Detection method, device, medium and structure

Abstract

The invention provides a detection method and device, a medium and a structure. The detection method is used for detecting the air tightness of a hydrogen fuel cell, and comprises the following steps: keeping a to-be-detected cell static, and collecting three-dimensional coordinates of all points on the surface of the to-be-detected cell to establish a three-dimensional model of the to-be-detected cell; introducing detection gas into the to-be-detected battery, and after the air pressure in the to-be-detected battery reaches a preset air pressure value, collecting sound information at each point on the surface of the to-be-detected battery to obtain a sound spectrum characteristic value at each point on the surface of the to-be-detected battery; mapping the sound spectrum characteristic value to a three-dimensional model, and determining a leakage point on the surface of the battery to be detected according to the size of the sound spectrum characteristic value; wherein the sound spectrum characteristic value comprises the amplitude and the frequency of the sound. According to the technical scheme provided by the invention, the technical problem of relatively low airtightness test efficiency of the hydrogen fuel cell in the prior art can be solved.

Description

Technical Field

[0001] The present invention relates to the technical field of fuel cells, and in particular, to a detection method, device, medium and structure. Background Technique

[0002] At present, a hydrogen fuel cell is assembled by stacking components such as end plates, bipolar plates, and membrane electrodes, and energy conversion is achieved by the flow of air, hydrogen, and cooling water in the cavities of the components. Sealing materials must be used between the cavities to ensure the sealing of each medium cavity and the reasonable distribution of gas and water. Therefore, after the hydrogen fuel cell is assembled, an airtightness test must be carried out to check whether the material tightness, assembly consistency, pressure uniformity, etc. meet the requirements. If the airtightness test is unqualified, the work of leak detection and location needs to be carried out.

[0003] However, at present, the airtightness test of a hydrogen fuel cell stack mainly adopts the method of pressure-holding leak detection, and the method of spraying leak detection liquid at each position is used to find the leak point. This method has low positioning efficiency, incomplete search, and there are also false detection and missed detection situations, resulting in a waste of a large amount of production costs. The use of lye also has the problem of polluting the fuel cell stack and even causing insulation failure. In addition, there is also a method of realizing leak point location by disassembling and assembling small stacks from large stacks. This method requires repeated disassembly and assembly of the stack, which not only cannot meet the requirements of mass production, but also cannot ensure the changes in sealing problems during the disassembly and assembly process, and cannot realize the function of rapid positioning of seal failure, resulting in low efficiency of the airtightness test. Summary of the Invention

[0004] The main object of the present invention is to provide a detection method, device, medium and structure to solve the technical problem of low airtightness test efficiency of hydrogen fuel cells in the prior art.

[0005] To achieve the above object, according to one aspect of the present invention, a detection method is provided for detecting the airtightness of a hydrogen fuel cell. The detection method includes:

[0006] Keep the battery to be detected stationary, and collect the three-dimensional coordinates of each point on the surface of the battery to be detected to establish a three-dimensional model of the battery to be detected;

[0007] Introduce a detection gas into the battery to be detected. After the air pressure in the battery to be detected reaches a preset air pressure value, collect the sound information at each point on the surface of the battery to be detected to obtain the spectrogram characteristic values at each point on the surface of the battery to be detected;

[0008] Map the spectrogram characteristic values to the three-dimensional model, and determine the leakage points on the surface of the battery to be detected according to the magnitudes of the spectrogram characteristic values;

[0009] Wherein, the spectrogram characteristic values include the amplitude and frequency of the sound.

[0010] Further, collect the sound information at each point on the surface of the battery to be detected to obtain the spectral characteristic values at each point on the surface of the battery to be detected, including:

[0011] Collect the sound information at each point on the surface of the battery to be detected, and perform digital signal processing on the sound information at each point to obtain a sound signal;

[0012] Preprocess the sound signal to obtain a sound signal to be analyzed; wherein, the preprocessing includes at least one of noise reduction processing and filtering processing;

[0013] Obtain the amplitude and frequency of the sound signal to be analyzed at each point to obtain the spectral characteristic values at each point on the surface of the battery to be detected.

[0014] Further, determine the leakage points on the surface of the battery to be detected according to the magnitudes of the spectral characteristic values, including:

[0015] Obtain the spectrum of the sound signal to be analyzed at each point, and determine the sound signal to be analyzed within the leakage frequency range according to the spectrum;

[0016] Obtain the maximum amplitude of the sound signal to be analyzed within the leakage frequency range;

[0017] Compare the amplitude of the sound signal to be analyzed at each point with the maximum amplitude; when the amplitude of the sound signal to be analyzed at each point is greater than or equal to the maximum amplitude, the corresponding point is the leakage point.

[0018] Further, before keeping the battery to be detected stationary, the detection method further includes:

[0019] Introduce a detection gas into the simulated battery. After the air pressure in the simulated battery reaches a preset pressure value, collect the sound information at each point on the surface of the simulated battery, and determine the leakage frequency range according to the frequency of the sound information at the leakage point of the simulated battery; wherein, the simulated battery is a battery with a leakage point.

[0020] Further, map the spectral characteristic values to a three-dimensional model, including: establishing a one-to-one correspondence between the magnitude of the spectral characteristic values and the magnitude of the color gradient values, and mapping the color gradient values corresponding to the spectral characteristic values at each point on the surface of the battery to be detected to the surface of the three-dimensional model; wherein, the color gradient values include at least any one of the lightness value, saturation value, and hue value of the color; and / or,

[0021] Before keeping the battery to be detected stationary, the detection method further includes: placing the battery to be detected at a preset detection position; and / or,

[0022] Keep the battery to be detected stationary, including: obtaining the ambient noise of the environment where the battery to be detected is located; when the ambient noise is less than or equal to a preset noise value, keeping the battery to be detected stationary; when the ambient noise is greater than the preset noise value, obtaining the ambient noise again.

