Battery detection system

Abstract

According to the battery detection system provided by the invention, the X-ray generation device and the fluorescent X-ray generation device are arranged and emit the X-rays, and the X-rays emitted by the X-ray generation device penetrate through the battery in the detection area, so that the detection image in the battery is obtained; fluorescent X-rays emitted by the fluorescent X-ray generating device irradiate a battery in a detection area, the fluorescent X-rays can penetrate through a shell of the battery, irradiate the interior of the battery and then are reflected back to the fluorescent X-ray receiving device, so that elements in the battery can be detected, and the two devices detect the battery by emitting different X-rays. In the detection process, whether defects occur in the battery or not can be detected without disassembling the battery, nondestructive detection of the battery can be achieved only by irradiating the battery with X-rays, the target type of the battery is obtained, the battery type of the battery and whether internal defects exist or not are determined, battery detection can be conducted without damaging the battery in the process, and the detection efficiency is improved. The process does not need manual participation, and is low in cost and high in efficiency.

Description

Technical Field

[0001] This application relates to the technical field of battery classification, and in particular to a battery detection system. Background Art

[0002] During the recycling and use of batteries, different types of batteries are processed differently. Therefore, it is necessary to classify and detect the batteries.

[0003] In some battery detection schemes, batteries are classified manually according to battery labels. This scheme has low efficiency and is prone to misjudgment. In some other battery detection schemes, a manipulator is used to pick up the battery and scan the code to detect the battery type. The cost of using the manipulator to pick up the battery and scan the code is high, and the positions of the battery QR codes are inconsistent, with poor compatibility. At the same time, the above two schemes can only determine the type of the battery and cannot confirm the internal defects of the battery. During the recycling and use of batteries, defective batteries need to be specially processed. Therefore, the above battery detection schemes have high costs and low accuracy. Summary of the Utility Model

[0004] This application provides a battery detection system to solve the problems of high cost and low accuracy of battery detection schemes.

[0005] This application provides a battery detection system, including: a conveyor belt, an X-ray generating device, an X-ray receiver, a fluorescent X-ray generating device, a fluorescent X-ray receiving device, and a controller. Among them,

[0006] An X-ray generating device, a fluorescent X-ray generating device, and a fluorescent X-ray receiving device are arranged above the conveyor belt, and an X-ray receiver is arranged at a position opposite to the X-ray generating device below the conveyor belt. The area between the X-ray generating device and the X-ray receiver forms a detection area.

[0007] The fluorescent X-ray generating device and the fluorescent X-ray receiving device are located on both sides of the detection area.

[0008] The battery is transported to the detection area through the conveyor belt. The X-rays emitted by the X-ray generating device penetrate into the battery and then enter the X-ray receiver. The fluorescent X-rays emitted by the fluorescent X-ray generating device irradiate the battery and are reflected into the fluorescent X-ray receiving device.

[0009] The controller is connected to the X-ray receiver and the fluorescent X-ray receiving device, and is used to detect the battery according to the data received by the X-ray receiver and the fluorescent X-ray receiving device.

[0010] In this application, an X-ray generating device and a fluorescent X-ray generating device are provided. The two devices emit X-rays. The X-rays emitted by the X-ray generating device penetrate through the battery in the detection area, thereby obtaining a detection image inside the battery. The fluorescent X-rays emitted by the fluorescent X-ray generating device irradiate on the battery in the detection area. The fluorescent X-rays can penetrate the outer shell of the battery, irradiate on the inside of the battery, and then be reflected back to the fluorescent X-ray receiving device, thereby detecting the elements inside the battery. The two devices detect the battery by emitting different X-rays. This detection process can detect whether there are defects inside the battery without disassembling the battery. Only by irradiating the X-rays on the battery can non-destructive detection of the battery be achieved, obtaining the target category of the battery to determine the battery category to which the battery belongs and whether there are internal defects. In this process, the battery can be detected without damaging it, and this process does not require manual participation, with low cost and high efficiency. Description of the Drawings

[0011] The drawings here are incorporated into the specification and form a part of this specification, showing embodiments consistent with this application, and are used together with the specification to explain the principles of this application.

