A method and system for testing new energy battery packs

Abstract

This invention provides a method and system for detecting new energy battery packs. The method includes: when the battery pack is detected in a target detection area in real time, performing a full scan of the battery pack using a preset binocular vision system to detect several target feature points corresponding to the battery pack in real time; acquiring corresponding ultrasonic signals at each target feature point in real time using a preset ultrasonic composite probe, and generating corresponding time-spectrum diagrams and envelope signals based on the ultrasonic signals in real time; calculating the target confidence level corresponding to each target feature point in real time based on preset rules according to the time-spectrum diagrams and envelope signals, and determining in real time whether the target confidence level is greater than a preset confidence threshold; if the target confidence level is determined to be greater than the preset confidence threshold in real time, it is determined that the battery pack has no defects, and a corresponding detection report is generated. This invention can objectively and accurately complete the detection of battery packs, thereby improving detection efficiency.

Description

Technical Field

[0001] This invention relates to the field of new energy vehicle technology, and in particular to a method and system for testing new energy battery packs. Background Technology

[0002] With the advancement of technology and the rapid development of productivity, the production technology of new energy vehicles has become increasingly mature and has been widely adopted in people's daily lives, gaining their recognition and making life more convenient.

[0003] Among them, the battery pack is one of the core components of new energy electric vehicles, which is used to provide power to the drive motor and other components inside the vehicle. Based on this, in order to ensure the performance of the battery pack, existing technologies will conduct corresponding tests before the battery pack leaves the factory to ensure the quality of the battery pack.

[0004] Furthermore, existing technologies mostly rely on manual visual inspection or the use of corresponding inspection tools to inspect the appearance and internal structure of battery packs. However, the judgment results of this inspection method depend entirely on human subjective judgment, which can easily lead to missed or false detections, thereby reducing the inspection efficiency of battery packs. Summary of the Invention

[0005] Therefore, the purpose of this invention is to provide a method and system for testing new energy battery packs, so as to solve the problem that most of the existing technology relies on manual testing of battery packs, which easily leads to missed detections and false detections.

[0006] The first aspect of the present invention proposes:

[0007] A method for testing new energy battery packs, wherein the method includes:

[0008] When the battery pack is detected to be in the target detection area in real time, the battery pack is fully scanned by a preset binocular vision system to detect several target feature points corresponding to the battery pack in real time.

[0009] By using a preset ultrasonic composite probe, corresponding ultrasonic signals are collected in real time at each of the target feature points, and corresponding time-spectrum diagrams and envelope signals are generated in real time based on the ultrasonic signals.

[0010] Based on preset rules, the target confidence level corresponding to each target feature point is calculated in real time according to the time-frequency spectrum and the envelope signal, and it is determined in real time whether the target confidence level is greater than the preset confidence threshold.

[0011] If it is determined in real time that the target confidence level is greater than the preset confidence threshold, then it is determined that the battery pack has no defects and a corresponding inspection report is generated.

[0012] The beneficial effects of this invention are: by detecting in real time whether the battery pack falls into the detection area, it is possible to determine in real time whether scanning is required. Based on this, after the battery pack is scanned, the corresponding target feature points can be acquired synchronously. Based on this, the target feature points can accurately reflect whether the battery pack has defects. Thus, the time spectrum diagram and envelope signal of the current target feature points are acquired in real time, and the corresponding target confidence level is finally calculated. This enables the subsequent judgment to be completed objectively and accurately, thereby eliminating the need for manual intervention and improving the detection efficiency of the battery pack.

[0013] Furthermore, the step of performing a full scan of the battery pack using a preset binocular vision system to detect several target feature points corresponding to the battery pack in real time includes:

[0014] The preset binocular vision system acquires the three-dimensional dimensions corresponding to the battery pack in real time, and the preset three-dimensional program creates a target battery pack model that matches the battery pack in real time based on the three-dimensional dimensions.

[0015] The system detects the target model corresponding to the battery pack in real time using a preset database, and detects several target feature points corresponding to the battery pack in real time based on the target model and the target battery pack model. Each target feature point is unique.

[0016] Furthermore, the step of detecting several target feature points corresponding to the battery pack in real time based on the target model and the target battery pack model includes:

[0017] When the target model is obtained in real time, the corresponding components inside the battery pack are determined in real time based on the target model.

[0018] Within the target battery pack model, component models corresponding to each of the aforementioned components are created in real time, and corresponding target identifiers are added to each.

