Debris flow monitoring and early warning method and device

Abstract

The invention provides a debris flow monitoring and early warning method and device, and belongs to the field of geological disaster monitoring. The method comprises the following steps: dividing a debris flow channel after investigation, obtaining geological basic information, and deploying a double-fishbone-shaped optical fiber monitoring network along two sides of the channel; environment parameters are collected, and a temperature difference threshold value and a wave amplitude difference threshold value are preset; judging whether debris flow is started at the i moment according to the air temperature at the i moment, the temperature of the temperature sensor and a temperature difference threshold; if so, extracting the temperature of the temperature sensor at each horizontal position, searching an active sensor to determine a muddy water level height value and a rising rate value, judging the position of a caving object, and counting; calculating the change of the sound wave amplitude of the sonic sensor from the (i-1) th moment to the ith moment, comparing the change with a threshold value, and judging whether foreign matters intervene or not; if yes, sound wave characteristics of the first sound wave sensors on the left side and the right side are collected at the same time, debris flow is judged during matching, and then the flow velocity is calculated and early warning is performed. According to the invention, the accuracy, stability and precision of debris flow early warning are improved.

Description

Technical Field

[0001] The present invention belongs to the field of geological disaster monitoring, and particularly relates to a debris flow monitoring and early warning method and device. Background Art

[0002] Debris flow is a natural disaster that usually occurs in mountainous areas, with characteristics such as suddenness, fast flow velocity, large flow rate, large material capacity, and strong destructive power; usually, real-time monitoring and early warning methods are adopted to effectively prevent and respond to debris flows.

[0003] In the prior art, there are the following deficiencies in the monitoring and early warning of debris flows: First, there are obvious shortcomings in terms of energy consumption. For currently common devices such as imaging lidar and video surveillance used for debris flow monitoring, most of them need to be deployed in the wild gullies and other areas for a long time to carry out work. These places often have poor lighting conditions. Even with the battery equipped and supplemented by a solar panel for power supply, it is still difficult to meet the power required for the normal operation of the device. The continuous working ability of the device is limited, and it often experiences operation interruptions due to insufficient power. This not only affects the coherence of the monitoring work but also greatly increases the operation and maintenance costs and the operation and maintenance difficulty, bringing many inconveniences to the long-term and stable monitoring work.

[0004] Second, the signal transmission is unstable. The unique complex terrain in mountainous areas, such as the interlacing of high mountains and deep valleys and the undulating terrain, combined with the changeable climate conditions, such as rainstorms, strong winds, and thick fog, occur frequently. These factors are intertwined, seriously interfering with the data transmission link of the monitoring device. In the process of data transmission, phenomena such as signal interruption and packet loss are common, resulting in the crucial monitoring data not being transmitted to the monitoring center on time and accurately. As a result, it is difficult for the monitoring personnel to make reliable early warning judgments based on these data in a timely manner, greatly weakening the effectiveness of the early warning work.

[0005] Third, the data transmission capacity is insufficient. In the wild environment, the relevant devices for device communication generally have a small data throughput and are difficult to meet the multi-dimensional and large-data-volume data collection and transmission requirements generated during the formation process of debris flows. For example, during the monitoring process, key data such as sound waves and video streams often emerge in large quantities in a short period of time, but the existing devices cannot send these massive data to the monitoring center for timely processing completely and efficiently. This will undoubtedly cause the loss of some valuable data or delay the analysis time, which is not conducive to grasping the overall situation of debris flows.

[0006] Fourth, the monitoring of mud level and flow velocity data is not accurate enough. This problem is particularly prominent. The accuracy of some monitoring devices is limited. In complex and harsh field environments, they are extremely vulnerable to various environmental factors such as water flow impact, sediment deposition, and electromagnetic interference, which will lead to a large deviation between the collected data and the actual situation. Moreover, in extreme environmental conditions, some devices will frequently malfunction and cannot normally obtain the true changes in mud level and flow velocity, making it difficult to accurately judge the possibility and scale of debris flow occurrence, and ultimately resulting in a significant reduction in the timeliness and accuracy of early warning.

[0007] For example, the radar mud level gauge used for debris flow monitoring measures the change in mud level height by relying on radar waves. Due to its application limitations, the collected data is easily interfered by the quality of the measured water surface or wind, and large abnormal data is likely to occur, with changes ranging from dozens of centimeters to dozens of meters, which is likely to cause trouble to early warning personnel. Another example is the video monitoring station, which has problems such as high power consumption, wide video stream bandwidth, and difficulty in transmission except for 4G network. Summary of the Invention

[0008] In view of the above defects or deficiencies in the prior art, the present invention aims to provide a debris flow monitoring and early warning method and device, which can efficiently, stably, and accurately monitor and early warn debris flow disasters and improve the ability to defend against debris flow disasters.

[0009] To achieve the above object, the embodiments of the present invention adopt the following technical solutions: In the first aspect, the embodiments of the present invention provide a debris flow monitoring and early warning method, and the method includes the following steps: Step S1, conduct an investigation on the area to be monitored, divide the debris flow gully and obtain geological basic information; Step S2, form a monitoring plan based on the geological basic information, and deploy a "double fishbone" - shaped optical fiber monitoring network along both sides of the debris flow gully according to the monitoring plan. The "double fishbone" - shaped optical fiber monitoring network includes a backbone transmission optical fiber and optical fiber temperature sensors, optical fiber acoustic sensors, and optical fiber strain sensors connected to the backbone transmission optical fiber; Step S3, collect the environmental parameters of the area to be monitored to form a background database; preset a temperature difference threshold ΔT0 and a wave amplitude difference threshold ΔP0; Step S4, according to the air temperature T a (i) in the background database at the i - th moment and the lowest horizontal temperature T1(i) of the temperature sensor in the "double fishbone" - shaped optical fiber monitoring network, calculate ΔT(i)= T1(i)- T a (i); when |ΔT(i)|≥ΔT0, it is determined that the debris flow starts at the i - th moment, and step S5 is executed; otherwise, step S11 is executed; Step S5: Extract the temperatures of the temperature sensors at each horizontal position, which are T1, …, T k , …, T H . When T k (i) - T k (i - 1) ≠ 0, the first to the k-th temperature sensors are active sensors; determine the mud water level height value and the rising speed rate value ΔH(i) at the current moment according to the spacing and quantity of the active sensors; Step S6: Determine whether there is debris at the position q where the strain sensor is arranged according to the strain sensor; if there is debris, count the debris, denoted as N q ; if not, N q = 0; Step S7: Calculate the mudslide flow velocity and the average flow velocity; Step S8: Conduct mudslide early warning according to the mud water level height value, the rising speed rate value, the debris position and count, the mudslide flow velocity and the average flow velocity; Step S9: The monitoring time i = i + 1, and return to Step S4.