[0012] Figure 1 Structural diagram of a battery detection system shown in an embodiment of this application;

[0013] Figure 2 Structural diagram of a collimator shown in an embodiment of this application;

[0014] Figure 3 Side view of a collimator shown in an embodiment of this application;

[0015] Figure 4 Front view of a collimator shown in an embodiment of this application;

[0016] Figure 5 Flowchart of a battery detection method shown in an embodiment of this application;

[0017] Figure 6 Element band data diagram of a battery shown in an embodiment of this application;

[0018] Figure 7 Structural schematic diagram of a battery detection device shown in an embodiment of this application;

[0019] Figure 8 Block diagram of an electronic device shown in an exemplary embodiment of this application.

[0020] Through the above-mentioned accompanying drawings, specific embodiments of the present application have been shown, and more detailed descriptions will be provided hereinafter. These drawings and textual descriptions are not intended to limit the scope of the concept of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. Detailed Description of the Embodiments

[0021] Here, exemplary embodiments will be described in detail, and examples are shown in the accompanying drawings. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numerals in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0022] Power battery detection can be used for battery recycling and utilization. Currently, the mainstream power batteries on the market mainly include ternary lithium, lithium iron phosphate, lithium manganate, etc. These different types of batteries have significant differences in chemical properties, material structures, etc. Therefore, different processing techniques are required during battery detection, and there are great differences in the processing methods during the recycling or utilization of different types of batteries, so complete compatibility cannot be achieved.

[0023] Generally, there are two methods for reuse in recycling. One is cascade utilization, and the other is regenerative utilization. For cascade utilization, battery detection is a necessary step. In cascade utilization, the battery cell is the smallest unit of the battery, and its performance and state directly determine the overall performance and lifespan of the battery. Therefore, before cascade utilization, it is necessary to detect the battery and remove the damaged batteries to ensure the effect and safety of cascade utilization.

[0024] Non-destructive testing is an important technology for battery detection. It can evaluate the performance and quality of the battery through specific detection means, avoiding destructive testing and losses of the battery. The type and state of the recycled power batteries cannot be guaranteed. In order to ensure the quality of the subsequent cascade utilization batteries and the regenerated electrode powder materials, it is very necessary to perform detection and pre-sorting through technical means in the previous process.

[0025] In some ways, batteries can be classified by battery labels manually, but this classification method is inefficient, prone to misjudgment, and manual inspection can only detect the appearance of the battery and cannot determine the internal defects of the battery; in other ways, a manipulator grabs the battery to scan the code to detect the battery type, and detects whether the battery is defective through voltage, internal resistance, etc. However, the cost of the manipulator grabbing the battery to scan the code is high, the positions of the battery two-dimensional codes are inconsistent, the compatibility is not strong, the detection of voltage, internal resistance, etc. requires battery disassembly, and this disassembly process requires manual participation and cannot be automatically detected. The initial inspection efficiency of all batteries for cascade utilization by this method is low.

[0026] Based on this, this embodiment provides a battery detection method, which can quickly and nondestructively detect the type of battery and whether there are defects in the battery. Refer to Figure 1 , which is a structural diagram of a battery detection system proposed in an embodiment of the present application. The battery detection system includes a conveyor belt 101, an X-ray generating device 102, an X-ray receiver 103, a fluorescent X-ray generating device 104, a fluorescent X-ray receiving device 105, a controller 106, and a battery 107.

[0027] It can be understood that the battery 107 in this embodiment is a complete battery and does not need to be disassembled or processed.

[0028] In this embodiment, an X-ray generating device 102 is arranged above the conveyor belt 101, and an X-ray receiver 103 is arranged at a position opposite to the X-ray generating device 102 below the conveyor belt 101. The area between the X-ray generating device 102 and the X-ray receiver 103 forms a detection area.

