Defect detection method and device, electronic equipment and storage medium

Abstract

The invention provides a defect detection method and device, electronic equipment and a storage medium, and the method comprises the steps: controlling a first motor to drive detection equipment to move along a first axis, and controlling a second motor to drive the detection equipment to move along a second axis; under the condition that it is determined that the detection equipment starts to move, obtaining an image obtained by shooting the photovoltaic equipment by the detection equipment; under the condition that the first motor and the second motor move to preset termination positions, the first motor and the second motor are controlled to stop driving the detection equipment to move; and determining defect information of the photovoltaic equipment according to the image. The invention relates to the technical field of defect detection, and can improve the accuracy of defect detection.

Description

Technical Field

[0001] This application relates to the technical field of defect detection, and in particular to a defect detection method, device, electronic device, and storage medium. Background Art

[0002] Currently, in the practice of detecting hidden cracks in photovoltaic power plants, most solutions rely on the electroluminescence (EL) detection technology. This detection method usually adopts a sampling inspection mode and requires the detection operation to be completed in a darkroom environment. The unique requirements of this detection method limit the development of defect detection work. It not only requires the special construction of darkroom facilities, increasing the detection cost and the pre-preparation time, but also makes it difficult to carry out the detection work regularly and efficiently due to factors such as site and environment. Moreover, this sampling inspection method cannot comprehensively detect all photovoltaic modules in the power plant, and it is difficult to accurately and comprehensively find all the hidden crack modules in the power plant, resulting in low accuracy in detecting the defects of photovoltaic equipment. Summary of the Invention

[0003] In view of the above, it is necessary to provide a defect detection method, device, electronic device, and storage medium to solve the technical problem of low accuracy in detecting the defects of photovoltaic equipment.

[0004] This application provides a defect detection method applied to an electronic device. The electronic device is respectively communicatively connected to a first motor, a second motor, and a detection device. The first motor and the second motor are used to drive the detection device to move. The method includes: controlling the first motor to drive the detection device to move along a first axis, and controlling the second motor to drive the detection device to move along a second axis; obtaining an image of a photovoltaic device captured by the detection device when it is determined that the detection device starts to move; controlling the first motor and the second motor to stop driving the detection device to move when the first motor and the second motor move to a preset termination position; and determining defect information of the photovoltaic device according to the image.

[0005] In some embodiments, controlling the first motor to drive the detection device to move along the first axis and controlling the second motor to drive the detection device to move along the second axis when a start signal is received includes: controlling the first motor and the second motor to drive the detection device to move multiple times based on a preset movement pattern; wherein the movement pattern includes: controlling the first motor to drive the detection device to move along the first axis in a first direction; when it is determined that the first motor moves to the termination position of the first axis, controlling the second motor to drive the detection device to move along the second axis in a second direction by a preset first distance; controlling the first motor to drive the detection device to move along the first axis in a third direction; wherein the first direction and the third direction are opposite; when it is determined that the first motor moves to the termination position of the first axis, controlling the second motor to drive the detection device to move along the second axis in a second direction by a preset first distance.

[0006] In some embodiments, controlling the first motor to drive the detection device to move along the first axis and controlling the second motor to drive the detection device to move along the second axis when a start signal is received includes: controlling the first motor and the second motor to drive the detection device to move multiple times based on a preset movement pattern; wherein the movement pattern includes: controlling the second motor to drive the detection device to move along the second axis in a second direction by a preset first distance; controlling the first motor to drive the detection device to move along the first axis in a first direction; when it is determined that the first motor moves to the termination position of the first axis, controlling the second motor to drive the detection device to move along the second axis in a second direction by a preset first distance; controlling the first motor to drive the detection device to move along the first axis in a third direction; wherein the first direction and the third direction are opposite.

[0007] In some embodiments, controlling the first motor and the second motor to stop driving the detection device to move when the first motor and the second motor move to preset termination positions includes: when a first termination signal of the first motor is obtained, determining that the first motor moves to the termination position of the first axis; the first termination signal is used to indicate that the first motor abuts against a limiting member connected to the first axis; when a second termination signal of the second motor is obtained, determining that the second motor moves to the termination position of the second axis; the second termination signal is used to indicate that the second motor abuts against a limiting member connected to the second axis; controlling the first motor and the second motor to stop driving the detection device to move.

[0008] In some embodiments, acquiring an image obtained by the detection device photographing a photovoltaic device when it is determined that the detection device starts to move includes: when it is determined that the detection device starts to move, controlling the detection device to photograph the photovoltaic device according to a preset first sampling frequency to obtain an image corresponding to the photovoltaic device.

[0009] In some embodiments, the method further includes: after detecting a defect of the photovoltaic device based on the image, controlling the detection device to photograph the photovoltaic device according to a second sampling frequency to obtain an image corresponding to the photovoltaic device; wherein the second sampling frequency is greater than the first sampling frequency; when the first motor moves to the termination position of the first axis or the second motor moves to the termination position of the second axis, controlling the detection device to photograph the photovoltaic device according to a third sampling frequency to obtain an image corresponding to the photovoltaic device; wherein the third sampling frequency is less than the first sampling frequency.