[0010] As a preferred embodiment of the present invention, The said Step S7 includes: Step S71: Calculate the change ΔP(i) = P 11 (i) - P 11 (i - 1) of the acoustic wave amplitude of the first acoustic wave sensor on either side of the mudslide channel from the (i - 1)-th moment to the i-th moment; if ΔP(i) ≥ ΔP0, it is determined that there is a foreign object intervening in the mudslide channel, and execute Step S72; if ΔP(i) < ΔP0, it is determined that there is no foreign object intervening in the mudslide channel, and execute Step S9; Step S72: Simultaneously collect the acoustic wave features F 11 and F 21 of the first acoustic wave sensor on the left side and the first acoustic wave sensor on the right side of the mudslide channel; if F 11 and F 21 match, it is determined that a mudslide has occurred, and execute Step S73; if F 11 and F 21 do not match, it is determined that no mudslide has occurred, and execute Step S9; Step S73: Collect the monitoring signal time difference t between the first acoustic wave sensor and the second acoustic wave sensor on either side of the mudslide channel, calculate the flow velocity s = L1 / t of the mudslide as the flow velocity of the mudslide monitored by the first acoustic wave sensor, where L1 is the distance between the installation position of the first acoustic wave sensor and the installation position of the second acoustic wave sensor, calculate the flow velocities of the mudslide monitored by all acoustic wave sensors in the same way, and calculate the average flow velocity S of the mudslide; And, The debris flow channel includes a source area, a starting area, a flowing area, and a disaster area; When deploying the "double fishbone" - shaped optical fiber monitoring network, the backbone transmission optical fibers on each side of the debris flow channel are set in a fishbone shape; On the backbone transmission optical fibers on each side, the optical fiber temperature sensors are deployed in the debris flow starting area, in physical contact with the mud - water, and are vertically arranged in the mud - water; the optical fiber acoustic sensors are deployed in the debris flow flowing area and are set at a predetermined distance from the debris flow channel; the optical fiber strain sensors are deployed in the debris flow source area, horizontally placed and parallel to the slope.

[0011] As a preferred embodiment of the present invention, there are at least two optical fiber acoustic sensors deployed in the flowing area, and they are arranged at an angle of 45° with the debris flow channel.

[0012] As a preferred embodiment of the present invention, the optical fiber temperature sensor includes an outer cylinder 111, an inner cylinder 112, an optical fiber inclination sensor 113, a first optical cable 114, and a second optical cable 115; where The outer cylinder 111 and the inner cylinder 112 are concentrically sleeved by two tubes with different diameters; heat - insulating coatings are respectively provided on the inner side of the outer cylinder 111 and the outer side of the inner cylinder 112; the optical fiber inclination sensor is arranged on the upper side of the inner cylinder; the first optical cable 114 is wound around the lower end of the outer side of the inner cylinder 112, and the second optical cable 115 is wound around the upper end of the outer side of the inner cylinder 112; An outer - cylinder window 116 is provided on the outer cylinder 111; the outer - cylinder window 116 is provided on the front and rear sides of the outer cylinder 111. Each side includes a first section corresponding to the first optical cable 114 at the lower end of the outer cylinder 111 and a second section corresponding to the second optical cable 115 at the upper end, both of which are set as rounded - bar - shaped windows, and the size is at least large enough to expose the first optical cable 114 and the second optical cable 115 wound around the inner cylinder 112; The first optical cable 114 and the second optical cable 115 are temperature optical cables, engraved with a number of fiber Bragg gratings FBG; the first optical cable 114 is tightly wound around the lower end of the outer side of the inner cylinder 112 according to a first preset parameter, and the winding height is from the bottom of the cylinder upwards to a predetermined position; the second optical cable 115 is loosely wound around the upper end of the outer side of the inner cylinder 112 according to a second preset parameter, and the winding height is from the predetermined position to the top of the cylinder; When the first optical cable 114 is tightly wound, the center distance between the cables in the axial direction is adjusted according to the monitoring accuracy requirements; when the second optical cable 115 is loosely wound, the distance between the cables in the axial direction is greater than the center distance of the first optical cable, and the total number of turns is not less than 3; the distance between the FBGs engraved in the first optical cable 114 and the second optical cable 115 is determined according to the outer diameter of the inner cylinder, ensuring that each turn of the winding contains one FGB.

[0013] As a preferred embodiment of the present invention, in step S5, to determine the mud - water level height value H, the following formula is used for calculation: H=(k - 1)*d (1) In Equation (1), H represents the rising height of the mud water level, k represents the number of active sensors, and d represents the spacing between active sensors.

[0014] As a preferred embodiment of the present invention, when determining whether there is a landslide at the position q where the strain sensor is arranged according to the strain sensor in step S6, the temperature drift coefficient of the fifth optical cable is calibrated by using the temperature value T6(i) at the current i-th moment collected by the sixth optical cable, and the strain signal after temperature calibration of the fifth optical cable at the current i-th moment is obtained.

[0015] As a preferred embodiment of the present invention, the acoustic wave characteristics in step S72 include the amplitude size of the main frequency band and the time-frequency power spectrum.

[0016] As a preferred embodiment of the present invention, in step S73, when calculating the debris flow velocity by using the acoustic wave sensor in the flow-through area, the temperature drift coefficient of the third optical cable is calibrated by using the temperature value T4(i) at the current i-th moment collected by the fourth optical cable, and the acoustic wave signal after temperature calibration of the third optical cable at the current i-th moment is obtained, and the average debris flow migration velocity value S(i) is calculated through waveform feature matching.

[0017] As a preferred embodiment of the present invention, when carrying out debris flow early warning in step S8, the warning situations are divided into four levels; the following steps are included: Step S81, judge the change situation of the difference ΔH(i) between the mud water level height value H(i) at the current i-th moment and the mud water level height value H(i - 1) at the (i - 1)-th moment. If 0 < ΔH(i) ≤ H v , and H(i) ≤ H e , it is judged that the mud water level is rising, but it belongs to the normal water level periodic change and no early warning is made; where H v is the mud water level rising rate threshold, and H e is the mud water level height threshold; Step S82, if 0 < ΔH(i) ≤ H v and H e < H(i), it is judged that the mud water level is rising, exceeding the historical normal water level and rising rate, and it is easy to cause flood disasters, and a first-level early warning is issued; Step S83, if H v < ΔH(i), and H e < H(i), it is judged that the mud water level is rising fiercely and it is easy to cause debris flow in the short term, and a second-level early warning is issued; if H v < ΔH(i) and H e < H(i) and the landslide count N in the source area q ≥ Q, where Q is the landslide quantity threshold, it is judged that the debris flow source is rich and the conditions for debris flow outbreak are met, and a third-level early warning is issued; Step S84, if H v < ΔH(i) and He <H(i) and it is recognized that the acoustic wave in the debris flow channel is enhanced, it is judged that the debris flow is erupting, a level-IV warning is issued, the arrival time of the debris flow is calculated according to the average flow velocity S of the debris flow and the total length L of the debris flow channel, and warning information is sent to the masses through multimedia, and the evacuation time is given.

