A full life cycle slope protection net system

Abstract

The embodiment of the present application provides a full life cycle slope protection net system, the full life cycle slope protection net system includes active protection net system (1), the active protection net system (1) includes a plurality of fiber grating sensors (14), the fiber grating sensor (14) is arranged on the first net body (11), is used for obtaining the strain information of first anchor rod (13) and / or the strain information of anchor clasp according to the deformation of first net body (11), and the strain information is converted into first electric signal or first optical signal;The fiber grating sensor (14) is electrically connected to the edge computing node arranged near the active protection net system (1);The edge computing node is electrically connected to the cloud platform through the wireless sensor (3). The force and deformation information of the local protection net can be obtained in real time and accurately, which provides accurate data support for subsequent early warning and regulation.

Description

Technical Field

[0001] This invention relates to the field of slope disaster prevention, specifically to a full life-cycle slope protection net system. Background Technology

[0002] With the rapid development of infrastructure construction, slope structure engineering in projects such as water conservancy, hydropower, and transportation is gradually increasing. Under the influence of internal and external dynamic factors such as frequent earthquakes, strong unloading, periodic rainfall, and high-frequency freeze-thaw cycles, slope engineering construction and operation and maintenance often face various geological disasters, such as collapses, landslides, and debris flows, posing great safety hazards to social economy, urban development, and the safety of people's lives and property. Although traditional active protection nets can prevent loose rock and soil from sliding or collapsing by closely adhering to the rock and soil surface and adding prestress or anchoring, they cannot monitor the stress state and disaster parameters of the net in real time, making it difficult to provide early warning and automatic adjustment when adverse loads occur. Summary of the Invention

[0003] This invention provides a full life-cycle slope protection net system that can solve the above-mentioned technical problems in the prior art.

[0004] To achieve the above objectives, in a first aspect, embodiments of the present invention provide a full life-cycle slope protection net system, the full life-cycle slope protection net system including an active protection net system, the active protection net system including a first net body, a first net cable and a first anchor rod;

[0005] The first anchor bolts are fixed at intervals on the slope, and multiple first anchor bolts form a transverse column and a longitudinal column that intersects with the transverse column. The first net cable is tensioned and connected between adjacent first anchor bolts, and the first net cable is attached to the rock and soil of the slope surface.

[0006] The first net has multiple bodies, each of which is placed on the rock and soil of the slope surface. The edge of each first net is connected to the adjacent first net cable by a soft rope and the first net is in a taut state. The contact section between the soft rope and the first net cable is fixed by an anchor buckle.

[0007] The active protection network system also includes multiple fiber Bragg grating sensors, which are disposed on the first net body and are used to obtain the strain information of the first anchor rod and / or the strain information of the anchor buckle based on the deformation of the first net body, and convert the strain information into a first electrical signal or a first optical signal; the fiber Bragg grating sensors are electrically connected to an edge computing node located near the active protection network system;

[0008] The edge computing nodes are connected to the cloud platform via wireless sensors.

[0009] Secondly, embodiments of the present invention provide a slope protection method covering the entire life cycle, comprising:

[0010] During the slope operation period, the fiber optic grating sensor of the active protection net system obtains the strain information of the first anchor rod and / or the strain information of the anchor buckle based on the deformation of the first net body, and converts the strain information into a first electrical signal or a first optical signal.

[0011] The fiber Bragg grating sensor transmits a first electrical signal or a first optical signal to an edge computing node located near the active protection network system;

[0012] The edge computing node transmits a first electrical signal or a first optical signal to the cloud platform via a wireless sensor.

[0013] The slope stability is calculated by using the background diagnostic model in the cloud platform based on the strain information of the first anchor rod and / or the strain information of the anchor buckle corresponding to the first electrical signal or the first optical signal.

[0014] Based on slope stability, corresponding maintenance strategies are proposed;

[0015] The active protection net system includes a first net body, a first net cable, and a first anchor rod. The first anchor rods are fixed at intervals on the slope, and multiple first anchor rods respectively form a transverse column and a longitudinal column intersecting the transverse column. The first net cable is tensioned and connected between adjacent first anchor rods, and the first net cable is attached to the rock and soil of the slope surface. There are multiple first net bodies, each of which covers the rock and soil of the slope surface. The edge of each first net body is connected to the adjacent first net cable by a soft rope, and the first net body is in a tensioned state. The contact section between the soft rope and the first net cable is fixed by an anchor buckle.

[0016] The active protection network system also includes multiple fiber Bragg grating sensors, which are disposed on the first net body and are used to obtain the strain information of the first anchor rod and / or the strain information of the anchor buckle based on the deformation of the first net body, and convert the strain information into a first electrical signal or a first optical signal; the fiber Bragg grating sensors are electrically connected to an edge computing node located near the active protection network system;

[0017] The edge computing nodes are connected to the cloud platform via wireless sensors.

[0018] The above technical solution has the following beneficial effects: it can acquire local stress and deformation information of the protective net in real time and accurately, providing accurate data support for subsequent early warning and control. Compared with traditional protective nets that cannot monitor local conditions in real time, it greatly improves the accuracy and timeliness of monitoring, helps to detect potential safety hazards in advance, and ensures the safety of the protective net. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a schematic diagram of the active protection network system according to an embodiment of the present invention;

[0021] Figure 3 This is a flowchart of the active protection network system according to an embodiment of the present invention;

[0022] Figure 2 This is a schematic diagram of the passive protection network system according to an embodiment of the present invention;

[0023] Figure 4 This is a flowchart illustrating the operation of the passive protection network system according to an embodiment of the present invention.

[0024] Figure 5 This is a flowchart of a slope protection method covering the entire life cycle according to an embodiment of the present invention.

[0025] The reference numerals in the attached figures are as follows:

[0026] 1. Active protection net system; 2. Passive protection net system; 3. Wireless sensor; 11. First net body; 12. First net cable; 13. First anchor bolt; 14. Fiber optic grating sensor; 15. Miniature strain sensor; 16. Energy sensing and mechanical control module; 17. Soft rope; 21. Second net body; 22. Vertical rod; 23. Second anchor bolt; 24. Second net cable; 25. Displacement sensor; 26. Ultrasonic sensor; 27. Camera; 28. Vibration sensor. Detailed Implementation

[0027] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0028] like Figure 1 As shown, in conjunction with an embodiment of the present invention, a full life cycle slope protection net system is provided. The full life cycle slope protection net system includes an active protection net system 1, which includes a first net body 11, a first net cable 12, and a first anchor rod 13.

[0029] The first anchor rods 13 are fixed at intervals on the slope. Multiple first anchor rods 13 form a transverse column and a longitudinal column that intersects with the transverse column. The first net cable 12 is tensioned and connected between adjacent first anchor rods 13, and the first net cable 12 is attached to the rock and soil of the slope surface.

[0030] The first net body 11 has multiple parts, each first net body 11 is covered on the rock and soil of the slope surface, and the edge of each first net body 11 is connected to the adjacent first net cable 12 by a soft rope 17 and the first net body 11 is in a tensioned state. The contact section between the soft rope 17 and the first net cable 12 is fixed by an anchor buckle.

[0031] The active protection network system 1 also includes multiple fiber Bragg grating sensors 14, which are disposed on the first mesh body 11 and are used to obtain the strain information of the first anchor rod 13 and / or the strain information of the anchor buckle based on the deformation of the first mesh body 11, and convert the strain information into a first electrical signal or a first optical signal; the fiber Bragg grating sensors 14 are electrically connected to an edge computing node located near the active protection network system 1;

[0032] The edge computing node is electrically connected to the cloud platform via a wireless sensor 3.

[0033] It can acquire real-time and accurate information on the stress and deformation of local areas of the protective net, providing accurate data support for subsequent early warning and control. Compared with traditional protective nets that cannot monitor local conditions in real time, it greatly improves the accuracy and timeliness of monitoring, helps to detect potential safety hazards in advance, and ensures the safety of the protective net.

[0034] Preferably, the active protection network system 1 further includes a micro strain sensor 15, which is disposed on each of the first anchor rods 13 to acquire strain information of the first anchor rod 13. The micro strain sensor 15 is also disposed on the anchor buckle to acquire strain information of the anchor buckle and convert the strain information into a second electrical signal or a second optical signal. The micro strain sensor 15 is electrically connected to the edge computing node.

