CN111356914A - Detection method and detection device - Google Patents
Detection method and detection device Download PDFInfo
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- CN111356914A CN111356914A CN201880068619.2A CN201880068619A CN111356914A CN 111356914 A CN111356914 A CN 111356914A CN 201880068619 A CN201880068619 A CN 201880068619A CN 111356914 A CN111356914 A CN 111356914A
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Abstract
The embodiment of the application discloses a detection method and a detection device, wherein the method comprises the following steps: the processor acquires a plurality of preset exposure durations corresponding to the measured object from the memory, and the processor acquires a radioactive ray transmission diagram of the measured object corresponding to each preset exposure duration according to the radioactive rays acquired by the detector in each preset exposure duration; any of the radiation transmission maps includes one or more distinct target sub-regions; the processor identifies the target sub-area in each radioactive ray transmission image and obtains a fused image of the measured object according to all the identified target sub-areas; and the processor identifies the fused image according to the defect model to obtain a detection result of the detected object. According to the method, the radiation is used for irradiating the measured object to obtain the plurality of radiation perspective views corresponding to different exposure durations, and then the fused image is identified according to the defect model, so that the detection efficiency and the detection precision are improved.
Description
The embodiment of the application relates to the technical field of electronics, in particular to a detection method and a detection device.
In order to ensure that the electronic product normally functions, it is necessary to detect whether the electronic product has defects before the electronic product is used. The traditional detection method is to manually detect the electronic product by using the magnifying glass, and because the electronic product has the characteristics of compact structure and concentrated component arrangement, when the traditional detection method is used for detecting the electronic product, a detection result is observed by depending on the vision of a tester, the efficiency is low, and the precision is not guaranteed.
Disclosure of Invention
The embodiment of the application provides a detection method and a detection device, which can improve detection efficiency and detection precision.
In a first aspect, an embodiment of the present application provides a detection method, which is applied to an electronic device, where the electronic device includes: the device comprises a radioactive ray emission unit, a detector, a processor and a memory, wherein a measured object is placed between the radioactive ray emission unit and the detector; the method comprises the following steps:
the processor acquires N preset exposure durations corresponding to the measured object from the memory, wherein N is an integer equal to or greater than 2, and the radiation transmission diagram corresponding to any one preset exposure duration comprises one or more clear target sub-areas;
the processor obtains a radiation transmission diagram of the measured object corresponding to each preset exposure duration according to the radiation acquired by the detector in each preset exposure duration in the N preset exposure durations;
the processor identifies a target sub-area in each radioactive ray transmission image and obtains a fused image of the measured object according to the identified target sub-area;
and the processor identifies the fused image according to the defect model to obtain a detection result of the detected object.
According to the method and the device, the radiation is adopted to irradiate the measured object to obtain the plurality of radiation perspective views corresponding to different exposure durations, the target sub-region in each radiation transmission image is identified, the fused image is obtained according to the identified target sub-region, and then the fused image is identified according to the defect model to obtain the detection result of the measured object. Because the fused image is obtained by a plurality of clear target subregions, the fused image is identified according to the defect model, and the detection efficiency and the detection precision are improved.
In some possible embodiments of the present application, the electronic device further includes an output unit, and the method further includes:
the processor sends a first message to the output unit, wherein the first message carries the detection result;
the output unit outputs the detection result according to the received first message.
In some possible embodiments of the present application, the detection result includes: one or more of normal, broken, rough edge, scratch, terminal skew, pin missing;
in some possible embodiments of the present application, the output unit may include a display screen, and may display the probabilities of the various possible detection results, or the number of the various detection results, or mark the positions of the detected defects in a graph in combination with a picture representing the detected object, and mark the detected defects. This is advantageous for visually displaying and observing possible defects of the object to be measured.
In some possible embodiments of the present application, before the processor obtains, from the memory, N preset exposure time periods corresponding to the object to be measured, the method further includes:
the sampling unit identifies the measured object and sends an identification result to the processor;
and the processor acquires N preset exposure durations corresponding to the measured object from the memory according to the acquired identification result.
The identification result may be a category identifier of the measured object, the measured objects of different categories may correspond to different exposure durations, the category identifier and exposure duration information corresponding thereto may be pre-stored in the database, and the processor searches for data stored in the database after acquiring the category identifier of the measured object, to obtain N exposure durations corresponding to the measured object.
By adopting the embodiment, the automatic detection of the detected object is facilitated, and the processor can directly acquire the N preset exposure durations corresponding to the detected object according to the identification result of the detected object.
In some possible embodiments of the present application, the electronic device further includes a transmission unit; before the sampling unit identifies the measured object, the method further includes:
the transmission unit moves different detected objects to a detection position every preset time, and the detection position is located between the radioactive ray emission source and the detector.
By adopting the embodiment, a plurality of detected objects can be automatically moved to the detection position one by one for detection, and the detection efficiency is favorably improved.
In some possible embodiments of the present application, before the processor identifies the fused image according to a defect model, the method further includes:
and the processor performs defect data training and learning according to a preset defect training sample corresponding to the detected object to obtain a defect model corresponding to the detected object.
It should be noted that the defect model may be obtained by the processor through training and learning the defect data according to the preset defect sample, or may be obtained from other devices.
In some possible embodiments of the present application, before the processor obtains, from the memory, N preset exposure durations corresponding to the object to be measured, the method further includes:
and the processor determines N preset exposure durations corresponding to the object to be detected according to the structure and/or the test of the object to be detected, and stores the N preset exposure durations into the memory.
It should be noted that different substances have different transmission capacities for radiation, and a plurality of exposure durations are determined according to the structure of the object to be detected or by a test or by referring to the structure of the object to be detected and combining the test, so that clear pictures of each part of the object to be detected in different exposure durations can be acquired, and the detection precision can be improved.