[0018] Second, the embodiment of the present invention also provides a debris flow monitoring and warning device, which includes: a geological information acquisition module, an optical fiber temperature sensor, an optical fiber acoustic wave sensor, an optical fiber strain sensor, a "double fishbone" shaped optical fiber monitoring network construction module, a background data determination module, a temperature start determination module, a mud water level calculation module, a landslide debris determination and counting module, an acoustic wave foreign object determination module, an acoustic wave start determination module, a flow velocity calculation module and a warning module; wherein, The geological information acquisition module is used to conduct an investigation on the area to be monitored, divide the debris flow channel and obtain the geological basic information; The optical fiber temperature sensor is used to be arranged in the starting area of the debris flow channel to monitor the temperature; The optical fiber acoustic wave sensor is used to be arranged in the flowing area of the debris flow channel to monitor the acoustic wave amplitude and frequency; The optical fiber strain sensor is used to be arranged in the source area of the debris flow channel to locate the landslide debris; The "double fishbone" shaped optical fiber monitoring network construction module is used to form a monitoring plan based on the geological basic information and deploy a "double fishbone" shaped optical fiber monitoring network along both sides of the debris flow channel according to the monitoring plan; The background data determination module is used to collect the environmental parameters of the area to be monitored to form a background database; it is also used to preset a temperature difference threshold ΔT0 and a wave amplitude difference threshold ΔP0; The temperature start determination module is used to calculate ΔT(i)= T1(i)- T a (i) according to the air temperature T a (i) in the background database at the i-th moment and the lowest horizontal temperature T1(i) of the temperature sensor in the "double fishbone" shaped optical fiber monitoring network; when |ΔT(i)|≥ΔT0, it is determined that the debris flow starts at the i-th moment, and the mud water level calculation module is started; otherwise, the monitoring of the next moment is executed; The mud water level calculation module is used to extract the temperatures of the temperature sensors at each horizontal position, which are T1,..., T k ,..., T H , when T k (i)-T k (i-1)≠0, the first to the k-th temperature sensors are active sensors; according to the spacing and quantity of the active sensors, the mud water level height value and the current moment's rising speed value ΔH(i) are determined; The rockfall determination and counting module is used to determine whether there is rockfall at the position q where the strain sensor is arranged according to the strain sensor; if there is rockfall, the rockfall is counted and recorded as N q ; if not, then N q = 0; The acoustic wave foreign object determination module is used to calculate the change ΔP(i) = P 11 (i) - P 11 (i - 1) of the acoustic wave amplitude of the first acoustic wave sensor on either side of the debris flow channel from the (i - 1)-th moment to the i-th moment; if ΔP(i) ≥ ΔP0, it is determined that there is a foreign object intervening in the debris flow channel, and the acoustic wave start determination module is activated; if ΔP(i) < ΔP0, it is determined that there is no foreign object intervening in the debris flow channel, and the monitoring of the next moment is executed; The acoustic wave start determination module is used to simultaneously collect the acoustic wave characteristics F 11 and F 21 of the first acoustic wave sensor on the left side and the first acoustic wave sensor on the right side of the debris flow channel; if F 11 and F 21 match, it is determined that a debris flow has occurred, and the flow velocity calculation module is activated; if F 11 and F 21 do not match, it is determined that no debris flow has occurred, and the monitoring of the next moment is executed; The flow velocity calculation module is used to collect the time difference t of the monitoring signals from the first acoustic wave sensor to the second acoustic wave sensor on either side of the debris flow channel, calculate the flow velocity s = L1 / t of the debris flow as the flow velocity of the debris flow monitored by the first acoustic wave sensor, where L1 is the distance between the installation position of the first acoustic wave sensor and the installation position of the second acoustic wave sensor, and calculate the flow velocities of the debris flow monitored by all acoustic wave sensors in the same way, and calculate the average flow velocity S of the debris flow; The early warning module is used to issue an early warning of debris flow according to the mud water level height value, the rising speed value, the rockfall position and count, the debris flow velocity and the average flow velocity.

[0019] The technical solution provided by the embodiment of the present invention has the following beneficial effects: As can be seen from the above technical solutions, the debris flow monitoring and early warning method or device provided by the embodiments of the present invention can effectively monitor the dynamic changes of debris flow in each stage from initiation to outbreak in real time and give the early warning level and early warning time by setting up a distributed "double fishbone"-shaped optical fiber monitoring network. On the one hand, an optical fiber temperature sensor is used to collect the temperature change of the water level in the debris flow gully, and then two parameters, namely the water level rise and the rise rate, are calculated to determine whether the debris flow starts; since the temperature sensor is in direct contact with the flowing water, accurate data can be obtained without being affected by the environment or electromagnetic interference. On the second hand, an optical fiber strain sensor is used to monitor the avalanche materials in the source area, and the avalanche materials are counted according to the strain signal of the strain sensor, so as to locate the position and scale of the avalanche materials, and then judge the degree of danger of the debris flow outbreak. On the third hand, optical fiber acoustic wave sensors are deployed at corresponding positions on both sides of the flow area of the debris flow gully. By performing feature matching on the data collected by the acoustic wave sensors at the corresponding positions on both sides, it is further determined whether the debris flow breaks out. If it breaks out, the average migration speed of the debris flow and the time to reach the disaster area are calculated, and an early warning is sent to the disaster area in advance, providing sufficient response time for the disaster area. On the fourth hand, using non-electrical optical fibers as the sensors and transmission network for debris flow monitoring and early warning can overcome the problems of high power consumption, unstable transmission, small data throughput, and poor monitoring accuracy of existing monitoring devices.

[0020] Of course, it is not necessary for any product or method implementing the present invention to simultaneously achieve all the above-mentioned advantages. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0022] Figure 1 is the flowchart of the debris flow monitoring and early warning method described in the embodiments of the present invention; Figure 2 is the schematic diagram of the sensor distribution in the debris flow monitoring and early warning system according to the embodiments of the present invention; Figure 3 is Figure 2 the schematic diagram of the structure of the optical fiber temperature sensor in Figure 4 is Figure 2 the schematic diagram of the structure of the optical fiber acoustic wave sensor in Figure 5 is Figure 2 the schematic diagram of the structure of the optical fiber strain sensor in

[0023] Description of the reference numerals: 1 - "Double fishbone" - shaped optical fiber monitoring network; 11 - optical fiber temperature sensor; 111 - outer cylinder; 112 - inner cylinder; 113 - optical fiber inclination sensor; 114 - first optical cable; 115 - second optical cable; 116 - outer cylinder window opening; 12 - optical fiber acoustic wave sensor; 121 - acoustic wave cylinder; 122 - acoustic wave sealing glue; 123 - third optical cable; 124 - fourth optical cable; 13 - optical fiber strain sensor; 131 - strain cylinder; 132 - strain sealing glue; 133 - fifth optical cable; 134 - sixth optical cable; 14 - backbone transmission optical fiber; 2 - debris flow channel; 3 - debris flow acoustic wave. Detailed implementation manners

[0024] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. The components of the embodiments of the present invention usually described and illustrated in the accompanying drawings here can be arranged and designed in various different configurations. It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments can also be combined with each other.

[0025] It should be noted that: similar reference numerals and letters denote similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. In the description of the present invention, the terms "first", "second", "third", "fourth", etc. are only used for distinguishing descriptions and cannot be understood as indicating or implying relative importance.

[0026] Based on the monitoring and early warning requirements for debris flow disasters, the embodiments of the present invention provide a debris flow monitoring and early warning method and device. Sensors are distributed based on optical fibers, and distributed measurement of parameters related to disaster early warning is realized along the entire length of the optical fiber. Then, the data collected by the optical fiber sensors are processed and analyzed to improve the stability, accuracy, and precision of debris flow early warning and improve the early warning efficiency.

[0027] As Figure 1 shown, the debris flow monitoring and early warning method provided by the embodiments of the present invention includes the following steps: Step S1, conduct an investigation on the area to be monitored, divide the debris flow channels, and obtain geological basic information.

