Sensor network design based on system-wide reliability criteria. Part II: Formulations and applications

In part I of this series of articles, the concept of overall system reliability was presented for two applications: reliable estimation of variables for steady state linear flow processes, and reliable fault detection and diagnosis for any process. In this part, systematic generation of the proposed system-wide reliability expression is discussed. In particular, an approach for generating the system reliability using the sum of disjoint product method is presented. This serves as the objective function to be maximized in various constrained optimization formulations for sensor network design, which are also proposed in this work for both applications. A heuristic is proposed to solve the resulting nonlinear integer programming problems. The sensor network design formulations are applied to two benchmark case studies: (1) Tennessee Eastman process, (2) Steam metering process. Results indicate the utility of the proposed sensor network design approach in designing optimal sensor networks that maximize system reliability.     

多尺度传感网络失效节点检测系统设计

对多尺度传感网络中的失效节点进行准确检测与定位,实现故障节点的高效检测,保障传感网络的可靠运行。提出一种基于多传感器量化融合跟踪滤波检测的失效节点检测算法,并进行检测系统优化设计。构建多尺度传感网络的节点分布实体对象模型,进行失效节点检测系统总体设计和技术指标分析。设计基于多传感器量化融合跟踪滤波检测的失效节点检测算法。进行系统的硬件设计,包括A/D模块设计、时钟电路设计、程序加载电路设计、传感器通信模块设计和系统电源模块设计。在ARM Cortex?-M0平台上进行检测系统软件开发。系统仿真结果表明,该系统进行多尺度传感网络失效节点检测的准确度较高,提高了传感器网络的寿命周期。     

A duality based framework for integrating reliability and precision for sensor network design

In sensor network design literature, requirements such as maximization of the network reliability [Y. Ali, S. Narasimhan, Sensor network design for maximizing reliability of linear processes, AIChE J. 39 (1993) 820–828; Y. Ali, S. Narasimhan, Redundant sensor network design for linear processes, AIChE J. 41 (1995) 2237–2249] and minimization of cost subject to precision constraints [M. Bagajewicz, Design and retrofit of sensor networks in process plants, AIChE J. 43 (1997) 2300–2306; M. Bagajewicz, E. Cabrera, New MILP formulation for instrumentation network design and upgrade, AIChE J. 48 (2002) 2271–2282] have been proposed as a criteria for optimally locating sensors. In this article, we show that the problems of maximizing reliability and maximizing precision (or minimizing variance) for linear processes are dual of each other. To achieve this duality, we propose transformations which can be used to convert sensor failure probabilities into equivalent sensor variances and vice versa. Thus, the duality enables working in a single framework with specified criteria on reliability as well as precision. As an application of this duality, we propose two formulations for the sensor network design problem viz., maximization of the network reliability subject to precision constraints and minimization of the network variance subject to reliability constraints. We also show the utility of these formulations to determine the pareto-front for the combinatorial sensor network design problem. Hydrodealkylation and steam-metering case studies are used to illustrate the proposed ideas.     

Achieving maximum reliability in fault tolerant network design for variable networks

The objective of this paper is to present a novel method to achieve maximum reliability for fault tolerant optimal network design when network has variable size. Reliability calculation is most important and critical component when fault tolerant optimal network design is required. A network must be supplied with certain parameters that guarantee proper functionality and maintainability under worse situations. Many alternative methods for measuring reliability have been stated in literature for optimal network design. Most of these methods mentioned in literature for evaluating reliability may be analytical and simulation based. These methods provide significant way to compute reliability when network has limited size. Also, significant computational effort is required for growing variable sized networks. Therefore, a novel neural network method is presented to achieve significant high reliability for fault tolerant optimal network design in highly growing variable networks. This paper computes reliability with improved learning rate gradient descent based neural network method. The result shows that improved optimal network design with maximum reliability is achievable by novel neural network at manageable computational cost.     