In a second aspect, an embodiment of the present application provides a detection apparatus, including: the device comprises a radioactive ray emission unit, a detector, a processor and a memory, wherein a measured object is placed between the radioactive ray emission unit and the detector;
the radioactive ray emission unit is used for emitting radioactive rays which are used for irradiating the object to be measured;
the detector is used for receiving the radioactive rays transmitted by the measured object;
the processor is used for acquiring N preset exposure durations corresponding to the measured object from the memory, wherein N is an integer equal to or greater than 2, and the radiation transmission diagram corresponding to any one preset exposure duration comprises one or more clear target sub-areas;
the processor is further configured to obtain a radiation transmission diagram of the measured object corresponding to each preset exposure duration according to the radiation acquired by the detector in each preset exposure duration of the N preset exposure durations;
the processor is further configured to identify a target sub-region in each of the radiation transmission maps, obtain a fused image of the object to be detected according to the identified target sub-region, and identify the fused image according to a defect model to obtain a detection result of the object to be detected.
According to the method and the device, the measured object is irradiated by radioactive rays to obtain a plurality of radioactive ray perspective views corresponding to different exposure durations, then the target sub-regions in each radioactive ray transmission image are identified, the fused images are obtained according to the identified target sub-regions, and then the fused images are identified according to the defect model to obtain the detection result of the measured object. Because the fused image is obtained by a plurality of clear target subregions, the fused image is identified according to the defect model, and the detection efficiency and the detection precision are improved.
In some possible embodiments of the present application, the electronic device further includes: an output unit;
the processor is further configured to send a first message to the output unit, where the first message carries the detection result;
the output unit outputs the detection result according to the received first message.
In some possible embodiments of the present application, the detection result includes: one or more of normal, broken, rough edge, scratch, terminal skew, pin missing;
in some possible embodiments of the present application, the output unit may include a display screen, and may display the probabilities of the various possible detection results, or the number of the various detection results, or mark the positions of the detected defects in a graph in combination with a picture representing the detected object, and mark the detected defects. This is advantageous for visually displaying and observing possible defects of the object to be measured.
In some possible embodiments of the present application, the detecting device further includes:
and the sampling unit is used for identifying the measured object and sending an identification result to the processor before the processor acquires the N preset exposure durations corresponding to the measured object from the memory.
The processor is specifically configured to, in terms of acquiring the N preset exposure durations corresponding to the object to be measured from the memory, acquire the N preset exposure durations corresponding to the object to be measured from the memory according to the identification result acquired from the sampling unit.
In some possible embodiments of the present application, the detecting device further includes:
and the transmission unit is used for moving different detected objects to a detection position every preset time before the sampling unit identifies the detected objects, and the detection position is positioned between the radioactive ray emission source and the detector.
By adopting the embodiment, a plurality of detected objects can be automatically moved to the detection position one by one for detection, and the detection efficiency is favorably improved.
In some possible embodiments of the present application, the processor is further configured to, before identifying the defect of the object to be measured according to the defect model and the fusion image, perform defect data training and learning according to a preset defect training sample corresponding to the object to be measured, and obtain the defect model corresponding to the object to be measured.
In some possible embodiments of the present application, the processor is further configured to determine, according to a structure and/or an experiment of the object to be tested, N preset exposure durations corresponding to the object to be tested before obtaining the N preset exposure durations corresponding to the object to be tested from the memory, and hold the N preset exposure durations in the memory.
It should be noted that different substances have different transmission capacities for radiation, and a plurality of exposure durations are determined according to the structure of the object to be detected or by tests or by referring to the structure of the object to be detected and combining the tests, so that clear pictures of parts of the object to be detected under different durations can be acquired, and the detection precision can be improved.
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic view of an application scenario of an electronic device including a detection apparatus according to an embodiment of the present application;
fig. 2A is a schematic flowchart of a detection method according to an embodiment of the present disclosure;
fig. 2B is a schematic flow chart of another detection method provided in the embodiment of the present application;
fig. 2C is a schematic flow chart of another detection method provided in the embodiment of the present application;
fig. 3A is a schematic structural diagram of a detection apparatus according to an embodiment of the present disclosure;
fig. 3B is a schematic structural diagram of another detection apparatus provided in the embodiment of the present application;
fig. 3C is a schematic structural diagram of another detection apparatus provided in the embodiment of the present application.
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It is to be understood that the terminology used in the embodiments of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the examples of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It is noted that the following detailed description describes embodiments of the invention, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative only and should not be construed as limiting the invention.
The following disclosure provides many different embodiments, or examples, for implementing different features of the invention. To simplify the disclosure of the present invention, the components and arrangements of specific examples are described below. Of course, they are merely examples and are not intended to limit the present invention. Furthermore, the present invention may repeat reference numerals and/or letters in the various examples. This repetition is for the purpose of simplicity and clarity and does not in itself dictate a relationship between the various embodiments and/or configurations discussed.
The form and the structure of the connector vary greatly, along with the difference of applied object, frequency, power, applied environment, etc., there are various different forms of connectors, but no matter which kind of connector, when it works normally, all will guarantee that the electric current circulates smoothly continuously and reliably, the needle pin in the connector is the important structure of connector, mainly used for electric conduction and signal transmission, the connector is in the production process, pin is when assembling, because the cylinder motion has the uneven condition of atress, lead to the pin foot to appear inclining probably, influence the final quality of product, therefore it is necessary to detect the pin foot of connector, traditional detection method is that the inspector uses the magnifying glass to detect whether the connector is qualified, this kind of method relies on inspector's visual intuition completely, the rate of accuracy is low, the precision is not ensured. According to the method and the device, the object to be detected is irradiated by radioactive rays, the multiple target sub-regions are obtained by utilizing the radioactive ray transmission images corresponding to different exposure durations, the fused image of the object to be detected is obtained according to the target sub-regions, and then the fused image is identified according to the defect model, so that the detection result of the object to be detected is obtained. Because the fused image is obtained by a plurality of clear target subregions, the fused image is identified according to the defect model, and the detection efficiency and the detection precision are improved.
