A dam safety online monitoring and management method and system based on the Internet of Things

Abstract

The present invention is applicable to the field of monitoring and management technology, and particularly relates to an Internet of Things (IoT)-based online monitoring and management method and system for dam safety. The method comprises: S100: obtaining the location of a dam bottom sump, the sump being evenly distributed around the dam, collecting liquid level data from IoT devices within the location, and marking a liquid level threshold; S200: setting nodes corresponding to the location, wherein the nodes include a first node, a second node, a third node, ..., and an nth node, transferring the liquid level data to the nodes, creating a multi-hop network architecture, integrating all nodes into the multi-hop network architecture, generating a monitoring network, and inserting tags composed of monitoring templates. By generating alarm information and the location of the disappearance, the present invention can promptly locate the location of a dam piping burst, effectively preventing catastrophic accidents, optimizing maintenance efficiency, enhancing emergency response capabilities, and ensuring the safe and stable operation of the dam.

Description

Technical Field

[0001] The present invention relates to the technical field of monitoring and management, and in particular to an Internet of Things-based dam safety online monitoring and management method and system. Background Art

[0002] Online monitoring of dam safety is a key means to ensure the safe operation of dams. It uses sensors, data acquisition equipment and wireless communication technology to monitor key dam parameters in real time, such as water level, dam deformation, leakage and environmental conditions. It also analyzes, processes and predicts these data to achieve all-weather dynamic monitoring, risk assessment and prediction of the dam's operating status.

[0003] Dam piping refers to the phenomenon of water flowing through the dam body at a certain part of the dam. This phenomenon may cause stability problems of the dam body and may even cause damage to the dam body. The piping phenomenon is generally caused by water erosion in the dam body. This erosion will gradually expand to form an underground water flow channel, eventually leading to the instability of the dam body. Therefore, "how to monitor dam piping online" is the technical problem that the present invention needs to solve. Summary of the Invention

[0004] The purpose of the present invention is to provide a dam safety online monitoring and management method and system based on the Internet of Things to solve the problem of "how to monitor dam piping online" raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A dam safety online monitoring and management method based on the Internet of Things, the method comprising:

[0007] S100: Obtaining the location of the sump at the bottom of the dam, where the sump is evenly distributed around the dam, collecting liquid level data from IoT devices at the location, and marking a liquid level threshold;

[0008] S200: Setting nodes corresponding to the positions one by one, wherein the nodes include: a first node, a second node, a third node, ..., an nth node, transferring the liquid level data to the nodes, creating a multi-hop network architecture, integrating all the nodes into the multi-hop network architecture, generating a monitoring network, and inserting a label composed of a monitoring template;

[0009] S300: establishing a communication link between the nodes, unidirectionally linking all the nodes, and embedding an activation mechanism into the communication link, wherein the nth node is linked to the first node;

[0010] The activation mechanism includes: when the liquid level data in the first node does not exceed the liquid level threshold, generating a trigger signal and sending the trigger signal to the second node, and if it exceeds, closing the communication link;

[0011] S400: Integrate a monitoring strategy into the first node, wherein the monitoring strategy is that if the first node does not receive a trigger signal within a preset time period, an alarm message is generated, the disappearance position of the trigger signal is traversed by using the communication link, the disappearance position is integrated into the alarm message, and the integrated alarm message is sent to a preset terminal.

[0012] Furthermore, the S100 includes:

[0013] Collecting structural data of the dam, drawing a plan distribution map, determining the location of the sump, and marking the location on the plan distribution map using GPS positioning technology;

[0014] The sump is numbered, the unique identifier of the IoT device is collected, and a corresponding relationship between the number and the unique identifier is configured.

[0015] Furthermore, the S200 includes:

[0016] Constructing the same number of nodes as the sump, and synchronizing the liquid level data and liquid level thresholds into the nodes;

[0017] Determine the span frequency of each node based on the liquid level data, and locate the corresponding relationship between the span frequency and time;

[0018] Get the current time, determine whether the current time meets the crossing frequency, if so, traverse all nodes in sequence, if not, cross the node.

[0019] Furthermore, the S200 further includes:

[0020] Configuring attributes of the node, wherein the attributes at least include: the location, liquid level data, and liquid level threshold;

[0021] A warning value is inserted into the node, and when the liquid level data is greater than the warning value, the warning information is generated, and the liquid level data of the node is integrated into the warning information.

