A plastic packaging quality analysis method, system, electronic device and medium

Abstract

The present invention provides a plastic packaging quality analysis method, system, electronic device and medium, which relate to the technical field of plastic packaging. The method comprises using a DTW algorithm to process ultrasonic reflection data of multiple beverage plastic packages to be analyzed and ultrasonic reflection data of qualified beverage plastic packages to determine multiple beverage plastic packages to be panoramically detected; using a panoramic detection model based on panoramic videos of multiple beverage plastic packages to be panoramically detected to determine information of each beverage plastic package to be panoramically detected; constructing two nodes and an edge between the two nodes; and processing two nodes and an edge between the two nodes based on a graph convolutional network to determine whether the beverage plastic package to be panoramically detected is damaged. The method can quickly and accurately detect whether the beverage plastic package is damaged.

Description

Technical Field

[0001] The present invention relates to the technical field of plastic packaging, and in particular to a quality analysis method, system, electronic equipment and medium for plastic packaging. Background Art

[0002] In the modern beverage production process, ensuring product quality is crucial. To achieve this goal, manufacturers need to adopt efficient detection methods to identify and eliminate possible defective products. In this process, detecting the integrity of beverage plastic packaging is a key step in ensuring product quality. Traditional detection methods often rely on manual visual inspection, which is inefficient and easily affected by subjective judgment.

[0003] Therefore, how to quickly and accurately detect whether the plastic packaging of beverages is damaged is a problem that needs to be solved urgently. Summary of the invention

[0004] The main technical problem solved by the present invention is how to quickly and accurately detect whether a beverage plastic package is damaged.

[0005] According to a first aspect, the present invention provides a method for analyzing the quality of plastic packaging, comprising: obtaining ultrasonic reflection data of multiple beverage plastic packages to be analyzed and ultrasonic reflection data of qualified beverage plastic packages; using a DTW algorithm to process the ultrasonic reflection data of the multiple beverage plastic packages to be analyzed and the ultrasonic reflection data of the qualified beverage plastic packages to determine multiple beverage plastic packages to be panoramically inspected; obtaining panoramic videos of the multiple beverage plastic packages to be panoramically inspected; and determining whether the beverage plastic packages to be panoramically inspected are damaged based on the panoramic videos of the multiple beverage plastic packages to be panoramically inspected.

[0006] In a possible implementation, the determining whether the plastic packaging of beverages to be panoramically inspected is damaged based on the panoramic videos of the multiple plastic packaging of beverages to be panoramically inspected includes: using a panoramic detection model to determine the information of each plastic packaging of beverages to be panoramically inspected based on the panoramic videos of the multiple plastic packaging of beverages to be panoramically inspected, the information of each plastic packaging of beverages to be panoramically inspected includes lid information, bottle body information, liquid information, and matching information; constructing two nodes and an edge between the two nodes, the two nodes include a lid node and a bottle body node, the node feature of the lid node includes the lid information, the node feature of the bottle body node includes the bottle body information and the liquid information, and the edge feature of an edge between the two nodes includes the matching information; processing the two nodes and an edge between the two nodes based on a graph convolutional network to determine whether the plastic packaging of beverages to be panoramically inspected is damaged.

[0007] In one possible implementation, the lid information includes a panoramic image, shape, flatness, and transparency of the lid; the bottle body information includes a panoramic image, shape, flatness, and transparency of the bottle body; the liquid information includes the color and fluidity of the liquid beverage; and the matching information includes the shortest distance between the lid and the bottle body, the longest distance between the lid and the bottle body, and the matching degree between the lid and the bottle body.

[0008] In one possible implementation, the use of the DTW algorithm to process the ultrasonic reflection data of the multiple beverage plastic packages to be analyzed and the ultrasonic reflection data of the qualified beverage plastic packages to determine the multiple beverage plastic packages to be panoramically detected includes: determining the similarity between the ultrasonic reflection data of each beverage plastic package to be analyzed and the ultrasonic reflection data of the qualified beverage plastic package based on the DTW algorithm; and taking the multiple beverage plastic packages corresponding to the similarity being less than a similarity threshold as the multiple beverage plastic packages to be panoramically detected.

[0009] In a possible implementation, the panoramic videos of the multiple beverage plastic packages to be panoramically inspected are synthesized by shooting with a high-definition camera.

[0010] According to a second aspect, the present invention provides a plastic packaging quality analysis system, comprising: a first acquisition module, for acquiring ultrasonic reflection data of a plurality of beverage plastic packages to be analyzed and ultrasonic reflection data of qualified beverage plastic packages;

[0011] A processing module, used for processing the ultrasonic reflection data of the plurality of beverage plastic packages to be analyzed and the ultrasonic reflection data of the qualified beverage plastic packages using a DTW algorithm to determine a plurality of beverage plastic packages to be fully inspected;

[0012] A second acquisition module is used to acquire panoramic videos of the plurality of beverage plastic packages to be panoramically inspected;

[0013] A damage determination module is used to determine whether the beverage plastic package to be panoramically inspected is damaged based on the panoramic videos of the multiple beverage plastic packages to be panoramically inspected.

[0014] In a possible implementation manner, the damage determination module is further configured to:

[0015] Determine information of each plastic beverage package to be panoramically detected using a panoramic detection model based on the panoramic videos of the plurality of plastic beverage packages to be panoramically detected, wherein the information of each plastic beverage package to be panoramically detected includes lid information, bottle body information, liquid information, and matching information;

[0016] Constructing two nodes and an edge between the two nodes, the two nodes include a lid node and a bottle body node, the node feature of the lid node includes the lid information, the node feature of the bottle body node includes the bottle body information and the liquid information, and the edge feature of the edge between the two nodes includes the matching information;

[0017] The two nodes and an edge between the two nodes are processed based on a graph convolutional network to determine whether the beverage plastic package to be panoramically inspected is damaged.