Referring to fig. 1, fig. 1 is a schematic view of an application scenario of an electronic device including a detection apparatus according to an embodiment of the present disclosure. As shown in fig. 1, the electronic device may include: a radiation emitting unit 101, a detector 103, a memory 104, and a processor 105, with an object under test 102 placed between the radiation emitting unit 101 and the detector 103; when an object 102 to be measured is detected, the radiation emitting unit 101 emits radiation to irradiate the object 102 to be measured, the detector 103 generates an image corresponding to the object 102 to be measured according to the radiation passing through the object 102 to be measured, the processor 105 acquires N preset exposure time durations corresponding to the object 102 to be measured from the memory 104, wherein N is an integer equal to or greater than 2, and a radiation transmission image corresponding to any one preset exposure time duration comprises one or more clear target sub-areas; the processor 105 obtains a radiation transmission diagram of the measured object 102 corresponding to each preset exposure duration according to the radiation acquired by the detector 103 in each preset exposure duration in the N preset exposure durations; the processor 105 identifies a target sub-region in each radiation transmission map, and obtains a fused image of the object to be measured 102, that is, an image including a plurality of target sub-regions, according to the identified target sub-regions; the processor 105 identifies the fused image according to the defect model to obtain a detection result of the object 102 to be detected. Because the fused image is obtained by a plurality of clear target subregions, the fused image is identified according to the defect model, and the detection efficiency and the detection precision are improved.
Referring to fig. 2A, fig. 2A is a schematic flowchart of a detection method provided in an embodiment of the present application, where the detection method is applied to an electronic device, and the electronic device includes: the device comprises a radioactive ray emission unit, a detector, a processor and a memory, wherein a measured object is placed between the radioactive ray emission unit and the detector; the method comprises the following steps 201-204:
201. the processor obtains N preset exposure time lengths corresponding to the measured object from the memory, wherein N is an integer equal to or greater than 2, and the radioactive ray transmission diagram corresponding to any preset exposure time length comprises one or more clear target sub-areas.
In some possible embodiments, the processor may determine N preset exposure durations corresponding to the object to be measured according to a structure of the object to be measured, and store the N preset exposure durations in the memory. For example, if the object to be measured includes structures G1, G2, and G3 made of 3 different materials, if the three different structures have different degrees of sharpness when exposed for different periods of time, N may be set to 3, and it is determined by experiments how long the different structures are exposed to obtain a sharp image, for example, if the structure G1 has a period of 2 seconds, the processor may obtain a sharp image of the structure G1 according to the radiation received by the detector, and the preset exposure period corresponding to the structure G1 is 2 seconds. If the processor obtains a clear image of the structure G2 according to the radiation received by the detector when the exposure time of the structure G2 is 5 seconds, the preset exposure time corresponding to the structure G2 is 5 seconds. If the processor obtains a clear image of the structure G3 according to the radiation received by the detector when the exposure time of the structure G3 is 9 seconds, the preset exposure time corresponding to the structure G3 is 9 seconds. Therefore, 3 preset exposure time periods corresponding to the measured object may be set in advance to be 2 seconds, 5 seconds, and 9 seconds, respectively.
It is understood that, in some possible embodiments, the material of different positions of the object to be detected is the same, because there are differences in shape structures and the like, for example, the thickness is different, so that the sharpness of the images obtained by different positions of the object to be detected in different exposure time periods is different, and the images obtained according to different exposure time periods can be used for detecting different positions. It can be understood that the determination of the preset time length of the measured object can be determined through tests, the preset time length is stored in the memory after the determination, and when a certain measured object is detected, the preset time length corresponding to the measured object is taken out from the memory.
202. And the processor obtains the radioactive ray transmission diagram of the measured object corresponding to each preset exposure time length according to the radioactive ray obtained by the detector in each preset exposure time length in the N preset exposure time lengths.
The processor can obtain the radiation transmission images corresponding to the measured object under different exposure time lengths according to the radiation acquired by the detector under different exposure time lengths. Taking fig. 1 as an example, the object under test 102 includes three different regions: a region a1, a region a2, and a region An, wherein the region a1 is most clear in the radiation transmission chart corresponding to the exposure time period T1, the region a2 is most clear in the radiation transmission chart corresponding to the exposure time period T2, and the region An is most clear in the radiation transmission chart corresponding to the exposure time period Tn. The processor generates radiation transmittance maps p1, p2 and p3 of the object 102 to be measured from the radiation received by the detectors when the object is exposed for time periods T1, T2 and Tn, respectively.
203. And the processor identifies the target sub-area in each radioactive ray transmission image and obtains a fused image of the measured object according to the identified target sub-area.
Taking the object 102 in fig. 1 as An example, after the processor 105 acquires the radiation transmission maps p1, p2 and p3 of the object 102 generated from the radiation received by the detector when the exposure time of the object 102 is T1, T2 and Tn, respectively, the processor identifies the clear regions in each perspective view, i.e., the target sub-regions of each picture, such as the target sub-region a1 from the map p1, the target sub-region a2 from the map p2 and the target sub-region An from the map p 3. The processor then processes each extracted target sub-region to obtain a fused image p comprising a1, a2 and A3.
It should be noted that, when the object to be detected is a connector, the materials of different structural members on the connector are different, so that the imaging quality of different structural members on the connector is affected by different exposure time factors to different degrees, and the imaging quality can be expressed in the aspects of brightness, contrast, edge information and the like.
204. And the processor identifies the fused image according to the defect model to obtain a detection result of the detected object.
