A study on unsupervised monaural reverberant speech separation

Hemavathi, R.; Kumaraswamy, R.

doi:10.1007/s10772-020-09706-x

Cited by 1 publication

(1 citation statement)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In 1998, Huang et al [8] proposed EMD. EMD is an adaptive decomposition method, and it has been widely used in biomedicine [9][10][11], speech recognition [12,13], system modeling [14][15][16], and process control [17][18][19]. EMD can decompose the original signal into different frequency bands and enrich the feature information of the original signal by extracting feature information in different frequency bands.…”

Section: Introductionmentioning

confidence: 99%

Research on Fault Diagnosis Method of Electro‐Hydrostatic Actuator

Lei

Lvjun

et al. 2021

Shock and Vibration

View full text Add to dashboard Cite

Electrohydrostatic actuator is a type of actuator that uses hydraulic energy as the energy transmission carrier, which has the advantages of small size and high power. Since it is commonly used in harsh conditions such as strong vibration, high pressure, and heavy loads, condition monitoring and fault diagnosis of its hydraulic system are particularly important. This paper proposed a novel fault feature extraction method and applied to fault diagnosis of electrohydrostatic actuator. Firstly, the pressure signal of the hydraulic system is decomposed at multiple scales to obtain the center frequency of its maximum energy intrinsic mode component, and the feature data set is constructed based on the statistical features of the time domain. Then, a fault identification model of hydraulic system based on support vector machine is established. Finally, the fault classification and identification results of the hydraulic system are outputted. After a variety of method comparisons, the method proposed in this paper has a fault time ratio accuracy of 96.7%, which provides a basis and a new way for the fault diagnosis of the hydraulic system.

show abstract