Method and device for automatically expelling violation personnel in hydroelectric power plant based on real-time target detection

Abstract

The invention discloses a method and a device for automatically expelling violation persons in a hydroelectric power plant based on real-time target detection. The method comprises the following steps: acquiring target low-light image data and real-time motion data; generating a first expelling data set according to the low-light image data and a preset expelling rule; performing linear fitting on the first expelling data set and the real-time motion data to obtain a second expelling data set; and according to the second expelling data set, warning and expelling prompts are sent to related personnel. According to the invention, the technical problem that the overall determination of the expelled personnel is low in efficiency and not accurate enough due to the fact that the personnel expelling means in the prior art only carries out determination through simple image data and does not analyze factors such as movement of other personnel is solved.

Description

Technical Field

[0001] The present invention relates to the field of target recognition and early warning processing, and in particular to a method and a device for automatically driving away illegal personnel in a hydropower plant based on real-time target detection. Background Art

[0002] With the continuous development of intelligent technology, people are using more and more intelligent devices in their lives, work and study. The use of intelligent technology has improved the quality of people's lives and increased the efficiency of their study and work.

[0003] At present, the early warning and expulsion of illegal personnel around hydropower plants usually involves manual judgment or image recognition algorithms based on the image content displayed by the monitoring equipment. The recognition results are used as the criteria for judging the objects of expulsion to generate a personnel expulsion strategy, thereby expelling illegal personnel around the hydropower plant and ensuring the safety of system operation. However, the personnel expulsion means in the prior art only judge through simple image data, without analyzing other factors such as personnel movement, resulting in low efficiency and inaccuracy in the overall judgment of expulsion.

[0004] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0005] The embodiments of the present invention provide a method and device for automatically expelling illegal personnel from a hydropower plant based on real-time target detection, so as to at least solve the technical problem that the personnel expulsion means in the prior art are only judged by simple image data, and other factors such as personnel movement are not analyzed, resulting in low efficiency and inaccuracy in the overall judgment of expelling personnel.

[0006] According to one aspect of an embodiment of the present invention, a method for automatically expelling illegal personnel from a hydropower plant based on real-time target detection is provided, comprising: collecting target low-light image data and real-time motion data; generating a first expulsion data set according to the low-light image data and preset expulsion rules; performing linear fitting on the first expulsion data set and the real-time motion data to obtain a second expulsion data set; and issuing a warning and expulsion prompt to relevant personnel according to the second expulsion data set.

[0007] Optionally, the low-light image data includes: ultra-precise infrared image data and ultra-precise grayscale image data.

[0008] Optionally, generating the first drive-away data set according to the low-light image data and the preset drive-away rule includes: generating an image drive-away model according to the preset drive-away rule and historical drive-away data; inputting the low-light image data into the image drive-away model to obtain the first drive-away data set, wherein the hidden layer of the image drive-away model is a double-layer matching layer, and the matching matrix is ​​a secondary hidden matching matrix, specifically:

[0009]

[0010] Among them, Y1 to Yn are n items of low-light image data to be matched, and Z1 to Zn are n items of corresponding personnel data that are eligible for expulsion.

[0011] Optionally, performing linear fitting on the first drive-away data set and the real-time motion data to obtain the second drive-away data set includes: collecting position parameters and displacement parameters in the real-time motion data; adding the displacement parameters as data labels to the position parameters to obtain personnel trajectory data; fitting the personnel trajectory data and the first drive-away data set by formula

[0012]

[0013] The second drive-away data set is generated by fitting, wherein F represents vectorial second drive-away data, and f1 and f2 represent personnel trajectory data and the first drive-away data set respectively.

[0014] According to another aspect of an embodiment of the present invention, there is also provided a device for automatically expelling illegal personnel from a hydropower plant based on real-time target detection, comprising: an acquisition module, used to acquire target low-light image data and real-time motion data; a generation module, used to generate a first expulsion data set according to the low-light image data and a preset expulsion rule; a fitting module, used to linearly fit the first expulsion data set and the real-time motion data to obtain a second expulsion data set; and a warning module, used to issue a warning expulsion prompt to relevant personnel according to the second expulsion data set.

