CN116862898A - Defect detection method and device for parts, storage medium and electronic equipment - Google Patents
Defect detection method and device for parts, storage medium and electronic equipment Download PDFInfo
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- G06T7/0002—Inspection of images, e.g. flaw detection
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Abstract
The disclosure relates to a defect detection method and device for parts, a storage medium and electronic equipment, and relates to the technical field of vehicles, wherein the method comprises the following steps: collecting a first image of a part to be detected; performing defect detection on the first image based on the defect detection model to obtain a defect detection result; executing three-dimensional modeling operation according to the first image and the defect detection result to obtain three-dimensional point cloud data; performing connected domain construction operation on the three-dimensional point cloud data to obtain a target connected domain; and determining a target detection result of the part to be detected based on the target connected domain. The present disclosure can improve accuracy of defect detection by performing a three-dimensional modeling operation.
Description
Technical Field
The disclosure relates to the technical field of vehicles, and in particular relates to a defect detection method and device for parts, a storage medium and electronic equipment.
Background
At present, the defect detection has wide application in the fields of industrial production, manufacturing, quality monitoring and the like, such as defect detection of parts. Defects of the product can be found through defect detection, so that maintenance personnel can timely correct the product to ensure the quality of the product, and after the target product image is obtained, the target product image is required to be carefully analyzed and finely identified in order to accurately judge whether the quality of the product is qualified, select which process to maintain, and the like. However, at present, accuracy of quality inspection results is mainly guaranteed through a manual quality inspection mode, and the mode is high in cost and low in efficiency.
Disclosure of Invention
In order to overcome the problems in the related art, the present disclosure provides a defect detection method, device, storage medium and electronic apparatus for parts.
According to a first aspect of an embodiment of the present disclosure, there is provided a defect detection method for a component, including:
collecting a first image of a part to be detected;
performing defect detection on the first image based on the defect detection model to obtain a defect detection result;
executing three-dimensional modeling operation according to the first image and the defect detection result to obtain three-dimensional point cloud data;
performing connected domain construction operation on the three-dimensional point cloud data to obtain a target connected domain;
and determining a target detection result of the part to be detected based on the target connected domain.
Optionally, the performing a three-dimensional modeling operation according to the first image and the defect detection result to obtain three-dimensional point cloud data includes:
obtaining standard model data corresponding to the part to be detected;
and executing three-dimensional modeling operation according to the first image, the defect detection result and the standard model data to obtain the three-dimensional point cloud data.
Optionally, the performing three-dimensional modeling operation according to the first image, the defect detection result and the standard model data to obtain three-dimensional point cloud data includes:
constructing initial point cloud data based on the first image and the defect detection result;
and correcting the initial point cloud data according to the standard model data to obtain the three-dimensional point cloud data.
Optionally, the defect detection result includes a defect number and a defect volume, and the method further includes:
determining the quality level of the part to be detected according to the defect quantity and the defect volume;
and determining whether the part to be detected is qualified or not based on the quality level.
Optionally, the defect detection result further includes a defect morphology, and the method further includes:
and if the part is determined to be disqualified, eliminating the part, and/or adjusting the production process of the part to be detected based on at least one of the defect number, the defect volume and the defect morphology.
Optionally, the first image is an X-Ray image.
According to a second aspect of the embodiments of the present disclosure, there is provided a defect detecting device for a component, including:
the acquisition module is configured to acquire a first image of the part to be detected;
the acquisition module is configured to detect the defects of the first image based on the defect detection model to obtain a defect detection result;
the modeling module is configured to execute three-dimensional modeling operation according to the first image and the defect detection result to obtain three-dimensional point cloud data;
the construction module is configured to execute connected domain construction operation aiming at the three-dimensional point cloud data to obtain a target connected domain;
and the determining module is configured to determine a target detection result of the part to be detected based on the target connected domain.
According to a third aspect of embodiments of the present disclosure, there is provided an electronic device comprising:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to:
collecting a first image of a part to be detected;
performing defect detection on the first image based on the defect detection model to obtain a defect detection result;
executing three-dimensional modeling operation according to the first image and the defect detection result to obtain three-dimensional point cloud data;
performing connected domain construction operation on the three-dimensional point cloud data to obtain a target connected domain;
and determining a target detection result of the part to be detected based on the target connected domain.
