CN115218961A - High-efficiency hydraulic dam safety early warning system - Google Patents
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Abstract
The invention relates to the field of dam safety early warning, in particular to a high-efficiency hydraulic dam safety early warning system, which is characterized in that a data acquisition module, a data storage module and a data processing module are arranged to acquire the humidity, the temperature osmotic pressure and the osmotic pressure around a monitored dam in real time, the characteristic information and historical data of a plurality of dams are stored in the data storage module, a safety evaluation coefficient is calculated through the data processing module and is compared with a preset threshold value to send out early warning, the data processing module divides similar dams according to the characteristic information of the dams, selects a comparison dam among the similar dams of the monitored dams, corrects the first preset threshold value according to the historical data of the comparison dams and the similar level of the characteristic information, divides the similar dams, intervenes the current monitoring precision by considering the historical data of the similar dams, adjusts the intervention quantity according to the similar level, effectively predicts the safety risk, achieves the effect of early warning in advance, and improves the accuracy of the dam safety early warning.
Description
Technical Field
The invention relates to the field of dam safety early warning, in particular to a high-efficiency safety early warning system for a hydraulic dam.
Background
The dam is an important component in a national protection engineering system, has obvious benefits in the aspects of industrial and drinking water supply, agricultural irrigation, power generation and the like, and is an important problem related to the development of people on how to ensure the healthy operation of the built and to-be-built dams under the action of various external forces. The dam safety monitoring system is an effective means for people to know the running state and the safety condition of the dam and is one of important measures for ensuring the safe running of the dam;
the patent document with chinese patent publication No. CN106918365A discloses that the prediction of dam safety by using model combination includes a model base establishment module, a weight determination module, a combination determination module and an evaluation module, where the model base establishment module is used to establish an alternative model base, which includes a plurality of monitoring models, the weight determination module is used to set weights for each monitoring model in the alternative model base, the combination determination module is used to determine an optimal model combination related to each monitoring model according to the weights, and the evaluation module is used to evaluate the optimal model combination performance. The beneficial effects of the invention are as follows: and the high-reliability safety monitoring of the dam is realized.
However, the following problems still exist in the prior art:
1. the application of historical data in dam safety monitoring is less;
2. the accuracy of safety early warning is not corrected in dam safety monitoring;
in actual conditions, because the influence factors of dam evaluation are diverse, the interference of the current early warning precision by using similar dam operation parameters and historical operation parameters is very necessary, when the similar dam has operation risks, the current environmental parameters are acquired, the interference of the current early warning precision is combined with the monitoring of the real-time environmental parameters of the dam, the safety risk can be effectively predicted, and the early warning effect is achieved.
Disclosure of Invention
In order to solve the above problems, the present invention provides an efficient safety early warning system for a hydraulic dam, comprising:
the system comprises a data acquisition module, a data acquisition module and a data processing module, wherein the data acquisition module comprises a temperature sensor, a humidity sensor, a plurality of osmotic pressure sensors and a plurality of seepage flow sensors which are arranged around a monitoring dam and is used for monitoring the ambient temperature, the ambient humidity, the dam osmotic pressure and the dam seepage flow of the monitoring dam in real time;
the data storage module is connected with the cloud data platform, and the data storage module stores characteristic information and historical data of a plurality of dams;
the data processing module is connected with the data acquisition module and the data processing module and completes data exchange, calculates a safety evaluation coefficient A in real time according to the ambient temperature, the ambient humidity, the seepage flow and the osmotic pressure around the monitoring dam, and sends out an early warning when the safety evaluation coefficient A is larger than a first preset threshold A1;
and the data processing module divides similar dams according to the characteristic information of the dams, selects a comparison dam from the similar dams of the monitoring dams, and corrects the first preset threshold according to historical data of the comparison dam and the similar level of the characteristic information.
Further, the data processing module calculates a safety evaluation coefficient A according to the following formula based on the data acquired by the data acquisition module,
wherein: a represents T to represent the ambient temperature around the monitoring dam, T0 represents a preset ambient temperature contrast value, C represents the ambient humidity around the monitoring dam, C0 represents a preset ambient humidity contrast value, P represents the current seepage rate of the monitoring dam, P0 represents a preset seepage rate contrast value, L represents the current osmotic pressure of the monitoring dam, and L0 represents a preset osmotic pressure contrast value;
the data processing module compares the safety evaluation coefficient A with a first preset threshold value A1,
and when A is larger than A1, the data processing module sends out early warning information.
