CN113515507B - Method and system applied to dam water seepage detection - Google Patents
Method and system applied to dam water seepage detection Download PDFInfo
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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Abstract
The invention discloses a method and a system applied to dam seepage detection, which acquire seepage detection data of a target detection result, wherein the seepage detection data are used for responding to a detection event; transmitting preset water seepage comparison data to a plurality of data nodes in a data detection training model, wherein the preset water seepage comparison data are used for acquiring data labels of the plurality of data nodes on detection events; acquiring data labels of detection events returned by a plurality of data nodes in response to preset water seepage comparison data; the data labels of the detection events are processed by the data nodes of the data detection nodes, and the data labels are detected by the data detection nodes, so that the detection accuracy of the data labels is higher than that of the data labels detected by the data detection nodes by using one node, the technical problem that the accuracy of the dam water seepage detection data labels in the related technology is lower can be solved, and the technical effect of improving the detection accuracy is achieved.
Description
Technical Field
The invention relates to the technical field of data detection, in particular to a method and a system applied to dam seepage detection.
Background
Generally, in the construction of data center projects, data sources are changed widely, and when data extraction and cleaning conversion are performed by using ETL (Extract-Transform-Load) tool software, some important data are found to be either missing or not in compliance with specifications. Therefore, before the data is put in storage, the data after extraction and cleaning conversion needs to be subjected to relevant quality detection, normal data are put in storage, problem data and analysis results of the problem data are provided, and a data source is urged to improve the data quality.
However, dam seepage data of the data center are different, the data are various, and monitoring rules or detection rules applicable to different data are correspondingly different. At present, a plurality of preset different detection rules are generally adopted to uniformly detect different dam seepage data, but some detection rules are irrelevant to the types of the dam seepage data, for example, the dam seepage data are identification card numbers, a certain detection rule is whether detection time is illegal, the dam seepage data are not related to the detection rules of whether the detection time is illegal, and when the detection rules are adopted to detect the dam seepage data, the detection is equivalent to invalid detection, so that the detection efficiency is affected. Or, the coverage of the preset detection rules is not wide enough, the data cannot be comprehensively detected, the quality of the warehouse-in data is affected, meanwhile, the problem data and the analysis result of the problem data are abnormal, and the data source cannot be accurately supervised to improve the data quality.
Therefore, when dam seepage data are detected at present, the transformation monitoring rule or the detection rule cannot be flexibly dealt with according to the dam seepage data to be detected, so that the data analysis tracking investigation of the problem is output to the data source, the data quality is urged to be improved, the detection efficiency is also influenced, the quality of the warehouse entry data is also influenced, meanwhile, the problem data and the analysis result of the problem data are abnormal, and the data source cannot be accurately urged to be improved.
Disclosure of Invention
The technical problem to be solved by the invention is the technical problem of the background technology, and the invention aims to provide a method and a system for detecting dam seepage and solve the problem of timely detecting dam seepage.
The invention is realized by the following technical scheme:
a method for use in dam water penetration detection, the method comprising:
obtaining water seepage detection data of a target detection result, wherein the water seepage detection data are used for responding to a detection event, and the target detection result is input into a data detection terminal;
transmitting preset water seepage comparison data to a plurality of data nodes in a data detection training model, wherein the preset water seepage comparison data are used for acquiring data labels of the plurality of data nodes on the detection event;
acquiring data labels of the detection events returned by the plurality of data nodes in response to the preset water seepage comparison data;
and detecting the data labels of the data nodes on the detection events through a plurality of data detection nodes, wherein the water seepage rate of the data detection nodes is smaller than the water seepage rate of other database nodes except the data detection nodes in the database.
Further, detecting, by a plurality of data detection nodes, a data tag of the detection event by the plurality of data nodes includes:
detecting whether the data label of the data node is correct or not by each data detection node in the plurality of data detection nodes, wherein the data nodes to which the data labels of any two data detection nodes belong are different, one node in the plurality of data detection nodes performs data label operation on the detection event in a first detection route segment, the other node in the plurality of data detection nodes performs data label operation on the detection event in a second detection route segment, and part or all of the first detection route segment and the second detection route segment are overlapped.