[0035] The miniature strain sensor 15 and the fiber optic grating sensor 14 are complementary.

[0036] Preferably, the active protection network system 1 further includes a rain sensor installed on the edge computing node for real-time monitoring of rainfall, and a seismic sensor installed on the edge computing node for sensing seismic wave parameters, wherein the rain sensor and the seismic sensor are electrically connected to the edge computing node.

[0037] Preferably, the active protective net system 1 further includes hydraulic actuators spaced apart at the first anchor rod 13 and the first net body 11. The hydraulic actuators include hydraulic cylinders, one end of which is connected to the head of the first anchor rod 13, and the other end of which is connected to the first net body 11. The hydraulic actuators apply or adjust the force by pushing the piston rod to reciprocate through the pressure of hydraulic oil, thereby changing the preload (i.e., prestress) of the entire protective net system. Existing hydraulic cylinders can be used. The specifications, structure, and principle of hydraulic cylinders are common knowledge, and there are no restrictions on the specifications, structure, and principle of hydraulic cylinders. As long as the functions in the embodiments of the present invention can be achieved, they will not be described in detail here.

[0038] The active protection net system 1 also includes an intelligent sensing and mechanical control module 16, which is used to send control commands to a designated hydraulic actuator according to the maintenance strategy, and the designated hydraulic actuator is used to adjust the prestress of the first anchor rod 13 according to the control commands.

[0039] Preferably, it also includes a background diagnostic model located in the cloud platform. The background diagnostic model is used to receive signal data about the active protection network system 1 sent by the edge computing node, evaluate the working status and damage level of the active protection network system 1 based on the signal data, and provide corresponding maintenance strategies.

[0040] Preferably, the full life cycle slope protection net system further includes a passive protection net system 2, which is vertically installed at the bottom of the active protection net system 1. The passive protection net system 2 includes: a second net body 21, vertical poles 22, second anchor rods 23, and second net cables 24. The vertical poles 22 are fixed to the ground at intervals. The second net body 21 is tensioned and connected to two adjacent vertical poles 22. The second anchor rods 23 are fixed to the bottom surface near the vertical poles 22. Each vertical pole 22 is fixedly connected to the corresponding second anchor rod 23 by at least two second net cables 24.

[0041] The passive protection net system 2 also includes a vibration sensor 28 installed at the connection between the second net body 21 and the vertical rod 221. The vibration sensor 28 is used to detect the vibration of the second net body 21 when it is subjected to impact and convert the vibration into a third electrical signal. The vibration sensor 28 is electrically connected to the edge computing node.

[0042] Preferably, the passive protection net system 2 further includes a displacement sensor 25 installed on each of the second net bodies 21. The displacement sensor 25 is used to monitor the displacement change of the second net body 21 to obtain the slack of the second net cable 24 and convert the slack into a fourth electrical signal; the displacement sensor 25 is electrically connected to the edge computing node.

[0043] Preferably, the passive protection net system 2 further includes an ultrasonic sensor 26 installed at the bottom of the passive protection net system 2. The ultrasonic sensor 26 is used to measure the height of the debris accumulation in the passive protection net system 2 by emitting and receiving ultrasonic waves, calculate the amount of debris accumulation, and convert the amount of debris accumulation into a fifth electrical signal; the ultrasonic sensor 26 is electrically connected to the edge computing node.

[0044] The passive protection net system 2 also includes a camera 27 installed at the top of the vertical pole 22. The camera 27 is used to capture images of the rubble accumulation within the passive protection net system 2 in real time and convert the rubble accumulation images into a sixth electrical signal. The camera 27 is electrically connected to the edge computing node.

[0045] Preferably, the passive protection net system 2 further includes a pneumatic scraper device disposed within the passive protection net system 2. The pneumatic scraper device includes a pneumatic scraper, a guide rail, and a pneumatic drive device. The pneumatic scraper matches the curved surface on the second net body 21. The pneumatic scraper is movably disposed on the guide rail. The specific connection method is not limited, as long as it can move on the guide rail. The guide rail is installed on the edge or surface of the second net body 21. The pneumatic drive device is used to drive the pneumatic scraper to move on the guide rail. The pneumatic drive device can be a device that uses gas to generate power in the prior art, which is not limited here and will not be described in detail.

[0046] When the amount of gravel accumulated in the passive protection net system 2 reaches a certain level, the pneumatic scraper device provides power through a pneumatic drive device according to the instructions of the control system, so that the pneumatic scraper moves on the guide rail and along the inner net surface of the passive protection net system 2, so as to scrape the gravel to the designated position by the pneumatic scraper.

[0047] Preferably, the full life cycle slope protection net system further includes a background diagnostic model located in a cloud platform. The background diagnostic model is used to receive signal data about the passive protection net system 2 sent by edge computing nodes, evaluate the working status and damage level of the passive protection net system 2 based on the signal data, and provide corresponding maintenance strategies.

[0048] like Figure 5 As shown, in conjunction with embodiments of the present invention, a slope protection method covering the entire life cycle is provided, comprising:

[0049] S101: During the operation period of the slope, the fiber optic grating sensor of the active protection net system obtains the strain information of the first anchor rod and / or the strain information of the anchor buckle based on the deformation of the first net body, and converts the strain information into a first electrical signal or a first optical signal.

[0050] S102: The fiber optic grating sensor transmits the first electrical signal or the first optical signal to the edge computing node located near the active protection network system;

[0051] S103: The edge computing node transmits the first electrical signal or the first optical signal to the cloud platform through a wireless sensor;

[0052] S104: Calculate the slope stability using the background diagnostic model within the cloud platform based on the strain information of the first anchor bolt and / or the strain information of the anchor buckle corresponding to the first electrical signal or the first optical signal; and provide corresponding maintenance strategies based on the slope stability.

[0053] The active protection net system 1 includes a first net body 11, a first net cable 12, and a first anchor rod 13. The first anchor rods 13 are fixed at intervals on the slope, and multiple first anchor rods 13 form a transverse column and a longitudinal column intersecting the transverse column. The first net cable 12 is tensioned and connected between adjacent first anchor rods 13, and the first net cable 12 is attached to the rock and soil of the slope surface. There are multiple first net bodies 11, and each first net body 11 is covered on the rock and soil of the slope surface. The edge of each first net body 11 is connected to the adjacent first net cable 12 by a soft rope 17 and the first net body 11 is in a tensioned state. The contact section between the soft rope 17 and the first net cable 12 is fixed by an anchor buckle.

[0054] The active protection network system 1 also includes multiple fiber Bragg grating sensors 14, which are disposed on the first mesh body 11 and are used to obtain the strain information of the first anchor rod 13 and / or the strain information of the anchor buckle based on the deformation of the first mesh body 11, and convert the strain information into a first electrical signal or a first optical signal; the fiber Bragg grating sensors 14 are electrically connected to an edge computing node located near the active protection network system 1;

[0055] The edge computing node is electrically connected to the cloud platform via a wireless sensor 3.

[0056] It can acquire real-time and accurate information on the stress and deformation of local areas of the protective net, providing accurate data support for subsequent early warning and control. Compared with traditional protective nets that cannot monitor local conditions in real time, it greatly improves the accuracy and timeliness of monitoring, helps to detect potential safety hazards in advance, and ensures the safety of the protective net.

[0057] Preferably, the slope protection method covering the entire life cycle further includes:

[0058] The strain information of the first anchor rod 13 is obtained by a miniature strain sensor 15 installed on each of the first anchor rods 13;

[0059] The strain information of the anchor is obtained by a miniature strain sensor 15 installed on the anchor, and the strain information is converted into a second electrical signal or a second optical signal.

[0060] The second electrical signal or the second optical signal is transmitted to the edge computing node via the micro strain sensor 15;

[0061] The edge computing node transmits a second electrical signal or a second optical signal to the cloud platform via wireless sensor 3.

[0062] The slope stability is calculated by using the background diagnostic model in the cloud platform based on the strain information of the first anchor rod 13 and / or the strain information of the anchor buckle corresponding to the second electrical signal or the second optical signal.