According to a fourth aspect of embodiments of the present disclosure, there is provided a computer-readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the steps of the defect detection method of the component provided by the first aspect of the present disclosure.
According to a fifth aspect of embodiments of the present disclosure, there is provided a chip comprising a processor and an interface; the processor is configured to read instructions to implement the steps of the method for detecting defects of a component provided in the first aspect of the present disclosure.
According to the method and the device, the defect detection result of the part to be detected is accurately determined through the three-dimensional point cloud data obtained based on the three-dimensional modeling. Specifically, a first image of a part to be detected is collected, defect detection is performed on the first image based on a defect detection model, a defect detection result is obtained, on the basis, three-dimensional modeling operation is performed according to the first image and the defect detection result, three-dimensional point cloud data is obtained, connected domain construction operation is performed on the three-dimensional point cloud data, a more accurate target connected domain can be obtained, and then the target detection result of the part to be detected is determined based on the target connected domain.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure.
Fig. 1 is a flowchart illustrating a method of defect detection of a component, according to an exemplary embodiment.
Fig. 2 is a flowchart illustrating another method of defect detection of a component according to an exemplary embodiment.
Fig. 3 is a block diagram illustrating a defect detection apparatus for a component according to an exemplary embodiment.
Fig. 4 is a block diagram of an electronic device, according to an example embodiment.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present disclosure as detailed in the accompanying claims.
In the description of the present disclosure, terms such as "first," "second," and the like are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. In addition, unless otherwise stated, in the description with reference to the drawings, the same reference numerals in different drawings denote the same elements.
Although operations or steps are described in a particular order in the figures in the disclosed embodiments, it should not be understood as requiring that such operations or steps be performed in the particular order shown or in sequential order, or that all illustrated operations or steps be performed, to achieve desirable results. In embodiments of the present disclosure, these operations or steps may be performed serially; these operations or steps may also be performed in parallel; some of these operations or steps may also be performed.
To ensure that mass produced parts meet quality standards, it is often necessary to detect defects in the manufactured parts to find possible defects and repair them in time. The related art is mainly based on two-dimensional images when performing defect detection. However, the defect detection based on the two-dimensional image generally has the problem of inaccurate detection, and the main reason is that the two-dimensional image generally has the problem of overlapping, so that the same defect can be detected multiple times, and the accuracy of the defect detection is further affected.
Fig. 1 is a flowchart illustrating a method for detecting defects of a component according to an exemplary embodiment, and the method for detecting defects of a component is used in an electronic device as shown in fig. 1, and includes the following steps.
In step S110, a first image of the part to be inspected is acquired.
In the embodiment of the disclosure, the first image of the part to be detected may be a set of images, that is, the first image may be a plurality of images obtained by shooting the part to be detected from different angles. The first image may be a plurality of images acquired by capturing the parts to be detected in the up, down, left, right, front and rear directions.
As an alternative, the component to be detected may be a component on a vehicle, may be a component on a mobile phone, or may be a component on another product, where the component to be detected is specifically a component on what product is not explicitly limited.
Alternatively, the first image in the embodiment of the present disclosure may be an X-Ray (X-Ray) image, and the first image may be an X-Ray image of the component to be detected by scanning the component to be detected with X-rays emitted from the X-Ray emitter, so as to obtain the X-Ray image of the component to be detected.
In step S120, defect detection is performed on the first image based on the defect detection model, so as to obtain a defect detection result.
As an alternative, after the first image of the part to be detected is acquired, the embodiment of the disclosure may perform defect detection on the first image based on the defect detection model to obtain a defect detection result. Here, the defect detection model may perform semantic analysis on the first image after the first image is acquired, so as to obtain a defect detection result.
The defect detection model may be a deep learning model, and in the process of performing defect detection on the first image by using the defect detection model, the electronic device may input the first image into the defect detection model to obtain a defect detection result, that is, the output of the defect detection model may be the defect detection result. Here, the defect detection result may include a position of the defect, a kind of the defect, and the like.
In the embodiment of the disclosure, the defect detection model may be obtained by training a large number of data sets, where the data sets may include a large number of defect images and defect labels corresponding to each defect image, and training deep learning by using the data sets may obtain the defect detection model.
