ArticleSensors (Basel, Switzerland)2022
An Oversampling Method of Unbalanced Data for Mechanical Fault Diagnosis Based on MeanRadius-SMOTE.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Article
- Development and evaluation of a convolutional neural network model for sex prediction using cephalometric radiographs and cranial photographs.BMC medical imaging · 2025Article
- RS-SCBiGRU: a noise-robust neural network for high-speed motor fault diagnosis with limited samples.Scientific reports · 2025Article
- Adaptive Sampling Framework for Imbalanced DDoS Traffic Classification.Sensors (Basel, Switzerland) · 2025Article
- Enhancing patient rehabilitation outcomes: artificial intelligence-driven predictive modeling for home discharge in neurological and orthopedic conditions.Journal of neuroengineering and rehabilitation · 2025Article
- Predicting pregnancy at the first year following metabolic-bariatric surgery: development and validation of machine learning models.Surgical endoscopy · 2025Article
- Fault Diagnosis of Semi-Supervised Electromechanical Transmission Systems Under Imbalanced Unlabeled Sample Class Information Screening.Entropy (Basel, Switzerland) · 2025Article
- Predictive analytics technique based on hybrid sampling to manage unbalanced data in smart cities.Heliyon · 2024Article
- Multinomial classification of NLRP3 inhibitory compounds based on large scale machine learning approaches.Molecular diversity · 2024Article
- Machine learning-enabled prediction of prolonged length of stay in hospital after surgery for tuberculosis spondylitis patients with unbalanced data: a novel approach using explainable artificial intelligence (XAI).European journal of medical research · 2024Article
- Predictive modeling for postoperative delirium in elderly patients with abdominal malignancies using synthetic minority oversampling technique.World journal of gastrointestinal oncology · 2024Article
- Transformer fault diagnosis method based on SMOTE and NGO-GBDT.Scientific reports · 2024Article
- Advanced Fault Diagnosis and Health Monitoring Techniques for Complex Engineering Systems.Sensors (Basel, Switzerland) · 2022Article
- Application of machine learning techniques in real-world research to predict the risk of liver metastasis in rectal cancer.Frontiers in oncology · 2022Article
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Authors and funding
4 authors.
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Abstract
With the development of machine learning, data-driven mechanical fault diagnosis methods have been widely used in the field of PHM. Due to the limitation of the amount of fault data, it is a difficult problem for fault diagnosis to solve the problem of unbalanced data sets. Under unbalanced data sets, faults with little historical data are always difficult to diagnose and lead to economic losses. In order to improve the prediction accuracy under unbalanced data sets, this paper proposes MeanRadius-SMOTE based on the traditional SMOTE oversampling algorithm, which effectively avoids the generation of useless samples and noise samples. This paper validates the effectiveness of the algorithm on three linear unbalanced data sets and four step unbalanced data sets. Experimental results show that MeanRadius-SMOTE outperforms SMOTE and LR-SMOTE in various evaluation indicators, as well as has better robustness against different imbalance rates. In addition, MeanRadius-SMOTE can take into account the prediction accuracy of the overall and minority class, which is of great significance for engineering applications.
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