[0022] Furthermore, the S300 includes:

[0023] Defining a start condition for the activation mechanism, wherein the start condition is a time or an event;

[0024] All of the nodes are linked to generate a sequential activation architecture.

[0025] Furthermore, the S400 includes:

[0026] Based on the sequential activation architecture and the activation mechanism, determining whether the first node receives a trigger signal;

[0027] Integrating a root node into the first node, and establishing a coordination relationship between the root node and all nodes;

[0028] The monitoring time of the node is determined, and a monitoring schedule is drawn according to the spanning frequency, and synchronized to the root node.

[0029] Furthermore, the method further comprises:

[0030] Collecting water quality data uploaded by sensors in the disappearing location, the water quality data including historical water quality data and real-time water quality data;

[0031] Abnormal features are extracted from the historical water quality data, and a water quality curve is drawn with the current moment as the horizontal coordinate and the real-time water quality data as the vertical coordinate, and the abnormal features are marked on the water quality curve.

[0032] Furthermore, the system includes:

[0033] A marking module is used to obtain the location of the water collection pits at the bottom of the dam, which are evenly distributed around the dam, collect liquid level data from IoT devices at these locations, and mark the liquid level threshold;

[0034] an insertion module configured to set nodes corresponding to the positions one by one, wherein the nodes include: a first node, a second node, a third node, ..., an nth node, transfer the liquid level data into the nodes, create a multi-hop network architecture, integrate all the nodes into the multi-hop network architecture, generate a monitoring network, and insert a label composed of a monitoring template;

[0035] an embedding module for establishing a communication link between the nodes and unidirectionally linking all nodes, and embedding an activation mechanism into the communication link, wherein the nth node is linked to the first node;

[0036] The activation mechanism includes: when the liquid level data in the first node does not exceed the liquid level threshold, generating a trigger signal and sending the trigger signal to the second node, and if it exceeds, closing the communication link;

[0037] A sending module is used to integrate a monitoring strategy into the first node, wherein the monitoring strategy is that if the first node does not receive a trigger signal within a preset time period, an alarm message is generated, the disappearance position of the trigger signal is traversed by using the communication link, the disappearance position is integrated into the alarm message, and the integrated alarm message is sent to a preset terminal.

[0038] Furthermore, the marking module includes:

[0039] A collection unit is used to collect structural data of the dam, draw a plan distribution map, determine the location of the sump, and mark the location on the plan distribution map using GPS positioning technology;

[0040] The corresponding unit is used to number the sump, collect the unique identifier of the Internet of Things device, and configure the corresponding relationship between the number and the unique identifier.

[0041] Furthermore, the insertion module includes:

[0042] A synchronization unit, configured to construct the same number of nodes as the sump, and synchronize the liquid level data and liquid level thresholds to the nodes;

[0043] a positioning unit, configured to determine the span frequency of each node based on the liquid level data, and locate the corresponding relationship between the span frequency and time;

[0044] A spanning unit is used to obtain the current time, determine whether the current time satisfies the spanning frequency, and if so, traverse all nodes in sequence; if not, span the node;

[0045] A configuration unit, configured to configure attributes of the node, wherein the attributes include at least: the location, liquid level data, and liquid level threshold;

[0046] The integration unit is used to insert a warning value into the node, generate the alarm information when the liquid level data is greater than the warning value, and integrate the liquid level data of the node into the alarm information.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] 1. By collecting liquid level data in the sump, it is possible to quantify the piping of the dam and discover structural hazards of the dam at an early stage to avoid dam instability. By setting up nodes and monitoring networks, it is possible to achieve all-round online monitoring of the dam. At the same time, it is also possible to optimize monitoring management and greatly improve the safety of the dam. By building an activation mechanism, it is possible to further improve the maintenance efficiency of the dam and provide data support for dam management decisions. By generating alarm information and disappearance locations, the location of the piping in the dam can be located in time, effectively preventing catastrophic accidents, enhancing emergency response capabilities, and ensuring the safe and stable operation of the dam.

