Abstract
Reinforced concrete structures are widely used in modern buildings such as buildings, bridges, and tunnels. However, the structural damage caused by reinforcement corrosion seriously affects the service life of the buildings. Because the corrosion of reinforcement in concrete is a very slow process, the continuous detection of reinforcement corrosion is very important. In view of the slow development of steel corrosion detection equipment in China, which cannot meet the application requirements of concrete structures in China, wireless monitoring technology has more advantages than traditional monitoring technology. In this paper, combined with wireless transmission technology, a concrete reinforcement corrosion detection system based on wireless sensor network is designed. Embedded sensors based on the principle of electromagnetic coupling are used to collect steel corrosion information. It is determined that the 16-bit ultralow power consumption microcontroller MSP430F149 is the main control chip, the AD9850 based on DDS technology is the signal generation chip, and the nRF905 is the detection circuit scheme of the wireless transceiver chip. The star network is determined by polling the entire network topology and MAC protocol. The embedded sensor is designed through simulation. This article discusses the principle of using embedded sensors to detect steel corrosion and determines the feasibility of its low-cost implementation. The embedded sensor and steel corrosion detection system were tested. The simulation method of the embedded sensor is verified through actual measurement. The test results show that the system network is normal and all parts work stably, which can meet the requirements of the project.
1. Introduction
Nowadays, all countries in the world are building civil engineering and strengthening national infrastructure. With the widespread use of reinforced concrete, the problems of waste of resources, environmental damage, and building damage caused by its insufficient durability have become one of the bottlenecks in the sustainable development of civil engineering. In the service process of reinforced concrete, its internal or external and man-made or natural factors, material aging, and structural damage will be inevitable, which is an irreversible process; the accumulation of such damage will lead to the deterioration of the resulting performance and durability reduction. In today’s world, the causes of concrete damage are listed in the order of repetitive descending: steel corrosion, frost damage in cold climate, and physical and chemical action of erosion environment. Thus, it can be seen that reinforcement corrosion plays an important role in the study of concrete durability. Worldwide steel bar corrosion were seen as leading to premature failure of concrete structure, one of the most important factors of steel corrosion can reduce the ductility of the concrete structure and reduces its carrying capacity, the result is a direct impact on the safety performance and durability of the structure, and the more serious corrosion will directly cause structural damage, leading to higher maintenance costs. This is because of the corrosion of the steel bar; the resulting corrosion product expands 2.4 times in volume and is a loose sheet structure, which reduces the sectional area of the steel bar on the one hand and reduces the strength and ductility. On the other hand, the protective layer of concrete will crack and fall off due to the corrosion of steel reinforcement, which will reduce the effective cross-sectional area of concrete and reduce or lose the bond between steel reinforcement and concrete.
In the traditional concept, people believe that concrete has a long service life. Although steel bars are vulnerable to corrosion due to the influence of external environment, steel bars are not easy to be corroded due to the presence of concrete wrapping and protection [1]. Based on this, reinforced concrete combines the advantages of concrete and steel to become the most used building material and the most important structural material, and people have high expectations on the service life and safety of reinforced concrete structures [2]. However, a large number of reinforced concrete structures often fail when they are far from reaching the design life, resulting in the decrease of the applicability and safety capability of the structure itself, which seriously affects the use of the structure. The premature failure of reinforced concrete structure is not only related to the defects at the beginning of the design, such as insufficient design bearing capacity, but also the failure caused by insufficient durability of the structure [3]. Due to the difference of application environment and people’s low protection awareness of reinforced concrete, structural failure and even collapse accidents occur due to insufficient durability before reaching the predetermined service life. Because people ignore the durability of reinforced concrete structure and the research on it is lagging behind, it has paid a heavy price, brought a huge threat to the safety of people’s lives, and caused a lot of economic losses. Historical statistics show that the direct and indirect economic losses caused by steel corrosion accounted for 4.9% and 4.0% of GDP, respectively, in the United States in 1976 and 2002. In the past 30 years, the economic losses caused by corrosion accounted for 3.5% of GDP in Britain, 4.2% in Australia, and 6-10% in Poland. In China, the durability of reinforced concrete structures is also quite serious. According to the investigation report of the Chinese academy of building sciences, the damage of industrial buildings in service in China is very serious. The service life of structures cannot be guaranteed for 50 years, and most of them need to be reinforced or overhauled within 25 to 30 years [4, 5]. China is in the period of large-scale construction, and concrete structures are applied on a large scale in various fields related to the safety of people’s lives and property. The infrastructure construction scale, mainly civil and hydraulic engineering, has exceeded the total of all other countries in the world every year [6]. The near future will gradually enter the basic construction in China which focuses on service building maintenance phase, in order to ensure the safety of the structure, reduce the economic loss and casualties, try to improve steel bar corrosion resistant ability, and extend the service life of structure and real-time control of the steel corrosion of reinforced concrete major projects at the same time; the safety performance has become more and more important [7]. The development of high durability testing technology and the long-term monitoring and evaluation technology for the corrosion and damage evolution characteristics of reinforced concrete structure have significant technical support for the safety of major projects of reinforced concrete structure and have achieved significant economic value and strategic significance.