[0023] Further, collecting the three-dimensional coordinates of each point on the surface of the battery to be detected, including: obtaining the external shape of the battery to be detected; determining the collection order and collection positions of each point on the surface of the battery to be detected according to the external shape of the battery to be detected, so as to obtain a model collection path; collecting the three-dimensional coordinates of each point on the surface of the battery to be detected according to the model collection path; and / or,

[0024] Collecting the sound signals at each point on the surface of the battery to be detected, including: obtaining the external shape of the battery to be detected; determining the collection order and collection positions of each point on the surface of the battery to be detected according to the external shape of the battery to be detected, so as to obtain a sound collection path; collecting the sound signals at each point on the surface of the battery to be detected according to the sound collection path.

[0025] Further, the detection method further includes:

[0026] Obtaining the process parameters during the assembly process of the battery to be detected, and mapping the process parameters to a three-dimensional model according to the acquisition position on the battery to be detected corresponding to the process parameters;

[0027] Comparing the process parameters corresponding to the points on the three-dimensional model where the leakage points are located with preset standard parameters, and when the corresponding process parameters do not conform to the preset standard parameters, recording the corresponding process parameters as problem parameters;

[0028] Wherein, the process parameters at least include any one or more of the pressure distribution values of each component of the hydrogen fuel cell, the airtightness distribution value of the single plate of the hydrogen fuel cell plate, and the compression deformation distribution value of the sealing material of the hydrogen fuel cell.

[0029] According to another aspect of the present invention, there is provided a detection device for performing the above-provided detection method, and the detection device includes:

[0030] A first acquisition unit for keeping the battery to be detected stationary and collecting the three-dimensional coordinates of each point on the surface of the battery to be detected to establish a three-dimensional model of the battery to be detected;

[0031] A second acquisition unit for introducing a detection gas into the battery to be detected that is kept stationary by the first acquisition unit, and after the air pressure in the battery to be detected reaches a preset air pressure value, collecting the sound information at each point on the surface of the battery to be detected to obtain the sound spectrum characteristic values at each point on the surface of the battery to be detected;

[0032] The detection unit is configured to map the acoustic spectrum eigenvalue to a three-dimensional model and determine leakage points on the surface of the battery to be detected according to the magnitude of the acoustic spectrum eigenvalue.

[0033] According to another aspect of the present invention, a non-volatile storage medium is provided. The non-volatile storage medium includes a stored program. When the program runs, it controls the device where the non-volatile storage medium is located to execute the above-provided detection method.

[0034] According to still another aspect of the present invention, a detection structure is provided, which is applicable to the above-provided detection method. The detection structure includes:

[0035] A detection platform having a bearing surface for bearing the battery to be detected;

[0036] A gas supply assembly, the inlet end of which is used to communicate with a test gas source, and the outlet end of which is used to communicate with the inside of the battery to be detected;

[0037] A visual detection assembly is arranged on the detection platform, and the detection end of the visual detection assembly is movably arranged to collect the three-dimensional coordinates of each point on the surface of the battery to be detected;

[0038] A sound detection assembly is arranged on the detection platform, and the detection end of the sound detection assembly is movably arranged to collect the sound signals at each point on the surface of the battery to be detected.

[0039] Further, the detection structure further includes:

[0040] A moving assembly is arranged on the detection platform, and the moving part of the moving assembly is movably arranged. The visual detection assembly and the sound detection assembly can be selectively connected to the moving part; and / or,

[0041] A fixing assembly is arranged on the bearing surface, and the outer edge of the fixing part of the fixing assembly protrudes from the bearing surface. The fixing part is used to be inserted into the opening of the battery to be detected and is arranged to be adapted to the opening of the battery to be detected; wherein, the opening of the battery to be detected includes the water outlet of the fuel cell stack and the gas outlet of the fuel cell stack.

[0042] Applying the technical solution of the present invention to perform airtightness detection by collecting sound information is a non-contact detection method. During the detection process, there is no need to disassemble and assemble the stack, so the original stack state is not damaged, and no physical damage will be caused to the hydrogen fuel cell. Moreover, by mapping the sound spectrum characteristic values to a three-dimensional model and combining the amplitude and frequency information of the sound, the leakage points on the surface of the hydrogen fuel cell can be accurately located, improving the detection speed and accuracy. In this way, by marking points on the three-dimensional model to determine the leakage position of the stack, the detection is fast and accurate. After establishing a fault database later, the cause of the fault can also be accurately determined. In addition, this detection method has high applicability to the battery to be detected and can be applied to hydrogen fuel cells of different models and sizes. Only by adjusting the parameters of three-dimensional coordinate acquisition and sound spectrum analysis according to the battery type, various detection requirements can be flexibly met. Therefore, through the technical solution of the present invention, the technical problem of low airtightness test efficiency of hydrogen fuel cells in the prior art can be solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The accompanying drawings forming a part of this application are used to provide a further understanding of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation to the present invention. In the drawings:

[0044] Figure 1 The schematic diagram of the steps of the detection method provided in Embodiment 1 of the present invention is shown;

[0045] Figure 2 The logical schematic diagram of the detection method provided in Embodiment 1 of the present invention is shown;

[0046] Figure 3 The structural schematic diagram of the detection structure provided in Embodiment 4 of the present invention is shown.

