CN115115173B - Dam risk evaluation method under earthquake condition - Google Patents
Dam risk evaluation method under earthquake condition Download PDFInfo
- Publication number
- CN115115173B CN115115173B CN202210530391.2A CN202210530391A CN115115173B CN 115115173 B CN115115173 B CN 115115173B CN 202210530391 A CN202210530391 A CN 202210530391A CN 115115173 B CN115115173 B CN 115115173B
- Authority
- CN
- China
- Prior art keywords
- dam
- processing system
- data processing
- parameter
- earthquake
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/08—Construction
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A10/00—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE at coastal zones; at river basins
- Y02A10/40—Controlling or monitoring, e.g. of flood or hurricane; Forecasting, e.g. risk assessment or mapping
Abstract
The invention relates to the technical field of safety precaution, in particular to a dam risk evaluation method under earthquake conditions, which comprises the following steps: the method comprises the steps of S1, hardware deployment, S2, data acquisition, S3 and data calculation, wherein the data processing system collects acquired data, performs risk assessment, and alarms when the risk is exceeded; when risk assessment is carried out, risk scoring parameters are set, and the values of the risk scoring parameters are determined by the acquired seismic information. According to the method, the dam risk score is calculated when the safety of the dam is evaluated, the data processing system compares the dam risk score with the risk score parameters, so that monitored data are more visual, the accuracy of a monitoring result is improved, meanwhile, the value of the risk score parameters is determined by the earthquake information, after an earthquake occurs, the risk score parameters are continuously adjusted, the operation safety of the dam is evaluated by combining the earthquake information, and the accuracy of post-earthquake evaluation is improved.
Description
Technical Field
The invention relates to the technical field of safety precaution, in particular to a dam risk evaluation method under earthquake conditions.
Background
The dam safety monitoring is to measure and observe the main structure, foundation base, two bank slopes, related facilities and surrounding environment of the hydraulic and hydroelectric engineering through instrument observation and inspection; "monitoring" includes both instrumental observations made at regular intervals at fixed points of a building, and periodic or unscheduled visual inspection and instrumental exploration of a wide range of objects on the exterior and interior of a building.
Chinese patent CN111709465a discloses a method for intelligent identification of gross error of dam safety monitoring data, which does not need to manually formulate evaluation rules and thresholds, and can accurately and efficiently process large-scale multi-type monitoring data. The technical scheme of the invention is as follows: s1, reading dam safety monitoring data to be detected, wherein the data format is [ time, data ]; s2, detecting a monitoring data sequence to be detected by adopting an unsupervised learning algorithm, identifying data with obvious abnormality, and marking suspected gross error data I and possible normal data I; s3, smoothing the possible normal data I by adopting a filtering algorithm, subtracting the smoothed data from the original data to obtain residual errors, detecting the residual errors of the data sequence again by using an unsupervised learning algorithm, identifying the possible abnormal data according to the residual error classification, and marking the suspected gross error data II and the possible normal data II. And (3) current dam monitoring, namely, improving the data quality of model samples through rough difference identification and rough difference processing, and establishing different early warning models and indexes according to monitoring items, independent variable relevance, historical monitoring data quantity and historical monitoring data distribution.
However, the service life of the dam is longer, the dam is likely to experience earthquake and geological disasters in the time of dam operation, and the current dam safety monitoring usually only carries out statistical evaluation on conventional data, and does not consider post-earthquake dam safety evaluation.
Disclosure of Invention
Therefore, the invention provides a dam risk evaluation method under the earthquake condition, which is used for solving the problems that the current dam safety monitoring in the prior art only carries out statistical evaluation on conventional data and does not consider the post-earthquake dam safety evaluation.
In order to achieve the above object, the present invention provides a dam risk evaluation method under seismic conditions, comprising,
s1, hardware deployment, including arranging a plurality of displacement sensors and a plurality of stress detection devices in a dam body to detect deformation displacement conditions and stress conditions of each point of materials in the dam body; a temperature sensor group is arranged on the surface of the bottom of the dam body, a water level detector is arranged on the dam body and used for detecting the water level in the dam, and a data processing system is arranged for carrying out integration judgment on the detected data;
s2, data acquisition, namely transmitting detected data to the data processing system by using the sensors, the detection device and the detector, wherein the data processing system is connected with an external database, and the external database can acquire weather information, upstream drainage information and seismic information and transmit acquisition results to the data processing system;
s3, data calculation and risk assessment are carried out, the data processing system gathers the collected data, risk assessment is carried out, and the data processing system alarms when the risk expectation is exceeded;
when risk assessment is carried out, risk scoring parameters are set, and the values of the risk scoring parameters are determined by the acquired seismic information.