[0019] Based on the target identifier, several target feature points are detected in real time in the target battery pack model, and each target identifier is unique.

[0020] Furthermore, the step of detecting several target feature points in the target battery pack model in real time based on the target identifier includes:

[0021] When each target identifier is marked in real time, the corresponding fixed points and connection points generated by the corresponding component model inside the target battery pack model are detected according to each target identifier.

[0022] In the target battery pack model, the fixed points and the connection points are highlighted and set as the target feature points, and each fixed point and each connection point is unique.

[0023] Furthermore, the step of calculating the target confidence level corresponding to each target feature point in real time based on the time-spectrum diagram and the envelope signal according to preset rules includes:

[0024] When the time spectrum is acquired in real time, the time spectrum is parsed in real time to detect the corresponding spectrum curve contained in the time spectrum in real time.

[0025] The starting point and ending point of the spectrum curve are detected in real time, and several maximum points and several minimum points that appear sequentially in the spectrum curve within the range between the starting point and the ending point are detected in real time.

[0026] Several maximum points and several minimum points are set as feature values ​​corresponding to the time spectrum diagram, and the target confidence level corresponding to each target feature point is calculated in real time based on the feature values ​​and the envelope signal. Each maximum point and each minimum point is relatively unique.

[0027] Furthermore, the step of calculating the target confidence level corresponding to each target feature point in real time based on the feature value and the envelope signal includes:

[0028] When the envelope signal is acquired in real time, the envelope value corresponding to each target feature point is matched in real time from the envelope signal.

[0029] The corresponding target feature sequence is created in real time based on the feature value, and the corresponding target envelope sequence is created in real time based on the envelope value.

[0030] The target confidence level of the target feature point is generated based on the target feature sequence and the target envelope sequence, and each envelope value is unique.

[0031] Furthermore, the step of generating the target confidence score of the target feature points based on the target feature sequence and the target envelope sequence includes:

[0032] When the target feature sequence and the target envelope sequence are obtained respectively, the target feature sequence and the target envelope sequence are interleaved and fused to generate the corresponding target confidence sequence in real time.

[0033] The target confidence sequence is transformed in real time using a preset algorithm to generate the target confidence in real time, and the target confidence sequence is unique.

[0034] The second aspect of the present invention proposes:

[0035] A new energy battery pack testing system, wherein the system includes:

[0036] The scanning module is used to perform a full scan of the battery pack using a preset binocular vision system when the battery pack is detected to be located in the target detection area in real time, so as to detect a number of target feature points corresponding to the battery pack in real time.

[0037] The acquisition module is used to acquire the corresponding ultrasound signal at each of the target feature points in real time using a preset ultrasound composite probe, and generate the corresponding time-spectrum diagram and envelope signal in real time based on the ultrasound signal.

[0038] The calculation module is used to calculate the target confidence level corresponding to each target feature point in real time based on the time-frequency diagram and the envelope signal according to the preset rules, and to determine in real time whether the target confidence level is greater than the preset confidence level threshold.

[0039] The judgment module is used to determine that the battery pack has no defects if it is determined in real time that the target confidence level is greater than the preset confidence threshold, and to generate a corresponding inspection report.

[0040] Furthermore, the scanning module is specifically used for:

[0041] The preset binocular vision system acquires the three-dimensional dimensions corresponding to the battery pack in real time, and the preset three-dimensional program creates a target battery pack model that matches the battery pack in real time based on the three-dimensional dimensions.

[0042] The system detects the target model corresponding to the battery pack in real time using a preset database, and detects several target feature points corresponding to the battery pack in real time based on the target model and the target battery pack model. Each target feature point is unique.

[0043] Furthermore, the scanning module is specifically used for:

[0044] When the target model is obtained in real time, the corresponding components inside the battery pack are determined in real time based on the target model.

[0045] Within the target battery pack model, component models corresponding to each of the aforementioned components are created in real time, and corresponding target identifiers are added to each.

[0046] Based on the target identifier, several target feature points are detected in real time in the target battery pack model, and each target identifier is unique.

[0047] Furthermore, the scanning module is specifically used for:

[0048] When each target identifier is marked in real time, the corresponding fixed points and connection points generated by the corresponding component model inside the target battery pack model are detected according to each target identifier.

[0049] In the target battery pack model, the fixed points and the connection points are highlighted and set as the target feature points, and each fixed point and each connection point is unique.