[0047] Among them, the above-mentioned accompanying drawings include the following reference numerals:

[0048] 10, detection platform; 11, bearing surface;

[0049] 20, gas supply component; 21, intake end;

[0050] 30, visual detection component;

[0051] 40, sound detection component;

[0052] 50, moving component; 51, moving part;

[0053] 60, fixing component; 61, fixing part;

[0054] 70, battery to be detected. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0055] It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the drawings and in conjunction with the embodiments.

[0056] As Figure 1 and Figure 2 shown, Embodiment 1 of the present invention provides a detection method for detecting the airtightness of a hydrogen fuel cell. The detection method includes: keeping the battery 70 to be detected stationary, and collecting the three-dimensional coordinates of each point on the surface of the battery 70 to be detected to establish a three-dimensional model of the battery 70 to be detected; introducing a detection gas into the battery 70 to be detected, and after the air pressure in the battery 70 to be detected reaches a preset air pressure value, collecting the sound information at each point on the surface of the battery 70 to be detected to obtain the spectral characteristic values at each point on the surface of the battery 70 to be detected; mapping the spectral characteristic values to the three-dimensional model, and determining the leakage points on the surface of the battery 70 to be detected according to the magnitudes of the spectral characteristic values; wherein, the spectral characteristic values include the amplitude and frequency of the sound.

[0057] By using the detection method provided in Embodiment 1 of the present invention, airtightness detection is carried out by collecting sound information, which is a non-contact detection method. The detection process does not require disassembly and assembly of the stack, so the original stack state is not damaged and the hydrogen fuel cell will not be physically damaged. And by mapping the spectral characteristic values to the three-dimensional model and combining the amplitude and frequency information of the sound, the leakage points on the surface of the hydrogen fuel cell can be accurately located, improving the detection speed and accuracy. In this way, by marking points on the three-dimensional model to judge the leakage position of the stack, the detection is fast and accurate. After establishing a fault database later, the fault cause can also be accurately judged. In addition, this detection method has high applicability to the battery 70 to be detected and can be applied to hydrogen fuel cells of different models and sizes. Only by adjusting the parameters of three-dimensional coordinate collection and spectral analysis according to the battery type, various detection requirements can be flexibly met. Therefore, through the detection method provided in this embodiment, the technical problem of low airtightness test efficiency of hydrogen fuel cells in the prior art can be solved.

[0058] Specifically, the method for collecting the three-dimensional coordinates of each point on the surface of the battery 70 to be detected to establish a three-dimensional model of the battery 70 to be detected includes: using Autodesk ReCaph (3D scanning software) to generate a three-dimensional model according to the point cloud data or image data of the surface of the battery 70 to be detected scanned by the camera.

[0059] Specifically, the detection gas can be air or an inert gas. The preset air pressure value is higher than the normal working pressure when the battery 70 to be detected is working, so as to more easily detect the leakage points.

[0060] Specifically, the method for collecting the sound information at each point on the surface of the battery 70 to be detected to obtain the spectral characteristic values at each point on the surface of the battery 70 to be detected includes: collecting the sound information at each point on the surface of the battery 70 to be detected, and performing digital signal processing on the sound information at each point to obtain a sound signal; preprocessing the sound signal to obtain a sound signal to be analyzed; wherein the preprocessing includes at least one of noise reduction processing and filtering processing; obtaining the amplitude and frequency of the sound signal to be analyzed at each point to obtain the spectral characteristic values at each point on the surface of the battery 70 to be detected. With such a setting, through digital signal processing, the analog sound information is converted into a quantifiable digital signal, which is convenient for subsequent analysis and processing, and at the same time, the standardization of the spectral characteristic values is realized, ensuring the comparability of data between different detection points. Through preprocessing, including noise reduction and filtering processing, the background noise and interference signals in the collected sound signal can be effectively removed, improving the accuracy of the spectral characteristic values and ensuring the reliability of the detection results. This method not only obtains the amplitude of the sound signal, but also pays attention to the frequency information of the sound. Leakage usually generates acoustic signals within a specific frequency range. This is because the gas flow during leakage will excite vibrations at specific frequencies, and the frequencies of these vibrations are related to the leakage location, leakage rate, and structural characteristics. By identifying these specific frequencies, the presence and location of the leakage can be determined more accurately. Even in the absence of leakage, the acoustic characteristics at each point on the battery surface may vary due to material, structural, or environmental factors, resulting in local changes in the amplitude size. If the amplitude size is directly used, these local changes may be misinterpreted as leakage. By combining the analysis of the amplitude and frequency of the sound, the leakage point can be located more accurately, thereby improving the accuracy of leakage detection.

[0061] It should be noted that the sound signal to be analyzed is the sound signal after preprocessing.

[0062] Specifically, LabVIEW (program development environment) is used to complete the noise reduction, filtering, and spectrum analysis of the sound data, extract the time-domain characteristics and frequency-domain characteristics of the sound, and then obtain the amplitude and frequency of the sound signal to be analyzed. Specifically, a feature extraction algorithm is designed in advance. The feature extraction algorithm includes the noise reduction, filtering, and spectrum analysis of the sound data, and can finally obtain the spectral characteristic values corresponding to each point. The feature extraction algorithm is applied to process the sound signal in each subsequent test.