In some possible embodiments, the processor performs defect data training and learning according to a preset defect training sample corresponding to the detected object to obtain a defect model corresponding to the detected object. Taking fig. 1 as an example, if it is determined through recognition that the area corresponding to a1 has no defect and the areas corresponding to a2 and A3 have a defect, an image corresponding to the area including the defect may be displayed as a detection result. It is understood that the existence of defects can be further reminded through voice or icons or dynamic reminding pictures.
In some possible embodiments, the processor may automatically identify the defect of the object under test using a deep learning neural network. Before detecting the measured object, the defect of the measured object is identified in advance through a large number of training samples, for example, more than 100 images are respectively collected according to different defect types to be used as training samples, the samples capable of directly reflecting the defect are subjected to classification training to obtain the defect image of the measured object after training, when detection is carried out, the image after image fusion is compared with the defect image of the measured object obtained in advance, the possible defect is identified, and the identification result possibly comprises: normal, damaged, rough edges, scratches, terminals distorted, missing pins, etc.
According to the method and the device, the radiation is adopted to irradiate the measured object to obtain the plurality of radiation perspective views corresponding to different exposure durations, the target sub-region in each radiation transmission image is identified, the fused image is obtained according to the identified target sub-region, and then the fused image is identified according to the defect model to obtain the detection result of the measured object. Because the fused image is obtained by a plurality of clear target subregions, the fused image is identified according to the defect model, and the detection efficiency and the detection precision are improved.
Referring to fig. 2B, fig. 2B is a schematic flowchart of a detection method according to another embodiment of the present application, where the detection method is applied to an electronic device, and the electronic device includes: the device comprises a radioactive ray emission unit, a detector, a processor and a memory, wherein a measured object is placed between the radioactive ray emission unit and the detector; the method comprises step 211-215, which is as follows:
211. the sampling unit identifies the measured object and sends an identification result to the processor.
For example, after the object to be measured is placed between the radiation emitting unit and the detector, the sampling unit starts to detect the object to be measured, taking the object to be measured as the connector as an example, and after the connector is placed between the radiation emitting unit and the detector, the sampling unit identifies the object to be measured, and identifies the object to be measured as the connector.
212. And the processor acquires N preset exposure durations corresponding to the measured object from the memory according to the acquired identification result. And N is an integer equal to or greater than 2, and the radiation transmission diagram corresponding to any one preset exposure time period comprises one or more clear target sub-regions.
It should be noted that the memory stores the preset exposure time length corresponding to at least one detection object, for example, N preset exposure time lengths corresponding to connectors are stored in the memory in advance, for example, N may be 3, and the preset exposure time lengths may be 2 seconds, 5 seconds, and 9 seconds.
In some possible embodiments, the processor may determine N preset exposure durations corresponding to the object to be measured according to a structure of the object to be measured, and store the N preset exposure durations in the memory. For example, if the object to be measured includes structures G1, G2, and G3 made of 3 different materials, if the three different structures have different degrees of sharpness when exposed for different periods of time, N may be set to 3, and it is determined by experiments how long the different structures are exposed to obtain a sharp image, for example, if the structure G1 has a period of 2 seconds, the processor may obtain a sharp image of the structure G1 according to the radiation received by the detector, and the preset exposure period corresponding to the structure G1 is 2 seconds. If the processor obtains a clear image of the structure G2 according to the radiation received by the detector when the exposure time of the structure G2 is 5 seconds, the preset exposure time corresponding to the structure G2 is 5 seconds. If the processor obtains a clear image of the structure G3 according to the radiation received by the detector when the exposure time of the structure G3 is 9 seconds, the preset exposure time corresponding to the structure G3 is 9 seconds. Therefore, 3 preset exposure time periods corresponding to the measured object may be set in advance to be 2 seconds, 5 seconds, and 9 seconds, respectively.
It is understood that, in some possible embodiments, the material of different positions of the object to be detected is the same, because there are differences in shape structures and the like, for example, the thickness is different, so that the sharpness of the images obtained by different positions of the object to be detected in different exposure time periods is different, and the images obtained according to different exposure time periods can be used for detecting different positions. It can be understood that the determination of the preset time length of the measured object can be determined through tests, the preset time length is stored in the memory after the determination, and when a certain measured object is detected, the preset time length corresponding to the measured object is taken out from the memory.
213. And the processor obtains the radioactive ray transmission diagram of the measured object corresponding to each preset exposure time length according to the radioactive ray obtained by the detector in each preset exposure time length in the N preset exposure time lengths.
The processor can obtain the radiation transmission images corresponding to the measured object under different exposure time lengths according to the radiation acquired by the detector under different exposure time lengths. Taking fig. 1 as an example, the object under test 102 includes three different regions: a region a1, a region a2, and a region An, wherein the region a1 is most clear in the radiation transmission chart corresponding to the exposure time period T1, the region a2 is most clear in the radiation transmission chart corresponding to the exposure time period T2, and the region An is most clear in the radiation transmission chart corresponding to the exposure time period Tn. The processor generates radiation transmittance maps p1, p2 and p3 of the object 102 to be measured from the radiation received by the detectors when the object is exposed for time periods T1, T2 and Tn, respectively.
214. And the processor identifies the target sub-area in each radioactive ray transmission image and obtains a fused image of the measured object according to the identified target sub-area.
Taking the object 102 in fig. 1 as An example, after the processor 105 acquires the radiation transmission maps p1, p2 and p3 of the object 102 generated from the radiation received by the detector when the exposure time of the object 102 is T1, T2 and Tn, respectively, the processor identifies the clear regions in each perspective view, i.e., the target sub-regions of each picture, such as the target sub-region a1 from the map p1, the target sub-region a2 from the map p2 and the target sub-region An from the map p 3. The processor then processes each extracted target sub-region to obtain a fused image p comprising a1, a2 and A3.
