Shock and Vibration

Vibration-Based Health Monitoring of Mechanical Systems


Publishing date
01 Dec 2019
Status
Closed
Submission deadline
26 Jul 2019

Lead Editor
Guest Editors

1Libera Università di Bolzano, Bolzano, Italy

2Università degli Studi di Firenze, Florence, Italy

3Politecnico di Milano, Milano, Italy

This issue is now closed for submissions.

Vibration-Based Health Monitoring of Mechanical Systems

This issue is now closed for submissions.

Description

Many industrial components, ranging from industrial machines to automotive applications and so forth, are subjected to cumulative damage phenomena often associated with cyclic loads. These are often caused by vibrations, occasional shocks, and acoustic emissions. In a damage tolerant (DT) scenario, each mechanical component needs to retain its residual health, safety, and functionality for as long as possible in order to avoid maintenance interventions that are expensive or simply difficult to perform. However, this requires extensive knowledge of the damage/wear state, and in several applications being able to identify the presence of a defect in time can be challenging. This is a general problem affecting not only pure mechanical components, but also a lot of different mechatronic subsystems that are integrated in the machine in order to obtain desired functionalities. These mechanical and mechatronic systems are currently monitored during both scheduled and unscheduled maintenance, by means of nondestructive inspection technologies (NDIs); however, in recent years the problem of real-time monitoring of mechanically stressed components has become a critical research topic.

As an example, many different sensing technologies can be exploited in a structural health monitoring (SHM) scenario, based on either local or distributed sensor networks that can deal with data coming from heterogeneous sources that are properly conditioned for the correct evaluation of the observed phenomena. In particular, distributed sensor networks are especially suited to monitoring not only large mechanical systems, but also fleets of different components particularly for vehicle or mobile applications. Resources involved in a complete experimental identification of relations between applied loads, environmental conditions, and the corresponding degradation of the tested system are often expensive and time consuming. In particular, this last aspect is becoming of fundamental importance due to market specifications that often constrain the final development of the tested component, system, or more generally the product.

The aim of this special issue is to collect original research and review articles describing theoretical findings as well as new experimental results related to vibration-based health monitoring of mechanical systems. The research should be industry-oriented and intended to improve the state-of-the-art. Requirements and constraints of the specific applications should be considered, and the results of the research must clearly demonstrate enhancements compared to other traditional techniques.

Potential topics include but are not limited to the following:

  • Optimization of the sensing layout (with focus on noise, vibration, and harshness (NVH) measurements)
  • Advanced modeling techniques able to provide relevant information for design, verification, and validation of the monitoring system within the observed component or structure
  • Advanced signal conditioning techniques (with focus on vibration measurements and signal processing) to detect the presence of damage and evaluate its progression
  • Advanced calibration, validation, and verification methods
  • Innovative applications and technologies in the field of shock and vibration analysis

Articles

  • Special Issue
  • - Volume 2019
  • - Article ID 7806015
  • - Research Article

CEEMDAN-Based Permutation Entropy: A Suitable Feature for the Fault Identification of Spiral-Bevel Gears

Lingli Jiang | Hongchuang Tan | ... | Dalian Yang
  • Special Issue
  • - Volume 2019
  • - Article ID 3839191
  • - Research Article

Investigation on Monitoring System for Pantograph and Catenary Based on Condition-Based Recognition of Pantograph

Ning Zhou | Wenjie Yang | ... | Dong Wang
  • Special Issue
  • - Volume 2019
  • - Article ID 7607214
  • - Research Article

Online Monitoring of Flexural Damage Index of a Cable-Stayed Bridge

Byeong Hwa Kim
  • Special Issue
  • - Volume 2019
  • - Article ID 6450719
  • - Research Article

Research on the Feature Selection of Rolling Bearings’ Degradation Features

Yaolong Li | Hongru Li | ... | Weiguo Wang
  • Special Issue
  • - Volume 2019
  • - Article ID 2832089
  • - Research Article

Design and Implementation of a Structural Health Monitoring System for a Large Sea-Crossing Project with Bridges and Tunnel

Yu Yan | Xingquan Mao | ... | Lei Fang
  • Special Issue
  • - Volume 2019
  • - Article ID 1531079
  • - Research Article

Fine-Grained Fault Diagnosis Method of Rolling Bearing Combining Multisynchrosqueezing Transform and Sparse Feature Coding Based on Dictionary Learning

Guodong Sun | Yuan Gao | ... | Ye Hu
  • Special Issue
  • - Volume 2019
  • - Article ID 7082538
  • - Research Article

Frequency-Domain-Based Nonlinear Response Analysis of Stationary Ring Displacement of Noncontact Mechanical Seal

Dian Feng Sun | Jian Jun Sun | ... | Qiu Ping Yu
  • Special Issue
  • - Volume 2019
  • - Article ID 7230194
  • - Research Article

Fault Diagnosis of High-Speed Train Bogie Based on Synchrony Group Convolutions

Yunpu Wu | Weidong Jin | ... | Zhang Sun
  • Special Issue
  • - Volume 2019
  • - Article ID 7320196
  • - Research Article

Mass-Stiffness Combined Perturbation Method for Mode Shape Monitoring of Bridge Structures

Liye Zhang | Ye Xia | ... | Limin Sun
  • Special Issue
  • - Volume 2019
  • - Article ID 7386523
  • - Research Article

Milling Tool Wear State Recognition by Vibration Signal Using a Stacked Generalization Ensemble Model

Yang Hui | Xuesong Mei | ... | Ziwei Ma
Shock and Vibration
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Acceptance rate25%
Submission to final decision95 days
Acceptance to publication17 days
CiteScore2.800
Journal Citation Indicator0.400
Impact Factor1.6
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