[0050] Furthermore, the calculation module is specifically used for:

[0051] When the time spectrum is acquired in real time, the time spectrum is parsed in real time to detect the corresponding spectrum curve contained in the time spectrum in real time.

[0052] The starting point and ending point of the spectrum curve are detected in real time, and several maximum points and several minimum points that appear sequentially in the spectrum curve within the range between the starting point and the ending point are detected in real time.

[0053] Several maximum points and several minimum points are set as feature values ​​corresponding to the time spectrum diagram, and the target confidence level corresponding to each target feature point is calculated in real time based on the feature values ​​and the envelope signal. Each maximum point and each minimum point is relatively unique.

[0054] Furthermore, the calculation module is specifically used for:

[0055] When the envelope signal is acquired in real time, the envelope value corresponding to each target feature point is matched in real time from the envelope signal.

[0056] The corresponding target feature sequence is created in real time based on the feature value, and the corresponding target envelope sequence is created in real time based on the envelope value.

[0057] The target confidence level of the target feature point is generated based on the target feature sequence and the target envelope sequence, and each envelope value is unique.

[0058] Furthermore, the calculation module is specifically used for:

[0059] When the target feature sequence and the target envelope sequence are obtained respectively, the target feature sequence and the target envelope sequence are interleaved and fused to generate the corresponding target confidence sequence in real time.

[0060] The target confidence sequence is transformed in real time using a preset algorithm to generate the target confidence in real time, and the target confidence sequence is unique.

[0061] The third aspect of the present invention proposes:

[0062] A computer includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the new energy battery pack detection method described above.

[0063] The fourth aspect of the present invention proposes:

[0064] A readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the new energy battery pack detection method as described above.

[0065] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0066] Figure 1 This is a flowchart of the new energy battery pack testing method provided in the first embodiment of the present invention;

[0067] Figure 2 This is a structural block diagram of a new energy battery pack testing system provided in the third embodiment of the present invention.

[0068] The following detailed description, in conjunction with the accompanying drawings, will further illustrate the present invention. Detailed Implementation

[0069] To facilitate understanding of the present invention, a more complete description will be given below with reference to the accompanying drawings. Several embodiments of the invention are illustrated in the drawings. However, the invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.

[0070] It should be noted that when a component is said to be "fixed to" another component, it can be directly on the other component or there may be an intervening component. When a component is said to be "connected to" another component, it can be directly connected to the other component or there may be an intervening component. The terms "vertical," "horizontal," "left," "right," and similar expressions used in this document are for illustrative purposes only.

[0071] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0072] Please see Figure 1 The image shows a new energy battery pack testing method provided in the first embodiment of the present invention. The new energy battery pack testing method provided in this embodiment can objectively and accurately detect whether the battery pack meets the standards, and can also save manual intervention, thereby improving the testing efficiency of the battery pack.

[0073] Specifically, this embodiment provides:

[0074] A method for testing new energy battery packs, specifically including the following steps:

[0075] Step S10: When the battery pack is detected to be in the target detection area in real time, the battery pack is fully scanned by a preset binocular vision system to detect several target feature points corresponding to the battery pack in real time.

[0076] It should be noted that, in order to ensure the performance of the battery pack, existing technologies require structural testing of the entire battery pack before it leaves the factory to prevent structural defects. Therefore, to improve testing efficiency, this invention pre-sets a target detection area on the production line. It should be pointed out that a corresponding sensor is installed inside this target detection area. This sensor can detect in real time whether the battery pack has entered the target detection area. Specifically, if so, a pre-set binocular vision system is immediately activated, and the entire battery pack is immediately scanned using the existing binocular vision system. This system can detect several target feature points inside the battery pack in real time, i.e., locations prone to structural defects, to facilitate subsequent processing.

[0077] Step S20: Acquire corresponding ultrasonic signals at each target feature point in real time using a preset ultrasonic composite probe, and generate corresponding time-spectrum diagrams and envelope signals in real time based on the ultrasonic signals.