[0018] In one possible implementation, the lid information includes a panoramic image, shape, flatness, and transparency of the lid; the bottle body information includes a panoramic image, shape, flatness, and transparency of the bottle body; the liquid information includes the color and fluidity of the liquid beverage; and the matching information includes the shortest distance between the lid and the bottle body, the longest distance between the lid and the bottle body, and the matching degree between the lid and the bottle body.

[0019] According to a third aspect, an embodiment of the present invention provides an electronic device, comprising: a processor; a memory; and a computer program; wherein the computer program is stored in the memory and is configured to be executed by the processor to implement a method as described above, the method comprising: obtaining ultrasonic reflection data of multiple beverage plastic packages to be analyzed and ultrasonic reflection data of qualified beverage plastic packages; using a DTW algorithm to process the ultrasonic reflection data of the multiple beverage plastic packages to be analyzed and the ultrasonic reflection data of the qualified beverage plastic packages to determine multiple beverage plastic packages to be panoramically detected; obtaining panoramic videos of the multiple beverage plastic packages to be panoramically detected; and determining whether the beverage plastic packages to be panoramically detected are damaged based on the panoramic videos of the multiple beverage plastic packages to be panoramically detected.

[0020] According to the fourth aspect, the present embodiment provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the aforementioned plastic packaging quality analysis method, the method comprising: obtaining ultrasonic reflection data of multiple beverage plastic packages to be analyzed and ultrasonic reflection data of qualified beverage plastic packages; using a DTW algorithm to process the ultrasonic reflection data of the multiple beverage plastic packages to be analyzed and the ultrasonic reflection data of the qualified beverage plastic packages to determine multiple beverage plastic packages to be panoramically inspected; obtaining panoramic videos of the multiple beverage plastic packages to be panoramically inspected; and determining whether the beverage plastic packages to be panoramically inspected are damaged based on the panoramic videos of the multiple beverage plastic packages to be panoramically inspected.

[0021] The present invention provides a plastic packaging quality analysis method, system, electronic device and medium. The method includes obtaining ultrasonic reflection data of multiple beverage plastic packages to be analyzed and ultrasonic reflection data of qualified beverage plastic packages; using the DTW algorithm to process the ultrasonic reflection data of the multiple beverage plastic packages to be analyzed and the ultrasonic reflection data of the qualified beverage plastic packages to determine multiple beverage plastic packages to be panoramically inspected; obtaining panoramic videos of the multiple beverage plastic packages to be panoramically inspected; and determining whether the beverage plastic packages to be panoramically inspected are damaged based on the panoramic videos of the multiple beverage plastic packages to be panoramically inspected. The method can quickly and accurately detect whether the beverage plastic packages are damaged. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 A schematic flow chart of a plastic packaging quality analysis method provided by an embodiment of the present invention;

[0023] Figure 2 A schematic diagram of a process for determining whether a beverage plastic package to be inspected is damaged provided by an embodiment of the present invention;

[0024] Figure 3 A schematic diagram of a plastic packaging quality analysis system provided by an embodiment of the present invention;

[0025] Figure 4 A schematic diagram of an electronic device provided by an embodiment of the present invention;

[0026] Figure 5 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0027] The present invention is further described in detail below by specific embodiments in conjunction with the accompanying drawings. Wherein similar elements in different embodiments adopt associated similar element numbers. In the following embodiments, many detailed descriptions are for making the present invention better understood. However, those skilled in the art can easily recognize that some features can be omitted in different situations, or can be replaced by other elements, materials, methods. In some cases, some operations related to the present invention are not shown or described in the specification, this is to avoid the core part of the present invention being overwhelmed by too much description, and for those skilled in the art, it is not necessary to describe these related operations in detail, and they can fully understand the related operations according to the description in the specification and the general technical knowledge in the art.

[0028] In addition, the features, operations or characteristics described in the specification can be combined in any appropriate manner to form various implementations. At the same time, the steps or actions in the method description can also be interchanged or adjusted in a manner that is obvious to those skilled in the art. Therefore, the various sequences in the specification and the drawings are only for the purpose of clearly describing a certain embodiment and are not meant to be a required sequence, unless otherwise specified that a certain sequence must be followed.

[0029] The serial numbers assigned to the components herein, such as "first", "second", etc., are only used to distinguish the objects described and do not have any order or technical meaning. The "connection" and "coupling" mentioned in the present invention include direct and indirect connections (couplings) unless otherwise specified.

[0030] In an embodiment of the present invention, there is provided Figure 1 A plastic packaging quality analysis method is shown, the plastic packaging quality analysis method comprises steps S1 to S4:

[0031] Step S1, obtaining ultrasonic reflection data of a plurality of beverage plastic packages to be analyzed and ultrasonic reflection data of qualified beverage plastic packages.

[0032] The beverage plastic packaging to be analyzed refers to the liquid beverage plastic packaging that needs to be tested, and the beverage plastic packaging to be analyzed may have problems such as damage.

[0033] Qualified beverage plastic packaging refers to liquid beverage plastic packaging that is not damaged or deformed. Qualified beverage plastic packaging includes the lid and bottle body.

[0034] In some embodiments, ultrasonic detection equipment may emit ultrasonic waves to beverage plastic packages and receive echo signals to obtain ultrasonic reflection data of multiple beverage plastic packages to be analyzed and ultrasonic reflection data of qualified beverage plastic packages.

[0035] Step S2: using a DTW algorithm to process the ultrasonic reflection data of the plurality of beverage plastic packages to be analyzed and the ultrasonic reflection data of the qualified beverage plastic packages to determine a plurality of beverage plastic packages to be fully inspected.

[0036] The beverage plastic packages to be fully inspected refer to beverage plastic packages that are screened from the multiple beverage plastic packages to be analyzed and that need to be further inspected.