Further, detecting, by each of the plurality of data detection nodes, whether the data label of the data node is correct includes:
the method comprises the steps of sending water seepage detection service data to a third node in a neural network waiting to be checked, wherein the third node is used for transmitting the water seepage detection service data to a plurality of data detection nodes in the neural network waiting to be checked, and the water seepage detection service data received by any one data detection node is derived from the third node or another data detection node;
and receiving the data labels of the plurality of data detection nodes returned by the third node.
Further, the sending the water seepage detection service data to a third node in the waiting neural network comprises:
and sending the water seepage detection service data to the third node in the database, wherein all database nodes in the database are connected by adopting the peer-to-peer verification neural network, the third node is a water seepage detection node of the database, the third node is used for selecting the data detection node from all database nodes, and the data detection node is a node with water seepage rate smaller than that of database nodes except the data detection node in all database nodes.
Further, after detecting, by a plurality of data detection nodes, a data tag of the detection event by the plurality of data nodes, the method further comprises:
determining that the detection event is a passing detection when the plurality of data detection nodes pass the inspection of the data labels of the plurality of data nodes;
in the event that at least one of the data detection nodes fails the verification of the data label of the data node, determining that the detection event is not a pass detection.
Further, before detecting, by a plurality of data detection nodes, a data tag of the detection event by the plurality of data nodes, the method further comprises:
obtaining a plurality of detection parameters from the plurality of data nodes, wherein each detection parameter of the plurality of detection parameters is used for a data tag of one data node of the data detection nodes;
and sending the detection parameters to a third node in the neural network waiting to be checked, and transmitting the detection parameters to other nodes in the neural network waiting to be checked through the third node, wherein the other nodes in the neural network waiting to be checked are nodes adopting dam water seepage data programming array data detection terminals, and any node in the neural network waiting to be checked is used for transmitting the received detection parameters to the nodes connected with the nodes by signals under the condition that the detection parameters are received.
Further, obtaining the water seepage detection data of the target detection result includes:
and acquiring the water seepage detection data of the target detection result through a fourth node in the data acquisition end, wherein the water seepage rate of the fourth node is not more than that of nodes except the fourth node in the data acquisition end.
Further, before or after the water seepage detection data of the target detection result is acquired through the fourth node in the data acquisition end, the method further includes:
under the condition that the water seepage rate of all nodes in an activated state in the data acquisition end reaches a first threshold value, switching the state of a standby node configured for the data acquisition end from the standby state to the activated state, and adding the standby node into the data acquisition end; and/or the number of the groups of groups,
and under the condition that the water seepage rate of all nodes in an activated state in the data acquisition end is smaller than a second threshold value, switching the unused node state in the data acquisition end from the activated state to a standby state, and deleting the unused node in the data acquisition end, wherein the second threshold value is smaller than the first threshold value.
Further, the method further comprises:
and under the condition that the water seepage rates of all nodes in an activated state in the data acquisition end reach a first threshold value, sending prompt information to a data detection terminal for sending the water seepage detection data, wherein the prompt information is used for prompting that the water seepage rates of all nodes in the data acquisition end reach the first threshold value.
The system method applied to dam seepage detection comprises a data acquisition end and a data processing end, wherein the data acquisition end is in communication connection with the data processing end, and the data processing end is specifically used for:
obtaining water seepage detection data of a target detection result, wherein the water seepage detection data are used for responding to a detection event, and the target detection result is input into a data detection terminal;
transmitting preset water seepage comparison data to a plurality of data nodes in a data detection training model, wherein the preset water seepage comparison data are used for acquiring data labels of the plurality of data nodes on the detection event;
acquiring data labels of the detection events returned by the plurality of data nodes in response to the preset water seepage comparison data;
and detecting the data labels of the data nodes on the detection events through a plurality of data detection nodes, wherein the water seepage rate of the data detection nodes is smaller than the water seepage rate of other database nodes except the data detection nodes in the database.