Further, the data storage module stores characteristic information of a plurality of dams in advance, wherein the characteristic information comprises water storage capacity information, length information, average dam height information, average dam thickness information, monthly average rainfall information of a local area and monthly average temperature information of the local area;
the data processing module divides similar dams according to the characteristic information of the dams, compares the characteristic information of each dam, judges that the dams are similar when the difference percentage K between the characteristic information corresponding to any two dams in a plurality of dams is smaller than a preset difference percentage K0, stores the characteristic sets of the similar dams into the same information set to form a plurality of similar dam information sets, and calculates the difference percentage K according to the following formula,
wherein b1 (x) represents the xth information in the first dam corresponding characteristic information, and b2 (x) represents the xth information in the second dam corresponding characteristic information.
Furthermore, discrete contrast parameters F1 and F2 are preset in the data processing module, wherein F1 is more than 0 and less than F2, the data processing module calculates the discrete parameter F of any characteristic information in the similar dam information set according to the following formula,
b1 represents the water storage capacity information in any characteristic information, B2 represents the length information in any characteristic information, B3 represents the average height information of the dam body in any characteristic information, B4 represents the average thickness information of the dam body in any characteristic information, B5 represents the average rainfall information of the region in which the characteristic information is located, B6 represents the average temperature information of the dam body in any characteristic information, B10 represents the average value of the water storage capacity information corresponding to all the characteristic information in the similar dam information set, B20 represents the average value of the length information corresponding to all the characteristic information in the similar dam information set, B30 represents the average value of the average height information of the dam body corresponding to all the characteristic information in the similar dam information set, B40 represents the average thickness information of the dam body corresponding to all the characteristic information in the dam information set, B50 represents the average value of the average rainfall information corresponding to all the characteristic information in the dam information set, and B60 represents the average value of the average temperature information of the dam information set;
the data processing module classifies similar grades for the characteristic information according to the discrete parameters F corresponding to the characteristic information of the similar dam information set, wherein,
for any feature information within the set Bi of similar dams,
when the F is more than or equal to the F2, the data processing module divides the characteristic information into a first similar grade;
when F1 is not more than F and is less than F2, the data processing module divides the characteristic information into a second similar grade;
and when F is less than F1, the data processing module divides the characteristic information into a third similarity grade.
Furthermore, a second preset threshold value A2 is preset in the data processing module, A2 is less than A1, the data processing module calculates a safety evaluation coefficient A corresponding to the dam in real time according to the data acquired by the data acquisition module,
when the safety evaluation coefficient A corresponding to the dam is larger than the second preset threshold A2, the data processing module retrieves from the data storage module and judges whether the dam has a similar dam or not, wherein,
if the dam has a similar dam, correcting the first preset threshold value;
and if the dam does not have a similar dam, not correcting the first preset threshold value.
Further, the data processing module corrects the first preset threshold, when a comparison dam is selected from the similar dams of the monitoring dams, calls a similar dam information set for storing feature information corresponding to the monitoring dams, judges whether a situation that a safety evaluation coefficient A is larger than a second preset threshold A2 exists in historical data corresponding to the similar dams of the monitoring dams, marks the corresponding similar dams if the situation exists, differentiates discrete parameters corresponding to the feature information of the marked similar dams from discrete parameters corresponding to the feature information of the monitoring dams if the quantity of the marked similar dams is larger than 2, selects the similar dam corresponding to the discrete parameter with the smallest difference as the comparison dam, calls humidity, temperature, seepage flow and seepage pressure of the ambient environment of the comparison dam when the historical maximum value Amax of the safety evaluation coefficient A exists in the comparison dam, calculates the contact ratio of the comparison dam and the similar dams, and determines the first preset threshold according to the correction amount and the similar grades of the monitoring dams.
