The Characterisation and Simulation of Environmental Shock and Vibration

A special issue of Vibration (ISSN 2571-631X).

Deadline for manuscript submissions: closed (30 April 2019)

Special Issue Editor


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Guest Editor
College of Engineering, Victoria University, Australia
Interests: non-stationary random vibration; non-Gaussian random vibration; random vibration simulation; synthesis of environmental shock and vibration; transport dynamics; pavement topography; pavements vehicles dynamics; road vehicle vibration; multi-axis vibration; vibration damage; transport shock and vibration

Special Issue Information

Dear Colleagues,

Shocks and vibrations are pervasive in many environments where engineering endeavours take place. These include the interaction between water waves and marine vehicles and structures; when ground vehicles travel on uneven surfaces; and when air interacts with structures and vehicles. Shocks and vibrations experienced by space vehicles and their payload emanating from their propulsion systems are also often classified environmental. These shocks and vibrations often have a detrimental effect on the structures and vehicles involved, as well as their cargo, both human and inert. Inert shipments, however, often suffer damage due to excessive levels of shock and vibration generated by the vehicles and require the use of protective packaging materials which, nearly always, end-up as solid waste. In terms of impact, shocks and vibrations generated by road vehicles are made more significant by the fact that road transport’s domination of the distribution industry and is expected to continue to rise for many years to come.

As the vast majority of environmental shocks and vibrations are random and highly (statistically) non-stationary, simply replicating the shocks and vibrations recorded form a single event (however long) will not be sufficiently representative of all possible types of shocks and vibrations that can occur. Producing a suitably representative function (or set of functions) that adequately takes into account randomly-occurring shocks as well as vibration non-stationarities from a finite number of sample records is not easily achieved. This Special Issue addresses the latest approaches and techniques specially developed or adapted for the characterisation and simulation environmental shocks and vibrations.

Prof. Dr. Vincent Rouillard
Guest Editor

Manuscript Submission Information

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Keywords

  • random vibration
  • environmental shock
  • random shock
  • vehicle vibration
  • vehicle dynamics
  • ride quality
  • random vibration simulation
  • vibration synthesis
  • shock-on-random
  • sine-on-random
  • vibration response

Published Papers (1 paper)

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Research

19 pages, 7939 KiB  
Article
Evaluation of Shock Detection Algorithm for Road Vehicle Vibration Analysis
by Julien Lepine and Vincent Rouillard
Vibration 2018, 1(2), 220-238; https://0-doi-org.brum.beds.ac.uk/10.3390/vibration1020016 - 11 Oct 2018
Cited by 2 | Viewed by 4101
Abstract
The ability to characterize shocks which occur during road transport is a vital prerequisite for the design of optimized protective packaging, which can assist in reducing cost and waste related to products and good transport. Many methods have been developed to detect shocks [...] Read more.
The ability to characterize shocks which occur during road transport is a vital prerequisite for the design of optimized protective packaging, which can assist in reducing cost and waste related to products and good transport. Many methods have been developed to detect shocks buried in road vehicle vibration signals, but none has yet considered the nonstationary nature of vehicle vibration and how, individually, they fail to accurately detect shocks. Using machine learning, several shock detection methods can be combined, and the reliability and accuracy of shock detection can also be improved. This paper presents how these methods can be integrated into four different machine learning algorithms (Decision Tree, k-Nearest Neighbors, Bagged Ensemble, and Support Vector Machine). The Pseudo-Energy Ratio/Fall-Out (PERFO) curve, a novel classification assessment tool, is also introduced to calibrate the algorithms and compare their detection performance. In the context of shock detection, the PERFO curve has an advantage over classical assessment tools, such as the Receiver Operating Characteristic (ROC) curve, as it gives more importance to high-amplitude shocks. Full article
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