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Soft sensors have been widely used in chemical plants to estimate process variables that are difficult to measure online. One crucial difficulty of soft sensors is that predictive accuracy drops due to changes in state of chemical plants. The predictive accuracy of traditional soft sensor models decreases when sudden process changes occur. However, an online support vector regression (OSVR) model with the time variable can adapt to rapid changes among process variables. One crucial problem is finding appropriate hyperparameters and window size, which means the numbers of data for the model construction, and thus, we discussed three methods to select hyperparameters based on predictive accuracy and computation time. The window size of the proposed method was discussed through simulation data and real industrial data analyses and the proposed method achieved high predictive accuracy when time-varying changes in process characteristics occurred. 相似文献
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Development of a vision‐based online soft sensor for oil sands flotation using support vector regression and its application in the dynamic monitoring of bitumen extraction
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Highly uniform NiO nano-particles with a crystallite size of about 3 nm were obtained by room-temperature ball-milling of the parent Ni(OH)2, which was derived using a sol-gel method. The obtained nano-structured NiO precursor was then utilized for the fabrication of NiO-sensing electrodes (SEs), which were further examined in the mixed-potential-type YSZ-based planar NO2 sensor. The obtained results revealed the attractive advantages for the application of mechanochemical approach in regard to achieve high NO2 sensitivity, NO2 selectivity and reproducibility. All of the evaluated sensors attached with the nano-structured NiO-SEs, regardless of its sintering temperature, were found to exhibit high NO2 sensitivity at 800 °C under the wet condition (5 vol.% water vapor). In addition to high NO2 sensitivity, the sensor attached with 1100 °C-sintered NiO-SE showed highly selective properties towards NO2. The observed improvement in NO2-sensing characteristics as well as the attainment of highly reproducible behavior for different sensor devices is discussed based on morphological and electrochemical observations of the studied sensors. 相似文献