| Statistical fault detection using PCA-based GLR hypothesis testing F Harrou, MN Nounou, HN Nounou, M Madakyaru Journal of loss prevention in the process industries 26 (1), 129-139, 2013 | 109 | 2013 |
| PLS-based EWMA fault detection strategy for process monitoring F Harrou, MN Nounou, HN Nounou, M Madakyaru Journal of Loss Prevention in the Process Industries 36, 108-119, 2015 | 92 | 2015 |
| Black anodizing of a magnesium-lithium alloy AK Sharma, RU Rani, A Malek, KSN Acharya, M Muddu, S Kumar Metal Finishing 94 (4), 16, 1996 | 87 | 1996 |
| Statistical process monitoring using advanced data-driven and deep learning approaches: theory and practical applications F Harrou, Y Sun, AS Hering, M Madakyaru Elsevier, 2020 | 74 | 2020 |
| Improved data-based fault detection strategy and application to distillation columns M Madakyaru, F Harrou, Y Sun Process Safety and Environmental Protection 107, 22-34, 2017 | 53 | 2017 |
| Kullback-leibler distance-based enhanced detection of incipient anomalies F Harrou, Y Sun, M Madakyaru Journal of Loss Prevention in the Process Industries 44, 73-87, 2016 | 47 | 2016 |
| An improved multivariate chart using partial least squares with continuous ranked probability score F Harrou, Y Sun, M Madakyaru, B Bouyedou IEEE Sensors Journal 18 (16), 6715-6726, 2018 | 46 | 2018 |
| Reparametrized ARX models for predictive control of staged and packed bed distillation columns M Muddu, A Narang, SC Patwardhan Control engineering practice 18 (2), 114-130, 2010 | 25 | 2010 |
| Improved detection of incipient anomalies via multivariate memory monitoring charts: Application to an air flow heating system F Harrou, M Madakyaru, Y Sun, S Khadraoui Applied Thermal Engineering 109, 65-74, 2016 | 24 | 2016 |
| Improved nonlinear fault detection strategy based on the Hellinger distance metric: Plug flow reactor monitoring F Harrou, M Madakyaru, Y Sun Energy and Buildings 143, 149-161, 2017 | 23 | 2017 |
| Monitoring distillation column systems using improved nonlinear partial least squares-based strategies M Madakyaru, F Harrou, Y Sun IEEE Sensors Journal 19 (23), 11697-11705, 2019 | 18 | 2019 |
| Improved process monitoring scheme using multi-scale independent component analysis KR Kini, M Madakyaru Arabian Journal for Science and Engineering 47 (5), 5985-6000, 2022 | 15 | 2022 |
| Improved process monitoring strategy using Kantorovich distance-independent component analysis: An application to Tennessee Eastman process KR Kini, M Madakyaru IEEE Access 8, 205863-205877, 2020 | 14 | 2020 |
| Development of ARX models for predictive control using fractional order and orthonormal basis filter parametrization M Madakyaru, A Narang, SC Patwardhan Industrial & engineering chemistry research 48 (19), 8966-8979, 2009 | 14 | 2009 |
| Unsupervised deep learning-based process monitoring methods F Harrou, Y Sun, AS Hering, M Madakyaru, A Dairi Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning …, 2021 | 12 | 2021 |
| Development of ARX models for predictive control using fractional order and orthonormal basis filter parameterization M Muddu, A Narang, SC Patwardhan Ind. Eng. Chem. Res 48 (19), 8966-8979, 2009 | 12 | 2009 |
| Improved anomaly detection using multi-scale PLS and generalized likelihood ratio test M Madakyaru, F Harrou, Y Sun 2016 IEEE Symposium Series on Computational Intelligence (SSCI), 1-6, 2016 | 11 | 2016 |
| Linear inferential modeling: theoretical perspectives, extensions, and comparative analysis M Madakyaru, MN Nounou, HN Nounou Scientific Research Publishing, 2012 | 11 | 2012 |
| Unsupervised recurrent deep learning scheme for process monitoring F Harrou, Y Sun, AS Hering, M Madakyaru, A Dairi Elsevier BV, 2021 | 9 | 2021 |
| Anomaly detection using multi-scale dynamic principal component analysis for Tenneesse Eastman Process KR Kini, M Madakyaru 2019 Fifth Indian Control Conference (ICC), 219-224, 2019 | 9 | 2019 |