[0078] It should be noted that, in order to objectively and accurately determine whether structural defects exist at each target feature point, it is necessary to collect corresponding detection data in real time for subsequent judgment. Based on this, the present invention uses an existing ultrasonic composite probe to immediately collect data on each target feature point in real time, and can simultaneously acquire the required ultrasonic signals. It should also be pointed out that, in order to comprehensively analyze whether there are defects in the current battery pack, the current ultrasonic signal is further processed by decomposing it, and the corresponding time-spectrum diagram and envelope signal can be extracted for subsequent processing. Specifically, the present invention uses the existing DTW (Dynamic Programming) algorithm to decompose the current ultrasonic signal. During this process, the internal spectral and envelope information of the current ultrasonic signal can be parsed in real time, thereby generating the required time-spectrum diagram and envelope signal, enabling comprehensive analysis for subsequent processing.

[0079] Step S30: Based on preset rules, calculate the target confidence level corresponding to each target feature point in real time according to the time spectrum and the envelope signal, and determine in real time whether the target confidence level is greater than the preset confidence level threshold.

[0080] It should be noted that after obtaining the required time-spectrum and envelope signal in real time through the above steps, corresponding calculations can be performed. Specifically, this invention can immediately calculate the target confidence level corresponding to each target feature point in real time according to pre-set calculation rules, i.e., the probability that the current target feature point has a structural defect. Based on this, it is necessary to determine in real time whether the target confidence level is greater than a pre-set confidence threshold for subsequent processing. It should be pointed out that the higher the target confidence level, the lower the probability of a structural defect occurring; conversely, the lower the target confidence level, the higher the probability of a structural defect occurring.

[0081] Step S40: If it is determined in real time that the target confidence level is greater than the preset confidence threshold, then it is determined that the battery pack has no defects and a corresponding inspection report is generated.

[0082] It should be noted that if the current target confidence level is determined to be greater than the preset confidence threshold in real time, it can be directly determined that the target feature point corresponding to the current target confidence level is free of defects. Conversely, if the current target confidence level is less than the preset confidence threshold, it can be directly determined that the current target feature point has a defect, and corresponding return-to-factory processing is required. This allows for objective and accurate testing of each battery pack, thereby improving the testing efficiency of the battery pack. It should also be pointed out that the preset confidence threshold set in this invention can be 90% or 95%, etc., and can be changed according to specific circumstances.

[0083] Second Embodiment

[0084] Furthermore, the step of performing a full scan of the battery pack using a preset binocular vision system to detect several target feature points corresponding to the battery pack in real time includes:

[0085] The preset binocular vision system acquires the three-dimensional dimensions corresponding to the battery pack in real time, and the preset three-dimensional program creates a target battery pack model that matches the battery pack in real time based on the three-dimensional dimensions.

[0086] The system detects the target model corresponding to the battery pack in real time using a preset database, and detects several target feature points corresponding to the battery pack in real time based on the target model and the target battery pack model. Each target feature point is unique.

[0087] It should be noted that, in order to objectively and accurately analyze the target feature points corresponding to the current battery pack, this invention specifically acquires the three-dimensional dimensions corresponding to the current battery pack in real time through the aforementioned binocular vision system. Simultaneously, existing 3D programs such as UG or SolidWorks can create a target battery pack model adapted to the current battery pack based on these dimensions. Therefore, to facilitate subsequent judgment, it is also necessary to detect the target model corresponding to the current battery pack in real time from the existing database. It should be pointed out that there are numerous existing battery pack models, and the structure of each model is not entirely the same. Therefore, by detecting the target model of the battery pack in real time, subsequent detection can be accurately completed for subsequent processing.

[0088] Furthermore, the step of detecting several target feature points corresponding to the battery pack in real time based on the target model and the target battery pack model includes:

[0089] When the target model is obtained in real time, the corresponding components inside the battery pack are determined in real time based on the target model.

[0090] Within the target battery pack model, component models corresponding to each of the aforementioned components are created in real time, and corresponding target identifiers are added to each.

[0091] Based on the target identifier, several target feature points are detected in real time in the target battery pack model, and each target identifier is unique.

[0092] It should be noted that after the target model of the battery pack is determined in real time, the existing database can be used to detect the internal components of the current battery pack. Similarly, in order to realistically simulate the current battery pack, component models corresponding to each component will be created in real time within the target battery pack model. To facilitate subsequent differentiation, corresponding target identifiers will be added to each component for subsequent processing.

[0093] Furthermore, the step of detecting several target feature points in the target battery pack model in real time based on the target identifier includes:

[0094] When each target identifier is marked in real time, the corresponding fixed points and connection points generated by the corresponding component model inside the target battery pack model are detected according to each target identifier.

