A hydraulic concrete durability monitoring system based on intelligent sensor network

Abstract

The application belongs to the field of concrete monitoring, and discloses a hydraulic concrete durability monitoring system based on an intelligent sensor network, which comprises a sensor module, a data transmission module, a data processing and analysis module and a warning module; the sensor module is used for acquiring monitoring parameters of the hydraulic concrete; the data transmission module is used for transmitting the monitoring parameters acquired by the sensor module to the data processing and analysis module; the data processing and analysis module is used for analyzing the durability of the hydraulic concrete according to the monitoring parameters and obtaining an analysis result; and the warning module is used for warning the durability of the hydraulic concrete according to the analysis result. Compared with the prior art, the application can continuously acquire monitoring parameters by setting the sensor module, can realize real-time monitoring of the hydraulic concrete, can automatically realize durability warning, and has higher monitoring efficiency.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of concrete monitoring, and particularly relates to a hydraulic concrete durability monitoring system based on an intelligent sensor network. BACKGROUND

[0002] Hydraulic concrete refers to concrete used for hydraulic structures that are often or periodically subjected to the action of environmental water. Hydraulic concrete structures are prone to chemical corrosion, physical wear and tear, and biological corrosion due to long-term exposure to a water environment, resulting in a decrease in structural durability. Traditional durability monitoring methods rely on periodic manual detection, and have problems such as low monitoring efficiency, discontinuous data, and inability to provide real-time early warning. SUMMARY

[0003] The present application aims to disclose a hydraulic concrete durability monitoring system based on an intelligent sensor network, which solves the technical problems presented in the background.

[0004] In order to achieve the above-mentioned purpose, the present application provides the following technical solutions:

[0005] The present application provides a hydraulic concrete durability monitoring system based on an intelligent sensor network, comprising a sensor module, a data transmission module, a data processing and analysis module, and an early warning module.

[0006] The sensor module is used to obtain monitoring parameters of the hydraulic concrete.

[0007] The data transmission module is used to transmit the monitoring parameters obtained by the sensor module to the data processing and analysis module.

[0008] The data processing and analysis module is used to analyze the durability of the hydraulic concrete according to the monitoring parameters, and obtain an analysis result.

[0009] The early warning module is used to provide durability early warning for the hydraulic concrete according to the analysis result.

[0010] Optionally, the monitoring parameters include temperature, humidity, stress, and chloride ion content.

[0011] Optionally, the sensor module comprises a temperature sensor, a humidity sensor, a stress sensor, and a chloride ion detection sensor.

[0012] The temperature sensor is used to obtain the temperature of the hydraulic concrete.

[0013] The humidity sensor is used to obtain the humidity of the hydraulic concrete.

[0014] The stress sensor is used to obtain the stress of the hydraulic concrete.

[0015] The chloride ion detection sensor is used to obtain the chloride ion content of the hydraulic concrete.

[0016] Optionally, the data transmission module comprises an Internet of Things gateway and a plurality of wireless sensor nodes.

[0017] The wireless sensor nodes are connected with the sensor modules, and the sensor modules transmit the obtained monitoring parameters to the wireless sensor nodes.

[0018] The Internet of Things gateway is used for clustering the wireless sensor nodes, and the wireless sensor nodes are divided into member nodes and cluster head nodes.

[0019] The member nodes are used for sending the monitoring parameters to the cluster head nodes.

[0020] The cluster head nodes are used for receiving the monitoring parameters sent by the member nodes, and for sending the monitoring parameters received from the sensor modules and the monitoring parameters received from the member nodes to the Internet of Things gateway.

[0021] The Internet of Things gateway is used for transmitting the monitoring parameters to the data processing and analysis module.

[0022] Optionally, the clustering of the wireless sensor nodes comprises dividing the wireless sensor nodes into member nodes and cluster head nodes, and comprises:

[0023] The wireless sensor nodes are clustered by using an adaptive clustering interval, and the wireless sensor nodes are divided into member nodes and cluster head nodes.

[0024] Optionally, the determination process of the adaptive clustering interval comprises:

[0025] The adaptive clustering interval is calculated by using the following formula:

[0026]

[0027] T b and T b-1 respectively represent the bth and (b-1)th clustering intervals, B represents an upper limit value of the set clustering times, ts represents a set time length, and miT represents a lower limit value of the clustering interval, and b is greater than or equal to 2.