Compared with the prior art, the invention has the following advantages and beneficial effects:
the invention is applied to a dam seepage detection method and system, and seepage detection data of a target detection result are obtained, wherein the seepage detection data are used for responding to detection events; transmitting preset water seepage comparison data to a plurality of data nodes in a data detection training model, wherein the preset water seepage comparison data are used for acquiring data labels of the plurality of data nodes on detection events; acquiring data labels of detection events returned by a plurality of data nodes in response to preset water seepage comparison data; the data labels of the detection events are processed by the data nodes of the data detection nodes, and the data labels are detected by the data detection nodes, so that the detection accuracy of the data labels is higher than that of the data labels detected by the data detection nodes by using one node, the technical problem that the accuracy of the dam water seepage detection data labels in the related technology is lower can be solved, and the technical effect of improving the detection accuracy is achieved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
FIG. 1 is a schematic diagram of a system for dam seepage detection according to an embodiment of the present invention;
FIG. 2 is a flow chart of a method for dam seepage detection according to an embodiment of the present invention;
fig. 3 is a functional block diagram of a device for dam seepage detection according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present application as detailed in the accompanying claims.
For convenience in describing the above method and system for dam water seepage detection, please refer to fig. 1, which provides a schematic diagram of a communication architecture of a system 100 for dam water seepage detection according to an embodiment of the present invention. The system 100 for dam seepage detection may include a data processing terminal 200 and an information acquisition terminal 300, where the data processing terminal 200 is communicatively connected with the information acquisition terminal 300.
In a specific embodiment, the data processing terminal 200 and the information collecting terminal 300 may be a desktop computer, a tablet computer, a notebook computer, a mobile phone or other electronic devices capable of implementing data processing and data communication, which are not limited herein.
On the basis of the foregoing, please refer to fig. 2 in combination, which is a schematic flow chart of a method for dam seepage detection according to an embodiment of the present invention, the method for dam seepage detection may be applied to the data processing in fig. 1, and further, the method for dam seepage detection may specifically include the following descriptions of step S21 to step S24.
And S21, acquiring water seepage detection data of a target detection result, wherein the water seepage detection data are used for responding to a detection event, and the target detection result is input into a data detection terminal.
Step S22, preset water seepage comparison data are sent to a plurality of data nodes in a data detection training model, wherein the preset water seepage comparison data are used for obtaining data labels of the plurality of data nodes on the detection event.
Step S23, obtaining data labels of the detection events returned by the data nodes in response to the preset water seepage comparison data.
And step S24, detecting data labels of the data nodes on the detection events through a plurality of data detection nodes, wherein the water seepage rate of the data detection nodes is smaller than that of other database nodes except the data detection nodes in the database.
It will be appreciated that, when the above description of step S21 to step S24 is performed, water penetration detection data of the target detection result is obtained, where the water penetration detection data is used to respond to the detection event; transmitting preset water seepage comparison data to a plurality of data nodes in a data detection training model, wherein the preset water seepage comparison data are used for acquiring data labels of the plurality of data nodes on detection events; acquiring data labels of detection events returned by a plurality of data nodes in response to preset water seepage comparison data; the data labels of the detection events are processed by the data nodes of the data detection nodes, and the data labels are detected by the data detection nodes, so that the detection accuracy of the data labels is higher than that of the data labels detected by the data detection nodes by using one node, the technical problem that the accuracy of the dam water seepage detection data labels in the related technology is lower can be solved, and the technical effect of improving the detection accuracy is achieved.
In a specific implementation process, the inventor finds that when detecting the data labels of the detection events by the plurality of data detection nodes, there is a technical problem that the plurality of data detection nodes are inaccurate, so that the data labels of the detection events are obtained inaccurately, and in order to improve the technical problem, the step of detecting the data labels of the detection events by the plurality of data detection nodes described in step S24 may specifically include what is described in the following step S241.