[0010] In some embodiments, determining defect information of the photovoltaic device based on the image includes: determining a texture feature in the image according to a gray value of a pixel point in the image; determining a candidate defect region in the image according to the texture feature; and determining the defect information of the photovoltaic device according to the semantics of image information of the candidate defect region.

[0011] An embodiment of the present application further provides a defect detection device, which is applied to an electronic device. The electronic device is respectively communicatively connected to a first motor, a second motor, and a detection device. The first motor and the second motor are used to drive the detection device to move. The device includes: controlling the first motor to drive the detection device to move along a first axis, and controlling the second motor to drive the detection device to move along a second axis; acquiring an image obtained by the detection device photographing a photovoltaic device when it is determined that the detection device starts to move; when the first motor and the second motor move to a preset termination position, controlling the first motor and the second motor to stop driving the detection device to move; and determining defect information of the photovoltaic device according to the image.

[0012] An embodiment of the present application further provides an electronic device, which includes: a memory storing at least one instruction; and a processor executing the instruction stored in the memory to implement the described defect detection method.

[0013] An embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the defect detection method is implemented.

[0014] As can be seen from the above technical solutions, the embodiments of the present application can automatically control the first motor and the second motor to drive the detection device to move along the first axis and the second axis, and automatically acquire images after the detection device starts to move, which can reduce the need for manual intervention to improve the speed of defect detection. The electronic device can process and analyze the images captured by the detection device in real time, shorten the detection cycle, and improve the efficiency of the defect detection task. By controlling the movement of the first motor and the second motor, the electronic device ensures that the detection device can move along a preset path and speed, which can ensure that the detection range covers the entire area of the photovoltaic device, reduce errors in the detection process, and improve the accuracy of defect identification. Moreover, the electronic device can optimize image acquisition parameters (such as exposure time, light source brightness, etc.) to ensure high-quality images are obtained, providing data support for subsequent defect identification. In addition, the electronic device can preset the termination position according to the actual detection requirements to ensure that the detection device automatically stops moving after completing the detection of the preset area, which can adapt to the detection requirements of photovoltaic devices of different sizes and shapes, thereby enhancing the flexibility of defect detection for photovoltaic devices. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 FIG. is an application scenario diagram of a defect detection method provided by an embodiment of the present application.

[0016] Figure 2 FIG. is a flowchart of a defect detection method provided by an embodiment of the present application.

[0017] Figure 3 FIG. is a functional module diagram of a defect detection device provided by an embodiment of the present application.

[0018] Figure 4 FIG. is a schematic structural diagram of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] In order to more clearly understand the objectives, features, and advantages of the present application, the present application will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, without conflict, the embodiments of the present application and the features in the embodiments may be combined with each other. In the following description, many specific details are set forth to fully understand the present application. The described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments.

[0020] In addition, the terms "first" and "second" are only used for descriptive purposes, and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of the described features. In the description of the present application, "a plurality" means two or more, unless otherwise specifically defined.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field to which this application belongs. The terms used in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0022] Embodiments of this application provide a defect detection method that can be applied to one or more electronic devices. An electronic device is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions. Its hardware includes, but is not limited to, a microprocessor, an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a digital signal processor (DSP), an embedded device, etc.

[0023] An electronic device can be any electronic product that can interact with a customer. For example, a personal computer, a tablet computer, a smart phone, a personal digital assistant (PDA), an Internet protocol television (IPTV), a smart wearable device, etc.

[0024] The electronic device may also include a network device and / or a client device. Among them, the network device includes, but is not limited to, a single network server, a server group composed of multiple network servers, or a cloud composed of a large number of hosts or network servers based on cloud computing.

[0025] The network where the electronic device is located includes, but is not limited to, the Internet, a wide area network, a metropolitan area network, a local area network, a virtual private network (VPN), etc.

[0026] Such as Figure 1The figure shows an application scenario diagram of a defect detection method provided by an embodiment of the present application. The defect detection method provided by the present application can be applied to an electronic device 100. Among them, the electronic device 100 can be any device with data transmission and data analysis functions, and the present application does not limit this. The electronic device 100 is respectively communicatively connected to a first motor 200, a second motor 300, and a detection device 400. The first motor 200 and the second motor 300 are used to drive the detection device 400 to move. Specifically, when the electronic device 100 receives a start signal input by the user, it controls the first motor 200 to drive the detection device 400 to move along a first axis 500, and controls the second motor 300 to drive the detection device 400 to move along a second axis 600. When the electronic device 100 determines that the detection device 400 starts to move, it acquires an image obtained by the detection device 400 photographing a photovoltaic device 700. When the first motor 200 and the second motor 300 move to a preset termination position, the electronic device 100 controls the first motor 200 and the second motor 300 to stop driving the detection device 400 to move. The electronic device 100 also determines defect information of the photovoltaic device 500 according to the image.

