A wireless vibrating wire sensor node for continuous structural health monitoring

With the advancements in information, communication, and sensing technologies, structural health monitoring (SHM) has matured into a substantial pillar of infrastructure maintenance. In particular, wireless sensor networks have gradually been incorporated into SHM, leveraging new opportunities towards reduced installation efforts and enhanced flexibility and scalability, as compared to cable-based SHM systems. However, wireless sensor nodes are installed at fixed locations and need to be employed at high density to reliably monitor large infrastructure, which may cause high installation costs. Furthermore, the limited power autonomy of wireless sensor networks, installed at fixed locations for unattended long-term operation, still represents a significant constraint when deploying stationary wireless sensor nodes for SHM. To resolve the critical constraints stemming from costly high-density deployment and limited power autonomy, a mobile structural health monitoring concept based on legged robots is proposed in the study reported in this paper. The study explores the accuracy and cost-efficiency of deploying legged robots in dense measurement setups for wireless SHM of civil infrastructure, aiming to gain insights into the advantages of mobile wireless sensor nodes in general and of legged robots in particular, in terms of obtaining rich information on the structural condition. As is shown in this paper, the legged robots, as compared to stationary wireless sensor nodes, require a smaller number of nodes to be deployed in civil infrastructure to achieve rich sensor information, entailing more cost-efficient, yet accurate, SHM. In conclusion, this study represents a first step towards autonomous robotic fleets advancing structural health monitoring.

This paper presents recent developments in an extremely compact, wireless impedance sensor node for use in structural health monitoring (SHM). The sensor node uses a low-cost integrated circuit that can measure and record the electric impedance of a piezoelectric active-sensor. The sensor node also integrates several components, including a microcontroller for local computing, telemetry for wireless data transmission, multiplexers for managing up to seven piezoelectric transducers per node, energy storage mediums, and several triggering options including a wireless triggering circuit into one package to truly realize a comprehensive, self-contained wireless active-sensor node for SHM applications. It is estimated that this sensor node requires less than 75 mW of total power to operate measurement, computation and data transmission. In addition, the sensor node can also be used for the active-sensor self-diagnostic process that can monitor the operational condition of piezoelectric transducers used in SHM applications. The performance of this miniaturized and portable device is compared to our previous results and its broader capabilities are demonstrated.

A wireless pressure sensor node design method and realization is put forward aiming at problems of dynamic pressure test in the hermetic cavity or cabin, such as high wiring difficulty and influence on air flow field. Dynamic gauge pressure signal is transmitted by a wireless sensor node in consideration of temperature affection factors. The sensor node is mainly composed of gauge and atmospheric pressure, temperature sensor, signal acquisition and modulation module, wireless RF module, data memory, lithium battery. On the basis of the above, the prototype is developed. The effectiveness and reliability of the wireless pressure sensor node are verified in means of sea trial test.

Wireless sensor networks are increasingly adopted both in aircraft and civil structural health monitoring. However, due to the limited resources on a wireless sensor node, structural evaluation ability of the wireless sensor network is also limited, especially for large-scale structures. This paper presents a multi-agent cooperation system based on mobile agent technology for wireless sensor network-based structural health monitoring which deals with the evaluation of large-scale structure. Mobile agent with the signal processing or evaluation algorithm is designed to migrate among different sensor nodes and perform network self-organization, data processing, information fusion, and damage estimation. This method can reduce the request to the sensor nodes and achieve a better monitoring and evaluation performance through multiagent cooperation. The proposed mobile multiagent system is evaluated by a large dimension aerospace aluminum structure monitoring experiment in which strain distribution and joint failure are monitored by different sensors. Experimental results show that the system can significantly improve the monitoring performance for large-scale structures.

Water is an important natural resource which needs constant quality monitoring for ensuring its safe use. This paper introduces a river water quality monitoring system based on wireless sensor network which helps in continuous and remote monitoring of the water quality data in India. The wireless sensor node in the system is designed for monitoring the pH of water, which is one of the main parameters that affect the quality of water. The proposed sensor node design mainly comprises of a signal conditioning module, processing module, wireless communication module and the power module. The sensed pH value will be wirelessly transmitted to the base station using Zigbee communication after the required signal conditioning and processing techniques. The circuit for the sensor node is designed, simulated and the hardware prototype is developed using the appropriate components which minimize the power requirement of the system and provides a cost effective platform for monitoring water quality.