[0063] When one of the micro strain sensor 15 and the fiber optic grating sensor 14 fails to acquire strain information or acquires inaccurate strain information, the strain information acquired by the other sensor is used.

[0064] Preferably, the slope protection method covering the entire life cycle further includes:

[0065] Rainfall is monitored in real time by a rainfall sensor installed on an edge computing node belonging to the active protection network system 1, and the rainfall is transmitted to the edge computing node. The edge computing node then transmits the rainfall to the cloud platform via a wireless sensor 3.

[0066] The background diagnostic model within the cloud platform calculates the slope stability based on the rainfall and the strain information of the first anchor bolt 13 and / or the anchor buckle, combined with historical disaster data, and determines whether the stability has reached a preset warning threshold; if the preset warning threshold is reached, a warning message is issued to the management personnel.

[0067] The seismic wave parameters are sensed in real time by the seismic sensors installed on the edge computing nodes belonging to the active protection network system 1, and the seismic wave parameters are transmitted to the edge computing nodes. The edge computing nodes then transmit the seismic wave parameters to the cloud platform through the wireless sensor 3.

[0068] The background diagnostic model within the cloud platform calculates the slope stability based on the seismic wave parameters, the strain information of the first anchor bolt 13, and / or the strain information of the anchor buckle, combined with historical disaster data and rainfall data when rainfall is present. It then determines whether the stability has reached a preset warning threshold. If the preset warning threshold is reached, a warning message is sent to the management personnel.

[0069] Preferably, the slope protection method covering the entire life cycle further includes:

[0070] The intelligent sensing and mechanical control module 16 of the active protection network system 1 sends control commands to the designated hydraulic actuators according to the maintenance strategy, and designates the hydraulic actuators to adjust the prestress of the first anchor rod 13 according to the control commands.

[0071] The active protective net system 1 further includes hydraulic actuators spaced apart at the first anchor rod 13 and the first net body 11. Each hydraulic actuator includes a hydraulic cylinder, one end of which is connected to the head of the first anchor rod 13, and the other end to the first net body 11. The hydraulic actuator uses hydraulic oil pressure to drive a piston rod in reciprocating motion to apply or adjust the force, thereby changing the preload (i.e., prestress) of the entire protective net system. Existing hydraulic cylinders are acceptable; their specifications, structure, and principles are common knowledge, and there are no limitations on their specifications, structure, and principles, as long as they can achieve the functions described in this embodiment. Further details are omitted here.

[0072] Preferably, the slope protection method covering the entire life cycle further includes:

[0073] Vibration sensor 28 detects the vibration of the second mesh 21 when it is subjected to impact, and converts the vibration into a third electrical signal;

[0074] The vibration sensor 28 transmits the third electrical signal to the edge computing node located near the active protection network system 1.

[0075] The edge computing node transmits a third electrical signal to the cloud platform via wireless sensor 3.

[0076] The background diagnostic model within the cloud platform determines the size of the falling body based on the vibration corresponding to the third electrical signal and provides corresponding maintenance strategies.

[0077] The passive protection net system 2 is vertically installed at the bottom of the active protection net system 1. The passive protection net system 2 includes: a second net body 21, vertical poles 22, second anchor rods 23, and second net cables 24. The vertical poles 22 are fixed to the ground at intervals. The second net body 21 is tensioned and connected to two adjacent vertical poles 22. The second anchor rods 23 are fixed to the bottom surface near the vertical poles 22. Each vertical pole 22 is fixedly connected to the corresponding second anchor rod 23 by at least two second net cables 24.

[0078] The passive protection net system 2 also includes a vibration sensor 28 installed at the connection between the second net body 21 and the vertical rod 221. The vibration sensor is used to detect the vibration of the second net body 21 when it is subjected to impact and convert the vibration into a third electrical signal. The vibration sensor is electrically connected to the edge computing node.

[0079] Preferably, the slope protection method covering the entire life cycle further includes:

[0080] The displacement sensor 25 monitors the displacement change of the second net body 21 to obtain the slack of the second net cable 24, and converts the slack into a fourth electrical signal.

[0081] The fourth electrical signal is transmitted to the edge computing node located near the active protection network system 1 via the displacement sensor 25.

[0082] The edge computing node transmits the fourth electrical signal to the cloud platform via wireless sensor 3.

[0083] Based on the relaxation amount corresponding to the fourth electrical signal, the background diagnostic model in the cloud platform provides a corresponding maintenance strategy for the second anchor bolt 23.

[0084] The passive protection net system 2 further includes a displacement sensor 25 installed on each of the second net bodies 21. The displacement sensor 25 is used to monitor the displacement change of the second net body 21 to obtain the slack of the second net cable 24 and convert the slack into a fourth electrical signal. The displacement sensor 25 is electrically connected to the edge computing node.

[0085] Preferably, the slope protection method covering the entire life cycle further includes:

[0086] The ultrasonic sensor 26 installed at the bottom of the passive protection net system 2 transmits and receives ultrasonic waves to measure the height of the gravel accumulation in the passive protection net system 2, calculates the amount of gravel accumulation, and converts the amount of gravel accumulation into a fifth electrical signal.

[0087] The ultrasonic sensor 26 transmits the fifth electrical signal to the edge computing node located near the active protection network system 1.

[0088] The edge computing node transmits the fifth electrical signal to the cloud platform via wireless sensor 3.

[0089] The background diagnostic model within the cloud platform uses the amount of gravel accumulation corresponding to the fifth electrical signal to provide corresponding gravel treatment strategies.

[0090] Preferably, the slope protection method covering the entire life cycle further includes:

[0091] The camera 27, installed at the top of the vertical pole 22, captures real-time images of the debris accumulation within the passive protection netting system 2, and converts these images into a sixth electrical signal.

[0092] The sixth electrical signal is transmitted via the camera 27 to an edge computing node located near the active protection network system 1; the edge computing node transmits the sixth electrical signal to the cloud platform via the wireless sensor 3;

[0093] Based on the image corresponding to the sixth electrical signal and the amount of gravel accumulation corresponding to the fifth electrical signal, the background diagnostic model in the cloud platform provides a corresponding gravel treatment strategy.

[0094] The camera 27 is electrically connected to the edge computing node.

[0095] Preferably, the slope protection method covering the entire life cycle further includes:

[0096] During the slope maintenance period, when the amount of gravel accumulated in the passive protection net system 2 reaches a certain level, the slope maintenance period begins. According to the instructions of the control system, the pneumatic scraper device moves along the inner net surface of the passive protection net system 2 to scrape the gravel to the designated position.

[0097] The passive protection net system 2 further includes a pneumatic scraper device disposed within the system. The pneumatic scraper device comprises a pneumatic scraper, a guide rail, and a pneumatic drive device. The pneumatic scraper matches the curved surface of the second net body 21. The pneumatic scraper is movably mounted on the guide rail; the specific connection method is not limited, as long as it allows movement along the guide rail. The guide rail is installed on the edge or surface of the second net body 21. The pneumatic drive device drives the pneumatic scraper to move along the guide rail. The pneumatic drive device can be any existing gas-driven power generation device; this is not limited or elaborated upon here.

[0098] When the amount of gravel accumulated in the passive protection net system 2 reaches a certain level, the pneumatic scraper device provides power through a pneumatic drive device according to the instructions of the control system, so that the pneumatic scraper moves on the guide rail and along the inner net surface of the passive protection net system 2, so as to scrape the gravel to the designated position by the pneumatic scraper.

[0099] Preferably, the slope protection method covering the entire life cycle also includes...

[0100] During the slope maintenance period, the slope protection method of the whole life cycle is used to continuously monitor: the strain information of the first anchor 13 and / or the strain information of the anchor buckle, rainfall, seismic wave parameters, vibration of the second net body 21 when it is impacted, the slack of the second net cable 24, the amount of gravel accumulation in the net and the image of gravel accumulation.

[0101] By using the backend diagnostic model within the cloud platform, combined with historical pile data and geological conditions and climate information of the slope, the amount of gravel accumulation in the future can be predicted; when the predicted accumulation is about to reach the clearing threshold, an early warning message is issued.

[0102] The technical solutions of the present invention will be described in detail below with reference to specific application examples. For technical details not described in the implementation process, please refer to the relevant descriptions above.