Further, the data processing module calculates the contact ratio E according to the following formula according to the humidity, the temperature, the seepage flow and the seepage pressure of the environment around the comparison dam and the humidity, the temperature, the seepage flow and the seepage pressure of the current environment of the monitoring dam,
wherein T1 represents the current ambient temperature of the monitoring dam, T2 represents the called ambient temperature of the comparison dam, C1 represents the current ambient humidity of the monitoring dam, C2 represents the called ambient humidity of the comparison dam, P1 represents the current seepage flow of the monitoring dam, P2 represents the called seepage flow of the comparison dam, L1 represents the current seepage pressure of the monitoring dam, and L2 represents the called seepage pressure of the comparison dam;
when E is larger than or equal to E2, the data processing module corrects the first preset threshold A1 to A1', and sets A1' = A1- (A01 +. DELTA.A.times.alpha.);
when E1 is not less than E and less than E2, the data processing module corrects the first preset threshold value A1 to A1', and sets A1' = A1- (A02 +. DELTA.A × alpha);
when E < E1, the data processing module corrects the first preset threshold value A1 to A1', and sets A1' = A1- (A03 +. DELTA.A.times.alpha.);
wherein E1 represents a preset first coincidence degree comparison parameter, E2 represents a preset second coincidence degree comparison parameter, a01 represents a first preset correction amount, a02 represents a second preset correction amount, a03 represents a third preset correction amount, a03 > a02 > a01, α is a variation parameter, and Δ a = Amax-A1.
Further, the data processing module determines alpha according to the calculation parameters corresponding to the similar grades of the comparison dam and the monitoring dam, and sets the calculation parameter corresponding to the first similar grade to be 1, the calculation parameter corresponding to the second similar grade to be 2, the calculation parameter corresponding to the third similar grade to be 3 when determining,
when the sum of the corresponding calculation parameters of the comparison dam and the monitoring dam in the similar grades is equal to 2, alpha is 0.5, when the comparison dam and the monitoring dam in the similar grades are the same and the sum of the corresponding calculation parameters of the similar grades is equal to 4 or 6, alpha is 0.4, when the comparison dam and the monitoring dam in the similar grades are different and the sum of the corresponding calculation parameters of the similar grades is equal to 3 or 5, alpha is 0.3, and when the comparison dam and the monitoring dam in the similar grades are different and the sum of the corresponding calculation parameters of the similar grades is equal to 4, alpha is 0.2.
Further, the historical data stored in the data processing module includes the safety evaluation coefficient a corresponding to each moment of each dam, and the ambient environment humidity, ambient environment temperature, seepage flow rate and seepage pressure of each dam corresponding to each moment.
Further, the cloud data platform updates characteristic information and historical data of each dam at preset time intervals.
Compared with the prior art, the method has the advantages that the data acquisition module, the data storage module and the data processing module are arranged to acquire the humidity, the temperature osmotic pressure and the osmotic pressure around the monitored dam in real time, the characteristic information and the historical data of a plurality of dams are stored in the data storage module, the data processing module is used for calculating the safety evaluation coefficient and comparing the safety evaluation coefficient with the preset threshold value to send out early warning, the data processing module is used for dividing the similar dams according to the characteristic information of the dams, selecting the comparison dams from the similar dams of the monitored dams, correcting the first preset threshold value according to the historical data of the comparison dams and the similar grade of the characteristic information, and interfering the current monitoring precision by dividing the similar dams, considering the historical data of the similar dams, adjusting the intervention amount according to the similar grade, effectively predicting the safety risk, achieving the effect of early warning and improving the accuracy of dam safety monitoring and early warning.
Particularly, the characteristic data and the historical data of the dams are stored in the data storage module, the stored characteristic data has representation on the characteristics of the dams, the similar dams are divided in an information difference mode, different dams can be effectively distinguished, when the first preset threshold value is corrected, the similar dams serve as the reference, data interference of the dissimilar dams can be effectively avoided, the intervention effect is more accurate, and the accuracy of monitoring and early warning is further improved.
Particularly, the characteristic data of the similar dam are stored in the data set of the similar dam through the data processing module, data processing is facilitated, meanwhile, the similarity degree can be better distinguished in the data set of the similar dam through calculation of the discrete parameter F, the similar dam is divided again, division is better and more accurate, the intervention effect is better and more accurate, early warning is accurately sent in advance, and the accuracy of dam safety monitoring is improved.
Particularly, the data processing module of the invention sets a second preset threshold which is smaller than the first preset threshold, corrects the early warning precision when the early warning standard is not reached, intervenes the monitoring precision by using the historical data of the similar dam, and further effectively predicts the safety risk, achieves the effect of early warning in advance and improves the accuracy of the dam safety monitoring early warning.
