A hardware-software WSN platform for machine and structural monitoring
01 Jun 2017-pp 1-6
TL;DR: A novel hardware-software platform designed to monitor machinery in remote deployments and expedite collection of experimental data, which could also be used for structural monitoring, and can facilitate the execution of sensing experiments in rotating machinery and similar equipment is presented.
Abstract: Traditional wired vibration and acoustic sensors used for machine and structural monitoring are currently being replaced by low-cost MEMS-based wireless sensor networks (WSN). However, existing platforms are lacking in computing capabilities and integration, as well as the necessary software features to manage wireless sensing experiments. In this paper, we present a novel hardware-software platform designed to monitor machinery in remote deployments and expedite collection of experimental data, which could also be used for structural monitoring. The hardware module is composed of a single PCB with an IEEE 802.15.4-compatible microcontroller, waterproof Micro-USB connector, battery, battery charger/monitor, humidity/temperature sensor, IMU, and a MEMS microphone. The software developed allows for wireless experiment control and data collection through a gateway node connected to a laptop. Additionally, the user interface supports the placement of the nodes in a 3D view of the environment, as well as visualisation of the collected data. The platform was tested in the laboratory in two different motor setups by measuring vibration and sound in normal operation, showing that the system can facilitate the execution of sensing experiments in rotating machinery and similar equipment.
Citations
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TL;DR: A novel on-chip order tracking method using WSNs based on hardware cross-layer design is proposed, in which the vibration data can be sampled with uniform angle on chip.
Abstract: Order-tracking technique is widely accepted to account for speed variation. Meanwhile, Wireless Sensor Networks (WSNs) is highly focused since the nodes can collect vibration data in special applications. Thus, it’s meaningful to realize order-tracking using WSNs. In this paper, a novel on-chip order tracking method using WSNs based on hardware cross-layer design is proposed, in which the vibration data can be sampled with uniform angle on chip. First, a high performance WSNs system based on dual-core architecture is developed to monitor shaft angle and machine vibration, and hardware cross-layer design is researched to send key-phase pulse with low delay jitter. Second, a data sampling control method is established to realize on-chip uniform angle sampling. Finally, the performance of the proposed on-chip order tracking method is verified by some experiments.
5 citations
TL;DR: This is the first time that this full range of physical link quality indicators has been measured in this type of application environment, and it is found that in all three scenarios the network performed with over 90% PDR average, indicating that although a WSN could operate in these scenarios under different conditions, a pre-deployment practical study is essential for each new scenario.
Abstract: Wireless sensor networks (WSN) are finding increasing use in all-metal marine environments such as ships, oil and gas rigs, freight container terminals, and marine energy platforms. However, wireless propagation in an all-metal environment with ducting and sealed doors between compartments is difficult to model, and the operating machinery further complicates wireless network planning. This makes it necessary to characterize the performance of the physical wireless links in the actual operating environments. However, little has been reported in the literature on methodologies for measuring the full range of physical link quality indicators. In this paper, we present a methodology for doing this that we have verified by the deployment of a 2.4 GHz network of 18 nodes in three different all-metal scenarios: a cluster of freight containers, a full-sized shore-based working ship’s engine room training facility, and an operational ship’s engine room. The output variables included the key link quality indicators of packet delivery ratio (PDR), RSSI, and LQI for every possible link, as well as the performance of every node. We believe that this is the first time that this full range of physical link quality indicators has been measured in this type of application environment. We found that in all three scenarios the network performed with over 90% PDR average. However, as the scenarios become more complex, the communications become more unpredictable, yielding a wider transition zone, indicating that although a WSN could operate in these scenarios under different conditions, a pre-deployment practical study is essential for each new scenario.
5 citations
Cites methods from "A hardware-software WSN platform fo..."
...We made the decision to perform burst experiments based on the target application, considering that machine and structural monitoring often require data bursts from accelerometers and other high sample rate sensors [23]....
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01 Jun 2018
TL;DR: The main objective of the study is to observe the impact of several factors (altitude, distance, obstacles, interference) over the collection process.
Abstract: In recent years, data collection has been a subject of interest in the field of Wireless Sensor Networks. Most papers tackle with concepts at a theoretical level by making reviews or limited implementations in simulated or controlled environments. Few of these go further on and study implementations in real life environments. For this reason, the current paper has the objective to study a data gathering implementation that uses wireless sensors and unmanned aerial vehicles. The main objective of the study is to observe the impact of several factors (altitude, distance, obstacles, interference) over the collection process.