[0049] 2. By monitoring the water quality at the pipe burst, hidden dangers can be discovered and diagnosed in a timely manner. At the same time, risk assessment of the pipe burst can also be carried out to provide decision-making support for dam safety management. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 A flowchart of a dam safety online monitoring and management method based on the Internet of Things provided in an embodiment of the present invention;

[0051] Figure 2 A block diagram of the first sub-process of the method for online monitoring and management of dam safety based on the Internet of Things provided in an embodiment of the present invention;

[0052] Figure 3 A second sub-flow diagram of the method for online monitoring and management of dam safety based on the Internet of Things provided in an embodiment of the present invention;

[0053] Figure 4 A third sub-flow chart of the method for online monitoring and management of dam safety based on the Internet of Things provided in an embodiment of the present invention;

[0054] Figure 5 A fourth sub-flow chart of the method for online monitoring and management of dam safety based on the Internet of Things provided in an embodiment of the present invention;

[0055] Figure 6 A block diagram of the composition of the dam safety online monitoring and management method and system based on the Internet of Things provided by an embodiment of the present invention;

[0056] Figure 7 A block diagram of the composition of the marking module in the dam safety online monitoring and management system based on the Internet of Things provided by an embodiment of the present invention;

[0057] Figure 8 A block diagram of the components of the plug-in module in the dam safety online monitoring and management system based on the Internet of Things provided by an embodiment of the present invention;

[0058] Figure 9 A block diagram of the components of the embedded modules in the dam safety online monitoring and management system based on the Internet of Things provided by an embodiment of the present invention;

[0059] Figure 10 This is a block diagram of the composition of the sending module in the Internet of Things-based dam safety online monitoring and management system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0060] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0061] In Example 1, Figure 1 The implementation process of the dam safety online monitoring and management method based on the Internet of Things provided by an embodiment of the present invention is shown and described in detail below:

[0062] S100: Obtain the location of the sump at the bottom of the dam. The sump is evenly distributed around the dam. Collect liquid level data of IoT devices at the location and mark the liquid level threshold.

[0063] It is necessary to set up a circle of water collection tanks around the dam at the bottom of the dam, and set up collection pits in the water collection tanks at regular intervals. IoT level meters are installed in the collection pits to collect liquid level data in the collection pits and mark the liquid level thresholds.

[0064] In actual production, the water in the sump evaporates naturally, and under normal circumstances, the liquid level should be low or even zero.

[0065] S200: Setting nodes corresponding to the positions one by one, wherein the nodes include: a first node, a second node, a third node, ..., an nth node, transferring the liquid level data into the nodes, creating a multi-hop network architecture, and integrating all the nodes into the multi-hop network architecture to generate a monitoring network, and inserting a label consisting of a monitoring template.

[0066] Set up the same number of nodes as the sumps, including the first node, the second node, the third node, and the nth node, synchronize the liquid level data of the sumps to the nodes, create a multi-hop network architecture, and integrate the nodes into the multi-hop network architecture to generate a monitoring network.

[0067] The multi-hop network architecture is a data transmission structure in which data is not transmitted directly to the target node, but is forwarded through multiple intermediate nodes. In this application, the data in each node is transmitted sequentially. The monitoring template is a template used to collect node level data, attributes, etc. This data is filled into the monitoring template, and a label is generated. Finally, the label is inserted into the monitoring network. The advantage of this is that the node level data can be quickly found.

[0068] S300: establishing a communication link between the nodes, unidirectionally linking all the nodes, and embedding an activation mechanism into the communication link, wherein the nth node is linked to the first node;

[0069] The activation mechanism includes: when the liquid level data in the first node does not exceed the liquid level threshold, generating a trigger signal and sending the trigger signal to the second node; if it exceeds, closing the communication link.

[0070] Build a communication link between nodes, and link all nodes in sequence, link the nth node to the first node to form a closed loop; when the liquid level data in the first node does not exceed the liquid level threshold, generate a trigger signal and send this trigger signal to the second node. If the liquid level data in the second node does not exceed the liquid level threshold, continue to send the trigger signal to the third node. If the liquid level data in the second node exceeds the liquid level threshold, close the communication link between the second node and the third node.

[0071] S400: Integrate a monitoring strategy into the first node, wherein the monitoring strategy is that if the first node does not receive a trigger signal within a preset time period, an alarm message is generated, the disappearance position of the trigger signal is traversed by using the communication link, the disappearance position is integrated into the alarm message, and the integrated alarm message is sent to a preset terminal.

[0072] A monitoring strategy is integrated into the first node. If the first node does not receive a trigger signal within a preset time period, an alarm message is generated, where the preset time period is pre-determined by the staff. When the alarm message is generated, the communication link is traced back to locate the disappearance position of the trigger signal, and the disappearance position is integrated into the alarm message. The integrated alarm message is sent to a preset terminal, where the preset terminal can be a management terminal.