At present, many experts at home and abroad are committed to the research of corrosion detection of reinforced concrete and have made fruitful achievements. Using the method of absorption spectrum, city university of England used fiber optics to measure the change of pH value of concrete structures to determine the corrosion of steel reinforcement [8]. Wang and Jiang introduced the nuclear magnetic resonance (NMR) technology in the field of chemical and biological analysis of steel corrosion in concrete [9], the use of homemade sol gel-sensitive probe and commercial wafer pH-sensitive probe solution and experiment of concrete and steel is put forward to detection, LC oscillation circuit, and equivalent electromagnetic coupling technology of combining the plan to build a passive sensor of leadless [10], and for the steel corrosion, detection points to a development direction; Ma et al. developed a long-period grating sensor for the detection of steel corrosion in concrete [11], and Galmés et al. developed a fiber optic sensor for the detection of steel corrosion in concrete by chemically depositing carbon-ferroalloy film on the surface of optical fiber [12]. The application of wireless sensor network technology in the field of building structure detection started in 1998 and was first proposed by Straser. In the following four years, Ghari et al. applied wireless detection to practical engineering [13]. In addition, the University of California, Berkeley, in cooperation with cross-bow company, developed a monitoring system based on mote wireless sensor network, which was deployed on the San Francisco bridge to detect the damage and aging of the bridge body [14]. In some domestic research institutes and universities, structure of wireless sensor network technology applied to monitoring has been carried on the related research. Xu et al. discuss wireless sensor network applications in bridge monitoring [15], developed based on an offshore platform and other civil engineering structural health monitoring of wireless sensor network, but the whole, domestic research and commercialization level are still some gap compared with abroad. In the future, with the rapid development of China’s economy, the corrosion detection technology based on wireless sensor network will be widely applied [16].
In this paper, combined with wireless transmission technology, a corrosion detection system for concrete reinforcement based on wireless sensor network is designed. Combined with wireless transmission technology, this paper designs a concrete reinforcement corrosion detection system based on wireless sensor network, which provides a reference scheme for the continuous and effective detection of reinforced concrete corrosion. The embedded sensor based on electromagnetic coupling principle is used to collect corrosion information of steel reinforcement; determine the detection circuit scheme with 16-bit ultralow power consumption microcontroller MSP430F149 as the main control chip, AD9850 based on DDS technology as the signal generation chip, and nRF905 as the wireless transceiver chip; and determine the stellate network with polling for the entire network topology and MAC protocol. The embedded sensor is designed by simulation. This paper discusses the principle of using embedded sensor to detect the corrosion of steel reinforcement and determines the feasibility of its low-cost realization. The experiments of embedded sensor and corrosion detection system of steel reinforcement were carried out. The simulation method of embedded sensor is verified by actual measurement. The test results show that the system network is normal and all parts work stably, which can meet the requirements of the project. The feasibility of the system scheme in reinforced concrete corrosion detection is determined.