Step S241, detecting, by each of the plurality of data detection nodes, whether the data label of the data node is correct, where the data nodes to which the data labels of any two data detection nodes belong are different, one of the plurality of data detection nodes performs a data label operation on the detection event in a first detection route segment, and another of the plurality of data detection nodes performs a data label operation on the detection event in a second detection route segment, where the first detection route segment and the second detection route segment are partially or completely overlapped.
It will be appreciated that when the above description of step S241 is performed, the technical problem of inaccuracy of the plurality of data detection nodes is avoided when the data labels of the detection event are detected by the plurality of data detection nodes, so that the data labels of the detection event are obtained accurately.
In a specific implementation process, the inventor finds that when the data label of the data node is detected to be correct by each of the plurality of data detection nodes, there is a technical problem that the data detection node is incorrect, so that it is difficult to correctly determine whether the data label is correct, and in order to improve the technical problem, the step of detecting, by each of the plurality of data detection nodes, whether the data label of the data node is correct in step S241 may specifically include the following steps A1 and A2.
And A1, transmitting water seepage detection service data to a third node in the neural network waiting to be checked, wherein the third node is used for transmitting the water seepage detection service data to the plurality of data detection nodes in the neural network waiting to be checked, and the water seepage detection service data received by any one data detection node is sourced from the third node or another data detection node.
And step A2, receiving the data labels of the plurality of data detection nodes returned by the third node.
It can be appreciated that when the above-described steps A1 and A2 are performed, when each of the plurality of data detection nodes detects whether the data label of the data node is correct, the technical problem that the data detection node is incorrect is avoided, so that whether the data label is correct can be correctly determined.
In a specific implementation process, the inventor finds that when the water seepage detection service data is sent to a third node in the neural network waiting for verification, the technical problem that the water seepage detection service data is unreliable exists, so that the water seepage detection cannot be reliably performed, and in order to improve the technical problem, the step of sending the water seepage detection service data to the third node in the neural network waiting for verification, which is described in the step A1, may specifically include the following description of the step A1.
Step a1, the water seepage detection service data are sent to the third node in the database, wherein all database nodes in the database are connected by adopting the peer-to-peer verification neural network, the third node is a water seepage detection node of the database, the third node is used for selecting the data detection node from all database nodes, and the data detection node is a node with water seepage rate smaller than that of database nodes except the data detection node in all database nodes.
It can be understood that when the content described in the step a1 is executed, the technical problem that the water seepage detection service data is unreliable is avoided when the water seepage detection service data is sent to a third node in the waiting neural network, so that the water seepage detection can be reliably performed.
Based on the above, after detecting the data labels of the detection events by the plurality of data nodes by the plurality of data detection nodes, the method further includes the following descriptions of step q1 and step q 2.
And q1, determining that the detection event is passing detection when all the data labels of the plurality of data nodes pass detection by the plurality of data detection nodes.
And q2, determining that the detection event is not passing detection in the case that the at least one data detection node fails to check the data label of the data node.
It can be appreciated that when the above-described steps q1 and q2 are performed, the data tag of the detected event can be accurately obtained, so that the detected data is more accurate, and the consequences caused by water seepage are avoided.
Based on the above, the method further comprises the descriptions of step e1 and step e2 before detecting the data labels of the detection events by the plurality of data nodes by the plurality of data detection nodes.
And e1, acquiring a plurality of detection parameters from the plurality of data nodes, wherein each detection parameter in the plurality of detection parameters is used for a data label of one data node of the data detection nodes.
And e2, sending the detection parameters to a third node in the neural network waiting to be checked, and transmitting the detection parameters to other nodes in the neural network waiting to be checked through the third node, wherein the other nodes in the neural network waiting to be checked are nodes adopting dam seepage data programming array data detection terminals, and any node in the neural network waiting to be checked is used for transmitting the received detection parameters to the nodes connected with the nodes by signals under the condition of receiving the detection parameters.