[0029] In some embodiments, the number of the X-ray generating device 102 and the X-ray receiver 103 can be one or more, and they are distributed above and below the conveyor belt 101. When the battery 107 is transported to the detection area by the conveyor belt 101, the X-ray generating device 102 emits X-rays, and the signal after the X-rays pass through the battery 107 reaches the X-ray receiver 103.

[0030] In some embodiments, when the battery 107 detection system is operating, the X-ray generating device 102 continuously emits X-rays. Thus, after the battery 107 is delivered to the detection area by the conveyor belt 101, the X-ray receiver 103 can receive different signals.

[0031] In other embodiments, when the battery 107 detection system is operating, only when the battery 107 is delivered to the detection area by the conveyor belt 101, the X-ray generating device 102 and the X-ray receiver 103 start to work. The X-ray generating device 102 emits X-rays, and the X-ray receiver 103 receives the signals.

[0032] In this embodiment, the controller 106 is also connected to the X-ray generating device 102 and the fluorescent X-ray generating device 104 to control the X-ray generating device 102 and the fluorescent X-ray generating device 104 to emit fluorescent X-rays.

[0033] In some embodiments, sensors can be arranged at the edge of the detection area. When the sensors receive the arrival of the battery 107, the sensors can send signals to the controller 106, and the controller 106 controls the X-ray generating device 102 and the X-ray receiver 103 to work.

[0034] In this embodiment, the sensor can be a pressure sensor, a laser sensor, an infrared sensor, etc.

[0035] In this embodiment, the battery 107 is transported to the detection area through the conveyor belt 101, and the fluorescent X-ray emitted by the fluorescent X-ray generating device 104 irradiates the battery 107 in the detection area and is reflected into the fluorescent X-ray receiving device 105.

[0036] In this embodiment, the fluorescent X-ray emitted by the fluorescent X-ray generating device 104 does not penetrate the battery 107, but after passing through the battery 107, it is reflected to the fluorescent X-ray receiving device 105.

[0037] As Figure 1 shown by the dashed arrow in, which indicates the path of the fluorescent X-ray emitted by the fluorescent X-ray generating device 104.

[0038] The X-ray emitted by the X-ray generating device 102 penetrates the battery 107 in the detection area and enters the X-ray receiver 103. The controller 106 is connected to the X-ray receiver 103 and the fluorescent X-ray receiving device 105, and is used to detect the battery 107 according to the data received by the X-ray receiver 103 and the fluorescent X-ray receiving device 105.

[0039] In some embodiments, the angle between the fluorescent X-ray generating device 104 and the conveyor belt 101 is 100° - 170°.

[0040] In this embodiment, the angle of the fluorescent X-ray generating device 104 can be changed, but the fluorescent X-ray emitted by the fluorescent X-ray generating device 104 needs to irradiate the detection area. In this way, after the battery 107 reaches the detection area, the fluorescent X-ray emitted by the fluorescent X-ray generating device 104 shines on the battery 107.

[0041] In some embodiments, the angle between the fluorescent X-ray receiving device 105 and the conveyor belt 101 is 10° - 80°.

[0042] It can be understood that the angle of the fluorescent X-ray receiving device 105 can be changed, but it is necessary to ensure that the fluorescent X-ray emitted by the fluorescent X-ray generating device 104 irradiates the battery 107 in the detection area, and the reflected X-ray enters the fluorescent X-ray receiving device 105, that is, the focus of the fluorescent X-ray generating device 104 and the fluorescent X-ray receiving device 105 should be located at the same position on the conveyor belt in the detection area.

