Photovoltaic remote-control visible direct-current cable laying machine suitable for mountainous regions

Abstract

The invention provides a photovoltaic remote control visible direct-current cable laying machine suitable for mountainous regions, and relates to the technical field of direct-current cable laying machines, the photovoltaic remote control visible direct-current cable laying machine comprises a machine body, a plurality of steering wheels are arranged on the machine body, a tunneling tool bit is arranged in front of the machine body, a visible probe is arranged in the center of the tunneling tool bit, and the tail of the machine body is used for fixing a cable. The small drilling laying machine is used for replacing a traditional large cable laying machine for cable laying, the risk of hillside operation of the large cable laying machine is avoided, and meanwhile the laying efficiency is improved due to the fact that the size is small and flexibility is high.

Description

Technical Field

[0001] The invention belongs to the technical field of DC cable laying machines, and in particular relates to a remote-controlled visual DC cable laying machine suitable for mountain photovoltaic applications. Background Art

[0002] Solar energy is an inexhaustible renewable energy source for human beings. It has the advantages of full cleanliness, absolute safety, relative extensiveness and maintenance-freeness, sufficient resources and potential economy. As a new power generation project in China, solar photovoltaic power generation system has the characteristics of safety, reliability, noiselessness, clean energy, abundant resources, no geographical boundaries and short construction period. Its application will greatly reduce greenhouse gas emissions, reduce human dependence on fossil fuels, effectively reduce environmental pollution, and has obvious environmental benefits compared with traditional fossil energy.

[0003] During the construction phase of mountain photovoltaic infrastructure, the terrain is sloping, and there is a high risk of mechanical vehicles operating on the slopes. The workload of laying DC cables between photovoltaic modules and inverters is large, and it is inconvenient to use traditional large-scale cable laying machines to dig cable trenches. Manual excavation is time-consuming, labor-intensive and inefficient. At the same time, due to the large number of slopes, there are major safety hazards. Summary of the invention

[0004] The present invention provides a photovoltaic remote-controlled visual DC cable laying machine suitable for mountain areas, which is used to solve at least one of the technical problems mentioned above.

[0005] In order to solve the above technical problems, the present invention discloses a photovoltaic remote-controlled visual DC cable laying machine suitable for mountain areas, comprising a machine body, a plurality of steering wheels provided on the machine body, a tunneling head provided in the front of the machine body, a visual probe provided in the center of the tunneling head, and the tail of the machine body for fixing the cable.

[0006] Preferably, a motor and a battery are provided in the machine body, the battery is used to power the motor, and the output end of the motor is connected to the tunneling cutter head to drive the tunneling cutter head to rotate;

[0007] A data transmitter is provided at the tail of the tunneling cutter head, and the data transmitter is electrically connected to a movable terminal of the visual probe.

[0008] Preferably, the machine body is in an elongated oval shape, and a DC cable fixing buckle is provided at the rear of the machine body, and the DC cable fixing buckle is used to fix the cable.

[0009] Preferably, it also includes an intelligent route change warning module, which includes:

[0010] The video frame extraction submodule is used to divide the collected video in the current monitoring and collection cycle of the visual probe into several single video frames;

[0011] The obstruction area to be confirmed identification submodule is used to identify the obstruction area to be confirmed based on a plurality of video single frames;

[0012] The obstruction confirmation submodule is used to confirm whether there is an obstruction in the obstruction to be confirmed area based on several video single frames in the obstruction to be confirmed area, and to determine the type of obstruction, which includes obstruction of living things, irresistible obstruction of inanimate objects, and resilient obstruction of inanimate objects;

[0013] The rerouting judgment module provides a rerouting plan and issues an alarm if the obstruction type is a living object obstruction or a dead object that can resist obstruction, prompting the staff to reselect the laying route.