[0063] Specifically, the method for determining the leakage points on the surface of the battery 70 to be detected according to the magnitude of the acoustic spectrum eigenvalue includes: obtaining the spectrum of the sound signal to be analyzed at each point, and determining the sound signal to be analyzed within the leakage frequency range according to the spectrum; obtaining the maximum amplitude of the sound signal to be analyzed within the leakage frequency range; comparing the amplitudes of the sound signals to be analyzed at each point with the maximum amplitude; when the amplitude of the sound signal to be analyzed at each point is greater than or equal to the maximum amplitude, the corresponding point is the leakage point. With such a setting, by limiting the leakage frequency range, background noise unrelated to leakage can be effectively filtered out, thereby reducing the false alarm rate and ensuring the reliability of the detection result. After determining the leakage frequency range, the detection method can focus on analyzing the sound signals within this frequency band, improving the detection efficiency, and making the leakage detection more targeted and accurate. And setting the comparison threshold between the amplitude and the maximum amplitude can provide an objective and quantitative leakage judgment standard, improving the repeatability and reliability of the detection result.

[0064] Specifically, the method for obtaining the acoustic spectrum eigenvalue at each point on the surface of the battery to be detected includes: obtaining the difference between the amplitude of the sound signal to be analyzed at each point and the maximum amplitude to obtain the acoustic spectrum eigenvalue, and the magnitude of the acoustic spectrum eigenvalue is the leakage amount at the corresponding point. In this way, it is convenient to quickly judge whether there is a leakage at a certain point and the level of the leakage, improving the efficiency of leakage detection.

[0065] In this embodiment, before keeping the battery 70 to be detected stationary, the detection method further includes: introducing a detection gas into the simulated battery, and after the air pressure in the simulated battery reaches a preset air pressure value, collecting the sound information at each point on the surface of the simulated battery, and determining the leakage frequency range according to the frequency of the sound information at the leakage point of the simulated battery; wherein, the simulated battery is a battery with a leakage point. With such a setting, by collecting and analyzing the frequency of the sound information at the leakage point of the simulated battery, the leakage frequency range can be accurately determined. By analyzing the simulated battery with a known leakage point, the detection efficiency and accuracy of the battery 70 to be detected of the same model can be improved. Specifically, there are multiple models of the simulated battery, and there are multiple models of the battery 70 to be detected, and various models of the simulated battery correspond one by one to various models of the battery 70 to be detected.

[0066] Specifically, the method of mapping the acoustic spectrum eigenvalue to the three-dimensional model includes: establishing a one-to-one correspondence between the magnitude of the acoustic spectrum eigenvalue and the magnitude of the color gradient value, and mapping the color gradient value corresponding to the acoustic spectrum eigenvalue at each point on the surface of the battery 70 to be detected to the surface of the three-dimensional model; wherein, the color gradient value includes at least any one of the lightness value, saturation value, and hue value of the color. With such a setting, by establishing a one-to-one correspondence between the acoustic spectrum eigenvalue and the color gradient value and mapping it to the three-dimensional model, the position and leakage degree of the leakage point can be visually displayed, which is beneficial for rapid positioning and fault analysis. This method can not only locate the leakage point, but also reflect the severity of the leakage through the quantization degree of the color change, providing detailed data support for subsequent fault handling and process optimization.

[0067] Specifically, before keeping the battery 70 to be detected stationary, the detection method further includes: placing the battery 70 to be detected at a preset detection position. With such a setting, by placing the battery to be detected at a preset detection position, the consistency of each test can be ensured, improving the repeatability of the test and the reliability of the results. It ensures that the subsequent automated detection process can proceed smoothly, reduces the error of manual operation, and improves the degree of automation of the detection.

[0068] Specifically, the method of keeping the battery 70 to be detected stationary further includes: obtaining the ambient noise of the environment where the battery 70 to be detected is located; when the ambient noise is less than or equal to a preset noise value, keeping the battery 70 to be detected stationary; when the ambient noise is greater than the preset noise value, obtaining the ambient noise again. In this way, the accuracy of the detection result can be better guaranteed, the detection efficiency can be improved, and the interference of ambient noise on the detection can be reduced.

[0069] Specifically, the preset noise value is 8 dB.

[0070] Specifically, the method of collecting the three-dimensional coordinates of each point on the surface of the battery 70 to be detected includes: obtaining the external shape of the battery 70 to be detected; determining the collection sequence and collection position of each point on the surface of the battery 70 to be detected according to the external shape of the battery 70 to be detected to obtain a model collection path; collecting the three-dimensional coordinates of each point on the surface of the battery 70 to be detected according to the model collection path. With such a setting, determining the model collection path according to the external shape of the battery to be detected can achieve efficient and rapid collection of the three-dimensional coordinates of the entire surface, improving the efficiency of data collection. The reasonable collection sequence and position planning avoid blind spots during the collection process, ensuring that the three-dimensional coordinate information of all key areas is accurately obtained. The planning of the model collection path ensures the integrity and accuracy of data collection, providing high-quality basic data for subsequent three-dimensional modeling.

[0071] Specifically, the method for collecting sound signals at each point on the surface of the battery 70 to be detected includes: obtaining the external shape of the battery 70 to be detected; determining the collection sequence and collection positions of each point on the surface of the battery 70 to be detected according to the external shape of the battery 70 to be detected, so as to obtain a sound collection path; and collecting sound signals at each point on the surface of the battery 70 to be detected according to the sound collection path. With such a setting, the planning of the sound signal collection path can optimize the collection sequence and positions, reduce unnecessary collection time and processes, and improve the overall detection speed. By designing the collection path according to the external shape of the battery, the mutual interference of sound signals between different collection points can be effectively avoided, and the purity of sound signal collection is improved. The planning of the sound collection path ensures the consistency and comparability of sound data at different detection points, facilitating subsequent analysis and comparison of sound spectrum characteristics.