[0027] As Figure 2 shown, it is a flowchart of a defect detection method provided by an embodiment of the present application. According to different requirements, the order of steps in this flowchart can be changed, and some steps can be omitted. The defect detection method provided by the embodiments of the present application includes the following steps.

[0028] S20, control the first motor to drive the detection device to move along the first axis, and control the second motor to drive the detection device to move along the second axis.

[0029] In an embodiment of the present application, during the process of controlling the first motor and the second motor to drive the detection device to move along the two axes and acquire images, initial parameter configuration can be performed first to establish a basic environment for motion control and image acquisition. Specifically, the electronic device can read preset parameters (such as moving speed, acceleration, sampling frequency, image resolution, etc.) from a pre-stored configuration file or the cloud; and verify the states of sensors such as the encoders, laser rangefinders, and IMUs of the first motor and the second motor to ensure that the first motor and the second motor are in a fault-free state; it can also establish a spatial mapping relationship between the detection device and the photovoltaic panel through a calibration board or a laser tracker on the detection device.

[0030] In an embodiment of the present application, the electronic device also performs path planning and kinematic calculation on the first motor and the second motor, so as to convert the abstract detection requirements into pulse signals executable by the motors. Specifically, when generating the trajectory, a B-spline curve or NURBS algorithm can be used to generate a smooth trajectory according to the size of the photovoltaic panel and the defect distribution density, avoiding sudden stops and starts. When performing inverse kinematic calculation, the trajectory points are converted into the target positions of the motors on the first axis (for example, the X axis) and the second axis (for example, the Y axis), taking into account the length of the robotic arm and the joint angle limits. When performing speed planning, an S-shaped acceleration and deceleration curve can be used to reduce the impact of mechanical vibration on imaging.

[0031] In an embodiment of the present application, the electronic device also performs cooperative control on the first motor and the second motor, so as to achieve precise synchronous movement of the first motor and the second motor. Virtual spindle control: Taking the position of the main motor (such as the X axis) as the reference, a virtual axis signal is generated, and the slave motor (Y axis) follows the virtual axis. Dual closed-loop control: Outer loop (position loop): The position deviation is reduced through a PID controller. Inner loop (speed / current loop): Feedforward compensation is used to suppress load disturbances. Real-time compensation: The Kalman filter is used to fuse the encoder and IMU data to correct mechanical backlash and nonlinear errors.

[0032] In an embodiment of the present application, the electronic device also performs dynamic imaging timing control on the detection device, so as to capture high-quality images at the best time. Specifically, the triggering strategies include predictive triggering, predicting the time when the detection device reaches the key detection point based on the kinematic model and triggering image acquisition 20 ms in advance; the triggering strategy also includes event-driven triggering, using an event camera to image only when there is a sudden change in light (such as the edge of a crack); the triggering strategy also includes multi-modal synchronous triggering, synchronizing the acquisition timings of visible light, infrared, and ultrasonic sensors to achieve spatio-temporal alignment of data.

[0033] In an embodiment of the present application, during the process of defect detection of the photovoltaic device, the operating conditions of the first motor and the second motor are also detected for abnormalities and protected for safety, so as to improve the system robustness and prevent equipment damage. The electronic device also records the performance and operating status of the first motor, the second motor, and the detection device based on the operation log, so as to provide data support for optimizing long-term detection tasks.

[0034] In an embodiment of the present application, during the process of controlling the first motor and the second motor to drive the detection device to move, in order to increase the coverage range during the movement of the detection device, the first motor and the second motor can be controlled to drive the detection device to move multiple times based on a preset movement pattern.

[0035] In an embodiment of the present application, the movement mode includes: controlling the first motor to drive the detection device to move along the first direction of the first axis; when it is determined that the first motor moves to the end position of the first axis, controlling the second motor to drive the detection device to move a preset first distance along the second direction of the second axis; controlling the first motor to drive the detection device to move along the third direction of the first axis; wherein, the first direction and the third direction are opposite; when it is determined that the first motor moves to the end position of the first axis, controlling the second motor to drive the detection device to move a preset first distance along the second direction of the second axis.

[0036] In another embodiment of the present application, the movement mode includes: controlling the second motor to drive the detection device to move a preset first distance along the second direction of the second axis; controlling the first motor to drive the detection device to move along the first direction of the first axis; when it is determined that the first motor moves to the end position of the first axis, controlling the second motor to drive the detection device to move a preset first distance along the second direction of the second axis; controlling the first motor to drive the detection device to move along the third direction of the first axis; wherein, the first direction and the third direction are opposite.

[0037] S21, when it is determined that the detection device starts to move, obtain the image obtained by the detection device photographing the photovoltaic device.