[0014] Preferably, the obstruction to be confirmed area identification submodule includes:

[0015] A calculation pixel acquisition unit is used to obtain the average of the pixel values ​​of adjacent pixels at each pixel position of all video single frames in the current monitoring acquisition cycle, and use it as the calculation pixel of the pixel at the corresponding pixel position of the video single frame, and obtain several calculation pixels of the corresponding pixel point through the same pixel position of several video single frames;

[0016] The background acquisition unit of the obstruction area to be confirmed takes the quotient of the sum of several calculated pixels of each pixel point and the total number of all video single frames of each collected video in the current monitoring and collection cycle as the background pixel value of each pixel point, and the image constructed by the background pixel values ​​of all pixels points is taken as the background of the obstruction area to be confirmed in the current monitoring and collection cycle;

[0017] The obstruction area to be confirmed identification unit calculates the absolute value of the difference between the background pixel value of each pixel position in the background of the obstruction area to be confirmed at the current moment and the pixel value of the corresponding pixel position in the single frame of the video at the current moment. If the absolute value of the difference corresponding to the pixel position is greater than the preset pixel difference, the pixel position is marked as the pixel position of the obstruction area to be confirmed, and the area composed of all the pixel positions of the obstruction area to be confirmed is the obstruction area to be confirmed.

[0018] Preferably, the obstruction confirmation submodule includes:

[0019] The obstruction judgment unit is used to compare the pixel value of each pixel point of a single frame of the video of the obstruction area to be confirmed with the pixel values ​​of all pixel points in a preset obstruction image established based on the background of the obstruction area to be confirmed. If the pixel value of the corresponding pixel point of the single frame of the video of the obstruction area to be confirmed is greater than the pixel value of the corresponding pixel point of the preset obstruction image, it is marked as an obstruction pixel point. If the degree of aggregation of the obstruction pixels is greater than the preset degree of aggregation, it is judged that there is an obstruction, otherwise there is no obstruction;

[0020] The dynamic and static obstruction type classification unit uses the optical flow analysis method to extract the motion information of the obstruction pixel points, including the motion speed and direction. If the obstruction pixel points have motion information, they are marked as dynamic obstruction pixels and the corresponding type is classified as living obstruction. Otherwise, they are marked as static obstruction pixels and the corresponding type is classified as inanimate irresistible obstruction or inanimate resistible obstruction.

[0021] The resistance distinguishing unit is used to distinguish between the inanimate object's irresistible resistance and the inanimate object's resistance to resistance based on the three-channel values ​​of the static resistance pixel points.

[0022] Preferably, the anti-differentiation unit comprises:

[0023] The weight determination subunit is used to sort the three-channel values ​​of the static obstruction pixel points, and take the quotient of the maximum value of the three-channel pixel values ​​of each static obstruction pixel point and the sum of its three-channel pixel values ​​as the maximum channel weight of the corresponding static obstruction pixel point;

[0024] The judgment value calculation subunit calculates the irresistible judgment value of the obstacle on the current video single frame based on the pixel values ​​of all static obstruction pixels on the current video single frame and the maximum weight of the static obstruction pixels.

[0025] Among them, β is the unstoppable judgment value of the obstacle in the current video single frame, n is the total number of static obstruction pixels in the current video single frame, is the pixel value of the i-th static obstruction pixel in the current video frame, γ i is the maximum weight of the i-th static obstruction pixel in the current video frame;

[0026] The classification subunit compares the force majeure judgment value of the obstacle on the current video single frame with the preset force majeure judgment value. If the force majeure judgment value of the obstacle on the current video single frame is greater than the preset force majeure judgment value, the current obstacle is force majeure, otherwise it is resistible.

[0027] Preferably, a surplus soil output assembly is provided at the rear of the machine body, and the surplus soil output assembly comprises a suction pipe, an intermediate hose and an output pipe, wherein the suction pipe and the output pipe are hard pipes, and a negative pressure air pump is provided at the output pipe opening.

[0028] Preferably, a GPS locator is provided on the machine body for locating the cable laying machine.

[0029] Preferably, an emergency stop alarm module is also included, and the emergency stop alarm module includes:

[0030] The first-level detection unit is used to collect the load value of the machine body at each moment and monitor the load change value at each moment. If the actual load change value is greater than the preset load change value, the second-level detection is triggered;

[0031] The secondary detection unit is used to detect the moving speed of the body at each moment and monitor the change value of the moving speed at each moment. If the actual moving speed change value is greater than the preset speed change value, the third level detection is triggered;

[0032] The third-level detection unit is used to detect the fuselage tilt angle of the fuselage at each moment, and detect the change value of the fuselage tilt angle at each moment. If the actual fuselage tilt angle change value is greater than the preset tilt angle change value, an emergency stop alarm prompt will be issued.