2. Proposed Method
2.1. Wireless Sensor Network
In recent years, with the active development of microelectromechanical systems technology and wireless technology, wireless sensor networks have made significant progress. Wireless sensor network is a distributed network of a series of sensor nodes arranged in the monitoring area. Through joint work between the sensor nodes, it detects the target information, computation, and storage and can be sent wirelessly. Wireless sensor network is a wireless network composed of a large number of static or moving sensors in the way of self-organization and multihop. It realizes three functions of data acquisition, processing, and transmission. The wireless sensor network, sensor technology, and distributed information processing technology, including a computer and wireless communication technology, military surveillance, environmental monitoring, and wide range of applications, are expected in many areas such as climate and earthquake prediction, a significant impact on the 21st century [17]. Wireless sensor network includes sensor technology, distributed information processing technology, and computer and wireless communication technology. It has broad application prospects in many aspects such as military monitoring, environmental monitoring, and climate and earthquake prediction and provides better technical equipment and information platform for environmental management, resource protection, disaster monitoring, and other related fields. It has been identified as one of the technologies that will have a significant impact in the 21st century. At present, the research based on wireless sensor networks mainly focuses on target discovery and location, routing protocols, routing recovery, and MAC protocols of wireless sensor networks. In wireless sensor networks, sensor nodes can pass way, such as plane, artificial put deployment at a specified monitoring area, the nodes in the form of collaboration in the collection and processing network coverage area simply object information, and the data collected by wireless transmission way of information transmitted to the gathering node, and gathering node can be connected to the Internet [18, 19], the final data information to the user management side (18 to 19). The user management terminal can manage the wireless sensor network, publish the detection task, and collect the detection data information. The architecture of the wireless sensor network is shown in Figure 1.
Wireless sensor network (WSN) is a field involving multiple disciplines and has the following important features: (1)The sensor is small in size, low in cost, and limited in power supply, computing, and storage capacity. Sensor nodes are miniature embedded devices responsible for data collection and simple processing. Due to the limitations of embedded processors and memory, the computing and storage capacity of sensors is very limited [20]. At the same time, in order to obtain accurate detection data information and reduce the blind area, a large number of sensor nodes need to be arranged in the monitoring area, so the price must be low. In addition, sensor nodes often work in the field, usually powered by button batteries or dry batteries that carry a very limited amount of energy(2)WSN is a dynamic network, which has the function of dynamic topology organization. Wireless sensor network topology changes, with adaptive wireless sensor network environment having no stability and deteriorated performance, and can result in wireless communication frequently occur off the pass, and sensor nodes may be due to the consumption of power supply malfunction or failure and at the same time may also have a new wireless sensor network node to join, etc.; these factors can lead to changes in network topology, and this requires the protocol of wireless sensor network with adaptive [21](3)Wireless sensor network has a high degree of reliability. Sensor nodes may be deployed in harsh environments or places that are difficult for people to reach and may work in an open environment. In this way, they may be exposed to the wind, rain, or sun and may even be destroyed by animals or unrelated personnel. In addition, network maintenance can be difficult or even impossible due to the limitations of the specific environment in the monitoring area. All of the above require that the hardware and software of sensor nodes be very reliable to adapt to a variety of harsh environments [22]
2.2. Reinforcement Corrosion Detection Technology
According to whether the protective layer of the concrete structure is damaged during the inspection, the method of steel corrosion inspection can be divided into damage inspection and nondestructive inspection. Damage detection is a traditional steel corrosion detection method. During the detection, the protective layer of the concrete structure needs to be chiseled, and the corrosion degree of the steel reinforcement is detected visually [23]. The advantages of this method are accuracy, directness, and simplicity. The concrete structure will be damaged, and some parts such as bridge piers are more difficult to detect, so its application is less and less now; nondestructive testing can make up for the deficiency of damage detection. This detection technology can carry out accurate detection without damaging the integrity of concrete structure. Nondestructive testing is divided into analytical method, physical method, and electrochemical method according to different detection principles, among which analytical method based on the measured data on site and comprehensively considering the environment in which the concrete structure is located; a mathematical model is established to infer the degree of steel corrosion. Nondestructive testing can detect the reinforcement dynamically and in real time and quickly determine the corrosion position and corrosion damage range of reinforcement.
Through the detection of corrosion of steel reinforcement in concrete structure, the state of the structure can be monitored and evaluated, and the warning information can be issued when the structure state is abnormal, revealing the potential danger, providing basis and reference for the maintenance, repair, and demolition of the structure, so as to ensure the safety of the project. In the traditional sense of the steel corrosion in concrete structure detection is generally live operator by using some instruments for testing and register for the record, so by site operation personnel’s subjective factors, influence is bigger; in addition, when you need to test concrete structure distribution area is wide, or environment is poor, the in-situ test on the economy and practice is not desirable, in order to solve these problems; it gradually produced the modern steel corrosion in concrete detection technology [24]. Modern steel bar corrosion detection is not an improvement of traditional detection technology but is produced with the development of computer, communication, microelectronics, and network technology, which breaks the regional limit and transmits information through the network, realizing remote and real-time monitoring, and diagnosis of concrete structure state. It can monitor the corrosion damage of reinforcement for a long time and deduce the change trend of reinforcement corrosion. The corrosion monitoring mode of reinforcement in modern concrete is shown in Figure 2.