[0073] In Example 2, Figure 2 The implementation process of the online monitoring and management method for dam safety based on the Internet of Things provided by an embodiment of the present invention is shown. S100 is described in detail below:

[0074] S101: Collect structural data of the dam, draw a plane distribution map, determine the location of the sump, and use GPS positioning technology to mark the location on the plane distribution map.

[0075] Collect the structural data of the dam, where the structural data comes from design drawings and construction records, draw a plan distribution map of the dam, and determine the location of the sump. Use GPS positioning technology to mark the location on the plan distribution map.

[0076] S102: Numbering the sump, collecting unique identifiers of IoT devices, and configuring a correspondence between the numbers and the unique identifiers.

[0077] The collection pits are numbered, and the unique identifiers of the IoT devices are collected to establish a corresponding relationship between the numbers and the unique identifiers. The advantage of this is that the location of the collection pit can be quickly located based on the unique identifiers of the IoT devices.

[0078] In Example 3, Figure 3The implementation process of the online monitoring and management method for dam safety based on the Internet of Things provided by an embodiment of the present invention is shown. S200 is described in detail below:

[0079] S201: Constructing the same number of nodes as the sump, and synchronizing the liquid level data and liquid level thresholds into the nodes.

[0080] Build the same number of nodes as the sumps, and synchronize the liquid level data and liquid level thresholds to the nodes to complete the data construction of the nodes.

[0081] S202: Determine the span frequency of each node according to the liquid level data, and locate the corresponding relationship between the span frequency and time.

[0082] The span frequency of each node is located, and the corresponding relationship between the span frequency and time is determined. Each node has its corresponding span frequency, which means that only when the time set by the span frequency is reached will the IoT device be started to collect liquid level data.

[0083] S203: Obtain the current time, determine whether the current time satisfies the crossing frequency, if so, traverse all nodes in sequence, if not, cross the node.

[0084] Get the current moment, find the nodes that meet the crossing frequency, collect liquid level data for these nodes, generate trigger signals, and traverse the nodes in turn; if a node does not meet the crossing frequency, directly skip this node, where skipping means omitting or skipping.

[0085] For example, the first node collects liquid level data every 2 hours, the second node collects liquid level data every 3 hours, and the third node collects liquid level data every 2 hours. That is, in the first 2 hours of traversal, the second node is omitted.

[0086] In Example 4, Figure 3 The implementation process of the online monitoring and management method for dam safety based on the Internet of Things provided by an embodiment of the present invention is shown. S200 is further described in detail below.

[0087] S204: Configuring attributes of the node, wherein the attributes at least include: the location, liquid level data, and liquid level threshold.

[0088] Determine the attributes of each node, where the attributes include the node's location, the node's liquid level data, and the liquid level threshold, etc. In addition, the attributes should also include the node number, the number of the adjacent node, etc.

[0089] S205: inserting a warning value into the node, generating the warning information when the liquid level data is greater than the warning value, and integrating the liquid level data of the node into the warning information.

[0090] Insert a warning value into the node. If the liquid level data is greater than the warning value, it means that the piping flow is too large and requires immediate attention. The liquid level data for this node is integrated into the alarm information. It is important to note that the warning value is greater than the liquid level threshold. When the liquid level data reaches the warning value, it needs to be processed immediately. When the liquid level data reaches the liquid level threshold, the changes in the liquid level data should be closely monitored. In actual production, small, regular piping may be caused by relatively stable groundwater pressure and flow, and relatively uniform soil pore structure. In this case, close attention to the piping flow is sufficient. However, if a piping with abnormal flow occurs, it may indicate abnormal groundwater pressure or changes in the internal soil structure, which requires immediate attention.

[0091] In Example 5, Figure 4 The implementation process of the online monitoring and management method for dam safety based on the Internet of Things provided by an embodiment of the present invention is shown. S300 is described in detail below:

[0092] S301: defining a start condition of the activation mechanism, where the start condition is time or event.

[0093] Determine the starting conditions of the activation mechanism. Only when the time or event meets the starting conditions will the activation mechanism be started, and all nodes will be traversed in turn. The advantage of doing this is that it can reduce the burden on monitoring equipment and reduce data processing and storage requirements.

[0094] S302: Link all the nodes to generate a sequential activation architecture.

