Modularized transformer substation intelligent monitoring terminal based on electric red-ong

Abstract

The invention relates to the technical field of transformer substation intelligent monitoring, in particular to a modular transformer substation intelligent monitoring terminal based on electric red-ong, which comprises a lens movement module used for capturing image and video data; the self-checking module is used for detecting the running state and the surrounding environment of the device and can monitor faults and abnormities of the device in real time; the motor control module is used for controlling the horizontal and vertical movement of the lens; the light control module can automatically adjust the brightness according to the ambient light; the communication module is used for exchanging data with an external system; the modular design of the device can provide standardized hardware modules such as a lens movement, a power supply, a motor, a light control module and the like, and is convenient to adapt to a modular power transformation monitoring terminal.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent monitoring of substations, and in particular to a modular intelligent monitoring terminal for substations based on Dianhong. Background Art

[0002] With the advancement of power equipment technology, smart substation technology has been significantly developed, which has prompted the renewal of substation design concepts and the development of substation design towards prefabricated modularization. Substation patrol monitoring equipment is the most widely used intelligent terminal in smart substations. Its design, production and manufacturing are all integrated. In the case of camera damage, the maintenance method adopted is to replace the whole camera. In addition, patrol monitoring equipment lacks built-in self-checking algorithms, which is prone to abnormal situations that affect patrol monitoring without faults, affecting the normal operation of patrol monitoring.

[0003] Video detection algorithms mainly analyze image frames in video sequences and use computer vision algorithms to identify and locate target objects in images. The core principle of this technology is to combine deep learning models, especially convolutional neural networks (CNNs), to extract image features and use these features to identify the location and category of target objects. In this process, the algorithm learns the visual attributes of the target, such as shape, texture, and color, and can stably detect targets under different environments and lighting conditions. In addition, in order to process the temporal information in the video, recurrent neural networks (RNNs) or long short-term memory networks (LSTMs) are usually incorporated to consider the dynamic changes of targets in the time dimension. Overall, video object detection technology emphasizes accurate and real-time identification and tracking of targets in continuous image frames, thereby achieving a deep understanding of the video content. It is a solution to the problem of how to locate and identify targets that appear in each video. Compared with image object detection, video detection has the characteristics of high redundancy.

[0004] Aiming at the requirements of plant and station inspections, the present invention designs and develops a substation monitoring terminal with split, module plug-in and self-test functions, and adopts Dianhong to achieve standard unification from hardware to equipment, which helps to promote independent and intelligent upgrades at the power operation, maintenance and monitoring level. Summary of the invention

[0005] In view of the above problems or problems existing in the prior art, the present invention is proposed.

[0006] Therefore, the object of the present invention is to provide a modular substation intelligent monitoring terminal based on Dianhong.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions: a modular substation intelligent monitoring terminal based on Dianhong, comprising:

[0008] A lens core module for capturing image and video data;

[0009] A self-check module, which is used to detect the operating status and surrounding environment of the device and can monitor the faults and abnormalities of the device in real time;

[0010] A motor control module, which is used to control the horizontal and vertical movement of the lens;

[0011] Lighting control module, which can automatically adjust the brightness according to the ambient light;

[0012] A communication module, which is used to exchange data with an external system;

[0013] The power module is used to supply power to each module.

[0014] As a preferred solution of the modular substation intelligent monitoring terminal based on Dianhong of the present invention, wherein: the self-check module is provided with a picture blur self-check algorithm, which is used for real-time detection and early warning of picture blur;

[0015] The image blur self-checking algorithm adopts an image clarity evaluation model and an image feature extraction model, and its feature calculation rules include evaluating the sharpness of the edge in the image and the frequency components of the image.

[0016] As a preferred solution of the modular substation intelligent monitoring terminal based on Dianhong of the present invention, wherein: a jitter detection algorithm is provided in the self-check module, which is used for real-time detection and early warning of screen jitter;

[0017] The jitter detection algorithm uses an object detection model, an image quality assessment model and a motion detection model, and its feature calculation rules include analyzing pixel motion between consecutive frames to identify jitter patterns.

[0018] As a preferred solution of the modular substation intelligent monitoring terminal based on Dianhong of the present invention, wherein: a reflection detection algorithm is provided in the self-check module, which is used for real-time detection and early warning of the reflection of the screen;

[0019] The reflection detection algorithm adopts a target detection model, an image quality assessment model and a motion detection model, and its feature calculation rules include identifying abnormal highlight areas in the image.

[0020] As a preferred solution of the modular substation intelligent monitoring terminal based on Dianhong of the present invention, wherein: a lens condensation detection algorithm is provided in the self-check module, which is used for real-time detection and early warning of lens condensation;

[0021] The lens condensation detection algorithm adopts a target detection model, an image quality assessment model and a motion detection model, and its feature calculation rules include analyzing the brightness and color changes of local areas in the image.

[0022] As a preferred solution of the modular substation intelligent monitoring terminal based on Dianhong of the present invention, wherein: the self-check module is provided with a dirt detection algorithm, which is used for real-time detection and early warning of the dirtiness of the screen;

[0023] The dirt detection algorithm adopts a target detection model, an image quality assessment model and a motion detection model, and its feature calculation rules include identifying the dirt area in the image.

[0024] As a preferred solution of the modular substation intelligent monitoring terminal based on Dianhong of the present invention, wherein: the self-check module is provided with a foreign body occlusion detection algorithm, which is used for real-time detection and early warning of foreign body occlusion in the picture;

[0025] The foreign body occlusion detection algorithm adopts a target detection model, an image quality assessment model and a motion detection model, and its feature calculation rules include identifying objects that suddenly appear.

[0026] As a preferred solution of the modular substation intelligent monitoring terminal based on Dianhong of the present invention, wherein: a lens skew detection algorithm is provided in the self-check module, which is used to determine whether the lens deviates from the vertical direction;

[0027] The lens skew detection algorithm adopts a target detection model, an image quality assessment model and a motion detection model, and its feature calculation rules include analyzing geometric transformations in the image.

[0028] As a preferred solution of the modular substation intelligent monitoring terminal based on Dianhong of the present invention, the lens movement module includes a high-definition camera, an optical lens, and an image sensor, and the high-definition camera can adjust the optical lens according to the detection of the image sensor.

[0029] As a preferred solution of the modular substation intelligent monitoring terminal based on Dianhong of the present invention, wherein: the motor control module includes a motor driver and a position sensor, the motor driver can control the horizontal and vertical movement of the lens, and the position sensor is used to detect the current position of the position sensor;

[0030] The lighting control module includes an LED lamp, an infrared lamp, and a photosensitive sensor, and the photosensitive sensor determines whether to use the LED lamp or the infrared lamp according to the intensity of the detected light;

[0031] The communication module includes a wireless communication chip, an antenna, and a network interface.

[0032] The beneficial effects of the modular substation intelligent monitoring terminal based on Dianhong of the present invention: the modular design of the device can provide standardized hardware modules such as lens movement, power supply, motor, lighting control, etc., which is convenient for adapting to the modular substation monitoring terminal. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0034] Figure 1 This is a schematic diagram of the overall framework of the modular substation intelligent monitoring terminal based on Dianhong.

[0035] Figure 2 This is the software operation logic diagram of the modular substation intelligent monitoring terminal based on Dianhong. DETAILED DESCRIPTION

[0036] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0037] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0038] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0039] Example 1, reference Figure 1 , which is the first embodiment of the present invention, and provides a modular substation intelligent monitoring terminal based on Dianhong, including:

[0040] The lens movement module is used to capture image and video data; it should be noted that the lens movement module is the core perception unit of the intelligent monitoring device, responsible for capturing image and video data.

[0041] Specifically, the lens movement module includes a high-definition camera, an optical lens, and an image sensor. The high-definition camera can adjust the optical lens according to the detection of the image sensor, and can adjust the focal length, aperture, and focus according to monitoring requirements.

[0042] Self-check module, which is used to detect the operating status and surrounding environment of the device, and can monitor the faults and abnormalities of the device in real time, such as lens contamination, occlusion, motion detection, etc., and trigger corresponding alarms. The self-check module is equipped with self-check algorithms and related sensors;

[0043] The motor control module is used to control the horizontal and vertical movement of the lens; the motor control module includes a motor driver and a position sensor. The motor driver can control the horizontal and vertical movement of the lens, and the position sensor is used to detect the current position of the position sensor; by changing the position of the lens, the monitoring range can cover a wider area.

[0044] The lighting control module can automatically adjust the brightness according to the ambient light; the lighting control module includes LED lights, infrared lights, and photosensors. The photosensors determine whether to use LED lights or infrared lights according to the intensity of the detected light; the lighting control module can improve the monitoring effect at night or in low-light environments and is responsible for adjusting auxiliary lighting.

[0045] The communication module is used to exchange data with external systems; including connection with the Internet of Things platform and collaboration with other monitoring devices. The communication module includes a wireless communication chip, antenna, and network interface; and supports multiple communication protocols.

[0046] The power module is used to supply power to each module and provide necessary power supply to ensure the stable operation of the intelligent monitoring device.

[0047] In summary, the modular design of the device can provide standardized hardware modules such as lens movement, power supply, motor, and lighting control, which is convenient for adapting to modular substation monitoring terminals. Therefore, the software and hardware systems of the device can realize the split type, module plug-in and unplug, and self-test functions of the patrol equipment.

[0048] Example 2, reference Figure 1-2 , which is the second embodiment of the present invention. Different from the previous embodiment, a picture blur self-detection algorithm is provided in the self-detection module, which is used to perform real-time detection and early warning of picture blur; the picture blur self-detection algorithm focuses on the real-time picture captured by the camera, and the picture blur self-detection algorithm adopts an image clarity evaluation model and an image feature extraction model, and its feature calculation rules include evaluating the sharpness of the edges in the picture and the frequency components of the image.

[0049] In terms of specific implementation, by using edge detection operators such as the Laplace operator and Sobel operator to calculate the sharpness of the image, and using fast Fourier transform (FFT) to analyze the frequency components of the image, real-time monitoring and early warning of image blur are achieved.

[0050] Specifically, a jitter detection algorithm is provided in the self-check module, which is used to perform real-time detection and early warning of image jitter; the jitter detection algorithm focuses on the real-time image captured by the camera; the jitter detection algorithm adopts a target detection model, an image quality assessment model and a motion detection model, and its feature calculation rules include analyzing pixel motion between consecutive frames to identify jitter patterns.

[0051] In terms of specific implementation, the optical flow method is used to track pixel motion, and the Gaussian mixture model (GMM) or other statistical methods are used to analyze the distribution of pixel motion, thus achieving real-time monitoring and early warning of image jitter.

[0052] The self-check module is equipped with a reflection detection algorithm, which is used to perform real-time detection and early warning of image reflections; the reflection detection algorithm focuses on the real-time images captured by the camera; the reflection detection algorithm adopts a target detection model, an image quality assessment model and a motion detection model, and its feature calculation rules include identifying abnormal highlight areas in the image.

[0053] In terms of specific implementation, by using color and brightness histogram analysis and area-based background subtraction, sudden reflections in fixed camera scenes are identified, achieving real-time monitoring and early warning of reflection conditions in the picture.

[0054] The self-check module is equipped with a lens condensation detection algorithm, which is used to perform real-time detection and early warning of lens condensation. The lens condensation detection algorithm focuses on the real-time images captured by the camera. The lens condensation detection algorithm adopts a target detection model, an image quality assessment model and a motion detection model, and its feature calculation rules include analyzing the brightness and color changes of local areas in the image.

[0055] In terms of specific implementation, by using morphological operations such as expansion and corrosion, and combining temperature and humidity sensor data, and using decision trees or neural networks to predict the formation of condensation, real-time monitoring and early warning of lens condensation conditions are achieved.

[0056] The self-inspection module is equipped with a dirt detection algorithm, which is used for real-time detection and early warning of screen dirtiness; the dirt detection algorithm focuses on the real-time picture captured by the camera; the dirt detection algorithm adopts a target detection model, an image quality assessment model and a motion detection model, and its feature calculation rules include identifying the stain area in the image.

[0057] In terms of specific implementation, by applying image segmentation technology, such as threshold segmentation or region-based segmentation, and using texture analysis, such as local binary pattern (LBP) or local frequency analysis, to identify the texture features of stains, real-time monitoring and early warning of image contamination are achieved.

[0058] The self-inspection module is equipped with a foreign object occlusion detection algorithm, which is used to perform real-time detection and early warning of foreign object occlusion in the picture; the foreign object occlusion detection algorithm focuses on the real-time picture captured by the camera; the foreign object occlusion detection algorithm adopts the target detection model, image quality assessment model and motion detection model, and its feature calculation rules include identifying objects that suddenly appear.

[0059] In terms of specific implementation, through background modeling and foreground detection technologies, such as background subtraction or frame difference method, as well as the use of contour detection and shape analysis, the shape and size of the obstruction can be identified, thus achieving real-time monitoring and early warning of foreign object obstruction in the picture.

[0060] The self-check module is equipped with a lens skew detection algorithm, which is used to determine whether the lens deviates from the vertical direction; the lens skew detection algorithm focuses on the real-time image captured by the camera. The lens skew detection algorithm adopts a target detection model, an image quality assessment model and a motion detection model, and its feature calculation rules include analyzing the geometric transformation in the image.

[0061] In specific implementation, straight line detection algorithms, such as Hough transform, and feature point detection and matching, such as SIFT or SURF, are used to analyze geometric transformations in images. Through these technical means, the lens skew detection algorithm can monitor and warn of lens skew in real time, ensuring the accuracy and stability of the monitoring image.

[0062] The rest of the structure is the same as that of Example 1.

[0063] The self-check algorithm can detect problems such as blurred images, jitter, reflections, lens condensation, dirt, foreign objects blocking, lens skew, and monitoring field of view not meeting technical specifications. The main problems solved are: "Convenient operation and maintenance": using standardized module plug-in replacement to replace the original whole machine replacement to improve fault recovery speed; using a split structure design to solve the problem of needing to climb high / power outages during maintenance. "Reducing costs": The overall replacement cost is too high. Reducing the cost of replacing and iterative upgrading of monitoring equipment is conducive to large-scale promotion. "Problem self-checking": Unable to quickly locate the damage of the camera module. Quickly locate the damaged module of the camera and non-fault abnormal problems, replace the traditional equipment fault diagnosis method, and actively check and quickly report through equipment self-checking. "Dianhong adaptation": Use the standard Dianhong system for research and development to accelerate the diversity and adaptability of the Dianhong ecosystem.

[0064] At the system level, the device can implement self-detection algorithms for image blur, jitter, reflection, lens condensation, dirt, foreign object obstruction, lens tilt, and monitoring field of view that does not meet technical specifications. It effectively solves problems such as the difficulty in operation and maintenance of plant inspection terminals, the high overall replacement cost, the inability to quickly locate camera module damage, and electric adaptation, helping to promote autonomous and intelligent upgrades at the power operation, maintenance and monitoring level.

[0065] The software operation logic diagram of the device with the Internet of Things monitoring system can be referred to Figure 2 , since it is not the main design point, it is only for reference and will not be elaborated here.

[0066] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A modular substation intelligent monitoring terminal based on Dianhong, characterized by: include, A lens core module for capturing image and video data; A self-check module, which is used to detect the operating status and surrounding environment of the device and can monitor the faults and abnormalities of the device in real time; A motor control module, which is used to control the horizontal and vertical movement of the lens; Lighting control module, which can automatically adjust the brightness according to the ambient light; A communication module, which is used to exchange data with an external system; The power module is used to supply power to each module.

2. The modular substation intelligent monitoring terminal based on Dianhong as claimed in claim 1 is characterized by: The self-check module is provided with a picture blur self-check algorithm, which is used to perform real-time detection and early warning of picture blur; The image blur self-detection algorithm adopts an image clarity evaluation model and an image feature extraction model. Its feature calculation rules include evaluating the sharpness of edges in the picture and the frequency content of the image.

3. The modular substation intelligent monitoring terminal based on Dianhong as claimed in claim 1 is characterized in that: The self-check module is provided with a jitter detection algorithm, which is used to detect and warn of image jitter in real time; The jitter detection algorithm uses a target detection model, an image quality assessment model, and a motion detection model. Its feature calculation algorithm involves analyzing the pixel motion between consecutive frames to identify jitter patterns.

4. The modular substation intelligent monitoring terminal based on Dianhong as claimed in claim 1 is characterized in that: The self-check module is provided with a reflection detection algorithm, which is used to perform real-time detection and early warning of the reflection of the screen; The reflection detection algorithm adopts target detection model, image quality assessment model and motion detection model. Its feature calculation rules include identifying abnormal highlighted areas in the image.

5. The modular substation intelligent monitoring terminal based on Dianhong as claimed in claim 1 is characterized in that: The self-check module is provided with a lens condensation detection algorithm, which is used to perform real-time detection and early warning of lens condensation; The lens condensation detection algorithm adopts target detection model, image quality assessment model and motion detection model. Its feature calculation rules include analyzing the brightness and color changes of local areas in the image.

6. The modular substation intelligent monitoring terminal based on Dianhong as claimed in claim 1 is characterized by: The self-check module is provided with a dirt detection algorithm, which is used to detect and warn of the dirtiness of the screen in real time; The dirt detection algorithm adopts a target detection model, an image quality assessment model and a motion detection model, and its feature calculation rules include identifying the dirt area in the image.

7. The modular substation intelligent monitoring terminal based on Dianhong as claimed in claim 1 is characterized by: The self-check module is provided with a foreign body occlusion detection algorithm, which is used to perform real-time detection and early warning of foreign body occlusion in the picture; The foreign body occlusion detection algorithm adopts target detection model, image quality assessment model and motion detection model. Its feature calculation rules include the recognition of objects that appear suddenly.

8. The modular substation intelligent monitoring terminal based on Dianhong as claimed in claim 1 is characterized by: The self-check module is provided with a lens skew detection algorithm, which is used to determine whether the lens deviates from the vertical direction; The lens skew detection algorithm adopts a target detection model, an image quality assessment model and a motion detection model, and its feature calculation rules include analyzing geometric transformations in the image.

9. The modular substation intelligent monitoring terminal based on Dianhong according to any one of claims 1 to 8, characterized in that: The lens movement module includes a high-definition camera, an optical lens, and an image sensor. The high-definition camera can adjust the optical lens according to the detection of the image sensor.

10. The modular substation intelligent monitoring terminal based on Dianhong as claimed in claim 9, characterized in that: The motor control module includes a motor driver and a position sensor, wherein the motor driver can control the horizontal and vertical movement of the lens, and the position sensor is used to detect the current position of the position sensor; The lighting control module includes an LED lamp, an infrared lamp, and a photosensitive sensor, and the photosensitive sensor determines whether to use the LED lamp or the infrared lamp according to the intensity of the detected light; The communication module includes a wireless communication chip, an antenna, and a network interface.

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