Dec 15, 2023 · Automatic fault diagnosis in many systems is performed via the analysis of vibration data in the time or frequency domain.
Dec 15, 2023 · AbstractAutomatic fault diagnosis in many systems is performed via the analysis of vibration data in the time or frequency domain.
Compared with state-of-the-art denoising methods and fault diagnosis methods, the proposed method achieves higher accuracy and robustness under variable noise ...
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An evolutionary ensemble convolutional neural network for fault diagnosis problem. Automatic fault diagnosis in many systems is performed via the analysis of ...
Jun 23, 2023 · An evolutionary ensemble convolutional neural network for fault diagnosis problem ... ensemble machine learning algorithm. The weights of the ...
Oct 17, 2022 · This paper proposes a fault diagnosis method for rotating machinery based on evolutionary convolutional neural network (ECNN).
Multi-sensor data fusion is a feasible technique to achieve accurate and robust results in fault diagnosis of rotating machinery under complex conditions.
Missing: evolutionary | Show results with:evolutionary
Aug 9, 2022 · In BIER, a single CNN model is trained end-to-end with an online boosting technique. The training set in the BIER is reweighed via the negative ...
Nov 6, 2021 · The presented experiments proved that evolution works in two dimensions. It can improve single base models and further improve detection results ...
Sep 1, 2023 · We proposed the simplest way to perform HSE and investigated more than 20 ensemble strategies for HSE as comparison. Experiments are conducted ...