[0095] Link all nodes to generate a sequential activation architecture, where the sequential activation architecture is a structure that activates nodes in a specific order. The activation of each node depends on the trigger signal output by the previous node.

[0096] In Example 6, Figure 5 The implementation process of the online monitoring and management method for dam safety based on the Internet of Things provided by an embodiment of the present invention is shown. S400 is described in detail below:

[0097] S401: Based on the sequential activation architecture and the activation mechanism, determine whether a first node receives a trigger signal.

[0098] According to the sequential activation architecture and activation mechanism, after traversing in sequence, it is determined whether the first node receives the trigger signal.

[0099] S402: Integrate a root node into the first node, and establish a coordination relationship between the root node and all nodes.

[0100] Integrate the root node into the first node and manage all nodes using the coordination relationship.

[0101] S403: Determine the monitoring time of the node, draw a monitoring schedule according to the spanning frequency, and synchronize it to the root node.

[0102] Determine the monitoring time for each node. The monitoring time is determined by the corresponding relationship between the span frequency and time. The monitoring events are summarized and a monitoring schedule is generated. After the trigger signal is generated, if the next node has not reached the monitoring time, the next node is skipped.

[0103] In Example 7, different from Example 1, in this embodiment of the present invention, the method further includes:

[0104] Collecting water quality data uploaded by sensors in the disappearing location, the water quality data including historical water quality data and real-time water quality data;

[0105] Abnormal features are extracted from the historical water quality data, and a water quality curve is drawn with the current moment as the horizontal coordinate and the real-time water quality data as the vertical coordinate, and the abnormal features are marked on the water quality curve.

[0106] A water quality sensing device is set in the sump corresponding to the disappearance position, wherein the water quality sensing device can be a turbidity sensor or an optical sensor, etc. The measured water quality data is divided into historical water quality data and real-time water quality data, and abnormal features in the historical water quality data are extracted. The abnormal features are the water quality data corresponding to when the pipe water in the sump is muddy water.

[0107] The real-time water quality curve is drawn with the current time as the horizontal axis and the real-time water quality as the vertical axis. When the real-time water quality curve meets the abnormal characteristics, an alarm message is generated.

[0108] In actual production, if the water gushing out of the pipe contains silt, it means that the dam may be potentially dangerous or damaged and needs to be treated immediately.

[0109] Figure 6 The following is a structural block diagram of a dam safety online monitoring and management system based on the Internet of Things provided by an embodiment of the present invention. The dam safety online monitoring and management system based on the Internet of Things 1 includes:

[0110] The marking module 11 is used to obtain the location of the water collection pit at the bottom of the dam, which is evenly distributed around the dam, collect the liquid level data of the IoT devices at the location, and mark the liquid level threshold;

[0111] An insertion module 12 is configured to set nodes corresponding to the positions one by one, wherein the nodes include: a first node, a second node, a third node, ..., an nth node, transfer the liquid level data to the nodes, create a multi-hop network architecture, integrate all the nodes into the multi-hop network architecture, generate a monitoring network, and insert a label composed of a monitoring template;

[0112] an embedding module 13 for establishing a communication link between the nodes and unidirectionally linking all nodes, and embedding an activation mechanism into the communication link, wherein the nth node is linked to the first node;

[0113] The activation mechanism includes: when the liquid level data in the first node does not exceed the liquid level threshold, generating a trigger signal and sending the trigger signal to the second node, and if it exceeds, closing the communication link;

[0114] The sending module 14 is used to integrate a monitoring strategy into the first node, wherein the monitoring strategy is that if the first node does not receive a trigger signal within a preset time period, an alarm message is generated, the disappearance position of the trigger signal is traversed by using the communication link, the disappearance position is integrated into the alarm message, and the integrated alarm message is sent to a preset terminal.

[0115] Figure 7 The following is a structural block diagram of the dam safety online monitoring and management system based on the Internet of Things provided by an embodiment of the present invention. The marking module 11 includes:

[0116] The acquisition unit 111 is used to collect structural data of the dam, draw a plan distribution map, determine the location of the sump, and mark the location in the plan distribution map using GPS positioning technology;

[0117] The corresponding unit 112 is used to number the sump, collect the unique identifier of the IoT device, and configure the corresponding relationship between the number and the unique identifier.