Optionally, after the first image of the part to be detected is obtained, the embodiment of the disclosure may input the first image into a trained defect detection model to obtain a defect detection result, where the defect detection result includes a position, a kind, and the like of the defect in the first image. It should be noted that the defect detection result is obtained based on a two-dimensional image, so the defect detection result is also a two-dimensional detection result.
In addition, as known from the above description, the first image may be composed of a plurality of images, so that in the process of performing defect detection, the plurality of images may be input into the defect detection model, so as to obtain a defect detection result corresponding to each image. In other words, the defect detection result may include defect detection results of a plurality of images acquired in different directions.
In step S130, a three-dimensional modeling operation is performed according to the first image and the defect detection result, resulting in three-dimensional point cloud data.
As an alternative, the embodiment of the disclosure may perform a three-dimensional modeling operation according to the first image and the defect detection result, to obtain three-dimensional point cloud data. In other words, the three-dimensional reconstruction operation can be realized by using the first image and the defect detection result, and then a three-dimensional model corresponding to the part to be detected can be obtained, wherein the three-dimensional model can be composed of three-dimensional point cloud data.
In the embodiment of the disclosure, the three-dimensional point cloud data may include normal point cloud data and defect point cloud data, wherein the defect point cloud data may be acquired based on a defect detection result. The electronic equipment can determine the position of the defect point in the defect detection result in the process of executing the three-dimensional modeling operation, and map the position of the defect point to the position corresponding to the three-dimensional modeling on the basis, so that the position of the defect point in the three-dimensional model can be known.
In other words, the embodiment of the disclosure can mark the defect point when performing three-dimensional modeling, so that the finally obtained three-dimensional point cloud data is ensured to have semantics, namely, the semanteme of the defect is realized. In summary, the defect point cloud data in the three-dimensional point cloud data are marked, so that the defect detection of the parts can be more accurately and effectively realized.
It should be noted that, the step S120 and the step S130 may be performed simultaneously or sequentially, and the execution sequence of the two steps is not limited in the embodiment of the present disclosure.
In step S140, a connected domain construction operation is performed on the three-dimensional point cloud data, to obtain a target connected domain.
As an alternative, after the three-dimensional point cloud data is acquired, the embodiments of the present disclosure may perform a connected domain construction operation to obtain the target connected domain. In order to better realize statistics of defect points, the embodiment of the disclosure can construct a 3D connected domain of the obtained three-dimensional point cloud data, namely, the defect points belonging to the same defect area are connected.
Alternatively, since each defect in the three-dimensional point cloud data is represented by a point, if the number of defects is determined directly based on the defective point cloud data in the three-dimensional point cloud data, the spatial relationship between the defective points cannot be known, which not only results in an increase in difficulty of defect detection, but also results in an increase in cost of detection. Therefore, the embodiment of the disclosure can connect the defect points before counting the defect number, so that the defect number obtained finally is accurate, and the defect number is not the defect point number.
In summary, a piece of defect point cloud data in the embodiments of the present disclosure may represent a defect, and by performing the connected domain construction operation, a target detection result may be more quickly and effectively obtained.
In step S150, a target detection result of the component to be detected is determined based on the target connected domain.
As an alternative, after obtaining the target connected domain, the embodiments of the present disclosure may count the defective area in the target connected domain to obtain the target detection result of the part to be detected. Specifically, the number of the defect areas in the target connected domain is counted, and the morphology of the defect areas in the target connected domain is counted, so that a target detection result is obtained.
In the embodiment of the disclosure, the target detection result may include a defect number, a defect morphology, a defect volume, a defect category, and the like. The defect shape may be a shape of a defect region, for example, the defect shape may include a stripe shape, a circular shape, an oval shape, and the like. In addition, the defect type refers to a type of defect, and specifically, the defect type may include a crack, a burr, a bubble, a hole, and the like.
It should be noted that the defect detection in the embodiments of the present disclosure may be directed to the surface of the component. When the first image is an X-Ray image, the defect detection in the embodiments of the present disclosure is mainly directed to the inside of the component.
According to the method and the device, the defect detection result of the part to be detected is accurately determined through the three-dimensional point cloud data obtained based on the three-dimensional modeling. Specifically, a first image of a part to be detected is collected, defect detection is performed on the first image based on a defect detection model, a defect detection result is obtained, on the basis, three-dimensional modeling operation is performed according to the first image and the defect detection result, three-dimensional point cloud data is obtained, connected domain construction operation is performed on the three-dimensional point cloud data, a more accurate target connected domain can be obtained, and then the target detection result of the part to be detected is determined based on the target connected domain.