Audit of sensor networks for efficient fault diagnosis

The problem of sensor network design is to choose a set of variables that are to be measured in the process for satisfying various objectives related to estimability, data reconciliation, gross error detection, fault diagnosis, etc. Approaches to design base case sensor network as well as modify existing network by reallocating and upgrading sensors are available in the literature. In this work we extend the concept of reallocation and upgrade by developing an optimization based strategy to perform audit of a sensor network. Apart from identifying sensors to be reallocated and upgraded, the audit strategy also identifies sensors whose removal does not lead to a decrease in the performance of the sensor network. Such information can possibly be utilized in deciding what variables (or in what sequence) to be displayed to the process operator/engineer to accomplish a particular objective. In this work, we focus on fault diagnosis related performance criteria to illustrate the sensor network audit idea. In particular, we perform sensor network audit with objectives being: (i) ensuring observability of all faults, (ii) minimizing the unreliability of detection of faults (i.e. minimizing the probability of faults occurring and remaining undetected). The latter problem is in turn solved for two scenarios: when probability data and cause–effect models used for sensor network design are accurately known as well as for situations when there is uncertainty associated with such information. The resulting optimization problems are mixed integer linear programming in nature. The utility of the proposed approaches is demonstrated by applying them to the well known Tennessee Eastman process.     

Multi-objective evolutionary approaches for intelligent design of sensor networks in the petrochemical industry

The design of optimal sensor networks for an industrial process is a complex problem that requires the resolution of several tasks with a high level of expertise. The first of these subproblems consists in selecting an initial sensor network as the starting point for the instrumentation design. This particular task constitutes a combinatorial optimization problem, where several goals are prosecuted by the designer. Therefore, the initialization procedure can be defined as a multi-objective optimization problem. In this paper, the use of multi-objective evolutionary approaches to assist experts in the design of an initial sensor network is proposed and analyzed. The aim is to contrast the advantages and limitations of Pareto and non-Pareto techniques in the context of this industrial application. The algorithms consider objectives related to cost, reliability and level of information associated with a sensor network. The techniques were evaluated by means of a comparative analysis for a strongly non-linear mathematical model that represents an ammonia synthesis plant. Results have been contrasted in terms of the set coverage and spacing metrics. As a final conclusion, the non-Pareto strategy converged closer to the Pareto front than the Pareto-based algorithms. In contrast, the Pareto-based algorithms achieved better relative distance among solutions than the non-Pareto method. In all cases, the use of evolutionary computation is useful for the expert to take the final decision on the preferred initial sensor network.     

基于功率调节的IWSN实时可靠路由研究

针对工业无线传感器网络对延迟、可靠传输以及成本的特殊要求,研究了一种基于功率调节的实时可靠路由协议,将两跳速度策略引入到路由算法中,提高工业无线传感器网络的实时性;将节点剩余能量以及能耗同时考虑,以平衡网络能量并提高网络寿命;引入功率调节机制以绕开路由空洞,提高节点可靠性.仿真结果显示,与已有方法相比,采用的方法在总可靠度、截止期错失率以及包平均延迟上有着显著改善.     

Poly: A reliable and energy efficient topology control protocol for wireless sensor networks

Energy efficiency and reliability are the two important requirements for mission-critical wireless sensor networks. In the context of sensor topology control for routing and dissemination, Connected Dominating Set (CDS) based techniques proposed in prior literature provide the most promising efficiency and reliability. In a CDS-based topology control technique, a backbone - comprising a set of highly connected nodes - is formed which allows communication between any arbitrary pair of nodes in the network. In this paper, we show that formation of a polygon in the network provides a reliable and energy-efficient topology. Based on this observation, we propose Poly, a novel topology construction protocol based on the idea of polygons. We compare the performance of Poly with three prominent CDS-based topology construction protocols namely CDS-Rule K, Energy-efficient CDS (EECDS) and A3. Our simulation results demonstrate that Poly performs consistently better in terms of message overhead and other selected metrics. We also model the reliability of Poly and compare it with other CDS-based techniques to show that it achieves better connectivity under highly dynamic network topologies.     

