A Novel RFID-Based Strain Sensor for Wireless Structural Health Monitoring

Conventional tools for deformation measurement are widely used for structural health monitoring—i.e. strain gauges and fiber optic sensors—due to their relative low cost and efficiency. However, these techniques still present some drawbacks particularly in limited access locations, since their usage requires some sort of cabling or battery-driven electronics. Thus, in a few situations there may be room for new technologies for deformation monitoring of structures. One of the options are passive radio frequency identification (RFID)-based sensors. In synthesis, like conventional methods, these sensors are attached to the surface a test-piece, but are then remotely interrogated and powered by a transmitter. The solidarity of the sensor to the underlying material means that the detected signal is modified in a way that can be correlated to sample strain in a given direction. This paper encompasses the project of a wireless deformation sensor based on an inverted-F antenna focusing on its miniaturization and performance optimization. For this purpose, such an antenna was designed with the help of finite element modelling tools for operation on a 2.0 mm-thick aluminium sheet, and then experimentally validated through static loading tests. Finally, even though sensors of this kind are still in early developments, results show that RFID sensors represents a promising method for remote deformation assessment in components.     

Wireless Acoustic Emission Sensor Network for Structural Monitoring

The paper presents a prototype wireless system for the detection of active fatigue cracks in aging railways bridges in real-time. The system is based on a small low-cost sensor node, called an AEPod, that has four acoustic emission (AE) channels and a strain channel for sensing, as well as the capability to communicate in a wireless fashion with other nodes and a base station. AEPods are placed at fracture-critical bridge locations. The strain sensor detects oncoming traffic and triggers the AEPod out of its hibernation mode. As the train stresses the fracture-critical member, acoustic emission and strain data are acquired. The data are compressed and filtered at the AEPod and transmitted off the bridge using cell-phone communication.     

A Wireless Sensor Network for Cold-Chain Monitoring

This paper deals with a wireless sensor network that was specifically designed to monitor temperature-sensitive products during their distribution with the aim of conforming to the cold-chain assurance requirements. The measurement problems and the constraints that have been encountered in this application are initially highlighted, and then, an architecture that takes such problems into account is proposed. The proposed architecture is based on specifically designed measuring nodes that are inserted into the products to identify their behavior under real operating conditions, e.g., during a typical distribution. Such product nodes communicate through a wireless channel with a base station, which collects and processes the data sent by all the nodes. A peculiarity of the product nodes is the low cost, which allows the information on the cold-chain integrity to be provided to the final customer. The results that refer to the functional tests of the proposed system and to the experimental tests performed on a refrigerated vehicle during a distribution are reported.     

浅述无线传感器网络技术

无线传感器网络能够通过节点上的传感器对被监测量进行感知、采集和实时监测,并将这些信息传递给监测中心,具有部署快、无人值守、功耗低、性价比高等优点,十分适用于环境监测。     

Illumimote: Multimodal and High-Fidelity Light Sensor Module for Wireless Sensor Networks

We describe the system requirements, design, system integration, and performance evaluation of the Illumimote, a new light-sensing module for wireless sensor networks. The Illumimote supports three different light-sensing modalities: incident light intensity, color intensities, and incident light angle (the angle of ray arrival from the strongest source); and two situational sensing modalities: attitude and temperature. The Illumimote achieves high performance, comparable to commercial light meters, while conforming to the size and energy constraints imposed by its application in wireless sensor networks. We evaluated the performance of our Illumimote for light intensity, color temperature, and incident light angle measurements and verified the function of the attitude sensor. The Illumimote consumes about 90 mW when all features on board are activated. We describe our design and the experiment design for the performance evaluation.     

Experimental Characterization of Wireless Sensor Networks for Industrial Applications

The effects of interference in the setup of wireless sensor networks (WSNs) represent a critical issue, and as such, it needs to be carefully addressed. To this aim, helpful information can be achieved through measurements to be carried out in advance on suitable prototypes and testbeds. In this paper, the measurement of industrial WSN performance is dealt with. In particular, a suitable testbed enlisting IEEE 802.15.4 wireless sensor nodes is presented along with the results of some experiments carried out even in the presence of interference. The purpose is to show how to evaluate some specific parameters of a WSN employed for industrial applications to obtain useful information for its setup optimization in the presence of interference. The analysis will show that from the measurement of these parameters (number of failed pollings, polling round-trip time, experimental cycle time, and alarm latency), interference effects can effectively be recognized, and the network setup can be optimized.      

