4 papers
Learning a Factorized Orthogonal Latent Space using Encoder-only Architecture for Fault Detection; An Alarm management perspective
Vahid MohammadZadeh Eivaghi, Mahdi Aliyari Shoorehdeli
False and nuisance alarms in industrial fault detection systems are often triggered by uncertainty, causing normal process variable fluctuations to be erroneously identified as fau…
Dynamic Importance Learning using Fisher Information Matrix (FIM) for Nonlinear Dynamic Mapping
Vahid MohammadZadeh Eivaghi, Mahdi Aliyari Shoorehdeli
Understanding output variance is critical in modeling nonlinear dynamic systems, as it reflects the system's sensitivity to input variations and feature interactions. This work pre…
Exploiting the capacity of deep networks only at training stage for nonlinear black-box system identification
Vahid MohammadZadeh Eivaghi, Mahdi Aliyari Shooredeli
To benefit from the modeling capacity of deep models in system identification, without worrying about inference time, this study presents a novel training strategy that uses deep m…
Contrastive Multi-Modal Representation Learning for Spark Plug Fault Diagnosis
Ardavan Modarres, Vahid Mohammad-Zadeh Eivaghi, Mahdi Aliyari Shoorehdeli +1
Due to the incapability of one sensory measurement to provide enough information for condition monitoring of some complex engineered industrial mechanisms and also for overcoming t…