It should be noted that, when the object to be detected is a connector, the materials of different structural members on the connector are different, so that the imaging quality of different structural members on the connector is affected by different exposure time factors to different degrees, and the imaging quality can be expressed in the aspects of brightness, contrast, edge information and the like. 215. And the processor identifies the fused image according to the defect model to obtain a detection result of the detected object.
In some possible embodiments, the processor performs defect data training and learning according to a preset defect training sample corresponding to the detected object to obtain a defect model corresponding to the detected object. Taking fig. 1 as an example, if it is determined through recognition that the area corresponding to a1 has no defect and the areas corresponding to a2 and A3 have a defect, an image corresponding to the area including the defect may be displayed as a detection result. It is understood that the existence of defects can be further reminded through voice or icons or dynamic reminding pictures.
In some possible embodiments, the processor may automatically identify the defect of the object under test using a deep learning neural network. Before detecting the measured object, the defect of the measured object is identified in advance through a large number of training samples, for example, more than 100 images are respectively collected according to different defect types to be used as training samples, the samples capable of directly reflecting the defect are subjected to classification training to obtain the defect image of the measured object after training, when detection is carried out, the image after image fusion is compared with the defect image of the measured object obtained in advance, the possible defect is identified, and the identification result possibly comprises: normal, damaged, rough edges, scratches, terminals distorted, missing pins, etc.
Referring to fig. 2C, fig. 2C is a schematic flowchart of a detection method according to another embodiment of the present application, where the detection method is applied to an electronic device, and the electronic device includes: the device comprises a radioactive ray emission unit, a detector, a processor and a memory, wherein a measured object is placed between the radioactive ray emission unit and the detector; the method comprises steps 221-226, which are as follows:
221. the transmission unit transmits different detected objects to a detection position every preset time, and the detection position is located between the radioactive ray emission source and the detector.
In some possible embodiments, the length of the interval between the transmission of the object to be detected by the transmission belt is determined by the detection speed of the object to be detected, and the transmission of the next object to be detected between the radiation emitting unit and the detector via the transmission belt may be set after the detection result of the current object to be detected is obtained. For example, if the detection period of one object to be detected is 15 seconds, the conveyor belt conveys another object to be detected to the detection position every 15 seconds. It can be understood that the conveying speed of the conveyor belt is different for different objects to be measured, for example, if the detection time duration of the first object to be measured is 15 seconds, and the detection time duration of the second object to be measured is 30 seconds, when the first object to be measured is detected, the conveyor belt conveys the next first object to be measured to the measured position every 15 seconds. When the second type of measured object is detected, the conveyor belt conveys the next second type of measured object to the measured position every 30 seconds. It can be understood that the conveying speed of the conveying belt may also adopt the detection time corresponding to the detected object with the longest detection time as the interval time for the conveying belt to convey two adjacent detected objects.
222. The sampling unit identifies the measured object and sends an identification result to the processor.
For example, after the object to be measured is placed between the radiation emitting unit and the detector, the sampling unit starts to detect the object to be measured, taking the object to be measured as the connector as an example, and after the connector is placed between the radiation emitting unit and the detector, the sampling unit identifies the object to be measured, and identifies the object to be measured as the connector.
223. And the processor acquires N preset exposure durations corresponding to the measured object from the memory according to the acquired identification result. And N is an integer equal to or greater than 2, and the radiation transmission map corresponding to any one preset exposure time comprises one or more clear target sub-regions.
It should be noted that the memory stores the preset exposure time length corresponding to at least one detection object, for example, N preset exposure time lengths corresponding to connectors are stored in the memory in advance, for example, N may be 3, and the preset exposure time lengths may be 2 seconds, 5 seconds, and 9 seconds.
In some possible embodiments, the processor may determine N preset exposure durations corresponding to the object to be measured according to a structure of the object to be measured, and store the N preset exposure durations in the memory. For example, if the object to be measured includes structures G1, G2, and G3 made of 3 different materials, if the three different structures have different degrees of sharpness when exposed for different periods of time, N may be set to 3, and it is determined by experiments how long the different structures are exposed to obtain a sharp image, for example, if the structure G1 has a period of 2 seconds, the processor may obtain a sharp image of the structure G1 according to the radiation received by the detector, and the preset exposure period corresponding to the structure G1 is 2 seconds. If the processor obtains a clear image of the structure G2 according to the radiation received by the detector when the exposure time of the structure G2 is 5 seconds, the preset exposure time corresponding to the structure G2 is 5 seconds. If the processor obtains a clear image of the structure G3 according to the radiation received by the detector when the exposure time of the structure G3 is 9 seconds, the preset exposure time corresponding to the structure G3 is 9 seconds. Therefore, 3 preset exposure time periods corresponding to the measured object may be set in advance to be 2 seconds, 5 seconds, and 9 seconds, respectively.
It is understood that, in some possible embodiments, the material of different positions of the object to be detected is the same, because there are differences in shape structures and the like, for example, the thickness is different, so that the sharpness of the images obtained by different positions of the object to be detected in different exposure time periods is different, and the images obtained according to different exposure time periods can be used for detecting different positions. It can be understood that the determination of the preset time length of the measured object can be determined through tests, the preset time length is stored in the memory after the determination, and when a certain measured object is detected, the preset time length corresponding to the measured object is taken out from the memory.
224. And the processor obtains the radioactive ray transmission diagram of the measured object corresponding to each preset exposure time length according to the radioactive ray obtained by the detector in each preset exposure time length in the N preset exposure time lengths.
The processor can obtain the radiation transmission images corresponding to the measured object under different exposure time lengths according to the radiation acquired by the detector under different exposure time lengths. Taking fig. 1 as an example, the object under test 102 includes three different regions: a region a1, a region a2, and a region An, wherein the region a1 is most clear in the radiation transmission chart corresponding to the exposure time period T1, the region a2 is most clear in the radiation transmission chart corresponding to the exposure time period T2, and the region An is most clear in the radiation transmission chart corresponding to the exposure time period Tn. The processor generates radiation transmittance maps p1, p2 and p3 of the object 102 to be measured from the radiation received by the detectors when the object is exposed for time periods T1, T2 and Tn, respectively.
