Wireless sensor networks (WSNs), possessing sensing, computing, and communication capabilities, integrate sensor technology, embedded computing technology, distributed information processing technology, and communication technology. They can collaboratively monitor, sense, and collect information about various environments or monitored objects within the network's distributed area in real time, process this information to obtain detailed and accurate data, and transmit it to users who need it. Due to the immense application value of WSNs, they have attracted widespread attention from military departments, industries, and academia in many countries around the world, and are widely used in military, industrial process control, national security, environmental monitoring, and other fields. The U.S. Department of Defense and various military departments have attached great importance to WSN (Wireless Sensor Network), proposing the C4KISR (Computer-In-Service Intelligence) program based on C4ISR (Computer-In-Service Intelligence). This program emphasizes battlefield intelligence perception, information integration, and information utilization capabilities, establishing WSN as a key research area and setting up a series of military sensor network research projects. For example, the U.S. Army proposed the "Smart Sensor Network Communications" program in 2001, which was approved as a science and technology research program for fiscal year 2001 and implemented from fiscal years 2001 to 2005. The U.S. Navy's recently developed mesh sensor system (CEC, cooperative engagement capability) can detect and engage even the most advanced anti-ship cruise missiles in real time. In the civilian sector, in 2002, Intel released its "New Computing Development Plan Based on WSN." Intel is committed to the application of WSN in preventive medicine, environmental monitoring, forest fire fighting, and even seafloor plate surveys and planetary exploration. The U.S. National Science Foundation (NSF) formulated a WSN research plan in 2003, investing $34 million to support related basic theoretical research. Driven by the NSF, institutions in the United States such as the University of California, Berkeley, MIT, Rockwell Research Center, and UCLA began research on the fundamental theories and key technologies of WSNs. Universities and research institutions in countries such as the UK, Japan, and Italy also launched research in this field. Academic research mainly focuses on sensor network technology and communication protocols, and some research has also been conducted on sensor data query and processing technologies, yielding some preliminary results. Domestic research institutions such as the Chinese Academy of Sciences, Tsinghua University, National University of Defense Technology, University of Electronic Science and Technology of China, Harbin Institute of Technology, and Zhejiang University have conducted follow-up research on WSNs. The 2006 China Next Generation Internet Demonstration Project (CNGI) included a research project on wireless sensor network nodes. Undoubtedly, tracking the development of foreign WSN technologies and conducting pioneering research is of great significance to the modernization of my country's national defense. 1. Definition and Characteristics of WSN Dr. Jason Hill, the developer of the TinyOS141 wireless sensor network operating system, defines WSN as: Sensing + CPU + Radio = Thousands of potential applications. Professor Li Jianzhong of Harbin Institute of Technology defines WSN as: A wired or wireless network composed of a group of sensor nodes in a self-organizing manner. Its purpose is to collaboratively sense, collect, and process information about objects in the geographical area covered by the network, and then publish it to observers. As shown in Figure 1, from a hardware perspective, a WSN node mainly consists of a data acquisition unit, a data processing unit, a wireless data transceiver unit, and a small battery unit. It is typically small in size and features low cost, low power consumption, and multifunctionality. From a software perspective, it effectively detects environmental parameters such as temperature, humidity, light intensity, and pressure in the area it is in, as well as physical parameters such as voltage and current of the object being measured, using built-in sensors. The detected information is then transmitted to a data aggregation center for processing, analysis, and forwarding via a wireless network. WSN has significant advantages compared to traditional sensors and measurement and control systems. It employs point-to-point or point-to-multipoint wireless connections, significantly reducing cable costs. At the sensor node end, it integrates analog-to-digital signal conversion, digital signal processing, and network communication functions. The nodes have self-testing capabilities, resulting in significantly improved system performance and reliability while substantially reducing costs. WSN has the following characteristics: ① Limited hardware resources. WSN nodes use embedded processors and memory, resulting in very limited computing and storage capabilities. Therefore, it is necessary to solve the problem of how to perform collaborative distributed information processing under limited computing power. ② Limited power capacity. WSN nodes provide power through their own batteries. When the battery is depleted, they are often discarded, or even cause network outages. Therefore, any research on WSN technology and protocols must prioritize energy conservation. ③ Decentralized. WSN has no strict control center; all nodes are equal, forming a peer-to-peer network. Nodes can join or leave the network at any time, and the failure of any node will not affect the operation of the entire network, exhibiting strong resilience. ④ Self-organizing. The deployment and expansion of the network do not rely on any pre-set network infrastructure. Nodes coordinate their behavior through