Fig. 2 is a flowchart illustrating another method of detecting defects of a component according to an exemplary embodiment, and the method of detecting defects of a component is used in an electronic device as shown in fig. 2, and includes the following steps.
In step S210, a first image of a part to be inspected is acquired.
In step S220, defect detection is performed on the first image based on the defect detection model, so as to obtain a defect detection result.
The specific embodiments of step S210 to step S220 have been described in detail, and will not be described here again.
In step S230, standard model data corresponding to the part to be detected is obtained.
As an alternative, the embodiment of the disclosure may acquire standard model data corresponding to the part to be detected. Specifically, the embodiment of the disclosure can identify the part to be detected in the first image, and acquire standard model data corresponding to the part to be detected on the basis of the identification. The standard model data may be design prototype data of the part to be detected, that is, the part to be detected may be produced based on the standard model data.
Optionally, before the standard model data is acquired, the embodiment of the disclosure may also acquire the part to be detected, where the part to be detected may be acquired by identifying the first image. Alternatively, the part to be detected may be input by the user, for example, the model number of the part to be detected is 0001, and it is possible to directly determine which part to be detected is.
As an alternative, after the to-be-detected component is obtained, the embodiment of the present disclosure may obtain the first mapping relationship, and then obtain the standard model data based on the to-be-detected component and the first mapping relationship. In the first mapping relationship, a relationship corresponding to each other between the part to be detected and the standard model data may exist.
In step S240, a three-dimensional modeling operation is performed according to the first image, the defect detection result, and the standard model data, to obtain three-dimensional point cloud data.
As an alternative, embodiments of the present disclosure may perform a three-dimensional modeling operation according to the first image, the defect detection result, and the standard model data to obtain three-dimensional point cloud data. Specifically, initial point cloud data is constructed based on the first image and the defect detection result, and on the basis, the initial point cloud data is corrected according to standard model data to obtain three-dimensional point cloud data. Here, the standard model data can be used as a constraint of three-dimensional reconstruction, and the finally obtained three-dimensional point cloud data can be more accurate by introducing the standard model data.
For example, if shake occurs during the process of acquiring the first image, the acquired first image may not conform to the shape or structure of the actual part to be detected, so that standard model data may be introduced in the overcharge for performing the three-dimensional reconstruction, so as to correct the three-dimensional model constructed based on the first image through the standard model data.
It should be noted that, the standard model data may be introduced after the initial point cloud data is acquired, that is, after the initial point cloud data is acquired, the standard model data is used to correct the initial point cloud data to obtain the three-dimensional point cloud data. Alternatively, the standard model data may be introduced during the process of performing the three-dimensional modeling operation, that is, during the process of performing three-dimensional reconstruction using the first image and the defect detection result, the standard model data is used as a constraint, so as to obtain final three-dimensional point cloud data. Specific to when the standard model data is introduced, no explicit limitation is made here, and the selection can be made according to the actual situation.
In step S250, a connected domain construction operation is performed on the three-dimensional point cloud data, to obtain a target connected domain.
As an alternative, after the three-dimensional power data is obtained, the embodiment of the disclosure may use a 3D (3 Dimensions) connected domain calculation method to obtain a target connected domain, where the target connected domain may include a defective connected domain and a normal connected domain.
Optionally, after the target connected domain is obtained, the embodiment of the disclosure may also match the target connected domain with the defect detection result, and if it is determined that the target connected domain and the defect detection result are not matched and the degree of mismatching exceeds a preset threshold, the defect detection model is adjusted, so that accuracy of obtaining the defect detection result by the defect detection model can be improved.
In step S260, a target detection result of the component to be detected is determined based on the target connected domain.
The above embodiment of step S260 is described in detail, and will not be described herein.
As an alternative, the target inspection result may include a defect number and a defect volume, and after the target inspection result is obtained, the embodiment of the present disclosure may determine a quality level of the part to be inspected according to the defect number and the defect volume. On the basis, whether the part to be detected is qualified or not is determined based on the quality level.