[0028] In this step, the area to be monitored is generally the target debris flow channel, which includes a source area, a starting area, a flowing area, and a disaster area. The obtained geological basic information includes the distribution, action range, and line length (the length along the debris flow channel direction) of the debris flow source area, starting area, flowing area, and disaster area in the area to be monitored. Among them, the source area is the area where accumulations are formed, including materials falling from landslides, collapses, and unstable slopes. Generally, when there is a source area, debris flow can be formed under the action of rainwater; without a source area, floods are formed. The starting area is downstream of the source area and is the place where debris flow has just formed, i.e., the starting position of the debris flow. The flowing area is the middle reaches of the debris flow channel, where a large-scale debris flow disaster has formed. The disaster area is the downstream of the debris flow channel, where there are residents, and when the debris flow passes through, it will cause losses to people and the economy and disasters.

[0029] Step S2: Based on the geological basic information, form a monitoring plan, and deploy a "double fishbone"-shaped optical fiber monitoring network 1 along both sides of the debris flow channel according to the monitoring plan. The "double fishbone"-shaped optical fiber monitoring network 1 includes a backbone transmission optical fiber 14 and optical fiber temperature sensors 11, optical fiber acoustic wave sensors 12, and optical fiber strain sensors 13 connected to the backbone transmission optical fiber.

[0030] In this step, the monitoring plan includes monitoring parameters, the number and positions of monitoring points. Among them, the selection of the monitoring parameters is determined according to the actual type of debris flow. For example, for rainfall-induced debris flow with rich sources, the monitoring parameters include the mud water level rise parameter, the debris flow velocity parameter, and the material migration parameter in the source area. Among them, the material migration parameter in the source area refers to the changes in the source area, including whether there are falling objects, the scale, position, and composition of the accumulations. For rainfall-induced debris flow with scarce sources, the monitoring parameters include the mud water level rise parameter, the debris flow velocity parameter, etc., and the monitoring of the material migration parameter is appropriately reduced. The number and positions of the monitoring points are determined according to the characteristics of the debris flow channel. On the one hand, the number of monitoring points needs to be selected according to the length of the debris flow channel. On the other hand, monitoring points should be set separately in the channel sections with different material compositions and in the channels where the hydrothermal drop exceeds the threshold.

[0031] Such as Figure 2As shown in the figure, when deploying the "double fishbone" - shaped optical fiber monitoring network 1, the backbone transmission optical fibers on each side of the debris - flow channel are set in a fishbone shape; the optical fiber temperature sensor 11 is deployed in the debris - flow initiation area and is in physical contact with the mud and water. The optical fiber temperature sensor is based on a fiber Bragg grating (FBG) optical fiber and is designed using the sensitivity of the temperature - grating optical fiber to temperature. Preferably, the optical fiber temperature sensor is vertically arranged in the mud and water. The optical fiber acoustic wave sensor 12 is deployed in the debris - flow passage area and is set at a predetermined distance from the debris - flow channel; in the passage area, at least two optical fiber acoustic wave sensors 12 are arranged and are laid out at an angle of 45° with the debris - flow channel, so as to enhance the receiving sensitivity of the acoustic wave sensor 12 in the axial direction. The optical fiber strain sensor 13 is deployed in the debris - flow source area and is designed based on a fiber Bragg grating (FBG) and using the sensitivity of the strain - grating optical fiber to strain. It is horizontally placed and parallel to the slope. When there is a collapse object falling, the optical fiber strain sensor can sense the strain condition of the monitoring device, judge the scale of the collapsed object, and combine with at least three other optical fiber acoustic wave sensors to locate the category of abnormal vibration, improve the monitoring anti - interference ability, and accurately monitor the position of the collapsed object.

[0032] In addition, in a preferred embodiment, optical fiber acoustic wave sensors can also be set in the source area. In the source area, at least three optical fiber acoustic wave sensors 12 are arranged. The centers of the three optical fiber acoustic wave sensors 12 form a triangle. Among them, two are horizontally placed and are laid out at an angle of 45° with the debris - flow channel, and the third one is horizontally set and parallel to the debris - flow channel. For the acoustic wave sensors in the source area, the time - difference - of - arrival positioning method is adopted and combined with the "double fishbone" monitoring network to form a triangular network for monitoring the collapsed object and realize the triangular positioning of the collapsed object. When realizing triangular positioning through three acoustic wave sensors, if the collapsed object is within the triangular network, the collapsed position can be directly calculated. However, at this time, the acoustic wave sensor signal may be formed by the collapsed object or may be formed by passing pedestrians or animals, and it cannot be uniquely determined that it is the collapsed object forming the debris - flow; if the collapsed object is outside the triangular network, first determine the direction of the collapsed object through the strain sensor, and then calculate the unique position through triangular positioning. The collapsed object that can be determined by both the strain sensor and the acoustic wave sensor can be uniquely confirmed as the collapsed object.

[0033] As Figure 3As shown, the structure of the fiber optic temperature sensor includes an outer cylinder 111, an inner cylinder 112, a fiber optic inclination sensor 113, a first optical cable 114, and a second optical cable 115, where an outer cylinder window 116 is provided on the outer cylinder 111. The outer cylinder 111 and the inner cylinder 112 are concentrically sleeved by two tubes with different diameters. Preferably, the outer cylinder 111 and the inner cylinder 112 are made of stainless steel, with a height set to 1.5 - 2.5 meters, generally 2 meters; the gap between the outer cylinder 111 and the inner cylinder 112 is set to 8 - 15 cm, generally 10 cm; heat insulation coatings are respectively provided on the outer sides of the outer cylinder 111 and the inner cylinder 112, and the heat insulation coatings can use aerogel materials. The first optical cable 114 is wound around the lower end of the outer side of the inner cylinder 112, and the second optical cable 115 is wound around the upper end of the outer side of the inner cylinder 112; the outer cylinder window 116 is provided on the front and back sides of the outer cylinder 111, and each side includes a first section corresponding to the first optical cable at the lower end of the outer cylinder 111 and a second section corresponding to the second optical cable at the upper end, both of which are set as rounded bar-shaped windows, with a size that at least exposes the first optical cable and the second optical cable wound on the inner cylinder. For example, when the cylinder height is 2 meters, generally the window size is at least 1500 cm from the lowest point to the highest point. The first optical cable is a temperature optical cable and is tightly wound around the lower end of the outer side of the inner cylinder 112 according to a first preset parameter, and the winding height is from the bottom of the cylinder upwards to a predetermined position (when the cylinder height is 2 meters, generally at 1500 mm). The second optical cable is a temperature optical cable and is loosely wound around the upper end of the outer side of the inner cylinder 112 according to a second preset parameter, and the winding height is from the predetermined position to the top of the cylinder. Both the first optical cable and the second optical cable are engraved with a number of Fiber Bragg Gratings (FBG). When the first optical cable is tightly wound, the distance between the cables in the axial direction is adjusted according to the monitoring accuracy requirements. For example, if the required monitoring accuracy is 5 mm, an optical cable with a wrapping layer less than 5 mm can be selected for winding, and the center distance between two turns of the cable is set to 5 mm; if the required monitoring accuracy is 20 mm, an optical cable with a wrapping layer less than 10 mm can be selected for winding, and the center distance between two turns of the cable is set to 20 mm. When the second optical cable is loosely wound, the distance between the cables in the axial direction can be enlarged without a specific regulation, but not less than 3 turns. The distance between the FBGs engraved in the first optical cable and the second optical cable is determined by the outer diameter of the inner cylinder, ensuring that each winding contains one FGB.

