Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Journal Bearings01:23

Journal Bearings

881
Journal bearings are mechanical components that support and provide lateral stability to rotating shafts and axles. They are crucial in reducing friction, wear, and vibration in machinery such as engines, turbines, and pumps. The principle behind journal bearings is forming a thin lubricant film between the bearing surface and the rotating shaft, which minimizes direct contact and reduces frictional forces.
To better understand the concept of journal bearings, consider a rope winch with dry or...
881
Transmission Shafts: Problem Solving01:09

Transmission Shafts: Problem Solving

356
Designing a solid shaft that transmits power from a motor to a machine tool involves a series of calculations to ensure the shaft can withstand the stresses applied by bending moments and torques. First, calculate the torque exerted on the gear, considering the power transmitted by the shaft and its rotational speed. Following this, compute the tangential forces acting on the gears, which directly relate to the torque and the gear radius.
Next, use bending moment diagrams for the shaft to...
356
Design of Transmission Shafts01:16

Design of Transmission Shafts

556
The design of a transmission shaft is governed by two primary specifications: the power it transmits and its rotational speed. These parameters guide the selection of the shaft's material and cross-sectional dimensions, ensuring that the material's maximum shearing stress remains within the elastic limit while transmitting the desired power at the given speed. The system's power is intrinsically linked to the applied torque. The torque applied to the shaft can be calculated by reconfiguring the...
556
Multimachine Stability01:25

Multimachine Stability

264
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
264
Design of Transmission Shafts - Stress Analysis01:15

Design of Transmission Shafts - Stress Analysis

561
Designing a transmission shaft requires a thorough understanding of the stresses induced by bending moments and torques, especially in systems where power is transferred through gears. These forces create force-couple systems at the centers of the shaft's cross-sections, leading to both transverse and torsional loading. Although shearing stresses from transverse loads are typically smaller than those from torques and are often overlooked, the significant normal stresses from these loads...
561
Simplified Synchronous Machine Model01:30

Simplified Synchronous Machine Model

396
The Synchronous Machine Model is a fundamental tool in analyzing and ensuring the transient stability of power systems. This model simplifies the representation of a synchronous machine under balanced three-phase positive-sequence conditions, assuming constant excitation and ignoring losses and saturation. The model is pivotal for understanding the behavior of synchronous generators connected to a power grid, particularly during transient events.
In this model, each generator is connected to a...
396

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Event-Triggered Multiple Leaders Formation Tracking for Networked Swarm System With Resilience to Noncooperative Nodes.

IEEE transactions on cybernetics·2025
Same author

A framework for resilience assessment of transportation networks exposed to geohazard threats.

Risk analysis : an official publication of the Society for Risk Analysis·2025
Same author

A modelling framework to analyze climate change effects on radionuclide aquifer contamination.

Journal of contaminant hydrology·2024
Same author

Multi-Fractal Weibull Adaptive Model for the Remaining Useful Life Prediction of Electric Vehicle Lithium Batteries.

Entropy (Basel, Switzerland)·2023
Same author

An Adaptive Sampling Framework for Life Cycle Degradation Monitoring.

Sensors (Basel, Switzerland)·2023
Same author

An optimization model for planning testing and control strategies to limit the spread of a pandemic - The case of COVID-19.

European journal of operational research·2021

Related Experiment Video

Updated: Nov 5, 2025

Parametric Optimization Design Method for Friction Plates of Hydro-Viscous Clutches
10:58

Parametric Optimization Design Method for Friction Plates of Hydro-Viscous Clutches

Published on: July 22, 2025

366

Metabolism and difference iterative forecasting model based on long-range dependent and grey for gearbox reliability.

He Liu1, Wanqing Song1, Enrico Zio2

  • 1School of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai, China.

ISA Transactions
|May 17, 2021
PubMed
Summary

This study introduces a hybrid iterative forecasting model for gearbox reliability. The novel approach enhances gearbox fault detection and improves long-term reliability predictions.

Keywords:
Difference iterative formFractional Lévy stable motionGear degradationGrey modelMetabolism method

More Related Videos

A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump
09:04

A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump

Published on: June 1, 2022

3.3K
A Rapid Method for Modeling a Variable Cycle Engine
04:58

A Rapid Method for Modeling a Variable Cycle Engine

Published on: August 13, 2019

7.8K

Related Experiment Videos

Last Updated: Nov 5, 2025

Parametric Optimization Design Method for Friction Plates of Hydro-Viscous Clutches
10:58

Parametric Optimization Design Method for Friction Plates of Hydro-Viscous Clutches

Published on: July 22, 2025

366
A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump
09:04

A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump

Published on: June 1, 2022

3.3K
A Rapid Method for Modeling a Variable Cycle Engine
04:58

A Rapid Method for Modeling a Variable Cycle Engine

Published on: August 13, 2019

7.8K

Area of Science:

  • Mechanical Engineering
  • Reliability Engineering
  • Data Science

Background:

  • Gearbox reliability prediction is a significant challenge in engineering.
  • Accurate forecasting is crucial for maintenance and operational efficiency.
  • Existing methods struggle with early detection of subtle gearbox faults.

Purpose of the Study:

  • To propose a novel hybrid difference iterative forecasting model for gearbox reliability.
  • To enhance the detection of gearbox degradation through advanced feature extraction.
  • To improve the accuracy and scope of gearbox reliability predictions.

Main Methods:

  • Feature extraction to identify gearbox degradation patterns.
  • Least square theory to decompose degradation into deterministic and stochastic components.
  • Fractional Lévy stable motion (fLsm) for stochastic terms with Long-Range Dependence (LRD) and non-Gaussian properties.
  • Grey Model (GM) for deterministic terms.
  • Metabolism method for updating degradation sequences and long-term trend forecasting.

Main Results:

  • The hybrid model effectively reveals gearbox degradation, even with weak faults.
  • Separation of degradation into deterministic and stochastic terms allows for targeted modeling.
  • The fractional Lévy stable motion component accurately forecasts the stochastic term.
  • The Grey Model effectively simulates the deterministic component.
  • The metabolism method enables dynamic updates and long-term trend analysis.

Conclusions:

  • The proposed hybrid forecasting model demonstrates superior performance and generality for gearbox reliability prediction.
  • The integration of fLsm, GM, and metabolism method offers a robust solution for complex reliability challenges.
  • The methodology provides a significant advancement in predicting gearbox operational lifespan and potential failures.