Problems such as poor noise immunity and overfitting are prone to occur when convolutional neural network (CNN) is exploited in the fault diagnosis of ZDJ7 railway point machine. In addition, some features unbalanced have multiple tags, which lead low accuracy. Therefore, an improved deep (DCNN) support vector data description (SVDD) classification proposed. First, depthwise separable convoluti...

Abstract Support vector data description (SVDD) method aims to address the one-class classification (OCC) problem find a hypersphere-shaped of target set. For extending SVDD multiclass while remaining ability detecting outliers, we propose novel scheme which can be used in effective feature mapping and meta-class separation based on extreme learning machine algorithm (ELM-MSVDD). Accordingly, i...

The evaluation of rolling bearing performance degradation has important implications for the prediction and health management (PHM) rotating equipment. A method based on comprehensive index reduction support vector data description (SVDD) is proposed in this study. Firstly, improved variational mode decomposition (VMD) was used to decompose vibration signals, defect frequency amplitude ratio wh...

Existing thruster fault diagnosis methods for AUV (autonomous underwater vehicle) usually need sufficient labeled training data. However, it is unrealistic to get data each working condition in practice. Based on this challenge, a transferable approach proposed. In the approach, an IPSE (instantaneous power spectrum entropy) and STNED (signal-to-noise energy difference) are added SPWVD (smoothe...

Initiation of efavirenz-based combination antiretroviral therapy (cART) is associated with Vitamin D deficiency, but the risk factors including efavirenz pharmacokinetics for cART-induced severe vitamin D deficiency (SVDD) and the impact of anti-tuberculosis (TB) cotreatment are not explored. We investigated the prevalence of SVDD in HIV and TB-HIV coinfected patients and associated risk factor...