[0072] In this embodiment, the detection method further includes: obtaining the process parameters during the assembly process of the battery 70 to be detected, mapping the process parameters to a three-dimensional model according to the acquisition positions on the battery 70 to be detected corresponding to the process parameters; comparing the process parameters corresponding to the points on the three-dimensional model corresponding to the leakage points with preset standard parameters, and when the corresponding process parameters do not conform to the preset standard parameters, recording the corresponding process parameters as problem parameters; where the process parameters at least include any one or more of the pressure distribution values of the components of the hydrogen fuel cell, the airtightness distribution value of the single plate of the hydrogen fuel cell plate, and the compression deformation distribution value of the sealing material of the hydrogen fuel cell. With such a setting, by collecting the key parameters (such as pressure distribution, airtightness distribution, compression deformation distribution of the sealing material) during the assembly process of the hydrogen fuel cell and mapping them to a three-dimensional model, the intuitive association between the process parameters and the detection results is realized, facilitating the analysis of the relationship between the airtightness problem and the assembly process. The identified problem parameters can be used as the direct basis for process improvement, helping to adjust and optimize the assembly process in a timely manner, improving the airtightness of the hydrogen fuel cell and the overall product quality. Since the stacking of the current hydrogen fuel cell realizes the seal between the sealant and the material through press-fitting, the relevant process parameters during the stacking process will ultimately be reflected in the airtightness of the product. The stacking process data is the process parameters or detection data controlled during the stacking process, or the pressure distribution data obtained from traditional laboratory modeling and simulation. Therefore, after mapping the stacking process data to the three-dimensional model, the association and comparison between the leakage points and the process parameters can be realized, and then it is possible to facilitate the judgment of whether there are abnormalities in the relevant process parameters, materials, etc., such as whether the leakage is concentrated in the area with concentrated pressure strain, and whether the leakage amount is small or large, thereby facilitating the discovery of problems and rules.

[0073] It should be noted that the pressure distribution values of the components of a hydrogen fuel cell refer to the pressure distribution of each component or chamber (such as the hydrogen chamber, air chamber, and cooling chamber) inside the battery during airtight testing or normal operation. In a hydrogen fuel cell stack, the uniformity of the pressure distribution is crucial for the performance and lifespan of the battery. The pressure distribution values of the components can help analyze whether the pressure inside the stack is uniform and whether there are problems of excessively high or low local pressure, thereby judging the sealing effect and the rationality of the air flow distribution. During the assembly and testing process, the pressure of each component can be monitored in real time through pressure sensors, and then the pressure distribution values can be obtained. The airtightness distribution value of a single plate of the bipolar plate of a hydrogen fuel cell refers to the airtightness distribution value of a single component such as the bipolar plate or membrane electrode assembly (MEA) in a hydrogen fuel cell stack, which reflects the airtightness state of these single plates after assembly, that is, whether gas can leak out through the sealed area under a specific pressure environment. Through special testing methods (such as helium mass spectrometry leak detection, pressure decay testing, etc.), the airtightness distribution value of each single plate of the bipolar plate can be obtained, which helps to identify which single plates or sealed areas have airtightness problems. The compression deformation distribution value of the sealing material of a hydrogen fuel cell refers to the compression of the sealing material during the assembly of the hydrogen fuel cell, and its deformation directly affects the airtightness and performance of the battery. The compression deformation distribution value reflects the compression degree and deformation state of the sealing material at different positions. Usually, the compression deformation of the sealing material can be obtained through contact sensors or optical measurement techniques, which helps to evaluate the performance and durability of the sealing material and the effectiveness of the seal design. The compression deformation distribution value can help judge whether there is local under-compression or over-compression, thus affecting the airtightness.

[0074] Specifically, such as Figure 2As shown, the detection method includes: 1. Hardware connection: Fix the product to be detected at a fixed position and complete the connection of the test gas circuit; 2. System initialization: Initialize the manipulator (equivalent to the moving component 50) and its control system, data server, and modeling analysis software. When it is used for the first time or when the product is changed, actions such as hand-eye calibration, three-dimensional space Bounding Box calculation, collision detection algorithm verification, and generation of G-code motion instructions should also be completed in advance; 3. Path planning: Plan the acquisition and movement path of the manipulator so that the manipulator can stably and safely surround the product to be detected for one week with the detection component to achieve scanning and modeling; 4. Data acquisition, data processing, and three-dimensional modeling data storage: The manipulator carries a 3D camera (equivalent to the visual detection component 30) and completes the scanning and shooting actions according to the specified path, acquires the point cloud data and pose data on the product surface, uses the ICP algorithm to complete point cloud registration, and completes three-dimensional modeling. The modeling data is associated and stored to prepare for subsequent calls. Specifically, a one-to-one correspondence is established between the manipulator position and attitude data and the shooting data in the database, mainly including establishing a meta-database, three-dimensional data storage, and establishing a spatial index for subsequent data association projection; 5. Sound acquisition system: Remove the 3D camera carried by the manipulator and install the directional microphone (equivalent to the sound detection component 40) on the manipulator; 6. Path planning and data synchronous acquisition: Plan the acquisition and movement path of the manipulator. The manipulator carries the microphone, completes the scanning action, acquires the sound data, and synchronously acquires the trajectory of the manipulator. When it is used for the first time or when the product is changed, calibration, program design, and collision testing should also be completed in advance, and the program check before the test should be completed to prevent collision and position deviation; 7. Sound signal processing and data association storage: Process the collected sound data, obtain the sound spectrum feature values according to the sound spectrum feature extraction algorithm completed in advance, and perform associated storage in the database. Establish a one-to-one correspondence between the sound data and the manipulator position and attitude data in the database; 8. Three-dimensional sound field modeling and leakage point analysis: Call the data and complete the modeling through spatial mapping. Generate a color gradient according to the sound spectrum feature values and map it to the surface of the three-dimensional model. According to the set color, the leakage point can be located, and the depth of the leakage point color represents the size of the leakage amount.