[0034] Such as Figure 4As shown in the figure, the fiber optic acoustic wave sensor 12 is designed based on a fiber Bragg grating (FBG) fiber, taking advantage of the sensitivity of the acoustic grating fiber to vibration. Its structure includes an acoustic cylinder 121, acoustic sealing glue 122, a third optical cable 123, and a fourth optical cable 124. The acoustic cylinder 121 is a single-layer stainless steel cylinder, preferably with a diameter of 60 mm and a length of 600 mm. The third optical cable 123 is an acoustic optical cable, and the optical cable with FBG inscribed is attached to the inner side of the cylinder. The fourth optical cable 124 is a temperature optical cable, and the optical cable with FBG inscribed is attached to the inner side of the cylinder. The acoustic sealing glue is anaerobic glue, which is used to bond the third optical cable 123 and the fourth optical cable 124 into the stainless steel cylinder and fill the inner cavity of the acoustic cylinder 121. For the acoustic wave sensors in the flow area, starting from the boundary between the flow area and the source area, the first acoustic wave sensor and the second acoustic wave sensor on the left side and the first acoustic wave sensor and the second acoustic wave sensor on the right side are successively arranged on both sides of the channel. If the flow area of the channel is relatively long, the third acoustic wave sensor, the fourth acoustic wave sensor, etc. can also be arranged on both sides respectively.

[0035] As Figure 5 shown in the figure, the fiber optic strain sensor 13 includes a strain cylinder 131, a fifth optical cable 133, a sixth optical cable 134, and strain sealing glue 132. Among them, the strain cylinder 131 is a single-layer stainless steel cylinder, preferably with a diameter of 60 mm and a length of 2000 mm. The fifth optical cable 133 is a strain optical cable, and the optical cable with FBG inscribed is attached to the inner side of the cylinder. The sixth optical cable is a temperature optical cable, and the optical cable with FBG inscribed is attached to the inner side of the cylinder. The strain sealing glue 132 is anaerobic glue, which is used to bond the fifth optical cable 133 and the sixth optical cable 134 into the stainless steel cylinder and fill the inner cavity of the strain cylinder 131.

[0036] Step S3: Collect the environmental parameters of the area to be monitored to form a background database; preset a temperature difference threshold ΔT0 and a wave amplitude difference threshold ΔP0.

[0037] In this step, the environmental parameters include the temperature at each monitoring point, the air temperature, the surface acoustic wave propagation speed in sections with different material compositions, and the background characteristics of the acoustic waves of the debris flow channel water. The two monitoring thresholds are determined according to the actual situation, on-site experiments, or experience.

[0038] Step S4: According to the air temperature T a (i) in the background database at the i-th moment and the lowest horizontal temperature T1(i) of the temperature sensors in the "double fishbone" shaped fiber optic monitoring network, calculate ΔT(i) = T1(i) - T a (i); when |ΔT(i)| ≥ ΔT0, it is determined that a debris flow starts at the i-th moment, and step S5 is executed; otherwise, step S11 is executed.

[0039] Step S5: Extract the temperatures of the temperature sensors at each horizontal position, which are T1, …, T k , …, T H . When T k (i) - T k (i - 1) ≠ 0, the first to the k-th temperature sensors are active sensors; based on the spacing and quantity of the active sensors, determine the mud water level height value and the rising speed rate value ΔH(i) at the current moment.

[0040] In this step, to determine the mud water level height value H, the following formula is used for calculation: H = (k - 1) * d (1) In formula (1), H represents the rising height of the mud water level, k represents the quantity of active sensors, and d represents the spacing of the active sensors.

[0041] Specifically, when monitoring the mud water level height value using the fiber optic temperature sensor as shown in Figure 3 , tightly wind the first optical cable on the outer side of the inner cylinder, photoetch a temperature sensing grating on the optical fiber of each loop of the optical cable, the fiber optic demodulator emits light waves to the grating through the laser, and receives the optical signals reflected back by each grating to calculate the temperature change. If the optical signal returned by the grating of a certain loop changes, after demodulation, it is obtained that the temperature of this grating is the same as that of the grating below it and different from the temperature of the grating of the second optical cable, then it can be determined that the mud water level has risen to the position of this grating. If the temperatures of multiple gratings have changed, it means the water level has risen high. The second optical cable is used as a reference to monitor the air temperature. Coating aerogel on the outer side of the inner cylinder and the inner side of the outer cylinder of the double cylindrical barrel can reduce the thermal conduction interference of the cylindrical steel barrel. Opening a window on the outer barrel of the double cylindrical barrel can, on the one hand, allow water flow to enter the outer barrel to fully contact the fiber gratings of the inner barrel, and on the other hand, the outer barrel can block the impact and damage of mud and stones on the fiber gratings of the inner barrel. A fiber optic inclinometer or a fiber optic tilt sensor is set at the top of the cylinder to judge the vertical state of the cylinder in real time to ensure the accuracy of monitoring the water level. If the cylinder is washed down by mud and water, abnormal data can also be excluded.

[0042] Step S6: According to the strain sensor, judge whether there is a caving object at the position q where the strain sensor is arranged; if there is a caving object, count the caving object, denoted as N q ; if not, then N q = 0.

[0043] In this step, when judging whether there is a caving object at the position q where the strain sensor is arranged according to the strain sensor, use the temperature value T6(i) at the current i-th moment collected by the sixth optical cable to calibrate the temperature drift coefficient of the fifth optical cable, and obtain the strain signal after temperature calibration of the fifth optical cable at the current i-th moment.

[0044] In this step, it is also possible to further confirm and determine whether there are avalanche materials based on three fiber optic acoustic wave sensors installed in the provenance area, and to count the avalanche materials, etc. At this time, according to the acoustic wave signals collected by the three acoustic wave sensors at three positions, the specific position of the avalanche material is calculated through the triangulation principle and a status value Y or N is given. The three acoustic wave sensors at the three positions are selected according to the monitoring network. Where Y indicates an avalanche has occurred, and N indicates no avalanche has occurred.

[0045] Step S7: Calculate the flow velocity and average flow velocity of the debris flow.

[0046] Specifically, this step includes: Step S71: Calculate the change ΔP(i) = P 11 (i) - P 11 (i - 1) of the acoustic wave amplitude of the first acoustic wave sensor on either side of the debris flow channel from the (i - 1)-th moment to the i-th moment; if ΔP(i) ≥ ΔP0, it is determined that there is a foreign object intervening in the debris flow channel, and step S72 is executed; if ΔP(i) < ΔP0, it is determined that there is no foreign object intervening in the debris flow channel, and step S9 is executed.

[0047] Step S72: Simultaneously collect the acoustic wave characteristics F 11 and F 21 of the first acoustic wave sensor on the left side and the first acoustic wave sensor on the right side of the debris flow channel; if F 11 and F 21 match, it is determined that a debris flow has occurred, and step S73 is executed; if F 11 and F 21 do not match, it is determined that no debris flow has occurred, and step S9 is executed.

[0048] In this step, the acoustic wave characteristics include the amplitude size of the main frequency band and the time-frequency power spectrum.