Structural health monitoring (SHM) involves the development of strategies to assess the condition of instrumented engineering structures. One of the most critical applications of SHM systems is civil infrastructure. For this application, it is particularly important that SHM systems be inexpensive and easy to deploy, since the maintenance of infrastructure is often inadequately funded. Wireless sensor networks (WSN) can be very useful toward this end. We present an efficient WSN-based SHM algorithm for detecting, localizing, and monitoring the progression of damage in infrastructure applications. The algorithm utilizes a novel vibration-based pattern matching technique that is very well suited for low-power WSN nodes. During a training phase, a body of reference patterns is formed from vibrations observed at sensor nodes distributed throughout the structure. During the operational phase, observed patterns are compared to the reference patterns to determine if a match exists. Through the use of an innovative distributed algorithm, a time complexity of O(logN) is achieved for the matching process. If a match does not exist, potential damage is indicated and the reference pattern closest to the observed pattern is determined using Euclidean distance. The difference between the two patterns indicates the sensor nodes at which potential damage exists. Clusters are then formed around these sensor nodes in order to monitor the progression of local damage. Simulations are performed in MATLAB for a typical bridge deployment in order to determine the degree of overlapping that occurs as clusters are generated in response to potential damage. The simulations indicate that overlapping increases gracefully as the number of nodes experiencing damage increases.

As wireless sensor network (WSN)-based structural health monitoring (SHM) systems are increasingly being employed in civil infrastructures and building structures, the management of large numbers of sensing devices and the large amount of data acquired from WSNs will become increasingly difficult unless systematic expressions of the sensor network are provided. This study introduces a practical WSN for SHM that consists of sensors, wireless sensor nodes, repeater nodes, master nodes, and monitoring servers. This study also proposes a symbolic and graphical representation scheme (SGRS) for this system, in which the communication relationships and respective location information of the distributed sensing components are expressed in a concise manner. The SGRS was applied to the proposed WSN, which is employed in an actual large-scale irregular structure in which three types of sensors (75 vibrating wire strain gauges, 10 inclinometers, and three laser displacement sensors) and customized wireless sensor nodes are installed. The application results demonstrate that prompt identification of sensing units and effective management of the distributed sensor network can be realized from the SGRS. The results also demonstrate the superiority of the SGRS over conventional expression methods in which a box diagram or tree diagram representing the ID of sensors and data loggers is used.

Structural Health Monitoring (SHM) is the science and technology of monitoring and assessing the condition of aerospace, civil and mechanical infrastructures using a sensing system integrated into the structure. Impedance-based SHM measures impedance of a structure using a PZT (Lead Zirconate Titanate) patch. This paper presents a low-power wireless autonomous and active SHM node called Autonomous SHM Sensor 2 (ASN-2), which is based on the impedance method. In this study, we incorporated three methods to save power. First, entire data processing is performed on-board, which minimizes radio transmission time. Considering that the radio of a wireless sensor node consumes the highest power among all modules, reduction of the transmission time saves substantial power. Second, a rectangular pulse train is used to excite a PZT patch instead of a sinusoidal wave. This eliminates a digital-to-analog converter and reduces the memory space. Third, ASN-2 senses the phase of the response signal instead of the magnitude. Sensing the phase of the signal eliminates an analog-to-digital converter and Fast Fourier Transform operation, which not only saves power, but also enables us to use a low-end low-power processor. Our SHM sensor node ASN-2 is implemented using a TI MSP430 microcontroller evaluation board. A cluster of ASN-2 nodes forms a wireless network. Each node wakes up at a predetermined interval, such as once in four hours, performs an SHM operation, reports the result to the central node wirelessly, and returns to sleep. The power consumption of our ASN-2 is 0.15 mW during the inactive mode and 18 mW during the active mode. Each SHM operation takes about 13 seconds to consume 236 mJ. When our ASN-2 operates once in every four hours, it is estimated to run for about 2.5 years with two AAA-size batteries ignoring the internal battery leakage.

To mitigate infrastructure deterioration, structural health monitoring (SHM) has been employed for more than half a century, gaining momentum with recent advancements in information, communication, and sensing technologies. In particular, wireless sensor networks have gradually been incorporated into SHM, offering new opportunities towards enhanced flexibility and scalability, as compared to cable-based SHM systems. However, wireless sensor nodes are installed at fixed locations and, causing high installation costs, need to be employed at high density to reliably monitor large infrastructure. This feasibility study proposes quadruped robots for wireless SHM of civil infrastructure, leveraging advantages regarding cost-efficiency and maneuverability. Aiming at cost-efficiency, the quadruped robots are implemented using off-the-shelf components. The robots are equipped with sensors to collect acceleration data relevant to SHM of civil infrastructure, with cameras for navigation, and with embedded algorithms, facilitating autonomous data processing, analysis, synchronization, and communication. The accuracy of the quadruped robots is validated in laboratory tests on a shear-frame structure by comparing the SHM data collected and analyzed by the quadruped robots with SHM data collected by a high-precision cable-based SHM system. Furthermore, the maneuverability and efficiency of the quadruped robots is demonstrated through field tests conducted on a road bridge by comparing the sensor information collected by the robots with the respective sensor information collected by a comprehensive benchmark SHM system. The results confirm that the quadruped robots, as compared to stationary wireless sensor nodes, require a smaller number of nodes to achieve the same sensor information and, as compared to wheeled robots, offer better maneuverability, as critical parts of civil infrastructure may be hard to reach. In summary, this feasibility study represents a first step towards robotic fleets employed for autonomous SHM.