Further, a risk scoring parameter basic value Fa is arranged in the data processing system, when the data processing system acquires the earthquake information from the external database, the data processing system acquires the earthquake intensity Q, the earthquake duration time T and the distance L between the earthquake center and the dam from the earthquake information, the data processing system calculates a risk scoring parameter Fc according to the acquired information,
wherein q is the calculated compensation parameter of the earthquake intensity to the risk scoring parameter, t is the calculated compensation parameter of the earthquake duration to the risk scoring parameter, and l is the calculated compensation parameter of the distance of the earthquake center from the dam to the risk scoring parameter.
The compensation parameters have two functions, namely, the balance calculation dimension and the adjustment calculation result data.
Further, the value of the calculated compensation parameter Q of the seismic intensity versus the risk score parameter is determined by the seismic intensity Q, q=k Q +b, wherein K is the calculated adjustment base value of the compensation parameter q, qb is the base value of the compensation parameter q.
Further, the value of the calculated compensation parameter T of the earthquake duration time to the risk scoring parameter is determined by the earthquake duration time, t=v T +b, wherein V is the calculated adjustment base value of the compensation parameter t, and tb is the base value of the compensation parameter t.
Further, the data processing system is internally provided with a first preset center distance dam distance calculation compensation parameter value L1, a second preset center distance dam distance calculation compensation parameter value L2, a third preset center distance dam distance calculation compensation parameter value L3, a first preset center distance dam distance evaluation parameter L1, a second preset center distance dam distance evaluation parameter L2,
the data processing system compares the distance L of the center of the shake distance dam with a first preset center of the shake distance dam distance evaluation parameter L1 and a second preset center of the shake distance dam distance evaluation parameter L2,
when L is less than or equal to L1, the data processing system selects L1 as the numerical value of the calculated compensation parameter L of the distance between the earthquake center and the dam to the risk scoring parameter;
when L1 is more than L and less than or equal to L2, the data processing system selects L2 as the numerical value of the calculated compensation parameter L of the distance between the earthquake center and the dam to the risk scoring parameter;
when L is more than L2, the data processing system selects L3 as the value of the calculated compensation parameter L of the distance between the earthquake center and the dam and the risk scoring parameter.
Further, when evaluating the safety of the dam, calculating a dam risk score F, F= (F1+F2+F3) x Tg, wherein F1 is a displacement degree score, F2 is a stress degree score, F3 is a water quantity score, and Tg is a correction parameter of the dam operation working time length to the dam risk score;
a risk scoring parameter Fc is arranged in the data processing system, the data processing system compares the dam risk score F with the risk scoring parameter Fc,
when F is less than or equal to Fc, the data processing system judges that the dam risk score is within a safety range;
when F is more than Fc, the data processing system judges that the dam danger score is not in the safety range, and the data processing system alarms.
Further, the stress detection devices are provided with m stress detection devices, which are respectively marked as a first stress detection device and a second stress detection device; each stress detection device detects the stress condition of each point and transmits the detection result to the data processing system, the stress value detected by the first stress detection device is recorded as Y1, the stress value detected by the second stress detection device is recorded as Y2, the stress value detected by the mth stress detection device is recorded as Ym,
for the stress level score F2,
the Yi is the stress value detected by the ith stress detection device, qi is the calculated compensation parameter of the corresponding strength score of Yi, and R is the adjustment parameter of the stress score.
Further, the water level sensor detects a current water level value H1 and transmits a detection result to the data processing system, the data processing system acquires weather information and upstream drainage information, the data processing system predicts a highest water level H2 in a period T1 according to the current water level value H1, the weather information and the upstream drainage information, a standard water level value Hb is arranged in the data processing system, and the data processing system calculates a water level score F3, f3=s (H2-Hb) +Y, wherein S is the water quantity score calculation adjustment parameter, and Y is the water quantity score basic value.
Further, for a displacement score F1, f1=f1c×cw, where F1c is the displacement initial score, cw is the temperature versus displacement score correction parameter,
the displacement degree initial score F1c is determined by the displacement value of each displacement sensor detector;
the temperature versus displacement degree scoring correction parameter Cw is determined from real-time temperature and historical temperature data.
Further, n displacement sensors are provided and are respectively marked as a first displacement sensor, a second displacement sensor and a … … nth displacement sensor;
the displacement detected by each displacement sensor detector is transmitted to the data processing system, the moving distance detected by the first displacement sensor is recorded as L1, the moving distance detected by the second displacement sensor is recorded as L2, the moving distance detected by the third displacement sensor is recorded as L3, the moving distance detected by the nth displacement sensor of … … is recorded as Ln,
the data processing system calculates a displacement degree initial score F1c,
wherein Li is the moving distance detected by the ith displacement sensor, pi is the initial score calculation compensation parameter of the moving distance detected by the ith displacement sensor to the calculated displacement.