Particularly, when the comparison dam is selected, the data processing module selects according to the condition that whether the safety evaluation coefficient in the historical data exceeds the second preset threshold value, calls the corresponding environmental data at the moment, compares the corresponding environmental data with the current environmental data to select the correction parameter, and further selects the more similar environmental data to compare the more similar environmental data on the basis of the similar dam, so that the intervention on the current early warning precision is better and more accurate, the risk can be effectively predicted, and the accuracy of dam safety monitoring and early warning is improved.
Drawings
Fig. 1 is a schematic diagram of a high-efficiency hydraulic dam safety early warning system provided in an embodiment of the present invention;
fig. 2 is a logic diagram illustrating a first threshold value of the high-efficiency hydraulic dam safety early warning system according to an embodiment of the present invention.
Detailed Description
In order that the objects and advantages of the invention will be more clearly understood, the invention is further described below with reference to examples; it should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit 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 only for explaining the technical principle of the present invention, and do not limit the scope of the present invention.
It should be noted that in the description of the present invention, the terms of direction or positional relationship indicated by the terms "upper", "lower", "left", "right", "inner", "outer", etc. are based on the directions or positional relationships shown in the drawings, which are only for convenience of description, and do not indicate or imply that the device or element 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 otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
Example 1
Referring to fig. 1, which is a schematic view of a high-efficiency safety early warning system for a hydraulic dam according to the present embodiment, the high-efficiency safety monitoring system for a dam of the present invention includes:
the system comprises a data acquisition module, a data acquisition module and a data processing module, wherein the data acquisition module comprises a temperature sensor, a humidity sensor, a plurality of osmotic pressure sensors and a plurality of seepage flow sensors which are arranged around a monitoring dam and is used for monitoring the ambient temperature, the ambient humidity, the dam osmotic pressure and the dam seepage flow of the monitoring dam in real time;
the data storage module is connected with the cloud data platform, and the data storage module stores characteristic information and historical data of a plurality of dams;
the data processing module is connected with the data acquisition module and the data processing module, completes data exchange, calculates a safety evaluation coefficient A in real time according to the ambient temperature, the ambient humidity, the seepage flow and the osmotic pressure around the monitoring dam, and sends out early warning when the safety evaluation coefficient A is larger than a first preset threshold value A1;
and the data processing module divides similar dams according to the characteristic information of the dams, selects a comparison dam from the similar dams of the monitoring dams, and corrects the first preset threshold according to historical data of the comparison dam and the similar level of the characteristic information.
Specifically, the specific forms of the data storage module and the data processing module are not limited, and the data processing module is mature prior art, the data processing module can be a database and only needs to store data, and the data processing module can be a computer and only needs to complete data receiving and data sending.
Specifically, the sensor layout mode is not limited, and the sensor layout mode is also mature prior art, and only needs to be in accordance with the cognition of the technical personnel in the field and can exert the function of monitoring the corresponding data.
Specifically, the data processing module calculates a safety evaluation coefficient A according to the following formula based on the data acquired by the data acquisition module,
wherein: a represents T to represent the ambient temperature around the monitoring dam, T0 represents a preset ambient temperature contrast value, C represents the ambient humidity around the monitoring dam, C0 represents a preset ambient humidity contrast value, P represents the current seepage rate of the monitoring dam, P0 represents a preset seepage rate contrast value, L represents the current osmotic pressure of the monitoring dam, and L0 represents a preset osmotic pressure contrast value;
the data processing module compares the safety evaluation coefficient A with a first preset threshold value A1,
and when A is larger than A1, the data processing module sends out early warning information.
Specifically, according to the invention, for the selection of the preset ambient temperature contrast value T0, the preset ambient humidity contrast value C0, the preset seepage flow contrast value P0 and the preset osmotic pressure contrast value L0, seepage flow and osmotic pressure born by different dams are set according to different dams and are used as the preset seepage flow pair inhibition PO and the preset osmotic pressure contrast value L0, and for the preset temperature contrast value T and the preset humidity contrast value C0, the annual average temperature of the dam in the current year and the annual average humidity of the dam in the current year are monitored through big data acquisition.
