This paper presents the design of a wireless sensor network particularly designed for remote monitoring and control of industrial parameters. The article describes the network components, protocol and sensor deployment, aimed to accomplish industrial constraint and to assure reliability and low power consumption. A particular case of study is presented. The system consists of a base station, gas sensing nodes, a tree-based routing scheme for the wireless sensor nodes and a real-time monitoring application that operates from a remote computer and a mobile phone. The system assures that the industrial safety quality and the measurement and monitoring system achieves an efficient industrial monitoring operations. The robustness of the developed system and the security in the communications have been guaranteed both in hardware and software level. The system is flexible and can be adapted to different environments. The testing of the system confirms the feasibility of the proposed implementation and validates the functional requirements of the developed devices, the networking solution and the power consumption management.

An Efficient Wireless Sensor Network for Industrial Monitoring and Control.

Latent factor &#x0028 LF &#x0029 models are highly effective in extracting useful knowledge from High-Dimensional and Sparse &#x0028 HiDS &#x0029 matrices which are commonly seen in various industrial applications. An LF model usually adopts iterative optimizers, which may consume many iterations to achieve a local optima, resulting in considerable time cost. Hence, determining how to accelerate the training process for LF models has become a significant issue. To address this, this work proposes a randomized latent factor &#x0028 RLF &#x0029 model. It incorporates the principle of randomized learning techniques from neural networks into the LF analysis of HiDS matrices, thereby greatly alleviating computational burden. It also extends a standard learning process for randomized neural networks in context of LF analysis to make the resulting model represent an HiDS matrix correctly. Experimental results on three HiDS matrices from industrial applications demonstrate that compared with state-of-the-art LF models, RLF is able to achieve significantly higher computational efficiency and comparable prediction accuracy for missing data. I provides an important alternative approach to LF analysis of HiDS matrices, which is especially desired for industrial applications demanding highly efficient models.

Randomized latent factor model for high-dimensional and sparse matrices from industrial applications

Using wireless sensor network (WSN) for building new sensing and actuating applications in space and extreme environments (SEEs) can fuel a new application paradigm if it can be adopted into a new strategy. This complementary contribution from the Guest Editors carries an important message of breaking away from conventional WSN research and developments and adopting a heterogeneous agile unconventional wireless sensing (UWS) approach deployment. For this, we urge the use of lightweight WSN known as wireless sensor systems (WSS) to develop optimized solutions for SEE. This paper also discusses some critical technologies of WSS-SEE and includes three key aspects of a new approach to examine: 1) the characterizes of SEE; 2) potential applications of UWS; and 3) heterogeneously nature of the applications. A further clarification for deployment of UWS is demonstrated using a table with six groups of typical application areas from the recent publications media.

Wireless Sensor Systems for Space and Extreme Environments: A Review

Aiming at the problems of the low mobility, low location accuracy, high communication overhead, and high energy consumption of sensor nodes in underwater acoustic sensor networks, the MPL (movement prediction location) algorithm is proposed in this article. The algorithm is divided into two stages: mobile prediction and node location. In the node location phase, a TOA (time of arrival)-based ranging strategy is first proposed to reduce communication overhead and energy consumption. Then, after dimension reduction processing, the grey wolf optimizer (GWO) is used to find the optimal location of the secondary nodes with low location accuracy. Finally, the node location is obtained and the node movement prediction stage is entered. In coastal areas, the tidal phenomenon is the main factor leading to node movement; thus, a more practical node movement model is constructed by combining the tidal model with node stress. Therefore, in the movement prediction stage, the velocity and position of each time point in the prediction window are predicted according to the node movement model, and underwater location is then completed. Finally, the proposed MPL algorithm is simulated and analyzed; the simulation results show that the proposed MPL algorithm has higher localization performance compared with the LSLS, SLMP, and GA-SLMP algorithms. Additionally, the proposed MPL algorithm not only effectively reduces the network communication overhead and energy consumption, but also improves the network location coverage and node location accuracy.

A Node Location Algorithm Based on Node Movement Prediction in Underwater Acoustic Sensor Networks

Fully electrified ships, which is known as the “all-electric ships (AESs)”, have the potentials to bring great economic /environmental benefits. To further improve the energy efficiency of AESs, PV generations are gradually integrated, which introduces uncertainties to the AES operation. However, current researches mostly focus on sizing problem whereas rarely concern the operation. In this perspective, a data-driven robust coordination of generation and demand-side is proposed to properly address the onboard PV generation uncertainties as well as reducing the fuel cost of AESs, which consists of an extreme learning machine (ELM) based PV uncertainty forecasting method and a two-stage operating framework, where the first stage for the worst PV generation case and the second stage targets at the uncertainty realization. A 4-DG AES is implemented into the case study and the simulation results show that the ELM-based method can well characterize the PV uncertainties, and the two-stage operating framework can well accommodate the onboard PV uncertainties. Further analysis also demonstrates the proposed method has enough flexibility when facing working condition variations.