[0118] Figure 8 The following is a structural block diagram of the dam safety online monitoring and management system based on the Internet of Things provided by an embodiment of the present invention. The insertion module 12 includes:

[0119] A synchronization unit 121 is used to construct the same number of nodes as the sump, and synchronize the liquid level data and liquid level threshold to the nodes;

[0120] A positioning unit 122 is configured to determine the span frequency of each node based on the liquid level data, and locate the corresponding relationship between the span frequency and time;

[0121] The spanning unit 123 is configured to obtain the current time, determine whether the current time satisfies the spanning frequency, and if so, traverse all nodes in sequence; if not, span the node;

[0122] A configuration unit 124 is configured to configure attributes of the node, wherein the attributes include at least: the location, liquid level data, and liquid level threshold;

[0123] The integration unit 125 is configured to insert a warning value into the node, generate the warning information when the liquid level data is greater than the warning value, and integrate the liquid level data of the node into the warning information.

[0124] Figure 9 The following is a structural block diagram of the dam safety online monitoring and management system based on the Internet of Things provided by an embodiment of the present invention. The embedded module 13 includes:

[0125] A definition unit 131 is configured to define a start condition for the activation mechanism, wherein the start condition is a time or an event;

[0126] The linking unit 132 is used to link all the nodes to generate a sequential activation architecture.

[0127] Figure 10 The following is a structural block diagram of the dam safety online monitoring and management system based on the Internet of Things provided by an embodiment of the present invention. The sending module 14 includes:

[0128] A determination unit 141 is configured to determine whether the first node receives a trigger signal according to the sequential activation architecture and the activation mechanism;

[0129] An establishing unit 142 is configured to integrate a root node into the first node and establish a coordinated relationship between the root node and all nodes;

[0130] The drawing unit 143 is configured to determine the monitoring events of the node, draw a monitoring schedule according to the spanning frequency, and synchronize the schedule to the root node.

[0131] The marking module 11 is mainly used to complete step S100, the inserting module 12 is mainly used to complete step S200, the embedding module 13 is mainly used to complete step S300, and the sending module 14 is mainly used to complete step S400;

[0132] The acquisition unit 111 is mainly used to complete step S101, and the corresponding unit 112 is mainly used to complete step S102;

[0133] The synchronization unit 121 is mainly used to complete step S201, the positioning unit 122 is mainly used to complete step S202, the spanning unit 123 is mainly used to complete step S203, the configuration unit 124 is mainly used to complete step S204, and the integration unit 125 is mainly used to complete step S205;

[0134] The definition unit 131 is mainly used to complete step S301, and the linking unit 132 is mainly used to complete step S302;

[0135] The judging unit 141 is mainly used to complete step S401 , the establishing unit 142 is mainly used to complete step S402 , and the drawing unit 143 is mainly used to complete step S403 .

[0136] The technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above-mentioned embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0137] The above-described embodiments merely illustrate several implementations of the present invention, and while their descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art would be able to make numerous variations and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be determined by the appended claims.

[0138] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A dam safety online monitoring and management method based on the Internet of Things, characterized in that: The method comprises: S100: Obtaining the location of the sump at the bottom of the dam, where the sump is evenly distributed around the dam, collecting liquid level data from IoT devices at the location, and marking a liquid level threshold; S200: Setting nodes corresponding to the positions one by one, wherein the nodes include: a first node, a second node, a third node, ..., an nth node, transferring the liquid level data to the nodes, creating a multi-hop network architecture, integrating all the nodes into the multi-hop network architecture, generating a monitoring network, and inserting a label composed of a monitoring template; S300: establishing a communication link between the nodes, unidirectionally linking all the nodes, and embedding an activation mechanism into the communication link, wherein the nth node is linked to the first node; The activation mechanism includes: when the liquid level data in the first node does not exceed the liquid level threshold, generating a trigger signal and sending the trigger signal to the second node, and if it exceeds, closing the communication link; S400: Integrate a monitoring strategy into the first node, wherein the monitoring strategy is that if the first node does not receive a trigger signal within a preset time period, an alarm message is generated, the disappearance position of the trigger signal is traversed by using the communication link, the disappearance position is integrated into the alarm message, and the integrated alarm message is sent to a preset terminal.

2. The dam safety online monitoring and management method based on the Internet of Things according to claim 1 is characterized in that: The S100 includes: Collecting structural data of the dam, drawing a plan distribution map, determining the location of the sump, and marking the location on the plan distribution map using GPS positioning technology; The sump is numbered, the unique identifier of the IoT device is collected, and a corresponding relationship between the number and the unique identifier is configured.