Wireless sensor nodes for generic signal conditioning: Application to Structural Health Monitoring of wind turbines

As newer and more reliable ways of construction were developed, civilization began to spread out further and retain functional infrastructure for longer periods of time.[...]

Structural health monitoring (SHM) has been an important research area for evaluating and designing reliability of engineering structures in recent years. And with recent advances in the technologies in sensing, wireless communication, and micro electro mechanical systems (MEMS), wireless sensor technique has been developed rapidly and used gradually in the SHM for engineering structures. In this paper, wireless inclinometer sensor and its Data Acquisition System(DAS) for swing monitoring of large scale structures are designed. Firstly, a kind of wireless inclinometer acquisition system structure is introduced. Secondly, the sensing unit MEME SCA100T’s principles and design are discussed in detail, the development of wireless communication module and power unit are given, and all hardware units are integrated into a wireless inclinometer sensor node. Thirdly, the data acquisition system software, which can finish such the functions as data collection, data FFT, is designed. Finally, Experimental results are given to show the feasibility of the developed wireless inclinometer sensor and its data acquisition system.

The efficiency of transportation system depends on many factors, such as traffic congestion, vehicle accidents and road conditions. To improve the reliability, productivity and safety of the system, many researchers propose to use a wireless sensor network (WSN) as a solution. A WSN usually consists of many tiny sensor nodes for sensing, data processing and communication. In this study, we present the development of a small-sized, low-power and lightweight wireless sensor node. It is equipped with a 3-axes accelerometer, an altimeter sensor, humidity sensor, temperature sensor, 315 MHz RF transceiver module and a typical coin-sized lithium battery (3.0 V, 220 mAh). The entire sensor node fits within a 28 × 20 × 8 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> volume and is only 7 grams (not including the antenna). An 8-bit MCU is included in the RF transceiver module to control sensor node operation. It collects and transmits sensors data in real time to the RF repeater with bit rate 24 kbps. During continuous operation, the sensor node consumes less than 3 mA current. Thus for a 220 mAh battery, the wireless sensor node can continue operating for more than 75 hours.

Over the last few years, IoT devices have multiplied their number and functionality. These devices are located all over the world and batteries are their main source of energy. In this paper the usage of wireless LoRaWAN sensor node in smart Internet of Things applications was analyzed. The study focuses on the reduction of power consumption from wireless LoRaWAN sensor nodes. An analysis of the energy consumption of the various components of the architecture of the wireless sensor nodes is performed. An energy model of the energy consumed by the sensor nodes is presented and analyzed. The result of the analysis provides an accurate identification of the main energy consumers, the magnitude of their consumption and an in-depth understanding of the key mechanisms that need to be applied to improve energy efficiency in wireless sensor nodes. The emphasis is on the presented energy efficient protocol. Three action scenarios from the sensor nodes are presented, outlining the main guidelines and strategies for improving the efficiency of the wireless nodes. In addition, the research results reveal the magnitude of energy savings that can be achieved by implementing the improved duty cycle mechanisms in wireless sensor nodes.

The frequency shift and amplitude change in Schumann resonance (SR) as a precursor of some moderate to strong earthquakes was observed and reported. Co-seismic SR variation could be occurring at even large magnitude and scale. In this study, we first model Schumann resonance associated with the occurrence of an earthquake and assess the SR variation recorded from an earth-based sensor network. Based on the computer simulation results, we then propose a wireless observation system to monitor SR as a potential precursor prior to an earthquake using a wireless sensor network (WSN). A WSN based on single antenna wireless sensor nodes are cooperated to establish a multiple-antenna WSN that is called virtual MIMO-WSN. Virtual MIMO-WSN is adjustable and tunable to monitor electromagnetic signals in different frequencies based on the number of the cooperative wireless sensor nodes. An electromagnetic map could then be generated by activating a virtual MIMO-WSN in specific direction by switching on/off certain sensor nodes based on their location (also known as beamforming). Cost effectiveness, system scalability, ease of deployment, adjustability in frequency tuning, and reliability in ELF/VLF direction-finding are the key design factors in virtual MIMO-WSN to overcome the bottlenecks in the existing techniques for ELF/VLF monitoring systems. Simulation results are used to evaluate these quality indices of the proposed virtual MIMO-WSN.