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Fault Feature Extraction of Rolling Element Bearing under Complex Transmission Path Based on Multiband Signals Cross-Correlation Spectrum
Aiming at the problem that bearing fault signals are influenced by complex transmission path and multiple structures of equipment, which results in...
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A New Method for Rubbing Fault Identification Based on the Combination of Improved Particle Swarm Optimization with Self-Adaptive Stochastic Resonance
To fulfill the effective diagnosis of the rubbing fault between the rotor and the stator, the combination strategy of adaptive weight particle swarm...
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A Lightweight Damage Diagnosis Method for Frame Structure Based on SGNet Model
Due to the complex structure of most frame structure, a large amount of sensor data needs to be processed for damage diagnosis, which increases the...
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Support Vector Machine for Misalignment Fault Classification Under Different Loading Conditions Using Vibro-Acoustic Sensor Data Fusion
In condition monitoring, accurate fault identification is an essential task for designing a proper maintenance strategy. Misalignment is one of the...
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A transient fault data management algorithm for low-voltage station based on overall situation power big data
In view of the problem that the transient fault data in low-voltage area is easily affected by objective noise because of the large number of...
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Diagnosis of Bearing Faults Using Temporal Vibration Signals: A Comparative Study of Machine Learning Models with Feature Selection Techniques
Accurately identifying bearing defects is crucial for guaranteeing the dependability and effectiveness of industrial systems. Although the use of...
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Failure Diagnostic of Emergency Shutdown Valve (ESDV) Based on Fault-Symptom Tree and Fuzzy Inference System: A Case Study
The Emergency Shutdown System (ESD) is a type of Safety Instrumented Systems (SIS) used to shut down the system in the event of anomalous conditions,...
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Spur Gear Fault Detection Using Design of Experiments and Support Vector Machine (SVM) Algorithm
In this research, the primary objective is to ensure the appropriate functioning of transmission components, particularly the gearbox, which is...
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Fault Diagnosis for Nonlinear Biological Processes Based on Machine Learning Models
Kernel-based learning techniques have been widely used to monitor and detect faults in biological systems. However, it is well known that the data...
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Utilizing Principal Component Analysis for the Identification of Gas Turbine Defects
This study explores the use of the nonlinear principal component analysis (NLPCA) technique for detecting gas turbine faults. The resurgence of...
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Failure Analysis of Medium Voltage Underground Power Câbles Based on Voltage Measurements
This paper presents a classification-based failure analysis of medium voltage underground power cables using voltage measurements with an echometer....
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Detection of Electrical Fault in Medium Voltage Installation Using Support Vector Machine and Artificial Neural Network
AbstractInfrared thermography plays an important role in the inspection of electrical installations allowing to avoid failures and breakdowns....
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Bearing Fault Severity Analysis on A Multi-stage Gearbox Subjected to Fluctuating Speeds
Early detection of bearing defects may prevent the occurrence of catastrophic failures of the whole associated system. Condition monitoring...
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Recent Applications of Artificial Intelligence in Fault Diagnosis of Photovoltaic Systems
This chapter presents a brief survey on the recent applications of artificial intelligence (AI) techniques in fault diagnosis of photovoltaic (PV)...
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Weld Quality Diagnosis of Gas Metal Arc Welding Based on Variational Mode Decomposition, Fuzzy Entropy, and Online Sequential Extreme Learning Machine
The current signal of gas metal arc welding (GMAW) is commonly nonstationary and nonlinear, and its complexity changes when weld defects occur....
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Rolling Element Bearing Fault Diagnosis Based on Adaptive Local Iterative Filtering Decomposition and Teager–Kaiser Energy Operator
The fault feature of rolling element bearings in early failure period is so weak and susceptible to random noise that it is very difficult to be...
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Reliability Evaluation of Environmental Test Chambers Based on Bayesian Network
Emphasis has been given to the reliability of a wide range of equipment in recent years. However, the reliability of environmental test chambers has...
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Fault Diagnosis of a Double-Row Spherical Roller Bearing for Induction Motor Using Vibration Monitoring Technique
Vibration monitoring techniques employing sophisticated instruments are widely used in industries for regular inspection and diagnosis of the health...
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Spectrum Prediction Indicating Bearing State in Induction Motor by Forced Vibration Analysis and Fuzzy Logic Technique
Bearing faults (BF) are the main cause of induction motor failures; virtually, all techniques for diagnosing these faults have been based on...
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Classification and Detection Techniques of Fault in Solar PV System: A Review
Nowadays, solar Photo-Voltaic (PV) system has become more significant than any other system for power generation. PV systems suffer from huge amount...