[0015] Optionally, the low-light image data includes: ultra-precise infrared image data and ultra-precise grayscale image data.

[0016] Optionally, the generation module includes: a model unit, used to generate an image drive-away model according to the preset drive-away rule and historical drive-away data; an output unit, used to input the low-light image data into the image drive-away model to obtain the first drive-away data set, wherein the hidden layer of the image drive-away model is a double-layer matching layer, and the matching matrix is ​​a secondary hidden matching matrix, specifically:

[0017]

[0018] Among them, Y1 to Yn are n items of low-light image data to be matched, and Z1 to Zn are n items of corresponding personnel data that are eligible for expulsion.

[0019] Optionally, the fitting module includes: a collection unit for collecting position parameters and displacement parameters in the real-time motion data; a label unit for adding the displacement parameters as data labels to the position parameters to obtain personnel trajectory data; a fitting unit for fitting the personnel trajectory data and the first expulsion data set through the formula

[0020]

[0021] The second drive-away data set is generated by fitting, wherein F represents vectorial second drive-away data, and f1 and f2 represent personnel trajectory data and the first drive-away data set respectively.

[0022] According to another aspect of an embodiment of the present invention, a non-volatile storage medium is also provided, wherein the non-volatile storage medium includes a stored program, wherein when the program is run, the device where the non-volatile storage medium is located is controlled to execute a method for automatically expelling illegal personnel from a hydropower plant based on real-time target detection.

[0023] According to another aspect of an embodiment of the present invention, there is also provided an electronic device comprising a processor and a memory; the memory stores computer-readable instructions, and the processor is used to run the computer-readable instructions, wherein when the computer-readable instructions are run, a method for automatically expelling illegal personnel from a hydropower plant based on real-time target detection is executed.

[0024] In the embodiments of the present invention, target low-light image data and real-time motion data are collected; a first expulsion data set is generated according to the low-light image data and a preset expulsion rule; the first expulsion data set and the real-time motion data are linearly fitted to obtain a second expulsion data set; and a warning expulsion prompt is issued to relevant personnel according to the second expulsion data set, thereby solving the technical problem that the personnel expulsion means in the prior art only judges through simple image data without analyzing other factors such as personnel movement, resulting in low efficiency and inaccuracy in the overall judgment of expelling personnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0026] Figure 1is a flow chart of a method for automatically expelling illegal personnel from a hydropower plant based on real-time target detection according to an embodiment of the present invention;

[0027] Figure 2 is a structural block diagram of a device for automatically driving away illegal personnel in a hydropower plant based on real-time target detection according to an embodiment of the present invention;

[0028] Figure 3 is a block diagram of a terminal device for executing a method according to an embodiment of the present invention;

[0029] Figure 4 It is a storage unit for holding or carrying a program code for implementing a method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0030] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0031] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0032] According to an embodiment of the present invention, a method embodiment of a method for automatically expelling illegal personnel from a hydroelectric power plant based on real-time target detection is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0033] Embodiment 1

[0034] Figure 1is a flow chart of a method for automatically driving away illegal personnel from a hydropower plant based on real-time target detection according to an embodiment of the present invention. Figure 1 As shown, the method comprises the following steps:

[0035] Step S102, collecting target low-light image data and real-time motion data;

[0036] Step S104, generating a first drive-away data set according to the low-light image data and a preset drive-away rule;

[0037] Step S106, performing linear fitting on the first drive-away data set and the real-time motion data to obtain a second drive-away data set;

[0038] Step S108: issuing a warning and prompting relevant personnel to leave according to the second expulsion data set.

[0039] Optionally, the low-light image data includes: ultra-precise infrared image data and ultra-precise grayscale image data.