Further, the temperature sensor group detects the water temperature in the dam in real time and transmits detected data to the data processing system, and for any moment, the data processing system calculates an average value Wp of all the current temperatures detected by the temperature sensor group and records a calculation result;
the data processing system integrates the water temperature average value data to generate a temperature curve W=f (t), wherein W=f (t) is a time-dependent change curve of the water temperature in the dam, the data processing system calculates a temperature versus displacement degree scoring correction parameter Cw,
wherein Wt is a temperature value at any time on a temperature curve w=f (t) within a detection time period t, c1 is a calculated compensation parameter of a historical water temperature value pair Cw, ws is a current water temperature average value detected by a temperature sensor, and c2 is a calculated compensation parameter of a current water temperature pair Cw.
Compared with the prior art, the method has the beneficial effects that when the safety of the dam is evaluated, the dam risk score is calculated, the data processing system compares the dam risk score with the risk score parameters, so that the monitored data are more visual, the accuracy of the monitoring result is improved, meanwhile, the value of the risk score parameters is determined by the earthquake information, the risk score parameters are continuously adjusted after the earthquake occurs, the operation safety of the dam is evaluated by combining the earthquake information, and the accuracy of the post-earthquake evaluation is improved.
Further, through the earthquake intensity, the earthquake duration and the distance between the earthquake center and the dam are used for correcting the risk scoring parameters, and the longer the risk scoring parameters are, the shorter the earthquake duration is, the smaller the value corrected by the risk scoring parameters is, the operation safety of the dam is evaluated by combining the earthquake information, and the accuracy of post-earthquake evaluation is improved.
In particular, the compensation parameter Q and the earthquake intensity Q are in an exponential growth relation, after the earthquake intensity is increased, the compensation parameter Q is increased exponentially, the larger the earthquake intensity Q is, the larger the damage to a dam body is, the dam operation safety is evaluated by combining the earthquake information, and the accuracy of post-earthquake evaluation is improved.
In particular, the compensation parameter T and the earthquake duration time T are in an exponential growth relation, after the earthquake intensity is increased, the compensation parameter T is increased exponentially, the larger the earthquake duration time T is, the larger the damage to the dam body is, the operation safety of the dam is evaluated by combining the earthquake information, and the accuracy of post-earthquake evaluation is improved.
In particular, the farther the distance between the earthquake center and the dam is, the smaller the damage degree of the earthquake to the dam body is, the numerical value of the compensation parameter l is reduced along with the increase of the distance between the earthquake center and the dam, so that the numerical value is more accurate, the operation safety of the dam is evaluated by combining the earthquake information, and the accuracy of post-earthquake evaluation is improved.
Further, when the safety of the dam is evaluated, the dam risk score is calculated and consists of displacement degree score, stress degree score and water quantity score, the risk score parameter is set in the data processing system, the data processing system compares the dam risk score with the risk score parameter, the safety score is set simultaneously by considering multiparty data, so that the monitored data are more visual, and the accuracy of the monitoring result is improved.
Further, the stress detection devices are arranged in m, each stress detection device detects the stress condition of each point and transmits the detection result to the data processing system, the stress degree is different at different places of the dam, and the accurate stress condition of the dam body can be reasonably and integrally obtained by setting the compensation parameters for the stress of each point, so that the calculation result is more accurate.
Further, the water level sensor detects a current water level value H1 and transmits a detection result to the data processing system, the data processing system obtains weather information and upstream drainage information, and the data processing system predicts a highest water level H2 in a period T1 according to the current water level value H1, the weather information and the upstream drainage information, and the dataA standard water level value Hb is arranged in the processing system, and the data processing system calculates a water quantity score F3, F3=S (H2-Hb) And +Y, the water level condition in a certain time is evaluated by acquiring the external condition in real time, the higher the water level is, the larger the water quantity scoring value is, and the conversion process is exponentially increased, so that dangerous cases are acquired more timely, and the evaluation accuracy is improved.
Further, the displacement degree score consists of a displacement degree initial score and a temperature versus displacement degree score correction parameter, wherein the displacement degree initial score is determined by the displacement value of each displacement sensor detector; the temperature versus displacement degree scoring correction parameters are determined by real-time temperature and historical temperature data; the dam body of the dam is internally provided with a plurality of displacement sensors for detecting displacement conditions of each point in the dam, when the displacement degree is calculated, the displacement degree is adjusted through temperature, the influence of temperature transformation on position transformation of the displacement sensors is reduced, and meanwhile, the influence of self-deformation due to aging is reduced through setting time correction parameters.