[0095] In the target battery pack model, the fixed points and the connection points are highlighted and set as the target feature points, and each fixed point and each connection point is unique.

[0096] It should be noted that after determining the target identifier of each component model in real time through the above steps, the fixed points and connection points between the current component models can be intuitively detected inside the current target battery pack model. It should be noted that fixed points and connection points are the most likely locations for defects. Based on this, the present invention will highlight the current fixed points and connection points and set them as the required target feature points to facilitate subsequent processing.

[0097] Furthermore, the step of calculating the target confidence level corresponding to each target feature point in real time based on the time-spectrum diagram and the envelope signal according to preset rules includes:

[0098] When the time spectrum is acquired in real time, the time spectrum is parsed in real time to detect the corresponding spectrum curve contained in the time spectrum in real time.

[0099] The starting point and ending point of the spectrum curve are detected in real time, and several maximum points and several minimum points that appear sequentially in the spectrum curve within the range between the starting point and the ending point are detected in real time.

[0100] Several maximum points and several minimum points are set as feature values ​​corresponding to the time spectrum diagram, and the target confidence level corresponding to each target feature point is calculated in real time based on the feature values ​​and the envelope signal. Each maximum point and each minimum point is relatively unique.

[0101] It should be noted that after determining each target feature point and its corresponding time-spectrum and envelope signal in real time through the above steps, the final calculation process can be completed. Specifically, this invention first analyzes the spectrum curve contained within the current time-spectrum. It should be pointed out that the spectrum curve has a certain range and can detect several maxima and minima that appear sequentially within this range in real time. It should be noted that the current maxima and minima can directly reflect the smoothness of the current target feature point, that is, they can reflect the possibility of defects, and are immediately set as the required feature values. Then, by combining the feature values ​​with the current envelope signal, the required target confidence can be calculated for subsequent processing.

[0102] Furthermore, the step of calculating the target confidence level corresponding to each target feature point in real time based on the feature value and the envelope signal includes:

[0103] When the envelope signal is acquired in real time, the envelope value corresponding to each target feature point is matched in real time from the envelope signal.

[0104] The corresponding target feature sequence is created in real time based on the feature value, and the corresponding target envelope sequence is created in real time based on the envelope value.

[0105] The target confidence level of the target feature point is generated based on the target feature sequence and the target envelope sequence, and each envelope value is unique.

[0106] It should be noted that the magnitude of the aforementioned envelope signal can intuitively reflect the type of defect appearing at the current target feature point. Therefore, to facilitate subsequent comprehensive analysis, this invention will also match the envelope value corresponding to each target feature point in real time within the current envelope signal. Based on this, a corresponding target feature sequence can be created in real time based on each current feature value. Similarly, a corresponding target envelope sequence can be created in real time based on each current envelope value for subsequent processing. It should be pointed out that the types of defects appearing at the aforementioned target feature points can include fractures, gaps, and detachments, thus enabling subsequent return to the factory for repair and processing.

[0107] Furthermore, the step of generating the target confidence score of the target feature points based on the target feature sequence and the target envelope sequence includes:

[0108] When the target feature sequence and the target envelope sequence are obtained respectively, the target feature sequence and the target envelope sequence are interleaved and fused to generate the corresponding target confidence sequence in real time.

[0109] The target confidence sequence is transformed in real time using a preset algorithm to generate the target confidence in real time, and the target confidence sequence is unique.

[0110] It should be noted that after obtaining the required target feature sequence and target envelope sequence in real time through the above steps, the current target feature sequence and target envelope sequence can be interleaved and fused using the existing interleaving fusion algorithm, and can be fused into a whole, that is, the required target confidence sequence is generated in real time. Based on this, the current target confidence sequence is finally transformed in real time using the existing DTW algorithm, which can generate the above-mentioned target confidence, thereby enabling the objective and accurate detection of various types of battery packs, while eliminating the need for manual intervention and improving the detection efficiency of battery packs.

[0111] Please see Figure 2 The third embodiment of the present invention provides:

[0112] A new energy battery pack testing system, wherein the system includes:

[0113] The scanning module is used to perform a full scan of the battery pack using a preset binocular vision system when the battery pack is detected to be located in the target detection area in real time, so as to detect a number of target feature points corresponding to the battery pack in real time.

[0114] The acquisition module is used to acquire the corresponding ultrasound signal at each of the target feature points in real time using a preset ultrasound composite probe, and generate the corresponding time-spectrum diagram and envelope signal in real time based on the ultrasound signal.

