Underground management and control patrol operation and maintenance early warning method based on unmanned aerial vehicle

Abstract

The invention relates to the technical field of underground management and control, in particular to an unmanned aerial vehicle-based underground management and control inspection operation and maintenance early warning method, which comprises the following steps of: inspecting an underground passage by using an unmanned aerial vehicle according to initial parameters, collecting pipeline data and environmental data in the passage, and storing the pipeline data and the environmental data; dividing the patrol route into a plurality of road sections with different risk levels according to the comprehensive risk value of the risk event type in the channel, and determining unmanned aerial vehicle patrol parameters; comparing the current data in the single road section with historical data to determine a data change rate, and determining a storage level of the data of the single road section according to the data change rate; determining a data storage optimization strategy of the single road section according to the data change index of the single road section after the preset number of times of inspection; and determining a response strategy based on the comprehensive data change rate of the single road section patrolled for a plurality of times after the patrolling frequency is increased. According to the invention, the intelligent level and emergency response efficiency of underground management and control patrol operation and maintenance are improved.

Description

Technical Field

[0001] The present invention relates to the field of underground control technology, and in particular to an underground control, inspection, operation and maintenance early warning method based on a drone. Background Art

[0002] With the acceleration of urbanization, the scale of underground spaces (such as utility corridors, subway tunnels, and underground pipeline networks) continues to expand, posing significant challenges to their safe operation and maintenance. Traditional underground inspections rely primarily on manual patrols or fixed sensor monitoring, which suffer from low efficiency, incomplete coverage, and delayed response. For example, manual inspections struggle to cover complex and hidden areas and lack real-time data. Fixed sensors, on the other hand, are expensive to deploy and lack flexibility, making them difficult to dynamically adapt to monitoring needs at varying risk levels.

[0003] Chinese patent application publication number: CN116128466A, discloses a method and system for internal and external linkage control of flood risks in underground integrated pipeline corridors, involving the field of flood early warning technology. The method includes: determining, based on existing standards and specifications for underground integrated pipeline corridors and the causes of floods in historical cases, monitoring objects that can characterize the flood situation in the surface area outside the underground integrated pipeline corridor, monitoring objects that can characterize the flood situation inside the underground integrated pipeline corridor, and monitoring indicators corresponding to each of the monitoring objects; determining the source of the flood in the underground integrated pipeline corridor based on the monitoring objects and the corresponding monitoring indicators; determining the flood risk level of the underground integrated pipeline corridor based on the four-level risk level judgment principle, the monitoring objects and the corresponding monitoring indicators; and determining emergency response measures based on the flood risk level and the source of the flood in the underground integrated pipeline corridor.

[0004] However, the existing technology has the following problems: the existing technology cannot dynamically adjust the risk assessment strategy according to real-time monitoring data, resulting in a delayed response to sudden risks or progressive hidden dangers. Summary of the Invention

[0005] To this end, the present invention provides an underground control, inspection, operation and maintenance early warning method based on drones, which is used to overcome the problem in the existing technology that dynamic monitoring and control cannot be achieved, resulting in delayed early warning response.

[0006] To achieve the above objectives, the present invention provides an underground control, inspection, operation and maintenance early warning method based on a drone, comprising:

[0007] Step S1: Using a drone to patrol an underground tunnel with initial parameters, collecting pipeline data and environmental data in the tunnel and storing them. The pipeline data includes pipeline distribution density and corrosion area at pipeline connections, and the environmental data includes humidity, tunnel crack size, water depth, and vibration frequency.

[0008] Step S2: dividing the patrol route into several sections of different risk levels according to the comprehensive risk value of the risk event type in the channel and determining the parameters of the drone patrol, wherein the parameters include speed and clarity;

[0009] Step S3, comparing the current data in the single road section with the historical data to determine the data change rate and determining the storage level of the single road section data according to the data change rate;

[0010] Step S4, determining a data storage optimization strategy for a single road section based on the data change index in the single road section after a preset number of patrols, including reducing the patrol comparison frequency, adjusting patrol parameters, and increasing the patrol frequency;

[0011] Step S6: determining a response strategy based on the comprehensive data change rate of a single road section patrolled several times after the patrol frequency is increased.

[0012] Furthermore, the risk event types include one or more of the following:

[0013] The pipeline distribution density is greater than the preset density;

[0014] Or, the corrosion area ratio at the pipeline connection is greater than the preset area ratio;

[0015] Or, the humidity in the channel is greater than the preset humidity;

[0016] Or, the channel crack size is larger than the preset size;

[0017] Or, the depth of accumulated water is greater than the preset depth;

[0018] Or, the channel vibration frequency is greater than the preset frequency.

[0019] Furthermore, the risk level of the road section is determined according to the comprehensive risk value of the risk event type in the channel, and the parameters of the drone patrol are determined. If the comprehensive risk value is less than or equal to a first preset risk value, the road section is determined to be a low-risk road section, and the speed of the drone patrol is determined to be the first preset speed and the clarity is determined to be the first preset clarity.

[0020] If the comprehensive risk value is greater than the first preset risk value and less than or equal to the second preset risk value, the road section is determined to be a medium-risk road section, and the speed of the drone patrol is determined to be the second preset speed and the clarity is determined to be the second preset clarity;

[0021] If the comprehensive risk value is greater than the second preset risk value, the road section is determined to be a high-risk road section, and the speed of the drone patrol is determined to be a third preset speed and the clarity is determined to be a third preset clarity;

[0022] The comprehensive risk value is determined by the number of risk event types and weight coefficients.

[0023] Furthermore, the storage level of the single-segment data is determined according to the data change rate. If the data change rate is less than a first preset change rate, the storage level of the single-segment data is determined to be level three, and the level three storage is high-compression storage.

[0024] If the data change rate is greater than or equal to the first preset change rate and less than the second preset change rate, the storage level of the single-segment data is determined to be level 2, and the level 2 storage is low-compression storage;

[0025] If the data change rate is greater than or equal to the second preset change rate, the storage level of the single-segment data is determined to be level one, and level one storage is lossless storage.

[0026] Furthermore, a data storage optimization strategy for the single road section is determined based on a data change index in the single road section after a preset number of patrols, wherein if the data change index is less than a first preset change index, the data storage optimization strategy for the single road section is determined to be reducing the data comparison frequency based on a difference between the first preset change index and the data change index;

[0027] If the data change index is greater than or equal to the first preset change index and less than the second preset change index, determining that the data storage optimization strategy for the single road section is to adjust the patrol parameters according to the risk proportion characteristic value of the risk event type to which the change data belongs;

[0028] If the data change index is greater than or equal to the second preset change index, the data storage optimization strategy for the single road section is determined to upgrade the storage level of the road section and increase the patrol frequency according to the difference between the data change index and the second preset change index.

[0029] Furthermore, the data comparison frequency is positively correlated with the change index difference, wherein the change index difference is the difference between the first preset change index and the data change index.

[0030] Furthermore, the parameters of the patrol are adjusted according to the risk ratio characteristic value, wherein, if the risk ratio characteristic value is less than a preset risk ratio characteristic value, the patrol speed is reduced according to the difference between the preset risk ratio characteristic value and the risk ratio characteristic value;

[0031] If the risk ratio characteristic value is greater than or equal to the preset risk ratio characteristic value, then the patrol clarity is increased according to the difference between the risk ratio characteristic value and the preset risk ratio characteristic value under the condition of low patrol speed.

[0032] Furthermore, the risk proportion characteristic value is determined according to the proportion of the risk event type to which the change data belongs, wherein the proportion includes the proportion of the first category and the proportion of the second category;

[0033] The risk event types of the first category include pipeline distribution density greater than a preset density, humidity in the channel greater than a preset humidity, and channel vibration frequency greater than a preset frequency;

[0034] The risk event types of the second category include the proportion of the rust area at the pipeline connection being greater than the preset area proportion, the size of the channel crack being greater than the preset size, and the depth of water accumulation being greater than the preset depth.

[0035] Furthermore, several adjustment methods are provided for the patrol frequency, and each adjustment method has a different adjustment range for the patrol frequency.

[0036] Further, a response strategy is determined based on a comprehensive data change rate of a single road section patrolled several times after the patrol frequency is increased, wherein if the comprehensive data change rate is less than a first preset change rate, the response strategy is determined to be downgrading the storage level;

[0037] If the comprehensive data change rate is greater than or equal to the first preset change rate and less than the second preset change rate, the response strategy is determined to be to initiate a low-level warning, and the low-level warning strategy is to remind the operation and maintenance personnel to pay attention to the data changes of the road section and arrange regular inspections;

[0038] If the comprehensive data change rate is greater than or equal to the second preset change rate, the response strategy is determined to start an advanced warning. The advanced warning strategy is to call the operation and maintenance personnel to immediately go to the abnormal section for detailed inspection and perform emergency repairs or maintenance.

[0039] Compared with the existing technology, the beneficial effect of the present invention is that the present invention uses drones to patrol and collect pipeline data and environmental data in the channel, obtains data change parameters based on the comparison results of real-time data and historical data, and determines the operation and maintenance response strategy according to the parameters, thereby improving the intelligence level and emergency response efficiency of underground control, patrol and operation.

[0040] Furthermore, the present invention divides the patrol route into several sections with different risk levels according to the comprehensive risk value of the risk event type in the channel and determines the parameters of the drone patrol. It can adopt appropriate patrol strategies for sections with different risk levels to improve patrol efficiency and pertinence.

[0041] Furthermore, the present invention determines the data change rate by comparing the current data of a single road section with the historical data, and then determines the data storage level, thereby realizing hierarchical storage of data with different degrees of change, which is conducive to the rational use of storage resources.

[0042] Furthermore, the present invention determines a data storage optimization strategy based on the single-section data change index after a preset number of patrols, including reducing the patrol comparison frequency, adjusting patrol parameters and increasing the patrol frequency, further optimizing the data storage and patrol strategy and improving the system's operating efficiency.

[0043] Furthermore, the present invention adjusts the inspection parameters according to the risk ratio characteristic value, comprehensively considers the impact of different risk event types on the inspection parameters, and can more reasonably adjust the inspection strategy and improve the inspection effect.

[0044] Furthermore, the present invention determines a response strategy based on the rate of change of comprehensive data of a single road section after several inspections with increased patrol frequency, including storage level downgrade, activation of low-level warning and activation of high-level warning, etc., clarifies the response measures in different situations, and can deal with abnormal situations in underground passages in a timely and effective manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 This is a flow chart of an underground control, inspection, operation and maintenance early warning method based on a drone according to an embodiment of the present invention;

[0046] Figure 2 A flowchart for determining the storage level of single-segment data according to an embodiment of the present invention;

[0047] Figure 3 A flowchart of a data storage optimization strategy for determining a single road segment according to an embodiment of the present invention;

[0048] Figure 4 This is a flowchart for determining an underground management and control response strategy according to an embodiment of the present invention. DETAILED DESCRIPTION

[0049] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are merely used to explain the present invention and are not intended to limit the present invention.

[0050] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0051] It should be pointed out that the data in this embodiment are obtained by comprehensive analysis and evaluation of the historical test data and the corresponding historical test results of the three months before this test. It can be understood by those skilled in the art that the present invention can determine the above parameters for a single item by selecting the value with the highest proportion as the preset standard parameter based on the data distribution, using weighted summation to use the obtained value as the preset standard parameter, substituting each historical data into a specific formula and using the value obtained by the formula as the preset standard parameter or other selection methods, as long as the present invention can clearly define the different specific situations in the single determination process through the obtained values.

[0052] See also Figures 1 to 4 As shown, they are respectively a flowchart of an underground control, inspection, operation and maintenance early warning method based on drones according to an embodiment of the present invention; a flowchart of determining the storage level of single road section data according to an embodiment of the present invention; a flowchart of determining the data storage optimization strategy for a single road section according to an embodiment of the present invention; and a flowchart of determining the underground control response strategy according to an embodiment of the present invention.

[0053] The embodiment of the present invention provides an underground control, inspection, operation and maintenance early warning method based on a drone, including:

[0054] Step S1: Using a drone to patrol an underground tunnel with initial parameters, collecting pipeline data and environmental data in the tunnel and storing them. The pipeline data includes pipeline distribution density and corrosion area at pipeline connections, and the environmental data includes humidity, tunnel crack size, water depth, and vibration frequency.

[0055] Step S2: dividing the patrol route into several sections of different risk levels according to the comprehensive risk value of the risk event type in the channel and determining the parameters of the drone patrol, wherein the parameters include speed and clarity;

[0056] Step S3, comparing the current data in the single road section with the historical data to determine the data change rate and determining the storage level of the single road section data according to the data change rate;

[0057] Step S4, determining a data storage optimization strategy for a single road section based on the data change index in the single road section after a preset number of patrols, including reducing the patrol comparison frequency, adjusting patrol parameters, and increasing the patrol frequency;

[0058] Step S5: determining a response strategy based on the comprehensive data change rate of a single road section patrolled several times after the patrol frequency is increased.

[0059] Specifically, the initial parameters in step S1 include: a patrol speed of 0.5 m / s and a resolution of 4 k.

[0060] Specifically, the length of the single road section in step S2 is 10m.

[0061] Specifically, the risk event types include one or more of the following:

[0062] The pipeline distribution density is greater than the preset density of 15 pipelines / m 2 ;

[0063] Or, the corrosion area of the pipeline connection is greater than 10% of the preset area;

[0064] Or, the humidity in the channel is greater than the preset humidity 85% RH;

[0065] Or, the channel crack size is larger than a preset size, wherein the preset size includes a width larger than 5 mm, or a length larger than 0.5 m;

[0066] Or, the depth of water is greater than the preset depth of 10cm;

[0067] Or, the channel vibration frequency is greater than the preset frequency 50Hz.

[0068] In the embodiment of the present invention, the preset density is 15 pieces / m 2 The preset area ratio is 10%, the preset humidity is 85% RH, the preset depth is 10 cm, and the preset frequency is 50 Hz, but the above values are not limited thereto. Those skilled in the art can adjust the above values according to actual needs.

[0069] Specifically, the drone is equipped with a high-resolution camera for obtaining pipeline distribution density and channel crack size; a multispectral camera for identifying the rust area at pipeline connections; a micro-meteorological sensor for obtaining the humidity in the channel; an ultrasonic sensor for obtaining the depth of water accumulation; and an acoustic sensor for obtaining the vibration frequency of the channel.

[0070] Specifically, the risk level of the road section is determined based on the comprehensive risk value of the risk event type in the channel, and the parameters of the drone patrol are determined. If the comprehensive risk value is less than or equal to the first preset risk value of 0.1, the road section is determined to be a low-risk section, and the speed of the drone patrol is determined to be the first preset speed of 1m / s, and the resolution is determined to be the first preset resolution of 1080p;

[0071] If the comprehensive risk value is greater than the first preset risk value and less than or equal to the second preset risk value of 0.3, the road section is determined to be a medium-risk road section, and the speed of the drone patrol is determined to be the second preset speed of 0.7 m / s and the clarity is determined to be the second preset clarity of 2k;

[0072] If the comprehensive risk value is greater than the second preset risk value, the road section is determined to be a high-risk road section, and the speed of the drone patrol is determined to be a third preset speed of 0.5 m / s, and the clarity is determined to be a third preset clarity of 3k;

[0073] The comprehensive risk value is determined by the number of risk event types and weight coefficients.

[0074] Specifically, the comprehensive risk value is the sum of the product of the number of risk event types and the type weight coefficient.

[0075] Specifically, the weight coefficient of pipeline distribution density is 0.05, the weight coefficient of corrosion area is 0.1, the weight coefficient of humidity is 0.2, the weight coefficient of crack size is 0.05, the weight coefficient of water depth is 0.3, and the weight coefficient of vibration frequency is 0.3.

[0076] In the embodiment of the present invention, the first preset risk value is 0.1, and the second preset risk value is 0.3, but the above values are not limited thereto, and those skilled in the art may adjust the above values according to actual needs.

[0077] Specifically, the storage level of the single-segment data is determined according to the data change rate. If the data change rate is less than 10% of the first preset change rate, the storage level of the single-segment data is determined to be level three, and the level three storage is high-compression storage.

[0078] If the data change rate is greater than or equal to the first preset change rate and less than 20% of the second preset change rate, the storage level of the single-segment data is determined to be level 2, and the level 2 storage is low-compression storage;

[0079] If the data change rate is greater than or equal to the second preset change rate, the storage level of the single-segment data is determined to be level one, and level one storage is lossless storage.

[0080] Specifically, the data change rate is the proportion of the changed data to the total data. In an embodiment of the present invention, the first preset change rate is 10%, and the second preset change rate is 20%, but the above values are not limited to this. Those skilled in the art can adjust the above values according to actual needs.

[0081] Specifically, the compression rate of the tertiary storage is 50%, and the compression rate of the secondary storage is 30%.

[0082] Specifically, the data storage optimization strategy for the single road section is determined according to the data change index in the single road section after a preset number of 10 patrols, wherein if the data change index is less than a first preset change index of 0.05, the data storage optimization strategy for the single road section is determined to be reducing the data comparison frequency according to the difference between the first preset change index and the data change index;

[0083] If the data change index is greater than or equal to the first preset change index and less than the second preset change index of 0.15, then determining that the data storage optimization strategy for the single road section is to adjust the patrol parameters according to the risk proportion characteristic value of the risk event type to which the change data belongs;

[0084] If the data change index is greater than or equal to the second preset change index, the data storage optimization strategy for the single road section is determined to upgrade the storage level of the road section and increase the patrol frequency according to the difference between the data change index and the second preset change index.

[0085] Specifically, the data change index is the variance of the change rate of each change data, which is calculated and obtained by the data analysis module.

[0086] In an embodiment of the present invention, the preset number of times is 10 times, the first preset change index is 0.05, and the second preset change index is 0.15, but the above values are not limited to this. Those skilled in the art can adjust the above values according to actual needs.

[0087] Specifically, upgrading the storage level is to reduce the level number by one, and the upgrade strategy for level one storage is to extend the storage duration to 1 month.

[0088] Specifically, the first preset change index is a parameter obtained after the data changes normally. The present invention reduces the data comparison frequency based on the condition that the data change index is less than the first preset change index, thereby improving the management and control efficiency.

[0089] Specifically, the data comparison frequency is positively correlated with the change index difference, wherein if the change index difference is less than a first preset change index difference of 0.01, the data comparison frequency is reduced to a corresponding value using a first frequency adjustment coefficient of 0.5;

[0090] If the change index difference is greater than or equal to the first preset change index difference and less than the second preset change index difference of 0.03, then using a second frequency adjustment coefficient of 0.2 to reduce the data comparison frequency to a corresponding value;

[0091] If the change index difference is greater than or equal to the second preset change index difference, then using a third frequency adjustment coefficient of 0.1 to reduce the data comparison frequency to a corresponding value;

[0092] The change index difference is the difference between the first preset change index and the data change index.

[0093] In an embodiment of the present invention, the initial frequency of the data comparison frequency is one comparison per patrol, the first preset change index difference value is 0.01, and the second preset change index difference value is 0.03, but the above values are not limited to this. Those skilled in the art can adjust the above values according to actual needs.

[0094] Specifically, the patrol parameters are adjusted according to the risk ratio characteristic value, wherein, if the risk ratio characteristic value is less than the preset risk ratio characteristic value of 0.5, the patrol speed is reduced according to the difference between the preset risk ratio characteristic value and the risk ratio characteristic value;

[0095] If the risk ratio characteristic value is greater than or equal to the preset risk ratio characteristic value, then the patrol clarity is increased according to the difference between the risk ratio characteristic value and the preset risk ratio characteristic value under the condition of low patrol speed.

[0096] In the embodiment of the present invention, the preset risk ratio characteristic value is 0.5, the patrol speed is adjusted in the range of 0.3 to 1.0 m / s, and the definition is adjusted in the range of 1080P to 4K.

[0097] Specifically, the risk proportion characteristic value is determined according to the proportion of the risk event type to which the change data belongs, wherein the proportion includes the proportion of the first category and the proportion of the second category;

[0098] The risk event types of the first category include pipeline distribution density greater than a preset density, humidity in the channel greater than a preset humidity, and channel vibration frequency greater than a preset frequency;

[0099] The risk event types of the second category include the proportion of the rust area at the pipeline connection being greater than the preset area proportion, the size of the channel crack being greater than the preset size, and the depth of water accumulation being greater than the preset depth.

[0100] Specifically, the risk proportion characteristic value is determined by a first-class proportion evaluation value and a second-class proportion evaluation value, wherein the first-class proportion evaluation value is the product of the first-class proportion of the risk event type to which the change data belongs and a first weight coefficient of 0.5;

[0101] The second-category proportion evaluation value is the product of the second-category proportion of the risk event type to which the change data belongs and the first weight coefficient 0.5;

[0102] The risk proportion characteristic value is obtained by adding the first-class proportion evaluation value and the second-class proportion evaluation value.

[0103] Specifically, there are several adjustment methods for the patrol frequency, and each adjustment method has a different adjustment range for the patrol frequency. The patrol frequency is positively correlated with the second change index difference, and the second change index difference is the difference between the data change index and the second preset change index.

[0104] In the embodiment of the present invention, the patrol frequency can be adjusted in a range from once a day to once a week.

[0105] Specifically, a response strategy is determined based on the comprehensive data change rate of a single road section patrolled three times after the patrol frequency is increased, wherein if the comprehensive data change rate is less than a first preset change rate of 0.02, the response strategy is determined to be to downgrade the storage level;

[0106] If the comprehensive data change rate is greater than or equal to the first preset change rate and less than 0.1 of the second preset change rate, the response strategy is determined to be to initiate a low-level warning. The low-level warning strategy is to remind the operation and maintenance personnel to pay attention to the data changes of the road section and arrange regular inspections;

[0107] If the comprehensive data change rate is greater than or equal to the second preset change rate, the response strategy is determined to start an advanced warning. The advanced warning strategy is to call the operation and maintenance personnel to immediately go to the abnormal section for detailed inspection and perform emergency repairs or maintenance.

[0108] Specifically, the comprehensive data change rate is the average value of the ratio of the change rate of each change data to the unit time (h).

[0109] In the embodiment of the present invention, the first preset change rate is 0.02% / h, and the second preset change rate is 0.1, but the above values are not limited thereto. Those skilled in the art may adjust the above values according to actual needs.

[0110] Specifically, downgrading the storage level is to increase the storage level by one, and the downgrading strategy for the third-level storage is to increase the compression rate to 70%.

[0111] Thus far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art may make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present invention.

[0112] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that the present invention is susceptible to various modifications and variations. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A method for underground control, inspection, operation and maintenance early warning based on drones, characterized in that: include: Step S1: Using a drone to patrol an underground tunnel with initial parameters, collecting pipeline data and environmental data in the tunnel and storing them. The pipeline data includes pipeline distribution density and corrosion area at pipeline connections, and the environmental data includes humidity, tunnel crack size, water depth, and vibration frequency. Step S2: dividing the patrol route into several sections of different risk levels according to the comprehensive risk value of the risk event type in the channel and determining the parameters of the drone patrol, wherein the parameters include speed and clarity; Step S3, comparing the current data in the single road section with the historical data to determine the data change rate and determining the storage level of the single road section data according to the data change rate; Step S4, determining a data storage optimization strategy for a single road section based on the data change index in the single road section after a preset number of patrols, including reducing the patrol comparison frequency, adjusting patrol parameters, and increasing the patrol frequency; Step S5: determining a response strategy based on the comprehensive data change rate of a single road section patrolled several times after the patrol frequency is increased.

2. The underground control, inspection, operation and maintenance early warning method based on drone according to claim 1 is characterized in that: The risk event types include one or more of the following: The pipeline distribution density is greater than the preset density; Or, the corrosion area ratio at the pipeline connection is greater than the preset area ratio; Or, the humidity in the channel is greater than the preset humidity; Or, the channel crack size is larger than the preset size; Or, the depth of accumulated water is greater than the preset depth; Or, the channel vibration frequency is greater than the preset frequency.

3. The underground control, inspection, operation and maintenance early warning method based on drone according to claim 1 is characterized in that: Determining the risk level of the road section and the parameters of the drone patrol based on the comprehensive risk value of the risk event type in the channel, wherein if the comprehensive risk value is less than or equal to a first preset risk value, the road section is determined to be a low-risk road section, and the speed of the drone patrol is determined to be the first preset speed and the clarity is determined to be the first preset clarity; If the comprehensive risk value is greater than the first preset risk value and less than or equal to the second preset risk value, the road section is determined to be a medium-risk road section, and the speed of the drone patrol is determined to be the second preset speed and the clarity is determined to be the second preset clarity; If the comprehensive risk value is greater than the second preset risk value, the road section is determined to be a high-risk road section, and the speed of the drone patrol is determined to be a third preset speed and the clarity is determined to be a third preset clarity; The comprehensive risk value is determined by the number of risk event types and weight coefficients.

4. The underground control, inspection, operation and maintenance early warning method based on drone according to claim 1 is characterized in that: determining a storage level of the single-segment data according to the data change rate; if the data change rate is less than a first preset change rate, determining the storage level of the single-segment data to be level three, where level three storage is high-compression storage; If the data change rate is greater than or equal to the first preset change rate and less than the second preset change rate, the storage level of the single-segment data is determined to be level 2, and the level 2 storage is low-compression storage; If the data change rate is greater than or equal to the second preset change rate, the storage level of the single-segment data is determined to be level one, and level one storage is lossless storage.

5. The underground control, inspection, operation and maintenance early warning method based on drone according to claim 1 is characterized in that: Determining a data storage optimization strategy for the single road section based on a data change index in the single road section after a preset number of patrols, wherein, if the data change index is less than a first preset change index, determining the data storage optimization strategy for the single road section to be reducing a data comparison frequency based on a difference between the first preset change index and the data change index; If the data change index is greater than or equal to the first preset change index and less than the second preset change index, determining that the data storage optimization strategy for the single road section is to adjust the patrol parameters according to the risk proportion characteristic value of the risk event type to which the change data belongs; If the data change index is greater than or equal to the second preset change index, the data storage optimization strategy for the single road section is determined to upgrade the storage level of the road section and increase the patrol frequency according to the difference between the data change index and the second preset change index.

6. The underground control, inspection, operation and maintenance early warning method based on drone according to claim 5 is characterized in that: The data comparison frequency is positively correlated with the change index difference, wherein the change index difference is the difference between the first preset change index and the data change index.

7. The underground control, inspection, operation and maintenance early warning method based on drone according to claim 5 is characterized in that: Adjusting patrol parameters according to the risk ratio characteristic value, wherein, if the risk ratio characteristic value is less than a preset risk ratio characteristic value, reducing the patrol speed according to the difference between the preset risk ratio characteristic value and the risk ratio characteristic value; If the risk ratio characteristic value is greater than or equal to the preset risk ratio characteristic value, then the patrol clarity is increased according to the difference between the risk ratio characteristic value and the preset risk ratio characteristic value under the condition of low patrol speed.

8. The underground control, inspection, operation and maintenance early warning method based on drone according to claim 7 is characterized in that: The risk proportion characteristic value is determined according to the proportion of the risk event type to which the change data belongs, wherein the proportion includes the proportion of the first category and the proportion of the second category; The risk event types of the first category include pipeline distribution density greater than a preset density, humidity in the channel greater than a preset humidity, and channel vibration frequency greater than a preset frequency; The risk event types of the second category include the proportion of the rust area at the pipeline connection being greater than the preset area proportion, the size of the channel crack being greater than the preset size, and the depth of water accumulation being greater than the preset depth.

9. The underground control, inspection, operation and maintenance early warning method based on drone according to claim 5 is characterized in that: There are several adjustment methods for patrol frequency settings, and each adjustment method has a different adjustment range for the patrol frequency.

10. The underground control, inspection, operation and maintenance early warning method based on drone according to claim 1 is characterized in that: Determining a response strategy based on a comprehensive data change rate of a single road section patrolled several times after the patrol frequency is increased, wherein if the comprehensive data change rate is less than a first preset change rate, determining the response strategy to be downgrading the storage level; If the comprehensive data change rate is greater than or equal to the first preset change rate and less than the second preset change rate, the response strategy is determined to be to initiate a low-level warning, and the low-level warning strategy is to remind the operation and maintenance personnel to pay attention to the data changes of the road section and arrange regular inspections; If the comprehensive data change rate is greater than or equal to the second preset change rate, the response strategy is determined to start an advanced warning. The advanced warning strategy is to call the operation and maintenance personnel to immediately go to the abnormal section for detailed inspection and perform emergency repairs or maintenance.

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