Further, the displacement sensors are provided with n displacement sensors, the accurate displacement distance scores are obtained through multipoint monitoring, and different compensation parameters are set for different places, so that the evaluation result is more accurate.
Further, the temperature sensor group detects the water temperature in the dam in real time and transmits detected data to the data processing system, and for any moment, the data processing system calculates the average value of all the current temperatures detected by the temperature sensor group and records the calculated result. The data processing system integrates the water temperature average value data to generate a temperature curve, and when calculating the correction parameters of the temperature and the displacement degree score, the historical water temperature and the real-time water temperature are considered, so that the calculation result is more accurate.
Drawings
FIG. 1 is a flow chart of a dam risk assessment method under seismic conditions according to an embodiment of the present invention.
Detailed Description
In order that the objects and advantages of the invention will become more apparent, the invention will be further described with reference to the following examples; it should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
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 merely for explaining the technical principles of the present invention, and are not intended to limit the scope of the present invention.
It should be noted that, in the description of the present invention, terms such as "upper," "lower," "left," "right," "inner," "outer," and the like indicate directions or positional relationships based on the directions or positional relationships shown in the drawings, which are merely for convenience of description, and do not indicate or imply that the apparatus or elements must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present invention.
Furthermore, it should be noted that, in the description of the present invention, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention can be understood by those skilled in the art according to the specific circumstances.
Referring to fig. 1, fig. 1 is a flowchart of a dam risk evaluation method under seismic conditions according to an embodiment of the invention.
The invention provides a dam risk evaluation method under the condition of earthquake, which comprises the following steps of,
s1, hardware deployment, including arranging a plurality of displacement sensors and a plurality of stress detection devices in a dam body to detect deformation displacement conditions and stress conditions of each point of materials in the dam body; a temperature sensor group is arranged on the surface of the bottom of the dam body, a water level detector is arranged on the dam body and used for detecting the water level in the dam, and a data processing system is arranged for carrying out integration judgment on the detected data;
s2, data acquisition, namely transmitting detected data to the data processing system by using the sensors, the detection device and the detector, wherein the data processing system is connected with an external database, and the external database can acquire weather information, upstream drainage information and seismic information and transmit acquisition results to the data processing system;
s3, data calculation and risk assessment are carried out, the data processing system gathers the collected data, risk assessment is carried out, and the data processing system alarms when the risk expectation is exceeded;
when risk assessment is carried out, risk scoring parameters are set, and the values of the risk scoring parameters are determined by the acquired seismic information.
When the safety of the dam is evaluated, the dam risk score is calculated, the data processing system compares the dam risk score with the risk score parameters, so that monitored data are more visual, the accuracy of a monitoring result is improved, meanwhile, the value of the risk score parameters is determined by earthquake information, after an earthquake occurs, the risk score parameters are continuously adjusted, the operation safety of the dam is evaluated by combining the earthquake information, and the accuracy of post-earthquake evaluation is improved.
Specifically, the data processing system is internally provided with a risk scoring parameter basic value Fa, when the data processing system acquires the earthquake information from the external database, the data processing system acquires the earthquake intensity Q, the earthquake duration time T and the distance L between the earthquake center and the dam from the earthquake information, and calculates a risk scoring parameter Fc according to the acquired information,
wherein q is the calculated compensation parameter of the earthquake intensity to the risk scoring parameter, t is the calculated compensation parameter of the earthquake duration to the risk scoring parameter, and l is the calculated compensation parameter of the distance of the earthquake center from the dam to the risk scoring parameter.
The compensation parameters have two functions, namely, the balance calculation dimension and the adjustment calculation result data.
Through the earthquake intensity, the earthquake duration, the distance between the earthquake center and the dam are used for correcting the risk scoring parameters, and the longer the risk scoring parameters are, the shorter the earthquake duration is, the smaller the value of the corrected risk scoring parameters is, the safety of the operation of the dam is evaluated by combining the earthquake information, and the accuracy of post-earthquake evaluation is improved.
Specifically, the value of the seismic intensity-to-risk score parameter calculated compensation parameter Q is determined by the seismic intensity Q, q=k Q +b, wherein K is the calculated adjustment base value of the compensation parameter q, qb is the base value of the compensation parameter q.
The compensation parameter Q and the earthquake intensity Q are in an exponential growth relation, after the earthquake intensity is increased, the compensation parameter Q is increased exponentially, the larger the earthquake intensity Q is, the larger the damage to the dam body is, the dam operation safety is evaluated by combining the earthquake information, and the accuracy of post-earthquake evaluation is improved.
Specifically, the value of the calculated compensation parameter T of the earthquake duration versus the risk scoring parameter is determined by the earthquake duration T, t=v T +b, wherein V is the calculated adjustment base value of the compensation parameter t, and tb is the base value of the compensation parameter t.
