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Equipment Failure Analysis

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A RUL Estimation System from Clustered Run-to-Failure Degradation Signals.

Sensors (Basel, Switzerland)
The prognostics and health management disciplines provide an efficient solution to improve a system's durability, taking advantage of its lifespan in functionality before a failure appears. Prognostics are performed to estimate the system or subsyste...

A Robust Deep Neural Network for Rolling Element Fault Diagnosis under Various Operating and Noisy Conditions.

Sensors (Basel, Switzerland)
This study proposes a new intelligent diagnostic method for bearing faults in rotating machinery. The method uses a combination of nonlinear mode decomposition based on the improved fast kurtogram, gramian angular field, and convolutional neural netw...

Intelligent Fault Diagnosis and Forecast of Time-Varying Bearing Based on Deep Learning VMD-DenseNet.

Sensors (Basel, Switzerland)
Rolling bearings are important in rotating machinery and equipment. This research proposes variational mode decomposition (VMD)-DenseNet to diagnose faults in bearings. The research feature involves analyzing the Hilbert spectrum through VMD whereby ...

Application Combining VMD and ResNet101 in Intelligent Diagnosis of Motor Faults.

Sensors (Basel, Switzerland)
Motor failure is one of the biggest problems in the safe and reliable operation of large mechanical equipment such as wind power equipment, electric vehicles, and computer numerical control machines. Fault diagnosis is a method to ensure the safe ope...

Crack Size Identification for Bearings Using an Adaptive Digital Twin.

Sensors (Basel, Switzerland)
In this research, the aim is to investigate an adaptive digital twin algorithm for fault diagnosis and crack size identification in bearings. The main contribution of this research is to design an adaptive digital twin (ADT). The design of the ADT te...

Pre-Processing Method to Improve Cross-Domain Fault Diagnosis for Bearing.

Sensors (Basel, Switzerland)
Models trained with one system fail to identify other systems accurately because of domain shifts. To perform domain adaptation, numerous studies have been conducted in many fields and have successfully aligned different domains into one domain. The ...

A fault diagnosis method based on Auxiliary Classifier Generative Adversarial Network for rolling bearing.

PloS one
Rolling bearing fault diagnosis is one of the challenging tasks and hot research topics in the condition monitoring and fault diagnosis of rotating machinery. However, in practical engineering applications, the working conditions of rotating machiner...

Machine learning for pattern detection in cochlear implant FDA adverse event reports.

Cochlear implants international
Medical device performance and safety databases can be analyzed for patterns and novel opportunities for improving patient safety and/or device design. The objective of this analysis was to use supervised machine learning to explore patterns in rep...

Intelligent Fault-Prediction Assisted Self-Healing for Embryonic Hardware.

IEEE transactions on biomedical circuits and systems
This paper proposes novel methods for making embryonic bio-inspired hardware efficient against faults through self-healing, fault prediction, and fault-prediction assisted self-healing. The proposed self-healing recovers a faulty embryonic cell throu...

Advantages of aquatic animals as models for bio-inspired drones over present AUV technology.

Bioinspiration & biomimetics
Robotic systems are becoming more ubiquitous, whether on land, in the air, or in water. In the aquatic realm, aquatic drones including ROVs (remotely operated vehicles) and AUVs (autonomous underwater vehicles) have opened new opportunities to invest...