Specifically, the data storage module stores characteristic information of a plurality of dams in advance, wherein the characteristic information comprises water storage capacity information, length information, average dam height information, average dam thickness information, monthly average rainfall information of a local area and monthly average temperature information of the local area;
the data processing module divides similar dams according to the feature information of the dams, compares the feature information of each dam, judges that the dams are similar when the difference percentage K between the feature information corresponding to any two dams in the dams is smaller than a preset difference percentage K0, stores the feature sets of the similar dams into the same information set to form a plurality of similar dam information sets, and calculates the difference percentage K according to the following formula,
the information processing method comprises the steps that b1 (x) represents the x-th information in the characteristic information corresponding to the first dam, b2 (x) represents the x-th information in the characteristic information corresponding to the second dam, for example, the first information in the characteristic information is water storage capacity information, the second information in the characteristic information is length information, and the like, and six information in the characteristic information is monthly average temperature information of a region where the information is located.
Specifically, the characteristic data and the historical data of a plurality of dams are stored in the data storage module, the stored characteristic data have representation performance on the characteristics of the dams, the similar dams are divided in an information difference mode, different dams can be effectively distinguished, when a first preset threshold value is corrected, the similar dams serve as the reference, data interference of dissimilar dams can be effectively avoided, the interference effect is more accurate, and the accuracy of monitoring and early warning is further improved.
Specifically, discrete contrast parameters F1 and F2 are preset in the data processing module, wherein F1 is more than 0 and less than F2, the data processing module calculates the discrete parameter F of any feature information in the similar dam information set according to the following formula,
b1 represents the water storage amount information in any characteristic information, B2 represents the length information in any characteristic information, B3 represents the average height information of the dam body in any characteristic information, B4 represents the average thickness information of the dam body in any characteristic information, B5 represents the average rainfall information of the region in which the characteristic information is located, B6 represents the average temperature information of the dam body in any characteristic information, B10 represents the average value of the water storage amount information corresponding to all the characteristic information in the similar dam information set, B20 represents the average value of the length information corresponding to all the characteristic information in the similar dam information set, B30 represents the average value of the average height information of the dam body corresponding to all the characteristic information in the similar dam information set, B40 represents the average thickness information of the dam body corresponding to all the characteristic information in the dam information set, B50 represents the average value of the average rainfall information corresponding to all the characteristic information in the dam information set, and B60 represents the average value of the average temperature information of the dam information set;
the data processing module classifies similar grades of the characteristic information according to discrete parameters F corresponding to the characteristic information of the similar dam information set, wherein,
for any feature information within the set Bi of similar dams,
when the F is more than or equal to the F2, the data processing module divides the characteristic information into a first similar grade;
when F1 is not more than F and is less than F2, the data processing module divides the characteristic information into a second similar grade;
and when F is less than F1, the data processing module divides the characteristic information into a third similarity grade.
Specifically, as shown in fig. 2, the characteristic data of the similar dam is stored in the data set of the similar dam through the data processing module, so that data processing is facilitated, meanwhile, the similarity degree in the data set of the similar dam can be better distinguished through calculating the discrete parameter F, the similar dam is divided again, so that the division is better and more accurate, the intervention effect is better and more accurate, and then the early warning is accurately sent in advance, so that the accuracy of dam safety monitoring is improved.
Specifically, a second preset threshold A2 is preset in the data processing module, A2 is less than A1, the data processing module calculates a safety evaluation coefficient A corresponding to the dam in real time according to the data acquired by the data acquisition module,
when the safety evaluation coefficient A corresponding to the dam is larger than the second preset threshold A2, the data processing module retrieves from the data storage module and judges whether the dam has a similar dam or not, wherein,
if the dam has a similar dam, correcting the first preset threshold value;
and if the dam does not have a similar dam, not correcting the first preset threshold value.
Specifically, the data processing module sets a second preset threshold which is smaller than the first preset threshold, the early warning precision is corrected when the early warning standard is not reached, the monitoring precision is interfered by using historical data of a similar dam, the safety risk is effectively predicted, the early warning effect is achieved, and the dam safety monitoring and early warning accuracy is improved.