As an example, a second mapping relationship is obtained, where there is a correspondence between the number of defects, the volume of defects, and the quality level in the second mapping relationship. Accordingly, after the number of defects and the defect volume are acquired, the corresponding quality level may be acquired based on the second mapping relation.
Optionally, when the quality level is determined to exceed the preset level, determining that the part to be detected is qualified, i.e. the part to be detected is good. Optionally, when the quality level is determined to be lower than the preset level, determining that the part to be detected is unqualified.
As an alternative, in the case of determining that the component to be detected is not acceptable, the embodiments of the present disclosure may eliminate the component, so that the problem components may be avoided from being used, and thus unnecessary risks brought by the problem components may be reduced.
Optionally, in the case of determining that the part to be inspected is not acceptable, the embodiments of the present disclosure may adjust a production process of the part to be inspected based on at least one of a defect number, a defect volume, and a defect morphology of the part to be inspected. Specifically, the formation reason of the defect on the part to be detected can be known by analyzing the target detection result, so that the production process can be correspondingly adjusted, the quality of the part can be improved, and the production cost is saved.
It should be noted that, after the target detection result is obtained, the embodiment of the present disclosure may display the target detection result. Through the above description, it is known that the target detection result may include defect number, defect type, defect morphology, defect volume, and the like, and based on these information, defect detection of the component may be more flexibly and accurately implemented.
According to the method and the device, the defect detection result of the part to be detected is accurately determined through the three-dimensional point cloud data obtained based on the three-dimensional modeling. Specifically, a first image of a part to be detected is collected, defect detection is performed on the first image based on a defect detection model, a defect detection result is obtained, on the basis, three-dimensional modeling operation is performed according to the first image and the defect detection result, three-dimensional point cloud data is obtained, connected domain construction operation is performed on the three-dimensional point cloud data, a more accurate target connected domain can be obtained, and then the target detection result of the part to be detected is determined based on the target connected domain. In addition, the embodiment of the disclosure calculates the internal defects of the parts by a method of sampling the connected domain, and can accurately position the positions, the shapes and the number of the defects.
Fig. 3 is a block diagram of a defect detection apparatus for a component, according to an exemplary embodiment. Referring to fig. 3, the defect detection apparatus 300 of the part may include an acquisition module 310, an acquisition module 320, a modeling module 330, a construction module 340, and a determination module 350.
The acquisition module 310 is configured to acquire a first image of a part to be inspected;
the obtaining module 320 is configured to perform defect detection on the first image based on the defect detection model, so as to obtain a defect detection result;
the modeling module 330 is configured to perform a three-dimensional modeling operation according to the first image and the defect detection result, so as to obtain three-dimensional point cloud data;
the construction module 340 is configured to perform a connected domain construction operation on the three-dimensional point cloud data to obtain a target connected domain;
the determining module 350 is configured to determine a target detection result of the component to be detected based on the target connected domain.
In some implementations, the modeling module 330 can include:
the standard data acquisition sub-module is configured to acquire standard model data corresponding to the part to be detected;
and the three-dimensional modeling module is configured to execute three-dimensional modeling operation according to the first image, the defect detection result and the standard model data to obtain the three-dimensional point cloud data.
In some embodiments, the three-dimensional modeling sub-module is further configured to construct initial point cloud data based on the first image and the defect detection result; and correcting the initial point cloud data according to the standard model data to obtain the three-dimensional point cloud data.
In some embodiments, the defect detection result includes a defect number and a defect volume, and the defect detection apparatus 300 for a part further includes:
the grade determining module is configured to determine the quality grade of the part to be detected according to the defect quantity and the defect volume;
and the qualification determining module is configured to determine whether the part to be detected is qualified or not based on the quality level.
In some embodiments, the defect detection result further includes a defect shape, and the defect detection apparatus 300 for a part further includes:
and the processing module is configured to eliminate the part if the part is determined to be unqualified, and/or adjust the production process of the part to be detected based on at least one of the defect number, the defect volume and the defect morphology.
In some embodiments, the first image is an X-Ray image.
According to the method and the device, the defect detection result of the part to be detected is accurately determined through the three-dimensional point cloud data obtained based on the three-dimensional modeling. Specifically, a first image of a part to be detected is collected, defect detection is performed on the first image based on a defect detection model, a defect detection result is obtained, on the basis, three-dimensional modeling operation is performed according to the first image and the defect detection result, three-dimensional point cloud data is obtained, connected domain construction operation is performed on the three-dimensional point cloud data, a more accurate target connected domain can be obtained, and then the target detection result of the part to be detected is determined based on the target connected domain.