[0043] In some embodiments, the battery 107 detection system further includes a collimator, and the collimator is arranged at the X-ray emission port of the X-ray generating device 102. Figure 1 which is not shown in, and the collimator can be referred to Figures 2 to 4 ,Figure 2 Structural diagram of the collimator Figure 3 Side view of the collimator Figure 4 Front view of the collimator

[0044] In some embodiments, the collimator is cylindrical Figures 2 to 4 The values of are the thickness, outer diameter, slit width, slit length, etc. of the collimator. Among them, the collimator thickness is 4 mm (millimeters), the outer diameter is 50 mm, the slit width is 4 mm, and the slit length is 35 mm. Of course Figures 2 to 4 The structure and parameters in are exemplary. In other embodiments, the collimator can also be of other shapes or other parameters. For example, in other embodiments, the collimator thickness is 2 - 5 mm, the outer diameter is 30 - 70 mm, the slit width is 1 - 7 mm, and the slit length is 15 - 40 mm. No specific limitation is made here

[0045] Figure 3 The values of 35 for the length and 4 for the width shown in are the slits of the collimator. The X - rays emitted by the X - ray generating device 102 pass through the slits of the collimator and transmit through the battery 107 in the detection area

[0046] In this embodiment, a collimator is provided at the X - ray emission port of the X - ray generating device 102 to prevent the influence of the X - rays emitted by the X - ray generating device 102 on the rays emitted by the fluorescent X - ray generating device 104. For example Figure 2 The collimator in can change the range of the X - rays emitted by the X - ray generating device 102 from a 50 - mm circle to a 50×4 - mm rectangle

[0047] In some embodiments, the X - rays emitted by the X - ray generating device 102 are X - ray transmission light, and the X - rays emitted by the fluorescent X - ray generating device 104 are high - energy X - rays, which are used for fluorescence detection

[0048] In some embodiments, the signal of the X - rays emitted by the X - ray generating device 102 after passing through the battery enters the X - ray receiver. The fluorescent X - rays emitted by the fluorescent X - ray generating device irradiate the battery in the detection area and are reflected into the fluorescent X - ray receiving device. The controller acquires the signals received in the X - ray receiver and the fluorescent X - ray receiving device, obtains the detection image based on the signal in the X - ray receiver, obtains the elemental band data inside the battery based on the signal received in the fluorescent X - ray receiving device, so as to obtain the first category representing the defect type of the battery based on the detection image, and obtain the second category representing the type of the battery based on the elemental band data; The first category and the second category are used as the target category of the battery

[0049] The battery detection system proposed in this embodiment can automatically perform battery detection, not only classify the batteries, but also detect the internal defects of the batteries, with low cost and high efficiency

[0050] In some other embodiments, the battery detection system may further include a classification structure, which may include a plurality of sub-conveyor belts, each corresponding to a target category of a battery; each sub-conveyor belt is connected to the conveyor belt, and a classifier is provided at the connection position between the sub-conveyor belt and the conveyor belt. After the battery passes through the detection area and the controller obtains the target category of the battery, the controller sends a control signal to the classifier, and the classifier controls the battery to enter the corresponding sub-conveyor belt, thereby realizing automatic classification of the batteries.

[0051] For example, if the target category corresponding to a sub-conveyor belt is that the first category is defective and the second category is ternary lithium, when the controller detects that the first category in the target category of the battery is defective and the second category is ternary lithium, the classifier will send the battery into the corresponding sub-conveyor belt, and the sub-conveyor belt can transport the battery to a warehouse or other structures, which is not specifically limited here.

[0052] In this embodiment, by setting the X-ray generating device 102 and the fluorescent X-ray generating device 104, the two devices emit X-rays. The X-rays emitted by the X-ray generating device 102 pass through the battery 107 in the detection area, thereby obtaining a detection image of the inside of the battery 107. The fluorescent X-rays emitted by the fluorescent X-ray generating device 104 irradiate on the battery 107 in the detection area. The fluorescent X-rays can penetrate the outer shell of the battery 107, irradiate on the inside of the battery 107, and then be reflected back to the fluorescent X-ray receiving device 105, thereby detecting the elements inside the battery 107. The two devices detect the battery 107 by emitting different X-rays. This detection process can detect whether there are defects inside the battery without disassembling the battery 107. Only by irradiating the X-rays on the battery 107 can non-destructive detection of the battery be achieved, obtaining the target category of the battery 107 to determine the battery category to which the battery 107 belongs and whether there are internal defects.

