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Assessment of Gearbox Fault DetectionUsing Vibration Signal Analysis and Acoustic Emission Technique

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Probability based vehicle fault diagnosis: Bayesian network method

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Online monitoring and fault identification of mean shifts in bivariate processes using decision tree learning techniques

inferredcites →https://doi.org/10.1007/s11804-011-1036-7openalex-snapshot

Fault detection and diagnosis of a gearbox in marine propulsion systems using bispectrum analysis and artificial neural networks

inferredcites →https://doi.org/10.1016/b978-0-7506-6275-8.x5000-0openalex-snapshot

Practical Machinery Vibration Analysis and Predictive Maintenance

inferredcites →https://doi.org/10.1016/j.apacoust.2012.03.008openalex-snapshot

Condition monitoring of worm gears

inferredcites →https://doi.org/10.1016/j.eswa.2007.08.026openalex-snapshot

A comparative study on classification of features by SVM and PSVM extracted using Morlet wavelet for fault diagnosis of spur bevel gear box

inferredcites →https://doi.org/10.1016/j.ndteint.2004.06.008openalex-snapshot

Application of acoustic emission to seeded gear fault detection

inferredcites →https://doi.org/10.1016/j.sigpro.2003.07.019openalex-snapshot

Novelty detection: a review—part 2:

inferredcites →https://doi.org/10.1016/j.ymssp.2006.06.010openalex-snapshot

Decision tree and PCA-based fault diagnosis of rotating machinery

inferredcites →https://doi.org/10.1016/j.ymssp.2009.01.009openalex-snapshot

Gear crack level identification based on weighted K nearest neighbor classification algorithm

inferredcites →https://doi.org/10.1109/3477.969494openalex-snapshot

Evolving fuzzy neural networks for supervised/unsupervised online knowledge-based learning

inferredcites →https://doi.org/10.1109/tmee.2011.6199353openalex-snapshot

A comparison of acoustic emission and vibration on bearing fault detection

inferredcites →https://doi.org/10.1243/0954405041486109openalex-snapshot

Real-time fault detection and isolation in industrial machines using learning vector quantization

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Condition-Based Maintenance Modeling Using Vibration Signature Analysis

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Spur Gear Fault Detection Using Design of Experiments and Support Vector Machine (SVM) Algorithm

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A comparison between psychoacoustic parameters and condition indicators for machinery fault diagnosis using vibration signals

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Anomaly detection in Smart-manufacturing era: A review

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Multi-agent reinforcement learning approach for predictive maintenance of a Smart Building lighting system

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An effective method for bearing faults diagnosis

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Vibro-acoustic Modal Analysis of Motor Predictive Monitoring Sensor Enclosure Fabricated Using Additive Manufacturing

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A summary of vibration analysis techniques for fault detection and diagnosis in bearing

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Regression and Classification-Based Model Predictive Maintenance of Aircrafts Using Machine Learning

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Vibration-induced failures in industrial ventilation systems: A predictive maintenance approach

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Damage detection in spur gears using vibration kurtosis analysis: An experimental data-driven mathematical model and machine learning approach

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Bearing vibration detection and analysis using enhanced fast Fourier transform algorithm

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Reviews of bearing vibration measurement using fast Fourier transform and enhanced fast Fourier transform algorithms

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Fault Diagnosis in Rotating System Based on Vibration Analysis

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Predictive Maintenance of Aircrafts on Large Scale Industrial Units Using Machine Learning Algorithms

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From Corrective to Predictive Maintenance—A Review of Maintenance Approaches for the Power Industry

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Characterization of Fatigue Damage in Hadfield Steel Using Acoustic Emission and Machine Learning-Based Methods

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Demarcation of Gear Defect from Roller Bearing Defect Based on Optimized Wavelet Decomposition Technique

inferred← citeshttps://doi.org/10.48550/arxiv.2010.03207openalex-snapshot

Deep learning models for predictive maintenance: a survey, comparison, challenges and prospect

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Development of Prediction Algorithm Featuring 1-D CNN for Vehicle Wheel Nuts

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"Predictive Maintenance of Machines on Large Scale Industrial Units Using Machine Learning"

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Fault Classification Model Based on Time Domain Feature Extraction of Vibration Data

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