[0040] Optionally, generating the first drive-away data set according to the low-light image data and the preset drive-away rule includes: generating an image drive-away model according to the preset drive-away rule and historical drive-away data; inputting the low-light image data into the image drive-away model to obtain the first drive-away data set, wherein the hidden layer of the image drive-away model is a double-layer matching layer, and the matching matrix is ​​a secondary hidden matching matrix, specifically:

[0041]

[0042] Among them, Y1 to Yn are n items of low-light image data to be matched, and Z1 to Zn are n items of corresponding personnel data that are eligible for expulsion.

[0043] Optionally, performing linear fitting on the first drive-away data set and the real-time motion data to obtain the second drive-away data set includes: collecting position parameters and displacement parameters in the real-time motion data; adding the displacement parameters as data labels to the position parameters to obtain personnel trajectory data; fitting the personnel trajectory data and the first drive-away data set by formula

[0044]

[0045] The second drive-away data set is generated by fitting, wherein F represents vectorial second drive-away data, and f1 and f2 represent personnel trajectory data and the first drive-away data set respectively.

[0046] The above embodiments solve the technical problem that the personnel removal means in the prior art is only judged by simple image data without analyzing other factors such as personnel movement, resulting in low efficiency and inaccuracy in the overall judgment of personnel removal.

[0047] Embodiment 2

[0048] Figure 2 is a structural block diagram of a device for automatically driving away illegal personnel in a hydropower plant based on real-time target detection according to an embodiment of the present invention, such as Figure 2 As shown, the device comprises:

[0049] The acquisition module 20 is used to acquire target low-light image data and real-time motion data;

[0050] A generating module 22, configured to generate a first drive-away data set according to the low-light image data and a preset drive-away rule;

[0051] A fitting module 24, configured to perform linear fitting on the first drive-away data set and the real-time motion data to obtain a second drive-away data set;

[0052] The warning module 26 is used to issue a warning to relevant personnel to drive away according to the second drive away data set.

[0053] Optionally, the low-light image data includes: ultra-precise infrared image data and ultra-precise grayscale image data.

[0054] Optionally, the generation module includes: a model unit, used to generate an image drive-away model according to the preset drive-away rule and historical drive-away data; an output unit, used to input the low-light image data into the image drive-away model to obtain the first drive-away data set, wherein the hidden layer of the image drive-away model is a double-layer matching layer, and the matching matrix is ​​a secondary hidden matching matrix, specifically:

[0055]

[0056] Among them, Y1 to Yn are n items of low-light image data to be matched, and Z1 to Zn are n items of corresponding personnel data that are eligible for expulsion.

[0057] Optionally, the fitting module includes: a collection unit for collecting position parameters and displacement parameters in the real-time motion data; a label unit for adding the displacement parameters as data labels to the position parameters to obtain personnel trajectory data; a fitting unit for fitting the personnel trajectory data and the first expulsion data set through the formula

[0058]

[0059] The second drive-away data set is generated by fitting, wherein F represents vectorial second drive-away data, and f1 and f2 represent personnel trajectory data and the first drive-away data set respectively.

[0060] The above embodiments solve the technical problem that the personnel removal means in the prior art is only judged by simple image data without analyzing other factors such as personnel movement, resulting in low efficiency and inaccuracy in the overall judgment of personnel removal.

[0061] According to another aspect of an embodiment of the present invention, a non-volatile storage medium is also provided, wherein the non-volatile storage medium includes a stored program, wherein when the program is run, the device where the non-volatile storage medium is located is controlled to execute a method for automatically expelling illegal personnel from a hydropower plant based on real-time target detection.

