Shock and Vibration

Vibration Analysis as a Diagnosis Tool for Health Monitoring of Industrial Machines


Status
Published

1Universidad de Guanajuato, Guanajuato, Mexico

2University of Oxford, Oxford, UK

3University of Valladolid, Valladolid, Spain

4Autonomous University of Queretaro, San Juan del Río, Mexico


Vibration Analysis as a Diagnosis Tool for Health Monitoring of Industrial Machines

Description

The need for health monitoring in industrial machines using vibration analysis for diagnosis is an ever growing requirement in all types of industries. Vibrations in machinery can take various forms, and most of the time these vibrations are unintended and undesirable. It is known that every moving element in the kinematic chain of a given industrial machine generates a vibration signal that is unique. A brief list of industrial machines that are susceptible to vibrations includes, but is not limited to, industrial robots, computerized numerical control (CNC) machines, production lines, and pick-and-place systems. Monitoring the vibration characteristics of a machine can provide the information of its health condition, and this information can be used to detect problems that might be incipient or developing. The regular use of a machine condition monitoring system allows for observing the problems during their incipient stage or when they are developing. Sometimes a machine can be running into a major failure, even though it appears to be functioning normally. This could lead to a dangerous situation because if this faulty condition is not monitored and detected on time, the problem could lead to the manufacturing of poor quality products, large yield losses, rework costs, and so forth. The vibration signature of a specific machine can then be processed to extract the features related to the fault and give a diagnosis of the machine condition.

Therefore, researchers in the field are invited to submit their experimental and theoretical results to this special issue.

Potential topics include, but are not limited to:

  • Time-series feature analysis of vibration signals
  • Feature analysis of vibration signals in the frequency domain
  • Time-frequency decomposition methodologies applied to vibrations
  • Signal processing techniques in vibration analysis for condition monitoring of industrial machines
  • Development of instruments for online monitoring of vibrations and diagnosis
  • Hardware implementations of real-time monitoring and diagnosis techniques using vibrations
  • Structural, mechanical, and electrical repercussions of vibrations in industrial machines and their kinematic chain
  • Sound and vibrations monitoring
  • Magnetic field harmonic analysis of healthy and faulty cases of electrical machines through computational or analytical methods

Articles

  • Special Issue
  • - Volume 2016
  • - Article ID 1235139
  • - Editorial

Vibration Analysis as a Diagnosis Tool for Health Monitoring of Industrial Machines

Arturo Garcia-Perez | Juan Pablo Amezquita-Sanchez | ... | Konstantinos N. Gyftakis
  • Special Issue
  • - Volume 2016
  • - Article ID 2971749
  • - Research Article

A Two-Stage Compression Method for the Fault Detection of Roller Bearings

Huaqing Wang | Yanliang Ke | ... | Gang Tang
  • Special Issue
  • - Volume 2016
  • - Article ID 3975285
  • - Research Article

Feature Extraction and Selection Scheme for Intelligent Engine Fault Diagnosis Based on 2DNMF, Mutual Information, and NSGA-II

Peng-yuan Liu | Bing Li | ... | Feng Wang
  • Special Issue
  • - Volume 2016
  • - Article ID 4135102
  • - Research Article

A Fault Feature Extraction Method for Rolling Bearing Based on Pulse Adaptive Time-Frequency Transform

Jinbao Yao | Baoping Tang | Jie Zhao
  • Special Issue
  • - Volume 2016
  • - Article ID 6954012
  • - Research Article

Vibration Suppression for Improving the Estimation of Kinematic Parameters on Industrial Robots

David Alejandro Elvira-Ortiz | Rene de Jesus Romero-Troncoso | ... | Roque Alfredo Osornio-Rios
  • Special Issue
  • - Volume 2016
  • - Article ID 5467643
  • - Research Article

Multiple-Fault Detection Methodology Based on Vibration and Current Analysis Applied to Bearings in Induction Motors and Gearboxes on the Kinematic Chain

Juan Jose Saucedo-Dorantes | Miguel Delgado-Prieto | ... | Rene de Jesus Romero-Troncoso
  • Special Issue
  • - Volume 2016
  • - Article ID 4836516
  • - Research Article

Experimental Investigation into Vibration Characteristics for Damage Minimization in a Lapping Process

J. Suwatthikul | S. Sornmuang | ... | C. Supavasuthi
  • Special Issue
  • - Volume 2016
  • - Article ID 4805383
  • - Research Article

Bearing Fault Diagnosis Using a Novel Classifier Ensemble Based on Lifting Wavelet Packet Transforms and Sample Entropy

Lei Zhang | Long Zhang | ... | Guoliang Xiong
  • Special Issue
  • - Volume 2016
  • - Article ID 8538165
  • - Research Article

A New Feature Extraction Technique Based on 1D Local Binary Pattern for Gear Fault Detection

Zrar Kh. Abdul | Abdulbasit Al-Talabani | Ayub O. Abdulrahman
  • Special Issue
  • - Volume 2016
  • - Article ID 9278581
  • - Research Article

Fault Diagnosis of Rotating Machinery Based on Adaptive Stochastic Resonance and AMD-EEMD

Peiming Shi | Cuijiao Su | Dongying Han
Shock and Vibration
 Journal metrics
Acceptance rate36%
Submission to final decision92 days
Acceptance to publication38 days
CiteScore2.400
Impact Factor1.298
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