Specifically, the data processing module corrects the first preset threshold, when a comparison dam is selected from the similar dams of the monitoring dams, calls a similar dam information set storing feature information corresponding to the monitoring dams, determines whether a situation that a safety evaluation coefficient a is larger than a second preset threshold A2 occurs in historical data corresponding to the similar dams of the monitoring dams, marks the corresponding similar dams if the situation occurs, and if the quantity of the marked similar dams is larger than 2, differentiates discrete parameters corresponding to the feature information of the marked similar dams and discrete parameters corresponding to the feature information of the monitoring dams, selects the similar dam corresponding to the discrete parameter with the smallest difference as the comparison dam, calls the humidity, the temperature, the seepage pressure and the seepage pressure of the environment around the comparison dam when the historical maximum Amax of the safety evaluation coefficient a occurs in the comparison dam, calculates the contact ratio of the comparison dam and the similar dams, and determines the first preset threshold according to the correction amount and the similarity level of the monitoring dams.
Specifically, the data processing module calculates the contact ratio E according to the following formula according to the humidity, the temperature, the seepage flow and the seepage pressure of the environment around the comparison dam and the humidity, the temperature, the seepage flow and the seepage pressure of the current environment of the monitoring dam,
wherein T1 represents the current ambient temperature of the monitoring dam, T2 represents the called contrast dam ambient temperature, C1 represents the current ambient humidity of the monitoring dam, C2 represents the called contrast dam ambient humidity, P1 represents the current seepage flow of the monitoring dam, P2 represents the called contrast dam seepage flow, L1 represents the current seepage pressure of the monitoring dam, and L2 represents the called contrast dam seepage pressure;
when E is larger than or equal to E2, the data processing module corrects the first preset threshold A1 to A1', and sets A1' = A1- (A01 +. DELTA.A.times.alpha.);
when E1 is not less than E and less than E2, the data processing module corrects the first preset threshold A1 to A1', and sets A1' = A1- (A02 +. DELTA.A.times.alpha.);
when E < E1, the data processing module corrects the first preset threshold value A1 to A1', and sets A1' = A1- (A03 +. DELTA.A.times.alpha.);
wherein E1 represents a preset first coincidence degree comparison parameter, E2 represents a preset second coincidence degree comparison parameter, a01 represents a first preset correction amount, a02 represents a second preset correction amount, a03 represents a third preset correction amount, a03 > a02 > a01, α is a variation parameter, and Δ a = Amax-A1.
Specifically, the data processing module determines alpha according to the calculation parameters corresponding to the similar grades of the comparison dam and the monitoring dam, and sets the calculation parameter corresponding to the first similar grade to be 1, the calculation parameter corresponding to the second similar grade to be 2, the calculation parameter corresponding to the third similar grade to be 3 when determining,
when the sum of the corresponding calculation parameters of the comparison dam and the monitoring dam in the similar grade is equal to 2, alpha is 0.5, when the comparison dam and the monitoring dam in the similar grade are the same, and the sum of the corresponding calculation parameters of the similar grade is equal to 4 or 6, alpha is 0.4, when the comparison dam and the monitoring dam in the similar grade are different, and the sum of the corresponding calculation parameters of the similar grade is equal to 3 or 5, alpha is 0.3, when the comparison dam and the monitoring dam in the similar grade are different, and the sum of the corresponding calculation parameters of the similar grade is equal to 4, alpha is 0.2.
Specifically, when the comparison dam is selected, the data processing module selects according to the fact that whether the safety evaluation coefficient in the historical data exceeds a second preset threshold value, calls the corresponding environmental data at the time, compares the coincidence degree with the current environmental data, selects the correction parameter, further selects the more similar environmental data on the basis of the similar dam to compare the more similar environmental data, enables the intervention on the current early warning precision to be better and more accurate, can effectively predict risks, and improves the accuracy of dam safety monitoring and early warning.
Specifically, the historical data stored in the data processing module includes the safety evaluation coefficient a corresponding to each moment of each dam, and the ambient environment humidity, ambient environment temperature, dam seepage flow rate, and dam seepage pressure of each moment of each dam.
Specifically, the cloud data platform updates characteristic information and historical data of each dam every preset time.
So far, the technical solutions of the present invention have been described in connection with the preferred embodiments shown in the drawings, but it is apparent to those skilled in the art that the scope of the present invention is not limited to these specific embodiments. Equivalent changes or substitutions of related technical features can be made by those skilled in the art without departing from the principle of the invention, and the technical scheme after the changes or substitutions can fall into the protection scope of the invention.