4 citations
Cites background or methods from "A hardware-software WSN platform fo..."
...Experiments in [13] have shown a reliable data collection, but with long download times due to which the authors propose exploring the use of compression algorithms or basic fault detection mechanisms on the node....
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...In [13] is proposed a hardware-software system for monitoring marine energy platforms and their machinery....
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...Moreover, authors of [13] also used Abstract—In recent years, data collection has been a subject of interest in the field o f W ireless S ensor N etworks....
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30 Mar 2021
TL;DR: A literature review on the use of vibration analysis in flow rate metrological systems in order to identify research opportunities for indirect measurement of this magnitude is presented in this paper, where a line of work is found based on soft flow rate sensors that use the analysis of pipeline vibrations integrated into computational intelligence routines, which allows inference of the flow rate value.
Abstract: espanolEl caudal es una variable necesaria en procesos industriales, por lo que existe gran variedad de instrumentos para su medicion. Sin embargo, las alternativas mejor aceptadas de registro presentan inconvenientes por lo invasivo o intrusivo que requiere ser el medidor para su confiabilidad. El reto cientifico y tecnologico consiste en lograr la medicion explotando todas las posibilidades fenomenologicas mediante un mecanismo no intrusivo, de facil instalacion, portatil y de bajo costo. Este articulo presenta una revision del estado del arte sobre el uso del analisis de vibraciones en sistemas metrologicos de caudal a fin de identificar oportunidades de investigacion para su medicion indirecta. La metodologia para esta revision, se compuso detres etapas: revision, analisis y discusion, sobre un conjunto amplio de documentos publicados entre 2004y 2020. La informacion analizada muestra la relacion fenomenologica entre las caracteristicas de la vibracion en una tuberia y la magnitud del caudal circulante en ella, lo cual puede ser usadocon propositos metrologicos. Sin embargo, variosestudiosreportan limitaciones que sugieren necesidades de mejoramiento, relacionadas con rutinas deadquisicion, pruebas decalibracion y analisis delaincertidumbre, asi como exploracionesde tiempo-frecuencia.Se encontro una linea de trabajo promisoria basada en soft sensores para caudal que, con el analisis de vibraciones de la tuberia integradoa rutinas de inteligencia computacional, permite inferir el valor del caudal. Los hallazgosimpulsan a seguir con nuevas apuestas tecnico-cientificas. EnglishFlow rate is a necessary variable in industrial processes and, therefore, there is a wide variety of instruments designed to measure it. However, the most accepted measuring devices have the problem of being invasive or intrusive. The scientific and technological challenge is to achieve measurement by exploiting all the phenomenological possibilities using a non-intrusive, easy-to-install, portable and low-cost mechanism. This paper presents a literature review on the use of vibration analysis in flow rate metrological systems in order to identify research opportunities for the indirect measurement of this magnitude.The methodology forthis review was made up by three stages: revision, analysis and discussion, performed over a wide set of documents published between 2004and 2020. The analyzed information shows the phenomenological relationship between the featuresof the vibrations in a pipe andthe flow rate magnitude circulating through it,which can be used for metrological purposes. However,severalstudies report limitationsthat suggest improvement needs, related toacquisitionroutines, calibration testsand uncertainty analysis, as well as time-frequency explorations. A promising line of work was found based on soft flow rate sensors that use the analysis of pipeline vibrations integrated into computational intelligence routines, which allows inference of the flow rate value. The findings promote to continue with new technical and scientific challenges.
2 citations
Cites methods from "A hardware-software WSN platform fo..."
...Acoustic sensors have been used in machine and structural monitoring [30], leak detection systems [31], the detection of solid particles in water-conveying pipe flow [32] and biomedical applications [33], among others....
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23 Apr 2019
TL;DR: This thesis investigates the problem of security provisioning in WSNs based critical monitoring infrastructures and proposes a trust based hierarchical model for malicious nodes detection specially for Black-hole attacks, and presents the performance metrics for four different IDSs schemes.