The sampling equipment converts the analog signal of the information about the corrosion state of the steel collected by the sensor into a digital signal through the A/D converter and transmits the data to the control center through the data processing of the on-site controller and wired or wireless communication. At the same time, remote diagnosis is carried out by network engineers, and remote diagnosis engineers can use these data to analyze and evaluate the structural status and return the diagnosis results to the field operators to provide guidance for their steps [25]. This mode greatly reduces the knowledge level of field operators and the influence of subjective factors. Diagnostic engineers can intuitively understand the state information of the structure as they do in the field and make timely and accurate judgments and take effective measures to provide technical support and support for the project. In addition, due to the high fidelity of digital signals in long-distance transmission and the small impact of time and space, the conclusions obtained from diagnosis are relatively reliable, and accurate, remote, and real-time detection can be realized in a real sense. The technology of reinforcement corrosion detection in modern concrete structures integrates information collection, transmission, analysis, and management, realizes the sharing of information and resources, provides people with a comprehensive, efficient, accurate, safe, and fast service mode, and leads the development direction of reinforcement corrosion detection. In addition, because wireless sensor network has a large coverage area, data transmission is more convenient than wired communication and other advantages, so the wireless sensor network-based reinforcement corrosion detection technology has become an important research area.
2.3. Hardware and Software Design of Reinforcement Corrosion Detection System
Module control and wireless data transmission play an important role in the whole system design. Based on the analysis of the above chapters, this chapter designs the hardware part and software part of the concrete reinforcement corrosion detection system based on wireless sensor network. The whole system includes three parts: sensor node, sink node, and human-computer interaction interface. Among them, the sensor node is deployed at the key part of the concrete structure to be tested to collect the corrosion information of steel reinforcement and transmit it to the sink node. The sink node centrally controls each sensor node and receives the corrosion information collected by each sensor node and uplows it to the human-computer interaction interface. The man-machine interface issues the start detection command and displays and saves the corrosion information collected by each sensor node, providing convenience for people to evaluate the corrosion of steel reinforcement.
2.3.1. Hardware Design of Sensor Nodes
Sensor nodes are composed of embedded sensors and detection circuits, which are composed of MSP430F149 microcontroller, DDS sweep signal source, low-pass filter, amplifier drive circuit, peak detection circuit, and nRF905 wireless transceiver circuit. Under the control of the microcontroller, DDS frequency sweep signal produced by low-pass filter to produce A smooth sine wave, the sine wave by reading after amplification drive circuit inductance to provide energy for embedded sensors, again through the peak detection circuit to get all frequency sweep points at both ends of inductive voltage amplitude value, these values are stored in the microcontroller after A/D conversion, and then, through the microcontroller, all sampling voltage LC resonance frequency values are obtained, the value that corresponds to the degree of reinforcement corrosion and finally through the wireless transceiver circuit will be sent to the resonance frequency value node.
2.3.2. Hardware Design of Sink Node
On the one hand, the sink node can control each sensor node to start working through the wireless transceiver circuit; on the other hand, it can receive the information of steel corrosion collected by each sensor node and finally upload the information to the human-computer interaction interface. There is a communication choice problem between sink node and human-computer interaction interface. The two communication modes commonly used are serial communication and parallel communication. Considering that the interface of serial communication circuit is simple and the software programming is easy to realize, and the data transmission rate is not too high in this design, the serial communication mode is adopted. Compared with sensor nodes, sensor, signal generation, and processing circuits, the sink node also has the nRF905 wireless transceiver circuit, clock circuit, power circuit, reset circuit, and JTAG interface required by MSP430F149 periphery. As there is no need for analog-to-digital conversion, in-chip A/D converter is not required, which increases serial communication circuit, reduces embedded sensor, signal generation, and processing circuit, and also has nRF905 wireless transceiver circuit and clock circuit, power circuit, reset circuit, and JTAG interface required by MSP430F149 periphery.