[0062] Specifically, the above method includes: collecting target low-light image data and real-time motion data; generating a first expulsion data set based on the low-light image data and preset expulsion rules; linearly fitting the first expulsion data set and the real-time motion data to obtain a second expulsion data set; and issuing a warning and expulsion prompt to relevant personnel based on the second expulsion data set. Optionally, the low-light image data includes: ultra-precision infrared image data and ultra-precision grayscale image data. Optionally, generating a first expulsion data set based on the low-light image data and preset expulsion rules includes: generating an image expulsion model based on the preset expulsion rules and historical expulsion data; inputting the low-light image data into the image expulsion model to obtain the first expulsion data set, wherein the hidden layer of the image expulsion model is a double-layer matching layer, and the matching matrix is ​​a quadratic hidden matching matrix, specifically:

[0063]

[0064] Wherein, Y1 to Yn are n items of low-light image data to be matched, and Z1 to Zn are n items of corresponding personnel data that meet the requirements of expulsion. Optionally, performing linear fitting on the first expulsion data set and the real-time motion data to obtain the second expulsion data set includes: collecting position parameters and displacement parameters in the real-time motion data; adding the displacement parameters as data labels to the position parameters to obtain personnel trajectory data; fitting the personnel trajectory data and the first expulsion data set by formula

[0065]

[0066] The second drive-away data set is generated by fitting, wherein F represents vectorial second drive-away data, and f1 and f2 represent personnel trajectory data and the first drive-away data set respectively.

[0067] According to another aspect of an embodiment of the present invention, there is also provided an electronic device comprising a processor and a memory; the memory stores computer-readable instructions, and the processor is used to run the computer-readable instructions, wherein when the computer-readable instructions are run, a method for automatically expelling illegal personnel from a hydropower plant based on real-time target detection is executed.

[0068] Specifically, the above method includes: collecting target low-light image data and real-time motion data; generating a first expulsion data set based on the low-light image data and preset expulsion rules; linearly fitting the first expulsion data set and the real-time motion data to obtain a second expulsion data set; and issuing a warning and expulsion prompt to relevant personnel based on the second expulsion data set. Optionally, the low-light image data includes: ultra-precision infrared image data and ultra-precision grayscale image data. Optionally, generating a first expulsion data set based on the low-light image data and preset expulsion rules includes: generating an image expulsion model based on the preset expulsion rules and historical expulsion data; inputting the low-light image data into the image expulsion model to obtain the first expulsion data set, wherein the hidden layer of the image expulsion model is a double-layer matching layer, and the matching matrix is ​​a quadratic hidden matching matrix, specifically:

[0069]

[0070] Wherein, Y1 to Yn are n items of low-light image data to be matched, and Z1 to Zn are n items of corresponding personnel data that meet the requirements of expulsion. Optionally, performing linear fitting on the first expulsion data set and the real-time motion data to obtain the second expulsion data set includes: collecting position parameters and displacement parameters in the real-time motion data; adding the displacement parameters as data labels to the position parameters to obtain personnel trajectory data; fitting the personnel trajectory data and the first expulsion data set by formula

[0071]

[0072] The second drive-away data set is generated by fitting, wherein F represents vectorial second drive-away data, and f1 and f2 represent personnel trajectory data and the first drive-away data set respectively.

[0073] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0074] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0075] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0076] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0077] in addition, Figure 3 This is a schematic diagram of the hardware structure of a terminal device provided in one embodiment of the present application. Figure 3 As shown, the terminal device may include an input device 30, a processor 31, an output device 32, a memory 33 and at least one communication bus 34. The communication bus 34 is used to realize the communication connection between the components. The memory 33 may include a high-speed RAM memory, and may also include a non-volatile storage NVM, such as at least one disk memory. Various programs can be stored in the memory 33 to complete various processing functions and implement the method steps of this embodiment.

[0078] Optionally, the processor 31 may be implemented as a central processing unit (CPU), an application-specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a controller, a microcontroller, a microprocessor or other electronic components, and the processor 31 is coupled to the input device 30 and the output device 32 via a wired or wireless connection.