Validation of HDOP Measure for Impact Detection in Sensor Network-Based Structural Health Monitoring

This paper studies the validity of horizontal dilution of precision (HDOP) measure to evaluate sensor network geometries when localizing impacts in structural health monitoring (SHM). First, HDOP is defined similarly to navigation applications. Even though several low-complexity closed-form solutions have been proposed recently, HDOP measure has been theoretically justified only for iterative least-squares approach. The localization errors of popular impact localization methods are experimentally collected and compared with HDOP data for validation. The experimental setup is also described. It is shown that HDOP, in general, correlates with the positioning error and can be used to characterize geometry.      

A Ring-Shaped Photodiode Designed for Use in a Reflectance Pulse Oximetry Sensor in Wireless Health Monitoring Applications

We report a photodiode for use in a reflectance pulse oximeter for use in autonomous and low-power homecare applications. The novelty of the reflectance pulse oximeter is a large ring shaped backside silicon pn photodiode. The ring-shaped photodiode gives optimal gathering of light and thereby enable very low light-emitting diode (LED) driving currents for the pulse oximeter. The photodiode also have a two layer SiO₂/SiN interference filter yielding 98% transmission at the measuring wavelengths, 660 nm and 940 nm, and suppressing other wavelengths down to 50% transmission. The photodiode has a radius of 3.68 mm and a width of 0.78 mm giving an area of 18 mm². The capacitance of the photodiode is measured to 34.5 nF. The quantum efficiency of the photodiode is measured to 55% and 62% at 660 nm and 940 nm, respectively. It is acceptable for this prototype but can be improved. The sensor also has an on-chip integrated Au thermistor for measuring the skin temperature of the body. The thermistor has a Temperature Coefficient of Resistance of 2.7·10^-3 K^-1 and a repeatability on temperature measurements of ±0.26°C. The photodiode is fabricated in a clean room environment by two diffusion processes and an Advanced Silicon Etch to make the hole in the middle for the LEDs. The sensor is designed to be integrated in a sticking patch of hydrocolloid polymer together with integrated electronics, radio communication unit, and a coin cell battery. The reflectance pulse oximetry sensor is demonstrated to work in a laboratory setup with a Ledtronics dual LED with wavelengths of 660 and 940 nm. Using this setup photoplethysmograms which clearly show the cardiovascular cycle have been recorded. The sensor is shown to work very well with low currents of less than 10 mA.     

A Reliable and High-Bandwidth Multihop Wireless Sensor Network for Mine Tunnel Monitoring

Wireless sensor network (WSN) is considered here for remote monitoring of mine tunnels. Since mine transport and exploiting plane monitoring are the complex tasks that require video monitoring, a major challenge of remote mine tunnel monitoring is the multipath and diffraction effect due to unreliable channel and limited capacity. We propose here a braided cooperative reliable transport (BCRT) algorithm for reliable video transmission within mine tunnel. BCRT maintains one-hop reliability to ensure end-to-end reliability so that it is robust to path breaks. In addition, the BCRT-based WSN uses three consecutive forward neighbors to adjust the data rate to improve the sensing reliability. The proposed WSN is implemented in a real-life mine tunnel. And it is demonstrated to be able to enhance the reliability of the end-to-end monitoring of mine tunnels.     

Feature Extraction and Sensor Fusion for Ultrasonic Structural Health Monitoring Under Changing Environmental Conditions

Strongly reverberating diffuse-like ultrasonic waves can interrogate large areas of complex structures that do not support more easily interpreted guided waves. However, sensitivity to environmental changes such as temperature and surface wetting can degrade the performance of a structural health monitoring system using these types of waves. Surface wetting is investigated here with a simplified experiment where controlled amounts of water are applied to the surface of a specimen in conjunction with incrementally introduced artificial damage. A feature-based approach is taken whereby differential features between a signal and a baseline are defined that are sensitive to damage but less sensitive to surface wetting, and multiple features obtained from a spatially distributed sensor array are combined via a voting strategy. In addition, the features considered are insensitive to moderate temperature changes, which are unavoidable even in the laboratory. Experimental results show a probability of detection greater than 90% when detecting damage in the presence of modest surface wetting while maintaining a false alarm rate under 5%.     