hierarchical protocols and distributed algorithms, and can quickly and automatically form an independent network after powering on. ⑤ Multi-hop routing. WSN nodes have limited communication capabilities, with a coverage range of only tens to hundreds of meters. Nodes can only communicate directly with their neighbors. If they want to communicate with nodes outside their radio frequency coverage range, they need to route through intermediate nodes. Multi-hop routing in WSN is performed by ordinary network nodes. ⑥ Dynamic topology. WSN is a dynamic network where nodes can move freely. A node may exit the network due to battery depletion or other failures, or it may be added to the network as needed. These factors cause the network topology to change at any time, so the network should have dynamic topology organization capabilities. ⑦ Numerous and densely distributed nodes. WSN nodes are numerous and widely distributed, making them difficult or even impossible to maintain. Therefore, it is necessary to address how to improve the software and hardware robustness and fault tolerance of sensor networks. 2 Key technologies of wind tunnel measurement and control WSN In view of the characteristics of WSN and the application requirements in wind tunnel measurement and control, there are still many pioneering and challenging problems to be solved in the field of WSN research, mainly including the following research contents. 2.1 WSN energy-saving technology Energy is the most important resource of WSN. How to effectively save energy is a key technology that WSN must consider. WSN nodes operate in four modes, ranked from lowest to highest power consumption: sleep, idle, receive, and transmit. Effectively entering sleep and idle modes and reducing data transmission significantly saves energy. Employing appropriate routing algorithms and channel access methods is also crucial for energy conservation. 2.2 WSN Node Miniaturization Technology Currently, WSN node miniaturization technology focuses on hardware circuit design. Using small, low-power chips and devices, along with modular design and layered wiring, minimizes the size. However, with the increasing maturity of MEMS (Micro-Electro-Mechanical Systems) technology, WSN nodes will become increasingly smaller in the near future. 2.3 WSN Networking Technology WSN is essentially a self-organizing network based on Ad hoc technology. In areas where WSNs are deployed (such as high-pressure gas storage tank clusters in the field), where there is no network infrastructure, a wireless transmission network environment must be formed through the self-organization of WSN nodes. By aggregating and merging relevant data, the parameters of the corresponding test objects can be transmitted to the monitoring center. The primary goal of traditional wireless networks is to provide high quality of service and efficient use of network bandwidth, with energy conservation being a secondary consideration. However, the primary goal of WSNs is efficient energy use and extending the network system's lifespan. Therefore, existing network routing protocols are unsuitable for WSNs. Thus, it is necessary to design and research new data-oriented, low-power, self-organizing information transmission path establishment mechanisms and network management schemes, meeting the following technical requirements: ① Efficiency: Data collected by nodes must undergo multi-hop processing before reaching the sink node for aggregation. Therefore, the network routing/networking protocol must be efficient, simple to implement, and combined with data fusion technology to reduce transmission and computational overhead, using as little energy as possible to meet the energy and time constraints of WSNs. ② Robustness: When applied in experimental fluid mechanics, WSNs must adapt to the characteristics of WSN node failure in the field environment and the instability of wireless channels caused by electromagnetic interference in wind tunnel environments. Robust and redundant routing channels must be established to avoid sensing blind spots caused by the failure of individual nodes or sudden interruptions of the wireless channel. ③ Scalability: The number of WSN nodes frequently changes, ranging from hundreds to thousands. Routing/networking protocols and sensor network management systems must be able to adapt to these changes in WSN topology. ④ Convergence: The WSN routing/networking and network management scheme must cover all network nodes and rapidly form a stable network topology. 2.4 WSN Data Aggregation Technology In the wind tunnel measurement and control application environment of WSNs, WSN nodes need to collect various environmental parameters such as temperature, humidity, light, and pressure. A single node often cannot measure and identify environmental targets. A single sensor only obtains local and partial information about the wind tunnel environment characteristics, and its information content is very limited. Moreover, each WSN node is also affected by its own quality, performance, and wind tunnel noise, and the information collected is often incomplete, with significant uncertainty, or even errors. This necessitates the research and development of algorithms that allow multiple WSN nodes with certain attributes to exchange information, process, summarize, and filter the acquired data, and obtain the final result in the form of events. This is WSN data aggregation. Multi-sensor data fusion is a new interdisciplinary technology. The basic requirements for information fusion methods are robustness and parallel processing capabilities. Generally, nonlinear mathematical methods, if they possess fault tolerance, adaptability, associative memory, and parallel processing capabilities, can be used as fusion methods. Currently, commonly used data fusion methods can be broadly categorized into two types: stochastic and artificial intelligence. Stochastic methods include weighted average, Kalman filtering, multi-Bayes estimation, and DS evidence reasoning; while artificial intelligence methods include fuzzy logic and neural networks. 