CN-121999597-A - Intelligent slope safety early warning method and system for hydraulic and hydroelectric engineering

CN121999597ACN 121999597 ACN121999597 ACN 121999597ACN-121999597-A

Abstract

The invention discloses a slope safety intelligent early warning method and system for hydraulic and hydroelectric engineering, which relate to the technical field of hydraulic and hydroelectric engineering early warning, the invention takes a slope unit as an object, uniformly processes construction disturbance, structural response, supporting state and seepage state to generate disturbance response characteristic data, and further construct risk transfer chain data and trigger window data, not only can discern the current anomaly of side slope, can also discern risk extension direction and trigger opportunity, output early warning instruction data such as blasting suspension, support reinforcement and drainage are dealt with simultaneously, are applicable to the meticulous safety precaution of hydraulic and hydroelectric engineering complex construction side slope.

Inventors

YU HUIZHEN
CHENG QIANQIAN
QIAN DONGWEI
HE JIANMIN
YU CHANGJIANG
Zhai Debo

Assignees

厦门德露滋环保科技有限公司
厦门逸飞扬网络科技有限公司

Dates

Publication Date: 20260508
Application Date: 20260410

Claims (10)

1. The intelligent slope safety early warning method for the hydraulic and hydroelectric engineering is characterized by comprising the following steps of: Step S1, collecting slope partition data, construction disturbance data, structure response data, support state data and seepage state data, and constructing a slope unit data set; s2, extracting disturbance response characteristic data corresponding to each slope unit according to the slope unit data set; Step S3, constructing risk transfer chain data according to disturbance response characteristic data, spatial association data, structure association data, support association data and seepage association data among the slope units; step S4, identifying trigger window data according to the risk transfer chain data and outputting early warning grade data; and S5, generating early warning instruction data according to the trigger window data and the early warning grade data and sending the early warning instruction data to the control end.
2. The intelligent slope safety early warning method for the hydraulic and hydroelectric engineering according to claim 1, wherein the step S1 comprises the following sub-steps: step S101, slope partition data are obtained, wherein the slope partition data comprise step boundary data, slope section number data and structural surface exposure data; Step S102, construction disturbance data are obtained, wherein the construction disturbance data comprise excavation position data, bursting strength data and drainage operation data; Step S103, obtaining structural response data, support state data and seepage state data, wherein the structural response data comprises displacement data, crack change data and stress change data, the support state data comprises anchoring state data and spraying state data, and the seepage state data comprises rainfall data, seepage pressure data and water content change data; And step S104, carrying out slope unit collection on the slope partition data, the construction disturbance data, the structural response data, the support state data and the seepage state data, and outputting a slope unit data set.
3. The intelligent slope safety early warning method for the hydraulic and hydroelectric engineering according to claim 2, wherein the step S2 comprises the following sub-steps: Step S201, construction disturbance data, structure response data, support state data and seepage state data corresponding to each side slope unit in the side slope unit data set are read; step S202, unloading response data and blasting damage data are calculated according to construction disturbance data and structure response data; step S203, calculating support takeover data according to the support state data and the structure response data; step S204, infiltration hysteresis data are calculated according to the seepage state data and the structure response data; and step S205, disturbance response characteristic data are generated according to the unloading response data, the blasting damage data, the support pipe data and the infiltration hysteresis data.
4. The intelligent slope safety early warning method for the hydraulic and hydroelectric engineering according to claim 3, wherein the logic of the step S202 is as follows: Respectively calculating displacement change amplitude and stress change amplitude of each slope unit under the action of excavation position data, and generating unloading response data; respectively calculating a crack change amplitude and a displacement change amplitude of each side slope unit under the action of the bursting strength data to generate bursting damage data; And establishing a corresponding relation among unloading response data, blasting damage data and corresponding slope units, and outputting the corresponding relation to disturbance response characteristic data.
5. The intelligent slope safety early warning method for the hydraulic and hydroelectric engineering according to claim 4, wherein the step S3 comprises the following sub-steps: step S301, disturbance response characteristic data corresponding to each side slope unit are read; Step S302, establishing space association data between adjacent slope units according to the step boundary data and the slope segment number data; step S303, building structure association data between slope units according to the exposed data of the structural surface; Step S304, supporting association data between the slope units are established according to the anchoring state data and the spraying state data; step S305, establishing seepage correlation data among slope units according to rainfall data, seepage pressure data and water content change data; And step S306, connecting disturbance response characteristic data corresponding to each slope unit according to the space association data, the structure association data, the support association data and the seepage association data, and outputting risk transfer chain data.
6. The intelligent slope safety early warning method for the hydraulic and hydroelectric engineering according to claim 5, wherein the logic of the step S306 is as follows: If space association data exists between adjacent slope units, a first transfer relationship is established; If the structure association data exists between the adjacent slope units, a second transfer relationship is established; if support association data weakening transmission exists between adjacent slope units, carrying out attenuation treatment on the first transmission relation or the second transmission relation; If seepage correlation data enhancement transmission exists between adjacent slope units, enhancement processing is carried out on the first transmission relation or the second transmission relation; and generating risk transfer chain data according to the transfer relation after the attenuation processing and the transfer relation after the enhancement processing.
7. The intelligent slope safety early warning method for the hydraulic and hydroelectric engineering according to claim 6, wherein the step S4 comprises the following sub-steps: step S401, reading transmission intensity data and transmission range data corresponding to each slope unit in risk transmission chain data; step S402, judging whether the current side slope unit is in a blasting triggering state, an excavation triggering state or a drainage triggering state according to construction disturbance data; Step S403, judging whether the current side slope unit is in a rainfall triggering state according to the seepage state data; Step S404, marking as triggering window data when the transmission intensity data is larger than a preset transmission threshold value and a blasting triggering state, an excavation triggering state, a drainage triggering state or a rainfall triggering state exist; Step S405, outputting early warning grade data according to the trigger window data and the transmission range data.
8. The intelligent slope safety early warning method for the hydraulic and hydroelectric engineering according to claim 7, wherein the step S5 comprises the following sub-steps: step S501, early warning instruction data is selected according to early warning grade data, wherein the early warning instruction data comprises blasting suspension instruction data, support reinforcement instruction data, drainage treatment instruction data and patrol encryption instruction data; Step S502, if construction disturbance data corresponding to the trigger window data is blasting strength data, outputting blasting suspension instruction data; Step S503, if the supporting state data corresponding to the triggering window data is abnormal anchoring state data or abnormal spraying state data, outputting supporting reinforcement instruction data; Step S504, if the seepage state data corresponding to the trigger window data is abnormal in rainfall data, abnormal in seepage pressure data or abnormal in water content change data, outputting drainage disposal instruction data; Step S505, the early warning instruction data is sent to the control end.
9. The intelligent slope safety early warning method for the hydraulic and hydroelectric engineering according to claim 8, wherein the output logic of the early warning level data is as follows: if the transmission range data corresponding to the trigger window data only covers the current slope unit, outputting first-level early warning data; if the transmission range data corresponding to the triggering window data covers the current slope unit and the adjacent slope unit, outputting second-level early warning data; if the transmission range data corresponding to the trigger window data cover the side slope units corresponding to the plurality of slope segment number data, outputting three-level early warning data; And establishing a corresponding relation between the early warning grade data and the corresponding early warning instruction data, and sending the corresponding early warning instruction data to the control end.
10. The intelligent slope safety early warning system for the hydraulic and hydroelectric engineering is applied to the intelligent slope safety early warning method for the hydraulic and hydroelectric engineering according to any one of claims 1-9, and is characterized by comprising a unit construction module, a feature extraction module, a link generation module, a window identification module and an early warning output module; The unit construction module is used for collecting slope partition data, construction disturbance data, structure response data, support state data and seepage state data and constructing a slope unit data set; the feature extraction module is used for extracting disturbance response feature data corresponding to each slope unit according to the slope unit data set; the link generation module is used for constructing risk transfer link data according to disturbance response characteristic data, and space association data, structure association data, support association data and seepage association data among the slope units; the window identification module is used for identifying trigger window data according to the risk transfer chain data and outputting early warning grade data; the early warning output module is used for generating early warning instruction data according to the trigger window data and the early warning grade data and sending the early warning instruction data to the control end.