[0079] Optionally, the input device 30 may include multiple input devices, for example, it may include at least one of a user interface for users, a device interface for devices, a programmable interface for software, a camera, and a sensor. Optionally, the device interface for devices may be a wired interface for data transmission between devices, or a hardware insertion interface for data transmission between devices (such as a USB interface, a serial port, etc.); Optionally, the user interface for users may be, for example, a control button for users, a voice input device for receiving voice input, and a touch sensing device for users to receive user touch input (such as a touch screen with a touch sensing function, a touch pad, etc.); Optionally, the programmable interface for the software may be, for example, an entry for users to edit or modify programs, such as an input pin interface or an input interface of a chip; Optionally, the transceiver may be a radio frequency transceiver chip with communication function, a baseband processing chip, and a transceiver antenna, etc. Audio input devices such as microphones may receive voice data. The output device 32 may include output devices such as displays and speakers.

[0080] In this embodiment, the processor of the terminal device includes functions for executing each module of the data processing device in each device. The specific functions and technical effects can be referred to the above embodiments and will not be repeated here.

[0081] Figure 4 A schematic diagram of the hardware structure of a terminal device provided in another embodiment of the present application. Figure 4 Yes Figure 3 A specific embodiment in the implementation process. Figure 4 As shown, the terminal device of this embodiment includes a processor 41 and a memory 42.

[0082] The processor 41 executes the computer program code stored in the memory 42 to implement the method in the above embodiment.

[0083] The memory 42 is configured to store various types of data to support operations on the terminal device. Examples of such data include instructions for any application or method used to operate on the terminal device, such as messages, pictures, videos, etc. The memory 42 may include a random access memory (RAM) and may also include a non-volatile memory, such as at least one disk storage.

[0084] Optionally, the processor 41 is provided in the processing component 40. The terminal device may further include: a communication component 43, a power component 44, a multimedia component 45, an audio component 46, an input / output interface 47 and / or a sensor component 48. The specific components included in the terminal device are set according to actual needs, and this embodiment does not limit this.

[0085] The processing component 40 generally controls the overall operation of the terminal device. The processing component 40 may include one or more processors 41 to execute instructions to complete all or part of the steps of the above method. In addition, the processing component 40 may include one or more modules to facilitate the interaction between the processing component 40 and other components. For example, the processing component 40 may include a multimedia module to facilitate the interaction between the multimedia component 45 and the processing component 40.

[0086] The power supply component 44 provides power to various components of the terminal device. The power supply component 44 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the terminal device.

[0087] The multimedia component 45 includes a display screen that provides an output interface between the terminal device and the user. In some embodiments, the display screen may include a liquid crystal display (LCD) and a touch panel (TP). If the display screen includes a touch panel, the display screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation.

[0088] The audio component 46 is configured to output and / or input audio signals. For example, the audio component 46 includes a microphone (MIC), and when the terminal device is in an operating mode, such as a speech recognition mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in the memory 42 or sent via the communication component 43. In some embodiments, the audio component 46 also includes a speaker for outputting audio signals.

[0089] The input / output interface 47 provides an interface between the processing component 40 and the peripheral interface modules, which may be click wheels, buttons, etc. These buttons may include but are not limited to: volume buttons, start buttons, and lock buttons.

[0090] The sensor assembly 48 includes one or more sensors for providing various aspects of status assessment for the terminal device. For example, the sensor assembly 48 can detect the open / closed state of the terminal device, the relative positioning of the components, and the presence or absence of contact between the user and the terminal device. The sensor assembly 48 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact, including detecting the distance between the user and the terminal device. In some embodiments, the sensor assembly 48 may also include a camera, etc.

[0091] The communication component 43 is configured to facilitate wired or wireless communication between the terminal device and other devices. The terminal device can access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In one embodiment, the terminal device may include a SIM card slot for inserting a SIM card, so that the terminal device can log in to the GPRS network and establish communication with the service end through the Internet.