[0049] Step S73: Collect the monitoring signal time difference t between the first acoustic wave sensor and the second acoustic wave sensor on either side of the debris flow channel, and calculate the flow velocity s = L1 / t of the debris flow as the flow velocity of the debris flow monitored by the first acoustic wave sensor, where L1 is the distance between the installation position of the first acoustic wave sensor and the installation position of the second acoustic wave sensor. Calculate the flow velocities of the debris flow monitored by all acoustic wave sensors in the same way, and calculate the average flow velocity S of the debris flow.

[0050] In this step, when calculating the flow velocity of the debris flow using the acoustic wave sensors in the flow-through area, the temperature value T4(i) collected by the fourth optical cable at the current i-th moment is used to calibrate the temperature drift coefficient of the third optical cable, and the acoustic wave signal after temperature calibration of the third optical cable at the current i-th moment is obtained, and the flow velocity S(i) of the debris flow is calculated through waveform feature matching. When calculating the average flow velocity S of the debris flow, an integral method or an averaging method can be used for calculation.

[0051] Step S8, conduct debris flow early warning based on the mud water level height value, rising speed value, position and count of the avalanche, debris flow velocity, and average velocity.

[0052] In this step, preferably, the warning levels are divided into four levels. The specific early warning includes the following steps: Step S81, judge the change situation of the difference ΔH(i) between the mud water level height value H(i) at the current i-th moment and the mud water level height value H(i - 1) at the (i - 1)-th moment. If 0 < ΔH(i) ≤ H v , and H(i) ≤ H e , judge that the mud water level is rising, but it belongs to the normal water level periodic change, and no early warning is made; where H v is the mud water level rising speed threshold, and H e is the mud water level height threshold; Step S82, if 0 < ΔH(i) ≤ H v and H e < H(i), judge that the mud water level is rising, exceeding the historical normal water level and rising speed, and is likely to trigger a flood disaster, and issue a first-level early warning; Step S83, if H v < ΔH(i), and H e < H(i), judge that the rising trend of the mud water level is fierce, and a debris flow is likely to be triggered in the short term, and issue a second-level early warning; if H v < ΔH(i) and H e < H(i) and the count N q of the avalanche in the source area ≥ Q, where Q is the avalanche quantity threshold, judge that the debris flow source is rich and the conditions for debris flow outbreak are met, and issue a third-level early warning; Step S84, if H v < ΔH(i) and H e < H(i) and it is identified that there is enhanced sound wave in the debris flow gully, judge that the debris flow is erupting, issue a fourth-level early warning, calculate the debris flow arrival time according to the average velocity S of the debris flow and the total length L of the debris flow gully, and send early warning information to the masses through multimedia such as early warning broadcasts and text messages, and give the evacuation time.

[0053] Step S9, set the monitoring time i = i + 1, and return to step S4.

[0054] Based on the same idea, the embodiment of the present invention also provides a debris flow monitoring and early warning device, which includes: a geological information collection module, an optical fiber temperature sensor, an optical fiber acoustic wave sensor, an optical fiber strain sensor, a "double fishbone" shaped optical fiber monitoring network construction module, a background data determination module, a temperature start determination module, a mud water level calculation module, an avalanche determination and counting module, an acoustic wave foreign object determination module, an acoustic wave start determination module, a flow velocity calculation module, and an early warning module; Among them, the geological information acquisition module is used to conduct an investigation on the area to be monitored, divide the debris flow channels and obtain the geological basic information; The fiber optic temperature sensor is used to be arranged in the starting area of the debris flow channel to monitor the temperature; The fiber optic acoustic wave sensor is used to be arranged in the flowing area of the debris flow channel to monitor the acoustic wave amplitude and frequency; The fiber optic strain sensor is used to be arranged in the source area of the debris flow channel to locate the fallen debris; The "double fishbone" - shaped fiber optic monitoring network construction module is used to form a monitoring plan based on the geological basic information, and deploy the "double fishbone" - shaped fiber optic monitoring network along both sides of the debris flow channel according to the monitoring plan; The background data determination module is used to collect the environmental parameters of the area to be monitored to form a background database; it is also used to preset the temperature difference threshold ΔT0 and the wave amplitude difference threshold ΔP0; The temperature start determination module is used to calculate ΔT(i)= T1(i)- T a (i) according to the air temperature T a (i) in the background database at the i - th moment and the lowest horizontal position temperature T1(i) of the temperature sensors in the "double fishbone" - shaped fiber optic monitoring network; when |ΔT(i)|≥ΔT0, it is determined that the debris flow starts at the i - th moment, and the mud water level calculation module is started; otherwise, the monitoring of the next moment is executed; The mud water level calculation module is used to extract the temperatures of the temperature sensors at each horizontal position, which are T1,…,T k ,…,T H in ascending order; when T k (i)-T k (i - 1)≠0, the first to the k - th temperature sensors are active sensors; according to the spacing and quantity of the active sensors, the mud water level height value and the rising speed rate value ΔH(i) at the current moment are determined; The fallen debris determination and counting module is used to judge whether there is fallen debris at the position q where the strain sensor is arranged according to the strain sensor; if there is fallen debris, the fallen debris is counted and recorded as N q ; if not, then N q = 0; The acoustic wave foreign object determination module is used to calculate the change ΔP(i)= P 11 (i)- P 11 (i - 1) of the acoustic wave amplitude of the first acoustic wave sensor on either side of the debris flow channel from the (i - 1) - th moment to the i - th moment; if ΔP(i)≥ΔP0, it is determined that there is a foreign object intervening in the debris flow channel, and the acoustic wave start determination module is started; if ΔP(i)<ΔP0, it is determined that there is no foreign object intervening in the debris flow channel, and the monitoring of the next moment is executed; The acoustic wave startup determination module is used to collect the acoustic wave features F of the first acoustic wave sensors on the left and right sides of the debris flow channel simultaneously 11 and F 21 ; if F 11 and F 21 match, it is determined that a debris flow has occurred, and the flow velocity calculation module is started; if F 11 and F 21 do not match, it is determined that no debris flow has occurred, and the monitoring at the next moment is executed; The flow velocity calculation module is used to collect the time difference t of the monitoring signals from the first acoustic wave sensor to the second acoustic wave sensor on any side of the debris flow channel, calculate the flow velocity s = L1 / t of the debris flow, and use it as the flow velocity of the debris flow monitored by the first acoustic wave sensor. L1 is the distance between the installation position of the first acoustic wave sensor and the installation position of the second acoustic wave sensor. The flow velocities of the debris flow monitored by all acoustic wave sensors are calculated in the same way, and the average flow velocity S of the debris flow is calculated; The early warning module is used to issue early warnings for debris flows based on the mud water level height value, the rising speed value, the position and count of the fallen objects, the debris flow velocity and the average flow velocity.

[0055] In this embodiment, each module is implemented by a processor, and a memory is appropriately added when storage is required. Among them, the processor may be, but is not limited to, a microprocessor MPU, a central processing unit (CPU), a network processor (NP), a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), other programmable logic devices, discrete gate, transistor logic devices, discrete hardware components, etc. The memory may include a random access memory (RAM), and may also include a non-volatile memory (NVM), such as at least one disk memory. Optionally, the memory may also be at least one storage device located far from the aforementioned processor.