2.3.3. Software Design of Sensor Nodes
In the whole system, the control and function of all modules are realized by software algorithm, so the software design is also the key. In software design, modular design is adopted, so that the programming and debugging of each module are relatively independent, with clear structure and easy to maintain and expand functions. Finally, each module is used for system construction. Because the MSP430F149 microcontroller chip contains JTAG debugging interface and electrically writable FLASH memory, the program can be downloaded to FLASH through JATG interface and then through JATG port to control the program to run and read the contents of the chip, providing great convenience for development and debugging. In this design, we use C language to program and debug MSP430F149 in IARWorkbench software development tool.
2.3.4. Software Design Of Sink Node
The aggregation node centrally controls each sensor node, and when the detection result of the sensor node is received, the result is uploaded to the human-computer interaction interface. Since it takes about 5 s from the sink node to notify the sensor node to display the detection result in the human-computer interaction interface, the total detection time is not too long when the number of sensor nodes is large, so the sensor nodes can be controlled by polling in this design. (1)First turn off the watchdog timer; then, the system was initialized with 32.768 khz crystal cheer primary clock (MCLK), 8 MHz crystal oscillator as the secondary main clock (SMCLK), and the input and output pins required by nRF905 wireless transceiver chip and serial port communication. In addition, since nRF905 is required to adopt the interrupt mode for wireless transceiver, the interrupt trigger pin P2.5 is configured accordingly(2)Since the sink node needs to use the serial port to communicate with the human-computer interaction interface, this design uses the UART0 interface in MSP430F149 to realize the serial port communication, so it needs to be initialized; then, the sink node enters the low-power mode LMP4 and waits for the start detection command sent through the serial port from the human-computer interaction interface. This design adopts the mode of UART0 interruption to receive the start detection command and exits the low-power mode LMP4 in the interrupt service program so that the program continues to execute(3)Gathering node sent via nRF905 starting test command, the command word for each sensor node ID, and the sensor node receives the command word can be compared with the node ID of itself, to determine whether to start testing, it further enhanced the reliability of the network and reduced due to the unstable cause communication error detection; then, nRF905 is set to enter the receiving mode and wait for the detection result sent by the receiving sensor node in the LMP4 state of low power consumption mode(4)Since the sensor node may fail or cannot receive the start test command due to other reasons, it is not possible to just blindly wait for the receiving state and the acquisition node, so this design is based on the maximum value. The waiting time of each sensor node is 7 s, which is timed by the MSP430F149 chip timer, set the interrupt service routine human-computer interaction interface upload timeout identifier, and exit the LMP4 low-power mode(5)Because MSP430F149 supports interrupt nesting, it is necessary to turn off the interrupt function when nRF905 adopts P2 port interrupt to receive data and timer A to time each test. In addition, in the main program, the global interrupt function, P2.5 pin, and the interrupt function of timer A need to be properly configured to open and close, so as to avoid chaotic detection results
2.3.5. Software Design of Human-Computer Interaction Interface
In this design, the results of testing the corrosion degree of steel reinforcement in concrete are finally displayed on the human-computer interaction interface, and the friendly human-computer interaction interface can greatly facilitate people’s operation and management. Currently, VisualC++ is one of the world’s most widely used high-level programming tool, the user using the interface design, simple and convenient operation; in addition, the MFC (Microsoft Foundation Class) is a Microsoft company development effort to reduce the programmer designed a set of C++ class library, an object-oriented class library; using these classes can effectively help programmers to application development, so this topic on VisualC++6.0 platform uses MFC to develop human-computer interaction interface. The communication between sink node and human-computer interaction interface adopts serial port. This design uses Windows32API functions to realize serial port communication program. Windows32API is the programming interface of Microsoft 32-bit platform application program, which is an essential function for Windows application program development. Due to steel corrosion testing with a large number of sensor nodes, to list their respective test results, the design adopts MFC providing CListView class implementing a list view and sets the column header information: “node id,” “steel corrosion information (Hz),” and “time,” to facilitate people’s view of steel corrosion data. In addition, before the serial port communication, the serial port should be set, including port number, baud rate, data bit, check bit, and stop bit.
