A Reliable Wireless Sensor System for Monitoring Mechanical Wear-Out of Parts

Lee, Huang-Chen; Chang, Yu‐Chang; Huang, Yen-Shuo

doi:10.1109/tim.2014.2312498

Cited by 42 publications

(16 citation statements)

References 10 publications

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“…There are other issues that we will then need to evaluate on the field, in particular from the point of view of Electro-Magnetic Interferences (EMI) in a real-life railway environment, which may lead to loss of data. Analogous problems have been observed for wireless data communication in an industrial environment by Lee et al [19]. Therefore we plan to collect data in a typical freight train environment, as discussed later.…”

Section: Introductionmentioning

confidence: 88%

Derailment Detection and Data Collection in Freight Trains, Based on a Wireless Sensor Network

Macucci

Pascoli

Marconcini

et al. 2016

IEEE Trans. Instrum. Meas.

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We report the development of a network of wireless ultra-low-power sensors to be deployed on freight railway cars, with the main purpose of detecting derailment events and alerting the engineer in the cab of the leading locomotive. Since no power bus is available on freight cars, we plan to rely on energy scavenging from vibrations, therefore minimization of the power consumption has been one of our main priorities. We have therefore focused on ultra-low-power hardware and strived to reduce the time intervals during which it is in active mode, achieving an average power consumption below 0.5 mW with an active cycle of about 20 ms every 2 s. We discuss the overall concept that we propose, including the self-initialization protocol and the communication strategy we have developed, and present the results of measurements on a prototype network that we have implemented.

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Section: Introductionmentioning

confidence: 88%

Derailment Detection and Data Collection in Freight Trains, Based on a Wireless Sensor Network

Macucci

Pascoli

Marconcini

et al. 2016

IEEE Trans. Instrum. Meas.

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“…The wireless sensor consists of three main blocks: the physical sensor [13], the Microcontroller (MC) ATmega328p [14], and the radio part which uses ZigBee (based on IEEE802.15.4 properties). The baud rate of the computer and sensors is 19200 bits per second.…”

Section: Methodsmentioning

confidence: 99%

Design of Industrial Wireless Sensor System for Real-Time Data Collection in Steam Turbines

Lilo¹,

Latiff²,

Abu³

et al. 2016

IJEEE

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Wireless Sensors (WS) are utilized in industries, medical, greenhouses, and other applications to sense and monitor parameters required to control and utilize data. There are many challenges to implement WS networks such as collision, end-to-end delay, dead nodes and power consumption to name a few; however, the main challenge that face the implementation of WS are the sensing and transferring the data between the sensor and the system and the time taken. The time taken of a wired sensor to transfer data is undoubtedly slightly shorter than the time taken in WS. This paper intends to design WS that could reduce the data transfer time and compare the amount of transferred data and the time taken by the wired system. The WS design will be validated first by Bland-Altman method and data will be collected using MATLAB and the PLX-DAQ program. The results show that the amount and time taken to transfer data in WS is comparable to the wired system. The validated results suggested by this work are more than 95% in similarity to Bland-Altman. This led us to conclude that WS can be utilized with a multitude of applications in place of wired sensors.  Index Terms-industrial wireless sensor, real time processing, Bland-Altman plot, wireless speed sensor Aminudin Bin Haji Abu was born in Malaysia, in 1972. He received the Ph.D. in. Engineering Automotive Eng. from

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“…The main challenges for using the wireless sensor technique are the packet loss and real time needed to gather the data. Notably, the packet loss in the industrial environment is preoperational to the distance of the nodes, while the real time depends on the length of the data [15,38]. It seems that the scheme is used to manage data collection from WSN to improve the reliability of the system.…”

Section: Time Processing Of the Systemmentioning

confidence: 99%

Design and implementation of wireless system for vibration fault detection using fuzzy logic

Lilo

Mahammad

2020

IJ-AI

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This paper aims at constructing the wireless system for fault detecting and monitoring by computer depending on the wireless and fuzzy logic technique. Wireless applications are utilized to identify, classify, and monitor faults in the real time to protect machines from damage .Two schemes were tested; first scheme fault collected X-Y-Z-axes mode while the second scheme collected Y-axis mode, which is utilized to protect the induction motor (IM) from vibrations fault. The vibration signals were processed in the central computer to reduce noise by signal processing stage, and then the fault was classified and monitored based on Fuzzy Logic (FL). The wireless vibration sensor was designed depending on the wireless techniques and C++ code. A fault collection, noise reduction, vibration fault classification and monitoring were implemented by MATLAB code. In the second scheme the processed real time was reduced to 60%, which is included collection, filtering, and monitoring fault level. Results showed that the system has the ability to early detect the fault if appears on the machine with time processing of 1.721s. This work will reduce the maintenance cost and provide the ability to utilize the system with harsh industrial applications to diagnose the fault in real time processing.

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A Reliable Wireless Sensor System for Monitoring Mechanical Wear-Out of Parts

Cited by 42 publications

References 10 publications

Derailment Detection and Data Collection in Freight Trains, Based on a Wireless Sensor Network

Derailment Detection and Data Collection in Freight Trains, Based on a Wireless Sensor Network

Design of Industrial Wireless Sensor System for Real-Time Data Collection in Steam Turbines

Design and implementation of wireless system for vibration fault detection using fuzzy logic

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