A reliable multi-objective control strategy for batch processes based on bootstrap aggregated neural network models

This paper presents a reliable multi-objective optimal control method for batch processes based on bootstrap aggregated neural networks. In order to overcome the difficulty in developing detailed mechanistic models, bootstrap aggregated neural networks are used to model batch processes. Apart from being able to offer enhanced model prediction accuracy, bootstrap aggregated neural networks can also provide prediction confidence bounds indicating the reliability of the corresponding model predictions. In addition to the process operation objectives, the reliability of model prediction is incorporated in multi-objective optimisation in order to improve the reliability of the obtained optimal control policy. The standard error of the individual neural network predictions is taken as the indication of model prediction reliability. The additional objective of enhancing model prediction reliability forces the calculated optimal control policies to be within the regions where the model predictions are reliable. By such a means, the resulting control policies are reliable. The proposed method is demonstrated on a simulated fed-batch reactor and a simulated batch polymerisation process. It is shown that by incorporating model prediction reliability in the optimisation criteria, reliable control policy is obtained.     

无线传感器网络中基于网络编码的可靠数据传输策略

结合网络编码理论,提出了一种适应于无线传感器网络环境的可靠数据传输策略——M Growth Codes,通过基于梯度的有向路由,保证所有数据都朝着汇聚节点的方向汇聚。另外该数据传输策略还可以实现利用编码包实现对其他编码包的解码操作,进一步增强了数据的可恢复性。经过网络仿真验证表明M Growth Codes策略能有效提高无线传感器网络的吞吐量并改善数据传输的可靠性。     

嵌入式无线传感网络网关设计与远程维护

针对无线传感网络(WSN)网关软件系统维护不便问题,开发了一种基于ARM CortexA-8嵌入式平台的无线传感网络网关.阐述了网关的硬件设计方案和Linux操作系统平台上软件实现方法,实现了无线传感网络与Internet的信息互通.同时在C/S模式下,开发了网关远程维护软件,该软件采用TCP/IP协议确保了数据传输的可靠性,使用MTD工具实现了软件系统在线升级或更新.实验结果表明,该网关运行稳定可靠、系统维护方便高效.     

一种基于IEEE1451的嵌入式网络化智能前端的设计与实现

本文基于智能化、网络化的设计思想,借助IEEE1451智能变送器接口标准和网络技术,搭建了一个嵌入式、开放的设备网络化智能维护系统。基于敏捷制造对制造过程管理与控制的需求,研究并建立了制造系统智能前端的原型。基于IEEE1451标准的设计思想和DSP及ARM和HPI技术,介绍了智能前端的软硬件构成与网络接口设计。并针对该系统的高可靠性、网络化和智能化要求,提出了多参数集成智能维护前端的解决方案。实验表明,系统运行稳定,实时性良好。     

Optimal sensor network design for multirate systems

A methodology for generating optimal sensor network design for multirate systems is presented. Location of sensors, cost of measurement and frequency of sampling are important factors that have been incorporated in the sensor network design formulation. The proposed methodology is based on evaluating trade-off (Pareto optimal) solutions between the quality of state estimation and the total measurement cost associated with the sensor network. To accommodate different sampling frequencies and evaluate their effect on state estimation accuracy, a generic multirate extension of the traditional Kalman filter is used. In general, higher accuracies of the state estimates are realizable at expense of higher measurement cost. Incorporation of these conflicting objectives of minimizing measurement cost and maximizing estimation accuracy results in a combinatorial, implicit multiobjective optimization problem, which is solved using the well-known non-dominated sorting genetic algorithm-II. The resulting solutions can be then analyzed by the process designer for determining an appropriate sensor network. The methodology is demonstrated by generating optimal sensor network design for the benchmark quadruple tank set up [K.H. Johansson, The quadruple-tank process: a multivariable laboratory process with an adjustable zero, IEEE Trans. Control Syst. Tech. 8 (3) (2000) 456–465] and the Tennessee Eastman challenge process [J.J. Downs, E.F. Vogel, A plant-wide industrial process control problem, Comput. Chem. Eng. 17 (3) (1993) 245–255].     