The communication process between the human-computer interaction interface and the sink node is as follows: set the serial port according to the serial port setting dialog box; if the serial port is not occupied, the connection of the serial port will be successful. If the serial port is occupied, a prompt message will appear and the serial port needs to be reset. Click the “start” menu item or the shortcut key to send the start detection command to the sink node. Then, the sink node exits the low-power mode LMP4 and controls the sensor node to work. After receiving the results of the reinforcement corrosion detection, the collection node will upload the data to the human-computer interaction interface. Through processing in the serial port event processing function OnComm(), the binary information will be converted into ASCII code, and the detection results and detection time of each sensor node will be displayed in the corresponding parts of the list interface. When all the corroded data is received, the results can be saved to the hard disk of PC for later reference.
3. Experiments
The corrosion of steel reinforcement in concrete is a long process of change. In order to check the accuracy of the measuring equipment, the corrosion sensor of reinforced concrete was tested in a simulated environment. The corrosion degree of reinforcement in the corrosion detection of reinforced concrete is mainly reflected in the ac resistance value, so the main index studied in the experiment stage of this detection equipment is determined as the measurement of resistance value of professional sensors in concrete by this system.
Firstly, the resistance measured by the system is the resistance value in the ac state, so it is necessary to use CRC digital bridge (Figure 3(a) to compare and correct the measurement results in the experiment. Secondly, in the measurement phase of the system, the output waveform should be a square wave with the same positive and negative voltage amplitude and fixed frequency. In order to ensure the accuracy of the output signal, the output waveform should be calibrated with the help of a standard oscilloscope (Figure 3(b) in the experimental phase. Finally, in the system testing process, the voltage accuracy is required to be less than 0.1 mV, so the high-precision voltammeter is indispensable in the system experiment stage.
(a)
(b)
The main body of the reinforced concrete corrosion detection system is integrated circuit board, which is an integrated development board designed and made according to the principle of hardware design. The system software program is run in the development board, and the corrosion detection sensor of steel reinforcement is connected into the system. Through the serial communication interface reserved by the system, the collected resistance information is uploaded to the PC, and the obtained data is compared with the precision CRC digital bridge measurement data, so as to determine the accuracy of the detection system.
4. Discussion
The purpose of the experiment is to compare the error between the system measurement data and the CRC digital bridge measurement data of the precision instrument, so as to determine the accuracy and reliability of the system in the measurement process. The AC resistance measurement range of the system designed in this paper is 0~100, and the measurement accuracy error is required to be kept within ±10. This experiment is a comparison of a large number of data measured by the system at 20°C and -10°C.
4.1. System Data Analysis at 20°C
In 20°C environment by changing the concrete conditions of different humidity, precision instrument from the steel corrosion sensors measured the resistance value of the data, and the same condition, based on the arithmetic average and Butterworth software filtering algorithm, the respective resistance data and the corresponding error percentage are measured, respectively, as shown in Table 1. The resistance trend curve and the percentage error bar chart are shown in Figures 4 and 5, which are drawn, respectively, according to the data in Table 1.
As shown in Figure 4, the blue curve represents the ac resistance value of the steel corrosion sensor measured by the precision instrument at 20°C. The red curve represents the ac resistance value of the steel corrosion sensor collected by the arithmetic average filtering algorithm under the same conditions. The yellow curve represents the ac resistance value of the steel corrosion sensor collected by the design system using Butterworth filtering algorithm.
As shown in Figure 5, the blue curve represents the ac resistance value of the steel corrosion sensor measured by the precision instrument at 20°C. The red curve represents the ac resistance value of the steel corrosion sensor collected by the arithmetic average filtering algorithm under the same conditions. The green curve represents the ac resistance value of the steel corrosion sensor collected by the design system using Butterworth filtering algorithm.
By Table 1 and Figure 4, you can see the reinforced concrete corrosion detection system in 20°C environment and the entire range of the system within the range 0~100 k Ω, while there is a certain amount of measurement error, but the system can still be very good with precision instrument-measuring data, which completes the requirement of resistance measurement and the reliability of the system test results. By comparing Table 1 and Figure 5, it can be seen that the filtering algorithm of Butterworth software is better than that of arithmetic average filtering in this system, and the error percentage of the measured value is controlled at around ±5%, which completes the measurement requirements well.