[0075] Embodiment 2 of the present invention provides a detection device for performing the detection method provided in Embodiment 1. The detection device includes a first acquisition unit, a second acquisition unit, and a detection unit. The first acquisition unit is configured to keep the battery 70 to be detected stationary and collect the three-dimensional coordinates of each point on the surface of the battery 70 to be detected, so as to establish a three-dimensional model of the battery 70 to be detected; the second acquisition unit is configured to introduce a detection gas into the battery 70 to be detected that is kept stationary by the first acquisition unit, and after the air pressure in the battery 70 to be detected reaches a preset air pressure value, collect the sound information at each point on the surface of the battery 70 to be detected, so as to obtain the spectral feature values at each point on the surface of the battery 70 to be detected; the detection unit is configured to map the spectral feature values to the three-dimensional model and determine the leakage points on the surface of the battery 70 to be detected according to the magnitudes of the spectral feature values.

[0076] By using the detection device provided in Embodiment 2 of the present invention to perform airtightness detection by collecting sound information, it is a non-contact detection method. The detection process does not require disassembly and assembly of the stack, so the original stack state is not damaged and the hydrogen fuel cell will not be physically damaged. And by mapping the spectral feature values to the three-dimensional model and combining the amplitude and frequency information of the sound, the leakage points on the surface of the hydrogen fuel cell can be accurately located, improving the detection speed and accuracy. In this way, by marking points on the three-dimensional model to judge the leakage position of the stack, the detection is fast and accurate. After establishing a fault database later, the fault cause can also be accurately judged. In addition, this detection method has high applicability to the battery 70 to be detected and can be applied to hydrogen fuel cells of different models and sizes. Only by adjusting the parameters of three-dimensional coordinate acquisition and spectral analysis according to the battery type, various detection requirements can be flexibly met. Therefore, through the detection device provided in this embodiment, the technical problem of low airtight test efficiency of hydrogen fuel cells in the prior art can be solved.

[0077] Embodiment 3 of the present invention provides a non-volatile storage medium. The non-volatile storage medium includes a stored program, wherein when the program runs, it controls the device where the non-volatile storage medium is located to execute the detection method provided in Embodiment 1.

[0078] As Figure 3As shown in the figure, Embodiment 4 of the present invention provides a detection structure, which is applicable to the detection method provided in Embodiment 1. The detection structure includes a detection platform 10, a gas supply component 20, a visual detection component 30, and a sound detection component 40. The detection platform 10 has a bearing surface 11 for bearing the battery 70 to be detected. The intake end 21 of the gas supply component 20 is used to communicate with the test gas source, and the outlet end of the gas supply component 20 is used to communicate with the inside of the battery 70 to be detected. The visual detection component 30 is arranged on the detection platform 10, and the detection end of the visual detection component 30 is movably arranged to collect the three-dimensional coordinates of each point on the surface of the battery 70 to be detected. The sound detection component 40 is arranged on the detection platform 10, and the detection end of the sound detection component 40 is movably arranged to collect the sound signals at each point on the surface of the battery 70 to be detected.

[0079] By using the detection structure provided in Embodiment 4 of the present invention, the detection ends of the visual detection component 30 and the sound detection component 40 are movably arranged, which can realize high-precision data collection of each point on the surface of the battery 70 to be detected, and improve the accuracy and reliability of the detection. By integrating the detection platform 10, the gas supply component 20, the visual detection component 30, and the sound detection component 40 into a detection structure, the integrated operation of airtightness detection, three-dimensional coordinate acquisition, and acoustic signal collection of the hydrogen fuel cell stack is realized, enhancing the ability of the detection system and making the detection process more comprehensive and efficient. Therefore, through the detection structure provided in this embodiment, the technical problem of low airtight test efficiency of the hydrogen fuel cell in the prior art can be solved.

[0080] Specifically, the detection structure further includes a moving component 50. The moving component 50 is arranged on the detection platform 10, and the moving part 51 of the moving component 50 is movably arranged. The visual detection component 30 and the sound detection component 40 can both be selectively connected to the moving part 51. With such a structural arrangement, the moving component 50 enables the visual detection component 30 and the sound detection component 40 to move flexibly and accurately locate each point on the surface of the battery 70 to be detected, improving the automation level and flexibility of the detection. Through the selective connection of the moving part 51, it is possible to easily switch between visual detection and sound detection without complex manual adjustment, greatly shortening the detection preparation time and improving the overall detection efficiency.

[0081] Specifically, the detection structure further includes a fixing component 60. The fixing component 60 is arranged on the bearing surface 11. The outer edge of the fixing part 61 of the fixing component 60 protrudes from the bearing surface 11. The fixing part 61 is used to be inserted into the opening of the battery 70 to be detected and is arranged to be adapted to the opening of the battery 70 to be detected. Among them, the opening of the battery 70 to be detected includes the water outlet and the gas outlet of the fuel cell stack. With such a structural arrangement, the fixing part 61 of the fixing component 60 is inserted into the opening of the battery 70 to be detected, realizing the stable fixation of the fuel cell stack, preventing the displacement or vibration of the fuel cell stack during the detection process, ensuring the consistency of the detection conditions, and improving the comparability and credibility of the detection results. At the same time, the design that the fixing part 61 is adapted to the opening of the fuel cell stack also realizes the blocking of the water outlet and the gas outlet of the fuel cell stack, facilitating the subsequent introduction of test gas for airtightness testing, providing convenience for airtightness testing, and improving the testing efficiency.