[0028] The value of the first clustering interval T1 is δ×ts, and δ is a clustering control parameter.

[0029] Optionally, the clustering control parameter is 50.

[0030] Optionally, the member nodes and the cluster head nodes communicate with each other by using ZigBee protocol or lora protocol.

[0031] The cluster head nodes and the Internet of Things gateway communicate with each other by using ZigBee protocol or lora protocol.

[0032] Optionally, the communication mode between the Internet of Things gateway and the data processing and analysis module includes satellite communication, WiFi communication, 4G communication and 5G communication.

[0033] Optionally, the durability of the hydraulic concrete is analyzed according to the monitoring parameters to obtain an analysis result, including:

[0034] The monitoring index of the hydraulic concrete is calculated according to the monitoring parameters, and the monitoring index is taken as the analysis result.

[0035] The calculation formula of the monitoring index is:

[0036]

[0037] dura represents the monitoring index of the hydraulic concrete, Temp2 represents the set comparative temperature, Temp1 represents the average temperature calculated according to the monitoring parameters, Humi2 represents the set comparative humidity, Humi1 represents the average humidity calculated according to the monitoring parameters, Stre2 represents the set stress comparative value, Stre1 represents the average stress calculated according to the monitoring parameters, chlcnt1 represents the average chloride ion content calculated according to the monitoring parameters, chlcnt2 represents the set chloride ion content comparative value, w1, w2, w3 and w4 represent the first weight, the second weight, the third weight and the fourth weight respectively.

[0038] Beneficial effects:

[0039] Compared with the prior art, the monitoring parameters of the hydraulic concrete are acquired by setting the sensor module, the acquisition of the monitoring parameters can be continuously performed, real-time monitoring of the hydraulic concrete is realized, and the durability early warning can be automatically realized, and the monitoring efficiency is higher. BRIEF DESCRIPTION OF DRAWINGS

[0040] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0041] Figure 1 It is a schematic diagram of a hydraulic concrete durability monitoring system based on an intelligent sensor network.

[0042] Figure 2 It is a schematic diagram of the process of calculating the clustering comparison value of each wireless sensor node. DETAILED DESCRIPTION

[0043] With reference to the accompanying drawings: the technical solutions in the embodiments of the present application will be described clearly and completely, obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of the present application.

[0044] As shown in Figure 1 The present application provides a kind of hydraulic concrete durability monitoring system based on intelligent sensor network, including sensor module, data transmission module, data processing analysis module and early warning module;

[0045] Sensor module is used to obtain the monitoring parameter of hydraulic concrete;

[0046] Data transmission module is used to transmit the monitoring parameter obtained by sensor module to data processing analysis module;

[0047] Data processing analysis module is used to analyze the durability of hydraulic concrete according to monitoring parameter, obtains analysis result;

[0048] Early warning module is used to warn the durability of hydraulic concrete according to analysis result.

[0049] Through setting sensor module, the acquisition of monitoring parameter of hydraulic concrete can be carried out continuously, realizes the real-time monitoring of hydraulic concrete, and can automatically realize durability early warning, and the efficiency of monitoring is higher.

[0050] In the present application, sensor module has multiple, multiple sensor modules are dispersedly arranged at each place of the hydraulic concrete to be monitored, and large-scale comprehensive monitoring is realized.

[0051] Optionally, monitoring parameter includes temperature, humidity, stress and chloride ion content.

[0052] Optionally, sensor module includes temperature sensor, humidity sensor, stress sensor and chloride ion detection sensor;

[0053] Temperature sensor is used to obtain the temperature of hydraulic concrete;

[0054] Humidity sensor is used to obtain the humidity of hydraulic concrete;

[0055] Stress sensor is used to obtain the stress of hydraulic concrete;

[0056] Chloride ion detection sensor is used to obtain the chloride ion content of hydraulic concrete.

[0057] When the sensor is arranged on the hydraulic concrete under the water level, the survivability of the sensor in the harsh environment can be increased by using a corrosion-resistant coating on a part of the sensor or by using a special material to manufacture the sensor; and the replacement of the vulnerable parts is considered in the design of the sensor, so that the maintenance and replacement are possible without replacing the entire device.

[0058] In addition, the sensor module can further include a pH sensor; the pH sensor is used to acquire the pH of the hydraulic concrete.

