Intelligent early warning method for real-time online monitoring of slopes based on risk level

Abstract

The present invention discloses a real-time online monitoring intelligent early warning method for slopes based on risk levels, comprising the following steps: S1: dividing the importance levels of dangerous sources, and performing real-time online safety monitoring in a graded manner; S2: determining the displacement value of the dangerous source, and determining the risk factor of the distribution frequency of the dangerous source according to the distribution frequency of the displacement value of the dangerous source; S3: determining the monitoring threshold of the dangerous source, and determining the monitoring threshold ratio risk factor according to the ratio of the displacement value of the dangerous source to the monitoring threshold; S4: comprehensively determining the risk level of the dangerous source, and performing risk early warning. The method of the present invention divides the importance levels of dangerous sources, performs real-time online safety monitoring in a graded manner, determines the risk factors according to the distribution frequency of the displacement value of the dangerous source, the ratio of the displacement value to the monitoring threshold, and then comprehensively determines the monitoring and early warning risk factors of the dangerous source, and divides them into three risk levels of "high, medium, and low". Early warnings are issued to high-risk dangerous sources in real time through an information platform, and monitoring and early warnings can be performed more scientifically.

Description

Technical Field

[0001] The present invention relates to the technical field of slope protection and management of water conservancy and hydropower projects, and in particular to a real-time online monitoring and intelligent early warning method for slopes based on risk levels. Background Art

[0002] The mountainous and canyon areas in southwest my country are rich in hydropower resources, but the geological environment is fragile, the earthquake intensity is high, and the rock mass unloading is strong. As my country's hydropower projects are transferred to the southwest, slopes as high as hundreds of meters are often encountered. The excavation of the project slopes will further deteriorate the stability of the slopes. There are many dangerous sources such as blocks and dangerous rocks on the slopes, which are prone to high-level collapse and rolling, posing a great threat to the safety of construction personnel, equipment and buildings below. Slope collapse accidents are prone to occur, which not only cause large casualties, but also cause large economic losses.

[0003] There are many dangerous sources on high and steep slopes, and their locations are scattered, which poses a prominent safety risk. Therefore, it is necessary to monitor the operating status of dangerous sources, issue early warnings for any abnormal conditions found, and organize the evacuation of personnel and equipment. Reinforcement of dangerous sources can effectively reduce the losses caused by the instability of dangerous sources. At present, there are two main types of evaluation of the operating status of dangerous sources: one is to evaluate the operating status of dangerous sources through manual inspections, and issue early warnings in a timely manner when cracks or signs of sliding are found in dangerous sources; the other is to monitor dangerous sources and evaluate the operating status of dangerous sources through manual analysis of monitoring data.

[0004] The current methods for assessing the operational status of slope hazards have the following problems: (1) Although manual inspections can visually identify problems with the hazard source, they cannot be carried out continuously for a long time, especially during periods of severe weather conditions when slope instability is frequent. On the contrary, there are no conditions for manual inspections, making it difficult to detect the risk of instability of the hazard source in a timely manner; (2) Monitoring facilities can monitor the operational status of the hazard source in real time, but manual analysis of monitoring data cannot be achieved in real time. There is also a lack of scientific monitoring data analysis and early warning methods, and real-time intelligent early warnings cannot be carried out. Summary of the invention

[0005] The purpose of the present invention is to overcome the shortcomings of the above-mentioned background technology and provide a real-time online monitoring intelligent early warning method for slopes based on risk levels. The method divides the importance levels of hazardous sources and performs real-time online safety monitoring in a graded manner. The risk factors are determined according to the distribution frequency of the displacement values ​​of the hazardous sources and the ratio of the displacement values ​​to the monitoring threshold. The monitoring and early warning risk factors of the hazardous sources are then comprehensively determined and divided into three risk levels of "high, medium and low". Early warnings are issued to high-risk hazardous sources in real time through an information platform.