[0103] This invention relates to a full-lifecycle slope protection net system and corresponding method. Based on multi-source information fusion and intelligent control, it achieves comprehensive disaster management of slopes to effectively address geological disasters such as landslides and collapses. By combining an intelligent active protection net system with a multi-functional passive protection net system, and leveraging a digital platform to achieve full lifecycle management during the construction, operation, and maintenance periods, it overcomes the shortcomings of existing slope protection net technologies in real-time monitoring, automatic control, maintenance efficiency, and full-cycle management. This improves the safety of the protection net, extends its service life, reduces maintenance costs, and enhances disaster response capabilities, thereby improving the overall effectiveness and reliability of geological disaster protection.

[0104] I. Intelligent Active Protection Network System

[0105] (I) Structural Composition

[0106] The intelligent active protection network system is built upon traditional active protection networks, primarily adding intelligent sensing and mechanical control modules, and deploying wireless sensors at monitoring points to communicate with a digital platform. The intelligent active protection network system specifically includes:

[0107] 1. Net Structure and Anchoring Components: The net structure follows the traditional active protection net, secured to the slope's soil and rock surface using anchor bolts and other anchoring components. Sensing components are integrated at the anchor points where the net cables and anchor bolts connect to the net structure. An anchor bolt is a component that transmits tensile force to the stable soil and rock layer. It is typically made of high-strength, precision-rolled threaded steel bars, and sometimes a small amount of prestress is applied. The anchor bolt fully exerts its anchoring effect only after the soil and rock mass has undergone a certain degree of deformation.

[0108] 2. Sensors:

[0109] (1) Fiber Bragg Grating (FBG) Sensor: A fiber Bragg grating sensor is integrated into the cable net or anchor, wherein one fiber Bragg grating sensor 14 is installed on each anchor. A fiber Bragg grating is an optical device with a periodically changing refractive index formed in the core of an optical fiber. Changes in external stress will cause its Bragg wavelength to drift. By detecting the amount of wavelength drift, strain information of the cable net or anchor can be obtained, thereby realizing real-time monitoring of local stress.

[0110] (2) Miniature strain sensor: Also arranged at the net cable or anchor, the miniature strain sensor measures the strain of the net cable or anchor by the change in resistance or capacitance caused by strain in its internal sensitive element, thereby reflecting the local stress and deformation.

[0111] Since miniature strain sensors and fiber optic grating sensors operate on different principles, when one type of sensor is insensitive or cannot obtain strain information from the cable or anchor, the strain information from the cable or anchor obtained by the other type of sensor can be used.

[0112] (3) Disaster parameter sensors: Rainfall sensors are installed on edge computing nodes to monitor rainfall in real time, and seismic sensors installed on edge computing nodes near the active protection network system are used to sense relevant parameters of seismic waves, such as intensity and frequency. These sensors provide the system with external environmental parameters closely related to geological disasters.

[0113] 3. Mechanical control device: Install mechanical control devices such as hydraulic actuators to automatically apply or adjust the prestress to the protective net when the system determines that the prestress needs to be adjusted.

[0114] (II) Working principle and process, such as Figure 3 As shown

[0115] 1. Real-time monitoring phase:

[0116] (1) Local stress and deformation monitoring: When the slope soil and rock mass undergoes displacement or changes in stress, it will be transmitted to the net cables and anchors of the protective net, causing deformation. The Bragg wavelength of the fiber optic grating sensor or the resistance / capacitance of the miniature strain sensor will change accordingly, and the sensor will convert these changes into electrical or optical signals for output.

[0117] (2) Disaster parameter monitoring: Rainfall sensors continuously monitor rainfall and output the rainfall data in the form of electrical signals; seismic sensors sense seismic waves in real time and convert earthquake-related parameters into electrical signals. Big data algorithms are used to assess slope stability, especially to provide timely warnings of abnormal tension under extreme conditions such as heavy rainfall and earthquakes.

[0118] 2. Data Transmission and Preliminary Processing Stage: Signals output from various sensors are transmitted to edge computing nodes in the edge computing layer via wired (e.g., shielded cables) or wireless (e.g., ZigBee, LoRa) methods. These edge computing nodes are located near the active protection network. The edge computing nodes perform preliminary data processing, including signal amplification, noise filtering, and data format conversion, to improve data quality and facilitate subsequent analysis.

[0119] 3. Data Cloudification and Analysis / Early Warning Phase: After initial processing, the data is uploaded to the cloud platform via a LoRa gateway using a network (such as 4G / 5G or fiber optic networks). The cloud platform employs big data algorithms, combined with geological information of the slope, historical disaster data, and real-time monitoring data, to comprehensively assess the slope's stability. In extreme conditions such as heavy rainfall or earthquakes, if abnormal tensile forces or other key data reach preset warning thresholds, the system immediately identifies the issue using big data algorithms and issues a warning to management personnel. Warning methods include SMS and app push notifications.

[0120] 4. Automatic prestress adjustment stage of the stress adjustment device: Once the system issues an early warning, the intelligent sensing and mechanical control module will send control commands to the hydraulic actuator (the position of the anchor rod and the first net body (11)) according to the early warning information. The hydraulic actuator automatically adjusts the prestress of the protective net according to the command, enhances the anchoring force of the protective net to the soil and rock, and makes the protective net achieve the best interception and buffering effect, ensuring the stability of the slope. The hydraulic actuator changes the pretension (i.e., prestress) of the entire protective net system by applying or adjusting the force at the position of the anchor rod and the first net body 11. The purpose of the hydraulic actuator is to adjust the tension (i.e., prestress) of the protective net relative to the anchor rod. Therefore, its installation position is at the connection between the protective net system and the anchor point (anchor rod), and it can apply or adjust the tension / pressure. The hydraulic actuator is installed between the head of the main anchor rod and the protective net connection structure. A special connection device is installed on the part of the anchor rod that is exposed on the ground. One end of the hydraulic actuator (usually a hydraulic cylinder) is connected to the anchor head (or the bearing plate on it), and the other end is connected to the main load-bearing component of the protective netting system (e.g., the edge support rope connected to the "first netting (11)", or the connecting plate that gathers multiple wire ropes, etc.). When increased prestress is required, the hydraulic cylinder extends (or shortens, depending on the specific design), further tightening the protective netting system relative to the anchor. Conversely, it loosens. It can act directly on the connection between the anchor point and the netting system, and the adjustment effect is direct and clear.

[0121] The number of hydraulic actuators depends on the size of the protective net and the anchor layout: (1) Small or localized protective nets: Hydraulic actuators may only need to be installed at a few key anchor locations, such as the top anchors (bearing the main vertical loads) or the corner anchors (controlling the shape and boundary tension of the net). The number may be around 2 to 4. (2) Large or integral protective nets: To achieve more uniform and effective overall prestressing adjustment, hydraulic actuators may need to be installed at most or all major anchor locations (especially along the top boundary and possible side boundaries). The number may reach several or even a dozen. (3) Considering redundancy and zoned control: Even in large protective nets, not every anchor may be needed, but rather selectively installed on anchors that can effectively control the tension of the entire net surface or specific areas.

[0122] II. Intelligent Multifunctional Passive Protection Network System

[0123] (I) Structural Composition

[0124] like Figure 2 The passive protection network system shown is an intelligent and multifunctional system that improves upon the traditional passive protection network by adding the following components:

[0125] 1. Detection sensor:

[0126] (1) Vibration sensor: Installed at key parts of the passive net, such as the connection between the net and the supporting structure (vertical rod), to detect the vibration of the protective net when it is impacted, and to determine whether there is a rockfall or other impact.

[0127] (2) Displacement sensor: placed near the second net cable to monitor whether the net cable is loose. When the looseness of the net cable exceeds a certain range, it may affect the interception effect of the protective net and needs to be dealt with in time.

[0128] (3) Ultrasonic sensor: Installed in a suitable position within the passive net, it measures the height of the gravel accumulation within the net by emitting and receiving ultrasonic waves, and then calculates the amount of gravel accumulation.

[0129] (4) Camera: Install a camera at a key location in the passive net (top of the pole) to capture real-time images of the inside of the protective net and obtain image information of the accumulation of gravel inside the net to help determine the working status of the protective net.