225. And the processor identifies the target sub-area in each radioactive ray transmission image and obtains a fused image of the measured object according to the identified target sub-area.
Taking the object 102 in fig. 1 as An example, after the processor 105 acquires the radiation transmission maps p1, p2 and p3 of the object 102 generated from the radiation received by the detector when the exposure time of the object 102 is T1, T2 and Tn, respectively, the processor identifies the clear regions in each perspective view, i.e., the target sub-regions of each picture, such as the target sub-region a1 from the map p1, the target sub-region a2 from the map p2 and the target sub-region An from the map p 3. The processor then processes each extracted target sub-region to obtain a fused image p comprising a1, a2 and A3.
It should be noted that, when the object to be detected is a connector, the materials of different structural members on the connector are different, so that the imaging quality of different structural members on the connector is affected by different exposure time factors to different degrees, and the imaging quality can be expressed in the aspects of brightness, contrast, edge information and the like.
226. And the processor identifies the fused image according to the defect model to obtain a detection result of the detected object.
The conveying unit can automatically move a plurality of detected objects to the detection position one by one for detection, and detection efficiency is improved.
In some possible embodiments of the present application, the electronic device further includes an output unit, and the method further includes:
the processor sends a first message to the output unit, wherein the first message carries the detection result;
the output unit outputs the detection result according to the received first message.
In some possible embodiments of the present application, the output unit may include a display screen, and may display the probabilities of the various possible detection results, or the number of the various detection results, or mark the positions of the detected defects in a graph in combination with a picture representing the detected object, and mark the detected defects. This is advantageous for visually displaying and observing possible defects of the object to be measured.
The above description has introduced the solution of the embodiment of the present application mainly from the perspective of the method-side implementation process. It is understood that the terminal includes corresponding hardware structures and/or software modules for performing the respective functions in order to implement the above-described functions. Those of skill in the art will readily appreciate that the present application is capable of hardware or a combination of hardware and computer software implementing the various illustrative elements and algorithm steps described in connection with the embodiments provided herein. Whether a function is performed as hardware or computer software drives hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiment of the present application, the terminal may be divided into the functional units according to the above method example, for example, each functional unit may be divided corresponding to each function, or two or more functions may be integrated into one processing unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit. It should be noted that the division of the unit in the embodiment of the present application is schematic, and is only a logic function division, and there may be another division manner in actual implementation.
Referring to fig. 3A, fig. 3A is a schematic structural diagram of a detection apparatus according to an embodiment of the present disclosure. As shown in fig. 3A, the detecting device 310 includes: a radiation emitting unit 311, a detector 312, a processor 313, and a memory 314, with the object 300 under test placed between the radiation emitting unit 311 and the detector 312;
a radiation emitting unit 311 for emitting radiation for irradiating the object to be measured.
A detector 312 for receiving the radiation transmitted through the object to be measured.
And the processor 313 is configured to acquire N preset exposure durations corresponding to the object to be measured from the memory, where N is an integer equal to or greater than 2, and a radiation transmission map corresponding to any one of the preset exposure durations includes one or more clear target sub-regions.
The processor 313 is further configured to obtain a radiation transmittance map of the measured object corresponding to each preset exposure duration according to the radiation acquired by the detector in each preset exposure duration of the N preset exposure durations.
In some possible embodiments, the processor may determine N preset exposure durations corresponding to the object to be measured according to a structure of the object to be measured, and store the N preset exposure durations in the memory. For example, if the object to be measured includes structures G1, G2, and G3 made of 3 different materials, if the three different structures have different degrees of sharpness when exposed for different periods of time, N may be set to 3, and it is determined by experiments how long the different structures are exposed to obtain a sharp image, for example, if the structure G1 has a period of 2 seconds, the processor may obtain a sharp image of the structure G1 according to the radiation received by the detector, and the preset exposure period corresponding to the structure G1 is 2 seconds. If the processor obtains a clear image of the structure G2 according to the radiation received by the detector when the exposure time of the structure G2 is 5 seconds, the preset exposure time corresponding to the structure G2 is 5 seconds. If the processor obtains a clear image of the structure G3 according to the radiation received by the detector when the exposure time of the structure G3 is 9 seconds, the preset exposure time corresponding to the structure G3 is 9 seconds. Therefore, 3 preset exposure time periods corresponding to the measured object may be set in advance to be 2 seconds, 5 seconds, and 9 seconds, respectively.
It is understood that, in some possible embodiments, the material of different positions of the object to be detected is the same, because there are differences in shape structures and the like, for example, the thickness is different, so that the sharpness of the images obtained by different positions of the object to be detected in different exposure time periods is different, and the images obtained according to different exposure time periods can be used for detecting different positions. It can be understood that the determination of the preset time length of the measured object can be determined through tests, the preset time length is stored in the memory after the determination, and when a certain measured object is detected, the preset time length corresponding to the measured object is taken out from the memory.
The processor can obtain the radiation transmission images corresponding to the measured object under different exposure time lengths according to the radiation acquired by the detector under different exposure time lengths. Taking fig. 1 as an example, the object under test 102 includes three different regions: a region a1, a region a2, and a region An, wherein the region a1 is most clear in the radiation transmission chart corresponding to the exposure time period T1, the region a2 is most clear in the radiation transmission chart corresponding to the exposure time period T2, and the region An is most clear in the radiation transmission chart corresponding to the exposure time period Tn. The processor generates radiation transmittance maps p1, p2 and p3 of the object 102 to be measured from the radiation received by the detectors when the object is exposed for time periods T1, T2 and Tn, respectively.