[0059] Optionally, the monitoring parameter of the hydraulic concrete is acquired, including:

[0060] The monitoring parameter of the hydraulic concrete is acquired based on an adaptive acquisition frequency.

[0061] Optionally, the adaptive acquisition frequency is determined in the following manner:

[0062] If the hydraulic concrete is in the initial stage of pouring and curing, the acquisition frequency is set to once per hour;

[0063] In this stage, the temperature and humidity of the concrete change greatly, the hydration reaction is relatively intense, and real-time monitoring is needed.

[0064] If the hydraulic concrete is in the hardening stage, the acquisition frequency is set to once every 4 hours;

[0065] As the strength of the concrete gradually increases, the temperature and humidity change slow down, and the corresponding monitoring demand also decreases.

[0066] If the hydraulic concrete is in the long-term monitoring stage, the acquisition frequency is set to once every 12 hours.

[0067] After the state of the concrete is stable, the focus of the monitoring is usually the health and durability of the structure, such as stress, chloride ion content, etc.

[0068] By setting different acquisition frequencies for different stages, the present application can obtain the changes of the hydraulic concrete in time while avoiding the acquisition of monitoring data too frequently in the long-term monitoring stage, thereby improving the working life of the wireless sensor node.

[0069] Pouring and curing initial stage:

[0070] Time interval: 0 to 7 days (sometimes can be extended to 14 days)

[0071] Background: In the initial stage after the pouring of the concrete, the hydration reaction of the cement is the most active, the strength of the concrete rapidly increases, but at the same time, it is also relatively fragile. In this stage, the changes of the temperature and humidity have an important influence on the strength and cracks of the concrete, so high-frequency monitoring is needed.

[0072] Key activities: Monitoring of temperature, humidity, and stress, especially in mass concrete construction where temperature changes can cause thermal stress and cracking. High monitoring frequency is required.

[0073] Monitoring focus: Temperature, humidity, stress, early strength, etc. The main focus is on the curing conditions of the concrete to ensure its full hydration.

[0074] Hardening phase:

[0075] Time interval: 7 to 28 days (varies depending on concrete type and usage conditions)

[0076] Background: This phase is critical for the development of concrete strength. The concrete transitions from a plastic state to a hardened state, and the cement hydration reaction continues but slows down. Although the strength increases gradually, the concrete remains fragile, so monitoring frequency should be maintained.

[0077] Key activities: Temperature and humidity control are still important during the hardening phase, especially for the development of early strength and durability. Although the strength grows rapidly, stress and cracking issues can still occur, especially under extreme environmental conditions.

[0078] Monitoring focus: Monitor temperature changes, humidity retention, stress distribution, strength development, chloride ion content, etc. Temperature changes are small, but humidity and strength development should still be monitored.

[0079] Long-term monitoring phase:

[0080] Time interval: 28 days and beyond (usually years to decades, depending on project requirements)

[0081] Background: After 28 days, the concrete has completed its strength growth and is in a stable state. At this point, the performance of the concrete has stabilized, and the focus is on its long-term durability and safety, such as stress, chloride ion penetration, etc. Long-term monitoring is mainly used to ensure the health of the structure and to detect possible aging or damage in a timely manner.

[0082] Key activities: Long-term use of concrete structures, durability assessment, stress monitoring, crack inspection, chloride ion penetration, etc. Over time, environmental changes (such as temperature and humidity changes) will gradually affect the concrete, which may cause aging or other long-term problems.

[0083] Monitoring focus: Monitor the stress, chloride ion content, structural damage, and crack development of the concrete, focusing on the long-term durability of the concrete and the overall health of the structure.

[0084] Optionally, the data transmission module includes an Internet of Things gateway and a plurality of wireless sensor nodes;

[0085] The wireless sensor node is connected with the sensor module, and the sensor module transmits the obtained monitoring parameter to the wireless sensor node;

[0086] The Internet of Things gateway is used for clustering the wireless sensor nodes, and the wireless sensor nodes are divided into member nodes and cluster head nodes;

[0087] The member node is used for sending the monitoring parameter to the cluster head node;

[0088] The cluster head node is used for receiving the monitoring parameter sent by the member node, and for sending the monitoring parameter received from the sensor module and the monitoring parameter received from the member node to the Internet of Things gateway;

[0089] The Internet of Things gateway is used for transmitting the monitoring parameter to the data processing and analysis module.