[0130] 2. Cleaning Device: Equipped with a pneumatic scraper and other cleaning devices, when the amount of gravel accumulated inside the mesh reaches a certain level, the pneumatic scraper can move along the mesh surface under the command of the control system, scraping the gravel to a designated position, thus achieving partial cleaning. This reduces the stress on the mesh surface and allows for the collection of more gravel and other falling objects.

[0131] First, structural components: (1) Pneumatic scraper: As the main cleaning element, its shape conforms to the curved surface design of the second mesh body 21, that is, the pneumatic scraper matches the curved surface on the second mesh body 21 and can scrape away gravel along the mesh surface. (2) Guide rail system: Includes guide rails, which are installed on the surface or edge of the second mesh body 21 to allow the pneumatic scraper to move along the mesh surface according to control commands. (3) Pneumatic drive device: Provides power to the scraper to realize the translational movement of the scraper, and usually includes a cylinder, air pipe and air source interface. (4) Control system interface: Receives commands from the monitoring system and controls the start, stop and movement path of the pneumatic scraper. (5) Monitoring device (auxiliary): Detects the amount of gravel accumulation in the mesh and triggers cleaning commands.

[0132] Second, working principle: When the monitoring device detects that the accumulation of gravel inside the protective net has reached a preset threshold, the control system issues a start command. The pneumatic drive unit drives the pneumatic scraper to move along the guide rail, using the scraper surface to scrape the gravel along the net surface towards the predetermined collection or discharge position, thus partially clearing the gravel and reducing the load on the net surface. After cleaning is completed, the scraper returns to its initial position, and the system enters standby mode.

[0133] Third, working steps: (1) Monitoring and sensing: The monitoring device detects the amount of gravel accumulation in the protective net in real time.

[0134] (2) Warning Trigger: When the amount of gravel exceeds the set threshold, the control system is triggered to issue a cleaning command. (3) Command Execution: The control system starts the pneumatic drive device, and the pneumatic scraper begins to move slowly along the guide rail. (4) Gravel Scraping: As the scraper moves along the mesh surface, it scrapes the gravel on the mesh surface to the designated location. (5) Collection and Discharge: The gravel is scraped to the predetermined collection area for subsequent processing or natural dispersion. (6) Reset and Standby: After completing its stroke, the scraper returns to the initial position and waits for the next cleaning command.

[0135] 3. Intelligent Diagnosis and Control System: This includes edge computing nodes and a back-end diagnostic model. Edge computing nodes collect data from various sensors and perform preliminary processing. The back-end diagnostic model, located on a cloud platform, assesses the working status and damage level of the protective network based on sensor data and image processing results, and provides maintenance strategies.

[0136] (II) Working principle and process of intelligent multi-functional passive protection network system, such as Figure 4 As shown

[0137] 1. Data Acquisition Phase:

[0138] (1) Vibration and displacement detection: The vibration sensor monitors the vibration signal of the protective net in real time. When there is a rock impact or other external force, the vibration sensor outputs a corresponding electrical signal.

[0139] The displacement sensor continuously monitors the displacement changes of the net cable and converts the slack of the net cable into an electrical signal output.

[0140] (2) Detection of gravel accumulation: The ultrasonic sensor periodically emits ultrasonic waves. When the ultrasonic waves encounter the gravel accumulation, they are reflected back. The sensor calculates the height of the gravel accumulation based on the time difference between the emission and reception of the ultrasonic waves, thereby obtaining the gravel accumulation data.

[0141] (3) Image acquisition: The camera captures images of the inside of the protective net in real time to obtain information such as the location and shape of the pile of rubble inside the net.

[0142] 2. Data Transmission and Preliminary Processing Stage: Data collected by various sensors and images captured by cameras are transmitted to edge computing nodes via wired or wireless means. The edge computing nodes perform preliminary data processing, such as filtering and amplifying sensor data, and performing preprocessing operations like grayscale conversion and noise reduction on images, to improve data quality and facilitate subsequent analysis.

[0143] 3. Intelligent Diagnosis and Early Warning Phase: Preliminary processed data and images are uploaded to the cloud platform via a LoRa gateway. The cloud platform's backend diagnostic model uses image processing technology to analyze camera images and identify the specific situation of gravel accumulation. Combined with data from vibration, displacement, and accumulation sensors, it assesses the working status and damage level of the protective netting. When an anomaly is detected, such as severely loose netting, excessive gravel accumulation, or strong impact, the system immediately issues an early warning signal. The warning signal can be communicated to relevant personnel via audible and visual alarms, SMS, and app push notifications.

[0144] Detailed analysis of data processing, condition assessment, and maintenance strategies:

[0145] First, methods for processing data from different sources:

[0146] (1) Image data (from camera):

[0147] Preliminary processing (possibly at the edge or gateway): image compression, format conversion, timestamp marking; cloud processing (backend diagnostic model); image preprocessing: noise reduction, contrast enhancement, distortion correction; target detection and segmentation: identifying protective netting areas, support structures, and rubble deposits in the image. Accurately delineating the outline of rubble deposits; feature extraction: calculating the area and coverage ratio (percentage of the total netting area), estimating volume (combining possible depth information or historical data), and identifying the location distribution of deposits (whether they are concentrated in certain areas); change detection: comparing consecutive frames or periodically captured images to identify new large rocks, changes in netting morphology (such as damage, significant sagging), and abnormal support structures; damage identification: training the model to identify specific damage patterns, such as broken wire ropes, torn mesh, and abnormal anchor connections.

[0148] (2) Vibration data (from vibration sensor):

[0149] Preliminary processing: signal filtering (removing high-frequency noise and irrelevant frequencies), sampling; cloud processing; time-domain analysis: calculating the peak value (maximum amplitude), root mean square (RMS, reflecting energy magnitude), and kurtosis (reflecting impact) of the vibration signal. High amplitude and high peak value may indicate an impact event; frequency-domain analysis (e.g., FFT): analyzing the spectrum of the vibration signal to identify the dominant frequency and its changes. The natural frequency of the protective net structure can change due to tension, mass (accumulation), damage, etc. For example, a decrease in frequency may indicate loosening of the net cable or structural damage. Specific high-frequency components may indicate localized damage such as wire breakage; pattern recognition: comparing the current vibration pattern with the "baseline pattern" under normal conditions and known "impact event patterns," "relaxation patterns," etc.

[0150] (3) Displacement data (from displacement sensor):

[0151] Preliminary processing: data calibration and drift removal; cloud processing; absolute displacement calculation: measuring the displacement of key points (such as the center of the net, near anchor points) relative to the initial installation position or stable reference point. Large, sustained displacement usually indicates net slack or foundation deformation; relative displacement calculation: measuring the relative displacement between different points within the net and analyzing the deformation pattern of the net surface; rate of change analysis: calculating the velocity and acceleration of displacement. Rapid, large-amplitude displacement changes are usually associated with strong impact events; slow, sustained increases in displacement may indicate creep or progressive slack / damage.

[0152] (4) Accumulation data (from weighing sensors / load sensors, etc.):

[0153] Preliminary processing: Tare weight calculation, unit conversion (e.g., from voltage / current signals to weight / force values); Cloud processing; Total load calculation: Calculate the total weight borne by the protective netting or the total tensile force at the main anchoring points; Load distribution analysis: Review data from different sensors to understand whether the accumulated material is evenly distributed and whether there are local overloads; Threshold comparison: Compare the current total load or key point load with the design safety threshold; Load change rate: Analyze the rate at which the load increases. A sudden, large increase usually indicates an impact event or a large rockfall, while a slow, continuous increase represents the gradual accumulation of loose rocks.

[0154] Second, the method for assessing the working status of protective netting:

[0155] The cloud-based backend diagnostic model comprehensively processes the above multi-source data to perform a status assessment:

[0156] (1) Normal working condition, evaluation criteria: All sensor data are within the preset normal range. The image shows a normal mesh morphology with no obvious accumulation or damage. Vibration is stable and the frequency is consistent. Displacement is minimal. The load is far below the threshold.

