All Stories

  1. Phase space reconstruction features for LSTM-based fault classification in gearboxes and roller bearings
  2. A latent-dynamics self-supervised framework for limited-label fault diagnosis in cyclostationary vibration measurements
  3. Advanced Analytics for Reliability and Resilience of Energy System
  4. One-class transformer-based feature disentanglement with clustering-driven semisupervised learning for the fault diagnosis of reciprocating machinery
  5. One-Class Learning-Based Contrastive Reconstruction Framework for the Anomaly Detection of Reciprocating Machinery
  6. Selection of Vibration Signal Features in the Frequency Domain to Determine the Level of Failure Severity in Spur Gearboxes
  7. Electric torque for fault severity diagnosis in gearbox-type load: ML approaches based on Poincaré plot and statistical features
  8. Four-Phase University-Municipal Technology Transfer Framework: Validated Quadruple Helix Implementation in Developing Countries
  9. Attention-Based Multisignal Representation of High-Resolution Time Series: A Fault Detection Method for Industrial Machinery
  10. Condition Indicator Fusion and Machine Learning-Based Severity Assessment of Tooth Breakage Failures in Spur Gearboxes
  11. Industry 4.0 Technologies for an Observer-Based Gearbox Fault Detection Architecture
  12. Poincaré Features for Estimation of Remaining Useful Life in Roller Bearings
  13. Methodology for Feature Selection of Time Domain Vibration Signals for Assessing the Failure Severity Levels in Gearboxes
  14. A review on relevant failure modes in electric machines
  15. Detection and adaptation to concept evolution in data streams: an integral framework
  16. Gear fault severity classification using acoustic emission peaks and Poincaré plots
  17. Transformer framework for the fault detection of a reciprocating compressor
  18. Fault Diagnosis Generalization Improvement Through Contrastive Learning for a Multistage Centrifugal Pump
  19. Classification of the Severity Level of Breakage Failure in Spur Gearboxes Through Frequency Domain Vibration Signal Analysis
  20. Attainment of World Health Organization physical activity recommendations by Ecuadorian children: Analysis of social and anthropometrics factors in two distinct populations
  21. Comparative Analysis of Autoencoder and Contrastive One-Class Anomaly Detection in Reciprocating Compressors
  22. A simple yet realistic integrated dynamical modeling of an induction motor and one-stage spur gearbox system with broken tooth
  23. Evaluation of Hand-Crafted Feature Extraction for Fault Diagnosis in Rotating Machinery: A Survey
  24. Selection of the level of vibration signal decomposition and mother wavelets to determine the level of failure severity in spur gearboxes
  25. Gearbox faults severity classification using Poincaré plots of acoustic emission signals
  26. Improved Mel Frequency Cepstral Coefficients for Compressors and Pumps Fault Diagnosis with Deep Learning Models
  27. Modelos de variables latentes en patrones de alimentación y actividad física en niños/adolescentes: una revisión sistemática
  28. Unhealthy food consumption among Ecuadorian children: A cross-sectional study in the context of the school food regulation
  29. Scale-Fractal Detrended Fluctuation Analysis for Fault Diagnosis of a Centrifugal Pump and a Reciprocating Compressor
  30. Data-Driven Fault Detection in Reciprocating Compressors: A Method Based on PCA and GLRT
  31. Digital Model of a Wind Turbine Oriented to Broken Tooth Analysis
  32. Fault Classification in Reciprocating Compressors: A Comparison of Machine Learning and Deep Learning Approaches
  33. Improved Fault Diagnosis Model Based on Bootstrap Your Own Latent Algorithm for a Multistage Centrifugal Pump
  34. Observer-Based Fault Detection System for a Class of Industrial Process Implemented with MQTT Protocol
  35. Drive-train Third Stage-based Simplified Dynamic Modeling of a Wind Turbine Oriented to Vibration Analysis
  36. Adversarial Fault Detector Guided by One-Class Learning for a Multistage Centrifugal Pump