[0053] Figure 5 It is a flowchart of a battery detection method shown in an embodiment of the present application. As Figure 5 shown, the battery detection method includes:

[0054] Step S510: Receive the signal after the X-ray passes through the battery to obtain a detection image.

[0055] In this embodiment, a detection image can be obtained through the signal obtained by the X-ray passing through the battery.

[0056] In some embodiments, the X-ray has strong penetration ability and can penetrate a variety of substances. However, different types of substances have different absorption abilities for X-rays. Therefore, by the degree of absorption of X-rays, different properties and structures of the battery can be known.

[0057] When X-rays pass through a battery, the X-rays interact with the atoms in the battery. During the propagation of X-rays in the battery, absorption and scattering occur. Since the active materials (such as the cathode material) in the battery have different compositions and densities from other components, the absorption rates of X-rays are different. When X-rays pass through the battery, the active materials absorb a part of the X-rays, while other components (such as the electrolyte, electrodes, collectors, etc.) have a relatively small absorption of X-rays.

[0058] By setting an X-ray receiver at a position opposite to the device emitting X-rays, the intensity of the X-rays transmitted through the battery is measured. By analyzing the change in the intensity of the X-rays received by the detector, information about the distribution of substances in the battery can be obtained. For example, if a substance is more concentrated or has a higher density in a certain area, then the absorption of X-rays in that area will be greater, and the intensity received by the X-ray receiver will decrease accordingly. In this way, a detection image of the substance distribution can be obtained.

[0059] In this embodiment, the X-rays pass through the outer shell of the battery and then through the interior of the battery, and then reach the X-ray receiver, thereby obtaining a detection image.

[0060] Step S530: Receive the signal after the battery is irradiated with fluorescent X-rays to obtain the elemental band data inside the battery.

[0061] In this embodiment, different from step S510, the fluorescent X-rays do not pass through the battery, but are reflected back to the fluorescent X-ray receiving device after irradiating the battery, so that the elemental band data inside the battery can be obtained.

[0062] In this embodiment, the fluorescent X-rays in S530 are the fluorescent X-rays emitted by the fluorescent X-ray generating device. These fluorescent X-rays are high-energy X-rays. By using the interaction between high-energy X-rays and substances, the inherent X-rays of the elements in the measured substance are excited, and then the energy and quantity of these X-rays are measured, thereby inferring the types and contents of the elements present in the substance.

[0063] Specifically, when high-energy X-rays irradiate a substance, they interact with the atoms in the substance, exciting the inner electrons of the atoms and causing them to transition to higher energy levels. Once the electrons return from the excited state to the ground state, they release energy, and this energy is released in the form of X-rays. Since the X-rays released by different elements have specific energies or wavelengths, in this way, the elemental band data can be obtained.

[0064] Such as Figure 6 is the elemental band data diagram of a certain battery shown in an embodiment.

[0065] It can be understood that when the fluorescent X-ray in this embodiment irradiates on the battery, it will penetrate the outer shell of the battery, irradiate inside the battery, and then return information. Therefore, the elemental band data inside the battery obtained thereby should be the elemental-related data inside the battery protected by the outer shell of the battery.

[0066] In some embodiments, the elemental band data graph can also be regarded as the elemental band data of the battery core inside the battery. That is, when the fluorescent X-ray irradiates on the battery, it will penetrate the outer shell of the battery and reach the battery core inside the battery, and then the fluorescent X-ray is reflected back to the receiving device, so as to obtain the elemental band data. At this time, it can be regarded that the battery includes an outer shell and a battery core. The fluorescent X-ray penetrates the outer shell to reach the battery core, and then the reflected signal is used to obtain the elemental band data for determining the elements contained in the battery core.

[0067] Step S550: Obtain a first category characterizing the defect category of the battery based on the detection image, and obtain a second category characterizing the type of the battery based on the elemental band data.

[0068] In some embodiments, after the detection image reaches Figure 1 the controller in, the defect recognition model preset in the controller processes the detection image.