Data-Driven Robust Coordination of Generation and Demand-Side in Photovoltaic Integrated All-Electric Ship Microgrids

Wireless sensor networks (WSNs) are energyconstrained, so energy saving is one of the most important issues in typical applications. The clustered WSN topology is considered in this paper. To achieve the balance of energy consumption and utility of network resources, we explicitly model and factor the effect of power and rate. A novel joint optimization model is proposed with the protection for cluster head. By the mean of a choice of two appropriate sub-utility functions, the distributed iterative algorithm is obtained. The convergence of the proposed iterative algorithm is proved analytically. We consider general dual decomposition method to realize variable separation and distributed computation, which is practical in large-scale sensor networks. Numerical results show that the proposed joint optimal algorithm converges to the optimal power allocation and rate transmission, and validate the performance in terms of prolonging of network lifetime and improvement of throughput.

An approach of distributed joint optimization for cluster-based wireless sensor networks

Optimal power management of shipboard power system for failure mode (OPMSF) is a significant and challenging problem considering the safety of system and person. Many existing works focused on the transient-time recovery without consideration of the operating cost and the voyage plan. In this paper, the OPMSF problem is formulated considering the mid-time scheduling and the faults at bus and generator. Two-side adjustment methods including the load shedding and the reconfiguration are coordinated for reducing the fault effects. To address the formulated non-convex problem, the travel equality constraint and fractional energy efficiency operation indicator limitation are transformed into the convex forms. Then, considering the infeasibility scenario affected by faults, a further relaxation is adopted to formulate a new problem with feasibility guaranteed. Furthermore, a sufficient condition is derived to ensure that the new problem has the same optimal solution as the original one. Because of the mixed-integer nonlinear feature, an optimal management algorithm based on Benders decomposition (BD) is developed to solve the new one. Due to the slow convergence caused by the time-coupled constraints, a low-complexity near-optimal algorithm based on BD is proposed. The results verify the effectivity of the proposed methods and algorithms.

Optimal Power Management for Failure Mode of MVDC Microgrids in All-Electric Ships

In this paper, a mobile anchor node assisted RSSI localization scheme in underwater wireless sensor networks (UWSNs) is proposed, which aims to improve location accuracy and shorten location time. First, to improve location accuracy, we design a support vector regression (SVR) based interpolation method to estimate the projection of sensor nodes on the linear trajectory of the mobile anchor node. The proposed method increases the accuracy of the nonlinear regression model of noisy measured data and synchronously decreases the estimation error caused by the discreteness of measured data. Second, to shorten location time, we develop a curve matching method to obtain the perpendicular distance from sensor nodes to the linear trajectory of the mobile anchor node. The location of the sensor node can be calculated based on the projection and the perpendicular distance. Compared with existing schemes that require the anchor node to travel at least two trajectories, the proposed scheme only needs one-time trajectory to locate sensor nodes, and the location time is shortened with the reduction in the number of trajectories. Finally, simulation results prove that the proposed scheme can obtain more accurate sensor node location in less time compared with the existing schemes.

https://www.mdpi.com/1424-8220/19/20/4369/pdf

A Mobile Anchor Node Assisted RSSI Localization Scheme in Underwater Wireless Sensor Networks.

The invention discloses a power transmission line evaluation and diagnosis method, which includes the following steps: (A) acquiring the power data, abnormal power data and environmental data of a power transmission line on the sensing layer, including the voltage, current, electric quantity, power, frequency, power factor, phase, harmonic waves, power voltage loss, power phase failure, electricity theft, temperature, humidity, icing, wind deflection, lightning strike, power transmission tower side wind speed and rainfall, tension, stress, salt density, sag, displacement and acceleration of each node of the power transmission line; (B) transmitting the acquired data to the application layer via a network layer; (C) carrying out fluctuation analysis on the data on the application layer, carrying out evaluation and analysis on the power transmission line according to an analysis result, and remotely monitoring the site of the power transmission line via an Internet fixed port and the IP (Internet Protocol). The invention also discloses a power transmission line evaluation and diagnosis system. The invention realizes on-site monitoring and fault diagnosis on power transmission lines, and not only meets the requirement of remote information management, but also achieves an on-site equipment monitoring extension function.

Power transmission line evaluation and diagnosis system and power transmission line evaluation and diagnosis method

The invention discloses a wireless network system for achieving synchronous acquisition, a synchronous acquisition device and a method. The wireless network system for achieving synchronous acquisition comprises a master controller and n wireless data collection terminals (n is greater than or equal to 2). The synchronous acquisition device comprises a GPS receiver, a CPLD clock processing module and an analog digital converter. The method for achieving synchronous acquisition includes the steps that the data collection terminals are divided into a main data collection terminal and a plurality of assistant data collection terminals, the fact that all the data collection terminals are in a Ready state is confirmed before acquisition, then the master controller sends a Prestart order to the main data collection terminal, the main data collection terminal replies an OK order after receiving the Prestart order when the next PPS arrives, the master controller sends a Start order to all the data collection terminals after receiving the Prestart order, starting of all the data collection terminals at the same moment is achieved through the process, and synchronous acquisition is achieved ultimately.

Yazhou Yuan

Papers

An approach of distributed joint optimization for cluster-based wireless sensor networks

Optimal Power Management for Failure Mode of MVDC Microgrids in All-Electric Ships

A Mobile Anchor Node Assisted RSSI Localization Scheme in Underwater Wireless Sensor Networks.

Power transmission line evaluation and diagnosis system and power transmission line evaluation and diagnosis method

Wireless network system for achieving synchronous acquisition, synchronous acquisition device and method