[0037] The DTW algorithm is also called the Dynamic Time Warping (DTW) algorithm. The DTW algorithm is an algorithm used to measure the similarity between two sequences, and is particularly suitable for time series data. The DTW algorithm can handle the situation where the lengths of the two sequences are inconsistent, and find the best matching path between the two sequences through non-linear alignment, thereby calculating the similarity between them.

[0038] In some embodiments, the similarity between the ultrasonic reflection data of each beverage plastic package to be analyzed and the ultrasonic reflection data of the qualified beverage plastic package is determined based on the DTW algorithm; multiple beverage plastic packages corresponding to similarities less than a similarity threshold are used as multiple beverage plastic packages to be panoramically detected. The similarity threshold is artificially set in advance.

[0039] Step S3, obtaining panoramic videos of the plurality of beverage plastic packages to be panoramically inspected.

[0040] The panoramic videos of the multiple beverage plastic packages to be inspected refer to continuous videos that can capture the complete scene of the beverage plastic packages to be inspected. The panoramic videos of the multiple beverage plastic packages to be inspected include shots of the liquid beverage plastic packages observed from different angles, and can show the appearance, status and surrounding environment of the packages.

[0041] Step S4: determining whether the beverage plastic package to be panoramically inspected is damaged based on the panoramic videos of the plurality of beverage plastic packages to be panoramically inspected.

[0042] In some embodiments, Figure 2 A schematic diagram of a process for determining whether a beverage plastic package to be inspected is damaged is provided in an embodiment of the present invention. The process for determining whether a beverage plastic package to be inspected is damaged comprises steps S21 to S23:

[0043] Step S21, based on the panoramic videos of the multiple beverage plastic packages to be panoramically detected, use a panoramic detection model to determine the information of each beverage plastic package to be panoramically detected, wherein the information of each beverage plastic package to be panoramically detected includes lid information, bottle body information, liquid information, and matching information.

[0044] Based on the panoramic videos of the multiple beverage plastic packages to be panoramically inspected, a panoramic detection model is used to determine the information of each beverage plastic package to be panoramically inspected, wherein the information of each beverage plastic package to be panoramically inspected includes lid information, bottle body information, liquid information, and matching information. The lid information includes a panoramic image, shape, flatness, and transparency of the lid; the bottle body information includes a panoramic image, shape, flatness, and transparency of the bottle body; the liquid information includes the color and fluidity of the liquid beverage; and the matching information includes the shortest distance between the lid and the bottle body, the longest distance between the lid and the bottle body, and the matching degree between the lid and the bottle body.

[0045] The panoramic detection model is a recurrent neural network, the input of the panoramic detection model is the panoramic videos of the multiple beverage plastic packages to be panoramically detected, the output of the panoramic detection model is the information of each beverage plastic package to be panoramically detected, the information of each beverage plastic package to be panoramically detected includes lid information, bottle body information, liquid information, and matching information, the lid information includes the panoramic image, shape, flatness, and transparency of the lid, the bottle body information includes the panoramic image, shape, flatness, and transparency of the bottle body, the liquid information includes the color and fluidity of the liquid beverage, and the matching information includes the shortest distance between the lid and the bottle body, the longest distance between the lid and the bottle body, and the matching degree between the lid and the bottle body.

[0046] Recurrent neural networks are particularly suitable for processing data with time series characteristics because they can recurse in the direction of the sequence's evolution and capture dynamic information in the time dimension. In panoramic videos, each frame is a point in time, and recurrent neural networks can effectively process these consecutive frames and extract temporal features in the video. Recurrent neural networks have a "memory" function that allows them to consider previous information when processing current inputs. This is particularly important for video analysis because there is continuity and dependency between video frames. For example, the degree of fluidity of a liquid may require analysis of several consecutive frames to determine.

[0047] The panoramic image of the lid refers to a collection of lid images taken from multiple different viewing angles, which can fully display the appearance of the lid, including but not limited to the front, side and back sides, as well as detailed features such as color, texture and printing fonts of the lid.

[0048] The morphology of the lid describes the overall shape characteristics of the lid, such as round, square and other geometric shapes, which are used to identify and distinguish the design styles of the lid.

[0049] The flatness of the cover refers to the smoothness of the cover surface. The flatness of the cover can be used to indicate whether there are bumps, warps or other defects that affect the appearance and function of the cover.

[0050] The transparency of a cover indicates how much light the cover allows to pass through.

[0051] The shortest distance between the lid and the bottle body refers to the distance between the edge of the lid and the point closest to the bottle mouth, which reflects the fit between the lid and the bottle body.

[0052] The longest distance between the cap and the bottle body refers to the distance between the edge of the cap and the farthest point from the bottle mouth. It is used to assess whether the cap is far away from the bottle body, which may lead to a poor seal.

[0053] The matching degree between the cap and the bottle body describes the degree of fit between the cap and the bottle body, including the matching of shape, size and function, reflecting whether the cap is suitable for the bottle body.

[0054] The panoramic image of the bottle body is similar to the panoramic image of the lid. It is an image of the bottle body taken from multiple angles to show the comprehensive appearance and details of the bottle body.

[0055] The shape of the bottle: The overall shape of the bottle, such as cylindrical, conical, etc., describes the appearance design of the bottle.

[0056] The flatness of the bottle body can be used to indicate whether the bottle body has unevenness, warping or other defects.

[0057] The transparency of the bottle determines the bottle's ability to transmit light and the consumer's visibility of the liquid inside.

[0058] The color of the liquid beverage in the package refers to the color of the liquid beverage in the package, such as red, blue, transparent, etc. The change of color may indicate the integrity of the package or the quality of the liquid.

[0059] The fluidity of liquid beverages in packaging refers to the flow properties of the liquid in the packaging, including whether it is smooth and whether there is coagulation or precipitation, reflecting the physical state of the liquid and the sealing of the packaging.

