Hydraulic concrete durability monitoring system based on intelligent sensor network

Abstract

The invention 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 an early warning module, the sensor module is used for acquiring monitoring parameters of hydraulic concrete; the data transmission module is used for transmitting the monitoring parameters obtained by the sensor module to the data processing and analyzing module; the data processing and analyzing module is used for analyzing the durability of the hydraulic concrete according to the monitoring parameters to obtain an analysis result; and the early warning module is used for performing durability early warning on the hydraulic concrete according to the analysis result. Compared with the prior art, the monitoring parameters of the hydraulic concrete are obtained by arranging the sensor module, the monitoring parameters can be continuously obtained, real-time monitoring of the hydraulic concrete is achieved, durability early warning can be automatically achieved, and the monitoring efficiency is higher.

Description

Technical Field

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

[0002] Hydraulic concrete refers to the concrete used in hydraulic structures that are frequently or periodically affected by environmental water. Due to the long-term exposure of hydraulic concrete structures to the water environment, they are susceptible to chemical erosion, physical wear, and biological erosion, etc., resulting in a decline in structural durability. Traditional durability monitoring methods rely on regular manual inspections, which have problems such as low monitoring efficiency, discontinuous data, and inability to give real-time warnings. Summary of the Invention

[0003] The purpose of the present invention is to disclose a durability monitoring system for hydraulic concrete based on an intelligent sensor network to solve the technical problems raised in the background art.

[0004] To achieve the above purpose, the present invention provides the following technical solutions:

[0005] The present invention provides a durability monitoring system for hydraulic concrete based on an intelligent sensor network, including 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 the monitoring parameters of 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 hydraulic concrete based on the monitoring parameters to obtain an analysis result;

[0009] The early warning module is used to give a durability warning for 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 includes 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 hydraulic concrete;

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

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

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

[0016] Optionally, the data transmission module includes an Internet of Things gateway and multiple wireless sensor nodes;

[0017] The wireless sensor nodes are connected to the sensor module, and the sensor module transmits the obtained monitoring parameters to the wireless sensor nodes;

[0018] The Internet of Things gateway is used to cluster the wireless sensor nodes, dividing the wireless sensor nodes into member nodes and cluster head nodes;

[0019] The member nodes are used to send the monitoring parameters to the cluster head nodes;

[0020] The cluster head nodes are used to receive the monitoring parameters sent by the member nodes, and to send the monitoring parameters received from the sensor module and the monitoring parameters received from the member nodes to the Internet of Things gateway;

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

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

[0023] Clustering the wireless sensor nodes with an adaptive clustering interval, dividing the wireless sensor nodes into member nodes and cluster head nodes.

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

[0025] Use the following formula to calculate the adaptive clustering interval:

[0026]

[0027] T b and T b-1 respectively represent the b-th and (b - 1)-th clustering intervals, B represents the upper limit value of the set number of clustering times, ts represents the set duration, miT represents the 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, where δ is the 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 using the ZigBee protocol or the LoRa protocol;

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

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

[0033] Optionally, analyze the durability of hydraulic concrete based on the monitoring parameters to obtain the analysis results, including:

[0034] Calculate the monitoring index of the hydraulic concrete based on the monitoring parameters, and use the monitoring index 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 comparison temperature, Temp1 represents the average temperature calculated based on the monitoring parameters, Humi2 represents the set comparison humidity, Humi1 represents the average humidity calculated based on the monitoring parameters, Stre2 represents the set stress comparison value, Stre1 represents the average stress calculated based on the monitoring parameters, chlcnt1 represents the average chloride ion content calculated based on the monitoring parameters, chlcnt2 represents the set chloride ion content comparison value, and w1, w2, w3, and w4 respectively represent the first weight, the second weight, the third weight, and the fourth weight.

[0038] Beneficial effects:

[0039] Compared with the prior art, the present invention obtains the monitoring parameters of the hydraulic concrete by setting the sensor module, can continuously obtain the monitoring parameters, realizes the real-time monitoring of the hydraulic concrete, and can automatically realize the durability early warning, with higher monitoring efficiency. Description of the Drawings

[0040] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

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

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

[0043] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0044] As Figure 1 shown, the present invention provides a durability monitoring system for hydraulic concrete based on an intelligent sensor network, including a sensor module, a data transmission module, a data processing and analysis module, and an early warning module;

[0045] The sensor module is used to obtain the monitoring parameters of the hydraulic concrete;

[0046] The data transmission module is used to transmit the monitoring parameters obtained by the sensor module to the data processing and analysis module;

[0047] The data processing and analysis module is used to analyze the durability of the hydraulic concrete according to the monitoring parameters to obtain an analysis result;

[0048] The early warning module is used to give a durability early warning for the hydraulic concrete according to the analysis result.