[0092] From the above, we can see that Figure 4 The communication component 43, the audio component 46, the input / output interface 47, and the sensor component 48 involved in the embodiment can all be used as Figure 3 Implementation method of the input device in the embodiment.

[0093] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0094] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0095] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0096] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0097] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for automatically expelling illegal personnel from a hydropower plant based on real-time target detection, characterized in that: include: Collect target low-light image data and real-time motion data; generating a first drive-away data set according to the low-light image data and a preset drive-away rule; Performing linear fitting on the first drive-off data set and the real-time motion data to obtain a second drive-off data set; According to the second drive-away data set, a warning and drive-away prompt is issued to relevant personnel.

2. The method according to claim 1, characterized in that The low-light image data includes: ultra-precise infrared image data and ultra-precise grayscale image data.

3. The method according to claim 1, characterized in that The generating a first drive-away data set according to the low-light image data and a preset drive-away rule comprises: Generate an image expulsion model according to the preset expulsion rules and historical expulsion data; The low-light image data is input into the image drive-off model to obtain the first drive-off data set, wherein the hidden layer of the image drive-off model is a double-layer matching layer, and the matching matrix is ​​a secondary hidden matching matrix, specifically: Among them, Y1 to Yn are n items of low-light image data to be matched, and Z1 to Zn are n items of corresponding personnel data that are eligible for expulsion.

4. The method according to claim 1, characterized in that: The performing linear fitting on the first drive-away data set and the real-time motion data to obtain a second drive-away data set comprises: Collecting position parameters and displacement parameters in the real-time motion data; Adding the displacement parameter as a data tag to the position parameter to obtain personnel trajectory data; The personnel trajectory data and the first expulsion data set are combined by the formula The second drive-away data set is generated by fitting, wherein F represents vectorial second drive-away data, and f1 and f2 represent personnel trajectory data and the first drive-away data set respectively.

5. A device for automatically driving away illegal personnel from a hydropower plant based on real-time target detection, characterized in that: include: An acquisition module is used to acquire target low-light image data and real-time motion data; A generating module, configured to generate a first drive-away data set according to the low-light image data and a preset drive-away rule; a fitting module, configured to perform linear fitting on the first drive-away data set and the real-time motion data to obtain a second drive-away data set; The warning module is used to issue a warning and expulsion prompt to relevant personnel according to the second expulsion data set.

6. The device according to claim 5, characterized in that The low-light image data includes: ultra-precise infrared image data and ultra-precise grayscale image data.

7. The device according to claim 5, characterized in that The generation module comprises: A model unit, configured to generate an image expulsion model according to the preset expulsion rules and historical expulsion data; An output unit is used to input the low-light image data into the image drive-off model to obtain the first drive-off data set, wherein the hidden layer of the image drive-off model is a double-layer matching layer, and the matching matrix is ​​a secondary hidden matching matrix, specifically: Among them, Y1 to Yn are n items of low-light image data to be matched, and Z1 to Zn are n items of corresponding personnel data that are eligible for expulsion.

8. The device according to claim 5, characterized in that The fitting module comprises: A collection unit, used for collecting position parameters and displacement parameters in the real-time motion data; A label unit, used for adding the displacement parameter as a data label to the position parameter to obtain personnel trajectory data; A fitting unit is used to fit the personnel trajectory data and the first expulsion data set through a formula The second drive-away data set is generated by fitting, wherein F represents vectorial second drive-away data, and f1 and f2 represent personnel trajectory data and the first drive-away data set respectively.

9. A non-volatile storage medium, characterized in that: The non-volatile storage medium includes a stored program, wherein the program controls the device where the non-volatile storage medium is located to execute the method according to any one of claims 1 to 4 when the program is executed.

10. An electronic device, characterized in that: It comprises a processor and a memory; the memory stores computer-readable instructions, and the processor is used to execute the computer-readable instructions, wherein the computer-readable instructions execute the method described in any one of claims 1 to 4 when executed.

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