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.
More articles will be published in the near future.

Vibration-Based Health Monitoring of Mechanical Systems

This issue is now closed for submissions.
More articles will be published in the near future.

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 2020
  • - Article ID 1576150
  • - Research Article

The Fault Diagnosis of Rolling Bearing Based on Variational Mode Decomposition and Iterative Random Forest

Xiwen Qin | Jiajing Guo | ... | Yu Guo
  • Special Issue
  • - Volume 2020
  • - Article ID 3824216
  • - Research Article

Identification of Sudden Stiffness Change in the Acceleration Response of a Nonlinear Hysteretic Structure

Sheng-Lan Ma | Shao-Fei Jiang | ... | Si-Yao Wu
  • Special Issue
  • - Volume 2020
  • - Article ID 8973678
  • - Research Article

A Similarity Comparison Method of Homologous Fault Response Fragments under Variable Rotational Speed

Zhiyang He | Weidong Cheng | Weigang Wen
  • Special Issue
  • - Volume 2020
  • - Article ID 8950720
  • - Research Article

Damage Detection for Large-Scale Grid Structure Based on Virtual Axial Strain

Jian-xin Yu | Hui-feng Tan
  • Special Issue
  • - Volume 2020
  • - Article ID 8761278
  • - Research Article

Bearing Health Monitoring Based on the Orthogonal Empirical Mode Decomposition

C. Delprete | E. Brusa | ... | F. Bruzzone
  • Special Issue
  • - Volume 2019
  • - Article ID 2593973
  • - Research Article

A Morphological Filtering Method Based on Particle Swarm Optimization for Railway Vehicle Bearing Fault Diagnosis

Yan Huang | Jianhui Lin | ... | Chenguang Huang
  • Special Issue
  • - Volume 2019
  • - Article ID 1612576
  • - Research Article

Energy Evolution and Acoustic Emission Characteristics of Sandstone Specimens under Unloading Confining Pressure

Tao Qin | Yanwei Duan | ... | Lei Wang
  • Special Issue
  • - Volume 2019
  • - Article ID 6830519
  • - Research Article

Stress Distribution and Fluctuation Cycle on the Rack Face of the Rock Cutting Tool

Xiaofeng Yang | Yongchao Xue | Jiaheng Zhou
  • 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
Shock and Vibration
 Journal metrics
Acceptance rate39%
Submission to final decision93 days
Acceptance to publication39 days
CiteScore1.630
Impact Factor1.628
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