  37. Audit Model for the Management of Physical Assets Maintenance. Case Study: Mechanical Laboratories at Ecuadorian University
  38. Evaluation of Video Signals for Coupling Fault Detection Using the Mirror Technique
  39. A hybrid prototype selection-based deep learning approach for anomaly detection in industrial machines
  40. Fault Classification in a Reciprocating Compressor and a Centrifugal Pump Using Non-Linear Entropy Features
  41. AutoML for Feature Selection and Model Tuning Applied to Fault Severity Diagnosis in Spur Gearboxes
  42. Deep Ensemble-Based Classifier for Transfer Learning in Rotating Machinery Fault Diagnosis
  43. Methods for Transforming Observable to Latent Variables of Adolescent Eating Behavior Using Mathematical Tools and Social Behavior Criteria
  44. One-Shot Fault Diagnosis of Three-Dimensional Printers Through Improved Feature Space Learning
  45. Using the Kullback-Leibler Divergence and Kolmogorov-Smirnov Test to Select Input Sizes to the Fault Diagnosis Problem Based on a CNN Model
  46. From fault detection to one-class severity discrimination of 3D printers with one-class support vector machine
  47. Fusing convolutional generative adversarial encoders for 3D printer fault detection with only normal condition signals
  48. Gear and bearing fault classification under different load and speed by using Poincaré plot features and SVM
  49. Finite-time and fixed-time impulsive synchronization of chaotic systems
  50. Exploiting Generative Adversarial Networks as an Oversampling Method for Fault Diagnosis of an Industrial Robotic Manipulator
  51. Fast feature selection based on cluster validity index applied on data-driven bearing fault detection
  52. SOA based smartphone system for the fault detection in rotating machines
  53. Knowledge extraction from deep convolutional neural networks applied to cyclo-stationary time-series classification
  54. Evaluation of Time and Frequency Condition Indicators from Vibration Signals for Crack Detection in Railway Axles
  55. Fault Diagnosis of Wind Turbine Gearbox Based on the Optimized LSTM Neural Network with Cosine Loss
  56. Reciprocating Compressor Multi-Fault Classification Using Symbolic Dynamics and Complex Correlation Measure
  57. Bayesian approach and time series dimensionality reduction to LSTM-based model-building for fault diagnosis of a reciprocating compressor
  58. Finite-time leaderless consensus control of a group of Euler-Lagrangian systems with backlash nonlinearities
  59. A LSTM Neural Network Approach using Vibration Signals for Classifying Faults in a Gearbox
  60. A Systematic Review of Fuzzy Formalisms for Bearing Fault Diagnosis
  61. Vibration signal analysis using symbolic dynamics for gearbox fault diagnosis
  62. Accelerometer Placement Comparison for Crack Detection in Railway Axles Using Vibration Signals and Machine Learning
  63. Deep Learning-Based Gear Pitting Severity Assessment Using Acoustic Emission, Vibration and Currents Signals
  64. Influence of Accelerometer Position on Gearbox Fault Severity Classification through Evaluation of Deep Learning Models
  65. Multilayer Gated Recurrent Unit for Spur Gear Fault Diagnosis
  66. A hybrid heuristic algorithm for evolving models in simultaneous scenarios of classification and clustering
  67. Using a Support Vector Machine Based Decision Stage to Improve the Fault Diagnosis on Gearboxes
  68. Generative Adversarial Networks Selection Approach for Extremely Imbalanced Fault Diagnosis of Reciprocating Machinery
  69. Spur Gear Fault Diagnosis Using a Multilayer Gated Recurrent Unit Approach With Vibration Signal
  70. Wind Turbine Gearbox Fault Diagnosis using SAE-BP Transfer Neural Network
  71. GKFP: A New Fuzzy Clustering Method Applied to Bearings Diagnosis
  72. Convolutional Neural Networks Using Fourier Transform Spectrogram to Classify the Severity of Gear Tooth Breakage
  73. Gear Crack Level Classification by Using KNN and Time-Domain Features from Acoustic Emission Signals Under Different Motor Speeds and Loads
  74. Feature engineering based on ANOVA, cluster validity assessment and KNN for fault diagnosis in bearings
