Mechanical Systems and Signal Processing (MSSP) is an interdisciplinary journal in Mechanical, Aerospace and Civil Engineering with the purpose of reporting scientific advancements of the highest quality arising from new techniques in sensing, instrumentation, signal processing, modelling and control of dynamic systems. MSSP papers are expected to make a demonstrable original contribution to engineering knowledge, which should be significant in terms of advancement over established methods. Especially sought are papers that include both theoretical and experimental aspects, or that include theoretical material of high relevance to practical applications. MSSP is a leader in its field and research areas covered include:

1. Actuation, Sensing and Control

• Vibration & noise control
• Travelling waves
• Smart-material systems
• Piezoelectrics
• Adaptivity
• Integrated systems

2. Measurement & Signal Processing

• Signal processing for the understanding of mechanical systems
• Full-field vibration/acoustic measurements
• Big data problems

3. Nonlinearity

• Nonlinear vibration problems
• Nonlinear normal modes
• Energy harvesting

4. Rotating Machines, Machinery Diagnostics & SHM

• Diagnostics and prognostics
• Rotor dynamics
• Cracks in rotors
• Bearings and gears

5. Uncertainty Quantification

• Probabilistic, interval & fuzzy analysis
• Reliability and robustness
• Bayesian methods

6. Vibrations, Modal Analysis & Structures

• Structural modelling & identification
• Inverse problems
• Operational modal analysis
• Ambient vibration testing

Papers submitted to MSSP should include in the covering letter a clear statement of the original scientific contribution of the work. This should also be stated briefly in the Abstract and expanded upon in the Introduction. Also in the Introduction it is important to clearly define the specific problem treated with all conditions and assumptions made, and to place the contribution in relation to both the historical literature (usually in chronological order) and the state of art. The state of the art should, as much as possible, be summarised and classified but not given as a mere listing of papers. The specific reason(s) for introducing a new method or approach should become clear based on the presented state of the art. Any advantages of proposed methods over established techniques should be explained clearly and in detail, including comparative tests and experimental evidence wherever possible.

MSSP aims to maintain a high standard of written English and it is the authors' responsibility to ensure that the language is intelligible. Failure to do so may result in rejection of your paper.

Authors of papers with Machine-Learning or Signal Processing content should see the MSSP guidelines on these subjects: http://media.journals.elsevier.com/content/files/machine-learning-04180327.pdf
https://www.elsevier.com/__data/promis_misc/SignalProcessing.pdf

Editorial board

Editor-in-Chief

  • J.E. Mottershead
    University of Liverpool, Liverpool, England, UK

Associate Editors

  • J. Antoni
    INSA de Lyon, Villeurbanne, France
  • S. Fassois
    University of Patras, Patras, Greece
  • X. J. Jing
    The Hong Kong Polytechnic University, Hong Kong, China
  • P. Pennacchi
    Politecnico di Milano, Milan, Italy

Founding Editor

  • S.G. Braun
    Technion - Israel Institute of Technology, Haifa, Israel

Editorial Board

  • W. Bartelmus
    Wroclaw University of Technology, Wroclaw, Poland
  • M. Beer
    Leibniz Universität Hannover, Hannover, Germany
  • D. Bernal
    Northeastern University, Boston, Massachusetts, USA
  • M. Boltezar
    University of Ljubljana, Ljubljana, Slovenia
  • P. Borghesani
    University of New South Wales, Sydney, Australia
  • E. Chatzi
    ETH Zürich, Zürich, Switzerland
  • J. W. Choi
    Korea Advanced Institute of Science and Technology (KAIST), Daejeon, The Republic of Korea
  • S. De Rosa
    Università di Napoli Federico II, Italy
  • D.J. Ewins
    Imperial College London, London, UK
  • M.I. Friswell
    Swansea University, Swansea, Wales, UK
  • L. Garibaldi
    Politecnico di Torino, Torino, Italy
  • L. Gaul
    Universität Stuttgart, Stuttgart, Germany
  • Y. Halevi
    Technion - Israel Institute of Technology, Haifa, Israel
  • M. Hanss
    Universität Stuttgart, Stuttgart, Germany
  • G. Kerschen
    Université de Liège, Liège, Belgium
  • P.R.G. Kurka
    Universidade Estadual de Campinas (UNICAMP), Sao Paulo, Brazil
  • A. Le Bot
    Ecole Centrale de Lyon, Ecully, France
  • Y. Lei
    Xi'an Jiaotong University, Xi'an, China
  • M. Link
    Universität Kassel, Kassel, Germany
  • O. Ma
    New Mexico State University, Las Cruces, New Mexico, USA
  • N. M. M. Maia
    Technical University of Lisbon, Lisbon, Portugal
  • D. Moens
    K.U.Leuven Association, Sint-Katelijne-Waver, Belgium
  • A. Morassi
    Università degli Studi di Udine, Udine, Italy
  • S. Nagarajaiah
    Rice University, Houston, Texas, USA
  • J. Noël
    Université de Liège, Liege, Belgium
  • W. M. Ostachowicz
    Polish Academy of Sciences, Gdansk, Poland
  • R.B. Randall
    UNSW Australia, Sydney, New South Wales, Australia
  • D. Remond
    LaMCoS - Equipe DCS, VILLEURBANNE CEDEX, France
  • E. Reynders
    KU Leuven, Leuven, Belgium
  • J. Rodellar
    Technical University of Catalunya, Barcelona, Spain
  • A. Sestieri
    Università di Roma "La Sapienza", Roma, Italy
  • K. Shin
    Andong National University, Andong, Kyungbuk, The Republic of Korea
  • G. Totis
    University of Udine, Udine, Italy
  • P. Walker
    University of Technology Sydney, Sydney, New South Wales, Australia
  • K. Worden
    University of Sheffield, Sheffield, UK
  • D. Yurchenko
    Heriot-Watt University, Edinburgh, UK
  • H. Zhang
    The Ohio State University, Columbus, Ohio, USA