[0038] In an embodiment of the present application, when the first motor and the second motor drive the detection device to move, the imaging system of the detection device is synchronously activated, so as to ensure that the image captured by the detection device can cover a larger range, ensure that the information in the image can indicate all details of the surface of the photovoltaic device, and thus improve the accuracy of defect detection of the photovoltaic device.

[0039] In an embodiment of the present application, the movement state of the detection device can be monitored in real time through the encoder feedback data of the first motor and / or the second motor. When it is detected that the speed of the motor driving the detection device to move exceeds the threshold (for example, 0.1 m / s), the electronic device controls the detection device to trigger the activation signal of its imaging system. The detection device verifies the communication status of its camera, light source (for example, LED ring light), and synchronous controller to ensure that the working condition of the detection device is fault-free. In addition, the detection device also pre-adjusts the camera exposure time and gain according to the ambient light sensor data to shorten the imaging preparation time.

[0040] In an embodiment of the present application, when controlling the detection device to photograph the photovoltaic device, the imaging parameters of the detection device are also dynamically adjusted to optimize the image quality according to the real-time motion state of the detection device. Exemplarily, the exposure time of the camera of the detection device can be dynamically adjusted, and the rolling shutter compensation algorithm is adopted to adjust the exposure time according to the device moving speed to avoid motion blur. For example, when the speed exceeds 0.5 m / s, the exposure time of the camera of the detection device can be set below 1 / 1000 s. The spectral tunable LED light source can also be used to match the reflection characteristics of the surface materials (such as glass and backplane) of the photovoltaic panel. The pulse width modulation (PWM) technology is applied to dynamically adjust the light source brightness according to the ambient light intensity to ensure the lighting uniformity.

[0041] In an embodiment of the present application, in order to increase the quantity and quality of the acquired images, the sampling frequency of the detection device for acquiring images can also be set according to the moving speed of the detection device, and when it is determined that the detection device starts to move, the detection device is controlled to photograph the photovoltaic device according to a preset first sampling frequency to obtain the image corresponding to the photovoltaic device.

[0042] In an embodiment of the present application, during the image acquisition process, the accuracy and scale quantity of the acquired images can be improved to reduce the load of the electronic device for defect detection based on the images. Specifically, high-resolution local feature images and low-resolution global images can be captured simultaneously, so as to balance the detection accuracy and speed. During the subsequent defect detection process, an image pyramid structure can be adopted to perform multi-scale analysis on the defects of the photovoltaic device.

[0043] In an embodiment of the present application, a spatio-temporal correlation relationship between the image and the position of the detection device can be established during the image storage process. Specifically, the camera shutter signal of the detection device and the motor encoder pulse can be synchronized based on the (Precision Time Protocol, PTP) to ensure the correspondence of the image, the position of the detection device, and the timestamp.

[0044] In an embodiment of the present application, in order to implement an exception handling and fault tolerance mechanism during the image acquisition process, thereby improving the accuracy of the defect detection result, anomalies such as jitter (through IMU data) and sudden light changes (through spectral sensors) during the image acquisition process can also be monitored. And when an abnormal situation is detected, an image repair algorithm (such as GAN-based image completion) is triggered to repair the local blurred area. If the repair fails, the abnormal position is recorded and given priority for re-inspection in the subsequent detection cycle.

[0045] Thus, by correlating the temporal information and spatial information of the image, it is possible to bind the image to the position of the detection device, thereby achieving defect localization after determining the defects of the photovoltaic device. By combining rolling shutter compensation and global shutter, it is possible to eliminate the image blur caused by the image acquisition during the movement of the detection device, ensure the quality of the acquired image when the detection device moves at a high speed, provide data support for subsequent defect detection, and thus improve the accuracy of defect detection while ensuring the efficiency of defect detection.

[0046] S22. When the first motor and the second motor move to a preset termination position, control the first motor and the second motor to stop driving the detection device to move.

[0047] In an embodiment of the present application, when the first motor and the second motor move to a preset termination position, it indicates that the detection device has captured a global image of the photovoltaic device. Therefore, the first motor and the second motor can be controlled to stop driving the detection device to move. Exemplarily, when the first motor moves and / or the second motor moves a preset distance, it is determined that the first motor and / or the second motor move to a preset termination position; when the first motor reciprocates along the first axis a preset number of times, it is determined that the first motor moves to the termination position, and when the second motor moves along the second axis a preset number of times, it is determined that the second motor moves to the termination position.

[0048] In an embodiment of the present application, in order to stop moving in time after the detection device acquires the global image of the photovoltaic device to improve the efficiency of defect detection, the motor can also be stopped from driving the detection device to move according to the signal when the motor contacts the limiting member. Specifically, when the first motor and the second motor move to a preset termination position, controlling the first motor and the second motor to stop driving the detection device to move includes: when the first termination signal of the first motor is acquired, determining that the first motor moves to the termination position of the first axis; the first termination signal is used to indicate that the first motor abuts against the limiting member connected to the first axis; when the second termination signal of the second motor is acquired, determining that the second motor moves to the termination position of the second axis; the second termination signal is used to indicate that the second motor abuts against the limiting member connected to the second axis; controlling the first motor and the second motor to stop driving the detection device to move. Among them, the limiting member can be a magnetic steel provided at the ends of the first axis and the second axis, and the present application does not limit the specific type of the limiting member.