  75. Feature ranking for multi-fault diagnosis of rotating machinery by using random forest and KNN
  76. A comparison of fuzzy clustering algorithms for bearing fault diagnosis
  77. A semi-supervised approach based on evolving clusters for discovering unknown abnormal condition patterns in gearboxes
  78. Gearbox fault classification using dictionary sparse based representations of vibration signals
  79. Echo state network and variational autoencoder for efficient one-class learning on dynamical systems
  80. A fuzzy transition based approach for fault severity prediction in helical gearboxes
  81. An adaptive genomic difference based genetic algorithm and its application to memetic continuous optimization
  82. A comparative feature analysis for gear pitting level classification by using acoustic emission, vibration and current signals
  83. A review on data-driven fault severity assessment in rolling bearings
  84. Gearbox Fault Diagnosis Based on a Novel Hybrid Feature Reduction Method
  85. Poincaré plot features from vibration signal for gearbox fault diagnosis
  86. Automatic feature extraction of time-series applied to fault severity assessment of helical gearbox in stationary and non-stationary speed operation
  87. A Dictionary Sparse Based Representation of Vibration Signals for Gearbox Fault Detection
  88. A Bayesian approach to consequent parameter estimation in probabilistic fuzzy systems and its application to bearing fault classification
  89. ANOVA and Cluster Distance Based Contributions for Feature Empirical Analysis to Fault Diagnosis in Rotating Machinery
  90. Framework for Discovering Unknown Abnormal Condition Patterns in Gearboxes Using a Semi-supervised Approach
  91. Multi-fault Diagnosis of Rotating Machinery by Using Feature Ranking Methods and SVM-based Classifiers
  92. Some Preliminary Results on the Comparison of FCM, GK, FCMFP and FN-DBSCAN for Bearing Fault Diagnosis
  93. Vibration-based gearbox fault diagnosis using deep neural networks
  94. Attribute clustering using rough set theory for feature selection in fault severity classification of rotating machinery
  95. SOA Based Integrated Software to Develop Fault Diagnosis Models Using Machine Learning in Rotating Machinery
  96. A methodological framework using statistical tests for comparing machine learning based models applied to fault diagnosis in rotating machinery
  97. Rolling bearing fault diagnosis based on Deep Boltzmann machines
  98. Extracting repetitive transients for rotating machinery diagnosis using multiscale clustered grey infogram
  99. Gearbox fault diagnosis based on deep random forest fusion of acoustic and vibratory signals
  100. Clustering algorithm using rough set theory for unsupervised feature selection
  101. Fault Diagnosis for Rotating Machinery Using Vibration Measurement Deep Statistical Feature Learning
  102. A statistical comparison of neuroclassifiers and feature selection methods for gearbox fault diagnosis under realistic conditions
  103. Fuzzy determination of informative frequency band for bearing fault detection
  104. Observer-biased bearing condition monitoring: From fault detection to multi-fault classification
  105. Fault diagnosis in spur gears based on genetic algorithm and random forest
  106. Rolling element bearing defect detection using the generalized synchrosqueezing transform guided by time–frequency ridge enhancement
  107. Multimodal deep support vector classification with homologous features and its application to gearbox fault diagnosis
  108. Multi-Stage Feature Selection by Using Genetic Algorithms for Fault Diagnosis in Gearboxes Based on Vibration Signal
  109. Fault diagnosis of spur gearbox based on random forest and wavelet packet decomposition
  110. Introduction to the special issue on the VIII Latin-American Congress on Mechanical Engineering
  111. Fault Diagnosis for Controlled Continuous Systems from a Hybrid Approach: A Case Study
  112. Gearbox Fault Identification and Classification with Convolutional Neural Networks
  113. Diseño e implementación de un laboratorio de instrumentación industrial