[0069] Therefore, in this controller, obtaining the first category includes:

[0070] S10: Obtain a preset defect recognition model; wherein, the preset defect recognition model is trained based on historical detection images, and the historical detection images are the images obtained after X-rays penetrate defective batteries.

[0071] S11: Input the detection image into the preset defect recognition model to obtain the first category.

[0072] In this embodiment, the preset defect recognition model is a machine model for image processing, such as a neural network model, a random forest model, etc.

[0073] The defective battery in this embodiment is a battery confirmed to have defects inside, that is, a battery with the first category being defective. For this defective battery, the historical detection image is obtained by the method of step S510.

[0074] In this embodiment, a training method for the preset defect recognition model is also proposed, which may include:

[0075] S20: Obtain an initial defect recognition model; wherein, the initial defect recognition model includes a convolutional network layer and a pooling layer.

[0076] S21: Input the historical detection image into the initial defect recognition model, enabling the convolutional network layer to extract features from the historical detection image and input the extracted features into the pooling layer to obtain the predicted value output by the pooling layer, so as to train the initial defect recognition model based on the predicted value to obtain the preset defect recognition model.

[0077] In this embodiment, the initial defect recognition model includes a convolutional network layer and a pooling layer. The convolutional network layer is connected to the pooling layer. The convolutional network layer extracts features from the historical detection image. The number of convolutional network layers can be one or more. For example, each network convolutional layer uses a 3x3 small convolutional kernel. Of course, other-sized convolutional kernels can also be used, and no limitation is imposed here.

[0078] It can be understood that the structure of the initial defect recognition model including a convolutional network layer and a pooling layer proposed in this embodiment is exemplary. In other embodiments, an initial defect recognition model with other structures can also be used. For example, in one embodiment, the initial defect recognition model can also include structures such as an embedding layer and an attention network, as long as the initial defect recognition model can perform defect recognition on the detection image to obtain the first category after training.

[0079] After inputting the detection image into the preset defect recognition model, the detection image can be calculated through convolution operation to calculate the similarity degree of each position with the model. The stronger the similarity of each position with the model, the greater the response. For an image with a high response, it can be determined as a defective image.

[0080] In this embodiment, the first category is used to determine whether the battery has defects. The first category can specifically be a defect category and a non-defect feature category. If the first category is a defect category, the battery has defects. If the first category is a non-defect category, the battery has no defects.

[0081] In this embodiment, through X-ray transmission and the preset defect recognition model, automatic analysis, determination, and output of the detection result of the defect morphology characteristics can be carried out, achieving high-efficiency, high-stability, and high-intelligence non-destructive testing, obtaining whether the structure and assembly of the battery are normal, whether there are physical damages, deformations, or other abnormalities in the battery case, checking the connection and welding status inside the battery to check for breaks, looseness, or poor connections; through X-ray imaging technology, the distribution of active substances (such as the positive electrode material) in the battery can be observed to judge the charge and discharge efficiency and capacity attenuation of the battery. For multi-layer stacked batteries, X-ray can help detect the connection situation between battery layers and the uniformity of the layer warning structure.

[0082] In some embodiments, by analyzing the element band data, the second category of the battery can be determined, which specifically includes:

[0083] S30: Obtain a target band in the elemental band data with an intensity greater than a preset value.

[0084] S31: Obtain the elemental types in the battery based on the range of the target band.

[0085] S32: Obtain the second category of the battery based on the elemental types of the battery.

[0086] As Figure 6 shown, Figure 6 in which, the abscissa is the characteristic band of the element, and the ordinate is the intensity of that band. If there is a corresponding detected element, there will be a higher intensity in the band of the corresponding element, otherwise not.

[0087] It can be understood that the elemental types of the battery in this embodiment can be regarded as the elemental types inside the battery or the elemental types of the battery cells inside the battery. Through the elemental types of the battery cells, the second category of the battery can be determined.

[0088] Thus, the target band can be determined through the intensity of the band. In practical applications, the peak area or the maximum value of the region can be calculated to determine whether it is greater than the preset value to determine the target band. For example, if the peak area of the region is greater than 100, it is regarded that the region is the target band. If the maximum value of the region is greater than 10, it is determined that the region is the target band. In this embodiment, the preset values corresponding to the peak area and the maximum value of the region can be different.