[0157] (2) Severe slack in the netting. Assessment criteria: Main indicator: Displacement sensors detect continuous sagging or deformation exceeding the threshold. Auxiliary indicator: Vibration analysis shows a significant decrease in the natural frequency of the protective netting. Images may visually show the sagging of the netting surface. Anchor point load sensor readings may be relatively low (if slack causes some loads to be ineffectively transferred).

[0158] (3) Excessive accumulation of gravel. Assessment criteria: Main indicator: The accumulation (load) sensor reading exceeds the preset safety threshold (e.g., 60% or 70% of the design bearing capacity). Auxiliary indicator: Image processing analysis shows that the gravel coverage area / estimated volume exceeds the set limit. Displacement sensors may detect significant deformation due to weight.

[0159] (4) Under severe impact, assessment criteria: Main indicators: Vibration sensors detect short-duration, high-amplitude impact signals with specific frequency characteristics. Displacement sensors record instantaneous large displacements. Load sensors show a sudden surge in load. Auxiliary indicators: Images (if captured) may show significant changes at the moment of impact or after impact (such as the addition of large rocks, damage to the mesh).

[0160] (5) Potential structural damage (such as broken wires, damaged connectors, etc.). Assessment criteria: Main indicators: Abnormal frequencies appear in the vibration spectrum or the natural frequencies undergo unexplained changes (not caused by relaxation or accumulation). Image analysis identifies visual features such as local damage and fracture. After impact, even after removing the falling rocks, the displacement sensor still shows residual deformation. Abnormal readings of the local load sensor. Auxiliary indicators: Comparison with historical data reveals a trend of deterioration in certain parameters.

[0161] Third, the corresponding maintenance strategy:

[0162] After the system issues an early warning, corresponding maintenance strategies should be adopted based on different assessment statuses:

[0163] (1) For severe slack in the mesh

[0164] Short-term: Immediately conduct on-site verification of the degree and extent of slack and assess safety risks. Set up temporary warning signs. Medium-term: Arrange for professional personnel to re-tension the cables. Inspect and tighten all connections. Long-term: Analyze the causes of slack (e.g., material fatigue, foundation settlement, improper design), and reinforce or optimize the design if necessary. Check that components such as energy dissipation rings are functioning properly.

[0165] (2) Regarding excessive accumulation of gravel

[0166] Short-term: Confirm the accumulation situation on-site and assess whether it affects road / facility safety. Medium-term: Organize cleanup operations to remove accumulated materials from the netting. During and after cleanup, carefully inspect the protective netting for damage caused by overloading (e.g., wire wear, mesh deformation, loose connectors). Long-term: Assess the source and frequency of the gravel, and consider whether additional source control measures (e.g., slope reinforcement) are needed, or whether the cleanup cycle needs to be adjusted.

[0167] (3) In response to the severe impact

[0168] Short-term: Immediately cordon off potentially affected areas and conduct an emergency safety assessment. Medium-term: Conduct a comprehensive and detailed inspection of the impact area, including all components such as mesh panels, wire ropes, support ropes, anchor bolts, foundations, and energy dissipation devices. Repair or replace components as needed based on the extent of damage. Damaged energy dissipation devices (such as pressure-reducing rings) must be replaced. Long-term: Analyze whether the impact energy exceeded design expectations and assess whether an increase in protection level or the addition of buffer structures is necessary.

[0169] (4) Targeting potential structural damage

[0170] Short-term: Locate suspected damage areas based on early warning information. Medium-term: Dispatch technical personnel for targeted and detailed inspection, which may require the use of non-destructive testing methods such as endoscopy and ultrasonic testing. After confirming the damage, perform precise repair or replace the damaged component. Long-term: Analyze the cause of the damage (fatigue, corrosion, manufacturing defects, etc.), adjust the maintenance plan, and strengthen the monitoring and inspection of similar components.

[0171] General Strategy: Recording and Analysis: All early warnings, inspections, and maintenance activities should be meticulously recorded for subsequent analysis, model optimization, and maintenance plan improvement. Regular Inspections: Intelligent monitoring cannot completely replace regular manual on-site inspections; combining both provides a more comprehensive understanding of the protection network's status. Spare Parts Preparation: Based on historical data and potential risks, prepare spare parts for commonly used vulnerable and critical components. Personnel Training: Ensure maintenance personnel understand the meaning of the intelligent system's early warning information and possess the corresponding inspection and maintenance skills.

[0172] By implementing a closed-loop management system that involves data processing, status assessment, precise early warning, and targeted maintenance, the safety and maintenance efficiency of passive protection networks can be significantly improved.

[0173] 4. Automatic Cleaning and Maintenance Strategy Generation Phase: When the ultrasonic sensor detects that the amount of debris accumulated inside the net has reached a set threshold, the cloud platform sends a command to the control system of the pneumatic scraper to activate the pneumatic scraper and remove the debris outside the passive protective net. Simultaneously, the background diagnostic model generates a detailed maintenance strategy based on the overall assessment results of the protective net, such as indicating the locations of net cables that need to be replaced and areas that need reinforcement. This maintenance strategy is then fed back to management personnel to guide maintenance work.

[0174] III. Full Lifecycle Management

[0175] Existing technologies generally focus only on monitoring the operational phase of slope protection nets, lacking comprehensive consideration and systematic management of the construction and maintenance phases. This one-sided management model results in a lack of continuity and coordination between different stages throughout the entire lifecycle of the slope protection net system, making it impossible to achieve efficient and intelligent management from construction to operation and maintenance. However, the present invention can simultaneously address slope disaster prevention management during the construction, operation, and maintenance phases.

[0176] (I) Construction Phase - Intelligent Prestressing Loading

[0177] 1. System Equipment: During construction, intelligent tensioning equipment is used to apply prestress to the protective netting. The intelligent tensioning equipment is equipped with pressure sensors to monitor the applied prestress in real time. Simultaneously, a local control terminal is set up at the construction site, which is connected to the intelligent tensioning equipment and pressure sensors via wired or wireless means. The tensioning equipment is generally placed near the netting edge or anchor points where it is easy to operate during construction; if the construction area is large, multiple intelligent tensioning devices are deployed in shifts or groups, managed centrally by the local control terminal. The intelligent tensioning equipment is connected to the main load-bearing steel cable or anchor cable of the protective netting (such as the main wire rope, anchor rod end, or reserved tensioning section) via clamping devices, with the specific tensioning position determined according to the netting structure. The prestress value is measured by an integrated pressure sensor, measuring the hydraulic oil pressure or the torque of the loading motor, and converted into a tension value. Some systems also use tension sensors directly installed at the steel cable clamping points for measurement.

[0178] First, the specific structure and location of the intelligent tensioning equipment.

[0179] (1) Main body of intelligent tensioning equipment

[0180] Hydraulic jacks or electric tensioners: As the core component for applying force, hydraulic jacks extend the piston rod through hydraulic pressure to tighten the wire rope or cable; electric tensioners control the tension force through a motor and reduction gear, suitable for precise control. Tension sensors (pressure sensors): Typically installed in the hydraulic system's oil circuit or directly integrated into the jack's piston rod, they collect tension force data in real time and can also provide feedback to the loading system. Clamping devices (clamps): Used to clamp the protective netting cables, wire ropes, or anchor cables to be tensioned; commonly used are clamps, pliers, or hydraulic clamps to ensure slippage is prevented during force application.

[0181] (2) Connection structure and setting location

[0182] Connection Components: The intelligent tensioning equipment is connected to the main load-bearing steel cable or anchor cable of the protective netting (such as the main wire rope, anchor rod end, or reserved tensioning section) via a clamping device. The specific tensioning position is determined according to the netting structure. Force Measuring Components: The prestressing force value is measured by an integrated pressure sensor, which measures the hydraulic oil pressure or the torque of the loading motor and converts it into a tension force value. Some systems also use tension sensors directly installed at the cable clamping points for measurement. Construction Site Layout: The tensioning equipment is generally placed near the netting edge or anchoring points where it is convenient for construction. If the construction area is large, multiple intelligent tensioning devices are deployed in shifts or groups, and centrally managed by a local control terminal.

[0183] (3) Method of applying prestress

[0184] The extension of the jack piston rod is controlled by an intelligent tensioning device to gradually apply tension to the clamped steel cable. Real-time monitoring and feedback from sensors allow the control system to adjust the hydraulic pressure or drive motor, achieving accurate loading of the preset target prestress.