[0056] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present invention are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.).

[0057] In addition, it should be noted that the debris flow monitoring and early warning device described in this embodiment corresponds to the debris flow monitoring and early warning method. The description and limitation of the method also apply to the system and will not be repeated here.

[0058] As can be seen from the above technical solutions, the debris flow monitoring and early warning method or device provided by the embodiments of the present invention can effectively monitor the dynamic changes of debris flow in each stage from initiation to outbreak in real time by setting up a distributed "double fishbone"-shaped optical fiber monitoring network, and give the warning level and warning time. On the one hand, an optical fiber temperature sensor is used to collect the temperature change of the water level in the debris flow gully, and then two parameters, namely the water level rise and the rise rate, are calculated to determine whether the debris flow starts. Since the temperature sensor is in direct contact with the flowing water, accurate data can be obtained without being affected by the environment or electromagnetic interference. On the second hand, an optical fiber strain sensor is used to monitor the avalanche debris in the source area and count the avalanche debris to determine the position and scale of the avalanche debris, and then judge the danger level of the debris flow outbreak. On the third hand, optical fiber acoustic wave sensors are deployed at corresponding positions on both sides of the flowing area of the debris flow gully. By performing feature matching on the data collected by the acoustic wave sensors at the corresponding positions on both sides, it is determined whether the debris flow breaks out. If it breaks out, the average migration speed of the debris flow and the time to reach the disaster area are calculated, and an early warning is sent to the disaster area in advance to provide sufficient response time for the disaster area. On the fourth hand, using non-electrical optical fibers as the sensors and transmission network for debris flow monitoring and early warning can overcome the problems of high power consumption, unstable transmission, small data throughput, and poor monitoring accuracy of existing monitoring devices.

[0059] The above description is only a preferred embodiment of the present invention and an explanation of the applied technical principles, and is not intended to limit the scope of the claimed invention, but merely represents the preferred embodiments of the present invention. Those skilled in the art should understand that the scope of the invention involved in the present invention is not limited to the technical solutions formed by the specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the inventive concept. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts fall within the scope of protection of the present invention.

Claims

1. A debris flow monitoring and early warning method, characterized in that: The method comprises the following steps: Step S1, survey the area to be monitored, divide the debris flow channel and obtain basic geological information; Step S2, forming a monitoring plan based on the basic geological information, and deploying a "double fishbone" optical fiber monitoring network along both sides of the debris flow channel according to the monitoring plan, the "double fishbone" optical fiber monitoring network including a backbone transmission optical fiber and an optical fiber temperature sensor, an optical fiber acoustic wave sensor, and an optical fiber strain sensor connected to the backbone transmission optical fiber; Step S3, collecting environmental parameters of the area to be monitored to form a background database; A preset temperature difference threshold ΔT0 and a preset amplitude difference threshold ΔP0; Step S4: according to the air temperature T in the background database at the i-th moment a (i) and the lowest horizontal temperature T1(i) of the temperature sensor in the "double fishbone" optical fiber monitoring network, calculate ΔT(i) = T1(i) - T a (i); When |ΔT(i)|≥ΔT0, it is determined that the debris flow starts at time i, and step S5 is executed; Otherwise, execute step S11; Step S5, extract the temperature of the temperature sensor at each level, from low to high, in order of T1, ..., T k ,…,T H , when T k (i)-T k When (i-1)≠0, the 1st to kth temperature sensors are active sensors; according to the spacing and number of active sensors, the mud water level height value and the current rising rate value ΔH(i) are determined; Step S6, judging whether there is a collapse object at the position q where the strain sensor is arranged according to the strain sensor; if there is a collapse object, counting the collapse objects, recorded as N q ; If it does not exist, then N q =0; Step S7, calculating the debris flow velocity and average flow velocity; Step S8, providing debris flow warning according to the mud water level height value, the rising rate value, the location and count of landslides, the debris flow velocity and the average flow velocity; Step S9, monitor time i=i+1, and return to step S4.

2. The debris flow monitoring and early warning method according to claim 1 is characterized in that: The step S7 comprises: Step S71, calculate the change ΔP(i) of the acoustic wave amplitude of the first acoustic wave sensor on either side of the debris flow channel from the i-1th moment to the i-th moment = P 11 (i)- P 11 (i-1); if ΔP(i)≥ΔP0, it is determined that there is foreign matter in the debris flow channel, and step S72 is executed; if ΔP(i)<ΔP0, it is determined that there is no foreign matter in the debris flow channel, and step S9 is executed; Step S72, simultaneously collecting the acoustic wave characteristics F of the first acoustic wave sensor on the left side and the first acoustic wave sensor on the right side of the debris flow channel 11 and F 21 If F 11 and F 21 If the debris flow matches, it is determined that a debris flow has occurred, and step S73 is executed; if F 11 and F 21 If they do not match, it is determined that the debris flow has not occurred, and step S9 is executed; Step S73, collecting the monitoring signal time difference t from the first acoustic wave sensor to the second acoustic wave sensor on either side of the debris flow channel, calculating the debris flow velocity s=L1 / t as the debris flow velocity monitored by the first acoustic wave sensor, L1 is the distance between the installation position of the first acoustic wave sensor and the installation position of the second acoustic wave sensor, using the same method to calculate the debris flow velocity monitored by all acoustic wave sensors, and calculating the average debris flow velocity S; and, The debris flow channel includes the source area, the initiation area, the circulation area and the affected area; When deploying a "double fishbone" optical fiber monitoring network, the backbone transmission optical fiber on each side of the debris flow channel is set in a fishbone shape; On the backbone transmission optical fiber on each side, the optical fiber temperature sensor is deployed in the debris flow initiation area, in physical contact with the mud and water, and is set vertically in the mud and water; the optical fiber acoustic wave sensor is deployed in the debris flow flow area and is set at a predetermined distance from the debris flow channel; the optical fiber strain sensor is deployed in the debris flow source area, placed horizontally and parallel to the slope.

3. The debris flow monitoring and early warning method according to claim 2 is characterized in that: At least two fiber optic acoustic wave sensors are deployed in the flow area and arranged at an angle of 45° to the debris flow channel.

4. The debris flow monitoring and early warning method according to claim 2 is characterized in that: The optical fiber temperature sensor comprises an outer tube, an inner tube, an optical fiber tilt sensor, a first optical cable and a second optical cable; wherein, The outer tube and the inner tube are formed by concentrically fitting two tubes of different diameters; the inner side of the outer tube and the outer side of the inner tube are respectively provided with heat insulation coatings; the optical fiber tilt sensor is arranged on the upper side of the inner tube; the first optical cable is wound around the lower end of the outer side of the inner tube, and the second optical cable is wound around the upper end of the outer side of the inner tube; The outer cylinder is provided with an outer cylinder window; the outer cylinder window is arranged on both sides of the front and rear of the outer cylinder, each side includes a first section of the first optical cable corresponding to the lower end of the outer cylinder and a second section of the second optical cable corresponding to the upper end of the outer cylinder, both of which are arranged as rounded strip windows, and the size is at least large enough to expose the first optical cable and the second optical cable wound on the inner cylinder; The first optical cable and the second optical cable are temperature optical cables, engraved with a plurality of fiber Bragg gratings FBG; the first optical cable is tightly wound around the lower end of the outer side of the inner tube according to the first preset parameters, and the winding height is from the bottom of the tube to the predetermined position; the second optical cable is loosely wound around the upper end of the outer side of the inner tube according to the second preset parameters, and the winding height is from the predetermined position to the top of the tube; When the first optical cable is tightly wound, the center spacing between the cables in the axial direction is adjusted according to the monitoring accuracy requirements; when the second optical cable is loosely wound, the spacing between the cables in the axial direction is greater than the center spacing of the first optical cable, and the total number of turns is not less than 3 turns; the spacing of the FBG engraved in the first optical cable and the second optical cable is determined according to the outer diameter of the inner tube to ensure that each winding contains one FGB.