The processor 313 is further configured to identify a target sub-region in each of the radiation transmission maps, obtain a fused image of the object to be detected according to the identified target sub-region, and identify the fused image according to a defect model to obtain a detection result of the object to be detected.
Taking the object 102 in fig. 1 as An example, after the processor 105 acquires the radiation transmission maps p1, p2 and p3 of the object 102 generated from the radiation received by the detector when the exposure time of the object 102 is T1, T2 and Tn, respectively, the processor identifies the clear regions in each perspective view, i.e., the target sub-regions of each picture, such as the target sub-region a1 from the map p1, the target sub-region a2 from the map p2 and the target sub-region An from the map p 3. The processor then processes each extracted target sub-region to obtain a fused image p comprising a1, a2 and A3.
It should be noted that, when the object to be detected is a connector, the materials of different structural members on the connector are different, so that the imaging quality of different structural members on the connector is affected by different exposure time factors to different degrees, and the imaging quality can be expressed in the aspects of brightness, contrast, edge information and the like.
In some possible embodiments, the processor performs defect data training and learning according to a preset defect training sample corresponding to the detected object to obtain a defect model corresponding to the detected object. Taking fig. 1 as an example, if it is determined through recognition that the area corresponding to a1 has no defect and the areas corresponding to a2 and A3 have a defect, an image corresponding to the area including the defect may be displayed as a detection result. It is understood that the existence of defects can be further reminded through voice or icons or dynamic reminding pictures.
According to the method and the device, the radiation is adopted to irradiate the measured object to obtain the plurality of radiation perspective views corresponding to different exposure durations, the target sub-region in each radiation transmission image is identified, the fused image is obtained according to the identified target sub-region, and then the fused image is identified according to the defect model to obtain the detection result of the measured object. Because the fused image is obtained by a plurality of clear target subregions, the fused image is identified according to the defect model, and the detection efficiency and the detection precision are improved.
Referring to fig. 3B, fig. 3B is a schematic structural diagram of another detection apparatus according to an embodiment of the present disclosure. As shown in fig. 3B, the detecting device 310 further includes a sampling unit 315, which is opposite to the embodiment shown in fig. 3A.
The sampling unit 315 is configured to identify the object 300 to be tested before the processor 313 acquires the N preset exposure durations corresponding to the object 300 to be tested from the memory 314, and send the identification result to the processor 313.
For example, after the object to be measured is placed between the radiation emitting unit and the detector, the sampling unit starts to detect the object to be measured, taking the object to be measured as the connector as an example, and after the connector is placed between the radiation emitting unit and the detector, the sampling unit identifies the object to be measured, and identifies the object to be measured as the connector.
The processor 313 is specifically configured to, in terms of acquiring the N preset exposure durations corresponding to the object to be measured from the memory, acquire the N preset exposure durations corresponding to the object to be measured from the memory according to the identification result acquired from the sampling unit.
It should be noted that the memory stores the preset exposure time length corresponding to at least one detection object, for example, N preset exposure time lengths corresponding to connectors are stored in the memory in advance, for example, N may be 3, and the preset exposure time lengths may be 2 seconds, 5 seconds, and 9 seconds.
In some possible embodiments, the processor may determine N preset exposure durations corresponding to the object to be measured according to a structure of the object to be measured, and store the N preset exposure durations in the memory. For example, if the object to be measured includes structures G1, G2, and G3 made of 3 different materials, if the three different structures have different degrees of sharpness when exposed for different periods of time, N may be set to 3, and it is determined by experiments how long the different structures are exposed to obtain a sharp image, for example, if the structure G1 has a period of 2 seconds, the processor may obtain a sharp image of the structure G1 according to the radiation received by the detector, and the preset exposure period corresponding to the structure G1 is 2 seconds. If the processor obtains a clear image of the structure G2 according to the radiation received by the detector when the exposure time of the structure G2 is 5 seconds, the preset exposure time corresponding to the structure G2 is 5 seconds. If the processor obtains a clear image of the structure G3 according to the radiation received by the detector when the exposure time of the structure G3 is 9 seconds, the preset exposure time corresponding to the structure G3 is 9 seconds. Therefore, 3 preset exposure time periods corresponding to the measured object may be set in advance to be 2 seconds, 5 seconds, and 9 seconds, respectively.
It is understood that, in some possible embodiments, the material of different positions of the object to be detected is the same, because there are differences in shape structures and the like, for example, the thickness is different, so that the sharpness of the images obtained by different positions of the object to be detected in different exposure time periods is different, and the images obtained according to different exposure time periods can be used for detecting different positions. It can be understood that the determination of the preset time length of the measured object can be determined through tests, the preset time length is stored in the memory after the determination, and when a certain measured object is detected, the preset time length corresponding to the measured object is taken out from the memory.
By adopting the embodiment, the automatic detection of the detected object is facilitated, and the processor can directly acquire the N preset exposure durations corresponding to the detected object according to the identification result of the detected object.
Referring to fig. 3C, fig. 3C is a schematic structural diagram of another detection device according to an embodiment of the present disclosure. As shown in fig. 3C, this embodiment is opposite to the embodiment shown in fig. 3B, and the detection device 310 further includes a transmission unit 316.
The transfer unit 316 is configured to transfer different objects 300 to be measured to a detection position at intervals of a preset time period before the object 300 to be measured is identified by the sampling unit 315, the detection position being located between the radiation emitting unit 311 and the detector 312.