[0185] (4) Prestress measurement and feedback

[0186] The magnitude of prestress is primarily determined by monitoring the hydraulic system pressure using pressure sensors, which, combined with the area of ​​the hydraulic cylinder, is converted into the actual tension value. Alternatively, the tension of the steel cable can be directly measured using tension sensors. Real-time data from the sensors is transmitted to a local control terminal for display and monitoring, achieving closed-loop control of the force application process to ensure that the prestress meets design requirements. The intelligent tensioning equipment structure includes hydraulic jacks / electric tensioners, clamping devices, and pressure sensors. Clamped to the main steel cable or anchorage of the protective netting, it applies load through hydraulic drive or motor-controlled piston extension and retraction. Pressure or tension sensors measure the tension in real time, and all data is centrally transmitted to the local control terminal, enabling intelligent, real-time, and precise prestress application and monitoring.

[0187] 2. Workflow: During the installation of the protective netting, pressure sensors collect real-time prestress values ​​applied by the intelligent tensioning equipment and transmit the data to the local control terminal. The local control terminal is pre-set with the required standard prestress value for the protective netting. By comparing the real-time collected prestress values ​​with the standard value, it automatically adjusts the operating parameters of the intelligent tensioning equipment, such as tensioning speed and tension force. For example, when the collected prestress value is less than the standard value, the control terminal instructs the intelligent tensioning equipment to increase the tension force until the standard value is reached. In this way, it ensures that the prestress of the protective netting is accurately applied during construction, meeting design requirements and providing a guarantee for subsequent stable operation.

[0188] (II) Operational Period - Dynamic Load Adjustment

[0189] 1. System Devices: Dynamic load adjustment is achieved by relying on sensors, edge computing nodes, cloud platforms, and hydraulic actuators in the intelligent active protection network system.

[0190] 2. Workflow: During operation, various sensors in the intelligent active protective net system monitor the stress state of the protective net and external disaster parameters in real time. This data is initially processed by edge computing nodes and then uploaded to the cloud platform. The cloud platform uses big data algorithms to perform real-time assessments of slope stability. When the monitored stress state or disaster parameters indicate a change in slope stability that may affect the protective net's effectiveness, the cloud platform sends control commands to the hydraulic actuators through the intelligent sensing and mechanical control module. The hydraulic actuators automatically adjust the prestress of the protective net according to the commands, achieving dynamic load adjustment. This ensures that the protective net maintains optimal protective performance under different geological conditions and disaster threats, effectively improving the safety and service life of the protective net.

[0191] (III) Maintenance Period - Predicted Cleaning of Accumulated Amount

[0192] 1. System Equipment: The system utilizes ultrasonic sensors, cameras, edge computing nodes, cloud platforms, and big data prediction models within the intelligent multi-functional passive protection network system to achieve predictive cleaning of accumulated debris.

[0193] 2. Workflow: During the maintenance period, ultrasonic sensors continuously monitor the amount of gravel accumulation within the netting, while cameras acquire real-time image information. This data is initially processed by edge computing nodes and then uploaded to the cloud platform. The big data prediction model on the cloud platform combines historical accumulation data, real-time monitoring data, and information on the slope's geological conditions and climate to predict the amount of gravel accumulation in the near future. When the predicted accumulation is about to reach the cleaning threshold, an early warning is immediately issued to management personnel, and automatic cleaning devices (such as pneumatic scrapers) are activated for cleaning, or maintenance personnel are arranged for manual cleaning. This predictive cleaning method ensures the continuous and reliable operation of the protective netting throughout its entire lifecycle.

[0194] The beneficial technical effects achieved by the embodiments of the present invention are as follows:

[0195] I. Intelligent Active Protection Network System

[0196] 1. Employing sensor integration technology, this system can acquire real-time and accurate information on the stress and deformation of local areas within the protective netting, providing precise data support for subsequent early warning and control. Compared to traditional protective netting systems that cannot monitor local conditions in real time, this significantly improves the accuracy and timeliness of monitoring, helping to identify potential safety hazards early and ensuring the safety of the protective netting.

[0197] 2. Cloud-based data and risk warning algorithms: Leveraging the powerful data storage and computing capabilities of the cloud, combined with big data algorithms, comprehensive assessments of slope stability and timely warnings under extreme conditions are achieved. This enables dynamic management of disaster risks, allowing managers to understand the slope's safety status in real time and take sufficient time to respond before extreme events occur, reducing casualties and property damage. Simultaneously, it reduces the workload and potential errors associated with manual data analysis.

[0198] 3. Based on real-time monitoring data and early warning information, the prestress of the protective netting is automatically adjusted to ensure that the netting always maintains optimal interception and buffering effects. This improves the netting's adaptability, effectively responds to different geological conditions and disaster threats, extends the netting's service life, and reduces the risk of disasters caused by netting failure.

[0199] This approach avoids the problems of existing technologies: 1. Lack of real-time monitoring and automatic control: Traditional active protective nets mainly rely on being tightly attached to the soil and rock surface on slopes and applying prestress or anchoring to prevent loose soil and rock from sliding or collapsing. However, this type of protective net lacks the ability to monitor the stress state of the net body in real time, and cannot obtain various disaster parameters in real time. When facing adverse loads caused by extreme conditions such as heavy rainfall and earthquakes, it cannot automatically adjust the prestress in time, nor can it issue early warnings quickly, making it difficult for the protective net to achieve the best interception and buffering effect, thus making it difficult to guarantee the safety of the protective net, and may shorten its service life due to abnormal stress. 2. High cost and lagging management of manual inspections: Since traditional active protective nets do not have real-time monitoring functions, a large amount of manpower is required for regular inspections to ensure their safety. This method is not only costly, but also difficult to detect potential dangers in time due to the time intervals between inspections, and cannot achieve dynamic management of disaster risks. Once an extreme event occurs, it is difficult to issue early warnings and take effective countermeasures in time.

[0200] II. Passive Protection Network System

[0201] 1. Multiple sensors are used to monitor the working status of the passive protective netting from different angles, comprehensively acquiring information such as gravel accumulation, net cable loosening, and impact. Cameras, vibration sensors, displacement sensors, and ultrasonic sensors are deployed at key locations within the passive protective netting to achieve comprehensive monitoring of the amount of gravel accumulation, net cable loosening, and impact conditions. Compared to traditional passive protective netting that relies solely on manual inspections to identify problems, this significantly improves the comprehensiveness and real-time nature of monitoring, enabling timely detection of anomalies and providing accurate data for subsequent maintenance and cleaning.

[0202] 2. Utilizing camera images and sensor data for intelligent analysis, the system accurately assesses the working status and damage level of the protective netting, and provides targeted maintenance strategies. This reduces the subjectivity and blind spots of manual judgment, improves the efficiency and accuracy of maintenance work, lowers maintenance costs, and extends the service life of the protective netting.

[0203] 3. When the amount of debris accumulated inside the net reaches a threshold, automatic cleaning is initiated to maintain the permeability and effective interception capability of the protective net. This improves the efficiency of the protective net in dealing with sudden mudslides or debris blockages, reduces the risk of secondary disasters, and can maintain its protective capability even in extreme or unattended environments, reducing the workload and risks of manual cleaning.

[0204] To avoid the problems in existing technologies: 1. The main function of traditional passive protective nets is to intercept falling rocks or debris flows. However, in actual use, the nets are often subjected to excessive stress due to impacts from falling rocks or accumulated debris, and they are also prone to blockage. Once these problems occur, a large amount of manpower is usually required for cleaning or replacement of the protective nets. This not only consumes a lot of manpower, but if cleaning or replacement is not done in time, it will cause the protective nets to fail, reduce their service life, and greatly increase the risk of secondary disasters. 2. Risk of protective failure in extreme or unattended environments: In extreme environmental conditions or in unattended areas, it is difficult to detect and deal with problems with traditional passive protective nets in a timely manner. This makes it difficult to maintain the protective capability of the nets continuously in these situations, and thus cannot effectively guarantee the safety of the area.