Abstract: In most of critical infrastructures, Wireless Sensor Networks (WSNs) are deployed due to their low-cost, flexibility and efficiency as well as their wide usage in several infrastructures. Regardless of these advantages, WSNs introduce various security vulnerabilities such as different types of attacks and intruders due to the open nature of sensor nodes and unreliable wireless links. Therefore, the implementation of an efficient Intrusion Detection System (IDS) that achieves an acceptable security level is a stimulating issue that gained vital importance. In this thesis, we investigate the problem of security provisioning in WSNs based critical monitoring infrastructures. We propose a trust based hierarchical model for malicious nodes detection specially for Black-hole attacks. We also present various Machine Learning (ML)-driven IDSs schemes for wirelessly connected sensors that track critical infrastructures. In this thesis, we present an in-depth analysis of the use of machine learning, deep learning, adaptive machine learning, and reinforcement learning solutions to recognize intrusive behaviours in the monitored network. We evaluate the proposed schemes by using KDD’99 as real attacks data-sets in our simulations. To this end, we present the performance metrics for four different IDSs schemes namely the Clustered Hierarchical Hybrid IDS (CHH-IDS), Adaptively Supervised and Clustered Hybrid IDS (ASCH-IDS), Restricted Boltzmann Machine-based Clustered IDS (RBC-IDS) and Q-learning based IDS (QL-IDS) to detect malicious behaviours in a sensor network. Through simulations, we analyzed all presented schemes in terms of Accuracy Rates (ARs), Detection Rates (DRs), False Negative Rates (FNRs), Precision-recall ratios, F 1 scores and, the area under curves (ROC curves) which are the key performance parameters for all IDSs. To this end, we show that QL-IDS performs with ≈ 100% detection and accuracy rates.
References
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24 Apr 2005
TL;DR: Telos is the latest in a line of motes developed by UC Berkeley to enable wireless sensor network (WSN) research, a new mote design built from scratch based on experiences with previous mote generations, with three major goals to enable experimentation: minimal power consumption, easy to use, and increased software and hardware robustness.
Abstract: We present Telos, an ultra low power wireless sensor module ("mote") for research and experimentation. Telos is the latest in a line of motes developed by UC Berkeley to enable wireless sensor network (WSN) research. It is a new mote design built from scratch based on experiences with previous mote generations. Telos' new design consists of three major goals to enable experimentation: minimal power consumption, easy to use, and increased software and hardware robustness. We discuss how hardware components are selected and integrated in order to achieve these goals. Using a Texas Instruments MSP430 microcontroller, Chipcon IEEE 802.15.4-compliant radio, and USB, Telos' power profile is almost one-tenth the consumption of previous mote platforms while providing greater performance and throughput. It eliminates programming and support boards, while enabling experimentation with WSNs in both lab, testbed, and deployment settings.
2,115 citations
"A hardware-software WSN platform fo..." refers methods in this paper
...3) Temperature and humidity: The sensor selected for humidity and temperature monitoring is the SHT21, as the next generation of the SHT11 found in older WSN platforms such as the TelosB....
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...Similarly, Severino et al. [10] showed a platform for structural health monitoring using a TelosB [11] mote connected to an acquisition board and accelerometer....
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...While these experiments demonstrate the feasibility of using wireless sensors and MEMS to monitor these environments, most of the platforms used present a series of drawbacks: they are either This material is based upon works supported by the Science Foundation Ireland under Grant No. 12/RC/2302, the Marine Renewable Energy Ireland (MaREI) Centre research programme [1]. based on old platforms developed for networking research with limited processing capabilities and memory (e.g. TelosB and MICAz), which limits also the sampling rate of the sensors, or on more powerful platforms with higher power consumption and that do not support current standard WSN operating systems such as Contiki-OS [12]....
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...[10] showed a platform for structural health monitoring using a TelosB [11] mote connected to an acquisition board and accelerometer....
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TL;DR: This paper presents a preliminary review of Evidence Theory and explains how the multi-sensor engine diagnosis problem can be framed in the context of this theory, in terms of faults frame of discernment, mass functions and the rule for combining pieces of evidence.
Abstract: Engine diagnostics is a typical multi-sensor fusion problem. It involves the use of multi-sensor information such as vibration, sound, pressure and temperature, to detect and identify engine faults. From the viewpoint of evidence theory, information obtained from each sensor can be considered as a piece of evidence, and as such, multi-sensor based engine diagnosis can be viewed as a problem of evidence fusion. In this paper we investigate the use of Dempster-Shafer evidence theory as a tool for modeling and fusing multi-sensory pieces of evidence pertinent to engine quality. We present a preliminary review of Evidence Theory and explain how the multi-sensor engine diagnosis problem can be framed in the context of this theory, in terms of faults frame of discernment, mass functions and the rule for combining pieces of evidence. We introduce two new methods for enhancing the effectiveness of mass functions in modeling and combining pieces of evidence. Furthermore, we propose a rule for making rational decisions with respect to engine quality, and present a criterion to evaluate the performance of the proposed information fusion system. Finally, we report a case study to demonstrate the efficacy of this system in dealing with imprecise information cues and conflicts that may arise among the sensors.
