AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Vibration

Showing 81 to 90 of 146 articles

Clear Filters

A Fuzzy Fusion Rotating Machinery Fault Diagnosis Framework Based on the Enhancement Deep Convolutional Neural Networks.

Sensors (Basel, Switzerland)
Some artificial intelligence algorithms have gained much attention in the rotating machinery fault diagnosis due to their robust nonlinear regression properties. In addition, existing deep learning algorithms are usually dependent on single signal fe...

Non-Linear Regression Models with Vibration Amplitude Optimization Algorithms in a Microturbine.

Sensors (Basel, Switzerland)
Machinery condition monitoring and failure analysis is an engineering problem to pay attention to among all those being studied. Excessive vibration in a rotating system can damage the system and cannot be ignored. One option to prevent vibrations in...

AI-Enabled Predictive Maintenance Framework for Autonomous Mobile Cleaning Robots.

Sensors (Basel, Switzerland)
Vibration is an indicator of performance degradation or operational safety issues of mobile cleaning robots. Therefore, predicting the source of vibration at an early stage will help to avoid functional losses and hazardous operational environments. ...

Design of a vibration damping robot and force evaluation in intraoperative robotic-assisted femoral shaft repair using a modified soft damper.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Closed intra-medullary nailing fixation is a method for treating fractured femurs with minimal invasiveness. However, this method lacks safety and precision. To avert prevailing problems such as extended cracks in the already broken bone,...

Noise Eliminated Ensemble Empirical Mode Decomposition Scalogram Analysis for Rotating Machinery Fault Diagnosis.

Sensors (Basel, Switzerland)
Rotating machinery is one of the major components of industries that suffer from various faults due to the constant workload. Therefore, a fast and reliable fault diagnosis method is essential for machine condition monitoring. In this study, noise el...

Classification of Chaotic Squeak and Rattle Vibrations by CNN Using Recurrence Pattern.

Sensors (Basel, Switzerland)
The chaotic squeak and rattle (S&R) vibrations in mechanical systems were classified by deep learning. The rattle, single-mode, and multi-mode squeak models were constructed to generate chaotic S&R signals. The repetition of nonlinear signals generat...

A New Bearing Fault Diagnosis Method Based on Capsule Network and Markov Transition Field/Gramian Angular Field.

Sensors (Basel, Switzerland)
Compared to time-consuming and unreliable manual analysis, intelligent fault diagnosis techniques using deep learning models can improve the accuracy of intelligent fault diagnosis with their multi-layer nonlinear mapping capabilities. This paper pro...

An Expert System for Rotating Machine Fault Detection Using Vibration Signal Analysis.

Sensors (Basel, Switzerland)
Accurate and early detection of machine faults is an important step in the preventive maintenance of industrial enterprises. It is essential to avoid unexpected downtime as well as to ensure the reliability of equipment and safety of humans. In the c...

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 ...

Bearing Fault Diagnosis via Improved One-Dimensional Multi-Scale Dilated CNN.

Sensors (Basel, Switzerland)
Bearings are the key and important components of rotating machinery. Effective bearing fault diagnosis can ensure operation safety and reduce maintenance costs. This paper aims to develop a novel bearing fault diagnosis method via an improved multi-s...