[0089] Figure 6 in which, the abscissa value corresponding to the black solid line is 630 - 640, which can be regarded as the target band, and its corresponding element is iron. Then, the inside of the battery corresponding to the black solid line includes iron element, while Figure 6 the intensity of the dotted solid line in [specific figure] at the abscissa value of 630 - 640 is not high. Thus, the inside of the battery corresponding to the dotted solid line does not include iron element.

[0090] Thus, the elemental types inside the battery can be obtained, and then the second category of the battery can be determined based on the elemental types. For example, lithium iron phosphate batteries contain iron and phosphorus elements, and ternary lithium batteries do not contain iron and phosphorus elements. If the detected elemental types of the battery include iron element and phosphorus element, it can be regarded that the second category of this battery is a lithium iron phosphate battery. If the detected elemental types of the battery do not include iron element and phosphorus element, it can be regarded that the second category of this battery is a ternary lithium battery. Thus, by detecting whether the inside of the battery contains iron element or phosphorus element, the second category of the battery can be classified.

[0091] Of course, the above-mentioned lithium iron phosphate battery and ternary lithium battery are only exemplary. In other embodiments, the second category may also include other batteries, which are not specifically limited herein. Different second categories correspond to different element types. Therefore, the second category of batteries is divided based on the element types.

[0092] Step S570: Use the first category and the second category as the target categories of the battery.

[0093] In this embodiment, the first category is used to determine whether the battery has defects, and the second category is used to determine the type of the battery. Therefore, the battery can be specifically classified, defective batteries can be identified, and batteries of the same type can be practically applied.

[0094] In this embodiment, the internal defects of the battery are detected by X-ray transmission, and the type of the battery is detected by irradiating with fluorescent X-rays. Therefore, it is possible to distinguish whether the battery has defects and confirm the specific category of the battery. In this process, the battery is not damaged and no manual intervention is required, with low cost and high efficiency.

[0095] Figure 7 It is a schematic structural diagram of a battery detection device shown in an embodiment of the present application. As Figure 7 shown, the battery detection device 700 includes: a detection image acquisition module 710, configured to receive the signal after the X-ray transmits through the battery to obtain a detection image; an element band data acquisition module 730, configured to receive the signal after the battery is irradiated with fluorescent X-rays to obtain the element band data inside the battery; a classification module 750, configured to obtain a first category representing the defect category of the battery based on the detection image, and obtain a second category representing the type of the battery based on the element band data; a target category acquisition module 770, configured to use the first category and the second category as the target categories of the battery.

[0096] In one implementable manner, the classification module 750 includes: a model acquisition unit, configured to acquire a preset defect recognition model; wherein, the preset defect recognition model is trained based on historical detection images, and the historical detection images are the images obtained after the X-ray transmits through the defective battery; a first classification unit, configured to input the detection image into the preset defect recognition model to obtain the first category.

[0097] In one implementable manner, before obtaining the preset defect recognition model, the method further includes: an initial model obtaining unit configured to obtain an initial defect recognition model; wherein the initial defect recognition model includes a convolutional network layer and a pooling layer; a model training unit configured to input historical detection images into the initial defect recognition model, so that the convolutional network layer extracts features from the historical detection images, and inputs the extracted features into the pooling layer to obtain a predicted value output by the pooling layer, and based on the predicted value, train the initial defect recognition model to obtain the preset defect recognition model.

[0098] In one implementable manner, the classification module 750 includes: a band determination unit configured to obtain a target band in the elemental band data with an intensity greater than a preset value; an element obtaining unit configured to obtain the types of elements in the battery based on the range of the target band; a second classification unit configured to obtain a second category of the battery based on the types of elements in the battery.

[0099] The battery detection device provided in this embodiment can be used to execute the above battery detection method, and its implementation principle and technical effects are similar, which will not be elaborated here in this embodiment.