431 citations
"A hardware-software WSN platform fo..." refers background in this paper
...Moreover, accelerometer and acoustic sensors are rarely used together in these studies, even though the literature shows methods that can combine both sources of data to improve fault detection [4], [13], [14]....
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TL;DR: In this paper, the authors examined whether acoustic signals can be used effectively to detect the various local faults in gearboxes using the smoothed pseudo-Wigner-Ville distribution.
Abstract: Vibration analysis is widely used in machinery diagnostics and the Wigner–Ville distribution has also been implemented in many applications in the condition monitoring of machinery. In contrast to previous applications, this paper examines whether acoustic signal can be used effectively to detect the various local faults in gearboxes using the smoothed pseudo-Wigner–Ville distribution. Three types of progressing local faults, broken tooth, gear crack and localised wear, were simulated. The results from acoustic signals were compared with vibration signals. The results suggest that acoustic signals are very affective for the early detection of faults and may provide a powerful tool to indicate the various types of progressing faults in gearboxes.
312 citations
"A hardware-software WSN platform fo..." refers background in this paper
...Moreover, accelerometer and acoustic sensors are rarely used together in these studies, even though the literature shows methods that can combine both sources of data to improve fault detection [4], [13], [14]....
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TL;DR: This module is one of two laboratory modules focusing on machine condition monitoring applications that were developed for this course, and constitutes an instructional module on bearing fault detection that can be used as a stand-alone tutorial or incorporated into a course.
Abstract: Faculty in the College of Engineering at the University of Alabama developed a multidisciplinary course in applied spectral analysis that was first offered in 1996. The course is aimed at juniors majoring in electrical, mechanical, industrial, or aerospace engineering. No background in signal processing or Fourier analysis is assumed; the requisite fundamentals are covered early in the course and followed by a series of laboratories in which the fundamental concepts are applied. In this paper, a laboratory module on fault detection in rolling element bearings is presented. This module is one of two laboratory modules focusing on machine condition monitoring applications that were developed for this course. Background on the basic operational characteristics of rolling element bearings is presented, and formulas given for the calculation of the characteristic fault frequencies. The shortcomings of conventional vibration spectral analysis for the detection of bearing faults is examined in the context of a synthetic vibration signal that students generate in MATLAB. This signal shares several key features of vibration signatures measured on bearing housings. Envelope analysis and the connection between bearing fault signatures and amplitude modulation/demodulation is explained. Finally, a graphically driven software utility (a set of MATLAB m-files) is introduced. This software allows students to explore envelope analysis using measured data or the synthetic signal that they generated. The software utility and the material presented in this paper constitute an instructional module on bearing fault detection that can be used as a stand-alone tutorial or incorporated into a course.
261 citations
"A hardware-software WSN platform fo..." refers background or methods in this paper
...Vibration and acoustic sensors have been widely used for prognostics and fault diagnosis of bearings [2], motors [3], and different types of machinery [4], [5]....
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...2) IMU: As shown in the literature [2], [3], [9], a bandwidth of 100-200 Hz is sufficient to detect faults using vibration data in motors, bearings, and similar machinery,...
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01 May 2014
TL;DR: A review of recent advances in automatic vibration- and audio-based fault diagnosis in machinery using condition monitoring strategies is provided to provide a review of the most valuable techniques and results.
Abstract: The objective of this paper is to provide a review of recent advances in automatic vibration- and audio-based fault diagnosis in machinery using condition monitoring strategies. It presents the most valuable techniques and results in this field and highlights the most profitable directions of research to present. Automatic fault diagnosis systems provide greater security in surveillance of strategic infrastructures, such as electrical substations and industrial scenarios, reduce downtime of machines, decrease maintenance costs, and avoid accidents which may have devastating consequences. Automatic fault diagnosis systems include signal acquisition, signal processing, decision support, and fault diagnosis. The paper includes a comprehensive bibliography of more than 100 selected references which can be used by researchers working in this field.
223 citations
"A hardware-software WSN platform fo..." refers methods in this paper
...Vibration and acoustic sensors have been widely used for prognostics and fault diagnosis of bearings [2], motors [3], and different types of machinery [4], [5]....
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