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] The present invention utilizes a small hole drilling machine to replace a traditional large cable laying machine for cable laying, thereby avoiding the risk of large cable laying machines operating on hillsides. At the same time, due to its small size and high flexibility, the laying efficiency is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0036] Figure 1 This is a schematic structural diagram of a visual DC cable laying machine for mountain photovoltaic remote control proposed by the present invention.

[0037] In the figure: 1. Steering wheel; 2. Tunneling cutter head; 3. Visual probe; 4. Motor; 5. Battery; 6. Data transmitter; 7. DC cable fixing buckle. DETAILED DESCRIPTION

[0038] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0039] In addition, in the present invention, the descriptions of "first", "second", etc. are only used for descriptive purposes, and do not specifically refer to the order or sequence, nor are they used to limit the present invention. They are only used to distinguish components or operations described with the same technical terms, and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions and technical features between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0040] The present invention provides the following embodiments

[0041] Example 1

[0042] The embodiment of the present invention provides a remote-controlled visual DC cable laying machine suitable for mountain photovoltaic applications, such as Figure 1 As shown, it includes a machine body, a plurality of steering wheels 1 are arranged on the machine body, a tunneling cutter head 2 is arranged in front of the machine body, a visual probe 3 is arranged in the center of the tunneling cutter head 2, and the tail of the machine body is used for fixing the cable.

[0043] Preferably, the machine body is in the shape of an elongated oval, and a DC cable fixing buckle 7 is provided at the rear of the machine body, and the DC cable fixing buckle 7 is used to fix the cable.

[0044] Preferably, a GPS locator is provided on the machine body for locating the cable laying machine.

[0045] The working principle and beneficial effects of the above technical solution are as follows: during operation, the steering wheel 1 rotates to drive the machine body to move forward, and at the same time, the excavation cutter head 2 rotates underground to dig forward along the laying route, thereby driving the cable to follow the machine body and directly lay it into the dug tunnel, thereby realizing the laying of the cable. During the operation, the cable is fixed by the DC cable fixing buckle 7. The machine body is in an elongated elliptical shape, which facilitates the flexible movement of the machine body and can significantly reduce the friction between the machine body and the soil layer.

[0046] The present invention utilizes a small hole drilling machine to replace a traditional large cable laying machine for cable laying, thereby avoiding the risk of large cable laying machines operating on hillsides. At the same time, due to its small size and high flexibility, the laying efficiency is improved.

[0047] Example 2

[0048] On the basis of Example 1, a motor 4 and a battery 5 are provided in the machine body, the battery 5 is used to power the motor 4, and the output end of the motor 4 is connected to the tunneling cutter head 2 to drive the tunneling cutter head 2 to rotate;

[0049] A data transmitter 6 is provided at the rear of the tunneling cutter head 2 , and the data transmitter 6 is electrically connected to a movable terminal of the visual probe 3 .

[0050] The working principle and beneficial effects of the above technical solution are as follows: during the operation, the battery 5 is used to power the motor 4, and the motor 4 is used to drive the boring head 2 to rotate, thereby realizing the drilling action. During the drilling process, the visual probe 3 records the entire process and transmits the value to the mobile terminal through the data transmitter 6.

[0051] Example 3

[0052] On the basis of embodiment 1, an intelligent route change warning module is also included, and the intelligent route change warning module includes:

[0053] The video frame extraction submodule is used to divide the collected video in the current monitoring and collection cycle of the visual probe 3 into a number of single video frames;

[0054] The obstruction area to be confirmed identification submodule is used to identify the obstruction area to be confirmed based on a plurality of video single frames;

[0055] The obstruction confirmation submodule is used to confirm whether there is an obstruction in the obstruction to be confirmed area based on several video single frames in the obstruction to be confirmed area, and to determine the type of obstruction, which includes obstruction of living things, irresistible obstruction of inanimate objects, and resilient obstruction of inanimate objects;

[0056] The rerouting judgment module provides a rerouting plan and issues an alarm if the obstruction type is a living object obstruction or a dead object that can resist obstruction, prompting the staff to reselect the laying route.