[0006] To achieve the above object, the present invention provides a risk level-based real-time online monitoring intelligent early warning method for slopes, comprising the following steps:

[0007] S1: Divide the importance of hazardous sources and conduct real-time online safety monitoring in different levels;

[0008] S2: Determine the displacement value of the hazard source, and determine the hazard source distribution frequency risk factor according to the distribution frequency of the hazard source displacement value;

[0009] S3: Determine the monitoring threshold of the hazard source, and determine the monitoring threshold ratio risk factor according to the ratio of the hazard source displacement value to the monitoring threshold;

[0010] S4: Comprehensively determine the risk level of hazardous sources and issue risk warnings.

[0011] Furthermore, the step S1 specifically includes the following steps:

[0012] S101: number the hazard sources from 1 to N according to the hazard sources found in the geological survey; calculate the value of F(i)=v(i)*h(i)*m(i) according to the volume scale v(i) of the hazard source, the relative height h(i) of the hazard source and the ground, and the value m(i) of the threatened object, where i=1 to N;

[0013] S102: Sort the calculated values ​​F(i) from small to large, record the order of the calculated value F(i) of the i-th hazard source as P(i), and calculate the importance factor of the slope hazard source f1(i)=P(i) / N;

[0014] S103: Determine the monitoring importance factor F1(i)=f1(i) of the hazard source, and classify the importance of the hazard source; among them, 0.85<F1≤1 is very important; 0.5<F1≤0.85 is medium important; 0≤F1≤0.5 is generally important;

[0015] S104: A GNSS displacement monitoring station is set up on the opposite bank of the slope, and displacement monitoring points are set up on the surface of each hazard source to comprehensively monitor the displacement deformation of each hazard source;

[0016] S105: Determine the density of monitoring points and the frequency of monitoring according to the importance level of the hazard source; transmit all monitoring data to the online monitoring platform in real time through the Internet of Things.

[0017] Furthermore, the step S2 specifically includes the following steps:

[0018] S201: When a hazardous source is arranged with multiple monitoring points, the average displacement of each monitoring point is taken as the hazardous source displacement value Li; according to each hazardous source displacement value Li, the mean, standard deviation, probability density function and distribution function of each hazardous source displacement value are calculated;

[0019] S202: Calculate and determine the risk factor of each hazard source distribution frequency according to the hazard source displacement value distribution frequency

[0020] Furthermore, in step S201, the mean value of the displacement value of each hazard source is calculated by the following formula:

[0021]

[0022] Where μ is the mean displacement value of the hazardous source, i is the number of the hazardous source, n is the total number of hazardous sources, and Li is the displacement value of the i-th hazardous source.

[0023] Furthermore, in step S201, the standard deviation of the displacement value of each hazard source is calculated by the following formula:

[0024]

[0025] Where σ is the standard deviation of the hazard source displacement value, μ is the mean of the hazard source displacement value, i is the number of the hazard source, and n is the total number of hazard sources.

[0026] Furthermore, in step S201, the probability density function of the displacement value of each hazard source is calculated by the following formula:

[0027]

[0028] Where f(x) is the probability density function of the hazard source displacement value, x is an arbitrary value of the function, σ is the standard deviation of the hazard source displacement value, and μ is the mean of the hazard source displacement value.

[0029] Furthermore, in step S201, the distribution function of the displacement value of each hazard source is calculated by the following formula:

[0030]

[0031] Where F(x) is the distribution function of the displacement value of the hazardous source, t is a random variable, x is an arbitrary value of the function, σ is the standard deviation of the displacement value of the hazardous source, and μ is the mean of the displacement value of the hazardous source.

[0032] Furthermore, the step S3 specifically includes the following steps:

[0033] S301: Determine the monitoring threshold Si of each hazard source through calculation or engineering analogy according to the geological and topographic conditions of the hazard source;

[0034] S302: According to the displacement value Li of each hazard source, the ratio of the hazard source displacement value to the monitoring threshold is calculated to determine the monitoring threshold ratio risk factor f3(i)=Li / Si. The monitoring threshold ratio risk factor f3(i) indicates the degree of proximity to the monitoring threshold. The larger the ratio, the more dangerous it is.

[0035] Furthermore, the step S4 specifically includes the following steps:

[0036] S401: Based on the above risk factors, comprehensively determine the monitoring and early warning risk factor F(i)=max(f2(i), f3(i)) of the hazard source;

[0037] S402: Classify the risk level of hazardous sources: F>0.85, high risk; 0.5<F≤0.85, medium risk; 0≤F≤0.5, low risk;

[0038] S403: Sending early warning information through the monitoring platform to relevant personnel about the situation of high-risk dangerous sources;

[0039] S404: Comprehensively determine the monitoring importance factor of the hazard source, F1(i) = max(f1(i), f2(i), f3(i)); where F1>0.85, very important; 0.5<F1≤0.85, medium important; 0≤F1≤0.5, general important; based on the monitoring importance factor of the hazard source, redetermine the monitoring point layout density and monitoring frequency.

[0040] Compared with the prior art, the present invention has the following advantages:

[0041] (1) The method of the present invention comprehensively considers the distribution frequency of the displacement value of the hazard source and the ratio of the displacement value to the monitoring threshold, and can perform monitoring and early warning more scientifically. The method of the present invention calculates the mean, standard deviation, probability density function and distribution function of the displacement value of each hazard source according to the displacement value of each hazard source, and determines the risk factor according to the distribution frequency of the displacement value of the hazard source; at the same time, the monitoring threshold of each hazard source is determined by calculation or engineering analogy, and the risk factor is determined according to the ratio of the displacement value to the monitoring threshold. Finally, the larger value of the two is taken to comprehensively determine the monitoring and early warning risk factor of the hazard source, which can more accurately evaluate the operating status of the hazard source and more scientifically warn of slope risks.

[0042] (2) The method of the present invention comprehensively considers the importance level and risk level of the hazard source, comprehensively determines the density of the monitoring points of the hazard source and the monitoring frequency, and can provide more scientific guidance for slope safety monitoring. The method of the present invention comprehensively determines the importance level of the hazard source based on the volume scale of the slope hazard source, the relative height from the ground, and the value of the threatened object. At the same time, the risk level of the hazard source is comprehensively determined based on the distribution frequency of the displacement value of the hazard source and the ratio of the displacement value to the monitoring threshold. After comprehensively considering the importance and risk level of the hazard source, the density of the monitoring points of the hazard source and the monitoring frequency are comprehensively determined, which can provide more scientific guidance for slope safety monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 The figure is a flow chart of a real-time online monitoring and intelligent early warning method for slopes based on risk level. DETAILED DESCRIPTION

[0044] The following is a detailed description of the implementation of the present invention in conjunction with the implementation cases, but they do not constitute a limitation of the present invention and are only given as examples. At the same time, the advantages of the present invention will become clearer and easier to understand through the description.

[0045] The present invention provides a risk level-based real-time online monitoring intelligent early warning method for slopes, comprising the following steps:

[0046] S1: Divide the importance level of hazardous sources and conduct real-time online safety monitoring in different levels;

[0047] S101: number the hazard sources from 1 to N according to the hazard sources found in the geological survey; calculate the value of F(i)=v(i)*h(i)*m(i) according to the volume scale v(i) of the hazard source, the relative height h(i) of the hazard source and the ground, and the value m(i) of the threatened object, where i=1 to N;

[0048] S102: Sort the calculated values ​​F(i) from small to large, record the order of the calculated value F(i) of the i-th hazard source as P(i), and calculate the importance factor of the slope hazard source f1(i)=P(i) / N;

[0049] S103: Determine the monitoring importance factor F1(i)=f1(i) of the hazard source, and classify the importance of the hazard source; among them, 0.85<F1≤1 is very important; 0.5<F1≤0.85 is medium important; 0≤F1≤0.5 is generally important;

[0050] S104: A GNSS displacement monitoring station is set up on the opposite bank of the slope, and displacement monitoring points are set up on the surface of each hazard source to comprehensively monitor the displacement deformation of each hazard source;

[0051] S105: Determine the density of monitoring points and the frequency of monitoring according to the importance level of the hazard source; transmit all monitoring data to the online monitoring platform in real time through the Internet of Things.