[0060] In some embodiments, the panoramic detection model includes a panoramic image generation layer, a lid information generation layer, a bottle information generation layer, and a liquid information generation layer, and the panoramic image generation layer, the lid information generation layer, the bottle information generation layer, and the liquid beverage information generation layer are all recurrent neural networks. The input of the panoramic image generation layer is the panoramic video of the plurality of beverage plastic packages to be panoramically detected, and the output of the panoramic image generation layer is the panoramic image of the lid, the panoramic image of the bottle, the shortest distance between the lid and the bottle, the longest distance between the lid and the bottle, and the matching degree between the lid and the bottle. The input of the lid information generation layer is the panoramic image of the lid, and the output of the lid information generation layer is the panoramic image, shape, flatness, and transparency of the lid. The input of the bottle information generation layer is the panoramic image of the bottle, and the output of the bottle information generation layer is the shape, flatness, and transparency. The input of the liquid beverage information generation layer is the panoramic video of the plurality of beverage plastic packages to be panoramically detected, and the output of the liquid beverage information generation layer is the color and fluidity of the liquid beverage.

[0061] Specialized sub-models can learn and recognize specific types of patterns more accurately. For example, the liquid beverage information generation layer can focus on analyzing the color and fluidity of the liquid without being disturbed by the information of the cap and bottle body. This can improve the recognition accuracy of each feature, and when one sub-model encounters a problem, other sub-models can still work normally, thereby improving the robustness of the entire system.

[0062] Step S22, constructing two nodes and an edge between the two nodes, the two nodes include a lid node and a bottle body node, the node feature of the lid node includes the lid information, the node feature of the bottle body node includes the bottle body information and the liquid information, and the edge feature of the edge between the two nodes includes the matching information.

[0063] There are two main nodes in the graph, representing the lid and the bottle body. Each node has features associated with it, which are extracted from the previous steps.

[0064] The features of the lid node include the panoramic image, shape, flatness, transparency, etc. of the lid.

[0065] The characteristics of the bottle node include the panoramic image, shape, flatness, transparency of the bottle, as well as the color and fluidity of the liquid beverage.

[0066] The edges in the graph represent the relationship between the lid node and the bottle body node. The features of the edges include matching information, such as the shortest distance, longest distance, and matching degree between the lid and the bottle body. These features reflect the spatial relationship and matching between the lid and the bottle body.

[0067] Step S23: Process the two nodes and an edge between the two nodes based on a graph convolutional network to determine whether the beverage plastic package to be panoramically inspected is damaged.

[0068] Graph Convolutional Network (GCN) is a neural network architecture specifically designed to process graph structured data. Unlike traditional convolutional neural networks (CNNs) that process regular grid data (such as images), GCN is designed to process irregular graph data, which includes nodes and edges.

[0069] The integrity detection of beverage plastic packaging involves the relationship between multiple components (such as lids and bottles), as well as the individual properties of these components. The graph structure naturally represents these components and the interactions between them, allowing the model to capture complex spatial and logical relationships. Through the graph structure, the individual features of the lid and bottle (such as morphology, flatness, transparency) and the matching information between them (such as shortest distance, longest distance) can be integrated into a unified framework. This integration helps GCN learn more comprehensive feature representations. The graph structure enables GCN to consider the neighborhood information of the node, that is, the contextual information, when updating the node feature. This is crucial to understanding the role of the node in the entire packaging. The graph structure provides an intuitive way to understand the decision-making process of the model. The features of the nodes and edges and the relationships between them can be directly associated with the physical properties and state of the packaging, thereby improving the interpretability of the model.

[0070] Based on the same inventive concept, Figure 3 A schematic diagram of a plastic packaging quality analysis system provided by an embodiment of the present invention, the plastic packaging quality analysis system comprising:

[0071] A first acquisition module 31 is used to acquire ultrasonic reflection data of a plurality of beverage plastic packages to be analyzed and ultrasonic reflection data of qualified beverage plastic packages;

[0072] A processing module 32, configured to use a DTW algorithm to process the ultrasonic reflection data of the plurality of beverage plastic packages to be analyzed and the ultrasonic reflection data of the qualified beverage plastic packages to determine a plurality of beverage plastic packages to be fully inspected;

[0073] A second acquisition module 33 is used to acquire panoramic videos of the plurality of beverage plastic packages to be panoramically inspected;

[0074] The damage determination module 34 is used to determine whether the beverage plastic package to be panoramically inspected is damaged based on the panoramic videos of the plurality of beverage plastic packages to be panoramically inspected.

[0075] Based on the same inventive concept, an embodiment of the present invention provides an electronic device, such as Figure 4 As shown, including:

[0076] It includes: a processor 41; a memory 42; and a computer program; wherein the computer program is stored in the memory 42 and is configured to be executed by the processor 41 to implement the quality analysis method of plastic packaging as provided above, the method including: obtaining ultrasonic reflection data of multiple beverage plastic packages to be analyzed and ultrasonic reflection data of qualified beverage plastic packages; using a DTW algorithm to process the ultrasonic reflection data of the multiple beverage plastic packages to be analyzed and the ultrasonic reflection data of the qualified beverage plastic packages to determine multiple beverage plastic packages to be panoramically inspected; obtaining panoramic videos of the multiple beverage plastic packages to be panoramically inspected; and determining whether the beverage plastic packages to be panoramically inspected are damaged based on the panoramic videos of the multiple beverage plastic packages to be panoramically inspected.