The compensation parameter T and the earthquake duration time T are in an exponential growth relation, after the earthquake intensity is increased, the compensation parameter T is increased exponentially, the larger the earthquake duration time T is, the larger the damage to the dam body is, the dam operation safety is evaluated by combining the earthquake information, and the accuracy of post-earthquake evaluation is improved.
Specifically, the data processing system is internally provided with a first preset center distance dam distance calculation compensation parameter value L1, a second preset center distance dam distance calculation compensation parameter value L2, a third preset center distance dam distance calculation compensation parameter value L3, a first preset center distance dam distance evaluation parameter L1, a second preset center distance dam distance evaluation parameter L2,
the data processing system compares the distance L of the center of the shake distance dam with a first preset center of the shake distance dam distance evaluation parameter L1 and a second preset center of the shake distance dam distance evaluation parameter L2,
when L is less than or equal to L1, the data processing system selects L1 as the numerical value of the calculated compensation parameter L of the distance between the earthquake center and the dam to the risk scoring parameter;
when L1 is more than L and less than or equal to L2, the data processing system selects L2 as the numerical value of the calculated compensation parameter L of the distance between the earthquake center and the dam to the risk scoring parameter;
when L is more than L2, the data processing system selects L3 as the value of the calculated compensation parameter L of the distance between the earthquake center and the dam and the risk scoring parameter.
The further the distance between the earthquake center and the dam is, the smaller the damage degree of the earthquake to the dam body is, the numerical value of the compensation parameter l is reduced along with the increase of the distance between the earthquake center and the dam, so that the numerical value is more accurate, the operation safety of the dam is evaluated by combining the earthquake information, and the accuracy of post-earthquake evaluation is improved.
Specifically, when evaluating the safety of a dam, calculating a dam risk score F, F= (F1+F2+F3) x Tg, wherein F1 is a displacement degree score, F2 is a stress degree score, F3 is a water quantity score, and Tg is a correction parameter of the dam operation working time length to the dam risk score;
a risk scoring parameter Fc is arranged in the data processing system, the data processing system compares the dam risk score F with the risk scoring parameter Fc,
when F is less than or equal to Fc, the data processing system judges that the dam risk score is within a safety range;
when F is more than Fc, the data processing system judges that the dam danger score is not in the safety range, and the data processing system alarms.
When the safety of the dam is evaluated, calculating a dam risk score, wherein the dam risk score consists of a displacement degree score, a stress degree score and a water quantity score, a risk score parameter is arranged in a data processing system, the data processing system compares the dam risk score with the risk score parameter, the safety score is set by considering multiparty data, so that the monitored data is more visual, and the accuracy of a monitoring result is improved.
Specifically, m stress detection devices are provided, and are respectively named as a first stress detection device, a second stress detection device; each stress detection device detects the stress condition of each point and transmits the detection result to the data processing system, the stress value detected by the first stress detection device is recorded as Y1, the stress value detected by the second stress detection device is recorded as Y2, the stress value detected by the mth stress detection device is recorded as Ym,
for the stress level score F2,
the Yi is the stress value detected by the ith stress detection device, qi is the calculated compensation parameter of the corresponding strength score of Yi, and R is the adjustment parameter of the stress score.
The stress detection devices are arranged in number of m, each stress detection device detects the stress condition of each point and transmits the detection results to the data processing system, the stress degree is different at different places of the dam, and the accurate stress condition of the dam body can be reasonably and integrally obtained by setting compensation parameters for stress of each point, so that the calculation result is more accurate.
Specifically, the water level sensor detects a current water level value H1 and transmits the detection result to the data processing system, the data processing system acquires weather information and upstream drainage information, the data processing system predicts a highest water level H2 in a period T1 according to the current water level value H1, the weather information and the upstream drainage information, a standard water level value Hb is arranged in the data processing system, and the data processing system calculates a water level score F3, f3=s (H2-Hb) +Y, wherein S is the water quantity score calculation adjustment parameter, and Y is the water quantity score basic value.
The water level sensor detects a current water level value H1 and transmits a detection result to the data processing system, the data processing system acquires weather information and upstream drainage information, the data processing system predicts the highest water level H2 in a period T1 according to the current water level value H1, the weather information and the upstream drainage information, a standard water level value Hb is arranged in the data processing system, and the data processing system calculates a water level score F3, F3=S (H2-Hb) By acquiring the external conditions in real time, the water level condition in a certain time is estimated, the higher the water level is, the larger the water quantity scoring value is, and the conversion process is exponentially increased, so that the dangerous case is causedThe acquisition is more timely, and the evaluation accuracy is improved.