3. Application of WSN in Wind Tunnel Measurement and Control In the specific scenario of wind tunnel measurement and control, it is necessary to monitor and track the technical parameters of some key components and equipment to monitor equipment operation, rationally schedule equipment operation, predict the failure probability of key components, formulate maintenance or replacement plans for key components, avoid major system failures or long-term wind tunnel downtime, reduce workload and the probability of human error, improve wind tunnel testing efficiency, and ensure safe wind tunnel operation. Wireless sensor networks can be considered when it is inconvenient to install wired sensors. Specific application requirements of WSN include: ① Monitoring of rotating mechanisms: including monitoring and tracking of vibration characteristics of rotating mechanisms such as axial fans, angle-of-attack mechanisms, and ball screws, as well as model attitude detection and tracking. ② Monitoring of gas source systems: including monitoring of high/medium-pressure gas storage tank groups, high/medium-pressure compressor units, adsorption drying stations, cooling circulating water systems, etc. located in the field, specifically monitoring parameters such as temperature, pressure, and toxic gas concentration. ③ Wind tunnel operation monitoring: monitoring the operating status of wind tunnels, including pressure status during testing, ejector position status, temperature status of test sections, and wind tunnel safety interlock status, specifically monitoring physical parameters such as temperature, pressure, position, current, and voltage. ④ Other application environments where there is no basic network infrastructure and wired sensor system installation is inconvenient or unsafe. 3.1 Architecture of WSN Application System Based on the actual needs of wind tunnel measurement and control, such as complex deployment area structure, large number of parameters to be measured, and wide range, a layered WSN network topology is adopted, as shown in Figure 2. In the layered WSN shown in Figure 2, network nodes with some kind of association form a cluster. Within a cluster, there is typically a node elected according to certain rules, known as the cluster head (also called the sink). Ordinary nodes transmit the collected and compressed monitoring data to the sink node; then, the sink node and gateway node aggregate and transmit data from multiple WSN nodes via multi-hop relay; finally, the monitoring server (Control Center) centrally processes the data from the entire monitoring area. 3.2 Implementation of the WSN System The performance of a WSN largely depends on the characteristics of its nodes. Figure 3 shows a commercially available WSN node. The Mica2dot node uses a 4 MHz Atmel ATmega 128L microprocessor, has an 868/916 MHz multi-channel RF transceiver, 512 KB of on-chip storage, and integrates multiple sensors; its diameter is only 25 mm. It uses the TinyOS operating system to complete node data acquisition, data processing, and communication. TinyOS, an operating system designed for WSN applications, enables efficient and low-power parallel operations using limited resources. Its small core allows it to run effectively on WSNs, performing management tasks, automatically discovering and forming networks, providing reusable components, and offering a simple scheduling mechanism. TinyOS defines a series of very simple component models, exhibiting high modularity. Each component performs a specific task, and the entire operating system is essentially composed of these component models. When the system needs to complete a task, it invokes the event scheduler, which then sequentially calls various components to efficiently and orderly complete various functions. Applications running on this operating system are based on an event-driven model, using events to trigger sensor activation. TinyOS uses NESC, a C-like structured programming language, to write applications. 3.3 Preliminary Results Analysis A preliminary attempt at WSN wind tunnel monitoring was conducted in a 1.2m x 1.2m wind tunnel, achieving topology management of the WSN (see Figure 4). A 1.2m x 1.2m wind tunnel WSN wireless sensor network measurement system was developed (see Figure 5), enabling temperature measurement within the wind tunnel test section. [align=center] [/align] In Figure 4, node 0 serves as the base station, while nodes 1 and 2 are measurement nodes deployed in the wind tunnel test section and overspread section, respectively. The acquisition systems on nodes 1 and 2 collect local temperature parameters. Node 3 acts as a relay node; the temperature measurement data from nodes 1 and 2 are relayed through node 3 via multi-hop routing and finally converged at node 0. The base station then performs data aggregation, fusion, and result display. Figure 5 shows the temperature changes in the wind tunnel test section during the 1.2m x 1.2m wind tunnel test. This use of WSN temperature measurement data allows for effective correction of the measurement results in the fluid dynamics wind tunnel test. 4. Conclusion Wireless Sensor Networks (WSNs) are considered one of the most important technologies impacting the future of human life. This emerging technology provides people with a completely new way to acquire and process information. Due to the inherent characteristics of WSNs, they differ significantly from existing traditional network technologies, posing many new challenges. Given the significant national and societal importance of WSNs, research on WSNs is actively underway both domestically and internationally. It is hoped that this research will draw attention to this emerging technology in the field of measurement and control, promoting the research, application, and development of this new technology with national strategic significance.