[0077] Based on the same inventive concept, this embodiment provides a computer-readable storage medium having a computer program stored thereon, which, when executed by the processor 41, implements the aforementioned plastic packaging quality analysis method, the method comprising: obtaining ultrasonic reflection data of multiple beverage plastic packages to be analyzed and ultrasonic reflection data of qualified beverage plastic packages; using a DTW algorithm to process the ultrasonic reflection data of the multiple beverage plastic packages to be analyzed and the ultrasonic reflection data of the qualified beverage plastic packages to determine multiple beverage plastic packages to be panoramically inspected; obtaining panoramic videos of the multiple beverage plastic packages to be panoramically inspected; and determining whether the beverage plastic packages to be panoramically inspected are damaged based on the panoramic videos of the multiple beverage plastic packages to be panoramically inspected.

[0078] The quality analysis method of plastic packaging provided in the embodiment of the present application can be applied to terminal devices (such as mobile phones), tablet computers, laptops, ultra-mobile personal computers (UMPCs), handheld computers, netbooks, personal digital assistants (PDAs), wearable devices (such as smart watches, smart glasses or smart helmets, etc.), augmented reality (AR) and virtual reality (VR) devices, smart home devices, car computers and other electronic devices, and the embodiment of the present application does not impose any restrictions on this.

[0079] Taking the mobile phone 100 as an example of the electronic device, Figure 5 A schematic structural diagram of the mobile phone 100 is shown.

[0080] like Figure 5As shown, the mobile phone 100 may include a processing module 110, an external memory interface 120, an internal memory 121, a universal serial bus (USB) interface 130, a charging management module 140, a power management module 141, a battery 142, an antenna 1, an antenna 2, a mobile communication module 150, a wireless communication module 160, an audio module 170, a speaker 170A, a receiver 170B, a microphone 170C, an earphone interface 170D, a sensor module 180, a button 190, a motor 191, an indicator 192, a camera 193, a display screen 194, and a subscriber identification module (SIM) card interface 195, etc.

[0081] The sensor module 180 may include a distance sensor, a proximity light sensor, a fingerprint sensor, a temperature sensor, a touch sensor, an ambient light sensor and other sensors.

[0082] It is to be understood that the structure illustrated in this embodiment does not constitute a specific limitation on the mobile phone 100. In other embodiments of the present application, the mobile phone 100 may include more or fewer components than those illustrated, or combine certain components, or separate certain components, or arrange the components differently. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0083] The processing module 110 may include one or more processing units, for example, the processing module 110 may include an application processor (AP), a modem processor, a graphics processor (GPU), an image signal processor (ISP), a controller, a memory, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural-network processing unit (NPU), etc. Different processing units may be independent devices or integrated into one or more processors.

[0084] The controller can be the nerve center and command center of the mobile phone 100, and is the decision maker that commands the various components of the mobile phone 100 to work in coordination according to the instructions. The controller can generate an operation control signal according to the instruction operation code and timing signal to complete the control of fetching and executing instructions.

[0085] The application processor may be installed with an operating system of the mobile phone 100, which is used to manage the hardware and software resources of the mobile phone 100. For example, it may manage and configure memory, determine the priority of system resource supply and demand, manage file systems, manage drivers, etc. The operating system may also be used to provide an operating interface for users to interact with the system. Various types of software may be installed in the operating system, such as drivers, applications (applications, apps), etc. Exemplarily, the operating system of the mobile phone 100 may be an Android system, a Linux system, etc.

[0086] A memory may also be provided in the processing module 110 for storing instructions and data. In some embodiments, the memory in the processing module 110 is a cache memory. The memory may store instructions or data that have just been used or are cyclically used by the processing module 110. If the processing module 110 needs to use the instruction or data again, it may be directly called from the memory. This avoids repeated access, reduces the waiting time of the processing module 110, and thus improves the efficiency of the system.

[0087] In some embodiments, the processing module 110 may include one or more interfaces. The interface may include an inter-integrated circuit (I2C) interface, an inter-integrated circuits sound (I2S) interface, a pulse code modulation (PCM) interface, a universal asynchronous receiver / transmitter (UART) interface, a mobile industry processor interface (MIPI), a general-purpose input / output (GPIO) interface, a subscriber identity module (SIM) interface, and / or a universal serial bus (USB) interface, etc.

[0088] The processing module 110 can be used to: obtain ultrasonic reflection data of multiple beverage plastic packages to be analyzed and ultrasonic reflection data of qualified beverage plastic packages; use the DTW algorithm to process the ultrasonic reflection data of the multiple beverage plastic packages to be analyzed and the ultrasonic reflection data of the qualified beverage plastic packages to determine multiple beverage plastic packages to be panoramically detected; obtain panoramic videos of the multiple beverage plastic packages to be panoramically detected; and determine whether the beverage plastic packages to be panoramically detected are damaged based on the panoramic videos of the multiple beverage plastic packages to be panoramically detected.

[0089] The charging management module 140 is used to receive charging input from a charger. The charger may be a wireless charger or a wired charger. In some wired charging embodiments, the charging management module 140 may receive charging input from a wired charger through the USB interface 130. In some wireless charging embodiments, the charging management module 140 may receive wireless charging input through a wireless charging coil of the mobile phone 100. While the charging management module 140 is charging the battery 142, it may also power the electronic device through the power management module 141.

[0090] The power management module 141 is used to connect the battery 142, the charging management module 140 and the processing module 110. The power management module 141 receives input from the battery 142 and / or the charging management module 140, and supplies power to the processing module 110, the internal memory 121, the external memory, the display screen 194, the camera 193, and the wireless communication module 160. The power management module 141 can also be used to monitor parameters such as battery capacity, battery cycle number, battery health status (leakage, impedance), etc. In some other embodiments, the power management module 141 can also be set in the processing module 110. In other embodiments, the power management module 141 and the charging management module 140 can also be set in the same device.

[0091] The wireless communication function of the mobile phone 100 can be implemented through the antenna 1, the antenna 2, the mobile communication module 150, the wireless communication module 160, the modem processor and the baseband processor.