It can be appreciated that when the above steps e1 and e2 are performed, the plurality of data detection nodes are accurately calculated, so that the plurality of data detection nodes are more reliable, and the data labels of the detection events can be accurately obtained, thereby reducing the data errors.
In a specific implementation process, the inventor finds that when the water seepage detection data of the target detection result is obtained, there is a technical problem of data delay, so that it is difficult to quickly obtain the water seepage detection data, and in order to improve the technical problem, the step of obtaining the water seepage detection data of the target detection result described in step S21 may specifically include the following description of step S211.
Step S211, obtaining the water seepage detection data of the target detection result through a fourth node in the data acquisition end, where the water seepage rate of the fourth node is not greater than the water seepage rate of nodes except the fourth node in the data acquisition end.
It will be appreciated that, when the water seepage detection data of the target detection result is obtained when the above description of step S211 is performed, the technical problem of data delay is avoided, so that the water seepage detection data can be quickly obtained.
Based on the above, before or after the water penetration detection data of the target detection result is acquired through the fourth node in the data acquisition end, the method further includes the following descriptions of step f1 and step f 2.
Step f1, under the condition that the water seepage rate of all nodes in an activated state in the data acquisition end reaches a first threshold value, switching the state of a standby node configured for the data acquisition end from the standby state to the activated state, and adding the standby node into the data acquisition end; and/or.
And f2, under the condition that the water seepage rate of all nodes in an activated state in the data acquisition end is smaller than a second threshold value, switching the unused node state in the data acquisition end from the activated state to a standby state, and deleting the unused node in the data acquisition end, wherein the second threshold value is smaller than the first threshold value.
It will be appreciated that when the above description of step f1 and step f2 is performed, the water seepage problem of the dam is ensured by comparing the water seepage problem with the preset data of the preset database, so that the hidden danger of the dam is effectively reduced.
Based on the above, the method further comprises the following description of step t 1.
And step t1, under the condition that the water seepage rates of all nodes in an activated state in the data acquisition end reach a first threshold value, sending prompt information to a data detection terminal for sending the water seepage detection data, wherein the prompt information is used for prompting that the water seepage rates of all nodes in the data acquisition end reach the first threshold value.
It will be appreciated that when the above description of step t1 is performed, the indication is given that there is water seepage, so that maintenance can be performed on the dam water seepage area in time.
Based on the same inventive concept, a system method applied to dam seepage detection is also provided, and the system method comprises a data acquisition end and a data processing end, wherein the data acquisition end is in communication connection with the data processing end, and the data processing end is specifically used for:
obtaining water seepage detection data of a target detection result, wherein the water seepage detection data are used for responding to a detection event, and the target detection result is input into a data detection terminal;
transmitting preset water seepage comparison data to a plurality of data nodes in a data detection training model, wherein the preset water seepage comparison data are used for acquiring data labels of the plurality of data nodes on the detection event;
acquiring data labels of the detection events returned by the plurality of data nodes in response to the preset water seepage comparison data;
and detecting the data labels of the data nodes on the detection events through a plurality of data detection nodes, wherein the water seepage rate of the data detection nodes is smaller than the water seepage rate of other database nodes except the data detection nodes in the database.
Further, the data processing end is specifically configured to:
detecting whether the data label of the data node is correct or not by each data detection node in the plurality of data detection nodes, wherein the data nodes to which the data labels of any two data detection nodes belong are different, one node in the plurality of data detection nodes performs data label operation on the detection event in a first detection route segment, the other node in the plurality of data detection nodes performs data label operation on the detection event in a second detection route segment, and part or all of the first detection route segment and the second detection route segment are overlapped.
Further, the data processing end is specifically configured to:
the method comprises the steps of sending water seepage detection service data to a third node in a neural network waiting to be checked, wherein the third node is used for transmitting the water seepage detection service data to a plurality of data detection nodes in the neural network waiting to be checked, and the water seepage detection service data received by any one data detection node is derived from the third node or another data detection node;
and receiving the data labels of the plurality of data detection nodes returned by the third node.