[0115] The calculation module is used to calculate the target confidence level corresponding to each target feature point in real time based on the time-frequency diagram and the envelope signal according to the preset rules, and to determine in real time whether the target confidence level is greater than the preset confidence level threshold.

[0116] The judgment module is used to determine that the battery pack has no defects if it is determined in real time that the target confidence level is greater than the preset confidence threshold, and to generate a corresponding inspection report.

[0117] Furthermore, the scanning module is specifically used for:

[0118] The preset binocular vision system acquires the three-dimensional dimensions corresponding to the battery pack in real time, and the preset three-dimensional program creates a target battery pack model that matches the battery pack in real time based on the three-dimensional dimensions.

[0119] The system detects the target model corresponding to the battery pack in real time using a preset database, and detects several target feature points corresponding to the battery pack in real time based on the target model and the target battery pack model. Each target feature point is unique.

[0120] Furthermore, the scanning module is specifically used for:

[0121] When the target model is obtained in real time, the corresponding components inside the battery pack are determined in real time based on the target model.

[0122] Within the target battery pack model, component models corresponding to each of the aforementioned components are created in real time, and corresponding target identifiers are added to each.

[0123] Based on the target identifier, several target feature points are detected in real time in the target battery pack model, and each target identifier is unique.

[0124] Furthermore, the scanning module is specifically used for:

[0125] When each target identifier is marked in real time, the corresponding fixed points and connection points generated by the corresponding component model inside the target battery pack model are detected according to each target identifier.

[0126] In the target battery pack model, the fixed points and the connection points are highlighted and set as the target feature points, and each fixed point and each connection point is unique.

[0127] Furthermore, the calculation module is specifically used for:

[0128] When the time spectrum is acquired in real time, the time spectrum is parsed in real time to detect the corresponding spectrum curve contained in the time spectrum in real time.

[0129] The starting point and ending point of the spectrum curve are detected in real time, and several maximum points and several minimum points that appear sequentially in the spectrum curve within the range between the starting point and the ending point are detected in real time.

[0130] Several maximum points and several minimum points are set as feature values ​​corresponding to the time spectrum diagram, and the target confidence level corresponding to each target feature point is calculated in real time based on the feature values ​​and the envelope signal. Each maximum point and each minimum point is relatively unique.

[0131] Furthermore, the calculation module is specifically used for:

[0132] When the envelope signal is acquired in real time, the envelope value corresponding to each target feature point is matched in real time from the envelope signal.

[0133] The corresponding target feature sequence is created in real time based on the feature value, and the corresponding target envelope sequence is created in real time based on the envelope value.

[0134] The target confidence level of the target feature point is generated based on the target feature sequence and the target envelope sequence, and each envelope value is unique.

[0135] Furthermore, the calculation module is specifically used for:

[0136] When the target feature sequence and the target envelope sequence are obtained respectively, the target feature sequence and the target envelope sequence are interleaved and fused to generate the corresponding target confidence sequence in real time.

[0137] The target confidence sequence is transformed in real time using a preset algorithm to generate the target confidence in real time, and the target confidence sequence is unique.

[0138] The fourth embodiment of the present invention provides a computer, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the new energy battery pack detection method described above.

[0139] The fifth embodiment of the present invention provides a readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the new energy battery pack detection method as described above.

[0140] In summary, the new energy battery pack testing method and system provided by the above embodiments of the present invention can objectively and accurately complete the testing of battery packs, while eliminating the need for manual intervention, thereby improving the testing efficiency of battery packs.

[0141] It should be noted that the above modules can be functional modules or program modules, and can be implemented through software or hardware. For modules implemented through hardware, the above modules can reside in the same processor; or the above modules can be located in different processors in any combination.

[0142] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0143] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0144] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0145] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0146] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the appended claims.