[0092] Antenna 1 and antenna 2 are used to transmit and receive electromagnetic wave signals. Each antenna in mobile phone 100 can be used to cover a single or multiple communication frequency bands. Different antennas can also be reused to improve the utilization of antennas. For example, antenna 1 can be reused as a diversity antenna for a wireless local area network. In some other embodiments, the antenna can be used in combination with a tuning switch.

[0093] The mobile communication module 150 can provide solutions for wireless communications including 2G / 3G / 4G / 5G applied to the mobile phone 100. The mobile communication module 150 may include at least one filter, a switch, a power amplifier, a low noise amplifier (LNA), etc. The mobile communication module 150 can receive electromagnetic waves from the antenna 1, and filter, amplify, and process the received electromagnetic waves, and transmit them to the modulation and demodulation processor for demodulation. The mobile communication module 150 can also amplify the signal modulated by the modulation and demodulation processor, and convert it into electromagnetic waves for radiation through the antenna 1. In some embodiments, at least some of the functional modules of the mobile communication module 150 can be arranged in the processing module 110. In some embodiments, at least some of the functional modules of the mobile communication module 150 can be arranged in the same device as at least some of the modules of the processing module 110.

[0094] The modem processor may include a modulator and a demodulator. Among them, the modulator is used to modulate the low-frequency baseband signal to be sent into a medium-high frequency signal. The demodulator is used to demodulate the received electromagnetic wave signal into a low-frequency baseband signal. The demodulator then transmits the demodulated low-frequency baseband signal to the baseband processor for processing. After the low-frequency baseband signal is processed by the baseband processor, it is passed to the application processor. The application processor outputs a sound signal through an audio device (not limited to a speaker 170A, a receiver 170B, etc.), or displays an image or video through a display screen 194. In some embodiments, the modem processor may be an independent device. In other embodiments, the modem processor may be independent of the processing module 110 and be set in the same device as the mobile communication module 150 or other functional modules.

[0095] The wireless communication module 160 can provide wireless communication solutions including wireless local area networks (WLAN) (such as wireless fidelity (Wi-Fi) networks), bluetooth (BT), global navigation satellite system (GNSS), frequency modulation (FM), near field communication (NFC), infrared (IR), etc., which are applied to the mobile phone 100. The wireless communication module 160 can be one or more devices integrating at least one communication processing module. The wireless communication module 160 receives electromagnetic waves via the antenna 2, modulates the frequency of the electromagnetic wave signal and performs filtering, and sends the processed signal to the processing module 110. The wireless communication module 160 can also receive the signal to be sent from the processing module 110, modulate the frequency of the signal, amplify it, and convert it into electromagnetic waves for radiation through the antenna 2.

[0096] In some embodiments, the antenna 1 of the mobile phone 100 is coupled to the mobile communication module 150, and the antenna 2 is coupled to the wireless communication module 160, so that the mobile phone 100 can communicate with the network and other devices through wireless communication technology. The wireless communication technology may include global system for mobile communications (GSM), general packet radio service (GPRS), code division multiple access (CDMA), wideband code division multiple access (WCDMA), time-division code division multiple access (TD-SCDMA), long term evolution (LTE), BT, GNSS, WLAN, NFC, FM, and / or IR technology. The GNSS may include a global positioning system (GPS), a global navigation satellite system (GLONASS), a Beidou navigation satellite system (BDS), a quasi-zenith satellite system (QZSS) and / or a satellite based augmentation system (SBAS).

[0097] The mobile phone 100 implements the display function through a GPU, a display screen 194, and an application processor. The GPU is a microprocessor for image processing, which is connected to the display screen 194 and the application processor. The GPU is used to perform mathematical and geometric calculations for graphics rendering. The processing module 110 may include one or more GPUs, which execute program instructions to generate or change display information.

[0098] The display screen 194 is used to display images, videos, etc. The display screen 194 includes a display panel. The display panel can be a liquid crystal display (LCD), an organic light-emitting diode (OLED), an active-matrix organic light-emitting diode or an active-matrix organic light-emitting diode (AMOLED), a flexible light-emitting diode (FLED), Miniled, MicroLed, Micro-oLed, a quantum dot light-emitting diode (QLED), etc. In some embodiments, the mobile phone 100 may include 1 or N display screens 194, where N is a positive integer greater than 1.

[0099] The mobile phone 100 can realize the shooting function through the ISP, the camera 193, the video codec, the GPU, the display screen 194 and the application processor. In some embodiments, the mobile phone 100 can realize the video communication function through the ISP, the camera 193, the video codec, the GPU and the application processor.

[0100] ISP is used to process the data fed back by camera 193. For example, when taking a photo, the shutter is opened, and the light is transmitted to the camera photosensitive element through the lens. The light signal is converted into an electrical signal, and the camera photosensitive element transmits the electrical signal to ISP for processing and converts it into an image visible to the naked eye. ISP can also perform algorithm optimization on the noise, brightness, and skin color of the image. ISP can also optimize the exposure, color temperature and other parameters of the shooting scene. In some embodiments, ISP can be set in camera 193.

[0101] The camera 193 is used to capture still images or videos. The object generates an optical image through the lens and projects it onto the photosensitive element. The photosensitive element can be a charge coupled device (CCD) or a complementary metal-oxide-semiconductor (CMOS) phototransistor. The photosensitive element converts the optical signal into an electrical signal, and then passes the electrical signal to the ISP to be converted into a digital image signal. The ISP outputs the digital image signal to the DSP for processing. The DSP converts the digital image signal into an image signal in a standard RGB, YUV or other format. In some embodiments, the mobile phone 100 may include 1 or N cameras 193, where N is a positive integer greater than 1.

[0102] The digital signal processor is used to process digital signals, and can process not only digital image signals but also other digital signals. For example, when the mobile phone 100 is selecting a frequency point, the digital signal processor is used to perform Fourier transform on the frequency point energy.

