Using Learned Health Indicators and Deep Sequence Models to Predict Industrial Machine Health

Autor: Moncef Chioua, Diego Pareschi, Arzam Kotriwala, Ralf Gitzel, Ido Amihai

Publikováno v: The 7th International conference on Time Series and Forecasting.

In this paper, we describe a machine learning approach for predicting machine health indicators with a large time horizon into the future. The approach uses state-of-the-art neural network architectures for sequence modelling and can incorporate nume

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::854dd05b5a3540d4d8ae1d8d96689988
https://doi.org/10.3390/engproc2021005007

Online performance tracking and load sharing optimization for parallel operation of gas compressors

Autor: Andrea Cortinovis, Antonio De Marco, Mehmet Mercangöz, Matteo Zovadelli, Diego Pareschi, Sergio Bittanti

Publikováno v: Computers & Chemical Engineering. 88:145-156

Compressor stations on natural gas pipelines are typically composed of multiple parallel compressors for operational flexibility. The aim of load sharing optimization is to operate the compressor units of a gas compression station in an energy effici

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c3e9dd49dfd4aa969b45cb7786351ac2
https://doi.org/10.1016/j.compchemeng.2016.01.012

Modeling Machine Health Using Gated Recurrent Units with Entity Embeddings and K-Means Clustering

Autor: Guruprasad Sosale, Subanatarajan Subbiah, Diego Pareschi, Ralf Gitzel, Ido Amihai, Moncef Chioua, Arzam Kotriwala

Publikováno v: INDIN

We describe a machine learning approach for predicting machine health indicators two weeks into the future. The model developed uses a neural network architecture that incorporates sensor data inputs using gated recurrent units with metadata inputs u

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4a58baea58485958ea3fc43ddcd5f351
https://doi.org/10.1109/indin.2018.8472065

Voltage Dips Influence on Time to Surge in Compressor Application

Autor: Daniel Lewandowski, Diego Pareschi, Michał Kaczmarek, Andrea Cortinovis, Piotr Lipnicki

Publikováno v: Advances in Intelligent Systems and Computing ISBN: 9783319644738

This article investigates the effects of voltage dips on the operation of an electrical-motor-driven centrifugal gas compressors with major focus on time to surge key performance indicator behavior. Centrifugal and axial compressors are susceptible t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::5ffa497e39f8faeb235f6581aea0e05f
https://doi.org/10.1007/978-3-319-64474-5_29

On-line adaptation of performance maps for centrifugal gas compressors

Autor: Diego Pareschi, Sergio Bittanti, Andrea Cortinovis, Mehmet Mercangöz, Matteo Zovadelli, Antonio De Marco

Publikováno v: ECC
European Control Conference, pp. 1036–1041, 2014
info:cnr-pdr/source/autori:Cortinovis, Andrea; Zovadelli, Matteo; Mercangoez, Mehmet; Pareschi, Diego; De Marco, Antonio; Bittanti, Sergio/congresso_nome:European Control Conference/congresso_luogo:/congresso_data:2014/anno:2014/pagina_da:1036/pagina_a:1041/intervallo_pagine:1036–1041

This paper investigates the adaptation of different performance maps of centrifugal compressors driven by dualshaft gas turbines during operation. First the estimation of compressor, gas turbine and combined efficiency are considered. Obtaining perfo

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2120a9bf0490c3572940b418d1e5f76b
http://hdl.handle.net/11311/960192