[0082] Specifically, the airtightness test interface (equivalent to the intake end 21) of the air supply component 20 is designed in a quick-connect form, which is convenient for quick connection with the airtightness test equipment.

[0083] Specifically, the detection platform 10 is used to carry the product to be detected. The bearing surface 11 provides a reference surface, and the flatness of the bearing surface 11 is in the range of 0.05 - 0.1 mm (including 0.05 mm and 0.1 mm). The repeat positioning accuracy of the manipulator (equivalent to the moving component 50) is ±0.01 mm, and the absolute positioning accuracy is ±0.05 mm. The manipulator is used to perform the acquisition action. The detection structure includes two parts: hardware and software. The hardware part includes a positioning 3D camera (equivalent to the vision detection component 30) and a directional microphone system (equivalent to the sound detection component 40), which are mainly used for data acquisition work. The software part uses RobotStudio (robot simulation software) to complete the construction of the world coordinate system, the scanning and modeling path, the communication of the test system, and the communication of the database, realizing the collection, preliminary association, and storage of basic real data in the database.

[0084] From the above description, it can be seen that the above embodiments of the present invention achieve the following technical effects:

[0085] 1. Realize the functions of quickly and accurately positioning the airtight failure point of the fuel cell stack, greatly reducing the labor cost and rework cost of detection;

[0086] 2. Not only realize the fault location on the battery surface, but also expand the database in the later stage. Through the real-time collection and rapid processing of production data, deep-level problems such as pressure uniformity and material sealing can be discovered in time, which is convenient for timely adjustment of process parameters, improving product quality, and avoiding after-sales losses;

[0087] 3. The device realizes fully automated detection, has a low operation threshold, and can be quickly and scaled up for application.

[0088] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular forms are also intended to include the plural forms. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they specify the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0089] Unless otherwise specifically stated, the relative arrangements of components and steps, numerical expressions, and numerical values set forth in these embodiments do not limit the scope of the present application. At the same time, it should be understood that, for the sake of convenience of description, the dimensions of the various parts shown in the drawings are not drawn in actual proportional relationships. Technologies, methods, and devices known to those of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, the said technologies, methods, and devices should be regarded as part of the specification. In all the examples shown and discussed herein, any specific value should be construed as merely exemplary and not as a limitation. Therefore, other examples of the exemplary embodiments may have different values. It should be noted that like reference numerals and letters denote like items in the following drawings, and thus, once an item is defined in one drawing, it does not need to be further discussed in subsequent drawings.

[0090] In the description of the present application, it should be understood that the orientation or positional relationships indicated by orientation words such as "front, rear, upper, lower, left, right", "lateral, vertical, perpendicular, horizontal", and "top, bottom" are generally based on the orientation or positional relationships shown in the drawings, and are only for the convenience of describing the present application and simplifying the description. Without contrary description, these orientation words do not indicate and imply that the device or element referred to must have a specific orientation or be constructed and operated in a specific orientation, and thus should not be construed as limiting the protection scope of the present application; the orientation words "inside, outside" refer to the inside and outside relative to the contour of each component itself.

[0091] For ease of description, spatial relative terms such as "above", "over", "on the upper surface", "upper" etc. may be used herein to describe the spatial positional relationship of one device or feature to other devices or features as shown in the figures. It should be understood that the spatial relative terms are intended to encompass different orientations in use or operation in addition to the orientation depicted in the figures. For example, if the device in the figures is inverted, a device described as "above" or "over" other devices or structures will then be positioned "below" or "under" the other devices or structures. Thus, the exemplary term "above" can include both the orientations of "above" and "below". The device may also be positioned in other different ways (rotated 90 degrees or in other orientations), and corresponding interpretations of the spatial relative descriptions used herein will be made.

[0092] In addition, it should be noted that the use of terms such as "first" and "second" to define components is only for the convenience of differentiating the corresponding components. Without additional statements, the above terms have no special meanings, and thus should not be construed as limiting the scope of protection of this application.

[0093] The above are only the preferred embodiments of the present invention and are not used to limit the present invention. For those skilled in the art, the present invention may have various modifications and changes. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A detection method for detecting the airtightness of a hydrogen fuel cell, characterized in that, The detection method includes: Keeping the battery to be detected stationary, and collecting the three-dimensional coordinates of each point on the surface of the battery to be detected to establish a three-dimensional model of the battery to be detected; Introducing a detection gas into the battery to be detected, and after the air pressure in the battery to be detected reaches a preset air pressure value, collecting the sound information at each point on the surface of the battery to be detected to obtain the spectral characteristic values at each point on the surface of the battery to be detected; Mapping the spectral characteristic values to the three-dimensional model, and determining the leakage points on the surface of the battery to be detected according to the magnitudes of the spectral characteristic values; Wherein, the spectral characteristic values include the amplitude and frequency of the sound.

2. The detection method according to claim 1, characterized in that The step of collecting the sound information at each point on the surface of the battery to be detected to obtain the spectral characteristic values at each point on the surface of the battery to be detected includes: Collecting the sound information at each point on the surface of the battery to be detected, and performing digital signal processing on the sound information at each point to obtain a sound signal; Performing preprocessing on the sound signal to obtain a sound signal to be analyzed; wherein, the preprocessing includes at least one of noise reduction processing and filtering processing; Obtaining the amplitude and frequency of the sound signal to be analyzed at each point to obtain the spectral characteristic values at each point on the surface of the battery to be detected.