[0205] III. Full Lifecycle Management

[0206] 1. Intelligent prestressing loading during construction: This ensures accurate prestressing loading of the protective netting during the construction phase, meeting design requirements. It lays the foundation for the subsequent stable operation of the protective netting, avoids failure due to improper prestressing loading, and improves the construction quality and overall stability of the protective netting.

[0207] 2. Dynamic Load Adjustment During Operation: The prestress of the protective netting is dynamically adjusted based on real-time monitoring data to adapt to different operating conditions. This improves the safety and reliability of the protective netting during operation, effectively copes with various complex geological and climatic conditions, further extends the service life of the protective netting, and reduces operating costs. It avoids the failure of the protective netting due to excessive accumulation of gravel, realizes intelligent and refined management of maintenance work, reduces the waste of maintenance resources, and improves the maintenance efficiency and continuous protection capability of the protective netting.

[0208] III. Digital Platform Architecture

[0209] 1. Three-Tier Architecture Design: A three-tier architecture consisting of a physical protection layer, an edge computing layer, and a cloud platform enables efficient data acquisition, preliminary processing, and in-depth analysis. The rational division of data processing layers ensures an orderly flow of data from acquisition and preliminary processing to in-depth analysis, improving overall system efficiency. This reduces system complexity, facilitates maintenance and upgrades of each component, and simultaneously enhances data processing efficiency and reliability, ensuring the stable operation of the entire protection network system.

[0210] 2. Multi-source data fusion and interaction: The digital platform integrates multi-source data from the intelligent active protection network system and the intelligent multi-functional passive protection network system for centralized management and analysis. It also interacts with equipment and systems at each stage to achieve full lifecycle management. By integrating multi-source data from the intelligent active protection network system and the intelligent multi-functional passive protection network system, it enables collaborative operation and full lifecycle management of equipment and systems at each stage. This provides managers with a unified management platform, facilitating real-time monitoring of the overall operational status of the protection network system, enabling scientific decision-making, and improving the intelligence level and management efficiency of geological disaster prevention and control work.

[0211] It should be understood that the specific order or hierarchy of steps in the disclosed process is an example of an exemplary method. Based on design preferences, it should be understood that the specific order or hierarchy of steps in the process may be rearranged without departing from the scope of this disclosure. The appended method claims provide elements of various steps in an exemplary order and are not intended to limit the scope to the specific order or hierarchy described.

[0212] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A full life-cycle slope protection net system, characterized in that, The full life cycle slope protection net system includes an active protection net system (1), which includes a first net body (11), a first net cable (12), and a first anchor rod (13). The first anchor rod (13) is fixed at intervals on the slope. Multiple first anchor rods (13) form a transverse column and a longitudinal column that intersects with the transverse column. The first net cable (12) is tensioned and connected between adjacent first anchor rods (13), and the first net cable (12) is attached to the rock and soil of the slope surface. The first net body (11) has multiple parts, each first net body (11) is covered on the rock and soil of the slope, and the edge of each first net body (11) is connected to the adjacent first net cable (12) by a soft rope (17) and the first net body (11) is in a tensioned state. The contact section between the soft rope (17) and the first net cable (12) is fixed by an anchor buckle. The active protection network system (1) also includes multiple fiber Bragg grating sensors (14), which are disposed on the first net body (11) and are used to obtain the strain information of the first anchor rod (13) and / or the strain information of the anchor buckle according to the deformation of the first net body (11), and convert the strain information into a first electrical signal or a first optical signal; the fiber Bragg grating sensor (14) is electrically connected to an edge computing node located near the active protection network system (1); The edge computing node is electrically connected to the cloud platform via a wireless sensor (3); The full life cycle slope protection net system also includes a passive protection net system (2). The passive protection net system (2) is vertically installed at the bottom of the active protection net system (1). The passive protection net system (2) includes: a second net body (21), vertical rods (22), second anchor rods (23), and second net cables (24). The vertical rods (22) are fixed at intervals on the ground. The second net body (21) is tensioned and connected to two adjacent vertical rods (22). The second anchor rods (23) are fixed to the bottom surface near the vertical rods (22). Each vertical rod (22) is fixedly connected to the corresponding second anchor rod (23) by at least two second net cables (24). The passive protection net system (2) also includes a vibration sensor (28) installed at the connection between the second net body (21) and the vertical pole. The vibration sensor (28) is used to detect the vibration of the second net body (21) when it is impacted and convert the vibration into a third electrical signal. The vibration sensor (28) is electrically connected to the edge computing node. The passive protection net system (2) also includes a displacement sensor (25) installed on each of the second net bodies (21). The displacement sensor (25) is used to monitor the displacement change of the second net body (21) to obtain the slack of the second net cable (24) and convert the slack into a fourth electrical signal. The displacement sensor (25) is electrically connected to the edge computing node. The passive protection net system (2) also includes an ultrasonic sensor (26) installed at the bottom of the passive protection net system (2). The ultrasonic sensor (26) is used to measure the height of the gravel accumulation in the passive protection net system (2) by emitting and receiving ultrasonic waves, calculate the amount of gravel accumulation, and convert the amount of gravel accumulation into a fifth electrical signal. The ultrasonic sensor (26) is electrically connected to the edge computing node. The passive protection net system (2) also includes a camera (27) installed at the top of the vertical pole (22). The camera (27) is used to capture images of the rubble accumulation in the passive protection net system (2) in real time and convert the rubble accumulation images into a sixth electrical signal. The camera (27) is electrically connected to the edge computing node.

2. The full life cycle slope protection net system according to claim 1, characterized in that, The active protection network system (1) further includes a micro strain sensor (15), which is installed on each of the first anchor rods (13) to obtain the strain information of the first anchor rod (13). The micro strain sensor (15) is also installed on the anchor buckle to obtain the strain information of the anchor buckle and convert the strain information into a second electrical signal or a second optical signal. The micro strain sensor (15) is electrically connected to the edge computing node. The micro strain sensor (15) and the fiber optic grating sensor (14) are complementary.

3. The full life-cycle slope protection netting system according to claim 1, characterized in that, The active protection network system (1) also includes a rain sensor installed on the edge computing node for real-time monitoring of rainfall, and a seismic sensor installed on the edge computing node for sensing seismic wave parameters, wherein the rain sensor and the seismic sensor are electrically connected to the edge computing node.

4. The full life-cycle slope protection netting system according to claim 1, characterized in that, The active protection net system (1) also includes hydraulic actuators installed at intervals at the first anchor rod (13) and the first net body (11). The hydraulic actuators include hydraulic cylinders, one end of which is connected to the head of the first anchor rod (13) and the other end of which is connected to the first net body (11). The active protection net system (1) also includes an intelligent sensing and mechanical control module (16), which is used to send control commands to a designated hydraulic actuator according to the maintenance strategy, and the designated hydraulic actuator is used to adjust the prestress of the first anchor rod (13) according to the control command.

5. The full life-cycle slope protection netting system according to claim 1, characterized in that, It also includes a background diagnostic model located in the cloud platform. The background diagnostic model is used to receive signal data about the active protection network system (1) sent by the edge computing node, evaluate the working status and damage level of the active protection network system (1) based on the signal data, and give corresponding maintenance strategies.

6. The full life-cycle slope protection netting system according to claim 1, characterized in that, The passive protection net system (2) also includes a pneumatic scraper device disposed within the passive protection net system (2). The pneumatic scraper device includes a pneumatic scraper, a guide rail, and a pneumatic drive device. The pneumatic scraper matches the curved surface on the second net body (21). The pneumatic scraper is movably disposed on the guide rail. The guide rail is installed on the edge or surface of the second net body (21). The pneumatic drive device is used to drive the pneumatic scraper to move on the guide rail. The pneumatic scraper device is used to scrape the gravel to a designated position by moving along the inner mesh surface of the passive protection net system (2) according to the instructions of the control system when the amount of gravel accumulation in the passive protection net system (2) reaches a certain level.

7. The full life-cycle slope protection netting system according to claim 1, characterized in that, It also includes a background diagnostic model located in the cloud platform. The background diagnostic model is used to receive signal data about the passive protection network system (2) sent by the edge computing node, evaluate the working status and damage level of the passive protection network system (2) based on the signal data, and give corresponding maintenance strategies.

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