[0057] The working principle and beneficial effects of the above technical solution are as follows: the video frame extraction submodule extracts single-frame images from the video recorded by the visual probe 3 during the monitoring and acquisition cycle. Through continuous video frame extraction, the system can analyze the current excavation environment in real time. The obstacle to be confirmed area identification submodule identifies the area where there may be obstacles, that is, the obstacle to be confirmed area. After identifying the obstacle to be confirmed area, the obstacle confirmation submodule further analyzes several video single frames in these areas to confirm whether there is actual obstruction, and then distinguishes the types of obstruction, including living things (such as small animals), dead things that cannot resist obstruction (such as large stones) and dead things that can resist obstruction (such as small branches). The diversion judgment module generates a diversion plan based on the result of the obstruction confirmation, if a living thing obstruction or a dead thing that can resist obstruction is detected, and issues an alarm prompt to remind the staff to reselect the laying route to avoid damaging the equipment or causing unnecessary damage to the environment;

[0058] The intelligent reroute warning module can detect and identify obstacles in the construction path in real time, especially obstacles involving living things, to avoid accidental harm to living things while ensuring the safe operation of the machine. By intelligently identifying and judging the type of obstacle, the system can quickly decide whether a reroute is needed, reducing human judgment time and improving overall construction efficiency. The real-time video transmission and obstacle identification functions enable remote operators to understand the on-site situation more intuitively and make more accurate decisions.

[0059] Example 4

[0060] On the basis of Example 3, the obstacle to be confirmed area identification submodule includes:

[0061] A calculation pixel acquisition unit is used to obtain the average of the pixel values ​​of adjacent pixels at each pixel position of all video single frames in the current monitoring acquisition cycle, and use it as the calculation pixel of the pixel at the corresponding pixel position of the video single frame, and obtain several calculation pixels of the corresponding pixel point through the same pixel position of several video single frames;

[0062] The background acquisition unit of the obstruction area to be confirmed takes the quotient of the sum of several calculated pixels of each pixel point and the total number of all video single frames of each collected video in the current monitoring and collection cycle as the background pixel value of each pixel point, and the image constructed by the background pixel values ​​of all pixels points is taken as the background of the obstruction area to be confirmed in the current monitoring and collection cycle;

[0063] The obstruction area to be confirmed identification unit calculates the absolute value of the difference between the background pixel value of each pixel position in the background of the obstruction area to be confirmed at the current moment and the pixel value of the corresponding pixel position in the single frame of the video at the current moment. If the absolute value of the difference corresponding to the pixel position is greater than the preset pixel difference, the pixel position is marked as the pixel position of the obstruction area to be confirmed, and the area composed of all the pixel positions of the obstruction area to be confirmed is the obstruction area to be confirmed.

[0064] The working principle and beneficial effects of the above technical solution: By comparing the calculated pixels and background pixels, the system can more accurately identify the pixel areas that are significantly different from the background and effectively detect potential obstacles. The background modeling method is used to effectively reduce the false alarm rate, so that the system can maintain a high accuracy even in complex environments. The dynamic update of background pixel values ​​enables the system to adapt to environmental changes, such as changes in lighting and environmental color, thereby improving the robustness of the system. By accurately identifying the obstruction area to be confirmed, the system can make timely diversions or alarm prompts, reduce the risk of construction interruptions and equipment damage, and improve construction efficiency and safety.