[0100] Figure 8 is a block diagram of an electronic device shown according to an exemplary embodiment. Please refer to Figure 8 , the electronic device 800 may include: a processor 81 and a memory 82, wherein the processor 81 and the memory 82 can communicate; exemplarily, the processor 81 and the memory 82 communicate through a communication bus 83, the memory 82 is used to store instructions, and the processor 81 is used to call the instructions in the memory, so that the electronic device executes the battery detection method shown in any of the above embodiments.

[0101] It can be understood that the processor 81 may be Figure 1 the controller in

[0102] or a part of the structure in the controller. The above-mentioned processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in combination with the present application can be directly embodied as being executed by a hardware processor, or executed by a combination of hardware and software modules in the processor.

[0103] The present application provides a computer-readable storage medium, on which computer-executable instructions are stored; when the computer-executable instructions are executed by a processor, they are used to implement the battery detection method according to any of the above embodiments.

[0104] An embodiment of the present application provides a computer program product, the computer program product includes a computer program, and when the computer program is executed by a processor, the computer is caused to execute the above battery detection method.

[0105] Those skilled in the art will readily conceive of other embodiments of the present application after considering the specification and practicing the utility model disclosed herein. The present application is intended to cover any variations, uses, or adaptations of the present application, which follow the general principles of the present application and include known common knowledge or conventional technical means in the technical field not disclosed in the present application. The specification and embodiments are only regarded as exemplary, and the true scope and spirit of the present application are pointed out by the following claims.

[0106] It should be understood that the present application is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present application is only limited by the appended claims.

Claims

1. A battery detection system, characterized in that, Including: A conveyor belt, an X-ray generating device, an X-ray receiver, a fluorescent X-ray generating device, a fluorescent X-ray receiving device, and a controller; wherein, An X-ray generating device, a fluorescent X-ray generating device, and a fluorescent X-ray receiving device are arranged above the conveyor belt, and an X-ray receiver is arranged at a position opposite to the X-ray generating device below the conveyor belt. The area between the X-ray generating device and the X-ray receiver forms a detection area; The fluorescent X-ray generating device and the fluorescent X-ray receiving device are located on both sides of the detection area; The battery is transported to the detection area through the conveyor belt. The X-ray emitted by the X-ray generating device penetrates into the battery and then enters the X-ray receiver; the fluorescent X-ray emitted by the fluorescent X-ray generating device irradiates the battery and is reflected into the fluorescent X-ray receiving device; The controller is connected to the X-ray receiver and the fluorescent X-ray receiving device, and is used for detecting the battery according to the data received by the X-ray receiver and the fluorescent X-ray receiving device.

2. The battery detection system according to claim 1, wherein The angle between the fluorescent X-ray generating device and the conveyor belt is 100°-170°.

3. The battery detection system according to claim 2, wherein The angle between the fluorescent X-ray receiving device and the conveyor belt is 10°-80°.

4. The battery detection system according to claim 1, wherein The number of the X-ray generating device and the X-ray receiver is one or more.

5. The battery detection system according to claim 1, wherein, A sensor is arranged at the edge of the detection area.

6. The battery detection system according to claim 5, characterized in that The sensor is a pressure sensor, a laser sensor, or an infrared sensor.

7. The battery detection system according to claim 1, wherein The battery detection system further includes a collimator, and the collimator is arranged at the X-ray emitting port of the X-ray generating device.

8. The battery detection system according to claim 7, characterized in that, The collimator is cylindrical.

9. The battery detection system according to claim 1, wherein The battery detection system may further include a classification structure. The classification structure includes a plurality of sub-conveyor belts, and each sub-conveyor belt corresponds to a target category of a battery; each sub-conveyor belt is connected to the conveyor belt, and a classifier is arranged at the connection position between the sub-conveyor belt and the conveyor belt. When the battery passes through the detection area and the controller obtains the target category of the battery, the controller sends a control signal to the classifier, and the classifier controls the battery to enter the corresponding sub-conveyor belt.

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