Further, the data processing end is specifically configured to:
and sending the water seepage detection service data to the third node in the database, wherein all database nodes in the database are connected by adopting the peer-to-peer verification neural network, the third node is a water seepage detection node of the database, the third node is used for selecting the data detection node from all database nodes, and the data detection node is a node with water seepage rate smaller than that of database nodes except the data detection node in all database nodes.
Further, the data processing end is specifically configured to:
determining that the detection event is a passing detection when the plurality of data detection nodes pass the inspection of the data labels of the plurality of data nodes;
in the event that at least one of the data detection nodes fails the verification of the data label of the data node, determining that the detection event is not a pass detection.
Further, the data processing end is specifically configured to:
obtaining a plurality of detection parameters from the plurality of data nodes, wherein each detection parameter of the plurality of detection parameters is used for a data tag of one data node of the data detection nodes;
and sending the detection parameters to a third node in the neural network waiting to be checked, and transmitting the detection parameters to other nodes in the neural network waiting to be checked through the third node, wherein the other nodes in the neural network waiting to be checked are nodes adopting dam water seepage data programming array data detection terminals, and any node in the neural network waiting to be checked is used for transmitting the received detection parameters to the nodes connected with the nodes by signals under the condition that the detection parameters are received.
Further, the data processing end is specifically configured to:
and acquiring the water seepage detection data of the target detection result through a fourth node in the data acquisition end, wherein the water seepage rate of the fourth node is not more than that of nodes except the fourth node in the data acquisition end.
Further, the data processing end is specifically configured to:
under the condition that the water seepage rate of all nodes in an activated state in the data acquisition end reaches a first threshold value, switching the state of a standby node configured for the data acquisition end from the standby state to the activated state, and adding the standby node into the data acquisition end; and/or the number of the groups of groups,
and under the condition that the water seepage rate of all nodes in an activated state in the data acquisition end is smaller than a second threshold value, switching the unused node state in the data acquisition end from the activated state to a standby state, and deleting the unused node in the data acquisition end, wherein the second threshold value is smaller than the first threshold value.
Further, the data processing end is specifically configured to:
and under the condition that the water seepage rates of all nodes in an activated state in the data acquisition end reach a first threshold value, sending prompt information to a data detection terminal for sending the water seepage detection data, wherein the prompt information is used for prompting that the water seepage rates of all nodes in the data acquisition end reach the first threshold value.
Based on the same inventive concept as described above, please refer to fig. 3 in combination, a functional block diagram of an apparatus 500 for dam water seepage detection is also provided, and a detailed description of the apparatus 500 for dam water seepage detection is as follows.
A device 500 for dam water penetration detection, for use in a data processing terminal, said device 500 comprising:
the obtaining module 510 is configured to obtain water penetration detection data of a target detection result, where the water penetration detection data is used for responding to a detection event, and the target detection result is input to a data detection terminal;
the calculation module 520 is configured to send preset water seepage comparison data to a plurality of data nodes in a data detection training model, where the preset water seepage comparison data is used to obtain data labels of the plurality of data nodes on the detection event;
a return module 530, configured to obtain data labels returned by the plurality of data nodes in response to the preset water seepage comparison data for the detection event;
the detection module 540 is configured to detect data labels of the plurality of data nodes on the detection event through the plurality of data detection nodes, where a water permeability of the data detection nodes is smaller than a water permeability of other database nodes except the data detection nodes in the database.
