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MECHANICAL SYSTEMS AND SIGNAL PROCESSING

來源: 樹人論文網 瀏覽次數:401次
創刊時間:1987
所屬分區:2區
周期:Bimonthly
ISSN:0888-3270
影響因子:5.005
是否開源:No
年文章量:517
錄用比:較易
學科方向:工程:機械
研究方向:工程技術
通訊地址:ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD, 24-28 OVAL RD, LONDON, ENGLAND, NW1 7DX
官網地址:http://www.journals.elsevier.com/mechanical-systems-and-signal-processing/
投稿地址:http://ees.elsevier.com/ymssp/default.asp
網友分享經驗:約6.7個月

MECHANICAL SYSTEMS AND SIGNAL PROCESSING雜志中文介紹

《機械系統與信號處理》(MSSP)是機械、航天和土木工程領域的一本跨學科期刊,旨在報告傳感、儀表、信號處理、建模和控制動態系統等新技術所帶來的最高質量的科學進步。MSSP論文有望對工程知識做出可證明的原始貢獻,這在現有方法的進步方面應具有重要意義。特別尋求的是包括理論和實驗方面的論文,或者包括與實際應用高度相關的理論材料。MSSP是該領域的領導者,其研究領域包括:1、啟動、感應和控制?振動和噪音控制?行波?智能材料系統?壓電?適應能力?集成系統2、測量與信號處理?理解機械系統的信號處理?全場振動/聲學測量?大數據問題3、非線性?非線性振動問題?非線性正常模式?能量收集4、旋轉機械、機械診斷和SHM?診斷和預測?轉子動力學?轉子裂紋?軸承和齒輪5、不確定性的量化?概率、間隔和模糊分析?可靠性和魯棒性?貝葉斯方法6、振動、模態分析和結構?結構建模與識別?反問題?運行模式分析?環境振動測試提交給MSSP的文件應在附信中明確說明工作的原始科學貢獻。這也應在摘要中簡要說明,并在引言中加以擴展。此外,在導言中,重要的是要清楚地定義用所有條件和假設來處理的具體問題,并將貢獻與歷史文獻(通常按時間順序排列)和藝術現狀聯系起來。應盡可能對最新技術進行總結和分類,但不應僅列出文件。引入新方法或方法的具體原因應在現有技術的基礎上變得明確。應清楚詳細地說明所提出方法相對于已建立技術的任何優勢,包括盡可能進行的比較試驗和實驗證據。MSSP旨在保持高標準的書面英語,作者有責任確保該語言是可理解的。不這樣做可能會導致你的論文被拒。具有機器學習或信號處理內容的論文作者應參閱有關這些主題的MSSP指南:http://media.journals.elsevier.com/content/files/machine-learning-04180327.pdfhttps://www.elsevier.com//uuuu data/promis_misc/signalprocessing.pdf

MECHANICAL SYSTEMS AND SIGNAL PROCESSING雜志英文介紹

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 systems2. Measurement & Signal Processing? Signal processing for the understanding of mechanical systems? Full-field vibration/acoustic measurements? Big data problems3. Nonlinearity? Nonlinear vibration problems? Nonlinear normal modes? Energy harvesting4. Rotating Machines, Machinery Diagnostics & SHM? Diagnostics and prognostics? Rotor dynamics? Cracks in rotors? Bearings and gears5. Uncertainty Quantification? Probabilistic, interval & fuzzy analysis? Reliability and robustness? Bayesian methods6. Vibrations, Modal Analysis & Structures? Structural modelling & identification? Inverse problems? Operational modal analysis? Ambient vibration testingPapers 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.pdfhttps://www.elsevier.com/__data/promis_misc/SignalProcessing.pdf

MECHANICAL SYSTEMS AND SIGNAL PROCESSING影響因子

工程:機械領域相關期刊
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