[0090] Optionally, the wireless sensor nodes are clustered, and the wireless sensor nodes are divided into member nodes and cluster head nodes, comprising:

[0091] The wireless sensor nodes are clustered by using adaptive clustering interval, and the wireless sensor nodes are divided into member nodes and cluster head nodes.

[0092] Optionally, the wireless sensor nodes are clustered by using adaptive clustering interval, comprising:

[0093] The clustering comparison value of each wireless sensor node is calculated respectively;

[0094] The first tenth of the wireless sensor nodes with the largest clustering comparison value are taken as the cluster head nodes, and the remaining nodes are taken as the member nodes;

[0095] The member nodes are divided into the cluster in which the nearest cluster head node is located.

[0096] Specifically, after clustering, the list of the IDs of the member nodes and the cluster head nodes can be known, and the list is sent to each wireless sensor node, so that the wireless sensor node can know whether it belongs to the member node or the cluster head node.

[0097] Optionally, as Figure 2 The clustering comparison value of each wireless sensor node is calculated respectively, comprising:

[0098] In the first step, all the wireless sensor nodes are stored in a set U1;

[0099] In the second step, a wireless sensor node is randomly selected from the set U1, and the clustering comparison value of the selected wireless sensor node is calculated;

[0100] Thirdly, deleting the wireless sensor nodes in U1 which distance to the selected wireless sensor node is less than half of the maximum communication radius of the selected wireless sensor node;

[0101] Fourthly, setting the clustering comparison value of the wireless sensor nodes in U1 which distance to the selected wireless sensor node is less than half of the communication radius of the selected wireless sensor node as 0;

[0102] Fifthly, judging whether there still exists wireless sensor nodes in U1, if yes, entering the second step, if not, ending the calculation.

[0103] Different from the existing clustering method, the present application does not directly calculate the clustering comparison value of each wireless sensor node, because it is easy to cause the clustering comparison value of the wireless sensor nodes in the area where the wireless sensor nodes are densely distributed to be large, and the number of cluster heads generated in the area is too much, causing the packet loss rate to be too large. Therefore, the present application firstly selects a wireless sensor node to calculate the clustering comparison value, and then sets the clustering comparison value of the other wireless sensor nodes around as 0 and deletes them from U1, so that the number of cluster head nodes near the randomly selected wireless sensor node can be effectively reduced, the distribution of the cluster head nodes is more uniform, and the above problems are effectively solved.

[0104] Optionally, the calculation formula of the clustering comparison value is:

[0105]

[0106] acp s is the clustering comparison value of the wireless sensor node s, Ed s is the remaining percentage of the electric quantity of s, Ed max is the full percentage of the electric quantity of s, N1 s is the total number of the other wireless sensor nodes whose distance to s is less than half of the communication radius of s; N2 s is the total number of the other wireless sensor nodes whose distance to s is less than half of the communication radius of s, and a is the set proportion.

[0107] The clustering comparison value of the present application is calculated based on the data of the remaining electric quantity and the total number of the other wireless sensor nodes in the communication radius, if the value of Ed s is larger, the value of N1 s is larger, which indicates that s has stronger ability to serve as a cluster head and is more suitable to serve as a cluster head; if the value of Ed s is smaller, the value of N1 sThe smaller the value of s is, the weaker the ability of s to serve as a cluster head is, and s is less suitable to serve as a cluster head, so that the average working time of all wireless sensor nodes after a single battery replacement can be effectively balanced, and the frequency of battery replacement is reduced.

[0108] In the application, the set ratio can be 0.5.

[0109] Optionally, the process of determining the adaptive clustering interval comprises:

[0110] The adaptive clustering interval is calculated using the following formula:

[0111]

[0112] T b and T b-1 respectively represent the bth and (b-1)th clustering intervals, B represents the set upper limit value of the number of clustering times, ts represents the set time length, miT represents the lower limit value of the clustering interval, and b is greater than or equal to 2.

[0113] The value of the first clustering interval T1 is δ×ts, and δ is a clustering control parameter.

[0114] The clustering interval of the application is not fixed, but becomes smaller and smaller as the number of clustering times increases, so that the residual power among the wireless sensor nodes can be balanced more timely, and the average working time is improved.

