermore, the strength value of the filling material calculated in step 6 is displayed on the screen and stored in the built-in memory.

[0035] As a preferred embodiment, this application also includes a handheld device for detecting the strength of filling materials based on acoustic spectrum analysis, comprising: The device consists of: 1. main body of the device; 2. acoustic wave transmitting probe; 3. acoustic wave receiving probe; 4. display screen; 5. operation buttons; 6. signal processing module; 7. data analysis module; and 8. power interface. The front end of the main body 1 of the device is provided with the acoustic wave emitting probe 2 and the acoustic wave receiving probe 3; the signal processing module 6 and the data analysis module 7 are disposed inside the main body 1 of the device. The acoustic wave transmitting probe 2 and the acoustic wave receiving probe 3 are electrically connected to the signal processing module 6 and the data analysis module 7 via cables. When the user initiates the test via the operation button 5, the acoustic wave emitting probe 2 emits an acoustic wave signal towards the filling material to be tested. The acoustic wave signal passes through the filling material and is received by the acoustic wave receiving probe 3. The acoustic wave signal after passing through the filling material is then transmitted to the signal processing module 6. The signal processing module 6 processes the acoustic wave signal after passing through the filling material to obtain a processed digital signal. The data analysis module 7 extracts key feature parameters from the processed digital signal. The key feature parameters are input into the strength evaluation model to calculate the strength value of the filling material, and the strength value of the filling material is displayed on the display screen 4.

[0036] Furthermore, the detection device is charged by connecting to a power source through the power interface 8.

[0037] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments. In the above embodiments of the present invention, the descriptions of each embodiment have their own emphasis; parts not described in detail in a certain embodiment can be referred to in the relevant descriptions of other embodiments. It should be understood that the disclosed technical content in the several embodiments provided in this application can be implemented in other ways.

[0038] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for detecting the strength of filling materials based on acoustic spectrum analysis, characterized in that, Includes the following steps: Step 1: Start the detection device and initialize the device; Step 2: Select the mode of the detection device and set the operating parameters simultaneously; Step 3: Place the probe on the surface of the filling material to be tested, and simultaneously emit a preset acoustic signal into the filling material. Step 4: Receive the sound wave signal and convert the received sound wave signal into a digital signal; Step 5: Perform Fast Fourier Transform and Spectrum Analysis on the digital signal to obtain multiple key characteristic parameters closely related to the strength of the filling material; Step 6: Calculate and output the strength value of the filling material to be tested based on the key characteristic parameters.

2. The method for detecting the strength of filling materials based on acoustic spectrum analysis according to claim 1, characterized in that, In step 1, the device initialization includes cleaning the probe.

3. The method for detecting the strength of filling materials based on acoustic spectrum analysis according to claim 1, characterized in that, In step 3, the acoustic wave emitting probe and acoustic wave receiving probe at the front end of the main body of the detection device are tightly attached to the surface of the filling material to be tested using coupling gel, ensuring that there are no gaps between the acoustic wave emitting probe and the acoustic wave receiving probe and the surface of the filling material.

4. The method for detecting the strength of filling materials based on acoustic spectrum analysis according to claim 3, characterized in that, Both the acoustic wave emitting probe and the acoustic wave receiving probe are placed in a flat area on the surface of the filler to be tested, free of cracks or loose material.

5. The method for detecting the strength of filling materials based on acoustic spectrum analysis according to claim 1, characterized in that, In step 5, several key characteristic parameters closely related to the strength of the filling material are obtained, including: peak amplitude of the spectrum. frequency offset and changes in harmonic energy; Let the time-domain function of the original transmitted signal be... The time-domain function of the received signal is The corresponding spectrum obtained by fast Fourier transform is: ； ； By the spectrum of the received signal The method for finding the maximum amplitude in the spectrum is used to find the peak amplitude of the spectrum. ; ； in, Indicates the spectrum at frequency The amplitude at that point; By finding the transmission spectrum respectively and received spectrum Find the frequency corresponding to the point of maximum amplitude, and then calculate the difference between the two: ； in, Indicates the main frequency of the received signal; Indicates the main frequency of the transmitted signal; The harmonic energy variation is used to assess the integrity and strength of the filling material by analyzing the ratio of harmonic energy to fundamental energy.

6. The method for detecting the strength of filling materials based on acoustic spectrum analysis according to claim 1, characterized in that, In step 6, the strength value of the filling material to be tested is calculated and output by establishing a multiple regression strength assessment calculation model; the compressive strength of the filling material is regarded as a function of multiple acoustic spectrum characteristic parameters, and a multiple linear regression model is constructed to describe the relationship between compressive strength and acoustic spectrum characteristic parameters: ； in, This represents the predicted strength value of the filling material to be tested; All of these represent key feature parameters extracted from the acoustic spectrum; This represents the constant term, i.e., the intercept; , This represents the regression coefficient corresponding to the key feature parameter. The regression coefficient is calibrated and trained using experimental data.

7. The method for detecting the strength of filling materials based on acoustic spectrum analysis according to claim 6, characterized in that, The regression coefficients are obtained by the following steps: Sample preparation and testing: Filling blocks with different proportions and ages were prepared using filling materials from the mine under test. The actual compressive strength of each block was determined using a compression testing machine. ; Acoustic data acquisition: Before pressure destruction of the test blocks, acoustic detection is performed on each test block, and the complete acoustic reception signal is recorded; Feature parameter extraction: Perform spectral analysis on the acoustic signal of each test block to calculate the corresponding combination of key feature parameters. ; Regression analysis: Collects sample data to form a regression analysis that includes actual compressive strength values. Combination of key feature parameters The dataset was used; multiple regression analysis was performed on the data using the least squares method to obtain predicted values. Compared with actual strength value The optimal regression coefficient that minimizes the total error between the two.

8. The method for detecting the strength of filling materials based on acoustic spectrum analysis according to claim 1, characterized in that, The strength value of the filler to be tested calculated in step 6 is displayed on the screen and stored in the built-in memory.

9. A handheld device for testing the strength of filling materials based on acoustic spectrum analysis, wherein the device is used in accordance with the method described in any one of claims 1-8, characterized in that, include: The device consists of a main body (1), an acoustic wave transmitting probe (2), an acoustic wave receiving probe (3), a display screen (4), operation buttons (5), a signal processing module (6), a data analysis module (7), and a power interface (8). The front end of the main body (1) of the device is provided with the acoustic wave transmitting probe (2) and the acoustic wave receiving probe (3); the signal processing module (6) and the data analysis module (7) are disposed inside the main body (1) of the device; The acoustic wave transmitting probe (2) and the acoustic wave receiving probe (3) are electrically connected to the signal processing module (6) and the data analysis module (7) via cables; When the user starts the test by pressing the operation button (5), the sound wave emitting probe (2) emits a sound wave signal to the filling body to be tested. The sound wave signal passes through the filling body and is received by the sound wave receiving probe (3). The sound wave signal after passing through the filling body is transmitted to the signal processing module (6). The signal processing module (6) processes the sound wave signal after passing through the filling body to obtain a processed digital signal. The data analysis module (7) extracts the key feature parameters from the processed digital signal. The key feature parameters are input into the strength evaluation model to calculate the strength value of the filling body. The strength value of the filling body is then displayed on the display screen (4).

10. The infill strength testing device based on acoustic spectrum analysis according to claim 9, characterized in that, The detection device is charged by connecting to a power source through the power interface (8).

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