[0049] S23. Determine the defect information of the photovoltaic device according to the image.

[0050] In an embodiment of the present application, in order to improve the accuracy of defect detection, the quality of the image can be monitored and optimized after the image is acquired to ensure that the image quality meets the requirements of defect detection. Specifically, the image sharpness index (for example, the gray variance of all pixel points in the image) and the illumination uniformity (for example, the standard deviation of all pixel points in the image) can be calculated in real time. When the quality of the image does not meet the requirements of defect detection, the image can also be enhanced based on a model with image enhancement capabilities (for example, a convolutional neural network model) to obtain an enhanced image.

[0051] In an embodiment of the present application, when acquiring an image during the movement of the detection device, the image quality may deteriorate due to motion blur or posture change, resulting in the blurring or deformation of the image features representing defects in the image, thereby increasing the difficulty of subsequent image analysis and even causing misjudgment. Therefore, the method further includes: after detecting a defect of the photovoltaic device based on the image, controlling the detection device to capture the photovoltaic device according to a second sampling frequency to obtain an image corresponding to the photovoltaic device; wherein, the second sampling frequency is greater than the first sampling frequency; when the first motor moves to the termination position of the first axis, or the second motor moves to the termination position of the second axis, controlling the detection device to capture the photovoltaic device according to a third sampling frequency to obtain an image corresponding to the photovoltaic device; wherein, the third sampling frequency is less than the first sampling frequency.

[0052] Exemplarily, when the detection device starts to move, the photovoltaic device can be captured based on a default first sampling frequency (for example, 500 Hz); after detecting a defect of the photovoltaic device based on the image, in order to improve the accuracy of subsequent identification of the defect of the photovoltaic device, the frequency of the detection device for acquiring images can be increased, and the detection device can be controlled to capture the photovoltaic device according to a second sampling frequency (for example, 1000 Hz) to obtain an image corresponding to the photovoltaic device. In this way, fewer images can be acquired at the initial stage of the defect detection process to reduce the number of images and improve the efficiency of defect detection, and the sampling frequency can be increased after detecting the defect to increase the number of images, thereby improving the accuracy of defect detection. When the first motor moves to the termination position of the first axis, or the second motor moves to the termination position of the second axis, it indicates that the detection device is at the boundary of the photovoltaic device and the detection device is in a state of changing the moving direction. At this time, the photovoltaic device can be captured according to a third sampling frequency (for example, 200 Hz) to further reduce the number of images at the boundary of the photovoltaic device, so as to improve the efficiency of defect detection.

[0053] In an embodiment of the present application, the defect of the photovoltaic device is used to indicate the morphological changes on the surface of the photovoltaic device that affect the performance of the photovoltaic device. Exemplarily, the defect of the photovoltaic device may be a hidden crack defect on the surface of the photovoltaic device, may also be a depression on the surface of the photovoltaic device, or may also be a deformation on the surface of the photovoltaic device. The present application does not limit the specific type of the defect of the photovoltaic device.

[0054] Specifically, determining the defect information of the photovoltaic device according to the image includes: determining the texture feature in the image according to the gray value of the pixel points in the image; determining the candidate defect area in the image according to the texture feature; and determining the defect information of the photovoltaic device according to the semantics of the image information of the candidate defect area.

[0055] Among them, the texture feature in the image is used to indicate the set of pixel points with large gray value changes in the image. When the gray values of any plurality of pixel points change greatly, it indicates that there are defects in the area corresponding to the plurality of pixel points on the photovoltaic device. Therefore, the candidate defect area can be determined according to the positions of the pixel points indicated by the texture feature in the image. And the semantics of the image information in the candidate area are identified based on the semantic analysis model to determine the defect information of the photovoltaic device. Among them, the semantic analysis model may be a transfer model, a residual neural network model, etc., and the present application does not limit this.

[0056] It can be seen from the above technical solutions that the embodiment of the present application can automatically control the first motor and the second motor to drive the detection device to move along the first axis and the second axis, and automatically acquire images after the detection device starts to move, which can reduce the need for manual intervention to improve the speed of defect detection. The electronic device can process and analyze the images captured by the detection device in real time, shorten the detection cycle, and improve the efficiency of the defect detection task. The electronic device controls the movement of the first motor and the second motor to ensure that the detection device can move along the preset path and speed, which can ensure that the detection range covers the entire area of the photovoltaic device, reduce errors in the detection process, and improve the accuracy of defect identification. And the electronic device can ensure the acquisition of high-quality images by optimizing image acquisition parameters (such as exposure time, light source brightness, etc.), providing data support for subsequent defect identification. And the electronic device can preset the termination position according to the actual detection requirements to ensure that the detection device automatically stops moving after completing the detection of the preset area, which can adapt to the detection requirements of photovoltaic devices of different sizes and shapes, thereby improving the flexibility of defect detection for photovoltaic devices.