[0065] Example 5

[0066] Based on Example 3, the obstacle confirmation submodule includes:

[0067] The obstruction judgment unit is used to compare the pixel value of each pixel point of a single frame of the video of the obstruction area to be confirmed with the pixel values ​​of all pixel points in a preset obstruction image established based on the background of the obstruction area to be confirmed. If the pixel value of the corresponding pixel point of the single frame of the video of the obstruction area to be confirmed is greater than the pixel value of the corresponding pixel point of the preset obstruction image, it is marked as an obstruction pixel point. If the degree of aggregation of the obstruction pixels is greater than the preset degree of aggregation, it is judged that there is an obstruction, otherwise there is no obstruction;

[0068] The dynamic and static obstruction type classification unit uses the optical flow analysis method to extract the motion information of the obstruction pixel points, including the motion speed and direction. If the obstruction pixel points have motion information, they are marked as dynamic obstruction pixels and the corresponding type is classified as living obstruction. Otherwise, they are marked as static obstruction pixels and the corresponding type is classified as inanimate irresistible obstruction or inanimate resistible obstruction.

[0069] The resistance distinguishing unit is used to distinguish between the inanimate object's irresistible resistance and the inanimate object's resistance to resistance based on the three-channel values ​​of the static resistance pixel points.

[0070] The working principle and beneficial effects of the above technical solution are as follows: through pixel value comparison and aggregation degree analysis, the system can accurately identify whether there are obstacles, as well as the specific location and range of the obstacles. The dynamic and static obstacle type classification unit enables the system to distinguish between biological and non-biological obstacles, which is crucial to avoiding harm to small animals and accurate operation path selection. The anti-discrimination unit further refines the judgment of static obstacles through color and brightness information. Relying on optical flow analysis, the system can analyze motion information under real-time conditions and improve its adaptability to dynamic environments. The design of this module makes it suitable for cable laying in a variety of terrains and environments, which helps to maintain high performance in different construction scenarios.

[0071] Example 6

[0072] Based on Example 5, the anti-differentiation unit includes:

[0073] The weight determination subunit is used to sort the three-channel values ​​of the static obstruction pixel points, and take the quotient of the maximum value of the three-channel pixel values ​​of each static obstruction pixel point and the sum of its three-channel pixel values ​​as the maximum channel weight of the corresponding static obstruction pixel point;

[0074] The judgment value calculation subunit calculates the irresistible judgment value of the obstacle on the current video single frame based on the pixel values ​​of all static obstruction pixels on the current video single frame and the maximum weight of the static obstruction pixels.

[0075] Among them, β is the unstoppable judgment value of the obstacle in the current video single frame, n is the total number of static obstruction pixels in the current video single frame, is the pixel value of the i-th static obstruction pixel in the current video frame, γ i is the maximum weight of the i-th static obstruction pixel in the current video frame;

[0076] The classification subunit compares the force majeure judgment value of the obstacle on the current video single frame with the preset force majeure judgment value. If the force majeure judgment value of the obstacle on the current video single frame is greater than the preset force majeure judgment value, the current obstacle is force majeure, otherwise it is resistible.

[0077] The working principle and beneficial effects of the above technical solution are as follows: through the calculation of the maximum weight of the channel, the system can more finely evaluate the color characteristics of the obstacle, and the force majeure judgment value comprehensively considers the proportion of pixel value and weight, making the judgment of force majeure obstacles more robust and reliable. By refining the classification and judgment criteria, the system demonstrates more intelligent environmental adaptability and decision-making capabilities. Accurate obstacle classification reduces the frequency of manual confirmation and intervention, and improves the system's degree of automation.

[0078] Example 7

[0079] On the basis of Example 1, a residual soil output assembly is provided at the rear of the machine body, and the residual soil output assembly includes a suction pipe, an intermediate hose and an output pipe, wherein the suction pipe and the output pipe are hard pipes, and a negative pressure air pump is provided at the output pipe port.

[0080] The working principle and beneficial effects of the above technical solution are as follows: the negative pressure air pump is started to generate negative pressure, forming suction, the suction pipe sucks the remaining soil through the negative pressure, the soil is transported to the output pipe through the middle hose, and the output pipe discharges the remaining soil to the designated location to avoid soil accumulation at the construction site. The remaining soil generated during the construction process is removed while the cable is being laid, which can reduce the friction of the soil on the cable during the laying process.