Claims (10)
1. The utility model provides a hydraulic dam safety precaution system of high efficiency which characterized in that includes:
the data acquisition module comprises a temperature sensor, a humidity sensor, a plurality of osmotic pressure sensors and a plurality of seepage flow sensors which are arranged around the monitoring dam and is used for monitoring the ambient temperature, the ambient humidity, the dam osmotic pressure and the dam seepage flow of the monitoring dam in real time;
the data storage module is connected with the cloud data platform and internally stores characteristic information and historical data of a plurality of dams;
the data processing module is connected with the data acquisition module and the data processing module, completes data exchange, calculates a safety evaluation coefficient A in real time according to the ambient temperature, the ambient humidity, the seepage flow and the osmotic pressure around the monitoring dam, and sends out early warning when the safety evaluation coefficient A is larger than a first preset threshold value A1;
and the data processing module divides similar dams according to the characteristic information of the dams, selects a comparison dam from the similar dams of the monitoring dams, and corrects the first preset threshold according to historical data of the comparison dam and the similar level of the characteristic information.
2. The high-efficiency hydraulic dam safety early warning system according to claim 1, wherein the data processing module calculates a safety evaluation coefficient A according to the following formula based on the data obtained by the data obtaining module,
wherein: a represents T to represent the ambient temperature around the monitoring dam, T0 represents a preset ambient temperature contrast value, C represents the ambient humidity around the monitoring dam, C0 represents a preset ambient humidity contrast value, P represents the current seepage rate of the monitoring dam, P0 represents a preset seepage rate contrast value, L represents the current osmotic pressure of the monitoring dam, and L0 represents a preset osmotic pressure contrast value;
the data processing module compares the safety evaluation coefficient A with a first preset threshold value A1,
and when A is larger than A1, the data processing module sends out early warning information.
3. The high-efficiency safety early warning system for the hydraulic dams according to claim 1, wherein the data storage module is used for storing characteristic information of a plurality of dams in advance, and the characteristic information comprises water storage capacity information, length information, average dam height information, average dam thickness information, average monthly rainfall information of a located area and average monthly temperature information of the located area of the dams;
the data processing module divides similar dams according to the feature information of the dams, compares the feature information of each dam, judges that the dams are similar when the difference percentage K between the feature information corresponding to any two dams in the dams is smaller than a preset difference percentage K0, stores the feature sets of the similar dams into the same information set to form a plurality of similar dam information sets, and calculates the difference percentage K according to the following formula,
wherein b1 (x) represents the xth information in the first dam corresponding characteristic information, and b2 (x) represents the xth information in the second dam corresponding characteristic information.
4. The high-efficiency hydraulic dam safety early warning system according to claim 3, wherein discrete contrast parameters F1 and F2 are preset in the data processing module, F1 is more than 0 and less than F2, the data processing module calculates discrete parameter F of any characteristic information in the similar dam information set according to the following formula,
b1 represents the water storage capacity information in any characteristic information, B2 represents the length information in any characteristic information, B3 represents the average height information of the dam body in any characteristic information, B4 represents the average thickness information of the dam body in any characteristic information, B5 represents the average rainfall information of the region in which the characteristic information is located, B6 represents the average temperature information of the dam body in any characteristic information, B10 represents the average value of the water storage capacity information corresponding to all the characteristic information in the similar dam information set, B20 represents the average value of the length information corresponding to all the characteristic information in the similar dam information set, B30 represents the average value of the average height information of the dam body corresponding to all the characteristic information in the similar dam information set, B40 represents the average thickness information of the dam body corresponding to all the characteristic information in the dam information set, B50 represents the average value of the average rainfall information corresponding to all the characteristic information in the dam information set, and B60 represents the average value of the average temperature information of the dam information set;
the data processing module classifies similar grades for the characteristic information according to the discrete parameters F corresponding to the characteristic information of the similar dam information set, wherein,
for any feature information within the set Bi of similar dams,
when F is larger than or equal to F2, the data processing module divides the characteristic information into a first similar grade;
when F1 is more than or equal to F and less than F2, the data processing module divides the characteristic information into a second similar grade;
and when F is less than F1, the data processing module divides the characteristic information into a third similarity grade.
5. The high-efficiency hydraulic dam safety early warning system according to claim 4, wherein a second preset threshold A2 is preset in the data processing module, A2 is less than A1, the data processing module calculates a safety evaluation coefficient A corresponding to the dam in real time according to the data acquired by the data acquisition module,
when the safety evaluation coefficient A corresponding to the dam is larger than the second preset threshold value A2, the data processing module retrieves from the data storage module and judges whether the dam has a similar dam or not, wherein,
if the dam has a similar dam, correcting the first preset threshold value;
and if the dam does not have a similar dam, not correcting the first preset threshold value.