[0115] In the application, the set upper limit value of the number of clustering times can be 200. The set time length can be 1 hour. The lower limit value of the clustering interval can be 12 hours.

[0116] Specifically, when the battery of the wireless sensor node is replaced, the value of b is reset to 1.

[0117] Optionally, the clustering control parameter is 50.

[0118] Optionally, the member node and the cluster head node communicate with each other using ZigBee protocol or lora protocol.

[0119] The cluster head node and the Internet of Things gateway communicate with each other using ZigBee protocol or lora protocol.

[0120] Optionally, the communication mode between the Internet of Things gateway and the data processing and analysis module comprises satellite communication, WiFi communication, 4G communication and 5G communication.

[0121] Optionally, the durability of the hydraulic concrete is analyzed according to the monitoring parameters to obtain an analysis result, which comprises:

[0122] The monitoring index of the hydraulic concrete is calculated according to the monitoring parameters, and the monitoring index is taken as the analysis result.

[0123] The calculation formula of the monitoring index is as follows:

[0124]

[0125] dura represents the monitoring index of the hydraulic concrete, Temp2 represents the set comparative temperature, Temp1 represents the average temperature calculated according to the monitoring parameters, Humi2 represents the set comparative humidity, Humi1 represents the average humidity calculated according to the monitoring parameters, Stre2 represents the set stress comparative value, Stre1 represents the average stress calculated according to the monitoring parameters, chlcnt1 represents the average chloride ion content calculated according to the monitoring parameters, chlcnt2 represents the set chloride ion content comparative value, w1, w2, w3 and w4 represent the first weight, the second weight, the third weight and the fourth weight respectively.

[0126] The monitoring coefficient of the present application is calculated from multiple aspects, which can more effectively represent the state of the hydraulic concrete, and is beneficial to obtain more accurate monitoring results.

[0127] In the present application, the set comparative temperature can be 50 DEG C, the set comparative humidity can be 80%, the set stress comparative value can be 60% of the design compressive strength of the hydraulic concrete, and the set chloride ion content comparative value can be 0.03% (indicating that 0.03 grams of chloride ions are contained in 100 grams of cement).

[0128] In the present application, the average temperature calculated according to the monitoring parameters can be the average temperature calculated according to all the temperatures obtained in the recent day.

[0129] In addition, the average humidity, the average stress and the average chloride ion content can all be obtained by average value calculation according to the data obtained in a day.

[0130] In the present application, the first weight, the second weight, the third weight and the fourth weight can be 0.3, 0.2, 0.25 and 0.25 respectively.

[0131] Optionally, according to the analysis result, the durability of the hydraulic concrete is prewarned, including:

[0132] It is judged whether the monitoring index is greater than the set monitoring index threshold value, and if yes, a prewarning prompt is sent.

[0133] In the present application, the set monitoring index threshold value can be 0.6.

[0134] In the present application, the early warning prompt can be realized by the way of popping up a prompt box in the electronic device used by the operation and maintenance personnel.

[0135] In addition, the operation and maintenance personnel can also be prompted by the way of short message prompt.

[0136] The preferred embodiments disclosed above are only used to help explain the present application. The preferred embodiments do not describe all the details and do not limit the present application to the specific embodiments described. Obviously, many modifications and variations can be made according to the content of the present application. The present application selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present application, so that those skilled in the art can well understand and utilize the present application. The present application is limited only by the claims and their full scope and equivalents.