[0057] Please refer to Figure 3 , Figure 3It is a functional module diagram of a defect detection device provided by an embodiment of the present application. The defect detection device 31 includes a moving module 311 and a detection module 312. The module / unit mentioned in the present application refers to a series of computer-readable instruction segments that can be executed by a processor 13 and can complete fixed functions, and are stored in a memory 12. In this embodiment, the functions of each module / unit will be described in detail in subsequent embodiments.

[0058] The moving module 311 is used to control the first motor to drive the detection device to move along a first axis, and control the second motor to drive the detection device to move along a second axis.

[0059] The detection module 312 is used to obtain an image obtained by the detection device photographing a photovoltaic device when it is determined that the detection device starts to move.

[0060] The moving module 311 is further used to control the first motor and the second motor to stop driving the detection device to move when the first motor and the second motor move to a preset termination position.

[0061] The detection module 312 is further used to determine defect information of the photovoltaic device according to the image.

[0062] In some embodiments, the moving module 311 is further used to control the first motor and the second motor to drive the detection device to move multiple times based on a preset moving mode; wherein, the moving mode includes: controlling the first motor to drive the detection device to move along the first axis in a first direction; when it is determined that the first motor moves to the termination position of the first axis, controlling the second motor to drive the detection device to move along the second axis in a second direction by a preset first distance; controlling the first motor to drive the detection device to move along the first axis in a third direction; wherein, the first direction and the third direction are opposite; when it is determined that the first motor moves to the termination position of the first axis, controlling the second motor to drive the detection device to move along the second axis in a second direction by a preset first distance.

[0063] In some embodiments, the moving module 311 is further configured to control the first motor and the second motor to drive the detection device to move multiple times based on a preset moving pattern; wherein, the moving pattern includes: controlling the second motor to drive the detection device to move a preset first distance along the second direction of the second axis; controlling the first motor to drive the detection device to move along the first direction of the first axis; when it is determined that the first motor moves to the termination position of the first axis, controlling the second motor to drive the detection device to move a preset first distance along the second direction of the second axis; controlling the first motor to drive the detection device to move along the third direction of the first axis; wherein, the first direction and the third direction are opposite to each other.

[0064] In some embodiments, the moving module 311 is further configured to determine that the first motor moves to the termination position of the first axis when obtaining a first termination signal of the first motor; the first termination signal is used to indicate that the first motor abuts against a limiting member connected to the first axis; when obtaining a second termination signal of the second motor, determining that the second motor moves to the termination position of the second axis; the second termination signal is used to indicate that the second motor abuts against a limiting member connected to the second axis; controlling the first motor and the second motor to stop driving the detection device to move.

[0065] In some embodiments, the detection module 312 is further configured to, when it is determined that the detection device starts to move, control the detection device to photograph the photovoltaic device according to a preset first sampling frequency, so as to obtain an image corresponding to the photovoltaic device.

[0066] In some embodiments, the detection module 312 is further configured to, after detecting a defect of the photovoltaic device according to the image, control the detection device to photograph the photovoltaic device according to a second sampling frequency, so as to obtain an image corresponding to the photovoltaic device; wherein, the second sampling frequency is greater than the first sampling frequency; when the first motor moves to the termination position of the first axis, or the second motor moves to the termination position of the second axis, controlling the detection device to photograph the photovoltaic device according to a third sampling frequency, so as to obtain an image corresponding to the photovoltaic device; wherein, the third sampling frequency is less than the first sampling frequency.

[0067] In some embodiments, the detection module 312 is further configured to determine a texture feature in the image according to the gray value of a pixel point in the image; determine a candidate defect area in the image according to the texture feature; determine defect information of the photovoltaic device according to the semantics of the image information of the candidate defect area.

[0068] Please refer to Figure 4, which is a schematic structural diagram of an electronic device provided by an embodiment of the present application. The electronic device 100 includes a memory 12 and a processor 13. The memory 12 is used to store computer-readable instructions, and the processor 13 is configured to execute the computer-readable instructions stored in the memory to implement a defect detection method described in any of the above embodiments.

[0069] In an embodiment of the present application, the electronic device 100 further includes a bus and a computer program stored in the memory 12 and executable on the processor 13, such as a defect detection program.

[0070] Figure 4 Only the electronic device 100 with a memory 12 and a processor 13 is shown. Those skilled in the art can understand that Figure 4 the shown structure does not constitute a limitation on the electronic device 100, and it may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0071] Combined with Figure 2 , the memory 12 in the electronic device 100 stores multiple computer-readable instructions to implement the defect detection method, and the processor 13 can execute the multiple instructions to achieve: controlling the first motor to drive the detection device to move along the first axis, and controlling the second motor to drive the detection device to move along the second axis; obtaining an image of the photovoltaic device captured by the detection device when it is determined that the detection device starts to move; controlling the first motor and the second motor to stop driving the detection device to move when the first motor and the second motor move to a preset termination position; and determining defect information of the photovoltaic device according to the image.