6. The high-efficiency safety early warning system for hydraulic dams according to claim 5, wherein the data processing module corrects the first preset threshold, when a comparison dam is selected from similar dams of the monitoring dam, calls a similar dam information set storing characteristic information corresponding to the monitoring dam, determines whether a situation that a safety evaluation coefficient A is larger than the second preset threshold A2 occurs in historical data corresponding to the similar dams of the monitoring dam, marks the corresponding similar dams if the situation occurs, and if the quantity of the marked similar dams is larger than 2, differentiates a discrete parameter corresponding to the characteristic information of the marked similar dams from a parameter corresponding to the characteristic information of the monitoring dam, selects the similar dam corresponding to the discrete parameter with the smallest difference as the comparison dam, calls humidity, temperature, flow seepage and seepage pressure of the surrounding environment of the comparison dam when the historical maximum value Amax of the safety evaluation coefficient A occurs in the comparison dam, calculates a weight correction of the comparison dam and the similar dams, and determines the first preset comparison dam weight correction according to the comparison threshold of the monitoring dam.
7. The high-efficiency hydraulic dam safety precaution system according to claim 6, wherein the data processing module calculates the contact ratio E according to the following formula based on the humidity, temperature, seepage flow and seepage pressure of the environment around the control dam and the humidity, temperature, seepage flow and seepage pressure of the current environment of the monitoring dam,
wherein T1 represents the current ambient temperature of the monitoring dam, T2 represents the called contrast dam ambient temperature, C1 represents the current ambient humidity of the monitoring dam, C2 represents the called contrast dam ambient humidity, P1 represents the current seepage flow of the monitoring dam, P2 represents the called contrast dam seepage flow, L1 represents the current seepage pressure of the monitoring dam, and L2 represents the called contrast dam seepage pressure;
when E is larger than or equal to E2, the data processing module corrects the first preset threshold value A1 to A1', and sets A1' = A1- (A01 +. DELTA.A multiplied by alpha);
when E1 is not less than E and less than E2, the data processing module corrects the first preset threshold A1 to A1', and sets A1' = A1- (A02 +. DELTA.A.times.alpha.);
when E < E1, the data processing module corrects the first preset threshold value A1 to A1 'and sets A1' = A1- (A03 +. DELTA.A × alpha);
wherein, E1 represents a preset first coincidence degree contrast parameter, E2 represents a preset second coincidence degree contrast parameter, a01 represents a first preset correction amount, a02 represents a second preset correction amount, a03 represents a third preset correction amount, a03 > a02 > a01, α is a variation parameter, and Δ a = Amax-A1.
8. The high-efficiency safety early warning system for hydraulic dams according to claim 7, wherein the data processing module determines alpha according to the corresponding calculation parameters of the similarity levels of the comparison dam and the monitoring dam, and sets the corresponding calculation parameter of the first similarity level to 1, the corresponding calculation parameter of the second similarity level to 2, the corresponding calculation parameter of the third similarity level to 3 when determining alpha,
when the sum of the corresponding calculation parameters of the comparison dam and the monitoring dam in the similar grade is equal to 2, alpha is 0.5, when the comparison dam and the monitoring dam in the similar grade are the same, and the sum of the corresponding calculation parameters of the similar grade is equal to 4 or 6, alpha is 0.4, when the comparison dam and the monitoring dam in the similar grade are different, and the sum of the corresponding calculation parameters of the similar grade is equal to 3 or 5, alpha is 0.3, when the comparison dam and the monitoring dam in the similar grade are different, and the sum of the corresponding calculation parameters of the similar grade is equal to 4, alpha is 0.2.
9. The high-efficiency hydraulic dam safety early warning system according to claim 1, wherein the historical data stored in the data processing module includes a safety evaluation coefficient a corresponding to each moment of each dam, and dam ambient humidity, dam ambient temperature, dam seepage flow and dam osmotic pressure corresponding to each moment.
10. The efficient safety precaution system for hydraulic dams of claim 1, wherein the cloud data platform updates feature information and historical data of each dam at preset intervals.
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