Specifically, for a displacement degree score F1, f1=f1c×cw, where F1c is the displacement degree initial score, cw is the temperature versus displacement degree score correction parameter,
the displacement degree initial score F1c is determined by the displacement value of each displacement sensor detector;
the temperature versus displacement degree scoring correction parameter Cw is determined from real-time temperature and historical temperature data.
The displacement degree score consists of a displacement degree initial score and a temperature-to-displacement degree score correction parameter, wherein the displacement degree initial score is determined by the displacement value of each displacement sensor detector; the temperature versus displacement degree scoring correction parameters are determined by real-time temperature and historical temperature data; the dam body of the dam is internally provided with a plurality of displacement sensors for detecting displacement conditions of each point in the dam, when the displacement degree is calculated, the displacement degree is adjusted through temperature, the influence of temperature transformation on position transformation of the displacement sensors is reduced, and meanwhile, the influence of self-deformation due to aging is reduced through setting time correction parameters.
Specifically, n displacement sensors are provided and are respectively marked as a first displacement sensor, a second displacement sensor and a … … nth displacement sensor;
the displacement detected by each displacement sensor detector is transmitted to the data processing system, the moving distance detected by the first displacement sensor is recorded as L1, the moving distance detected by the second displacement sensor is recorded as L2, the moving distance detected by the third displacement sensor is recorded as L3, the moving distance detected by the nth displacement sensor of … … is recorded as Ln,
the data processing system calculates a displacement degree initial score F1c,
wherein Li is the moving distance detected by the ith displacement sensor, pi is the initial score calculation compensation parameter of the moving distance detected by the ith displacement sensor to the calculated displacement.
The displacement sensors are provided with n displacement sensors, the displacement sensors are monitored at multiple points, accurate displacement distance scores are obtained, and different compensation parameters are set for different places, so that the evaluation result is more accurate.
Specifically, the temperature sensor group detects the water temperature in the dam in real time and transmits detection data to the data processing system, and for any moment, the data processing system calculates the average value Wp of all the current temperatures detected by the temperature sensor group and records the calculation result.
The data processing system integrates the water temperature average value data to generate a temperature curve W=f (t), wherein W=f (t) is a time-dependent change curve of the water temperature in the dam, the data processing system calculates a temperature versus displacement degree scoring correction parameter Cw,
wherein Wt is a temperature value at any time on a temperature curve w=f (t) within a detection time period t, c1 is a calculated compensation parameter of a historical water temperature value pair Cw, ws is a current water temperature average value detected by a temperature sensor, and c2 is a calculated compensation parameter of a current water temperature pair Cw.
The temperature sensor group detects the water temperature in the dam in real time and transmits the detected data to the data processing system, and for any moment, the data processing system calculates the average value of all the current temperatures detected by the temperature sensor group and records the calculated result. The data processing system integrates the water temperature average value data to generate a temperature curve, and when calculating the correction parameters of the temperature and the displacement degree score, the historical water temperature and the real-time water temperature are considered, so that the calculation result is more accurate.
Thus far, the technical solution of the present invention has been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of protection of the present invention is not limited to these specific embodiments. Equivalent modifications and substitutions for related technical features may be made by those skilled in the art without departing from the principles of the present invention, and such modifications and substitutions will be within the scope of the present invention.