[0072] Specifically, the specific implementation method of the processor 13 for the above instructions can refer to Figure 2 the description of the relevant steps in the corresponding embodiment, which will not be elaborated here.

[0073] Those skilled in the art can understand that the schematic diagram is only an example of the electronic device 100 and does not constitute a limitation on the electronic device 100. The electronic device 100 can be a bus structure or a star structure. The electronic device 100 may further include more or fewer other hardware or software than shown, or different component arrangements. For example, the electronic device 100 may further include input / output devices, network access devices, etc.

[0074] It should be noted that the electronic device 100 is only an example, and other existing or future electronic products that can be adapted to the present application should also be included in the protection scope of the present application and are included herein by reference.

[0075] Among them, the memory 12 includes at least one type of readable storage medium, which can be non-volatile or volatile. The readable storage medium includes flash memory, mobile hard disk, multimedia card, card-type memory (such as SD or DX memory, etc.), magnetic memory, magnetic disk, optical disc, etc. In some embodiments, the memory 12 can be an internal storage unit of the electronic device 100, such as the mobile hard disk of the electronic device 100. In other embodiments, the memory 12 can also be an external storage device of the electronic device 100, such as a plug-in mobile hard disk, Smart Media Card (SMC), Secure Digital (SD) card, FlashCard, etc. equipped on the electronic device 100. The memory 12 can not only be used to store application software installed on the electronic device 100 and various types of data, such as the code of a defect detection program, etc., but also be used to temporarily store the data that has been output or will be output.

[0076] In some embodiments, the processor 13 can be composed of integrated circuits. For example, it can be composed of a single packaged integrated circuit, or can be composed of multiple integrated circuits with the same or different functions packaged, including a combination of one or more Central Processing Units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips, etc. The processor 13 is the control core (Control Unit) of the electronic device 100, connecting various components of the entire electronic device 100 through various interfaces and lines, and by running or executing programs or modules stored in the memory 12 (such as executing a defect detection program, etc.), and calling the data stored in the memory 12, to execute various functions of the electronic device 100 and process data.

[0077] The processor 13 executes the operating system of the electronic device 100 and various installed application programs. The processor 13 executes the application programs to implement the steps in the above-mentioned various embodiments of the defect detection method, such as Figure 2 the steps shown.

[0078] Exemplarily, the computer program can be divided into one or more modules / units, and the one or more modules / units are stored in the memory 12 and executed by the processor 13 to complete this application. The one or more modules / units can be a series of computer-readable instruction segments capable of performing specific functions, and these instruction segments are used to describe the execution process of the computer program in the electronic device 100. For example, the computer program can be divided into a mobile module 311 and a detection module 312.

[0079] The integrated units implemented in the form of software function modules can be stored in a computer-readable storage medium. The above-mentioned software function modules are stored in a storage medium and include several instructions for causing a computer device (which can be a personal computer, a computer device, or a network device, etc.) or a processor to execute a part of the defect detection method described in various embodiments of the present application.

[0080] If the integrated modules / units of the electronic device 100 are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, to implement all or part of the processes in the above-mentioned embodiment methods of the present application, it can also be completed by a computer program instructing relevant hardware devices. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-mentioned various method embodiments can be implemented.

[0081] Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory (ROM, Read-Only Memory), random access memory, and other memories, etc.

[0082] Furthermore, the computer-readable storage medium mainly includes a storage program area and a storage data area. Among them, the storage program area can store an operating system, application programs required for at least one function, etc.; the storage data area can store data created according to the use of the blockchain node, etc.

[0083] The bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of representation, in Figure 4 only one arrow is used to represent it, but it does not mean that there is only one bus or one type of bus. The bus is set to realize the connection and communication between the memory 12 and at least one processor 13, etc.

[0084] The embodiments of the present application also provide a computer-readable storage medium (not shown in the figure), in which computer-readable instructions are stored, and the computer-readable instructions are executed by a processor in an electronic device to implement the defect detection method described in any of the above embodiments.

[0085] In several embodiments provided by the present application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.

[0086] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0087] In addition, in each embodiment of the present application, the functional modules can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated unit can be implemented in the form of hardware, or in the form of hardware plus software functional modules.

[0088] In addition, obviously, the term "including" does not exclude other units or steps, and the singular does not exclude the plural. The multiple units or devices described in the specification can also be implemented by one unit or device through software or hardware. Words such as first and second are used to represent names and do not indicate any specific order.

[0089] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and not to limit them. Although the present application has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present application can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present application.