The specific manner in which the various modules perform the operations in the apparatus of the above embodiments have been described in detail in connection with the embodiments of the method, and will not be described in detail herein.
The present disclosure also provides a computer-readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the steps of the defect detection method of the component provided by the present disclosure.
Fig. 4 is a block diagram illustrating an electronic device 800 for defect detection of a component, according to an example embodiment. For example, electronic device 800 may be a mobile phone, computer, digital broadcast terminal, messaging device, game console, tablet device, medical device, exercise device, personal digital assistant, or the like.
Referring to fig. 4, the electronic device 800 may include one or more of the following components: a processing component 802, a memory 804, a power component 806, a multimedia component 808, an audio component 810, an input/output interface 812, a sensor component 814, and a communication component 816.
The processing component 802 generally controls overall operation of the electronic device 800, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. Processing assembly 802 may include one or more processors 820 to execute instructions to perform all or part of the steps of the defect detection method for components described above. Further, the processing component 802 can include one or more modules that facilitate interactions between the processing component 802 and other components. For example, the processing component 802 can include a multimedia module to facilitate interaction between the multimedia component 808 and the processing component 802.
The memory 804 is configured to store various types of data to support operations at the electronic device 800. Examples of such data include instructions for any application or method operating on the electronic device 800, contact data, phonebook data, messages, pictures, videos, and so forth. The memory 804 may be implemented by any type or combination of volatile or nonvolatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk.
The power supply component 806 provides power to the various components of the electronic device 800. The power components 806 may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power for the electronic device 800.
The multimedia component 808 includes a screen between the electronic device 800 and the user that provides an output interface. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from a user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensor may sense not only the boundary of a touch or slide action, but also the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front camera and/or a rear camera. When the electronic device 800 is in an operational mode, such as a shooting mode or a video mode, the front camera and/or the rear camera may receive external multimedia data. Each front camera and rear camera may be a fixed optical lens system or have focal length and optical zoom capabilities.
The audio component 810 is configured to output and/or input audio signals. For example, the audio component 810 includes a Microphone (MIC) configured to receive external audio signals when the electronic device 800 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may be further stored in the memory 804 or transmitted via the communication component 816. In some embodiments, audio component 810 further includes a speaker for outputting audio signals.
Input/output interface 812 provides an interface between processing component 802 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: homepage button, volume button, start button, and lock button.
The sensor assembly 814 includes one or more sensors for providing status assessment of various aspects of the electronic device 800. For example, the sensor assembly 814 may detect an on/off state of the electronic device 800, a relative positioning of the components, such as a display and keypad of the electronic device 800, the sensor assembly 814 may also detect a change in position of the electronic device 800 or a component of the electronic device 800, the presence or absence of a user's contact with the electronic device 800, an orientation or acceleration/deceleration of the electronic device 800, and a change in temperature of the electronic device 800. The sensor assembly 814 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an acceleration sensor, a gyroscopic sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.
The communication component 816 is configured to facilitate communication between the electronic device 800 and other devices, either wired or wireless. The electronic device 800 may access a wireless network based on a communication standard, such as WiFi,2G, or 3G, or a combination thereof. In one exemplary embodiment, the communication component 816 receives broadcast signals or broadcast related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, the communication component 816 further includes a Near Field Communication (NFC) module to facilitate short range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, ultra Wideband (UWB) technology, bluetooth (BT) technology, and other technologies.
In an exemplary embodiment, the electronic device 800 may be implemented by one or more Application Specific Integrated Circuits (ASICs), digital Signal Processors (DSPs), digital Signal Processing Devices (DSPDs), programmable Logic Devices (PLDs), field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic elements for performing the defect detection methods of the above-described components.
In an exemplary embodiment, a non-transitory computer readable storage medium is also provided, such as memory 804 including instructions executable by processor 820 of electronic device 800 to perform the method of defect detection of components described above. For example, the non-transitory computer readable storage medium may be ROM, random Access Memory (RAM), CD-ROM, magnetic tape, floppy disk, optical data storage device, etc.
