Diagnostics using self-sufficient wireless sensor network for a condition-based maintenance strategy strategy for tram bearing diagnostics

Wolf, Maik; Hofbauer, Julian; Rudolph, Mathias

doi:10.1109/ssd.2016.7473698

Cited by 2 publications

(3 citation statements)

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“…Whereby after a running performance of 500.000 km or at the latest after 8 years the execution of a general inspection is legally prescribed [9]. For a detailed description of the measurement procedure, see [4,5,10].…”

Section: Measurementsmentioning

confidence: 99%

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Concept for an event-triggered wireless sensor network for vibration-based diagnosis in trams

Wolf¹,

Rudolph²,

Kanoun³

2019

Vib. proced.

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Trams are the most durable and resource efficient forms of public transportation. However, because of the varying wear in dependence on their operation mode and load levels, there is a need for condition monitoring and early maintenance. Vibration sensors provide interesting possibilities to monitor the relevant tram drive components. In this contribution we investigate their use under real conditions. On the basis of cable bound vibration measurements, the influence of the crossed track section, the tram speed and the tram condition is shown. Based on the investigation results, a concept is proposed in which a meshed and wireless sensor network, event-triggered, can acquire vibration measurement data, which are suitable for the diagnosis of tram drive components. The proposed concept has the potential to operate the sensor nodes in an energy efficient way through decentralized data evaluation taking place on the sensor node.

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Section: Measurementsmentioning

confidence: 99%

“…To address the reliability and usability, the measured values have to be recorded in a wireless manner by a sensor network. [4][5][6][7] show the essential aspects and advantages of autonomous and energy efficient sensor networks in trams compared to conventional (cable bound) measurements.…”

Section: Introductionmentioning

confidence: 99%

Concept for an event-triggered wireless sensor network for vibration-based diagnosis in trams

Wolf¹,

Rudolph²,

Kanoun³

2019

Vib. proced.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Experiments show that this method can reduce data transmission by 95% compared with direct transmission of raw data. Besides machine condition monitoring and fault diagnosis, WSNs also plays an irreplaceable role in the fields of structure monitoring [17][18][19], home automation [20], mass transportation [21][22] and security prevention [23].…”

Section: Introductionmentioning

confidence: 99%

Fault Diagnosis of Rolling Bearing Using Wireless Sensor Networks and Convolutional Neural Network

Huang

2020

Int. J. Onl. Eng.

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Rolling bearings are widely used in modern production equipment. Effective bearing fault diagnosis method will improve the reliability of the machinery and increase its operating efficiency. In this paper, a novel fault diagnosis method based on WSN and CNN has been proposed to fully utilize the strong fault classification capability of CNN and the inherent merits of WSNs, such as relatively low cost, convenience of installation, and ease of relocation. The feasibility and effectiveness of proposed system are evaluated using the vibration data sets of seven motor operating conditions released by the Case Western Reserve University Bearing Data Center. The experimental results show the fault diagnosis accuracy of the proposed approach can reach 97.6%.

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Diagnostics using self-sufficient wireless sensor network for a condition-based maintenance strategy strategy for tram bearing diagnostics

Cited by 2 publications

References 0 publications

Concept for an event-triggered wireless sensor network for vibration-based diagnosis in trams

Concept for an event-triggered wireless sensor network for vibration-based diagnosis in trams

Fault Diagnosis of Rolling Bearing Using Wireless Sensor Networks and Convolutional Neural Network

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