Reputation-Enabled Self-Modification for Target Sensing in Wireless Sensor Networks

Wireless sensor networks provide new tools for sensing physical environments. However, the general existence of faulty sensor measurements in networks will cause degradation of the network service quality and huge burden of the precious energy. While cryptography-based approaches are helpless of information generation, reputation systems are demonstrated of positive results. In this paper, we investigate the benefits of a distributed reputation system in target localization. A node reputation is defined as its measurement performance and is computed by the Dirichlet distribution. By assuming the sensing model of each node to be mixed Gaussian, we use reputation to estimate parameters of the sensing model and modify a node's original measurement. We also develop a reputation-based local voting algorithm to filter the untrustworthy data and then estimate the target location by a particle swarm optimization algorithm. To assure energy efficiency of the proposed approach, we use a reputation-based model to indicate the information importance of each data packet and ensure that a more important packet can be delivered with higher reliability. Finally, we experimentally evaluate the reputation system and demonstrate its accuracy and energy efficiency.      

A Parallel Simulated Annealing Architecture for Model Updating in Wireless Sensor Networks

In recent years, wireless sensing technologies have provided a much sought-after alternative to expensive cabled monitoring systems. Wireless sensing networks forego the high data transfer rates associated with cabled sensors in exchange for low-cost and low-power communication between a large number of sensing devices, each of which features embedded data processing capabilities. As such, a new paradigm in large-scale data processing has emerged; one where communication bandwidth is somewhat limited but distributed data processing centers are abundant. By taking advantage of this grid of computational resources, data processing tasks once performed independently by a central processing unit can now be parallelized, automated, and carried out within a wireless sensor network. By utilizing the intelligent organization and self-healing properties of many wireless networks, an extremely scalable multiprocessor computational framework can be developed to perform advanced engineering analyses. In this study, a novel parallelization of the simulated annealing stochastic search algorithm is presented and used to update structural models by comparing model predictions to experimental results. The resulting distributed model updating algorithm is validated within a network of wireless sensors by identifying the mass, stiffness, and damping properties of a three-story steel structure subjected to seismic base motion.     

Bandwidth-Efficient Geographic Multicast Routing Protocol for Wireless Sensor Networks

We present geographic multicast routing (GMR), a new multicast routing protocol for wireless sensor networks. It is a fully localized algorithm that efficiently delivers multicast data messages to multiple destinations. It does not require any type of flooding throughout the network. Each node propagating a multicast data message needs to select a subset of its neighbors as relay nodes towards destinations. GMR optimizes the cost over progress ratio where the cost is equal to the number of neighbors selected for relaying and the progress is the overall reduction of the remaining distances to destinations. Such neighbor selection achieves a good tradeoff between the bandwidth of the multicast tree and the effectiveness of the data distribution. Our cost-aware neighbor selection is based on a greedy set merging scheme achieving a O(Dnmin(D,n)³) computation time, where n is the number of neighbors of current node and D is the number of destinations. As in traditional geographic routing algorithms, delivery to all destinations is guaranteed by applying face routing when necessary. Our simulation results show that GMR outperforms position based multicast in terms of cost of the trees and computation time over a variety of networking scenarios     

Miniature Mobile Sensor Platforms for Condition Monitoring of Structures

In this paper, a wireless, multisensor inspection system for nondestructive evaluation (NDE) of materials is described. The sensor configuration enables two inspection modes-magnetic (flux leakage and eddy current) and noncontact ultrasound. Each is designed to function in a complementary manner, maximizing the potential for detection of both surface and internal defects. Particular emphasis is placed on the generic architecture of a novel, intelligent sensor platform, and its positioning on the structure under test. The sensor units are capable of wireless communication with a remote host computer, which controls manipulation and data interpretation. Results are presented in the form of automatic scans with different NDE sensors in a series of experiments on thin plate structures. To highlight the advantage of utilizing multiple inspection modalities, data fusion approaches are employed to combine data collected by complementary sensor systems. Fusion of data is shown to demonstrate the potential for improved inspection reliability.     

Structural Health Monitoring of an Annular Component using a Statistical Approach

Abstract:  For aerospace components there is undoubtedly a critical need to detect incipient damage in the structure, as any microscopic crack or defect can potentially lead to catastrophic failure and loss of human life. This paper investigates the scattering of an ultrasonic-guided wave into a hollow cylinder-like structure, under both damaged and undamaged conditions. Hollow cylinder structures are widely used not only in aerospace components but also in other engineering applications. The wave was sequentially transmitted and captured by means of a 'real-time data-acquisition system' combined with integrated disc-shaped piezoceramic transducers. The integration of the tested structure and the transducers formed a structural health monitoring system. Wave responses were recorded from both of the structural conditions for the purpose of damage identification using a novelty detection method called 'outlier analysis'. The principal component analysis method of reducing the dimensionality of the feature space is also presented in this paper, with its main aim being to visualise how the data sets behave as a function of the structural conditions.     