3. The detection method according to claim 2, wherein The step of determining the leakage points on the surface of the battery to be detected according to the magnitudes of the spectral characteristic values includes: Obtaining the spectrum of the sound signal to be analyzed at each point, and determining the sound signal to be analyzed within the leakage frequency range according to the spectrum; Obtaining the maximum amplitude of the sound signal to be analyzed within the leakage frequency range; Comparing the amplitude of the sound signal to be analyzed at each point with the maximum amplitude; when the amplitude of the sound signal to be analyzed at each point is greater than or equal to the maximum amplitude, the corresponding point is the leakage point.

4. The detection method according to claim 3, characterized in that, Before keeping the battery to be detected stationary, the detection method further includes: Introducing a detection gas into a simulated battery, and after the air pressure in the simulated battery reaches the preset air pressure value, collecting the sound information at each point on the surface of the simulated battery, and determining the leakage frequency range according to the frequency of the sound information at the leakage point of the simulated battery; wherein, the simulated battery is a battery with a leakage point.

5. The detection method according to claim 1, characterized in that, The step of mapping the spectral characteristic values to the three-dimensional model includes: establishing a one-to-one correspondence between the magnitude of the spectral characteristic value and the magnitude of the color gradient value, and mapping the color gradient value corresponding to the spectral characteristic value at each point on the surface of the battery to be detected to the surface of the three-dimensional model; wherein, the color gradient value includes at least any one of the lightness value, saturation value, and hue value of the color; and / or, Before keeping the battery to be detected stationary, the detection method further includes: placing the battery to be detected at a preset detection position; and / or, The step of keeping the battery to be detected stationary includes: obtaining the environmental noise of the environment where the battery to be detected is located; when the environmental noise is less than or equal to a preset noise value, keeping the battery to be detected stationary; when the environmental noise is greater than the preset noise value, re-obtaining the environmental noise.

6. The detection method according to claim 1, characterized in that Collecting the three-dimensional coordinates of each point on the surface of the battery to be detected includes: obtaining the external shape of the battery to be detected; determining the collection sequence and collection positions of each point on the surface of the battery to be detected according to the external shape of the battery to be detected, so as to obtain a model collection path; collecting the three-dimensional coordinates of each point on the surface of the battery to be detected according to the model collection path; and / or, Collecting the sound signals at each point on the surface of the battery to be detected includes: obtaining the external shape of the battery to be detected; determining the collection sequence and collection positions of each point on the surface of the battery to be detected according to the external shape of the battery to be detected, so as to obtain a sound collection path; collecting the sound signals at each point on the surface of the battery to be detected according to the sound collection path.

7. The detection method according to any one of claims 1 to 6, characterized in that The detection method further includes: Obtaining the process parameters during the assembly process of the battery to be detected, and mapping the process parameters to the three-dimensional model according to the acquisition position on the battery to be detected corresponding to the process parameters; Comparing the process parameters corresponding to the points on the three-dimensional model corresponding to the leakage points with the preset standard parameters, and when the corresponding process parameters do not conform to the preset standard parameters, recording the corresponding process parameters as problem parameters; Wherein, the process parameters at least include any one or more of the pressure distribution values of the components of the hydrogen fuel cell, the airtightness distribution values of the single plates of the hydrogen fuel cell plate, and the compression deformation distribution values of the sealing materials of the hydrogen fuel cell.

8. A detection device, characterized in that, For implementing the detection method according to any one of claims 1 to 7, the detection device includes: A first acquisition unit, configured to keep the battery to be detected stationary and collect the three-dimensional coordinates of each point on the surface of the battery to be detected, so as to establish a three-dimensional model of the battery to be detected; A second acquisition unit, configured to introduce a detection gas into the battery to be detected that is kept stationary by the first acquisition unit, and after the air pressure in the battery to be detected reaches a preset air pressure value, collect the sound information at each point on the surface of the battery to be detected, so as to obtain the spectrogram characteristic values at each point on the surface of the battery to be detected; A detection unit, configured to map the spectrogram characteristic values to the three-dimensional model, and determine the leakage points on the surface of the battery to be detected according to the magnitudes of the spectrogram characteristic values.

9. A non-volatile storage medium, characterized in that, The non-volatile storage medium includes a stored program, wherein when the program runs, it controls the device where the non-volatile storage medium is located to execute the detection method according to any one of claims 1 to 7.

10. A detection structure, characterized in that, Applicable to the detection method according to any one of claims 1 to 7, the detection structure includes: A detection platform (10), the detection platform (10) having a bearing surface (11) for bearing the battery to be detected; A gas supply assembly (20), an intake end (21) of the gas supply assembly (20) being used for communicating with a test gas source, and an outlet end of the gas supply assembly (20) being used for communicating with the inside of the battery to be detected; A visual detection assembly (30), arranged on the detection platform (10), a detection end of the visual detection assembly (30) being movably arranged to collect the three-dimensional coordinates of each point on the surface of the battery to be detected; A sound detection component (40) is provided on the detection platform (10), and the detection end of the sound detection component (40) is movably arranged to collect sound signals at various points on the surface of the battery to be detected.

11. The detection structure according to claim 10, wherein, The detection structure further includes: A moving component (50) is provided on the detection platform (10), and the moving part (51) of the moving component (50) is movably arranged. The visual detection component (30) and the sound detection component (40) can be selectively connected to the moving part (51); and / or, A fixing component (60) is provided on the bearing surface (11), and the outer edge of the fixing part (61) of the fixing component (60) protrudes from the bearing surface (11). The fixing part (61) is used for being inserted into the opening of the battery to be detected and is arranged to be adapted to the opening of the battery to be detected; wherein, the opening of the battery to be detected includes the water outlet of the fuel cell stack and the gas outlet of the fuel cell stack.

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