The foregoing description of the embodiments has been provided for the purpose of illustrating the general principles of the invention, and is not meant to limit the scope of the invention, but to limit the invention to the particular embodiments, and any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (6)
1. A method for dam water penetration detection, the method comprising:
obtaining water seepage detection data of a target detection result, wherein the water seepage detection data are used for responding to a detection event, and the target detection result is input into a data detection terminal;
transmitting preset water seepage comparison data to a plurality of data nodes in a data detection training model, wherein the preset water seepage comparison data are used for acquiring data labels of the plurality of data nodes on the detection event;
acquiring data labels of the detection events returned by the plurality of data nodes in response to the preset water seepage comparison data;
detecting data labels of the data nodes on the detection events through a plurality of data detection nodes, wherein the water seepage rate of the data detection nodes is smaller than that of other database nodes except the data detection nodes in a database;
detecting, by a plurality of data detection nodes, a data tag of the detection event by the plurality of data nodes includes:
detecting whether the data label of the data node is correct or not by each data detection node in the plurality of data detection nodes, wherein the data nodes to which the data labels of any two data detection nodes belong are different, one node in the plurality of data detection nodes performs data label operation on the detection event in a first detection route segment, the other node in the plurality of data detection nodes performs data label operation on the detection event in a second detection route segment, and part or all of the first detection route segment and the second detection route segment are overlapped;
detecting, by each of the plurality of data detection nodes, whether a data tag of the data node is correct includes:
the method comprises the steps of sending water seepage detection service data to a third node in a neural network waiting to be checked, wherein the third node is used for transmitting the water seepage detection service data to a plurality of data detection nodes in the neural network waiting to be checked, and the water seepage detection service data received by any one data detection node is sourced from the third node or another data detection node;
receiving data labels of the plurality of data detection nodes returned by the third node;
the sending of the water seepage detection service data to a third node in the waiting neural network comprises the following steps:
and sending the water seepage detection service data to the third node in the database, wherein all database nodes in the database are connected by adopting the peer-to-peer verification neural network, the third node is a water seepage detection node of the database, the third node is used for selecting the data detection node from all database nodes, and the data detection node is a node with water seepage rate smaller than that of database nodes except the data detection node in all database nodes.
2. The method of claim 1, wherein after detecting the data tag of the detection event by the plurality of data nodes by the plurality of data detection nodes, the method further comprises:
determining that the detection event is a passing detection when the plurality of data detection nodes pass the inspection of the data labels of the plurality of data nodes;
in the event that at least one of the data detection nodes fails the verification of the data label of the data node, determining that the detection event is not a pass detection.
3. The method according to any one of claims 1 to 2, wherein prior to detecting data tags of the detection event by a plurality of data detection nodes, the method further comprises:
obtaining a plurality of detection parameters from the plurality of data nodes, wherein each detection parameter of the plurality of detection parameters is used for a data tag of one data node of the data detection nodes;
and sending the detection parameters to a third node in the neural network waiting to be checked, and transmitting the detection parameters to other nodes in the neural network waiting to be checked through the third node, wherein the other nodes in the neural network waiting to be checked are nodes adopting dam water seepage data programming array data detection terminals, and any node in the neural network waiting to be checked is used for transmitting the received detection parameters to the nodes connected with the nodes by signals under the condition that the detection parameters are received.
4. The method according to any one of claims 1 to 2, wherein obtaining water penetration detection data of the target detection result includes:
and acquiring the water seepage detection data of the target detection result through a fourth node in the data acquisition end, wherein the water seepage rate of the fourth node is not more than that of nodes except the fourth node in the data acquisition end.
5. The method of claim 4, wherein before or after the water penetration detection data of the target detection result is obtained by a fourth node in a data acquisition end, the method further comprises:
under the condition that the water seepage rate of all nodes in an activated state in the data acquisition end reaches a first threshold value, switching the state of a standby node configured for the data acquisition end from the standby state to the activated state, and adding the standby node into the data acquisition end; and/or the number of the groups of groups,
and under the condition that the water seepage rate of all nodes in an activated state in the data acquisition end is smaller than a second threshold value, switching the unused node state in the data acquisition end from the activated state to a standby state, and deleting the unused node in the data acquisition end, wherein the second threshold value is smaller than the first threshold value.
6. The method of claim 5, wherein the method further comprises:
and under the condition that the water seepage rates of all nodes in an activated state in the data acquisition end reach a first threshold value, sending prompt information to a data detection terminal for sending the water seepage detection data, wherein the prompt information is used for prompting that the water seepage rates of all nodes in the data acquisition end reach the first threshold value.
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