Claims (1)
1. A dam risk evaluation method under earthquake conditions is characterized by comprising the following steps of,
s1, hardware deployment, including arranging a plurality of displacement sensors and a plurality of stress detection devices in a dam body to detect deformation displacement conditions and stress conditions of each point of materials in the dam body; a temperature sensor group is arranged on the surface of the bottom of the dam body, a water level detector is arranged on the dam body and used for detecting the water level in the dam, and a data processing system is arranged for carrying out integration judgment on the detected data;
s2, data acquisition, namely transmitting detected data to the data processing system by using the sensors, the detection device and the detector, wherein the data processing system is connected with an external database, and the external database can acquire weather information, upstream drainage information and seismic information and transmit acquisition results to the data processing system;
s3, data calculation and risk assessment are carried out, the data processing system gathers the collected data, risk assessment is carried out, and the data processing system alarms when the risk expectation is exceeded;
setting risk scoring parameters when risk assessment is carried out, wherein the values of the risk scoring parameters are determined by the acquired seismic information;
the data processing system is internally provided with a risk scoring parameter basic value Fa, when the data processing system acquires the earthquake information from the external database, the data processing system acquires the earthquake intensity Q, the earthquake duration time T and the distance L between the earthquake center and the dam from the earthquake information, and calculates a risk scoring parameter Fc according to the acquired information,
wherein q is the calculated compensation parameter of the earthquake intensity to the risk scoring parameter, t is the calculated compensation parameter of the earthquake duration to the risk scoring parameter, and l is the calculated compensation parameter of the distance between the earthquake center and the dam to the risk scoring parameter;
the value of the seismic intensity-to-risk scoring parameter calculated compensation parameter Q is determined by the seismic intensity Q, q=k Q +b, wherein K is a calculated adjustment basic value of the compensation parameter q, qb is a basic value of the compensation parameter q;
the value of the calculated compensation parameter T of the earthquake duration time to the danger scoring parameter is determined by the earthquake duration time T, and t=V T +b, wherein V is the calculated adjustment basic value of the compensation parameter t, and tb is the basic value of the compensation parameter t;
the data processing system is internally provided with a calculated compensation parameter value L1 of a first preset earthquake center distance dam distance to a risk scoring parameter, a calculated compensation parameter value L2 of a second preset earthquake center distance dam distance to a risk scoring parameter, a calculated compensation parameter value L3 of a third preset earthquake center distance dam distance to a risk scoring parameter, a first preset earthquake center distance dam distance evaluation parameter L1, a second preset earthquake center distance dam distance evaluation parameter L2,
the data processing system compares the distance L of the center of the shake distance dam with a first preset center of the shake distance dam distance evaluation parameter L1 and a second preset center of the shake distance dam distance evaluation parameter L2,
when L is less than or equal to L1, the data processing system selects L1 as the numerical value of the calculated compensation parameter L of the distance between the earthquake center and the dam to the risk scoring parameter;
when L1 is more than L and less than or equal to L2, the data processing system selects L2 as the numerical value of the calculated compensation parameter L of the distance between the earthquake center and the dam to the risk scoring parameter;
when L is more than L2, the data processing system selects L3 as the numerical value of the calculated compensation parameter L of the distance between the earthquake center and the dam to the risk scoring parameter;
calculating dam risk scores F, F= (F1+F2+F3) x Tg when evaluating the safety of the dam, wherein F1 is displacement degree score, F2 is stress degree score, F3 is water quantity score, and Tg is a correction parameter of dam operation working time length to dam risk score;
a risk scoring parameter Fc is arranged in the data processing system, the data processing system compares the dam risk score F with the risk scoring parameter Fc,
when F is less than or equal to Fc, the data processing system judges that the dam risk score is within a safety range;
when F is more than Fc, the data processing system judges that the dam risk score is not in a safety range, and the data processing system alarms;
the stress detection devices are respectively marked as a first stress detection device and a second stress detection device, and the number of the stress detection devices is m; each stress detection device detects the stress condition of each point and transmits the detection result to the data processing system, the stress value detected by the first stress detection device is recorded as Y1, the stress value detected by the second stress detection device is recorded as Y2, the stress value detected by the mth stress detection device is recorded as Ym,
for the stress level score F2,
the stress detection device is used for detecting the stress value of the stress, wherein Yi is a calculated compensation parameter of the corresponding strength score of Yi, and R is an adjustment parameter of the stress score;
the water level sensor detects a current water level value H1 and transmits a detection result to the data processing system, the data processing system acquires weather information and upstream drainage information, the data processing system predicts the highest water level H2 in a period T1 according to the current water level value H1, the weather information and the upstream drainage information, a standard water level value Hb is arranged in the data processing system, and the data processing system calculates a water level score F3, F3=S (H2-Hb) S is a water quantity grading calculation adjustment parameter, and Y is a water quantity grading basic value;
for a displacement score F1, f1=f1c×cw, where F1c is the displacement initial score, cw is the temperature versus displacement score correction parameter,
the displacement degree initial score F1c is determined by the displacement value of each displacement sensor detector;
