Apr 25, 2019 · In this paper, a sparse echo autoencoder network (SEAEN) is proposed for the fault diagnosis of delta 3-D printers using attitude data.

Zhang et al. [34] proposed a novel approach named deep hybrid state network integrating sparse AE and double-structure ESN for fault diagnosis of 3-D printers.

In this paper, a sparse echo autoencoder network (SEAEN) is proposed for the fault diagnosis of delta 3-D printers using atti- tude data. Considering the ...

Intelligent fault diagnosis algorithms based on machine learning and deep learning techniques have been widely used in industrial applications and have obtained ...

A novel sparse echo autoencoder network for data-driven fault diagnosis of delta 3-D printers. IEEE Trans Instrum Meas, vol. 69 (3) (2020), pp. 683-692.

A Novel Sparse Echo Autoencoder Network for Data-Driven Fault Diagnosis of Delta 3-D Printers · Engineering, Computer Science. IEEE Transactions on ...

A novel sparse echo autoencoder network for data-driven fault diagnosis of delta 3-D printers. J Long, Z Sun, C Li, Y Hong, Y Bai, S Zhang. IEEE Transactions on ...

Novelty detection is a challenging task for the machinery fault diagnosis. A novel fault diagnostic method is developed for dealing with not only diagnosing ...

A novel sparse echo autoencoder network for data-driven fault diagnosis of delta 3-D printers. IEEE Trans. Instrum. Meas. 2019, 69, 683–692. [Google Scholar] ...

A novel sparse echo autoencoder network for data-driven fault diagnosis of delta 3-D printers. IEEE Trans. Instrum. Meas., 2020, 69(3): 683-692, https://doi ...