4.2. System Analysis of Experimental Data at -10°C
By changing the humidity condition of reinforced concrete, the resistance value of the precision instrument is measured from the corrosion sensor of reinforced steel. Under the same conditions, the detection system is based on the resistance data measured by arithmetic mean and Butterworth software filtering algorithm and the corresponding measurement error percentage. The resistance trend ladder diagram and the error percentage comparison curve are shown in Figures 6 and 7.
As shown in Figure 6, the blue line represents the ac resistance value of the steel corrosion sensor measured by the precision instrument at -10°C. The red line represents the ac resistance value of the steel corrosion sensor collected by the arithmetic average filtering algorithm under the same conditions. The yellow curve represents the ac resistance value of the steel corrosion sensor collected by the design system using Butterworth filtering algorithm.
As shown in Figure 7, the blue curve represents the error percentage curve between the measured data and the measured data of the precision instrument by using the arithmetic average filter algorithm under the environment of -10°C. The red curve represents the error percentage curve of the data measured with the Butterworth filter algorithm and the precision instrument under the same conditions.
By comparing Figures 6 and 7, you can see that the reinforced concrete corrosion detection system in 5-10°C environment, in the whole system within the scope of range (0 ~ 100 k Ω), can complete resistance measurement tasks, and the system detection results have certain reliability; the effect of Butterworth software filtering algorithm is better than that of arithmetic average filtering algorithm, and the error percentage of the measured value is controlled at ±5%, which completes the measurement requirements well.
To sum up, the corrosion detection system of reinforced concrete has certain detection ability to corrosion of reinforced concrete in general environment with special sensors, reaching the desired level of system design.
5. Conclusions
Reinforced concrete is a very important part of modern architecture, such as bridges, tunnels, and buildings. In order to ensure the safe use of buildings, timely find the problems that may occur in the use of concrete structures, and make corresponding remedial measures to protect the national economy and people’s life and property from infringement; the construction quality testing technology of concrete joints has become a very important research topic in today’s society. In this paper, a wireless sensor network-based corrosion detection system for concrete reinforcement is designed and implemented.
In this paper, combined with wireless transmission technology, a concrete reinforcement corrosion detection system based on wireless sensor network is designed, and the hardware and software of the system are designed and implemented in detail. Firstly, the hardware design of the sensor node is introduced. Secondly, the hardware circuit design of the sensor node is mainly introduced. Thirdly, the software design of the sensor node is introduced. The embedded sensor based on electromagnetic coupling principle is used to collect corrosion information of steel reinforcement; determine the detection circuit scheme with 16-bit ultralow power consumption microcontroller MSP430F149 as the main control chip, AD9850 based on DDS technology as the signal generation chip, and nRF905 as the wireless transceiver chip; and determine the stellate network with polling for the entire network topology and MAC protocol. The embedded sensor is designed by simulation. This paper discusses the principle of using embedded sensor to detect the corrosion of steel reinforcement and determines the feasibility of its low-cost realization. The experiments of embedded sensor and corrosion detection system of steel reinforcement were carried out. The simulation method of embedded sensor is verified by actual measurement. The test results show that the system network is normal and all parts work stably, which can meet the requirements of the project.
As the society pays more and more attention to the corrosion of reinforced concrete, the research on the corrosion of reinforced concrete goes deeper and deeper, and the corrosion detection technology of reinforced concrete based on site is becoming more and more mature. With the rapid development of computer technology and network technology, it is believed that in the near future, corrosion detection of reinforced concrete will become more convenient, more timely, and effective. In this article, although the research of reinforced concrete corrosion detection system has been carried out and achieved some results, there are a lot of need to improve and further research aspect, which mainly includes the following: reinforced concrete corrosion detection is a complicated and difficult task and is designed in this paper, the data collected is relatively single, and the corrosion of rebar in concrete situation is not very accurate judgment and also has some error. In order to detect more accurately, more parameters need to be measured, and more inspection methods should be combined to judge the corrosion of steel reinforcement from more aspects. In this design, only the most basic design functions are realized; the aesthetics, convenience, and reliability of the software have not been optimized and tested, which need further improvement. To sum up, the overall stability, durability, and anti-interference ability of the system need to be improved. The research of reinforced concrete corrosion detection equipment is of great significance and plays a great role in protecting people’s life and property safety and maintaining the stable development of national economy.
Data Availability
The data that support the findings of this study are available from the corresponding author upon reasonable request.
Conflicts of Interest
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.