[0052] S2: Determine the displacement value of the hazard source, and determine the hazard source distribution frequency risk factor according to the distribution frequency of the hazard source displacement value;

[0053] S201: When a hazardous source is arranged with multiple monitoring points, the average displacement of each monitoring point is taken as the hazardous source displacement value Li; according to each hazardous source displacement value Li, the mean, standard deviation, probability density function and distribution function of each hazardous source displacement value are calculated;

[0054] In step S201, the mean value of the displacement values ​​of each hazard source is calculated by the following formula:

[0055]

[0056] Where μ is the mean displacement value of the hazardous source, i is the number of the hazardous source, n is the total number of hazardous sources, and Li is the displacement value of the i-th hazardous source.

[0057] In step S201, the standard deviation of the displacement value of each hazard source is calculated by the following formula:

[0058]

[0059] Where σ is the standard deviation of the hazard source displacement value, μ is the mean of the hazard source displacement value, i is the number of the hazard source, n is the total number of hazard sources, and Li is the displacement value of the i-th hazard source.

[0060] In step S201, the probability density function of the displacement value of each hazard source is calculated by the following formula:

[0061]

[0062] Where f(x) is the probability density function of the hazard source displacement value, x is an arbitrary value of the function, σ is the standard deviation of the hazard source displacement value, and μ is the mean of the hazard source displacement value.

[0063] The distribution function of the displacement value of each hazard source is calculated by the following formula:

[0064]

[0065] Where F(x) is the distribution function of the displacement value of the hazardous source, t is a random variable, x is an arbitrary value of the function, σ is the standard deviation of the displacement value of the hazardous source, and μ is the mean of the displacement value of the hazardous source.

[0066] S202: Calculate and determine the risk factor of each hazard source distribution frequency according to the hazard source displacement value distribution frequency

[0067] S3: Determine the monitoring threshold of the hazard source, and determine the monitoring threshold ratio risk factor according to the ratio of the hazard source displacement value to the monitoring threshold;

[0068] S301: Determine the monitoring threshold Si of each hazard source through calculation or engineering analogy according to the geological and topographic conditions of the hazard source;

[0069] S302: According to the displacement values ​​Li of each hazard source, the ratio of the hazard source displacement value to the monitoring threshold is calculated to determine the monitoring threshold ratio risk factor f3(i)=Li / Si.

[0070] S4: Comprehensively determine the risk level of hazardous sources and conduct risk warning:

[0071] S401: Based on the above risk factors, comprehensively determine the monitoring and early warning risk factor F(i)=max(f2(i), f3(i)) of the hazard source;

[0072] S402: Classify the risk level of hazardous sources: F>0.85, high risk; 0.5<F≤0.85, medium risk; 0≤F≤0.5, low risk;

[0073] S403: Sending early warning information through the monitoring platform to relevant personnel about the situation of high-risk dangerous sources;

[0074] S404: Comprehensively determine the monitoring importance factor of the hazard source, F1(i) = max(f1(i), f2(i), f3(i)); where F1>0.85, very important; 0.5<F1≤0.85, medium important; 0≤F1≤0.5, general important; based on the monitoring importance factor of the hazard source, redetermine the monitoring point layout density and monitoring frequency.

[0075] Example:

[0076] like Figure 1 As shown, the real-time online monitoring intelligent early warning method for slopes based on risk level in this embodiment includes the following steps:

[0077] (1) Based on the hazards found during geological surveys, the hazards are numbered in sequence starting from 1, with the maximum number being N.

[0078] (2) According to the volume scale v(i) of the hazard source, the relative height h(i) between the hazard source and the ground, and the value m(i) of the threatened object, calculate the value of F(i) = v(i)*h(i)*m(i), where i = 1 to N.

[0079] (3) Sort the calculated values ​​F(i) from small to large, record the order of the calculated value F(i) of the i-th hazard source as P(i), and calculate the importance factor of the slope hazard source f1(i) = P(i) / N.

[0080] (4) Determine the monitoring importance factor of the hazard source F1(i) = f1(i) and classify the importance of the hazard source; among them, 0.85<F1≤1 is very important; 0.5<F1≤0.85 is medium important; 0≤F1≤0.5 is generally important.

[0081] (5) Set up a GNSS displacement monitoring station on the opposite bank of the slope, and set up displacement monitoring points on the surface of each hazardous source to comprehensively monitor the displacement deformation of each hazardous source. Determine the density and frequency of monitoring points according to the importance level of the hazardous source. Set up three monitoring points for very important hazardous sources, and collect monitoring data every 10 seconds; set up two monitoring points for medium-important hazardous sources, and collect monitoring data every 20 seconds; set up one monitoring point for general-important hazardous sources, and collect monitoring data every 30 seconds. All monitoring data will be transmitted to the online monitoring platform in real time through the Internet of Things.

[0082] (6) When there are multiple monitoring points for a hazardous source, the average displacement of each monitoring point is taken as the hazardous source displacement value Li. Based on the displacement values ​​Li of each hazardous source, the mean, standard deviation, probability density function and distribution function of each hazardous source displacement value are calculated.

[0083] The mean displacement value of each hazard source is calculated by the following formula:

[0084]

[0085] Where μ is the mean displacement value of the hazardous source, i is the number of the hazardous source, n is the total number of hazardous sources, and Li is the displacement value of the i-th hazardous source.

[0086] The standard deviation of the displacement value of each hazard source is calculated by the following formula:

[0087]

[0088] Where σ is the standard deviation of the hazard source displacement value, μ is the mean of the hazard source displacement value, i is the number of the hazard source, n is the total number of hazard sources, and Li is the displacement value of the i-th hazard source.

[0089] The probability density function of the displacement value of each hazard source is calculated by the following formula:

[0090]

[0091] Where f(x) is the probability density function of the hazard source displacement value, x is an arbitrary value of the function, σ is the standard deviation of the hazard source displacement value, and μ is the mean of the hazard source displacement value.

[0092] The distribution function of the displacement value of each hazard source is calculated by the following formula:

[0093]

[0094] Where F(x) is the distribution function of the displacement value of the hazardous source, t is a random variable, x is an arbitrary value of the function, σ is the standard deviation of the displacement value of the hazardous source, and μ is the mean of the displacement value of the hazardous source.

[0095] (7) According to the calculation formula in step (6), calculate and determine the risk factor of each hazard source distribution frequency according to the hazard source displacement value distribution frequency

[0096] (8) Based on the geological and topographical conditions of the hazard source, determine the monitoring threshold Si of each hazard source through calculation or engineering analogy.

[0097] (9) According to the displacement value Li of each hazard source, the ratio of the hazard source displacement value to the monitoring threshold is calculated, that is, f3(i) = Li / Si. The monitoring threshold ratio risk factor f3(i) indicates the degree of proximity to the monitoring threshold. The larger the ratio, the more dangerous it is.

[0098] (10) Based on the risk factors calculated in steps (7) and (9), comprehensively determine the monitoring and early warning risk factor F(i)=max(f2(i), f3(i)) of the hazard source.

[0099] (11) The risk levels of hazardous sources are classified as follows: F>0.85, which is high risk; 0.5<F≤0.85, which is medium risk; 0≤F≤0.5, which is low risk.

[0100] (12) Issue early warning information through the monitoring platform and send the situation of high-risk hazardous sources to relevant personnel.

[0101] (13) Comprehensively determine the monitoring importance factor of the hazard source F1(i) = max(f1(i), f2(i), f3(i)); where F1>0.85 is very important; 0.5<F1≤0.85 is moderately important; 0≤F1≤0.5 is generally important; based on the monitoring importance factor of the hazard source, redefine the density of monitoring points and the frequency of monitoring.

[0102] The above are only specific embodiments of the present invention. It should be pointed out that any changes or substitutions that can be easily thought of by any technician familiar with the field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention, and the rest not described in detail belong to the prior art.

Claims

1. A real-time online monitoring and intelligent early warning method for slopes based on risk level, characterized by: The steps include: S1: Divide the importance level of the hazard sources and conduct real-time online safety monitoring in different levels, which includes the following steps: S101: number the hazard sources from 1 to N according to the hazard sources found in the geological survey; calculate the value of F(i)=v(i)*h(i)*m(i) according to the volume scale v(i) of the hazard source, the relative height h(i) of the hazard source and the ground, and the value m(i) of the threatened object, where i=1 to N; S102: Sort the calculated values ​​F(i) from small to large, record the order of the calculated value F(i) of the i-th hazard source as P(i), and calculate the importance factor of the slope hazard source f1(i)=P(i) / N; S103: Determine the monitoring importance factor F1(i)=f1(i) of the hazard source, and classify the importance of the hazard source; among them, 0.85<F1≤1 is very important; 0.5<F1≤0.85 is medium important; 0≤F1≤0.5 is generally important; S104: A GNSS displacement monitoring station is set up on the opposite bank of the slope, and displacement monitoring points are set up on the surface of each hazard source to comprehensively monitor the displacement deformation of each hazard source; S105: Determine the density and frequency of monitoring points according to the importance level of the hazard source; transmit all monitoring data to the online monitoring platform in real time through the Internet of Things; S2: Determine the displacement value of the hazard source, and determine the hazard source distribution frequency risk factor according to the distribution frequency of the hazard source displacement value, which specifically includes the following steps: S201: When a hazardous source is arranged with multiple monitoring points, the average displacement of each monitoring point is taken as the hazardous source displacement value Li; according to each hazardous source displacement value Li, the mean, standard deviation, probability density function and distribution function of each hazardous source displacement value are calculated; S202: Calculate and determine the risk factor of each hazard source distribution frequency according to the hazard source displacement value distribution frequency S3: Determine the monitoring threshold of the hazard source, and determine the monitoring threshold ratio risk factor according to the ratio of the hazard source displacement value to the monitoring threshold, which specifically includes the following steps: S301: Determine the monitoring threshold Si of each hazard source through calculation or engineering analogy according to the geological and topographic conditions of the hazard source; S302: According to the displacement value Li of each hazard source, the ratio of the hazard source displacement value to the monitoring threshold is calculated to determine the monitoring threshold ratio risk factor f3(i)=Li / Si; S4: Comprehensively determine the risk level of the hazard source and conduct risk warning, which specifically includes the following steps: S401: Based on the above risk factors, comprehensively determine the monitoring and early warning risk factor F(i)=max(f2(i), f3(i)) of the hazard source; S402: Classify the risk level of hazardous sources: F>0.85, high risk; 0.5<F≤0.85, medium risk; 0≤F≤0.5, low risk; S403: Sending early warning information through the monitoring platform to relevant personnel about the situation of high-risk dangerous sources; S404: Comprehensively determine the monitoring importance factor of the hazard source, F1(i) = max(f1(i), f2(i), f3(i)); where F1>0.85, very important; 0.5<F1≤0.85, medium important; 0≤F1≤0.5, general important; based on the monitoring importance factor of the hazard source, redetermine the monitoring point layout density and monitoring frequency.

2. The method for real-time online monitoring and intelligent early warning of slopes based on risk level according to claim 1 is characterized in that: In step S201, the mean value of the displacement values ​​of each hazard source is calculated by the following formula: Where μ is the mean displacement value of the hazardous source, i is the number of the hazardous source, n is the total number of hazardous sources, and Li is the displacement value of the i-th hazardous source.

3. The method for real-time online monitoring and intelligent early warning of slopes based on risk level according to claim 1 is characterized in that: In step S201, the standard deviation of the displacement value of each hazard source is calculated by the following formula: Where σ is the standard deviation of the hazard source displacement value, μ is the mean of the hazard source displacement value, i is the number of the hazard source, n is the total number of hazard sources, and Li is the displacement value of the i-th hazard source.

4. The method for real-time online monitoring and intelligent early warning of slopes based on risk level according to claim 1 is characterized in that: In step S201, the probability density function of the displacement value of each hazard source is calculated by the following formula: Where f(x) is the probability density function of the hazard source displacement value, x is an arbitrary value of the function, σ is the standard deviation of the hazard source displacement value, and μ is the mean of the hazard source displacement value.

5. The method for real-time online monitoring and intelligent early warning of slopes based on risk level according to claim 1 is characterized in that: In step S201, the distribution function of the displacement value of each hazard source is calculated by the following formula: Where F(x) is the distribution function of the displacement value of the hazardous source, t is a random variable, x is an arbitrary value of the function, σ is the standard deviation of the displacement value of the hazardous source, and μ is the mean of the displacement value of the hazardous source.

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