[0049] By setting the sensor module to obtain the monitoring parameters of the hydraulic concrete, it is possible to continuously obtain the monitoring parameters, realize the real-time monitoring of the hydraulic concrete, and automatically give a durability early warning, with higher monitoring efficiency.

[0050] In the present invention, there are multiple sensor modules, and the multiple sensor modules are dispersedly arranged at various places of the monitored hydraulic concrete to achieve comprehensive monitoring over a large range.

[0051] Optionally, the monitoring parameters include temperature, humidity, stress, and chloride ion content.

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

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

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

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

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

[0057] When the sensor is arranged on the hydraulic concrete under the water level, an anti-corrosion coating can be used on a part of the sensor or the sensor can be made of special materials, which can increase its viability in harsh environments; when designing the sensor, the replacement of vulnerable parts is considered, making maintenance and replacement possible without replacing the entire device.

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

[0059] Optionally, obtaining the monitoring parameters of the hydraulic concrete includes:

[0060] Obtaining the monitoring parameters of the hydraulic concrete 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] At this stage, the temperature and humidity of the concrete change greatly, and the hydration reaction is relatively intense, requiring real-time monitoring.

[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 changes slow down, and the corresponding monitoring requirements also decrease.

[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 concrete state is stable, the focus of 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 invention can obtain the changes of the hydraulic concrete in a timely manner while avoiding obtaining monitoring data too frequently in the long-term monitoring stage, and improving the working life of the wireless sensor node.

[0069] Initial stage of pouring and curing:

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

[0071] Background basis: In the initial stage after concrete pouring, the hydration reaction of cement is the most active, the strength of the concrete increases rapidly, but it is also relatively fragile. At this stage, the temperature and humidity changes have an important impact on the strength and crack generation of the concrete, so high-frequency monitoring is required.

[0072] Key activities: The hydration reaction of concrete, temperature control, and humidity management. Especially during the construction of mass concrete, temperature changes may cause temperature stress and cracks, so the monitoring frequency is relatively high.

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

[0074] Hardening stage:

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

[0076] Background basis: This stage is a critical period for the strength development of concrete. Concrete changes from a plastic state to a hardened state, and the cement hydration reaction continues but gradually slows down. Although the strength gradually increases, the concrete is still relatively fragile, so a certain monitoring frequency is still required.

[0077] Key activities: During the hardening stage, the control of temperature and humidity is still important, especially for the influence on early strength and durability development. Although the strength increases rapidly, stress and crack problems may still occur at this time, especially in extreme environmental conditions.

[0078] Monitoring focuses: Monitor temperature changes, humidity maintenance, stress distribution, strength development, chloride ion content, etc. The temperature change is relatively small, but the humidity and strength development still need to be monitored.

[0079] Long-term monitoring stage:

[0080] Time interval: 28 days and later (usually several years to decades, according to engineering requirements)

[0081] Background basis: Concrete has basically completed its strength growth after 28 days and is in a stable state. At this time, the performance of concrete is relatively stable, mainly focusing 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 timely detect possible aging or damage.

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

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

[0084] Optionally, the data transmission module includes an IoT gateway and multiple wireless sensor nodes;

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

[0086] The Internet of Things gateway is used to cluster the wireless sensor nodes, dividing the wireless sensor nodes into member nodes and cluster head nodes;

[0087] The member nodes are used to send the monitoring parameters to the cluster head nodes;

[0088] The cluster head nodes are used to receive the monitoring parameters sent by the member nodes, and to send the monitoring parameters received from the sensor module and the monitoring parameters received from the member nodes to the Internet of Things gateway;

[0089] The Internet of Things gateway is used to transmit the monitoring parameters to the data processing and analysis module.

[0090] Optionally, clustering the wireless sensor nodes, dividing the wireless sensor nodes into member nodes and cluster head nodes, includes:

[0091] Clustering the wireless sensor nodes with an adaptive clustering interval, dividing the wireless sensor nodes into member nodes and cluster head nodes.

[0092] Optionally, clustering the wireless sensor nodes with an adaptive clustering interval includes:

[0093] Calculating the clustering comparison value of each wireless sensor node respectively;

[0094] Taking the top one-tenth of the wireless sensor nodes with the largest clustering comparison values as the cluster head nodes, and the remaining nodes as the member nodes;

[0095] Assigning the member nodes to the cluster where 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 a member node or a cluster head node.