Claims

1. A hydraulic concrete durability monitoring system based on intelligent sensor network, characterized by, The system comprises a sensor module, a data transmission module, a data processing and analysis module, and a warning module. The sensor module is used to obtain monitoring parameters of the hydraulic concrete. The data transmission module is used to transmit the monitoring parameters obtained by the sensor module to the data processing and analysis module. The data processing and analysis module is used to analyze the durability of the hydraulic concrete according to the monitoring parameters, and obtain an analysis result. The warning module is used to give a durability warning for the hydraulic concrete according to the analysis result. The data transmission module comprises an Internet of Things gateway and a plurality of wireless sensor nodes. The wireless sensor nodes are connected with the sensor module, and the sensor module transmits the obtained monitoring parameters to the wireless sensor nodes. The Internet of Things gateway is used to cluster the wireless sensor nodes, and divide the wireless sensor nodes into member nodes and cluster head nodes. The member nodes are used to send the monitoring parameters to the cluster head nodes. The cluster head nodes are used to receive the monitoring parameters sent by the member nodes, and send the monitoring parameters received from the sensor module and the monitoring parameters received from the member nodes to the Internet of Things gateway. The Internet of Things gateway is used to transmit the monitoring parameters to the data processing and analysis module. The clustering of the wireless sensor nodes comprises: The clustering of the wireless sensor nodes is performed by using an adaptive clustering interval, and the wireless sensor nodes are divided into member nodes and cluster head nodes. The clustering of the wireless sensor nodes by using an adaptive clustering interval comprises: The clustering comparison value of each wireless sensor node is calculated respectively. The first tenth of the wireless sensor nodes with the largest clustering comparison value are taken as the cluster head nodes, and the remaining nodes are taken as the member nodes. The member nodes are divided into the cluster where the nearest cluster head node is located. The clustering comparison value of each wireless sensor node is calculated respectively, which comprises: Step 1: all the wireless sensor nodes are stored in a set U1; Step 2: a wireless sensor node is randomly selected from the set U1, and the clustering comparison value of the selected wireless sensor node is calculated; Step 3: the wireless sensor nodes in U1 whose distance from the selected wireless sensor node is less than half of the maximum communication radius of the selected wireless sensor node are deleted; Step 4: the clustering comparison value of the wireless sensor nodes in U1 whose distance from the selected wireless sensor node is less than half of the communication radius of the selected wireless sensor node is set to 0; Step 5: whether there is still a wireless sensor node in U1 is judged, if yes, step 2 is entered, and if no, the calculation is ended. 2.The hydraulic concrete durability monitoring system based on intelligent sensor network according to claim 1, characterized in that, The monitoring parameters comprise temperature, humidity, stress, and chloride ion content. 3.The hydraulic concrete durability monitoring system based on intelligent sensor network according to claim 2, characterized in that, The sensor module comprises a temperature sensor, a humidity sensor, a stress sensor, and a chloride ion detection sensor. The temperature sensor is used to obtain the temperature of the hydraulic concrete. The humidity sensor is used to obtain the humidity of the hydraulic concrete. The stress sensor is used to obtain the stress of the hydraulic concrete. The chloride ion detection sensor is used to obtain the chloride ion content of the hydraulic concrete.

4. The system for monitoring durability of hydraulic concrete according to claim 1, wherein The determination process of the adaptive clustering interval comprises: The adaptive clustering interval is calculated by using the following formula: T b and T b-1 respectively represent the bth and (b-1)th clustering interval, B represents a set upper limit value of the number of times of clustering, ts represents a set time length, miT represents a lower limit value of the clustering interval, and b is greater than or equal to 2; The value of the first clustering interval T1 is δ×ts, and δ is a clustering control parameter.

5. The system for monitoring durability of hydraulic concrete according to claim 4, wherein The clustering control parameter is 50. 6.The hydraulic concrete durability monitoring system based on intelligent sensor network according to claim 1, wherein, The member nodes and the cluster head nodes communicate with each other by adopting ZigBee protocol or lora protocol; The cluster head nodes and the Internet of Things gateway communicate by adopting ZigBee protocol or lora protocol.

7. The system for monitoring durability of hydraulic concrete according to claim 1, wherein The communication mode between the Internet of Things gateway and the data processing and analysis module includes satellite communication, WiFi communication, 4G communication and 5G communication. 8.The hydraulic concrete durability monitoring system based on intelligent sensor network according to claim 3, characterized in that, According to the monitoring parameters, the durability of the hydraulic concrete is analyzed, and analysis results are obtained, including: According to the monitoring parameters, a monitoring index of the hydraulic concrete is calculated, and the monitoring index is taken as the analysis result; The calculation formula of the monitoring index is: dura represents the monitoring index of the hydraulic concrete, Temp2 represents a set comparative temperature, Temp1 represents an average temperature calculated according to the monitoring parameters, Humi2 represents a set comparative humidity, Humi1 represents an average humidity calculated according to the monitoring parameters, Stre2 represents a set stress comparative value, Stre1 represents an average stress calculated according to the monitoring parameters, chlcnt1 represents an average chloride ion content calculated according to the monitoring parameters, chlcnt2 represents a set comparative value of the chloride ion content, w1, w2, w3 and w4 respectively represent a first weight, a second weight, a third weight and a fourth weight.

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