Claims

1. A method for testing new energy battery packs, characterized in that, The method includes: When the battery pack is detected to be in the target detection area in real time, the battery pack is fully scanned by a preset binocular vision system to detect several target feature points corresponding to the battery pack in real time. By using a preset ultrasonic composite probe, corresponding ultrasonic signals are collected in real time at each of the target feature points, and corresponding time-spectrum diagrams and envelope signals are generated in real time based on the ultrasonic signals. Based on preset rules, the target confidence level corresponding to each target feature point is calculated in real time according to the time-frequency spectrum and the envelope signal, and it is determined in real time whether the target confidence level is greater than the preset confidence threshold. If it is determined in real time that the target confidence level is greater than the preset confidence threshold, then it is determined that the battery pack has no defects and a corresponding inspection report is generated. The step of performing a full scan of the battery pack using a preset binocular vision system to detect several target feature points corresponding to the battery pack in real time includes: The preset binocular vision system acquires the three-dimensional dimensions corresponding to the battery pack in real time, and the preset three-dimensional program creates a target battery pack model that matches the battery pack in real time based on the three-dimensional dimensions. The system detects the target model corresponding to the battery pack in real time using a preset database, and detects several target feature points corresponding to the battery pack in real time based on the target model and the target battery pack model. Each target feature point is unique. The step of detecting several target feature points corresponding to the battery pack in real time based on the target model and the target battery pack model includes: When the target model is obtained in real time, the corresponding components inside the battery pack are determined in real time based on the target model. Within the target battery pack model, component models corresponding to each of the aforementioned components are created in real time, and corresponding target identifiers are added to each. Based on the target identifier, several target feature points are detected in real time in the target battery pack model, and each target identifier is unique; The step of detecting several target feature points in the target battery pack model in real time based on the target identifier includes: When each target identifier is marked in real time, the corresponding fixed points and connection points generated by the corresponding component model inside the target battery pack model are detected according to each target identifier. In the target battery pack model, the fixed points and the connection points are highlighted and set as the target feature points, and each fixed point and each connection point is unique.

2. The new energy battery pack testing method according to claim 1, characterized in that: The step of calculating the target confidence level corresponding to each target feature point in real time based on the time-spectrum diagram and the envelope signal according to preset rules includes: When the time spectrum is acquired in real time, the time spectrum is parsed in real time to detect the corresponding spectrum curve contained in the time spectrum in real time. The starting point and ending point of the spectrum curve are detected in real time, and several maximum points and several minimum points that appear sequentially in the spectrum curve within the range between the starting point and the ending point are detected in real time. Several maximum points and several minimum points are set as feature values ​​corresponding to the time spectrum diagram, and the target confidence level corresponding to each target feature point is calculated in real time based on the feature values ​​and the envelope signal. Each maximum point and each minimum point is relatively unique.

3. The new energy battery pack testing method according to claim 2, characterized in that: The step of calculating the target confidence level corresponding to each target feature point in real time based on the feature value and the envelope signal includes: When the envelope signal is acquired in real time, the envelope value corresponding to each target feature point is matched in real time from the envelope signal. The corresponding target feature sequence is created in real time based on the feature value, and the corresponding target envelope sequence is created in real time based on the envelope value; The target confidence level of the target feature point is generated based on the target feature sequence and the target envelope sequence, and each envelope value is unique.

4. The new energy battery pack testing method according to claim 3, characterized in that: The step of generating the target confidence score of the target feature points based on the target feature sequence and the corresponding target envelope sequence includes: When the target feature sequence and the target envelope sequence are obtained respectively, the target feature sequence and the target envelope sequence are interleaved and fused to generate the corresponding target confidence sequence in real time. The target confidence sequence is transformed in real time using a preset algorithm to generate the target confidence in real time, and the target confidence sequence is unique.

5. A new energy battery pack testing system, characterized in that, The system for implementing the new energy battery pack testing method as described in any one of claims 1 to 4 includes: The scanning module is used to perform a full scan of the battery pack using a preset binocular vision system when the battery pack is detected to be in the target detection area in real time, so as to detect a number of target feature points corresponding to the battery pack in real time. The acquisition module is used to acquire the corresponding ultrasonic signal at each of the target feature points in real time using a preset ultrasonic composite probe, and to generate the corresponding time-spectrum diagram and envelope signal in real time based on the ultrasonic signal. The calculation module is used to calculate the target confidence level corresponding to each target feature point in real time based on the time-frequency diagram and the envelope signal according to the preset rules, and to determine in real time whether the target confidence level is greater than the preset confidence level threshold. The judgment module is used to determine that the battery pack has no defects if it is determined in real time that the target confidence level is greater than the preset confidence threshold, and to generate a corresponding inspection report.

6. A computer comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the new energy battery pack detection method as described in any one of claims 1 to 4.

7. A readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the new energy battery pack detection method as described in any one of claims 1 to 4.

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