[0097] Optionally, as Figure 2 , calculating the clustering comparison value of each wireless sensor node respectively, includes:

[0098] The first step is to store all the wireless sensor nodes in the set U1;

[0099] The second step is to randomly select a wireless sensor node from the set U1 and calculate the clustering comparison value of the selected wireless sensor node;

[0100] Step 3: Delete the wireless sensor nodes in U1 whose distances from the selected wireless sensor nodes are less than half of the maximum communication radius of the selected wireless sensor nodes;

[0101] Step 4: Set the clustering comparison values of the wireless sensor nodes in U1 whose distances from the selected wireless sensor nodes are less than half of the communication radius of the selected wireless sensor nodes to 0;

[0102] Step 5: Determine whether there are still wireless sensor nodes in U1. If so, go to Step 2; if not, end the calculation.

[0103] Different from the existing clustering methods, the present invention does not directly calculate the clustering comparison values of each wireless sensor node respectively, because this is likely to cause the clustering comparison values of the wireless sensor nodes in the area where the wireless sensor nodes are densely distributed to be too large, and the number of cluster heads generated in this area is too large, resulting in too large a packet loss rate. Therefore, the present invention first randomly selects a wireless sensor node to calculate the clustering comparison value, and then sets the clustering comparison values of other surrounding wireless sensor nodes to 0 and deletes them from U1. In this way, the number of cluster head nodes near the randomly selected wireless sensor node can be effectively reduced, making the distribution of cluster head nodes more uniform and effectively solving the above problems.

[0104] Optionally, the calculation formula for 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 battery percentage of s, Ed max is the full battery percentage of s, N1 s is the total number of other wireless sensor nodes whose distances from s are less than half of the communication radius of s; N2 s is the total number of other wireless sensor nodes whose distances from s are less than the communication radius of s, and α is the set ratio.

[0107] The clustering comparison value of the present invention is calculated based on the data of the remaining battery and the total number of other wireless sensor nodes within the communication radius. If the value of Ed s is larger and the value of N1 s is larger, it means that the ability of s to act as a cluster head is stronger and it is more suitable to be a cluster head; if the value of Ed s is smaller and the value of N1 sThe smaller the value is, the weaker the ability of s to act as a cluster head, and the less suitable it is to be a cluster head. In this way, the average working duration of all wireless sensor nodes after a single battery replacement can be effectively balanced, and the frequency of battery replacement can be reduced.

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

[0109] Optionally, the determination process of the adaptive clustering interval includes:

[0110] Calculate the adaptive clustering interval using the following formula:

[0111]

[0112] T b and T b-1 respectively represent the b-th and (b - 1)-th clustering intervals, B represents the set upper limit value of the number of clustering times, ts represents the set duration, 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, where δ is the clustering control parameter.

[0114] The clustering interval of the present invention is not fixed, but decreases as the number of clustering times increases. In this way, the remaining power between wireless sensor nodes can be balanced more timely, and the average working duration can be improved.

[0115] In the present invention, the set upper limit value of the number of clustering times can be 200. The set duration 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 nodes and the cluster head node communicate with each other using the ZigBee protocol or the LoRa protocol;

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

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

[0121] Optionally, analyze the durability of hydraulic concrete according to the monitoring parameters to obtain the analysis results, including:

[0122] Calculate the monitoring index of hydraulic concrete based on the monitoring parameters, and use the monitoring index as the analysis result;

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

[0124]

[0125] dura represents the monitoring index of hydraulic concrete, Temp2 represents the set comparison temperature, Temp1 represents the average temperature calculated based on the monitoring parameters, Humi2 represents the set comparison humidity, Humi1 represents the average humidity calculated based on the monitoring parameters, Stre2 represents the set stress comparison value, Stre1 represents the average stress calculated based on the monitoring parameters, chlcnt1 represents the average chloride ion content calculated based on the monitoring parameters, chlcnt2 represents the set chloride ion content comparison value, and 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 invention is comprehensively calculated from multiple aspects, which can more effectively represent the state of hydraulic concrete and is conducive to obtaining more accurate monitoring results.

[0127] In the present invention, the set comparison temperature can be 50 °C; the set comparison humidity can be 80%; the set stress comparison value can be 60% of the designed compressive strength of the hydraulic concrete; the set chloride ion content comparison value can be 0.03% (indicating that there are 0.03 grams of chloride ions in every 100 grams of cement).

[0128] In the present invention, the average temperature calculated based on the monitoring parameters can be the average temperature calculated based on all the temperatures obtained in the most recent day.