[0081] Example 8

[0082] On the basis of embodiment 1, an emergency stop alarm module is also included, and the emergency stop alarm module includes:

[0083] The first-level detection unit is used to collect the load value of the machine body at each moment and monitor the load change value at each moment. If the actual load change value is greater than the preset load change value, the second-level detection is triggered;

[0084] The secondary detection unit is used to detect the moving speed of the body at each moment and monitor the change value of the moving speed at each moment. If the actual moving speed change value is greater than the preset speed change value, the third level detection is triggered;

[0085] The third-level detection unit is used to detect the fuselage tilt angle of the fuselage at each moment, and detect the change value of the fuselage tilt angle at each moment. If the actual fuselage tilt angle change value is greater than the preset tilt angle change value, an emergency stop alarm prompt will be issued.

[0086] The working principle and beneficial effects of the above technical solution are as follows: during the cable laying process, if the length of the laid cable reaches a preset length, the machine body may suddenly stop and overturn due to the friction between the cable and the soil or the cable being bent. The present invention identifies this phenomenon by detecting the actual load change value, the actual moving speed change value and the actual machine body tilt angle change value, and promptly issues an alarm when this phenomenon occurs, prompting the staff to adjust the cable in time to avoid further scratches on the cable or damage to the machine body.

[0087] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A remote-controlled visual DC cable laying machine suitable for mountain photovoltaic applications, characterized in that: The machine comprises a machine body, on which a plurality of steering wheels (1) are arranged, a tunneling cutter head (2) is arranged in front of the machine body, a visual probe (3) is arranged in the center of the tunneling cutter head (2), and the tail of the machine body is used for fixing cables.

2. According to the photovoltaic remote-controlled visual DC cable laying machine suitable for mountain areas as described in claim 1, a motor (4) and a battery (5) are arranged in the machine body, the battery (5) is used to power the motor (4), and the output end of the motor (4) is connected to the tunneling cutter head (2) to drive the tunneling cutter head (2) to rotate; A data transmitter (6) is provided at the rear of the tunneling cutter head (2), and the data transmitter (6) is electrically connected to a movable terminal of the visual probe (3).

3. The photovoltaic remote control visual DC cable laying machine suitable for mountain areas according to claim 1, characterized in that: The machine body is in the shape of an elongated ellipse. A DC cable fixing buckle (7) is provided at the rear of the machine body. The DC cable fixing buckle (7) is used to fix the cable.

4. The photovoltaic remote control visual DC cable laying machine suitable for mountain areas according to claim 1, characterized in that: It also includes an intelligent diversion warning module, which includes: A video frame extraction submodule, used for dividing the collected video in the current monitoring and collection cycle of the visual probe (3) into a plurality of single video frames; The obstruction area to be confirmed identification submodule is used to identify the obstruction area to be confirmed based on a number of video single frames; The obstruction confirmation submodule is used to confirm whether there is an obstruction in the obstruction to be confirmed area based on several video single frames in the obstruction to be confirmed area, and to determine the type of obstruction, which includes obstruction of living things, irresistible obstruction of inanimate objects, and resilient obstruction of inanimate objects; The rerouting judgment module provides a rerouting plan and issues an alarm if the obstruction type is a living object obstruction or a dead object that can resist obstruction, prompting the staff to reselect the laying route.

5. The photovoltaic remote control visual DC cable laying machine suitable for mountain areas according to claim 4, characterized in that: The submodules for identifying the area to be confirmed include: A calculation pixel acquisition unit is used to obtain the average of the pixel values ​​of adjacent pixels at each pixel position of all video single frames in the current monitoring acquisition cycle, and use it as the calculation pixel of the pixel at the corresponding pixel position of the video single frame, and obtain several calculation pixels of the corresponding pixel point through the same pixel position of several video single frames; The background acquisition unit of the obstruction area to be confirmed takes the quotient of the sum of several calculated pixels of each pixel point and the total number of all video single frames of each collected video in the current monitoring and collection cycle as the background pixel value of each pixel point, and the image constructed by the background pixel values ​​of all pixels points is taken as the background of the obstruction area to be confirmed in the current monitoring and collection cycle; The obstruction area to be confirmed identification unit calculates the absolute value of the difference between the background pixel value of each pixel position in the background of the obstruction area to be confirmed at the current moment and the pixel value of the corresponding pixel position in the single frame of the video at the current moment. If the absolute value of the difference corresponding to the pixel position is greater than the preset pixel difference, the pixel position is marked as the pixel position of the obstruction area to be confirmed, and the area composed of all the pixel positions of the obstruction area to be confirmed is the obstruction area to be confirmed.