[0103] Video codecs are used to compress or decompress digital videos. Mobile phone 100 may support one or more video codecs. Thus, mobile phone 100 may play or record videos in various coding formats, such as Moving Picture Experts Group (MPEG) 1, MPEG2, MPEG3, MPEG4, etc.

[0104] NPU is a neural network (NN) computing processor. By drawing on the structure of biological neural networks, such as the transmission mode between neurons in the human brain, it can quickly process input information and can also continuously self-learn. Through NPU, the intelligent cognition of the mobile phone 100 can be realized, such as image recognition, face recognition, voice recognition, text understanding, etc.

[0105] The external memory interface 120 can be used to connect an external memory card, such as a Micro SD card, to expand the storage capacity of the mobile phone 100. The external memory card communicates with the processing module 110 through the external memory interface 120 to implement a data storage function, such as storing music, video and other files in the external memory card.

[0106] The internal memory 121 can be used to store computer executable program codes, which include instructions. The processing module 110 executes various functional applications and data processing of the mobile phone 100 by running the instructions stored in the internal memory 121. The internal memory 121 may include a program storage area and a data storage area. Among them, the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc. The data storage area can store data created during the use of the mobile phone 100 (such as audio data, a phone book, etc.), etc. In addition, the internal memory 121 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, a universal flash storage (UFS), etc.

[0107] The mobile phone 100 can implement audio functions such as music playing and recording through the audio module 170, the speaker 170A, the receiver 170B, the microphone 170C, the earphone interface 170D, and the application processor.

[0108] The audio module 170 is used to convert digital audio information into analog audio signal output, and is also used to convert analog audio input into digital audio signals. The audio module 170 can also be used to encode and decode audio signals. In some embodiments, the audio module 170 can be arranged in the processing module 110, or some functional modules of the audio module 170 can be arranged in the processing module 110.

[0109] The speaker 170A, also called a "speaker", is used to convert an audio electrical signal into a sound signal. The mobile phone 100 can listen to music or listen to a hands-free call through the speaker 170A.

[0110] The receiver 170B, also called a "earpiece", is used to convert audio electrical signals into sound signals. When the mobile phone 100 receives a call or voice message, the voice can be received by placing the receiver 170B close to the ear.

[0111] Microphone 170C, also called "microphone" or "microphone", is used to convert sound signals into electrical signals. When making a call or sending a voice message, the user can speak by putting their mouth close to the microphone 170C to input the sound signal into the microphone 170C. The mobile phone 100 can be provided with at least one microphone 170C. In other embodiments, the mobile phone 100 can be provided with two microphones 170C, which can not only collect sound signals but also realize noise reduction function. In other embodiments, the mobile phone 100 can also be provided with three, four or more microphones 170C to collect sound signals, reduce noise, identify the sound source, realize directional recording function, etc.

[0112] The earphone interface 170D is used to connect a wired earphone and can be a USB interface 130 or a 3.5 mm open mobile terminal platform (OMTP) standard interface or a cellular telecommunications industry association of the USA (CTIA) standard interface.

[0113] The key 190 includes a power key, a volume key, etc. The key 190 can be a mechanical key or a touch key. The mobile phone 100 can receive key input and generate key signal input related to the user settings and function control of the mobile phone 100.

[0114] Motor 191 can generate vibration prompts. Motor 191 can be used for incoming call vibration prompts, and can also be used for touch vibration feedback. For example, touch operations acting on different applications (such as taking pictures, audio playback, etc.) can correspond to different vibration feedback effects. For touch operations acting on different areas of the display screen 194, motor 191 can also correspond to different vibration feedback effects. Different application scenarios (for example: time reminders, receiving messages, alarm clocks, games, etc.) can also correspond to different vibration feedback effects. The touch vibration feedback effect can also support customization.

[0115] The indicator 192 may be an indicator light, which may be used to indicate the charging status, power changes, messages, missed calls, notifications, etc.

[0116] The SIM card interface 195 is used to connect the SIM card. The SIM card can be connected to and separated from the mobile phone 100 by inserting it into the SIM card interface 195 or pulling it out from the SIM card interface 195. The mobile phone 100 can support 1 or N SIM card interfaces, where N is a positive integer greater than 1. The SIM card interface 195 can support Nano SIM cards, Micro SIM cards, SIM cards, etc. Multiple cards can be inserted into the same SIM card interface 195 at the same time. The types of the multiple cards can be the same or different. The SIM card interface 195 can also be compatible with different types of SIM cards. The SIM card interface 195 can also be compatible with external memory cards. The mobile phone 100 interacts with the network through the SIM card to realize functions such as calls and data communications. In some embodiments, the mobile phone 100 uses an eSIM, i.e., an embedded SIM card. The eSIM card can be embedded in the mobile phone 100 and cannot be separated from the mobile phone 100.

[0117] The basic concepts have been described above. Obviously, for those skilled in the art, the above detailed disclosure is only for example and does not constitute a limitation of this specification. Although not explicitly stated here, those skilled in the art may make various modifications, improvements and corrections to this specification. Such modifications, improvements and corrections are suggested in this specification, so such modifications, improvements and corrections still belong to the spirit and scope of the exemplary embodiments of this specification.

[0118] At the same time, this specification uses specific words to describe the embodiments of this specification. For example, "one embodiment", "an embodiment", and / or "some embodiments" refer to a certain feature, structure or characteristic related to at least one embodiment of this specification. Therefore, it should be emphasized and noted that "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more in different positions in this specification does not necessarily refer to the same embodiment. In addition, certain features, structures or characteristics in one or more embodiments of this specification can be appropriately combined.