A Wearable and Wireless Sensor System for Real-Time Monitoring of Toxic Environmental Volatile Organic Compounds

An integrated volatile organic toxicants sensor with a Bluetooth device interface has been developed. The device is based on novel tuning fork sensor platform along with a wireless communication/interface technology taken in an integrated system approach. It features high sensitivity and selectivity. The sensitivity and selectivity are accomplished through the use of novel tuning fork sensor modified by design (molecularly imprinted) polymers and selective filtering. Experiments have shown that the device can detect toxic volatile organic compounds (VOCs) under high concentrations of common interferents from flavors and fragrances. Applications of the device for detection of BTEX in real-world situations such as outdoor and gas station VOCs have also been demonstrated. All these features make the device a promising candidate to be deployed in real-world applications, particularly in environmental health and air pollution studies.      

结构健康监测的光纤Bragg光栅传感器网络自修复实现

针对采用支持向量机理论识别飞机机翼盒段上外加载荷位置的光纤Bragg光栅传感器网络,研究了提高位置识别精度的方法;分析了网络中部分传感器失效对位置识别精度的影响,针对故障情况提出了基于模型重构的容错位置识别算法,并对采用容错位置识别算法前后载荷位置识别精度进行了详细的比较.研究结果表明:当网络中某个传感器失效时,通过模型重构容错位置识别算法可有效地实现传感器网络的自修复能力,提高传感器网络的可靠性.     

分布式无线传感器网络及其应用核心技术研究

提出一种分布式无线传感器网络体系结构,阐述了相关理论观点,分析其应用价值与研究现状：以减少传感器对网络的依赖为原则,增强传感器感知能力和感知精度、网络强壮性和容错性,并以传感器低功耗为研究思路;设计了以ARM体系结构32 b RISC（Reduce Instruction Computer）微处理器、uC／OS-Ⅱ嵌入式实时操作系统、轻量级TCP／IP网络协议LwIP（Lightweight TCP／IP Stack）,TR1000无线通信模块为核心的一种基于Internet的分布式微型无线网络传感器。     

A Novel Nonlinear Acoustic Health Monitoring Approach for Detecting Loose Bolts

To date, sensors have been the inevitable component of structural health monitoring (SHM) systems. Typically, sensory signals are digitized, processed by computers, and then the information is presented to the operator with plots or warnings depending on the sophistication of the system. This study proposes a novel nonlinear acoustic health monitoring (NAHM) approach for detection of loose bolts, which can work with and without any sensors. The structure is excited with bitonal excitations, which their difference is in the audible range. When the bolts are well tightened, the structure remains silent. But, the structure creates audible sound or verbal warnings in the presence of one or more loose bolts. There is no need for sensor(s), A/D converters or computers between the operator and the structure. However, it is also possible to attach a piezoelectric sensor or to use a microphone/sound level meter for further analysis of the structure’s response. The feasibility of the concept was demonstrated by detecting the loose bolt in a bolted plate system. For demonstrating the industrial potential of the proposed NAHM system, the concept was implemented for two simple washers held with nuts and bolts. Additionally, the intensities of the audible alarms were studied at different torque levels. The proposed NAHM may be used as a low-cost sensor-free SHM or as a backup for conventional nonlinear SHM systems.     

Energy-Efficient Distributed Adaptive Multisensor Scheduling for Target Tracking in Wireless Sensor Networks

Due to uncertainties in target motion and limited sensing regions of sensors, single-sensor-based collaborative target tracking in wireless sensor networks (WSNs), as addressed in many previous approaches, suffers from low tracking accuracy and lack of reliability when a target cannot be detected by a scheduled sensor. Generally, actuating multiple sensors can achieve better tracking performance but with high energy consumption. Tracking accuracy, reliability, and energy consumed are affected by the sampling interval between two successive time steps. In this paper, an adaptive energy-efficient multisensor scheduling scheme is proposed for collaborative target tracking in WSNs. It calculates the optimal sampling interval to satisfy a specification on predicted tracking accuracy, selects the cluster of tasking sensors according to their joint detection probability, and designates one of the tasking sensors as the cluster head for estimation update and sensor scheduling according to a cluster head energy measure (CHEM) function. Simulation results show that, compared with existing single-sensor scheduling and multisensor scheduling with a uniform sampling interval, the proposed adaptive multisensor scheduling scheme can achieve superior energy efficiency and tracking reliability while satisfying the tracking accuracy requirement. It is also robust to the uncertainty of the process noise.