Multi‐attribute quantitative bearing fault diagnosis based on convolutional neural network
Existing bearing fault diagnosis methods have some disadvantages, one being that most methods cannot completely consider all specific fault attributes. Another disadvantage is that the qualitative diagnosis method considers different fault types ...
Design and research of a robotic system for ultrasonic‐assisted lamellar keratoplasty
In order to solve the problem of uncontrollable cutting depth and the rough incision edge of the cornea with manual trephine in lamellar keratoplasty, an ultrasonic‐assisted corneal trephination method has been proposed for the first time in ...
Exploring conventional enhancement and separation methods for multi‐speech enhancement in indoor environments
Speech enhancement is an important preprocessing step in a wide diversity of practical fields related to speech signals, and many signal‐processing methods have already been proposed for speech enhancement. However, the lack of a comprehensive and ...
Improved fault diagnosis algorithm based on artificial immune network model and neighbourhood rough set theory
With the aim to identify new fault diagnosis and advanced robotic systems, this paper first proposes a fault diagnosis algorithm based on an artificial immune network model that can adjust the pruning threshold. Secondly, the algorithm is improved ...
Minimum error entropy criterion‐based randomised autoencoder
The extreme learning machine‐based autoencoder (ELM‐AE) has attracted a lot of attention due to its fast learning speed and promising representation capability. However, the existing ELM‐AE algorithms only reconstruct the original input and ...
Optimization of a GIS sensor layout based on global detection probability distribution evaluation
Gas‐insulated switchgear (GIS) is an important power equipment. The implementation of health monitoring is limited by the number of sensors, and the global detection results of the system should be highly credible to ensure the reliability of the ...
Soil moisture content prediction model for tea plantations based on SVM optimised by the bald eagle search algorithm
In order to solve the problem of low accuracy and efficiency of soil moisture content prediction in tea plantations and improve the level of soil water content prediction, a soil moisture content prediction model for tea plantations based on the ...
