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This paper introduces a process monitoring method using a convolutional neural network (CNN) with dual‐channel pooling and homologous bilinear models (DCP‐HBM). This method aims to enhance the stability of industrial coking furnaces and reduce maintenance costs. It is significantly relevant for addressing challenges such as complexity, high dimensionality, and strong coupling, which are difficult to manage with traditional fault diagnosis methods. In this study, a deep feature extraction module is employed to gather feature information. To effectively reduce the impact of noise and strengthen the correlation between features, DCP is incorporated after deep feature extraction. Concurrently, a HBM is introduced for feature fusion, further refining the characteristics of each state. Faults are then accurately classified through a classification module. The method utilizes DCP to filter and focus input data, thus making the model more attentive to task‐relevant information. This enhances the model's understanding and representation of the input data. The introduction of the HBM further refines the features extracted by the network and increases the precision of feature extraction. This leads to improved recognition of faults with high similarity, thereby enhancing the accuracy of the overall process monitoring. Experimental results demonstrate that this method exhibits strong performance in the monitoring of industrial coking furnaces, indicating its wide‐ranging application prospects. [ABSTRACT FROM AUTHOR]

Knock is one of the main obstacles to improving the thermal efficiency of spark-ignition internal combustion engines. Although knock has been widely studied and accepted as a result of end-gas auto-ignition, the fundamentals regarding auto-ignition behaviors are still not fully revealed. In this study, the ignition behaviors of primary reference fuels were investigated in an optical rapid compression machine equipped with a quartz combustion chamber allowing for visualizing the combustion process from the lateral view. By combining both the lateral view and the top view photography, ignition behaviors under vortex-existing conditions with a creviced piston and vortex-minimized conditions with a flat piston were comprehensively analyzed to reveal the impact of the vortex on the ignition behaviors of PRF fuels. The influence of fuel reactivity was also investigated. The results showed that mild ignition was prevalent under large Da* numbers. The occurrence of mild ignition was closely related to the ignition delay time of the mixture, and the critical ignition delay time was not fixed but decreased with increasing initial temperature. The propensity of mild ignition could be boosted under vortex-existing conditions due to the increasing hotspot formation probability. Vortices were demonstrated to be capable of mitigating knock intensity via 1) the buffer effect of surrounding burned regions on the shock waves generated from surrounded unburnt pockets; 2) a larger burned mass fraction at the instant of the final ignition under vortex-existing conditions. The results also showed that strong ignition was more likely to occur under vortex-minimized conditions. Besides, higher fuel reactivity also could increase the probability of strong ignition occurrence. Compared with the creviced piston, the use of the flat piston could shift the ignition regime towards regions with higher Re t and lower Da t in the Da t - Re t diagram, where the strong ignition is less pronounced. [ABSTRACT FROM AUTHOR]

A novel design of robust constrained model predictive tracking control is proposed for systems with polytopic description. Unlike the conventional robust model predictive tracking control, the proposed method adopts an improved state space model in which the process state variables and tracking error are combined such that they can be tuned in the cost function optimization separately. Based on the proposed new model, more degrees of freedom are provided for the subsequent controller design, which leads to improved control performance. The relevant feasibility and robust stability issues are further discussed, and the effectiveness of the proposed approach is tested on the control of a system which is open-loop unstable with dead time and reverse responses. [ABSTRACT FROM AUTHOR]