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

[0130] In the present invention, 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, based on the analysis result, durability early warning is performed on the hydraulic concrete, including:

[0132] Judge whether the monitoring index is greater than the set monitoring index threshold. If so, issue a warning prompt.

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

[0134] In the present invention, the warning prompt can be implemented by popping up a prompt box in the electronic device used by the operation and maintenance personnel.

[0135] In addition, it can also be a way of prompting the operation and maintenance personnel through text message prompts.

[0136] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific embodiments described. Obviously, according to the content of this specification, many modifications and changes can be made. These embodiments are selected and specifically described in this specification in order to better explain the principle and practical application of the present invention, so that those skilled in the art can understand and utilize the present invention well. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A hydraulic concrete durability monitoring system based on an intelligent sensor network, characterized in that: It includes sensor module, data transmission module, data processing and analysis module and early warning module; The sensor module is used to obtain monitoring parameters of 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 hydraulic concrete according to the monitoring parameters and obtain the analysis results; The early warning module is used to provide durability early warning for hydraulic concrete based on the analysis results.

2. The hydraulic concrete durability monitoring system based on intelligent sensor network according to claim 1 is characterized in that: Monitored parameters include temperature, humidity, stress and chloride ion content.

3. The hydraulic concrete durability monitoring system based on intelligent sensor network according to claim 2 is characterized in that: The sensor module includes 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 hydraulic concrete; Humidity sensors are used to obtain the humidity of hydraulic concrete; Stress sensors are used to obtain stress in hydraulic concrete; The chloride ion detection sensor is used to obtain the chloride ion content of hydraulic concrete.

4. The hydraulic concrete durability monitoring system based on intelligent sensor network according to claim 1 is characterized in that: The data transmission module includes an IoT gateway and multiple wireless sensor nodes; The wireless sensor node is connected to the sensor module, and the sensor module transmits the acquired monitoring parameters to the wireless sensor node; The IoT gateway is used to cluster the wireless sensor nodes into member nodes and cluster head nodes; The member nodes are used to send monitoring parameters to the cluster head node; The cluster head node is used to receive the monitoring parameters sent by the member nodes, and is used to 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 IoT gateway is used to transmit monitoring parameters to the data processing and analysis module.

5. The hydraulic concrete durability monitoring system based on intelligent sensor network according to claim 4 is characterized in that: The wireless sensor nodes are clustered into member nodes and cluster head nodes, including: Adaptive clustering interval is used to cluster the wireless sensor nodes, and the wireless sensor nodes are divided into member nodes and cluster head nodes.

6. The hydraulic concrete durability monitoring system based on intelligent sensor network according to claim 5 is characterized in that: The process of determining the adaptive clustering interval includes: The adaptive clustering interval is calculated using the following formula: T b and T b-1 They represent the bth and b-1th clustering intervals respectively, B represents the upper limit of the number of clustering times, ts represents the set duration, miT represents the lower limit of the clustering interval, and b is greater than or equal to 2; The value of the first clustering interval T1 is δ×ts, where δ is a clustering control parameter.

7. The hydraulic concrete durability monitoring system based on intelligent sensor network according to claim 6 is characterized in that: The clustering control parameter is 50.

8. The hydraulic concrete durability monitoring system based on intelligent sensor network according to claim 4 is characterized in that: Member nodes and cluster head nodes communicate with each other using ZigBee protocol or Lora protocol; The cluster head node and the IoT gateway communicate using the ZigBee protocol or the Lora protocol.

9. The hydraulic concrete durability monitoring system based on intelligent sensor network according to claim 4 is characterized in that: The communication methods between the IoT gateway and the data processing and analysis module include satellite communication, WiFi communication, 4G communication and 5G communication.

10. The hydraulic concrete durability monitoring system based on intelligent sensor network according to claim 3 is characterized in that: The durability of hydraulic concrete is analyzed according to the monitoring parameters to obtain the analysis results, including: Calculate the monitoring index of hydraulic concrete according to the monitoring parameters and use the monitoring index as the analysis result; The calculation formula of the monitoring index is: dura represents the monitoring index of hydraulic concrete, Temp2 represents the set contrast temperature, Temp1 represents the average temperature calculated according to the monitoring parameters, Humi2 represents the set contrast humidity, Humi1 represents the average humidity calculated according to the monitoring parameters, Stre2 represents the set stress contrast 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 contrast value, w1, w2, w3 and w4 represent the first weight, the second weight, the third weight and the fourth weight respectively.

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