6. The photovoltaic remote control visual DC cable laying machine suitable for mountain areas according to claim 4, characterized in that: The obstacle confirmation submodules include: The obstruction judgment unit is used to compare the pixel value of each pixel point of a single frame of the video of the obstruction area to be confirmed with the pixel values ​​of all pixel points in a preset obstruction image established based on the background of the obstruction area to be confirmed. If the pixel value of the corresponding pixel point of the single frame of the video of the obstruction area to be confirmed is greater than the pixel value of the corresponding pixel point of the preset obstruction image, it is marked as an obstruction pixel point. If the degree of aggregation of the obstruction pixels is greater than the preset degree of aggregation, it is judged that there is an obstruction, otherwise there is no obstruction; The dynamic and static obstruction type classification unit uses the optical flow analysis method to extract the motion information of the obstruction pixel points, including the motion speed and direction. If the obstruction pixel points have motion information, they are marked as dynamic obstruction pixels and the corresponding type is classified as living obstruction. Otherwise, they are marked as static obstruction pixels and the corresponding type is classified as inanimate irresistible obstruction or inanimate resistible obstruction. The resistance distinguishing unit is used to distinguish between the inanimate object's irresistible resistance and the inanimate object's resistance to resistance based on the three-channel values ​​of the static resistance pixel points.

7. The photovoltaic remote control visual DC cable laying machine suitable for mountain areas according to claim 6, characterized in that: The anti-differentiation units include: The weight determination subunit is used to sort the three-channel values ​​of the static obstruction pixel points, and take the quotient of the maximum value of the three-channel pixel values ​​of each static obstruction pixel point and the sum of its three-channel pixel values ​​as the maximum channel weight of the corresponding static obstruction pixel point; The judgment value calculation subunit calculates the irresistible judgment value of the obstacle on the current video single frame based on the pixel values ​​of all static obstruction pixels on the current video single frame and the maximum weight of the static obstruction pixels. Among them, β is the unstoppable judgment value of the obstacle in the current video single frame, n is the total number of static obstruction pixels in the current video single frame, is the pixel value of the i-th static obstruction pixel in the current video frame, γ i is the maximum weight of the i-th static obstruction pixel in the current video frame; The classification subunit compares the force majeure judgment value of the obstacle on the current video single frame with the preset force majeure judgment value. If the force majeure judgment value of the obstacle on the current video single frame is greater than the preset force majeure judgment value, the current obstacle is force majeure, otherwise it is resistible.

8. The photovoltaic remote control visual DC cable laying machine suitable for mountain areas according to claim 1, characterized in that: The tail of the machine body is provided with a surplus soil output assembly, which comprises a suction pipe, an intermediate hose and an output pipe, wherein the suction pipe and the output pipe are hard pipes, and a negative pressure air pump is provided at the output pipe opening.

9. The photovoltaic remote control visual DC cable laying machine suitable for mountain areas according to claim 1, characterized in that: The machine body is provided with a GPS locator for locating the cable laying machine.

10. The photovoltaic remote control visual DC cable laying machine suitable for mountain areas according to claim 1, characterized in that: It also includes an emergency stop alarm module, which includes: The primary detection unit is used to collect the load value of the machine body at each moment and monitor the load change value at each moment. If the actual load change value is greater than the preset load change value, the secondary detection is triggered; The secondary detection unit is used to detect the moving speed of the body at each moment and monitor the change value of the moving speed at each moment. If the actual moving speed change value is greater than the preset speed change value, the third level detection is triggered; The third-level detection unit is used to detect the fuselage inclination angle of the fuselage at each moment, and detect the fuselage inclination angle change value at each moment. If the actual fuselage inclination angle change value is greater than the preset inclination angle change value, an emergency stop alarm prompt is issued.

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