用于大坝安全监测的长距离WSNs节点设计

针对大坝安全监测的需求,结合无线传感器网络的特点,设计了一种基于JN5139无线射频模块的用于大坝安全监测的无线传感器网络节点。简要介绍了无线传感器网络的典型网络结构,重点描述了无线传感器网络节点的硬件和软件设计,并通过在野外环境下搭建簇—树型网络,对传感器网络进行测试。实验结果表明节点数据采集准确,传输可靠。     

Reliable Communication Networks for Smart Grid Transmission Systems

In this paper, we discuss the communications reliability requirements posed by the smart power grid with a focus on communications in support of wide area situational awareness. Implementation of wide area situational awareness relies on both transmission substation networks and wide area optical networks. We study the reliability of a sample communications network of the California Power Grid and find that its reliability falls short of proposed requirements. To overcome this issue, we consider the problem of designing the substation network and the wide area network to meet the reliability requirements while minimizing the network cost. For the wide area network design problem, we propose two alternate design approaches, namely: (1) following the power lines and (2) a mesh based design interconnecting the nodes. For the first approach we develop two greedy iterative heuristics and a heuristic integer linear programming (H-ILP) model using minimum cut-sets for network reliability optimization. The greedy iterative algorithms outperform the H-ILP approach in terms of cost, but require a larger amount of computing resources. Both proposed models are in fact complementary and thus provide a framework to optimize the reliability of smart grid communications networks restricted to following the power lines. In the second approach a greenfield mesh network method is proposed based on starting with a minimum spanning tree which is then augmented through a greedy heuristic into a mesh. Comparative numerical results show that the reliable mesh design has advantages in terms of the number of links and total link distance needed.     

WirelessHART无线传感器网络技术及其应用

WirelessHART是面向过程控制和资产管理可靠的协议。近几年,工业过程自动化用户选用WirelessHART协议已超过其它标准,该通信协议从而成为最好的无线传感器网络国际标准。本文较全面论述WirelessHART工业无线传感器网络技术的优点、数据传送技术、时间同步网状网络协议（TSMP）、系统架构、网络系统应用,以及WirelessHART无线网络的组网与设计。较详细阐述了菲尼克斯电气公司最近研发的具有WLAN能力的WirelessHART智能网关,它将消除回程电缆,大大提高网络的灵活性和进一步降低成本。最后,给出WirelessHART组网设计的原则。     

基于ZigBee与数传电台的矿井环境检测系统节点设计及其组网方案

针对因煤矿井下环境复杂造成无线传感器网络无法有效地远距离传输信息的问题,提出了一种基于ZigBee无线传感器网络与数传电台的矿井环境检测系统的设计方案,给出了系统总体结构,介绍了以CC2430为核心的传感器节点和网关节点的设计,阐述了适合于矿井环境的ZigBee无线传感器树形网络组网方案的实现。实际测试结果表明,该系统采用ZigBee无线传感器网络与数传电台相结合的通信方案是切实可行的,有效解决了低功耗、远距离传输、高可靠性方面的问题;对节点进行编号的组网规则使网络拓扑结构更具有针对性,提高了节点的精确定位功能,降低了井下作业的危险性。     

基于幂函数曲线和网络编码的多媒体传感网大数据可靠传输控制

提出了一种适用于无线多媒体传感器网络的基于幂函数回归曲线预测和随机线性网络编码的协同合作大数据可靠传输控制机制,以为多媒体大数据传输提供高可靠性、资源利用率和服务质量的保障。首先根据多媒体数据特征和动态网络拓扑,提出一种基于幂函数回归曲线的预测模型;然后在网络层和物理层以视频帧为单位进行网络编码;最后建立一种基于预测和网络编码的协同合作大数据可靠传输控制机制。通过数学分析和仿真验证,分析了所提机制与传统机制的系统性能,证明了所提机制的优越性能。     

无线传感器网络中间件技术研究综述

无线传感器网络在受到广泛应用与关注的同时,由于网络复杂度及网络应用的增加,普遍存在缺乏统一开放接口的问题。针对无线传感器网络结构及特点,介绍无线传感器网络中间件技术概念,在全面分析中间件面临的问题与挑战的基础上,比较几种不同设计方法,并且通过典型实例在几个重要性能参数方面进行了对比。最后在中间件QoS机制模型方面提出了一种改进方法。