Description

Intelligent slope safety early warning method and system for hydraulic and hydroelectric engineering Technical Field The invention relates to the technical field of hydraulic and hydroelectric engineering early warning, in particular to a slope safety intelligent early warning method and system for hydraulic and hydroelectric engineering. Background The hydraulic and hydroelectric engineering has the characteristics of large slope scale, complex slope structure, frequent construction disturbance and changeable environmental influence factors, and particularly has the continuous effects of various factors such as excavation unloading, blasting vibration, rainfall infiltration, support lag, unsmooth slope drainage and the like in the processes of dam foundation excavation, underground factory entrance slope construction, flood discharge tunnel face excavation and diversion system slope remediation. The factors have continuity in time and transitivity in space, so that local abnormality is easily gradually expanded into slope grade risk, and even safety problems such as slump, block dropping or local instability are formed. The existing slope early warning technology is mostly based on single monitoring data such as displacement, cracks, osmotic pressure, rainfall and the like, and the early warning result is output through fixed threshold judgment, comprehensive scoring judgment or conventional model recognition mode. Although the method can reflect the current state of the slope to a certain extent, the method is usually focused on the abnormal identification of a single monitoring point or a single monitoring index, the influence difference of construction disturbance on different areas of the slope is difficult to reflect, and the method is difficult to explain how the abnormality is gradually transferred along the slope structural relationship, the slope section relationship and the seepage action relationship. For a common step-type excavation slope in water conservancy and hydropower engineering, the abnormality of a certain slope section often does not occur in isolation, but a continuous risk evolution process can be formed under the combined actions of blasting disturbance, excavation exposure, support unclosed and rainwater infiltration. Particularly in actual construction sites, the manager really care not only whether a certain monitoring value exceeds a threshold value, but also which side slope unit is currently in a risk amplifying stage, along which path the risk is to be expanded to an adjacent unit, whether the existing support can effectively block the risk transmission, and whether the next blasting, rainfall or drainage abnormality can trigger the side slope to be changed from local abnormality to substantial instability. The prior art generally lacks the targeted treatment to the problems, which results in insufficient connection between the early warning result and the site construction organization, support scheduling and drainage disposal, and is difficult to meet the refined and prospective requirements of the side slope safety early warning under the complex scene of the hydraulic and hydroelectric engineering. Disclosure of Invention The method solves the technical problem that in the prior art, a key slope unit triggering instability, a risk expansion path and corresponding early warning opportunities are difficult to accurately identify aiming at a continuous risk transfer process formed by the hydraulic and hydroelectric engineering slopes under the combined actions of excavation disturbance, blasting effect, rainfall infiltration and support hysteresis. In order to solve the technical problems, the invention provides the following technical scheme: A slope safety intelligent early warning method for hydraulic and hydroelectric engineering comprises the following steps: Step S1, collecting slope partition data, construction disturbance data, structure response data, support state data and seepage state data, and constructing a slope unit data set; s2, extracting disturbance response characteristic data corresponding to each slope unit according to the slope unit data set; Step S3, constructing risk transfer chain data according to disturbance response characteristic data, spatial association data, structure association data, support association data and seepage association data among the slope units; step S4, identifying trigger window data according to the risk transfer chain data and outputting early warning grade data; and S5, generating early warning instruction data according to the trigger window data and the early warning grade data and sending the early warning instruction data to the control end. Preferably, the step S1 includes the following sub-steps: step S101, slope partition data are obtained, wherein the slope partition data comprise step boundary data, slope section number data and structural surface exposure data; Step S102, construction disturbance data are obt