The electronic device may be a stand-alone electronic device or may be part of a stand-alone electronic device, for example, in one embodiment, the electronic device may be an integrated circuit (Integrated Circuit, IC) or a chip, where the integrated circuit may be an IC or a collection of ICs; the chip may include, but is not limited to, the following: GPU (Graphics Processing Unit, graphics processor), CPU (Central Processing Unit ), FPGA (Field Programmable Gate Array, programmable logic array), DSP (Digital Signal Processor ), ASIC (Application Specific Integrated Circuit, application specific integrated circuit), SOC (System on Chip, SOC, system on Chip or System on Chip), etc. The integrated circuit or the chip may be used to execute executable instructions (or codes) to implement the defect detection method of the component. The executable instructions may be stored on the integrated circuit or chip or may be retrieved from another device or apparatus, such as the integrated circuit or chip including a processor, memory, and interface for communicating with other devices. The executable instructions may be stored in the memory, which when executed by the processor, implement the above-described method of defect detection of a component; alternatively, the integrated circuit or the chip may receive the executable instruction through the interface and transmit the executable instruction to the processor for execution, so as to implement the defect detection method of the component.
In another exemplary embodiment, a computer program product is also provided, comprising a computer program executable by a programmable apparatus, the computer program having code portions for performing the above-described defect detection method of a component when executed by the programmable apparatus.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure. This disclosure is intended to cover any adaptations, uses, or adaptations of the disclosure following the general principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It is to be understood that the present disclosure is not limited to the precise arrangements and instrumentalities shown in the drawings, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (10)
1. A method of detecting defects in a component, comprising:
collecting a first image of a part to be detected;
performing defect detection on the first image based on the defect detection model to obtain a defect detection result;
executing three-dimensional modeling operation according to the first image and the defect detection result to obtain three-dimensional point cloud data;
performing connected domain construction operation on the three-dimensional point cloud data to obtain a target connected domain;
and determining a target detection result of the part to be detected based on the target connected domain.
2. The method of claim 1, wherein performing a three-dimensional modeling operation based on the first image and the defect detection result to obtain three-dimensional point cloud data comprises:
obtaining standard model data corresponding to the part to be detected;
and executing three-dimensional modeling operation according to the first image, the defect detection result and the standard model data to obtain the three-dimensional point cloud data.
3. The method of claim 2, wherein performing a three-dimensional modeling operation based on the first image, the defect detection result, and the standard model data to obtain three-dimensional point cloud data comprises:
constructing initial point cloud data based on the first image and the defect detection result;
and correcting the initial point cloud data according to the standard model data to obtain the three-dimensional point cloud data.
4. The method of claim 1, wherein the defect detection results include a defect number and a defect volume, the method further comprising:
determining the quality level of the part to be detected according to the defect quantity and the defect volume;
and determining whether the part to be detected is qualified or not based on the quality level.
5. The method of claim 4, wherein the defect detection result further comprises a defect morphology, the method further comprising:
and if the part is determined to be disqualified, eliminating the part, and/or adjusting the production process of the part to be detected based on at least one of the defect number, the defect volume and the defect morphology.
6. The method of any one of claims 1 to 5, wherein the first image is an X-Ray image.
7. A defect detecting device for a component, comprising:
the acquisition module is configured to acquire a first image of the part to be detected;
the acquisition module is configured to detect the defects of the first image based on the defect detection model to obtain a defect detection result;
the modeling module is configured to execute three-dimensional modeling operation according to the first image and the defect detection result to obtain three-dimensional point cloud data;
the construction module is configured to execute connected domain construction operation aiming at the three-dimensional point cloud data to obtain a target connected domain;
and the determining module is configured to determine a target detection result of the part to be detected based on the target connected domain.
8. An electronic device, comprising:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to:
collecting a first image of a part to be detected;
performing defect detection on the first image based on the defect detection model to obtain a defect detection result;
executing three-dimensional modeling operation according to the first image and the defect detection result to obtain three-dimensional point cloud data;
performing connected domain construction operation on the three-dimensional point cloud data to obtain a target connected domain;
and determining a target detection result of the part to be detected based on the target connected domain.
9. A computer readable storage medium having stored thereon computer program instructions, which when executed by a processor, implement the steps of the method of any of claims 1 to 6.
10. A chip, comprising a processor and an interface; the processor is configured to read instructions to perform the method of any one of claims 1 to 6.
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