[0119] In addition, unless explicitly stated in the claims, the order of the processing elements and sequences described in this specification, the use of alphanumeric characters, or the use of other names are not intended to limit the order of the processes and methods of this specification. Although the above disclosure discusses some invention embodiments that are currently considered useful through various examples, it should be understood that such details are only for illustrative purposes, and the attached claims are not limited to the disclosed embodiments. On the contrary, the claims are intended to cover all modifications and equivalent combinations that are consistent with the essence and scope of the embodiments of this specification. For example, although the system components described above can be implemented by hardware devices, they can also be implemented only by software solutions, such as installing the described system on an existing server or mobile device.

[0120] Similarly, it should be noted that in order to simplify the description disclosed in this specification and thus help understand one or more embodiments of the invention, in the above description of the embodiments of this specification, multiple features are sometimes combined into one embodiment, figure or description thereof. However, this disclosure method does not mean that the features required by the subject matter of this specification are more than the features mentioned in the claims. In fact, the features of the embodiments are less than all the features of the single embodiment disclosed above.

[0121] Finally, it should be understood that the embodiments described in this specification are only used to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, as an example and not a limitation, alternative configurations of the embodiments of this specification may be considered consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly introduced and described in this specification.

Claims

1. A method for analyzing the quality of plastic packaging, characterized in that: include: Acquire ultrasonic reflection data of multiple beverage plastic packages to be analyzed and ultrasonic reflection data of qualified beverage plastic packages; Using the DTW algorithm, the ultrasonic reflection data of the plurality of beverage plastic packages to be analyzed and the ultrasonic reflection data of the qualified beverage plastic packages are processed to determine a plurality of beverage plastic packages to be fully inspected; Acquire panoramic videos of the plurality of beverage plastic packages to be panoramically inspected; Determining whether the beverage plastic package to be detected is damaged based on the panoramic videos of the plurality of beverage plastic packages to be detected, wherein determining whether the beverage plastic package to be detected is damaged based on the panoramic videos of the plurality of beverage plastic packages to be detected comprises: Based on the panoramic videos of the plurality of beverage plastic packages to be panoramically inspected, the panoramic inspection model is used to determine the information of each beverage plastic package to be panoramically inspected, wherein the information of each beverage plastic package to be panoramically inspected includes lid information, bottle body information, liquid information, and matching information, wherein the lid information includes a panoramic image, shape, flatness, and transparency of the lid, the bottle body information includes a panoramic image, shape, flatness, and transparency of the bottle body, the liquid information includes the color and fluidity of the liquid beverage, and the matching information includes the shortest distance between the lid and the bottle body, the longest distance between the lid and the bottle body, and the matching degree between the lid and the bottle body; Constructing two nodes and an edge between the two nodes, the two nodes include a lid node and a bottle body node, the node feature of the lid node includes the lid information, the node feature of the bottle body node includes the bottle body information and the liquid information, and the edge feature of the edge between the two nodes includes the matching information; The two nodes and an edge between the two nodes are processed based on a graph convolutional network to determine whether the beverage plastic package to be panoramically inspected is damaged.

2. The method for analyzing the quality of plastic packaging according to claim 1, characterized in that: The method of using the DTW algorithm to process the ultrasonic reflection data of the multiple beverage plastic packages to be analyzed and the ultrasonic reflection data of the qualified beverage plastic packages to determine the multiple beverage plastic packages to be panoramically detected includes: determining the similarity between the ultrasonic reflection data of each beverage plastic package to be analyzed and the ultrasonic reflection data of the qualified beverage plastic packages based on the DTW algorithm; and taking the multiple beverage plastic packages corresponding to the similarity being less than a similarity threshold as the multiple beverage plastic packages to be panoramically detected.

3. The quality analysis method of plastic packaging according to claim 1, characterized in that: The panoramic videos of the multiple beverage plastic packages to be panoramically inspected are synthesized by shooting with a high-definition camera.

4. A plastic packaging quality analysis system, characterized in that: include: A first acquisition module is used to acquire ultrasonic reflection data of a plurality of beverage plastic packages to be analyzed and ultrasonic reflection data of qualified beverage plastic packages; A processing module, used for processing the ultrasonic reflection data of the plurality of beverage plastic packages to be analyzed and the ultrasonic reflection data of the qualified beverage plastic packages using a DTW algorithm to determine a plurality of beverage plastic packages to be fully inspected; A second acquisition module is used to acquire panoramic videos of the plurality of beverage plastic packages to be panoramically inspected; A damage determination module is used to determine whether the beverage plastic package to be panoramically inspected is damaged based on the panoramic videos of the plurality of beverage plastic packages to be panoramically inspected, and the damage determination module is also used to: Based on the panoramic videos of the plurality of beverage plastic packages to be panoramically inspected, the panoramic inspection model is used to determine the information of each beverage plastic package to be panoramically inspected, wherein the information of each beverage plastic package to be panoramically inspected includes lid information, bottle body information, liquid information, and matching information, wherein the lid information includes a panoramic image, shape, flatness, and transparency of the lid, the bottle body information includes a panoramic image, shape, flatness, and transparency of the bottle body, the liquid information includes the color and fluidity of the liquid beverage, and the matching information includes the shortest distance between the lid and the bottle body, the longest distance between the lid and the bottle body, and the matching degree between the lid and the bottle body; Constructing two nodes and an edge between the two nodes, the two nodes include a lid node and a bottle body node, the node feature of the lid node includes the lid information, the node feature of the bottle body node includes the bottle body information and the liquid information, and the edge feature of the edge between the two nodes includes the matching information; The two nodes and an edge between the two nodes are processed based on a graph convolutional network to determine whether the beverage plastic package to be panoramically inspected is damaged.

5. An electronic device, characterized in that: include: processor; Memory; And a computer program; wherein the computer program is stored in the memory and is configured to be executed by the processor to implement the quality analysis method of plastic packaging according to any one of claims 1 to 3.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the quality analysis method of plastic packaging as described in any one of claims 1 to 3 is implemented.

Images