3. The dam safety online monitoring and management method based on the Internet of Things according to claim 2 is characterized in that: The S200 includes: Constructing the same number of nodes as the sump, and synchronizing the liquid level data and liquid level thresholds into the nodes; Determine the span frequency of each node based on the liquid level data, and locate the corresponding relationship between the span frequency and time; Get the current time, determine whether the current time meets the crossing frequency, if so, traverse all nodes in sequence, if not, cross the node.

4. The online monitoring and management method for dam safety based on the Internet of Things according to claim 3 is characterized in that: The S200 further includes: Configuring attributes of the node, wherein the attributes include at least: location, liquid level data, and liquid level threshold; A warning value is inserted into the node, and when the liquid level data is greater than the warning value, the warning information is generated, and the liquid level data of the node is integrated into the warning information.

5. The dam safety online monitoring and management method based on the Internet of Things according to claim 3 is characterized in that: The S300 includes: Defining a start condition for the activation mechanism, wherein the start condition is a time or an event; All of the nodes are linked to generate a sequential activation architecture.

6. The method for online monitoring and management of dam safety based on the Internet of Things according to claim 5 is characterized in that: The S400 includes: Based on the sequential activation architecture and the activation mechanism, determining whether the first node receives a trigger signal; Integrating a root node into the first node, and establishing a coordination relationship between the root node and all nodes; The monitoring time of all nodes is determined, and a monitoring schedule is drawn according to the spanning frequency, and synchronized to the root node.

7. The online monitoring and management method for dam safety based on the Internet of Things according to claim 3 is characterized in that: The method further comprises: Collecting water quality data uploaded by sensors in the disappearing location, the water quality data including historical water quality data and real-time water quality data; Abnormal features are extracted from the historical water quality data, and a water quality curve is drawn with the current moment as the horizontal coordinate and the real-time water quality data as the vertical coordinate, and the abnormal features are marked on the water quality curve.

8. A dam safety online monitoring and management system based on the Internet of Things, characterized by: The system comprises: A marking module is used to obtain the location of the water collection pits at the bottom of the dam, which are evenly distributed around the dam, collect liquid level data from IoT devices at these locations, and mark the liquid level threshold; an insertion module configured to set nodes corresponding to the positions one by one, wherein the nodes include: a first node, a second node, a third node, ..., an nth node, transfer the liquid level data into the nodes, create a multi-hop network architecture, integrate all the nodes into the multi-hop network architecture, generate a monitoring network, and insert a label composed of a monitoring template; an embedding module for establishing a communication link between the nodes and unidirectionally linking all nodes, and embedding an activation mechanism into the communication link, wherein the nth node is linked to the first node; The activation mechanism includes: when the liquid level data in the first node does not exceed the liquid level threshold, generating a trigger signal and sending the trigger signal to the second node, and if it exceeds, closing the communication link; A sending module is used to integrate a monitoring strategy into the first node, wherein the monitoring strategy is that if the first node does not receive a trigger signal within a preset time period, an alarm message is generated, the disappearance position of the trigger signal is traversed by using the communication link, the disappearance position is integrated into the alarm message, and the integrated alarm message is sent to a preset terminal.

9. The dam safety online monitoring and management system based on the Internet of Things according to claim 8, wherein the marking module comprises: A collection unit is used to collect structural data of the dam, draw a plan distribution map, determine the location of the sump, and mark the location on the plan distribution map using GPS positioning technology; The corresponding unit is used to number the sump, collect the unique identifier of the Internet of Things device, and configure the corresponding relationship between the number and the unique identifier.

10. The dam safety online monitoring and management system based on the Internet of Things according to claim 9, wherein the plug-in module comprises: A synchronization unit, configured to construct the same number of nodes as the sump, and synchronize the liquid level data and liquid level thresholds to the nodes; a positioning unit, configured to determine the span frequency of each node based on the liquid level data, and locate the corresponding relationship between the span frequency and time; A spanning unit is used to obtain the current time, determine whether the current time satisfies the spanning frequency, and if so, traverse all nodes in sequence; if not, span the node; A configuration unit, configured to configure attributes of the node, wherein the attributes include at least: the location, liquid level data, and liquid level threshold; The integration unit is used to insert a warning value into the node, generate the alarm information when the liquid level data is greater than the warning value, and integrate the liquid level data of the node into the alarm information.

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