@article{discovery10111724,
            note = {This version is the version of record. For information on re-use, please refer to the publisher's terms and conditions.},
          volume = {43},
          editor = {A Friedl and JJ Klemes and S Radl and PS Varbanov and T Wallek},
           pages = {1171--1176},
          series = {Computer Aided Chemical Engineering},
         journal = {Computer Aided Chemical Engineering},
            year = {2018},
           title = {Fault detection of fermentation processes},
       publisher = {ELSEVIER SCIENCE BV},
        keywords = {Fault detection, fermentation, parameter estimation, multiparametric programming},
             url = {https://doi.org/10.1016/B978-0-444-64235-6.50204-7},
          author = {Mid, EC and Dua, V},
        abstract = {Fault detection is becoming an important issue in fermentation processes. Any improper formulation or contamination in the fermentation may change the kinetic model parameters and lead to a process fault. In this work, a square system of parametric nonlinear algebraic equations is formulated and solved symbolically to obtain the kinetic model parameters as an explicit function of measurements, so as to estimate the parameters to detect and diagnose the faults in fermentation processes. A number of scenarios are considered to show the effectiveness of the presented approach. The proposed approach successfully estimates the model parameters and detects the faults in the system.}
}