the temperature-to-displacement degree scoring correction parameter Cw is determined by real-time temperature and historical temperature data;
the number of the displacement sensors is n, and the displacement sensors are respectively recorded as a first displacement sensor, a second displacement sensor and a … … nth displacement sensor;
the displacement detected by each displacement sensor detector is transmitted to the data processing system, the moving distance detected by the first displacement sensor is recorded as L1, the moving distance detected by the second displacement sensor is recorded as L2, the moving distance detected by the third displacement sensor is recorded as L3, the moving distance detected by the nth displacement sensor of … … is recorded as Ln,
the data processing system calculates a displacement degree initial score F1c,
wherein Li is the moving distance detected by the ith displacement sensor, pi is the initial score calculation compensation parameter of the moving distance pair calculated displacement degree detected by the ith displacement sensor;
the temperature sensor group detects the water temperature in the dam in real time and transmits detected data to the data processing system, and for any moment, the data processing system calculates the average value Wp of all the current temperatures detected by the temperature sensor group and records the calculation result;
the data processing system integrates the water temperature average value data to generate a temperature curve W=f (t), wherein W=f (t) is a time-dependent change curve of the water temperature in the dam, the data processing system calculates a temperature versus displacement degree scoring correction parameter Cw,
wherein Wt is a temperature value at any time on a temperature curve w=f (t) within a detection time period t, c1 is a calculated compensation parameter of a historical water temperature value pair Cw, ws is a current water temperature average value detected by a temperature sensor, and c2 is a calculated compensation parameter of a current water temperature pair Cw. />
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210530391.2A CN115115173B (en) | 2022-05-16 | 2022-05-16 | Dam risk evaluation method under earthquake condition |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210530391.2A CN115115173B (en) | 2022-05-16 | 2022-05-16 | Dam risk evaluation method under earthquake condition |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115115173A CN115115173A (en) | 2022-09-27 |
| CN115115173B true CN115115173B (en) | 2023-05-05 |
Family
ID=83326977
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210530391.2A Active CN115115173B (en) | 2022-05-16 | 2022-05-16 | Dam risk evaluation method under earthquake condition |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115115173B (en) |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104482991A (en) * | 2014-12-10 | 2015-04-01 | 青岛理工大学 | Parameter measuring and early warning method for determining dangerous dam body safe reservoir water level |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103292762B (en) * | 2013-05-23 | 2016-08-03 | 青岛理工大学 | Differentiate the displacement monitoring method of dam stability |
| CN112287608B (en) * | 2020-11-19 | 2023-11-24 | 中国水利水电科学研究院 | Dam safety prediction system and method based on fuzzy comprehensive evaluation |
-
2022
- 2022-05-16 CN CN202210530391.2A patent/CN115115173B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104482991A (en) * | 2014-12-10 | 2015-04-01 | 青岛理工大学 | Parameter measuring and early warning method for determining dangerous dam body safe reservoir water level |
Non-Patent Citations (1)
| Title |
|---|
| 秦朋 ; 谭恺炎 ; 张志奎 ; 张金杰 ; 刘国彦 ; .运行期大坝安全评价.大坝与安全.2016,(05),全文. * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115115173A (en) | 2022-09-27 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114882689B (en) | Dam safety detection early warning method based on big data | |
| CN111504268B (en) | Intelligent early warning and forecasting method for dangerous case of soil slope | |
| CN106198924B (en) | Precarious rock mass monitoring system and its methods of risk assessment based on adaptive frequency acquisition | |
| CN109298697A (en) | Thermal power plant's various parts working state evaluation method based on DBM Dynamic Baseline Model | |
| US9009001B2 (en) | Monitoring for invalid data from field instruments | |
| KR102169452B1 (en) | METHOD FOR ENSURING STABILITY OF DATA COLLECTED IN IoT WEATHER ENVIRONMENT | |
| CN103631145B (en) | Multiple operating modes process monitoring method and system based on monitor control index switching | |
| CN108257365B (en) | Industrial alarm design method based on global uncertainty evidence dynamic fusion | |
| KR102325991B1 (en) | Intelligent asset management system for wastewater treatment facilities and the operation method using it | |
| CN111307110A (en) | Personnel positioning system in foundation pit construction and risk assessment method | |
| CN113177646B (en) | Power distribution equipment online monitoring method and system based on self-adaptive edge proxy | |
| CN114689994A (en) | System and method for online positioning and monitoring fault of transmission line | |
| CN113155196A (en) | Bridge operation real-time monitoring system based on AIoT and monitoring method thereof | |
| CN115115173B (en) | Dam risk evaluation method under earthquake condition | |
| KR102582180B1 (en) | Small river smart prediction management system using accumulated data and its method | |
| CN115112167A (en) | Temperature and humidity sensor early warning system and method applied to production area of cigarette factory | |
| CN110455370B (en) | Flood-prevention drought-resisting remote measuring display system | |
| CN110131784B (en) | Thermal heating system and all-day temperature deviation accumulation leakage detection method thereof | |
| CN115078239B (en) | Reinforcing steel bar corrosion data acquisition unit, monitoring subsystem, regional system and monitoring system | |
| CN116046079B (en) | Geological environment thematic data integrated management system based on position | |
| CN117592013B (en) | Real-time risk rate quantification and early warning method for deformation of sluice building | |
| CN115980890B (en) | Rainfall station abnormal data detection method based on space-time elements | |
| CN116990847B (en) | Beidou GNSS receiver resolving method and system based on edge calculation | |
| CN116878592B (en) | Water conservancy project main dam upstream surface slope protection safety detection system and detection method | |
| CN113727322B (en) | Emergency rescue auxiliary device and method based on Beidou positioning |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |