A multi-modal video monitoring abnormal behavior recognition device for power grid safety supervision

Abstract

The utility model belongs to monitoring technical field discloses a kind of multi-modal video monitoring abnormal behavior identification devices for power grid safety supervision, the device includes including multi-modal data acquisition module, data preprocessing module, abnormal behavior identification module, alarm module and power module;The multi-modal data acquisition module is connected with data preprocessing module, the data preprocessing module is connected with abnormal behavior identification module, the abnormal behavior identification module is connected with alarm module, the power module is respectively for multi-modal data acquisition module, data preprocessing module, abnormal behavior identification module and alarm module power supply;The utility model adopts multi-modal data acquisition, fuses color video image, infrared thermal imaging and sound various information, can improve the accuracy of abnormal behavior identification under complex environment, overcome the limitation of traditional single visual monitoring.

Description

Technical Field

[0001] This utility model belongs to, but is not limited to, the field of monitoring technology, and particularly relates to a multimodal video surveillance abnormal behavior recognition device for power grid safety monitoring. Background Technology

[0002] The power grid is a vital national infrastructure, and its safe and stable operation is directly related to national economic development and social stability. In the daily operation of the power grid, real-time monitoring of key components such as substations and transmission lines is necessary to promptly detect and address potential safety hazards and abnormal behaviors, such as unauthorized personnel entry, abnormal equipment operation, and line faults.

[0003] Currently, power grid safety monitoring mainly relies on traditional video surveillance, which involves manually reviewing monitoring footage to identify abnormal behavior. However, this method has many drawbacks: on the one hand, manual monitoring requires a significant investment of manpower, and prolonged monitoring can easily lead to personnel fatigue, resulting in missed or false detections of abnormal behavior; on the other hand, traditional video surveillance relies solely on visual information, and in complex environments (such as nighttime, heavy fog, or heavy rain), the monitoring effect is poor, making it difficult to accurately identify abnormal behavior.

[0004] Therefore, developing a device that can automatically and accurately identify abnormal behaviors in power grid safety monitoring is of great significance for improving the level of power grid safety monitoring and ensuring the safe operation of the power grid. Utility Model Content

[0005] To address the problems existing in the prior art, this utility model provides a multimodal video surveillance abnormal behavior recognition device for power grid safety monitoring.

[0006] This utility model is implemented as follows: a multimodal video surveillance abnormal behavior identification device for power grid safety monitoring, the device includes a multimodal data acquisition module, a data preprocessing module, an abnormal behavior identification module, an alarm module, and a power supply module;

[0007] The multimodal data acquisition module is connected to the data preprocessing module, the data preprocessing module is connected to the abnormal behavior recognition module, the abnormal behavior recognition module is connected to the alarm module, and the power supply module provides power to the multimodal data acquisition module, the data preprocessing module, the abnormal behavior recognition module, and the alarm module respectively.

[0008] The multimodal data acquisition module includes a high-definition camera, an infrared thermal imager, and a sound sensor. The high-definition camera is used to acquire color video image data of the power grid monitoring area, the infrared thermal imager is used to acquire infrared thermal imaging data of the power grid monitoring area, and the sound sensor is used to acquire sound data of the power grid monitoring area.

[0009] The abnormal behavior recognition module includes an embedded processor and a storage unit. The storage unit pre-stores an abnormal behavior recognition algorithm, and the embedded processor is used to call the abnormal behavior recognition algorithm to recognize abnormal behavior in the pre-processed data.

[0010] Furthermore, the data preprocessing module includes an image preprocessing unit and an audio preprocessing unit. The image preprocessing unit is connected to a high-definition camera and an infrared thermal imager, and is used to perform noise reduction, enhancement, and format conversion processing on color video image data and infrared thermal imaging data. The audio preprocessing unit is connected to an audio sensor, and is used to perform filtering, amplification, and analog-to-digital conversion processing on audio data.

[0011] Furthermore, the alarm module includes an audible and visual alarm and a wireless communication unit. The audible and visual alarm is used to emit audible and visual alarm signals, and the wireless communication unit is used to send abnormal behavior information to a remote monitoring center.

[0012] Furthermore, the wireless communication unit adopts 4G, 5G or WiFi communication methods.

[0013] Furthermore, the power module includes a solar panel, a battery, and a power management unit. The solar panel is connected to the battery, and the battery is connected to a multimodal data acquisition module, a data preprocessing module, an abnormal behavior recognition module, and an alarm module through the power management unit.

[0014] Furthermore, the high-definition camera is a spherical camera with 360-degree rotation capability.

[0015] Furthermore, the embedded processor is an ARM architecture processor or a DSP processor.

[0016] Furthermore, the storage unit is an SD card or a solid-state drive.

[0017] Based on the above technical solutions and the technical problems solved, the advantages and positive effects of the technical solution to be protected by this utility model are as follows:

[0018] Employing multimodal data acquisition, which integrates color video images, infrared thermal imaging, and sound information, it can improve the accuracy of abnormal behavior identification in complex environments and overcome the limitations of traditional single-vision monitoring.

[0019] The intelligent algorithm in the abnormal behavior recognition module enables automatic identification of abnormal behavior, reducing manual intervention and labor costs. At the same time, it avoids missed detections and false detections caused by manual monitoring, thereby improving the efficiency and reliability of monitoring.

[0020] The alarm module can promptly issue audible and visual alarm signals and send abnormal information to the remote monitoring center, enabling on-site personnel and remote monitoring personnel to respond quickly, handle abnormal situations in a timely manner, and eliminate potential safety hazards in their infancy.

[0021] The use of solar power adapts to the environment of the field power grid monitoring area, saves energy, and improves the applicability of the device. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of the structure of a multimodal video surveillance abnormal behavior recognition device for power grid safety supervision provided in this embodiment of the utility model;

[0023] Figure 2 This is a schematic diagram of the structure of the multimodal data acquisition module provided in this embodiment of the utility model;

[0024] Figure 3 This is a schematic diagram of the abnormal behavior recognition module structure provided in this embodiment of the utility model;

[0025] Figure 4 This is a schematic diagram of the alarm module structure provided in this embodiment of the utility model;

[0026] In the diagram: 1. Multimodal data acquisition module; 2. Data preprocessing module; 3. Abnormal behavior recognition module; 4. Alarm module; 5. Power supply module; 6. High-definition camera; 7. Infrared thermal imager; 8. Sound sensor; 9. Embedded processor; 10. Storage unit; 11. Audible and visual alarm; 12. Wireless communication unit. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of this utility model clearer, the following detailed description is provided in conjunction with embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this utility model.

[0028] like Figure 1 As shown, this utility model embodiment provides a multimodal video surveillance abnormal behavior recognition device for power grid safety monitoring. The device includes a multimodal data acquisition module 1, a data preprocessing module 2, an abnormal behavior recognition module 3, an alarm module 4, and a power supply module 5.

[0029] The multimodal data acquisition module 1 is connected to the data preprocessing module 2, the data preprocessing module 2 is connected to the abnormal behavior identification module 3, the abnormal behavior identification module 3 is connected to the alarm module 4, and the power supply module 5 provides power to the multimodal data acquisition module 1, the data preprocessing module 2, the abnormal behavior identification module 3 and the alarm module 4 respectively.

[0030] like Figure 2 As shown, the multimodal data acquisition module 1 includes a high-definition camera 6, an infrared thermal imager 7, and a sound sensor 8. The high-definition camera 6 is used to acquire color video image data of the power grid monitoring area, the infrared thermal imager 7 is used to acquire infrared thermal imaging data of the power grid monitoring area, and the sound sensor 8 is used to acquire sound data of the power grid monitoring area.

[0031] like Figure 3 As shown, the abnormal behavior recognition module 3 includes an embedded processor 9 and a storage unit 10. The storage unit 10 pre-stores an abnormal behavior recognition algorithm, and the embedded processor 9 is used to call the abnormal behavior recognition algorithm to perform abnormal behavior recognition on the pre-processed data.

[0032] The data preprocessing module 2 includes an image preprocessing unit and an audio preprocessing unit. The image preprocessing unit is connected to a high-definition camera and an infrared thermal imager, and is used to perform noise reduction, enhancement, and format conversion processing on color video image data and infrared thermal imaging data. The audio preprocessing unit is connected to an audio sensor, and is used to perform filtering, amplification, and analog-to-digital conversion processing on audio data.

[0033] like Figure 4 As shown, the alarm module 4 includes an audible and visual alarm 11 and a wireless communication unit 12. The audible and visual alarm 11 is used to emit audible and visual alarm signals, and the wireless communication unit 12 is used to send abnormal behavior information to a remote monitoring center.

[0034] The wireless communication unit 12 adopts 4G, 5G or WiFi communication methods.

[0035] The power module 5 includes a solar panel, a battery, and a power management unit. The solar panel is connected to the battery, and the battery is connected to a multimodal data acquisition module, a data preprocessing module, an abnormal behavior recognition module, and an alarm module through the power management unit.

[0036] The high-definition camera 6 is a spherical camera with 360-degree rotation capability.

[0037] The embedded processor 9 is an ARM architecture processor or a DSP processor.

[0038] The storage unit 10 is an SD card or a solid-state drive.

[0039] In the description of this utility model, unless otherwise stated, "a plurality of" means two or more; the terms "upper," "lower," "left," "right," "inner," "outer," "front end," "rear end," "head," "tail," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing this utility model and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this utility model. In addition, the terms "first," "second," "third," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0040] The above description is only a specific embodiment of this utility model, but the protection scope of this utility model is not limited thereto. Any modifications, equivalent substitutions and improvements made by those skilled in the art within the technical scope disclosed in this utility model, and within the spirit and principles of this utility model, should be included within the protection scope of this utility model.

Claims

1. A multimodal video surveillance abnormal behavior recognition device for power grid safety monitoring, characterized in that, The device includes a multimodal data acquisition module, a data preprocessing module, an abnormal behavior recognition module, an alarm module, and a power supply module; The multimodal data acquisition module is connected to the data preprocessing module, the data preprocessing module is connected to the abnormal behavior recognition module, the abnormal behavior recognition module is connected to the alarm module, and the power supply module provides power to the multimodal data acquisition module, the data preprocessing module, the abnormal behavior recognition module, and the alarm module respectively. The multimodal data acquisition module includes a high-definition camera, an infrared thermal imager, and a sound sensor. The high-definition camera is used to acquire color video image data of the power grid monitoring area, the infrared thermal imager is used to acquire infrared thermal imaging data of the power grid monitoring area, and the sound sensor is used to acquire sound data of the power grid monitoring area. The abnormal behavior recognition module includes an embedded processor and a storage unit. The storage unit pre-stores an abnormal behavior recognition algorithm, and the embedded processor is used to call the abnormal behavior recognition algorithm to recognize abnormal behavior in the pre-processed data.

2. The multimodal video surveillance abnormal behavior recognition device for power grid safety monitoring according to claim 1, characterized in that, The data preprocessing module includes an image preprocessing unit and an audio preprocessing unit. The image preprocessing unit is connected to a high-definition camera and an infrared thermal imager, and is used to perform noise reduction, enhancement and format conversion processing on color video image data and infrared thermal imaging data. The sound preprocessing unit is connected to the sound sensor and is used to filter, amplify, and perform analog-to-digital conversion on the sound data.

3. The multimodal video surveillance abnormal behavior recognition device for power grid safety monitoring according to claim 1, characterized in that, The alarm module includes an audible and visual alarm and a wireless communication unit. The audible and visual alarm is used to emit audible and visual alarm signals, and the wireless communication unit is used to send abnormal behavior information to a remote monitoring center.

4. The multimodal video surveillance abnormal behavior recognition device for power grid safety monitoring according to claim 3, characterized in that, The wireless communication unit uses 4G, 5G or WiFi communication methods.

5. The multimodal video surveillance abnormal behavior recognition device for power grid safety monitoring according to claim 1, characterized in that, The power module includes a solar panel, a battery, and a power management unit. The solar panel is connected to the battery, and the battery is connected to a multimodal data acquisition module, a data preprocessing module, an abnormal behavior recognition module, and an alarm module through the power management unit.

6. The multimodal video surveillance abnormal behavior recognition device for power grid safety monitoring according to claim 1, characterized in that, The high-definition camera is a spherical camera with 360-degree rotation capability.

7. The multimodal video surveillance abnormal behavior recognition device for power grid safety monitoring according to claim 1, characterized in that, The embedded processor is an ARM architecture processor or a DSP processor.

8. The multimodal video surveillance abnormal behavior recognition device for power grid safety monitoring according to claim 1, characterized in that, The storage unit is an SD card or a solid-state drive.

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