Claims

1. A defect detection method, applied to an electronic device, the electronic device being respectively communicatively connected to a first motor, a second motor, and a detection device, the first motor and the second motor being used to drive the detection device to move, characterized in that, The method includes: Controlling the first motor to drive the detection device to move along a first axis, and controlling the second motor to drive the detection device to move along a second axis; When it is determined that the detection device starts to move, acquiring an image obtained by the detection device photographing a photovoltaic device; When the first motor and the second motor move to a preset termination position, controlling the first motor and the second motor to stop driving the detection device to move; Determining defect information of the photovoltaic device according to the image.

2. The defect detection method according to claim 1, wherein The controlling the first motor to drive the detection device to move along the first axis and controlling the second motor to drive the detection device to move along the second axis when a start signal is received includes: Controlling the first motor and the second motor to drive the detection device to move multiple times based on a preset movement pattern; wherein, the movement pattern includes: Controlling the first motor to drive the detection device to move along the first axis in a first direction; When it is determined that the first motor moves to the termination position of the first axis, controlling the second motor to drive the detection device to move along the second axis in a second direction by a preset first distance; Controlling the first motor to drive the detection device to move along the first axis in a third direction; wherein, the first direction and the third direction are opposite; When it is determined that the first motor moves to the termination position of the first axis, controlling the second motor to drive the detection device to move along the second axis in a second direction by a preset first distance.

3. The defect detection method according to claim 1, wherein The controlling the first motor to drive the detection device to move along the first axis and controlling the second motor to drive the detection device to move along the second axis when a start signal is received includes: Controlling the first motor and the second motor to drive the detection device to move multiple times based on a preset movement pattern; wherein, the movement pattern includes: Controlling the second motor to drive the detection device to move along the second axis in a second direction by a preset first distance; Controlling the first motor to drive the detection device to move along the first axis in a first direction; When it is determined that the first motor moves to the termination position of the first axis, controlling the second motor to drive the detection device to move along the second axis in a second direction by a preset first distance; Controlling the first motor to drive the detection device to move along the first axis in a third direction; wherein, the first direction and the third direction are opposite.

4. The defect detection method according to claim 1, wherein The controlling the first motor and the second motor to stop driving the detection device to move when the first motor and the second motor move to a preset termination position includes: When a first termination signal of the first motor is acquired, determining that the first motor moves to the termination position of the first axis; the first termination signal is used to indicate that the first motor abuts against a limiting member connected to the first axis; When a second termination signal of the second motor is acquired, determining that the second motor moves to the termination position of the second axis; the second termination signal is used to indicate that the second motor abuts against a limiting member connected to the second axis; Controlling the first motor and the second motor to stop driving the detection device to move.

5. The defect detection method according to claim 1, characterized in that, When it is determined that the detection device starts to move, obtaining the image obtained by the detection device photographing the photovoltaic device includes: When it is determined that the detection device starts to move, controlling the detection device to photograph the photovoltaic device according to a preset first sampling frequency to obtain an image corresponding to the photovoltaic device.

6. The defect detection method according to claim 5, wherein The method further includes: After detecting a defect of the photovoltaic device based on the image, controlling the detection device to photograph the photovoltaic device according to a second sampling frequency to obtain an image corresponding to the photovoltaic device; wherein, the second sampling frequency is greater than the first sampling frequency. When the first motor moves to the termination position of the first axis or the second motor moves to the termination position of the second axis, controlling the detection device to photograph the photovoltaic device according to a third sampling frequency to obtain an image corresponding to the photovoltaic device; wherein, the third sampling frequency is less than the first sampling frequency.

7. The defect detection method according to claim 1, characterized in that Determining the defect information of the photovoltaic device based on the image includes: Determining the texture feature in the image according to the gray value of the pixel points in the image. Determining the candidate defect area in the image according to the texture feature. Determining the defect information of the photovoltaic device according to the semantics of the image information of the candidate defect area.

8. A defect detection device, characterized in that, Applied to an electronic device, the electronic device is respectively communicatively connected to a first motor, a second motor and a detection device, the first motor and the second motor are used to drive the detection device to move, and the device includes: A moving module, configured to control the first motor to drive the detection device to move along a first axis and control the second motor to drive the detection device to move along a second axis. A detection module, configured to obtain an image obtained by the detection device photographing the photovoltaic device when it is determined that the detection device starts to move. The moving module is further configured to control the first motor and the second motor to stop driving the detection device to move when the first motor and the second motor move to preset termination positions. The detection module is further configured to determine the defect information of the photovoltaic device according to the image.

9. An electronic device, characterized in that, The electronic device includes a processor and a storage device, and the processor is configured to implement the defect detection method according to any one of claims 1 to 7 when executing a computer program stored in the storage device.

10. A computer-readable storage medium, characterized in that, A computer-readable instruction is stored on the computer-readable storage medium, and when the computer-readable instruction is executed by a processor, the defect detection method according to any one of claims 1 to 7 is implemented.

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