In some possible embodiments, the length of the interval between the transmission of the object to be detected by the transmission belt is determined by the detection speed of the object to be detected, and the transmission of the next object to be detected between the radiation emitting unit and the detector via the transmission belt may be set after the detection result of the current object to be detected is obtained. For example, if the detection period of one object to be detected is 15 seconds, the conveyor belt conveys another object to be detected to the detection position every 15 seconds. It can be understood that the conveying speed of the conveyor belt is different for different objects to be measured, for example, if the detection time duration of the first object to be measured is 15 seconds, and the detection time duration of the second object to be measured is 30 seconds, when the first object to be measured is detected, the conveyor belt conveys the next first object to be measured to the measured position every 15 seconds. When the second type of measured object is detected, the conveyor belt conveys the next second type of measured object to the measured position every 30 seconds. It can be understood that the conveying speed of the conveyor belt may also adopt the detection period corresponding to the detected object with the longest detection time as the interval time for the conveyor belt to convey two adjacent detected objects.
The conveying unit can automatically move a plurality of detected objects to the detection position one by one for detection, and detection efficiency is improved.
In some possible embodiments of the present application, the detection device may further include: an output unit; the processor is further configured to send a first message to the output unit, where the first message carries the detection result; the output unit outputs the detection result according to the received first message. The detection result comprises: one or more of normal, broken, rough edge, scratch, terminal skew, pin missing; the output unit may include a display screen, and may display the probability of each possible detection result, or the number of each detection result, or mark the detected defect in the image by combining with the image representing the detected object, and mark the detected defect. This is advantageous for visually displaying and observing possible defects of the object to be measured.
The embodiment of the application also provides electronic equipment comprising the detection device, and the detection device can be the detection device in any one of the previous embodiments.
Embodiments of the present application also provide a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, and the computer program enables a computer to execute part or all of the steps of any one of the detection methods as described in the above method embodiments.
Embodiments of the present application also provide a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program causes a computer to execute part or all of the steps of any one of the detection methods as described in the above method embodiments.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one type of division of logical functions, and there may be other divisions when actually implementing, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or units, and may be an electric or other form.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable memory, which may include: flash memory disks, read-only memory, random access memory, magnetic or optical disks, and the like.
While the invention has been described with reference to a preferred embodiment, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
- The detection method is applied to electronic equipment, and the electronic equipment comprises the following steps: the device comprises a radioactive ray emission unit, a detector, a processor and a memory, wherein a measured object is placed between the radioactive ray emission unit and the detector; the method comprises the following steps:the processor acquires N preset exposure durations corresponding to the measured object from the memory, wherein N is an integer equal to or greater than 2, and the radiation transmission diagram corresponding to any one preset exposure duration comprises one or more clear target sub-areas;the processor obtains a radiation transmission diagram of the measured object corresponding to each preset exposure duration according to the radiation acquired by the detector in each preset exposure duration in the N preset exposure durations;the processor identifies a target sub-area in each radioactive ray transmission image and obtains a fused image of the measured object according to the identified target sub-area;and the processor identifies the fused image according to the defect model to obtain a detection result of the detected object.
- The method of claim 1, wherein the electronic device further comprises a sampling unit, and before the processor obtains the N preset exposure time periods corresponding to the object to be measured from the memory, the method further comprises:the sampling unit identifies the measured object and sends an identification result to the processor;and the processor acquires N preset exposure durations corresponding to the measured object from the memory according to the acquired identification result.
- The method of claim 2, wherein the electronic device further comprises a transmitting unit; before the sampling unit identifies the measured object, the method further includes:the transmission unit transmits different detected objects to a detection position every preset time, and the detection position is located between the radioactive ray emission source and the detector.
- The method of claim 1, wherein prior to the processor identifying the fused image from a defect model, the method further comprises:and the processor performs defect data training and learning according to a preset defect training sample corresponding to the detected object to obtain a defect model corresponding to the detected object.
- The method according to any one of claims 1 to 4, wherein before the processor obtains the N preset exposure time periods corresponding to the object under test from the memory, the method further comprises:and the processor determines N preset exposure durations corresponding to the object to be detected according to the structure and/or the test of the object to be detected, and stores the N preset exposure durations into the memory.
- A detection device, comprising: the device comprises a radioactive ray emission unit, a detector, a processor and a memory, wherein a measured object is placed between the radioactive ray emission unit and the detector;the radioactive ray emission unit is used for emitting radioactive rays which are used for irradiating the object to be measured;the detector is used for receiving the radioactive rays transmitted by the measured object;the processor is used for acquiring N preset exposure durations corresponding to the measured object from the memory, wherein N is an integer equal to or greater than 2, and the radiation transmission diagram corresponding to any one preset exposure duration comprises one or more clear target sub-areas;the processor is further configured to obtain a radiation transmission diagram of the measured object corresponding to each preset exposure duration according to the radiation acquired by the detector in each preset exposure duration of the N preset exposure durations;the processor is further configured to identify a target sub-region in each of the radiation transmission maps, obtain a fused image of the object to be detected according to the identified target sub-region, and identify the fused image according to a defect model to obtain a detection result of the object to be detected.
- The detection device of claim 6, further comprising:the sampling unit is used for identifying the object to be detected before the processor acquires N preset exposure durations corresponding to the object to be detected from the memory and sending an identification result to the processor;the processor is specifically configured to, in terms of acquiring the N preset exposure durations corresponding to the object to be measured from the memory, acquire the N preset exposure durations corresponding to the object to be measured from the memory according to the identification result acquired from the sampling unit.
- The detection device according to claim 7, further comprising:and the transmitting unit is used for transmitting different detected objects to a detection position every preset time before the sampling unit identifies the detected objects, and the detection position is positioned between the radioactive ray emission source and the detector.
- The detection apparatus according to claim 6,and the processor is further used for carrying out defect data training and learning according to a preset defect training sample corresponding to the detected object before identifying the fused image according to the defect model to obtain the defect model corresponding to the detected object.
- The detection apparatus according to any one of claims 6 to 9,and the processor is further used for determining the N preset exposure durations corresponding to the measured object according to the structure and/or the test of the measured object before acquiring the N preset exposure durations corresponding to the measured object from the memory, and storing the N preset exposure durations into the memory.
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