ArticleScientific reports2024
Wear fault diagnosis in hydro-turbine via the incorporation of the IWSO algorithm optimized CNN-LSTM neural network.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- A CNN Feature Extraction and BKA-Optimized LSSVM Classification Method for Small-Sample Rolling Bearing Fault Diagnosis.Sensors (Basel, Switzerland) · 2026Article
- Research on Time Difference Prediction of RTD Fluxgate Sensors Based on an Improved Transformer Neural Network.Sensors (Basel, Switzerland) · 2026Article
- Analyzing the geometric dependence of thermoelastic Q-factor in micro hemispherical resonators via a data-augmented CNN-transformer model.Microsystems & nanoengineering · 2026Article
- SPHT-LSTM: a novel industrial equipment condition prediction method.Scientific reports · 2026Article
- MultiScaleWave: a wavelet-based multiscale framework for univariate time series forecasting.Scientific reports · 2026Article
- A Hybrid Intelligent Fault Diagnosis Framework for Rolling Bearings and Gears Based on BAYES-ICEEMDAN-SNR Feature Enhancement and ITOC-LSSVM.Sensors (Basel, Switzerland) · 2026Article
- Neural Network-Based Model Predictive Trajectory Tracking Control for Dual-Motor-Driven a Tracked Unmanned Vehicle.Sensors (Basel, Switzerland) · 2025Article
- Fault Diagnosis and Location Method for Stator-Winding Single-Phase Grounding of Large Generator Based on Stepped-Frequency Pulse Injection.Sensors (Basel, Switzerland) · 2025Article
- A Hybrid Deep Learning Framework for Fault Diagnosis in Milling Machines.Sensors (Basel, Switzerland) · 2025Article
- Intelligent Identification of Internal Leakage of Spring Full-Lift Safety Valve Based on Improved Convolutional Neural Network.Sensors (Basel, Switzerland) · 2025Article
- A method for constructing digital twins of CNC machine tools feed systems based on hybrid mechanism-data.Scientific reports · 2025Article
- Hyperspectral Imaging for Foreign Matter Detection in Foods: Advances, Challenges, and Future Directions.Foods (Basel, Switzerland) · 2025Review
- Multi-fault diagnosis and damage assessment of rolling bearings based on IDBO-VMD and CNN-BiLSTM.Scientific reports · 2025Article
- A Fusion Model for Intelligent Diagnosis of Gear Faults with Small Sample Sizes.Sensors (Basel, Switzerland) · 2025Article
- Attention-Guided Residual Spatiotemporal Network with Label Regularization for Fault Diagnosis with Small Samples.Sensors (Basel, Switzerland) · 2025Article
- Fault Diagnosis Method for Shearer Arm Gear Based on Improved S-Transform and Depthwise Separable Convolution.Sensors (Basel, Switzerland) · 2025Article
- Innovative framework for fault detection and system resilience in hydropower operations using digital twins and deep learning.Scientific reports · 2025Article
- A Hybrid Deep Learning Approach for Bearing Fault Diagnosis Using Continuous Wavelet Transform and Attention-Enhanced Spatiotemporal Feature Extraction.Sensors (Basel, Switzerland) · 2025Article
- Fault Diagnosis Method for Centrifugal Pumps in Nuclear Power Plants Based on a Multi-Scale Convolutional Self-Attention Network.Sensors (Basel, Switzerland) · 2025Article
- An NDT Method for Measuring the Diameter and Embedment Depth of the Main Rebar in Cement Poles Based on Rotating Permanent Magnet Excitation.Sensors (Basel, Switzerland) · 2025Article
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Authors and funding
4 authors.
Funding
Abstract
When a hydropower unit operates in a sediment-laden river, the sediment accelerates hydro-turbine wear, leading to efficiency loss or even shutdown. Therefore, wear fault diagnosis is crucial for its safe and stable operation. A hydro-turbine wear fault diagnosis method based on improved WT (wavelet threshold algorithm) preprocessing combined with IWSO (improved white shark optimizer) optimized CNN-LSTM (convolutional neural network-long-short term memory) is proposed. The improved WT algorithm is utilized to denoise the preprocessing of the original signals. Chaotic mapping, bird flock search, and cosine elite variation strategies are introduced to enhance the WSO algorithm's robust performance, and the CNN-LSTM model's hyperparameters are optimized using the IWSO algorithm to improve the diagnostic performance. The experimental results show that the accuracy of the proposed method reaches 96.2%, which is 8.9% higher than that of the IWSO-CNN-LSTM model without denoising. The study also found that the diagnostic accuracy of hydro-turbine wear faults increased with increasing sediment concentration in the water. This study can supplement the existing hydro-turbine condition monitoring and fault diagnosis system. Meanwhile, diagnosing wear faults in hydro-turbines can improve power generation efficiency and quality and minimize resource consumption.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.