5. The debris flow monitoring and early warning method according to claim 1 is characterized in that: In step S5, the mud water level height H is determined and calculated using the following formula: H=(k-1)*d (1) In formula (1), H represents the height of mud water level rise, k represents the number of active sensors, and d represents the spacing between active sensors.

6. The debris flow monitoring and early warning method according to claim 1 is characterized in that: In step S6, when judging whether there is collapsed material at the position q where the strain sensor is arranged according to the strain sensor, the temperature value T6(i) collected by the sixth optical cable at the current time i is used to calibrate the temperature drift coefficient of the fifth optical cable, and obtain the strain signal of the fifth optical cable after temperature calibration at the current time i.

7. The debris flow monitoring and early warning method according to claim 2 is characterized in that: The sound wave characteristics in step S72 include the amplitude of the main frequency band and the time-frequency power spectrum.

8. The debris flow monitoring and early warning method according to claim 2 is characterized in that: In step S73, when the ultrasonic sensor in the flow area is used to calculate the velocity of the debris flow, the temperature value T4(i) collected by the fourth optical cable at the current time i is used to calibrate the temperature drift coefficient of the third optical cable, and the acoustic wave signal of the third optical cable after temperature calibration at the current time i is obtained, and the average velocity value S(i) of the debris flow is calculated by waveform feature matching.

9. The debris flow monitoring and early warning method according to claim 2, characterized in that: When performing a debris flow warning in step S8, the warning situation is divided into four levels; the steps include: Step S81, determine the change of the difference ΔH(i) between the mud water level value H(i) at the current time i and the mud water level value H(i-1) at the time i-1. If 0<ΔH(i)≤H v , and H(i)≤H e , it is judged that the mud water level is rising, but it is a normal water level cycle change, and no warning is given; among them, H v is the mud water level rising rate threshold, H e is the mud water level height threshold; Step S82, if 0<ΔH(i)≤H v And H e <H(i), it is judged that the mud water level is rising, exceeding the historical normal water level and rising rate, which is likely to cause flood disasters, and a first-level warning is issued; Step S83, if H v <ΔH(i), and H e <H(i), it is judged that the mud and water level is rising violently and is likely to cause mudslides in the short term, and a second-level warning is issued; if H v <ΔH(i) and H e <H(i) and the number of caving materials in the source area is N q ≥Q, where Q is the threshold of the amount of landslides. It is judged that the debris flow source is abundant and the conditions for debris flow outbreak are met, and a level 3 warning is issued; Step S84, if H v <ΔH(i) and H e <H(i) and identify the sound wave enhancement in the debris flow channel, judge that the debris flow is erupting, issue a fourth-level warning, calculate the arrival time of the debris flow according to the average flow velocity S of the debris flow and the total length L of the debris flow channel, send warning information to the public through multimedia, and give the time to avoid danger.

10. A debris flow monitoring and early warning device, characterized in that: The device comprises: a geological information acquisition module, an optical fiber temperature sensor, an optical fiber acoustic wave sensor, an optical fiber strain sensor, a "double fishbone" optical fiber monitoring network construction module, a background data determination module, a temperature start determination module, a mud water level calculation module, a collapse object determination and counting module, an acoustic wave foreign body determination module, an acoustic wave start determination module, a flow velocity calculation module and an early warning module; wherein, The geological information acquisition module is used to survey the area to be monitored, divide the debris flow channel and obtain basic geological information; The optical fiber temperature sensor is used to be arranged in the starting area of ​​the debris flow channel to monitor the temperature; The optical fiber acoustic wave sensor is used to be arranged in the flow area of ​​the debris flow channel to monitor the amplitude and frequency of the acoustic wave; The optical fiber strain sensor is used to be deployed in the source area of ​​the debris flow channel to locate the collapsed materials; The "double fishbone" optical fiber monitoring network construction module is used to form a monitoring plan based on basic geological information, and deploy the "double fishbone" optical fiber monitoring network along both sides of the debris flow channel according to the monitoring plan; The background data determination module is used to collect environmental parameters of the area to be monitored to form a background database; it is also used to preset a temperature difference threshold ΔT0 and an amplitude difference threshold ΔP0; The temperature start determination module is used to determine the air temperature T in the background database at the i-th moment. a (i) and the lowest horizontal temperature T1(i) of the temperature sensor in the "double fishbone" optical fiber monitoring network, calculate ΔT(i) = T1(i) - T a (i); When |ΔT(i)|≥ΔT0, it is determined that the debris flow has started at time i, and the mud water level calculation module is started; otherwise, the monitoring at the next time is performed; The mud level calculation module is used to extract the temperature of the temperature sensor at each level, which is T1, ..., T2 in descending order. k ,…,T H , when T k (i)-T k When (i-1)≠0, the 1st to kth temperature sensors are active sensors; according to the spacing and number of active sensors, the mud water level height value and the current rising rate value ΔH(i) are determined; The collapse object determination and counting module is used to determine whether there is collapse object at the position q where the strain sensor is arranged according to the strain sensor; if there is collapse object, the collapse object is counted and recorded as N q ; If it does not exist, then N q =0; The acoustic foreign body determination module is used to calculate the change ΔP(i) of the acoustic wave amplitude of the first acoustic wave sensor on either side of the debris flow channel from the i-1th moment to the ith moment. 11 (i)- P 11 (i-1); if ΔP(i)≥ΔP0, it is determined that there is foreign matter in the debris flow channel, and the acoustic wave start-up determination module is started; if ΔP(i)<ΔP0, it is determined that there is no foreign matter in the debris flow channel, and the monitoring at the next moment is performed; The acoustic wave start determination module is used to simultaneously collect the acoustic wave characteristics F of the first acoustic wave sensor on the left side and the first acoustic wave sensor on the right side of the debris flow channel. 11 and F 21 If F 11 and F 21 If the debris flow is matched, the debris flow is determined to have occurred and the velocity calculation module is started; if F 11 and F 21 If they do not match, it is determined that the debris flow has not occurred and the monitoring at the next moment is performed; The flow velocity calculation module is used to collect the monitoring signal time difference t from the first acoustic wave sensor to the second acoustic wave sensor on either side of the debris flow channel, calculate the flow velocity s=L1 / t of the debris flow as the debris flow velocity monitored by the first acoustic wave sensor, L1 is the distance between the installation position of the first acoustic wave sensor and the installation position of the second acoustic wave sensor, and use the same method to calculate the debris flow velocity monitored by all acoustic wave sensors, and calculate the average flow velocity S of the debris flow; The early warning module is used to issue a debris flow early warning based on the mud and water level height value, the rising rate value, the location and count of collapsed objects, the debris flow velocity and the average flow velocity.

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